Land-use change: assessing the net climate forcing, and options for climate change mitigation and adaptation

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement number 603542.

The potential effects of land-based mitigation on the

climate system and the wider environment: A synthesis

of current knowledge in support of policy

Ylva Longva, University of Edinburgh

Mark D.A. Rounsevell, University of Edinburgh and Karlsruhe Institute of Technology

Almut Arneth, Karlsruhe Institute of Technology

Elizabeth Clarke, University of Edinburgh

Jo House, University of Bristol

Annalisa Savaresi, University of Edinburgh

Lucia Perugini, CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici)

Peter Verburg, VU Amsterdam

September 2017

luc4c.eu

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Executive Summary Land-based options to mitigate climate change are expected to deliver approximately a quarter of

emissions reductions pledged by countries in their Nationally Determined Contributions (NDCs) under

the Paris Climate Agreement, and is key to achieving the zero balance target between anthropogenic

emissions and removals in the second half of the 21st Century. We review new scientific knowledge on

land-based mitigation options, the effect of these options on land-use and land-cover change (LULCC)

and their interplay with other environmental concerns. Land-based mitigation provides policy-makers

with competing demands and trade-offs, but also possible co-benefits, and it is through this policy lens

that we synthesise the state of the current knowledge. The primary mitigation options considered in this

summary are: (i) afforestation-reforestation and avoided deforestation, and (ii) bioenergy with carbon

capture and storage (BECCS)1.

Message 1: Land-based mitigation competes for land with food production, other

ecosystem services & biodiversity

There is evidence to suggest that land-based mitigation already has increased food prices, and models

predict further increases, due to the competition for land and the direct use of food crops as a

bioenergy feedstock. The land area required to achieve emission reductions from land-based mitigation

consistent with most 2°C scenarios, is substantially higher than the available land area currently

identified as marginal or abandoned. However, potential land allocation for climate change mitigation

depends on other claims on the same lands, the degree of climate change, technological developments

and dietary preferences. Intensification of agricultural land use could free up more land for climate

mitigation, but this can have other environmental impacts if not done sustainably.

Land-based mitigation policies and strategies in one location affect land use elsewhere due to

displacement; an example of indirect land-use change (iLUC). iLUC can be a major source of GHG

emissions that are not always reported, particularly when the displacement happens in countries with

limited reporting of GHG fluxes. When iLUC is included in life-cycle analyses of different bioenergy

feedstocks, it alters the feedstock’s relative GHG mitigation performance, which has the potential to

undermine conventional bioenergy crops as a sustainable energy source. EU legislation assumes that

the biomass used for electricity generation is carbon-neutral, as it assumes that the land sector captures

both direct and indirect LUC emissions. Not reporting the land sector emissions embodied in the goods

produced within a country can lead to substantial emissions under-reporting. Labelling and certification

schemes for biofuel feedstocks could decrease iLUC and embodied emissions. Furthermore, recent

changes in EU policy seek to limit the share of food-based biofuels and to promote advanced feedstocks.

Terrestrial ecosystems provide a range of ecosystem services, but land-based mitigation impacts on

the ability of ecosystems to provide both the amount and the quality of some of these services. For

instance, bioenergy production has a higher water demand than any other alternative energy source,

1 A third important option, reducing greenhouse gas emissions (esp. N2O and CH4) through agricultural practices was not within

the remit of the LUC4C project.

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and can compete with other water uses unless managed carefully. Intensification of food production

could lead to more land being available for other uses, but is associated with large nitrogen losses to the

atmosphere and water pollution from fertilisers. Provisioning services, such as food and biomass

production, and regulating services, such as carbon sequestration or flood protection, are currently

often not compatible, but could be with more integrated approaches to land management. Provisioning

services are often more tangible and easier to exchange in the market than regulating services, cultural

services or the protection of biodiversity. European policies and emissions targets raise the demand for

woody biomass, consequently reducing forest carbon sinks. However, the carbon sink reduction would

be small if advanced bioenergy crops rather than forest removals were used to meet energy demand.

Land-based mitigation competes for land with biodiversity, but there is potential for achieving co-

benefits. Some land-based mitigation options are incompatible with biodiversity goals. Afforestation

using monoculture plantations reduces species richness when introduced into (semi-)natural grasslands;

a habitat that is prioritised by EU policies on biodiversity. Evidence suggests that when faced with

conflicting mitigation and biodiversity goals, biodiversity is typically given a lower priority, especially if

the mitigation option is considered risk-free and economically feasible. Approaches that promote

synergies, such as avoided deforestation, land sparing and sustainable farming practices in bioenergy

production, and longer rotation-times and mixed-species forests in afforestation-reforestation, can

avoid the loss of biodiversity from land-based mitigation. Systematic land-use planning would help to

achieve land-based mitigation options that also limit trade-offs with biodiversity.

Message 2: Biophysical effects are significant and can have important co-benefits

LULCC affects climate not only through greenhouse gas emissions and uptake, but also through

biophysical effects, especially at the regional scale. Biophysical effects include the reflectance of

sunlight from the Earth’s surface (albedo), cooling from evapotranspiration and the absorbance of wind

energy. Changes in vegetation cover alter the reflection of sunlight (albedo); crops and pastures tend to

be more reflective than darker forests, and this has a cooling effect. However, forests have higher

evapotranspiration rates than crops and pastures, which cools the land surface as well as recycling water

to fall as rain. Forests also absorb wind energy and this has implications for local surface temperatures.

The net effects of these processes play out differently in different parts of the world. Satellite

observations show that large-scale regional deforestation has a predominantly warming effect in the

tropics, and parts of the temperate zone, due to reduced evapotranspiration. However, deforestation

causes cooling in the boreal regions, due to increased reflection of sunlight, especially in winter and

spring, but unlike the tropics, in boreal regions the agreement between measurements and models is

less clear. Uncertainties remain regarding the magnitude of the effect, especially for seasonal variables

(e.g., maximum summer temperatures), and for the effects on precipitation, but it is now well

established that the regional biophysical effects of land-cover change are substantial. Furthermore,

biophysical effects on local temperature are more rapid than warming arising from global atmospheric

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CO2 levels. Thus, mitigation actions taken at the regional level would benefit from considering the

consequences of biophysical effects on local temperature as well as the impacts of GHG emissions. There

are major benefits in doing so, since accounting for the biophysical climate effects of LULCC can support

both mitigation and adaptation objectives and thus, make policy more effective.

Current global, policy frameworks do not consider biophysical effects, and hence opportunities exist

for policy to realise co-benefits. Although local biophysical climate impacts from LULCC are large, they

tend to be much smaller when aggregated globally and this has implications for global policy. The

process of including land-based mitigation in the UNFCCC context has been a matter of long and complex

negotiations. Hence, the relatively small and currently uncertain global biophysical effects make it

difficult to justify efforts to include these effects in the complex negotiations of the UNFCCC process, at

present. However, it is now possible to evaluate the regional biophysical impacts (changes in local

temperature) of land cover transitions, following a tiered method similar to that of the IPCC to estimate

the effects of GHG emissions. The method applies three levels of increasing complexity, from Tier 1 (i.e.

default method and factors) to Tier 3 (i.e. country-specific methods and factors). The procedures

proposed for each tier method are transparent, taking into consideration the UNFCCC reporting

principles and could inform mitigation efforts at regional or national scales to realise the co-benefits of

accounting for biophysical effects.

Policies that support avoided deforestation, especially in tropical regions, have especially large co-

benefits. Avoided deforestation mitigates global climate change by reducing CO2 emissions. It also

affects the local climate in a positive way by maintaining cooler surface temperatures through

biophysical effects. Future climate change will also increase vegetation growth through the effect of

atmospheric CO2 fertilisation and this will further enhance the biophysical cooling effects of forests.

Thus, avoided deforestation as a land-based mitigation option benefits from positive effects on both the

regional and global climate systems.

Message 3: Time lags and multiple goals strongly limit the effectiveness of land-based

mitigation, but there is potential for improvement and co-benefits can be achieved

The relative contribution to climate mitigation of different land-based mitigation options changes

through time. Avoided deforestation provides immediate mitigation gains by reducing rapid carbon

emissions that take place when forests are cut or burnt (as well as having co-benefits with multiple

ecosystem services). Afforestation-reforestation can take-up carbon immediately upon planting, but

with varying, relatively small annual gains due to the slow rate of forest growth, especially as forests

approach maturity. The current carbon sink of EU forests due to past afforestation will likely decline due

to forest ageing. Harvesting and replanting, with carbon storage in harvested wood products or use as

bioenergy, can enable the same land to continue to contribute to mitigation, but care has to be taken

to sustainably manage repeated harvesting in order not to deplete soil carbon stocks. Overall, bioenergy

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(especially lignocellulosic) is expected to contribute more to mitigation scenarios in the second half of

the century, but this will depend on the availability of advanced technologies.

Time lags in policy implementation and uptake strongly influence the effectiveness of land-based

mitigation policy. There are large uncertainties associated with the development and implementation

of BECCS, and other land-based mitigation options. Barriers arising from the rate of technological

development and the considerable need for financial investment mean that the large scale

implementation of BECCS is not likely until around the middle of the 21st century, at the very earliest.

Furthermore, the rate of uptake of bioenergy crops by farmers can be slow in spite of the existence of

financial support. Such barriers could limit the success of bioenergy as a land-based mitigation option.

This demonstrates the importance of immediate policy action, and measures to support more rapid

policy intervention and uptake.

The success of afforestation-reforestation and avoided deforestation as mitigation options are subject

to the changing risks from disturbances that affect forest permanence and depend on continued

monitoring and management of forest stands over the long term. Disturbances arising from climate

extremes, wild fires, pest and diseases affect afforestation-reforestation and avoided deforestation, but

also yields of bioenergy crops. The risk of these disturbances will also change with future climate change.

Better understanding disturbances and how to manage them in a changing climate would reduce

uncertainty and therefore the risks associated with investment in mitigation options. Monitoring,

Reporting and Verification (MRV) of forest carbon and other land based mitigation schemes need to be

able to account for disturbances (and associated carbon losses) to provide confidence that land-based

mitigation projects will meet their long-term objectives. Recent advances in satellites and modelling

capabilities can support MRV, along with capacity building in developing countries.

There are potential synergies between land-based mitigation and adaptation that would allow co-

benefits to be achieved. Primary forests, in contrast to monoculture plantations, provide a wide range

of ecosystem services and have more biodiversity, which are characteristics of a resilient forest

ecosystem. Hence, avoided deforestation of primary forests could benefit both mitigation (retaining

carbon) and adaptation (greater resilience) to climate change. Furthermore, planting trees in urban

areas has mitigation benefits (carbon storage) as well as adaptation benefits (cooling effects, and

reducing surface water run-off and flooding). Changing food consumption patterns (e.g. through low-

meat diets, reducing over-eating and waste, and eating alternative protein sources) reduces the land

area needed for food production providing opportunities for land-based mitigation. This also builds

resilience to climate change, since the additional availability of land could offset the negative impact of

climate change on crop yields and thus food production. These examples demonstrate potential

opportunities, but there is little scientific evidence to support understanding of the full extent of

mitigation-adaptation synergies (or trade-offs), which is a major knowledge gap.

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Developing policies that systematically cut across policy sectors would achieve co-benefits for

multiple policy goals. Co-benefits are not always realised, and a single sector focus can often cause

unintended negative impacts on other sectors, e.g. by promoting land clearing, which is associated with

negative impacts on carbon and flooding. Well-grounded, land-based mitigation strategies can have

positive social benefits, but conversely, land-based mitigation can have negative environmental and

social impacts if poorly planned. There is considerable potential for rural development and job creation

linked to European bioenergy markets. However, entry into the sector often requires economies of scale

(excluding smallholders) and time lags in implementation and up-take are also constraints (as outlined

above).

In Summary

Land-based mitigation is not a ‘silver-bullet’ to avoid climate change, but alongside drastic reductions

in fossil fuel emissions, it can contribute to delivering the “balance of sources and sinks” in the Paris

Agreement. Land-based mitigation is currently the only way to remove CO2 from the atmosphere at a

scale that is potentially relevant to climate mitigation. The land sector will not be emissions free due to

the emissions necessarily associated with food production. Moreover, there is a real danger that land-

based mitigation will compete with food production, the provision of other ecosystem services and

biodiversity. Further analysis is required to understand fully the many trade-offs, beyond climate

mitigation that arise from land management and to identify policy options that support co-benefits.

Land-based mitigation could potentially enable the land sector as a whole to approach a balance of

sources and sinks, and, if barriers are overcome and sustainability ensured, it could further offset some

of the more unavoidable emissions from fossil fuels.

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Table of Contents

Executive Summary ...................................................................................................................... 2

Introduction .................................................................................................................................. 10

Box 1: Introducing the LUC4C Project ............................................................................................... 11

Box 2: Defining land-based mitigation options ................................................................................. 14

Box 3: Projected bioenergy trends in Europe ................................................................................... 15

Topic 1: Land-based mitigation competes for land and this has negative

consequences .................................................................................................................. 16

1a. Land-based mitigation increases food prices because of land competition and the direct

use of food crops as a bioenergy feedstock ......................................................................... 16

1b. Land-based mitigation competes for land with ‘nature’ and the maintenance of

biodiversity .................................................................................................................................. 18

1c. Land-based mitigation in one location can directly affect land use elsewhere due to

displacement effects, an example of indirect land-use change ......................................... 20

Topic 2: Land-based mitigation has trade-offs with, but also co-benefits for, the

provision of ecosystem services .................................................................................. 22

2a. Land-based mitigation impacts on the ability of ‘nature’ to provide other ecosystem

services ....................................................................................................................................... 22

2b. Co-benefits between land-based mitigation and ecosystem service provision are

feasible ........................................................................................................................................ 24

2c. There are trade-offs between energy generation and carbon stocks for different land-

based mitigation options........................................................................................................... 27

Topic 3: Biophysical and biochemical cycles ......................................................................... 28

3a. LULCC affects climate not only through greenhouse gas emissions and uptake, but also

through biophysical effects, especially at the regional scale, but this is not accounted

for in policy ................................................................................................................................. 28

Topic 4: The longevity and timing of land-based mitigation strategies ............................. 31

4a. The relative contribution of different land-based mitigation options changes through

time. ............................................................................................................................................. 31

4b. Time lags in the science-policy-society exchange process influence the effectiveness

of land-based mitigation policy ................................................................................................ 32

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4c. The success of A/R and AD as mitigation options depends on continued monitoring and

management of forest stands .................................................................................................. 34

4d. The success of avoided deforestation and reforestation depends on the changing risks

from disturbances, such as climate extremes, wild fires and pest and diseases, which

affect forest permanence ......................................................................................................... 36

Topic 5: Landscape management and alternate land-use futures ...................................... 37

5a. Forest management is increasingly recognised as an important contributor to land

sector carbon fluxes in both science and policy communities ............................................ 37

5b. Livestock and cropping systems are significant contributors to global emissions of non-

CO2 GHGs. The management of these systems has the potential to reduce GHG

emissions .................................................................................................................................... 40

5c. There are a number of alternative scenarios of land-based mitigation that are rarely

explored since most future scenarios are based on a limited set of conventional

options such as agricultural management, A/R and BECCS ............................................. 45

Topic 6: Multiple policy goals and co-benefits ....................................................................... 47

6a. There are potential synergies between land-based mitigation and adaptation that would

allow co-benefits to be achieved ............................................................................................. 47

6b. Positive social benefits can be derived from well-grounded land-based mitigation

strategies, but, conversely, land-based mitigation can have negative social impacts

if poorly planned ........................................................................................................................ 49

6c. Co-benefits are possible across a set of policy targets if policy is developed

systematically across sectors rather than in isolation .......................................................... 51

6d. The implementation of BECCS is uncertain ............................................................................... 53

6e. Land-based mitigation is not a ‘silver-bullet’ to avoid climate change and must be part

of a policy framework that also reduces fossil fuel based emissions ................................ 54

Abbreviations ............................................................................................................................... 57

Annex 1: Relevant International Climate Policies .................................................................. 58

A1.1 Climate Change within the UN policy framework .................................................................... 58

A1.2 Biodiversity and Ecosystem Services with the UN policy framework .................................. 59

A1.3 Sustainable Development Goals ............................................................................................... 59

Annex 2: Relevant European Policies ...................................................................................... 59

A2.1 EU Climate and Energy Package .............................................................................................. 59

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A2.2 European ETS .............................................................................................................................. 60

A2.3 European Effort-Sharing Decision and Effort-Sharing Regulation ....................................... 60

A2.4 European Land Use Decision .................................................................................................... 61

A2.5 Renewable Energy Directive and Fuel Quality Directive ....................................................... 61

A2.6 Forest 2013 strategy .................................................................................................................... 62

A2.7 Common Agricultural Policy ....................................................................................................... 63

References .................................................................................................................................... 64

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Introduction Land-use and land-cover change (LULCC) impacts the climate regionally, as a consequence of biophysical

changes (see [1]), and globally, as a consequence of greenhouse gas (GHG) emissions/sequestration

(biogeochemical processes) (see [2]). LULCC emissions from activities such as deforestation, logging and

intensive agriculture constitute the second largest anthropogenic source of CO2 [2]). Houghton et al.

1999 [3] estimates that 124 PgC were released to the atmosphere as a consequence of LULCC between

1850 and 1990; approximately one-third of total anthropogenic emissions. Between 1990 and 2000,

LULCC derived CO2 emissions represented 20% of total anthropogenic CO2 emissions [2], decreasing to

9% between 2006 and 2015 [4]. If non-CO2 GHG emissions, such as methane (CH4) and nitrous oxide

(N2O), are included, this number rises to nearly a quarter [5].

The land use, land-use change and forestry (LULUCF) sector has the potential to both emit and store

carbon. Citing the United Nations Framework Convention on Climate Change (UNFCCC) inventory data,

Frank et al. (2016) [6] estimate the European land-use based carbon sink to have been approximately

329 MtCO2 in 2012, that is, the sector absorbed more carbon than it emitted. This ability to store and

sequester carbon makes the land sector an important contributor to mitigating climate change.

The Paris Climate Agreement is committed to limiting global temperature rise to less than 2 °C relative

to pre-industrial levels (Art. 2) (UNFCCC, 2017). The LULUCF sector is a key component of the (Intended)

Nationally Determined Contributions ((I)NDCs) proposed by parties to the agreement. On a global scale,

the sector must be converted from a net anthropogenic source (1.3 ± 1.1 GtCO2eq/yr between 1990

and 2010) to a net sink (up to -1.1 ± 0.5 GtCO2eq/yr) by 2030 [7]. In relative terms, the sector must

provide approximately one quarter of total emissions reductions planned in the (I)NDCs [7]. This

importance of negative emissions is further emphasised in the Intergovernmental Panel on Climate

Change (IPCC) climate scenarios. Of the 116 scenarios in the IPCC AR5 database that are consistent with

a greater than 66% probability of keeping warming within 2°C, 87% apply negative emissions

technologies (NETs) in the second half of this century [8]. Bioenergy with carbon capture and storage

(BECCS) is currently one of the most commonly considered NETs, and of the abovementioned IPCC AR5

scenario, 104 utilise the largescale deployment of this technology [9].

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Box 1: Introducing the LUC4C Project

The EU funded LUC4C project (Land-use change: assessing the net climate forcing, and options for

climate change mitigation and adaptation), aims to advance our knowledge of the interactions of

climate change and land-use change. The scientists in LUC4C are working on the development of

complex earth system models, tools for providing an integrated assessment of the land-use change-

climate change interplay, and options for policy and other societal stakeholders. LUC4C seeks to

identify and understand the societal and environmental drivers of land-use and land-cover change, as

well as why they are relevant to climate change. The project evaluates different mitigation and

adaptation policies in view of how these affect important ecosystem processes, and whether

(unintended) conflict with other ecosystem services related to land-use and land-cover change arise

from the implementation of such policies.

In international policy frameworks, land-based mitigation is primarily the preserve of UN climate

frameworks such as the UNFCCC, Paris Agreement and Kyoto Protocol (KP) (Table 1 and Annex 1.1).

However, as will be exemplified in this synthesis, land-based mitigation has the potential to be both

synergistic with and counter to multiple non-climate, environment and sustainability conventions and

policies. At the EU level, emissions from the LULUCF sector are presently accounted for, but do not

contribute to achieving the EU emission reduction targets for 2020 (Table 2 and Annex 2.4). The EU has,

however, made plans to use the LULUCF sector to achieve its 2030 targets [10, 11] (see Issue 5a).

Land-based mitigation is cross-sectoral (forestry and agriculture), with influences on water, biodiversity,

and ecosystem services. Land-based mitigation strategies have the potential to interact with a diversity

of EU policies that do not focus on the climate or land sectors, for example the Water Framework

Directive, National Emissions Ceiling Directive (clean Air Policy Package) and Circular economy package.

We review new scientific knowledge on land-based options to mitigate climate change, the effect of

these options on land-use and land-cover change (LULCC) and their interplay with other environmental

concerns. Land-based mitigation presents policy-makers with competing demands and trade-offs, but

also possible co-benefits, and it is through this policy lens that we synthesise the state of the current

knowledge. The primary focus is on land-based mitigation through: (i) afforestation-reforestation (A/R)

and avoided deforestation (AD), and (ii) bioenergy with carbon capture and storage (BECCS). A third

important option, reduced greenhouse gas emissions (especially N2O and CH4) through agricultural

practices, was not within the remit of the LUC4C project, but is explored in a review of external literature

(Issue 5b). Additional negative emission technologies, such as the direct air capture of CO2, enhanced

mineral weathering (and storage), the modification of ocean CO2 uptake, aquatic biomass and biochar

storage [8, 9] are not explicitly explored here. While representing distinct processes, the terms land-use

(management/use) and land-cover (biophysical materials) change (LULCC) will be treated as

synonymous for the purpose of this review.

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Table 1: International climate policy relevant to the land sector and land-based mitigation [10, 11, 12]

Policy Land Sector Relevance

UNFCCC Reporting of LULUCF sector GHG emissions/sinks associated with land-use

conversions and management activities.

Kyoto Protocol (KP)

Kyoto Protocol 1 (KP1): 2008-2012

Kyoto Protocol 2 (KP2): 2013-2020

Parties must report emissions/sinks from afforestation, reforestation,

deforestation and forest management (mandatory in KP2). Parties can

optionally report on human-induced revegetation, grassland management

and cropland management.

Paris Climate Agreement Land-based mitigation to be included in countries’ NDCs.

REDD+ Scheme for reducing emissions from deforestation and forest degradation

in developing countries, through funding pledged by developed countries.

Parties have to develop a national strategy or action plan, national forest

monitoring system national forest reference emission level and/or forest

reference level, and safeguard information system.

Table 2: European climate policy relevant to the land sector and land-based mitigation [10, 13, 14, 15]

Policy Land Sector Relevance

2020 Climate and Energy Framework

(COM(2008) 30 final; [16])

Outlines three key targets: (i) to reduce GHG emissions by 20% (on 1990 levels),

(ii) to increase the share of renewable energy to 20%, and (iii) improve energy

efficiency by 20%. Renewable energy targets are one driver of future land use

(Box 2).

2030 Climate and Energy Framework

(COM(2014) 15 final; [17])

Outlines three key targets: (i) to reduce GHG emissions by 40% (on 1990 levels),

(ii) to increase the share of renewable energy to 27%, and (iii) improve energy

efficiency by 27%. Renewable energy targets are one driver of future land use

(Box 2).

Effort Sharing Decision (EU-ESD)

(406/2009/EC; [18])

The EU-ESD for 2013-2020 encompasses non-ETS sectors such as transport,

buildings, agriculture (non-CO2 only) and waste, but excludes CO2 emissions

from the LULUCF sector.

Effort Sharing Regulation (EU-ESR)

(COM(2016) 479 final; [19])

The proposed EU-ESR for 2021-2030 provides additional flexibilities enabling

all Member States to use removals from the LULUCF sector to offset EU-ESR

emissions, and for some Member States (based on eligibility criteria) to use

part of their EU-ETS to meet EU-ESR targets.

LULUCF Accounting Rules

(529/2013/EU; [20])

Requires Member States to prepare and maintain GHG accounts

(emissions/sequestration) for forests, cropland and grasslands. In the 2013-

2020 accounting period, only the reporting of forest activities (A/R, D and FM)

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is mandatory. Member States must report CM and DM emissions/removals

from 2015 onwards including an outline on the intended improvements in

these reporting systems; prior to their mandatory inclusion from 2021

onwards.

Renewable Energy Directive (EU-

RED),

(2009/28/EC; [21])

Requires that Member States use renewable sources to fulfil at least 20% of all

energy needs and ensure that at least 10% of transport fuels are derived from

renewable sources. by 2020. This directive has implications for biofuel use.

Also relevant to the land sector are the specified biofuel sustainability criteria.

Revised Renewable Energy Directive

(EU-REDII)

(2016/0382; [22])

This proposal sets an EU target of at least 27% renewable energy sources by

2030, and requires that the share of food-based biofuels is limited to 3.8% and

that the share of advanced biofuels increases to 3.6% by 2030.

Fuel Quality Directive (FQD)

(2009/30/EC; [23])

Mandates a carbon intensity reduction of transport fuels within the EU by 6%,

compared to the GHG emissions of conventional fossil-fuel based fuels.

2015 Biofuel Legislation Directive

(2015/1513; [24])

Amends current biofuel legislation (EU-RED, EU-FQD). Of relevance to the land

sector, this amendment (i) limits the share of biofuels and bioliquids derived

from cereal, starch-rich crops, sugars and oil crops and crops grown primarily

grown for energy purposes on agricultural land to no greater than 7% of

specified targets by 2020, and (ii) sets indicative targets for advanced biofuel

use by 2017, (iii) specifies and harmonises the list of biofuels which contribute

double to 2020 transport energy targets.

EU Forest strategy

(COM(2013) 659; [25, 26])

Provides a framework for forest related policies promoting a coherent and

holistic management approach. It identifies principles to strengthen forest

management whilst also ensuring forest protection and the maintenance of

ecosystem services.

Common Agricultural Policy (EU-

CAP) [27]

Considered central for steering farm level decisions in support of climate

protection in Europe. The new EU-CAP (2014-2020) is centred around three

long-term objectives: (i) viable food production, (ii) sustainable management

of natural resources and climate action, and (iii) balanced territorial

development. Pillar one supports the income of farmers via direct payments.

Included within this pillar are a set of three ‘greening measures’, namely, (i)

the maintenance of permanent grassland, (ii) ecological focus areas, and (iii)

crop diversification. Pillar two supports rural development and requires that

national and/or regional rural development programs (RDPs), be based upon

common EU priorities; which include the restoration of ecosystems and shifts

towards low carbon/climate resilient agricultural systems.

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Box 2: Defining land-based mitigation options

Bioenergy is a term referring to multiple types of biomass used for fuel, electricity or heat generation.

Liquid biofuels (most commonly bioethanol and biodiesel) can be used as a replacement for, or

additive to, conventional transport fuels. Bioethanol is obtained from the fermentation of sugar or

starch rich crops (sugarcane, sugar beet, wheat) [28]. Biodiesel is produced through the

transesterification of animal and vegetable fats (rapeseed, soybeans, palm oil, Jatropha) [28]. The EU,

as of 2011, was the largest producer and consumer of biodiesel [28].

Bioenergy feedstocks can be referred to as first (conventional) or second (advanced) generation.

Second generation bioenergy sources are derived from feedstocks that are not food crops. The only

food crops that can be used in second generation processes are those that have already fulfilled their

food purpose, that is, wastes or residues. Third and fourth generation biofuels are typically algal or

microbe based and do not require arable land for their production [29]. Currently an area of

experimental research, third and fourth generation biofuels are not included in this synthesis.

In future development scenarios, bioenergy use is typically deployed in parallel with carbon capture

and storage (CCS), referred to as bioenergy with carbon capture and storage (BECCS). The

combination of biomass and CCS is based on the principle that CO2 sequestered by the biomass during

its production is prevented from re-entering the atmosphere when that biomass is harvested/used.

Instead, the CO2 is captured, transported and deposited in long-term geological storage. The highest

potential for BECCS has been identified in the electricity sector [30].

In the context of the Kyoto Protocol (see Annex 1.1), afforestation is defined as the “direct human-

induced conversion of land that has not been forested for a period of at least 50 years to forest land

through planting, seeding and/or the human-induced promotion of natural seed sources” [31].

Reforestation has a similar Kyoto Protocol definition in that it is a consequence of human-induced

planting, seeding and/or natural seed source promotion. However, reforestation is defined to occur

on land “that was forested that has been converted to non-forested land2” [31]. Deforestation is “the

direct human-induced conversion of forested land to non-forested land” [31].

2 Within first commitment period (KP1) reforestation activities were limited to “reforestation occurring on those lands that did

not contain forest on 31 December 1989” [31].

15

Box 3: Projected bioenergy trends in Europe

In Europe, renewable energy sources are projected to increase in line with legislative targets.

Bioenergy is a key element in this renewable energy portfolio with projections estimating it will

account for 56% of renewable energy supply, in the EU-27, by 2020 [32]. It is expected that dedicated

energy crops will contribute most to this energy source with estimates of the resource increasing to

4.3-6.0 EJyr-1 in 2030, 3-56 EJyr-1 in 2050 and 22-34 EJyr-1 by 2100. This is in comparison to 2010 levels,

which are estimated to be between 0.8-2.0 EJyr-1 [32]. Agricultural residues, predominantly from

cereals (wheat, maize, barley and rye), are utilised as an alternate biomass source in Europe.

However, Bentsen and Felby (2012) [32] could identify no unanimous future trend in the continued

and/or expanding use of this resource. High levels of uncertainty were also associated with the

estimation of current and future forest biomass trends (Bentsen and Felby, 2012) [32].

Based on 23 National Renewable Energy Action Plans (NREAPs) defined under the EU-RED, Bowyer et

al. (2011) [33] estimates that, by 2020, a total of 26 MtOe (Million tonnes of oil equivalent) of biofuels,

72% biodiesel, will be used by the transport sector of these EU Member States. The same Member

States used approximately 9.4 MtOe in 2008. Over 92% of this projected biofuel increase is estimated

to come from conventional (first generation) feedstocks with a high reliance on imports; the 23

Member States anticipate importing 50% and 41% of bioethanol and biodiesel, respectively, in 2020

[33]. Despite the inclusion of incentives to promote second generation (or advanced) biofuel use

under the EU-RED, their increased adoption was not apparent in the NREAPs. NREAPs anticipated that

advanced biofuels would account for only 0.6% of total transport energy inputs in 2020. However,

increased variability was observed at the scale of the Member States [33].

16

Topic 1: Land-based mitigation competes for land and this has negative consequences 1a. Land-based mitigation increases food prices because of land

competition and the direct use of food crops as a bioenergy feedstock

Land-based mitigation, biodiversity conservation and agricultural production represent competing land-

use demands. For a given CO2 sequestration rate, land competition will, in part, be a function of the

land-use intensity of the mitigation strategy employed; the area of land required per CO2 equivalent

removed from the atmosphere. BECCS land-use intensities, while variable (1 - 1.7 ha t-1 Ceq yr-1 for forest

residuals to 0.1 - 0.4 ha t-1 Ceq yr-1 for bioenergy crops [8], are typically higher than for A/R [34] A median

BECCS deployment of 3.3 GtCyr-1, as typical of 2 °C consistent scenarios, would require 7-25% of

agricultural land as of 2000, if achieved with highly productive bioenergy crops [8]. A/R removals of 1.1

GtCyr-1 or 3.3 GtCyr-1 require 6-20% or 21-64% of agricultural land, respectively, and are largely

considered unrealistic [8]. None of the stated land requirements can be accommodated in current

agricultural areas identified as being abandoned or marginal, as they exceed these land categories by

two to four times [8].

Biofuel production competes with food production both directly, that is, food crops are diverted into

first generation biofuels, and indirectly, through resource (land, labour, inputs) competition [28] In 2011,

bioenergy feedstocks represented approximately 1.8% of total agricultural area, an expansion of 36%

since 19943 [35]. Evidence suggests that food prices, particularly during 2002 and 2007, were influenced

by increased biofuel production; biofuel expansion may have contributed up to 30% of the observed rise

in cereal prices [28].

Cereal based biofuel targets will significantly disrupt food/feed production; model projections conclude

that cereal price increases of 5%, 20% and 34% may be observed where first generation biofuels

constitute 2%, 4% and 6% of the transport fuel mix, respectively, by 2020 [36]. Price impacts are not

uniform, with a greater concentration of impacts in developing countries. NREAPs demonstrate that

bioenergy demand in the EU-27 will require an increase in biomass to 10.0 EJ by 2020. This requirement

includes approximately 0.1 EJ of EU grown food crops (first generation biofuels) and 0.5 EJ from

countries external to the EU-27 [32]. These results support the consensus that there is insufficient land

to meet biofuel feedstock demand within the EU [32, 37] and demonstrates the international reach of

EU policy on the use of foodstuffs as a renewable energy source.

Restrictions on agricultural expansion, as a consequence of A/R and AD policies, may have substantial

effects on food pricing [34, 38]. Kreidenweis et al. (2016) [34] demonstrate a 40% increase in global food

prices where AD mitigation policies are prioritised. In modelled scenarios, unrestricted A/R policies were

projected to result in a 400% food price increase up until 2100; a consequence of substantial

3 While expanding significantly, bioenergy represented less than one-tenth of the increase in agricultural land demand globally;

change is primarily driven by dietary preferences (see Issue 5c) (Alexander et al., 2015).

17

land/resource competition. Geographically targeting A/R policies within the tropics, the zone of highest

cooling effectiveness (see Issue 3), minimised food price impacts at a global, but not regional, scale.

Land-based mitigation is one factor in a complex set of drivers of food production, food pricing and

agricultural change. Future agricultural expansion will be a function of a complex interaction of

intensification dynamics, endogenous factors (population dynamics, consumption, wastage,

technologies, political decisions) and exogenous factors (international trade) [39, 40].

Climate change at lower levels and associated influences on crop productivity (CO2 fertilisation and crop

water efficiency), has been associated with reduced global demand for agricultural land (330 Mha in

2100) (Humpenoder et al., 2015) [41]. This agricultural reduction translated into a greater retention of

forests (62 Mha) and increased availability of land on which natural vegetation regrowth could be

permitted (268 Mha); outcomes that increase land-based carbon sequestration [41].

Technological developments and the intensification of food production could also reduce the arable

area required to meet demand and, consequently, provide additional space for land-based mitigation

measures. Yield increases, it is argued, are required in the presence of afforestation [34] and BECCS [42]

policies. Required bioenergy yield increases (of 1-1.38% yr-1 up until 2100) are lower than historic

change. However, it is unclear whether future yield increases in the agricultural sector will be applicable

to bioenergy crops; food production targets the edible parts as opposed to carbon accumulation pools

of the crop [42]. Increased research and development is required if projected yield requirements are to

be met in both food and energy crops [34, 42]. However, while increasing yields may be advantageous

from a land resource perspective, agricultural intensification must not be considered in isolation.

Caution must be exercised when such increases require substantial increases in agricultural inputs

(energy, fertiliser); inputs associated with GHG emissions and environmental impacts (see Issue 2a).

Yield increases may also be associated with rebound-effects, that is, increased consumption. Increasing

consumption is a benefit where it reduces hunger, but is less positive in the context of excessive

consumption and obesity [43].

Policy implications

Resource competition between food and bioenergy has led many countries to prohibit the use of first

generation (food-based) biofuels. Legislative approaches include the incentivising of non-food crops

(Molasses/Jatropha in India) or use of low-quality stockpiled food crops (corn in China) [44] for biofuel

production. In Europe, the 2015 RED directive (2015/1513 [23]) limits the share of food based biofuels

(7% of specified targets by 2020), sets indicative targets for and incentivises advanced (second

generation) biofuel use. European agricultural policy also has a direct influence on biofuel trends with

an increasing trend towards short rotation (1-10 year) energy crops (lignocellulose) due (in part) to

financial support under the CAP [32].

18

Multiple studies have demonstrated a causal link between future land-based mitigation policies and

food production/pricing [40-42, 44]. Stevanovic et al. (2017) [40] demonstrate that incentive-based

policies (carbon taxes, forest protection) have a greater impact on food prices than preference-based

approaches (dietary change, waste reduction) despite their similar mitigation potentials. Incentive-

based policies increase land and resource competition and thereby food production costs. Conversely,

preference-based mitigation increases land availability and concentrates agricultural production in the

most productive areas, lowering the costs [40]. Policies targeting consumer preferences, consumer

education programmes, and transparent markets should be considered in tandem with production or

supply-side mitigation approaches [40] (see Issue 5c). Incentive-driven policy, with an aim of food price

stabilisation, would benefit from some form of social safety programme in order to exclude food price

impacts on poorer communities [40, 41].

The food-energy nexus of land-based mitigation requires integrated policy to balance cross-sectoral

synergies and trade-offs. Land-based mitigation measures linked to improved food production (and

potentially food security), such as agroforestry, sustainable intensification of agricultural production and

integrated systems, should be explored as potential co-benefits [43].

1b. Land-based mitigation competes for land with ‘nature’ and the

maintenance of biodiversity

The magnitude of habitat loss, change and degradation associated with bioenergy driven LULCC, is a

function of multiple factors, including: (i) the type of LULCC conversion, for example the conversion of

natural ecosystems will have greater biodiversity impacts than a change in crop within currently

cultivated areas [44]; (ii) the spatial extent and pattern of this conversion [45]; (iii) the feedstock being

produced, as for example some feedstock species have been identified as invasive [28, 44]; and (iv)

changing hydrological regimes (see Issue 2a).

A/R cannot be assumed to be synergistic with biodiversity protection and/or enhancement. In Europe,

temperate forest extent has increased as a consequence of A/R policies and the successional

development of abandoned semi-natural grasslands (grasslands created/maintained by low-intensity

management). While above-ground carbon stocks will increase with the establishment of woody

vegetation, the implications for biodiversity and soil carbon are less clear; plant species richness has

been shown to decrease [46]. In European production forests, policies designed to support climate

change adaptation and mitigation are increasingly being identified as counterproductive to biodiversity

goals [47]. Mitigation strategies that reduce the native species composition/diversity of forests (e.g.

conversion to introduced conifers), the removal of important habitat structures (e.g. the removal of

19

coarse woody debris as logging residue), or change natural disturbance regimes (e.g. shortened rotation

times) have been found incompatible with national biodiversity policies, exemplified by Sweden [47].

Competition for land can be satisfied by fulfilling multiple demands at once (multi-functional land

systems) or the specialisation of landscapes in terms of the goods/services they provide [48]. Eitelberg

et al. (2016) [48] conclude that biodiversity conservation and/or carbon storage are likely to benefit

from the specialisation (and spatial segregation) of land systems, although results are region specific. In

Europe, the authors conclude that the protection of biodiversity is likely to increase cropland

intensification within a constrained and contracting area when compared to carbon storage or reference

scenarios [48]. The role of specialisation and intensification of land systems in a biodiversity context is

debated. Several authors propose that intensification is an inevitable step towards protecting

biodiversity [49, 50] while others argue that such specialisation does not account for the complexity of

species/ecosystem interactions [51, 52].

Policy implications

From a policy perspective, biodiversity protection is typically used as a criterion in sustainability

standards; see, for, example EU-RED [21] and EU-FQD [23]. Voluntary sustainability standards in a

biofuel context include the Roundtable on Sustainable Biofuels or those relating to a particular feedstock

(e.g., Roundtable on Sustainable Palm Oil). Such initiatives have a significant influence on the

development of the biofuels sector [28]. While such frameworks are advantageous in terms of their

simplicity, Gasparatos et al. (2011) [28] argue that a discrete list of sustainability criteria/targets excludes

the interrelations between, and dynamic nature of, criteria within social-ecological systems. It is in this

context that authors argue for the integration of biofuels within an ecosystem services narrative.

Adaptation and mitigation strategies inconsistent with biodiversity goals will, Felton et al. (2016) [47]

argue, continue to be used (and expanded) as long as they are perceived to (i) carry a reduced risk, (ii)

increase production capacities, or (iii) are associated with increased economic returns. In plantation

forests, for example, the removal of logging residues is risk free in terms of continued production and

produces an additional income [47]. In the context of forest management, feasible pathways that

through targeted regulations or policy incentives support continued forest production, climate

adaptation/mitigation strategies and biodiversity, can be identified [47]. Such pathways (i) prioritise and

incentivise the use of strategies consistent with both goals, (ii) adjust conservation practices to

compensate for mitigation strategies inconsistent with biodiversity goals, and (iii) ensure forest

management at a landscape scale encompasses a range of techniques, including those beneficial to

biodiversity [47].

The introduction of fast-growing, short rotation woody biofuel crops, as seen in Europe, in part due to

CAP incentives [32], has mixed biodiversity impacts; a function of the species introduced and

20

management practices implemented [47]. Short rotation times are inconsistent with biodiversity goals

that aim to increase the age-diversity of forests and emulate natural disturbance regimes [47]. Crop

rotation length, from an energy perspective, characterises the flexibility (regarding crop selection),

productivity, and growth pattern of the bioenergy resource [32]. Combining the characteristics of

different woody biofuel crops may therefore be beneficial to the development of a productive and

secure energy supply [32]. Increased crop diversity also resonates with biodiversity/sustainability goals

[47]. Such a synergy highlights the ability of policies to encompass energy security, land-based mitigation

and biodiversity.

Multiple European biodiversity policies specifically address the maintenance of semi-natural grasslands,

for example the Natura 2000 network and LIFE+ programme [46]. However, conflicting climate-driven

policies, which prioritise A/R within these regions, have the potential to further risk biodiversity loss

[46]. Conflicting policy objectives and outcomes are ineffective. An integrated, cross-sectoral policy

framework is fundamental in promoting synergies and balancing trade-offs.

1c. Land-based mitigation in one location can directly affect land use

elsewhere due to displacement effects, an example of indirect land-

use change

Indirect land use change (iLUC) is caused when existing arable land is used to grow, for example,

bioenergy crops, pushing food and feed production into new areas such as forests and grasslands [54].

iLUC is associated with substantial GHG emissions, as there are major initial emissions from converting

natural ecosystems into cropland through the release of locked up carbon in biomass [55] and soil [56].

In croplands, regular harvest undermines carbon storage over time [55]. When replacing natural

vegetation, it can take between 1 and 162 years to achieve GHG savings as compared to continued fossil

fuel use, depending on the LULCC conversion, crop, management intensity and geographical location;

GHG payback times tend to be longer in tropical regions [55]. iLUC derived GHG emissions have the

potential to undermine conventional biofuel technologies as a sustainable and renewable energy source

[33].

When GHG emissions from iLUC are included in life-cycle analyses (LCA) of biofuels, it can alter the

relative performance of crops [37]. Evidence suggests that bioethanol feedstocks such as cereals and

sugar perform better than biodiesel crops when iLUC is included in the analysis [37]. When accounting

for iLUC, the transport biofuel targets put forward by the EU-RED could lead to between 80.5% and

166.5% more GHG emissions than if the same fuel needs were met from fossil fuel sources.4 However,

the inclusion of iLUC in LCAs of biofuel production and use is variable, as these factors are often

associated with great uncertainty.

4 This estimate represents a mean of three emission estimates each based on different default emission values associated with

a land use conversion to arable lands. Results encompass 23 EU Member States [35].

21

The displaced production can move to distant geographical locations, and in the EU, iLUC will take place

outside the union’s borders almost in its entirety [33]. As deforestation inside the EU is negligible, the

concept of ‘embodied deforestation’ aims to link deforestation to consumption, by considering the life-

cycle of imported commodities [57]. The EU (EU-27) was the largest net global importer of embodied

deforestation in 2013, and particular concern has been highlighted with regard to the continued use and

intensification of palm oil derived biodiesel inside the European market, a principal commodity

associated with embodied deforestation. However, the introduction of sustainability standards (see

Table 3) is expected to reduce the overall iLUC of palm oil [37].

Farm-management intensification significantly influences soil organic carbon losses and the GHG

emissions of resource inputs (machinery, fertiliser). Models have associated cultivating biofuels under

high input (fertiliser and irrigation) systems has been with shortened GHG payback times in a majority

of locations due to the offset of GHG emissions by higher crop yields [55]. However, agricultural

intensification cannot be considered in isolation with potential trade-offs with environmental

sustainability criteria (see Issue 2a).

Displacement, also referred to as forest leakage, has been a key criticism of REDD+ [38]. Equally, the

exclusive protection of forests could increase (i) conversion pressures on non-forest, high-carbon,

ecosystems (shrubland/savannah), or (ii) result in the conversion of grassland and pasture (which

maintain vegetation cover and are associated with higher levels of soil carbon) [38]. Popp et al., (2014)

[38] estimate a sink (uptake) of 55Gt CO2 (until 2100) under a REDD+ type (forest-only) conservation

policy. This is in comparison to 191Gt CO2 under a more inclusive global, terrestrial carbon policy (a

universal carbon tax). Policies that are inclusive of all land cover types minimise forest and non-forest

leakage. However, in the absence of such an encompassing approach, there is a need to protect non-

forest ecosystems of high value for carbon storage and biodiversity [38].

Policy implications

It can be argued that iLUC, and associated GHG emissions, necessitate policies to be refocussed towards

alternate routes of delivering the 2020 EU-RED transport targets, for example, by using advanced

biofuels or promoting energy efficiencies within the sector [33]. To some extent, this change was

enacted in the 2015 EU-RED directive (2015/1513; [23]), which limits the share of food based biofuels

(7% of specified targets by 2020) and sets indicative targets for advanced (second-generation) biofuel

use. However, with a consensus that there is insufficient land to meet biofuel feedstock demand within

the EU [37], strong EU-RED sustainability criteria (and associated policies) will be required to prevent

iLUC.

Under current EU legislation, biomass used in the generation of electricity, heating or cooling is

considered carbon neutral in respect to emission targets, for example in the EU-ETS, as it assumes that

both direct and indirect LUC emissions will be captured in the land sector. This assumption of carbon-

neutrality underestimates total GHG emissions by failing to consider biomass production (and associated

22

iLUC), processing and transportation. Such exclusions can result in substantive emissions under-

reporting, for example, Murphy and McDonnell (2017) [58] demonstrate a 30% increase in EU-ETS

emissions reported at a single co-fired power station with the inclusion of biomass accounting.

In reviewing the INDCs for Malaysia, Indonesia and Ukraine, significant biomass sources within the Irish

energy sector, Murphy and McDonnell (2017) [58] reflect on how post-COP21 (Paris Agreement) pledges

might influence indirect (iLUC) GHG emissions. Of the INDCs analysed, only the Indonesian INDC

mentioned measures with the potential to reduce GHG emissions within exported biomass (in this

instance, a moratorium on the clearing of primary forests and prohibition of peatland conversion) [58].

If achieved, such measures were demonstrated to decrease indirect GHG emissions from Indonesian

palm kernel shell feedstocks by 32%. It is in this context that the Paris Agreement, and its associated

legislative instruments, has the potential to reduce existing carbon leakage [58].

In Europe, adjustments in trade policy, labelling schemes and voluntary certification schemes could

significantly decrease embodied emissions from European imports [37]. Specific policy options are: (i)

biofuel sustainability criteria are extended (by regulatory measures, market-based instruments and

voluntary agreements) to multiple agricultural crops (food, vegetable oils, feed crops, products); (ii) that

the forest law enforcement, governance and trade mechanism apply to commodities derived from

illegally (iLUC) created agricultural fields in addition to timber products; (iii) that a forest footprint is

compulsorily labelled on food products imported into the EU; and (iv) that sustainability criteria be

introduced on products associated with deforestation (for example, import tariffs) with the potential to

ban those linked to high levels of iLUC [37].

Promoting cross-sectoral, integrated and coherent policies is fundamental. For example, a strengthening

of the CAP could, Massey et al. (2015) [37] argue, promote the conversion of land removed from

agricultural production (that is, abandoned agricultural areas) to biofuel production. Such a policy has

the potential to decrease agricultural expansion, and/or iLUC, as a function of growth in the biofuel

sector.

Topic 2: Land-based mitigation has trade-offs with, but also co-benefits for, the provision of ecosystem services 2a. Land-based mitigation impacts on the ability of ‘nature’ to provide

other ecosystem services

Ecosystem services can be defined as the benefits people derive from ecosystems, and include

provisioning, regulating, cultural and supporting services [59]. LULCC has the potential to (i) exclude

ecosystem service provision, for example, due to the removal of natural ecosystems, and/or (ii) impair

the quality and quantity of a service provided by an ecosystem.

Biofuels influence both the quantity and quality of the water provisioning ecosystem service. The water

footprint of biofuels is larger than for alternative forms of energy, ranging from 1,400 to 20,000 litres of

23

water per litre of biofuel produced5, and aggregate water demand is expected to double by the end of

the century6. Increased water consumption must be framed within the context of a changing climate;

high temperatures necessitate more irrigation to maintain crop yields [62], and extensively irrigated

bioethanol production has the potential to deplete aquifers vulnerable to water shortages under future

climate scenarios [63]. The water demand of biofuels can be constrained with water protection policies,

but increasing land demand and yield technology investment are characteristics of scenarios with

stringent water policies [61, 64]. In the presence of extensive water protection policies (excluding

irrigated bioenergy production) the land required to meet the same biofuel target (300 EJ/yr) increases

substantially (+41%), typically at the expense of pasture areas and tropical forests [61].

The influence of land-based mitigation strategies on the hydrological cycle is not confined to bioenergy

feedstock production, with changes also attributed to A/R, forest management and deforestation [43].

Tree species selection can influence the water balance, for example, species roughness and species type

influence evapotranspiration (see Issue 3). Plantation forests, and the use of exotic species, can

negatively impact water availability within a region due to modified evapotranspiration regimes,

particularly in the context of a changing climate regime [65]. For example, species conversion from pine

to hardwood species was found to decrease streamflow by approximately 200 mmyr-1 [66].

The climate-regulating function of forests (precipitation, temperature) at local and regional scales

should be recognised in addition to their role in carbon storage, timber and non-timber service

production [65]. In an alternate perspective, proposed by Ellison et al. (2017) [65], the carbon-

sequestration potential of forests could be seen as a co-benefit of reforestation targeted to protect the

hydrological cycle and increase localised cooling.

Feedstock production requires fertiliser and agrochemical use; chemicals that can enter natural

ecosystems, in particular water bodies, and disrupt ecosystem functions (see exemplar studies citied in

[28] and [44]). Increasing land-use intensities, due to LULCC and/or changing management practices,

increase potential nitrogen losses [43]. Nitrogen losses to the atmosphere (NH3, NOx) and water bodies

(eutrophication) contribute to issues of both air and water quality. The removal of biomass from an

agricultural or natural ecosystem, for use as a bioenergy feedstock, removes nutrients from the site. This

soil nutrient depletion necessitates future fertiliser inputs, which links to GHG emissions and nitrogen

loss [8].

LULCC is currently a source of GHG emissions and hence impairs the ecosystem service of climate

regulation. The magnitude of these emissions is a function of the LULCC conversion and subsequent

crop/land management practices which influences the soil carbon balance, for example perennial

biofuel feedstocks (Miscanthus, sugar cane) sequester more soil carbon than annual species [32]. Biofuel

production emits N2O primarily through fertilisation of the crop during feedstock cultivation.

Uncertainty remains in both the quantification and inclusion of N2O emissions within biofuel LCA [28].

As with other plants, biofuel feedstocks emit volatile organic compounds, in particular isoprene, during

cultivation. Studies have demonstrated that such emissions may be greater over tree plantations (for

example, oil palm) than natural ecosystems. Other emissions from biofuel cultivation that can impact

5 These numbers represent 12 of the most common bioenergy crops [60]. 6 If bioenergy demand is expected to reach 300 EJ/yr [61].

24

air quality include particulate pollution resulting from land clearance, particularly where clearance is via

slash/burn methods [28].

Policy implications

Mitigation measures identified to reduce the impact of bioenergy on ecosystems and biodiversity

include the adoption of environmentally friendly production practices, the locating of bioenergy

production in marginal/degraded lands, and the design of multi-functional landscapes. Therefore, there

is a need for systematic land-use planning in achieving bioenergy production targets while also balancing

trade-offs [44]. Measures designed to minimise biofuel impacts could be promoted through both

regulatory instruments and market-based mechanisms such as certification.

Complexities within (i) the biofuel production chain, for example in terms of the feedstock or land

management approach, and (ii) biofuel markets which are driven by multiple incentives/drivers, make

sustainable policy-making challenging. Gasparatos et al. (2011) [28] contend that markets cannot

provide an institutional framework sufficiently able to communicate and value ecosystems and the

services they provide. There is, therefore, a need to establish a set of sustainable development standards

for biofuels grounded in the ecosystem service concept.

Integrated policy frameworks (explored further in Issue 6b) are fundamental to sustainable

environmental management. As exemplified above, policies that incentivise rain-fed bioenergy

production, while useful in protecting water resources, neglect the trade-off with land resources [63,

64]. Rather than universally promoting rain-fed bioenergy production, policies could promote

sustainable levels of water use as defined at a site-specific scale [63], for example by environmental

flows [61]. The incorporation of bioenergy in an integrated water (and land) management strategy

should minimise the land area of bioenergy crops by increasing yields under irrigation while protecting

freshwater from over-extraction and natural ecosystems from iLUC [61]. A further element of the policy

nexus is, however, identified, one of sustainable development; where water management strategies are

put in place, policies must consider the economic implications of increased land competition and their

resultant implications for, for example, food prices [64].

2b. Co-benefits between land-based mitigation and ecosystem service

provision are feasible

While discords between EU forest based adaptation/mitigation strategies and biodiversity policies has

been identified, synergies are clearly evident (Felton et al., 2016). Increased rotation times within

plantation forests can increase carbon storage while also increasing tree age-diversity, increasing coarse

woody debris and providing disturbance regimes more similar to natural conditions; all aspects

identified as important in forest biodiversity goals (Felton et al., 2016). Mixed species forests may be

25

more productive and resilient ecosystems than monocultures and often appear to be characterised by

improved drought resilience and tree growth [65].

Biofuel feedstocks can be used to purify wastewater, restore aquifers and improve marginal lands.

Jatropha, for example, has the potential to improve soil quality and control soil erosion [28]. Second

generation biofuel crops also have the potential to provide species habitats and/or enhance ecosystem

service provision, for example, through pollination or biocontrol [28]. However, the expansion of second

generation biofuels into non-cultivated areas would impact biodiversity, irrespective of these co-

benefits [44]. The biodiversity impacts of biofuel feedstock cultivation can be lowered where techniques

such as land sparing and sustainable farming approaches are employed, for example the exclusion of

extensive monocultures [28].

REDD+ programmes to reduce climate change emissions are designed to provide co-benefits through

forest conservation and sustainable forest management. The maintenance of intact forest ecosystems,

habitats and species diversity supports purification of the air/water, soil conservation and provides

benefits to the local community (health, spiritual, access to food, fibre) [67]. Upland reforestation, at a

catchment scale, has been shown to regulate water flows [65] and improve water quality [32]. Tree-

planting (A/R) can create wind-breaks that improve soil retention and support salinity remediation [43].

Synergies between A/R, AD and their associated co-benefits must be effectively designed and managed.

The scale of carbon-sequestration from afforested climate-resilient genotypes is dependent on the

ability of the new species to sequester carbon [68]. Equally, tree species selection can affect carbon

allocation to above- and below- ground stocks; soil carbon stocks are larger under hardwoods or

nitrogen-fixing tree species [39]. Woodland establishment on upland grasslands, while increasing above-

ground carbon storage, may under certain soil/tree species conditions result in soil carbon losses and/or

the removal of land from agricultural systems [69]. While woodland ecosystems as a whole (above-

ground biomass and soil carbon) have a greater carbon storage potential, silvo-pasture systems

(agroforestry), which integrate farming and forestry on the same area of land, have similar or higher soil

carbon stocks [68]. Silvo-pastoral systems, therefore, offer increased carbon stock benefits (in

comparison to pasture) without the exclusion of livestock and loss of agricultural land [69]. Silvio-

pastoral systems have also been shown to reduce wind erosion, promote soil fertility, control land

degradation/erosion and increase productivity while also co-benefiting biodiversity [43].

Protecting biodiversity can improve carbon stocks, contributing to land-based mitigation, where

degraded (high-carbon) ecosystems are restored and retained [70]. The protection, maintenance and

restoration of these ecosystems would also align with indicators and objectives in the EU 2020

biodiversity strategy [71]. Climate-smart conservation, the identification of regions with high

biodiversity and high soil carbon content, but low land price, is a cost-efficient approach to climate-

biodiversity management. Protected areas within the Natura 2000 network (EU-28 excluding Croatia

and Cyprus), although not designed for this function, capture a proportionally higher (10%) top soil

carbon than unprotected sites [70].

26

Harnessing synergies within multi-functional landscapes offers the potential to reduce resource (land,

water) competition. For example, the low-intensity management (and restoration) of semi-natural

habitats (meadows, dunes, grasslands, heaths and wetlands) in the Natura 2000 network could produce

harvestable bioenergy feedstock; estimated at 12.0 to 14.7 Tg (dry matter) annually [72] Biomass

production within these ecosystems has the potential to contribute to rural livelihoods by raising and

diversifying farm incomes and increase employment. As Natura 2000 sites do not overlap with food

production areas, the use of Natura 2000 bioenergy could offset iLUC; sites with bioenergy potential are

estimated to be between 1.2 and 2.8 Mha. The active management (in addition to delineation) of

protected areas in semi-natural ecosystems, characteristics of the Natura 2000 network, is essential in

preventing their degradation and preventing biodiversity loss [72]. Such management can also support

land-based mitigation policies.

Within agricultural dominant ecosystems, grassland restoration and protection, the conversion of arable

land to grassland, rewetting and expansions of agricultural peatlands (mires, bogs, fens) and reduced

peat use, have been identified as important LULCC conversions that can support multiple co-benefits,

including land-based mitigation [37]. Grazing can increase/decrease soil carbon stocks; as a function of

the grazing intensity. Crop residue management (removal or retention), tillage practices can influence

GHG emissions, and soil carbon [39].

Policy implications

There are few explicit references to, or analyses of, the within- and cross-sectoral impacts of climate

adaptation and mitigation measures; synergies and conflicts are under-represented [68]. The need for

cross-sectoral integration and the identification of co-benefits is acknowledged in current international

adaptation policies; the EU strategy on adaptation to climate change highlights the increasing

importance and recognition of ecosystem-based approaches. There is, however, a need to consider

within- and cross-sectoral interactions when implementing mitigation policies, to enhance positive

outcomes and avoid unintended consequences. The realisation of co-benefits and synergies will provide

opportunities for more efficient and cost-effective land-based mitigation (and climate adaptation)

strategies [68].

Different policies and policy mechanisms (e.g. uniform, discriminatory, and targeted sectors payments)

can be devised to support both carbon sequestration (land-based mitigation) and biodiversity co-

benefits. In a comparison of alternate policy scenarios, Bryan et al. (2015) [73] argue that discriminatory

(rather than uniform) payment schemes, which take advantage of land-use competition and seek

multiple (multi-functional) outcomes, are the most cost-effective with an ability to be tailored to achieve

a combination of carbon and biodiversity co-benefits. Uniform payments with land competition

between carbon sequestration and biodiversity goals achieved significant carbon sequestration, but

minimal biodiversity benefits [73]. Policy design and implementation is therefore fundamental in

ensuring policy mechanisms that balance both land-based mitigation and targeted co-benefits.

27

2c. There are trade-offs between energy generation and carbon stocks

for different land-based mitigation options

Land-based mitigation strategies, such as BECCS, A/R and AD, each demand land. Combining mitigation

strategies has the potential to increase overall carbon sequestration rates [42]. However, the strategies

may also compete for resources [6, 42]. Land-based mitigation strategies currently propose the use of

forests (i) as a source of woody biomass for bioenergy production, and (ii) to maximise carbon

sequestration via forest management techniques. Forests are therefore required to provide both

provisioning (bioenergy) and regulating (sequestration) ecosystem services. This multifaceted strategy

has the potential to result in trade-offs [74].

In Finland, current policies have been found to promote forest bioenergy more than, and at the

detriment of, carbon sequestration; indirectly policies are reducing the carbon sink [74]. Bioenergy

demand was found to be supported by specific national policy instruments as a direct consequence of

the assumption that forest biomass is “carbon neutral”. Conversely, no operationalised instruments

were found to govern carbon sequestration (the carbon sink) which was governed only by national

strategies and international frameworks (KP). Makkonen et al. (2015) [74] argue that forest bioenergy

as a provisioning service is a tangible ecosystem services more readily encompassed in a market than

other types of ecosystem services; characteristics that support direct/positive governance through

explicit instruments. This is in contrast to carbon sequestration, a regulating and less tangible ecosystem

service.

At a broader European scale, European policies (and emissions targets, see Table 2) could impact the

current LULUCF sector carbon sink; a function of increased woody biomass demand, changing forest

management and LULCC [6]. In a modelled comparison of the impacts of the proposed 40% GHG

reduction target and energy efficiency/renewable energy policy scenarios, Frank et al. (2016) [6]

conclude that the target will have a small (-1%) negative impact on the European LULUCF sector sink if

biomass demand is largely met through lignocellulosic (advanced biofuel) energy crops rather than

forest removals. Where forest harvest increases (in high biomass scenarios) the LULUCF sink is reduced

by a greater amount (-3%). The European LULUCF sector sink may therefore be vulnerable to policies

that result in increased woody biomass use.

Where ecosystems are both tangible and intangible, as in forests, which provide provisioning

(bioenergy) and regulating (sequestration) services, there is a need to ensure policies balance the need

for both types of services. Tangible ecosystem services are more rigorously governed (as they sit within

established markets) than less tangible ecosystem services, for which markets are emergent and

uncertain [74]. Policy design would benefit therefore from ensuring that synergies and trade-offs are

fully explored, and that the multiple ecosystem services and land-based mitigation strategies are

balanced [74].

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Topic 3: Biophysical and biochemical cycles 3a. LULCC affects climate not only through greenhouse gas emissions

and uptake, but also through biophysical effects, especially at the

regional scale, but this is not accounted for in policy

Biophysical effects include the reflectance of sunlight from the Earth’s surface (albedo), cooling from

evapotranspiration and the absorbance of wind energy. Changes in vegetation cover alter the reflection

of sunlight (albedo); crops and pastures tend to be more reflective than darker forests, and this has a

cooling effect. However, forests have higher evapotranspiration rates than crops and pastures, which

cools the land surface as well as recycling water to fall as rain. Forests also absorb wind energy and this

has implications for local surface temperatures.

Between 2003 and 2012, variation in forest cover generated a mean biophysical warming equivalent to

approximately 18% of global biogeochemical warming caused by CO2 emissions from land-use change

over the same period [1]. The net effects of these processes play out differently in different parts of the

world. Satellite observations show that large-scale regional deforestation has a predominantly warming

effect in the tropics, and parts of the temperate zone, due to reduced evapotranspiration [75]. However,

deforestation causes cooling in the boreal regions, due to increased reflection of sunlight, especially in

winter and spring, but unlike the tropics, in boreal regions the agreement between measurements and

models is less clear [1, 75]. Uncertainties remain regarding the magnitude of the effect, especially for

seasonal variables (e.g., maximum summer temperatures), and for the effects on precipitation, but it is

now well established that the regional biophysical effects of land-cover change are substantial.

Furthermore, biophysical effects on local temperature are more rapid than warming arising from global

atmospheric CO2 levels. Thus, mitigation actions taken at the regional level would benefit from

considering the consequences of biophysical effects on local temperature as well as the impacts of GHG

emissions. There are major benefits in doing so, since accounting for the biophysical climate effects of

LULCC can support both mitigation and adaptation objectives and thus, make policy more effective.

Biogeochemical and biophysical effects vary as a function of the specific management action and/or

dominant land use/cover (Fehler! Verweisquelle konnte nicht gefunden werden.) [39]. Such

management-driven effects operate on a range of timescales; for example, a deforestation event is

associated with immediate emissions and biophysical changes, and, over longer timescales, soil organic

carbon losses [39].

29

Figure 1: The magnitude and extent of biogeochemical and biophysical effects as a function of different ecosystem management regimes [39].

Agricultural practices have the potential to modify surface biophysical properties. Grazing can change

albedo if, for example, plant biomass is reduced and an underlying light/dark soil exposed. Pasture

roughness may also have a small influence on turbulent fluxes. Crop harvest changes surface albedo

while subsequent residue management and/or tillage can affect surface roughness. Soil moisture

changes, due to crop harvest, tillage and/or irrigation, can change both evapotranspiration from, and

the albedo of, the surface [39].

Crops vary in their biophysical properties, in particular albedo (surface reflectance), which has a

dominant effect, in comparison to other biophysical factors, at a global scale; particularly in mid-latitude

temperate and high-latitude boreal regions [76]. The large-scale expansion of bioenergy crops, and

resultant LULCC, will influence albedo driven surface warming/cooling. Projected corn ethanol

expansion in the US has been associated with a net cooling effect (-1.8 g CO2eq per MJ of biofuel

produced), although regionally this varies between 2.0 g CO2eq per MJ (net warming) and -5.7 CO2eq

30

per MJ. Switchgrass expansion is associated with a significant warming effect, on average, 12.1 CO2eq

per MJ and a regional maximum of 21.0 g CO2eq per MJ. While the albedo effect of LULCC is relatively

small for corn, its inclusion in the life-cycle analysis of switchgrass reduces the relative performance of

this bioenergy source; from an 81% (without albedo) to 68% (with albedo) emissions reduction (when

compared to petroleum-derived gasoline) [58]. While albedo effects, resulting from bioenergy driven

LULCC, can be relatively large, they are spatially variable (heterogeneous) as a function of the LULCC

conversion, biofuel type and geographic region [76]. An improved understanding is required of the

biophysical effects of crop selections at local to regionals scales in support of spatial planning and policy

design [76].

Forests are fundamental in driving evapotranspiration and associated rainfall [65]. Forests also influence

rainfall intensity, by providing biological particles for moisture condensation, and have an important role

in moisture transport. Large-scale deforestation has been modelled as resulting in rainfall reductions of

up to 30% [65]. Such characteristics have important policy implications as they imply LULCC in one

location can have significant impacts in spatially disparate areas. Impacts occur over both short and long

distances, for example, long distance dependencies include the Congo and Ethiopian Highlands, or

Amazon and Argentinian Andes [65]. Such dependencies require a greater knowledge and

understanding of evapotranspiration/precipitation triggers, regional scale catchment management and

a greater recognition of forest-water-energy linkages. Integrated policies would benefit from being

placed in policy frameworks that link forests, water and energy at both local and continental scales [65].

Policy implications

Global policy frameworks do not, to date, consider biophysical effects, and hence opportunities exist for

policy to realise co-benefits. Although local biophysical climate impacts from LULCC are large, they tend

to be much smaller when aggregated globally and this has implications for global policy [75]. The process

of including land-based mitigation in the UNFCCC context has been a matter of long and complex

negotiations. Hence, the relatively small and currently uncertain global biophysical effects make it

difficult to justify efforts to include these effects in the complex negotiations of the UNFCCC process, at

present. However, it is now possible to evaluate the regional biophysical impacts (changes in local

temperature) of land cover transitions, following a tiered method similar to that of the IPCC to estimate

the effects of GHG emissions. The method applies three levels of increasing complexity, from Tier 1 (i.e.

default method and factors) to Tier 3 (i.e. country-specific methods and factors). The procedures

proposed for each tier method are transparent, taking into consideration the UNFCCC reporting

principles and could inform mitigation efforts at regional or national scales to realise the co-benefits of

accounting for biophysical effects. Biophysical effects are important for regional scale ecosystem,

biodiversity and water-cycle management (see 0).

Policies that support avoided deforestation, especially in tropical regions, have especially large co-

benefits. Avoided deforestation mitigates global climate change by reducing CO2 emissions. It also

affects the local climate in a positive way by maintaining cooler surface temperatures through

31

biophysical effects. Future climate change will also increase vegetation growth through the effect of

atmospheric CO2 fertilisation and this will further enhance the biophysical cooling effects of forests.

Thus, avoided deforestation as a land-based mitigation option benefits from positive effects on both the

regional and global climate systems.

Topic 4: The longevity and timing of land-based mitiga-tion strategies 4a. The relative contribution of different land-based mitigation

options changes through time

AD provides immediate mitigation gains, whereas afforestation-reforestation can take-up carbon

immediately, but with relatively small annual gains due to the slow rate of forest growth, especially as

forests approach maturity. BECCS enables land to be used indefinitely for carbon mitigation, but barriers

and technology/policy time lags mean large-scale implementation is not likely until around the middle

of the century.

AD requires minimal technology-based input and provides immediate mitigation gains. Implementation

costs vary as a function of both the legislative requirements to protect the forest, and lost opportunity

costs (that is, the benefits which would have been gained by the LULCC) [77]. In contrast, BECCS

deployment is slower, with large-scale implementation unlikely until the middle of the century (see Issue

6d); a consequence of uptake barriers (social, technological and political) and time-lags (see Issue 4b).

As a land-based mitigation option, A/R offers a high carbon sequestration potential at moderate cost

(Kreidenweis et al., 2016) and, as a consequence, becomes cost-effective at a relatively low carbon price

[42]. This contrasts with BECCS, which only becomes cost-effective when the carbon price increases

significantly. As such, land-based mitigation strategies are sensitive to GHG emission taxes and their

trajectories [42], and different strategies become cost-efficient at different points in time, resulting in

different mitigation potentials over a longer time-frame.

In contrast to BECCS, A/R (and soil carbon increases) is associated with CO2 saturation over time [78].

This saturating behaviour of A/R is a consequence of declining carbon removal rates as forests reach

maturity and the land available for A/R becomes constrained [42]. Proposals have been made to mitigate

this effect, for example, Zeng et al. (2013) [79] suggest a cyclical, carbon sequestration strategy in which

A/R trees are harvested and buried, preventing decomposition. Such an approach mitigates (or delays)

the saturating behaviour of mature forests, as a single area can be replanted multiple times.

Alternatively, A/R forest may become a BECCS feedstock where the profitability of carbon removal is

greater under BECCS than A/R [42].

32

As a direct result of increasing woodland harvest and forest aging, the EU LULUCF sink is projected, under

current policy/wood product consumption levels, to decline from -303 MtCO2 in 2010 to -126 MtCO2 in

2030 in managed forests [6]. Compensating factors for this decline are projected A/R, decreasing

deforestation and the long-term storage of carbon in harvested wood products (see Issue 5a).

Consequently, the resultant decrease in the LULUCF carbon sink is estimated to be approximately 18%

(-235 MtCO2 in 2010 to -192 MtCO2 in 2030) [6].

4b. Time lags in the science-policy-society exchange process influence

the effectiveness of land-based mitigation policy

Lags occur in developing science knowledge, exchanging this knowledge with decision makers, policy

implementation, policy uptake (e.g. farmers changing to bioenergy land use), the response of the earth

system to new measures (e.g. the slow rate of tree growth or the take up of carbon dioxide and heat by

land and oceans) and the feedback of policy needs driving the generation of new science knowledge.

Longer-term emission reduction pathways are bounded by multiple factors, including technology

lifetimes, the inertia of change in societal/consumer preferences, policy formation and technology

deployment rates [80]. These processes, and their interaction, influence the effectiveness of land-based

mitigation pathways.

Technology development is further modified by the rate of adoption. The transport sector, and in

particular the vehicle fleet, is typically characterised by a higher technological turn-over rate than, for

example, other industrial sectors, and is, as a consequence, quicker to respond to carbon pricing or

policy mechanisms [81]. It is in this context that von Stechow et al. (2016) [81] conclude that a higher

fuel diversity by 2050 is achievable within this sector, even in the presence of delayed (rather than

optimal) 2°C mitigation pathways.

Financial constraints may impair land-based mitigation uptake. Delayed income returns, a need to

secure start-up finance and project transaction costs constrain the uptake of A/R projects [82]. As forests

require a significant amount of time to become established and yield net carbon sequestration

outcomes, income revenues are delayed; a factor identified as a major constraint to the KP’s Clean

Development Mechanism (CDM) project uptake (see Annex 1.1) [82]. A/R income returns are slower

than both alternate renewable energy programmes and/or land-use types (agriculture). The profitability

of forest-based carbon sequestration is dependent upon multiple factors including carbon prices, on-

going project monitoring/validation costs, and the ability of owners to access additional (agroforestry)

income. High carbon prices, in comparison to timber prices, provide an economic incentive for forest

maintenance. However, where carbon prices fall and timber or other land-use activities become more

profitable, there is an increased risk of deforestation [82]. This is an issue of project permanence (see

Issue 4c).

33

It has traditionally been assumed that land-use systems decisions are based on economically rational

behaviour; an approach which neglects both individual and social behaviours [83, 84]. Increasingly,

evidence shows that mitigation (and adaptation) responses depend on a wider range of social and

political factors both at the scale of the individual and institutions [83]. Societal behaviour has the

potential to influence both the rate and pattern of future LULCC [84].

The spatial diffusion of agricultural practices and technologies is an important behavioural factor driving

patterns of LULCC [85] and, in the context of land-based mitigation, policy effectiveness. According to

the “diffusion of innovation” theory (Rogers, 2003 [86] cited in Niles et al., 2015 [87]), diffusion is a

function of the technology/innovation, social context and communication channels through which the

innovation spreads. The heterogeneity of both the innovation and agricultural space limit universal

predictors of behavioural change in agriculture [87].

Despite financial incentives in the UK bioenergy sector, the area of perennial energy crops is limited

(around 17,000 ha for short rotation coppice willow and miscanthus in 2009) [88] with continued slow

uptake (an area of 1305 ha received establishment grants between 2007 and 2011) [89]. Based on

modelled behaviours and historical analogues (UK oilseed-rape adoption), it can be shown that the

complete adoption of bioenergy crops, to the level identified/proposed for the UK in 2020, could take

20 years or more; even in the presence of favourable policies and subsidies [85]. This has important

implications for policy effectiveness and implies that even with favourable conditions, time lags exist in

the uptake of crops or technologies [85]. Time-lags are evident across land-based mitigation strategies.

Woodland expansion, also incentivised in multiple grant schemes in the UK, is currently insufficient to

meet A/R targets [90]. Farmers and other landholders are critically important in achieving A/R targets.

However, a survey of Scottish farmers demonstrated that those not intending to undertake future A/R

projects outnumbered those who would consider/were intending to expand woodland by more than six

to one [90].

Land-based mitigation depends, through financial incentives, on the support of farmers and landholders;

actors who are influenced by more than economic factors. While economic factors were deemed

important for the uptake of biofuel, in north-east Scotland, non-economic factors were also shown to

be important to respondents; 23% were willing to sacrifice a percentage of their revenue if it meant a

reduction in GHG emissions [91]. Research is increasingly looking to characterise “farmer-types”, a key

set of farmer characteristics that may identify willingness to engage in biofuel [91] and A/R [90] policy

initiatives. As an example, farmers who reported an intent to implement A/R policies were typically

already operating forestry (or another type of diversification), involved in environmental schemes, more

educated, employing higher numbers of people and ‘new’ to farming [90]. Such insights enable

integrated policy formation; for example, support for new entrants to farming, farm diversification and

environmental scheme participation may indirectly encourage A/R [90].

Farmer attitudes and preferences do not exist in isolation, for example, while farmer-types characterise

attitudes to biofuel adoption, uptake is also a function of farming enterprise [91]. In Scotland, for

34

example, cereal farmers were willing to adopt bioenergy crops at a significantly lower incentive level

than other farmers (£210 ha-1 under a subsidy/tax incentive, compared to, for example, £670 for mixed

farmers). Equally, dairy farmers did not adopt biofuels under any financial (subsidy and tax) mechanism.

Policy adoption is a complex interaction of decision-making influences [91].

Policy implications

In characterising decision-making behaviour, it is possible to identify policy mechanisms/instruments

that may influence adoption rates. In the UK, for example, A/R policy could be refocused towards

forestry being an activity that complements and benefits farming, possibly through the avocation of

smaller areas of woodland [90]. Equally, the establishment of strong markets and/or government

supported demand (in the form of subsidies), as a means of ensuring income security and stability, have

been identified as important factors in the establishment of bioenergy crops [91].

Caution is, however, required, when characterising decision making behaviours, as a disparity exists

between intended and actual adoption practices; a disparity that makes policies based on intended

actions ineffective [87]. Drivers of intended and actual adoption of climate change mitigation practices

are different; a belief in climate change was found to be correlated with intentions, but not actions

among New Zealand farmers. Only perceived capacity and self-efficacy were proven to be important

predictors of both a farmers intentions and actions. In this context, policies that build capacity and

support behaviour change could be important in designing and promoting the adoption of mitigation

policies [87].

Different rates of adoption, as a function of farmer-type or enterprise, can lead to inequality within the

farming sector. Farmers who adopt early at a low subsidy/incentive/carbon tax price will gain more, in

terms of their differential income, than those who adopt later, but at a higher price. Increasing financial

incentives, which aim to increase adoption, over compensate those who have already adopted [91].

Such issues highlight a need for equitable policy design.

4c. The success of A/R and AD as mitigation options depends on

continued monitoring and management of forest stands

The inclusion of land use in mitigation policy and reporting frameworks is complex. For forests,

challenges to the policy design stem from the issues of: (i) additionality, a need to show that the land-

use change, for example AD, is additional to “business-as-usual” and separate from non-anthropogenic

effects; (ii) leakage, the displacement of land-use activities to other areas, for example, AD in a given

region could result in iLUC (see Issue 1c); (iii) the heterogeneous nature in which forests sequester

carbon as a function of climate, hydrology and species; (iv) uncertainty in growth conditions (and

therefore sequestration rates) due to variable weather; and (v) permanence, the need to ensure

continued carbon storage [92].

35

Forest based trading in carbon markets, while increasing from 2.1 MtCO2eq in 2005 to 32.7 MtCO2eq in

2013 [129], is only a small proportion (approximately 0.5%) of carbon emissions traded [93]. Forest

trading can be categorised under (a) voluntary schemes (e.g. REDD+), or (b) compliance markets (e.g.

Australia and California), with the average 2013 price of each being USD 4.8/tonne CO2eq and USD

9.7/tonne CO2eq, respectively. However, prices are variable [94].

Forest based trading has, to date, predominantly used project-by-project differentiated carbon

payments [92]. This differentiated payment is at the exclusion of a uniform price per unit (forest area or

management practice). While differentiated systems do not have the efficiency losses associated with

the uniform price approach, transaction costs do increase, that is, the cost of monitoring and verification

on a project-by-project basis. Transaction costs for REDD+ projects, for example, can be considerable,

amounting to up to 25% of the total cost [92].

A further policy mechanism to handle issues of heterogeneity and uncertainty in forest carbon markets

is the inclusion of a risk discount. This approach is exemplified by the New Zealand Emissions Trading

Scheme in which two tonnes of forest carbon are required to offset a single tonne of CO2eq emissions

[92]. In addition to accounting for uncertainty/heterogeneity in the rates of carbon sequestration, this

discount ratio can also encompass the uncertainty associated with non-additionality and/or

permanence.

Standards are a common approach utilised to manage and test for non-additionality; the Verified Carbon

Standard was identified as the most common voluntary standard, accounting for 46% of transaction

volumes in 2013 [94]. Compliance market equivalents include, for example, the Carbon Farming

Initiative of Australia [92].

Two main credit-based approaches, used in practice, have been identified to alleviate issues of

permanence. The first approach is to buffer credits; credits set aside as an insurance against future

carbon reversal (typically within the contract period) whereby liability is transferred to the seller [92].

The second approach differentiates between temporary and permanent credits, an approach utilised by

the CDM. In addition to credit-based approaches, schemes, such as REDD+, also utilise performance

payments to incentivise due diligence in forest management/permanence [92].

Forests are heterogeneous in their carbon sequestration rate leading to uncertainty in forest-based

carbon pricing mechanisms. As A/R mitigation projects are typically based on long rotations, climate

change (temperature, precipitation, CO2 concentration) could both impact future forest carbon stocks

[41]; an additional source of uncertainty. Negative impacts (declining forest carbon sequestration rates)

have the potential to offset carbon sequestration benefits in future time-steps. However, stopping an

A/R project, and converting the land to an alternate use, is prohibitive; the standing forest has a CO2

emissions cost. It is in this context, that A/R projects introduce a path-dependent land-use policy; a path-

dependency which prohibits abrupt land-use change [41].

36

4d. The success of avoided deforestation and reforestation depends

on the changing risks from disturbances, such as climate extremes,

wild fires and pest and diseases, which affect forest permanence

The land-based mitigation strategies of A/R and AD are based on the sequestration of carbon into

standing forest biomass. This sequestration is, however, reversible if natural systems are disturbed; a

process to which they are inherently vulnerable [78]. It is in this context that land-based mitigation

strategies should incorporate risk management, that is, a consideration of those events/factors that may

reverse carbon storage; factors such as wildfires, extreme weather events, pests and diseases [9].

Natural disturbances affect the carbon dynamics and age-structures of terrestrial ecosystems. Such

impacts are largely carbon neutral (over the longer-term) under natural disturbance regimes; a

consequence of ecosystem recovery [95]. Increased climate extremes (heat, waves, storms and

droughts) have the potential to increase the risk of natural disturbance events. A warmer climate could

increase insect outbreaks and/or shift the range of pest species, increase the risks of fires and/or wind

throw. As a consequence, climate change could impact/impair mitigation strategies that are dependent

on the maintenance of long-term terrestrial carbon sinks.

European carbon stocks are significantly influenced by natural disturbances, particularly storms, and the

management strategies (e.g. salvage logging) applied following the event [96]. To date, storms have had

a greater (5-10 times) impact on forest carbon stocks than fire.

Strategies can be employed in an attempt to mitigate natural disturbance threats and ensure robust

land-based mitigation policies. Forest structural changes, such as the promotion of single-species

(conifer) over mixed-species stands, have been shown to increase the susceptibility of forests to natural

disturbances [97]. Tree species selection and appropriate mixes can be used to prevent the spread of

diseases and/or pests, which are factors that can cause tree mortality and a significant release of carbon

[39].

Policy implications

Altered natural disturbance (hurricane, fire, droughts) regimes have critical implications for the

efficiency and pace of societal/technological change required within mitigation pathways [95]. Higher

disturbance regimes lower strategy efficiencies and require larger-scale investments in adaptive

infrastructure and technological investment/deployment. Technology has to be deployed sooner when

it is more expensive and less efficient. Mitigating climate change (to a 3.7 Wm-2 level) under increasing

disturbance regimes is both more demanding and costly; up to 2.5 times more costly in the case of

doubled disturbance rates [95]. Conversely, in the presence of decreasing disturbance rates, the costs

of climate change mitigation strategies are potentially reduced. Understanding future disturbance

regimes is therefore key in understanding and formulating policies for future climate mitigation

pathways.

37

Risks to forest survival jeopardise the permanence of A/R projects, an important consideration in terms

of their associated policy and funding mechanisms. Where policy mechanisms issue temporary credits,

for example, for forest sequestration, natural disturbances pose a risk to the financial income of a given

project; when forests are lost, so too are their associated income. Such risks, and the threat they pose

in terms of income losses, could act as a disincentive to engagement in the scheme [82].

Topic 5: Landscape management and alternate land-use futures 5a. Forest management is increasingly recognised as an important

contributor to land sector carbon fluxes in both science and policy

communities

Forest Management (FM), in the context of the UNFCCC and KP, is defined as “a system of practices for

stewardship and use of forest land aimed at fulfilling relevant ecological (including biological diversity),

economic and social functions of the forest in a sustainable manner” [31]. Also associated with FM,

within UNFCCC and KP, is the Harvested Wood Products (HWP). The HWP constitutes wood and paper

products harvested from forests as part of their management [31].

When considering all activities (FM, A/R, D and HWP), EU forests (i) correspond to approximately 8% of

total EU GHG emissions (without LULUCF), and (ii) are a net sink equal to, on average, -409 MtCO2/yr

between 2000 and 2012. FM accounts for approximately 90% of this sink, with A/R representing the

remaining 10%. The sink is primarily associated with the living biomass carbon pool (80%) with the

remaining proportion in the dead organic matter pool (10%) and HWP pool (10%) [96].

Forest management can influence both the biogeochemical properties of a forest, that is, the sink can

increase or decrease, and its biophysical structure, also a determinant of local climate (see Issue 3). In a

reconstruction of historic European land cover and land use, Naudts et al. (2016) [98] argue that recent

FM in the EU has not resulted in a cooler climate.

Despite the current strength of EU forests as a carbon sink [96], Naudts et al. (2016) [98] conclude that

EU forests are associated with a carbon debt of 3.1 PgC when compared to carbon stocks at the start of

the time series, that is, the year 1750. This carbon debt is a consequence of deforestation, species

conversion and wood extraction from previously unmanaged forests. An associated increase in summer

boundary-layer temperatures, of 0.12K, is primarily associated with a conversion to coniferous (as

opposed to broadleaf) species. A/R had a more influential effect on the radiative imbalance simulated

(0.12 Wm-2) at the top of the atmosphere. A net increase in forest area (by 10%) and conversion (of 85%)

of forests to managed forestry has not resulted in a net CO2 removal from the atmosphere (due to wood

extraction). Furthermore, a change to coniferous species has had a warming effect.

38

Based on the composition of the current forest sink (90% of which is attributed to FM [Pilli et al., 2016])

and influence of forest biophysical structure on climate change mitigation [98], land-based mitigation

strategies should, it is argued, consider both A/R and FM. Under the second KP period, (i) the reporting

of FM is mandatory, through a forest management reference level (FMRL), (ii) FM accounting must

include carbon stock change in the HWP, and (iii) natural disturbance emissions may be excluded, under

certain circumstances, for accounting purposes [96]. The Paris Agreement leaves it to States to

determine how they intend to mitigate their emissions in this sector while reaffirming the importance

of incentivising, as appropriate, any non-carbon benefits.

The EU is considering integrating emissions from land use in the European 2030 climate and energy

strategy (COM(2016) 479 final; [10]) by allowing Member States to (i) use excess LULUCF sector

removals (above the no-debit limit) within EU-ERS accounting, and (ii) meet their “no-debit”

commitment with excess EU-ERS allocations (COM(2016) 479 final; [10]).

To date (and under future proposals), LULUCF-generated carbon credits cannot be traded within the EU-

ETS. Equally, CDM forest-based credits, in contrast to other CDM credits, cannot be traded in the EU-

ETS. This exclusion of the LULUCF sector from current EU policy, in combination with substantive

UNFCCC and Kyoto-based limitations on domestic forest-based carbon credits, (i) isolates the potential

impact of the forestry sector on the EU climate policy framework [99], (ii) leaves a significant land-based

mitigation source untapped [99], and (iii) could lead to forests becoming a biofuel feedstock, that is, a

source of carbon emissions rather than a sink [100].

The inclusion of LULUCF within the EU-ETS has been identified as difficult due to issues of uncertainty

(in carbon sequestration rates and their inter-annual variability), required administrative apparatus and

disparities in the annual compliance cycles of the EU-ETS and longer-term cycles of national forest

inventories [99] (see Issue 4c for a further discussion of these policy issues). Furthermore, concerns have

been raised as to whether the inclusion of LULUCF could weaken the EU-ETS by reducing pressure on

high-emitting industries to reduce fossil fuel use [99].

Forest and FM represent a cost-effective approach to achieving emissions targets. Vass and Elofsson

(2016) [100] assess the cost-effectiveness of forest-based carbon sequestration (at the expense of

bioenergy and the harvesting of forest products) in terms of achieving the EU 2050 carbon reduction

target. In particular, the authors consider whether abatement costs could be reduced by recognising

additional sequestration by standing forest biomass within EU climate policy. Results point to cost-

efficiency in using forest carbon sequestration as a mitigation approach; the inclusion of forest carbon-

sequestration is associated with a 23% reduction in the cost of achieving EU carbon targets [100].

FM accounting, which is mandatory under KP2, is based on a FMRL, that is, a quantified amount against

which performance is compared in the reporting period [13]. The FMRL precludes the definition of a

single base (or reference) year. Proponents of the FMRL argue that it provides a flexible approach able

to accommodate diverse forest sectors and forest age structures in mandatory KP2 reporting. Equally,

the FMRL, as a function of its definition, has the potential to incentivise mitigation actions within the

39

forestry sector. Concerns, in respect to the FMRL, focus on its definition, difference in approach to other

sectors and that it allows real emissions (under the FMRL) to remain unaccounted for. The FRML is

applied, within KP2, in combination with a credit cap, that is, emission removals from FM are capped at

3.5% of 1990 baseline emissions without LULUCF [11].

In a European context, Ellison et al. (2014) [99] criticise the FMRL and cap as, the authors argue, the cap

is (i) preferential to high per capita emitters at the baseline, (ii) unrelated to forest cover/forest potential

growth, and (iii) does not include the adjustments possible under KP1 (3% of 1990 emissions or 15% of

net removals in forests). The authors argue that the FRML and cap system leads to inequalities across

EU Member States and imbalances in the carbon accounting system. Imbalances which could result in

future forest growth not being mobilised and harvest being encouraged [99].

Ellison et al. (2014) [99] provide a discussion on the relationship between the FMRL and set of incentives

it creates. Based on this analysis, it is evident that a conflict exists between the incentives of EU Members

(Parties) and landowners; while Parties face KP2 incentives these are not transferred to landowners.

This, the authors argue, could result in landowners following potentially contradictory incentives, for

example, the harvesting of forests (and their replacement with biofuels). Ellison et al. (2014) [99] argue

that this would, to some extent, be mitigated by the full inclusion of LULUCF within EU climate policy

frameworks. However, this stance remains contested.

Pilli et al. (2016) [95] estimate that in five of the 26 EU Member States analysed (Cyprus and Malta are

excluded from the EU-28) the HWP pool contributes greater than 20% of the current total FM carbon

sink. The HWP sink, which in the future can be maintained or further increased (by increasing harvest

rates or the proportion of harvest held in long-lived products), represents an important component of

land-based mitigation. Policies and mitigation strategies should, however, consider the HWP with

caution. In four of the EU countries analysed, Pilli et al. (2016) [95] find that the current HWP is an

emissions source (due to industrial roundwood harvest). Careful management of the HWP, and its

balance between being an emissions source or sink, is therefore required. This is particularly pertinent

where the HWP is influenced by other policies. Ellison et al. (2014) [99] demonstrate, for example, that

in Sweden, the average HWP carbon pool represents approximately 14% of removals. The authors do,

however, argue that the KP2 cap, which applies equally to FM removals and HWP, marginalises almost

the entire HWP carbon pool.

EU policy is criticised for a lack of centrally coordinated forest management, in particular, national

forests plans (NFP) development by Member States [37]. Such decentralised and uncoordinated policy

development could pose a threat in terms of conflicting forest practices and regional climatic effects.

This decentralisation is further emphasised by the high proportion (over 50%) of privately owned and

managed forests. Fostering communication between forest owners and NFPs should be an important

element of future EU Forest Strategy updates [37].

40

5b. Livestock and cropping systems are significant contributors to

global emissions of non-CO2 GHGs. The management of these systems

has the potential to reduce GHG emissions

Land-based mitigation in the form of reducing GHG emissions from agricultural systems was not within

the remit of the LUC4C project, but is explored in this section through a review of external literature.

Agricultural GHG emissions are predominantly from non-CO2 sources; methane (CH4), nitrous oxide

(N2O), nitric oxide (NO) and ammonia (NH3). In 2014, agriculture contributed approximately 10% of

Europe’s non-CO2 GHG emissions; this is in comparison to 0.13% of CO2 emissions (EU-28 and ISL) [11].

In the EU, nitrous oxide accounts for 58% of non-CO2 agricultural emissions, while methane represents

42% [11].

Methane emissions, associated with livestock (enteric fermentation and manure management), are

strongly determined by ruminant feedstock, in particular, the fraction of grass biomass [39]. Nitrogen

fertilisers, both organic (derived from manure/slurry) or mineral (synthetic), are a significant source of

nitrous oxide, nitric oxide and ammonia emissions. Nitrate emission rates, from agricultural fertilisation,

are a function of the application rate, fertiliser type, crop type and environmental conditions [39].

However, a fertilised cropland will typically emit two to three times more nitrogen than it would under

non-fertilised conditions, or three to four times more N2O for grasslands [39]. EU non-CO2 agricultural

emissions can be attributed to three primary sources: enteric fermentation (42%), agricultural soil

management (38%) and manure management (15.4%) [11].

GHG emissions derived from agriculture are highly variable across EU Member States, as national

emissions in 2013 ranged from 3% (in Malta) to 32% [11]. This variability is a consequence of

heterogeneous farming systems, management practices and biogeographic characteristics across the

region. Agricultural producers are equally as heterogeneous. Grosjean et al. (2016) [101] demonstrate

that 38% of emissions within the sector are generated by the top 10% of emitters, and the top 20% of

emitters generate 58% of sectoral emissions, indicating the uneven distribution of emissions across the

sector. In terms of absolute emissions, three countries (France, Germany and the UK) contribute

approximately 44% of total EU-28 agricultural emissions [11].

Agricultural non-CO2 emissions fell by 21% (113 MtCO2eq) between 1990 and 2014, a decline largely

attributable to a reduction in ruminant livestock numbers [11]. With a stabilisation/slowing in the

reduction of livestock numbers, this declining emissions trend has slowed over time; a 16% decline

observed between 1990 and 2000 fell to 8% between 2001 and 2012 [11].

Climate change mitigation in the agricultural sector can be achieved by emissions reductions (CO2 and

non-CO2), increased carbon sequestration and contribution to the renewable energy sector. Such

mitigation actions must, however, be balanced with other aspects of sustainable development (food

production, air/water quality, biodiversity) and placed in the context of global agricultural systems (for

a discussion on iLUC, see 1c). Of major concern to the agricultural sector is the potential for mitigation

41

to impair production. It is in this context that mitigation has tended to focus on those strategies with

the least production impacts or those that are economically beneficial to the sector, for example, by

increasing efficiency (e.g. reduced/targeted fertiliser application) [11].

Tubiello et al. (2015) [5] argue that (i) an increasing GHG emissions trend from the agricultural sector

(ca 12% globally between 1990 and 2010) in contrast to a declining emissions trend from forestry and

other land-use activities, (ii) the dominance of agriculture (11%) within agriculture, forestry and other

land use emissions (FOLU; 10%), and (iii) high proportion of deforestation driven by agricultural

expansion, indicates an increasing need for emissions reductions within the sector.

Policy implications

Mitigation in the agricultural sector remains a challenge to climate negotiations. Agriculture has been

identified as a priority sector for the UNFCCC; however, discussions on the contribution and potential

inclusion of the sector remain (following COP17 in 2011) an agenda item for the UNFCCC Subsidiary Body

for Scientific and Technical Advice [11]. In the absence of this COP scale integration, agriculture is

included under a set of different UNFCCC sections (Nairobi Work Programme, Cancun Adaptation

framework, finance mechanism, technology mechanism). This disaggregated approach has led to

concerns that synergies and trade-offs cannot be addressed [11].

The European 2050 Roadmap (COM (2011) 112 final; [102]) sets a (non-binding) reduction target for

non-CO2 agricultural emissions of between 42% and 49% (relative to 1990) by 2050. Non-CO2 agricultural

emissions are included in the EU-ESD (406/2009/EC; [18)]. Agriculture could, therefore, represent an

important sector in terms of EU Member States achieving their EU-ESD targets. For example, 43% of EU-

ESD emissions in Ireland are attributable to the agricultural sector. Consequently, Ireland may need to

apply significant mitigation in this sector, overachieve in other EU-ESD sectors or make use of other

flexibility mechanisms to meet its current EU-ESD emission reduction target of 20% [11]. Agriculture is

not included in the EU-ETS; however, emissions from, for example, fertiliser production facilities

(indirectly linked to agriculture) would be. CO2 emissions from CM and GM are covered by both the EU

2013 Land Use Decision (mandatory; (529/2013/EU; [20]) and KP2 accounting (voluntary). In summary,

beyond monitoring and reporting requirements, there are no legislative targets for the agricultural

sector within the current EU or international policy frameworks.

Hart et al. (2017) [11] demonstrate that, in their UNFCCC/KP reporting, 26 EU Member States identify

agricultural soils as key sources of nitrous oxide emissions, and 20 to 22 Member States identify manure

management and enteric fermentation as a significant source of methane. However, in spite of this clear

link between the agricultural sector and GHG emissions, Hart et al. (2017) [11] argue that policies to

address these sources are disproportionally lacking. The authors conclude that 13 Member States will

be unable to meet their respective 2020 and 2030 EU-ESD targets without modifications to agricultural

emissions policies/measures or consideration of flexibility mechanisms. However, Member States

expect EU-ESD targets to be met within current policy structures, as agriculture is rarely mentioned in

42

reported Policies and Measures, the mechanism through which Member States express how they expect

to meet emission reduction targets [11].

Impact assessments accompanying the 2016 EU-ERS proposal (COM(2016) 479 final; [19]) indicate that

little change would be required in the agricultural sector to meet specified targets, contrasting the 2030

climate change package assessment, which indicated that agricultural emissions would need to be

reduced by approximately 28%. This, however, is a consequence of differing assumptions [11].

Matthews (2016) [103] highlights eight EU Member States7 Where significant additional efforts might be

required within the agricultural sector. Foreseen agricultural action in the identified countries is, Hart et

al. (2017) [11] conclude, highly variable. For example, while France set specific agricultural sector

reductions, none are stipulated for the sector in Ireland.

Agricultural practices in the EU are significantly influenced by the CAP. Climate action is, following the

2013 CAP reform, included in the three core CAP objectives and central to both CAP Pillars [27]. Hart et

al. (2017) [11] have identified the following CAP key instruments as having the potential to support

climate change mitigation:

Standard for Good Agricultural and Environmental Condition (GAEC): Implemented by farmers

receiving payments under both CAP Pillars, these standards have the potential to protect soil organic

carbon (e.g. by the establishment of watercourse buffer strips or minimum soil cover standard),

reduce the risk of wetland losses (e.g. through improved irrigation practices), and promote carbon

sequestration (e.g. by the retention of woody landscape features).

Pillar 1 Greening Payments: Greening payments support agricultural practices that are beneficial to

both the climate and environment. Greening obligations include: crop diversification, grassland

maintenance and Ecological Focus Areas (EFAs); land-use types designed to safeguard and improve

biodiversity, which must be included within the farmed area. Climate mitigation can be realised

where permanent grasslands are retained and ploughing prohibited. While EFAs are defined to

protect diversity, climate mitigation co-benefits can be identified, for example, carbon sequestration

(woodlands, agro-forestry) or soil carbon protection.

Farm Advisory System: It is compulsory that this advisory service, in each Member State, cover all

aspects of the CAP. However, there is the potential for Member States to also offer information on

a broader set of topics, including farm-based climate mitigation measures.

Rural Development Programmes (RDPs): All RDPs must address at least four of the six EU level

priorities for rural development in addition to a set of cross-cutting objectives. Priority five, which

promotes resource efficiency and a shift towards a low carbon and climate resilient economy, is

particularly relevant to climate change mitigation. The authors identify several RDP measures with

a high potential for climate change mitigation and adaptation.

Several CAP measures have climate mitigation benefits, although issues with these have been

highlighted; Massey et al. (2015) [37], in a synthesis of policy relevant literature, conclude that (i) GAECs

is not an explicit condition of greening payments, (ii) organic soils are not effectively managed or

7 Austria, Belgium, Denmark, France, Germany, Ireland, Luxembourg and The Netherlands [103].

43

unmanaged outside Natura 2000 areas, (iii) grassland protection is not consistent, (iv) sanction systems

are not binding, and (v) LULCC in support of climate mitigation is not supported.

Within the CAP, there is considerable flexibility in terms of the implementation of these measures. As a

consequence, the realisation of climate benefits is highly dependent on both Member States and the

farming community. Hart et al. (2017) [11] provide a full review of the CAP measures in terms of their

reach, scope (area of potential implementation) and potential climate benefits. In conclusion, they argue

that the implementation of CAP instruments, in support of climate mitigation, is highly variable across

Member States and, in many instances, minimal. For example, (i) the RDP budget allocations for climate

priorities (at 8%) are lower than other priorities, and (ii) targets are set low; only 1.8% of EU agricultural

land is projected to be under RDP contracts contributing to carbon sequestration by 2020. In the context

of the three mandatory “greening” elements of the reformed CAP, Westhoek et al. (2012) [104] conclude

that they will have limited emission reduction impacts (2% between 2010 and 2020), and emissions may

even increase due to leakage to regions outside of the EU.

The EU 2050 Roadmap allocates approximately 500 kg CO2eq per capita per year to agricultural nitrous

oxide and methane emissions, and Bryngelsson et al. (2016) [105] compare four broad strategies for

achieving such a target: (i) agricultural productivity/efficiency gains, (ii) technology options for emissions

reduction, (iii) changing demand (diets), and (iv) food waste reductions. Using Sweden as a European

proxy, they conclude that even under optimistic technological change, current and future projected

dietary preferences cannot achieve EU agricultural emissions targets; emissions remain at about 600-

900 kg CO2eq per capita per year. Dietary change, in particular reduced ruminant based diets, is,

therefore, identified as an important mitigation strategy. Smaller, yet significant, technology based

emissions reductions for methane and nitrous oxide sources can be achieved [105]. However, to meet

EU non-CO2 targets with a high degree of certainty, a 50% or greater reduction in ruminant meat

consumption is required. While ruminant based meat sources must be reduced to meet emissions

targets, the authors find that meat consumption need not be curtailed/significantly reduced if diets are

primarily based on non-ruminant sources [105]. High ruminant meat and dairy based diets, Bryngelsson

et al. (2016) [105] conclude, are incompatible with the EU non-CO2 targets unless accompanied by

significant technological advancements (animal productivity, manure-management). Food waste was

found, even under optimistic conditions, to have a lower impact on future emissions pathways; halving

current waste production in Sweden reduced emissions by only an additional 1% to 3%. It is in this

context that authors have argued for policy interventions in favour of guiding diets towards lower non-

CO2 GHG emissions pathways [105] (see Issue 5c).

Energy use is a dominant cause of CO2 emissions from agricultural production. As such, the de-

carbonisation of the energy supply has the potential to result in significant emissions reductions [105].

Equally, net CO2 emissions from CM and GM activities are greater than emissions from FM in some EU

Member States8, indicating that the inclusion of these in agricultural emissions targets could significantly

impact future management practices [99].

8 Emissions from CM and GM exceed emissions from FM in The Netherlands, Denmark and Germany [99].

44

Technical and political challenges of achieving cost-efficient GHG emissions in the agricultural sector,

and a lack of clear emissions targets, have led to little large-scale action on climate mitigation in this

sector [11]. Current policy discourses also contrast, for example, the EU’s current subsidisation of beef

and mutton production with recommendations of shifting demand towards lower GHG emission diets

[105]. The CAP direct payments and coupled support for the livestock sector continue to favour high

yield areas, which has significant implications for GHG emissions in the livestock sector [11].

Massey et al. (2015) [37] argue that the significant potential of the CAP to support climate mitigation

remains untapped, for example grassland protection and/or climate-friendly land conversion (reed-

grass cultivation, rewetting). Hart et al. (2015) [11] contend that the currently proposed EU-ESR and

integration of LULUCF into EU emission policies will have limited impact on the agricultural sector in

terms of incentivising emissions reductions. However, in the absence of targets, short-term adaptation

measures are increasingly being adopted in the sector; a trend not observed for mitigation measures.

The reform of the CAP post 2020 has been identified by several authors as an opportunity to strengthen

climate action in the agricultural sector [11, 37]. Hart et al., (2017) [11] identify six CAP priorities post

2020 in the context of climate mitigation: (i) the protection of carbon-rich soils, (ii) the management of

soil organic matter (minimising losses and increasing stores), (iii) measures to encourage efficient

management of nutrients, (iv) inclusion of climate mitigation within the Farm Advisory System, (v) the

inclusion of climate mitigation within the CAPs monitoring and evaluation framework, and (vi) a review

and change in the orientation of CAP towards emission-neutral production. Massey et al. (2015) [37]

further add, (vii) a review of incentivised LULCC conversions, to increase the protection of grassland and

promote climate mitigation strategies, (viii) favourable economic and financial conditions for climate

actions (modified sanctions and incentivised biofuels, rewetting) and (ix) increased capacity building and

communication.

The EU-ETS does not currently cover the agricultural emissions. However, some authors highlight the

cost-efficient mitigation potential of the agricultural sector using such market-based instruments [101].

However, this remains a contested stance, as the potential scope of the EU-ETS is disputed, and other

mechanisms might be better suited in the LULUCF sector. Grosjean et al. (2016) [101] identify three key

obstacles or barriers to a market-based agricultural mitigation policy; transaction costs, leakage risks

and potential distributional impacts on farmers/consumers.

45

5c. There are a number of alternative scenarios of land-based

mitigation that are rarely explored since most future scenarios are

based on a limited set of conventional options such as agricultural

management, A/R and BECCS

In addition to population dynamics and economic growth, future land-use change trajectories depend

on socio-economic conditions such as, for agricultural systems, technological change and investment,

dietary patterns and demand, trade, and interactions with other competing land use sectors [106]. The

IPCC shared socio-economic pathways (SSPs), Popp et al. (2017) [106] argue, provide a diverse set of

socio-economic conditions and potential land-use futures. Under ambitious mitigation scenarios, for

example in SSP4, cropland is projected to expand by up to 1413 Mha (until in 2100), an expansion

associated with bioenergy, whereas in SSP5, pasture decreases by up to 940 Mha [106]. Such results

demonstrate the importance of socio-economic context in future land-use pathways.

Future scenarios, and those of land-based mitigation implementation, tend to follow conventional

development pathways. However, a number of “less-conventional” pathways, which have the potential

to profoundly affect land use and land-based emissions, can be envisaged.

A comparison of the relative importance of dietary change towards animal based products and

bioenergy expansion in driving agricultural land-use change since 1994 are compared, the rates of

change (35.7 Mha/year for diet versus 3.2 Mha/year for bioenergy) suggest that changing diets have

had an impact eleven times greater than bioenergy [35]. Food production and the influence dietary

change has on demand are, therefore, significant drivers of LULCC. Furthermore, in considering food

production demand, Alexander et al., (2016) [107] show that the types of commodities consumed (diet)

is more important than the quantity (per-capita) consumption in determining agricultural area

requirements. In 2011, 635% of land per capita required to sustain an Indian diet was required to sustain

a typical US diet. The US diet had a 65% greater (or 99% greater in terms of protein) energy content; a

significant disparity compared to the differing land requirements [107]. This difference is attributable to

the commodities consumed, with 30% versus 9% of energy derived from animal products in the US and

India, respectively [107].

Diet and dietary trends have the potential, therefore, to significantly influence the extent of agricultural

land required to fulfil demand. Alexander et al. (2016) [107] conclude that the global adoption of an

Indian diet would require 55% less agricultural land to fulfil demand than what is currently the case.

Conversely, the global adoption of a diet typical of the United States would require six times current

agricultural area. The global adoption of two contrasting (but not extreme) diets could therefore lead to

a magnitude of change greater than doubling or halving current agricultural land areas. The authors note

that while a global shift to a diet resembling a typical US diet is unlikely in the shorter term, this is the

prevailing trend in terms of recent consumption patterns. This is a consequence of, among other factors,

46

increasing per capita income in developing countries (China, Brazil), rural-urban migration and a greater

consumption of animal products. However, given current yields and production systems, a global

adoption of a typical US diet would prove impossible, as it would require 98 per cent of all land. An

Indian diet, while more desirable from an environmental perspective, implies a shift in consumption

away from both current trends and those typically observed with an increasing per capita income [107].

Limiting agricultural land requirements has direct and positive climate change mitigation impacts, as it

minimises LULCC and reduces the competition with land-based mitigation strategies for land resources.

Equally, reduced agricultural production demand may, indirectly, reduce production based emissions

(fertiliser, mechanisation, manure management).

Erb et al. (2016) [108] explore the food production option space, in terms of supply-side (cropland

intensification, cropland expansion into grazing areas, livestock system efficiency gains) and demand-

side (dietary changes) measures, within the constraints of a hypothetical zero-deforestation boundary

constraint. Approximately two-thirds of the 500 scenario combinations considered by the authors were

deemed feasible or probably feasible, that is, food demand could be met within the zero-deforestation

constraint; deforestation is not a requirement to meet food demand in 2050 [108]. The authors conclude

that human diets are more important than yield (crop or livestock intensity) and cropland expansion in

determining the feasible option space; vegan and low-livestock diet variants showed the highest

proportion of feasible scenarios [108]. The authors also identify scenario combinations where Western

diets could be adopted if associated with increasing yields and the expansion of cropland into current

grazing areas. Equally, low-yield (e.g. organic) production is feasible in a zero-deforestation scenario if

paired with changing diets (to vegetarian/vegan) and/or cropland expansion.

Animal based production is associated with high levels of water consumption, GHG emissions (see Issue

5b) and land-use change [107]. Relative to their land-use footprint, constituted of pasture lands (68% of

all agricultural lands in 2011) and arable feeds (33% of croplands in 2011), animal products contribute a

disproportionally low amount of energy (18%) and protein (39%) to human diets [35]. Diets based on

low levels of meat intake are associated with lower land requirements (such as the Indian diet of

Alexander et al., 2015 [35]) and more “plausible” alternatives with the food production option space of

[108]. Reduced meat consumption has also been linked to multiple health benefits, particularly where

consumption is currently above recommended levels [43]. While associated with a larger GHG emissions

footprint, livestock, Erb et al. (2016) [108] argue, do provide non-food resources (wool, draught power)

and are able to increase society’s food resource by converting marginal land into a protein source.

Changing food preferences and demand may be possible through either behaviour change (portion

sizes) and/or economic approaches (e.g. sugar taxes versus fruit/vegetable subsides). Authors argue,

however, that taxation and subsidies alone are unlikely to be sufficient to change diets without policies

targeted across society [109]. The trade-offs in yield, expansion and diet explored by Erb et al. (2016)

[108] also have an important trade-off with national food security or self-sufficiency. The option space

47

identified, the authors argue, would be substantially reduced in the presence of socio-economic trade-

barriers (subsidy systems, tariffs, regulations).

Topic 6: Multiple policy goals and co-benefits 6a. There are potential synergies between land-based mitigation and

adaptation that would allow co-benefits to be achieved

Linkages exist between the mitigation of, and adaptation to, climate change. When land-based

mitigation in the form of avoided deforestation retains primary forests, emissions from deforestation

are prevented and, as a co-benefit, biodiversity and ecosystem service provision are maintained. These

are both characteristics of a resilient ecosystem. Conversely, secondary forest, and particularly

monocultures, can reduce biodiversity, thereby diminishing the adaptive capacity of the ecosystem to

respond to climate change [43]. Furthermore, planting trees in urban areas (see Figure 1) has mitigation

benefits through the capacity for carbon storage, as well as adaptation benefits through cooling effects,

and reducing surface water run-off and flooding [110]. Adaptive measures are also synergistic with

mitigation; the adaptive management of fire-regimes, for example, may ensure the permanence of

carbon stocks [43].

Changing food consumption patterns, for example through low-meat diets, reducing over-eating and

waste, and eating alternative protein sources (see 5c), reduces the land area needed for food

production, thereby providing opportunities for using this land for land-based mitigation [43, 111, 112].

This also builds resilience to climate change, since the additional availability of land could offset the

negative impact of climate change on crop yields and thus food production.

These examples demonstrate potential opportunities, but there is limited scientific evidence to support

the understanding of the full extent of mitigation-adaptation synergies and trade-offs, constituting a

major knowledge gap.

48

Figure 1: Known and potential relationships between mitigation and adaptation measures and their impacts on biodiversity. Urban tree planning is identified as a win-win-win situation, being beneficial for biodiversity, mitigation and adaptation [110].

Policy implications

The co-benefits of integrating adaptation and mitigation to realise sustainable development goals have

been recognised both within the (i) IPCC 5th Assessment Report, through the definition of climate-

resilient pathways, and (ii) the Paris Agreement, for example, Articles 4 (NDCs) and 5 (forest sector). The

Paris Agreement also highlights the two-way nature of this synergy (Article 7) [11].

The integration of mitigation and adaptation objectives, governance structures and policy-making

processes is essential in ensuring coherent land sector policies [113]. Full integration requires that the

policy intends, from the outset, to contribute to both outcomes; synergies are exploited and trade-offs

minimised. It does not require the merger of institutions, actions or policies, only that the objectives are

considered simultaneously. Di Gregorio et al. (2017) [113] define adaptation/mitigation policy

integration across four dimensions (Table 3): (i) Internal – the integration of mitigation and adaptation,

that is, benefits are observed for both aims within the policy sector (i.e. forestry); (ii) External – the

consideration and exploitation of synergies between the climate change aims (mitigation or adaptation)

and non-climate objectives; (iii) Vertical – integration within a single policy sector (i.e. forestry); and (iv)

49

Horizontal – integration across policy sectors (i.e. forestry and agriculture). A policy environment based

on all four of these dimensions is essential in facilitating climate resilient land-use pathways [113].

Table 3: The four dimensions of climate policy integration as proposed by [113].

6b. Positive social benefits can be derived from well-grounded land-

based mitigation strategies, but, conversely, land-based mitigation

can have negative social impacts if poorly planned

Land tenure and land rights are important considerations in the expansion and deployment of land-

based mitigation. Insecure land tenure, vague property rights, and uncertain government policies and

carbon market prices can make carbon sequestration policies ineffective; seller-uncertainty prevents

participation in the market [92]. Weak land tenure rights can lead to the exclusion of smallholders and

indigenous communities from the market [28, 43]. Land tenure issues can also be linked to the large-

scale leasing of land by foreign governments or firms for, in part, feedstock production, so-called ‘land-

grabbing’ [37]. Such leases remove land from smallholder/local food production systems with products

often being exported [28], and raise concerns about sustainable development and equity [43] Land rents

and food pricing are important sustainable development concerns for land-based mitigation (see Issue

1a). One factor potentially driving land prices/rents upwards is phantom production; the purchasing of

land, and its removal from the land resource without any subsequent development, market exchanges

or expected environmental/social benefits [114]

50

Land-based mitigation can impair ecosystem service provisioning (see Issue 2a). Impaired water

availability, water quality, air quality and increased agrochemical use have all been linked to issues of

social well-being and human health impacts. Exclusion from, or access to, degraded ecosystem services

may disproportionally impact poorer members of society, leading to inequalities. Cultural services, a set

of less tangible ecosystem services, may be impacted upon by LULCC changing people’s perception and

use of a landscape [28].

The development of bioenergy markets supports rural development and job creation; evidence for this

can be found in both developing and developed countries [28]. The EC biofuel impact assessment [115]

estimates that, in 2020, employment related to biofuels in the EU could be approximately 400,000 jobs

distributed across the supply chain; agriculture, logistics and at processing/production facilities. Farmer

income, within bioenergy markets, is dependent upon the feedstock production model, for example,

plantations, contract farming, independent smallholder farming or subsistence farming [114]. A

conversion to cash crops (feedstocks) by rural populations may not represent a net income gain as cash

crop prices are highly vulnerable to world markets. Equally, biofuel production has the potential to lock

both labour and land resources into inflexible contracts in which risks are borne by the smallholder [114].

Biofuel production favours economies of scale [28]. In such circumstances, additional benefits may not

be seen by smallholders who cannot compete in large-scale markets. Smallholders may be further

excluded by the risk/uncertainty typically associated with land-based mitigation markets [28].

Land-based mitigation measures can promote equality when implemented within a transparent,

participatory policy system that distributes socio-economic, economic and technological benefits,

shares the burden of implementation and ensures equal access to decision-making. In the absence of

such mechanisms, land-based mitigation has been associated with both inter- and intra-generational

inequality [43]. Multiple authors have, summarised in [28], demonstrated the potential gender

imbalance of impacts arising from biofuel expansion; women being more likely to face the negative

socio-economic and environmental impacts.

Land-based mitigation policies can engender inequalities between regions and/or states. The inclusion

of forest sequestration as an abatement method in EU policies, could lower the cost of achieving 2020

abatement targets by between 53% and 85% [116]. However, the inclusion of forest based sequestration

(particularly under certain conditions), when assessed against six equality measures, leads to greater

disparities between EU Member States in terms of their burden sharing. Such negative impacts on

equality may require the revision of targets, allocations or allowances to support those disadvantaged

[116].

Small scale biofuel initiatives can, through access to energy, poverty reduction and rural capacity

development, improve human well-being [28]. Biofuel production by rural communities can also

produce co-benefits, for example, Riera and Swinnen (2016) [117] conclude that castor biofuel contract

farming in Ethiopia was correlated with food production improvements, perhaps due to improved

fertiliser access, improved soil quality (from the biofuel production) and increased technical assistance

51

from the project agents. Biofuels offer countries an opportunity to establish both national and local scale

security in their energy supply [28]. Land-based mitigation measures offer the potential to clarify and

harmonise land rights/tenure in the presence of regulating institutions and enforcement [43].

Policy implications

Sustainable development and positive social outcomes can result from land-based mitigation [28, 43,

114]. Buck (2016) [114] argues that markets are unable to deliver outcomes that are beneficial to broad

sectors of society and that, in this context, strong policies, support and guidance are needed.

The take-up of A/R projects within the CDM has historically been low (0.2% of total activity within the

CDM) [82]. Implemented projects are characterised by initial funding support, the provision of design

and implementation technical expertise by large organisations, secured property rights and cooperation

of local communities, including the redirection of CDM benefits back to local people. Such insights can

support effective policy design. Thomas et al. (2010) [82] argue that such insights should, for example,

inform the reform of the CDM, namely (i) to increase the flexibility of institutional mechanisms to reflect

the varying conditions of Member States and notion that LULUCF measures are context-specific, (ii) to

build technical and organisational capacity within Member States, and (iii) simplify methodological and

documentation procedures, (iv) strengthen the economic environment in which the policy operates so

as to provide long-term price signals and lower the risk, and (iv) broaden the definition of both forests

and projects applicable within the mechanism. Successful projects, it is argued, will engage local people

and be mediated by trusted institutions. Furthermore, the environmental, social and economic goals of

projects have an increased chance of being achieved where the technical capacity is developed locally,

within local populations [82]. As it stands, the nature of a replacement for the CDM under the Paris

Agreement is uncertain and undecided.

6c. Co-benefits are possible across a set of policy targets if policy is

developed systematically across sectors rather than in isolation

Numerous socio-economic issues are linked to climate change. However, despite the recognition that

these issues are not mutually exclusive, strategies are frequently discussed and implemented

independently; synergies are not often considered within policy [118]. Co-benefits have the potential to

maximise efficiency while achieving the objectives of both land-based mitigation and other international

and national sustainability agendas [43].

Climate policies have the potential to interact and overlap with non-climate and sustainable

development policies/goals. Sustainable development is fundamental to the Paris Agreement, and

avoiding dangerous climate change is a Sustainable Development Goal (SDG 13) [14, 81]. Land-based

mitigation has the potential to interact with multiple SDGs related to poverty, hunger, health and well-

being (SDGs 1, 2 and 3), water and land (SDGs 6, 14 and 15), and energy (SDG 7). As von Stechow et al.

52

(2016) [81] state, “sustainable development hinges on the successful implementation of non-climate

policies that complement or support climate policies in other dimensions” (pp. 2).

The ability of society to achieve the SDGs, and the risk of the goals not being met, varies as a function of

the pathways deployed to achieve the 2°C target [81]. Meeting the 2°C target can significantly influence

the risk associated with meeting other SDGs and sustainable energy objectives. Reduced fossil fuel and

energy demand, in the short-term, is associated with a range of longer-term non-climate co-benefits,

such as air quality, energy security, water use, reduced pollution, health benefits (associated with

declining fuel poverty and improved mobility patterns) and local employment; such co-benefits are

reduced in the presence of weak short-term climate policies, similar to the low short-term ambition

pathways of the INDCs [81]. Adding technological constraints can minimise the risks associated with

particular energy technologies. However, other risk levels may be exacerbated, particularly those risks

associated with socio-economic SDGs. For example, while limiting the global deployment of biofuels

reduces environmental risks, risks of not meeting socio-economic SDGs increase. In some pathways, the

climate SDG itself is threatened; the 2°C target is not achieved. The achievement of low energy growth,

that is, energy efficiency improvements across sectors, and a societal change away from current high-

energy lifestyles, is, von Stechow et al. (2016) [81] argue, essential in increasing synergies and managing

trade-offs between climate and non-climate SDGs. This interaction between climate and non-climate

SDGs, and their associated policies, supports the integration of climate and SDG agendas into a single,

integrated monitoring framework [81].

Ecosystem-based management approaches are increasingly recognised as fundamental to climate

change adaptation and mitigation; functional ecosystems are vital in supporting and increasing climate

change resilience and minimising risk at multiple spatial scales [28, 118, 119]. The link between

ecosystem-based mitigation9 and biodiversity has been established in multiple decisions (X/33; XII/20)

of the Convention on Biological Diversity (CBD) [119]. Parties were invited to implement an ecosystem-

based approach to mitigation through, for example, the conservation, sustainable management and

restoration of natural forests, grasslands, peatlands, mangroves, seagrass beds and salt marshes

(Decision X/33). Aichi Target 15 of the CBD is directly relevant to climate change mitigation and

adaptation in that it calls on Parties to enhance ecosystem resilience and the contribution of biodiversity

to carbon stocks [119]. Ecosystem-based mitigation also has synergies with Aichi targets 5 (habitat loss),

7 (sustainable agriculture/forestry), 11 (protected area extent) and 14 (ecosystem services) [119].

Ecosystem-based mitigation approaches can be significantly enhanced when incorporated into

landscape-scale planning mechanisms, that is, planning which considers different sectoral/stakeholder

demands in addition to the interactions between ecosystems and the services they provide [119].

Barriers to integrated management can be overcome by including mechanisms to support multiple

stakeholder planning, clarifying land tenure, including regulatory instruments/incentives appropriate to

the national/local context, and adaptive management. National and sectoral policy harmonisation

across climate change, agriculture, forestry, biodiversity conservation and economic development will

9 Ecosystem-based mitigation and adaptation, that is, the management of ecosystems and biodiversity in such a way as to

mitigate climate change emissions or help people adapt to climate change, are synergistic [119].

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enable ecosystem-based mitigation to be integrated with other land-use functions at a landscape scale

[119].

6d. The implementation of BECCS is uncertain

As previously discussed, of the 116 IPCC AR5 scenarios that are consistent with a greater than 66%

probability of keeping warming below 2°C, 87% apply NETs in the second half of this century [7]. Equally,

of these 116 IPCC AR5 scenarios, 104 utilise the large-scale deployment of BECCS [9] necessarily

assuming that this implementation is technologically, economically and socially viable [120] If BECCS is

excluded as a NETs option, the 2°C goal is not attained, or reached only at substantially higher costs [30].

The speculative nature and development stages of NETs (particularly BECCS, in the context of land-based

mitigation) has raised alarm in the academic literature and elicited multiple commentaries as to whether

such scenarios are feasible. Multiple authors have argued that scenarios, and integrated assessment

models (IAMs), are too dependent on BECCs, given its scientific (technical, scale, cost) and political

uncertainties [120, 30, 8, 9].

IAMs and scenarios relying on BECCs deployment are founded on a set of assumptions. Vaughan and

Gough (2016) [121] in a survey of expert opinions with regard to these assumptions, conclude that IAMs

are unrealistic in their assumptions as to (i) the extent of bioenergy deployment possible (available land,

future yields, contribution to energy system), and (ii) the establishment of adequate policy frameworks

and social acceptance in support of large-scale NETs. Conversely, the expert review panel deemed the

technological assumptions for CCS (storage capacity, technology uptake, capture rate) to be more

realistic. Of the ten assumptions considered, seven were defined as falling in a perceived “danger-zone”,

that is, assumptions had a high degree of influence on modelling outcomes, but a low pedigree in terms

of support across the expert panel [121]. The implication of unrealistically ambitious BECCS targets

and/or reliance on these NETs in mitigation pathways is the exceedance of cumulative carbon budgets

and, consequently, an inability to achieve emission targets associated with a 2°C pathway [30, 121].

CCS is not solely a land-based mitigation technology, it is for example used in combination with fossil

fuel based industries. A review of the ethical (see Medvecky et al., 2014 [122]) and social (see Fridahl,

2017 [30]) implications surrounding the large-scale implementation of CCS technologies is considered

beyond the scope of this document. While understanding the social aspects of CCS is important in

exploring BECCS [114], Fridahl (2017) [30] argues that BECCS is distinct from CCS, for example, it is

associated with the benefits of negative emissions, different uncertainties and risks. Such differences

justify a need for targeted research on the public/political acceptance of BECCS [30]. Political, public and

industrial priorities can significantly influence the deployment of BECCS; conditions that disfavour large-

scale deployment could significantly impede the scale of deployment required by IAM 2°C scenarios.

Fridahl (2017) [30] conclude that among climate change informed stakeholders, governmental and non-

governmental stakeholders at UNFCCC conferences, BECCS has a lower priority than other renewable

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energy technologies. Preference varies with geographic region, aligning to some extent, with the

technological potential of the region. However, the authors argue that the low preferences observed,

could be a barrier to BECCS inclusion (and incentives) in carbon pricing policies [30].

Fridahl (2017) [30] argues that current market conditions prohibit the commercialisation of BECCS.

Mobilisation of BECCS at the scale suggested in models will, the authors argue, be dependent on national

or regional policy decisions acting to regulate the market in favour of BECCS. Fridahl (2017) [30] also

identifies a set of key uncertainties in conceptualising BECCS deployment, namely (i) the ability to

sustainably produce biomass and the scale of this resource; (ii) knowledge gaps and uncertainties in the

magnitude of the global CO2 storage capacity available, the risks associated with this storage, and, as

Peters et al. (2017) [123] add, the development trajectory of this technology, which is slower than that

expected; (iii) economies of scale regarding BECCS deployment and infrastructural requirements; and

(iv) the carbon price at which BECCS is commercially viable.

The production of bioenergy with CCS has only been implemented in a limited number of projects. In

contrast, experience has generated a breadth of knowledge on the implementation and monitoring of

A/R strategies at scale [9]. However, under these contrasting uncertainties, it would be incorrect to

assume A/R is a silver bullet. Kreidenweis et al. (2016) [34] argue that A/R is rather a part of a set of

mitigation strategies; the context and location of A/R must still be right.

Anderson and Peters (2016) [120] argue that a reliance on NETs, in particular BECCS, to realise the Paris

Agreement is an issue of risk and inequality; if NETs fail, impacts are most likely to occur in low-emitting

communities that are geographically and financially vulnerable to climate change. This leads the authors

to argue that “negative emission technologies are not an insurance policy but rather an unjust and high-

stakes gamble” (pp. 183), further stating that the equity and risk aversion principles of the Paris

Agreement preclude NETs as the focal point of a mitigation agenda [120]. Smith et al. (2016) [8], in a

review of NETs, argue that there is “[…] no NET (or combination of NETs) currently available that could

be implemented to meet the <2°C target without significant impact on either land, energy, water,

nutrients, albedo or cost […]” (pp. 49). This statement is supported by the synergies and trade-offs

explored in this synthesis document and discussed above.

6e. Land-based mitigation is not a ‘silver-bullet’ to avoid climate

change and must be part of a policy framework that also reduces fossil

fuel based emissions

Land-mitigation effects are site-specific and challenging to generalise; a consequence of their

development context and scale of implementation [43]. The impacts of land-based mitigation may not

overlap spatially, temporally or socially with the site of implementation. Equally, estimating the

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magnitude of these benefits, co-benefits, adverse impacts and their trade-offs is challenging, as no

standardised metrics or attribution methodologies have been agreed on [43].

Kameyama and Kawamoto (2016) [124] propose that NDC progress can be assessed by comparison to

four intermediate, energy based policy goals for emissions mitigation; (i) decarbonising energy, (ii)

improving energy efficiency, (iii) minimising energy demand, and (iv) sequestering carbon and reducing

non-CO2 GHG emissions. In a review of current policies, they highlight that the number of policies

categorised as goal (iv), which is the most applicable to land-based mitigation, is low (Figure 2). Policies

in goal (i) may or may not include BECCS. The relatively low number of land-based mitigation policies is,

it is argued, indicative of the extent of policy changes required to fully support large-scale, land-based

mitigation deployment.

Figure 2: Number of absolute policies CHN (113), GER (185), JPN (119), UK (130), US (265), derived from [124].

Institutional capacity (strong, transparent and accountable institutions) and international agreement,

Bustamante et al. (2014) [43] argue, are important for a framework supporting the wider

implementation of land-based mitigation strategies. Frameworks must support equitable social benefits

and strengthen land rights (see Issue 6b).

Ecological barriers to land-based mitigation strategies are site-specific and dependent upon the

mitigation strategy, its scale and implementation mechanisms. However, as demonstrated in this

synthesis, land-based mitigation must be integrated with non-climate policies to fully support

sustainable development. Land-based mitigation is not unconstrained; ecological barriers include, for

example, the saturating behaviour of A/R or limits on the land available for biofuel feedstocks.

As identified in this synthesis, economic barriers are one contributing factor in land-based mitigation

deployment. Equally, land-based mitigation strategies are sensitive to the differing trajectories of GHG

emission taxes, that is, the different strategies become cost-efficient at different points in time resulting

in different mitigation potentials and pathways by the end of the century [42].

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Bustamante et al. (2014) [43] summarise that for the full realisation of land-based mitigation policy

potential, financing mechanisms must be put in place to cover the costs of (i) monitoring/transactions

and (ii) opportunity costs, that is, mitigation strategies must be as attractive as other land-use

alternatives.

The long-term effectiveness of NETs is uncertain both as a function of their deployment but also within

the context of the Earth system. Jones et al. (2016) [125] argue that there is a need to better understand

the interaction between NETs and carbon cycle feedbacks. The authors find that Earth system models

suggest a significant weakening, and possible reversal, of ocean and land sinks under NETs in the 23rd

Century; such patterns may limit the longer-term (although not shorter-term) effectiveness of NETs.

Short-term decisions change long-term commitments within the context of the 2°C target. For example,

low range emission reduction targets up to 2050 imply more rapid reduction pathways (and greater

NETs deployment) beyond 2050, if the target is to be achieved [126]. Conversely, rapid emission

reductions and/or the large-scale deployment of NETs pathways implies trade-offs with other policy

objectives. In this context, the mitigation pathway followed significantly influences both climate change

impacts and policy risks [126].

Fuss et al. (2014) argue that “the reliance of current scenarios on negative emissions, despite very limited

knowledge calls for a major new transdisciplinary research agenda” (pp. 851) and “determining how safe

it is to bet on negative emissions in the second half of this century to avoid dangerous climate change

should be among our top priorities” (pp. 852). Furthermore, Rogelj et al. (pp. 222) [127] state that

“exploring futures in which a global balance of GHG emissions can be achieved in the second half of this

century with technically feasible and societally acceptable technologies represents a major research

challenge emerging from the Paris Agreement”.

A key message, across this synthesis, has been the need for integrated, coherent mitigation policies.

Mitigation strategies should not be planned in isolation, but within integrated ecosystem-based

approaches. Synergies, and trade-offs, should be explored both across climate and non-climate policies,

and across land use sectors. Land-based mitigation must be judged within the context of the Earth-

system in which its sits; benefits and impacts can be multi-scalar, and spatially dissociated. Land-based

mitigation represents one option within a mix of policy options. This includes the aggressive reduction

of fossil fuel based GHG emissions reductions.

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Abbreviations

AD – Avoided Deforestation

A/R – Afforestation/Reforestation

BECCS – Bioenergy with carbon capture and storage

CAP – Common Agricultural Policy

CBD – Convention on biological diversity

CDM – Clean Development Mechanism

CM – Cropland management

CSS – Carbon capture and storage

EU-ESD – EU Effort Sharing Decision

EU-ESR – EU Effort Sharing Regulation

EU-ETS – EU Emissions Trading Scheme

FM – Forest management

FQD – Fuel Quality Directive

GHG – Greenhouse gas

GM – Grassland management

IAMs – Integrated Assessment Models

iLUC – Indirect land-use change

INDCs – Intended Nationally Determined Contributions

IPCC – Intergovernmental Panel on Climate Change

KP – Kyoto Protocol

LCA – Life-cycle analysis

LULCC – Land-use and land-cover change

LULUCF – Land use, land-use change and forestry

NDCs – Nationally Determined Contributions

NETs – Negative emissions technologies

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NREAPs – National Renewable Energy Action Plans

SDGs – Sustainable Development Goals

UNFCCC – The United Nations Framework Convention on Climate Change

Annex 1: Relevant International Climate Policies A1.1 Climate Change within the UN policy framework

The United Nations Framework Convention on Climate Change (UNFCCC) requires signatories to (i)

adopt national-scale policies to limit anthropogenic greenhouse-gas (GHG) emissions, (ii) protect and

maintain GHG stores, and (iii) periodically publish national inventories, outlining these emissions/sinks

according to methodologies developed by the Intergovernmental Panel on Climate Change (IPCC). The

land use, land-use change and forestry (LULUCF) sector report emissions/sinks associated with

conversions between land-use types and the management of activities on these lands [13].

Parties to the UNFCCC may also have ratified the 1997 Kyoto Protocol (KP); a legally binding set of

emission targets for developed countries for the period between 2008 and 2012 (KP1) and subsequently,

but not formally in force and legally binding, for 2013 and 2020 (KP2). Emissions/sinks must be reported

from the activities of afforestation, reforestation (A/R), deforestation and forest management (FM)

(mandatory in KP2) [13]. Additionally, parties can select to report on human-induced revegetation,

grassland management (GM) and cropland management (CM) [13].

The Clean Development Mechanism (CDM) is a market-based mechanism implemented under the KP.

The CDM allows emission-reduction projects in developing countries to earn certified emission

reduction (CER) credits. CER credits can be traded and used, in part, by developing countries to meet

their KP emission targets.

The Paris Climate Agreement, ratified by 132 parties (as of February 2017), entered into force in

November 2016 and includes commitments to keep global temperatures “well below” 2 °C, while

pursuing a target of 1.5 °C, and to achieve GHG neutrality (a balance between sources and sinks) by the

second half of the century [13]. The Paris agreement also establishes binding Nationally Determined

Contributions (NDCs) which parties must prepare, communicate and maintain [14]. Unlike the KP,

emission targets as specified in the NDCs are not legally binding. Currently, these is uncertainty as to

what mechanisms, accounting approaches and differentiation (between developed/developing

countries) rules are to be included in the Paris Agreement with negotiations on-going.

Reducing Emissions from Deforestation and Forest Degradation (REDD+) is a mechanism, developed

under the UNFCCC, aimed at incentivising forest conservation, sustainable management and

enhancement [12].

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A1.2 Biodiversity and Ecosystem Services with the UN policy

framework

The Convention on Biological Diversity (CBD) aims to (i) conserve, and (ii) use sustainably biological

diversity, while also (iii) ensuring the fair and equitable sharing of those benefits which arise from the

use of genetic resources [96]. The CBD is one of seven international treaties relating to biodiversity [128,

129].

The 10th Conference of the Parties (COP) for the CBD included decision X/2, the strategic plan for

biodiversity between 2011 and 2020 [130].This decision included the Aichi Biodiversity Targets (Aichi

Targets); a set of 20 global targets which can be grouped into five strategic goals: (i) the mainstreaming

of biodiversity across government and society so to address the drivers of biodiversity loss, (ii) to reduce

pressure on biodiversity and promote sustainable use, (iii) to safeguard ecosystems, species and genetic

diversity, (iv) the enhancement of ecosystem services, and (v) to improve implementation of the CBD

through knowledge management and capacity building [130].

A1.3 Sustainable Development Goals

The Sustainable Development Goals (SDGs) arose from the UN Conference on Sustainable Development

in Rio de Janeiro. Replacing and building on the Millennium Development Goals, the SDGs are defined

with the UN strategy; “Transforming our world: the 2030 Agenda for Sustainable Development”. The

SDGs are defined around 17 goals and 169 targets (UN, 2015) [131].

Annex 2: Relevant European Policies A2.1 EU Climate and Energy Package

Arising from the earlier European Climate Change Programmes, the 2020 climate and energy

framework was introduced in 2007 (COM (2008) 30 final; [16]). This framework introduces three key

targets, which are also aligned with the Europe 2020 strategy: (i) to reduced GHG emissions by 20% (on

1990 levels), (ii) to increase the share of renewable energy to 20%, and (iii) improve energy efficiencies

by 20% (EC, 2008). These targets will be achieved by a 21% reduction in sectors covered by the EU

Emissions Trading Scheme (EU-ETS) and 10% reduction in non-ETS (EU-ESD) schemes.

To place the 2020 framework into a broader context, particularly in relation to the KP, the EU has

developed a roadmap to deliver a low-carbon economy by 2050 (COM (2011) 112 final; [102]). While

non-binding, the roadmap outlines a set of suggested actions and targets which, if undertaken, would

allow Europe to achieve its longer term climate targets.

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A renewed 2030 climate and energy framework was adopted in 2014 (COM (2014) 15 final; [17]). This

framework, which aligns with the 2050 roadmap, establishes GHG reduction targets of 40% (on 1990

levels) by 2030 and increases in both renewable energy and energy efficiencies of 27% [14]. Targets are

distributed across both EU-ETS (43% emission reductions on 2005) and non-ETS (30% emission

reductions on 2005) sectors.

A2.2 European ETS

The European Emissions Trading Scheme (EU-ETS) is a “cap and trade” scheme operational within 31

countries (EU-28, Iceland, Liechtenstein and Norway). While the EU-ETS has the potential to cover

multiple sectors, it is currently focused on those sectors where emission can be measured, reported and

verified with a high level of accuracy. In this context, the EU-ETS limits emissions (CO2, N2O and PFCs)

from high-energy industries and airlines operating between these countries [24].

A2.3 European Effort-Sharing Decision and Effort-Sharing Regulation

The European Effort Sharing Decision (EU-ESD), which came into force as part of the 2020 climate and

energy package, establishes binding annual GHG emission targets for each Member state between 2013

and 2020 (406/2009/EC; [18]). EU-ESD emission reporting encompasses non-ETS sectors such as

transport, buildings, agriculture (non-CO2 only) and waste. National scale targets will collectively achieve

a 10% reduction in EU emissions (on 2005 levels). National targets were defined as a function of the

Member States relative wealth (GDP per capita) and range from a reduction of 20% (IE, DK) to permitted

increases (emission ceilings) of 20% (BG) [18]. It is worth noting that the EU-ESD excludes CO2 emissions

from the LULUCF sector.

The EU-ESD covers multiple sectors with flexibility on how overall emissions targets are reached.

Geographic flexibility allows Member States to transfer up to 5% of their GHG emissions to another

Member state. Temporal flexibility allows Member States to bank or borrow emission allocations

between years in the trading period. Additional flexibility, is achieved by allowing Member state to use

project activity credits, for example, from the CDM, towards reduction targets (up to 3% of 2005

emission levels) [11].

The Effort Sharing Regulation (EU-ESR) is a follow-up to the EU-ESD, defined in-line with the 2030

climate and energy framework. The EU-ESR, which is at the proposal stage, continues the definition of

national binding GHG emissions targets (for 2021-2030) for non-ETS sectors (COM(2016) 479 final; [19])

The EU-ESR retains the geographic and temporal flexibilities of the EU-ESD. However, credits from non-

EU project activities (CDM) would be excluded. Additional proposed flexibilities would enable Member

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States to use removals from the LULUCF sector to offset EU-ESR emissions, and for a subset of Member

States (based on eligibility criteria) to use part of their EU-ETS to meet their EU-ESR targets [11].

A2.4 European Land Use Decision

At present the LULUCF (land use, land-use change and forestry) sector while included in KP accounting,

remains outside EU climate policies and emission reduction targets; the sector does not contribute to

the 20% GHG reduction by 2020 target. There are however a number of salient decisions and proposals

within this sector.

The European 2013 Land Use Decision (529/2013/EU; [20]) requires all Member States to prepare and

maintain GHG accounts (emissions/sequestration) for forests, cropland and grasslands in a manner

comparable to the IPCC guidelines for National GHG inventory reporting. Within the 2013-2020

accounting period only the reporting of forest activities (A/R, D and FM) is mandatory. The preparation

of cropland (CM) and grassland (GM) accounts is required as a first step towards ensuring the inclusion

of these sectors (as mandatory) in 2021 onwards. As a consequence, Member States must report CM

and GM emissions/removals from 2015 onwards including an outline on the intended improvements in

these reporting systems. The EU 2013 land use decision also allows Member States to prepare and

maintain emission accounts from revegetation and the drainage/rewetting of wetlands.

During July 2016 a legislative proposal was presented by the EC to integrate the LULUCF sector into the

2030 climate and energy framework (COM(2016) 479 final; [10]). The proposal sets a legally binding

commitment for all Member States to ensure a “no debit rule” within the LULUCF sector, that is,

emissions should be equivalent to removals. While this “no debit” commitment is already part of the

KP, the proposal would place the same commitment into EU law for the period between 2021 and 2030.

The introduction of greater flexibilities within the proposed LULUCF decision would allow Member

States to use excess allocations from the EU-ESR to meet the intended “no-debit” commitment, and

temporal flexibility in terms of the banking or borrowing of emissions between years (as per the EU-ESD)

[11].

A2.5 Renewable Energy Directive and Fuel Quality Directive

The Renewable Energy Directive (EU-RED), (2009/28/EC; [21]), requires that the EU (through Member

States national targets) use renewable sources to fulfil at least 20% of all its energy requirements by

2020. Also included in the EU-RED is the mandate that all EU Member States must ensure at least 10%

of transport fuels are derived from renewable sources by 2020 [21].

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The Fuel Quality Directive (FQD), (2009/30/EC; [23]) mandates a carbon intensity reduction of transport

fuels within the EU by 6% (when compared to the GHG emissions of conventional fossil-fuel based fuels).

In the context of these policies, the EU has defined a set of biofuel (transport) and bioliquid (electricity

and heating) sustainability criteria. Only biofuels compliant with these criteria count towards renewable

energy targets as specified in the EU-RED and EU-FQD (2010/C 160/02; [132]). The main sustainability

criteria are, (i) that biofuels achieve a specified GHG saving when compared to fossil fuel sources, (ii)

that biofuels cannot be grown on converted land which previously have a high carbon stock (wetlands,

forest), and (iii) that biofuel feedstocks cannot be obtained from lands with a high biodiversity status

(primary forests or high biodiverse grasslands). Compliance with these criteria is assessed by adherence

to either a national and/or recognised voluntary scheme [133].

A 2015 directive (2015/1513; [22]) amended current biofuel legislation (EU-RED, EU-FQD) so to reduce

the risk of indirect LULCC arising from biofuel production, and support the development of advanced

(second-generation) biofuels. This amendment (i) limits the share of biofuels and bioliquids derived from

cereal, starch-rich crops, sugars and oil crops and crops grown primarily grown for energy purposes on

agricultural land to no greater than 7% of specified targets by 2020, (ii) sets indicative targets for

advanced biofuel use by 2017, (iii) specified and harmonises the list of biofuels which contribute double

to 2020 transport energy targets, (iv) sets GHG emission targets for new biofuel installations, and (v)

supports the inclusion of renewable electricity sources within 2020 transport targets [22, 134].

The 2016 European Strategy for low-emission mobility, (COM(2016) 501; [135], highlights that there is

a need for an assessment of the investment needs for advanced biofuels and that, at this time, these

biofuels cannot compete with fossil fuels or food-based biofuels [135].

A 2016 directive of the European Parliament publishes a proposal for a revised Renewable Energy

Directive (EU-REDII), (2016/0382; [15]) for the period 2020 to 2030. This proposed framework sets an

EU target of at least 27% renewable energy sources by 2030 [15]. This directive also includes a proposal

to limit the share of food-based biofuels to 3.8% by 2030 (starting in 2021) and increase the share of

advanced biofuels to 3.6% by 2030.

A2.6 Forest 2013 strategy

No specific forest provisions are made in the EU Treaty. However, the EU contributes to sustainable

forest management and national policy decisions, by Member’s states, through developments in, for

example, rural development policy, the EU climate and energy package, industrial policy, the Europe

2020 strategy and so on [25].

The EU forest strategy (COM(2013) 659; [25]), published in 2013, has been adopted (as a resolution

2014/2223(INI)) by the European Parliament. The forest strategy provides a framework for forest related

63

policies promoting a coherent and holistic forest management approach. It identified the principles to

strengthen forest management whilst also ensuring forest protection and the maintenance of

ecosystem service delivery [25, 26].

The EU Forest Action Plan (2007 – 2011) was implemented in support of a more pro-active and coherent

approach to forest management within the EU. The Action Plan was based on the principles and

objectives of the earlier 1998 EU Forest strategy (EC, 2016d). The action plan focussed on a vision of

long-term multifunctional forestry which fulfilled the needs of society now and in the future and

supported forest-related livelihoods [136]. The key objectives of the plan were: (i) improving long-term

competitiveness, (ii) environmental protection and improvement, (iii) contributing to the quality of life,

and (iv) fostering coordination and communication. These objectives were translated into 18 key actions

to be implemented over the five-year implementation period. The EU Forest Action Plan was reviewed

both during (mid-term) and following (ex-post) its implementation; a summary of the review findings is

provided in [24].

A2.7 Common Agricultural Policy

The Common Agricultural Policy (EU-CAP), is considered central for steering farm level decisions in

support of climate protection in Europe [37].

The new EU-CAP (2014-2020), agreed in 2013 [27], is centred around three long-term objectives: (i)

viable food production, (ii) sustainable management of natural resources and climate action, and (iii)

balanced territorial development. CAP 2014-2020 comprises two pillars. Pillar one supports the income

of farmers via direct payments. Included within this pillar are a set of three ‘greening measures’ namely,

(i) the maintenance of permanent grassland, (ii) ecological focus areas, and (iii) crop diversification [27].

Greening payments must constitute at least 30% of Member state direct payments [137] EU-CAP

environmental objectives are continued under the second pillar, of rural development. Rural

development, implemented through national and/or regional rural development programs (RDPs), must

be based upon four of six common EU priorities; priorities which include (amongst others) the

restoration of ecosystems and shifts towards low carbon/climate resilient agricultural systems [27].

Member States must make at least 30% of their budget for RDPs available for those voluntary measures

which are environment/climate beneficial, for example, climate payments, organic farming, areas of

natural constraints (ANC), Natura 2000 areas, and forestry measures [27].

64

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