bd5010 - synthesising review’ of the use of environmental
TRANSCRIPT
BD5010 - Synthesising Review’ of the use of Environmental Stewardship for
restoring, maintaining and enhancing a coherent ecological network in England.
ANNEX 1: Review of the principles underlying ecological networks in the
context of environmental stewardship
Introduction
Ecological Networks
The publication of the “Making Space for Nature” report (Lawton et al., 2010)
provided a blueprint for the development of ecological networks within the UK, This
was further supported by the UK Government’s Natural Environment White Paper
“The Natural Choice: Securing the value of nature” (Defra 2011) that proposed the
creation of a resilient ecological network across England.
A key question is how can a resilient ecological network for England be developed
from the current protected areas and sites within the UK, particularly as Lawton et al.
(2010) concluded that the current tiers of protected sites in England do not comprise a
coherent and resilient network, especially as many sites are too small and there are
insufficient natural connections within the countryside.
Donald & Evans (2006) have argued that metapopulation theory would suggest wide
ecological benefits from agri-environment schemes that do not appear to be being
realised. They noted that models suggest that improving the quality of the landscape
(in terms of improving the heterogeneity of the matrix) can offset extinction risk
caused by habitat loss and that agri-environment schemes could have a significant role
in reducing extinction rates by softening intensive agricultural landscapes. They
argued that the measures would need to be precisely defined and targeted (to specific
species and landscapes) in order to have measureable impacts on biota. The potential
benefit of agri-environment schemes to ecological networks and connectivity between
populations is echoed in a recent review of connectivity research (Kool et al., 2013).
Given a limited budget for development of a resilient ecological network, the question
of prioritising actions to achieve cost-effectiveness becomes increasingly important.
As Environmental Stewardship (ES) provides a mechanism for achieving large scale
management or modification of existing land and has aims that include the
conservation of wildlife and biodiversity and maintaining and enhancing landscape
quality and character, then we can ask the question, can we utilise the existing options
within ES to support the development of a coherent ecological network for England.
To address this question, Defra commissioned this project BD5010. The project has 4
key objectives:
To summarise current knowledge and expert judgment on the application of
the principles of ecological network development, as outlined in Making
Space for Nature (Lawton et al. 2010), to Environmental Stewardship.
To provide draft guidelines and recommendations for the use of
Environmental Stewardship options in the maintenance and development of
coherent ecological networks, through enhancement of connectivity and
reduction of ecological pressures.
To identify key knowledge gaps in the use of Environmental Stewardship to
maintain and develop coherent ecological networks
To recommend further research for evaluation of the application of
Environmental Stewardship options as a means of enhancing the resilience and
coherence of ecological networks.
The first objective is split into two key components: summarising current knowledge
and identification of the key processes within ecological networks that ES options can
be used to support and a review of the evidence for the ecological benefits of ES
options, mapped to the key processes identified from the first component. This review
is the output from the first component of objective and as such is solely aimed at
determining the current state of knowledge and understanding regarding the principles
underpinning ecological networks and identifying the key functions that ES options
could be used to support. It is beyond the scope of this review to consider which ES
options map to which specific functions as this is covered in the second stage of
BD5010 and is reported separately in Annex 2 (a,b and c).…..
The review is structured into three sections that provide a summary of current
knowledge regarding the underpinning theory behind ecological networks, a summary
of current knowledge regarding the importance of connectivity for ecological
networks and a synthesis of current knowledge, identification and prioritization of the
key processes involved in ecological networks that ES can support .
The underpinning functions of ecological networks
Lawton et al. (2010) identified an ecological network as consisting of the following
components:
Core areas
Corridors and “stepping stones”
Restoration Areas
Buffer zones
Sustainable use areas.
Based on these components, they suggested that there are five key actions that can be
taken to improve ecological network coherence:
Improve the quality of current sites
Increase the size of current sites
Enhance connections through corridors or stepping stones
Create new sites
Reduce pressures by improving the wider environment.
These components and actions are provided in order of a hierarchy of anticipated
benefits to ecological networks and can be attributed to the main metapopulation
principles on which ecological networks are based. Within this section of the review,
we will look at the underpinning theory of ecological networks that of metapopulation
dynamics to determine the relative importance of the five key actions listed above and
prioritised them in relation to where support from ES options should be provided.
Definitions used in this document
There is a high potential for confusion with regards to terminology in the context of
metapopulation theory, connectivity and ecological networks. To provide consistency
we have produced a set of definitions based on the work of Zetterberg (2009) shown
in Figure 1.
Figure 1: Copy of Figure 6, page 21 in Zetterberg (2009), which illustrates the concept of a nested
hierarchy of networks that create metapopulation structure.
The splitting of daily/seasonal dynamics from inter-generational (annual) dynamics
intuitively allows species that utilise multiple habitats to provide their resource
requirements to be considered in the same framework as species that utilise a single
habitat to provide their resource requirements. Consideration of resource availability
has been shown to be important in increasing the abundance and species richness of
landscapes. Recent work by Marja et al. (2013) showed that fields containing open
drainage ditches, which provide foraging and nesting resources supported more bird
species that fields with sub-surface drainage in Finland. Eyre et al. (2013) showed that
the distribution and species richness of ground beetles in agroecosystems was
influence by boundary type and crop type, as well as disturbance, all factors that
determine resource availability in the landscape. Dapporto & Dennis (2013) in their
analysis of the distribution of British butterflies called for the development of wide
ecological networks of heterogeneous sets of resources over the landscape, as these
were crucial to allowing generalist butterflies to survive. They also noted that
specialists were able to survive in isolated habitats as long as the habitats were large
enough. Wretenberg et al. (2007) analysed bird trends in Sweden to show that
extensification of farmland led to increasing in populations of key species, and
suggested that this was due to increased resource availability from measures such as
non-rotational set aside. They did however indicate that landscape structure would
play a significant role in determining the effect of extensification on farmland birds.
Finally, Persson & Smith (2013) showed that bumblebee abundance was significantly
reduced in simplified landscape containing less floral resources (and a lower
proportion of perennials) compared to complex landscapes.
There is therefore ample evidence to suggest that considering a patch as a resource
network makes ecological sense, and hence we have adopted this framework for use
in this project. Using this framework, the following key definitions have been
produced, and will be used throughout the rest of this review:
Habitat – a specific land cover that provides resources used by a species
(Resource) Site – a geographically delimited area of habitat providing resources
used by a species
Patch – a network of one or more sites providing sufficient resources to support
one or more reproductive units of a species.
Connectivity between resource sites – Resource sites are deemed to be connected
when they both fall within the home range (or daily/seasonal foraging distance) of
a species.
Connectivity between patches – Patches are deemed to be connected when the
distance between their boundaries is less than the dispersal distance of the species.
theory definition of a patch being able to support a population)
Classic metapopulation dynamics
The key underlying principle of ecological networks is metapopulation dynamics
(Bennett, 2003; Donald & Evans, 2006; Hanski, 1994; Hodgson et al, 2009; Lawton
et al., 2010; Moilanen et al., 2005; Moilanen & Wintle, 2006; Opdam et al., 2006). A
metapopulation is often described as a “population of populations”; each individual
population is in a patch of suitable habitat. The classical metapopulation (sensu
Levins (1969)) is based on the following assumptions (Etienne, 2000; Hanski, 1994)
All patches (where a patch is assumed to provide all the resources that a
species population requires (i.e. contains the resource network for the species))
are of equal size
All patches are equally spaced and equally accessible
(this allows the dynamics of a single patch to represent the dynamics of the
entire system)
The population in any patch has the ability to go extinct
Within patch dynamics are asynchronous
The above assumptions were used in early metapopulation work to simplify the
system in order to make it mathematically tractable when determining how the ratio of
colonisations to extinctions (at a patch level) affected the potential for extinction of
the metapopulation. It should be noted that this formulation of the theory does not
include any specific representation of the spatial arrangement of patches. Despite all
these simplifications, the theory produces a number of important predictions about
how metapopulations should behave.
Classic metapopulations should persist if each patch contributes to the colonisation of
at least one other patch and patch occupancy is less than 90% (Gyllenberg et al. 2004;
Fronhofer et al., 2012; Hanski, 1994). The implications of these predictions are two-
fold: unoccupied patches are as important as occupied patches from a metapopulation
persistence perspective and also local (i.e. within patch) extinctions are acceptable as
long as the population persists at the regional level (Opdam et al., 1991). However, it
has been shown that systems with low occupancy will become extinct sooner than
systems with higher occupancy (Etienne & Nagelkerke, 2002; Araújo et al., 2002),
which suggests that increasing occupancy is important for the conservation of a
population.
As the simplifying assumptions are not particularly representative of the real world, it
is important to examine the key predictions from studies where the theory has been
extended to more accurately represent the real world situation. Here, we will consider
two main types of extension to the metapopulation theory: varying within patch
factors, such as size, quality and emigration rates, and varying the spatial arrangement
of patches.
Extensions to classic metapopulation dynamics – variance in within patch factors
The effect of patch size on the persistence of metapopulations was first considered by
Hanski (1994), who developed a metapopulation model, formulated as a stochastic
patch occupancy model (SPOM) based on the butterfly (Melitaea cinxia) using an
incidence function approach. He showed that as the size of patches decreased, there
was a greater chance of extinction of the metapopulation due to patches becoming
more isolated. This conclusion was supported by Day & Possingham (1995) who
developed a stochastic model based on the Mallee Fowl in Australia. They concluded
that including variable patch sizes led to higher probabilities of extinction, but felt that
this would not be a general result as the effect of including variable patch size would
be specific to the distribution of patch sizes used in the model and the colonisation
rate particularly where extinction was a function of patch area. Hokit & Branch
(2003) showed that with area sensitive species demographic parameters, extinction
rates were higher for smaller patches and declined rapidly above a threshold size (10-
20ha), which supports the findings of Hanski (1994). However, when the
demographic parameters were independent of patch size a more linear decline in
extinction probabilities occurred. These conclusions on the effect of patch size on
extinction rates were reinforced experimentally by examining the local extinction
probabilities of two scrub lizard species, which showed that local extinction was much
greater for patches smaller than 5-10ha. In addition, a recent analysis of the
distribution of British butterflies (Dapporto & Dennis, 2013) has suggested that
specialist species can survive fragmentation in isolated patches if these patches are
large enough. Prugh et al. (2008), in an analysis of occupancy data of over 1000
species, suggested that patch area was a better predictor of occupancy than isolation
and that total habitat amount was probably the main determinant of population size.
They further suggested that spatial configuration was unlikely to affect occupancy of
patches until a threshold was reached, but were unable to test this hypothesis in the
analysis due to lack of information on the proportions of habitat and non-habitat in the
studies.
The impact of patch preference for immigration (occupied or empty) was shown to
have a significant impact on the proportion of empty patches by Etienne (2000) using
a modified Levins model. If occupied patches were preferred the proportion of empty
patches increased with the proportion of suitable habitat (towards an asymptotic
value), but if empty patches were preferred then this relationship no longer held and
the proportion of empty patches could either decrease or remain constant as the
proportion of suitable habitat increased, the latter case occurring if a rescue effect
(simultaneous extinction and recolonisation) existed.
Latore et al. (1999) examined the impact of habitat quality (in terms of heterogeneity
of resource availability) and dispersal using an artificial landscape, assuming
parameters of relevance to plants. They estimated the critical habitat size (minimum
size required to support a persistent population) based on the incorporation of a
habitat quality function (equivalent to a resource availability function) into a
metapopulation model with different dispersal types. They determined that
populations had a higher probability of persistence when patches were of uniform
high quality, were close together and there was one dominant large patch, which is
reminiscent of the mainland-island metapopulation structure. They also showed that
this result was consistent across the dispersal functions used, indicating that habitat
quality effects are more important than connectivity effects. This is supported
experimentally by Fleishman et al. (2002), Franzen & Nilsson (2009), and Öryössy
et al. (2012) and who have shown habitat quality effects on populations of the
butterfly (Speyeria nokomis apacheana), solitary bees (Andrena hattorfiana) and the
false ringlet butterfly (Coenonympha oedippus), respectively. Furthermore, over the 6
years of their study, Fleishman et al. (2002) were able to show that habitat quality
factors were better indicators of patch occupancy than patch area.
Extensions to classic metapopulation dynamics – incorporating temporal and spatial
structure
As temporal and spatial structure of the habitat patches are key components of real
fragmented landscapes, recent metapopulation modelling effort has included a focus
on including these factors in metapopulation models.
DeWoody et al. (2005), Gyllenberg et al. (2004), Keymer et al. (2000) & Vuilleumier
et al. (2007) investigated the impacts of temporal changes in patch availability or
local dynamics within patches. They all concluded that long term dynamics of the
metapopulation are determined by the relationship between the scale of
metapopulation dynamics and the landscape dynamics, i.e. if the landscape changes
faster than colonisation-extinction process then the metapopulation will become
extinct. This implies that the rate of habitat turnover or loss is important in
determining the species persistence, with Keymer et al. (2000) suggesting that models
incorporating temporal dynamics predict more frequent extinctions than models
considering only reductions in area, increase in isolation and loss of connectivity. At
high rates of habitat loss, the landscape spatial structure will be critical for species that
are poor dispersers as they will be constrained by their dispersal. For species that
utilise ephemeral habitats, both studies suggest that increasing the habitat lifespan is
the more beneficial than changing its amount, as there is a threshold habitat lifespan
above which persistence of the metapopulation is ensured. However, Gyllenberg et
al., 2002 showed that where the colonization to extinction ratio is less than one (i.e.
the metapopulation is doomed to extinction without any intervention), the average
time to extinction (assuming at least one patch is occupied) increased logarithmically
with the number of patches. They did caution that their models were far less concrete
than those based on a detailed understanding of species ecology and with explicit
consideration of patch spatial structure. Vuilleumier et al. (2007) examined the impact
of landscape shape, showing that extinction could be twice as high in elongated patch
configurations (long and thin) compared to compact patch configurations (short and
fat) for the same levels of connectivity and disturbance. They suggested that a
metapopulation within an elongated patch network structure experiencing a fixed
disturbance regime was almost certain to become extinct compared to a compact
patch network which would remain viable in almost all cases.
The papers above indicate the importance of the spatial structure of the habitat
network and this is taken further in work on marine ecosystems (Artzy-Randup &
Stone, 2010) that showed that a more heterogeneous network (i.e. one with greater
connections and linkages between the nodes (or patches) within the network) would
lead to greater persistence due to the presence of a greater number of potential
cyclical routes for dispersal (where a cyclical route occurs when a set of patches are
linked such that A is connected to B which is connected to C, which is connected to
A). They suggested that the dominant cyclic component of the network determines the
persistence of the metapopulation, something that is supported by previous work by
Wu et al. (1993) who showed, using a simple model of 3 habitat patches, that
persistence was greater when more inter-patch connections were present, i.e. the
patches formed a cyclical network. The implication of this body of work is that spatial
structure is important in determining the persistence of a species, especially in
ephemeral habitats and if that species is a poor disperser.
Day & Possingham (1995) concluded from their work on a metapopulation model for
the Mallee Fowl that explicitly incorporating the spatial positions of the patches
within the network, using distance to determine level of accessibility of the patch, did
not provide significantly different extinction probabilities to assuming all patches
were pairwise equidistant. This is supported by work by Graniero (2007) who
compared a model explicitly representing local colonisation of patches, based on the
spatial arrangement of patches within the landscape, with a model where spatial
structure was not explicitly represented, and colonisation of patches was considered at
a landscape scale. They showed that there were no noticeable differences in the spatial
patterns of species distributions in the landscape between the two models. However,
when the model was extended to include local variation in patch quality, it was shown
that long term persistent landscape-scale metapopulation patterns occurred, such that
both the local and global distributions of species were affected by landscape pattern.
In other words, the heterogeneity of the environment and pattern of resource
availability within the landscape is important in determining metapopulation
dynamics. This latter model is one of two models examining multiple species
(competitors) metapopulations (Graniero, 2007; Taneyhill, 2000), which suggest that
if the metapopulations of both species are to persist, recolonisation of empty patches
or patches occupied by a single species from patches occupied both species is
important. In addition, Graniero (2007) suggested that resource heterogeneity plays a
major role in determining species occupancy in a patch, by interacting with dispersal
distance, such that local dynamics drive metapopulation persistence through source-
sink dynamics, where a large persistent patch continually contributes immigrants to
smaller patches that would be unoccupied without the continuous immigration. In
work based on the long term monitoring of butterfly populations, Thomas et al.
(2001) showed that patch quality was three times better at explaining which habitat
patches supported a species population than either patch isolation or area. They also
showed that patch area and occupancy were not correlated for any of the species
studied. They pressed for a re-evaluation of conservation priorities to account for the
importance of within-patch quality, and suggested that geographical sites for
conservation focus should no longer be selected solely on the basis of size or lack of
isolation, but should be selected for high habitat quality as well.
Using metapopulation theory for management of populations
A number of studies have used metapopulation theory or models to identify
appropriate strategies for conservation management and it is appropriate to determine
whether they can aid the identification of the key functions that are required for the
development of ecological networks.
Focussing of resources
Several studies have examined strategies for determining how to focus limited
resources, utilising metapopulation models or theory to aid selection of appropriate
landscape elements to focus resource use on. Etienne & Hesterbeek (2001) used a
metapopulation model to show that decreasing local extinction was preferable to
increasing colonisation (improving connectivity), except in the following cases:
the probability of patch recolonisation is (very) low and extinction probability for
a patch is smaller than (1 – (1/(n-1)), where n is the number of patches (this
exception is primarily relevant for networks with few patches where
recolonisation between the patches is limited).
high probability of patch recolonisation with continuous interchange of
individuals between patches (this exception is due to the fact that if patch
recolonisation is a certainty, extinction is not possible unless all patches go extinct
simultaneously) ,
when increasing colonisation rates is preferred. They then examined sets of extreme
cases to determine that :
Reduction of local extinction should be focussed on the patch with the lowest
local extinction probability except if extinction probabilities are (almost) equal,
when the extinction probability of the best connected patch should be reduced.
Colonisation probability between patches with the lowest extinction probabilities
should be increased preferentially. Only if the extinction probabilities are (almost)
equal (and not very low) should the highest colonisation probability be increased.
The authors noted that these rules would indicate that managing a single large
extinction-proof patch would appear to be the best option, but did state that these rules
of thumb will only hold true if metapopulation extinction is the criterion of choice.
Etienne (2004) extended the work described by using an artificial landscape to
determine which patch should receive the management to reduce local extinction rates
and whether manipulating quality or area was the better approach. He determined that
in general it is preferable to increase the size of the largest patch (and reduce the inter-
patch distance between the largest patches), but there were two, significant,
exceptions.
1. If adding an absolute area (e.g. 1ha to one existing patch) then the smallest patch
should be chosen
2. If adding a strip (e.g. 100m) of habitat around an existing patch (lies between
absolute and relative addition), then any patch can be chosen, although the largest
patch should prevail, particularly when patches are relatively isolated.
The rules provided above are supported by recent work examining the consequences
of spatial and temporal habitat dynamics on conservation planning (Van Teeffelen et
al., 2012). They reviewed the literature (70 papers) on metapopulations with respect
to habitat dynamics to determine what strategies were most effective in increasing
metapopulation persistence in dynamic (constantly changing) networks. They
concluded that:
Increasing the network area (area of patches) always increases metapopulation
persistence (and 20-60% of the landscape should be habitat to buffer against
turnover effects).
Larger patches are more beneficial, except:
If total network area is larger when the total area of smaller patches is
considered (i.e. there is greater coverage of landscape through a network of
numerous small patches compared to a few larger patches).
If networks had exceeded a threshold area, which was species dependent
and was determined by the time horizon over which extinction risk was
evaluated.
If within-patch competition was stronger in larger patches.
Patches with higher quality (resource availability and accessibility) will (almost)
always have increased population persistence and habitat disturbance (i.e.
temporally restricting resource availability or accessibility) will generally decrease
metapopulation persistence.
Improving connectivity increases colonisation and increases metapopulation
persistence in most cases, particularly for species with a high dispersal capability.
Patch lifetime should exceed the species generation time.
They also suggested that increasing network area and increasing network connectivity
are interchangeable options for species with low dispersal capability, but for species
with a high dispersal capability, the specific network properties would determine the
most appropriate strategy. For habitat restoration they suggest that this should take
place close to existing populations and as quickly as possible, and that enlarging
current patches is preferable to adding new patches, except where patch turnover is
high (i.e. where habitat patch lifetime is short relative to the generation time of the
species). The focus on improving patch quality is also supported by the work of North
and Ovaskainen (2007), who modelled the interactions between dispersal, competition
and landscape heterogeneity using a spatial explicit individual-based model. As they
were interested primarily in plants, they assumed that dispersal was homogeneous
between different habitat types and that habitat heterogeneity manifested thorough
changes in the reproductive potential of the model organism. They showed that it is
better to maintain high quality habitat at the expense of lower quality habitat as the
model predicts that organism will aggregate into high quality areas. However, the
validity of the assumption of homogeneous dispersal is limited, and further work is
needed to understand the implications of breaking this assumption on the conclusions
drawn from the model.
The utility of rules of thumbs was questioned by Westphal (2003), who showed, using
a SPOM (stochastic patch occupancy model) for the Southern Emu Wren in Australia,
that following rules of thumb provided the optimal set of decisions in no more than
50% of cases, where the optimal decision making process accounted for landscape
structure, but the rules of thumb did not. However, following a rule of thumb led to
30% increase in time to extinction of the metapopulation, relative to the baseline
condition of doing nothing, whereas the optimal decision making led to a 50-80%
increase in the time to extinction of the population. This paper highlights that
incorporating greater knowledge into the decision making process is always going to
be better than a rule of thumb, but that in the absence of knowledge the rule of thumb
is an acceptable strategy as it is better than no form of intervention.
Reserve design
A number of papers have utilised metapopulation theory and models in determining
the most appropriate design for reserves for the conservation of species, a problem
analogous to ecological network design (Cabeza & Moilanen, 2001; Cabeza et al,
2004; Dalang & Hesperberger, 2012; Moilanen et al., 2005; Moilanen & Wintle,
2006). These papers tend show that larger more aggregated structures are most
beneficial as reserves, which fits with the rules of thumb (Etienne & Hesterbeek 2001;
Etienne, 2004; Van Teeffelen et al., 2012) described above, but they caution that the
models used are primarily for identification of key areas where more detailed
planning should be focussed. Dalang & Hesperberger (2012) suggest that the optimal
choice for a compensation scenario in a reserve (increasing area, quality or
connectivity) will depend on the ecological characteristics of the target species, the
spatial characteristics of the network and the permeability of the matrix. The need for
good quality data is echoed by Ter Braak et al. (1998), who demonstrated that using
snapshot data to parameterise SPOMs may lead to incorrect estimation of parameters,
especially when the (meta)population is not in a colonisation/extinction equilibrium, a
key assumption of SPOMs.
Using simple metapopulation models to estimate the best strategy for reserve design,
Etienne & Hesterbeek (2000) showed that if increasing the time to extinction is the
primary goal, then maximising the size of the patch is the most appropriate strategy.
However, they also demonstrated that if the goal was to maximise the colonisation
potential, there was an intermediate size of reserve that was optimal. However, they
acknowledged that defining the optimal size was difficult as it relied on species
specific parameters, and that miscalculations might have large consequences.
Summary of review on metapopulations
The most important message that we can take from the metapopulation theory are that
increasing patch area, increasing patch quality and increasing connectivity will always
be beneficial in terms of increasing metapopulation persistence (Artzy-Randup &
stone, 2010; Cabeza & Moilanen, 2001; Cabeza et al, 2004; Dalang & Hesperberger,
2012; Etienne & Hesterbeek, 2001; Etienne, 2004; Hanski, 1994; Hokit & Branch,
2003; Latore et al., 1999; Moilanen et al., 2005; Moilanen & Wintle, 2006; Thomas
et al., 2001; Van Teeffelen et al., 2012; Wu et al., 1993).
The next question is whether we can determine a hierarchy of importance of these for
these three actions to increase metapopulation persistence. In doing this, it is perhaps
wise to separate ephemeral from non-ephemeral habitats. In doing this we can propose
the following orders of importance of the actions:
For non-ephemeral habitats
Increasing patch quality is of greater importance than increasing patch area
which is of greater importance than increasing connectivity, which is of
greater importance than increasing the number of patches. (Day & Possingham,
1995; Cabeza & Moilanen, 2001; Cabeza et al, 2004; Dalang & Hesperberger,
2012;Etienne & Hesterbeek, 2001; Etienne, 2004; Fleishman, 2001; Graniero,
2007; Latore et al., 1999; Moilanen et al., 2005; Moilanen & Wintle, 2006;
Thomas et al, 2001; Van Teeffelen et al., 2012).
For ephemeral habitats (where there is high turnover of patches)
Increasing patch lifetime is of greater importance than increasing the number of
patches which is of greater importance than increasing patch quality, area or
connectivity.
(DeWoody et al, 2005; Gyllenberg et al, 2004; Keymer et al., 2000; Van
Teeffelen et al., 2012; Vuilleumier et al., 2007)
Although we can propose a preferred order of importance for actions to improve
metapopulation persistence, it is essential to remember that the spatial structure of the
patches in the landscape combined with the ecology of the species of interest will
determine the most appropriate actions to improve its metapopulation persistence
(Cabeza & Moilanen, 2001; Cabeza et al, 2004; Dalang & Hesperberger, 2012;
Etienne & Hesterbeek, 2000; Hokit & Branch, 2003; Moilanen et al., 2005; Moilanen
& Wintle, 2006; Ter Braak et al., 1998). Therefore, in an ideal situation, the choice of
action would be determined based on a sound understanding of the ecology and
spatial structure of the habitat network of each species of interest.
Connectivity for ecological networks
Opdam et al. (2006) contended that sustainability for conservation could not be
achieved at local sites, but that linking these sites in a cohesive network might spread
the risk of local extinction across the landscape, which is the fundamental underlying
principle of metapopulation theory. Hodgson et al. (2009) recently re-examined the
assumptions underlying conservation planning and concluded that connectivity is
plagued by uncertainties and can be co-incidentally improved by targetting habitat
quality and area. They argued that the effects of increasing connectivity on the total
carrying capacity of an organism in a landscape are unknown, but increasing habitat
area and quality will always increase the total carrying capacity of the landscape. In
contrast, Doerr et al. (2011) suggested that increases in habitat extent will not
necessarily increase connectivity, except when patches are close enough to allow gap
crossing. Doerr et al. (2011) focussed on structural connectivity (the physical
characteristics of the landscape between patches of occupied habitat), arguing that the
effects of structural connectivity are predictable, applicable to a wide range of species
using a similar environment, and can be directly quantified due to recent advances in
understanding of species movement. However, it is not clear whether Doerr et al.
(2011) are concerned with foraging movement or inter-generational patch dispersal, a
distinction which is critical when considering ecological networks and metapopulation
dynamics. It could be argued that structural connectivity is more applicable for
connectivity in resource networks (intra-patch) where short distances are likely to be
involved that for inter-patch connectivity where species may be dispersing over large
distances and utilising a different behavioural strategy to intra-patch foraging
movements.
Gaston (2006) suggested that the development of ecological networks in the UK is in
its infancy and there is a paucity of data for determining both the baseline and
assessing the effectiveness of protected areas. Also, Opdam et al (2006) argue that
ecological networks should be able to change in area, shape and location over time
without changing their conservation potential, and hence should place a greater
reliance on increasing the movement of a species through the landscape rather than on
creating fixed corridors or stepping stones to assist species movement. There is
therefore a need to understand the current knowledge regarding connectivity
(including corridors and stepping stones) and assess its importance for the
development of ecological networks.
Review of current knowledge and understanding of connectivity
Gilbert-Norton et al. (2010) and Eycott et al. (2010, 2012) have both reviewed
published experimental work on the effectiveness of corridors. They both concluded
that corridors (defined as a narrow linear piece of habitat connecting two larger
patches of habitat) increased the movement between habitat patches by approximately
50% compared to patches not connected by corridors. Gilbert-Norton et al. (2010), in
their meta-analysis of 78 studies covering a wide range of taxa (birds, fish,
invertebrates, amphibians, mammals and plants), noted that controlling for distances
between source and recipient patches led to a decrease in the estimated movement
through corridors compared to not controlling for these variables but that corridors
worked equally well for all taxa. They also identified that there was more movement
through natural corridors than through artificially created corridors in manipulative
experiments, although they noted that the artificial corridors creates at a single site
(Savannah River, where forest corridors were created in clear cut landscapes) were of
similar effectiveness to natural corridors. In both reviews, the majority of these
studies were conducted over short time-scales and therefore probably do not reflect
true dispersal, but are more likely to represent foraging movements and hence the
increased area of habitat acts as an extension of the patches that it joins. This point
was highlighted by Bailey (2007) in her review of woodland connectivity and was
demonstrated experimentally by Delattre et al. (2011) for butterflies. Additionally, in
his work on the movement of butterflies, Ricketts (2001) clearly emphasised that he
was experimentally manipulating local (foraging) movements rather than longer
distance dispersal and that dispersing individuals would probably respond differently.
The latter point highlights the need to be very clear regarding the type of movement
we are interested in from the perspective of conservation and ecological networks.
Jacobson & Peres-Neto (2010) identified three forms of movement behaviour:
movement (foraging and behaviour within a home range); migration (a bi-directional
seasonal movement) and dispersal (uni-directional in search of a new home range),
where dispersal is assumed to influence system (metapopulation) persistence and the
dynamics of both the population that it emigrates from and the population that it
immigrates into. From these definitions, it is dispersal that is predominantly
considered within metapopulation dynamics and hence the movement type that should
be the focus of connectivity in relation to ecological networks, particularly if it can be
assumed that the patches within the ecological network should be of sufficient size to
allow foraging movements. The only exception would be for species that show a
nomadic behaviour (Berbert & Fagan, 2012) where species wander between a number
of ephemeral feeding sites over the landscape. However these species could simply be
considered to have a very large home range. There is some evidence (Baguette & Van
Dyck, 2007) that dispersal behaviour evolves in response to landscape configuration
and that the distribution of resource patches in the landscape, relative to the perceptual
range of a species, is crucial in driving this evolution, such that the movement
behaviour of a species will differ in different landscapes.
The use of short timescales for corridor effectiveness experiments, as a problem in
determining their efficacy, was emphasised by Bailey (2007) in her review of
woodland connectivity, where she suggested that it was a possible explanation for the
lack of evidence for an increase in species richness following an increase in woodland
connectivity, and by Bennett (2003) in a review of the role of corridors and
connectivity for the IUCN. Bennett (2003) further suggested that the acceptance of the
concept of corridors and stepping stones had outpaced scientific understanding and
rephrased the question of connectivity as:
“What is the most effective pattern of habitats in the landscape to ensure
ecological connectivity for species, community and ecological processes?”
He proposed that connectivity could be achieved in two ways:
1. Managing the whole landscape mosaic to promote movement and population
continuity (most preferable)
2. Managing specific habitats within the landscape to achieve this purpose.
However, he conceded that for fragmented landscapes the first option was probably
not possible and that whole landscape management should primarily be used in
natural or semi-natural landscapes where it was of most benefit to species ranging
over a wide area.
Bennett (2003) noted that there is no general connectivity solution that will meet the
requirements of all species and that different types of connections are needed for
movements spanning different scales. For example, corridor type connections are
likely to be beneficial to specialists with limited dispersal capacity, whilst stepping
stones benefit species that are relatively mobile and are tolerant of disturbed
landscapes or are nomadic. He expressed a need for better understanding of
connections, particularly at the landscape, regional and continental scales as most
work to date has been done at a local scale for short distances through cleared land.
The need for species specific information to assess connectivity has been emphasised
by Szabó et al. (2012); who tested a number of connectivity metrics for grassland
species using GIS data and CORINE land cover data. They concluded that the
location of patches within the landscape is more important than their size in
estimating connectivity and that a lack of knowledge regarding the movement
behaviour of focal species limits the usefulness of connectivity indices.
Bennett (2003) also highlighted the importance of linear features (hedgerows,
fencerows, streams, roadsides, forest corridors) as a means of retaining connectivity in
agricultural landscapes. This importance has also been emphasised by Bailey (2007)
in a review of the evidence for connectivity in woodlands, where it was suggested that
dispersal of woodland species was more likely if the availability of resources in the
matrix was increased, with stream-sides, riparian strips, meadows, bracken, ungrazed
pasture and hedgerows having been shown to provide suitable conditions for
woodland species. The importance of hedgerows for movement of birds, as well as in
providing cover, feeding resources and nesting habitat was reinforced by Hinsley and
Bellamy (2000) who proposed that bigger hedges are generally better, but that there
should be a heterogeneity of hedge sizes, shapes and species compositions in the
landscape due to differences in preferences of the bird species for these factors.
However, Davies & Pullin (2006), in a review of the role of hedgerows as corridors
stated that there was insufficient evidence to evaluate the effectiveness of hedgerows
as corridors for woodland species. However, they did note that there is anecdotal
evidence of positive local population effects and that some species use hedgerows as
conduits. They did concur with Hinsley and Bellamy (2000) on the fact that a greater
structural and vegetational diversity would provide resources for multiple species. The
use of roadside verges as a means of movement has been noted for hedgehogs
(Rondini & Doncaster, 2002) and carabid beetles (Noordijk et al., 2011).
In a review of woodland connectivity, Bailey (2007) noted that there is a lack of firm
empirical evidence that species richness increases after attempts to increase
connectivity between fragmented woodlands and that biodiversity loss was most
likely to be due to habitat loss rather than fragmentation. If this assertion is correct,
then it implies that, for woodland, increasing habitat is more important that increasing
connectivity in terms of increasing species richness. The importance of long-distance
dispersal events in maintaining populations and allowing species to shift ranges was
also highlighted with an example of four saproxylic insects, previously thought to
have poor dispersal, experiencing a rapid expansion in range due to more
favourable habitat becoming available. There is a lack of recognition of the
importance of long distance dispersal for population persistence (Trakhtenbrot et al.
2005), despite the fact that long distance dispersal has been shown to be rare and
difficult to measure (Jacobson & Peres-Neto, 2010), it is both central to a number of
population processes in heterogeneous environments and the higher the degree of
fragmentation the more important long distance dispersal becomes in ensuring
metapopulation persistence (Trakhtenbrot et al. , 2005; Marco et al. , 2011; Pearson
& Dawson, 2005) Indeed, Opdam (1991) highlighted the skewed distribution of
dispersal distances associated with woodland birds, with most going short distances,
but a few covering large distances as being important in understanding the
metapopulation dynamics of woodland species. Using simulations for plant seeds,
Pearson & Dawson (2005) also showed that with a constant proportion of suitable
habitat in a landscape, the structure of the landscape becomes increasingly important
in ensuring metapopulation persistence as long distance dispersal increases.
Donald & Evans (2006) in reviewing the theory and literature regarding connectivity,
suggested that a general softening of the matrix (increasing its quality through
inclusion of a greater proportion of non-crop habitats), using agri-environment
schemes, should lead to improved connectivity. This is supported by Eycott et al.
(2010, 2012) in their review of species movement which showed that species
preferred to move through landscape matrices with a similar structure to the habitat
patches and were more likely to leave patches if the surrounding landscape had a
similar structure, although there was significant heterogeneity in the studies. Bailey
(2007) also supported the concept of softening the matrix, by providing resources that
could be utilised by woodland species. Briers (2011) in his review of the evidence
base for habitat networks concluded that there was sufficient evidence to support the
view that general landscape features (linear habitats and land-uses) affect the ability
of a species to move through the landscape, but that for the UK, the evidence base is
extremely small and taxonomically limited and that there was insufficient information
to allow assessment of how different land covers affected the dispersal distance of a
species. In modelling work using GIS least cost modelling to identify habitat networks
for England, Catchpole (2007) suggested that increasing the permeability of the
landscape (which is equivalent to softening the matrix) should be the exception rather
than the norm, where budgets are limited
Although evidence that softening the matrix increases dispersal is limited, there is
some evidence from the ecosystem services literature that increasing resource
availability and accessibility leads to increased abundance of species in farmland.
Holzschuh et al. (2009) have shown that providing grass strip corridors connected to
woodland (that contains the primary nesting sites for the parasitic wasps studied) led
to increased species richness and abundance of parasitic wasps in farmland, compared
to isolated grass strips (although the latter still supported populations of species that
were highly mobile). Recent work on ecosystem services (Bianchi et al., 2013) has
suggested, based on case studies focussed primarily on provision of floral and grass
strip resources, that for enhancement of farmland biodiversity a minimum permanent
non-crop area of 5% is required, and that above non-crop areas of 20-30% no further
positive benefits have been reported. However they do note that there is limited
information on the effectiveness of agri-environment measures for increasing species
movement, abundance and richness in a landscape.
The importance of the matrix was shown experimentally for butterfly populations by
Ricketts (2001), with four out of six butterfly taxa responding to matrix composition.
However, it was noted that these four species were intermediate in their movements
compared to the other two species. This study does reinforce the importance of
understanding species responses and movement behaviours when considering
connectivity. In addition, Kindlmann et al (2005) showed that the movements
between subpopulations in the butterfly (Maniola jurtina) could be affected by the
intervening matrix and that emigration declines with patch size. Good (1998) in
reviewing the potential for using regional ecological corridors (and stepping stones)
for habitat conservation in Ireland, came to the conclusion that it was preferable to
consider the total permeability of the landscape rather than specific corridors, unless
the latter were linear landscape features. Good (1998) also advised that:
“The concept of ecological corridors should not be allowed to deflect attention from
dispersal processes (such as seed dispersal by livestock) to landscape patterns. Habitat
fragmentation and integrated dispersal management must be considered on a case-by-
case basis comparing the cost-benefit of the range of available options.”
This sentiment is shared by Hodgson et al. (2009) who also support the softening of
the matrix, suggesting that increasing environmental heterogeneity one of the four
principles for robust conservation strategies, and that:
“The conservation of high quality existing habitats should … remain the primary
focus of conservation efforts to maintain biodiversity.”
Summary of connectivity understanding
The main message from the literature is that understanding the autecology of the
species is crucial to determining the importance of connectivity as the most
appropriate methods for achieving connectivity will vary with species (Bailey,
2007; Bennett, 2003; Briers, 2011; Hinsley & Bellamy, 2000, Opdam et al., 2006,
Pascual-Hortal & Saura, 2007). This is especially relevant with respect to the
dispersal and movement behaviours of species and how they perceive the landscape
(Bennet,2003; Jacobson & Peres-Neto, 2010; Marco et al. , 2011; Pearson & Dawson,
2005; Szabó et al., 2012; Trakhtenbrot et al., 2005). The need to understand species
autecology has been demonstrated experimentally by Rickets (2001), who showed
that the perception of different habitats as barriers differed among butterfly species.
This is supported by the work of Uezu et al. (2005), who showed that for 7 species of
forest birds, connectivity was the main factor governing abundance in only 2 species,
with one species responding to inter-patch distance and the other to the presence of
corridors. In their report on the Breckland Biodiversity Audit, Dolman et al. (2010)
showed how different assumptions about the movement ecology of species affected
ecological network identification. They analysed 87.1 km2 of dry heath to identify
ecological networks for species with different dispersal abilities and showed that for
species with a low dispersal capability (<100m), there were 162 networks all isolated
from each other, whilst for species with moderate dispersal abilities (up to 1km) there
were 52 networks, whilst for species with good dispersal (up to 2km) there was a
single connected network.
There is a need to recognise the importance of long-distance dispersal and the role
that it plays in maintaining metapopulation dynamics (Bailey, 2007; Good, 1998;
Marco et al., 2011; Pearson & Dawson, 2005; Trakhtenbrot et al. , 2005). Although
rare, these events may maintain connectivity between distant sites and should be taken
into account when planning an ecological network.
Since it is recognised that there is a paucity of data for the development of ecological
networks (Bennett, 2003; Gaston, 2006) we have to consider what options we have to
increase connectivity in the event that we do not have a thorough understanding of the
ecology of the species of interest. The literature would suggest that the most
preferable option is to soften the matrix by increasing the availability or resources of
benefit to multiple species (Bailey, 2007; Donald & Evans, 2006; Eycott et al., 2010,
2012; Hodgson et al., 2009), although it should be noted that softening the matrix is
likely to be of less benefit to species with restricted foraging and dispersal movements
(Donald & Evans, 2006). Accepting that softening the matrix is most likely to benefit
more mobile species, it is possible to prioritise increasing the amount, quality and
heterogeneity of linear features (hedges, riparian strips, etc) as these are known to
benefit a wide range of species (Bennett, 2003; Bailey, 2007; Hinsley & Bellamy,
2000) over a general increasing of resource availability (via reduction of intensity of
management) within the landscape.
Synthesis of current knowledge
Core functions underpinning ecological networks to be supported by ES options
In order to synthesise the current understanding regarding metapopulation theory and
connectivity into a set of useful guidelines we need to accept that most populations
exist as metapopulations within the landscape. If we allow the definition of
metapopulations to encompass spatially structured populations (sensu Fronhofer et al.,
2012), then the consensus view is that metapopulation theory is applicable to most
populations that would be considered within an ecological network (Donald & Evans,
2006; Hodgson et al., 2009; Lawton et al., 2010; Opdam et al., 2006).
From the metapopulation theory we can identify the key functions required to support
an ecological network and these are, in order of priority: improvement of patch
quality; increase of patch area and improvement of patch connectivity (Day &
Possingham, 1995; Cabeza & Moilanen, 2001; Cabeza et al, 2004; Dalang &
Hesperberger, 2012;Etienne & Hesterbeek, 2001; Etienne, 2004; Fleishman, 2001;
Graniero, 2007; Latore et al., 1999; Moilanen et al., 2005; Moilanen & Wintle, 2006;
Thomas et al., 2001; Van Teeffelen et al., 2012). Additionally, where environmental
disturbance causes a high turnover of sites and/or patches, then two additional
functions occur, which are (in order of priority): increasing the lifetime of the patch
(by reducing disturbance\ and increasing the number of patches through creation
of new patches, where these two functions have priority over the three above
(DeWoody et al, 2005; Gyllenberg et al, 2004; Keymer et al., 2000; Van Teeffelen et
al., 2012; Vuilleumier et al., 2007).
Metapopulation theory is primarily concerned with patch quality, area and
connectivity, but what is meant by patch connectivity? Taking the conceptual view of
Zetterberg (2009), illustrated in Figure 1 at the start of this review, we can consider a
patch to consist of a network of sites, where the network of sites provide the resources
required to support a population. The precise management actions required will be
defined by the structure of the patches in terms of sites, the spatial pattern of patches
and sites, the nature of disturbance to the sites and the ecological requirements of
species (Bennett, 2003; Bailey, 2007; Cabeza & Moilanen, 2001; Cabeza et al, 2004;
Dalang & Hesperberger, 2012; Etienne & Hesterbeek, 2000; Hinsley & Bellamy,
2000; Hokit & Branch, 2003; Moilanen et al., 2005; Moilanen & Wintle, 2006;
Opdam et al., 2006; Pascual-Hortal & Saura, 2007; Ter Braak et al., 1998), as well as
the aims of the ecological network.
Where ecological information is limited, or where actions are being applied in the
wider environment as opposed to defined patches, then we need to determine whether
there are key management actions that can be supported by ES options to provide one
or more of the functions identified above. Using the framework of Zetterberg (2009)
we can assume that increasing patch area and quality are akin to increasing resource
availability (and/or accessibility). We can also assume that increasing the lifetime of a
patch is akin to managing environmental disturbance either through management of
the habitat or buffering of adverse environmental impacts. Using these assumptions,
we can identify the following actions as being beneficial where information is limited:
Increasing the amount and quality of linear habitats
This action will improve connectivity, whilst simultaneously increasing the
quality and area of the linear habitat (Bennett, 2003; Bailey, 2007; Hinsley &
Bellamy 2000). Additionally, certain linear habitats have the potential to also
reduce environmental disturbance (e.g. riparian vegetation reducing diffuse
pollution inputs into rivers).
Improvement of the general heterogeneity (softening) of the landscape matrix
This action will act to increase resource availability within the general
environment through an increase in the proportion of non-crop habitats within the
landscape and has the potential to improve connectivity (Bailey, 2007; Donald &
Evans, 2006; Eycott et al., 2010, 2012; Hodgson et al., 2009). However, it is
likely to be more important in farmed landscapes than in predominantly natural or
semi-natural landscapes (i.e. where the matrix is considered to be hostile to the
majority of species).
Restoration of degraded sites or returning site to good condition
This action will act to increase the quality of a site by increasing resource
availability, but also has the potential to improve connectivity if restored sites are
close to existing sites (Latore et al., 1999; Van Teeffelen, 2012).
Management of environmental disturbance to sites
Managing environmental disturbance to a site through buffering or altering the
management regime has the potential to improve the site’s quality, and increase
the lifetime of the site, which is important where disturbance is frequent or
intense. (DeWoody et al, 2005; Gyllenberg et al, 2004; Keymer et al., 2000; Van
Teeffelen et al., 2012; Vuilleumier et al., 2007).
Creation of new sites or habitat
This management option has the potential to improve connectivity if the habitat is
created close to existing sites, and is particularly important for sites that are
ephemeral or subject to disturbance (DeWoody et al, 2005; Gyllenberg et al,
2004; Keymer et al., 2000; Van Teeffelen et al., 2012; Vuilleumier et al., 2007).
It will also contribute to the enlargement of patches if done close to existing sites
and potential to aid the softening of the matrix where creation is in small pockets
widely distributed across the landscape.
It is difficult to provide a prioritisation of these actions as the most appropriate
choices will be circumstance-dependent and linked to the availability of knowledge on
the factors influencing site condition or quality, the spatial structure of sites, the level
of disturbance experienced by sites and the costs of providing the appropriate
management actions. Where knowledge regarding habitat quality and species
requirements is lacking, then the first two actions can be prioritised. Being focussed
on connectivity, these actions will provide generic benefits in any situation, as
increasing connectivity is always beneficial to metapopulations (Artzy-Randup &
stone, 2010; Cabeza & Moilanen, 2001; Cabeza et al, 2004; Dalang & Hesperberger,
2012; Etienne & Hesterbeek, 2001; Etienne, 2004; Hanski, 1994; Hokit & Branch,
2003; Latore et al., 1999; Moilanen et al., 2005; Moilanen & Wintle, 2006; Van
Teeffelen et al., 2012; Wu et al., 1993), although they may not necessarily be the
optimal choice of action.
However, where a particular habitat is being focussed upon, or there is some
knowledge regarding habitat quality and species requirements (a set of key or focal
species), we can use the resource and patch network concepts to suggest that actions
dealing with patch area and quality are akin to modifying the resource network. From
this we can therefore suggest that in cases where resources are limited due to poor
quality habitat in the sites forming the network, or poor quality habitat is available in
close proximity to existing sites within the resource network, then restoring these
habitats to good quality should be the priority. Where the quality of habitats is
degraded due to pollution or external disturbance, then buffering of these effects is the
priority. However, for ephemeral habitats or where there is a temporally rapid
turnover of sites (i.e. within the generation time of key species), then reducing the
longevity of the patches through appropriate management or buffering of adverse
environmental disturbance is preferred, followed by the creation of new habitat in
close proximity to existing sites.
If sufficient resources exist, but the species use of resources is limited by its ability to
move between the resources (i.e. the resource network is not connected), then the
priority will be to increase the connectivity between sites in the resource network.
Where species have a small home range or foraging distance then creating physical
corridors or stepping stones to aid movement is likely to be most beneficial. However,
if the cost of creating corridors is prohibitive, then enhancing natural linear features as
corridors would be a good alternative. Both of these options should be preferred over
softening the matrix through increasing the proportion of non-crop habitat, which is
primarily applicable to intensively farmed landscapes and not those landscapes which
are dominated by natural or semi-natural habitat.
Where the resource network is functioning appropriately and supporting populations
and the limitation is in the exchange of individuals between patches (resource
networks), then the priority is to use those actions associated with connectivity. The
restoration of sites or creation of new sites to act as corridors or stepping stones will
be a priority where suitable locations can be identified and there are no other
constraints to their development (although due to the larger distances involved in
dispersal between patches, the cost may be prohibitive (Catchpole, 2007). The
alternative to providing corridors and stepping stones will be to enhance linear
features to act as natural corridors between patches. As with accessibility to resources,
softening the matrix is the lowest priority action due to the high degree of uncertainty
about the impacts this will have (Hodgson et al., 2009, Kool et al., 2013).
If sufficient information about species resource requirements, habitat associations,
foraging and dispersal movements is available (i.e. the autecology of the species is
known in some detail), then tools can be used to provide detailed spatial planning and
identification of priority areas and the key functions that need to be provided by ES
options. A number of tools currently exist for spatial decision support/planning, and a
number of these were reviewed in Defra project WC0794 (Jones, 2012), although
these were primarily concerned with mutli-criteria decision making and providing
information on biodiversity and ecosystem services rather than planning ecological
networks. Within Jones(2012), although there were a number of models to determine
reserved design (Cabeza & Moilanen, 2001; Cabeza et al, 2004; Dalang &
Hesperberger, 2012; Moilanen et al., 2005; Moilanen & Wintle, 2006), these
operated primarily at large spatial scales (>1km2) and are therefore useful in
identifying strategic areas where more detailed planning can take place. Only two
instances of specific tools for detailed planning of ecological networks were
identified, MulTyLink (Brás et al., 2012) and LARCH – Landscape ecological
Analysis and Rules for the Configuration of Habitat (van der Sluis & Pedroli, 2004;
van Rooij et al. 2003). However, there is a significant literature on the use of least-
cost modelling approaches with GIS data for identification and planning of ecological
networks (Briers, 2010; Catchpole, 2006, 2010, 2012; Eycott et al., 2007; Kool et al.,
2013; Zetterberg, 2009). A brief summary of these modelling approaches and their
benefits and drawbacks is given below.
MulTyLink aims to identify cost-effective linkages between habitats with benefits for
multiple species. It uses geographical input data, information on species occurrence,
data on the costs to the species of movement through different habitats and
information on habitats that act as barriers to species movement combined with a
distance threshold to identify linkages between habitats using graph theory. The costs
are used to identify the minimum cost linkage. Two heuristics are used to identify this
linkage, one identifies the optimal solution for each individual species and then
combining the solutions and removing linkages to identify the minimal cost solution
and the second iteratively links randomly selected habitat patches and once all patches
are linked removes linkages to identify the minimal cost solution. Both these
heuristics have no guarantee of being optimal and for large areas the algorithms can
take a long time to reach a solution, if they are not limited by computer memory. As
the input to the software is in the form of a text file, a large amount of data pre-
processing is required to convert geographic information into the appropriate format
required for input, and this may not be easily automated due to the formatting used for
the text file. Also, the estimation of movement costs is often difficult and relies on
expert opinion (Baguette & Van Dyck, 2007; Kool et al., 2013). Although the
software is freely available from http://pascal.iseg.utl.pt/~rbras/MulTyLink/, it comes
with limited documentation. It has the advantage of allowing the identification of
solutions of benefit to multiple species, but the drawback is that it only identifies one
solution, which is not necessarily optimal. As the calculations are based on a grid of
cells, the usefulness of the tool will depend on the resolution of the data provided to
the tool.
LARCH is designed to provide information on the metapopulation structure and
population persistence in relation to habitat distribution and can also be used to
identify appropriate potential habitat management for a single species. It is
underpinned by the concepts of key patches (Verboom et al, 2001) and ecologically
scaled landscape indices (Vos et al., 2001) and uses habitat data in the form of a land
use map or vegetation map and species ecological parameters (home range, dispersal
distance, carrying capacity for all habitat types) as input. The parameters used in
LARCH are based on literature and empirical data and these parameters, along with
set standards used in LARCH, have been rigorously tested (over 12 years) using the
METAPHOR model (Vos et al., 2001) which describes the dynamics of a
metapopulation in discrete time. The system does not require actual species
abundance as it assesses the potential for an ecological network of a species. The
LARCH system has been used for a wide range of species (198 species in 47 studies
throughout Europe, according to the LARCH species list spreadsheet from 2002
(http://webdocs.alterra.wur.nl/internet/Landschap/modellarch/soortenlijst.xls)). The
LARCH system has been used in the UK to design the Cheshire ecological network
(van Rooij et al., 2003) and its ability to provide detailed spatial planning accounting
for the key ecological information about a species makes it the most appropriate tool
currently. However, it has two main drawbacks, the first is that it is not publically
available and the second is that it is unable to cope with multiple species, although
this could be done post LARCH modelling through GIS analysis across layers for
multiple species.
The least-cost modelling approach has been used in the UK to identify potential
ecological networks for a number of habitats and key species (Briers, 2010;
Catchpole, 2006, 2010, 2012; Eycott et al., 2007). The approach is based on the idea
of functional connectivity, i.e. that movement through a habitat incurs a cost
(Baguette & Van Dyck, 2007; Catchpole, 2007; Eycott et al., 2007; Kool et al., 2013)
and hence different habitats offer different resistances to movement. Based on this,
simple GIS tools are used to map least cost pathways through the landscape, such that
connections between sites or patches can be identified. This is in effect using a
weighted distance approach to identify connected sites or patches, where the
weighting is the measure of ease with which a species will move through a landscape.
The advantages of this approach are that it is easy to use and works with existing GIS
software, uses ecological concepts to identify networks (allowing identification of
both resource networks and patch networks), and is able to operate at a range of
spatial scales. The main drawbacks are that there is extremely limited information on
the costs of movement for different species, and these are often determine solely
based on expert opinion (Baguette & Van Dyck, 2007; Kool et al., 2013) and that it is
currently only being used in a single species context. However, as the approach
produces a GIS layer for each species, it would be relatively simple to derive
methodology to combine ecological network layers from multiple species to identify
priority areas that would benefit multiple species as a means of targetting ecological
network development actions. Indeed, this approach has been used to identify
ecological networks for woodlands in the UK (Briers, 2010; Eycott et al, 2007) and
ecological networks for broad habitats, with prioritisation of key areas for different
management actions (e.g creation of habitat and restoration of habitat) (Catchpole,
2006, 2007, 2010). However, Briers (2010) cautioned that the least cost modelling
approach lacks the ability to show estimates of uncertainty and therefore only rates a
medium level of confidence if used for prioritisation of management actions. He
concluded that the best use for this approach was in assessing the effect of land-use
changes on habitat networks. Whilst these conclusions are correct for the current
usage of least cost modelling approaches, with the inclusion of more ecological detail,
it is almost certainly possible to improve the approach to allow it to be used to
identify priority areas for targetting of management actions for both single and
multiple species.
Jones (2012) identified Polyscape (Jackson et al., 2013) as one of the multi-objective
systems for assessing ecosystem services. Polyscape has been designed as a GIS
toolbox, and is compatible with existing GIS software and utilises existing land cover
and elevation data. Jackson et al. (2013) highlight that the Polyscape tool includes a
least cost modelling approach for calculation of habitat connectivity. Therefore this
tool includes all the benefits of least-cost modelling, with the associated limitations.
In addition, the Polyscape tool also includes algorithms to calculate flood mitigation,
sediment delivery, carbon sequestration and agricultural productivity and a method for
evaluating trade-offs between these different aspects of landscape planning. Polyscape
therefore represents a powerful tool for planning ecological networks in the context of
multiple environmental objectives, and assessing the impacts of different scenarios.
The drawbacks are that it will require GIS skills to use and it is not currently publicly
available, although Jackson et al. (2013) state that information on its availability will
be available soon on www.polyscape.org.
Summary and Conclusions
This review has synthesised the current knowledge regarding metapopulation theory
and connectivity, with respect to ecological networks. A set of key management
actions and rules of thumb regarding the prioritisation of these actions to enhance
ecological networks have been developed. The review has also tried to provide some
linkage between the theoretical and practical thinking regarding ecological networks
by using the conceptual framework of Zetterberg (2009), to consider sites of a single
habitat as the base unit of management, and that a network of sites providing
sufficient resources to support a population (one or more reproductive units) forms a
patch. This allows the consideration of management to affect connectivity at the level
of daily/seasonal foraging and home ranges within the resource network and also the
dispersal movement between patches that occurs on a longer (annual) timescale.
The synthesis present in this review will form the basis for the assessment of ES
options in terms of providing the key management actions identified in this review
and also their ecological benefits to different species. This assessment will then be
used in conjunction with the prioritisation of the management actions identified in this
review to develop a set of guidelines for the use of ES options to support ecological
network development, accounting for the ecology of species of interest.
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