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Quantifying the benefits of different types of protection for freshwater biodiversity

Eren Turak,Simon Ferrier, Michael Drielsma, Glenn Manion, Tom Barrett, Edwina Mesley Janet Stein,Gavin Doyle and Geoff Gordon

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FPAs and the conservation of freshwater biodiversity

• Will they make a difference? • How much?• How do FPAs compare with other

interventions? • How will they be affected by change?

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Scenario planning: Dealing with uncertainty and uncontrollability

Controllability

Unc

erta

inty Adaptive

management

Scenario planning

Optimal control Hedging

UncontrollableControllable

Low

High

Peterson G.D., Cumming G.S., Carpenter S.R. 2002. Scenario planning: a tool for conservation in an uncertain world. Conservation Biology, Pages 358-366.

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Forecasting the persistence of freshwater biodiversity

• Scenarios: alternative futures• Landscape/ riverscape scale evaluations• Best spatial data and knowledge• Trial in the Hunter region, SE Australia.

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Present Future

Current local disturbance

Statistical model for predicting river biodiversity at any location

Ecological river type maps

Species-area relationships

River type similarity matrices

Biodiversity (river sites)

Cumulative disturbance

Regional evaluation

Scenarios

Future cumulative disturbance

Future biodiversity

Future local disturbance

River type evaluation

Outputs

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0.4 0.6 0.8 1.0

0.2

0.4

0.6

0.8

1.0

Predicted

Obs

erve

d

Regression modelRelating biodiversity measures (AUSRIVAS O/E values) to disturbance*Adjusted r2= 0.745

*Stein, J.L, Stein J.A., Nix, H.A. 2002 Spatial analysis of anthropogenic river disturbance at regional and continental scales: identifying the wild rivers of Australia Landscape and Urban Planning, 60, 1-25.

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Predicted river condition

Current AUSRIVAS O/E values as the proportion of the predicted pristine condition

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LC Name Weight Explanation/Description

1 Recreation/ park 0.30 Relatively high use areas with large proportions of planted grass where fertilizer use is common.

2 Grazing-low TC 0.50 Light or no tree cover (<30%). Nutrient and sediment impacts on streams are likely.

3 High vegetation cover 0.00 High tree cover (> 70%). Optimum catchment condition for aquatic ecosystems.

4 Low vegetation cover 0.40 Light tree cover (< 30%) but little or no grazing. Nutrient and sediment impacts are likely.

5 Medium vegetation cover 0.15 Medium tree cover (30-70%). Short-term target condition for replanting activities.

6 Cropping 0.75 Heavy tillage operations. Significant potential for nutrient, sediment and chemical impacts.

7 Grazing – Irrigated 0.55 Intensive grazing usually associated with dairying (usually nil tree cover).

8 Grazing - Medium TC 0.40 Medium tree cover in grazing areas. Some impacts from stock (30-70% cover).

9 Grazing - Heavy TC 0.25 Heavy tree cover in grazing areas (>70% cover).

10 Horticulture 0.60 Intensive agriculture with likely input of nutrients and chemicals into streams

11 Organic pollution source 1.00 Intensive animal production, abattoirs or sewage ponds with discharges into waterways.

12 Mining 0.90 Significant sediment input and acid, saline discharges in to streams are likely.

13 Industrial 0.90 Intensive land use with multiple disturbances (e.g. hydrological, sediments, contaminants).

14 Waterways 0.00 All water courses. They are not differentiated by condition.

15 Urban - Low Density 0.50 Rural residential areas. Similar to grazing with possible nutrient impacts (septic).

16 Urban - High Density 0.85 High hydrological impacts and nutrient and sediment inputs into streams.

17 Wetlands 0.00 Freshwater and estuarine wetlands and coastal lakes. They are not differentiated by condition.

18 Grazing - Sustainable * 0.25 Best management practice for grazing. Limited nutrient and sediment impacts on the streams.

19 Regrowth 0.15 Regrowth after clearing or native plantations.

20 Exotic plantations 0.25 Softwood and poplar plantations.

Land use classes and weights given to them (aggragated from 172 classes)

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Priority maps

• Landuse, Infrastructure and settlement factors hypothetically changed

• Catchment protection priority– Degraded condition simulated by changing all factors to 1.

• Catchment restoration priority:Improvement in condition was simulated by changing factors as follows

If factor value ≤ 0.2 then it was adjusted to 0.If factor value > 0.2 then 0.1 was subtracted from factor value

• River section conservation priority:– Priority = BDI with river section-BDI without river section/ area

of sub-catchment

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Catchment protection priority

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Catchment restoration priority

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River section conservation priority

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0.9266

0.9268

0.927

0.9272

0.9274

0.9276

0.9278

0.928

0.9282

0.9284

Current Terrrestrial BAU River

BDI

Spatial prioritisation of investment by Catchment Management Authorities:

Alternative scenarios for selecting 25,000 ha of cleared land for revegetationTerrestrial: Based on priority map for terrestrial biodiversity. BAU: Business as usual (based on existing investment patterns). River: Based on priority map for terrestrial biodiversity

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FPA paradigms• Protected area categories (IUCN) unsuitable for

freshwaters. • Place based strategies proposed (Abell. et al

2007)– Freshwater focal areas– Critical management zones– Catchment management zones

• Choice may be dictated by monetary and social cost.

Abell, R., Allan, J. D. & Lehner, B. (2007) Unlocking the potential of protected areas for freshwaters. Biological Conservation, 134, 48-63.

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Biodiversity forecasting and place-based strategies

• Freshwater focal areas – River section conservation priority– Endangered species, communities, ecosystems– HCVAE ‘s based on other criteria

• Critical management zones– Catchment protection and restoration priority

• Catchment management zones– Catchment protection and restoration priority

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Conclusion

• The potential effects on river biodiversity, of every type of management action or disturbance, at any location can be predicted.

• Freshwater Protected Areas should be considered in the context of Integrated catchment management (ICM).