Heini Kujala

Metapopulation Research Group

University of Helsinki, Finland

Introduction to ZONATION v1.0© 2004 – 2007 Atte Moilanen

Zonation

Produces a hierarchical zoning of a landscape by looking for priority sites for conservation aiming at species persistence using large grids

2%

2-5%

5-10%

10-25%

25-50%

50-80%

80-100%

Top fraction of the landscape

2%

2-5%

5-10%

10-25%

25-50%

50-80%

80-100%

Top fraction of the landscape

Zonation Features

Species prioritization (weighting) Costs Species-specific connectivity Uncertainty analysis Replacement cost analysis for current or

proposed conservation areas

Direct link from GIS distribution modeling Zonation

The Zonation meta-algorithm

1. Start from full landscape

2. Determine cell that has least marginal value and remove it

3. Repeat (2) until no cells remain

Cell removal in Zonation

Map of landscape showing the cell removal ranking

Basic output 1

2%

2-5%

5-10%

10-25%

25-50%

50-80%

80-100%

Top fraction of the landscape

2%

2-5%

5-10%

10-25%

25-50%

50-80%

80-100%

Top fraction of the landscape

Best 10% of the landscapeArea needed to achieve 30% of sp distributions

Proportion of cells removed

10% top fraction

Basic output 2

Curves specifying performance of spp or spp groups at different levels of cell removal

Pro

po

rtio

n o

f sp

eci

es

dis

trib

utio

n p

rote

cte

d

Eg.

• Comparison of different solutions

• Connected sets of sites with similar species compositions can be connected into management landscapes

Basic output 3: Post-processing analyses

Zonation Data

Large grids (ASCII files)- Species data: P/A, abundance etc.- Cost layer- Mask layer- Species-specific uncertainty maps

Species-specific connectivity specification

Present Zonation Data limits

4000 grid maps

Max. 16M elements per spp in map

With 4 GB memory:700 spp x 1M element map

Cell removal rule

Cell removal rules

Determine how the value of a cell is calculated

Three alternatives core-area Zonation additive benefit function targeting benefit function

These alternatives have different aims value representations differently

Cell removal rules:

Finnish breeding birds

Number of species< 3030 - 6060 - 9090 - 120> 120

Additive benefit functionCore-area Zonation

Cell Ranking0 - 50 %50 - 75 %75 - 90 %90 - 100 %No Data

Cell removal rules

additive benefit function target-based planning

Species prioritization

Proportion of cells removed

Species weighting

Best 10% of total area

Endemic spp weighted higher

All spp with equal weights

Pro

port

ion

of s

peci

es d

istr

ibut

ion

prot

ecte

d

Proportion of cells removed

Connectivity

Qualitative:

1. Removal from edge

2. Boundary Length Penalty

Species-specific:

3. Distribution smoothing

4. Boundary Quality Penalty

Accounting for connectivity

Accounting for connectivity:

Distribution smoothing

original distribution

smoothed distribution

Accounting for connectivity:

Distribution smoothing

No aggregation

Top 20% (color) is scrappy Top 20% well connected

Using distribution smoothing

Accounting for connectivity:

Boundary Quality Penalty (BQP)

Species-specific decrease in local quality due to proximity of reserve boundary

– Forces connectivity only where needed.– Allows fragmentation where it does not hurt

Small effect of neighboring habitat

loss

large buffer

Accounting for connectivity: Boundary Quality Penalty (BQP)

Strong effect of neighboring habitat loss

focal cell

small buffer

Moilanen and Wintle 2006

7 species of interest

Hierarchical priorities

Hunter Valley, Australia

Accounting for connectivity: Boundary Quality Penalty (BQP)

Distributions

Accounting for connectivity: Boundary Quality Penalty (BQP)

Uncertainty

Uncertainty analysis

important

avoid

negativesurprises

positive surprise

s

cert

ain

ty o

f in

form

ati

on

high

conservation value

high

low

robustnessrequirement

opportunity

low

Uncertainty analysis:

Distribution discounting

Distribution model

Discounted distribution

Error surface

Replacement cost analysis

Replacement cost analysis

Situation where areas need to be included to or excluded from the final solution

– Eg. evaluation of existing and proposed reserves

Replacement cost analysis

Optimal solution Forced solution

Proposed reserves

Replacement cost analysis

1. Calculate biologically optimal solution

2. Force in areas that need to be protected

or force out areas that cannot be protected

3. Reoptimize under constraint and calculate the difference in cost/benefit

Replacement cost analysisP

ropo

rtio

n of

spe

cies

dis

trib

utio

n pr

otec

ted

Proportion of cells removed

COST = loss in biological value

Performance curve forideal solution

Curve forforced solution

Leathwick et al. 2006

Replacement cost analysis:

New Zealand EEZ

Leathwick et al. 2006

Replacement cost analysis:

New Zealand EEZ

• 122 fish species• Data resolution 1 km2

• Cost layer: commercial trawl effort

Cell removal rank0 - 50%50 - 75%75 - 90%90 - 100% (= 10% best)

Leathwick et al. 2006

NetworkCost

loss for fishermen

Benefitspecies protected

Existing reserves 18.1% 29.8%

Proposed by fisheries 0.2% 11.9%

Zonation softwareno costs

19.9% 31.1%

Zonation softwarecost-adjusted

1.6% 28.6%

Replacement cost analysis:

New Zealand EEZ

Leathwick et al. 2006

New features to come

New features to come

Zonation v1.1 Histograms of habitat quality Planning unit layer Species of special interest (SSI) - point

location data Directed (freshwater) connectivity

Zonation

www.helsinki.fi/bioscience/consplan

Zonation program User manual Tutorial

Thank You!

Acknowledgments:

Atte MoilanenMar Cabeza

Evgeniy Meike

John LeathwickBrendan Wintle

Hunter Region Organization of Councils

Moilanen, A., Franco, A.M.A., Early, R., Fox, R., Wintle, B., and C.D. Thomas. 2005. Prioritising multiple-use landscapes for conservation: methods for large multi-species planning problems. Proc. Royal Society of London, Series B, 272: 1885-1891.Moilanen, A. 2005. Reserve selection using nonlinear species distribution models. American Naturalist 165: 695-706.Arponen, A., Heikkinen, R., Thomas, C.D. and A. Moilanen. 2005. The value of biodiversity in reserve selection: representation, species weighting and benefit functions. Conservation Biology 19: 2009-2014.Moilanen, A. and B.A. Wintle. 2006. Uncertainty analysis favours selection of spatially aggregated reserve structures. Biological Conservation, 129: 427-343.Moilanen, A., B.A. Wintle., J. Elith and M. Burgman. 2006a. Uncertainty analysis for regional-scale reserve selection. Conservation Biology, 20: 1688-1697.Moilanen, A., M. Runge, J. Elith, A. Tyre, Y. Carmel, E. Fegraus, B. Wintle, M.Burgman and Y. Ben-Haim. 2006b. Planning for robust reserve networks using uncertainty analysis. Ecological Modeling, 119: 115-124.Cabeza, M. and A. Moilanen. 2006. Replacement cost: a useful measure of site value for conservation planning. Biological Conservation, 132: 336-342.Moilanen, A. and H. Kujala. 2006. Zonation spatial conservation planning framework and software v1.0. User manual. Edita, Helsinki, Finland.Moilanen, A. 2007. Landscape zonation, benefit functions and target-based planning: Unifying reserve selection strategies. Biological Conservation 134: 571-579.Moilanen, A., and B. A. Wintle. 2007. The boundary-quality penalty: a quantitative method for approximating species responses to fragmentation in reserve selection. Conservation Biology, 21:355-364.Moilanen, A., J. Leathwick and J. Elith. 2008. A method for spatial freshwater conservation prioritization. Submitted manuscript.

Relevant references