Heini Kujala Metapopulation Research Group University of Helsinki, Finland Introduction to ZONATION...
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Transcript of Heini Kujala Metapopulation Research Group University of Helsinki, Finland Introduction to ZONATION...
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