Elucidating The Mechanisms Behind Successful Indicators of Biodiversity Joshua Lawler National Research Council / U.S. Environmental Protection Agency.

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Presentation transcript:

Elucidating The Mechanisms Behind Successful Indicators of Biodiversity Joshua Lawler National Research Council / U.S. Environmental Protection Agency Denis White U.S. Environmental Protection Agency Lawrence Master NatureServe, Boston, Massachusetts USA

Overview 1.What surrogates are and why we use them 2.A comparison of surrogate group performance in two regions 3.An investigation of four potential explanations of surrogate group performance

Selecting Areas to Protect Biodiversity Maximize the representation of biodiversity Provide for viable populations and functioning ecosystems

Surrogates of Biodiversity Lack of data requires shortcuts …successful shortcuts

Surrogates of Biodiversity Indicators Focal species Umbrellas Keystones

Testing Surrogates Correlations Hotspot Overlap Complementarity Amphibian species richness Bird species richness

Why do results differ? Types of tests are often different Different surrogate groups are tested Studies are conducted at different scales Location

How do surrogates work?

Study regions

Data: sampling grid ~650 km 2

Species Occurrence Data Compiled by The Nature Conservancy and Natural Heritage Programs.

Site Selection Stochastic optimization: simulated annealing

A Comparison of Surrogate Performance Is there consistency in the performance of surrogate groups across regions ?

East vs. West % Non-surrogate group species covered Surrogate group East West

Conclusions Amphibians, reptiles, and mussels are better surrogates in the east. Mammals, birds, and butterflies are better surrogates in the west. Fish and rare species are the best surrogates in both regions

Why?

How do surrogates work? Or What makes a good surrogate? They represent biodiversity hotspots They are taxonomically diverse They are rare They (as a group) inhabit diverse environments

Analysis of 100 groups of surrogates randomly selected 100 sets of 20 species from a pool of 920 species Selected sets of sites to include all species in each set at least one time compared performance of each group to group attributes including: -hotspot overlap -taxonomic diversity -mean range size -environmental diversity

Performance of randomly selected surrogates % Coverage Frequency

Hotspots % overlap with richness hotspots % Coverage

Taxonomic diversity % Coverage ClassesOrders FamiliesGenera % Coverage

Range size Maximum range diameter (km) % Coverage

Environmental diversity Land-cover dissimilarity % Coverage

Comparison of random surrogates to the best surrogates randomly selected 100 sets of 20 species from the pool of 920 species optimally selected 100 of the “best” groups of surrogates Selected sets of sites to include all species in each set at least one time compared the two groups with respect to: -hotspot overlap -taxonomic diversity -mean range size -environmental diversity

Performance of randomly selected and optimally selected surrogates % Coverage Frequency Random Best

Comparison of randomly selected and optimally selected surrogates AttributeRandomBest Hotspot overlap (%)6.0 (0.8)4.7 (0.7) Taxonomic diversity: classes6.4 (0.7)6.3 (0.7) orders11.0 (1.7)11.6 (1.5) families15.0 (1.8)14.6 (1.9) genera19.0 (1.1) Range diameter (km)539 (68)313 (59) Environmental dissimilarity0.46 (0.05)0.60 (0.03)

The simple answer Number of sites (total area) % Coverage

The simple answer Range size Environmental diversity Number of sites Performance

Controlling for number of sites: Performance % Coverage Frequency Random Best

Controlling for number of sites: Range Sizes Maximum range diameter (km) RandomBest

Conclusions For relatively simple reasons good surrogate groups contain rare species that together occupy diverse environments. Neither taxonomic diversity nor hotspot representation appear to be key attributes of successful surrogates. Further research needs to be done to get to the root of surrogate performance

Acknowledgements Pilar Hernandez, Roly Russell, Anne Guerry, John Van Sickle, National Research Council (NRC), U.S. Environmental Protection Agency (EPA), Betsy Smith and EPA’s Regional Vulnerability Assessment Program (ReVA)