The potential for species distribution models to distinguish source populations from sinks

While species distribution models (SDM) are frequently used to predict species occurrences to help inform conservation management, there is limited evidence evaluating whether habitat suitability can reliably predict intrinsic growth rates or distinguish source populations from sinks. Filling this k...

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Veröffentlicht in:The Journal of animal ecology 2024-12, Vol.93 (12), p.1924-1934
Hauptverfasser: Şen, Bilgecan, Che‐Castaldo, Christian, Akçakaya, H. Reşit
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container_end_page 1934
container_issue 12
container_start_page 1924
container_title The Journal of animal ecology
container_volume 93
creator Şen, Bilgecan
Che‐Castaldo, Christian
Akçakaya, H. Reşit
description While species distribution models (SDM) are frequently used to predict species occurrences to help inform conservation management, there is limited evidence evaluating whether habitat suitability can reliably predict intrinsic growth rates or distinguish source populations from sinks. Filling this knowledge gap is critical for conservation science, as applications of SDMs for management purposes ultimately depend on these typically unobserved population or metapopulation dynamics. Using linear regression, we associated previously published population level estimates of intrinsic growth and abundance derived from a Bayesian analysis of mark‐recapture data for 17 bird species found in the contiguous United States with SDM habitat suitability estimates fitted here to opportunistic data for these same species. We then used the area under the ROC curve (AUC) to measure how well SDMs can distinguish populations categorized as sources and sinks. We built SDMs using two different approaches, boosted regression trees (BRT) and generalized linear models (GLM), and compared their source/sink predictive performance. Each SDM was built with presence points obtained from eBird (a web‐available database) and 10 environmental variables previously selected to model intrinsic growth rates and abundance for these species. We show that SDMs built with opportunistic data are poor predictors of species demography in general; both BRT and GLM explained very little spatial variation of intrinsic growth rate and population abundance (median R2 across 17 species was close to 0.1 for both SDM methods). SDMs, however, estimated higher suitability for source populations as compared to sinks. Out of 13 species which had both source and sink populations, both BRT and GLM had AUC values greater than 0.7 for 7 species when discriminating between sources and sinks. Habitat suitability have the potential to be a useful measure to indicate a population's ability to sustain itself as a source population; however more research on a diverse set of taxa is essential to fully explore this potential. This interpretation of habitat suitability can be particularly useful for conservation practice, and identification of explicit cases of when and how SDMs fail to match population demography can be informative for advancing ecological theory. We demonstrate the potential of species distributions models to distinguish source/sink dynamics of animal populations.
doi_str_mv 10.1111/1365-2656.14201
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subjects Abundance
Animal Distribution
Animals
Bayes Theorem
Bayesian analysis
Birds - physiology
Conservation
Conservation of Natural Resources
Conservation practices
Demographic variables
Demography
Ecosystem
Estimates
Generalized linear models
Geographical distribution
Growth rate
habitat suitability
Habitats
intrinsic growth rate
Linear Models
Mathematical models
Metapopulations
Models, Biological
Population
population abundance
population demography
Population Dynamics
Populations
Regression analysis
Sinkholes
source‐sink dynamics
Spatial data
Spatial variations
Species
species distribution models
Statistical models
United States
title The potential for species distribution models to distinguish source populations from sinks
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