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Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients

Species distribution models (SDM) link species occurrence with a suite of environmental predictors and provide an estimate of habitat quality when the variable set captures the biological requirements of the species. SDMs are inherently more complex when they include components of a species’ ecology...

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Autores principales: Beerens, James M., Noonburg, Erik G., Gawlik, Dale E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4480858/
https://www.ncbi.nlm.nih.gov/pubmed/26107386
http://dx.doi.org/10.1371/journal.pone.0128182
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author Beerens, James M.
Noonburg, Erik G.
Gawlik, Dale E.
author_facet Beerens, James M.
Noonburg, Erik G.
Gawlik, Dale E.
author_sort Beerens, James M.
collection PubMed
description Species distribution models (SDM) link species occurrence with a suite of environmental predictors and provide an estimate of habitat quality when the variable set captures the biological requirements of the species. SDMs are inherently more complex when they include components of a species’ ecology such as conspecific attraction and behavioral flexibility to exploit resources that vary across time and space. Wading birds are highly mobile, demonstrate flexible habitat selection, and respond quickly to changes in habitat quality; thus serving as important indicator species for wetland systems. We developed a spatio-temporal, multi-SDM framework using Great Egret (Ardea alba), White Ibis (Eudocimus albus), and Wood Stork (Mycteria Americana) distributions over a decadal gradient of environmental conditions to predict species-specific abundance across space and locations used on the landscape over time. In models of temporal dynamics, species demonstrated conditional preferences for resources based on resource levels linked to differing temporal scales. Wading bird abundance was highest when prey production from optimal periods of inundation was concentrated in shallow depths. Similar responses were observed in models predicting locations used over time, accounting for spatial autocorrelation. Species clustered in response to differing habitat conditions, indicating that social attraction can co-vary with foraging strategy, water-level changes, and habitat quality. This modeling framework can be applied to evaluate the multi-annual resource pulses occurring in real-time, climate change scenarios, or restorative hydrological regimes by tracking changing seasonal and annual distribution and abundance of high quality foraging patches.
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spelling pubmed-44808582015-06-29 Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients Beerens, James M. Noonburg, Erik G. Gawlik, Dale E. PLoS One Research Article Species distribution models (SDM) link species occurrence with a suite of environmental predictors and provide an estimate of habitat quality when the variable set captures the biological requirements of the species. SDMs are inherently more complex when they include components of a species’ ecology such as conspecific attraction and behavioral flexibility to exploit resources that vary across time and space. Wading birds are highly mobile, demonstrate flexible habitat selection, and respond quickly to changes in habitat quality; thus serving as important indicator species for wetland systems. We developed a spatio-temporal, multi-SDM framework using Great Egret (Ardea alba), White Ibis (Eudocimus albus), and Wood Stork (Mycteria Americana) distributions over a decadal gradient of environmental conditions to predict species-specific abundance across space and locations used on the landscape over time. In models of temporal dynamics, species demonstrated conditional preferences for resources based on resource levels linked to differing temporal scales. Wading bird abundance was highest when prey production from optimal periods of inundation was concentrated in shallow depths. Similar responses were observed in models predicting locations used over time, accounting for spatial autocorrelation. Species clustered in response to differing habitat conditions, indicating that social attraction can co-vary with foraging strategy, water-level changes, and habitat quality. This modeling framework can be applied to evaluate the multi-annual resource pulses occurring in real-time, climate change scenarios, or restorative hydrological regimes by tracking changing seasonal and annual distribution and abundance of high quality foraging patches. Public Library of Science 2015-06-24 /pmc/articles/PMC4480858/ /pubmed/26107386 http://dx.doi.org/10.1371/journal.pone.0128182 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
spellingShingle Research Article
Beerens, James M.
Noonburg, Erik G.
Gawlik, Dale E.
Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients
title Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients
title_full Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients
title_fullStr Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients
title_full_unstemmed Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients
title_short Linking Dynamic Habitat Selection with Wading Bird Foraging Distributions across Resource Gradients
title_sort linking dynamic habitat selection with wading bird foraging distributions across resource gradients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4480858/
https://www.ncbi.nlm.nih.gov/pubmed/26107386
http://dx.doi.org/10.1371/journal.pone.0128182
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