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<p>Temporal dynamics of ecological processes are complex, and their influence on species-habitat relationships and abundance operates on various spatial and temporal scales. Researchers often use spatiotemporal point process models to model species-habitat relationships and estimate abundance across different spatial and temporal scales; however, their robustness to changing temporal scales is rarely studied. To gain an understanding of species’ relationship to their habitat and abundance over time, it is essential to examine the temporal dynamics of ecological processes across the entirety of spatiotemporal scales. Therefore, investigating how changes in the temporal support impact the robustness of these models is critical to ensure accurate insights into species distribution. In our study, we assess the robustness of spatiotemporal point process models to changing temporal scales using two distinct data sources: distance sampling and capture-recapture data. We integrate these data sources using a data fusion approach, enhancing our ability to analyze species distributions within complex spatiotemporal contexts, effectively overcoming inherent limitations in each data source. To evaluate the performance of our modeling framework and assess the impact of the temporal support on the models’ robustness, we conduct a simulation experiment involving four scenarios where species interact with spatiotemporal covariates on continuous, daily, weekly, and monthly time scales. We illustrate the influence of temporal support to model species-habitat relationships and abundance using data on Grasshopper Sparrows (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13253_2025_684_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="192" /> </InlineMediaObject> <EquationSource Format="TEX">\(\textit{Ammodramus savannarum}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="italic">Ammodramus savannarum</mi> </mrow> </math></EquationSource> </InlineEquation>) in northeastern Kansas, USA.</p>

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Robustness of Point Process Species Distribution Models to Misspecified Temporal Support

  • 期刊论文

  • 发表日期：

    2025年3月18日

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  • Narmadha M. Mohankumar,
  • Trevor J. Hefley,
  • W. Alice Boyle

摘要

Temporal dynamics of ecological processes are complex, and their influence on species-habitat relationships and abundance operates on various spatial and temporal scales. Researchers often use spatiotemporal point process models to model species-habitat relationships and estimate abundance across different spatial and temporal scales; however, their robustness to changing temporal scales is rarely studied. To gain an understanding of species’ relationship to their habitat and abundance over time, it is essential to examine the temporal dynamics of ecological processes across the entirety of spatiotemporal scales. Therefore, investigating how changes in the temporal support impact the robustness of these models is critical to ensure accurate insights into species distribution. In our study, we assess the robustness of spatiotemporal point process models to changing temporal scales using two distinct data sources: distance sampling and capture-recapture data. We integrate these data sources using a data fusion approach, enhancing our ability to analyze species distributions within complex spatiotemporal contexts, effectively overcoming inherent limitations in each data source. To evaluate the performance of our modeling framework and assess the impact of the temporal support on the models’ robustness, we conduct a simulation experiment involving four scenarios where species interact with spatiotemporal covariates on continuous, daily, weekly, and monthly time scales. We illustrate the influence of temporal support to model species-habitat relationships and abundance using data on Grasshopper Sparrows ( \(\textit{Ammodramus savannarum}\) Ammodramus savannarum ) in northeastern Kansas, USA.