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Impact of an Updated Climate Database on Model Performance and Niche Variability in Species Distribution Modeling.

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Title: Impact of an Updated Climate Database on Model Performance and Niche Variability in Species Distribution Modeling.
Authors: Song, Jae‐Woo1 (AUTHOR), Yoon, Sunhee2 (AUTHOR), Jung, Sunghoon3 (AUTHOR), Lee, Wang‐Hee1,2 (AUTHOR) wanghee@cnu.ac.kr
Source: Ecology & Evolution (20457758). Jun2026, Vol. 16 Issue 6, p1-14. 14p.
Subject Terms: *Species distribution, *Climate change, *Ecological niche, Biological databases, Model validation, Maximum entropy method
Abstract: Despite the continuous accrual of occurrence data, the climate datasets used in species distribution modeling (SDM), particularly in mechanistic frameworks such as CLIMEX, often remain based on outdated climate baselines. Here, we present an updated global climate database (1992–2021) and corresponding bioclimatic variables, specifically structured for CLIMEX compatibility while also supporting application across multiple SDM frameworks. By providing a temporally updated climate baseline and enhancing cross‐framework usability, this resource addresses a key barrier to the integration of contemporary climate data into applied ecological modeling. To evaluate its utility, we developed CLIMEX and MaxEnt models for three species and compared model performance, predicted distributions, and niche similarity between the traditional 1961–1990 baseline and the updated 1992–2021 climate data. While overall model performance and broad niche overlaps remained similar between the two periods, localized habitat suitability and occurrence probabilities exhibited noteworthy variability. These results highlight the importance of temporally synchronized climate and occurrence data for reducing predictive uncertainty and accurately assessing climate impacts on species distributions. We provide the updated climate database and associated processing workflows through an open‐access repository. By facilitating the use of contemporary climate data across both mechanistic and correlative SDM approaches, this resource supports reliable pest risk analyses, targeted surveillance, and evidence‐based biosecurity decision‐making under current environmental conditions. [ABSTRACT FROM AUTHOR]
Copyright of Ecology & Evolution (20457758) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: GreenFILE
An: 194870785
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
  Group: Ti
  Data: Impact of an Updated Climate Database on Model Performance and Niche Variability in Species Distribution Modeling.
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  Data: <searchLink fieldCode="AR" term="%22Song%2C+Jae‐Woo%22">Song, Jae‐Woo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yoon%2C+Sunhee%22">Yoon, Sunhee</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jung%2C+Sunghoon%22">Jung, Sunghoon</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Wang‐Hee%22">Lee, Wang‐Hee</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> wanghee@cnu.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Ecology+%26+Evolution+%2820457758%29%22">Ecology & Evolution (20457758)</searchLink>. Jun2026, Vol. 16 Issue 6, p1-14. 14p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Species+distribution%22">Species distribution</searchLink><br />*<searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br />*<searchLink fieldCode="DE" term="%22Ecological+niche%22">Ecological niche</searchLink><br /><searchLink fieldCode="DE" term="%22Biological+databases%22">Biological databases</searchLink><br /><searchLink fieldCode="DE" term="%22Model+validation%22">Model validation</searchLink><br /><searchLink fieldCode="DE" term="%22Maximum+entropy+method%22">Maximum entropy method</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Despite the continuous accrual of occurrence data, the climate datasets used in species distribution modeling (SDM), particularly in mechanistic frameworks such as CLIMEX, often remain based on outdated climate baselines. Here, we present an updated global climate database (1992–2021) and corresponding bioclimatic variables, specifically structured for CLIMEX compatibility while also supporting application across multiple SDM frameworks. By providing a temporally updated climate baseline and enhancing cross‐framework usability, this resource addresses a key barrier to the integration of contemporary climate data into applied ecological modeling. To evaluate its utility, we developed CLIMEX and MaxEnt models for three species and compared model performance, predicted distributions, and niche similarity between the traditional 1961–1990 baseline and the updated 1992–2021 climate data. While overall model performance and broad niche overlaps remained similar between the two periods, localized habitat suitability and occurrence probabilities exhibited noteworthy variability. These results highlight the importance of temporally synchronized climate and occurrence data for reducing predictive uncertainty and accurately assessing climate impacts on species distributions. We provide the updated climate database and associated processing workflows through an open‐access repository. By facilitating the use of contemporary climate data across both mechanistic and correlative SDM approaches, this resource supports reliable pest risk analyses, targeted surveillance, and evidence‐based biosecurity decision‐making under current environmental conditions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Ecology & Evolution (20457758) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=8gh&AN=194870785
RecordInfo BibRecord:
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        Value: 10.1002/ece3.73891
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      – Code: eng
        Text: English
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        PageCount: 14
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      – SubjectFull: Species distribution
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Ecological niche
        Type: general
      – SubjectFull: Biological databases
        Type: general
      – SubjectFull: Model validation
        Type: general
      – SubjectFull: Maximum entropy method
        Type: general
    Titles:
      – TitleFull: Impact of an Updated Climate Database on Model Performance and Niche Variability in Species Distribution Modeling.
        Type: main
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            NameFull: Song, Jae‐Woo
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            NameFull: Yoon, Sunhee
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            NameFull: Jung, Sunghoon
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            NameFull: Lee, Wang‐Hee
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            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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