Species Distribution Modeling of Costa Rica’s National Bird Under Four Climate Futures

Turdus grayi, the clay-colored thrush and the national bird of Costa Rica, is the most frequent species in the country’s eBird database, with more than 345,599 occurrence records. A robust Species Distribution Model (SDM) was built using this dataset to evaluate Turdus grayi’s present and future habitat suitability under climate change. Four algorithms for modeling: MaxEnt, Generalized Linear Models (GLM), Random Forest (RF), and XGBoost were used to make the prediction of species distributions, with MaxEnt giving the highest AUC of 0.84. The most influential environmental variables shaping the distribution of Turdus grayi were bio-7 (Annual Temperature Range) and bio-11 (Mean Temperature of Coldest Quarter). Future projections were made under four Shared Socioeconomic Pathways (SSPs) representing increasing levels of greenhouse gas emissions and climate change. Maps of environmental novelty were also prepared based on Multivariate Environmental Similarity Surfaces (MESS) to locate areas of extensive climatic change. Under all SSPs, the models indicate a gradual withdrawal and latitudinal shift in suitable habitats, with severe losses under high-emission futures (SSP 585). The results are important for long-term conservation planning and highlight the need for climate mitigation to preserve Costa Rica's avian biodiversity

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Publication Details

Journal
George Mason University
Published
2025-09-15
DOI
https://doi.org/10.13021/jssr2025.5265
Primary Topic
Prenatal Screening and Diagnostics
Type
article
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article

Species Distribution Modeling of Costa Rica’s National Bird Under Four Climate Futures

George Mason University
Prenatal Screening and Diagnostics
article

Species Distribution Modeling of Costa Rica’s National Bird Under Four Climate Futures

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Abstract

Turdus grayi, the clay-colored thrush and the national bird of Costa Rica, is the most frequent species in the country’s eBird database, with more than 345,599 occurrence records. A robust Species Distribution Model (SDM) was built using this dataset to evaluate Turdus grayi’s present and future habitat suitability under climate change. Four algorithms for modeling: MaxEnt, Generalized Linear Models (GLM), Random Forest (RF), and XGBoost were used to make the prediction of species distributions, with MaxEnt giving the highest AUC of 0.84. The most influential environmental variables shaping the distribution of Turdus grayi were bio-7 (Annual Temperature Range) and bio-11 (Mean Temperature of Coldest Quarter). Future projections were made under four Shared Socioeconomic Pathways (SSPs) representing increasing levels of greenhouse gas emissions and climate change. Maps of environmental novelty were also prepared based on Multivariate Environmental Similarity Surfaces (MESS) to locate areas of extensive climatic change. Under all SSPs, the models indicate a gradual withdrawal and latitudinal shift in suitable habitats, with severe losses under high-emission futures (SSP 585). The results are important for long-term conservation planning and highlight the need for climate mitigation to preserve Costa Rica's avian biodiversity

George Mason University
George Mason University (US)
Climate action
Openalex Percentile: Top 27%
Prenatal Screening and Diagnostics
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