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Assessing spatial and temporal trends over time in potential species richness using satellite time-series and ecological niche models

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Author
García, Nuno
Campos, João C.
Alírio, João
Duarte, Lia B.
Arenas Castro, Salvador
Pôças, Isabel
Teodoro, Ana C.
Sillero, Neftalí
Publisher
Springer
Date
2024
Subject
Biodiversity conservation
GEE
MaxEnt
Potential species richness
Protected areas
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Abstract
Assessing biodiversity in protected areas is essential for effective conservation management. However, conventional methods for estimating species richness can lead to inaccurate assessments of biodiversity in these regions. To address this, we present a complementary approach to assess potential species richness at a 1 km resolution in the special conservation area of Montesinho/Nogueira (SAC-MN; Portugal), based on a spatial and temporal estimates of species richness trends over time (2001–2021). We compiled 10,190 species occurrence records from four taxonomic groups: amphibians, reptiles, birds, and mammals. We created correlative ecological niche models (MaxEnt) with a time series of satellite-remote sensing variables (SRS-ENMs) using Google Earth Engine (GEE). We calculated annual potential species richness (PSR) maps by stacking the SRS-ENMs and identified positive and negative trends with the Mann–Kendall test. Each species’ ecological niche model revealed unique patterns of habitat suitability within SAC-MN over time. The eastern and western boundaries of SAC-MN revealed an increase in PSR, while the central area indicated PSR declines. Each group displayed different trends in PSR: birds and mammals were more similar between them than amphibians and reptiles. This approach provides ecologists and conservationists with valuable tools to evaluate PSR and trends over time, offering crucial insights for decision-makers and stakeholders to support local biodiversity conservation efforts.
URI
http://hdl.handle.net/10396/32532
Fuente
Garcia, N., Campos, J.C., Alírio, J. et al. Assessing spatial and temporal trends over time in potential species richness using satellite time-series and ecological niche models. Biodivers Conserv (2024). https://doi.org/10.1007/s10531-024-02979-7
Versión del Editor
https://doi.org/10.1007/s10531-024-02979-7
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