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

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.

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Publication Details

Journal
Biodiversity and Conservation
Published
2024-11-25
DOI
https://doi.org/10.1007/s10531-024-02979-7
Citations
6
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
5.52

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article

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

Lia Duarte, Nuno Garcia, João C. Campos, Neftalí Sillero et al.
6 citations
Biodiversity and Conservation
Species Distribution and Climate Change
5.52
article

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

Lia Duarte, Nuno Garcia, João C. Campos, Neftalí Sillero, Isabel Pôças, Ana Cláudia Teodoro, Salvador Arenas‐Castro, João Alírio
article en
6 citations

Abstract

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.

Biodiversity and ConservationVol. 34(2)
Universidade do Porto (PT), University of Córdoba (ES)
European Commission, Universidade do Porto, Cohesion Fund, Fundação para a Ciência e a Tecnologia
Life in Land
Openalex Percentile: Top 5%
Species Distribution and Climate Change
5.52
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