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Ecotrends: an R package for estimating habitat suitability trends over time

Author

Listed:
  • Sillero, Neftalí
  • Alírio, João
  • Garcia, Nuno
  • Freitas, Inês
  • Campos, João C.
  • Duarte, Lia Bárbara
  • Pôças, Isabel
  • Teodoro, Ana Cláudia
  • Arenas-Castro, Salvador
  • Barbosa, A.Márcia

Abstract

ecotrends is an R package that provides a comprehensive framework for assessing species vulnerability by analysing temporal trends in habitat suitability. The framework consists of calculating ecological niche models successively on the same species occurrence data over time, using a time series of environmental variables, for any period and periodicity. Then, a trend analysis of habitat suitability is performed with Sen's slope, based on non-parametric Kendall's rank correlation. ecotrends includes functions for automatically gathering a yearly time series of environmental data from TerraClimate, calculating and evaluating Maxent models, assessing temporal trends in habitat suitability, and estimating variable importance. Although the built-in functions facilitate the use of a specific environmental database and modelling method, ecotrends works as well with any variables and models the user may provide. This adaptable framework can be applied to any taxon or guild, study area, spatial scale, or temporal resolution, as long as the required data are available. ecotrends offers a valuable tool for estimating species vulnerability over time and for supporting the evaluation of conservation measures. ecotrends allows the analysis of habitat suitability trends over time, requiring only species occurrence data and a time series of environmental data.

Suggested Citation

  • Sillero, Neftalí & Alírio, João & Garcia, Nuno & Freitas, Inês & Campos, João C. & Duarte, Lia Bárbara & Pôças, Isabel & Teodoro, Ana Cláudia & Arenas-Castro, Salvador & Barbosa, A.Márcia, 2026. "Ecotrends: an R package for estimating habitat suitability trends over time," Ecological Modelling, Elsevier, vol. 513(C).
    • Handle: RePEc:eee:ecomod:v:513:y:2026:i:c:s0304380025004120
    DOI: 10.1016/j.ecolmodel.2025.111426
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    References listed on IDEAS

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    1. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    2. Uilson Ricardo Venâncio Aires & Demetrius David Silva & Michel Castro Moreira & Carlos Antônio Alvares Soares Ribeiro & Celso Bandeira de Melo Ribeiro, 2020. "The Use of the Normalized Difference Vegetation Index to Analyze the Influence of Vegetation Cover Changes on the Streamflow in the Manhuaçu River Basin, Brazil," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 1933-1949, April.
    3. Sillero, Neftalí & Campos, João Carlos & Arenas-Castro, Salvador & Barbosa, A.Márcia, 2023. "A curated list of R packages for ecological niche modelling," Ecological Modelling, Elsevier, vol. 476(C).
    4. José-Silva, Leandro & dos Santos, Reginaldo Carvalho & de Lima, Bruna Martins & Lima, Mendelson & de Oliveira-Júnior, José Francisco & Teodoro, Paulo Eduardo & Eisenlohr, Pedro V. & da Silva Junior, C, 2018. "Improving the validation of ecological niche models with remote sensing analysis," Ecological Modelling, Elsevier, vol. 380(C), pages 22-30.
    5. Sillero, Neftalí, 2011. "What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods," Ecological Modelling, Elsevier, vol. 222(8), pages 1343-1346.
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