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Aquatic Ecology

, Volume 53, Issue 4, pp 595–605 | Cite as

On the environmental background of aquatic organisms for ecological niche modeling: a call for caution

  • Javier Nori
  • Octavio Rojas-SotoEmail author
Article

Abstract

Ecological niche modeling (ENM) is a technique widely used in many disciplines of science. Recently, the extent of using the environmental background for ENM calibration has been pointed out as playing a crucial role in determining model outcomes. However, when modeling freshwater species, the need for a background refinement has been ignored and its consideration possesses important implications not taken into account before. Here, using Maxent algorithm and global occurrence data characterizing the distribution of the invasive freshwater turtle, Trachemys scripta, we performed ENM transfer and compared native and invasive niche estimates for the species in the environmental space. We used two environmental backgrounds: (a) a traditional area, based on the current distribution and dispersal capacity of the species, and (b) a more restricted area, which corresponds exclusively to freshwater bodies. Our analysis revealed strong differences between the traditional and the restricted backgrounds in niche transferability, with differences in Maxent probability values ranging from − 0.59 to 0.41. Also, during comparisons between native and invasive niches, the niches were more similar when the traditional approach was used, compared to the restricted approach. Our results highlight the importance of considering the biological restriction of the species when establishing the extent of the background in ecological niche modeling; in this case, a more restricted area represented by freshwater environments.

Keywords

Freshwater species Maxent background Niche comparisons Niche transferability Rivers 

Notes

Acknowledgements

A.T. Peterson provided useful comments to the MS. This MS also benefitted from discussions with Rosario Landgrave, David Prieto-Torres, Claudio Mota-Vargas, Mauricio Ortega-Andrade, Fabricio Villalobos and Andrés Lira. Special thanks to the Instituto de Ecología, A. C., for providing permission and support for O. Rojas-Soto´s sabbatical year at the Centro de Zoología Aplicada, and logistic support for this research. Javier Nori is a staff researcher at CONICET and Universidad Nacional de Córdoba; his work was funded by FONCYT and SECYT- UNC.

Supplementary material

10452_2019_9711_MOESM1_ESM.pdf (175 kb)
Supplementary material 1 (PDF 175 kb)
10452_2019_9711_MOESM2_ESM.pdf (193 kb)
Pearson correlation among variables (PDF 193 kb)
10452_2019_9711_MOESM3_ESM.pdf (6.7 mb)
Full page size maps of Figure 2, for graphical details (PDF 6852 kb)
10452_2019_9711_MOESM4_ESM.pdf (436 kb)
Multivariate environmental similarity surface (MESS) analysis. This test was used to compare the environmental variables used for projection (Argentina) to those used for training the model (its native range in North America). Negative values (shown in red) indicate novel climate; these represent one or more environmental variables outside the range present in the training data; so predictions in those areas should be treated with strong caution. Positive values (shown in blue) represent points that are not novel at different degrees (e.g., a score of 100 meaning that a point is not at all novel; Elith et al., 2010) (PDF 436 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Instituto de Diversidad y Ecología Animal (IDEA-CONICET) and Centro de Zoología AplicadaUniversidad Nacional de CórdobaCórdobaArgentina
  2. 2.Laboratorio de Bioclimatología, Red de Biología EvolutivaInstituto de Ecología, A.C.XalapaMéxico

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