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We thank the editors of the Grime Reviews for their interest in the proposed paper, and the anonymous reviewers who took some of their time to assess this submission. A.G. received support from the Swiss Federal Office for the Environment (Valpar.CH project) funding A.A. and from the Swiss National Science Foundation (grants 310030L_197777, GEN4MIG project) funding F.C. R.G.M. was supported by project grants Connect2restore (TED2021-129589B-I00, funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR), and NextDive (PID2021-124187NB-I00, funded by MCIN/AEI/10.13039/501100011033 and by ERDF, a way of making Europe).

Analysis of institutional authors

Zarzo-Arias, AlejandraAuthorMateo, Ruben GAuthor

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May 26, 2025
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Spatially nested species distribution models (N-SDM): An effective tool to overcome niche truncation for more robust inference and projections

Publicated to:JOURNAL OF ECOLOGY (): - - 2025-05-16 (), DOI: 10.1111/1365-2745.70063

Authors: Guisan A; Chevalier M; Adde A; Zarzo-Arias A; Goicolea T; Broennimann O; Petitpierre B; Scherrer D; Rey PL; Collart F; Riva F; Steen B; Mateo RG

Affiliations

Eawag Swiss Fed Inst Aquat Sci & Technol, Dept Aquat Ecol, Dubendorf, Switzerland - Author
IFREMER, Ctr Bretagne, DYNECO, Lab Ecol Benth Cotiere LEBCO, Plouzane, France - Author
Info Flora, Swiss Ctr Florist Data, Geneva, Switzerland - Author
Sapienza Univ Rome, Rome, Italy - Author
Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland - Author
Univ Autonoma Madrid, Ctr Invest Biodiversidad & Cambio Global CIBC UAM, Madrid, Spain - Author
Univ Autonoma Madrid, Dept Biol, Madrid, Spain - Author
Univ Lausanne, Dept Ecol & Evolut, Lausanne, Switzerland - Author
Univ Lausanne, Inst Earth Surface Dynam, Lausanne, Switzerland - Author
Univ Lausanne, Interdisciplinary Ctr Mt Res, Lausanne, Switzerland - Author
Univ Liege, Dept Biol Ecol Evolut, Liege, Belgium - Author
Univ Oviedo, Oviedo, Spain - Author
Vrije Univ Amsterdam, Inst Environm Studies, Environm Geog Dept, Amsterdam, Netherlands - Author
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Abstract

Species distribution models (SDMs) relate species observations to mapped environmental variables to estimate the realized niche of species and predict their distribution. SDMs are key tools for projecting the impact of climate change on species and have been used in many biodiversity assessments. However, when fitted within spatial extents that do not encompass the whole species range (i.e. subrange), the estimated realized environmental niche can be truncated, which can lead to wrong or inaccurate predictions. A simple solution to this niche truncation consists in fitting SDMs at a spatial extent that encompasses the whole species range, but this often implies using a spatial resolution too coarse for local conservation assessments. To keep a fine resolution, a solution is to fit spatially nested SDMs (N-SDMs), where a whole range, coarse-grain SDM is combined with a subrange, fine-grain SDM. N-SDMs have demonstrated superior performance to subrange (truncated) SDMs in projecting species distributions under climate change and have accordingly regained considerable interest. Here, we review developments, applications and effectiveness of N-SDMs. We present and discuss existing methods and tools to fit N-SDMs, and assess when N-SDMs are not needed. We highlight strengths and weaknesses of N-SDMs, underline their importance in reducing niche truncation, and identify remaining challenges and future perspectives. Our review highlights that subrange SDMs most often lead to niche truncation and thus to incorrect spatial projections, a problem that can be overcome by using N-SDMs. We show that the various N-SDM methods come with their strengths and weaknesses and should be selected depending on the intended goal of the study. Synthesis. N-SDMs are key tools to develop untruncated regional climate change forecasts of species distributions at fine resolution over restricted extent. While several N-SDM approaches were proposed, there is currently no universal solution suggesting that further developments and testing are crucial if we are to derive robust future projections of species distributions, at least until SDMs can be applied for most species at high resolution over large geographic extents. Les mod & egrave;les de distribution d'esp & egrave;ces (SDM) relient les observations des esp & egrave;ces & agrave; des cartes environnementales afin d'estimer la niche r & eacute;alis & eacute;e de l'esp & egrave;ce et de pr & eacute;dire sa distribution. Les SDMs sont des outils essentiels pour pr & eacute;voir l'impact du changement climatique sur les esp & egrave;ces et ont & eacute;t & eacute; utilis & eacute;s dans de nombreuses & eacute;valuations de la biodiversit & eacute;. Cependant, lorsqu'ils sont ajust & eacute;s & agrave; des & eacute;chelles qui n'englobent pas l'ensemble de l'aire de r & eacute;partition des esp & egrave;ces (sous-aires) et ne comprennent qu'une partie de leurs tol & eacute;rances environnementales, les SDMs et leurs pr & eacute;visions risquent d'& ecirc;tre affect & eacute;s par la troncation de niche. Une solution simple & agrave; ce probl & egrave;me consiste & agrave; ajuster les SDMs & agrave; une & eacute;tendue englobant la totalit & eacute; de l'aire de r & eacute;partition des esp & egrave;ces, mais la r & eacute;solution est souvent trop grossi & egrave;re pour les & eacute;valuations de conservation & agrave; & eacute;chelle locale ou r & eacute;gionale. Une autre solution, qui tient mieux compte de l'& eacute;cologie des esp & egrave;ces, repose sur l'ajustement de SDM hi & eacute;rarchiques spatialement imbriqu & eacute;s (N-SDM) en combinant un SDM

Keywords

BiasClimate changeClimate-changeConservationEcological nicheFrameworkGeographic restrictionHabitat suitabilityImpactsIntegrated modelsLand-coverMultiple scalesPotential distributionsPredicPredictionsRangeResponse curveResponse curvesScale

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal JOURNAL OF ECOLOGY due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 27/273, thus managing to position itself as a Q1 (Primer Cuartil), in the category Plant Sciences. Notably, the journal is positioned above the 90th percentile.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-11-01:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 43.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 41 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 27.45.
  • The number of mentions on the social network X (formerly Twitter): 14 (Altmetric).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Belgium; France; Italy; Netherlands; Switzerland.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (GARCIA MATEO, RUBEN).