Navigating the integration of biotic interactions in biogeography

Author:

Thuiller Wilfried1ORCID,Calderón‐Sanou Irene123ORCID,Chalmandrier Loïc4,Gaüzère Pierre1,O'Connor Louise M. J.15,Ohlmann Marc1,Poggiato Giovanni1,Münkemüller Tamara1

Affiliation:

1. Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA Grenoble France

2. German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany

3. Institute of Biology Martin Luther Univ. Halle Wittenberg Halle (Saale) Germany

4. Univ. Grenoble Alpes, CNRS, LIPhy Grenoble France

5. Biodiversity and Natural Resources Program International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria

Abstract

AbstractBiotic interactions are widely recognised as the backbone of ecological communities, but how best to study them is a subject of intense debate, especially at macro‐ecological scales. While some researchers claim that biotic interactions need to be observed directly, others use proxies and statistical approaches to infer them. Despite this ambiguity, studying and predicting the influence of biotic interactions on biogeographic patterns is a thriving area of research with crucial implications for conservation. Three distinct approaches are currently being explored. The first approach involves empirical observation and measurement of biotic interactions' effects on species demography in laboratory or field settings. While these findings contribute to theory and to understanding species' demographies, they can be challenging to generalise on a larger scale. The second approach centers on inferring biotic associations from observed co‐occurrences in space and time. The goal is to distinguish the environmental and biotic effects on species distributions. The third approach constructs extensive potential interaction networks, known as metanetworks, by leveraging existing knowledge about species ecology and interactions. This approach analyses local realisations of these networks using occurrence data and allows understanding large distributions of multi‐taxa assemblages. In this piece, we appraise these three approaches, highlighting their respective strengths and limitations. Instead of seeing them as conflicting, we advocate for their integration to enhance our understanding and expand applications in the emerging field of interaction biogeography. This integration shows promise for ecosystem understanding and management in the Anthropocene era.

Funder

Agence Nationale de la Recherche

Marie Curie

Publisher

Wiley

Subject

Ecology,Ecology, Evolution, Behavior and Systematics

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