Sebastian Steibl, Simon Steiger, Luís Valente, James C. Russell
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Using a global island plant dataset for atolls (378 islands across 19 atolls) – prototypical examples for small‐island dynamics – we show that the degree of residual variance in species–area curves can be captured, modelled, and linked to environmental conditions. Our heteroscedastic modelling approach demonstrates that apparent stochasticity in species–area relationships is not random but predictable through environmental drivers. Specifically, we found that increased rainfall reduces the residual variance around the species–area curve, indicating that resource availability is a critical factor enabling conformity to species–area scaling. Cyclone disturbance frequency did not drive stochasticity, challenging the prevailing view that disturbance regimes drive the stochasticity in species–area scaling on small islands. By treating residual variance as an explicit model parameter in species–area relationships rather than unexplainable noise, our approach provides new insights into the conditions enabling biological communities to conform to species–area scaling. Shifting the focus in species–area studies on the residual variance as an interpretable model parameter that captures the degree of conformity to species–area scaling offers novel perspectives into the environmental factors prerequisite for species–area scaling. This contributes to unifying the apparent anomalous, stochastic nature of small‐island systems with the general law of linear species–area scaling.","PeriodicalId":51026,"journal":{"name":"Ecography","volume":"19 1","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rainfall increases conformity and strength of species–area relationships\",\"authors\":\"Sebastian Steibl, Simon Steiger, Luís Valente, James C. Russell\",\"doi\":\"10.1002/ecog.08159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The positive relationship between species richness and area is regarded as one of the few laws in ecology. Therefore, deviations from predictable species–area scaling, evident as high residual variance in species–area curves, are often interpreted as anomalous behaviour. Small‐island systems often do not conform to species–area relationships, yet the high stochasticity in their species–area curves is frequently treated as unexplainable noise or attributed to idiosyncratic extinction rates. Here, we introduce a statistical framework that incorporates the degree of stochasticity in species–area relationships as an explicit, interpretable model parameter. Using a global island plant dataset for atolls (378 islands across 19 atolls) – prototypical examples for small‐island dynamics – we show that the degree of residual variance in species–area curves can be captured, modelled, and linked to environmental conditions. Our heteroscedastic modelling approach demonstrates that apparent stochasticity in species–area relationships is not random but predictable through environmental drivers. Specifically, we found that increased rainfall reduces the residual variance around the species–area curve, indicating that resource availability is a critical factor enabling conformity to species–area scaling. Cyclone disturbance frequency did not drive stochasticity, challenging the prevailing view that disturbance regimes drive the stochasticity in species–area scaling on small islands. By treating residual variance as an explicit model parameter in species–area relationships rather than unexplainable noise, our approach provides new insights into the conditions enabling biological communities to conform to species–area scaling. Shifting the focus in species–area studies on the residual variance as an interpretable model parameter that captures the degree of conformity to species–area scaling offers novel perspectives into the environmental factors prerequisite for species–area scaling. 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Rainfall increases conformity and strength of species–area relationships
The positive relationship between species richness and area is regarded as one of the few laws in ecology. Therefore, deviations from predictable species–area scaling, evident as high residual variance in species–area curves, are often interpreted as anomalous behaviour. Small‐island systems often do not conform to species–area relationships, yet the high stochasticity in their species–area curves is frequently treated as unexplainable noise or attributed to idiosyncratic extinction rates. Here, we introduce a statistical framework that incorporates the degree of stochasticity in species–area relationships as an explicit, interpretable model parameter. Using a global island plant dataset for atolls (378 islands across 19 atolls) – prototypical examples for small‐island dynamics – we show that the degree of residual variance in species–area curves can be captured, modelled, and linked to environmental conditions. Our heteroscedastic modelling approach demonstrates that apparent stochasticity in species–area relationships is not random but predictable through environmental drivers. Specifically, we found that increased rainfall reduces the residual variance around the species–area curve, indicating that resource availability is a critical factor enabling conformity to species–area scaling. Cyclone disturbance frequency did not drive stochasticity, challenging the prevailing view that disturbance regimes drive the stochasticity in species–area scaling on small islands. By treating residual variance as an explicit model parameter in species–area relationships rather than unexplainable noise, our approach provides new insights into the conditions enabling biological communities to conform to species–area scaling. Shifting the focus in species–area studies on the residual variance as an interpretable model parameter that captures the degree of conformity to species–area scaling offers novel perspectives into the environmental factors prerequisite for species–area scaling. This contributes to unifying the apparent anomalous, stochastic nature of small‐island systems with the general law of linear species–area scaling.
期刊介绍:
ECOGRAPHY publishes exciting, novel, and important articles that significantly advance understanding of ecological or biodiversity patterns in space or time. Papers focusing on conservation or restoration are welcomed, provided they are anchored in ecological theory and convey a general message that goes beyond a single case study. We encourage papers that seek advancing the field through the development and testing of theory or methodology, or by proposing new tools for analysis or interpretation of ecological phenomena. Manuscripts are expected to address general principles in ecology, though they may do so using a specific model system if they adequately frame the problem relative to a generalized ecological question or problem.
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