Version 1
: Received: 29 August 2023 / Approved: 31 August 2023 / Online: 1 September 2023 (11:36:38 CEST)
How to cite:
Kiene, M.; Diel, P.; Schott, M.; Martin-Creuzburg, D.; Laforsch, C. Index for Adaptive Responses (InARes): A New Framework for Evaluating Adaptive, Functional Traits considering Complex Environments. Preprints2023, 2023090072. https://doi.org/10.20944/preprints202309.0072.v1
Kiene, M.; Diel, P.; Schott, M.; Martin-Creuzburg, D.; Laforsch, C. Index for Adaptive Responses (InARes): A New Framework for Evaluating Adaptive, Functional Traits considering Complex Environments. Preprints 2023, 2023090072. https://doi.org/10.20944/preprints202309.0072.v1
Kiene, M.; Diel, P.; Schott, M.; Martin-Creuzburg, D.; Laforsch, C. Index for Adaptive Responses (InARes): A New Framework for Evaluating Adaptive, Functional Traits considering Complex Environments. Preprints2023, 2023090072. https://doi.org/10.20944/preprints202309.0072.v1
APA Style
Kiene, M., Diel, P., Schott, M., Martin-Creuzburg, D., & Laforsch, C. (2023). Index for Adaptive Responses (InARes): A New Framework for Evaluating Adaptive, Functional Traits considering Complex Environments. Preprints. https://doi.org/10.20944/preprints202309.0072.v1
Chicago/Turabian Style
Kiene, M., Dominik Martin-Creuzburg and Christian Laforsch. 2023 "Index for Adaptive Responses (InARes): A New Framework for Evaluating Adaptive, Functional Traits considering Complex Environments" Preprints. https://doi.org/10.20944/preprints202309.0072.v1
Abstract
The focus of recent research shifts towards complex ‘whole organism’ responses (i.e., in multiple functional traits) in adaptation to or to defend against stressors under complex environmental conditions. This increasing complexity is challenging to analyse and demands sophisticated tools to drive meaningful conclusions from those data. Trait-based regression models, multivariate analyses, like principal component analyses, and plasticity indices can be used to tackle challenges with those complex investigations. But those methods have substantial limitations, like the need for high sample size, multi-dimensionality of results or the need for trait coordination in high-dimensional space, or the calculation on the population level, which might buffer or cover the de facto occurring individual effects. To improve and simplify studies on ‘whole organism’ responses, analyses, and their interpretation, we developed the Index for Adaptive Responses. This straightforward framework can unite all traits of an organism in one number. A newly developed transformation method, included in this framework, comprises a normalisation and standardisation to a baseline or control without changing the data or variance structure of the original data. We assessed the performance and accuracy of the framework with an application in an extensive predator-prey case study, with simulations and application examples using literature data. We show that the Index for Adaptive Responses respects adaptations as well as maladaptations and outperforms established approaches. The framework is robust against outliers and non-gaussian distribution. We further show that the qualitative prediction of the adaptiveness of included traits is highly accurate, even under challenging conditions, e.g., low replicate numbers. Functions and algorithms of the framework are provided with an R package but can easily be translated into other programming languages. The Index for Adaptive Responses will simplify future research on complex adaptive responses and improves our understanding of these responses’ ecological as well as evolutionary implications.
Keywords
adaptive response; complex environment; functional ecology; functional trait; Index for Adaptive Responses; phenotypic plasticity; plasticity index; whole organism response
Subject
Biology and Life Sciences, Ecology, Evolution, Behavior and Systematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
