Understanding and predicting physiological performance of organisms in fluctuating and multifactorial environments

Abstract

International audienceUnderstanding how variance in environmental factors affects physiological performance , population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-limitation theory into a single unified conceptual framework that has general applicability. We show how the framework can be applied (1) to generate mathematically tractable predictions of the physiological effects of multiple fluctuating co-limiting factors , (2) to understand how each co-limiting factor contributes to these effects, and (3) to detect mechanisms such as acclimation or physiological stress when they are at play. We show that the statistical covariance of co-limiting factors, which has not been considered before, can be a strong driver of physiological performance in various ecological contexts. Our framework can provide powerful insights on how the global change-induced shifts in multiple environmental factors affect the physiological performance of organisms

Modeling temperature‐dependent development rate and phenology in insects: review of major developments, challenges, and future directions

“…Numerous studies have indicated the effect of these factors, but few consider them simultaneously (Couret, ; Couret & Benedict, ). Large‐scale experiments would be required to quantify the effect of interacting factors on insect development rate, together with more complex models taking into account the fluctuating and multifactorial environment experienced by insects (Régnière et al., ; Crespo‐Pérez et al., ; Koussoroplis et al., ). An additional layer of complexity is the integration of trophic interactions and phenological synchrony (e.g., with host plants), of particular importance for accurate model predictions in a context of climate change (Mwalusepo et al., ).…”

The fallacy of the average: on the ubiquity, utility and continuing novelty of Jensen's inequality

“…For example, ecological physiologists and evolutionary biologists have innovatively incorporated the effects of Jensen's inequality into their efforts to model how plants and animals will respond to future changes in Earth's climate (e.g. Ruel and Ayres, 1999;Martin and Huey, 2008;Dillon et al, 2010;Williams et al, 2012;Vasseur et al, 2014;Colinet et al, 2015;Kingsolver et al, 2015;Dowd et al, 2015;Dillon and Woods, 2016;Koussoropolis et al, 2017). By contrast, biologists in other fields are often unaware of the quirks of nonlinear averaging.…”

Phytoplankton community responses to temperature fluctuations under different nutrient concentrations and stoichiometry

“…In a thermally fluctuating environment, such changes of the TRN imply that the effect size of thermal variance might strongly depend on the nutritional context (Koussoroplis et al. ; Fig. ), a prediction that remains to be verified.…”