Rate of environmental change across scales in ecology

Abstract

The rate of change (RoC) of environmental drivers matters: biotic and abiotic components respond differently when faced with a fast or slow change in their environment. This phenomenon occurs across spatial scales and thus levels of ecological organization. We investigated the RoC of environmental drivers in the ecological literature and examined publication trends across ecological levels, including prevalent types of evidence and drivers. Research interest in environmental driver RoC has increased over time (particularly in the last decade), however, the amount of research and type of studies were not equally distributed across levels of organization and different subfields of ecology use temporal terminology (e.g. ‘abrupt’ and ‘gradual’) differently, making it difficult to compare studies. At the level of individual organisms, evidence indicates that responses and underlying mechanisms are different when environmental driver treatments are applied at different rates, thus we propose including a time dimension into reaction norms. There is much less experimental evidence at higher levels of ecological organization (i.e. population, community, ecosystem), although theoretical work at the population level indicates the importance of RoC for evolutionary responses. We identified very few studies at the community and ecosystem levels, although existing evidence indicates that driver RoC is important at these scales and potentially could be particularly important for some processes, such as community stability and cascade effects. We recommend shifting from a categorical (e.g. abrupt versus gradual) to a quantitative and continuous (e.g. °C/h) RoC framework and explicit reporting of RoC parameters, including magnitude, duration and start and end points to ease cross‐scale synthesis and alleviate ambiguity. Understanding how driver RoC affects individuals, populations, communities and ecosystems, and furthermore how these effects can feed back between levels is critical to making improved predictions about ecological responses to global change drivers. The application of a unified quantitative RoC framework for ecological studies investigating environmental driver RoC will both allow cross‐scale synthesis to be accomplished more easily and has the potential for the generation of novel hypotheses.

Fast environmental change and eco-evolutionary feedbacks can drive regime shifts in ecosystems before tipping points are crossed

“…For instance, a recent study, using a model whose parameters were estimated from data, showed that behavioural feedbacks may cause rate-induced regime shifts in coral reefs [31]. However, determining whether a regime shift observed in the past was caused by the rate of change of an environmental condition may be challenging due to the lack of data on the effects of the rate of change in ecosystems [39]. Furthermore, documented regime shifts at the ecosystem scale rarely include information about trait changes of the organisms involved [10], which is necessary to study the feedbacks between ecological and evolutionary processes.…”

Rate-of-change analysis in palaeoecology revisited: a new approach

“…Consistent patterns in RoC peaks in several sequences may potentially indicate responses to exogenous drivers such as regional climate change, pathogenic attacks, or widespread human activity (Mottl et al, 2021). Ecologists are recognising the importance of quantifying RoC of environmental drivers such as temperature, toxins, and salinity on ecosystems (Pinek et al, 2020) and are developing new and powerful numerical tools for space–time analysis of community compositional data over time intervals of decades (e.g. Legendre and Gauthier, 2014).…”

Illuminating the intrinsic and extrinsic drivers of ecological stability across scales

“…The larger the sampling scale considered, the greater the likelihood of detecting environmental variation in space or time (Wiens, 1989). Consequently, environmental change is characterized not only by its mean and variance, but by the dynamics of its variance in space and time (its stochasticity , Shoemaker et al, 2019; Table 1), its rate of change (Pinek et al, 2020) and its velocity , which comprises both the spatial and temporal dimensions of environmental variation (Burrows et al, 2014). These heterogeneities affect both deterministic and stochastic processes influencing ecological populations (Shoemaker et al, 2019; Waldock et al, 2018) and thus, greater effort should be made to incorporate such heterogeneities into ecological theory and experiments.…”