Ecological and evolutionary consequences of changing seasonality.

Climate change and other anthropogenic drivers alter seasonal regimes across freshwater, terrestrial, and marine biomes. Seasonal patterns affect ecological and evolutionary processes at different ecological levels through changes to gene frequencies, species traits, population dynamics, species interactions, and different facets of biodiversity. We synthesize the mechanisms that determine biological responses to seasonality, to demonstrate how their interconnections can propagate impacts of altered seasonal patterns and complicate predictions. Given the potential for nonlinearities and the propagation of impacts across levels of ecological complexity, we advocate the use of mechanistic approaches that acknowledge species-specific responses to the environment and potential seasonal adaptations. Editor's summary: Climate change is having widely recognized effects on ecosystems by increasing temperatures, changing precipitation patterns, and causing more frequent extreme events. Less well understood are the effects of changes to seasonal patterns, which include shifts in the timing, size, and consistency of fluctuations. In a Review, Hernández-Carrasco et al. synthesized ways that seasonal shifts can span biological levels from individuals to populations and whole ecosystems. The authors highlight the roles that demographic responses to the environment, species specialization to seasonal trends, and evolutionary constraints play in ecological responses to changing seasonality. —Bianca Lopez BACKGROUND: Climate change is rapidly altering seasonal regimes in terrestrial, freshwater, and marine realms, disrupting the natural rhythm of ecological processes. Seasonality is so fundamental to ecosystems that these shifts threaten the maintenance of biodiversity and its contributions to society. Recent advances across several fields in ecology and evolution have identified links between environmental seasonality and processes affecting natural systems at different levels, from the genetic structure of populations to whole ecosystem functions. These connections reveal unexplored pathways through which changes in seasonality could affect biodiversity and propagate across multiple levels of ecological complexity. At the same time, ecological and evolutionary processes governed by seasonality can determine species' ability to adapt to changing seasonal patterns. Yet, despite the potential pervasive consequences for biological systems, changing environmental seasonality remains a largely overlooked dimension of climate change. We explore the diverse ways in which altered seasonal patterns can produce cross-level ecological responses. Given the prospect of further seasonal shifts over the next decades, it is imperative to identify and quantify the mechanisms that underpin biological responses to seasonal regimes and the potential for species to adapt. ADVANCES: We synthesize theoretical and empirical evidence to identify two broad pathways through which altered seasonality affects living systems: the demographic response to the experienced environment, and adaptations that allow the synchronization with environmental fluctuations. The former is closely linked to the physiological constraints and adaptations determining populations' demographic rates in different environmental conditions, whereas the latter depends on plastic, life-history, and behavioral traits that allow organisms to track seasonal fluctuations. We show that both pathways can propagate the effects of changes in the amplitude, timing, and predictability of seasonality, though the mechanisms may depend on the average conditions of the environment. This interplay provides a means for climate change to affect ecological processes linked to seasonality, including population phenology and species interactions, even when other attributes of seasonality remain unchanged. Furthermore, previous adaptations to seasonality, such as the use of environmental cues, could limit species' tracking of environmental changes through evolutionary adaptation and latitudinal range shifts. Recent developments in modeling enable the inclusion of complex interactions among processes operating at different levels. Such models can predict emergent properties such as biodiversity change by allowing the propagation of known effects across levels—an area ripe for advancement in the context of changing seasonality. OUTLOOK: The pervasive effects of seasonality and the interactions between processes operating at multiple levels increase uncertainty around the future of biodiversity in the face of global disruptions to seasonality. A deeper understanding of the effects of altered seasonality will help build tools to forecast ecological dynamics into a no-analog future. Empirical work is thus necessary to uncover and quantify these effects, but consensus between applied and theoretical studies is paramount. Such consensus can be achieved by using more ecologically informative measures of seasonality that incorporate the critical components to which biodiversity responds. The resulting theoretical knowledge can be used to inform mechanistic models that allow the propagation of effects across levels of ecological organization. Although part of the information required to build fully mechanistic models might currently be lacking, our synthesis suggests that including species' phenology and their demographic response to the environment can already improve current predictions. Understanding the mechanisms that allow the propagation of impacts opens new avenues for improving conservation planning, invasive species management, large-scale restoration, and biodiversity forecasting. Rapidly changing seasonal patterns can generate complex ecological impacts.: These impacts arise through (i) adaptations that allow a proactive response to periodic shifts in the environment (e.g., coat color changes with environmental cues) and (ii) individual performance under conditions experienced throughout the year (e.g., temperature-dependent growth). Such impacts propagate across levels of organization, often producing nonlinear responses, which require mechanistic approaches to anticipate. STOAT IMAGE CREDIT: IMAGEBROKER.COM/SHUTTERSTOCK.COM [ABSTRACT FROM AUTHOR]