Samuel B. Fey

Recent shifts in the occurrence, cause, and magnitude of animal mass mortality events

Significance Mass mortality events (MMEs), the rapid, catastrophic die-off of organisms, are an example of a rare event affecting natural populations. Individual reports of MMEs clearly demonstrate their ecological and evolutionary importance, yet our understanding of the general features characterizing such events is limited. Here, we conducted the first, to our knowledge, quantitative analysis of MMEs across the animal kingdom, and as such, we were able to explore novel patterns, trends, and features associated with MMEs. Our analysis uncovered the surprising finding that there have been recent shifts in the magnitudes of MMEs and their associated causes. Our database allows the recommendation of improvements for data collection in ways that will enhance our understanding of how MMEs relate to ongoing perturbations to ecosystems. Mass mortality events (MMEs) are rapidly occurring catastrophic demographic events that punctuate background mortality levels. Individual MMEs are staggering in their observed magnitude: removing more than 90% of a population, resulting in the death of more than a billion individuals, or producing 700 million tons of dead biomass in a single event. Despite extensive documentation of individual MMEs, we have no understanding of the major features characterizing the occurrence and magnitude of MMEs, their causes, or trends through time. Thus, no framework exists for contextualizing MMEs in the wake of ongoing global and regional perturbations to natural systems. Here we present an analysis of 727 published MMEs from across the globe, affecting 2,407 animal populations. We show that the magnitude of MMEs has been intensifying for birds, fishes, and marine invertebrates; invariant for mammals; and decreasing for reptiles and amphibians. These shifts in magnitude proved robust when we accounted for an increase in the occurrence of MMEs since 1940. However, it remains unclear whether the increase in the occurrence of MMEs represents a true pattern or simply a perceived increase. Regardless, the increase in MMEs appears to be associated with a rise in disease emergence, biotoxicity, and events produced by multiple interacting stressors, yet temporal trends in MME causes varied among taxa and may be associated with increased detectability. In addition, MMEs with the largest magnitudes were those that resulted from multiple stressors, starvation, and disease. These results advance our understanding of rare demographic processes and their relationship to global and regional perturbations to natural systems.

Autumn leaf subsidies influence spring dynamics of freshwater plankton communities

While ecologists primarily focus on the immediate impact of ecological subsidies, understanding the importance of ecological subsidies requires quantifying the long-term temporal dynamics of subsidies on recipient ecosystems. Deciduous leaf litter transferred from terrestrial to aquatic ecosystems exerts both immediate and lasting effects on stream food webs. Recently, deciduous leaf additions have also been shown to be important subsidies for planktonic food webs in ponds during autumn; however, the inter-seasonal effects of autumn leaf subsidies on planktonic food webs have not been studied. We hypothesized that autumn leaf drop will affect the spring dynamics of freshwater pond food webs by altering the availability of resources, water transparency, and the metabolic state of ponds. We created leaf-added and no-leaf-added field mesocosms in autumn 2012, allowed mesocosms to ice-over for the winter, and began sampling the physical, chemical, and biological properties of mesocosms immediately following ice-off in spring 2013. At ice-off, leaf additions reduced dissolved oxygen, elevated total phosphorus concentrations and dissolved materials, and did not alter temperature or total nitrogen. These initial abiotic effects contributed to higher bacterial densities and lower chlorophyll concentrations, but by the end of spring, the abiotic environment, chlorophyll and bacterial densities converged. By contrast, zooplankton densities diverged between treatments during the spring, with leaf additions stimulating copepods but inhibiting cladocerans. We hypothesized that these differences between zooplankton orders resulted from resource shifts following leaf additions. These results suggest that leaf subsidies can alter both the short- and long-term dynamics of planktonic food webs, and highlight the importance of fully understanding how ecological subsidies are integrated into recipient food webs.

Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii

Environmental variability is ubiquitous, but its effects on populations are not fully understood or predictable. Recent attention has focused on how rapid evolution can impact ecological dynamics via adaptive trait change. However, the impact of trait change arising from plastic responses has received less attention, and is often assumed to optimize performance and unfold on a separate, faster timescale than ecological dynamics. Challenging these assumptions, we propose that gradual plasticity is important for ecological dynamics, and present a study of the plastic responses of the freshwater green algae Chlamydomonas reinhardtii as it acclimates to temperature changes. First, we show that C. reinhardtiis gradual acclimation responses can both enhance and suppress its performance after a perturbation, depending on its prior thermal history. Second, we demonstrate that where conventional approaches fail to predict the population dynamics of C. reinhardtii exposed to temperature fluctuations, a new model of gradual acclimation succeeds. Finally, using high-resolution data, we show that phytoplankton in lake ecosystems can experience thermal variation sufficient to make acclimation relevant. These results challenge prevailing assumptions about plasticitys interactions with ecological dynamics. Amidst the current emphasis on rapid evolution, it is critical that we also develop predictive methods accounting for plasticity.

Thermal variability alters the impact of climate warming on consumer–resource systems

Thermal variation through space and time are prominent features of ecosystems that influence processes at multiple levels of biological organization. Yet, it remains unclear how populations embedded within biological communities will respond to climate warming in thermally variable environments, particularly as climate change alters existing patterns of thermal spatial and temporal variability. As environmental temperatures increase above historical ranges, organisms may increasingly rely on extreme habitats to effectively thermoregulate. Such locations desirable in their thermal attributes (e.g., thermal refugia) are often suboptimal for resource acquisition (e.g., underground tunnels). Thus, via the expected increase in both mean temperatures and diel thermal variation, climate warming may heighten the trade-off for consumers between behaviors maximizing thermal performance and those maximizing resource acquisition. Here, we integrate behavioral, physiological, and trophic ecology to provide a general framework for understanding how temporal thermal variation, mediated by access to a thermal refugium, alters the response of consumer-resource systems to warming. We use this framework to predict how temporal variation and access to thermal refugia affect the persistence of consumers and resources during climate warming, how the quality of thermal refugia impact consumer-resource systems, and how consumer-resource systems with fast vs. slow ecological dynamics respond to warming. Our results show that the spatial thermal variability provided by refugia can elevate consumer biomass at warmer temperatures despite reducing the fraction of time consumers spend foraging, that temporal variability detrimentally impacts consumers at high environmental temperatures, and that consumer-resource systems with fast ecological dynamics are most vulnerable to climate warming. Thus, incorporating both estimates of thermal variability and species interactions may be necessary to accurately predict how populations respond to warming.

Temporal heterogeneity increases with spatial heterogeneity in ecological communities

Heterogeneity is increasingly recognized as a foundational characteristic of ecological systems. Under global change, understanding temporal community heterogeneity is necessary for predicting the stability of ecosystem functions and services. Indeed, spatial heterogeneity is commonly used in alternative stable state theory as a predictor of temporal heterogeneity and therefore an early indicator of regime shifts. To evaluate whether spatial heterogeneity in species composition is predictive of temporal heterogeneity in ecological communities, we analyzed 68 community data sets spanning freshwater and terrestrial systems where measures of species abundance were replicated over space and time. Of the 68 data sets, 55 (81%) had a weak to strongly positive relationship between spatial and temporal heterogeneity, while in the remaining communities the relationship was weak to strongly negative (19%). Based on a mixed model analysis, we found a significant but weak overall positive relationship between spatial and temporal heterogeneity across all data sets combined, and within aquatic and terrestrial data sets separately. In addition, lifespan and successional stage were negatively and positively related to temporal heterogeneity, respectively. We conclude that spatial heterogeneity may be a predictor of temporal heterogeneity in ecological communities, and that this relationship may be a general property of many terrestrial and aquatic communities.

Advancing Ecosystem Science by Promoting Greater Use of Theory and Multiple Research Approaches in Graduate Education

Since the inaugural edition of Ecosystems was published in 1998, ecosystem science has undergone substantial changes including the development of new research methods and an increasing emphasis on collaborations across traditional academic boundaries. In response to this transformation, we reflect on the current state of theory in ecosystem science, and make recommendations for training the next generation of Ph.D.-level ecosystem scientists. Specifically, we call for increased integration of theory into ecosystem science and outline the utility of iterating between theory and data generated by observations, experiments, and quantitative models. We recommend exposing graduate students to these three major approaches for generating data and propose strategies that students, advisors, and departments can employ to ensure this exposure. Ultimately, a successful training program will provide students with an understanding of key theories related to ecosystem science and how they interact with data, an appreciation for the interconnectedness of approaches to scientific inference, and a well-developed skill set in at least one approach—thereby empowering them to confidently tackle our pressing environmental problems. Although this is a daunting list of goals, continuing to advance our understanding of how ecosystems function necessitates a rigorous and well-developed training program.

Uncertainty in geographical estimates of performance and fitness

How will new climates alter the performance of organisms and the ranges that they occupy? This question is pressing, as shifting ranges will affect the likelihood that populations will decline or go extinct (Bellard, Bertelsmeier, Leadley, Thuiller, & Courchamp, 2012; Thomas et al., 2004), how local communities and ecosystems will function (Walther, 2010), whether they will provide new, different, or diminished ecosystem services (Schröter, 2005), and how much change will be required in approaches to agriculture (Nelson et al., 2014). For most species, answers hinge on uncertainty in both biotic and abiotic aspects of the problem (Suzuki, Rivero, Shulaev, Blumwald, & Mittler, 2014). Here we focus on abiotic conditions, which by themselves still pose enormous uncertainties—about future climates (IPCC, 2014), Received: 3 September 2017 | Revised: 7 March 2018 | Accepted: 14 May 2018 DOI: 10.1111/2041-210X.13035