Advancing understanding and prediction in multiple stressor research through a mechanistic basis for null models

As a result of global climate change, species are experiencing an escalation in the severity and regularity of extreme thermal events. With patterns of disease distribution and transmission predicted to undergo considerable shifts in the coming years, the interplay between temperature and pathogen exposure will likely determine the capacity of a population to persist under the dual threat of global change and infectious disease. In this study, we investigated how exposure to a pathogen affects an individual's ability to cope with extreme temperatures. Using experimental infections of Daphnia magna with its obligate bacterial pathogen Pasteuria ramosa, we measured upper thermal limits of multiple host and pathogen genotype combinations across the dynamic process of infection and under various forms (static and ramping) of thermal stress. We find that pathogens substantially limit the thermal tolerance of their host, with the reduction in upper thermal limits on par with the breadth of variation seen across similar species entire geographical ranges. The precise magnitude of any reduction, however, was specific to the host and pathogen genotype combination. In addition, as thermal ramping rate slowed, upper thermal limits of both healthy and infected individuals were reduced. Our results suggest that the capacity of a population to evolve new thermal limits, when also faced with the threat of infection, will depend not only on a host's genetic variability in warmer environments, but also on the frequency of host and pathogen genotypes. We suggest that pathogen‐induced alterations of host thermal performance should be taken into account when assessing the resilience of any population and its potential for adaptation to global change.

Section: Discussionmentioning

confidence: 99%

Pathogen exposure disrupts an organism's ability to cope with thermal stress

Hector

Sgrò

Hall

2019

“…For example, a smaller reduction in the resource uptake in Figure 2g-i, or a larger reduction in R 1 , would have resulted in different outcomes of how the joint effect is categorized. This illustrates the idea that information obtained from null models cannot be extrapolated beyond the tested ranges of the environmental change drivers (Schäfer & Piggott, 2018). This feature limits the capacity of null models to assist ecosystem management.…”

Section: Comprehension Of Community and Ecosystem-level Effe Ctsmentioning

confidence: 97%

“…When the observed joint effects are smaller than or greater than those predictions, socalled antagonistic or synergistic effects are concluded, respectively (Crain et al, 2008). A variety of null models exists, each with their own assumptions and limitations (Piggott, Townsend, & Matthaei, 2015), and comprehensive overviews exist in the literature (Schäfer & Piggott, 2018). In general, these null models differ in their underlying assumption on how drivers combine to affect the biological variable of interest.…”

mentioning

confidence: 99%

Community‐ and ecosystem‐level effects of multiple environmental change drivers: Beyond null model testing

Laender

2018

Understanding the joint effect of multiple drivers of environmental change is a key scientific challenge. The dominant approach today is to compare observed joint effects with predictions from various types of null models. Drivers are said to combine synergistically (antagonistically) when their observed joint effect is larger (smaller) than that predicted by the null model. Here, I argue that this approach does not promote understanding of effects on important community- and ecosystem-level variables such as biodiversity and ecosystem function. I use ecological theory to show that different mechanisms can lead to the same deviation from a null model's prediction. Inversely, I show that the same mechanism can lead to different deviations from a null model's prediction. These examples illustrate that it is not possible to make strong mechanistic inferences from null models. Next, I present an alternative framework to study such effects. This framework makes a clear distinction between two different kinds of drivers (resource ratio shifts and multiple stressors) and integrates both by incorporating stressor effects into resource uptake theory. I show that this framework can advance understanding because of three reasons. First, it forces formalization of "multiple stressors," using factors that describe the number and kind of stressors, their selectivity and dynamic behaviour, and the initial trait diversity and tolerance among species. Second, it produces testable predictions on how these factors affect biodiversity and ecosystem function, alone and in combination with resource ratio shifts. Third, it can fail in informative ways. That is, its assumptions are clear, so that different kinds of deviations between predictions and observed effects can guide new experiments and theory improvement. I conclude that this framework will more effectively progress understanding of global change effects on communities and ecosystems than does the current practice of null model testing.

“…Several strategies exist to describe multiple pressure effects and possible interactions including the null model approach (Schäfer & Piggott, ; Thompson, MacLennan, & Vinebrooke, ) and mathematical classification (Piggott et al, ; Wagenhoff, Townsend, Phillips, & Matthaei, ). We described the effect using the model coefficients.…”

Section: Methodsmentioning

confidence: 99%

Quantifying multiple pressure interactions affecting populations of a recreationally and commercially important freshwater fish

Gutowsky

Giacomini

Kerckhove

et al. 2019

The expanding human global footprint and growing demand for freshwater have placed tremendous stress on inland aquatic ecosystems. Aichi Target 10 of the Convention on Biological Diversity aims to minimize anthropogenic pressures affecting vulnerable ecosystems, and pressure interactions are increasingly being incorporated into environmental management and climate change adaptation strategies. In this study, we explore how climate change, overfishing, forest disturbance, and invasive species pressures interact to affect inland lake walleye (Sander vitreus) populations. Walleye support subsistence, recreational, and commercial fisheries and are one of most sought‐after freshwater fish species in North America. Using data from 444 lakes situated across an area of 475 000 km2 in Ontario, Canada, we apply a novel statistical tool, R‐INLA, to determine how walleye biomass deficit (carrying capacity—observed biomass) is impacted by multiple pressures. Individually, angling activity and the presence of invasive zebra mussels (Dreissena polymorpha) were positively related to biomass deficits. In combination, zebra mussel presence interacted negatively and antagonistically with angling activity and percentage decrease in watershed mature forest cover. Velocity of climate change in growing degree days above 5°C and decrease in mature forest cover interacted to negatively affect walleye populations. Our study demonstrates how multiple pressure evaluations can be conducted for hundreds of populations to identify influential pressures and vulnerable ecosystems. Understanding pressure interactions is necessary to guide management and climate change adaptation strategies, and achieve global biodiversity targets.