Density dependence governs when population responses to multiple stressors are magnified or mitigated

Hodgson, Emma E.; Essington, Timothy E.; Halpern, Benjamin S.

doi:10.1002/ecy.1961

Cited by 29 publications

(38 citation statements)

References 72 publications

(157 reference statements)

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“…The yield y is the same for both species (0.1). When the supply rate of both resources (dot) falls within the zone (in grey) delimited by the consumption vectors, coexistence is possible DE LAENDER | 5023 model testing and start constructing a mechanistic framework (Griffen et al, 2016;Kroeker et al, 2017), as has been recently initiated at the level of populations (Galic, Grimm, & Forbes, 2017;Hodgson, Essington, & Halpern, 2017) and communities (Thompson et al, 2018). Here, I propose such a framework and show that deviations from its predictions can be informative, exactly because the assumptions underlying the predictions are well-defined.…”

Section: Community-and Ecosystem -Level Effects Of Environmental Changesmentioning

confidence: 98%

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

Laender

2018

Global Change Biology

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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.

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Section: Community-and Ecosystem -Level Effects Of Environmental Changesmentioning

confidence: 98%

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

Laender

2018

Global Change Biology

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“…This is because stressors act on this level and the established relationships are therefore presumably most robust (Hodgson, Essington, & Halpern, 2017;Maltby, 1999). On the population and community level and above, stressor-effect relationships are influenced by multiple ecological processes such as density dependence, biotic interactions or dispersal dynamics (Vellend, 2010) (Hodgson et al, 2017).…”

Section: Issues Of Study De Sign and Cross-stud Y Variabilitymentioning

confidence: 99%

“…by running experiments at the densities typical for the field situation or through modelling;Hodgson et al, 2017) and if meta-population dynamics can be incorporated or are irrelevant (e.g. by running experiments at the densities typical for the field situation or through modelling;Hodgson et al, 2017) and if meta-population dynamics can be incorporated or are irrelevant (e.g.…”

mentioning

confidence: 99%

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

Schäfer

Piggott

2018

Global Change Biology

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Global environmental change is driven by multiple anthropogenic stressors. Conservation and restoration require understanding the individual and joint action of these stressors to evaluate and prioritize management measures. To date, most studies on multiple stressor effects have sought to identify potential stressor interactions, defined as deviations from null models, and related meta-analyses have focused on quantifying the relative proportion of stressor interactions across studies. These studies have provided valuable insights about the complexity of multiple stressor effects, but remain largely devoid of a theoretical framework for null model selection and prediction of effects. We suggest that multiple stressor research would benefit by (1) integrating and developing additional null models and (2) selecting null models based on their mechanistic assumptions of the stressor mode of action and organism sensitivities as well as stressor-effect relationships for individuals and populations. We present a range of null models and outline their underlying assumptions and application in multiple stressor research. Moving beyond mere description requires multiple stressor research to shift its focus from identifying statistically significant interactions to the use and development of mechanistic (null) models. Justified selection of the appropriate null model is a first step to achieve this.

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“…Yet, density dependence can either exacerbate or ameliorate population‐level impacts of stressors in species with complex life cycles (Hodgson et al. ). Understanding the potential for multiple drivers of life‐history expression is particularly relevant for species of management or conservation importance as life‐history shifts can alter population recovery and sustainable exploitation rates (Rowe and Hutchings , de Roos et al.…”

Section: Introductionmentioning

confidence: 99%

“…In amphibians, for example, cues from predators, water temperatures, and density dependence can all influence the size and timing of metamorphosis and thereby influence adult fitness (Wilbur and Collins 1973, Semlitsch et al 1988, Relyea 2007). Yet, density dependence can either exacerbate or ameliorate population-level impacts of stressors in species with complex life cycles (Hodgson et al 2017). Understanding the potential for multiple drivers of life-history expression is particularly relevant for species of management or conservation importance as lifehistory shifts can alter population recovery and sustainable exploitation rates (Rowe andHutchings 2003, de Roos et al 2006).…”

Section: Introductionmentioning

confidence: 99%

The roles of extrinsic and intrinsic factors in the freshwater life‐history dynamics of a migratory salmonid

et al. 2018

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Key life‐cycle transitions, such as metamorphosis or migration, can be altered by a variety of external factors, such as climate variation, strong species interactions, and management intervention, or modulated by density dependence. Given that these life‐history transitions can influence population dynamics, understanding the simultaneous effects of intrinsic and extrinsic controls on life‐history expression is particularly relevant for species of management or conservation importance. Here, we examined how life histories of steelhead (Oncorhynchus mykiss) are affected by weather, pink salmon abundance (Oncorhynchus gorbuscha), experimental nutrient addition, and density‐dependent processes. We tested for impacts on the size of steelhead smolts (juveniles migrating to the sea), as well as their age and abundance across four decades in the Keogh River, British Columbia, Canada. Larger steelhead smolts were associated with warmer years and artificial nutrient addition. In addition, higher pink salmon abundance and artificial nutrient addition correlated with juvenile steelhead migrating at younger ages. While density dependence appeared to be the primary factor regulating the abundance of steelhead smolts, nutrient addition and temperature were positively and negatively associated with smolt production, respectively, prior to 1991, and pink salmon spawning abundance was positively associated with smolt production after 1990. Thus, this study provides evidence that the temporal dynamics of one species of salmon is linked to the juvenile life history of co‐occurring steelhead. A complex interplay of species interactions, nutrient subsidies, density dependence, and climatic variation can control the life‐history expression of species with complex life cycles.

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Density dependence governs when population responses to multiple stressors are magnified or mitigated

Cited by 29 publications

References 72 publications

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

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

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

The roles of extrinsic and intrinsic factors in the freshwater life‐history dynamics of a migratory salmonid

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