Evolutionary responses to environmental change: trophic interactions affect adaptation and persistence

Mellard, Jarad P.; Mazancourt, Claire de; Loreau, Michel

doi:10.1098/rspb.2014.1351

Cited by 18 publications

(31 citation statements)

References 57 publications

(77 reference statements)

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“…); phenotypic variance could respond more realistically to selection, mutation and drift (DeLong & Gibert ); and the model could consider potential trade‐offs with other fitness traits or selection pressures (Mellard et al . ), particularly outside laboratory conditions (Sinclair et al . ).…”

Section: Discussionmentioning

confidence: 99%

“…Fordham et al 2013). For example, modelling of selection on a trait like CT max could be expanded to consider optima on thermal performance curves or tolerance landscapes (Rezende et al 2014); phenotypic variance could respond more realistically to selection, mutation and drift (DeLong & Gibert 2016); and the model could consider potential trade-offs with other fitness traits or selection pressures (Mellard et al 2015), particularly outside laboratory conditions (Sinclair et al 2012). Although no trade-offs were found between heat tolerance and other traits in D. melanogaster , antagonistic relationships can severely constrain adaptive responses (Etterson & Shaw 2001).…”

Section: Challenges and Assumptionsmentioning

confidence: 99%

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Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change

et al. 2016

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Based on the sensitivity of species to ongoing climate change, and numerous challenges they face tracking suitable conditions, there is growing interest in species' capacity to adapt to climatic stress. Here, we develop and apply a new generic modelling approach (AdaptR) that incorporates adaptive capacity through physiological limits, phenotypic plasticity, evolutionary adaptation and dispersal into a species distribution modelling framework. Using AdaptR to predict change in the distribution of 17 species of Australian fruit flies (Drosophilidae), we show that accounting for adaptive capacity reduces projected range losses by up to 33% by 2105. We identify where local adaptation is likely to occur and apply sensitivity analyses to identify the critical factors of interest when parameters are uncertain. Our study suggests some species could be less vulnerable than previously thought, and indicates that spatiotemporal adaptive models could help improve management interventions that support increased species' resilience to climate change.

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Section: Discussionmentioning

confidence: 99%

Section: Challenges and Assumptionsmentioning

confidence: 99%

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change

et al. 2016

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“…S17) (Wetzel 1975). We also employ realistic temperature niche widths of species in this model to reflect this evidence (Mellard et al 2015). We also employ realistic temperature niche widths of species in this model to reflect this evidence (Mellard et al 2015).…”

Section: Concepts and Synthesismentioning

confidence: 99%

“…The well-documented influence of temperature in determining community structure across ecosystems (Sunagawa et al 2015) provides support for models with temperature niches. We also employ realistic temperature niche widths of species in this model to reflect this evidence (Mellard et al 2015). Further evidence to support this model include the distributions of individual species in the year.…”

Section: Concepts and Synthesismentioning

confidence: 99%

Seasonal patterns in species diversity across biomes

Mellard

Audoye

Loreau

2019

Ecology

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Citation: Mellard, J. P., P. Audoye, and M. Loreau. 2019. Seasonal patterns in species diversity across biomes. Ecology 100(4):Abstract. A conspicuous season-diversity relationship (SDR) can be seen in seasonal environments, often with a defined peak in active species diversity in the growing season. We ask is this a general pattern and are other patterns possible? In addition, we ask what is the ultimate cause of this pattern and can we understand it using existing ecological theory? To accomplish this task, we assembled a global database on changes in species diversity through time in seasonal environments for different taxa and habitats and also conducted a modeling study in an attempt to replicate observed patterns. Our global database includes terrestrial and aquatic habitats, temperate, tropical, and polar environments, and taxa from disparate groups including vertebrates, insects, and plankton. We constructed nine alternative models that vary in assumptions on type of seasonal forcing, responses to that forcing, species niches, and types of species interactions. We found that most guilds of species exhibit a repeatable SDR across years. For north temperate ecosystems, active species diversity generally peaks mid-year. The peak for a guild is generally more pronounced in terrestrial habitats than aquatic habitats and more pronounced in temperate and polar regions than the tropics. We now have evidence that at least several different habitat and taxa types are likely to have multiple peaks in diversity in a year, for example, guilds of both aquatic microbes and desert vertebrates can show a bimodal or multimodal SDR. We compared all nine candidate models in their ability to explain the patterns and match their assumptions to the data. Some performed considerably better than others in being able to match the different patterns. We conclude that a model that includes both temperature niches and environmental feedbacks is necessary to explain the different SDRs. We use such a model to make predictions about how the SDR could be impacted by climate change. More effort should be put into documenting and understanding baseline seasonal patterns in diversity in order to predict future responses to global change.

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“…Some studies have explored how evolution influences the persistence of prey (Mellard et al 2015) and predator (Abrams 2009a, Yamamichi andMiner 2015) populations experiencing increased mortality. First, we have a limited understanding of how prey and predator evolution individually affect predator extinction thresholds.…”

Section: Introductionmentioning

confidence: 99%

How (co)evolution alters predator responses to increased mortality: extinction thresholds and hydra effects

Cortez

Yamamichi

2019

Ecology

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Citation: Cortez, M. H., and M. Yamamichi. 2019. How (co)evolution alters predator responses to increased mortality: extinction thresholds and hydra effects. Ecology 100(10):Abstract. Population responses to environmental change depend on both the ecological interactions between species and the evolutionary responses of all species. In this study, we explore how evolution in prey, predators, or both species affect the responses of predator populations to a sustained increase in mortality. We use an eco-evolutionary predator-prey model to explore how evolution alters the predator extinction threshold (defined as the minimum mortality rate that prevents population growth at low predator densities) and predator hydra effects (increased predator abundance in response to increased mortality). Our analysis identifies how evolutionary responses of prey and predators individually affect the predator extinction threshold and hydra effects, and how those effects are altered by interactions between the evolutionary responses. Based on our theoretical results, we predict that it is common in natural systems for evolutionary responses in one or both species to allow predators to persist at higher mortality rates than would be possible in the absence of evolution (i.e., evolution increases the predator mortality extinction threshold). We also predict that evolution-driven hydra effects occur in a minority of natural systems, but are not rare. We revisited published eco-evolutionary models and found that evolution causes hydra effects and increases the predator extinction threshold in many studies, but those effects have been overlooked. We discuss the implications of these results for species conservation, predicting population responses to environmental change, and the possibility of evolutionary rescue.Notes: The terms J ij denote entries of the Jacobian in Eq. 3. All conditions assume the sign structure in Eq. 3. Coevolution conditions result in synergistic effects of prey and predator evolution, provided the conditions for only prey evolution and the conditions for only predator evolution are satisfied.

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Evolutionary responses to environmental change: trophic interactions affect adaptation and persistence

Cited by 18 publications

References 57 publications

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change

Incorporating evolutionary adaptation in species distribution modelling reduces projected vulnerability to climate change

Seasonal patterns in species diversity across biomes

How (co)evolution alters predator responses to increased mortality: extinction thresholds and hydra effects

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