How many, and when? Optimising targeted gene flow for a step change in the environment

Kelly, Ella; Phillips, Benjamin L.

doi:10.1101/341339

Cited by 4 publications

(6 citation statements)

References 37 publications

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“…These methods will require new data, or synthesis of old data, and will, in the coming years, reveal much about adaptation to climate. Once we identify important climate axes along which selection occurs for a species, such as temperature or precipitation, as discussed above, we will be in a position to identify source and recipient populations, and we can move on to the problem of optimising the timing and size of an introduction (e.g., [105]).…”

Section: Discussionmentioning

confidence: 99%

“…Climate-adjusted provenancing is already being applied to habitat restoration and may provide populations with an opportunity to respond appropriately using both genetic and plastic adaptation strategies [71,86]. A framework for choosing when to use assisted evolution of corals in important reef systems [28,111], and models investigating optimal timing and size of an introduction (e.g., [105]), provide starting points for development of assisted evolution strategies in other taxa.…”

Section: Discussionmentioning

confidence: 99%

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The Potential for Rapid Evolution under Anthropogenic Climate Change

et al. 2019

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Understanding how natural populations will respond to rapid anthropogenic climate change is one of the greatest challenges for ecologists and evolutionary biologists. Much research has focussed on whether physiological traits can evolve quickly enough under rapidly increasing temperatures. While the simple Breeder's equation helps to understand how extreme temperatures and genetic variation might drive within-population evolution under climate change, it does not consider two key areas: how different forms of phenotypic plasticity interact and variation among populations. Plasticity can modify the exposure to climatic extremes and the strength of selection from those extremes, while differences among populations provide adaptive diversity not apparent within them. Here, we focus on terrestrial vertebrates and, with a case study on a tropical lizard, demonstrate the complex interplay between spatial, genetic and plastic contributions to variation in climate-relevant physiological traits. We identify several problems that need to be better understood: which traits are under selection in a changing climate; the different forms of plasticity relevant to population persistence and rapid evolution; plastic versus genetic contributions to geographic variation in climate-associated traits and whether plasticity can be harnessed to promote persistence of species. Given ongoing uncertainties around whether natural populations can evolve rapidly enough to persist, we advocate the use of field trials aimed at increasing rates of adaptation, especially in systems known to be strongly impacted by human-driven changes in climate.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The Potential for Rapid Evolution under Anthropogenic Climate Change

et al. 2019

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“…This is particularly why predation was not considered as a focal interaction in this review: indeed, when predation is investigated from the point of view of the variation of a prey's trait conferring variable avoidance ability from the predator, or from the variation of a predator's trait conferring variable ability to catch prey, then it becomes a trait involved in competition among prey to escape predators, or among predators to optimize prey foraging and selection (e.g. Kelly & Phillips, 2019; Labonne & Hendry, 2010).…”

Section: Introductionmentioning

confidence: 99%

Importance of interindividual interactions in eco‐evolutionary population dynamics: The rise of demo‐genetic agent‐based models

Lamarins

Fririon

Folio

et al. 2022

Evolutionary Applications

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The study of eco‐evolutionary dynamics, that is of the intertwinning between ecological and evolutionary processes when they occur at comparable time scales, is of growing interest in the current context of global change. However, many eco‐evolutionary studies overlook the role of interindividual interactions, which are hard to predict and yet central to selective values. Here, we aimed at putting forward models that simulate interindividual interactions in an eco‐evolutionary framework: the demo‐genetic agent‐based models (DG‐ABMs). Being demo‐genetic, DG‐ABMs consider the feedback loop between ecological and evolutionary processes. Being agent‐based, DG‐ABMs follow populations of interacting individuals with sets of traits that vary among the individuals. We argue that the ability of DG‐ABMs to take into account the genetic heterogeneity—that affects individual decisions/traits related to local and instantaneous conditions—differentiates them from analytical models, another type of model largely used by evolutionary biologists to investigate eco‐evolutionary feedback loops. Based on the review of studies employing DG‐ABMs and explicitly or implicitly accounting for competitive, cooperative or reproductive interactions, we illustrate that DG‐ABMs are particularly relevant for the exploration of fundamental, yet pressing, questions in evolutionary ecology across various levels of organization. By jointly modelling the effects of management practices and other eco‐evolutionary processes on interindividual interactions and population dynamics, DG‐ABMs are also effective prospective and decision support tools to evaluate the short‐ and long‐term evolutionary costs and benefits of management strategies and to assess potential trade‐offs. Finally, we provide a list of the recent practical advances of the ABM community that should facilitate the development of DG‐ABMs.

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“…At a larger scale and considering adaptive genetic variation, Bush et al (2016) projected the distribution of 17 species of Australian drosophilids with genetic variation underlying their climatic tolerances and showed that drosophilids might have the capacity to adapt under realistic scenarios of climate change. Thus, models that consider evolutionary responses to changing or new environments and in a spatially explicit way are particularly useful for studying the interaction between genetic and demographic processes and alternative management strategies (Pavlova et al 2017, Kelly and Phillips 2019).…”

Section: A Model Typology For Animal Conservation and Restorationmentioning

confidence: 99%

Spatially explicit models for decision‐making in animal conservation and restoration

et al. 2021

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Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision-making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene-to-individual level and the community-to-ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision-making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier-to-use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best-practise guidelines for applying these models. Further, more robust decision-making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by longterm funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes.

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How many, and when? Optimising targeted gene flow for a step change in the environment

Cited by 4 publications

References 37 publications

The Potential for Rapid Evolution under Anthropogenic Climate Change

The Potential for Rapid Evolution under Anthropogenic Climate Change

Importance of interindividual interactions in eco‐evolutionary population dynamics: The rise of demo‐genetic agent‐based models

Spatially explicit models for decision‐making in animal conservation and restoration

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