Evolutionary rates for multivariate traits: the role of selection and genetic variation

Pitchers, William; Wolf, Jason B.; Tregenza, Tom; Hunt, John; Dworkin, Ian

doi:10.1098/rstb.2013.0252

Cited by 44 publications

(50 citation statements)

References 87 publications

(315 reference statements)

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“…As the findings reveal, the responsibilities of and functions provided by the elderly, together with the old-age support provided by their adult children, are still accepted as amounting to an evolutionary advantage. [53][54][55][56] Even so, the adaptation process of the drifting elderly is still challenged by pressures induced by differences compared with before migrating and difficulties after migration. They had not yet achieved their final adaptation status.…”

Section: Adaptation Status Is the Results Of The Principle Of Evolutmentioning

confidence: 99%

“…This mirrors biological evolutionary theory regarding the process of evolution and adaptation. 53,54 Therefore, the drifting elderly in this study did not solve all the conflicts before migrating, and they had not finalized the most suitable social structure for cooperation and support. Both new or intensified proximate and evolutionary factors will induce further adaptation pressure and induce a readaption process, which can occur in repeating cycles.…”

Section: Adaptation Needs To Be Increased By Strengthening Social Smentioning

confidence: 92%

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Social adaptation and adaptation pressure among the “drifting elderly” in China: A qualitative study in Shanghai

Ruan

Zhu

Lü

2019

Health Planning & Management

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Summary Objective In China, a population of “drifting elderly” that is mainly composed of older parents who migrate for nonemployment reasons has emerged and developed rapidly. The need to understand their social adaptation after migration is well recognized but neglected, so we explored this in the current study. Methods A qualitative study using a grounded theory approach was undertaken involving 53 elderly interprovincial migrants in five districts of Shanghai from July 2016 to May 2018. This involved in‐depth interviews with participants. Adaptation of the drifting elderly and their motivations for migrating were studied, and differences in daily life when compared with before migrating, difficulties encountered after migrating, and social‐adaptation pressure were analyzed. Results The drifting elderly had poor adaptation regarding self‐identity, daily activities, and social context. The adaptation process regarding daily life, social relationships, and obtaining social support was difficult. They experienced both proximate adaptation pressure (induced by providing and/or obtaining social support) and evolutionary adaptation pressure (induced by mismatch and/or constraints). Conclusion The social adaptation of the drifting elderly was affected by differences in daily life when compared with before migrating, and adaptation pressure was caused by both proximate and evolutionary factors. The decision to migrate was the result of a rational principle of maintaining the intergenerational support structure, and it was influenced by the evolutionary advantage related to maintaining this structure. Strengthening social support for the drifting elderly is necessary to promote their adaptation.

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Section: Adaptation Status Is the Results Of The Principle Of Evolutmentioning

confidence: 99%

Section: Adaptation Needs To Be Increased By Strengthening Social Smentioning

confidence: 92%

Social adaptation and adaptation pressure among the “drifting elderly” in China: A qualitative study in Shanghai

Ruan

Zhu

Lü

2019

Health Planning & Management

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“…A heuristic rule suggests that rates lower than 0.1 are plausible (and even higher values are found in animal and plant population; Pitchers et al 2014). As such, an evolutionary rate of 0.051 Haldanes within 50 generations for mean temperature is plausible (assuming this is the single adaptive peak of the species), so that R. diptycha could persist in the new climatic conditions.…”

Section: A Brief Overview Of Evolutionary Rescue Models Evolutionary mentioning

confidence: 99%

A macroecological approach to evolutionary rescue and adaptation to climate change

et al. 2019

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Despite the widespread use of ecological niche models (ENMs) for predicting the responses of species to climate change, these models do not explicitly incorporate any population‐level mechanism. On the other hand, mechanistic models adding population processes (e.g. biotic interactions, dispersal and adaptive potential to abiotic conditions) are much more complex and difficult to parameterize, especially if the goal is to predict range shifts for many species simultaneously. In particular, the adaptive potential (based on genetic adaptations, phenotypic plasticity and behavioral adjustments for physiological responses) of local populations has been a less studied mechanism affecting species’ responses to climatic change so far. Here, we discuss and apply an alternative macroecological framework to evaluate the potential role of evolutionary rescue under climate change based on ENMs. We begin by reviewing eco‐evolutionary models that evaluate the maximum sustainable evolutionary rate under a scenario of environmental change, showing how they can be used to understand the impact of temperature change on a Neotropical anuran species, the Schneider's toad Rhinella diptycha. Then we show how to evaluate spatial patterns of species’ geographic range shift using such models, by estimating evolutionary rates at the trailing edge of species distribution estimated by ENMs and by recalculating the relative amount of total range loss under climate change. We show how different models can reduce the expected range loss predicted for the studied species by potential ecophysiological adaptations in some regions of the trailing edge predicted by ENMs. For general applications, we believe that parameters for large numbers of species and populations can be obtained from macroecological generalizations (e.g. allometric equations and ecogeographical rules), so our framework coupling ENMs with eco‐evolutionary models can be applied to achieve a more accurate picture of potential impacts from climate change and other threats to biodiversity.

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“…Pitchers et al. (2014) found no consistent pattern on how genetic covariation and intensities of selection affect the magnitude of evolutionary response. However, they did not take the multivariate aspect of the phenotype space into consideration and, since the orientation of selection alters the available variation for response, this can explain the lack of a clear pattern.…”

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confidence: 99%

The evolution of phenotypic integration: How directional selection reshapes covariation in mice

et al. 2017

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Variation is the basis for evolution, and understanding how variation can evolve is a central question in biology. In complex phenotypes, covariation plays an even more important role, as genetic associations between traits can bias and alter evolutionary change. Covariation can be shaped by complex interactions between loci, and this genetic architecture can also change during evolution. In this article, we analyzed mouse lines experimentally selected for changes in size to address the question of how multivariate covariation changes under directional selection, as well as to identify the consequences of these changes to evolution. Selected lines showed a clear restructuring of covariation in their cranium and, instead of depleting their size variation, these lines increased their magnitude of integration and the proportion of variation associated with the direction of selection. This result is compatible with recent theoretical works on the evolution of covariation that take the complexities of genetic architecture into account. This result also contradicts the traditional view of the effects of selection on available covariation and suggests a much more complex view of how populations respond to selection.

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Evolutionary rates for multivariate traits: the role of selection and genetic variation

Cited by 44 publications

References 87 publications

Social adaptation and adaptation pressure among the “drifting elderly” in China: A qualitative study in Shanghai

Social adaptation and adaptation pressure among the “drifting elderly” in China: A qualitative study in Shanghai

A macroecological approach to evolutionary rescue and adaptation to climate change

The evolution of phenotypic integration: How directional selection reshapes covariation in mice

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