Periodic Reporting for period 2 - EVOWILD (Evolution in wild populations)
Berichtszeitraum: 2023-06-01 bis 2024-11-30
What is the problem/issue being addressed?
A key challenge for ecology and evolution today is to understand the impact of global environmental change on natural populations. Environmental change may have both immediate ecological response effects via plasticity in animal characteristics and properties ('phenotypic plasticity'), and more sustained evolutionary effects via genetic responses. The former may be comprised of immediate responses, but these may also be limited and may not necessarily enable a population to adapt to a changing environment. We know that the latter can also sometimes occur rapidly, but how often it does so is not yet clear, as identifying short-term genetic change in nature is difficult. A central challenge in understanding the effects of environmental change is therefore to distinguish ecological versus adaptive genetic evolutionary responses. Both are likely, but what is their relative importance, and how do they interact? And what are their implications for individual fitness, and for population dynamics?
Why important for society?
The significance of my programme lies in addressing the most substantial current challenge in ecology and evolutionary biology, the effects of current environmental change on biological systems. This work does so by
combining cutting‐edge genomic data, state-of-the-art statistical analytical tools and new conceptual advances with fundamental evolutionary theory. It combines measurements from multiple wild animal populations globally and will also inform the management of animal populations experiencing environmental change. Mammals frequently have large ecosystem impacts via herbivory or predation, as well as direct economic relevance. For the large herbivore species here, population management and hunting have substantial economic implications in their respective ranges. The meerkats, spotted hyaenas and Tasmanian devils also have high conservation and ecotourism significance for their respective countries. In all cases, understanding of populations’ responses to environmental change will have direct implications for management for the betterment and benefit of society.
What are the overall objectives?
This project will deliver a synthesis of analyses of multiple study systems, offering especially powerful insights into environmental change and evolutionary adaptation.
The work combines new genomic data, state‐of‐the‐art analytical methods and fundamental evolutionary theory with a powerful multi‐species consortium to address three linked Objectives:
1: to provide a substantive, comprehensive advance in our understanding and analysis of fitness, adaptation and social evolution;
2: to determine the effects of environmental variation on natural selection and adaptive evolutionary responses;
3: to quantify the relative impact of evolutionary vs ecological responses on phenotypes, fitness and population dynamics.
A key challenge for ecology and evolution today is to understand the impact of global environmental change on natural populations. Environmental change may have both immediate ecological response effects via plasticity in animal characteristics and properties ('phenotypic plasticity'), and more sustained evolutionary effects via genetic responses. The former may be comprised of immediate responses, but these may also be limited and may not necessarily enable a population to adapt to a changing environment. We know that the latter can also sometimes occur rapidly, but how often it does so is not yet clear, as identifying short-term genetic change in nature is difficult. A central challenge in understanding the effects of environmental change is therefore to distinguish ecological versus adaptive genetic evolutionary responses. Both are likely, but what is their relative importance, and how do they interact? And what are their implications for individual fitness, and for population dynamics?
Why important for society?
The significance of my programme lies in addressing the most substantial current challenge in ecology and evolutionary biology, the effects of current environmental change on biological systems. This work does so by
combining cutting‐edge genomic data, state-of-the-art statistical analytical tools and new conceptual advances with fundamental evolutionary theory. It combines measurements from multiple wild animal populations globally and will also inform the management of animal populations experiencing environmental change. Mammals frequently have large ecosystem impacts via herbivory or predation, as well as direct economic relevance. For the large herbivore species here, population management and hunting have substantial economic implications in their respective ranges. The meerkats, spotted hyaenas and Tasmanian devils also have high conservation and ecotourism significance for their respective countries. In all cases, understanding of populations’ responses to environmental change will have direct implications for management for the betterment and benefit of society.
What are the overall objectives?
This project will deliver a synthesis of analyses of multiple study systems, offering especially powerful insights into environmental change and evolutionary adaptation.
The work combines new genomic data, state‐of‐the‐art analytical methods and fundamental evolutionary theory with a powerful multi‐species consortium to address three linked Objectives:
1: to provide a substantive, comprehensive advance in our understanding and analysis of fitness, adaptation and social evolution;
2: to determine the effects of environmental variation on natural selection and adaptive evolutionary responses;
3: to quantify the relative impact of evolutionary vs ecological responses on phenotypes, fitness and population dynamics.
As outlined above, the project involves studying natural selection on and genetics of individual characteristics (e.g. deer antler size, kangaroo juvenile weight) across seven individually-monitored wild mammal populations. A first requirement for the study was comprehensive and error-free genome information for each sampled individual in each population, which also allows accurate pedigrees to be created. In the first half of the grant this has been achieved, allowing the project to move on to the statistical analyses that address the above objectives. Components of the project that have now been addressed include: (1) several aspects of how to actually measure individual fitness and hence natural selection in wild animal populations; (2) two analyses of the role of natural selection and evolutionary potential in the Tasmanian Devils in the face of a transmissible cancer; (3) two analyses documenting inbreeding depression and the consequences of social structure for how genetic variation varies around the landscape in spotted hyenas; (4) development of methods to harness satellite imagery to measure the food supply available to herbivores; (5) two analyses in red deer showing why, unlike all other characteristics of the deer, antler size does not appear to senesce – it is under genetic constraint, and showing that estimates of natural selection are not biased by the problem of non-random early death; (6) two software contributions that allow the user to simulate wild animal pedigrees and to document the characteristics of pedigrees; and (7) core field data collection for the Isle of Rum (Scotland) red deer population has continued throughout.
Progress beyond state of the art, Item 1: the development of the hyena genomic data set has proven that genome-wide SNP genotyping-by-sequencing, long thought by many to be impossible from non-invasive samples, can in fact be done if enough quality control steps are conducted along the way.
Progress beyond state of the art, Item 2: the successful development of the meerkat sequence-level dataset, very largely by imputation, while it follows an approach widely used in human and farm animal genomics, is the first effort we are aware of in an intensively sampled and phenotyped natural wild population and the approach is likely to be widely used in such populations in future.
Progress beyond state of the art, Item 2: the successful development of the meerkat sequence-level dataset, very largely by imputation, while it follows an approach widely used in human and farm animal genomics, is the first effort we are aware of in an intensively sampled and phenotyped natural wild population and the approach is likely to be widely used in such populations in future.