| 1. |
- Bonnet, Timothee, et al.
(author)
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Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals
- 2022
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In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 376:6596, s. 1012-1016
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Journal article (peer-reviewed)abstract
- The rate of adaptive evolution, the contribution of selection to genetic changes that increase mean fitness, is determined by the additive genetic variance in individual relative fitness. To date, there are few robust estimates of this parameter for natural populations, and it is therefore unclear whether adaptive evolution can play a meaningful role in short-term population dynamics. We developed and applied quantitative genetic methods to long-term datasets from 19 wild bird and mammal populations and found that, while estimates vary between populations, additive genetic variance in relative fitness is often substantial and, on average, twice that of previous estimates. We show that these rates of contemporary adaptive evolution can affect population dynamics and hence that natural selection has the potential to partly mitigate effects of current environmental change.
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| 2. |
- Culina, Antica, et al.
(author)
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Connecting the data landscape of long-term ecological studies : The SPI-Birds data hub
- 2021
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In: Journal of Animal Ecology. - : John Wiley & Sons. - 0021-8790 .- 1365-2656. ; 90:9, s. 2147-2160
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Journal article (peer-reviewed)abstract
- The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database ()-a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration.
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| 3. |
- Spagopoulou, Foteini, et al.
(author)
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Silver-spoon upbringing improves early-life fitness but promotes reproductive ageing in a wild bird
- 2020
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In: Ecology Letters. - : Wiley. - 1461-023X .- 1461-0248. ; 23:6, s. 994-1002
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Journal article (peer-reviewed)abstract
- Early-life conditions can have long-lasting effects and organisms that experience a poor start in life are often expected to age at a faster rate. Alternatively, individuals raised in high-quality environments can overinvest in early-reproduction resulting in rapid ageing. Here we use a long-term experimental manipulation of early-life conditions in a natural population of collared flycatchers (Ficedula albicollis), to show that females raised in a low-competition environment (artificially reduced broods) have higher early-life reproduction but lower late-life reproduction than females raised in high-competition environment (artificially increased broods). Reproductive success of high-competition females peaked in late-life, when low-competition females were already in steep reproductive decline and suffered from a higher mortality rate. Our results demonstrate that 'silver-spoon' natal conditions increase female early-life performance at the cost of faster reproductive ageing and increased late-life mortality. These findings demonstrate experimentally that natal environment shapes individual variation in reproductive and actuarial ageing in nature.
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| 4. |
- Urban, Mark C., et al.
(author)
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When and how can we predict adaptive responses to climate change?
- 2024
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In: Evolution Letters. - : Oxford University Press. - 2056-3744. ; 8:1, s. 172-187
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Journal article (peer-reviewed)abstract
- Predicting if, when, and how populations can adapt to climate change constitutes one of the greatest challenges in science today. Here, we build from contributions to the special issue on evolutionary adaptation to climate change, a survey of its authors, and recent literature to explore the limits and opportunities for predicting adaptive responses to climate change. We outline what might be predictable now, in the future, and perhaps never even with our best efforts. More accurate predictions are expected for traits characterized by a well-understood mapping between genotypes and phenotypes and traits experiencing strong, direct selection due to climate change. A meta-analysis revealed an overall moderate trait heritability and evolvability in studies performed under future climate conditions but indicated no significant change between current and future climate conditions, suggesting neither more nor less genetic variation for adapting to future climates. Predicting population persistence and evolutionary rescue remains uncertain, especially for the many species without sufficient ecological data. Still, when polled, authors contributing to this special issue were relatively optimistic about our ability to predict future evolutionary responses to climate change. Predictions will improve as we expand efforts to understand diverse organisms, their ecology, and their adaptive potential. Advancements in functional genomic resources, especially their extension to non-model species and the union of evolutionary experiments and "omics," should also enhance predictions. Although predicting evolutionary responses to climate change remains challenging, even small advances will reduce the substantial uncertainties surrounding future evolutionary responses to climate change. Preventing biological impacts from climate change will require accurate predictions about which species and ecosystems are most at risk and how best to protect them. Despite some progress, most predictive efforts still omit the potential for evolution to mediate climate change impacts. Here, we evaluate what is predictable now, in the future, and likely never based on recent literature, a survey of authors, and authors' contributions to a special issue on climate change evolution. Evidence indicates a growing ability to predict at least some components underlying evolutionary dynamics. For instance, the direct effects of climate change often alter natural selection regimes that could elicit evolutionary responses assuming sufficient additive genetic variation. We found no evidence for an increase or decrease in evolvability under future climate conditions, but we did find an overall moderate level of evolvability. However, the specific genetics underlying potential adaptive changes are still a "black box" that remains difficult to predict. We not only discuss the opportunities afforded by new genomic techniques to elucidate these genetic black boxes but also caution that the costs and limitations of such techniques for many species might not warrant their general practicality. We highlight further progress and challenges in predicting gene flow and population persistence, both of which can facilitate evolutionary rescue. We finish by listing ten activities that are needed to accelerate future progress in predicting climate change evolution. Despite the many complexities, we are relatively optimistic that evolutionary responses to climate change are becoming more accurate through time, especially assuming a more focused effort to fill key knowledge gaps in the coming years.
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