population genetics

Validating vulnerability: ground-truthing projections from genomic offsets

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How can we predict which species will adapt to climate change?

Across the globe, threatened species are already becoming impacted by the effects of climate change. While we understand many of the characteristics that make a species particularly vulnerable to climate change – those with small ranges, fragmented populations, or long lifespans, for example – predicting the capacity of a given species to respond remains a challenge. Developing analytical approaches and science-based frameworks to predict adaptive capacity in all species is a critical step forward for conservation management.

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A simplified guide to genomic vulnerability

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Predicting the future for biodiversity

Conservation biology is frequently referred to as a “crisis discipline“, a status which doesn’t appear to be changing any time soon. Like any response to a crisis, biologists of all walks of life operate under a prioritisation scheme – how can our finite resources be best utilised to save as much biodiversity as possible? This approach requires some knowledge of both current vulnerability and future threat – we need to focus our efforts on those populations and species which are most at-risk of extinction in the near (often immediate) future.

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Incomplete lineage sorting through Pachinko – a visual analogy

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Reconstructing evolutionary history

Unravelling the evolutionary history of organisms – one of the main goals of phylogenetic research – remains a challenging prospect due to a number of theoretical and analytical aspects. Particularly, trying to reconstruct evolutionary patterns based on current genetic data (the most common way phylogenetic trees are estimated) is prone to the erroneous influence of some secondary factors. One of these is referred to as ‘incomplete lineage sorting’, which can have a major effect on how phylogenetic relationships are estimated and the statistical confidence we may have around these patterns. Today, we’re going to take a look at incomplete lineage sorting (shortened to ILS for brevity herein) using a game-based analogy – a Pachinko machine. Or, if you’d rather, the same general analogy also works for those creepy clown carnival games, but I prefer the less frightening alternative.

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Managing genes in conservation and industry

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The fundamentals of population genetics

Many times in the past, we’ve discussed the importance of genetic diversity within populations as a foundation for adaptation and evolution. It includes both adaptive variation (which encompasses genetic variation directly under natural selection), as well as neutral variation (which is predominantly generated and maintained by non-selective forces such as demographic history and genetic drift). This pool of genetic variation acts as the underlying architecture for evolution by natural selection, and is a critically important component for future and ongoing evolution.

This all sounds important from an academic perspective: that population genetics can reveal a significant amount of information about the processes and outcomes of evolution and provide novel insights into concepts that have been around for ages. But how can this information be applied to real scenarios? With the ever-growing availability of massive genetic datasets for an increasing number of species, the sheer volume of information in existence that can be used is monumental.

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