• Energy Research

AbstractThe assessment of population vulnerability under climate change is crucial for planning conservation as well as for ensuring food security. Coffea canephora is, in its native habitat, an understorey tree that is mainly distributed in the lowland rainforests of tropical Africa. Also known as Robusta, its commercial value constitutes a significant revenue for many human populations in tropical countries. Comparing ecological and genomic vulnerabilities within the species’ native range can provide valuable insights about habitat loss and the species’ adaptive potential, allowing to identify genotypes that may act as a resource for varietal improvement. By applying species distribution models, we assessed ecological vulnerability as the decrease in climatic suitability under future climatic conditions from 492 occurrences. We then quantified genomic vulnerability (or risk of maladaptation) as the allelic composition change required to keep pace with predicted climate change. Genomic vulnerability was estimated from genomic environmental correlations throughout the native range. Suitable habitat was predicted to diminish to half its size by 2050, with populations near coastlines and around the Congo River being the most vulnerable. Whole‐genome sequencing revealed 165 candidate SNPs associated with climatic adaptation in C. canephora, which were located in genes involved in plant response to biotic and abiotic stressors. Genomic vulnerability was higher for populations in West Africa and in the region at the border between DRC and Uganda. Despite an overall low correlation between genomic and ecological vulnerability at broad scale, these two components of vulnerability overlap spatially in ways that may become damaging. Genomic vulnerability was estimated to be 23% higher in populations where habitat will be lost in 2050 compared to regions where habitat will remain suitable. These results highlight how ecological and genomic vulnerabilities are relevant when planning on how to cope with climate change regarding an economically important species.

ABSTRACTSpecies ranges are dynamic, experiencing expansions, contractions or shifts in response to habitat changes driven by extrinsic factors such as climate change or human activities. While existing research examines the genetic consequences of spatial processes, few studies integrate species‐specific traits to analyse how habitat changes affect co‐existing species. In this study, we address this gap by investigating how genetic diversity patterns vary among species with different traits (such as generation length, population density and dispersal) experiencing similar habitat changes. Using spatial simulations and a simpler panmictic population model, we investigate the temporal genetic diversity in refugium populations undergoing range expansion of their habitat, followed by stationary and contraction periods. By varying habitat contraction speed and species traits, we identified three distinct temporal dynamics of genetic diversity during contraction: (i) a decrease in genetic diversity, (ii) an initial increase followed by a decrease and (iii) a continuous increase throughout the contraction period. We show that genetic diversity trajectories during population decline can be predicted by comparing sampled population diversity to equilibrium values expected under expanded and contracted habitat ranges. Our study also challenges the belief that high genetic diversity in a refugium population is due to a recent and rapid habitat loss. Instead, we found contrasting effects of contraction speed on genetic diversity depending on the interaction between species‐specific traits and the dynamics of habitat change. Finally, using simulated genetic data, we found that demographic histories inferred from effective population size estimates may vary across species, even when they experience similar habitat changes.

AbstractUnderstanding vulnerabilities of plant populations to climate change could help preserve their biodiversity and reveal new elite parents for future breeding programmes. To this end, landscape genomics is a useful approach for assessing putative adaptations to future climatic conditions, especially in long‐lived species such as trees. We conducted a population genomics study of 207 Coffea canephora trees from seven forests along different climate gradients in Uganda. For this, we sequenced 323 candidate genes involved in key metabolic and defence pathways in coffee. Seventy‐one single nucleotide polymorphisms (SNPs) were found to be significantly associated with bioclimatic variables, and were thereby considered as putatively adaptive loci. These SNPs were linked to key candidate genes, including transcription factors, like DREB‐like and MYB family genes controlling plant responses to abiotic stresses, as well as other genes of organoleptic interest, such as the DXMT gene involved in caffeine biosynthesis and a putative pest repellent. These climate‐associated genetic markers were used to compute genetic offsets, predicting population responses to future climatic conditions based on local climate change forecasts. Using these measures of maladaptation to future conditions, substantial levels of genetic differentiation between present and future diversity were estimated for all populations and scenarios considered. The populations from the forests Zoka and Budongo, in the northernmost zone of Uganda, appeared to have the lowest genetic offsets under all predicted climate change patterns, while populations from Kalangala and Mabira, in the Lake Victoria region, exhibited the highest genetic offsets. The potential of these findings in terms of ex situ conservation strategies are discussed.