An integrated framework to identify wildlife populations under threat from climate change

Climate change is a major threat to global biodiversity that will produce a range of new selection pressures. Understanding species responses to climate change requires an interdisciplinary perspective, combining ecological, molecular and environmental approaches. We propose an applied integrated framework to identify populations under threat from climate change based on their extent of exposure, inherent sensitivity due to adaptive and neutral genetic variation and range shift potential. We consider intraspecific vulnerability and population‐level responses, an important but often neglected conservation research priority. We demonstrate how this framework can be applied to vertebrates with limited dispersal abilities using empirical data for the bat Plecotus austriacus. We use ecological niche modelling and environmental dissimilarity analysis to locate areas at high risk of exposure to future changes. Combining outlier tests with genotype–environment association analysis, we identify potential climate‐adaptive SNPs in our genomic data set and differences in the frequency of adaptive and neutral variation between populations. We assess landscape connectivity and show that changing environmental suitability may limit the future movement of individuals, thus affecting both the ability of populations to shift their distribution to climatically suitable areas and the probability of evolutionary rescue through the spread of adaptive genetic variation among populations. Therefore, a better understanding of movement ecology and landscape connectivity is needed for predicting population persistence under climate change. Our study highlights the importance of incorporating genomic data to determine sensitivity, adaptive potential and range shift potential, instead of relying solely on exposure to guide species vulnerability assessments and conservation planning.     

Combining phylogeography and landscape genetics to infer the evolutionary history of a short-range Mediterranean relict, <Emphasis Type="Italic">Salamandra salamandra longirostris</Emphasis>

Examining historical and contemporary processes underlying current patterns of genetic variation is key to reconstruct the evolutionary history of species and implement conservation measures promoting their long-term persistence. Combining phylogeographic and landscape genetic approaches can provide valuable insights, especially in regions harboring high levels of biodiversity that are currently threatened by climate and land cover changes, like southern Iberia. We used genetic (mtDNA and microsatellites) and spatial data (climate and land cover) to infer the evolutionary history and contemporary genetic connectivity in a short-range endemic salamander subspecies, Salamandra salamandra longirostris, using a combination of ecological niche modelling, phylogeographic, and landscape genetic analyses. Ecological-based analyses support a role of the Guadalquivir River Basin as a major vicariant agent in this taxon. The lower genetic diversity and greater differentiation of peripheral populations, together with analyses of climatically stable areas throughout time, suggest the persistence of a population in the central part of the current range since the Last Inter Glacial [LIG; ~?120,000–140,000 years BP], and a micro refugium in the eastern end of the range. Habitat heterogeneity plays a major role in shaping patterns of genetic differentiation in S. s. longirostris, with forests representing key areas for its long-term persistence under scenarios of environmental change. Our study stresses the importance of maintaining population genetic connectivity in low-dispersal organisms under rapidly changing environments, and will inform management plans for the long-term survival of this evolutionarily distinct Mediterranean endemic.     

Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change

Landscape genetics seeks to determine the effect of landscape features on gene flow and genetic structure. Often, such analyses are intended to inform conservation and management. However, depending on the many factors that influence the time to reach equilibrium, genetic structure may more strongly represent past rather than contemporary landscapes. This well‐known lag between current demographic processes and population genetic structure often makes it challenging to interpret how contemporary landscapes and anthropogenic activity shape gene flow. Here, we review the theoretical framework for factors that influence time lags, summarize approaches to address this temporal disconnect in landscape genetic studies, and evaluate ways to make inferences about landscape change and its effects on species using genetic data alone or in combination with other data. Those approaches include comparing correlation of genetic structure with historical versus contemporary landscapes, using molecular markers with different rates of evolution, contrasting metrics of genetic structure and gene flow that reflect population genetic processes operating at different temporal scales, comparing historical and contemporary samples, combining genetic data with contemporary estimates of species distribution or movement, and controlling for phylogeographic history. We recommend using simulated data sets to explore time lags in genetic structure, and argue that time lags should be explicitly considered both when designing and interpreting landscape genetic studies. We conclude that the time lag problem can be exploited to strengthen inferences about recent landscape changes and to establish conservation baselines, particularly when genetic data are combined with other data.     

Evidence for evolutionary change associated with the recent range expansion of the British butterfly, Aricia agestis, in response to climate change

Poleward range expansions are widespread responses to recent climate change and are crucial for the future persistence of many species. However, evolutionary change in traits such as colonization history and habitat preference may also be necessary to track environmental change across a fragmented landscape. Understanding the likelihood and speed of such adaptive change is important in determining the rate of species extinction with ongoing climate change. We conducted an amplified fragment length polymorphism (AFLP)‐based genome scan across the recently expanded UK range of the Brown Argus butterfly, Aricia agestis, and used outlier‐based (DFDIST and BayeScan) and association‐based (Isolation‐By‐Adaptation) statistical approaches to identify signatures of evolutionary change associated with range expansion and habitat use. We present evidence for (i) limited effects of range expansion on population genetic structure and (ii) strong signatures of selection at approximately 5% AFLP loci associated with both the poleward range expansion of A. agestis and differences in habitat use across long‐established and recently colonized sites. Patterns of allele frequency variation at these candidate loci suggest that adaptation to new habitats at the range margin has involved selection on genetic variation in habitat use found across the long‐established part of the range. Our results suggest that evolutionary change is likely to affect species’ responses to climate change and that genetic variation in ecological traits across species’ distributions should be maximized to facilitate range shifts across a fragmented landscape, particularly in species that show strong associations with particular habitats.     

Pliocene intraspecific divergence and Plio‐Pleistocene range expansions within Picea likiangensis (Lijiang spruce), a dominant forest tree of the Qinghai‐Tibet Plateau

A knowledge of intraspecific divergence and range dynamics of dominant forest trees in response to past geological and climate change is of major importance to an understanding of their recent evolution and demography. Such knowledge is informative of how forests were affected by environmental factors in the past and may provide pointers to their response to future environmental change. However, genetic signatures of such historical events are often weak at individual loci due to large effective population sizes and long generation times of forest trees. This problem can be overcome by analysing genetic variation across multiple loci. We used this approach to examine intraspecific divergence and past range dynamics in the conifer Picea likiangensis, a dominant tree of forests occurring in eastern and southern areas of the Qinghai‐Tibet Plateau (QTP). We sequenced 13 nuclear loci, two mitochondrial DNA regions and three plastid (chloroplast) DNA regions in 177 individuals sampled from 22 natural populations of this species, and tested the hypothesis that its evolutionary history was markedly affected by Pliocene QTP uplifts and Quaternary climatic oscillations. Consistent with the taxonomic delimitation of the three morphologically divergent varieties examined, all individuals clustered into three genetic groups with intervariety admixture detected in regions of geographical overlap. Divergence between varieties was estimated to have occurred within the Pliocene and ecological niche modelling based on 20 ecological variables suggested that niche differentiation was high. Furthermore, modelling of population‐genetic data indicated that two of the varieties (var. rubescens and var. linzhiensis) expanded their population sizes after the largest Quaternary glaciation in the QTP, while expansion of the third variety (var. likiangensis) began prior to this, probably following the Pliocene QTP uplift. These findings point to the importance of geological and climatic changes during the Pliocene and Pleistocene as causes of intraspecific diversification and range shifts of dominant tree species in the QTP biodiversity hot spot region.     

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.     

Eco‐evolution on the edge during climate change

We urgently need to predict species responses to climate change to minimize future biodiversity loss and ensure we do not waste limited resources on ineffective conservation strategies. Currently, most predictions of species responses to climate change ignore the potential for evolution. However, evolution can alter species ecological responses, and different aspects of evolution and ecology can interact to produce complex eco‐evolutionary dynamics under climate change. Here we review how evolution could alter ecological responses to climate change on species warm and cool range margins, where evolution could be especially important. We discuss different aspects of evolution in isolation, and then synthesize results to consider how multiple evolutionary processes might interact and affect conservation strategies. On species cool range margins, the evolution of dispersal could increase range expansion rates and allow species to adapt to novel conditions in their new range. However, low genetic variation and genetic drift in small range‐front populations could also slow or halt range expansions. Together, these eco‐evolutionary effects could cause a three‐step, stop‐and‐go expansion pattern for many species. On warm range margins, isolation among populations could maintain high genetic variation that facilitates evolution to novel climates and allows species to persist longer than expected without evolution. This ‘evolutionary extinction debt’ could then prevent other species from shifting their ranges. However, as climate change increases isolation among populations, increasing dispersal mortality could select for decreased dispersal and cause rapid range contractions. Some of these eco‐evolutionary dynamics could explain why many species are not responding to climate change as predicted. We conclude by suggesting that resurveying historical studies that measured trait frequencies, the strength of selection, or heritabilities could be an efficient way to increase our eco‐evolutionary knowledge in climate change biology.     

Noninvasive sampling reveals population genetic structure in the Royle’s pika,Ochotona roylei,in the western Himalaya

Understanding population genetic structure of climate‐sensitive herbivore species is important as it provides useful insights on how shifts in environmental conditions can alter their distribution and abundance. Herbivore responses to the environment can have a strong indirect cascading effect on community structure. This is particularly important for Royle's pika (Lagomorpha: Ochotona roylei), a herbivorous talus‐dwelling species in alpine ecosystem, which forms a major prey base for many carnivores in the Himalayan arc. In this study, we used seven polymorphic microsatellite loci to detect evidence for recent changes in genetic diversity and population structure in Royle's pika across five locations sampled between 8 and 160 km apart in the western Himalaya. Using four clustering approaches, we found the presence of significant contemporary genetic structure in Royle's pika populations. The detected genetic structure could be primarily attributed to the landscape features in alpine habitat (e.g., wide lowland valleys, rivers) that may act as semipermeable barriers to gene flow and distribution of food plants, which are key determinants in spatial distribution of herbivores. Pika showed low inbreeding coefficients (F_IS) and a high level of pairwise relatedness for individuals within 1 km suggesting low dispersal abilities of talus‐dwelling pikas. We have found evidence of a recent population bottleneck, possibly due to effects of environmental disturbances (e.g., snow melting patterns or thermal stress). Our results reveal significant evidence of isolation by distance in genetic differentiation (F_ST range = 0.04–0.19). This is the first population genetics study on Royle's pika, which helps to address evolutionary consequences of climate change which are expected to significantly affect the distribution and population dynamics in this talus‐dwelling species.     

The influence of historical climate changes on Southern Ocean marine predator populations: a comparative analysis

The Southern Ocean ecosystem is undergoing rapid physical and biological changes that are likely to have profound implications for higher‐order predators. Here, we compare the long‐term, historical responses of Southern Ocean predators to climate change. We examine palaeoecological evidence for changes in the abundance and distribution of seabirds and marine mammals, and place these into context with palaeoclimate records in order to identify key environmental drivers associated with population changes. Our synthesis revealed two key factors underlying Southern Ocean predator population changes; (i) the availability of ice‐free ground for breeding and (ii) access to productive foraging grounds. The processes of glaciation and sea ice fluctuation were key; the distributions and abundances of elephant seals, snow petrels, gentoo, chinstrap and Adélie penguins all responded strongly to the emergence of new breeding habitat coincident with deglaciation and reductions in sea ice. Access to productive foraging grounds was another limiting factor, with snow petrels, king and emperor penguins all affected by reduced prey availability in the past. Several species were isolated in glacial refugia and there is evidence that refuge populations were supported by polynyas. While the underlying drivers of population change were similar across most Southern Ocean predators, the individual responses of species to environmental change varied because of species specific factors such as dispersal ability and environmental sensitivity. Such interspecific differences are likely to affect the future climate change responses of Southern Ocean marine predators and should be considered in conservation plans. Comparative palaeoecological studies are a valuable source of long‐term data on species’ responses to environmental change that can provide important insights into future climate change responses. This synthesis highlights the importance of protecting productive foraging grounds proximate to breeding locations, as well as the potential role of polynyas as future Southern Ocean refugia.     

Phylogenetic approaches for studying diversification

Estimating rates of speciation and extinction, and understanding how and why they vary over evolutionary time, geographical space and species groups, is a key to understanding how ecological and evolutionary processes generate biological diversity. Such inferences will increasingly benefit from phylogenetic approaches given the ever‐accelerating rates of genetic sequencing. In the last few years, models designed to understand diversification from phylogenetic data have advanced significantly. Here, I review these approaches and what they have revealed about diversification in the natural world. I focus on key distinctions between different models, and I clarify the conclusions that can be drawn from each model. I identify promising areas for future research. A major challenge ahead is to develop models that more explicitly take into account ecology, in particular the interaction of species with each other and with their environment. This will not only improve our understanding of diversification; it will also present a new perspective to the use of phylogenies in community ecology, the science of interaction networks and conservation biology, and might shift the current focus in ecology on equilibrium biodiversity theories to non‐equilibrium theories recognising the crucial role of history.     

A life‐history perspective on the demographic drivers of structured population dynamics in changing environments

Current understanding of life‐history evolution and how demographic parameters contribute to population dynamics across species is largely based on assumptions of either constant environments or stationary environmental variation. Meanwhile, species are faced with non‐stationary environmental conditions (changing mean, variance, or both) created by climate and landscape change. To close the gap between contemporary reality and demographic theory, we develop a set of transient life table response experiments (LTREs) for decomposing realised population growth rates into contributions from specific vital rates and components of population structure. Using transient LTREs in a theoretical framework, we reveal that established concepts in population biology will require revision because of reliance on approaches that do not address the influence of unstable population structure on population growth and mean fitness. Going forward, transient LTREs will enhance understanding of demography and improve the explanatory power of models used to understand ecological and evolutionary dynamics.     

Genomics of natural history collections for understanding evolution in the wild

A long‐standing question in biology is how organisms change through time and space in response to their environment. This knowledge is of particular relevance to predicting how organisms might respond to future environmental changes caused by human‐induced global change. Usually researchers make inferences about past events based on an understanding of current static genetic patterns, but these are limited in their capacity to inform on underlying past processes. Natural history collections (NHCs) represent a unique and critical source of information to provide temporally deep and spatially broad time‐series of samples. By using NHC samples, researchers can directly observe genetic changes over time and space and link those changes with specific ecological/evolutionary events. Until recently, such genetic studies were hindered by the intrinsic challenges of NHC samples (i.e. low yield of highly fragmented DNA). However, recent methodological and technological developments have revolutionized the possibilities in the novel field of NHC genomics. In this Special Feature, we compile a range of studies spanning from methodological aspects to particular case studies which demonstrate the enormous potential of NHC samples for accessing large genomic data sets from the past to advance our knowledge on how populations and species respond to global change at multiple spatial–temporal scales. We also highlight possible limitations, recommendations and a few opportunities for future researchers aiming to study NHC genomics.     

Integrated modeling predicts shifts in waterbird population dynamics under climate change

Climate change has been identified as one of the most important drivers of wildlife population dynamics. The in‐depth knowledge of the complex relationships between climate and population sizes through density dependent demographic processes is important for understanding and predicting population shifts under climate change, which requires integrated population models (IPMs) that unify the analyses of demography and abundance data. In this study we developed an IPM based on Gaussian approximation to dynamic N‐mixture models for large scale population data. We then analyzed four decades (1972–2013) of mallard Anas platyrhynchos breeding population survey, band‐recovery and climate data covering a large spatial extent from North American prairies through boreal habitat to Alaska. We aimed to test the hypothesis that climate change will cause shifts in population dynamics if climatic effects on demographic parameters that have substantial contribution to population growth vary spatially. More specifically, we examined the spatial variation of climatic effects on density dependent population demography, identified the key demographic parameters that are influential to population growth, and forecasted population responses to climate change. Our results revealed that recruitment, which explained more variance of population growth than survival, was sensitive to the temporal variation of precipitation in the southern portion of the study area but not in the north. Survival, by contrast, was insensitive to climatic variation. We then forecasted a decrease in mallard breeding population density in the south and an increase in the northwestern portion of the study area, indicating potential shifts in population dynamics under future climate change. Our results implied that different strategies need to be considered across regions to conserve waterfowl populations in the face of climate change. Our modelling approach can be adapted for other species and thus has wide application to understanding and predicting population dynamics in the presence of global change.     

Spatial and temporal genetic dynamics of the grasshopper Oedaleus decorus revealed by museum genomics

Analyzing genetic variation through time and space is important to identify key evolutionary and ecological processes in populations. However, using contemporary genetic data to infer the dynamics of genetic diversity may be at risk of a bias, as inferences are performed from a set of extant populations, setting aside unavailable, rare, or now extinct lineages. Here, we took advantage of new developments in next‐generation sequencing to analyze the spatial and temporal genetic dynamics of the grasshopper Oedaleus decorus, a steppic Southwestern‐Palearctic species. We applied a recently developed hybridization capture (hyRAD) protocol that allows retrieving orthologous sequences even from degraded DNA characteristic of museum specimens. We identified single nucleotide polymorphisms in 68 historical and 51 modern samples in order to (i) unravel the spatial genetic structure across part of the species distribution and (ii) assess the loss of genetic diversity over the past century in Swiss populations. Our results revealed (i) the presence of three potential glacial refugia spread across the European continent and converging spatially in the Alpine area. In addition, and despite a limited population sample size, our results indicate (ii) a loss of allelic richness in contemporary Swiss populations compared to historical populations, whereas levels of expected heterozygosities were not significantly different. This observation is compatible with an increase in the bottleneck magnitude experienced by central European populations of O. decorus following human‐mediated land‐use change impacting steppic habitats. Our results confirm that application of hyRAD to museum samples produces valuable information to study genetic processes across time and space.     

Pleistocene climatic changes drive diversification across a tropical savanna

Spatial responses of species to past climate change depend on both intrinsic traits (climatic niche breadth, dispersal rates) and the scale of climatic fluctuations across the landscape. New capabilities in generating and analysing population genomic data, along with spatial modelling, have unleashed our capacity to infer how past climate changes have shaped populations, and by extension, complex communities. Combining these approaches, we uncover lineage diversity across four codistributed lizards from the Australian Monsoonal Tropics and explore how varying climatic tolerances interact with regional climate history to generate common vs. disparate responses to late Pleistocene change. We find more divergent spatial structuring and temporal demographic responses in the drier Kimberley region compared to the more mesic and consistently suitable Top End. We hypothesize that, in general, the effects of species’ traits on sensitivity to climate fluctuation will be more evident in climatically marginal regions. If true, this points to the need in climatically marginal areas to craft more species‐(or trait)‐specific strategies for persistence under future climate change.     

Plant adaptation to climate change—Where are we?

Climate change poses critical challenges for population persistence in natural communities, for agriculture and environmental sustainability, and for food security. In this review, we discuss recent progress in climatic adaptation in plants. We evaluate whether climate change exerts novel selection and disrupts local adaptation, whether gene flow can facilitate adaptive responses to climate change, and whether adaptive phenotypic plasticity could sustain populations in the short term. Furthermore, we discuss how climate change influences species interactions. Through a more in‐depth understanding of these eco‐evolutionary dynamics, we will increase our capacity to predict the adaptive potential of plants under climate change. In addition, we review studies that dissect the genetic basis of plant adaptation to climate change. Finally, we highlight key research gaps, ranging from validating gene function to elucidating molecular mechanisms, expanding research systems from model species to other natural species, testing the fitness consequences of alleles in natural environments, and designing multifactorial studies that more closely reflect the complex and interactive effects of multiple climate change factors. By leveraging interdisciplinary tools (e.g., cutting‐edge omics toolkits, novel ecological strategies, newly developed genome editing technology), researchers can more accurately predict the probability that species can persist through this rapid and intense period of environmental change, as well as cultivate crops to withstand climate change, and conserve biodiversity in natural systems.     

An overview of the utility of population simulation software in molecular ecology

Stochastic simulation software that simultaneously model genetic, population and environmental processes can inform many topics in molecular ecology. These include forecasting species and community response to environmental change, inferring dispersal ecology, revealing cryptic mating, quantifying past population dynamics, assessing in situ management options and monitoring neutral and adaptive biodiversity change. Advances in population demographic–genetic simulation software, especially with respect to individual life history, landscapes and genetic processes, are transforming and expanding the ways that molecular data can be used. The aim of this review is to explain the roles that such software can play in molecular ecology studies (whether as a principal component or a supporting function) so that researchers can decide whether, when and precisely how simulations can be incorporated into their work. First, I use seven case studies to demonstrate how simulations are employed, their specific advantage/necessity and what alternative or complementary (nonsimulation) approaches are available. I also explain how simulations can be integrated with existing spatial, environmental, historical and genetic data sets. I next describe simulation features that may be of interest to molecular ecologists, such as spatial and behavioural considerations and species' interactions, to provide guidance on how particular simulation capabilities can serve particular needs. Lastly, I discuss the prospect of simulation software in emerging challenges (climate change, biodiversity monitoring, population exploitation) and opportunities (genomics, ancient DNA), in order to emphasize that the scope of simulation‐based work is expanding. I also suggest practical considerations, priorities and elements of best practice. This should accelerate the uptake of simulation approaches and firmly embed them as a versatile tool in the molecular ecologist's toolbox.     

Synergistic effects of climate and land‐use change influence broad‐scale avian population declines

Climate and land‐use changes are expected to be the primary drivers of future global biodiversity loss. Although theory suggests that these factors impact species synergistically, past studies have either focused on only one in isolation or have substituted space for time, which often results in confounding between drivers. Tests of synergistic effects require congruent time series on animal populations, climate change and land‐use change replicated across landscapes that span the gradient of correlations between the drivers of change. Using a unique time series of high‐resolution climate (measured as temperature and precipitation) and land‐use change (measured as forest change) data, we show that these drivers of global change act synergistically to influence forest bird population declines over 29 years in the Pacific Northwest of the United States. Nearly half of the species examined had declined over this time. Populations declined most in response to loss of early seral and mature forest, with responses to loss of early seral forest amplified in landscapes that had warmed over time. In addition, birds declined more in response to loss of mature forest in areas that had dried over time. Climate change did not appear to impact populations in landscapes with limited habitat loss, except when those landscapes were initially warmer than the average landscape. Our results provide some of the first empirical evidence of synergistic effects of climate and land‐use change on animal population dynamics, suggesting accelerated loss of biodiversity in areas under pressure from multiple global change drivers. Furthermore, our findings suggest strong spatial variability in the impacts of climate change and highlight the need for future studies to evaluate multiple drivers simultaneously to avoid potential misattribution of effects.     

Genomic signals reveal past evolutionary dynamics of Quercus schottkyana and its response to future climate change

Understanding the past and future evolutionary dynamics of dominant species in a forest is important for guiding decisions for biodiversity conservation, forest management, and vegetation restoration. This study used Quercus schottkyana, a dominant tree in subtropical evergreen broad-leaved forests in southwest China, to investigate the influences of past environmental fluctuations and future changes in climate on the dynamics of tree demographics. Genomic data were obtained for 133 samples of Q. schottkyana from 22 populations using double-digest genotyping by sequencing. The single-nucleotide polymorphisms in the genome showed a uniform distribution. Based on principal component analysis and Admixture analysis, two distinct lineages and one mixed group were identified that corresponded to their geographical distribution. Approximate Bayesian computation analyses provided evidence that the divergence among Q. schottkyana populations could be driven by the collision between the Asian and Indian plates during the Miocene, and that climatic fluctuations in the late Pleistocene led to the introgression. The analysis of genotype-environment relationships showed that annual precipitation and geographic distance were associated with spatial genetic variation. Populations of Q. schottkyana in the northern area of the Jinsha River basin were predicted to be the most vulnerable to future climate change. To increase genetic diversity in the northern Jinsha River basin and to buffer threats from future climate change, managers could use a mixture of local and alien seeds during forest restoration and management. This case study can promote further investigations into assessing how past and future climate change impacts genetic divergence and local adaptation of trees in forests.     

Comparative phylogeography of Aedes mosquitoes and the role of past climatic change for evolution within Africa

The study of demographic processes involved in species diversification and evolution ultimately provides explanations for the complex distribution of biodiversity on earth, indicates regions important for the maintenance and generation of biodiversity, and identifies biological units important for conservation or medical consequence. African and forest biota have both received relatively little attention with regard to understanding their diversification, although one possible mechanism is that this has been driven by historical climate change. To investigate this, we implemented a standard population genetics approach along with Approximate Bayesian Computation, using sequence data from two exon‐primed intron‐crossing (EPIC) nuclear loci and mitochondrial cytochrome oxidase subunit I, to investigate the evolutionary history of five medically important and inherently forest dependent mosquito species of the genus Aedes. By testing different demographic hypotheses, we show that Aedes bromeliae and Aedes lilii fit the same model of lineage diversification, admixture, expansion, and recent population structure previously inferred for Aedes aegypti. In addition, analyses of population structure show that Aedes africanus has undergone lineage diversification and expansion while Aedes hansfordi has been impacted by population expansion within Uganda. This congruence in evolutionary history is likely to relate to historical climate‐driven habitat change within Africa during the late Pleistocene and Holocene epoch. We find differences in the population structure of mosquitoes from Tanzania and Uganda compared to Benin and Uganda which could relate to differences in the historical connectivity of forests across the continent. Our findings emphasize the importance of recent climate change in the evolution of African forest biota.