Search for: All records

In today’s rapidly changing world, it is critical to examine how animal populations will respond to severe environmental change. Following events such as pollution or deforestation that cause populations to decline, extinction will occur unless populations can adapt in response to natural selection, a process called evolutionary rescue. Theory predicts that immigration can delay extinction and provide novel genetic material that can prevent inbreeding depression and facilitate adaptation. However, when potential source populations have not experienced the new environment before (i.e., are naive), immigration can counteract selection and constrain adaptation. This study evaluated the effects of immigration of naive individuals on evolutionary rescue using the red flour beetle, Tribolium castaneum, as a model system. Small populations were exposed to a challenging environment, and 3 immigration rates (0, 1, or 5 migrants per generation) were implemented with migrants from a benign environment. Following an initial decline in population size across all treatments, populations receiving no immigration gained a higher growth rate one generation earlier than those with immigration, illustrating the constraining effects of immigration on adaptation. After 7 generations, a reciprocal transplant experiment found evidence for adaptation regardless of immigration rate. Thus, while the immigration of naive individuals briefly delayed adaptation, it did not increase extinction risk or prevent adaptation following environmental change.

 

How repeatable is evolution at genomic and phenotypic scales? We studied the repeatability of evolution during 8 generations of colonization using replicated microcosm experiments with the red flour beetle, Tribolium castaneum. Based on the patterns of shared allele frequency changes that occurred in populations from the same generation or experimental location, we found adaptive evolution to be more repeatable in the introduction and establishment phases of colonization than in the spread phase, when populations expand their range. Lastly, by studying changes in allele frequencies at conserved loci, we found evidence for the theoretical prediction that range expansion reduces the efficiency of selection to purge deleterious alleles. Overall, our results increase our understanding of adaptive evolution during colonization, demonstrating that evolution can be highly repeatable while also showing that stochasticity still plays an important role.

 

Following severe environmental change that reduces mean population fitness below replacement, populations must adapt to avoid eventual extinction, a process called evolutionary rescue. Models of evolutionary rescue demonstrate that initial size, genetic variation and degree of maladaptation influence population fates. However, many models feature populations that grow without negative density dependence or with constant genetic diversity despite precipitous population decline, assumptions likely to be violated in conservation settings. We examined the simultaneous influences of density-dependent growth and erosion of genetic diversity on populations adapting to novel environmental change using stochastic, individual-based simulations. Density dependence decreased the probability of rescue and increased the probability of extinction, especially in large and initially well-adapted populations that previously have been predicted to be at low risk. Increased extinction occurred shortly following environmental change, as populations under density dependence experienced more rapid decline and reached smaller sizes. Populations that experienced evolutionary rescue lost genetic diversity through drift and adaptation, particularly under density dependence. Populations that declined to extinction entered an extinction vortex, where small size increased drift, loss of genetic diversity and the fixation of maladaptive alleles, hindered adaptation and kept populations at small densities where they were vulnerable to extinction via demographic stochasticity.

 

Despite growing calls to develop data science students’ ethical awareness and expand human-centered approaches to data science education, introductory courses in the field remain largely technical. A new interdisciplinary data science program aims to merge STEM and humanities perspectives starting at the very beginning of the data science curriculum. Existing literature suggests that humanities integration can make STEM courses more appealing to a wider range of students, including women and students of color, and enhance student learning of essential concepts and foundational reasoning skills, such as those collectively known as data acumen. Cultivating students’ data acumen requires a more inclusive vision of how the knowledge and insights generated through computational methods and statistical analysis relates to other ways of knowing. 

Rapid environmental change presents a significant challenge to the persistence of natural populations. Rapid adaptation that increases population growth, enabling populations that declined following severe environmental change to grow and avoid extinction, is called evolutionary rescue. Numerous studies have shown that evolutionary rescue can indeed prevent extinction. Here, we extend those results by considering the demographic history of populations. To evaluate how demographic history influences evolutionary rescue, we created 80 populations of red flour beetle,Tribolium castaneum, with three classes of demographic history: diverse populations that did not experience a bottleneck, and populations that experienced either an intermediate or a strong bottleneck. We subjected these populations to a new and challenging environment for six discrete generations and tracked extinction and population size. Populations that did not experience a bottleneck in their demographic history avoided extinction entirely, while more than 20% of populations that experienced an intermediate or strong bottleneck went extinct. Similarly, among the extant populations at the end of the experiment, adaptation increased the growth rate in the novel environment the most for populations that had not experienced a bottleneck in their history. Taken together, these results highlight the importance of considering the demographic history of populations to make useful and effective conservation decisions and management strategies for populations experiencing environmental change that pushes them toward extinction.

 

Climate change can affect the length and timing of seasons, which in turn can alter the time available for insects to complete their life cycles and successfully reproduce. Intraspecific hybridization between individuals from genetically distinct populations, or admixture, can boost fitness in populations experiencing environmental challenges. Admixture can particularly benefit small and isolated populations that may have high genetic load by masking deleterious alleles, thereby immediately increasing fitness, and also by increasing the genetic variation available for adaptive evolution. To evaluate the effects of admixture on populations exposed to a novel life cycle constraint, we used the red flour beetle,Tribolium castaneum, as a model system. Distinct laboratory lineages were kept isolated or mixed together to create populations containing 1–4 lineages. We then compared the fitness of admixed populations to 1‐lineage populations while subjecting them to a shortened generation time for three generations. Admixture did not influence fitness after two generations. In contrast, in the third generation, admixed populations had significantly greater fitness compared with 1‐lineage populations. The timing of the increase in fitness for the admixed populations suggests that adaptation to the novel environmental constraint occurred in the experimental populations. Our study highlights the importance of admixture for facilitating rapid adaptation to changes in seasonality, and more broadly to environmental change.

 

Species expanding into new habitats as a result of climate change or human introductions will frequently encounter resident competitors. Theoretical models suggest that such interspecific competition can alter the speed of expansion and the shape of expanding range boundaries. However, competitive interactions are rarely considered when forecasting the success or speed of expansion, in part because there has been no direct experimental evidence that competition affects either expansion speed or boundary shape. Here we demonstrate that interspecific competition alters both expansion speed and range boundary shape. Using a two-species experimental system of the flour beetlesTribolium castaneumandTribolium confusum, we show that interspecific competition dramatically slows expansion across a landscape over multiple generations. Using a parameterized stochastic model of expansion, we find that this slowdown can persist over the long term. We also find that the shape of the moving range boundary changes continuously over many generations of expansion, first steepening and then becoming shallower, due to the competitive effect of the resident and density-dependent dispersal of the invader. This dynamic boundary shape suggests that current forecasting approaches assuming a constant shape could be misleading. More broadly, our results demonstrate that interactions between competing species can play a large role during range expansions and thus should be included in models and studies that monitor, forecast, or manage expansions in natural systems.

 

When managing natural systems, the importance of recognizing the role of uncertainty has been formalized as the precautionary approach. However, it is difficult to determine the role of stochasticity in the success or failure of management because there is almost always no replication; typically, only a single observation exists for a particular site or management strategy. Yet, assessing the role of stochasticity is important for providing a strong foundation for the precautionary approach, and learning from past outcomes is critical for implementing adaptive management of species or ecosystems. In addition, adaptive management relies on being able to implement a variety of strategies in order to learn—an often difficult task in natural systems. Here, we show that there is large, stochastically driven variability in success for management treatments to control an invasive species, particularly for moderate, and more feasible, management strategies. This is exactly where the precautionary approach should be important. Even when combining management strategies, we show that moderate effort in management either fails or is highly variable in its success. This variability allows some management treatments to, on average, meet their target, even when failure is probable. Our study is an important quantitative replicated experimental test of the precautionary approach and can serve as a way to understand the variability in management outcomes in natural systems which have the potential to be more variable than our tightly controlled system.