Immigration delays but does not prevent adaptation following environmental change: experimental evidence.

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 density dependence, genetic erosion and the extinction vortex impact evolutionary rescue.

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.

Interspecific competition slows range expansion and shapes range boundaries.

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 beetles Tribolium castaneum and Tribolium 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.

Integrative modelling reveals mechanisms linking productivity and plant species richness.

How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology. Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns. Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models. These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis, is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.

Success and failure of ecological management is highly variable in an experimental test.

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.

Initial abundance and stochasticity influence competitive outcome in communities.

Predicting competitive outcomes in communities frequently involves inferences based on deterministic population models since these provide clear criteria for exclusion (e.g. R* rule) or long-term coexistence (e.g. mutual invasibility). However, incorporating stochasticity into population- or community-level processes into models is necessary if the goal is to explain variation in natural systems, which are inherently stochastic. Similarly, in systems with demographic or environmental stochasticity, weaker competitors have the potential to exclude superior competitors, contributing to what is known as 'competitive indeterminacy'. The importance of such effects for natural communities is unknown, in part because it is difficult to demonstrate that multiple forms of stochasticity are present in these communities. Moreover, the effects of multiple forms of stochasticity on competitive outcomes are largely untested, even in theory. Here, we address these issues by examining the role of stochasticity in replicated communities of flour beetles (Tribolium sp.). To do so, we developed a set of two-species stochastic Ricker models incorporating four distinct forms of stochasticity: environmental stochasticity, demographic stochasticity, demographic heterogeneity and stochastic sex determination. By fitting models to experimental data, and simulating fit models to examine long- term behaviour, we found that both the duration of transient coexistence and the degree of competitive indeterminacy were sensitive to the forms of stochasticity included in our models. These findings suggest the current estimates of extinction risk, coexistence and time until competitive exclusion in communities may not be accurate when based on models that exclude relevant forms of stochasticity.

Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties.

Soil nitrogen (N) availability is critical for grassland functioning. However, human activities have increased the supply of biologically limiting nutrients, and changed the density and identity of mammalian herbivores. These anthropogenic changes may alter net soil N mineralization (soil net Nmin ), that is, the net balance between N mineralization and immobilization, which could severely impact grassland structure and functioning. Yet, to date, little is known about how fertilization and herbivore removal individually, or jointly, affect soil net Nmin across a wide range of grasslands that vary in soil and climatic properties. Here we collected data from 22 grasslands on five continents, all part of a globally replicated experiment, to assess how fertilization and herbivore removal affected potential (laboratory-based) and realized (field-based) soil net Nmin . Herbivore removal in the absence of fertilization did not alter potential and realized soil net Nmin . However, fertilization alone and in combination with herbivore removal consistently increased potential soil net Nmin. Realized soil net Nmin , in contrast, significantly decreased in fertilized plots where herbivores were removed. Treatment effects on potential and realized soil net Nmin were contingent on site-specific soil and climatic properties. Fertilization effects on potential soil net Nmin were larger at sites with higher mean annual precipitation (MAP) and temperature of the wettest quarter (T.q.wet). Reciprocally, realized soil net Nmin declined most strongly with fertilization and herbivore removal at sites with lower MAP and higher T.q.wet. In summary, our findings show that anthropogenic nutrient enrichment, herbivore exclusion and alterations in future climatic conditions can negatively impact soil net Nmin across global grasslands under realistic field conditions. This is an important context-dependent knowledge for grassland management worldwide.

Community context and dispersal stochasticity drive variation in spatial spread.

Dispersal is a key process in shaping species spatial distributions. Species interactions and variation in dispersal probabilities may jointly influence species spatial dynamics. However, many studies examine dispersal as a neutral process, independent of community context or intraspecific variation in dispersal behaviour. Here, we use controlled, replicated communities of two Tribolium species (T. castaneum and T. confusum) to examine how intraspecific variation in dispersal behaviour and community context influence dispersal dynamics in simple experimental landscapes composed of homogeneous habitat patches. We found considerable individual-level variation in dispersal probability that was unrelated to body size variation. Further, the context of dispersal mattered, as T. castaneum dispersal was reduced in two-species communities, while T. confusum dispersal was unaffected by community composition. Incorporating individual-level variation into a two-species stochastic spatial Ricker model, we provide evidence that individual-level variability in dispersal behaviour results in more variable spatial spread than assuming individuals have the same dispersal probability. Further, interspecific competition resulted in more variable spatial spread. The variability in spatial spread observed in our tightly controlled and replicated experimental system and in our stochastic model simulations points to potential fundamental limitations in forecasting species shifting ranges without considering potential interspecific interactions and demographic variability in dispersal behaviour.

Eutrophication weakens stabilizing effects of diversity in natural grasslands.

Studies of experimental grassland communities have demonstrated that plant diversity can stabilize productivity through species asynchrony, in which decreases in the biomass of some species are compensated for by increases in others. However, it remains unknown whether these findings are relevant to natural ecosystems, especially those for which species diversity is threatened by anthropogenic global change. Here we analyse diversity-stability relationships from 41 grasslands on five continents and examine how these relationships are affected by chronic fertilization, one of the strongest drivers of species loss globally. Unmanipulated communities with more species had greater species asynchrony, resulting in more stable biomass production, generalizing a result from biodiversity experiments to real-world grasslands. However, fertilization weakened the positive effect of diversity on stability. Contrary to expectations, this was not due to species loss after eutrophication but rather to an increase in the temporal variation of productivity in combination with a decrease in species asynchrony in diverse communities. Our results demonstrate separate and synergistic effects of diversity and eutrophication on stability, emphasizing the need to understand how drivers of global change interactively affect the reliable provisioning of ecosystem services in real-world systems.

Herbivores and nutrients control grassland plant diversity via light limitation.

Human alterations to nutrient cycles and herbivore communities are affecting global biodiversity dramatically. Ecological theory predicts these changes should be strongly counteractive: nutrient addition drives plant species loss through intensified competition for light, whereas herbivores prevent competitive exclusion by increasing ground-level light, particularly in productive systems. Here we use experimental data spanning a globally relevant range of conditions to test the hypothesis that herbaceous plant species losses caused by eutrophication may be offset by increased light availability due to herbivory. This experiment, replicated in 40 grasslands on 6 continents, demonstrates that nutrients and herbivores can serve as counteracting forces to control local plant diversity through light limitation, independent of site productivity, soil nitrogen, herbivore type and climate. Nutrient addition consistently reduced local diversity through light limitation, and herbivory rescued diversity at sites where it alleviated light limitation. Thus, species loss from anthropogenic eutrophication can be ameliorated in grasslands where herbivory increases ground-level light.

Stochastic processes drive rapid genomic divergence during experimental range expansions.

Range expansions are crucibles for rapid evolution, acting via both selective and neutral mechanisms. While selection on traits such as dispersal and fecundity may increase expansion speed, neutral mechanisms arising from repeated bottlenecks and genetic drift in edge populations (i.e. gene surfing) could slow spread or make it less predictable. Thus, it is necessary to disentangle the effects of selection from neutral mechanisms to robustly predict expansion dynamics. This is difficult to do with expansions in nature, as replicated expansions are required to distinguish selective and neutral processes in the genome. Using replicated microcosms of the red flour beetle ( Tribolium castaneum), we identify a robust signature of stochastic, neutral mechanisms in genomic changes arising over only eight generations of expansion and assess the role of standing variation and de novo mutations in driving these changes. Average genetic diversity was reduced within edge populations, but with substantial among-replicate variability in the changes at specific genomic windows. Such variability in genomic changes is consistent with a large role for stochastic, neutral processes. This increased genomic divergence among populations was mirrored by heightened variation in population size and expansion speed, suggesting that stochastic variation in the genome could increase unpredictability of range expansions.

When can competition and dispersal lead to checkerboard distributions?

Checkerboard distributions-mutually exclusive species co-occurrences-are a common observation in community ecology and biogeography. While the underlying causes of checkerboard distributions have remained elusive, a long-standing argument is that they are representative of strong competitive interactions and/or dispersal limitation. We explore this using a stochastic two-patch metacommunity model combined with an experimental two-patch system of competing Tribolium species, quantifying checkerboard distributions using the abundance-based index Ast . We find that maintenance of checkerboard distributions is possible in a limited parameter space consisting of low dispersal rates, low population growth rates and high interspecific competition. Checkerboards were not maintained in experimental metacommunities. Our model, parameterized using independent data, echoed this finding, providing a clear link between model and experiment, and suggested that only small regions of parameter space would allow for checkerboard distributions between patches with equally hospitable environments. These findings may provide insight into when interspecific competition and dispersal limitation would promote checkerboard distributions.

Experimental investigation of alternative transmission functions: Quantitative evidence for the importance of nonlinear transmission dynamics in host-parasite systems.

Understanding pathogen transmission is crucial for predicting and managing disease. Nonetheless, experimental comparisons of alternative functional forms of transmission remain rare, and those experiments that are conducted are often not designed to test the full range of possible forms. To differentiate among 10 candidate transmission functions, we used a novel experimental design in which we independently varied four factors-duration of exposure, numbers of parasites, numbers of hosts and parasite density-in laboratory infection experiments. We used interactions between amphibian hosts and trematode parasites as a model system and all candidate models incorporated parasite depletion. An additional manipulation involving anaesthesia addressed the effects of host behaviour on transmission form. Across all experiments, nonlinear transmission forms involving either a power law or a negative binomial function were the best-fitting models and consistently outperformed the linear density-dependent and density-independent functions. By testing previously published data for two other host-macroparasite systems, we also found support for the same nonlinear transmission forms. Although manipulations of parasite density are common in transmission studies, the comprehensive set of variables tested in our experiments revealed that variation in density alone was least likely to differentiate among competing transmission functions. Across host-pathogen systems, nonlinear functions may often more accurately represent transmission dynamics and thus provide more realistic predictions for infection.

Three types of rescue can avert extinction in a changing environment.

Setting aside high-quality large areas of habitat to protect threatened populations is becoming increasingly difficult as humans fragment and degrade the environment. Biologists and managers therefore must determine the best way to shepherd small populations through the dual challenges of reductions in both the number of individuals and genetic variability. By bringing in additional individuals, threatened populations can be increased in size (demographic rescue) or provided with variation to facilitate adaptation and reduce inbreeding (genetic rescue). The relative strengths of demographic and genetic rescue for reducing extinction and increasing growth of threatened populations are untested, and which type of rescue is effective may vary with population size. Using the flour beetle (Tribolium castaneum) in a microcosm experiment, we disentangled the genetic and demographic components of rescue, and compared them with adaptation from standing genetic variation (evolutionary rescue in the strictest sense) using 244 experimental populations founded at either a smaller (50 individuals) or larger (150 individuals) size. Both types of rescue reduced extinction, and those effects were additive. Over the course of six generations, genetic rescue increased population sizes and intrinsic fitness substantially. Both large and small populations showed evidence of being able to adapt from standing genetic variation. Our results support the practice of genetic rescue in facilitating adaptation and reducing inbreeding depression, and suggest that demographic rescue alone may suffice in larger populations even if only moderately inbred individuals are available for addition.

Genetic and demographic founder effects have long-term fitness consequences for colonising populations.

Colonisation is a fundamental ecological and evolutionary process that drives the distribution and abundance of organisms. The initial ability of colonists to establish is determined largely by the number of founders and their genetic background. We explore the importance of these demographic and genetic properties for longer term persistence and adaptation of populations colonising a novel habitat using experimental populations of Tribolium castaneum. We introduced individuals from three genetic backgrounds (inbred - outbred) into a novel environment at three founding sizes (2-32), and tracked populations for seven generations. Inbreeding had negative effects, whereas outbreeding generally had positive effects on establishment, population growth and long-term persistence. Severe bottlenecks due to small founding sizes reduced genetic variation and fitness but did not prevent adaptation if the founders originated from genetically diverse populations. Thus, we find important and largely independent roles for both demographic and genetic processes in driving colonisation success.

Short- and long-term effects of habitat fragmentation differ but are predicted by response to the matrix.

Habitat loss and fragmentation are major threats to biodiversity and ecosystem processes. Our current understanding of the impacts of habitat loss and fragmentation is based largely on studies that focus on either short-term or long-term responses. Short-term responses are often used to predict long-term responses and make management decisions. The lack of studies comparing short- and long-term responses to fragmentation means we do not adequately understand when and how well short-term responses can be extrapolated to predict long-term responses, and when or why they cannot. To address this gap, we used data from one of the world's longest-running fragmentation experiments, The Wog Wog Habitat Fragmentation Experiment. Using data for carabid beetles, we found that responses in the long term (more than 22 yr post-fragmentation ≈22 generations) often contrasted markedly with those in the short term (5 yr post-fragmentation). The total abundance of all carabids, species richness and the occurrence of six species declined in the short term in the fragments but increased over the long term. The occurrence of three species declined initially and continued to decline, whilst another species was positively affected initially but decreased in the long term. Species' responses to the matrix that surrounds the fragments strongly predicted both the direction (increase/decline in occurrence) and magnitude of their responses to fragmentation. Additionally, species' responses to the matrix were somewhat predicted by their preferences for different types of native habitat (open vs. shaded). Our study highlights the degree of the matrix's influence in fragmented landscapes, and how this influence can change over time. We urge caution in using short-term responses to forecast long-term responses in cases where the matrix (1) impacts species' responses to fragmentation (by isolating them, creating new habitat or altering fragment habitat) and (2) is likely to change through time.

Linking metacommunity paradigms to spatial coexistence mechanisms.

Four metacommunity paradigms-usually called neutral, species sorting, mass effects, and patch dynamics, respectively-are widely used for empirical and theoretical studies of spatial community dynamics. The paradigm framework highlights key ecological mechanisms operating in metacommunities, such as dispersal limitation, competition-colonization tradeoffs, or species equivalencies. However, differences in coexistence mechanisms between the paradigms and in situations with combined influences of multiple paradigms are not well understood. Here, we create a common model for competitive metacommunities, with unique parameterizations for each metacommunity paradigm and for scenarios with multiple paradigms operating simultaneously. We derive analytical expressions for the strength of Chesson's spatial coexistence mechanisms and quantify these for each paradigm via simulation. For our model, fitness-density covariance, a concentration effect measuring the importance of intraspecific aggregation of individuals, is the dominant coexistence mechanism in all three niche-based metacommunity paradigms. Increased dispersal between patches erodes intraspecific aggregation, leading to lower coexistence strength in the mass effects paradigm compared to species sorting. Our analysis demonstrates the potential importance of aggregation of individuals (fitness-density covariance) over co-variation in abiotic environments and competition between species (the storage effect), as fitness-density covariance can be stronger than the storage effect and is the sole stabilizing mechanism in the patch dynamics paradigm. As expected, stable coexistence does not occur in the neutral paradigm, which requires species to be equal and emphasizes the role of stochasticity. We show that stochasticity also plays an important role in niche-structured metacommunities by altering coexistence strength. We conclude that Chesson's spatial coexistence mechanisms provide a flexible framework for comparing metacommunities of varying complexity.

The roles of demography and genetics in the early stages of colonization.

Colonization success increases with the size of the founding group. Both demographic and genetic factors underlie this relationship, yet because genetic diversity normally increases with numbers of individuals, their relative importance remains unclear. Furthermore, their influence may depend on the environment and may change as colonization progresses from establishment through population growth and then dispersal. We tested the roles of genetics, demography and environment in the founding of Tribolium castaneum populations. Using three genetic backgrounds (inbred to outbred), we released individuals of four founding sizes (2-32) into two environments (natal and novel), and measured establishment success, initial population growth and dispersal. Establishment increased with founding size, whereas population growth was shaped by founding size, genetic background and environment. Population growth was depressed by inbreeding at small founding sizes, but growth rates were similar across genetic backgrounds at large founding size, an interaction indicating that the magnitude of the genetic effects depends upon founding population size. Dispersal rates increased with genetic diversity. These results suggest that numbers of individuals may drive initial establishment, but that subsequent population growth and spread, even in the first generation of colonization, can be driven by genetic processes, including both reduced growth owing to inbreeding depression, and increased dispersal with increased genetic diversity.

Extinction risk depends strongly on factors contributing to stochasticity.

Extinction risk in natural populations depends on stochastic factors that affect individuals, and is estimated by incorporating such factors into stochastic models. Stochasticity can be divided into four categories, which include the probabilistic nature of birth and death at the level of individuals (demographic stochasticity), variation in population-level birth and death rates among times or locations (environmental stochasticity), the sex of individuals and variation in vital rates among individuals within a population (demographic heterogeneity). Mechanistic stochastic models that include all of these factors have not previously been developed to examine their combined effects on extinction risk. Here we derive a family of stochastic Ricker models using different combinations of all these stochastic factors, and show that extinction risk depends strongly on the combination of factors that contribute to stochasticity. Furthermore, we show that only with the full stochastic model can the relative importance of environmental and demographic variability, and therefore extinction risk, be correctly determined. Using the full model, we find that demographic sources of stochasticity are the prominent cause of variability in a laboratory population of Tribolium castaneum (red flour beetle), whereas using only the standard simpler models would lead to the erroneous conclusion that environmental variability dominates. Our results demonstrate that current estimates of extinction risk for natural populations could be greatly underestimated because variability has been mistakenly attributed to the environment rather than the demographic factors described here that entail much higher extinction risk for the same variability level.

Evolution is more repeatable in the introduction than range expansion phase of colonization.

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.