Range expansion is both slower and more variable with rapid evolution across a spatial gradient in temperature.

Rapid evolution in colonising populations can alter our ability to predict future range expansions. Recent theory suggests that the dynamics of replicate range expansions are less variable, and hence more predictable, with increased selection at the expanding range front. Here, we test whether selection from environmental gradients across space produces more consistent range expansion speeds, using the experimental evolution of replicate duckweed populations colonising landscapes with and without a temperature gradient. We found that the range expansion across a temperature gradient was slower on average, with range-front populations displaying higher population densities, and genetic signatures and trait changes consistent with directional selection. Despite this, we found that with a spatial gradient range expansion speed became more variable and less consistent among replicates over time. Our results therefore challenge current theory, highlighting that chance can still shape the genetic response to selection to influence our ability to predict range expansion speeds.

The evolution of plasticity at geographic range edges.

Phenotypic plasticity enables rapid responses to environmental change, and could facilitate range shifts in response to climate change. What drives the evolution of plasticity at range edges, and the capacity of range-edge individuals to be plastic, remain unclear. Here, we propose that accurately predicting when plasticity itself evolves or mediates adaptive evolution at expanding range edges requires integrating knowledge on the demography and evolution of edge populations. Our synthesis shows that: (i) the demography of edge populations can amplify or attenuate responses to selection for plasticity through diverse pathways, and (ii) demographic effects on plasticity are modified by the stability of range edges. Our spatially explicit synthesis for plasticity has the potential to improve predictions for range shifts with climate change.

Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research.

The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research.

Adaptation across geographic ranges is consistent with strong selection in marginal climates and legacies of range expansion.

Every species experiences limits to its geographic distribution. Some evolutionary models predict that populations at range edges are less well adapted to their local environments due to drift, expansion load, or swamping gene flow from the range interior. Alternatively, populations near range edges might be uniquely adapted to marginal environments. In this study, we use a database of transplant studies that quantify performance at broad geographic scales to test how local adaptation, site quality, and population quality change from spatial and climatic range centers toward edges. We find that populations from poleward edges perform relatively poorly, both on average across all sites (15% lower population quality) and when compared to other populations at home (31% relative fitness disadvantage), consistent with these populations harboring high genetic load. Populations from equatorial edges also perform poorly on average (18% lower population quality) but, in contrast, outperform foreign populations (16% relative fitness advantage), suggesting that populations from equatorial edges have strongly adapted to unique environments. Finally, we find that populations from sites that are thermally extreme relative to the species' niche demonstrate strong local adaptation, regardless of their geographic position. Our findings indicate that both nonadaptive processes and adaptive evolution contribute to variation in adaptation across species' ranges.

On the Origin of Coexisting Species.

Speciation is frequently initiated but rarely completed, a phenomenon hypothesized to arise due to the failure of nascent lineages to persist. Although a failure to persist often has ecological causes, key gaps exist between ecological and evolutionary theories that, if filled, would clarify when and why speciation succeeds or fails. Here, we apply ecological coexistence theory to show how the alignment between different forms of niche opportunity and niche use shape the initiation, progression, and completion of speciation. Niche evolution may drive coexistence or competitive exclusion, and an ability to coexist ecologically may help or hinder speciation. Our perspective allows progress towards unifying the origin and maintenance of species diversity across the tree of life.

Eco-evolutionary dynamics of range expansion.

Understanding the movement of species' ranges is a classic ecological problem that takes on urgency in this era of global change. Historically treated as a purely ecological process, range expansion is now understood to involve eco-evolutionary feedbacks due to spatial genetic structure that emerges as populations spread. We synthesize empirical and theoretical work on the eco-evolutionary dynamics of range expansion, with emphasis on bridging directional, deterministic processes that favor evolved increases in dispersal and demographic traits with stochastic processes that lead to the random fixation of alleles and traits. We develop a framework for understanding the joint influence of these processes in changing the mean and variance of expansion speed and its underlying traits. Our synthesis of recent laboratory experiments supports the consistent role of evolution in accelerating expansion speed on average, and highlights unexpected diversity in how evolution can influence variability in speed: results not well predicted by current theory. We discuss and evaluate support for three classes of modifiers of eco-evolutionary range dynamics (landscape context, trait genetics, and biotic interactions), identify emerging themes, and suggest new directions for future work in a field that stands to increase in relevance as populations move in response to global change.

Computer Animation Technology in Behavioral Sciences: A Sequential, Automatic, and High-Throughput Approach to Quantifying Personality in Zebrafish (Danio rerio).

An emergent field of animal personality necessitates a method for repeated high-throughput quantification of behavioral traits across contexts. In this study, we have developed an automated video stimulus approach to sequentially present different contexts relevant to five "personality" traits (exploration, boldness, neophobia, aggression, and sociability), successfully quantifying repeatable trait measurements in multiple individuals simultaneously. Although our method is designed to quantify personality traits in zebrafish, our approach can accommodate the quantification of other behaviors, and could be customized for other species. All digital materials and detailed protocols are publicly available online for researchers to freely use and modify.

The French press: a repeatable and high-throughput approach to exercising zebrafish (Danio rerio).

Zebrafish are increasingly used as a vertebrate model organism for various traits including swimming performance, obesity and metabolism, necessitating high-throughput protocols to generate standardized phenotypic information. Here, we propose a novel and cost-effective method for exercising zebrafish, using a coffee plunger and magnetic stirrer. To demonstrate the use of this method, we conducted a pilot experiment to show that this simple system provides repeatable estimates of maximal swim performance (intra-class correlation [ICC] = 0.34-0.41) and observe that exercise training of zebrafish on this system significantly increases their maximum swimming speed. We propose this high-throughput and reproducible system as an alternative to traditional linear chamber systems for exercising zebrafish and similarly sized fishes.

Temporal shifts and temperature sensitivity of avian spring migratory phenology: a phylogenetic meta-analysis.

There are wide reports of advances in the timing of spring migration of birds over time and in relation to rising temperatures, though phenological responses vary substantially within and among species. An understanding of the ecological, life-history and geographic variables that predict this intra- and interspecific variation can guide our projections of how populations and species are likely to respond to future climate change. Here, we conduct phylogenetic meta-analyses addressing slope estimates of the timing of avian spring migration regressed on (i) year and (ii) temperature, representing a total of 413 species across five continents. We take into account slope estimation error and examine phylogenetic, ecological and geographic predictors of intra- and interspecific variation. We confirm earlier findings that on average birds have significantly advanced their spring migration time by 2·1 days per decade and 1·2 days °C-1 . We find that over time and in response to warmer spring conditions, short-distance migrants have advanced spring migratory phenology by more than long-distance migrants. We also find that larger bodied species show greater advance over time compared to smaller bodied species. Our results did not reveal any evidence that interspecific variation in migration response is predictable on the basis of species' habitat or diet. We detected a substantial phylogenetic signal in migration time in response to both year and temperature, suggesting that some of the shifts in migratory phenological response to climate are predictable on the basis of phylogeny. However, we estimate high levels of species and spatial variance relative to phylogenetic variance, which is consistent with plasticity in response to climate evolving fairly rapidly and being more influenced by adaptation to current local climate than by common descent. On average, avian spring migration times have advanced over time and as spring has become warmer. While we are able to identify predictors that explain some of the true among-species variation in response, substantial intra- and interspecific variation in migratory response remains to be explained.