Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale.

Dispersal is important for determining both species ecological processes, such as population viability, and its evolutionary processes, like gene flow and local adaptation. Yet obtaining accurate estimates in the wild through direct observation can be challenging or even impossible, particularly over large spatial and temporal scales. Genotyping many individuals from wild populations can provide detailed inferences about dispersal. We therefore utilized genomewide marker data to estimate dispersal in the classic metapopulation of the Glanville fritillary butterfly (Melitaea cinxia L.), in the Åland Islands in SW Finland. This is an ideal system to test the effectiveness of this approach due to the wealth of information already available covering dispersal across small spatial and temporal scales, but lack of information at larger spatial and temporal scales. We sampled three larvae per larval family group from 3732 groups over a six‐year period and genotyped for 272 SNPs across the genome. We used this empirical data set to reconstruct cases where full‐sibs were detected in different local populations to infer female effective dispersal distance, that is, dispersal events directly contributing to gene flow. On average this was one kilometre, closely matching previous dispersal estimates made using direct observation. To evaluate our power to detect full‐sib families, we performed forward simulations using an individual‐based model constructed and parameterized for the Glanville fritillary metapopulation. Using these simulations, 100% of predicted full‐sibs were correct and over 98% of all true full‐sib pairs were detected. We therefore demonstrate that even in a highly dynamic system with a relatively small number of markers, we can accurately reconstruct full‐sib families and for the first time make inferences on female effective dispersal. This highlights the utility of this approach in systems where it has previously been impossible to obtain accurate estimates of dispersal over both ecological and evolutionary scales.

This review examines the landscape genetics literature from 2011-2015 and summarises the genetic evidence for the roles of habitat amount (i.e. total area of habitat), configuration (i.e. spatial arrangement of habitat), and matrix (i.e. nature of the intervening landscape between habitat patches) in shaping genetic differentiation and diversity of populations. We found that the vast majority of landscape genetic studies focused on the effects of habitat configuration and intervening matrix permeability on genetic differentiation of populations, and very few consider the consequences of habitat loss (i.e. change in habitat amount) versus fragmentation per se (i.e. change in habitat configuration). In addition, disproportionately few studies consider genetic diversity as a response variable in landscape genetic models. We argue that by ignoring the effects of habitat amount, landscape geneticists are missing an important component of how landscape structure shapes patterns of genetic variation. On the other hand, landscape ecologists may need to consider the confounding role of the matrix to resolve the ongoing debate about the relative importance of habitat loss versus fragmentation per se in determining biological diversity.

The ecological impacts of extreme climatic events on population dynamics and community composition are profound and predominantly negative. Using extensive data of an ecological model system, we tested whether predictions from ecological models remain robust when environmental conditions are outside the bounds of observation. We observed a 10-fold demographic decline of the Glanville fritillary butterfly (Melitaea cinxia) metapopulation on the Åland islands, Finland in the summer of 2018 and used climatic and satellite data to demonstrate that this year was an anomaly with low climatic water balance values and low vegetation productivity indices across Åland. Population growth rates were strongly associated with spatiotemporal variation in climatic water balance. Covariates shown previously to affect the extinction probability of local populations in this metapopulation were less informative when populations were exposed to severe drought during the summer months. Our results highlight the unpredictable responses of natural populations to extreme climatic events.

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation-by-distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation-by-distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long-standing natural features (e.g. water bodies) co-exist on the landscape.