Significance Ecoevolutionary feedbacks on contemporary timescales were hypothesized over half a century ago, but only recently has evidence begun to emerge. The role that human activity plays in such dynamics is still unclear. Through a metaanalysis of >1,600 phenotypic changes in species across regions and ecosystem types, we examine the evidence that the rate of phenotypic change has an urban signature. Our findings indicate greater phenotypic change in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to trait changes that might affect ecosystem function, we provide insights into the potential ecoevolutionary implications for maintaining ecosystem function and the sustainability of human well-being.

Abstract Humans challenge the phenotypic, genetic, and cultural makeup of species by affecting the fitness landscapes on which they evolve. Recent studies show that cities might play a major role in contemporary evolution by accelerating phenotypic changes in wildlife, including animals, plants, fungi, and other organisms. Many studies of ecoevolutionary change have focused on anthropogenic drivers, but none of these studies has specifically examined the role that urbanization plays in ecoevolution or explicitly examined its mechanisms. This paper presents evidence on the mechanisms linking urban development patterns to rapid evolutionary changes for species that play important functional roles in communities and ecosystems. Through a metaanalysis of experimental and observational studies reporting more than 1,600 phenotypic changes in species across multiple regions, we ask whether we can discriminate an urban signature of phenotypic change beyond the established natural baselines and other anthropogenic signals. We then assess the relative impact of five types of urban disturbances including habitat modifications, biotic interactions, habitat heterogeneity, novel disturbances, and social interactions. Our study shows a clear urban signal; rates of phenotypic change are greater in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to traits that affect ecosystem function, we can map potential ecoevolutionary implications of emerging patterns of urban agglomerations and uncover insights for maintaining key ecosystem functions upon which the sustainability of human well-being depends.

Emerging evidence of phenotypic change on contemporary timescales challenges the assumption that evolution only occurs over hundreds or thousands of years. Anthropogenic changes in ecological conditions can drive evolutionary change in species traits that can alter ecosystem function (1⇓–3). However, the reciprocal and simultaneous outcomes of such interactions have only begun to emerge (4). Despite increasing evidence that humans are major drivers of microevolution, the role of human activities in such dynamics is still unclear. Might human-driven evolution lead to ecosystem change with consequences for human well-being within contemporary timescales (5, 6)?

To address this question, human-driven phenotypic change must be considered in the context of global rapid urbanization. In 1950, 30% of the world’s population lived in urban settlements (7). By 2014, that figure had risen to 54%, and by 2050 it is expected to reach 66% (7). By 2030, urban land cover is forecast to increase by 1.2 million km2, almost tripling the global urban land area of 2000 (8). Urbanization drives systemic changes to socioecological systems by accelerating rates of interactions among people, multiplying connections among distant places, and expanding the spatial scales and ecological consequences of human activities to global levels (9).

A critical question for sustainability is whether, on an increasingly urbanized planet, the expansion and patterns of urban environments accelerate the evolution of ecologically relevant traits with potential impacts on urban populations via basic ecosystem services such as food production, carbon sequestration, and human health. In cities, ecoevolutionary changes are occurring at an unprecedented pace. Humans challenge the phenotypic, genetic, and cultural makeup of species on the planet by changing the fitness landscapes on which they evolve. Examples of contemporary evolution associated with urbanization have been documented for many species (1, 5, 6, 10).

This paper examines the mechanisms linking urban development patterns to contemporary evolutionary changes. Through a metaanalysis of experimental and observational studies that report >1,600 phenotypic changes in many species across multiple regions, we investigated the emergence of distinct signatures of urban-driven phenotypic change. We hypothesize that shifts in the physical and socioeconomic structure and function of large urban complexes can drive rapid evolution of many species that play important roles in communities and ecosystems. Thus, urbanization-driven phenotypic change may, in turn, impact critical aspects of ecosystem function.

We ask the following two questions: (i) Is there evidence of an urban signature of phenotypic change beyond the established natural and anthropogenic signals, accelerating rates of phenotypic change in species across multiple regions? (ii) What are the relative impacts of five types of urban disturbance: habitat modification, biotic interaction, heterogeneity, novel disturbance, and social interaction?

Our hypothesis is grounded in the growing evidence that urbanization is a major driver of contemporary evolution. Urban development changes habitat structure (i.e., loss of forest cover and connectivity), processes (i.e., biogeochemical and nutrient cycling), and biotic interactions (i.e., predation) (6). Humans in cities mediate ecoevolutionary interactions by introducing novel disturbances and altering habitat heterogeneity. Urban environments can facilitate hybridization by reducing reproductive isolation (11). They can also isolate populations through habitat fragmentation (12). In addition to changes in the physical template, humans in cities modify the availability of resources and their variability over time, buffering their effects on community structure (12). Complex interactions resulting from changes in habitat and biotic interactions coupled with emerging spatial and temporal patterns of resource availability might produce new evolutionary dynamics and feedbacks. Furthermore, in cities, the rapid pace of change associated with increasing social interactions amplifies the impacts of human agency, both locally and at a distance (telecoupling). Understanding how urban-driven contemporary evolution affects ecosystem functions will provide insights for maintaining biodiversity and achieving global urban sustainability.

Discussion Our results show a clear urban signal of phenotypic change and reveal variable effects of urban disturbance mechanisms. Observed effects might be due to the multiple challenges that urbanization poses on adaptation. Multiple influences can increase the total strength of selection on a trait, or the number of traits under selection (20). Urban Disturbance Mechanisms. Urban Disturbance represents coupled mechanisms through which urban development affects natural processes and evolutionary dynamics. Model predictions highlight two categories driving the urban signature: social interactions and biotic interactions, specifically introduction of predators, prey, hosts, and competitors. Anthropogenic habitat modification had a lower than expected impact. The assessment of the effect of the various urban disturbances should be interpreted cautiously since it might reflect the classification of interrelated disturbances, and the nature of species observed in available studies. Habitat modification. Land cover conversion and loss of native habitat are major drivers of contemporary evolution. The observed counterintuitive lower phenotypic change associated with Habitat Modification relative to the Natural context in our study may reflect in part the vagility of birds generally, and an overrepresentation in the database of studies finding stable migration phenology of European birds in particular. It also might be due to the fact that habitat modification is captured by other interrelated urban disturbance classes and by other variables such as Δ City Lights that show the expected trend of greater phenotypic change. Urban-driven habitat modification can affect species traits and composition. For example, changes in climate, artificial lighting, and availability of food are all drivers of change in the timing and duration of reproduction in some bird species (21). Changes in productivity—the rate at which energy flows through an ecosystem—might explain species diversity patterns along the urban–rural gradient (22). Biotic interactions. We determined that introduction of predator, prey, host, or competition contributes to a higher rate of phenotypic change compared with range expansion after introduction or introduction alone. Urban development creates new opportunities and challenges for species competition and predation, both as exotic species are introduced and as invasive species migrate in, taking advantage of poorly integrated communities and patches. This might result in colonization, as more frequent introductions of exotic species translate into invasions (23). For example, McDonnell and Hahs (24) found higher levels of earthworm biomass and abundance in urban forests compared with rural ones, likely because of introduced species. Urbanization also alters the way species distribute and interact (25). Marzluff (25) found that, although diversity still emerges as the balance between extinction and colonization, species invasion plays a prominent role. Heterogeneity. At the community level, cities directly and indirectly affect phenotypic change by altering spatial and temporal habitat heterogeneity. Increasing evidence supports the hypothesis that urban regions amplify heterogeneity by the intensity and speed of human-biophysical and social interactions (26). Cities worldwide retain native species, but loss of functional heterogeneity driven by urbanization affects niche differentiation and species diversity (27). Furthermore, changes associated with urban land uses act as filters in urban species composition, and losses of native species drive the homogenization of ecological structures and functions (28). Habitat patches and their ecological communities are often isolated by a matrix of built environments. Fragmentation of natural patches due to urbanization affects the diversity, structure, and distribution of vegetation, and movement of organisms (29). Change in temporal microclimatic heterogeneity (e.g., heat islands) can extend the growing season in temperate cities, and droughts in desert urban areas (30). Phenotypic trait change within species, however, was not associated to heterogeneity in our analysis. Perhaps this is not surprising given that novel adaptations were allotted to a different process, and emphasis was placed on small-scale spatial heterogeneity where dispersion and gene flow is more likely. Novel disturbance. Human-induced disturbances in urban environments maintain urban habitats at an early successional stage (31). Such novel disturbances alter resource availability, ecosystem productivity, and species diversity (31). Cardinale et al. (32) suggested two ways that disturbance can moderate relationships between biodiversity and ecosystem functioning: it can increase the chance that diversity generates unique system properties, and it can suppress the probability of ecological processes being controlled by a single taxon. Urbanization not only modifies existing disturbance regimes (e.g., fire and flood management), it also creates novel disturbances including disrupted dispersal pathways or stressors, ecotoxins and pollutants (33, 34). Examples of phenotypic changes in response to new toxins include earthworms’ tolerance to metals (33) and changes in endocrine systems of fish and birds (34). Low statistical power might have hindered a stronger observed effect. Social interactions. Perhaps the most significant quality that distinguishes cities is their pace of change. Urbanization changes the dynamics of socioecological interactions by increasing interactions among people (35), between people and other species (36), and among distant places (9). Important properties of cities of all sizes (i.e., gross domestic product) increase, on average, faster than city population size (superlinearity). Increasing social interactions accelerate environmental changes and human impact on phenotypic traits via selective harvest (5). Socioeconomic shifts associated with urbanization can explain the emergence of a detectable urban signature of evolutionary change. The urban extent, regardless of boundary definitions, only partially defines the extent of urban disturbances. City functions depend on highly interconnected infrastructures and on flows of material, energy, and information from both proximate regions (e.g., via hydroelectric dams) and distant ones (e.g., via trade and telecommunication). In urbanizing regions, distant human–natural interactions are currently more prevalent and faster (9), challenging the ability to disentangle urban vs. nonurban anthropogenic influences on phenotypic traits. Linking Urban Evolutionary Change to Ecosystem Function. By explicitly linking urban development to traits that affect ecosystem functions and services, we start to map the ecoevolutionary implications of urban-driven phenotypic trait changes and identify existing gaps in knowledge. The evolution of antibiotic resistance, pesticide resistance, host–pathogen coevolution, and evolution in response to harvest and habitat change provide examples of the link between human-driven evolution and sustainability (37). Urban environments provide the context for many such interactions, bringing people into contact with novel pathogens, accelerating the spread of genes that confer resistance, and generally selecting for traits that enhance the survival and reproduction of organisms within human-built environments. When this selection facilitates the survival of desirable species, it can have important benefits for biodiversity, human health, and ecosystem services. For example, evolution of Daphnia may help improve water quality in the face of cultural eutrophication (38). However, adaptation can also enable the survival and reproduction of species that reduce biodiversity and human well-being. For example, evolution of pesticide resistance in agriculture and antibiotic resistance in human medicine represent critical threats to food security and human health (39, 40). Thus, evolution should take on a prominent role in the future of sustainability science. Table 2 identifies examples of traits for which there is evidence of phenotypic changes in response to environmental changes driven by urbanization. The evolution of traits that control ecosystem processes could lead to significant changes in ecosystem functions (49). For example, primary productivity is associated with consumers’ traits that regulate their demands for resources. Evolution in such traits can affect nutrient cycling and ultimately the magnitude and spatial distribution of primary production (4). Seed dispersers have a significant impact on plant diversity and their functional roles in urban ecosystems. A great diversity of organisms modify the physical structure of estuarine and coastal environments, particularly dune and marsh plants, mangroves, seagrasses, kelps, and infauna (50). Evolution in ecosystem-engineering traits has potential functional impacts on maintaining the stability and resilience (e.g., flood control) of coastal cities and the capacity of cities to adapt to climate change. Table 2. Mapping urban-driven phenotypic trait change to ecosystem function

Conclusions Rapid urbanization poses new challenges for species—some will go extinct (at least locally), whereas others will adapt or relocate (51). Our paper asked whether we can detect distinct signatures of urban-driven phenotypic change across taxa and determine the extent to which systemic changes to socioecological systems associated with urban agglomerations might accelerate ecoevolutionary change. We found a clear urban signal of phenotypic change, and greater phenotypic change in urbanizing systems compared with natural and nonurban anthropogenic systems. By explicitly linking urban development to heritable traits that affect ecosystem function, we can begin to map the ecoevolutionary implications of human-induced trait changes for Earth's evolution. We posit that urban-driven contemporary evolution will affect sustainability, from the level of the urban ecosystem to the planetary scale. We suggest that conservation biologists should pay increased attention to mechanisms by which the emergent human habitat influences population persistence (4). Such understanding will provide insights for maintaining ecosystem function in the long term and can direct policy makers toward sustainability solutions (37).

Materials and Methods Database on Rates of Phenotypic Change. We improved an existing database on rates of phenotypic change (5, 13⇓⇓⇓–17). We added new data published up to August of 2015. Studies were surveyed by searching ISI Web of Science, Google Scholar, and cross-references, using ad hoc keywords (e.g., quantitative trait, evolutionary change, rapid evolution, ecoevolutionary, anthropogenic change, urban disturbances, and system stability). Studies were screened (SI Appendix, Database Filtering), and, if selected, phenotypic rates were extracted (Statistical Analyses) and classified according to qualities of the study system including ecological and anthropogenic contexts (5). Each row corresponded to one phenotypic change rate estimate and associated contextual attributes including type of study: allochronic for longitudinal studies, or synchronic for cross-sectional studies comparing samples obtained synchronously from populations derived from a common ancestral population. Rates were classified according to whether phenotypic change could be attributed to quantitative genetic effects (Genetic), or could not be distinguished from phenotypic plasticity (Phenotypic). Generations was calculated as the number of years between population samples (or since population divergence, if synchronic) divided by expected generation time. The dataset had a hierarchical structure, with variable numbers of phenotypic change estimates (from different morphological characters and or populations) within study systems, species, and taxa. Study system was defined as population(s) of a species within a geographical region putatively exposed to similar environmental effects and high gene flow potential. We evaluated whether study systems were evolving in an anthropogenic vs. natural context (15), and the effect of Urban Disturbance (see next section). Urban Disturbance Classification and Georeferencing. We use the global urban area map at 1-km spatial resolution developed by Zhou et al. (52). The map is based on a cluster-based method to estimate optimal thresholds for mapping urban extent using DMSP/OLS NTL to account for regional variations in urban clusters (53). The anthropogenic biome of all samples was based on the Anthropogenic Biomes geodataset for the year 2000 (54). For samples in study systems in which the driver of evolutionary change is anthropogenic, we classify the Urban Disturbance as social interaction, biotic interaction, habitat modification, heterogeneity, or novel disturbance (6) (SI Appendix, Urban Disturbance Classification). Habitat modification represents changes in climate, modification of the landscape, or pollution. Biotic interactions stem from introductions, and are subcategorized depending on the study organism’s ecological role: introduced species vs. species in its native range responding to an introduction. Introduced species are further divided into species in a new range following introduction vs. introduced species after range expansion. Heterogeneity can refer to heterogeneity in space or time. Novel disturbances require novel adaptations, for example, rapid evolution of zinc tolerance (42). Social interactions refer to direct or intentional results of human agency. Examples are listed in Table 2. Statistical Analyses. We used an information-theoretic approach to rank statistical models and conduct multimodel inference, based on AICc (23, 55). AICc favors model fit (minimizing deviance) while avoiding model overfitting (penalizing for the number of estimated parameters, K), and was the basis for enforcing the parsimony principle given our sample sizes (1,663 rates nested in 175 study systems). The statistical models were GLMMs. The response variable, phenotypic change (square-root transformed), was measured as the absolute magnitude of phenotypic change standardized by character variation (Haldane numerator; ref. 19, as formulated in ref. 13). The square-root transformation minimized patterns in adjusted residuals plots in preliminary analyses. Because the data had a hierarchical structure, study system was always modeled as a random effect, with combinations of background and urban variables (fixed effects): H ( i ) ( 1 / 2 ) = α j ( i ) + β χ i + ε i , α j ∼Ν ( μ , σ 2 α ) , ε ∼ N ( 0,f ( γ ) ) , where the indexes i run from 1 to number of observations, and j run from 1 to number of study systems, H(1/2) is the response variable (square-root of Haldane numerator), α is normally distributed with mean μ (overall intercept) and variance σ2α, allowing for varying intercepts per study system, β is a vector of partial regression coefficients related to a matrix of explanatory variables X, and ε is the residual error with variance γ, which was modeled as follows: γ = 0.1494 ∗ ( C + | fitted | P ) 2 , where C is a constant by stratum (0.3233 for genetic; 0.1249 for phenotypic), and P is an exponent of absolute fitted values by stratum (2.0754 for genetic; 1.2376 for phenotypic). Hence, the chosen residual variance increased exponentially with fitted values, and slightly more so in genetic than phenotypic rates (SI Appendix, Materials and Methods—Statistical Analysis). We used exploratory multimodel inference to assess the relative importance of predictor variables for phenotypic change, and to make predictions about contrasting urban-related scenarios that considered information contained in all models. From three background plus six urban variables, we combined nine predictor variables to form 29 = 512 models, including a null model (intercept only), and excluding interactions. All models were fitted through maximum likelihood in the R package nlme (56). Models were ranked according to decreasing values of AICc (57), and further evaluated using standard methods after refitting through restricted maximum-likelihood estimation (58). Predictor variable relative importance was calculated by the sum of the Akaike weights of all models containing a particular predictor variable. Similarly, model-averaged partial regression coefficients were Akaike-weighted averages of coefficients from all models containing a particular term (18). Model ranking and inference was conducted in the R package MuMin, version 1.15.6 (55) (SI Appendix, Materials and Methods—Statistical Analysis).

Acknowledgments We thank the John D. and Catherine T. MacArthur Foundation for partially supporting the study (Grant 14-106477-000-USP). C.C. was funded by Comisión Nacional de Investigación Científica y Tecnológica-Programa de Atracción e Inserción de Capital Humano Avanzado (CONICYT-PAI) Grant 82130009 and Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) Grant 11150990.