Search for: All records

Understanding variation in food web structure over large spatial scales is an emerging research agenda in food web ecology. The density of predator–prey links in a food web (i.e., connectance) is a key measure of network complexity that describes the mean proportional dietary breadth of species within a food web. Connectance is a critical component of food web robustness to species loss: food webs with lower connectance have been shown to be more susceptible to secondary extinctions. Identifying geographic variation in food web connectance and its drivers may provide insight into community robustness to species loss. We investigated the food web connectance of ground-dwelling tropical forest mammal communities in multiple biogeographic regions to test for differences among regions in food web connectance and to test three potential drivers: primary productivity, contemporary anthropogenic pressure, and variation in mammal body mass distributions reflective of historical extinctions. Mammal communities from fifteen protected forests throughout the Neo-, Afro-, and Asian tropics were identified from systematic camera trap arrays. Predator–prey interaction data were collected from published literature, and we calculated connectance for each community as the number of observed predator–prey links relative to the number of possible predator–prey links. We used generalized linear models to test for differences among regions and to identify the site level characteristics that best predicted connectance. We found that mammal food web connectance varied significantly among continents and that body size range was the only significant predictor. More possible predator–prey links were observed in communities with smaller ranges in body size and therefore sites with smaller body size ranges had higher mean proportional dietary breadth. Specifically, mammal communities in the Neotropics and in Madagascar had significantly higher connectance than mammal communities in Africa. This geographic variation in contemporary mammalian food web structure may be the product of historical extinctions in the Late Quaternary, which led to greater losses of large-bodied species in the Neotropics and Madagascar thus contributing to higher average proportional dietary breadth among the remaining smaller bodied species in these regions.

 

Ongoing anthropogenic change is altering the planet at an unprecedented rate, threatening biodiversity, and ecosystem functioning. Species are responding to abiotic pressures at both individual and population levels, with changes affecting trophic interactions through consumptive pathways. Collectively, these impacts alter the goods and services that natural ecosystems will provide to society, as well as the persistence of all species. Here, we describe the physiological and behavioral responses of species to global changes on individual and population levels that result in detectable changes in diet across terrestrial and marine ecosystems. We illustrate shifts in the dynamics of food webs with implications for animal communities. Additionally, we highlight the myriad of tools available for researchers to investigate the dynamics of consumption patterns and trophic interactions, arguing that diet data are a crucial component of ecological studies on global change. We suggest that a holistic approach integrating the complexities of diet choice and trophic interactions with environmental drivers may be more robust at resolving trends in biodiversity, predicting food web responses, and potentially identifying early warning signs of diversity loss. Ultimately, despite the growing body of long‐term ecological datasets, there remains a dearth of diet ecology studies across temporal scales, a shortcoming that must be resolved to elucidate vulnerabilities to changing biophysical conditions.

 

Abstract Urbanization is changing Earth's ecosystems by altering the interactions and feedbacks between the fundamental ecological and evolutionary processes that maintain life. Humans in cities alter the eco-evolutionary play by simultaneously changing both the actors and the stage on which the eco-evolutionary play takes place. Urbanization modifies land surfaces, microclimates, habitat connectivity, ecological networks, food webs, species diversity, and species composition. These environmental changes can lead to changes in phenotypic, genetic, and cultural makeup of wild populations that have important consequences for ecosystem function and the essential services that nature provides to human society, such as nutrient cycling, pollination, seed dispersal, food production, and water and air purification. Understanding and monitoring urbanization-induced evolutionary changes is important to inform strategies to achieve sustainability. In the present article, we propose that understanding these dynamics requires rigorous characterization of urbanizing regions as rapidly evolving, tightly coupled human–natural systems. We explore how the emergent properties of urbanization affect eco-evolutionary dynamics across space and time. We identify five key urban drivers of change—habitat modification, connectivity, heterogeneity, novel disturbances, and biotic interactions—and highlight the direct consequences of urbanization-driven eco-evolutionary change for nature's contributions to people. Then, we explore five emerging complexities—landscape complexity, urban discontinuities, socio-ecological heterogeneity, cross-scale interactions, legacies and time lags—that need to be tackled in future research. We propose that the evolving metacommunity concept provides a powerful framework to study urban eco-evolutionary dynamics. 

Human activity and land use change impact every landscape on Earth, driving declines in many animal species while benefiting others. Species ecological and life history traits may predict success in human-dominated landscapes such that only species with “winning” combinations of traits will persist in disturbed environments. However, this link between species traits and successful coexistence with humans remains obscured by the complexity of anthropogenic disturbances and variability among study systems. We compiled detection data for 24 mammal species from 61 populations across North America to quantify the effects of (1) the direct presence of people and (2) the human footprint (landscape modification) on mammal occurrence and activity levels. Thirty-three percent of mammal species exhibited a net negative response (i.e., reduced occurrence or activity) to increasing human presence and/or footprint across populations, whereas 58% of species were positively associated with increasing disturbance. However, apparent benefits of human presence and footprint tended to decrease or disappear at higher disturbance levels, indicative of thresholds in mammal species’ capacity to tolerate disturbance or exploit human-dominated landscapes. Species ecological and life history traits were strong predictors of their responses to human footprint, with increasing footprint favoring smaller, less carnivorous, faster-reproducing species. The positive and negative effects of human presence were distributed more randomly with respect to species trait values, with apparent winners and losers across a range of body sizes and dietary guilds. Differential responses by some species to human presence and human footprint highlight the importance of considering these two forms of human disturbance separately when estimating anthropogenic impacts on wildlife. Our approach provides insights into the complex mechanisms through which human activities shape mammal communities globally, revealing the drivers of the loss of larger predators in human-modified landscapes. 

Camera trap studies have become a popular medium to assess many ecological phenomena including population dynamics, patterns of biodiversity, and monitoring of endangered species. In conjunction with the benefit to scientists, camera traps present an unprecedented opportunity to involve the public in scientific research via image classifications. However, this engagement strategy comes with a myriad of complications. Volunteers vary in their familiarity with wildlife, thus, the accuracy of user‐derived classifications may be biased by the commonness or popularity of species and user‐experience. From an extensive multi‐site camera trap study across Michigan, U.S.A, we compiled and classified images through a public science platform called Michigan ZoomIN. We aggregated responses from 15 independent users per image using multiple consensus methods to assess accuracy by comparing to species identification completed by wildlife experts. We also evaluated how different factors including consensus algorithms, study area, wildlife species, user support, and camera type influenced the accuracy of user‐derived classifications. Overall accuracy of user‐derived classification was 97%; although, several canid (e.g.,Canis lupus, Vulpes vulpes) and mustelid (e.g.,Neovison vison) species were repeatedly difficult to identify by users and had lower accuracy. When validating user‐derived classification, we found that study area, consensus method, and user support best explained accuracy. To overcome hesitancy associated with data collected by untrained participants, we demonstrated their value by showing that the accuracy from volunteers was comparable to experts when classifying North American mammals. Our hierarchical workflow that integrated multiple consensus methods led to more image classifications without extensive training and even when the expertise of the volunteer was unknown. Ultimately, adopting such an approach can harness broader participation, expedite future camera trap data synthesis, and improve allocation of resources by scholars to enhance performance of public participants and increase accuracy of user‐derived data. © 2021 The Wildlife Society.

 

Urban areas are dynamic ecological systems defined by interdependent biological, physical, and social components. The emergent structure and heterogeneity of urban landscapes drives biotic outcomes in these areas, and such spatial patterns are often attributed to the unequal stratification of wealth and power in human societies. Despite these patterns, few studies have effectively considered structural inequalities as drivers of ecological and evolutionary outcomes and have instead focused on indicator variables such as neighborhood wealth. In this analysis, we explicitly integrate ecology, evolution, and social processes to emphasize the relationships that bind social inequities—specifically racism—and biological change in urbanized landscapes. We draw on existing research to link racist practices, including residential segregation, to the heterogeneous patterns of flora and fauna observed by urban ecologists. In the future, urban ecology and evolution researchers must consider how systems of racial oppression affect the environmental factors that drive biological change in cities. Conceptual integration of the social and ecological sciences has amassed considerable scholarship in urban ecology over the past few decades, providing a solid foundation for incorporating environmental justice scholarship into urban ecological and evolutionary research. Such an undertaking is necessary to deconstruct urbanization’s biophysical patterns and processes, inform equitable and anti-racist initiatives promoting justice in urban conservation, and strengthen community resilience to global environmental change.