Cognitive abilities, such as learning and flexibility, are hypothesized to aid behavioral adaptation to urbanization. Although growing evidence suggests that cognition may indeed facilitate persistence in urban environments, we currently lack knowledge of the cognitive abilities of many urban taxa. Recent methodological advances, including radio frequency identification (RFID), have extended automated cognitive testing into the field but have yet to be applied to a diversity of taxa. Here, we used an RFID-enabled operant conditioning device to assess the habituation, learning and cognitive flexibility of a wild population of raccoons (Procyon lotor). We examined how several biological and behavioral traits influenced participation and performance in testing. We then compared the cognitive performance of wild raccoons tested in natural conditions with that of wild-caught raccoons tested in captivity from a previous study. In natural conditions, juvenile raccoons were more likely to habituate to the testing device, but performed worse in serial reversal learning, compared with adults. We also found that docile raccoons were more likely to learn how to operate the device in natural conditions, which suggests a relationship between emotional reactivity and cognitive ability in raccoons. Although raccoons in both captive and natural conditions demonstrated rapid associative learning and flexibility, raccoons in captive conditions generally performed better, likely owing to the heightened vigilance and social interference experienced by raccoons in natural conditions. Our results have important implications for future research on urban carnivores and cognition in field settings, as well as our understanding of behavioral adaptation to urbanization and coexistence with urban wildlife.

Global change is increasing the frequency and severity of human-wildlife interactions by pushing people and wildlife into increasingly resource-limited shared spaces. To understand the dynamics of human-wildlife interactions and what may constitute human-wildlife coexistence in the Anthropocene, there is a critical need to explore the spatial, temporal, sociocultural and ecological variables that contribute to human-wildlife conflicts in urban areas. Due to their opportunistic foraging and behavioural flexibility, coyotes (Canis latrans) frequently interact with people in urban environments. San Francisco, California, USA hosts a very high density of coyotes, making it an excellent region for analysing urban human-coyote interactions and attitudes toward coyotes over time and space. We used a community-curated long-term data source from San Francisco Animal Care and Control to summarise a decade of coyote sightings and human-coyote interactions in San Francisco and to characterise spatiotemporal patterns of attitudes and interaction types in relation to housing density, socioeconomics, pollution and human vulnerability metrics, and green space availability. We found that human-coyote conflict reports have been significantly increasing over the past 5 years and that there were more conflicts during the coyote pup-rearing season (April–June), the dry season (June–September) and the COVID-19 pandemic. Conflict reports were also more likely to involve dogs and occur inside of parks, despite more overall sightings occurring outside of parks. Generalised linear mixed models revealed that conflicts were more likely to occur in places with higher vegetation greenness and median income. Meanwhile reported coyote boldness, hazing and human attitudes toward coyotes were also correlated with pollution burden and human population vulnerability indices. Synthesis and applications: Our results provide compelling evidence suggesting that human-coyote conflicts are intimately associated with social-ecological heterogeneities and time, emphasizing that the road to coexistence will require socially informed strategies. Additional long-term research articulating how the social-ecological drivers of conflict (e.g. human food subsidies, interactions with domestic species, climate-induced droughts, socioeconomic disparities, etc.) change over time will be essential in building adaptive management efforts that effectively mitigate future conflicts from occurring. Read the free Plain Language Summary for this article on the Journal blog.

Cognitive skills, such as innovative problem-solving, are hypothesized to aid animals in urban environments. However, the significance of innovation in wild populations, and its expression across individuals and socio-ecological conditions, is poorly understood. To identify how and when innovation arises in urban-dwelling species, we used advanced technologies and new testing and analytical methods to evaluate innovative problem-solving abilities of wild raccoons (Procyon lotor). We deployed multi-compartment puzzle boxes with either one or multiple solution types and identified raccoons using radio frequency identification. Raccoons solved these novel extractive foraging tasks, and their success was influenced by age and exploratory diversity. Successful raccoons always discovered multiple different solution types, highlighting flexible problem-solving. Using a unique, comparative sequence analysis approach, we found that variation in raccoon solving techniques was greater between individuals than within individuals, and this self-similarity intensified during times of competition. Finally, the inclusion of an easier solution in the multi-solution trials enabled previously unsuccessful raccoons to bootstrap their learning and successfully open multiple difficult solutions. Our study suggests that innovative problem-solving is probably influenced by many factors and has provided novel field and analytical methods, as well as new insights on the socio-ecological dynamics of urban populations.

Human-wildlife interactions, including human-wildlife conflict, are increasingly common as expanding urbanization worldwide creates more opportunities for people to encounter wildlife. Wildlife-vehicle collisions, zoonotic disease transmission, property damage, and physical attacks to people or their pets have negative consequences for both people and wildlife, underscoring the need for comprehensive strategies that mitigate and prevent conflict altogether. Management techniques often aim to deter, relocate, or remove individual organisms, all of which may present a significant selective force in both urban and nonurban systems. Management-induced selection may significantly affect the adaptive or nonadaptive evolutionary processes of urban populations, yet few studies explicate the links among conflict, wildlife management, and urban evolution. Moreover, the intensity of conflict management can vary considerably by taxon, public perception, policy, religious and cultural beliefs, and geographic region, which underscores the complexity of developing flexible tools to reduce conflict. Here, we present a cross-disciplinary perspective that integrates human-wildlife conflict, wildlife management, and urban evolution to address how social-ecological processes drive wildlife adaptation in cities. We emphasize that variance in implemented management actions shapes the strength and rate of phenotypic and evolutionary change. We also consider how specific management strategies either promote genetic or plastic changes, and how leveraging those biological inferences could help optimize management actions while minimizing conflict. Investigating human-wildlife conflict as an evolutionary phenomenon may provide insights into how conflict arises and how management plays a critical role in shaping urban wildlife phenotypes.

Contributory science—including citizen and community science—allows scientists to leverage participant-generated data while providing an opportunity for engaging with local community members. Data yielded by participant-generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts. The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases. We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation, detectability, sampling and preference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data. Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog.