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Climate change has led animal species to shift their ranges to greater elevations, latitudes, and depths, tracking their preferred abiotic niche. However, there is extensive variation in these shifts, and some species have not shifted their ranges at all. Some of this variation arises because species’ distributions not only align with the abiotic environment but are also shaped by biotic factors and movement. Through facilitating rapid adaptive responses to climate-mediated changes to abiotic, biotic, and movement factors, behavioral plasticity allows populations to survive environmental change by persisting in place, while also enabling successful establishment in novel habitats when shifting in space. 

Large, well described gaps exist in both what we know and what we need to know to address the biodiversity crisis. Artificial intelligence (AI) offers new potential for filling these knowledge gaps, but where the biggest and most influential gains could be made remains unclear. To date, biodiversity-related uses of AI have largely focused on tracking and monitoring of wildlife populations. Rapid progress is being made in the use of AI to build phylogenetic trees and species distribution models. However, AI also has considerable unrealized potential in the re-evaluation of important ecological questions, especially those that require the integration of disparate and inherently complex data types, such as images, video, text, audio and DNA. This Review describes the current and potential future use of AI to address seven clearly defined shortfalls in biodiversity knowledge. Recommended steps for AI-based improvements include the re-use of existing image data and the development of novel paradigms, including the collaborative generation of new testable hypotheses. The resulting expansion of biodiversity knowledge could lead to science spanning from genes to ecosystems — advances that might represent our best hope for meeting the rapidly approaching 2030 targets of the Global Biodiversity Framework. 

Extreme weather events perturb ecosystems and increasingly threaten biodiversity1. Ecologists emphasize the need to forecast and mitigate the impacts of these events, which requires knowledge of how risk is distributed among species and environments. However, the scale and unpredictability of extreme events complicate risk assessment1–4—especially for large animals (megafauna), which are ecologically important and disproportionately threatened but are wide-ranging and difficult to monitor5. Traits such as body size, dispersal ability and habitat affiliation are hypothesized to determine the vulnerability of animals to natural hazards1,6,7. Yet it has rarely been possible to test these hypotheses or, more generally, to link the short-term and long-term ecological effects of weather-related disturbance8,9. Here we show how large herbivores and carnivores in Mozambique responded to Intense Tropical Cyclone Idai, the deadliest storm on record in Africa, across scales ranging from individual decisions in the hours after landfall to changes in community composition nearly 2 years later. Animals responded behaviourally to rising floodwaters by moving upslope and shifting their diets. Body size and habitat association independently predicted population-level impacts: five of the smallest and most lowland-affiliated herbivore species declined by an average of 28% in the 20 months after landfall, while four of the largest and most upland-affiliated species increased by an average of 26%. We attribute the sensitivity of small-bodied species to their limited mobility and physiological constraints, which restricted their ability to avoid the flood and endure subsequent reductions in the quantity and quality of food. Our results identify general traits that govern animal responses to severe weather, which may help to inform wildlife conservation in a volatile climate. 

Research on the ecology of fear has highlighted the importance of perceived risk from predators and humans in shaping animal behavior and physiology, with potential demographic and ecosystem-wide consequences. Despite recent conceptual advances and potential management implications of the ecology of fear, theory and conservation practices have rarely been linked. Many challenges in animal conservation may be alleviated by actively harnessing or compensating for risk perception and risk avoidance behavior in wild animal populations. Integration of the ecology of fear into conservation and management practice can contribute to the recovery of threatened populations, human–wildlife conflict mitigation, invasive species management, maintenance of sustainable harvest and species reintroduction plans. Here, we present an applied framework that links conservation interventions to desired outcomes by manipulating ecology of fear dynamics. We discuss how to reduce or amplify fear in wild animals by manipulating habitat structure, sensory stimuli, animal experience (previous exposure to risk) and food safety trade-offs to achieve management objectives. Changing the optimal decision-making of individuals in managed populations can then further conservation goals by shaping the spatiotemporal distribution of animals, changing predation rates and altering risk effects that scale up to demographic consequences. We also outline future directions for applied research on fear ecology that will better inform conservation practices. Our framework can help scientists and practitioners anticipate and mitigate unintended consequences of management decisions, and highlight new levers for multi-species conservation strategies that promote human–wildlife coexistence. 

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.