Megafauna extinctions produce idiosyncratic Anthropocene assemblages

Combining N-mixture and occupancy analysis offers a more complete picture of carnivore habitat use in Northeastern Türkiye

Occupancy and N-mixture analyses have been successfully used to understand habitat use in various species. However, since these methods fundamentally answer different questions about wildlife distribution, the results from each modelling approach may provide different insights into species' habitat use. In this study, we leveraged data from a long-term camera trapping study in northeastern Türkiye to compare the results from occupancy and N-mixture analyses, with the main objective of understanding how the modelling approach used can influence our knowledge of species' habitat use. Specifically, we compared the habitat use preferences from N-mixture and occupancy analyses for three carnivore species with varying baseline abundances. Our results provide evidence that occupancy and N-mixture analyses provide different insights into species' sensitivity to environmental and anthropogenic factors. Whereas occupancy analysis provides a relatively broad summary of the factors that affect where a species may or may not be located on a landscape or which areas they may be more likely to use over a certain time period, N-mixture modelling may provide insights into the factors that affect the degree of use at individual sites, with particular emphasis on being able to deduce small-scale changes in habitat use across a landscape. Furthermore, while the detection probability of an occupancy analysis has been formally used as a measure of site use intensity, N-Mixture models may offer higher resolution of the quantity of use. Therefore, as these two methods tend to investigate habitat use at different spatial scales, when used in conjunction they can provide a more refined understanding of species' habitat use through repeat-survey sampling methods like camera trapping.

Defaunation impacts on the carbon balance of tropical forests

The urgent need to mitigate and adapt to climate change necessitates a comprehensive understanding of carbon cycling dynamics. Traditionally, global carbon cycle models have focused on vegetation, but recent research suggests that animals can play a significant role in carbon dynamics under some circumstances, potentially enhancing the effectiveness of nature-based solutions to mitigate climate change. However, links between animals, plants, and carbon remain unclear. We explored the complex interactions between defaunation and ecosystem carbon in Earth's most biodiverse and carbon-rich biome, tropical rainforests. Defaunation can change patterns of seed dispersal, granivory, and herbivory in ways that alter tree species composition and, therefore, forest carbon above- and belowground. Most studies we reviewed show that defaunation reduces carbon storage 0-26% in the Neo- and Afrotropics, primarily via population declines in large-seeded, animal-dispersed trees. However, Asian forests are not predicted to experience changes because their high-carbon trees are wind dispersed. Extrapolating these local effects to entire ecosystems implies losses of ∼1.6 Pg CO2 equivalent across the Brazilian Atlantic Forest and 4-9.2 Pg across the Amazon over 100 years and of ∼14.7-26.3 Pg across the Congo basin over 250 years. In addition to being hard to quantify with precision, the effects of defaunation on ecosystem carbon are highly context dependent; outcomes varied based on the balance between antagonist and mutualist species interactions, abiotic conditions, human pressure, and numerous other factors. A combination of experiments, large-scale comparative studies, and mechanistic models could help disentangle the effects of defaunation from other anthropogenic forces in the face of the incredible complexity of tropical forest systems. Overall, our synthesis emphasizes the importance of-and inconsistent results when-integrating animal dynamics into carbon cycle models, which is crucial for developing climate change mitigation strategies and effective policies.

Scaling up area-based conservation to implement the Global Biodiversity Framework's 30x30 target: The role of Nature's Strongholds

The Global Biodiversity Framework (GBF), signed in 2022 by Parties to the Convention on Biological Diversity, recognized the importance of area-based conservation, and its goals and targets specify the characteristics of protected and conserved areas (PCAs) that disproportionately contribute to biodiversity conservation. To achieve the GBF's target of conserving a global area of 30% by 2030, this Essay argues for recognizing these characteristics and scaling them up through the conservation of areas that are: extensive (typically larger than 5,000 km2); have interconnected PCAs (either physically or as part of a jurisdictional network, and frequently embedded in larger conservation landscapes); have high ecological integrity; and are effectively managed and equitably governed. These areas are presented as "Nature's Strongholds," illustrated by examples from the Congo and Amazon basins. Conserving Nature's Strongholds offers an approach to scale up initiatives to address global threats to biodiversity.

Effects of human disturbances on wildlife behaviour and consequences for predator-prey overlap in Southeast Asia

Some animal species shift their activity towards increased nocturnality in disturbed habitats to avoid predominantly diurnal humans. This may alter diel overlap among species, a precondition to most predation and competition interactions that structure food webs. Here, using camera trap data from 10 tropical forest landscapes, we find that hyperdiverse Southeast Asian wildlife communities shift their peak activity from early mornings in intact habitats towards dawn and dusk in disturbed habitats (increased crepuscularity). Our results indicate that anthropogenic disturbances drive opposing behavioural adaptations based on rarity, size and feeding guild, with more nocturnality among the 59 rarer specialists' species, more diurnality for medium-sized generalists, and less diurnality for larger hunted species. Species turnover also played a role in underpinning community- and guild-level responses, with disturbances associated with markedly more detections of diurnal generalists and their medium-sized diurnal predators. However, overlap among predator-prey or competitor guilds does not vary with disturbance, suggesting that net species interactions may be conserved.

The rise of hyperabundant native generalists threatens both humans and nature

In many disturbed terrestrial landscapes, a subset of native generalist vertebrates thrives. The population trends of these disturbance-tolerant species may be driven by multiple factors, including habitat preferences, foraging opportunities (including crop raiding or human refuse), lower mortality when their predators are persecuted (the 'human shield' effect) and reduced competition due to declines of disturbance-sensitive species. A pronounced elevation in the abundance of disturbance-tolerant wildlife can drive numerous cascading impacts on food webs, biodiversity, vegetation structure and people in coupled human-natural systems. There is also concern for increased risk of zoonotic disease transfer to humans and domestic animals from wildlife species with high pathogen loads as their abundance and proximity to humans increases. Here we use field data from 58 landscapes to document a supra-regional phenomenon of the hyperabundance and community dominance of Southeast Asian wild pigs and macaques. These two groups were chosen as prime candidates capable of reaching hyperabundance as they are edge adapted, with gregarious social structure, omnivorous diets, rapid reproduction and high tolerance to human proximity. Compared to intact interior forests, population densities in degraded forests were 148% and 87% higher for wild boar and macaques, respectively. In landscapes with >60% oil palm coverage, wild boar and pig-tailed macaque estimated abundances were 337% and 447% higher than landscapes with <1% oil palm coverage, respectively, suggesting marked demographic benefits accrued by crop raiding on calorie-rich food subsidies. There was extreme community dominance in forest landscapes with >20% oil palm cover where two pig and two macaque species accounted for >80% of independent camera trap detections, leaving <20% for the other 85 mammal species >1 kg considered. Establishing the population trends of pigs and macaques is imperative since they are linked to cascading impacts on the fauna and flora of local forest ecosystems, disease and human health, and economics (i.e., crop losses). The severity of potential negative cascading effects may motivate control efforts to achieve ecosystem integrity, human health and conservation objectives. Our review concludes that the rise of native generalists can be mediated by specific types of degradation, which influences the ecology and conservation of natural areas, creating both positive and detrimental impacts on intact ecosystems and human society.

Inferring predator-prey interactions from camera traps: A Bayesian co-abundance modeling approach

Predator-prey dynamics are a fundamental part of ecology, but directly studying interactions has proven difficult. The proliferation of camera trapping has enabled the collection of large datasets on wildlife, but researchers face hurdles inferring interactions from observational data. Recent advances in hierarchical co-abundance models infer species interactions while accounting for two species' detection probabilities, shared responses to environmental covariates, and propagate uncertainty throughout the entire modeling process. However, current approaches remain unsuitable for interacting species whose natural densities differ by an order of magnitude and have contrasting detection probabilities, such as predator-prey interactions, which introduce zero inflation and overdispersion in count histories. Here, we developed a Bayesian hierarchical N-mixture co-abundance model that is suitable for inferring predator-prey interactions. We accounted for excessive zeros in count histories using an informed zero-inflated Poisson distribution in the abundance formula and accounted for overdispersion in count histories by including a random effect per sampling unit and sampling occasion in the detection probability formula. We demonstrate that models with these modifications outperform alternative approaches, improve model goodness-of-fit, and overcome parameter convergence failures. We highlight its utility using 20 camera trapping datasets from 10 tropical forest landscapes in Southeast Asia and estimate four predator-prey relationships between tigers, clouded leopards, and muntjac and sambar deer. Tigers had a negative effect on muntjac abundance, providing support for top-down regulation, while clouded leopards had a positive effect on muntjac and sambar deer, likely driven by shared responses to unmodelled covariates like hunting. This Bayesian co-abundance modeling approach to quantify predator-prey relationships is widely applicable across species, ecosystems, and sampling approaches and may be useful in forecasting cascading impacts following widespread predator declines. Taken together, this approach facilitates a nuanced and mechanistic understanding of food-web ecology.