Turning the tide on big cat trade: Expert opinion on trends and conservation lessons from the Republic of Korea.

Unsustainable trade in big cats affects all species in the genus, Panthera, and is one of the foremost threats to their conservation. To provide further insight into the impact of policy interventions intended to address this issue, we examine the case study of the Republic of Korea (South Korea), which in the early 1990s was one of the world's largest importers of tiger (Panthera tigris) bone and a major manufacturer of tiger-derived medicinal products. In 1993, South Korea became a Party to the Convention on International Trade in Endangered Species (CITES) and introduced a ban on commercial trade in CITES Appendix I-listed big cats a year later. We used an expert-based questionnaire survey and an exploration of the CITES trade database to investigate what has since happened to big cat trade in South Korea. Expert opinion suggested that big cat trade has likely substantially reduced since the early 1990s, as a result of the trade ban and broad socioeconomic changes. However, illegal trade has not been eradicated entirely and we were able to confirm that products reportedly derived from big cats were still publicly available for sale on a range of Korean online marketplaces, sometimes openly. The items most commonly reported by respondents from post-1994 trade and supported by expert-led evidence were tiger and leopard (Panthera pardus) skins and tiger bone wine. Although South Korea may provide a useful case study of a historically significant consumer country for tiger which has made strong progress in addressing unsustainable levels of big cat trade within a short period of time, there remains a need to address recalcitrant small-scale, illegal trade. We also recommend further investigation regarding reports of South Korean nationals being involved in illegal trade in tiger-derived products in Southeast Asia.

Seasonal trends and population status of the highly threatened Pteropus livingstonii in the Comoros archipelago.

Flying foxes of the genus Pteropus, especially those inhabiting islands, face increasing pressure from anthropogenic threats. A first step to implementing effective conservation actions is to establish monitoring projects to understand a species' population status and trend. Pteropus species are highly affected by seasonality which further requires regular, repeated, and long-term data to understand population trends, and reactions to severe weather events. In the present case study, a regular, bi-annual population census was implemented on Comoros between 2016 and 2023 for the highly threatened Livingstone's fruit bat, Pteropus livingstonii, and compared the results of standardized monitoring to historical population data. Seasonality had a large impact on the number of bats found at roost sites, with more bats present in the wet season, but the data over the past eight years revealed no significant in- or decrease in the number of bats counted on the island Anjouan. We estimated around 1,200-1,500 bats on Anjouan and 300-400 bats on Mohéli, and found that landcover type has no measurable effect on population distribution at roost sites. Our study highlights the need for long-term surveys to understand past population trends and that single counts are not sufficient to draw final conclusions of a species' status.

A meta-analysis on global change drivers and the risk of infectious disease.

Anthropogenic change is contributing to the rise in emerging infectious diseases, which are significantly correlated with socioeconomic, environmental and ecological factors1. Studies have shown that infectious disease risk is modified by changes to biodiversity2-6, climate change7-11, chemical pollution12-14, landscape transformations15-20 and species introductions21. However, it remains unclear which global change drivers most increase disease and under what contexts. Here we amassed a dataset from the literature that contains 2,938 observations of infectious disease responses to global change drivers across 1,497 host-parasite combinations, including plant, animal and human hosts. We found that biodiversity loss, chemical pollution, climate change and introduced species are associated with increases in disease-related end points or harm, whereas urbanization is associated with decreases in disease end points. Natural biodiversity gradients, deforestation and forest fragmentation are comparatively unimportant or idiosyncratic as drivers of disease. Overall, these results are consistent across human and non-human diseases. Nevertheless, context-dependent effects of the global change drivers on disease were found to be common. The findings uncovered by this meta-analysis should help target disease management and surveillance efforts towards global change drivers that increase disease. Specifically, reducing greenhouse gas emissions, managing ecosystem health, and preventing biological invasions and biodiversity loss could help to reduce the burden of plant, animal and human diseases, especially when coupled with improvements to social and economic determinants of health.

Ghost roads and the destruction of Asia-Pacific tropical forests.

Roads are expanding at the fastest pace in human history. This is the case especially in biodiversity-rich tropical nations, where roads can result in forest loss and fragmentation, wildfires, illicit land invasions and negative societal effects1-5. Many roads are being constructed illegally or informally and do not appear on any existing road map6-10; the toll of such 'ghost roads' on ecosystems is poorly understood. Here we use around 7,000 h of effort by trained volunteers to map ghost roads across the tropical Asia-Pacific region, sampling 1.42 million plots, each 1 km2 in area. Our intensive sampling revealed a total of 1.37 million km of roads in our plots-from 3.0 to 6.6 times more roads than were found in leading datasets of roads globally. Across our study area, road building almost always preceded local forest loss, and road density was by far the strongest correlate11 of deforestation out of 38 potential biophysical and socioeconomic covariates. The relationship between road density and forest loss was nonlinear, with deforestation peaking soon after roads penetrate a landscape and then declining as roads multiply and remaining accessible forests largely disappear. Notably, after controlling for lower road density inside protected areas, we found that protected areas had only modest additional effects on preventing forest loss, implying that their most vital conservation function is limiting roads and road-related environmental disruption. Collectively, our findings suggest that burgeoning, poorly studied ghost roads are among the gravest of all direct threats to tropical forests.

Revealing uncertainty in the status of biodiversity change.

Biodiversity faces unprecedented threats from rapid global change1. Signals of biodiversity change come from time-series abundance datasets for thousands of species over large geographic and temporal scales. Analyses of these biodiversity datasets have pointed to varied trends in abundance, including increases and decreases. However, these analyses have not fully accounted for spatial, temporal and phylogenetic structures in the data. Here, using a new statistical framework, we show across ten high-profile biodiversity datasets2-11 that increases and decreases under existing approaches vanish once spatial, temporal and phylogenetic structures are accounted for. This is a consequence of existing approaches severely underestimating trend uncertainty and sometimes misestimating the trend direction. Under our revised average abundance trends that appropriately recognize uncertainty, we failed to observe a single increasing or decreasing trend at 95% credible intervals in our ten datasets. This emphasizes how little is known about biodiversity change across vast spatial and taxonomic scales. Despite this uncertainty at vast scales, we reveal improved local-scale prediction accuracy by accounting for spatial, temporal and phylogenetic structures. Improved prediction offers hope of estimating biodiversity change at policy-relevant scales, guiding adaptive conservation responses.