Biodiversity is declining globally, yet many biodiversity hotspots still lack comprehensive species conservation assessments. Using multiple International Union for Conservation of Nature (IUCN) Red List criteria to evaluate extinction risks and millions of herbarium and forest inventory records, we present automated conservation assessments for all tree species of the Atlantic Forest biodiversity hotspot, including ~1100 heretofore unassessed species. About 65% of all species and 82% of endemic species are classified as threatened. We rediscovered five species classified as Extinct on the IUCN Red List and identified 13 endemics as possibly extinct. Uncertainties in species information had little influence on the assessments, but using fewer Red List criteria severely underestimated threat levels. We suggest that the conservation status of tropical forests worldwide is worse than previously reported.
Human pressure on nature has increased in recent decades, particularly in the tropics, where most of the planet’s biodiversity resides (1, 2). Consequently, we face a global biodiversity crisis (3). Reversing this crisis is a pressing challenge and begins by classifying species based on extinction risks, which are used to monitor biodiversity and prioritize conservation actions (4, 5). Also known as red listing, these conservation assessments are a cornerstone of global conservation programs, such as the International Union for Conservation of Nature (IUCN) Red List, which categorizes species extinction risks based on one or multiple criteria, including population size decline (criterion A), geographic range (criterion B), and very small populations (criterion D).
Efforts to include species on the IUCN Red List have grown in recent years, but much remains to be done (4–7). Even for the well-studied trees of Europe, red listing efforts have been published only recently (8). One reason why only a small part of global biodiversity has up-to-date conservation assessments is the difficulty in carrying out these assessments. They require detailed species information and the time, training, and resources to apply the IUCN Red List Categories and Criteria on a species-by-species basis (9), all of which are limited, especially in the tropics (4, 5). Therefore, automated assessments are increasingly being proposed as complements or alternatives to manual assessments (4, 10–13) to provide fast-track conservation assessments for megadiverse regions (14–16).
Assessments for tropical biodiversity hotspots, where most threatened species occur (17), remain rare. One of these hotspots is the Atlantic Forest in eastern South America, which has more than 15,000 plant species, of which half are endemic (18). With 35% of the South American human population living within its borders, about 80% of its original cover has been lost, and deforestation and degradation remain high (19, 20). Species conservation assessments are limited to about 25% of the Atlantic Forest flora and are mostly being conducted using few IUCN Red List criteria (21). A comprehensive assessment at the Atlantic Forest scale could provide insights into the conservation status of other tropical biodiversity hotspots, which do not all have the same amount of information available as the Atlantic Forest.
We present the conservation status of the Atlantic Forest tree flora, which represents a third of the entire hotspot’s plant diversity and is crucial to providing people with ecosystem services (5, 7, 12). We automated the conservation assessments for nearly 5000 species using more than 800,000 herbarium records, 1.3 million tree counts from forest inventories, and information on species life histories, commercial uses, and long time-series of habitat loss (fig. S1 and data S1) (22). We developed a replicable workflow that strictly adheres to the IUCN Red List Categories and Criteria (9) and delivers conservation assessments based on the IUCN criteria A to D (table S1). This workflow also evaluates the sensitivity of the assessments to the number of IUCN criteria applied and uncertainties in species information (tables S2 to S4). Finally, we predicted the conservation status of tropical forests worldwide using the relationship between species threat and habitat loss observed in the Atlantic Forest.
