A standard approach for including climate change responses in IUCN Red List assessments

The International Union for Conservation of Nature (IUCN) Red List is a central tool for extinction risk monitoring and influences global biodiversity policy and action. But, to be effective, it is crucial that it consistently accounts for each driver of extinction. Climate change is rapidly becoming a key extinction driver, but consideration of climate change information remains challenging for the IUCN. Several methods can be used to predict species' future decline, but they often fail to provide estimates of the symptoms of endangerment used by IUCN. We devised a standardized method to measure climate change impact in terms of change in habitat quality to inform criterion A3 on future population reduction. Using terrestrial nonvolant tetrapods as a case study, we measured this impact as the difference between the current and the future species climatic niche, defined based on current and future bioclimatic variables under alternative model algorithms, dispersal scenarios, emission scenarios, and climate models. Our models identified 171 species (13% out of those analyzed) for which their current red-list category could worsen under criterion A3 if they cannot disperse beyond their current range in the future. Categories for 14 species (1.5%) could worsen if maximum dispersal is possible. Although ours is a simulation exercise and not a formal red-list assessment, our results suggest that considering climate change impacts may reduce misclassification and strengthen consistency and comprehensiveness of IUCN Red List assessments.

Extinction risk predictions for the world's flowering plants to support their conservation

More than 70% of all vascular plants lack conservation status assessments. We aimed to address this shortfall in knowledge of species extinction risk by using the World Checklist of Vascular Plants to generate the first comprehensive set of predictions for a large clade: angiosperms (flowering plants, c. 330 000 species). We used Bayesian Additive Regression Trees (BART) to predict the extinction risk of all angiosperms using predictors relating to range size, human footprint, climate, and evolutionary history and applied a novel approach to estimate uncertainty of individual species-level predictions. From our model predictions, we estimate 45.1% of angiosperm species are potentially threatened with a lower bound of 44.5% and upper bound of 45.7%. Our species-level predictions, with associated uncertainty estimates, do not replace full global, or regional Red List assessments, but can be used to prioritise predicted threatened species for full Red List assessment and fast-track predicted non-threatened species for Least Concern assessments. Our predictions and uncertainty estimates can also guide fieldwork, inform systematic conservation planning and support global plant conservation efforts and targets.

Comprehensive conservation assessments reveal high extinction risks across Atlantic Forest trees

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.

More than 17,000 tree species are at risk from rapid global change

Trees are pivotal to global biodiversity and nature's contributions to people, yet accelerating global changes threaten global tree diversity, making accurate species extinction risk assessments necessary. To identify species that require expert-based re-evaluation, we assess exposure to change in six anthropogenic threats over the last two decades for 32,090 tree species. We estimated that over half (54.2%) of the assessed species have been exposed to increasing threats. Only 8.7% of these species are considered threatened by the IUCN Red List, whereas they include more than half of the Data Deficient species (57.8%). These findings suggest a substantial underestimation of threats and associated extinction risk for tree species in current assessments. We also map hotspots of tree species exposed to rapidly changing threats around the world. Our data-driven approach can strengthen the efforts going into expert-based IUCN Red List assessments by facilitating prioritization among species for re-evaluation, allowing for more efficient conservation efforts.

Modelling the probability of meeting IUCN Red List criteria to support reassessments

Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

A comprehensive database of squirrel distribution and occurrence in South Asia

Background

The Squirrels of South Asia (SOSA) database compiles comprehensive distribution and occurrence information on all squirrel species that occur in this region (34 species). These 34 squirrel species, including tree, flying and ground squirrels, represent 14% of global sciurid diversity. The database collates curated data from various sources such as museums, literature, primary fieldwork, citizen science and social media platforms and covers the entire distributional ranges of the target species, including countries in Central Asia and Southeast Asia when required. The SOSA database enhances our understanding of squirrel distribution, population dynamics and their conservation needs in South Asia by consolidating information. It aims to be a valuable resource for researchers, conservationists and wildlife enthusiasts.

New information

As of March 2023, the database comprises over 40,000 records of 34 species in over 30 countries globally. Spending an average of 334 hours on each species, more than 20 data collectors put in over 10,000 hours to gather, curate and build this database. The database has resulted in novel records of species occurrence in regions and countries that are poorly represented in currently available global data repositories. The current version which has been made public via GBIF comprises of 1187 records of all 34 species across multiple sources. This is a subset of the SOSA database.

Evolutionary diversity of the endemic genera of the vascular flora of Chile and its implications for conservation

As a direct consequence of global change, both natural and human-induced, a high percentage of biodiversity is now under threat worldwide. This has urged conservation planners to formulate and/or improve existing strategies to preserve species and their ecosystems. In this context, the present study focuses on two strategies using phylogeny-based measures of biodiversity to account for the processes that led to the biodiversity patterns observed today. It will contribute additional information that can aid decision-making regarding the assignment of threat status for some species, thus strengthening measures currently in use and facilitate the allocation of often scarce conservation resources. The Evolutionarily Distinct (ED) index prioritises species that are on long branches of the tree of life with few descendants, and the Evolutionarily Distinct and Globally Endangered (EDGE) index integrates evolutionary history with IUCN Red List threat status of species. It has been used mostly in animal groups, but since the threats faced by many plants have not been evaluated, it has been more difficult to compile for plants worldwide. Here, we apply the EDGE metric to species of the endemic genera of Chile. However, more than 50% of the endemic flora of the country are still lacking official threat status. We thus used an alternative measure (Relative Evolutionary Distinctness-RED), based on a range-weighted phylogenetic tree, which uses geographic ranges to adjust branch lengths, and calculate ED. The RED index was shown to be a suitable measure, yielding similar results compared to EDGE, at least for this group of species. Given the urgency to halt biodiversity loss and the time it would take to evaluate all species, we propose that this index is used to set conservation priorities until we can calculate EDGE for these unique endemic species. This would allow guiding decision-making until we can gather more data to assess and assign conservation status to new species.

Evidence-based guidelines for automated conservation assessments of plant species

Assessing species' extinction risk is vital to setting conservation priorities. However, assessment endeavors, such as those used to produce the IUCN Red List of Threatened Species, have significant gaps in taxonomic coverage. Automated assessment (AA) methods are gaining popularity to fill these gaps. Choices made in developing, using, and reporting results of AA methods could hinder their successful adoption or lead to poor allocation of conservation resources. We explored how choice of data cleaning type and level, taxonomic group, training sample, and automation method affect performance of threat status predictions for plant species. We used occurrences from the Global Biodiversity Information Facility (GBIF) to generate assessments for species in 3 taxonomic groups based on 6 different occurrence-based AA methods. We measured each method's performance and coverage following increasingly stringent occurrence cleaning. Automatically cleaned data from GBIF performed comparably to occurrence records cleaned manually by experts. However, all types of data cleaning limited the coverage of AAs. Overall, machine-learning-based methods performed well across taxa, even with minimal data cleaning. Results suggest a machine-learning-based method applied to minimally cleaned data offers the best compromise between performance and species coverage. However, optimal data cleaning, training sample, and automation methods depend on the study group, intended applications, and expertise.

Implications for conservation assessment from flux in the botanical record over 20 years in southwest Ghana

At best, conservation decisions can only be made using the data available at the time. For plants and especially in the tropics, natural history collections remain the best available baseline information upon which to base conservation assessments, in spite of well-documented limitations in their taxonomic, geographic, and temporal coverage. We explore the extent to which changes to the plant biological record over 20 years have changed our conception of the conservation importance of 931 plant taxa, and 114 vegetation samples, recorded in forest reserves of the southwest Ghana biodiversity hotspot. 36% of species-level assessments changed as a result of new distribution data. 12% of species accepted in 2016 had no assessment in 1996: of those, 20% are new species publications, 60% are new records for SW Ghana, and 20% are taxonomic resolutions. Apparent species ranges have increased over time as new records are made, but new species publications are overwhelmingly of globally rare species, keeping the balance of perceived rarity in the flora constant over 20 years. Thus, in spite of considerable flux at the species record level, range size rarity scores calculated for 114 vegetation samples of the reserves in 1996 and 2016 are highly correlated with each other: r(112) = 0.84, p < .0005, and showed no difference in mean score over 20 years: paired t(113) = -0.482, p = .631. This consistency in results at the area level allows for worthwhile conservation priority setting over time, and we argue is the better course of action than taking no action at all.

Potential climatic and elevational range shifts in the Italian narrow endemic Bellevalia webbiana (Asparagaceae) under climate change scenarios

The Webb’s hyacinth (Bellevalia webbiana Parl., Asparagaceae) is an Italian narrow endemic species, listed as Endangered (EN A2c) in the IUCN Global Red List of Threatened Species. The range of this bulbous perennial herb is restricted to two disjunct areas of Central Italy, separated by the mountain ridge of Northern Apennine. To evaluate the impact of climate change on this species, we used Ecological Niche Modelling (ENM) to predict future potential distribution under different scenarios, through Maximum entropy algorithm. The estimated potential distribution highlights the vulnerability of Webb’s hyacinth to the effects of climate change. The current potential Area Of Occupancy (AOO) (992 2×2 km cells) is forecast to dramatically decrease in the range 2041–2100, under the scenarios SSP3-7.0 (2070 = –249, 2100 = –682) and SSP5-8.5 (2070 = –372, 2100 = –948). In all future scenarios, the predicted potential distribution shifts towards higher elevations, located in the two main areas in which the species currently occurs. This could imply a loss of the current genetic differentiation documented at the population level. To overcome these problems, in addition to assisted colonization, an ex situ conservation programme should be planned.

The likely extinction of hundreds of palm species threatens their contributions to people and ecosystems

Protecting nature's contributions to people requires accelerating extinction risk assessment and better integrating evolutionary, functional and used diversity with conservation planning. Here, we report machine learning extinction risk predictions for 1,381 palm species (Arecaceae), a plant family of high socio-economic and ecological importance. We integrate these predictions with published assessments for 508 species (covering 75% of all palm species) and we identify top-priority regions for palm conservation on the basis of their proportion of threatened evolutionarily distinct, functionally distinct and used species. Finally, we explore palm use resilience to identify non-threatened species that could potentially serve as substitutes for threatened used species by providing similar products. We estimate that over a thousand palms (56%) are probably threatened, including 185 species with documented uses. Some regions (New Guinea, Vanuatu and Vietnam) emerge as top ten priorities for conservation only after incorporating machine learning extinction risk predictions. Potential substitutes are identified for 91% of the threatened used species and regional use resilience increases with total palm richness. However, 16 threatened used species lack potential substitutes and 30 regions lack substitutes for at least one of their threatened used palm species. Overall, we show that hundreds of species of this keystone family face extinction, some of them probably irreplaceable, at least locally. This highlights the need for urgent actions to avoid major repercussions on palm-associated ecosystem processes and human livelihoods in the coming decades.

More than half of data deficient species predicted to be threatened by extinction

The IUCN Red List of Threatened Species is essential for practical and theoretical efforts to protect biodiversity. However, species classified as “Data Deficient” (DD) regularly mislead practitioners due to their uncertain extinction risk. Here we present machine learning-derived probabilities of being threatened by extinction for 7699 DD species, comprising 17% of the entire IUCN spatial datasets. Our predictions suggest that DD species as a group may in fact be more threatened than data-sufficient species. We found that 85% of DD amphibians are likely to be threatened by extinction, as well as more than half of DD species in many other taxonomic groups, such as mammals and reptiles. Consequently, our predictions indicate that, amongst others, the conservation relevance of biodiversity hotspots in South America may be boosted by up to 20% if DD species were acknowledged. The predicted probabilities for DD species are highly variable across taxa and regions, implying current Red List-derived indices and priorities may be biased.

Data Deficient species are more likely to be at extinction risk than previously thought across multiple taxonomic groups.

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.

Does Phytogeography Change with Shifts in Geopolitics? The Curious Case of Cycads in the United States

The United States is currently home to five native cycad species. We provide a discussion on these five cycad species to illuminate how evolutionary and geopolitical processes influence phytogeography and published checklists of threatened plants. The number of threatened species in need of protection within any given country is a product of speciation that is contingent with evolutionary processes. However, this number may change instantaneously along with shifting of geopolitical boundaries brought about by armed conflict between rival states and multilateral negotiations. There are five contemporary cycad species within the United States, and the various historical bilateral and multilateral agreements that have generated this list are reviewed. Three of these five cycad species are threatened and in need of urgent protection. A discussion on the history of United States cycads as a microcosm of worldwide conservation issues is presented, with a focus on how federal conservation endeavors of individual nations may influence the world’s biodiversity crisis.

Rapid Least Concern: towards automating Red List assessments

Background

The IUCN Red List of Threatened Species^TM (hereafter the Red List) is an important global resource for conservation that supports conservation planning, safeguarding critical habitat and monitoring biodiversity change (Rodrigues et al. 2006). However, a major shortcoming of the Red List is that most of the world's described species have not yet been assessed and published on the Red List (Bachman et al. 2019Eisenhauer et al. 2019). Conservation efforts can be better supported if the Red List is expanded to achieve greater coverage of mega-diverse groups of organisms such as plants, fungi and invertebrates. There is, therefore, an urgent need to speed up the Red List assessment and documentation workflow.

One reason for this lack of species coverage is that a manual and relatively time-consuming procedure is usually employed to assess and document species. A recent update of Red List documentation standards (IUCN 2013) reduced the data requirements for publishing non-threatened or 'Least Concern' species on the Red List. The majority of the required fields for Least Concern plant species can be found in existing open-access data sources or can be easily calculated. There is an opportunity to consolidate these data and analyses into a simple application to fast-track the publication of Least Concern assessments for plants. There could be as many as 250,000 species of plants (60%) likely to be categorised as Least Concern (Bachman et al. 2019), for which automatically generated assessments could considerably reduce the outlay of time and valuable resources for Red Listing, allowing attention and resources to be dedicated to the assessment of those species most likely to be threatened.

New information

We present a web application, Rapid Least Concern, that addresses the challenge of accelerating the generation and documentation of Least Concern Red List assessments. Rapid Least Concern utilises open-source datasets, such as the Global Biodiversity Information Facility (GBIF) and Plants of the World Online (POWO) through a simple web interface. Initially, the application is intended for use on plants, but it could be extended to other groups, depending on the availability of equivalent datasets for these groups.

Rapid Least Concern users can assess a single species or upload a list of species that are assessed in a batch operation. The batch operation can either utilise georeferenced occurrence data from GBIF or occurrence data provided by the user. The output includes a series of CSV files and a point map file that meet the minimum data requirements for a Least Concern Red List assessment (IUCN 2013). The CSV files are compliant with the IUCN Red List SIS Connect system that transfers the data files to the IUCN database and, pending quality control checks and review, publication on the Red List.

We outline the knowledge gap this application aims to fill and describe how the application works. We demonstrate a use-case for Rapid Least Concern as part of an ongoing initiative to complete a global Red List assessment of all native species for the United Kingdom Overseas Territory of Bermuda.

A third of the tropical African flora is potentially threatened with extinction

Preserving tropical biodiversity is an urgent challenge when faced with the growing needs of countries. Despite their crucial importance for terrestrial ecosystems, most tropical plant species lack extinction risk assessments, limiting our ability to identify conservation priorities. Using a novel approach aligned with IUCN Red List criteria, we conducted a continental-scale preliminary conservation assessment of 22,036 vascular plant species in tropical Africa. Our results underline the high level of extinction risk of the tropical African flora. Thirty-three percent of the species are potentially threatened with extinction, and another third of species are likely rare, potentially becoming threatened in the near future. Four regions are highlighted with a high proportion (>40%) of potentially threatened species: Ethiopia, West Africa, central Tanzania, and southern Democratic Republic of the Congo. Our approach represents a first step toward data-driven conservation assessments applicable at continental scales providing crucial information for sustainable economic development prioritization.

Recent Anthropogenic Plant Extinctions Differ in Biodiversity Hotspots and Coldspots

During the Anthropocene, humans are changing the Earth system in ways that will be detectable for millennia to come [1]. Biologically, these changes include habitat destruction, biotic homogenization, increased species invasions, and accelerated extinctions [2]. Contemporary extinction rates far surpass background rates [3], but they seem remarkably low in plants [4, 5]. However, biodiversity is not evenly distributed, and as a result, extinction rates may vary among regions. Some authors have contentiously argued that novel anthropic habitats and human-induced plant speciation can actually increase regional biodiversity [6, 7]. Here, we report on one of the most comprehensive datasets to date, including regional and global plant extinctions in both biodiversity hotspots (mostly from Mediterranean-type climate regions) and coldspots (mostly from Eurasian countries). Our data come from regions covering 15.3% of the Earth's surface and span over 300 years. With this dataset, we explore the trends, causes, and temporal dynamics of recent plant extinctions. We found more, and faster accrual of, absolute numbers of extinction events in biodiversity hotspots compared to coldspots. Extinction rates were also substantially higher than historical background rates, but recent declines are evident. We found higher levels of taxonomic uniqueness being lost in biodiversity coldspots compared to hotspots. Causes of plant extinctions also showed distinct temporal patterns, with agriculture, invasions, and urbanization being significant drivers in hotspots, while hydrological disturbance was an important driver in coldspots. Overall, plant extinctions over the last three centuries appear to be low, with a recent (post-1990) and steady extinction rate of 1.26 extinctions/year.

Recent Trends in Research on the Genetic Diversity of Plants: Implications for Conservation

Genetic diversity and its distribution, both within and between populations, may be determined by micro-evolutionary processes, such as the demographic history of populations, natural selection, and gene flow. In plants, indices of genetic diversity (e.g., k, h and π) and structure (e.g., FST) are typically inferred from sequences of chloroplast markers. Given the recent advances and popularization of molecular techniques for research in population genetics, phylogenetics, phylogeography, and ecology, we adopted a scientometric approach to compile evidence on the recent trends in the use of cpDNA sequences as markers for the analysis of genetic diversity in botanical studies, over the years. We also used phylogenetic modeling to assess the relative contribution of relatedness or ecological and reproductive characters to the genetic diversity of plants. We postulated that genetic diversity could be defined not only by microevolutionary factors and life history traits, but also by relatedness, so that species more closely related phylogenetically would have similar genetic diversities. We found a clear tendency for an increase in the number of studies over time, confirming the hypothesis that the advances in the area of molecular genetics have supported the accumulation of data on the genetic diversity of plants. However, we found that the vast majority of these data have been produced by Chinese authors, and refer specifically to populations of Chinese plants. Most of the data on genetic diversity have been obtained for species in the International Union for Conservation of Nature (IUCN) category NE (Not Evaluated), which indicates a relative lack of attention on threatened species. In general, we observed very high FST values in the groups analyzed and, as we focused primarily on species that have not been evaluated by the IUCN, the number of plant species that are threatened with extinction may be much greater than that indicated by the listing of this organization. We also found that the number of haplotypes (k) was influenced by the type of geographic distribution of the plant, while haplotype diversity (h) was affected by the type of flower, and the fixation index (FST), by the type of habitat. The plant species most closely-related phylogenetically have similar levels of genetic diversity. Overall, then, it will important to consider phylogenetic dependence in future studies that evaluate the effects of life-history traits on plant genetic diversity.

The use and misuse of herbarium specimens in evaluating plant extinction risks

Herbarium specimens provide verifiable and citable evidence of the occurrence of particular plants at particular points in space and time, and are vital resources for assessing extinction risk in the tropics, where plant diversity and threats to plants are greatest. We reviewed approaches to assessing extinction risk in response to the Convention on Biological Diversity's Global Strategy for Plant Conservation Target 2: an assessment of the conservation status of all known plant species by 2020. We tested five alternative approaches, using herbarium-derived data for trees, shrubs and herbs in five different plant groups from temperate and tropical regions. All species were previously fully assessed for the IUCN Red List. We found significant variation in the accuracy with which different approaches classified species as threatened or not threatened. Accuracy was highest for the machine learning model (90%) but the least data-intensive approach also performed well (82%). Despite concerns about spatial, temporal and taxonomic biases and uncertainties in herbarium data, when specimens represent the best available evidence for particular species, their use as a basis for extinction risk assessment is appropriate, necessary and urgent. Resourcing herbaria to maintain, increase and disseminate their specimen data is essential to guide and focus conservation action.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.