Cost-effective assessment of extinction risk with limited information

Diversity, distribution and intrinsic extinction vulnerability of exploited marine bivalves

Marine bivalves are important components of ecosystems and exploited by humans for food across the world, but the intrinsic vulnerability of exploited bivalve species to global changes is poorly known. Here, we expand the list of shallow-marine bivalves known to be exploited worldwide, with 720 exploited bivalve species added beyond the 81 in the United Nations FAO Production Database, and investigate their diversity, distribution and extinction vulnerability using a metric based on ecological traits and evolutionary history. The added species shift the richness hotspot of exploited species from the northeast Atlantic to the west Pacific, with 55% of bivalve families being exploited, concentrated mostly in two major clades but all major body plans. We find that exploited species tend to be larger in size, occur in shallower waters, and have larger geographic and thermal ranges-the last two traits are known to confer extinction-resistance in marine bivalves. However, exploited bivalve species in certain regions such as the tropical east Atlantic and the temperate northeast and southeast Pacific, are among those with high intrinsic vulnerability and are a large fraction of regional faunal diversity. Our results pinpoint regional faunas and specific taxa of likely concern for management and conservation.

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.

Assessment of the threat status of the amphibians in Vietnam - Implementation of the One Plan Approach

The current decline in global biodiversity is most evident in amphibians with 41% percent of all species worldwide classified as threatened with extinction. Hence, a major challenge in amphibian conservation is the high number of threatened species, leading to a common approach of identifying priority species and regions for conservation efforts. As a part of one of 36 globally designated biodiversity hotspots, Vietnam is considered to be of particular importance for conservation action. To improve amphibian conservation in Vietnam, this study provides an updated species list and assesses their threat status by compiling data from a variety of sources. Furthermore, a Zoological Information Management System (ZIMS) analysis was conducted to determine the representation of extant amphibians from Vietnam in zoos worldwide. The batrachofauna of Vietnam is characterized by a high level of species richness and local endemism as well as a high rate of new discoveries, with more than half of the endemic species reported exclusively from their type locality, making them especially vulnerable to extinction. Up to 18% of all amphibians extant in Vietnam and 28% of endemic species are classified as threatened with extinction by the IUCN. In many cases, the IUCN Red List status is either missing or outdated, highlighting the urgent need of action. Around 14% of endemic amphibian species have been recorded exclusively from unprotected areas, suggesting prioritization for further research and conservation measures. The continuing decline in many species remains an unresolved problem. As a guide for future research and conservation measures, a list of the top 57 species was compiled. In addition, according to the ZIMS analysis, only 8% of threatened and 3% of endemic amphibian taxa from Vietnam are currently kept in zoos worldwide, and a richness analysis revealed that the highest density of husbandries is found in Europe and North America. To achieve maximum outcome for the conservation of threatened species, this study recommends a general shift by zoos towards maintaining species in greater need of captive assurance populations and breeding programs to support integrative strategies that combine in situ and ex situ conservation efforts following the IUCN’s One Plan Approach.

Automated assessment reveals that the extinction risk of reptiles is widely underestimated across space and phylogeny

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning–based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles—the only major tetrapod group without a comprehensive Red List assessment; and (3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.

Matrix condition mediates the effects of habitat fragmentation on species extinction risk

Habitat loss is the leading cause of the global decline in biodiversity, but the influence of human pressure within the matrix surrounding habitat fragments remains poorly understood. Here, we measure the relationship between fragmentation (the degree of fragmentation and the degree of patch isolation), matrix condition (measured as the extent of high human footprint levels), and the change in extinction risk of 4,426 terrestrial mammals. We find that the degree of fragmentation is strongly associated with changes in extinction risk, with higher predictive importance than life-history traits and human pressure variables. Importantly, we discover that fragmentation and the matrix condition are stronger predictors of risk than habitat loss and habitat amount. Moreover, the importance of fragmentation increases with an increasing deterioration of the matrix condition. These findings suggest that restoration of the habitat matrix may be an important conservation action for mitigating the negative effects of fragmentation on biodiversity.

The influence of human pressure within the matrix surrounding habitat fragments remains poorly understood. This study measures the relationship between habitat fragmentation, matrix condition and the change in extinction risk of 4,426 terrestrial mammals, finding that fragmentation and matrix condition are stronger predictors of risk than habitat loss and habitat amount.

Seabird meta-Population Viability Model (mPVA) methods

The seabird meta-population viability model (mPVA) uses a generalized approach to project abundance and quasi-extinction risk for 102 seabird species under various conservation scenarios. The mPVA is a stage-structured projection matrix that tracks abundance of multiple populations linked by dispersal, accounting for breeding island characteristics and spatial distribution. Data are derived from published studies, grey literature, and expert review (with over 500 contributions). Invasive species impacts were generalized to stage-specific vital rates by fitting a Bayesian state-space model to trend data from Islands where invasive removals had occurred, while accounting for characteristics of seabird biology, breeding islands and invasive species. Survival rates were estimated using a competing hazards formulation to account for impacts of multiple threats, while also allowing for environmental and demographic stochasticity, density dependence and parameter uncertainty.•The mPVA provides resource managers with a tool to quantitatively assess potential benefits of alternative management actions, for multiple species•The mPVA compares projected abundance and quasi-extinction risk under current conditions (no intervention) and various conservation scenarios, including removal of invasive species from specified breeding islands, translocation or reintroduction of individuals to an island of specified location and size, and at-sea mortality amelioration via reduction in annual at-sea deaths.

Tracking the rising extinction risk of sharks and rays in the Northeast Atlantic Ocean and Mediterranean Sea

The loss of biodiversity is increasingly well understood on land, but trajectories of extinction risk remain largely unknown in the ocean. We present regional Red List Indices (RLIs) to track the extinction risk of 119 Northeast Atlantic and 72 Mediterranean shark and ray species primarily threatened by overfishing. We combine two IUCN workshop assessments from 2003/2005 and 2015 with a retrospective backcast assessment for 1980. We incorporate predicted categorisations for Data Deficient species from our previously published research. The percentage of threatened species rose from 1980 to 2015 from 29 to 41% (Northeast Atlantic) and 47 to 65% (Mediterranean Sea). There are as many threatened sharks and rays in Europe as there are threatened birds, but the threat level is nearly six times greater by percentage (41%, n = 56 of 136 vs. 7%, n = 56 of 792). The Northeast Atlantic RLI declined by 8% from 1980 to 2015, while the higher-risk Mediterranean RLI declined by 13%. Larger-bodied, shallow-distributed, slow-growing species and those with range boundaries within the region are more likely to have worsening status in the Northeast Atlantic. Conversely, long-established, severe threat levels obscure any potential relationships between species' traits and the likelihood of worsening IUCN status in the Mediterranean Sea. These regional RLIs provide the first widespread evidence for increasing trends in regional shark and ray extinction risk and underscore that effective fisheries management is necessary to recover the ecosystem function of these predators.

Reallocating budgets among ongoing and emerging conservation projects

Conserving biodiversity and combating ecological hazards require cost-effective allocation of limited resources among potential management projects. Project priorities, however, can change over time as underlying social-ecological systems progress, novel priorities emerge, and management capabilities evolve. Thus, reallocation of ongoing investments in response to shifting priorities could improve management outcomes and address urgent demands, especially when additional funding is not available immediately. Resource reallocation, however, could incur transaction costs, require additional monitoring and reassessment, and be constrained by ongoing project commitments. Such complexities may prevent managers from considering potentially beneficial reallocation strategies, reducing long-term effectiveness. We propose an iterative project prioritization approach, based on marginal return-on-investment estimation and portfolio optimization, that guides resource reallocation among ongoing and new projects. Using simulation experiments in 2 case studies, we explored how this approach can improve efficacy under varying reallocation constraints, frequencies, costs, and rates of project portfolio change. Periodic budget reallocation could enhance the management of stochastically emerging invasive weeds in Australia and thus reduce the overall risk by up to 50% compared with a static budget. Reallocation frequency and the rate of new weed incursion synergistically increased the conservation gains achieved by allowing unconstrained reallocation. Conversely, budget reallocation would not improve the International Union for Conservation of Nature conservation status of threatened Australian birds due to slow rates of transition among conservation states; extinction risk could increase if portfolio reassessment is costly. Although other project prioritization studies may recommend periodic reassessment and reallocation, our findings revealed conditions when reallocation is valuable and demonstrated a structured approach that can help conservation agencies schedule and implement iterative budget-allocation decisions cost-effectively.

Artificial Intelligence Meets Citizen Science to Supercharge Ecological Monitoring

The development and uptake of citizen science and artificial intelligence (AI) techniques for ecological monitoring is increasing rapidly. Citizen science and AI allow scientists to create and process larger volumes of data than possible with conventional methods. However, managers of large ecological monitoring projects have little guidance on whether citizen science, AI, or both, best suit their resource capacity and objectives. To highlight the benefits of integrating the two techniques and guide future implementation by managers, we explore the opportunities, challenges, and complementarities of using citizen science and AI for ecological monitoring. We identify project attributes to consider when implementing these techniques and suggest that financial resources, engagement, participant training, technical expertise, and subject charisma and identification are important project considerations. Ultimately, we highlight that integration can supercharge outcomes for ecological monitoring, enhancing cost-efficiency, accuracy, and multi-sector engagement.

Citizen science and artificial intelligence (AI) are often used in isolation for ecological monitoring, but their integration likely has emergent benefits for management and scientific inquiry. We explore the complementarity of citizen science and AI for ecological monitoring, highlighting key opportunities and challenges. We show that strategic integration of citizen science and AI can improve outcomes for conservation activities. For example, coupling the public engagement benefits of citizen science with the advanced analytical capabilities of AI can increase multi-stakeholder accord on issues of public and scientific interest. Furthermore, both techniques speed up data collection and processing compared with conventional scientific techniques, suggesting that their integration can fast-track monitoring and conservation actions. We present key project attributes that will assist project managers in prioritizing the resources needed to implement citizen science, AI, or preferably both.

Changes in human footprint drive changes in species extinction risk

Predicting how species respond to human pressure is essential to anticipate their decline and identify appropriate conservation strategies. Both human pressure and extinction risk change over time, but their inter-relationship is rarely considered in extinction risk modelling. Here we measure the relationship between the change in terrestrial human footprint (HFP)—representing cumulative human pressure on the environment—and the change in extinction risk of the world’s terrestrial mammals. We find the values of HFP across space, and its change over time, are significantly correlated to trends in species extinction risk, with higher predictive importance than environmental or life-history variables. The anthropogenic conversion of areas with low pressure values (HFP < 3 out of 50) is the most significant predictor of change in extinction risk, but there are biogeographical variations. Our framework, calibrated on past extinction risk trends, can be used to predict the impact of increasing human pressure on biodiversity.

Species extinction risk is difficult to measure and often lags behind the pace of increasing threats. Here, the authors demonstrate how monitoring changes in cumulative human pressures could be used to rapidly assess potential change in species’ conservation status.

Optimal allocation of Red List assessments to guide conservation of biodiversity in a rapidly changing world

The IUCN Red List is the most extensive source of conservation status assessments for species worldwide, but important gaps in coverage remain. Here, we demonstrate the use of a spatial prioritization approach to efficiently prioritize species assessments to achieve increased and up-to-date coverage efficiently. We focus on freshwater fishes, which constitute a significant portion of vertebrate diversity, although comprehensive assessments are available for only 46% of species. We used marxan to identify ecoregions for future assessments that maximize the coverage of species while accounting for anthropogenic stress. We identified a set of priority regions that would help assess one-third (ca 4000 species) of all freshwater fishes in need of assessment by 2020. Such assessments could be achieved without increasing current investment levels. Our approach is suitable for any taxon and can help ensure that species threat assessments are sufficiently complete to guide global conservation efforts in a rapidly changing world.

Toward reassessing data-deficient species

One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data-deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data-deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data-deficient assessments. To develop this, we reviewed 2879 data-deficient assessments in 6 animal groups and identified 8 main justifications for assigning data-deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data-deficient species slipping unnoticed toward extinction.

Chemical antipredator defence is linked to higher extinction risk

Many attributes of species may be linked to contemporary extinction risk, though some such traits remain untested despite suggestions that they may be important. Here, I test whether a trait associated with higher background extinction rates, chemical antipredator defence, is also associated with current extinction risk, using amphibians as a model system-a group facing global population declines. I find that chemically defended species are approximately 60% more likely to be threatened than species without chemical defence, although the severity of the contemporary extinction risk may not relate to chemical defence. The results confirm that background and contemporary extinction rates can be predicted from the same traits, at least in certain cases. This suggests that associations between extinction risk and phenotypic traits can be temporally stable over long periods. The results also provide novel insights into the relevance of antipredator defences for species subject to conservation concerns.