Eimear Nic Lughadha

Societal Impact Statement: As of 2026, fewer than 23% of vascular plants have International Union for the Conservation of Nature (IUCN) Red List assessments, despite accelerating threats to biodiversity. Predictive models of extinction risk complement assessments and help prioritize conservation action but face a trade‐off between data resolution and species coverage. Using Ethiopian endemic flowering plants, we found that medium‐scale spatial data—similar to provinces or counties—strike a balance between resolution and coverage, improving predictive performance. Because these data can be obtained from multiple sources, including textual records, our approach can be implemented in future prediction models, helping experts direct limited resources toward species most at risk. Summary: Extinction risk predictions complement conservation assessments but are limited by available data, creating a trade‐off between resolution and taxonomic completeness. Fine‐scale predictors offer greater resolution but exclude data‐limited species, whereas coarse‐scale predictors maximize species coverage but lack resolution—especially at smaller scales. Recent comprehensive extinction risk assessment of Ethiopia's endemic angiosperms provides an opportunity to investigate the robustness of extinction risk predictions and identify patterns or systematic biases at a national scale. Here, we interrogate the performance of coarse‐scale predictions from Bachman et al. (2024) for Ethiopian endemics, using patterns in misclassifications to identify additional (protected area) and refined (geographic range size and human footprint) predictors that could improve future models. We found that number of floristic regions (similar in scale to provinces) significantly outperformed point‐based range size metrics (extent of occurrence and area of occupancy), and that recalculating human footprint at floristic region‐scale improved predictive performance. Protected area coverage did not improve model performance. While coordinates can be impossible to pinpoint for many records, administrative units can be obtained from textual data, unlocking more possibilities for georeferencing. By leveraging medium‐scale predictors, our approach balances resolution and taxonomic completeness, offering a scalable path to substantially improve global extinction risk predictions.

Aim: Effective implementation of the Global Biodiversity Framework and Global Strategy for Plant Conservation relies on accurate species distribution data. However, current vascular plant distribution data are often sparse and biased, requiring significant expansion. This study develops a scalable framework to prioritize areas for plant occurrence data acquisition, enabling botanical institutions to coordinate efforts and allocate resources efficiently. Location: Global and regional. Methods: Using a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) analysis, we prioritized areas based on: (a) ecosystem service value; (b) floristic value threatened by climate or land‐use change; and (c) uncertainty in species richness estimates. Analyses were stratified into tree‐dominated and grassland/deforested biomes. Prioritization maps were generated globally and for five major regions, then validated by field experts to ensure ecological relevance. Results: The data‐driven priority maps achieved high consensus among field experts, and high similarity between global and regional outputs demonstrated the model's scalability. By explicitly modelling sampling bias rather than relying on raw occurrence data, our framework successfully identified globally critical but historically overlooked areas for future data acquisition, such as Amazonia, the Putorana Plateau and Canada's Hudson Plain. Main Conclusions: Our approach provides a transparent, adaptable tool for supporting national implementation of the Global Biodiversity Framework. A key advantage of this framework is its capacity to systematically translate expert opinion into explicit, quantitative criteria, which facilitates clear communication with policymakers and funders. By prioritizing data acquisition through tailored variables and weightings, this research promotes the efficient use of limited resources to address global biodiversity knowledge gaps.

RISNA, R. A., LUGHADHA, E. N., PRASETYO, L. B., SUTOMO, AIDI, M. N., BUCHORI, D., PLUMMER, J., LATIFAH, D., YUSWANDI, A. Y. & YUDISTIRA, A. I. 2026. Climate-driven range shifts threaten keystone endemic figs of Java: complementing IUCN Red List assessment with species distribution modelling to guide conservation priorities. Reinwardtia 25(1): 49‒63. — This study evaluates the extinction risk and climate-driven habitat dynamics of two endemic figs of Java, Ficus trachycoma Miq. and F. miqueliana C.C.Berg. Both species are poorly known, with no confirmed field records for more than six decades. Conservation status was assessed under IUCN Red List criteria, with extent of occurrence (EOO) and area of occupancy (AOO) calculated using validated herbarium records. Ficus trachycoma is restricted to a single 19th-century locality, with an EOO and AOO of 4 km², a single known location, and continuing decline in habitat, qualifying it as Critically Endangered. Ficus miqueliana has been more widely recorded, with an AOO of 20 km² and an EOO of about 600 km², ≤5 locations, and continuing decline in habitat, meeting the thresholds for Endangered. Species distribution modelling using MaxEnt and CMIP6 climate projections (SSP2-4.5 and SSP5-8.5) was applied to predict current and future habitat suitability. The models performed with high accuracy (AUC = 0.912‒0.935, TSS = 1.0) and identified slope (52–73% contribution), temperature seasonality, and precipitation in the wettest, warmest, and coldest quarters as key predictors of occurrence. Ficus miqueliana’s current suitable habitat is 16,233 km² (12.4% of Java) in fragmented lowland and foothill forests. CMIP6 projections (MIROC6, SSP2-4.5/SSP5-8.5 for 2050s and 2090s) forecast net contractions with upslope shifts: mid-century losses of 9–11% in Java, late-century persistence in montane refugia under moderate emissions but severe fragmentation under high emissions. These findings demonstrate that both endemic figs are highly vulnerable to environmental change. Applying IUCN Red List assessments alongside species distribution modelling provides a replicable framework for evaluating extinction risk in data-limited species and identifies priority areas for climate-adaptive conservation planning on Java.

Societal Impact Statement: Plants sustain all life, providing the energetic and structural basis of ecosystems, but they face a growing risk of extinction. Reversing this decline requires an understanding of how scientific knowledge is distributed among species and identification of the biases and gaps that hinder effective responses to the threats they face. However, we reveal here that most threatened species remain understudied, while research focuses on nonthreatened species and a few species of economic value. Given this imbalance, we offer some suggestions for plant scientists, aiming to address gaps and biases and expand scientific knowledge. Summary: Scientific knowledge plays a vital role in guiding evidence‐based conservation efforts. However, not all species receive equal attention, and the scientific literature reflects structural biases that are often difficult to quantify. Here, we assessed how scientific attention to plant species in Brazil varies across extinction risk categories and identified the intrinsic and contextual factors shaping their representation in scientific studies. We analyzed 7524 native Brazilian species formally assessed for extinction risk, integrating systematic Web of Science searches with a complementary statistical framework to quantify and compare species‐level visibility and publication dynamics. The most threatened species receive less scientific attention, including a lower proportion of species studied and fewer publications per species throughout the study period compared to nonthreatened species. Although multiple factors influence scientific attention, economic value emerged as the strongest predictor of publication volume, exceeding conservation urgency and other factors. Scientific attention to Brazilian plants is misaligned with conservation needs, introducing systematic biases into the knowledge base that underpins research prioritization, conservation planning, and environmental policy.

Global biodiversity policies recognize the necessity to preserve evolutionary lineages, as their diversity underpins current and future benefits to people and the future of life on Earth. Plants are largely absent from global biodiversity assessments, resulting in a taxonomic imbalance that has undermined their conservation for decades. We present a tree of life and extinction risk estimates for all species of flowering plants (angiosperms), representing a global assessment of their threatened evolutionary history. We estimate that 21.2% of angiosperm evolutionary history is at risk of extinction and identify 9945 priority species that disproportionately account for total threatened evolutionary history. These prioritizations serve to redress imbalances between plants and animals, monitor conservation effectiveness, and optimize resource allocation in the face of increasing human pressures on biodiversity.

Aim: Effective implementation of the Global Biodiversity Framework and Global Strategy for Plant Conservation depends on accurate species distribution data. Current vascular plant distribution data, while crucial for understanding terrestrial ecosystems, is often sparse and biased and requires significant expansion. This study developed a scalable approach to prioritize areas for plant occurrence data acquisition, adaptable to national priorities and providing a framework for botanical institutions to coordinate efforts and allocate resources. Location: Global. Methods: Using a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) analysis, we prioritized areas based on: (a) ecosystem service value; (b) floristic value threatened by climate or land-use change; and (c) uncertainty in species richness estimates, stratified by biome and region. Regional prioritization maps for Africa & Madagascar; East, South and Southeast Asia; Siberia and the Russian Far East; South America; and North & Central America were reviewed by botanical experts for validation. Scalability was assessed by comparing regional and global analyses. Results: Data-driven priority maps, divided into tree-dominated and grassland/deforested areas, largely received expert support. High similarity between global and regional maps demonstrated scalability. Main conclusions: Our approach provides a framework for supporting national implementation of the Global Biodiversity Framework. Variables and their weights can be tailored to national or local needs. The method’s flexibility and adaptability extend to other taxonomic groups and objectives, such as protected area selection By prioritizing data acquisition, whether field-based or digital, this research promotes the efficient use of resources. A key advantage of this approach is its capacity to systematically translate expert opinion into explicit and quantitative criteria, which in turn facilitates clear communication with policymakers and funders.

Species in big angiosperm genera (≥500 species) are often considered to be less well-known than those in smaller genera. Consequently, species in big genera are likely underrepresented in conservation at all levels, from analyses to actions. However, emerging evidence indicates that species in larger genera tend to have smaller geographic ranges (a strong correlate of increased extinction risk). Here, we test the generality of this pattern by quantifying the relationships between plant taxon size, extinction risk and climatic zone on a global scale. We find that species in larger genera are more likely to have small ranges, less likely to have a global Red List assessment, and, when assessed, are more likely to be threatened. Persistent obstacles to improving conservation documentation of big genera include taxonomic uncertainty, data shortfalls and number of species involved, requiring continued collaboration between taxonomy and conservation to reduce this bias and enable effective conservation of the quarter of plant species that big genera encompass. Article Impact Statement: Species in big angiosperm genera are under-studied, under-assessed, and their extinction risk has been underestimated.

For over a century, epiphytes have been considered to have larger geographic ranges than terrestrial plants, yet this assumption is based on studies at restricted geographic and taxonomic scales and is contradicted by recent research. Misunderstanding the ranges of epiphytes may distort perceptions of their extinction risk. To address this, here we analysed global data on 330,087 angiosperm species, including 27,184 epiphytes, comparing range size and rarity between epiphytes and terrestrial plants. We calculated three range metrics, tested for differences across angiosperms and within epiphyte-rich families and used phylogenetic regressions to explore the role of epiphytism on species ranges. On average, epiphytes have larger ranges than closely related terrestrial species, supporting hypotheses that epiphytism promotes dispersal. However, small ranges are prevalent in epiphyte-rich families regardless of lifeform. Notably, about half of epiphyte species are rare, indicating greater vulnerability than terrestrials. Epiphyte rarity is attributable to evolutionary history and shared traits rather than epiphytism itself.

Extinction results in not only loss of species, but also loss of the unique evolutionary history that they represent and the irreplaceable features they exhibit. There is broad consensus regarding the necessity to optimise the preservation of the tree of life by including evolutionary information in conservation prioritisation, a notion also endorsed by major policy frameworks ^1–4 . However, evolutionarily-informed prioritisations are lacking for most plants, resulting in a taxonomic imbalance in the evolutionary information incorporated in global biodiversity analyses, which has undermined conservation for decades. Here, we use comprehensive species-level phylogenetic trees, and extinction risk estimates, to generate the first global assessment of angiosperm evolutionary history at risk, and to identify phylogenetically-informed conservation priorities for the world’s flowering plants. We estimate that more than one fifth of angiosperm evolutionary history is at risk of extinction in the short term. Using the Evolutionarily Distinct and Globally Endangered ^5,6 approach, we identify 9,945 threatened plant species that disproportionately account for total evolutionary history at risk. Species and area prioritisations incorporating evolutionary history are urgently needed to correct imbalances between plants and animals, monitor the effectiveness of conservation efforts, and optimise conservation resource allocation in the face of increasing human pressures on Earth’s biodiversity.