Accurate mapping of species’ distributions and monitoring their temporal changes are critical for ecological research, biodiversity assessment, and conservation planning, especially in response to accelerating global change. Current approaches to mapping species distributions, such as expert-derived maps or species distribution models (SDMs), often face significant limitations, including taxonomic and geographic incompleteness, sampling biases, and insufficient spatial coverage. In contrast, classical species range-mapping approaches based on species records geometry, while simpler and more accessible than SDMs, often lack ecological grounding and precision. Here, we present gbif.range, an R package designed to generate ecologically informed species range maps at various geographical scales by integrating occurrence records with well-known or custom ecoregions. The package offers tailored functions for retrieving, filtering, and customizing occurrence records from the Global Biodiversity Information Facility (GBIF) and associated ecoregion layers. This streamlined workflow significantly reduces technical complexity and improves data integration, making the tool accessible to researchers with varying levels of expertise. We detail the functionalities of gbif.range and showcase its ability to infer species richness distribution at both global and regional scales. At the global scale, we validate gbif.range using data from 381 species, revealing strong concordance correlations with IUCN expert-derived diversity distributions (Lin’s ccc ~0.76) and species range areas (Lin’s ccc ~0.73). Regionally, we illustrate the package’s capacity to assess the accuracy of range maps using various validation data sources. By addressing common barriers such as technical complexity and data availability, gbif.range enables life science researchers, from novices to advanced users, to generate, refine and evaluate species distributions. With the continuous expansion of ecological data sets, gbif.range is expected to mitigate current range mapping limitations, enhancing SDMs outputs and the ecological accuracy and practical relevance of species distribution maps.

Aim The Arctic ecosystems are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. This study assesses, models and maps the geographic patterns of community-level plant species richness in the Western Siberian Arctic and estimates the relative impact of environmental and anthropogenic factors driving these patterns. With our study, we aim at contributing towards conservation efforts for Arctic plant diversity. Location Western Siberian Arctic, Russia. Methods We investigated the relative importance of environmental and anthropogenic predictors of community-level plant species richness in the Western Siberian Arctic using macroecological models trained with an extensive geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non-vascular plants substantially contribute to species richness in the Arctic. Results We found that the mean community-level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South-West to North-East, which can be explained by environmental factors. We found that paleoclimatic factors exhibit higher explained deviance compared to contemporary climate, potentially indicating a lasting impact of ancient climate on tundra species richness. We also show that the existing protected areas cover only a small fraction of the regions with highest species richness. Conclusions Our results reveal complex spatial patterns of community-level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is secondary. We suggest that while plant species richness is mostly driven by environmental factors, an improved spatial sampling is needed to robustly assess anthropogenic impact on species richness. Our approach can be used to design conservation strategies and to investigate drivers of plant species richness in other arctic regions.

Aim The Arctic ecosystems are exposed to amplified climate warming and in some regions to rapidly developing economic activity. This study aims to identify, model and map the patterns of community-level plant species richness in the Western Siberian Arctic and the environmental and anthropogenic factors driving those patterns. With our results and methods, we aim at contributing towards conservation efforts for arctic species richness. Location Western Siberian Arctic, Russia. Methods We investigated the relative impact of environmental and anthropogenic factors on community-level plant species richness of the Western Siberian Arctic, using macroecological models trained with an extensive, newly assembled geobotanical dataset. We included vascular plants, mosses and lichens in our analysis, as non-vascular plants substantially contribute to species richness and ecosystem functions in the Arctic. Results We found that the mean community-level plant species richness in this vast Arctic region does not decrease with increasing latitude. Instead, we identified an increase in species richness from South-West to North-East, which can be explained by climatic, topographical and anthropogenic factors. We found that the lowest species richness is associated with a medium (≈ 35 km) distance to infrastructure while neighboring (<10 km) and remote (≈ 100 km) areas have relatively high species richness. We also show that the existing protected areas cover only a small part of the areas with the highest species richness. Conclusions Our results reveal complex spatial patterns of community-level species richness distribution in the Western Siberian Arctic. We suggest that the impact of economic activities on species richness is ambiguous and not limited to areas directly affected by infrastructure. We show that economic activities along with other factors contribute to heterogeneous distribution of species richness on a broad scale. Our approach and results can be used to develop nature protection strategies for other arctic regions facing similar challenges.

Re-analyzing data from our study, Bruun & Ejrnaes (2022) show that key species to productivity are more abundant than species threatened by extinction. They therefore conclude that biodiversity loss hardly hampers ecosystem processes. Acknowledging the validity of the findings, we clarify why we believe their conclusions are drawn too far.

While the impact of biodiversity, notably functional diversity, on ecosystem productivity has been extensively studied, little is known about the effect of individual species. Here, we identified species of high importance for productivity (key species) in over 28,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness, and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance than all statistics of functional composition. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of all non-environmental predictors increased considerably, and the relationships between functional composition and productivity varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a better consideration of species’ individual effects on ecosystem functioning in complement to community-level measures.