Nicolas J. Vereecken

Aim: Stingless bees are the most species‐rich group of eusocial bees, predominantly found in tropical and subtropical regions of the world. However, despite their diversity and importance, significant gaps remain in our understanding of their distribution patterns and the factors driving them, as these aspects have yet to be thoroughly investigated on a global scale. In this study, we aimed to fill this gap by mapping global habitat suitability for stingless bees. Location: Global. Taxon: Stingless bees (Apidae:Apinae:Meliponini). Method: We compiled over half a million spatiotemporal occurrence records from 361 species of stingless bees at an unprecedented scale from both public and private databases optimised using a recently published data‐cleaning workflow. Through a species distribution model approach, we assessed the relationship between stingless bee distribution, diversity, and environmental factors, ultimately characterising their ecological niche and producing the first habitat suitability maps for the bee tribe Meliponini. Results: Our results reveal significant discrepancies in occurrence records across the Neotropical, the Afrotropical, and the Indo‐Malayan, Papuasian, and Australian regions, as well as among taxa. Habitat suitability hotspots were identified in tropical forests and were associated with relatively high temperatures and humidity throughout the year. Projection maps further suggested that some temperate, xeric, and savannah regions could also be suitable habitats for stingless bees. Our results rescale the known environmental niche of stingless bees, demonstrating that suitable habitats exist well beyond the tropical and subtropical boundaries typically described in the literature. Main Conclusion: This study presents a novel, model‐based assessment of stingless bee distribution, revealing that it extends beyond tropical forests into drier, colder, and temperate regions more broadly than previously recognised. These findings highlight substantial gaps in ecological and distributional data, emphasising the need for taxonomic revision, targeted fieldwork, digitisation of collections, and foundational research on stingless bee ecology and evolution. Addressing these gaps will improve predictions of species responses to environmental change, inform conservation strategies, and advance understanding of stingless bees as essential providers of ecosystem services.

Madagascar hosts exceptional biodiversity and endemism, yet its native bee fauna remains poorly characterised. We assembled and cleaned the first comprehensive occurrence dataset for Malagasy bees, reducing 10,721 raw records to 4,071 validated occurrences covering 218 georeferenced species of the 224 checklist species across six families (89.3% endemic). Despite near-complete checklist coverage, the dataset remains critically sparse for Madagascar’s size, with most species documented by only a few records. Sampling was highly uneven across taxa: most genera were underrepresented while a few were disproportionately sampled due to ecological prevalence, detectability, and collector specialisation. Spatial concentration within limited grid cells amplified these biases. Temporally, effort varied markedly, with historical peaks driven by individual collectors and a post-2010 shift toward Apidae-dominated records. Spatially, 79.9% of 25×25 km grid cells intersecting Madagascar held no bee records, and 77.1% of records fell within 2.5 km of roads, mirroring global sampling patterns. Sampling clustered near major cities, with common species consistently found near roads and rare species spread across wider distance ranges. Among 231 Key Biodiversity Areas (KBAs), 68.4% were entirely unsampled; sampled KBAs held only 26.7% of all records, and sampling remained uneven even there, leaving substantial undetected diversity across most sites. These results reveal pervasive temporal, spatial, taxonomic, and collector-driven biases, underscoring the need for targeted surveys within KBAs and beyond roadsides to improve coverage of data-deficient species and strengthen conservation assessments.

Agricultural intensification is a major driver of soil biodiversity loss, threatening the ecosystem services provided by earthworms, often described as key engineers of soil structure and fertility. While earthworms are known to be affected by tillage and pesticide use, most studies rely on farming system comparisons (e.g. organic vs. conventional or tilled vs. no-till) and taxonomic metrics only, overlooking within-system practice variability and earthworm functional community responses.To address these limitations, we conducted a two-year survey across 43 on-farm winter cereal fields in Wallonia (Belgium), quantifying earthworm communities alongside continuous indicators of tillage intensity, pesticide pressure, and other management practices, combined with a trait-based functional approach.We show that continuous gradients of tillage intensity and soil pesticide residues outperform farming system classification for explaining earthworm community responses, because practice intensities overlapped extensively across systems. Soil tillage intensity (STIR) was the most consistent predictor: high-intensity tillage reduced density, biomass and species richness by 60–75% relative to low-disturbance sites, with inversion tillage and operations at 10–20 cm being the most critical components. Farming systems showed no consistent effects on most biodiversity metrics, apart from biomass, which was significantly lower in organic than in conservation agriculture systems. Soil pesticide residues selectively restructured functional trait composition without affecting abundance metrics, shifting assemblages from surface-dwelling species towards intermediate-depth dwellers (5–20 cm), with larger reproductive investment and lower mass-to-length ratios.Our results demonstrate that taxonomic and functional approaches capture distinct and complementary dimensions of agricultural impacts. Moving beyond farming system labels towards continuous practice-intensity gradients offers a stronger predictive framework for earthworm conservation. We anticipate this approach will provide farmers and policymakers with more actionable levers to simultaneously reduce mechanical and chemical soil disturbance, irrespective of system-level certification.

1. Arid and semi-arid ecosystems cover 40.6% of Earth's land surface and support 2.3 billion people (UNCCD 2024), providing critical ecosystem services including wood production, carbon sequestrati...

Islands harbor a disproportionate share of global biodiversity ¹ , yet insects, even invaluable pollinators such as bees ² , remain underrepresented in island biogeography research ³ . Here, we present the first global checklist of island bees, recording 4,140 species across 306 islands. Although islands comprise only ∼5% of Earth’s land area, they support ∼20% of global bee diversity, and 43% of insular species are endemic, making up ∼8% of all known bee species. Island bee species richness, mirroring continental trends ⁴ , peaks at mid-latitudes. Native richness increases with island area and declines with isolation, consistent with patterns in other taxa ⁵ . The strength of species–area relationships varies among biomes and is steepest in mediterranean-type systems, which also support disproportionately high bee richness relative to flowering plant diversity. Endemism is highest on large tropical islands, reflecting extensive in situ diversification. Major centers of bee endemism include Madagascar, Malesia (e.g. the Greater Sundas and New Guinea), and Hawai’i, where a single large radiation of Hylaeus ( Nesoprosopis ) dominates ⁶ . Among islands capable of supporting endemic species, endemism scales strongly with total richness. These findings highlight the need to integrate island bee diversity into global conservation planning and position bees as a model for understanding insect evolution and conservation on islands.

This perspective paper examines the multifaceted cultural ecosystem services (CESs) provided by wild bees with particular attention to the spiritual, medicinal, and traditional knowledge-based dimensions associated with Afrotropical stingless bees. We integrate these insights within a biocultural framework, highlighting their relational values and arguing that the systematic omission of these cultural roles in pollinator research, policy and conservation constitutes a form of epistemic injustice. We also argue that the systematic recognition and documentation of these cultural roles are critical to advancing more inclusive and effective conservation frameworks. Based on a synthesis of field observations, photo-documentation, and literature review, we propose future research and policy directions aimed at embedding these cultural values more comprehensively within biocultural conservation strategies.

Managed and wild bees contribute not only to ecological functions and agricultural productivity, but also to a wide range of cultural ecosystem services (CES) structuring human livelihoods and that remain largely overlooked in pollinator research, policy and conservation. This article examines the multifaceted CES provided by wild bees, with particular attention to the spiritual, medicinal, and traditional knowledge-based dimensions associated with Afrotropical stingless bees. We argue that systematic recognition and documentation of these cultural roles are critical to advancing more inclusive and effective conservation frameworks. Drawing on examples from sub-Saharan Africa, we demonstrate how CES simultaneously support biodiversity objectives and strengthen community resilience, and we propose future research and policy directions aimed at embedding these cultural values more comprehensively within conservation strategies.

Apple is one of the most important pollinator‐dependent fruit crops worldwide. To secure high‐quality yields, it is crucial to know which, and to what extent, pollinating insects contribute to its pollination success as measured by fruit set, fruit weight and seed set. We perform a meta‐analysis of field studies conducted across multiple orchards on insect‐mediated pollination in apple cultivation, using raw data from 29 studies, totalling 532 orchard replicates. We assessed the extent of pollen limitation on different pollination outcomes and assessed the contribution of honeybees, wild bees and bee species richness to apple pollination. Across all studies, we detected strong evidence of pollen limitation for fruit set and seed set, but not for fruit weight. Honeybees were the most abundant flower visitors (average relative visitation of 71.9%) compared to wild bees; but when correcting for their pollination efficiency, the relative pollination contribution of honeybees was lower compared to their relative visitation (vice versa for solitary bees). We conclude that honeybee visitation rate did not influence fruit or seed set; yet increasing honeybee visitation had a small, negative effect on fruit weight. Fruit set was not influenced by wild bee visitation rate, whereas wild bee visitation had a small, but clear positive effect on fruit weight and seed set. Bee species richness had a small, positive effect on seed set; whereas it did not affect fruit set and fruit weight. Syntheses and applications. Our study highlights that pollen limitation is common in this global crop. While managed honeybees are dominant pollinators, a diverse community of wild bees contributes significantly to apple pollination and high‐quality yield. The positive effect of wild bees and species richness on fruit weight and seed set demonstrates that wild bee pollination results in better‐quality fruit production (increased weight & seed set). Therefore, our synthesis highlights the importance of conserving pollinator diversity to maintain pollination services. The absence of a clear effect of honeybee visitation rate on fruit and seed set, coupled with its negative impact on fruit weight, suggests a need for further optimisation of honeybee management to improve the cost‐efficiency of pollination management.

Promoting diverse and abundant flowering plants in cities is essential to counteract the decline in wild bee diversity due to urbanisation. To support effective conservation, it is crucial to identify which flowers best enhance wild bee abundance and species richness. This requires large datasets and robust analytical tools. Here, we use a plant selection tool developed by M’Gonigle et al. (2016), which recommends flower mixes that maximise pollinator species richness based on visitation data. We analysed bee-flower interaction data from the Brussels Capital Region (Belgium), comparing two contrasting sources: (1) citizen science records and (2) standardised academic surveys. We evaluated the bipartite networks of these datasets and their combination and generated optimised flower mixes from each using the plant selection tool. Our results show that dataset composition and inherent biases strongly influence outcomes. The bipartite networks differed substantially (compositional difference = 0.86), mainly due to rewiring of bee-flower interactions (0.69). Consequently, the flower mixes derived from each dataset overlapped by only 7% when optimising for species richness. The combined dataset network more closely resembled the citizen science data (WN = 0.106) than the academic survey data (WN = 0.590). These findings highlight the substantial impact of data collection methods on ecological recommendations. Awareness of such biases is essential for making sound, evidence-based conservation decisions. To support wider application, we developed a free app that allows users to create flower mixes optimized for pollinator abundance, species richness, or both, using our dataset or their own.

The InsectAI COST action will support insect monitoring and conservation at the national and continental scale in order to understand and counteract widespread insect declines. The Action will bring together a critical mass of researchers and stakeholders in image-based insect AI technologies to direct and drive the research agenda, build research capacity across Europe and support innovation and application. There is mounting evidence that populations of insects around the world are in sharp decline. Understanding trends in species and their drivers is key to knowing the size of the challenge, its causes and how to address it. To identify solutions that lead to sustainable biodiversity alongside economic prosperity, insect monitoring should be efficient and provide standardised and frequently updated status indicators to guide conservation actions. The EU Biodiversity Strategy 2030 identifies the critical challenge of delivering standardised information about the state of nature and image-based insect AI can contribute to this. Specifically, the EU Nature Restoration Law will likely set binding targets for the high resolution data that cameras can provide. Thus, outputs of the Action will contribute directly to EU policies implementation, where biodiversity monitoring is considered a key component. The InsectAI COST Action will organise workshops, conferences, short-term scientific missions, hackathons, design-sprints and much more, across four Working Groups. These groups will address how image-based insect AI technologies can best address Societal Needs, support innovation in Image Collection hardware, create standardised approaches for Image Processing and develop novel Data Analysis and Integration methods for turning data into actionable insights.