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Chile’s isolation and varied climates have driven the evolution of a unique biodiversity with a high degree of endemism. The Mediterranean-type biome of Central Chile is one of 35 global biodiversity hotspots and has been highlighted as one of Chile’s most endangered areas. It is threatened by anthropogenic land use change impacting the integrity of local biomes and associated species. This area holds the most extensive collections of the country with high endemicity regarding native bee species. Characterising habitat requirements of bees is a pressing priority to safeguard them and the ecosystem services they provide.We investigated broad-scale patterns of bee diversity using newly accessible expert-validated datasets comprising digitized specimen records from both Chilean and US collections and novel, expert-validated type specimen data for the bees of Chile. We used a generalised dissimilarity modelling (GDM) approach to explore both compositional and phylogenetic β-diversity patterns across latitudinal, altitudinal, climate and habitat gradients in well-sampled bee assemblages in Central Chile. Using the GDM measures of increasing compositional and environmental dissimilarity we categorised and compared the most important drivers of these patterns and used them to classify ‘wild bee ecoregions’ (WBE) representing unique assemblages.Turnover of bee assemblages was explained primarily by latitudinal variation (proxy for climate) along Chile. However, temperature variations, precipitation and the presence of bare soil also significantly explained the observed patterns. In comparison, we observed less turnover in phylogenetic biodiversity corresponding to spatial gradients. We were able to develop six de novo ecoregions (WBE) all with distinct taxa, endemic lineages, and representative species. The WBE represent distinct spatial classifications but have similarities to existing biogeographical classifications, ecosystems and bioclimatic zones.This approach establishes the baseline needed to prioritise bee species conservation efforts across this global biodiversity hotspot. We discuss the novelty of this classification considering previous biogeographical characterisations and its relevance for assessing conservation priorities for bee conservation. We argue that Chile’s WBE show areas requiring funding for bee species exploration and description, distribution mapping and strengthening of conservation policies.

Apples are one of the most important global crops that relies heavily on insect pollination, which has been shown to increase apple production and value. However, recent reports indicate that apple production has been declining in certain regions, including in Bhutan. One of the potential causes of declining production are pollination deficits driven by a low abundance and diversity of pollinators, a phenomenon that has received little attention in Bhutan to date. Here, we present the first study examining the diversity of flying insects in Bhutanese apple orchards in relation to apple quality. During the apple flowering season, 1,006 insects comprising 44 unique (morpho-)species from the orders Hymenoptera, Diptera, and Lepidoptera were recorded using a standardized method of passive and active trapping within nine different orchards in Thimphu, Paro, and Haa districts, in the western part of Bhutan. During the harvest season, 495 apples were collected from these nine orchards, and we measured five different parameters; weight, size, sugar concentration, seed number, and malformation score. The most dominant flower visitors across all orchards were honey bees (mostly Apis mellifera, followed by A. cerana and A. dorsata). Orchards with a higher abundance of flying insects (both managed and wild) had better apple quality (weight, size and sugar concentration). Contrary to reports from other regions of the world, flower visitor diversity did not correlate with the quality of the apples. This represents the first study reporting on apple pollination in Bhutan and highlights the importance of pollinators and reinforces the need to develop pollinator friendly practices to ensure sustainable apple production.

Aim: Projections of biodiversity scenarios often rely solely on climate change to inform species distribution shifts in the future. Land use projections are rarely used due to their unavailability and, when available, are often at coarse spatial and thematic resolutions, making them unsuitable to capture fine scale habitat suitability. This study aims to (a) show how coupled land use change (LUC) models of high thematic resolution (HTR) can be used in species distribution models (SDM), (b) compare the impacts of HTR and low thematic resolution (LTR) explanatory predictors on biodiversity scenarios and (c) assess the impact of species' present area of occupancy on the effect of thematic resolution in SDMs. Location: Belgium. Taxon: Bumblebees (Bombus). Methods: We compared species distribution models with 17 land use predictors (HTR) against models with 5 land use predictors (LTR). We modelled the distribution of 17 bumblebee species in Belgium projected until 2035. We examined how model performance, variable importance and projections of distribution change differed depending on the thematic resolution of the land use predictors. Results: Overall, HTR models performed better than LTR models. LTR models predicted greater extent per species. HTR projected a greater percentage of range gains, and both models projected similar losses of suitable habitat. However, the percentage loss and connectivity of suitable habitats varied differently for HTR and LTR models along a gradient of rare to common species. The HTR models projected greater loss of suitable areas for rare species and less loss for common species compared to LTR models. Main conclusions: These results illustrate the importance of using ecologically relevant explanatory variables in SDMs, particularly for rare and localized species with specific habitat requirements. The results also indicate the need for large-scale LUC projections to improve future biodiversity scenarios under climate change and to improve the ability of conservationists and policymakers to use SDM projections., SCOPUS: ar.j, info:eu-repo/semantics/published

info:eu-repo/semantics/published

Aim: Among the numerous anthropogenic pressures threatening biodiversity, habitat destruction and climate change are pointed to as dominant. In response, a number of mitigation strategies are elaborated to save endangered living organisms. However, the taxonomic level and geographical extent at which conservation strategies should be designed and implemented remain generally unclear. Here, we aim to assess and discuss the importance to apply conservation strategies at an appropriate taxonomic scale. For this purpose, we focus our analyses on bumblebees (genus Bombus), a group of critically important and endangered pollinators. Location: West-Palaearctic. Methods: We use a species distribution modelling approach to investigate and compare climatic and habitat-related variables associated with the distribution of West-Palaearctic bumblebees. Our analyses are based on a data set gathering more than 125,000 unique observation points for 68 species. Results: We highlight species-specific associations with climatic and land cover variables, depicting the strong relevance of taxon-specific mitigation strategies for the conservation of those key pollinators. We also identify that the occurrence probability of localized and widespread species is mostly predicted by specific land cover characteristics and climatic conditions, respectively. Finally, we report the general absence of phylogenetic signal associated with the relative importance of each environmental variable in species distribution models, underlining the difficulty to predict species-specific environmental requirements based on evolutionary relationships. Main conclusions: In the light of these results, we conclude that climate change and landscape destruction are not expected to drive the fate of all bumblebee species in a same direction, even for phylogenetically close lineages. We argue in favour of geographically and taxonomically adapted conservation strategies and discuss the limitations of untargeted action plans for species with different climatic/habitat requirements., SCOPUS: ar.j, info:eu-repo/semantics/published

Recent studies have reported on dramatic cases of aerial insect population declines by focusing on the measure of the total biomass of caught insects. However, there is currently no consensus about how biomass patterns among sites and habitats might consistently capture the subtleties of changes in aerial insect community structure. Here, we investigated the relationship between the total biomass of wild bees collected using pan traps in urban, agricultural, and semi-natural habitats on one hand, and a spectrum of biodiversity metrics on the other hand, particularly species richness (SR), alpha diversity, functional diversity (FD) and three different forms of phylogenetic diversity (PD). Our results indicate that although biomass is significantly and highly correlated with the abundance of wild bees, it is generally significantly but only moderately and non-linearly correlated to the various facets of wild bee diversity among habitats. By contrast, we also found that all three measures of PD used are consistent across habitats, suggesting that a taxonomic hierarchy based on Linnaean classification could be used as a proxy for the measurement of PD in wild bees, particularly in other well-studied areas such as Western Europe where a multi-gene molecular phylogeny is unavailable as yet. Collectively, our results illustrate the clear limitations of biodiversity monitoring through measures of trapped insects biomass. We advocate for more robust measures of biodiversity trends in wild bees, requiring both standardized surveys, and the identification of caught specimens down to the species level to capture the subtleties of species, traits-based and phylogeny-based community changes across habitats or time. Scaling out this approach is an essential prerequisite for more global conservation planning tailored to the ecological requirements of the targeted insect species.

Agricultural intensification and loss of semi-natural grassland have contributed to biodiversity decline, including pollinator species, in pastures around the world. To reverse the decline, agri-environmental schemes have been implemented, varying widely in effectiveness. In addition, many countries, including the Netherlands, have established nature reserves in which semi-natural grasslands are restored and are often managed for specific groups of species, e.g. meadow birds or plants. The effects of such measures on insect biodiversity are not well known but recent reports on the dramatic decline of insect biomass in nature reserves have put even more attention to the impact of land use and management on biodiversity. This study compares pollinator abundance and species richness in three common semi-natural grassland management types in the Netherlands: (1) hay meadows, (2) herb-rich grasslands and (3) meadow bird grasslands. Pollinator abundance and species richness were assessed in eleven study areas, each with all three management types present. Standardized transects, insect sampling within a standard 20 min time frame and plot-based flower surveys were used in spring and summer to assess the relationships between management regime, floral abundance and diversity and pollinator communities. The results show that meadow bird grasslands have lower pollinator abundance and diversity and a less unique pollinator assemblage than both other types. Moreover, flower abundance has a positive effect on pollinator abundance and flower diversity has a positive effect on pollinator species richness. These results indicate that meadow-bird grasslands are a comparatively unfavourable habitat for bees, hoverflies and butterflies, which may be explained by a lack of flowers as well as unsuitable mowing practices. Measures benefitting both insectivorous birds and flower-visiting insects, such as rotational mowing, could remediate this imbalance. (C) 2019 The Authors. Published by Elsevier GmbH on behalf of Gesellschaft fur Okologie.

Aim: Biodiversity is rapidly disappearing at local and global scales also affecting the functional diversity of ecosystems. We aimed to assess whether functional diversity was correlated with species diversity and whether both were affected by similar land use and vegetation structure drivers. Better understanding of these relationships will allow us to improve our predictions regarding the effects of future changes in land use on ecosystem functions and services. Location: The Netherlands. Methods: We compiled a dataset of c. 3 million observations of 66 out of 106 known Dutch butterfly species collected across 6,075 sampling locations during a period of 7 years, together with very high-resolution maps of land use and countrywide vegetation structure data. Using a mixed-effects modelling framework, we investigated the relationship between functional and species diversity and their main land use and vegetation structure drivers. Results: We found that high species diversity does not translate into high functional diversity, as shown by their different spatial distribution patterns in the landscape. Functional and species diversity are mainly driven by different sets of structural and land use parameters (especially average vegetation height, amount of vegetation between 0.5 and 2 m, natural grassland, sandy soils vegetation, marsh vegetation and urban areas). We showed that it is a combination of both vegetation structural characteristics and land use variables that defines functional and species diversity. Main conclusions: Functional diversity and species diversity of butterflies are not consistently correlated and must therefore be treated separately. High functional diversity levels occurred even in areas with low species diversity. Thus, conservation actions may differ depending on whether the focus is on conservation of high functional diversity or high species diversity. A more integrative analysis of biodiversity at both species and trait levels is needed to infer the full effects of environmental change on ecosystem functioning.

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs' usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques., info:eu-repo/semantics/published