Bumblebee resilience to climate change, through plastic and adaptive responses.

Bumblebees are ubiquitous, cold-adapted eusocial bees found worldwide from subarctic to tropical regions of the world. They are key pollinators in most temperate and boreal ecosystems, and both wild and managed populations are significant contributors to agricultural pollination services. Despite their broad ecological niche at the genus level, bumblebee species are threatened by climate change, particularly by rising average temperatures, intensifying seasonality and the increasing frequency of extreme weather events. While some temperature extremes may be offset at the individual or colony level through temperature regulation, most bumblebees are expected to exhibit specific plastic responses, selection in various key traits, and/or range contractions under even the mildest climate change. In this review, we provide an in-depth and up-to-date review on the various ways by which bumblebees overcome the threats associated with current and future global change. We use examples relevant to the fields of bumblebee physiology, morphology, behaviour, phenology, and dispersal to illustrate and discuss the contours of this new theoretical framework. Furthermore, we speculate on the extent to which adaptive responses to climate change may be influenced by bumblebees' capacity to disperse and track suitable climate conditions. Closing the knowledge gap and improving our understanding of bumblebees' adaptability or avoidance behaviour to different climatic circumstances will be necessary to improve current species climate response models. These models are essential to make correct predictions of species vulnerability in the face of future climate change and human-induced environmental changes to unfold appropriate future conservation strategies.

Bumblebees moving up: shifts in elevation ranges in the Pyrenees over 115 years.

In a warming climate, species are expected to shift their geographical ranges to higher elevations and latitudes, and if interacting species shift at different rates, networks may be disrupted. To quantify the effects of ongoing climate change, repeating historical biodiversity surveys is necessary. In this study, we compare the distribution of a plant-pollinator community between two surveys 115 years apart (1889 and 2005-06), reporting distribution patterns and changes observed for bumblebee species and bumblebee-visited plants in the Gavarnie-Gèdre commune in the Pyrenees, located in southwest Europe at the French-Spanish border. The region has warmed significantly over this period, alongside shifts in agricultural land use and forest. The composition of the bumblebee community shows relative stability, but we observed clear shifts to higher elevations for bumblebees (averaging 129 m) and plants (229 m) and provide preliminary evidence that some bumblebee species shift with the plants they visit. We also observe that some species have been able to occupy the same climate range in both periods by shifting elevation range. The results suggest the need for long-term monitoring to determine the role and impact of the different drivers of global change, especially in montane habitats where the impacts of climate changes are anticipated to be more extreme.

Shift in size of bumblebee queens over the last century.

Species can respond differently when facing environmental changes, such as by shifting their geographical ranges or through plastic or adaptive modifications to new environmental conditions. Phenotypic modifications related to environmental factors have been mainly explored along latitudinal gradients, but they are relatively understudied through time despite their importance for key ecological interactions. Here we hypothesize that the average bumblebee queen body size has changed in Belgium during the last century. Based on historical and contemporary databases, we first tested if queen body sizes changed during the last century at the intraspecific level among four common bumblebee species and if it could be linked to global warming and/or habitat fragmentation as well as by the replacement by individuals from new populations. Then, we assessed body size changes at the community level, among 22 species, taking into account species population trends (i.e. increasing, stable or decreasing relative abundance). Our results show that the average queen body size of all four bumblebee species increased over the last century. This size increase was significantly correlated to global warming and habitat fragmentation, but not explained by changes in the population genetic structure (i.e. colonization). At the community level, species with stable or increasing relative abundance tend to be larger than declining species. Contrary to theoretical expectations from Bergmann's rule (i.e. increasing body size in colder climates), temperature does not seem to be the main driver of bumblebee body size during the last century as we observed the opposite body size trend. However, agricultural intensification and habitat fragmentation could be alternative mechanisms that shape body size clines. This study stresses the importance of considering alternative global change factors when assessing body size change.

The interplay of climate and land use change affects the distribution of EU bumblebees.

Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns.

A joint model for the estimation of species distributions and environmental characteristics from point-referenced data.

BACKGROUND: Predicting and explaining species occurrence using environmental characteristics is essential for nature conservation and management. Species distribution models consider species occurrence as the dependent variable and environmental conditions as the independent variables. Suitable conditions are estimated based on a sample of species observations, where one assumes that the underlying environmental conditions are known. This is not always the case, as environmental variables at broad spatial scales are regularly extrapolated from point-referenced data. However, treating the predicted environmental conditions as accurate surveys of independent variables at a specific point does not take into account their uncertainty. METHODS: We present a joint hierarchical Bayesian model where models for the environmental variables, rather than a set of predicted values, are input to the species distribution model. All models are fitted together based only on point-referenced observations, which results in a correct propagation of uncertainty. We use 50 plant species representative of the Dutch flora in natural areas with 8 soil condition predictors taken during field visits in the Netherlands as a case study. We compare the proposed model to the standard approach by studying the difference in associations, predicted maps, and cross-validated accuracy. FINDINGS: We find that there are differences between the two approaches in the estimated association between soil conditions and species occurrence (correlation 0.64-0.84), but the predicted maps are quite similar (correlation 0.82-1.00). The differences are more pronounced in the rarer species. The cross-validated accuracy is substantially better for 5 species out of the 50, and the species can also help to predict the soil characteristics. The estimated associations tend to have a smaller magnitude with more certainty. CONCLUSION: These findings suggests that the standard model is often sufficient for prediction, but effort should be taken to develop models which take the uncertainty in the independent variables into account for interpretation.

Are threatened species special? An assessment of Dutch bees in relation to land use and climate.

Red Lists are widely used as an indicator of the status and trends of biodiversity and are often used in directing conservation efforts. However, it is unclear whether species with a Least Concern status share a common relationship to environmental correlates compared to species that are on the Red List. To assess this, we focus here on the contribution and correlates of land use, climate, and soil to the occurrence of wild bees in the Netherlands. We used observation data and species distribution models to explain the relation between wild bees and the environment. Non-threatened bees had a relatively higher variable importance of the land use variables to their models, as opposed to the climate variables for the threatened bees. The threatened bees had a smaller extent of occurrence and occupied areas with more extreme climatic conditions. Bees with a Least Concern status showed more positive responses to urban green spaces and Red List species showed a different response to climatic variables, such as temperature and precipitation. Even though Red List bees were found in areas with a higher cover of natural areas, they showed a more selective response to natural land use types. Pastures and crops were the main contributing land use variables and showed almost exclusively a negative correlation with the distribution of all wild bees. This knowledge supports the implementation of appropriate, species-specific conservation measures, including the preservation of natural areas, and the improvement of land use practices in agricultural and urban areas, which may help mitigate the negative impacts of future global change on species' distributions.

Importance of natural land cover for plant species' conservation: A nationwide study in The Netherlands.

While shifts to high-intensity land cover have caused overwhelming biodiversity loss, it remains unclear how important natural land cover is to the occurrence, and thus the conservation, of different species groups. We used over 4 million plant species' observations to evaluate the conservation importance of natural land cover by its association with the occurrence probability of 1 122 native and 403 exotic plant species at 1 km resolution by species distribution models. We found that 74.9% of native species, 83.9% of the threatened species and 77.1% rare species preferred landscapes with over 50% natural land cover, while these landscapes only accounted for 15.6% of all grids. Most species preferred natural areas with a mixture of forest and open areas rather than areas with completely open or forested nature. Compared to native species, exotic species preferred areas with lower natural land cover and the cover of natural open area, but they both preferred extremely high and low cover of natural forest area. Threatened and rare species preferred higher natural land cover, either cover of natural forest area or cover of natural open area than not threatened and common species, but rare species were also more likely to occur in landscapes with 0-25% cover of natural open area. Although more natural land cover in a landscape will not automatically result in more native species, because there is often a non-linear increase in species occurrence probability when going from 0% to 100% natural land cover, for conserving purposes, over 80% natural land cover should be kept in landscapes for conserving threatened and very rare species, and 60% natural land cover is the best for conserving common native species. Our results stress the importance of natural areas for plant species' conservation. It also informs improvements to species conservation by increasing habitat diversity.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type.

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.