Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While ...Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species' data characteristics (i.e. sample size, spatial distribution).
The global increase in the proportion of land cultivated with pollinator‐dependent crops implies increased reliance on pollination services. Yet agricultural practices themselves can profoundly ...affect pollinator supply and pollination. Extensive monocultures are associated with a limited pollinator supply and reduced pollination, whereas agricultural diversification can enhance both. Therefore, areas where agricultural diversity has increased, or at least been maintained, may better sustain high and more stable productivity of pollinator‐dependent crops. Given that >80% of all crops depend, to varying extents, on insect pollination, a global increase in agricultural pollinator dependence over recent decades might have led to a concomitant increase in agricultural diversification. We evaluated whether an increase in the area of pollinator‐dependent crops has indeed been associated with an increase in agricultural diversity, measured here as crop diversity, at the global, regional, and country scales for the period 1961–2016. Globally, results show a relatively weak and decelerating rise in agricultural diversity over time that was largely decoupled from the strong and continually increasing trend in agricultural dependency on pollinators. At regional and country levels, there was no consistent relationship between temporal changes in pollinator dependence and crop diversification. Instead, our results show heterogeneous responses in which increasing pollinator dependence for some countries and regions has been associated with either an increase or a decrease in agricultural diversity. Particularly worrisome is a rapid expansion of pollinator‐dependent oilseed crops in several countries of the Americas and Asia that has resulted in a decrease in agricultural diversity. In these regions, reliance on pollinators is increasing, yet agricultural practices that undermine pollination services are expanding. Our analysis has thereby identified world regions of particular concern where environmentally damaging practices associated with large‐scale, industrial agriculture threaten key ecosystem services that underlie productivity, in addition to other benefits provided by biodiversity.
Increasing cultivation of pollinator‐dependent crops has placed a stress on global pollination capacity, which could have been ameliorated by a concomitant increase in agricultural diversification. However, this study reports a relatively weak and decelerating rise in agricultural diversity over time that was largely decoupled from the strong and continually increasing trend in agricultural dependency on pollinators. Particularly worrisome is a rapid expansion of pollinator‐dependent monocultures in several countries of the Americas and Asia that has resulted in a decrease in agricultural diversity. In these regions, reliance on pollinators is increasing, yet agricultural practices that undermine pollination services are expanding.
Declines in insect pollinators across Europe have raised concerns about the supply of pollination services to agriculture. Simultaneously, EU agricultural and biofuel policies have encouraged ...substantial growth in the cultivated area of insect pollinated crops across the continent. Using data from 41 European countries, this study demonstrates that the recommended number of honeybees required to provide crop pollination across Europe has risen 4.9 times as fast as honeybee stocks between 2005 and 2010. Consequently, honeybee stocks were insufficient to supply >90% of demands in 22 countries studied. These findings raise concerns about the capacity of many countries to cope with major losses of wild pollinators and highlight numerous critical gaps in current understanding of pollination service supplies and demands, pointing to a pressing need for further research into this issue.
Pollinators are a key component of global biodiversity, providing vital ecosystem services to crops and wild plants. There is clear evidence of recent declines in both wild and domesticated ...pollinators, and parallel declines in the plants that rely upon them. Here we describe the nature and extent of reported declines, and review the potential drivers of pollinator loss, including habitat loss and fragmentation, agrochemicals, pathogens, alien species, climate change and the interactions between them. Pollinator declines can result in loss of pollination services which have important negative ecological and economic impacts that could significantly affect the maintenance of wild plant diversity, wider ecosystem stability, crop production, food security and human welfare.
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.
•Multiple global change pressures are currently impacting animal-mediated pollination.•Understanding interactive effects is essential for developing mitigation measures.•We focus on empirical ...evidence of combined effects of global change pressures.•We found many positive (synergistic or additive) interactions between pressures.•However, studies are scarce, highlighting that knowledge is still limited.
Pollination is an essential process in the sexual reproduction of seed plants and a key ecosystem service to human welfare. Animal pollinators decline as a consequence of five major global change pressures: climate change, landscape alteration, agricultural intensification, non-native species, and spread of pathogens. These pressures, which differ in their biotic or abiotic nature and their spatiotemporal scales, can interact in nonadditive ways (synergistically or antagonistically), but are rarely considered together in studies of pollinator and/or pollination decline. Management actions aimed at buffering the impacts of a particular pressure could thereby prove ineffective if another pressure is present. Here, we focus on empirical evidence of the combined effects of global change pressures on pollination, highlighting gaps in current knowledge and future research needs.
Bee pollinators are currently recorded with many different sampling methods. However, the relative performances of these methods have not been systematically evaluated and compared. In response to ...the strong need to record ongoing shifts in pollinator diversity and abundance, global and regional pollinator initiatives must adopt standardized sampling protocols when developing large-scale and long-term monitoring schemes. We systematically evaluated the performance of six sampling methods (observation plots, pan traps, standardized and variable transect walks, trap nests with reed internodes or paper tubes) that are commonly used across a wide range of geographical regions in Europe and in two habitat types (agricultural and seminatural). We focused on bees since they represent the most important pollinator group worldwide. Several characteristics of the methods were considered in order to evaluate their performance in assessing bee diversity: sample coverage, observed species richness, species richness estimators, collector biases (identified by subunit-based rarefaction curves), species composition of the samples, and the indication of overall bee species richness (estimated from combined total samples). The most efficient method in all geographical regions, in both the agricultural and seminatural habitats, was the pan trap method. It had the highest sample coverage, collected the highest number of species, showed negligible collector bias, detected similar species as the transect methods, and was the best indicator of overall bee species richness. The transect methods were also relatively efficient, but they had a significant collector bias. The observation plots showed poor performance. As trap nests are restricted to cavity-nesting bee species, they had a naturally low sample coverage. However, both trap nest types detected additional species that were not recorded by any of the other methods. For large-scale and long-term monitoring schemes with surveyors with different experience levels, we recommend pan traps as the most efficient, unbiased, and cost-effective method for sampling bee diversity. Trap nests with reed internodes could be used as a complementary sampling method to maximize the numbers of collected species. Transect walks are the principal method for detailed studies focusing on plant—pollinator associations. Moreover, they can be used in monitoring schemes after training the surveyors to standardize their collection skills.
ABSTRACT
To manage agroecosystems for multiple ecosystem services, we need to know whether the management of one service has positive, negative, or no effects on other services. We do not yet have ...data on the interactions between pollination and pest‐control services. However, we do have data on the distributions of pollinators and natural enemies in agroecosystems. Therefore, we compared these two groups of ecosystem service providers, to see if the management of farms and agricultural landscapes might have similar effects on the abundance and richness of both. In a meta‐analysis, we compared 46 studies that sampled bees, predatory beetles, parasitic wasps, and spiders in fields, orchards, or vineyards of food crops. These studies used the proximity or proportion of non‐crop or natural habitats in the landscapes surrounding these crops (a measure of landscape complexity), or the proximity or diversity of non‐crop plants in the margins of these crops (a measure of local complexity), to explain the abundance or richness of these beneficial arthropods. Compositional complexity at both landscape and local scales had positive effects on both pollinators and natural enemies, but different effects on different taxa. Effects on bees and spiders were significantly positive, but effects on parasitoids and predatory beetles (mostly Carabidae and Staphylinidae) were inconclusive. Landscape complexity had significantly stronger effects on bees than it did on predatory beetles and significantly stronger effects in non‐woody rather than in woody crops. Effects on richness were significantly stronger than effects on abundance, but possibly only for spiders. This abundance‐richness difference might be caused by differences between generalists and specialists, or between arthropods that depend on non‐crop habitats (ecotone species and dispersers) and those that do not (cultural species). We call this the ‘specialist‐generalist’ or ‘cultural difference’ mechanism. If complexity has stronger effects on richness than abundance, it might have stronger effects on the stability than the magnitude of these arthropod‐mediated ecosystem services. We conclude that some pollinators and natural enemies seem to have compatible responses to complexity, and it might be possible to manage agroecosystems for the benefit of both. However, too few studies have compared the two, and so we cannot yet conclude that there are no negative interactions between pollinators and natural enemies, and no trade‐offs between pollination and pest‐control services. Therefore, we suggest a framework for future research to bridge these gaps in our knowledge.
While an increasing number of studies indicate that the range, diversity and abundance of many wild pollinators has declined, the global area of pollinator-dependent crops has significantly increased ...over the last few decades. Crop pollination studies to date have mainly focused on either identifying different guilds pollinating various crops, or on factors driving spatial changes and turnover observed in these communities. The mechanisms driving temporal stability for ecosystem functioning and services, however, remain poorly understood. Our study quantifies temporal variability observed in crop pollinators in 21 different crops across multiple years at a global scale. Using data from 43 studies from six continents, we show that (i) higher pollinator diversity confers greater inter-annual stability in pollinator communities, (ii) temporal variation observed in pollinator abundance is primarily driven by the three-most dominant species, and (iii) crops in tropical regions demonstrate higher inter-annual variability in pollinator species richness than crops in temperate regions. We highlight the importance of recognizing wild pollinator diversity in agricultural landscapes to stabilize pollinator persistence across years to protect both biodiversity and crop pollination services. Short-term agricultural management practices aimed at dominant species for stabilizing pollination services need to be considered alongside longer term conservation goals focussed on maintaining and facilitating biodiversity to confer ecological stability.
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.
At the local scale, land use land cover (LULC) change strongly affects the occurrence of bumblebees. However, at present LULC change is rarely included in models of future distributions of species. We compared models of climate‐only covariates to models with added static and dynamic LULC covariates. Dynamic models project less range loss and gain than climate only projections, and greater range loss and gain than static models. We recommend species‐specific modelling to understand how LULC and climate interact in future modelling.
PDF
