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- Carvalheiro, Luisa G., et al.
(author)
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Soil eutrophication shaped the composition of pollinator assemblages during the past century
- 2020
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In: Ecography. - : John Wiley & Sons. - 0906-7590 .- 1600-0587. ; 43, s. 209-221
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Journal article (peer-reviewed)abstract
- Atmospheric nitrogen deposition and other sources of environmental eutrophication have increased substantially over the past century worldwide, notwithstanding the recent declining trends in Europe. Despite the recognized susceptibility of plants to eutrophication, few studies evaluated how impacts propagate to consumers, such as pollinators. Here we aim to test if soil eutrophication contributes to the temporal dynamics of pollinators and their larval resources. We used a temporally and spatially explicit historical dataset with information on species occurrences to test if soil eutrophication, and more specifically nitrogen deposition, contributes to the patterns of change of plant and pollinator richness in the Netherlands over an 80 yr period. We focus on bees and butterflies, two groups for which we have good knowledge of larval resources that allowed us to define groups of species with different nitrogen related diet preferences. For each group we estimated richness changes between different 20-yr periods at local, regional and national scale, using analytical methods developed for analyzing richness changes based on collection data. Our findings suggest that the impacts of soil eutrophication on plant communities propagate to higher trophic levels, but with a time-lag. Pollinators with nitrogen-related diet preferences were particularly affected, in turn potentially impairing the performance of pollinator-dependent plants. Pollinator declines continued even after their focal plants started to recover. In addition, our results suggest that current levels of nitrogen deposition still have a negative impact on most groups here analyzed, constraining richness recoveries and accentuating declines. Our results indicate that the global increase in nitrogen availability plays an important role in the ongoing pollinator decline. Consequently, species tolerances to soil nitrogen levels should be considered across all trophic levels in management plans that aim to halt biodiversity loss and enhance ecosystems services worldwide.
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- Giménez-García, Angel, et al.
(author)
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Pollination supply models from a local to global scale
- 2023
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In: Web Ecology. - 1399-1183. ; 23:2, s. 99-129
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Journal article (peer-reviewed)abstract
- Ecological intensification has been embraced with great interest by the academic sector but is still rarely taken up by farmers because monitoring the state of different ecological functions is not straightforward. Modelling tools can represent a more accessible alternative of measuring ecological functions, which could help promote their use amongst farmers and other decision-makers. In the case of crop pollination, modelling has traditionally followed either a mechanistic or a data-driven approach. Mechanistic models simulate the habitat preferences and foraging behaviour of pollinators, while data-driven models associate georeferenced variables with real observations. Here, we test these two approaches to predict pollination supply and validate these predictions using data from a newly released global dataset on pollinator visitation rates to different crops. We use one of the most extensively used models for the mechanistic approach, while for the data-driven approach, we select from among a comprehensive set of state-of-The-Art machine-learning models. Moreover, we explore a mixed approach, where data-derived inputs, rather than expert assessment, inform the mechanistic model. We find that, at a global scale, machine-learning models work best, offering a rank correlation coefficient between predictions and observations of pollinator visitation rates of 0.56. In turn, the mechanistic model works moderately well at a global scale for wild bees other than bumblebees. Biomes characterized by temperate or Mediterranean forests show a better agreement between mechanistic model predictions and observations, probably due to more comprehensive ecological knowledge and therefore better parameterization of input variables for these biomes. This study highlights the challenges of transferring input variables across multiple biomes, as expected given the different composition of species in different biomes. Our results provide clear guidance on which pollination supply models perform best at different spatial scales-the first step towards bridging the stakeholder-Academia gap in modelling ecosystem service delivery under ecological intensification.
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