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- Senapathi, Deepa, et al.
(author)
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Wild insect diversity increases inter-annual stability in global crop pollinator communities
- 2021
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In: Royal Society of London. Proceedings B. Biological Sciences. - : The Royal Society. - 1471-2954 .- 0962-8452. ; 288:1947
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Journal article (peer-reviewed)abstract
- 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.
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| 2. |
- Gagic, Vesna, et al.
(author)
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Combined effects of agrochemicals and ecosystem services on crop yield across Europe
- 2017
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In: Ecology Letters. - : Wiley. - 1461-023X .- 1461-0248. ; 20:11, s. 1427-1436
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Journal article (peer-reviewed)abstract
- Simultaneously enhancing ecosystem services provided by biodiversity below and above ground is recommended to reduce dependence on chemical pesticides and mineral fertilisers in agriculture. However, consequences for crop yield have been poorly evaluated. Above ground, increased landscape complexity is assumed to enhance biological pest control, whereas below ground, soil organic carbon is a proxy for several yield-supporting services. In a field experiment replicated in 114 fields across Europe, we found that fertilisation had the strongest positive effect on yield, but hindered simultaneous harnessing of below- and above-ground ecosystem services. We furthermore show that enhancing natural enemies and pest control through increasing landscape complexity can prove disappointing in fields with low soil services or in intensively cropped regions. Thus, understanding ecological interdependences between land use, ecosystem services and yield is necessary to promote more environmentally friendly farming by identifying situations where ecosystem services are maximised and agrochemical inputs can be reduced.
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| 3. |
- Gardner, Emma, et al.
(author)
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Reliably predicting pollinator abundance : Challenges of calibrating process-based ecological models
- 2020
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In: Methods in Ecology and Evolution. - 2041-210X. ; 11:12, s. 1673-1689
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Journal article (peer-reviewed)abstract
- Pollination is a key ecosystem service for global agriculture but evidence of pollinator population declines is growing. Reliable spatial modelling of pollinator abundance is essential if we are to identify areas at risk of pollination service deficit and effectively target resources to support pollinator populations. Many models exist which predict pollinator abundance but few have been calibrated against observational data from multiple habitats to ensure their predictions are accurate. We selected the most advanced process-based pollinator abundance model available and calibrated it for bumblebees and solitary bees using survey data collected at 239 sites across Great Britain. We compared three versions of the model: one parameterised using estimates based on expert opinion, one where the parameters are calibrated using a purely data-driven approach and one where we allow the expert opinion estimates to inform the calibration process. All three model versions showed significant agreement with the survey data, demonstrating this model's potential to reliably map pollinator abundance. However, there were significant differences between the nesting/floral attractiveness scores obtained by the two calibration methods and from the original expert opinion scores. Our results highlight a key universal challenge of calibrating spatially explicit, process-based ecological models. Notably, the desire to reliably represent complex ecological processes in finely mapped landscapes necessarily generates a large number of parameters, which are challenging to calibrate with ecological and geographical data that are often noisy, biased, asynchronous and sometimes inaccurate. Purely data-driven calibration can therefore result in unrealistic parameter values, despite appearing to improve model-data agreement over initial expert opinion estimates. We therefore advocate a combined approach where data-driven calibration and expert opinion are integrated into an iterative Delphi-like process, which simultaneously combines model calibration and credibility assessment. This may provide the best opportunity to obtain realistic parameter estimates and reliable model predictions for ecological systems with expert knowledge gaps and patchy ecological data.
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