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The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis

Citation

Albrecht, Matthias et al. (2021), The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis, Dryad, Dataset, https://doi.org/10.5061/dryad.ns1rn8pq2

Abstract

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control (18 studies) and pollination services (17 studies) in adjacent crops in North America, Europe and New Zealand. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimize floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.

Methods

To identify datasets suitable to address the research questions of this quantitative synthesis a search in the ISI Web of Science and SCOPUS was performed. To minimise potential publication bias and to maximise the number of relevant datasets we also searched for unpublished data by contacting potential data holders through researcher networks. Data was requested through a standardized data sheet template from dataset holders. As different studies used different methods and measures to quantify pollination services, pest control services and crop yield, the data was standardized prior to statistical analysis using z-scores. A mixed effect-modelling approach was used to statistically analyse the data. Details on methods of data collection and analysis is are given in the material and methods section of the paper, and in the Supporting Figure 1 and Supporting Tables 1-5.

Usage Notes

Meta-data files (ReadMe files) with the information required to use this dataset are provided.