Rochelle Kennedy , Elisa Fuentes-Montemayor , Kirsty J. Park , Nick Littlewood
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Does mixed farming benefit moths? Exploring how different farming systems shape both local features and the wider landscape
Moths are important pollinators and provide an essential food source for higher taxa, yet many species that were once widespread are in decline across Europe. This is largely due to practices associated with intensive farming, such as pesticide and fertiliser applications and habitat loss. There is increasing interest in finding ways of farming that are beneficial to both humans and biodiversity. ‘Mixed’ farming, where livestock are integrated into the crop rotation, is thought to provide benefits to biodiversity by reducing synthetic inputs and by increasing habitat and crop diversity. However, at commercial stocking levels, livestock can have detrimental impacts on grassland Lepidoptera. We investigate the different pathways through which mixed farming could benefit moths in comparison to arable farming (where livestock are absent). Between June and August 2022, twenty-six farms in Scotland were surveyed for moths using light-trapping. Woodland edge density, which was higher on mixed farms, increased micro moth abundance and species richness. Positive effects of woodland were also observed for ‘farmland’ micro moths that do not feed on woody plants. However, for micro moth species richness this positive effect of woodland edge was outweighed by a direct negative effect of mixed farming, highlighting the need for more research to find livestock management practices that are beneficial for moths.
期刊介绍:
Agriculture, Ecosystems and Environment publishes scientific articles dealing with the interface between agroecosystems and the natural environment, specifically how agriculture influences the environment and how changes in that environment impact agroecosystems. Preference is given to papers from experimental and observational research at the field, system or landscape level, from studies that enhance our understanding of processes using data-based biophysical modelling, and papers that bridge scientific disciplines and integrate knowledge. All papers should be placed in an international or wide comparative context.