Published August 1, 2022 | Version v1
Dataset Open

Disentangling the interrelated abiotic and biotic pathways linking landscape composition and crop production

  • 1. Instituut voor Landbouw-, Visserij- en Voedingsonderzoek*

Description

Landscape composition and its related functional agrobiodiversity (FAB) was severely simplified during the last decades. As landscape composition is expected to influence the interrelated microclimate and arthropod community at different scales, this simplification might have led to a decline in multiple agro-ecosystem services, with potential impacts for the growth of crops with different demands from the environment.

To study landscape-scale effects on multi-crop yield and herbivory in combination with its potential drivers, including functional arthropod community and microclimate, we used standardised 1 m² mini-gardens planted with ten different vegetable crops as phytometers. The gardens were installed at locations varying in surrounding landscape composition and the vegetables were selected to have contrasting requirements in terms of growing conditions, pollination services, and susceptibility to pests. Monitoring of the mini-gardens was performed in 2018 and 2019 in Flanders (Belgium).

We found no relationship between landscape composition in a 500 meter radius and crop yield. Considering possible mechanisms, we found that an increasing share of woody vegetation (> 3 m high) in the surrounding landscape is important to buffer the temperature and soil moisture variation in the mini-gardens. The share of agricultural land use and urban green (< 3 m high) is, respectively, positively and negatively related with the activity-density of natural enemies and pollinators. The growth of different crops responded differently to higher temperature ranges and we found no relation between natural enemies and herbivory. In conclusion, these abiotic and biotic pathways did not cause an overall relationship between landscape composition and yield.

Notes

All datasets are compatible with Microsoft Excel and can be imported in all programs (R, Python, Matlab ...).

Funding provided by: Fonds Wetenschappelijk Onderzoek
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100003130
Award Number: 1S82421N

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