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Higher crop diversity in less diverse landscapes
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Abstract
CONTEXT: Agricultural landscapes need to be diversified for ensuring resilient agricultural production and supporting biodiversity and ecosystem services. However, the relationship between agricultural diversity and landscape diversity is largely understudied.
OBJECTIVES: We aim to assess the spatial organisational relationship between agricultural and landscape diversity and their underlying drivers in Brandenburg, Germany.
METHODS: We used the mean number of unique crop types per field per decade (i.e., crop rotational diversity) as a proxy for agricultural diversity and the number of land use and land cover types and the number of habitat types as proxies for landscape diversity. Soil and climate characteristics and geographical positions were used to identify potential drivers of the diversity facets. All spatial information was aggregated at 10x10 km resolution, and statistical associations were tested by employing Pearson’s correlation, machine learning and explainable artificial intelligence methods.
RESULTS: Results revealed a non-linear negative relationship of crop rotational diversity to landscape diversity metrics. We identified that soil quality was positively linked with crop rotational diversity and negatively linked with landscape diversity metrics. The link between mean temperature and crop rotational diversity was negative, while with landscape diversity it was positive.
CONCLUSION: Our study indicates a spatial trade-off between crop and landscape diversity potentially because of the preferred use of soils with higher quality for agricultural production with more diverse cash crops, large fields and less semi-natural habitats. For increasing crop and landscape diversity, the respective strategies and targets should be tailored to the corresponding local and regional conditions.
Title: Higher crop diversity in less diverse landscapes
Description:
Abstract
CONTEXT: Agricultural landscapes need to be diversified for ensuring resilient agricultural production and supporting biodiversity and ecosystem services.
However, the relationship between agricultural diversity and landscape diversity is largely understudied.
OBJECTIVES: We aim to assess the spatial organisational relationship between agricultural and landscape diversity and their underlying drivers in Brandenburg, Germany.
METHODS: We used the mean number of unique crop types per field per decade (i.
e.
, crop rotational diversity) as a proxy for agricultural diversity and the number of land use and land cover types and the number of habitat types as proxies for landscape diversity.
Soil and climate characteristics and geographical positions were used to identify potential drivers of the diversity facets.
All spatial information was aggregated at 10x10 km resolution, and statistical associations were tested by employing Pearson’s correlation, machine learning and explainable artificial intelligence methods.
RESULTS: Results revealed a non-linear negative relationship of crop rotational diversity to landscape diversity metrics.
We identified that soil quality was positively linked with crop rotational diversity and negatively linked with landscape diversity metrics.
The link between mean temperature and crop rotational diversity was negative, while with landscape diversity it was positive.
CONCLUSION: Our study indicates a spatial trade-off between crop and landscape diversity potentially because of the preferred use of soils with higher quality for agricultural production with more diverse cash crops, large fields and less semi-natural habitats.
For increasing crop and landscape diversity, the respective strategies and targets should be tailored to the corresponding local and regional conditions.
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