Partners: Wageningen Environmental Research
Objective
The primary aim of UC2 is to develop standardized methods for better understanding of the relationships between agricultural practices and farmland bird biodiversity through the application of machine learning techniques consistent over large scales. From a technological perspective, the use case shows how a data cube-based data infrastructure can facilitate improved access to biodiversity-related information. This is particularly valuable for stakeholders with need to analyse the interactions between biodiversity and human activities in agricultural landscapes, in combination with regional environmental variables such as land use, temperature, and precipitation.
Solutions and possible applications
The primary outcome of use case 2 was the ability to confirm causal relationship between the agricultural activity and biodiversity indicator specifically on the case of crop rotation index and species richness. The estimated effect suggests that higher crop rotation scores are associated with increased biodiversity.
From the technological point of view this use case contributes to understand how a data cube-based data infrastructure can improve the access to information related to biodiversity, for stakeholders interested in linking biodiversity and human activities in agricultural areas with changes in the environmental conditions of the region. With the continuation of research in this line, this will enable making more precise estimates of biodiversity in a detailed spatial context, as well as allowing stakeholders to make better-informed decisions on selecting more nature-inclusive practices promoting biodiversity.
The analysis tools used to extract causal relationship between different interventions at farm and landscape level, specific biodiversity indicators and further derived measures of biodiversity are provided within FAIRiCUBE for reuse both in different locations as well as pertaining to related questions.
Resources and further documentation
The use case provides a series of F.A.I.R. analysis-ready datasets, data processing pipelines, and deployed concept applications shared via FAIRiCUBE HUB for stakeholders to use. Comprehensive documentation is available in a dedicated section of the FAIRiCUBE Knowledge Base, where the research background, data processing steps, modelling workflows and evaluation approaches are described in detail.
Additional resources for UC2 include: