Diversely structured, species-rich viticulture landscapes can reduce the need for external inputs while being a cultural heritage that provide aesthetic values for human well-being and recreation.
To integrate biodiversity and agricultural production, we will examine new approaches at different spatial scales (plot, farm and landscape), assess the socio- economic consequences and formulate best practice recommendations for policy and farmers.
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VineDivers is designed for an efficient utilization of available resources for research and policy, by (i) sharing experimental infrastructure and expertise among the consortium members, (ii) coordinating
related activities at the European level by harmonized sampling protocols from Spain to Romania.
Most of VineDivers partners are or were already engaged in research on biodiversity and ecosystem services in their countries providing an important basis for the advancement of this research topic in Europe.
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VineDivers final project meeting
27 - 29 June 2018
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Riegler-Nurscher P, Prankl J, Bauer T, Strauss P, Prankl H (2018) A machine learning approach for pixel wise classification of residue and vegetation cover under field conditions. Biosystems Engineering 169: 188 - 198
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