Archetypes of agri-environmental potential: a multi-scale typology for spatial stratification and upscaling in Europe

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F22%3A73615831" target="_blank" >RIV/61989592:15310/22:73615831 - isvavai.cz</a>

Result on the web

<a href="https://iopscience.iop.org/article/10.1088/1748-9326/ac9cf5/pdf" target="_blank" >https://iopscience.iop.org/article/10.1088/1748-9326/ac9cf5/pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1748-9326/ac9cf5" target="_blank" >10.1088/1748-9326/ac9cf5</a>

Result language

angličtina

Original language name

Archetypes of agri-environmental potential: a multi-scale typology for spatial stratification and upscaling in Europe

Original language description

Developing spatially-targeted policies for farmland in the European Union (EU) requires synthesized, spatially-explicit knowledge of agricultural systems and their environmental conditions. Such synthesis needs to be flexible and scalable in a way that allows the generalization of European landscapes and their agricultural potential into spatial units that are informative at any given resolution and extent. In recent years, typologies of agricultural lands have been substantially improved, however, agriculturally relevant aspects have yet to be included. We here provide a spatial classification approach for identifying archetypal patterns of agri-environmental potential in Europe based on machine-learning clustering of 17 variables on bioclimatic conditions, soil characteristics and topographical parameters. We improve existing typologies by (a) including more recent biophysical data (e.g. agriculturally-important soil parameters), (b) employing a fully data-driven approach that reduces subjectivity in identifying archetypal patterns, and (c) providing a scalable approach suitable both for the entire European continent as well as smaller geographical extents. We demonstrate the utility and scalability of our typology by comparing the archetypes with independent data on cropland cover and field size at the European scale and in three regional case studies in Germany, Czechia and Spain. The resulting archetypes can be used to support spatial stratification, upscaling and designation of more spatially-targeted agricultural policies, such as those in the context of the EU&apos;s Common Agricultural Policy post-2020.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10511 - Environmental sciences (social aspects to be 5.7)

Project

—

Continuities

R - Projekt Ramcoveho programu EK

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Environmental Research Letters

ISSN

1748-9326

e-ISSN

—

Volume of the periodical

17

Issue of the periodical within the volume

11

Country of publishing house

GB - UNITED KINGDOM

Number of pages

20

Pages from-to

"115008-1"-"115008-20"

UT code for WoS article

000880405700001

EID of the result in the Scopus database

2-s2.0-85141939411