Data · dataset · 2024
Map of livestock grazing in semi-natural areas in the European Union and United Kingdom
Listed in IISH Dataverse
Livestock grazing throughout Europe has resulted in high diversity of semi-natural areas in past centuries.
Description
Currently, most low intensity grazing relying on semi-natural vegetation is found primarily in marginal lands. These areas still host a high-level of biodiversity but are subject to abandonment and agricultural intensification.
Spatial information on areas where semi-natural vegetation is still grazed, and how contextual geographic conditions encourage or limit grazing is missing, hindering their protection. We present an interdisciplinary approach, combining expert interviews with spatial distribution modeling using machine learning, to map the spatial distribution of grazing in semi-natural areas of the European Union (EU) and the United Kingdom (UK).
Read the rest (1 more)
We mapped both the grazing probability as well as actual spatial distribution of grazing on semi-natural areas for the whole of EU and UK. The maps are the first spatial distribution of low-intensity grazing for the wider EU region.
Links
Where it is published
- Dataverse dataset page dataverse.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FMRCTDG ↗
landing page · from datasets iisg amsterdam
- DOI doi.org/10.34894/mrctdg ↗
DOI / persistent id · from datasets iisg amsterdam
Catalogue records · 1
- Dataverse API dataverse.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FMRCT… ↗
metadata API · from datasets iisg amsterdam
Topics
- Stated by source
- Agricultural Sciences · Earth and Environmental Sciences
- From keywords
- Computer Science & AI · Earth & Environmental Science · Life Sciences · Machine learning
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IISH Dataverse | doi:10.34894/MRCTDG | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4611 | mapping · datasets iisg amsterdam | vocabulary-mapper@1.0.0 | keywords['machine learning'] |
| concepts[field].dataverse_subject:agricultural-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| created_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| description | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /description |
| publication_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| title | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /name |
| updated_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| version_label | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 |