Multi-year dataset of Eurasian lynx distribution in part of the Carpathian metapopulation (2022–2023) based on SCALP+
Data files
Oct 24, 2025 version files 1.02 MB
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README.md
2.55 KB
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SCALPplus2022.zip
1.01 MB
Apr 15, 2026 version files 1.98 MB
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README.md
2.81 KB
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SCALPplus2022.zip
1.01 MB
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SCALPplus2023.zip
962.47 KB
Abstract
The Status and Conservation of the Alpine Lynx Population (SCALP) was created in the early 1990s to survey the status of the lynx in the Alps, carry out monitoring activities in coordination between Alpine countries and close research gaps in the region. The project brings together a team of experts focused on compiling available data on lynx and standardising their interpretation. SCALP has not only been compiling data required for the description of the conservation status of the lynx population in the Alps, but has also been advancing the conceptual and methodological approach of transboundary monitoring with the SCALP criteria. The SCALP criteria classify species occurrence data according to their verifiability (i.e. C1 = hard fact data, C2 = verified records, C3 = unverified records or records which by their nature cannot be verified) and are now commonly used in several species. Thanks to the standardised data interpretation, direct comparison of lynx distribution between countries and populations is possible. Lynx presence was mapped at a 10 x 10 km (ETRS89-LAEA Europe) grid scale. This grid is widely used for Habitat Directive reporting to the European Union (EU) and can be downloaded at: [http://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2].
Since 2013, SCALP has been expanded to include additional countries in Europe and renamed to SCALP+. Here, we provide the shp files of SCALP+ for data of two years (2022 and 2023) from eleven countries. The shp files visualise the distribution of lynx in the respective countries, core areas of populations (where reproduction occurs) and variation in underlaying data quality.
Dataset DOI: 10.5061/dryad.wstqjq30d
Description of the data and file structure
We share annual lynx distribution data collected in eleven European countries as Shapefiles. Lynx presence was mapped at a 10 x 10 km (ETRS89-LAEA Europe) grid scale.
Dataset Versioning and Scope
This dataset was originally published with data from 2022.
The current version expands the dataset to include data from 2023 while retaining the original 2022 data.
The dataset should therefore be considered a continuous, cumulative dataset, not a replacement of previous versions.
Files and variables
File: SCALPplus2022.zip
File: SCALPplus2023.zip
Description: Shape files: Distribution of the lynx in eleven European countries in 2022 and 2023.
We additionally include the annual monitoring reports as a pdf, where we show the distribution map of lynx in the respective countries as well as a map of release sites of translocated lynx to reinforce the Central European lynx metapopulation.
| Metadata table | Information provided |
|---|---|
| CELLCODE | 10x10 km ETRS89-LAEA (Lambert Azimuthal Equal Area) Europe grid ID |
| EOFORIGIN | East coordinate in ETRS89-LAEA projection (EPSG:3035) |
| NOFORIGIN | North coordinate in ETRS89-LAEA projection (EPSG:3035) |
| CATEGORY | Presence category: "1reproduction", "2reproduction", "3reproduction", "1", "2", "3" |
For interpretation of "CATEGORY" see report Molinari-Jobin et al. 2025.
Code/software
Shapefiles are a common format for vector-based geographic information system (GIS) data. They can be opened and used in any GIS software and in R or Python. A shapefile consists of multiple file types beyond the .shp (specifically, .cpg, .dbf, .prj, .sbn, and .sbx). The user only interacts directly with the .shp file but the other files need to be in the same directory.
A distinction was made between different SCALP categories (category 1 = hard fact data, category 2 = confirmed records, category 3 = unconfirmed records) and whether the observation included a reproductive event or not.
Access information
Other publicly accessible locations of the data:
Changes after Oct 24, 2025: This update expands the dataset by adding data collected during 2023 while retaining the previously published 2022 dataset. The dataset is therefore cumulative and now represents a two-year time series (2022 and 2023).
The purpose of this update is to:
- Extend temporal coverage with newly collected data (2023)
- Provide a consistent, longitudinal dataset for comparative and time-series analyses