Presence-only data for wild ungulates and red fox in Spain based on hunting yields over a 10-year period.

IF 6.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-10 DOI:10.1038/s41597-025-04574-z

Sonia Illanas, Javier Fernández-López, Joaquín Vicente, Carmen Ruiz-Rodríguez, Sergio López-Padilla, Mario Sebastián-Pardo, Ludovica Preite, Azahara Gómez-Molina, Pelayo Acevedo, José Antonio Blanco-Aguiar

引用次数: 0

Abstract

The data sets provide long-term information (2013-2022) of the presence-only of eight wild ungulates and red fox derived from harvest data in a grid of 5 × 5 km of Spain (21,836 cells). The collected data has been processed and reported yearly, as well as in two monitoring periods in accordance with Habitats Directive from the European Union to facilitate data reporting about the State of nature, and the sum of the whole period. Data sets are structured following the Darwin Core biological standard. The data set was published in the Spanish node of the Global Biodiversity Information Facility (GBIF), which are the most updated publicly available information for these species' presence in Spain.

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西班牙野生有蹄类动物和赤狐的仅存数据是基于过去10年的狩猎产量。

这些数据集提供了西班牙5 × 5公里（21,836个单元）的收获数据中仅存在的8种野生有蹄类动物和赤狐的长期信息（2013-2022年）。收集到的数据每年进行处理和报告，并根据欧洲联盟生境指令在两个监测期进行处理和报告，以方便报告有关自然状态的数据，以及整个期间的总和。数据集的结构遵循达尔文核心生物学标准。该数据集发表在全球生物多样性信息设施（GBIF）的西班牙节点上，这是西班牙这些物种存在的最新公开信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.