{"title":"A high-precision dataset of breeding bird distributions in forested landscapes in Estonia","authors":"Asko Lõhmus","doi":"10.1016/j.dib.2024.111012","DOIUrl":null,"url":null,"abstract":"<div><div>Diversity and abundance of breeding birds are frequently reported and analysed as indicators of environmental change. However, such data available for forests typically contain either relative abundances based on snapshot observations or have been collected in small sample plots, which limit their distributional and ecological analysis across landscapes. I present a spatial dataset from three adjacent landscapes in Estonia (hemiboreal Europe), which has been obtained by standard multiple-visit mapping of nesting territories in 2020–2022. The records constitute the most likely centroids of distinct nesting territories of all 98 breeding species detected; these have been extracted and interpreted based on observations from an average 7–8 visits per season, and quality-assessed for three levels of spatial accuracy. One landscape was mapped in all three years, the others in either 2021 or 2022. The total area mapped was 14.3 km<sup>2</sup>, including 86 % woodlands of diverse types and origins; a woodland characteristics dataset accompanies the bird data to facilitate habitat analysis. The paper describes the study plots; technical protocols of fieldwork and record interpretation; limitations (notably the likely missing of 10–20 % of pairs in most species); and possibilities to use the data in basic and applied ecological research. The main values of the dataset are that (i) it provides landscape-scale distribution map for the whole breeding assemblage of birds at high spatial precision, (ii) has accompanying woodland habitat data, and (iii) it also includes a repeatedly mapped landscape for detecting temporal variation in bird distributions.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"57 ","pages":"Article 111012"},"PeriodicalIF":1.0000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data in Brief","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352340924009740","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Diversity and abundance of breeding birds are frequently reported and analysed as indicators of environmental change. However, such data available for forests typically contain either relative abundances based on snapshot observations or have been collected in small sample plots, which limit their distributional and ecological analysis across landscapes. I present a spatial dataset from three adjacent landscapes in Estonia (hemiboreal Europe), which has been obtained by standard multiple-visit mapping of nesting territories in 2020–2022. The records constitute the most likely centroids of distinct nesting territories of all 98 breeding species detected; these have been extracted and interpreted based on observations from an average 7–8 visits per season, and quality-assessed for three levels of spatial accuracy. One landscape was mapped in all three years, the others in either 2021 or 2022. The total area mapped was 14.3 km2, including 86 % woodlands of diverse types and origins; a woodland characteristics dataset accompanies the bird data to facilitate habitat analysis. The paper describes the study plots; technical protocols of fieldwork and record interpretation; limitations (notably the likely missing of 10–20 % of pairs in most species); and possibilities to use the data in basic and applied ecological research. The main values of the dataset are that (i) it provides landscape-scale distribution map for the whole breeding assemblage of birds at high spatial precision, (ii) has accompanying woodland habitat data, and (iii) it also includes a repeatedly mapped landscape for detecting temporal variation in bird distributions.
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