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10.1007/s10661-017-5837-2.pdf 1,44MB
WeightNameValue
1000 Titel
  • Assessing the habitat suitability of agricultural landscapes for characteristic breeding bird guilds using landscape metrics
1000 Autor/in
  1. Glemnitz, Michael |
  2. Schultz, Alfred |
  3. Stachow, Ulrich |
  4. Borges, Friederike |
1000 Erscheinungsjahr 2017
1000 LeibnizOpen
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2017-03-16
1000 Erschienen in
1000 Quellenangabe
  • 189: 166
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2017
1000 Lizenz
1000 Verlagsversion
  • http://doi.org/10.1007/s10661-017-5837-2 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355513/ |
1000 Ergänzendes Material
  • https://link.springer.com/article/10.1007%2Fs10661-017-5837-2#SupplementaryMaterial |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Many of the processes behind the decline of farmland birds can be related to modifications in landscape structure (composition and configuration), which can partly be expressed quantitatively with measurable or computable indices, i.e. landscape metrics. This paper aims to identify statistical relationships between the occurrence of birds and the landscape structure. We present a method that combines two comprehensive procedures: the “landscape-centred approach” and “guild classification”. Our study is based on more than 20,000 individual bird observations based on a 4-year bird monitoring approach in a typical agricultural area in the north-eastern German lowlands. Five characteristic bird guilds, each with three characteristic species, are defined for the typical habitat types of that area: farmland, grassland, hedgerow, forest and settlement. The suitability of each sample plot for each guild is indicated by the level of persistence (LOP) of occurrence of three respective species. Thus, the sample plots can be classified as “preferred” or “less preferred” depending on the lower and upper quartiles of the LOP values. The landscape structure is characterized by 16 different landscape metrics expressing various aspects of landscape composition and configuration. For each guild, the three landscape metrics with the strongest rank correlation with the LOP values and that are not mutually dependent were identified. For four of the bird guilds, the classification success was better than 80%, compared with only 66% for the grassland bird guild. A subset of six landscape metrics proved to be the most meaningful and sufficiently classified the sample areas with respect to bird guild suitability. In addition, derived logistic functions allowed the production of guild-specific habitat suitability maps for the whole landscape. The analytical results show that the proposed approach is appropriate to assess the habitat suitability of agricultural landscapes for characteristic bird guilds.
1000 Sacherschließung
lokal Landscape composition
lokal Moving windows
lokal Landscape assessment
lokal Landscape configuration
lokal Binary logistic regression
lokal Bird monitoring
1000 Fachgruppe
  1. Agrarwissenschaften |
  2. Umweltwissenschaften |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/R2xlbW5pdHosIE1pY2hhZWw=|https://frl.publisso.de/adhoc/creator/U2NodWx0eiwgQWxmcmVk|https://frl.publisso.de/adhoc/creator/U3RhY2hvdywgVWxyaWNo|http://orcid.org/0000-0001-9388-5896
1000 Label
1000 Förderer
  1. German Federal Ministry of Food and Agriculture (BMEL)
  2. Brandenburg Ministry of Sciences, Research and Culture (MWFK)
1000 Fördernummer
  1. -
  2. -
1000 Förderprogramm
  1. -
  2. -
1000 Dateien
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6403379.rdf
1000 Erstellt am 2017-07-05T15:08:31.064+0200
1000 Erstellt von 25
1000 beschreibt frl:6403379
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet 2020-01-30T17:58:02.508+0100
1000 Objekt bearb. Wed May 02 12:37:23 CEST 2018
1000 Vgl. frl:6403379
1000 Oai Id
  1. oai:frl.publisso.de:frl:6403379 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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