{\textcopyright} Springer International Publishing AG 2017. In this chapter we summarize a list of technical and statistical approaches, useful for studying High Nature Value (HNV) farmlands, and biodiversity components. We also focus on the use of suitable frameworks to monitor HNV farmland using bird species, providing some information about bird data collection in the field. The concept of bioindicators and the use of bird species as environmental surrogates are briefly described, as well as the most common diversity metrics used to describe bird communities (taxonomic diversity, functional diversity and phylogenetic diversity). Finally, we provide some suggestions about statistical methods that can be followed in order to link the study of HNV farmlands to biodiversity patterns and environmental characteristics of farmlands.

{Suitable methods for monitoring HNV farmland using bird species}

Federico Morelli
2017-01-01

Abstract

{\textcopyright} Springer International Publishing AG 2017. In this chapter we summarize a list of technical and statistical approaches, useful for studying High Nature Value (HNV) farmlands, and biodiversity components. We also focus on the use of suitable frameworks to monitor HNV farmland using bird species, providing some information about bird data collection in the field. The concept of bioindicators and the use of bird species as environmental surrogates are briefly described, as well as the most common diversity metrics used to describe bird communities (taxonomic diversity, functional diversity and phylogenetic diversity). Finally, we provide some suggestions about statistical methods that can be followed in order to link the study of HNV farmlands to biodiversity patterns and environmental characteristics of farmlands.
2017
Birds as Useful Indicators of High Nature Value Farmlands: Using Species Distribution Models as a Tool for Monitoring the Health of Agro-ecosystems
Federico Morelli
53
70
9783319502847
Bioindicator,Bird data collection,IndVal analysis,MRT,Point count,Species distribution model SDM
Piotr Tryjanowski; Federico Morelli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2119946
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