Literature DB >> 27139426

Alpine bird distributions along elevation gradients: the consistency of climate and habitat effects across geographic regions.

Dan Chamberlain1, Mattia Brambilla2,3, Enrico Caprio4, Paolo Pedrini2, Antonio Rolando4.   

Abstract

Many species have shown recent shifts in their distributions in response to climate change. Patterns in species occurrence or abundance along altitudinal gradients often serve as the basis for detecting such changes and assessing future sensitivity. Quantifying the distribution of species along altitudinal gradients acts as a fundamental basis for future studies on environmental change impacts, but in order for models of altitudinal distribution to have wide applicability, it is necessary to know the extent to which altitudinal trends in occurrence are consistent across geographically separated areas. This was assessed by fitting models of bird species occurrence across altitudinal gradients in relation to habitat and climate variables in two geographically separated alpine regions, Piedmont and Trentino. The ten species studied showed non-random altitudinal distributions which in most cases were consistent across regions in terms of pattern. Trends in relation to altitude and differences between regions could be explained mostly by habitat or a combination of habitat and climate variables. Variation partitioning showed that most variation explained by the models was attributable to habitat, or habitat and climate together, rather than climate alone or geographic region. The shape and position of the altitudinal distribution curve is important as it can be related to vulnerability where the available space is limited, i.e. where mountains are not of sufficient altitude for expansion. This study therefore suggests that incorporating habitat and climate variables should be sufficient to construct models with high transferability for many alpine species.

Entities:  

Keywords:  Altitude; Climate change; Model performance; Model transferability; Variation partitioning

Mesh:

Year:  2016        PMID: 27139426     DOI: 10.1007/s00442-016-3637-y

Source DB:  PubMed          Journal:  Oecologia        ISSN: 0029-8549            Impact factor:   3.225


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