Determinants of arctic-alpine pasture resources: the need for a spatially and functionally fine-scaled perspective. Issue 4 (2nd October 2017)

• Record Type: Journal Article
• Authors: Pape, Roland; Löffler, Jörg
• Is Part Of: Geografiska annaler. Volume 99:Issue 4(2017)
• Page Start: 353
• Page End: 370
• Publication Date: 2017-10-02
• Subjects: Arctic-alpine greening -- above-ground phytomass -- tundra ecosystems -- partial least squares regression -- landscape ecology -- Norway; Physical geography -- Periodicals; 551.4
• DOI: 10.1080/04353676.2017.1368833
• Languages: English
• ISSNs: 0435-3676

Abstract

ABSTRACT: The current greening of arctic-alpine landscapes poses the question about its underlying ecological mechanisms. Given its importance across various contexts and scales, it is vital to understand the drivers of contemporary patterns in phytomass and primary productivity to improve predictions under altered environmental conditions. Here, we analysed local patterns in above-ground phytomass, calorific energy contents, and primary productivity as important pasture resources in a complex arctic-alpine landscape along pronounced micro-topographical and elevational gradients. Using data from 110 sampling sites, of which 38 were equipped with on-site recordings of soil moisture and near-surface temperatures, we asked how the observed patterns in pasture resources are related to the environment and whether commonly used structural proxies or physiologically relevant, functional data were better suited for their explanation. Using partial least squares regression based on a set of structural plus functional explanatory variables, the latter revealed to be the best determinants. Our results suggest how the ecological mechanisms behind contemporary pasture resources and, likewise, the arctic-alpine greening are interactively driven by the near-surface thermal regime, associated snow coverage, and soil moisture availability. Moreover, they reveal an obvious decoupling of near-surface processes from the overall atmospheric and topographic constraints which are commonly used as proxies. We conclude that estimates of current and future pasture resources would be significantly improved if fine-scaled, functional data, rather than structural data, could be used. However, this implies further effort in providing such data, since appropriate regionalization techniques are still lacking.