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Spatio-temporal analysis of alpine ecotones: A spatial explicit model targeting altitudinal vegetation shifts

Authors :
Alberto Díaz Varela, R
Colombo, R
Meroni, M
Calvo Iglesias, M
Buffoni, A
Tagliaferri, A
Alberto Díaz Varela, RA
COLOMBO, ROBERTO
MERONI, MICHELE
Calvo Iglesias, MS
Tagliaferri, A.
Alberto Díaz Varela, R
Colombo, R
Meroni, M
Calvo Iglesias, M
Buffoni, A
Tagliaferri, A
Alberto Díaz Varela, RA
COLOMBO, ROBERTO
MERONI, MICHELE
Calvo Iglesias, MS
Tagliaferri, A.
Publication Year :
2010

Abstract

There is general agreement in literature that Alpine vegetation belt ecotones have shown a trend of upward migration in the last few decades. Despite the potential of such shifts as indicators of global change effects in mountain ecosystems, there are relatively few works focused on their assessment in a systematic and spatially explicit way. In this work our aim is to quantify the altitudinal shifts and analyse the spatial pattern dynamics of mountain ecotones. We developed a novel procedure to delineate the current and former state of three characteristic mountain ecotones, which we formalised as forest, tree and tundra lines. Our approach is based on the recognition of altitudinal extreme outposts identified with ecotone locations at a slope scale. The integration of multi-temporal datasets allows the identification and quantification of altitudinal advances and retreats in the outpost locations for a given period. We tested the method in a section of the Italian Alps for the period 1957-2003. Results show a general trend of an increase in altitude for the three ecotones, despite the occurrence of occasional decreases. We estimate decadal altitude increments of 25 m for forest line, 13 m for treeline and 11 m for tundra line. We also identified changes in ecotone spatial morphology between the two dates, with significant implications in connectivity and colonisation dynamics. © 2009 Elsevier B.V. All rights reserved.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1308899616
Document Type :
Electronic Resource