Understanding patterns of vegetation degradation at meaningful scales within saline landscapes

Callow, J. N. (2011) Understanding patterns of vegetation degradation at meaningful scales within saline landscapes. Ecohydrology, 4 6: 841-854. doi:10.1002/eco.190

Author Callow, J. N.
Title Understanding patterns of vegetation degradation at meaningful scales within saline landscapes
Journal name Ecohydrology   Check publisher's open access policy
ISSN 1936-0584
Publication date 2011-11
Sub-type Article (original research)
DOI 10.1002/eco.190
Volume 4
Issue 6
Start page 841
End page 854
Total pages 14
Collection year 2012
Language eng
Abstract Understanding patterns of vegetation degradation in saline catchments has been a major challenge to ecohydrology researchers in the conservation biology, geomorphology and hydrology disciplines. Hydrologists have measured streamflow quantity and quality at point locations and modelled at the landscape or macro-scale. Botanists have investigated species diversity, structure and patterns at the micro-scale in transect studies. Yet, the reach-scale is widely recognized as the most appropriate scale for management and considering geomorphology. As a result, links between streamflow salinity and vegetation condition and river health remain poorly understood in a spatial sense. This study uses digital multi-spectral imagery (DMSI) collected along a freshening downstream salinity gradient in a southwestern Australian catchment affected by secondary dryland salinity. DMSI was collected over 59 km in a 1200-m swath at the micro-scale (2-m pixels), and calibrated against field transect data from 12 sites across three sections (degraded, transitional and ‘locally healthy’) to map vegetation condition. Results show that measures of mean annual salinity cannot account for variability in vegetation condition, but peak salinity concentration maintained over a length of time similar to greenhouse trials of plant mortality (¾60 days) appears to be a physiologically meaningful descriptor of streamflow salinity. The 60-day peak salinity concentration showed high correlation to patterns of vegetation condition and published plant salinity tolerance values. Remote-sensed imagery that captures vegetative condition in combination with physiologically meaningful descriptors of streamflow salinity provides a powerful tool to identify the spatial patterns of vegetation degradation at meaningful management scales within a saline catchment.
Keyword Dryland salinity
Riparian vegetation
Digital multi-spectral imagery (DMSI)
Channel geomorphology
Catchment management
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2012 Collection
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Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 2 times in Scopus Article | Citations
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