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Utilizing a topographic moisture index to characterize understory vegetation patterns in the boreal forest

Author:
Echiverri, Laureen, Macdonald, S. Ellen
Source:
Forest ecology and management 2019 v.447 pp. 35-52
ISSN:
0378-1127
Subject:
biodiversity conservation, boreal forests, digital elevation models, forest types, landscapes, lidar, plant communities, remote sensing, species diversity, topography, understory, Alberta
Abstract:
For the purpose of informing biodiversity conservation efforts in managed landscapes, we explored whether and how understory plant communities (abundance, diversity, composition) were related to a topographic moisture index, called depth-to-water, in the boreal mixedwood forests of northwestern Alberta. Depth-to-water is an index of relative site moisture derived from the Wet Areas Mapping tool using a fine-scale digital elevation model based upon remotely-sensed lidar (light detection and ranging) data. Sample plots were placed along the depth-to-water moisture gradient in three forest types: conifer-dominated, mixedwood, and broadleaf -(deciduous) dominated. Understory vascular plant diversity, abundance, and composition were measured for each plot. We found understory attributes were related to the depth-to-water index with the relationships varying among forest types. In coniferous stands, diversity and abundance (cover) were higher on drier sites. In broadleaf and mixedwood stands, understory abundance was higher on drier sites, but diversity was not related to the depth-to-water index. Lastly, composition was significantly, but weakly, related to the depth-to-water index in all three forest types. Our study shows that this moisture index, based on remotely-sensed data, can be used to characterize patterns in understory vascular plant communities; hence it can be useful for identifying areas of particular interest for conservation or management.
Agid:
6449856