Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers

2021 | journal article; research paper. A publication with affiliation to the University of Göttingen.

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​Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers​
Seidel, D. ; Annighöfer, P.; Ammer, C. ; Ehbrecht, M.; Willim, K.; Bannister, J. & Soto, D. P.​ (2021) 
Remote Sensing13(8) pp. 1513​.​ DOI: https://doi.org/10.3390/rs13081513 

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Authors
Seidel, Dominik ; Annighöfer, Peter; Ammer, Christian ; Ehbrecht, Martin; Willim, Katharina; Bannister, Jan; Soto, Daniel P.
Abstract
The structural complexity of the understory layer of forests or shrub layer vegetation in open shrublands affects many ecosystem functions and services provided by these ecosystems. We investigated how the basal area of the overstory layer, annual and seasonal precipitation, annual mean temperature, as well as light availability affect the structural complexity of the understory layer along a gradient from closed forests to open shrubland with only scattered trees. Using terrestrial laser scanning data and the understory complexity index (UCI), we measured the structural complexity of sites across a wide range of precipitation and temperature, also covering a gradient in light availability and basal area. We found significant relationships between the UCI and tree basal area as well as canopy openness. Structural equation models (SEMs) confirmed significant direct effects of seasonal precipitation on the UCI without mediation through basal area or canopy openness. However, annual precipitation and temperature effects on the UCI are mediated through canopy openness and basal area, respectively. Understory complexity is, despite clear dependencies on the available light and overall stand density, significantly and directly driven by climatic parameters, particularly the amount of precipitation during the driest month.
Issue Date
2021
Journal
Remote Sensing 
Organization
Fakultät für Forstwissenschaften und Waldökologie ; Burckhardt-Institut ; Abteilung Räumliche Strukturen und Digitalisierung von Wäldern 
eISSN
2072-4292
Language
English
Sponsor
Deutsche Forschungsgemeinschaft
Fondo Nacional de Desarrollo Científico y Tecnológico
Open-Access-Publikationsfonds 2021

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