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Searching for rainforest understorey in wet Eucalyptus forest

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White, RJ 2017 , 'Searching for rainforest understorey in wet Eucalyptus forest', Honours thesis, University of Tasmania.

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Abstract

Increasing pressure from anthropogenic and natural disturbances can lead to irreversible shifts in the composition and structure of vegetation. Fire-sensitive rainforest communities in the understorey of Tasmania’s wet Eucalyptus forests are particularly susceptible to these disturbances. Currently, forest managers have no means of comprehensively mapping these understorey rainforest communities; fieldwork techniques are costly and impractical at the landscape scale, and most remote sensing techniques are unable to effectively map sub-canopy habitats due to the blocking effect of the canopy. This presents a challenge for forest managers that must be addressed if these forests are to be managed sustainably. In this project, I examine two techniques that explore potential relationships between floristic and structural forest components as a means of locating rainforest understoreys.
First, based on the premise that fire-driven succession of canopy and understorey strata follow parallel trajectories, I tested whether eucalypt canopy age-structure can be used to predict understorey floristics. I surveyed forty plots representative of the structural variation in the landscape, measuring the relative amounts of rainforest and old-growth eucalypts in each. From this, I generated a eucalypt old-growth and a rainforest variable, and compared these using Spearman’s rank correlation. While positive, the correlation between these variables was weak (ρ = 0.43). This result was unexpected, but may be explained by potentially independent effects of fire-disturbance in these two strata. Second, I used a LiDAR-based approach in an attempt to delineate rainforest understoreys based on structural characteristics. For this, I developed a suite of understorey LiDAR metrics that were tested against the amount of rainforest in the understorey using Spearman’s rank correlation and Random Forest analysis. Canopy density and height-based metrics showed significant positive correlations, but these were too weak for predictive purposes (ρ < 0.69). Similarly, the Random Forest analysis was unable to identify a predictive relationship (percent variance explained = 46 %). These analyses exposed notable structural overlap among the rainforest and wet sclerophyll understorey types.
This project revealed a mismatch between canopy age-structure and understorey floristics, and between the structure and floristics within the understorey. I suggest that to better understand these relationships more research into fire-driven disturbances on understorey and canopy strata is required. This research, and the use of novel remote sensing approaches and technologies, will enable more effective management of understorey rainforest communities.

Item Type: Thesis - Honours
Authors/Creators:White, RJ
Keywords: rainforest, LiDAR, remote sensing, WARRA, forest management, forest ecology
Copyright Information:

Copyright 2017 the author.

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