scholarly journals Vegetation Structural Complexity and Biodiversity Across Elevation Gradients in the Great Smoky Mountains

2020 ◽  
Author(s):  
Jonathan Walter ◽  
Atticus Stovall ◽  
Jeff Atkins
Keyword(s):  
Forest Structure ◽  
Vegetation Structure ◽  
Vascular Plant ◽  
Structural Complexity ◽  
Plant Biodiversity ◽  
Structural Variations ◽  
Elevation Gradients ◽  
Great Smoky Mountains ◽  
Complexity Metrics ◽  
Smoky Mountains

Questions: Elevation, biodiversity, and forest structure are commonly correlated, but their relationships near the positive extremes of biodiversity and elevation are unclear. We asked 1) How does forest structure vary with elevation in a high biodiversity, high topographic complexity region? 2) Does forest structure predict vascular plant biodiversity? 3) Is plant biodiversity more strongly related to elevation or to forest structure? Location: Great Smoky Mountains National Park, USAMethods: We used terrestrial LiDAR scanning (TLS) to characterize vegetation structure in 12 forest plots. We combined two new canopy structural complexity metrics with traditional TLS-derived forest structural metrics and vascular plant biodiversity data to investigate correlations among forest structure metrics, biodiversity, and elevation. Results: Forest structure varied widely across plots spanning the elevational range of GRSM. Our new measures of canopy density (Depth) and structural complexity (σDepth) were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Vascular plant biodiversity was negatively correlated with elevation, and more strongly positively correlated with vegetation structure variables. Conclusions: The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

Using Airborne Laser Scanning to characterize different land uses in a tropical landscape based on their structural complexity

2021 ◽  
Author(s):  
Nicoló Camarretta ◽  
Martin Ehbrecht ◽  
Arne Wenzel ◽  
Mohd Zuhdi ◽  
Miryam S. Merk ◽  
...  
Keyword(s):  
Land Use ◽  
Tropical Forest ◽  
Tropical Forests ◽  
Forest Structure ◽  
Oil Palm ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Structural Complexity ◽  
Airborne Laser ◽  
Structural Metrics

<p>Accurate characterization of land use and land cover (LULC) is important in a rapidly changing environment such as the Indonesian tropics. Over the past 30 years, native tropical forests have been cleared and replaced by fast-growing cash-crops, such as oil palm and rubber plantations. This change in land use dramatically alters the vegetation structure of the entire region. Vegetation structural complexity is highly variable in tropical forests, and provides habitat to a large number of native species. In addition, vegetation structure has an impact on micro-climate and the exchange of greenhouse gases (GHG), water and energy. Measuring vegetation structure in the field can be costly and time consuming, particularly in remote, inaccessible areas of tropical forest. In contrast, Airborne Laser Scanning (ALS) can provide very detailed three-dimensional information on forest structure without the need to reach remote areas in the field. Here, we aim to study the potential of ALS-derived measures of structural complexity as ecological indicators to highlight differences in forest structure across a gradient of LULC in Sumatra, Indonesia. We analysed the structural complexity of four main LULC types relevant to the region: tropical secondary forests, rubber agroforests, oil palm plantations and shrublands. Several structural metrics have been extracted from ALS data over 136 circular 0.1 ha plots (34 plots per LULC type): top height, height percentiles, rumple index, leaf area index (LAI), effective number of layers (ENL), vegetation cover, number of gaps. Results from a Principal Component Analysis (PCA) indicated number of gaps to be a major driver associated with the occurrence of oil palm plantations, while higher values of key structural metrics, such as top height, LAI and ENL were strongly linked with the presence of secondary tropical forest plots. Furthermore, a clear separation in metrics behaviour between forest and oil palm plots was evident from the pairwise comparison of these metrics, with rubber and shrubland plots behaving similarly to either forests or oil palm plantings according to different metrics. Our results show clear distinctions in several structural attributes among different LULC, which indicate the need for careful considerations regarding the impact of land-use change on ecosystem functioning, biodiversity and climate.</p>

scholarly journals Vegetation structural complexity and biodiversity in the Great Smoky Mountains

Ecosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
Author(s):  
Jonathan A. Walter ◽  
Atticus E. L. Stovall ◽  
Jeff W. Atkins
Keyword(s):  
Structural Complexity ◽  
Great Smoky Mountains ◽  
Smoky Mountains

Using Spatial Modeling to Improve Wetland Inventories in Great Smoky Mountains National Park

2019 ◽  
Vol 39 (4) ◽  
pp. 482
Author(s):  
Alix A. Pfennigwerth ◽  
Joshua Albritton ◽  
Troy Evans
Keyword(s):  
Spatial Modeling ◽  
National Park ◽  
Great Smoky Mountains ◽  
Smoky Mountains

Black Bear/Human Conflicts in the Great Smoky Mountains National Park

1980 ◽  
Vol 4 ◽  
pp. 137 ◽  
Author(s):  
Francis J. Singer ◽  
Susan Power Bratton
Keyword(s):  
National Park ◽  
Black Bear ◽  
Great Smoky Mountains ◽  
Smoky Mountains
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