Is Canopy Structural Complexity a Global Predictor of Primary Production?: Transforming Understanding of Forest Structure-Function Linkages Using NEON Sites.

Atkins, Jeffrey

Forests of the United States take up and store in plant biomass an enormous amount of carbon emitted from human activities, thereby slowing the accumulation of atmospheric carbon dioxide, a greenhouse gas. Canopy structure, an ecosystem feature that can be broadly characterized using remote sensing technologies, is a well-established determinant of forest carbon storage, with the quantity of canopy leaves a universal predictor of carbon storage that is incorporated into models used to forecast how the Nation's dynamic and diverse forested landscape affects climate. Recent work from a limited number of sites shows that the arrangement of leaves within a volume of canopy may be as influential to forest carbon storage as leaf quantity. Results from these studies suggest that leaf quantity and arrangement provide unique, complementary information about the underlying biological controls on forest carbon storage. Thus, coordinated measurements of both leaf quantity and arrangement within the canopies of a diverse array of forests may lead to substantially improved modeled estimates of carbon storage by the Nation's forests. In support of this goal, work here uses sites from the National Ecological Observatory Network (NEON) to evaluate whether canopy structural complexity, or the spatial variability in leaf arrangement within a canopy, is a global predictor of forest carbon storage within and across sites varying in physical structure, species composition and diversity, and climate. NEON's standardized methods, systematic sampling design, breadth of data, wide geographic footprint, and built-in gradient of forest physical structure provide an unprecedented opportunity to determine whether carbon storage-canopy structural complexity relationships are broadly generalizable. Enhanced knowledge of the role forest canopy structural complexity plays in carbon storage could transform fundamental understanding of how ecosystem structure affects carbon uptake, leading to more accurate climate models for informing science-based policy. Additionally, the results of this study have broad implications for how forests of the United States are managed in support of greenhouse gas mitigation and will provide new information on how management practices that modify canopy structure broadly affect land carbon sequestration. This project will train undergraduate, graduate, and postdoctoral researchers from a diverse group of academic institutions, and form the basis for a new Biology course at Virginia Commonwealth University taught by the project's postdoctoral associate. The researchers, including students and a postdoctoral associate, will play key roles in an NSF-supported research network that aims to develop broadly applicable remote sensing tools for quantifying forest features relevant to land managers, foresters, policy makers, and ecosystem and climate modelers. During the summer of 2016, we plan to use our portable canopy LiDAR (PCL) system to scan forests in order to quantify canopy structural complexity. The duration of our work would be three to five days per site and would be of minimum impact. The PCL is attached to the user. It is an upward facing, eye-safe laser that makes 2000 hz scans of the forest canopy. To conduct a scan, the user simply walks a predefined transect of 30-60 m length through the forest. To define a transect, a transect tape is laid out and flags are inserted into the ground at 10 m intervals. Following the scan, flags are removed and cleaned.

Is Canopy Structural Complexity a Global Predictor of Primary Production?: Transforming Understanding of Forest Structure-Function Linkages Using NEON Sites.

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