Sampling Vegetation for Biomass, Productivity, and Leaf Area Index at the Continental Scale

Monday, 15 December 2014
Courtney L Meier, Katherine D. Jones and Andrea Thorpe, NEON Inc., Boulder, CO, United States
As part of the NEON Terrestrial Observation System (TOS), the sampling design for plant biomass, productivity, and leaf area index (LAI) measurements forms the basis of how NEON will enable a nuanced understanding of terrestrial carbon cycle responses to ecosystem change drivers. The plant biomass and productivity sampling design is also critical to maximizing the utility of flux and soil measurements that are part of the Terrestrial Instrument System, as well as spectrometer and LiDAR measurements made by the Airborne Observation Platform, and the design explicitly states how these links are created. The plant biomass and productivity sampling falls into three main categories: 1) aboveground vegetation sampling; 2) belowground vegetation sampling; and 3) LAI sampling. Here, we describe the basic components of the sampling design associated with these three categories, and how sampling is standardized across very different suites of measurements. At the coarsest level, each terrestrial NEON site will support plant biomass and productivity measurements in three types of plots: Distributed plots located throughout the site, Gradient plots that capture site-level differences in important plant biophysical variables, and Tower plots that will enable a fine-grain partitioning of annual net primary productivity across different vegetation components. We also discuss how the timing of vegetation sampling will be standardized across the Observatory so that interannual variation in response variables can best be interpreted. Data from this sampling design will produce a long-term record of how plant biomass stocks and fluxes respond to change drivers at site, regional, and continental spatial scales. Ideally, the data will also inform and inspire process-based, PI-driven research within the user-community, as well as ecosystem modeling efforts.