Abstract
Research Highlights: Estimates using measurements from a sample of approximately 132,000 field plots imply that while the species composition of US forests varies substantially across different age groups, the specific gravity of wood in those forests does not. This suggests that models using increasingly accurate spaceborne measurements of tree size to model forest biomass do not need to consider stand age as a covariate, greatly reducing model complexity and calibration data requirements. Background and Objectives: Upcoming lidar and radar platforms will give us unprecedented information about how big the trees around the world are. To estimate biomass from these measurements, one must know if tall trees in young stands have the same biomass density as trees of equal size in older stands. Conventional succession theory suggests that fast-growing pioneers often have lower wood (and biomass) density than the species that eventually dominate older stands. Materials and Methods: We used a nationally consistent database of field measurements to analyze patterns of both wood specific gravity (WSG) across age groups in the United States and changes of species composition that would explain any shifts in WSG. Results: Shifts in species composition were observed across 12 different ecological divisions within the US, reflecting both successional processes and management history impacts. However, steady increases in WSG with age were not observed, and WSG differences were much larger across ecosystems than across within-ecosystem age groups. Conclusions: With no strong evidence that age is important in specifying how much biomass to ascribe to trees of a particular size, field data collection can focus on acquiring reference data in poorly sampled ecosystems instead of expanding existing samples to include a range of ages for each level of canopy height.
Highlights
Forest biomass is a globally important carbon reservoir, and forest growth can significantly mitigate the climate-altering effects of fossil fuel emissions [1,2]
With no strong evidence that age is important in specifying how much biomass to ascribe to trees of a particular size, field data collection can focus on acquiring reference data in poorly sampled ecosystems instead of expanding existing samples to include a range of ages for each level of canopy height
GEDI (NASA’s Global Ecosystem Dynamics Investigation) uses waveform lidar to measure aboveground biomass (AGB) at 22-m footprints, which is in turn used to infer mean biomass at the level of 1-km grid cells [3,4,5]; BIOMASS uses P-band radar to map AGB at
Summary
Forest biomass is a globally important carbon reservoir, and forest growth can significantly mitigate the climate-altering effects of fossil fuel emissions [1,2]. ICESAT-2 (NASA) uses linear tracks of pulse-counting lidar that, in combination with other instruments, allows measurement of vegetation biomass [8] While sensors such as these provide observations closely correlated with forest structure, biomass must be inferred through the use of models calibrated with ground measurements [9,10,11]. Such models imply, sometimes explicitly [12], a stand-level wood density: a ratio of measured canopy volume to biomass. Within individual ecosystems, it is well understood that faster-growing pioneer species often have lower WSG than later-successional trees [13,14]
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