Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests

Smallman, T. L.; Exbrayat, J. -F.; Mencuccini, M.; Bloom, A. A.; Williams, M.

doi:10.1002/2016JG003520

Title: Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests

Journal Article · Wed Mar 01 00:00:00 EST 2017 · Journal of Geophysical Research. Biogeosciences

DOI:https://doi.org/10.1002/2016JG003520· OSTI ID:1466301

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Univ. of Edinburgh, Scotland (United Kingdom). School of GeoSciences; Univ. of Edinburgh, Scotland (United Kingdom). National Centre for Earth Observation
Univ. of Edinburgh, Scotland (United Kingdom). School of GeoSciences; ICREA at CREAF, Cerdanyola del Valles (Spain)
California Inst. of Technology (CalTech), La Canada Flintridge, CA (United States). Jet Propulsion Lab.

Forest carbon sink strengths are governed by plant growth, mineralization of dead organic matter, and disturbance. Across landscapes, remote sensing can provide information about aboveground states of forests and this information can be linked to models to estimate carbon cycling in forests close to steady state. For aggrading forests this approach is more challenging and has not been demonstrated. Here in this paper we apply a Bayesian approach, linking a simple model to a range of data, to evaluate their information content, for two aggrading forests. We compare high information content analyses using local observations with retrievals using progressively sparser remotely sensed information (repeated, single, and no woody biomass observations). The net biome productivity of both forests is constrained to be a net sink with <2 Mg C ha^-1 yr^-1 variation across the range of inputs. However, the sequestration of particular carbon pool(s) varies with assimilated biomass information. Assimilation of repeated biomass observations reduces uncertainty and/or bias in all ecosystem C pools not just wood, compared to analyses using single or no stock information. As verification, our repeated biomass analysis explains 78–86% of variation in litter dynamics at one forest, while at the second forest total dead organic matter estimates are within observational uncertainty. The uncertainty of retrieved ecosystem traits in the repeated biomass analysis is reduced by up to 50% compared to analyses with less biomass information. This study quantifies the importance of repeated woody observations in constraining the dynamics of both wood and dead organic matter, highlighting the benefit of proposed remote sensing missions.

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Research Organization:: Duke Univ., Durham, NC (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: FG02-95ER62083; AC02-98CH10886

OSTI ID:: 1466301

Alternate ID(s):: OSTI ID: 1402168

Journal Information:: Journal of Geophysical Research. Biogeosciences, Vol. 122, Issue 3; ISSN 2169-8953

Publisher:: American Geophysical UnionCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 35 works

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