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Carbon Stocks and Fluxes in Kenyan Forests and Wooded Grasslands Derived from Earth Observation and Model-Data Fusion

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posted on 2021-03-16, 14:14 authored by Pedro Rodríguez-Veiga, Joao Carreiras, Thomas Luke Smallman, Jean-François Exbrayat, Jamleck Ndambiri, Faith Mutwiri, Divinah Nyasaka, Shaun Quegan, Mathew Williams, Heiko Balzter
The characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. Here we present the most detailed and rigorous national-scale assessment of aboveground woody biomass carbon stocks and dynamics for Kenya to date. A non-parametric random forest algorithm was trained to retrieve aboveground woody biomass carbon (AGBC) for the year 2014 ± 1 and forest disturbances for the 2014–2017 period using in situ forest inventory plot data and satellite Earth Observation (EO) data. The ecosystem carbon cycling of Kenya’s forests and wooded grassland were assessed using a model-data fusion framework, CARDAMOM, constrained by the woody biomass datasets from this study as well as time series information on leaf area, fire events and soil organic carbon. Our EO-derived AGBC stocks were estimated as 140 Mt C for forests and 199 Mt C for wooded grasslands. The total AGBC loss during the study period was estimated as 1.89 Mt C with a dispersion below 1%. The CARDAMOM analysis estimated woody productivity to be three times larger in forests (mean = 1.9 t C ha−1 yr−1) than wooded grasslands (0.6 t C ha−1 yr−1), and the mean residence time of woody C in forests (16 years) to be greater than in wooded grasslands (10 years). This study stresses the importance of carbon sequestration by forests in the international climate mitigation efforts under the Paris Agreement, but emphasizes the need to include non-forest ecosystems such as wooded grasslands in international greenhouse gas accounting frameworks.

History

Citation

Remote Sens. 2020, 12(15), 2380; https://doi.org/10.3390/rs12152380

Author affiliation

Centre for Landscape and Climate Research, School of Geography, Geology and the Environment

Version

  • VoR (Version of Record)

Published in

Remote Sensing

Volume

12

Issue

15

Pagination

2380

Publisher

MDPI AG

eissn

2072-4292

Acceptance date

2020-07-23

Copyright date

2020

Available date

2021-03-16

Language

en

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