Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands

The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was −0.05 petagrams of C per year (Pg C yr−1) associated with drying trends, and a net change of −0.02 Pg C yr−1 was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, −0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area.Low-frequency passive microwave data (L-VOD) allow quantification of biomass change in sub-Saharan Africa between 2010 and 2016, revealing climate-induced carbon losses, particularly in drylands.

[1]  R. Betts,et al.  Plant functional type classification for earth system models: results from the European Space Agency's Land Cover Climate Change Initiative , 2015 .

[2]  Thuy Le Toan,et al.  Biomass assessment in the Cameroon savanna using ALOS PALSAR data , 2014 .

[3]  David Kenfack,et al.  Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks , 2014 .

[4]  M. Wahlen,et al.  Interannual extremes in the rate of rise of atmospheric carbon dioxide since 1980 , 1995, Nature.

[5]  Jan Verbesselt,et al.  Combining satellite data for better tropical forest monitoring , 2016 .

[6]  Niklaus E. Zimmermann,et al.  Plant functional type mapping for earth system models , 2011 .

[7]  Benjamin Smith,et al.  Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model , 2013 .

[8]  Yann Kerr,et al.  Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission , 2001, IEEE Trans. Geosci. Remote. Sens..

[9]  Rasmus Fensholt,et al.  Greenness in semi-arid areas across the globe 1981–2007 — an Earth Observing Satellite based analysis of trends and drivers , 2012 .

[10]  P. Ciais,et al.  The carbon balance of Africa: synthesis of recent research studies , 2011, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[11]  I. C. Prentice,et al.  A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system , 2005 .

[12]  W. Salas,et al.  Benchmark map of forest carbon stocks in tropical regions across three continents , 2011, Proceedings of the National Academy of Sciences.

[13]  Yi Y. Liu,et al.  Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle , 2014, Nature.

[14]  A. Al Bitar,et al.  Modelling the Passive Microwave Signature from Land Surfaces: A Review of Recent Results and Application to the L-Band SMOS SMAP Soil Moisture Retrieval Algorithms , 2017 .

[15]  Matthew F. McCabe,et al.  Recent reversal in loss of global terrestrial biomass , 2015 .

[16]  Praveena Krishnan,et al.  CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America , 2017, Global change biology.

[17]  Arief Wijaya,et al.  An integrated pan‐tropical biomass map using multiple reference datasets , 2016, Global change biology.

[18]  J. Chambers,et al.  Tree allometry and improved estimation of carbon stocks and balance in tropical forests , 2005, Oecologia.

[19]  Arnaud Mialon,et al.  SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product , 2017, Remote. Sens..

[20]  Robert B. Cook,et al.  The North American Carbon Program Multi-scale Synthesis and Terrestrial Model Intercomparison Project – Part 2: Environmental driver data , 2013 .

[21]  Jinfeng Chang,et al.  Sensitivity of land use change emission estimates to historical land use and land cover mapping , 2017 .

[22]  Christopher A Williams,et al.  Africa and the global carbon cycle , 2007, Carbon balance and management.

[23]  Arnaud Mialon,et al.  The SMOS Soil Moisture Retrieval Algorithm , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Jianping Huang,et al.  Evolution of land surface air temperature trend , 2014 .

[25]  Sandra A. Brown,et al.  Monitoring and estimating tropical forest carbon stocks: making REDD a reality , 2007 .

[26]  P. Ciais,et al.  Vegetation greenness and land carbon-flux anomalies associated with climate variations: a focus on the year 2015 , 2017 .

[27]  J. Michaelsen,et al.  The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes , 2015, Scientific Data.

[28]  Martin Brandt,et al.  Human population growth offsets climate-driven increase in woody vegetation in sub-Saharan Africa , 2017, Nature Ecology &Evolution.

[29]  Béatrice Josse,et al.  Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes , 2013 .

[30]  N. McDowell,et al.  A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests , 2010 .

[31]  A. Arneth,et al.  Climate–fire interactions and savanna ecosystems: a dynamic vegetation modeling study for the African continent , 2010 .

[32]  William J. Bond,et al.  Woodland expansion in South African grassy biomes based on satellite observations (1990–2013): general patterns and potential drivers , 2017, Global change biology.

[33]  Martin Brandt,et al.  Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel , 2016 .

[34]  T. Rudel,et al.  The national determinants of deforestation in sub-Saharan Africa , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.

[35]  Richard A. Houghton,et al.  Global and regional fluxes of carbon from land use and land cover change 1850–2015 , 2017 .

[36]  Y. Kerr,et al.  L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields , 2007 .

[37]  Martin Brandt,et al.  Woody Vegetation Die off and Regeneration in Response to Rainfall Variability in the West African Sahel , 2017, Remote. Sens..

[38]  A. Al Bitar,et al.  Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation , 2016 .

[39]  Alan Grainger,et al.  The extent of forest in dryland biomes , 2017, Science.

[40]  Maurizio Santoro,et al.  Global covariation of carbon turnover times with climate in terrestrial ecosystems , 2014, Nature.

[41]  E. Stehfest,et al.  Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands , 2011 .

[42]  Atul K. Jain,et al.  The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink , 2015, Science.

[43]  A. Cazenave,et al.  The ESA Climate Change Initiative: Satellite Data Records for Essential Climate Variables , 2013 .

[44]  D. Etheridge,et al.  Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years from air in Antarctic ice and firn , 1996 .

[45]  S. Goetz,et al.  Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps , 2012 .

[46]  Dell,et al.  Contrasting carbon cycle responses of the tropical continents to the 2015–2016 El Niño , 2017, Science.

[47]  Nicola Stevens,et al.  Woody encroachment over 70 years in South African savannahs: overgrazing, global change or extinction aftershock? , 2016, Philosophical Transactions of the Royal Society B: Biological Sciences.

[48]  Earth Observation for Land and Emergency Monitoring , 2017 .

[49]  Biogeoscience: Africa's greenhouse-gas budget is in the red , 2014, Nature.

[50]  P. Jones,et al.  Updated high‐resolution grids of monthly climatic observations – the CRU TS3.10 Dataset , 2014 .

[51]  C. Justice,et al.  High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.