scholarly journals Precipitation as driver of carbon fluxes in 11 African ecosystems

2008 ◽  
Vol 5 (5) ◽  
pp. 4071-4105 ◽  
Author(s):  
L. Merbold ◽  
J. Ardö ◽  
A. Arneth ◽  
R. J. Scholes ◽  
Y. Nouvellon ◽  
...  
Keyword(s):  
Land Surface ◽  
Ecosystem Respiration ◽  
Carbon Assimilation ◽  
Vapour Pressure Deficit ◽  
Sub Saharan Africa ◽  
Annual Rainfall ◽  
C3 Plants ◽  
Water Vapour Pressure ◽  
Mean Annual Rainfall ◽  
Sub Saharan

Abstract. This study reports carbon and water fluxes between the land surface and atmosphere in eleven different ecosystems types in Sub-Saharan Africa, as measured using eddy covariance (EC) technology in the first two years of the CarboAfrica network operation. The ecosystems for which data were available ranged in mean annual rainfall from 320 mm (Sudan) to 1150 mm (The Republic of Congo) and include a spectrum of vegetation types (or land cover) (open savannas, woodlands, croplands and grasslands). Given the shortness of the record, the EC data were analysed across the network rather than longitudinally at sites, in order to understand the driving factors for ecosystem respiration and carbon assimilation, and to reveal the different water use strategies in these highly seasonal environments. Values for maximum net carbon assimilation rates (photosynthesis) ranged from 12 μmol CO2 m−2 s−1 in a dry, open Acacia savanna (C3-plants) up to 40 μmol CO2 m−2 s−1 for a tropical moist grassland. Maximum carbon assimilation rates were highly correlated with mean annual rainfall (R2=0.89). Maximum photosynthetic uptake rates were positively related to satellite-derived fAPAR. Ecosystem respiration was dependent on temperature at all sites, and was additionally dependent on soil water content at sites receiving less than 1000 mm of rain per year. All included ecosystems, except the Congolese grassland, showed a strong decrease in 30-min assimilation rates with increasing water vapour pressure deficit above 2.0 kPa.

scholarly journals Precipitation as driver of carbon fluxes in 11 African ecosystems

2009 ◽  
Vol 6 (6) ◽  
pp. 1027-1041 ◽  
Author(s):  
L. Merbold ◽  
J. Ardö ◽  
A. Arneth ◽  
R. J. Scholes ◽  
Y. Nouvellon ◽  
...  
Keyword(s):  
Land Surface ◽  
Ecosystem Respiration ◽  
Carbon Assimilation ◽  
Vapour Pressure Deficit ◽  
Sub Saharan Africa ◽  
Annual Rainfall ◽  
C3 Plants ◽  
Water Vapour Pressure ◽  
Mean Annual Rainfall ◽  
Sub Saharan

Abstract. This study reports carbon and water fluxes between the land surface and atmosphere in eleven different ecosystems types in Sub-Saharan Africa, as measured using eddy covariance (EC) technology in the first two years of the CarboAfrica network operation. The ecosystems for which data were available ranged in mean annual rainfall from 320 mm (Sudan) to 1150 mm (Republic of Congo) and include a spectrum of vegetation types (or land cover) (open savannas, woodlands, croplands and grasslands). Given the shortness of the record, the EC data were analysed across the network rather than longitudinally at sites, in order to understand the driving factors for ecosystem respiration and carbon assimilation, and to reveal the different water use strategies in these highly seasonal environments. Values for maximum net carbon assimilation rates (photosynthesis) ranged from −12.5 μmol CO2 m−2 s−1 in a dry, open Millet cropland (C4-plants) up to −48 μmol CO2 m−2 s−1 for a tropical moist grassland. Maximum carbon assimilation rates were highly correlated with mean annual rainfall (r2=0.74). Maximum photosynthetic uptake rates (Fpmax) were positively related to satellite-derived fAPAR. Ecosystem respiration was dependent on temperature at all sites, and was additionally dependent on soil water content at sites receiving less than 1000 mm of rain per year. All included ecosystems dominated by C3-plants, showed a strong decrease in 30-min assimilation rates with increasing water vapour pressure deficit above 2.0 kPa.

scholarly journals Farmers’ Perceptions on Climate Variability and Adaptation Strategies to Climate Change in Cinzana, Mali

2016 ◽  
Vol 4 (3) ◽  
pp. 13 ◽  
Author(s):  
Touré Halimatou ◽  
Zampaligre Nouhoun ◽  
Traoré Kalifa ◽  
Kyei-Baffour Nicholas
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Meteorological Data ◽  
Rainfall Variability ◽  
Adaptation Strategies ◽  
Sub Saharan Africa ◽  
Farm Size ◽  
Annual Rainfall ◽  
Sub Saharan ◽  
Future Economic Development

Several studies predict that climate change will highly affect the African continent. These changes in climate and climate variability may be challenging issues for future economic development of the continent in general, and particularly in the region of sub Saharan Africa. Offering a case study of Sahelian zone of Mali in the present study aimed to understand farmers’ perceptions of climate variability and change and to evaluate adaptation options used by farmers in the Cinzana commune of Mali. One hundred and nineteen farmers were interviewed using a questionnaire designed with six sections. The result showed that all farmers interviewed were aware of climate change and climate variability. The Farmers perceived a decrease in annual rainfall variability and an increase of temperature as main factors of climate change and climate variability. The observed meteorological data, showed a decrease of precipitation distribution during the last 14 years of which was observed by farmers. Several strategies such as selling animals, use of improved crop varieties, new activities (outside agriculture) and credit were the commonly preferred adaptation strategies to deal with climate change and variability. Factors surveyed, age, gender, education, household size, farm size were found to be significantly correlated to self-reported to adaptation.

scholarly journals LINKING SATELLITE REMOTE SENSING BASED ENVIRONMENTAL PREDICTORS TO DISEASE: AN APPLICATION TO THE SPATIOTEMPORAL MODELLING OF SCHISTOSOMIASIS IN GHANA

2016 ◽  
Vol XLI-B8 ◽  
pp. 215-221
Author(s):  
M. Wrable ◽  
A. Liss ◽  
A. Kulinkina ◽  
M. Koch ◽  
N. K. Biritwum ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Disease Transmission ◽  
Land Surface ◽  
Health Surveys ◽  
Risk Model ◽  
Clinical Symptoms ◽  
Sub Saharan Africa ◽  
Small Scale ◽  
Environmental Predictors ◽  
Sub Saharan

90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R<sup>2</sup> as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

scholarly journals Fire Activity and Fuel Consumption Dynamics in Sub-Saharan Africa

2018 ◽  
Vol 10 (10) ◽  
pp. 1591 ◽  
Author(s):  
Gareth Roberts ◽  
Martin Wooster ◽  
Weidong Xu ◽  
Jiangping He
Keyword(s):  
Fuel Consumption ◽  
Southern Hemisphere ◽  
Land Surface ◽  
Sub Saharan Africa ◽  
Fuel Load ◽  
Biomass Combustion ◽  
Fire Emissions ◽  
Fire Activity ◽  
Sub Saharan ◽  
The Impact

African landscape fires are widespread, recurrent and temporally dynamic. They burn large areas of the continent, modifying land surface properties and significantly affect the atmosphere. Satellite Earth Observation (EO) data play a pivotal role in capturing the spatial and temporal variability of African biomass burning, and provide the key data required to develop fire emissions inventories. Active fire observations of fire radiative power (FRP, MW) have been shown to be linearly related to rates of biomass combustion (kg s−1). The Meteosat FRP-PIXEL product, delivered in near real-time by the EUMETSAT Land Surface Analysis Satellite Applications Facility (LSA SAF), maps FRP at 3 km resolution and 15-min intervals and these data extend back to 2004. Here we use this information to assess spatio-temporal variations in fire activity across sub-Saharan Africa, and identify an overall trend of decreasing annual fire activity and fuel consumption, agreeing with the widely-used Global Fire Emissions Database (GFEDv4) based on burned area measures. We provide the first comprehensive assessment of relationships between per-fire FRE-derived fuel consumption (Tg dry matter, DM) and temporally integrated Moderate Resolution Imaging Spectroradiometer (MODIS) net photosynthesis (PSN) (Tg, which can be converted into pre-fire fuel load estimates). We find very strong linear relationships over southern hemisphere Africa (mean r = 0.96) that are partly biome dependent, though the FRE-derived fuel consumptions are far lower than those derived from the accumulated PSN, with mean fuel consumptions per unit area calculated as 0.14 kg DM m−2. In the northern hemisphere, FRE-derived fuel consumption is also far lower and characterized by a weaker linear relationship (mean r = 0.76). Differences in the parameterization of the biome look up table (BLUT) used by the MOD17 product over Northern Africa may be responsible but further research is required to reconcile these differences. The strong relationship between fire FRE and pre-fire fuel load in southern hemisphere Africa is encouraging and highlights the value of geostationary FRP retrievals in providing a metric that relates very well to fuel consumption and fire emission variations. The fact that the estimated fuel consumed is only a small fraction of the fuel available suggests underestimation of FRE by Spinning Enhanced Visible and Infrared Imager (SEVIRI) and/or that the FRE-to-fuel consumption conversion factor of 0.37 MJ kg−1 needs to be adjusted for application to SEVIRI. Future geostationary imaging sensors, such as on the forthcoming Meteosat Third Generation (MTG), will reduce the impact of this underestimation through its ability to detect even smaller and shorter-lived fires than can the current second generation Meteosat.

scholarly journals Kalahari Wildfires Drive Continental Post-Fire Brightening in Sub-Saharan Africa

2019 ◽  
Vol 11 (9) ◽  
pp. 1090
Author(s):  
Michael V. Saha ◽  
Paolo D’Odorico ◽  
Todd M. Scanlon
Keyword(s):  
Energy Budget ◽  
Land Surface ◽  
Regional Climate ◽  
Sub Saharan Africa ◽  
Continental Scale ◽  
Object Based ◽  
Negative Surface ◽  
Sub Saharan ◽  
Sahel Region ◽  
Almost All

Fire can induce long-lived changes to land-surface albedo, an important aspect of the Earth’s energy budget, but the temporal evolution of these anomalies is poorly understood. Due to the widespread presence of fire in Africa, this represents uncertainty in the continental energy budget, which has important implications for regional climate and hydrologic cycling. In this study, we present the first object-based accounting of albedo anomalies induced by larger (>1 km2) individual wildfires in sub-Saharan Africa. We group spatially contiguous wildfire pixels into fire objects and track the albedo anomaly for five years after the burn. We find that albedo anomalies all have the same general temporal signature: An immediate, brief period of darkening followed by persistent brightening. The strongest brightening is found in the Kalahari region while more intense and long-lived initial darkening is found in the Sahel region. The average southern hemisphere albedo anomaly is +1.50 × 10−3 in the year following wildfire, representing a statistically significant negative surface energy balance forcing on a continental scale. This study challenges an existing paradigm surrounding the physical effects of fire on the landscape. Our results suggest that models of albedo that assume a darkening and recovery to baseline are overly simplistic in almost all circumstances. Furthermore, the presumption that immediate darkening is the only meaningful effect on albedo is incorrect for the majority of the African continent.

scholarly journals Assessing Spatio-Temporal Variability of Wildfires and their Impact on Sub-Saharan Ecosystems and Air Quality Using Multisource Remotely Sensed Data and Trend Analysis

2019 ◽  
Vol 11 (23) ◽  
pp. 6811 ◽  
Author(s):  
Kganyago ◽  
Shikwambana
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
Land Surface ◽  
Ghg Emissions ◽  
Ambient Air ◽  
Remotely Sensed ◽  
Sub Saharan Africa ◽  
Height Distribution ◽  
Remotely Sensed Data ◽  
Sub Saharan

Globally, wildfires are considered the most commonly occurring disasters, resulting from natural and anthropogenic ignition sources. Wildfires consist of burning standing biomass at erratic degrees of intensity, severity, and frequency. Consequently, wildfires generate large amounts of smoke and other toxic pollutants that have devastating impacts on ambient air quality and human health. There is, therefore, a need for a comprehensive study that characterizes land–atmosphere interactions with regard to wildfires, critical for understanding the interrelated and multidimensional impacts of wildfires. Current studies have a limited scope and a narrow focus, usually only focusing on one aspect of wildfire impacts, such as air quality without simultaneously considering the impacts on land surface changes and vice versa. In this study, we use several multisource data to determine the spatial distribution, frequency, disturbance characteristics of and variability and distribution of pollutants emitted by wildfires. The specific objectives were to (1) study the sources of wildfires and the period they are prevalent in sub-Saharan Africa over a 9 year period, i.e., 2007–2016, (2) estimate the seasonal disturbance of wildfires on various vegetation types, (3) determine the spatial distribution of black carbon (BC), carbon monoxide (CO) and smoke, and (4) determine the vertical height distribution of smoke. The results show largest burned areas in December–January–February (DJF), June–July–August (JJA) and September–October–November (SON) seasons, and reciprocal high emissions of BC, CO, and smoke, as observed by Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). In addition, the results reveal an increasing trend in the magnitude of BC, and CO concentration driven by meteorological conditions such as low precipitation, low relative humidity, and low latent heat flux. Overall, this study demonstrates the value of multisource remotely sensed data in characterising long-term wildfire patterns and associated emissions. The results in this study are critical for informing better regional fire management and air quality control strategies to preserve endangered species and habitats, promote sustainable land management, and reduce greenhouse gases (GHG) emissions.

scholarly journals Drought and child vaccination coverage in 22 countries in sub-Saharan Africa: A retrospective analysis of national survey data from 2011 to 2019

PLoS Medicine ◽  
2021 ◽  
Vol 18 (9) ◽  
pp. e1003678
Author(s):  
Jason M. Nagata ◽  
Adrienne Epstein ◽  
Kyle T. Ganson ◽  
Tarik Benmarhnia ◽  
Sheri D. Weiser
Keyword(s):  
Retrospective Analysis ◽  
Vaccination Coverage ◽  
Sub Saharan Africa ◽  
Childhood Vaccination ◽  
Annual Rainfall ◽  
Demographic And Health Surveys ◽  
Negatively Associated ◽  
Bcg Vaccination ◽  
Measles Vaccination ◽  
Sub Saharan

Background Extreme weather events, including droughts, are expected to increase in parts of sub-Saharan Africa and are associated with a number of poor health outcomes; however, to the best of our knowledge, the link between drought and childhood vaccination remains unknown. The objective of this study was to evaluate the relationship between drought and vaccination coverage. Methods and findings We investigated the association between drought and vaccination coverage using a retrospective analysis of Demographic and Health Surveys data in 22 sub-Saharan African countries among 137,379 children (50.4% male) born from 2011 to 2019. Drought was defined as an established binary variable of annual rainfall less than or equal to the 15th percentile relative to the 29 previous years, using data from Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. We evaluated the association between drought at the date of birth and receipt of bacillus Calmette–Guérin (BCG), diphtheria–pertussis–tetanus (DPT), and polio vaccinations, and the association between drought at 12 months of age and receipt of measles vaccination. We specified logistic regression models with survey fixed effects and standard errors clustered at the enumeration area level, adjusting for child-, mother-, and household-level covariates and estimated marginal risk differences (RDs). The prevalence of drought at date of birth in the sample was 11.8%. Vaccination rates for each vaccination ranged from 70.6% (for 3 doses of the polio vaccine) to 86.0% (for BCG vaccination); however, only 57.6% of children 12 months and older received all recommended doses of BCG, DPT, polio, and measles vaccinations. In adjusted models, drought at date of birth was negatively associated with BCG vaccination (marginal RD = −1.5; 95% CI −2.2, −0.9), DPT vaccination (marginal RD = −1.4; 95% CI −2.2, −0.5), and polio vaccination (marginal RD = −1.3; 95% CI −2.3, −0.3). Drought at 12 months was negatively associated with measles vaccination (marginal RD = −1.9; 95% CI −2.8, −0.9). We found a dose–response relationship between drought and DPT and polio vaccinations, with the strongest associations closest to the timing of drought. Limitations include some heterogeneity in findings across countries. Conclusions In this study, we observed that drought was associated with lower odds of completion of childhood BCG, DPT, and polio vaccinations. These findings indicate that drought may hinder vaccination coverage, one of the most important interventions to prevent infections among children. This work adds to a growing body of literature suggesting that health programs should consider impacts of severe weather in their programming.

scholarly journals LINKING SATELLITE REMOTE SENSING BASED ENVIRONMENTAL PREDICTORS TO DISEASE: AN APPLICATION TO THE SPATIOTEMPORAL MODELLING OF SCHISTOSOMIASIS IN GHANA

2016 ◽  
Vol XLI-B8 ◽  
pp. 215-221
Author(s):  
M. Wrable ◽  
A. Liss ◽  
A. Kulinkina ◽  
M. Koch ◽  
N. K. Biritwum ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Disease Transmission ◽  
Land Surface ◽  
Health Surveys ◽  
Risk Model ◽  
Clinical Symptoms ◽  
Sub Saharan Africa ◽  
Small Scale ◽  
Environmental Predictors ◽  
Sub Saharan

90% of the worldwide schistosomiasis burden falls on sub-Saharan Africa. Control efforts are often based on infrequent, small-scale health surveys, which are expensive and logistically difficult to conduct. Use of satellite imagery to predictively model infectious disease transmission has great potential for public health applications. Transmission of schistosomiasis requires specific environmental conditions to sustain freshwater snails, however has unknown seasonality, and is difficult to study due to a long lag between infection and clinical symptoms. To overcome this, we employed a comprehensive 8-year time-series built from remote sensing feeds. The purely environmental predictor variables: accumulated precipitation, land surface temperature, vegetative growth indices, and climate zones created from a novel climate regionalization technique, were regressed against 8 years of national surveillance data in Ghana. All data were aggregated temporally into monthly observations, and spatially at the level of administrative districts. The result of an initial mixed effects model had 41% explained variance overall. Stratification by climate zone brought the R&lt;sup&gt;2&lt;/sup&gt; as high as 50% for major zones and as high as 59% for minor zones. This can lead to a predictive risk model used to develop a decision support framework to design treatment schemes and direct scarce resources to areas with the highest risk of infection. This framework can be applied to diseases sensitive to climate or to locations where remote sensing would be better suited than health surveys.

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