How to better account for livestock diversity and fodder seasonality in assessing the fodder intake of livestock grazing semi-arid sub-Saharan Africa rangelands

Assouma, Mohamed Habibou; Lecomte, Philippe; Hiernaux, Pierre; Ickowicz, Alexandre; Corniaux, Christian; Decruyenaere, Virginie; Diarra, Alassane; Vayssières, Jonathan

doi:10.1016/j.livsci.2018.07.002

Cited by 41 publications

(31 citation statements)

References 18 publications

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“…In the semi-arid ecosystems of sub-Saharan Africa, ecosystem productivity is strongly linked to soil moisture (Madani et al, 2017). Studies of sub-Saharan cattle have shown that animal weights and dry matter intake vary seasonally, linked to the availability of forage (Ayantunde et al, 2005;Assouma et al, 2018). As such, the seasonal variation of enteric fermentation CH 4 emissions from livestock could be a significant contributor to the seasonal cycle of total CH 4 emissions that we infer.…”

Section: Resultsmentioning

confidence: 72%

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

Lunt¹,

Palmer²,

Li³

et al. 2019

Preprint

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Abstract. Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing SATellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5&#8201;&#215;&#8201;0.625) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010&#8211;2016 range from 75 (72&#8211;78)&#8201;Tg&#8201;yr&#8722;1 to 80 (78&#8211;83)&#8201;Tg&#8201;yr&#8722;1, dependent on the proxy XCH4 data used, with larger differences in northern hemisphere Africa than southern hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our seven-year study period, with values of 1.5 (1.1&#8211;1.9)&#8201;Tg&#8201;yr&#8722;1 or 2.1 (1.7&#8211;2.5)&#8201;Tg&#8201;yr&#8722;1, dependent on the CO2 data product used in the proxy retrieval. A substantial portion of this increase is due to a short-term increase in emissions of 3&#8201;Tg&#8201;yr&#8722;1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data we find this increase in CH4 emission is consistent with an increase in wetland extent due to increased inflow from the White Nile. We find a strong seasonality in emissions across northern hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.

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Section: Resultsmentioning

confidence: 72%

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

Lunt¹,

Palmer²,

Li³

et al. 2019

Preprint

View full text Add to dashboard Cite

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Section: Seasonal Variations Of African Ch 4 Emissionsmentioning

confidence: 75%

“…However, evaporation not outflow is the major loss process of water from the lake, and the positive trends in altimetry data from further downstream at Lake Albert and in South Sudan indicate this explanation is unlikely, since they would not be consistent with a decrease in outflow. Furthermore, the recent increases in Lake Victoria water levels have been attributed to increased precipitation over the Lake Victoria basin (Awange et al, 2019). Whilst there may be no clear positive trend in monthly Figure 7.…”

Section: Annual Increases In South Sudanese Ch 4 Emissionsmentioning

confidence: 99%

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

et al. 2019

View full text Add to dashboard Cite

Abstract. Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5∘×0.625∘) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74–78) to 80 (78–82) Tg yr−1, depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, depending on the CO2 data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori CH4 emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.

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“…Tropical northern Africa (herein defined as between the 5th and 25th parallel north) is mostly occupied by open ecosystems, such as steppe and savannah 1 . The vegetation in these ecosystems is consumed by animals 2 , either wildlife or livestock, and is also used by the local communities for food, energy or medicinal purposes 3 . The open ecosystems in tropical northern Africa are of great importance for the economy, food security and human well-being.…”

Section: Background and Summarymentioning

confidence: 99%

FLOTROP, a massive contribution to plant diversity data for open ecosystems in northern tropical Africa

et al. 2019

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The FLOTROP dataset contains numerous plant observations (around 340,000 occurrences) in northern tropical Africa (from the 5 th to 25 th parallel north) in open ecosystems (savannah and steppe). They were collected by multiple collectors between 1920 and 2012 and were managed by Philippe Daget. These observations are probably the most important and unique source of plant distribution over the Sahel area. The data are now available in the Global Biodiversity Information Facility, Tela Botanica website, and as maps in the African Plant Database. For the overall area involved, this dataset has increased by 40% the data available in the GBIF. For some countries between the 15 th and 21 st parallel north, the FLOTROP dataset has increased available occurrences 10-fold compared to the data existing in the GBIF.

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How to better account for livestock diversity and fodder seasonality in assessing the fodder intake of livestock grazing semi-arid sub-Saharan Africa rangelands

Cited by 41 publications

References 18 publications

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

FLOTROP, a massive contribution to plant diversity data for open ecosystems in northern tropical Africa

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