To what extent are greenhouse-gas emissions offset by trees in a Sahelian silvopastoral system?
(2023) In Agricultural and Forest Meteorology 343.- Abstract
To assess the extent to which trees in a semi-arid silvopastoral system (SPS) can offset the greenhouse-gas (GHG) emissions of the system's livestock, this study used two process-based models (STEP-GENDEC-N2O and DynACof) to simulate 9 years of agricultural activity and resulting emissions in a SPS that has been operating in sahelian Senegal. STEP-GENDEC-N2O simulated soil N2O and CO2 fluxes, plus growth of the herbaceous layer, while DynACof focused on the tree layer. Outputs from the models included simulated time series of vegetative growth, water fluxes, and emissions. This output was validated through the use of published data, and measurements that were made at the SPS. Overall, the... (More)
To assess the extent to which trees in a semi-arid silvopastoral system (SPS) can offset the greenhouse-gas (GHG) emissions of the system's livestock, this study used two process-based models (STEP-GENDEC-N2O and DynACof) to simulate 9 years of agricultural activity and resulting emissions in a SPS that has been operating in sahelian Senegal. STEP-GENDEC-N2O simulated soil N2O and CO2 fluxes, plus growth of the herbaceous layer, while DynACof focused on the tree layer. Outputs from the models included simulated time series of vegetative growth, water fluxes, and emissions. This output was validated through the use of published data, and measurements that were made at the SPS. Overall, the outputs from STEP-GENDEC-N2O agreed well with validation data for water fluxes, soil N, soil C, herbaceous biomass, and N2O emissions. Good agreement was also found between the measured fluxes of the SPS ecosystem, and the simulated values that were generated by combining STEP-GENDEC-N2O's simulations (of the herbaceous layer's heterotrophic respiration, autotrophic respiration, and gross primary productivity (GPP)) with DynACof's simulations of the tree layer's autotrophic respiration and GPP. Among the insights gained from the simulations was that in this SPS's sandy soils, nitrification was the dominant process that leads to N2O emissions. Our results show that the trees, at their current density (81 ha−1) offset 18 % to 41 % of the GHG emissions from livestock. With further development, the model set-up can be used for estimating the GHG offset at other tree densities, and will be useful for guiding future policies regarding climate-change adaptation and mitigation in the management of the Sahel's SPSs.
(Less)
- author
- organization
- publishing date
- 2023-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Greenhouse gas emissions, Livestock, Process-based model, Silvopastoral systems, Trees
- in
- Agricultural and Forest Meteorology
- volume
- 343
- article number
- 109780
- publisher
- Elsevier
- external identifiers
-
- scopus:85175093383
- ISSN
- 0168-1923
- DOI
- 10.1016/j.agrformet.2023.109780
- language
- English
- LU publication?
- yes
- id
- 9461a563-54b2-4920-9ff2-a9d6eea74e38
- date added to LUP
- 2023-12-07 12:26:36
- date last changed
- 2023-12-07 12:27:36
@article{9461a563-54b2-4920-9ff2-a9d6eea74e38,
abstract = {{<p>To assess the extent to which trees in a semi-arid silvopastoral system (SPS) can offset the greenhouse-gas (GHG) emissions of the system's livestock, this study used two process-based models (STEP-GENDEC-N<sub>2</sub>O and DynACof) to simulate 9 years of agricultural activity and resulting emissions in a SPS that has been operating in sahelian Senegal. STEP-GENDEC-N<sub>2</sub>O simulated soil N<sub>2</sub>O and CO<sub>2</sub> fluxes, plus growth of the herbaceous layer, while DynACof focused on the tree layer. Outputs from the models included simulated time series of vegetative growth, water fluxes, and emissions. This output was validated through the use of published data, and measurements that were made at the SPS. Overall, the outputs from STEP-GENDEC-N<sub>2</sub>O agreed well with validation data for water fluxes, soil N, soil C, herbaceous biomass, and N<sub>2</sub>O emissions. Good agreement was also found between the measured fluxes of the SPS ecosystem, and the simulated values that were generated by combining STEP-GENDEC-N<sub>2</sub>O's simulations (of the herbaceous layer's heterotrophic respiration, autotrophic respiration, and gross primary productivity (GPP)) with DynACof's simulations of the tree layer's autotrophic respiration and GPP. Among the insights gained from the simulations was that in this SPS's sandy soils, nitrification was the dominant process that leads to N<sub>2</sub>O emissions. Our results show that the trees, at their current density (81 ha<sup>−1</sup>) offset 18 % to 41 % of the GHG emissions from livestock. With further development, the model set-up can be used for estimating the GHG offset at other tree densities, and will be useful for guiding future policies regarding climate-change adaptation and mitigation in the management of the Sahel's SPSs.</p>}},
author = {{Agbohessou, Yélognissè and Delon, Claire and Mougin, Eric and Grippa, Manuela and Tagesson, Torbern and Diedhiou, Moussa and Ba, Seydina and Ngom, Daouda and Vezy, Rémi and Ndiaye, Ousmane and Assouma, Mohamed H. and Diawara, Mamadou and Roupsard, Olivier}},
issn = {{0168-1923}},
keywords = {{Greenhouse gas emissions; Livestock; Process-based model; Silvopastoral systems; Trees}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Agricultural and Forest Meteorology}},
title = {{To what extent are greenhouse-gas emissions offset by trees in a Sahelian silvopastoral system?}},
url = {{http://dx.doi.org/10.1016/j.agrformet.2023.109780}},
doi = {{10.1016/j.agrformet.2023.109780}},
volume = {{343}},
year = {{2023}},
}