Farmers’ preferred tree species and their potential carbon stocks in southern Burkina Faso: Implications for biocarbon initiatives

Dimobe, Kangbéni; Tondoh, Jérôme E.; Weber, John C.; Bayala, Jules; Ouédraogo, Korotimi; Greenough, Karen Marie

doi:10.1371/journal.pone.0199488

Cited by 28 publications

(17 citation statements)

References 55 publications

(62 reference statements)

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“…We compared the models developed in this study with four previously published models developed by Brown et al (1989), Chave et al (2005), Chave et al (2014), andJucker et al (2017). We choose these models for comparison with our own model because they are commonly used for biomass estimation in Burkina Faso by previous studies (Qasim et al 2016;Dimobe et al 2018d;Dimobe et al 2019). The general lack of agreement between the models developed for D. mespiliformis in this study and the generic models, can only be viewed as discouraging.…”

Section: Comparison With Previously Published Modelsmentioning

confidence: 93%

Allometric models for estimating aboveground biomass and carbon stock for <i>Diospyros mespiliformis</i> in West Africa

Ouédraogo¹,

Dimobe²,

Thiombiano³

2020

Silva Fenn.

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Accurate estimates of aboveground biomass (AGB) strongly depend on the suitability and precision of allometric models. Hochst. ex A. DC. is a key component of most sub-Sahara agroforestry systems and, one of the most economically important trees in Africa. Despite its importance, very few scientific information exists regarding its biomass and carbon storage potential. In this study direct method was used to develop site-specific biomass models for tree components in Burkina Faso. Allometric models were developed for stem, branch and leaf biomass using data from 39 tree harvested in Sudanian savannas of Burkina Faso. Diameter at breast height (DBH), tree height, crown diameter (CD) and basal diameter (D) were regressed on biomass component using non-linear models with DBH alone, and DBH in combination with height and/or CD as predictor variables. Carbon content was estimated for each tree component using the ash method. Allometric models differed between the experimental sites, except for branch biomass models. Site-specific models developed in this study exhibited good model fit and performance, with explained variance of 81â98%. Using models developed from other areas would have underestimated or overestimated biomass by between â72% and +98%. Carbon content in aboveground components of in Tiogo, Boulon and Tapoa-Boopo was 55.40%âÂ±â1.50, 55.52%âÂ±â1.06 and 55.63%âÂ±â1.00, respectively, and did not vary significantly (-valueâ=â0.909). Site-specific models developed in this study are useful tool for estimating carbon stocks and can be used to accurately estimate tree components biomass in vegetation growing under similar conditions.Diospyros mespiliformisD. mespiliformis20D. mespiliformisP

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Section: Comparison With Previously Published Modelsmentioning

confidence: 93%

Allometric models for estimating aboveground biomass and carbon stock for <i>Diospyros mespiliformis</i> in West Africa

Ouédraogo¹,

Dimobe²,

Thiombiano³

2020

Silva Fenn.

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“…50 out of 217) address the relationships between agriculture and climate change in Burkina Faso or even single regions in the country e.g. north (Hänke et al, 2016;Kima et al, 2014;Rigolot et al, 2017), south (Borona et al, 2016;Dimobe et al, 2018), south-west (Fonta et al, 2015;Sanfo et al, 2017) and south-east (Mande et al, 2015).…”

Section: Bibliographical Metrics Of Research On Climate Change and Agriculture In Burkina Fasomentioning

confidence: 99%

“…Mutuo et al (2005) suggest that "Evidence is emerging that agroforestry systems are promising management practices to increase aboveground and soil C stocks and reduce soil degradation, as well as to mitigate greenhouse gas emissions" (p. 43). However, Dimobe et al (2018) underline that the success of carbon sequestration projects, including those involving agro-forestry, lies in the "involvement of local populations in the selection of woody species […] and information about the potential of these species to store carbon". Moreover, there are some doubts about whether carbon sequestration markets (cf.…”

Section: Climate Change Mitigation and Adaptationmentioning

confidence: 99%

“…Arthur and Baidoo (2011);;Bennetzen et al (2016);Bostick et al (2007);Dimobe et al (2018);Doelman et al (2018);;Henderson et al (2017);Hendrix and Glaser (2007);Kamoni and Gicheru (2015);Luedeling and Neufeldt (2012);Ogundari et al (2017);Perez et al (2007);Quintero and Cohen (2019);;; van Loon et al (2019) Adaptation Abidoye and Odusola (2015); Amjath-Babu et al (2016); Asafu-Adjaye (2014); Asare-Kyei et al (2017); Barbier et al (2009); Belesova et al (2019); Boansi et al (2017); Bodin et al (2016); Brockhaus et al (2012); Bryan et al (2018); Buhaug et al (2015); Bunclark et al (2018); Busby et al (2014); Callo-Concha (2016); Callo-Concha (2018); Calzadilla et al (2013); Chen et al (2018); Choptiany et al (2017); Cooper et al (2008); D'haen et al (2014); Di Leo et al (2016); Dixon and Stringer (2015); Douxchamps et al (2016); Fonta et al (2015); Gahi et al (2015); Garcia de Jalon et al (2018); Gray and Wise (2016); Guan et al (2017); Haile (2005); Haussmann et al (2012); Ingram et al (2002); Jarvis et al (2012); Johnson and Brown (2014); Jones and Thornton (2009); Kalame et al (2011); Kima et al (2014); Kima et al (2015); Kniveton et al (2012); Lay et al (2009); Lebel et al (2015); Lobell et al (2008); López-Carr et al (2014); McPeak (2017); Mertz (2011); Mertz et al (2010); Mertz et al (2016); Naumann et al (2014); Palazzo et al (2017); Parkes et al (2018); Pironon et al (2019); Ramin and McMichael (2009); Rasmussen (2018); Rasmussen et al (2014); Rigolot et al (2017); Rippke et al (2016); Roncoli et al (2001); Rosenthal and Ort (2012); Salack et al (2015); Sanfo et al (2017); Schlenker and Lobell (2010); Seo et al (2009); Serdeczny et al (2017); Sheffield et al (2014); Sidibé et al (2018); Siebert (2016); Sissoko et al (2011); Sonwa et al (2017); Sorgho et al (2016); Tankari (2020); Tesfaye et al (2015); Thornton and Herrero (2014); Thornton and Herrero (2015); Thornton et al (2011); Traoré et al (2011); van Oort and Zwart (2018); van Wesenbeeck et al (2016); vom Brocke et al (2014); von Uexkull (2014); Waha et al (2013); Waha et al (2016); Waongo et al (2015); West et al (2008); Wood et al (2014); Zampaligré and Fuchs (2019); Zampaligré et al (2014); Zidouemba (2017); Zorom et al (2010); Zorom et al (2013) Mitigation and adaptation Bayala et al (2014); Corbeels et al (2014); Coulibaly et al (2014); Descheemaeker et al (2016); Fanzo et al (2018); Garrity et al (2010); Hasegawa et al (2018); Henderson et al (2016); Lahmar et al (2012); Lobell et al (2013); Prestele and Verburg (2020); Richardson et al (2018); Steward et al (2018); Tittonell et al (2012)…”

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confidence: 99%

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Climate change and agriculture in Burkina Faso

Bilali

2021

jaa

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The impacts of climate change (CC) are expected to be higher in developing countries (e.g. Sub-Saharan Africa). However, these impacts will depend on agriculture development and resilience. Therefore, this paper provides a comprehensive analysis of the multifaceted relationships between CC and agriculture in Burkina Faso (BF). A search performed in March 2020 on the Web of Science yielded 1,820 documents and 217 of them were included in the systematic review. The paper provides an overview on both bibliometrics (e.g. journals, authors, institutions) and topics addressed in the literature viz. agriculture subsectors, climate trends in BF, agriculture and CC mitigation (e.g. agriculture-related emissions, soil carbon sequestration), impacts of CC on agriculture (e.g. natural resources, crop suitability, yields, food security) as well as adaptation strategies. BF is experiencing CC as evidenced by warming and an increase in the occurrence of climate extremes. The literature focuses on crops, while animal husbandry and, especially, fisheries are often overlooked. Moreover, most of the documents deal with CC adaptation by the Burkinabe farmers, pastoralists and rural populations. Analysed adaptation options include conservation agriculture and climate-smart agriculture, irrigation, crop diversification, intensification, livelihoods diversification and migration. However, the focus is mainly on agricultural and individual responses, while livelihoods strategies such as diversification and migration are less frequently addressed. Further research is needed on the dual relation between agriculture and CC to contribute to the achievement of the Sustainable Development Goals. Research results are crucial to inform policies aimed at CC mitigation and/or adaptation in rural BF.

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“…Mulberry, native to China, is of great economic importance as the sole food of the mulberry silkworm moth (Bombyx mori L.) and as a source of timber, fuelwood, fodder, food, drinks, medicines, constituents of cosmetics, etc. (Qin et al 2012;Gozlekci et al 2015;Dimobe et al 2018). Recently, Li et al (2020) found that the photosynthetic carbon sink of mulberry is greater compared to the total carbon emission, which indicates a beneficial effect for the environment.…”

Section: Introductionmentioning

confidence: 99%

Morphometry of leaf and shoot variables to assess aboveground biomass structure and carbon sequestration by different varieties of white mulberry (Morus alba L.)

Bajwa¹,

Umair

Nawab

et al. 2021

J. For. Res.

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Mulberry is economically important and can also play a pivotal role in mitigating greenhouse gases. Leaf and shoot traits were measured for Morus alba var. Kanmasi, M. alba var. Karyansuban, M. alba var. Latifolia, and M. alba var. PFI-1 to assess aboveground biomass (AGB) and carbon sequestration. Variety-specific and multivariety allometric AGB models were developed using the equivalent diameter at breast height (EDBH) and plant height (H). The complete-harvest method was used to measure leaf and shoot traits and biomass, and the ash method was used to measure organic carbon content. The results showed significant (p < 0.01) varietal differences in leaf and shoot traits, AGB and carbon sequestration. PFI-1 variety had the greatest leaf density (mean ± SE: 1828.3 ± 0.3 leaves tree−1), Karyansuban had the largest mean leaf area (185.94 ± 8.95 cm2). A diminishing return was found between leaf area and leaf density. Latifolia had the highest shoot density per tree (46.6 ± 1.83 shoots tree−1), total shoot length (264.1 ± 2.32 m), dry biomass (16.69 ± 0.58 kg tree−1), carbon sequestration (9.99 ± 0.32 kg tree−1) and CO2 mitigation (36.67 ± 1.16 kg). The variety-specific AGB models b(EDBH) and b(EDBH)2 showed good fit and reasonable accuracy with a coefficient of determination (R2) = 0.98–0.99, standard error of estimates (SEE) = 0.1125–0.3130 and root mean square error (RMSE) = 0.1084–0.3017. The multivariety models bln(EDBH) and (EDBH)0.756 showed good-fitness and accuracy with R2 = 0.85–0.86, SEE = 1.6231–1.6445 and RMSE = 1.609–1.630. On the basis of these findings, variety Latifolia has good potential for biomass production, and allometric equations based on EDBH can be used to estimate AGB with a reasonable accuracy.

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Farmers’ preferred tree species and their potential carbon stocks in southern Burkina Faso: Implications for biocarbon initiatives

Cited by 28 publications

References 55 publications

Allometric models for estimating aboveground biomass and carbon stock for <i>Diospyros mespiliformis</i> in West Africa

Allometric models for estimating aboveground biomass and carbon stock for <i>Diospyros mespiliformis</i> in West Africa

Climate change and agriculture in Burkina Faso

Morphometry of leaf and shoot variables to assess aboveground biomass structure and carbon sequestration by different varieties of white mulberry (Morus alba L.)

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