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Carbon Footprints 2023;2:7. 10.20517/cf.2022.081601 © The Author(s) 2023.
Open Access Review

Agroforestry systems for mitigating climate change and reducing Carbon Footprints of land-use systems in Southern Africa

1Department of Plant and Soil Sciences, University of Pretoria, Pretoria 0022, South Africa.

2Programme Coordinator - Climate Resilience, Southern African Confederation of Agricultural Unions, Centurion 0046, South Africa.

3Biological Sciences Department, Mzuzu University, Luwinga, Mzuzu 105203, Malawi.

4Department of Geography, Environment and Climate Change, Mukuba University, Kitwe 20382, Zambia.

5Agribusiness and Climate Resilience Expert, Devpact Consultants, Harare 7784, Zimbabwe.

Correspondence to: Prof. Paxie W. Chirwa, Department of Plant and Soil Sciences, University of Pretoria, Pretoria 0022, South Africa. E-mail:

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    Academic Editor: P. K. Ramachandran Nair | Copy Editor: Fangling Lan | Production Editor: Fangling Lan

    © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (, which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.


    Farming systems in Southern Africa are mostly maize mixed cropping, with some tree and/or root crop-based systems. Agroforestry systems (AFS), in particular, represent a model for ecological sustainability, with the potential of sequestering carbon (C) within soils and biomass. This review reveals that rotational woodlots sequester more C than other AFS types in the region. Additionally, C levels above and below ground range from 0.29 to 15.21 Mg ha-1 yr-1 and 30 to 300 Mg C ha-1 in the first 100 cm soil depth, respectively. To measure C below- and aboveground biomass in different AFS, variable - and not easily adoptable - methodologies are being used in Southern Africa, which limits the standardization of C stock accounting. Since the magnitude of C sequestered in AFS is dependent on the species used, AF and farm management, and environmental conditions, we recommend the adoption of rigorous and replicable methodologies to account for C stocks in different AFS over time in Southern Africa.


    Anthropogenic global warming is a current phenomenon that has aroused interest in several land-use systems that may help to avert or stabilize atmospheric CO2 concentrations[1]. Reducing atmospheric CO2 concentrations can be achieved by minimizing emissions or increasing C sequestration[2]. Forests have been a focus of emissions reduction strategies as they account for 45% of terrestrial C stocks[3,4]. Moreover, it is notable that trees in other land-use systems, including farmland, have considerable potential for C emission/sequestration owing to their spatial extent. More than 45% of farmland globally has up to 10% tree cover[5]. According to Nair[6] and Nair and Nair[7], biomass C stocks in farmland usually range from 3 to 18 t C ha-1. Previous studies have focused on the C contributions of forests. However, current evidence supports the importance of both trees outside forests and agroforestry (AF) for C sequestration[8]. Important practices that could contribute to C sequestration include afforestation and reforestation programs in different formations[9-13]. Since smallholder farmers in developing nations, such as those in Southern Africa, are the main practitioners of AF, there is the potential to mainstream different agroforestry systems (AFS) into C financing mechanisms. This possibility is especially relevant to the Clean Development Mechanism (CDM) of the United Nations Framework Convention on Climate Change (UNFCCC). The role of AF in C sequestration is also recognized by the Intergovernmental Panel on Climate Change (IPCC)[14]. In fact, some studies have suggested that AFS sequester more C than pastures or field crops[15-18]. This suggestion is premised on the hypothesis that the incorporation of trees in agricultural landscapes results in greater net C sequestration both above and below ground[12,13,19]. In addition, AFS remain in place for longer than annual crops, thus contributing to greater C sequestration.

    Agroforestry has been described as a dynamic, ecologically based, natural resources management system. These systems can diversify and sustain production, resulting in increased social, economic, and environmental benefits for land users at all levels[13,18,20], via the incorporation of trees in farms and agricultural landscapes.

    In this review, we examine the current evidence for the capacity of AF C pools to mitigate climate change in Southern Africa. We explore the extent to which AFS could enhance soil organic C (SOC) storage and contribute to climate change mitigation. Additionally, we highlight the different measurements that are employed to account for above- and belowground C in different AFS. The information presented in this review can help inform the emerging role of AFS in Southern Africa and the potential to sequester C.


    Ecosystems in the Southern Africa sub-region have been influenced by both natural and anthropogenic factors, such as fire, cultivation practices, and charcoal production. These factors have had an influence on both biodiversity and primary production and, in turn, C status. The degradation of agroecosystems in the sub-region is associated with a loss of nutrients, fauna, flora, and productive ecosystems. Agricultural land constitutes more of the land surface of Southern Africa than any other land-use type. These areas host a vast diversity of life, ranging from pests and associated organisms in cultivated lands to natural vegetation containing rare and endemic species that require protection.

    Agricultural systems in Southern Africa are largely subsistence farming on diminishing plots of land with declining soil fertility. These farming systems have been inadequate to cope with the population growth explosion experienced in the region. Traditional systems include the tree legume-based system of Faidherbia albida parklands, in which farmers have retained a low density of trees, or two-tiered systems in the tropics, especially in semi-arid areas, to improve the yield of understorey crops[21-23]. Other systems include dambo ecosystems, which are seasonally wet agricultural lands where dry season cropping (dimbas) is practiced, especially vegetables[22,24]. In animal-dominated landscapes, transhumance grazing systems are prevalent. For example, transhumance grazing is still practised in flood plains in some parts of Zambia and Zimbabwe[25,26]. In the last three decades, improved AF technologies have been promoted with varying success. Most of these have shown positive results with respect to soil C and general soil health.

    It has been argued that, despite a lack of investment in African farming, there have been changes in agricultural production. There has been a shift from diversified cropping systems-associated with healthy soils with respect to nutrients, including SOC - towards ecologically simpler cereal-based systems, characterized by inorganic fertilizer inputs (with a high C footprint), which have contributed to poor diet and crop diversity[22].

    The general agroecosystem/farming system in Tanzania, Zambia, and Malawi is maize mixed farming, but Tanzania and Zambia also have forest-based and root crop farming[27]. Forest-based farming is characteristically found in humid forests in the region, and farmers practice shifting cultivation by clearing a new plot in the forest every 3-5 years, with a fallow period of ~7-20 years. This system is the basis of the Chitemene system in Zambia and the Machambas that are used to cultivate crops such as cassava, maize, beans, and potatoes in the Niassa Province of Mozambique[27-29].

    Rice-tree crop farming is prevalent in some parts of Madagascar. Banana and coffee are major crops and are complemented by rice, maize, cassava, and legumes. Root crop farming is also practiced in southern Madagascar and is dominant in some parts of Mozambique, especially cassava (Manihot esculenta), which is grown in typical home gardens in the Indian Ocean coastline provinces, such as Inhambane in Mozambique.

    In South Africa, agroecosystems are both large commercial farms and smallholdings in semi-arid and dry sub-humid zones. These systems comprise scattered smallholdings in former homelands and large commercial farms, both with mixed cereal-livestock systems. Commercial farms are generally associated with a high C footprint as a result of the high mechanisation and inorganic fertilizer inputs. Also predominant in the commercial sector are private nature reserves, which contribute to in situ biodiversity conservation and potentially high above- (AGB) and belowground biomass (BGB) and C.


    AFS sequester more C than other agricultural systems[30] [Table 1]. However, below- and aboveground vegetation C sequestration is highly variable[13] as the amounts of biomass and SOC addition vary with tree species, soil type, rainfall, and environmental conditions. Overall, C sequestration in AFS is a function of the availability of resources with higher vegetation C sequestration rates in fertile humid areas than in water-limited and degraded sites. Larger SOC pools in AFS are a result of the quantity and quality of biomass C that is incorporated into the soil, which stabilizes and builds soil organic matter (SOM)[31,32]. Plant species and litter quality influence decomposition rates in AFS[33]. High lignin and tannin contents lower the rate of decomposition[34,35]. Additionally, the C/N ratio of the decomposing material affects the soil C inputs[36]. AF practises, known as “climate-smart”, contribute to increased SOC pools[37,38]. In Southern Africa, these include Faidherbia parklands, improved fallows, and conservation agriculture with trees[21]. AFS also improve the physical condition of soil as a result of better soil aggregation, lower bulk density, lower resistance to penetration[39], improved soil porosity and reduced surface sealing, and increased hydraulic conductivity[40], infiltration rates[38,39,41], and water holding capacity.

    Table 1

    Potential annual harvestable fuelwood produced from fertilizer trees planted in contour strips, woodlots, or rotational fallows

    Tree speciesAge (years)QuantityC (Mg ha-1 yr-1) Sufficient for N families of 6Country
    (Mg ha-1 yr-1)C/Factor
    Acacia crassicarpa522.40.511.207.7
    A. crassicarpa4220.511.008.2
    Vachellia nilotica71.20.50.600.4Tanzania
    Senegalia (Acacia) polycantha710.
    Acacia crassicarpa551.00.525.5017.5Tanzania
    A. mangium540.00.520.0013.7
    Senegalia (Acacia) polycantha539.00.519.5013.4
    Vachellia nilotica527.00.513.509.3

    While C sequestration depends on the type of AFS, there is a paucity of published information[21]. Gama-Rodrigues et al. reported SOC pools of 302 Mg C ha-1 in 0-100 cm depth soil in a 30-year-old cacao AFS in Brazil[42]. In fact, AFS are reported to have higher SOC than other land-use systems, apart from forests, and can be classified in the order forests > AFS > tree plantations > arable crops[13].


    In Southern Africa, multiple tree species have been shown to sequester a substantial amount of C through biomass accumulation[30] [Table 1]. In fact, some studies showed that improved fallows, especially those with exotic multipurpose species, sequester more carbon (2.0-6.0 Mg C ha-1 yr-1) than coppiced miombo woodlands (a dominant vegetation type in Southern Africa; < 1.0 Mg C ha-1 yr-1) [Table 2]. These rates depended on the species used, site characteristics, planting densities, and the formation or agroforestry technology used. For example, where improved fallows with Sesbania tree species are used in Eastern Zambia, AFS can sequester C at rates of 26-120 Mg C ha-1[43]. In Zimbabwe, Nyamadzawo et al. reported C accumulation of 26.3 and 25.4 Mg ha-1 in leaves and twigs in a two-year improved fallow with Acacia angustissima and Sesbania sesban[44]. In another fallow variant, where rotational woodlots were used in tobacco growing areas in Tanzania, five-year rotational woodlots sequestered 11.6 to 25.5 Mg C ha-1[45].

    Table 2

    SOC fixed in different improved fallow systems from selected countries in Southern Africa

    LocationFallow speciesSOC stocks (Mg ha-1)Source
    ZambiaCopping fallows32.2-37.8[43]
    ZambiaNon-coppicing fallows29.5-30.1[43]
    ZimbabweAcacia angustissima26.3[44]
    ZimbabweSesbania sesban25.4[44]
    Morogoro, TanzaniaAcacia crassicarpa15.8[45]
    TanzaniaAcacia mangium25.6[45]
    TanzaniaAcacia polyacantha21.6[45]
    TanzaniaGliricidia sepium18.8[45]
    TanzaniaAcacia nolotica22.7[45]

    In Malawi, a modified system that used permanent stands of Gliricidia sepium as fertilizer trees in a mixed intercropping formation sequestered between 123 and 149 Mg C ha-1 in the soil[46] [Table 3]. This rate is relatively higher than that recorded for a six-year stand of Faidherbia albida in Tanzania (9.4 Mg C ha-1)[47]. One explanation for this difference is that rotational fallows predominantly use fast-growing exotic species, such as Australian acacias. In contrast, Faidherbia parklands are traditional agroforestry systems. Faidherbia albida is also drought tolerant, as evidenced by its wide distribution as far as the Sahel region of Africa. Hence, F. albida can be considered a keystone species for climate-smart agriculture in much of Africa[23,53].

    Table 3

    Soil organic carbon sequestration in agroforestry systems in Southern Africa

    Agroforestry systemLocationAgeSoil depth (cm)Sequestration rate Mg C ha-1 year-1Reference
    Gliricidia sppMalawi0-20123-149[46]
    Faidherbia albida plantationTanzania61.2[47]
    Tree fallows (Sesbania sesban)Zimbabwe220025.4[44]
    Coppiced miomboZambia160.5[48]
    Coppiced miomboZambia350.9[49]
    Rotational woodlotsTanzania52.6-5.8[50]
    Rotational woodlots (wood C)Tanzania52.3-5.1[45]
    Rotational woodlots Zambia22.15-4.75[51]
    Conserved Forest-NyasambaTanzania0-1048.84[52]
    Trees speciesTanzania-Bubinza79.22tCO2 e/year[52]
    Tanzania-Nyasamba57.37tCO2 e/year
    HerbaceousTanzania-Bubinza125.36tCO2 e/year
    Tanzania-Nyasamba63.35tCO2 e/year

    In most systems, long-lived species sequester more C than short-term fallow systems or agroforestry technologies where fertilizer trees are used for biomass transfer, with the woody biomass used as fuel. In this case, one must provide proper C budgets to establish the net C in an ecosystem. In the miombo woodlands of Southern Africa, AGB, BGB, and C stocks were estimated at the stand level using allometric models. The best estimate of AGB was 222.2 Mg ha-1, which translated to C stocks in AGB of 125.3 Mg C ha-1[53,54]. Using a nonlinear seemingly unrelated regression, total tree biomass was estimated at 270.1 Mg ha-1 (95%Cl: 207.4-328.7 Mg ha-1), with resulting C stocks estimated at 152.1 Mg ha-1 (95%Cl: 115.9-184.1 Mg ha-1); in terms of the amount of CO2 sequestered in tree biomass, this translates to 558.3 Mg CO2 ha-1. Earlier studies on AGB and/or C sequestration also produced variable values for unevenly aged mature woodlands of miombo and mopane woodlands, ranging from 1.5 to 90 Mg ha-1[30,54].


    The main limiting factor to agricultural production in Southern Africa is low soil fertility. Hence, agroforestry with nitrogen-fixing multipurpose tree species has high potential in the region, where poor agricultural practices, such as slash-and-burn agriculture and charcoal production, are prevalent[55]. Agroforestry therefore has tremendous C sequestration potential and is an alternative to shifting cultivation or continuous monocropping, which has resulted in forest cover loss[56-58].

    In terms of SOC, a positive effect has been shown by all the systems previously discussed [Tables 2 and 3]. The SOC under canopies of Faidherbia was shown to be higher (3%-30%) than that outside the canopy[59]. In both improved and rotational fallows in Zimbabwe and Tanzania, respectively, SOC was higher than that under continuous cropping with maize (1.7 times higher in the former and 15.8-25.6 Mg ha-1vs. 13 Mg ha-1 in the latter)[44,45,50]. Other species have also been used in different agroforestry systems, including Tephrosia, Sesbania, and pigeon pea (Cajanus cajan), where SOC stocks were higher (27.3-31.2 Mg ha-1) than those under fully fertilized monocropped maize (26.2 Mg ha-1) and unfertilized monocropped maize (22.2 Mg ha-1) in eastern Zambia[43]. Tree-based intercropping systems using Gliricidia also showed that soil C doubled after 7-10 years compared with that for monocropped maize. These results clearly show the positive effect of agroforestry systems and technologies on soil C enhancement.


    AGB and BGB are critical constituents of terrestrial ecosystem C stocks in agroforestry C cycles. The amount of biomass, as well as C stocks distributed in different tree components (trunk, branches, twigs, leaves, and roots), are dependent on several critical factors, such as tree species, floristic composition and growth characteristics within a climatic zone, tree size and density, and geographic location[60,61]. Therefore, accurate measurement of the size and dynamics of C stocks requires that these factors are taken into consideration as essential inputs to the formulation of climate change mitigation and adaptation policies. IPCC[62] noted that to enhance strategic C management in AFS, the collection of reliable biomass data is required for successful screening of tree species potential. However, a major challenge in the measurement and monitoring of the C sequestration potential of agroforestry systems is accurate, replicable methods for measuring AGB, which stores a substantial amount of the C assimilated by these systems[63,64].

    Two methods are employed in AGB assessments: destructive (direct measurement) and non-destructive. Non-destructive biomass assessments use previously developed allometric equations selected from the literature. Although approximation of tree biomass by direct measurements of the actual weight of each tree constituent is the most accurate method, entire-tree harvesting is destructive, time-consuming, and costly[65]. However, sound statistical formulations, especially for AFS that have not been exhaustively explored, require destructively acquired data. The process entails totalling the quantity of harvested constituent tree parts (trunk, branches, and leaves)[53,66] and standing biomass. Prior to undertaking destructive sampling, all trees are identified to species level, and the diameter at breast height and tree height is measured (in m). Sub-samples, in the form of disks, are taken from the middle of the trunk, branches, and leaves, and the total wet weight of biomass is measured in the laboratory. Prior to oven drying, the irregular sample discs are first submerged in water for 48 h to reach saturation point and their volume is determined using the water displacement method. Oven drying of samples is conducted at 105 °C (stem and branch discs) and 60.5 °C (twigs and leaves) for 48 h and samples are subsequently weighed to obtain the dry weight. Oven-dried sample components (stem, branches, twigs, and leaves) are then ground into powder for analysis of C fractions.

    BGB and the C stocks of root systems of AFS are constituents of the C pool that demand greater attention. For example, Nair et al. noted that the ability of roots to store large quantities of C in the soil makes them an essential component of soil C stocks[13]. However, BGB and C stocks are poorly estimated for many forest formations; hence, their potential to mitigate the effects of climate change remains a major knowledge gap[67]. However, understanding root biomass dynamics, root profiles and architecture, and rooting depth is important for improving our understanding of the allocation and storage of C in AFS. It is worth noting that sampling depths vary from one study to another; hence, standardization is required to enable comparison of the contributions of root biomass to C sequestration along soil profiles. For determination of BGB, the entire root system of sampled trees is dug up and tracked outward from the stump to make sure that no detected roots are improperly assigned[53,68].

    Apart from root biomass and C, SOC is also determined separately as total soil C. The soil C pool is reportedly three times greater than the atmospheric C pool and is of particular significance in the global C cycle[69]. Various methods of measuring SOC exist, which creates high variability in the results[70,71]. Available methods include loss-on-ignition, the Walkley-Black method, and dry oxidation[72]. Studies in parts of the miombo woodlands in Southern Africa and other tropical forests used the following depths: 0, 5, 15, 25, and 50 cm[73]; 0-10, 0-20, and 0-30 cm[74]; 0-10, 10-20, and 20-30 cm[75]; 0-20 and 20-50 cm[76,77]; 0-10, 10-20, 20-45, and 45-60 cm[78]; and 0-10, 10-20, 20-40, 60-100, and 100-150 cm[79]. Results to date show that most soil C sequestration studies of AFS have focused on changes in the topsoil layer (0-20 cm) where the largest C pools are detected. This focus, however, ignores the important role of tree roots in sequestering C in the deeper soil layers, where substantial quantities of C are supplied through root exudes and root turnover[13,80]. These variations in sampling techniques require standardization to allow for comparability of SOC sequestration along the soil profile, rather than in the surface layer only.


    This review sought to highlight different land-use systems in Southern Africa and use available literature to establish the extent of C sequestration, accumulation, and measurement of C stocks in AGB and BGB in different AFS. The dominant farming system in the region is subsistence with declining soil fertility. Traditional tree legume-based systems, e.g., Faidherbia albida parklands, especially those in semi-arid areas, have been shown to improve the yield of understorey crops. The predominant farming systems in the region are maize mixed farming with some forest-based and root crop farming. Forest-based farming is characteristically found in humid forests in the region, where farmers practice shifting cultivation. Rotational woodlots have the potential to accumulate greater C stocks than other AFS types. C storage accumulation was greater in BGB than in AGB in the studied AFS in Southern Africa. In addition, it has been shown that C storage potential is a function of the species used, the quality of the biomass, and site characteristics. However, methodological challenges in C stocks accounting and the potential for climate change mitigation within diverse AFS types need to be addressed in the future.


    Authors’ contributions

    Conceived and wrote the manuscript: Chirwa PW, Musokwa M, Mwale SE, Handavu F, Nyamadzawo G

    Availability of data and materials

    Not applicable.

    Financial support and sponsorship


    Conflicts of interest

    All authors declared that there are no conflicts of interest.

    Ethical approval and consent to participate

    Not applicable.

    Consent for publication

    Not applicable.


    © The Author(s) 2023.


    • 1. IPCC. Climate change 2014: mitigation of climate change. Contribution of working group III to the fifth assessment report of the intergovernmental panel on climate. Cambridge: Cambridge University Press; 2014.

    • 2. Montagnini F, Nair P. Carbon sequestration: an underexploited environmental benefit of agroforestry systems. Agrofor Syst 2004;61-62:281-95.

    • 3. IPCC. Climate change 2007: mitigation. contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. In Metz B, Davidson OR, Bosch PR, Dave R, Meyer LA editors. Cambridge; New York, NY: Cambridge University Press. [Last accessed on 6 Dec 2022].

    • 4. IPCC. Use of models and facility-level data in greenhouse gas inventories. In Proceedings of the IPCC expert meeting on use of models and measurements in greenhouse gas inventories. Sydney, Australia; 2010.

    • 5. Zomer RJ, Trabucco A, Coe R, Place F. Trees on farm: an analysis of global extent and geographical patterns of agroforestry, ICRAF working paper no. 89. Nairobi, Kenya: World Agroforestry Centre; 2009.

    • 6. Nair PKR. Carbon sequestration studies in agroforestry systems: a reality-check. Agroforest Syst 2012;86:243-53.

    • 7. Nair PR, Nair VD. “Solid-fluid-gas”: the state of knowledge on carbon-sequestration potential of agroforestry systems in Africa. Curr Opin Environ Sustain 2014;6:22-7.

    • 8. De Foresta HE, Somarriba A, Temu D, Boulanger H, Feuilly M, Toward the assessment of trees outside forests. Resources assessment working paper. Rome: FAO; 2013.

    • 9. Albrecht A, Cadisch G, Blanchart E, Sitompul SM, Vanlauwe B. Below-ground inputs: relationships with soil quality, soil C storage. In: Noordwijk MV, Cadisch G, Ong CK, editors. Below-ground interactions in tropical agroecosystems: concepts and models with multiple plant components. Wallingford: CABI Publishing; 2004. pp. 193-207.

    • 10. Ramachandran Nair P, Nair V. Carbon storage in North American agroforestry systems. In: Kimble J, Lal R, Birdsey R, Heath L, editors. The potential of U.S. forest soils to sequester carbon and mitigate the greenhouse effect. Boca Raton: CRC Press; 2003.

    • 11. Makundi WR, Sathaye JA. Mitigation potential and cost in tropical forestry - relative role for agroforestry. Environ Dev Sustain 2004;6:235-60.

    • 12. Haile SG, Nair PK, Nair VD. Carbon storage of different soil-size fractions in Florida silvopastoral systems. J Environ Qual 2008;37:1789-97.

    • 13. Nair PK, Mohan Kumar B, Nair VD. Agroforestry as a strategy for carbon sequestration. J Plant Nutri Soil Sci 2009;172:10-23.

    • 14. IPCC. Land use, land-use change, and forestry. a special report of the IPCC. Cambridge: Cambridge University Press; 2000.

    • 15. Sanchez PA. Linking climate change research with food security and poverty reduction in the tropics. Agric Ecosyst Environ 2000;82:371-83.

    • 16. Roshetko JM, Delaney M, Hairiah K. Carbon stocks in Indonesian homegarden systems: Can smallholder systems be targeted for increased carbon storage? Am J Altern Agric 2002;17:138-48. Available from: [Last accessed on 7 Dec 2022].

    • 17. Sharrow S, Ismail S. Carbon and nitrogen storage in agroforests, tree plantations, and pastures in western Oregon, USA. Agrofor Syst 2004;60:123-30.

    • 18. Kirby KR, Potvin C. Variation in carbon storage among tree species: implications for the management of a small-scale carbon sink project. For Ecol Manag 2007;246:208-21.

    • 19. Palm C, Tomich T, Van Noordwijk M, et al. Mitigating GHG emissions in the humid tropics: case studies from the alternatives to slash-and-burn program (ASB). Environ Dev Sustain 2004;6:145-62.

    • 20. Nair PKR, Gordon AM, Mosquera-Losada MR. Agroforestry. In Jorgensen SE, Faith BD, editors, Encyclopedia of ecology, Oxford: Elsevier; 2008, pp. 101-10.

    • 21. Akinnifesi FK, Chirwa PW, Ajayi OC, et al. Contributions of agroforestry research to livelihood of smallholder farmers in Southern Africa: 1. Taking stock of the adaptation, adoption and impact of fertilizer tree options. Agric J 2008;3:58-75.

    • 22. Khumalo S, Chirwa P, Moyo B, Syampungani S. The status of agrobiodiversity management and conservation in major agroecosystems of Southern Africa. Agric Ecosyst Environ 2012;157:17-23.

    • 23. Garrity DP, Akinnifesi FK, Ajayi OC, et al. Evergreen agriculture: a robust approach to sustainable food security in Africa. Food Sec 2010;2:197-214.

    • 24. Moyo BHZ. The role and use of indigenous knowledge in small-scale agricultural systems in Africa: the case of farmers in northern Malawi. Ph.D thesis. Glasgow: University of Glasgow; 2008.

    • 25. Sørensen C. Control and sanctions over the use of forest products in the Kafue river Basin of Zambia. Rural Development forestry network paper 15a. London: Overseas Development Institute; 1993.

    • 26. Soones I. Livestock populations and the household economy: a case study from southern Zimbabwe. Ph.D thesis, London: Imperial College; 1990.

    • 27. Musinguzi E. An analysis of the agro-ecological systems, biodiversity use, nutrition and health in selected east and Southern Africa countries. Rome: Biodiversity International; 2011. 38p.

    • 28. Chidumayo EN. A shifting cultivation land use system under population pressure in Zambia. Agrofor Syst 1987;5:15-25.

    • 29. Landry J, Chirwa PW. Analysis of the potential socio-economic impact of establishing plantation forestry on rural communities in Sanga district, Niassa province, Mozambique. Land Use Policy 2011;28:542-51.

    • 30. Sileshi GW, Mafongoya PL, Akinnifesi FK, et al. Agroforestry: fertilizer trees. Encycl Agric Food Syst 2014;1:222-234.

    • 31. Sollins P, Swanston C, Kramer M. Stabilization and destabilization of soil organic matter - a new focus. Biogeochemistry 2007;85:1-7.

    • 32. Nyamadzawo G, Nyamugafata P, Wuta M, Nyamangara J. Maize yields under coppicing and non coppicing fallows in a fallow-maize rotation system in central Zimbabwe. Agroforest Syst 2012;84:273-86.

    • 33. Mafongoya PL, Dzowela BH. Biomass production of tree fallows and their residual effect on maize in Zimbabwe. Agrofor Syst 1999;47:139-51.

    • 34. Prescott C, Kishchuk B, Weetman G. Long-term effects of repeated N fertilization and straw application in a jack pine forest: 3. Nitrogen availability in the forest floor. Can J For Res 1995;25:1991-6.

    • 35. Prescott C, Kumi J, Weetman G. Long-term effects of repeated N fertilization and straw application in a jack pine forest: 2. Changes in the ericaceous ground vegetation. Can J For Res 1995;25:1984-90.

    • 36. Horwath W. Carbon cycling and formation of soil organic matter. In: Paul EA, editor. Soil microbiology, ecology, and biochemistry. Burlington: Academic; 2007. pp. 303-39.

    • 37. Soto-Pinto L, Anzueto M, Mendoza J, Ferrer GJ, de Jong B. Carbon sequestration through agroforestry in indigenous communities of Chiapas, Mexico. Agrofor Syst 2010;78:39-51.

    • 38. Nyamadzawo G, Nyamugafata P, Chikowo R, Chirwa T, Mafongoya PL. Soil and carbon losses under rainfall simulation from two contrasting soils under maize-improved fallows rotation in Eastern Zambia. In Roose EJ, Lal R, Feller C, Barthes B, Stewarts BA, editors. Soil Erosion and Carbon Dynamics. Boca Raton: CRC Publishers, Taylor and Francis Group; 2006. pp. 197-206.

    • 39. Lal R. Agroforestry systems and soil surface management of a tropical alfisol. Parts I-VI. Agrofort Syst 1989;8:97-111.

    • 40. Nyamadzawo G, Chikowo R, Nyamugafata P, Giller K. Improved legume tree fallows and tillage effects on structural stability and infiltration rates of a kaolinitic sandy soil from central Zimbabwe. Soil Tillage Res 2007;96:182-94.

    • 41. Nyamadzawo G, Nyamugafata P, Chikowo R, Giller K. Partitioning of simulated rainfall in a kaolinitic soil under improved fallow-maize rotation in Zimbabwe. Agrofor Syst 2003;59:207-14.

    • 42. Gama-Rodrigues EF, Ramachandran Nair PK, Nair VD, Gama-Rodrigues AC, Baligar VC, Machado RC. Carbon storage in soil size fractions under two cacao agroforestry systems in Bahia, Brazil. Environ Manag 2010;45:274-83.

    • 43. Kaonga M, Coleman K. Modelling soil organic carbon turnover in improved fallows in eastern Zambia using the RothC-26.3 model. Model For Ecol Manag 2008;256:1160-6.

    • 44. Nyamadzawo G, Chikowo R, Nyamugafata P, Nyamangara J, Giller KE. Soil organic carbon dynamics of improved fallow-maize rotation systems under conventional and no-tillage in Central Zimbabwe. Nutr Cycl Agroecosyst 2008;81:85-93.

    • 45. Kimaro AA. Sequential agroforestry systems for improving fuelwood supply and crop yield in semi-arid Tanzania. Ph.D thesis, Toronto: University of Toronto; 2009. 123p.

    • 46. Makumba W, Janssen B, Oenema O, Akinnifesi FK. Influence of time of application on the performance of Gliricidia prunings as a source of N for maize. Exp Agr 2006;42:51-63.

    • 47. Okorio J, Maghembe J. The growth and yield of Acacia albida intercropped with maize (Zea mays) and beans (Phaseolus vulgaris) at Morogoro, Tanzania. For Ecol Manag 1994;64:183-90.

    • 48. Stromgaard P. Biomass, growth, and burning of woodland in a shifting cultivation area of South Central Africa. For Ecol Manag 1985;12:163-78.

    • 49. Chidumayo EN. Effects of accidental and prescribed fires on miombo woodland, Zambia. Commonw For Rev 1997;6:268-72. Available from: [Last accessed on 7 Dec 2022].

    • 50. Nyadzi GI, Otsyina RM, Banzi FM, et al. Rotational woodlot technology in northwestern Tanzania: tree species and crop performance. Agrofor Syst 2003;59:253-63.

    • 51. Kaonga ML, Bayliss-smith TP. Carbon pools in tree biomass and the soil in improved fallows in eastern Zambia. Agrofor Syst 2009;76:37-51.

    • 52. Malunguja GK, Devi A, Kilonzo M, Rubanza CD. Climate change mitigation through carbon dioxide (CO2) sequestration in community reserved forests of northwest Tanzania. Arch Agric Environ Sci 2020;5:231-40.

    • 53. Handavu F, Syampungani S, Sileshi GW, Chirwa PWC. Aboveground and belowground tree biomass and carbon stocks in the miombo woodlands of the Copperbelt in Zambia. Carbon Manag 2021;12:307-21.

    • 54. Chirwa PWC, Syampungani S, Geldenhuys CJ. Managing Southern African woodlands for biomass production: the potential challenges and opportunities. In: Seifert, T, editor. Bioenergy from wood: sustainable production in the tropics, managing forest ecosystems. Cham: Springer; 2014. pp. 67-87.

    • 55. Musokwa M, Mafongoya PL, Zungu M, Kondwakwenda A. Soil macro fauna indices and their association with physical soil properties under agroforestry systems. Int J Agrofor Silvic 2020;8:001-9.

    • 56. Sileshi G, Akirmifesi FK, Ajayi OC, et al. Contributions of agroforestry to ecosystems services in the miombo eco-region of eastern and southern Africa. Afr J Environ Sci Technol 2007;1:68-80.

    • 57. Dinesh D, Campbell BM, Bonilla-findji O, Richards M. 10 Best bet innovations for adaptation in agriculture: a supplement to the UNFCCC NAP technical guidelines. Wageningen: The Netherlands; 2017.

    • 58. Sheppard JP, Bohn Reckziegel R, Borrass L, et al. Agroforestry: an appropriate and sustainable response to a changing climate in Southern Africa? Sustainability 2020;12:6796.

    • 59. Rhoades C. Seasonal pattern of nitrogen mineralization and soil moisture beneath Faidherbia albida (syn Acacia albida) in central malawi. Agrofor Syst 1995;29:133-45.

    • 60. Henry M, Picard N, Trotta C, et al. Estimating tree biomass of sub-Saharan African forests: a review of available allometric equations. Silva Fenn 2011;45:477-569.

    • 61. Vieilledent G, Vaudry R, Andriamanohisoa SFD, et al. A universal approach to estimate biomass and carbon stock in tropical forests using generic allometric models. Ecol Appl 2012;22:572-83.

    • 62. IPCC. Good practice guidance for land use, land-use change and forestry. In Penman J, Gytarsky M, Hiraishi T, editors. IPCC national greenhouse gas inventories programme. Kanagawa: Institute for Global Environmental Strategies (IGES); 2003.

    • 63. Wadham-Gagnon B, Sharpe D. Estimating carbon stocks in tropical hardwood plantations: using species-specific and non-destructive parameters to estimate aboveground biomass for six native species in Panama. Internship Report. 2006. Available from: [Last accessed 8 Dec 2022].

    • 64. Saglan B, Kucuki O, Bilgili E, Durmaz D, Basal I. Estimating fuel biomass of some shrub species (Maquis) in Turkey. Turk J Agric 2008;32:349-56. Available from: [Last accessed on 7 Dec 2022].

    • 65. Dong L, Zhang L, Li F. Additive biomass equations based on different dendrometric variables for two dominant species (larix gmelini rupr. and betula platyphyllasuk.) in natural forests in the eastern daxing’an mountains, Northeast China. Forests 2018;9:261.

    • 66. Picard N, Saint-Andre L, Henry M. Manual for building tree volume and biomass allometric equations: from field measurement to prediction. Montpellier: Food and Agricultural Organisation of the United Nations, Rome and Centre de Coorperation Internationale en Recherche Agronomique pour le Development; 2012; 215p.

    • 67. Robinson D. Implications of a large global root biomass for carbon sink estimates and for soil carbon dynamics. Proc Biol Sci 2007;274:2753-9.

      DOIPubMed PMC
    • 68. Koala J, Sawadogo L, Savadogo P, Aynekulu E, Helskanen J, Said M. Allometric equations for below-ground biomass of four key woody species in West African savanna-woodlands. Silva Fenn 2017:51.

    • 69. Scharlemann JPW, Tanner EVJ. Hiederer R, Kapos V. Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Manag 2014;5:1, 81-91.

    • 70. Ciais P, Bombelli A, Williams M, et al. The carbon balance of Africa: synthesis of recent research studies. Philos Trans A Math Phys Eng Sci 2011;369:2038-57.

    • 71. Handavu F, Chirwa PW, Syampungani S, Mahamane L. A review of carbon dynamics and assessment methods in the miombo woodlands. South For A J For Sci 2017;79:95-102.

    • 72. Donovan P. Measuring soil carbon change: a flexible, practical, local method. 2013. Available from: [Last accessed on 7 Dec 2022].

    • 73. Ryan CM, Williams M, Grace J. Above- and Belowground Carbon Stocks in a Miombo Woodland Landscape of Mozambique. Biotropica 2011;43:423-32.

    • 74. Vågen T, Lal R, Singh BR. Soil carbon sequestration in sub-Saharan Africa: a review. Land Degrad Dev 2005;16:53-71.

    • 75. Makipaa R, Liski J, Guendehou S, Malimbwi R, Kaaya A. Soil carbon monitoring using surveys and modelling: general description and application in the United Republic of Tanzania. FAO Forestry Paper 168. Rome: FAO; 2012.

    • 76. Walsh MG, Vågen TG. The land degradation surveillance framework: guide to field sampling and measurement procedures. Nairobi: World Agroforestry Centre; 2006.

    • 77. Vagen TG, Winowiecki L, Tondoh JE. The land degradation surveillance framework: field guide; 2013. Available from: [Last accessed on 8 Dec 2022].

    • 78. Ellert BH, Janzen HH, Entz T. Assessment of a method to measure temporal change in soil carbon storage. Soil Sci Soc Am J 2002;66:1687-95.

    • 79. Walker SM, Desanker PV. The impact of land use on soil carbon in Miombo Woodlands of Malawi. For Ecol Manag 2004;203:345-60.

    • 80. Makumba W, Akinnifesi FK, Janssen B, Oenema O. Long-term impact of a gliricidia-maize intercropping system on carbon sequestration in southern Malawi. Agric Ecosyst Environ 2007;118:237-43.


    Cite This Article

    OAE Style

    Chirwa PW, Musokwa M, Mwale SE, Handavu F, Nyamadzawo G. Agroforestry systems for mitigating climate change and reducing Carbon Footprints of land-use systems in Southern Africa. Carbon Footprints 2023;2:7.

    AMA Style

    Chirwa PW, Musokwa M, Mwale SE, Handavu F, Nyamadzawo G. Agroforestry systems for mitigating climate change and reducing Carbon Footprints of land-use systems in Southern Africa. Carbon Footprints. 2023; 2(2):7.

    Chicago/Turabian Style

    Chirwa, Paxie W., Misheck Musokwa, Saul E. Mwale, Ferdinand Handavu, George Nyamadzawo. 2023. "Agroforestry systems for mitigating climate change and reducing Carbon Footprints of land-use systems in Southern Africa" Carbon Footprints. 2, no.2: 7.

    ACS Style

    Chirwa, PW.; Musokwa M.; Mwale SE.; Handavu F.; Nyamadzawo G. Agroforestry systems for mitigating climate change and reducing Carbon Footprints of land-use systems in Southern Africa. Carbon Footprints. 20232, 7.




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