Environmental performance of agroforestry systems in the Cerrado biome, Brazil

Environmental performance of agroforestry systems in the Cerrado biome, Brazil

World Development 122 (2019) 339–348 Contents lists available at ScienceDirect World Development journal homepage: www.elsevier.com/locate/worlddev ...

820KB Sizes 0 Downloads 52 Views

World Development 122 (2019) 339–348

Contents lists available at ScienceDirect

World Development journal homepage: www.elsevier.com/locate/worlddev

Environmental performance of agroforestry systems in the Cerrado biome, Brazil Gabrielli do Carmo Martinelli a, Madalena Maria Schlindwein a, Milton Parron Padovan b, Everton Vogel a, Clandio Favarini Ruviaro a,⇑ a Agribusiness Postgraduate Program, Federal University of Grande Dourados (UFGD), Rodovia Dourados/Itahum, Km 12 – Unidade II, Caixa Postal: 364, Cep 79.804-970, Dourados, Mato Grosso do Sul, Brazil b Brazilian Agricultural Research Corporation (Embrapa), Rodovia BR 163, Km 253, 6 – Cx. Postal 449 – Zona Rural, Dourados, MS 79804-970, Brazil

a r t i c l e

i n f o

Article history: Accepted 6 June 2019

Keywords: Food production Preservation of resources Biotic factors Productive diversification Bioeconomics

a b s t r a c t Agriculture and land use practices must be significantly improved to satisfy the needs of future generations without placing further pressure on global ecosystems. Agroforestry systems (AFS) have been quoted as one of the best options to mitigate environmental impacts and at the same time, improve smallholders’ livelihoods in agricultural areas. However, studies investigating the environmental aspects and yield of agroforestry systems in rural settlements, established by governmental initiatives, are still uncommon in the literature. Therefore, the goal of this paper was to assess the contribution of five biodiverse AFS, located in the Cerrado biome, to global warming mitigation and the provision of ecosystem services to smallholder farmers. Additionally, the importance of agroforestry projects to family farms in Brazil was discussed. Relying on data from forestry inventory and in-depth interviews with farmers, the crop yield (including fruit) was estimated; and the life cycle assessment method was used to determine the Global Warming Potential (GWP), accounting for all emissions to establish and manage the AFS up until the date of analysis. The results show the significant capacity of AFS sequester carbon, represented by the negative values of GWP, ranging from (263) to (496) t CO2 equivalents per hectare. Each farmer adopted different tree and crop species at the AFS establishment what influenced yields and GWP. The high number of fruit trees contributed positively to the AFS outputs, allowing farmers to consume and sell a large variety of products. Furthermore, the households also benefit from microclimate and aesthetic benefits provided by the AFSs. Future agroforestry projects in rural settlements can contribute significantly to improve household livelihoods, as well as environmental protection. However, efforts should be taken to provide farmers with sound knowledge, financial support, and access to markets to thrive. Ó 2019 Elsevier Ltd. All rights reserved.

1. Introduction Agriculture and land use practices must be significantly improved to satisfy the needs of future generations without placing further pressure on global ecosystems. Although agriculture and forestry are vital for human survival, they are responsible for significant environmental impacts, the consequences of which reach local, national and global levels (Foley et al., 2011; Godfray et al., 2010; Guillaume et al., 2018). Activities such as logging and burning forests, management and fertilization of agricultural ⇑ Corresponding author at: Faculdade de Administração, Ciências Contábeis e Economia, Universidade Federal da Grande Dourados, Rodovia Dourados / Itahum, Km 12, Caixa Postal: 364, Cep: 79.804-970 Dourados, MS, Brazil. E-mail addresses: [email protected] (M.M. Schlindwein), [email protected] (M.P. Padovan), [email protected] (C.F. Ruviaro). https://doi.org/10.1016/j.worlddev.2019.06.003 0305-750X/Ó 2019 Elsevier Ltd. All rights reserved.

soils, and animal husbandry may lead to habitat loss, soil erosion, and species extinction (Duffy, Godwin, & Cardinale, 2017; FAO, 2017; Lemaire, Franzluebbers, Carvalho, & Dedieu, 2014; Salton et al., 2014). Also, global agriculture is responsible for about 24% of all Greenhouse Gas (GHG) emissions from anthropogenic activities, and therefore one of the main contributors to global warming (Foley et al., 2011; Smith et al., 2014). Furthermore, smallholder farmers in tropical developing countries are considered the most susceptible to the consequences of climate change (FAO, 2017; Shikuku et al., 2017; Wood, Jina, Jain, Kristjanson, & Defries, 2014). Extreme weather events, such as droughts, floods, severe high and low temperatures have increased in the last half century (Lobell & Field, 2007; Lobell, Schlenker, & Costa-Roberts, 2011; Nicholson, 2014). This can lead to an increase in diseases and pest outbreaks, livestock mortality, crop failures, human migration, and ultimately to more poverty (FAO, 2017).


G.C. Martinelli et al. / World Development 122 (2019) 339–348

While there is no single solution to this devastating problem, agroforestry1 has been quoted as one of the best alternatives for sustainable agriculture and enhancement of livelihoods in developing countries (Matthews et al., 2014; Nair, Nair, Kumar, & Showalter, 2010). Consequently, international agreements, such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol, led governments and international agencies to add agroforestry to their official agenda. With the Clean Development Mechanism (CDM), projects aiming at carbon sequestration have grown considerably in developing countries in the late 1990s (Boyd et al., 2009; Mori-Clement, 2019). In addition, in 2005 the United Nations launched the REDD programme (Reducing Emissions from Deforestation and Forest Degradation) which is considered one of the most relevant ecosystem protection projects, with the objectives of rewarding developing countries for avoiding forest degradation and using sustainable agroforestry practices (Duchelle et al., 2014; Ickowitz, Sills, & de Sassi, 2017; Matthews et al., 2014; Thangata & Hildebrand, 2012). Brazil has engaged with several projects in order to reduce GHG emissions and improve livelihoods in rural areas (e.g. REDD and CDM) (Ickowitz et al., 2017; MMA, 2018; Mori-Clement, 2019). In addition, the country also promoted projects for environmental conservation and agricultural development (e.g. Low Carbon Emission Plan) (MAPA, 2017), and approved the Law No. 12,805 of 2013, which formalized the National Policy for Integrated CropLivestock-Forestry Systems (BRASIL, 2013). These actions are incredibly relevant to further support 5 million rural households across the country (Medina, Almeida, Novaes, Godar, & Pokorny, 2015). Also, Brazil is one of the largest agricultural producers in the world, and is hence one of the most significant contributors to GHG emissions. In 2016, agriculture, livestock husbandry, and deforestation were responsible for approximately 70% of the 2.3 billion tons CO2 equivalent emitted by the country (SEEG, 2017). There were many approaches to understand the consequences of agroforestry projects to the environment, and people living in rural areas (Mbow, Smith, Skole, Duguma, & Bustamante, 2014; Rasmussen, Watkins, & Agrawal, 2017; Scherr, 1995). The significance of AFSs to carbon sequestration has been identified and confirmed by several review studies (Abbas et al., 2017; Albrecht & Kandji, 2003; Kim, Kirschbaum, & Beedy, 2016; Nair, Kumar, & Nair, 2009; Thangata & Hildebrand, 2012). More recently, research also has confirmed the AFSs’ contribution to a more extensive range of ecosystem services (ES) (Cerda et al., 2017; Jose, 2009; Torralba, Fagerholm, Burgess, Moreno, & Plieninger, 2016). While from the environmental viewpoint, agroforestry projects show significant superiority compared to commercial farming — at the socioeconomic side — there is still evidence of adverse outcomes, which affect directly the poorest households in rural areas (Duchelle et al., 2014; Euler, Krishna, Schwarze, Siregar, & Qaim, 2017; Jindal, Kerr, & Carter, 2012; Kansanga & Luginaah, 2019). The origin of these negative consequences may arise at different levels (local, regional, national and international) (Reynolds, 2012), and emerge due to various reasons (e.g. site-specific sequestration conditions, uncertainty in carbon sequestration, project structure, cultural reasons, governance structure, land tenure and economic incentives) (Gren & Zeleke, 2016; Ickowitz et al., 2017; Jindal et al., 2012; Scherr, 1995).

1 Nair (1993p. 14) explains that despite of many definitions formulated over the years, agroforestry can be understood as ‘‘. . . an approach to land use involving a deliberate mixture of trees with crops and/or animals”. Further, Leakey (1996) suggests that agroforestry should be seen as ‘‘. . . a dynamic, ecologically based, natural resource management system that, through the integration of trees in farm- and rangeland, diversifies and sustains smallholder production for increased social, economic and environmental benefits”.

In Brazil, agroforestry related studies investigated mainly projects with a dominant crop, such as cacao, rubber, oil palm and coffee (Alvim & Nair, 1986; Brienza Junior & GazelYared, 1991; De Souza, de Graaff, & Pulleman, 2012; Gama-Rodrigues et al., 2010; Jagoret, Kwesseu, Messie, Michel-Dounias, & Malézieux, 2014; Monroe, Gama-Rodrigues, Gama-Rodrigues, & Marques, 2016; Ramos, Vasconcelos, Kato, & Castellani, 2018) or the outcomes of international projects such as REDD and CDM (Duchelle et al., 2014; Sunderlin et al., 2014). However, the benefits of biodiverse AFS to environmental protection and smallholder farmers in rural settlements, established by governmental initiatives, are uncommon. Therefore, the goal of this paper is to evaluate ecosystem services provided by agroforestry systems located in a rural settlement. This namely applies to crop and fruit production, and net carbon offsets using the global warming potential indicator. Also, we discuss the benefits of AF projects for the provision of ecosystem services in rural settlements. Several methods and tools have been developed to assess the impacts of human actions in the environment (for an overview see Ahlroth & Finnveden, 2011; Finnveden & Moberg, 2005; Ness, Urbel-Piirsalu, Anderberg, & Olsson, 2007; Sala, Farioli, & Zamagni, 2013). As a result of the economic development and globalization experienced over the years, methods that are able to assess the performance of a system or product across different scales have become vital (Roy et al., 2009). The Life Cycle Assessment (LCA) approach is an environmental impact evaluation technique that allows the measurement and comparison of environmental impacts throughout the life cycle of systems or products (ISO 41404, 2006; ISO 1440, 2006). LCA has been used successfully to quantify and communicate environmental impacts from agricultural supply chains (Buratti et al., 2017; Goglio, Brankatschk, Knudsen, Williams, & Nemecek, 2018; Roy et al., 2009; Ruviaro, Gianezini, Brandão, Winck, & Dewes, 2012), and more recently, forestry and fruit production (Eldesouky, Mesias, Elghannam, & Escribano, 2018; Paolotti, Boggia, Castellini, Rocchi, & Rosati, 2016; Utomo, Prawoto, Bonnet, Bangviwat, & Gheewala, 2016). This paper is structured as follows: Section 2 presents the area of study and the life cycle assessment methodology; Sections 3 and 4 present the results and discussions; and Section 5 presents some limitations of our research and further recommendations.

2. Methods 2.1. Study area The agroforestry systems (AFSs) studied are part of the Santa Lucia Rural Settlement (SLRS), located in Bonito, state of Mato Grosso do Sul, Brazil, Fig. 1. Bonito’s economy is based on ecotourism and agriculture, mainly, beef cattle, maize and soybean production. The micro-region’s climate is humid tropical with an average annual temperature of 20°  22 °C. Annual precipitation varies around 1.500 mm and the rainy season occurs from November to April. The predominant vegetation is the Cerrado biome, composed of deciduous and semideciduous seasonal forests (Grechi, Lobo, Martins, & Lunas, 2010). According to the Ecological-Economic Zoning of the State of Mato Grosso do Sul (ZEE/MS, 2009), about 3.81% of the area occupied in the state corresponds to Red-Yellow Ultisols, which is the type of soil predominant in the study area. The SLRS was established as part of the Brazilian agrarian reform program. An original area of 1026 ha was divided into 37 plots of 16 ha each, plus a common area for environmental protection (i.e. Legal Reserve). The plots were then distributed, in 1998, to selected landless householders, under the supervision

G.C. Martinelli et al. / World Development 122 (2019) 339–348


Fig. 1. Geographical location of the municipality of Bonito-MS. Location of study area Santa Lucia Rural Settlement. Source: IBGE digital mesh, 2010.

of the National Institute for Colonization and Agrarian Reform (INCRA). Given the ecological and economic importance of the regional ecosystem, in the same period of the rural settlement establishment, an environmental protection project was launched in the region, i.e. the Integrated Management of the Rio Formoso River Basin (GEF Rio Formoso). The project’s objectives were to recover degraded areas, preserve the environment, and at the same time, improve farmers’ livelihoods in the region. The World Bank financed the project and it was managed by public institutions such as the Brazilian Agricultural Research Corporation (Embrapa), Agrarian Development and Rural Extension Agency (AGRAER), and Environment Institute of Mato Grosso do Sul (IMASUL). For a complete overview of the project’s actions (cf. World Bank (2010)). Consequently, the new farmers from the SLRS also received the benefits from the GEF Rio Formoso. Between the years 2000 and 2005, farmers agreed on establishing AFS and managed them under agroecological principles. All the resources needed for the AFS establishment were supplied, for free, as part of the project, e.g. seedlings, organic fertilizer, machinery for soil preparation. Also, training and technical support, during the implantation period, were provided by rural extensionists. When selecting seedlings for their AFS, farmers freely opted for exotic and native species with a large variety of fruit trees (Coutinho, 2011). 2.2. Forestry inventory and carbon estimation To understand the AFSs’ progression, in 2010, Embrapa surveyed the SLRS in collaboration with AGRAER, the NGOs Brazilian Neotropical Foundation, and the Institute of Águas da Serra da Bodoquena. During the survey, Embrapa’s team identified 15 AFS still standing. These AFS varied in size, reaching a maximal of 2.5 ha. They were classified as biodiverse (multispecies) and semi-open

(not homogeneous blocks), with the predominance of native species. Furthermore, in 2016 Embrapa selected five AFSs, ranging from 0.5 to 2.5 ha and conducted a detailed forestry inventory, including species’ botanical classification, trees circumference, height, and accumulated litter biomass. All tree and shrub species higher than 1.5 m were sampled. Also, interviews were conducted with the households were conducted to identify what management practices farmers used and what were the benefits they have with their AFS. Area of the AFS and species richness were the criteria adopted by Embrapa professionals to select the five AFS to be inventoried (Nascimento, 2016). The AFSs are identified and located at the following coordinates. Latitudes and longitudes (AFS I) 21°210 29.200 S and 56°350 11.900 W; (AFS II) 21°210 40.700 S and 56°350 48.100 W; (AFS III) 21°210 36.800 S and 56°350 31.400 W; (AFS IV) 21°200 23.700 S and 56°350 05.300 W; (AFS V) 21°210 40.300 S and 56°350 49.800 W. For the AFS carbon (C) estimation, we evaluate four C pools, namely, aboveground biomass (AGB), below ground biomass (BGB), litter, and soil organic carbon (SOC). The wood basic density (g cm3) for each species was identified, then AGB was estimated then using the equation described by (Chave et al., 2005), Eq. (1). The BGB was estimated as 28% of the AGB (Mokany, Raison, & Prokushkin, 2006). AGB and BGB were multiplied by 0.47 to find the total carbon biomass (IPCC, 2006). The litter carbon was derived directly from the inventory and laboratory analysis (Agostinho, 2017). Carbon stored in soil was estimated based on secondary data. The difference between final carbon stock in AFSs (120 t C ha1) (Iwata et al., 2012; Rocha et al., 2014) and carbon in soil under conventional tillage (68 t C ha1) (De Assis, Jucksch, Mendonça, & Neves, 2006; De Freitas, Blancaneaux, Gavinelli, Larré-Larrouy, & Feller, 2000) generated a value of 52 t C ha1 that was used as proxy in our study. The biome, climate, and vegetation studied


G.C. Martinelli et al. / World Development 122 (2019) 339–348

by the authors correspond to the area investigated in our study. Finally, to calculate the total carbon dioxide of each AFS, the amount of carbon is multiplied by 44/12 (stoichiometric weight of CO2 relative to C) (IPCC, 2006).

 0:916 AGB ¼ 0:112  qD2 H


and preserve the environment. Therefore, the FU is a one-hectare standing AFS. The allocation of environmental burdens is all addressed to the standing AFS. The system boundary included all activities and materials inputs to produce the seedlings, prepare the soil, establish and manage the AFS, up until 2016, the year of our analysis, Fig. 2.


q = density (g cm3) D = diameter of the tree (cm) H = tree height (m) 2.3. Life cycle assessment The life cycle assessment (LCA) methodology follows a structure composed of four phases which are described in ISO standards. A whole LCA includes all stages of a system or product, from raw material extraction, transportation, production, consumption, and disposal, often known as a cradle-to-grave approach (ISO 41404, 2006; ISO 1440, 2006). For additional details regarding the LCA structure and methods (cf. Finnveden et al., 2009; Guinée, 2002; ILCD, 2010), and for comparison of LCA with other environmental assessment methods (cf. Finnveden & Moberg, 2005; Sala et al., 2013). The four phases of LCA according to ISO are described as follows: i) Goal and scope definition: This phase includes the description of the system boundaries, Functional Unit (FU, is the reference unit to which the inputs and outputs are calculated for, e.g. one hectare), and impact categories. ii) Life Cycle Inventory (LCI): A detailed inventory, of all inputs and outputs related to the system under study is conducted. iii) Life Cycle Impact Assessment (LCIA): With the inventory of emissions, the life cycle impact assessment is modelled according to impacts categories. iv) Interpretation: the results are critically reviewed, to provide direction for further developments. 2.3.1. Goal and scope In addition to identifying the contribution to crop and fruit production, the goal of this study is to assess the global warming mitigation potential of agroforestry systems, based on their capacity for storing carbon. The primary function of selected agroforestry systems is to recover the degraded area, conserve biodiversity

2.3.2. Life cycle inventory To complete the LCI phase, an inventory of material and energy flows was conducted, to calculate the relevant GHG emissions and offsets for each AFS. This phase was modelled according to IPCC (2006) and Nemecek and Kägi (2007). Direct measurement of emission caused by agricultural practices are sometimes not possible or too costly. In this case, models are used to estimate emissions within the system boundary (Nemecek & Kägi, 2007). Therefore, we use preliminary field documentation, survey information, and the forestry inventory to model the emissions associated with the AFSs. Also, in March 2017, we conducted in-depth semi-structured interviews with the head of the householder to cross-check existing information and gather more data on actual management practices and fruit production in the AFSs. Data cross-checking was supervised by an Embrapa agronomist, an AFS expert, as suggested by IPCC guidelines (IPCC, 2006). To estimate emission from background processes (i.e. emission upstream in the supply chain not directed generated at the agroforestry system), we used secondary data and the EcoinventÒ database v. 3.2. Secondary data was used to model seedling production at nursery, which included the amount of fertilizer, lime, water, soil and non-toxic polypropylene tubes for growing seedlings (Instituto Brasileiro de Florestas, 2017; Macedo, 1993; Oliveira et al., 2016; Roscoe, Buurman, Velthorst, & Vasconcellos, 2001). The emissions associated with transportation, lime production, diesel production, and machinery operation were retrieved from Ecoinvent Centre (2018).

2.3.3. Life cycle impact assessment In the LCIA phase, characterization factors are used to convert the LCI results into the potential for environmental impact. For this purpose, we used the SimaProÒ v. 8.2.0 software (PRé Consultants) selecting the mid-point method Global Warming Potential (GWP), over a 100 year period. The characterization factors for each kg of CO2, CH4, and N2O emitted to atmosphere equals to 1 kg, 25 kg and 298 kg of CO2, respectively (IPCC, 2013).

Fig. 2. System boundary. Indicates the inputs and outputs of the analyzed agroforestry system (system size 1 ha).


G.C. Martinelli et al. / World Development 122 (2019) 339–348 Table 2 Life cycle inventory for the production of 1000 seedlings with six months.

3. Results In this section, we first present the main characteristics of the farms and AFSs, followed by the modelled LCI for the nursery phase, as well as the LCI regarding the five AFSs. Finally, we present the results of the LCIA related to the establishment and management of the AFSs, namely Global Warming Potential (kg CO2 eq.). 3.1. Farm and agroforestry system characteristics


The AFSs were established strategically around the house and range in area from 0.5 ha to AFS II and V, 0.6 ha and 1 ha to AFS I and III, respectively, and 2.5 ha for AFS IV. Regarding the original area (16 ha), farmers opted to dedicate 3–15% of their land to agroforestry. Farmers’ main income is from milk production, mainly grass-fed cows. However, during the dry season, farm outputs are used as supplementary fodder (e.g. sugarcane, fruit). Also, pigs and chicken are kept in order to provide meat and eggs. The main characteristics of the AFSs are presented in Table 1. A large variety of fruit trees were planted to provide farmers with fresh fruit, either for households to consume or to attend to the demands in the touristic town. Farmers sell the product as fresh fruit or processed products (e.g. dried fruit, jam or liqueur). Also, fruit that falls before ripe and bad fruit is fed to cattle and pigs. All farmers adopted inter-cropping during the first three years of the systems. They used both, annual crops such as beans and corn, and bi-annual crops such as cassava and sugarcane. Beans and cassava are mainly used for human consumption, while corn and sugarcane are used as animal feed. As the AFS canopy became dense, production of these staples moved to the area surrounding the AFS. Farmers also benefit from other ecosystem services (ES) provided by their AFS. The most evident benefits enjoyed by the households are shade and the aesthetic benefit of the AFSs. 3.2. Life inventory assessment results The nursery process modelled to represent seedlings production is presented in Table 2. The LCI data related to the AFS establishment and management are summarised in Table 3. For the AFS establishment, first soil was




Dolomitic limestone NPK (4-14-8) Water Soil kg Tubes* Outputs Seedlings

kg kg m3 kg p

1 5 1.8 197 63



Used for 16 production cycles.

ploughed and harrowed, then lime and cattle manure was applied and incorporated. Seedlings were then planted in the area. During the first three years, farmers were encouraged to plant green manure crops (Crotalaria juncea, Cajanus cajan, Mucuna aterrima) alongside annual and bi-annual crops, hence cycling nutrients, keeping the area free of spontaneous weeds and while having some staples and fodder. After the AFS establishment, the main activities conducted by farmers were: pest control (with home-made products); fertilization with farm yard cattle manure (first three years); pruning and harvesting, conducted manually. The impacts associated with cassava and sugarcane ‘‘stemseeds” were not included in the inventory (they are propagated by vegetative means, and the stems for planting were acquired from older plantations located in the neighbouring farms. Therefore, due to the lack of information on these neighbouring farms, associated emissions could not be accounted for).

3.3. Global warming potential After subtracting all negative impacts associated with the inputs needed to establish and manage the AFSs (Table 3), from the CO2 captured and stored in the systems, we found the global warming potential of (279); (496); (433); (475) and (263) t CO2 eq, for AFS I, II, III, IV and V, respectively, (i.e. CO2 was stored in the systems, represented by negative emissions), Fig. 3.

Table 1 Characteristics of the agroforestry system studied in Santa Lucia rural settlement. Characteristic







Age AFS area Density

years ha trees ha1 un.

10 0.65 390

12 0.50 730

15 1.00 410

14 2.43 662

10 0.50 546






% native % exotic m cm g cm3 Species

65 34 3.74 (2.31) 13.4 (12.0) 0.80 – Acrocomia aculeata – Citrus reticulata – Citrus sinensis – Dipteryx alata – Mangifera indica – Persea americana – Psidium guajava

50 50 5.23 (4.65) 16.6 (15.7) 0.61 – Anacardium occidentale – Carica papaya – Citrus reticulata – Citrus sinensis – Cocos nucifera – Dipteryx alata – Jacaratia spinosa – Mangifera indica – Musa paradisíaca – Persea americana – Psidium guajava

64 36 5.02 (2.61) 18.9 (14.7) 0.64 – Acrocomia aculeata – Anacardium occidentale – Citrus reticulata – Citrus sinensis – Cocos nucifera – Dipteryx alata – Genipa americana – Mangifera indica – Musa paradisíaca – Psidium guajava

74 26 8.24 (4.86) 18.4 (14.5) 0.66 – Acrocomia aculeata – Anacardium occidentale – Carica papaya – Citrus reticulata – Citrus sinensis – Cocos nucifera – Genipa americana – Jacaratia spinosa – Mangifera indica – Persea americana – Psidium guajava

61 39 3.92 (2.02) 13.7 (9.7) 0.51 – Acrocomia aculeata – Anacardium occidentale – Annona muricata – Citrus reticulata – Citrus sinensis – Dipteryx alata – Jacaratia spinosa – Mangifera indica – Musa paradisíaca – Persea americana – Psidium guajava

Number of species Composition Height * Diameter * Average density Fruit species

* Values in brackets represent standard deviation.


G.C. Martinelli et al. / World Development 122 (2019) 339–348

Table 3 Life cycle inventory for the production of a one-hectare standing agroforestry system. Amount









Land Seedlings Maize seeds Beans seeds Dolomitic limestone Cattle manure Diesel (soil preparation) Transport, freight, lorry 3.5–7.5 metric ton Carbon stored in live biomass Carbon stored in litter Carbon stored in soil 0–40 cm outputs Production of fruit Production of corn Production of cassava Production of beans Production of sugarcane

ha p kg kg kg kg kg t km-1 t t t

1 429 19 5 1300 2400 30 6 20 4 52

1 803 14 10 2000 6600 30 12 80 3 52

1 451 15 13 1500 2700 30 7 61 5 52

1 728 20 18 2000 3300 30 11 73 4 52

1 600 16 13 1600 3900 30 9 16 4 52

t t t t t

52 3.4 13 0.2

176 2.5 10 0.4 10

27 2.7 11 0.5

76 3.6 7 0.7

80 2.8 10 0.5 12

Fig. 3. Global warming potential of agroforestry systems.

4. Discussion 4.1. Global warming mitigation potential Emissions associated with AFSs occurred mainly during the establishment phase, and the following three years, when intercropping was practiced. This is consistent with past findings regarding agroforestry (Albrecht & Kandji, 2003), forestry (Brunori et al., 2017), and agricultural production, where soil management, diesel burned in machinery, and liming and manure application drive most of the emissions (De Figueirêdo et al., 2013; Nemecek, Dubois, Huguenin-Elie, & Gaillard, 2011; De Santos, Nunes, Giongo, Barros, & de Figueirêdo, 2018). Emissions associated with transport and seedling production were very low compared to liming and diesel emissions. Nevertheless, given the negative values of GWP, the final results confirm the capacity of biodiverse AFSs to mitigate emissions from the initial phase and reach positive C storage throughout their life cycle. Conducting direct comparisons among LCA studies would be incoherent since they usually differ in many methodological aspects (e.g. goal and scope definition, functional units, impact category, and study region). Nevertheless, the results of some studies are presented to give an idea of the GWP from AFSs in our study and other agricultural and forestry activities. We found values between 263 and 496 t CO2 eq. per ha in this study, while results for soybean production in Mato Grosso State, Brazil varied

from 0.33 to 1.11 t CO2 eq. per ha (Raucci et al., 2015); in the Brazilian Northeast region, melon production presented 21 t CO2 eq. per ha for conservationist system to 25 t CO2 eq. per ha for the conventional system (De Santos et al., 2018). In peach production in Spain, emissions varied from 4.6 to 6 t CO2 eq. per ha, depending on the year (Vinyes, Gasol, & Asin, 2015). In different farming systems in Switzerland it varied from 2.1 to 4.4 t CO2 eq. per ha (Nemecek et al., 2011). Furthermore, in forestry, the production of eucalyptus (average annual increment 10 m3 ha-1) and maritime pine (average annual increment 6 m3 ha-1) in Portugal presented maximal emissions of 0.02 and 0.01 t CO2 eq. per m3 of eucalyptus and pine respectively (Dias & Arroja, 2012). For 50 years normalized value, pine forest in the Pacific Northwest of North America, emissions reached 8.6 t CO2 eq. ha, of which 84% results from management practices (Sonne, 2006). A 34 year-old English oak plantation in Italy presented values of 339 t CO2 eq. per ha, with values of carbon stocks reaching positive balance after the fourth year after establishment (Brunori et al., 2017). 4.2. Food, fodder, and other ecosystem services Although the AFS have a significant potential for storing carbon, farmers must have other strong motivations to maintain the systems standing once they receive no payment for carbon sequestration and face high land opportunity costs (Ickowitz et al., 2017;

G.C. Martinelli et al. / World Development 122 (2019) 339–348

Scherr, 1995). We identify that farmers derive their main benefits by using the fruits produced in the systems (Table 1). Farmers derive direct economic benefits by selling fresh fruit, homemade jelly, and jam to the local Farmers Market. In addition, they also supply their products to public schools. This is made possible by the National School Feeding Program (PNAE), which supports the commercialization of family farm’s production for schools in Brazil (FNDE, 2014). Also, there are indirect economic benefits by avoiding expenditures with food for the household or fodder for animals. By using LCA and allocating the environmental burdens to the standing trees, we identified that the fruit from these AFSs might be considered carbon-neutral (Birkenberg & Birner, 2018; Tilman, Hill, & Lehman, 2006). Aligned to the fact that the AFSs have an agroecological character, carbon-neutral fruit and bioproducts of the systems could benefit from eco-friendly labels (e.g. organic, carbon-free), and therefore reach better prices in the market (Kilian, Hettinga, Jiménez, Molina, & White, 2012; Schaefer & Blanke, 2014). In addition to fruit provision, we identified that farmers motivations to maintain their AFS are also related to other cultural and regulating ES. First, the households benefit from the fact that the AFSs were established around their homes. Thus, the trees create a microclimate that alleviates heat stress, especially in hot summer days. This is an important characteristic of the AFS since there is strong evidence linking the presence of trees to human health (Donovan et al., 2013; Suminah, Sulistyantara, & Budiarti, 2017). Second, the aesthetic benefits households derive from the AFSs stands as an important characteristic for them; they appreciated the green around their house, as in a home garden, and have favourite trees that have particular value because of their blossom (e.g. Handroanthus ochraceus, and H. heptaphyllus). Although farmers have benefited in many ways from the AFSs from the establishment up until now, the following research should be carried out in the next few years, as the systems mature, to confirm their capacity of contributing to environmental benefits and livelihoods in the long term (Reed et al., 2017). For example, forestry inventories should be carried out more frequently, in order to provide a better understanding of AFS growth dynamics and to assess the maximum capacity of these systems to store carbon. Efforts also should be taken to assess the AFSs’ contribution to the household, in economic and nutritional terms, originating relevant information to policymakers (Rasmussen et al., 2017).

4.3. GEF Rio Formoso This study does not allow a complete evaluation of the success or failure of the GEF Rio Formoso project; however, under the scope of the present analysis, we see the outcomes as very positive. The focus on local environmental protection through agroforestry, promoted local direct and indirect benefits to households, as well as public goods, through carbon sequestration. In addition to the diffusion of biodiverse agroforestry systems, the project also promoted social learning among farmers at the SLRS. The possibility of selling products at farmer markets was also identified as a positive way for social interaction and experiences exchange (Borremans, Marchand, Visser, & Wauters, 2018). Despite the recognition that the AFSs require more labour than common monoculture crops, all farmers visited show satisfaction with their SAF. Furthermore, this was a voluntary-adoption project that provided only initial financial and technical support to farmers, and therefore seems less bureaucratic than projects focusing on longterm payment for ES, which needs a great deal of governmental and institutional organization to succeed (Alemagi, Duguma, Minang, & Nkeumoe, 2015; Cerbu, Sonwa, & Pokorny, 2013;


Murdiyarso, Brockhaus, Sunderlin, & Verchot, 2012; Reynolds, 2012). However, in order to reach success, agroforestry projects must be supported by national and regional environmental and agricultural policy (Simelton, Catacutan, Dao, Dam, & Le, 2017). Despite many advances in agricultural and environmental policies in Brazil in the last decades, at the ground level, many rural households are still far from receiving benefits considered essential to thrive, such as technical assistance and financial support (Flaviana, Antonio, & Ana, 2018; Medina et al., 2015). This consequently hinderis the country’s sustainable development. With more than 4.3 million family farms in Brazil, there are many opportunities to establish small-scale biodiverse agroforestry projects. For instance, in rural settlements, there are 972.289 households countrywide, that could benefit from agroforestry (INCRA, 2017). Also, AF in rural settlements, aiming at food, wood and fodder production, could help to avoid the exploitation of the communal legal reserve (Alif, Sahide, & Giessen, 2015; Boffa, Kindt, Katumba, Jourget, & Turyomurugyendo, 2008; Garrastazú et al., 2015).

5. Conclusions Facing the global challenges regarding poverty in rural regions and environmental impacts from agriculture, the results of this study confirm the importance of agroforestry systems for family farmers in a rural settlement regarding the provision of food, fodder and other ecosystem services. Farmers may have many motivations to keep their systems standing, however, the project’s design, focusing on financial and technical support during the establishment, nonetheless played a central role in their decision. Moreover, fruit production and access to markets contribute positively to the outcomes described. While Brazil increases the efforts to avoid environmental impacts from agriculture, either by new environmental agreements or laws, we cannot forget that around 29 million people are living in rural areas across the country and that most of them rely on agriculture and natural resources (IBGE, 2010). Therefore, projects focusing on sustainable agriculture, such as the low carbon agriculture, should consider environmental and socioeconomic impacts simultaneously, to improve the environment and livelihoods (Jung, Rasmussen, Watkins, Newton, & Agrawal, 2017; Medina et al., 2015). As economic feasibility of AFS projects have been confirmed across the country (Arco-verde, 2008; Dube et al., 2002; Martinelli, Schlindwein, Padovan, & Gimenes, 2019; Nunoo & Owusu, 2015), attention should be increased to provide farmers with comprehensive technical knowledge to establish their AFS, and the development of markets for agroforestry products (Flaviana et al., 2018; Rasmussen et al., 2017; Wittman & Blesh, 2017). The Life cycle assessment methodology proved to be an effective technique to assess the environmental performance of AFS, mainly due to its capacity for accounting for other source of emissions associated with AFS establishment and management (e.g. upstream emissions, land use, land use change), which is a concern regarding agroforestry projects (Albrecht & Kandji, 2003; Jindal et al., 2012). Therefore, LCA can give a more precise estimate on net global warming mitigation potential from AFS and AFS products. This is a relevant topic, as LCA is the standard tool to assess the environmental performance of agricultural products and grant them with Environmental Product Declaration (EPD), i.e. type III environmental declaration (Cerutti et al., 2014; Schau & Fet, 2008). Although still challenging, future studies should use a life cycle thinking approach, including in addition to environmental aspects, economic and social impacts assessment, under the same scope.


G.C. Martinelli et al. / World Development 122 (2019) 339–348

Among the limitations of the present study, the uncertainty that always arises when using models is worth mentioning — for example, the carbon estimation through allometric equations (Ketterings, Coe, Van Noordwijk, Ambagau, & Palm, 2001), or during the life cycle inventory construction (Henriksson, Guinée, Heijungs, de Koning, & Green, 2014). Also, by inventorying the most biodiverse AFS we identified the best outcomes of the project, however, this approach did not enable us to further discuss the reasons other AFSs have not reached the same outcomes (i.e. species richness and size). Furthermore, in order to evaluate the success of the GEF project, as a whole, more detailed socioeconomic data should be collected, expanding the sample among adopters and also including a control group of non-agroforestry adopters. However, due to technical and time limitations, we were not able to broaden the study’s scope. Declaration of Competing Interest None. Acknowledgment This research was funded by CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnologico), especially for the master’s scholarship. We also thank a Brazilian Agricultural Research Corporation (EMBRAPA AGROPECUÁRIA OESTE) for providing the data that supported the elaboration of this research. We also thank Arun Agrawal and two anonymous reviewers for comments and suggestions that significantly improved the paper. References Abbas, F., Hammad, H. M., Fahad, S., Cerdà, A., Rizwan, M., Farhad, W., et al. (2017). Agroforestry: A sustainable environmental practice for carbon sequestration under the climate change scenarios—A review. Environmental Science and Pollution Research, 24(12), 11177–11191. https://doi.org/10.1007/s11356-0178687-0. Ahlroth, S., & Finnveden, G. (2011). Ecovalue08-A new valuation set for environmental systems analysis tools. Journal of Cleaner Production, 19(17), 1994–2003. https://doi.org/10.1016/j.jclepro.2011.06.005. Albrecht, A., & Kandji, S. T. (2003). Carbon sequestration in tropical agroforestry systems. Agriculture Ecosystems and Environment, 99, 15–27. https://doi.org/ 10.1016/S0167-8809(03)00138-5. Alemagi, D., Duguma, L., Minang, P. A., & Nkeumoe, F. (2015). Intensification of cocoa agroforestry systems as a REDD + strategy in Cameroon: Hurdles, motivations, and challenges. Agricultural Sustainability, 13(3), 187–203. https:// doi.org/10.1080/14735903.2014.940705. Alif, Muhammad, Sahide, K., & Giessen, Lukas (2015). The fragmented land use administration in indonesia – analysing bureaucratic responsibilities influencing tropical rainforest transformation systems. Land Use Policy, 43, 96–110. https://doi.org/10.1016/j.landusepol.2014.11.005. Alvim, R., & Nair, P. K. R. (1986). Combination of cacao with other plantation crops: an agroforestry system in Southeast Bahia, Brazil. Agroforestry System, 4(1), 3–15. https://doi.org/10.1007/BF01834698. Arco-verde, M. F. (2008). Sustentabilidade Biofísica E Socioeconomica De Sistemas Agroflorestais Na Amazônia Brasileira. Do Paraná: Univ. Fed. Agostinho, P.R. Indicadores biológicos de qualidade de solo em sistemas agroflorestais biodiversos para fins de recuperação de áreas degradadas. (2017). 78 p. Dissertação (Mestrado em agronegócios) – Universidade Federal da Grande Dourados, Dourados. 2017. Available from: https://www.alice.cnptia. embrapa.br/bitstream/doc/1082930/1/36515.pdf. (accessed on december 6, 2017). Birkenberg, A., & Birner, R. (2018). The world’s first carbon neutral coffee: Lessons on certification and innovation from a pioneer case in Costa Rica. Journal of Cleaner Production, 189(10), 485–501. https://doi.org/10.1016/j. jclepro.2018.03.226. Boffa, J., Kindt, R., Katumba, B., Jourget, J. G., & Turyomurugyendo, L. (2008). Management of Tree Diversity in Agricultural Landscapes around Mabira Forest Reserve, Uganda. African Journal of Ecology, 46, 24–32. https://doi.org/10.1111/ j.1365-2028.2008.00926.x. Borremans, L., Marchand, F., Visser, M., & Wauters, E. (2018). Nurturing agroforestry systems in Flanders: Analysis from an Agricultural Innovation Systems Perspective. Agricultural Systems, 162, 205–219. https://doi.org/10.1016/j. agsy.2018.01.004. Boyd, E., Hultman, N., Timmons Roberts, J., Corbera, E., Cole, J., Bozmoski, A., et al. (2009). Reforming the CDM for sustainable development: Lessons learned and

policy futures. Environmental Science & Policy, 12(7), 820–831. https://doi.org/ 10.1016/j.envsci.2009.06.007. BRASIL (2013). Lei n° 12.805, de 29 de abril de 2013.Available from: http:// www.planalto.gov.br/ccivil_03/_Ato2011-2014/2013/Lei/L12805.htm. (accessed on December 12, 2018). Brienza Junior, S., & GazelYared, J. A. (1991). Agroforestry systems as an ecological approach in the Brazilian Amazon development. Forest Ecology and Management, 45(1–4), 319–323. https://doi.org/10.1016/0378-1127(91)90226L. Brunori, A. M. E., Sdringola, P., Dini, F., Ilarioni, L., Nasini, L., Regni, L., et al. (2017). Carbon balance and Life Cycle Assessment in an oak plantation for mined area reclamation. Journal of Cleaner Production, 144, 69–78. https://doi.org/10.1016/j. jclepro.2016.12.116. Buratti, C., Fantozzi, F., Barbaneira, M., Lascaro, E., Chiorri, M., & Cecchini, L. (2017). Science of the total environment carbon footprint of conventional and organic beef production systems: An Italian case study. Science of the Total Environment, 576, 129–137. https://doi.org/10.1016/j.scitotenv.2016.10.075. Cerbu, G. A., Sonwa, D. J., & Pokorny, B. (2013). Forest Policy and Economics Opportunities for and capacity barriers to the implementation of REDD + projects with smallholder farmers: Case study of Awae and Akok, Centre and South. Forest Policy and Economics, 36, 60–70. https://doi.org/10.1016/ j.forpol.2013.06.018. Cerda, R., Allinne, C., Gary, C., Tixier, P., Harvey, C. A., Krolczyk, L., et al. (2017). Effects of shade, altitude and management on multiple ecosystem services in coffee agroecosystems. European Journal of Agronomy, 82, 308–319. https://doi. org/10.1016/j.eja.2016.09.019. Cerutti, A. K., Beccaro, G. L., Bruun, S., Bosco, S., Donno, D., Notarnicola, B., et al. (2014). Life cycle assessment application in the fruit sector: State of the art and recommendations for environmental declarations of fruit products. Journal of Cleaner Production, 73(15), 125–135. https://doi.org/10.1016/j. jclepro.2013.09.017. Chave, J., Andalo, C., Brown, S., Cairns, M. A., Chambers, J. Q., Eamus, D., et al. (2005). Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia, 145, 87–99. https://doi.org/10.1007/s00442-0050100-x. Coutinho, H.L.C. Promoção da transição agroecológica em Bonito MS (Projeto GEF Rio Formoso) / Heitor Luiz da Costa Coutinho... [et al.]. – Dados eletrônicos. – Rio de Janeiro: Embrapa Solos, 2011. 21 p. - (Documentos / Embrapa Solos, ISSN 1517-2627; 138). De Assis, C. P., Jucksch, I., Mendonça, E. D. S., & Neves, J. C. L. (2006). Carbono e nitrogênio em agregados de Latossolo submetido a diferentes sistemas de uso e manejo. Pesquisa Agropecuária Brasileira, 41(10), 1541–1550. https://doi.org/ 10.1590/S0100-204X2006001000012. De Figueirêdo, M. C. B., Kroeze, C., Potting, J., Da Silva Barros, V., De Aragão, F. A. S., Gondim, R. S., et al. (2013). The carbon footprint of exported Brazilian yellow melon. Journal of Cleaner Production, 47, 404–414. https://doi.org/10.1016/j. jclepro.2012.09.015. De Freitas, P. L., Blancaneaux, P., Gavinelli, E., Larré-Larrouy, M. C., & Feller, C. (2000). Nível e natureza do estoque orgânico de latossolos sob diferentes sistemas de uso e manejo. Pesquisa Agropecuária Brasileira, 35(1), 157–170. https://doi.org/10.1590/S0100-204X2000000100018. De Santos, T. de L., Nunes, A. B. A., Giongo, V., Barros, V. da S., & de Figueirêdo, M. C. B. (2018). Cleaner fruit production with green manure: The case of Brazilian melons. Journal of Cleaner Production, 181, 260–270. https://doi.org/10.1016/j. jclepro.2017.12.266. De Souza, H. N., de Graaff, J., & Pulleman, M. M. (2012). Strategies and economics of farming systems with coffee in the Atlantic Rainforest Biome. Agroforestry Systems, 84(2), 227–242. https://doi.org/10.1007/s10457-011-9452-x. Dias, A. C., & Arroja, L. (2012). Environmental impacts of eucalypt and maritime pine wood production in Portugal. Journal of Cleaner Production, 37, 368–376. https:// doi.org/10.1016/j.jclepro.2012.07.056. Donovan, G. H., Butry, D. T., Michael, Y. L., Prestemon, J. P., Liebhold, A. M., Gatziolis, D., et al. (2013). The relationship between trees and human health: Evidence from the spread of the emerald ash borer. American Journal of Preventine Medicine, 44(2), 139–145. https://doi.org/10.1016/j.amepre.2012.09.066. Dube, F., Couto, L., Silva, M. L., Leite, H. G., Garcia, R., & Araújo, G. A. A. (2002). A simulation model for evaluating technical and economic aspects of an industrial eucalyptus based agroforestry. Agroforestry Systems, 55(1), 73–80. https://doi. org/10.1023/A:1020240107370. Duchelle, A. M. Y. E., Cromberg, M., Gebara, M. F., Melo, T., Larson, A., Sills, E., et al. (2014). Linking Forest Tenure Reform, Environmental Compliance, and Incentives : Lessons from REDD + Initiatives in the Brazilian Amazon. World Development, 55, 63–67. https://doi.org/10.1016/j.worlddev.2013.01.014. Duffy, J. E., Godwin, C. M., & Cardinale, B. J. (2017). Biodiversity effects in the wild are common and as strong as key drivers of productivity. Nature, 549, 261–264. https://doi.org/10.1038/nature23886. Ecoinvent Centre, (2018). Swiss Centre for Life Cycle Inventories. Ecoinvent Database v 3.2, Dübendorf. Eldesouky, A., Mesias, F. J., Elghannam, A., & Escribano, M. (2018). Can Extensi Fi Cation Compensate Livestock Greenhouse Gas Emissions? A Study of the Carbon Footprint in Spanish Agroforestry Systems. Journal of Cleaner Production, 200, 28–38. https://doi.org/10.1016/j.jclepro.2018.07.279. Euler, M., Krishna, V., Schwarze, S., Siregar, H., & Qaim, M. (2017). Oil Palm Adoption, Household Welfare, and Nutrition Among Smallholder Farmers in Indonesia. World Development, 93, 219–235. https://doi.org/10.1016/ j.worlddev.2016.12.019.

G.C. Martinelli et al. / World Development 122 (2019) 339–348 FAO (2017) - Food and Agriculture Organization of the United Nations. The future Trends of food and and challenges. Available from: http://www.fao.org/3/ai6583e.pdf. (accessed on February 24, 2017). Finnveden, G., Hauschild, M. Z., Ekvall, T., Guinée, J., Heijungs, R., Hellweg, S., Koehler, A., Pennington, D., & Suh, S. (2009). Recent developments in Life Cycle Assessment. J. Environ. Manage., 91, 1–21. https://doi.org/10.1016/ j.jenvman.2009.06.018. Finnveden, G., & Moberg, Å. (2005). Environmental systems analysis tools–An overview. Journal of Cleaner Production, 13(12), 1165–1173. https://doi.org/ 10.1016/j.jclepro.2004.06.004. Flaviana, C. da S., Antonio, L. S., & Ana, H. M. (2018). Public policy on the family farming sector in Brazil: Towards a model of sustainable agriculture. African Journal of Agriculture Research, 13, 1719–1729. https://doi.org/10.5897/ AJAR2018.13322. FNDE (2014) – National Development Fund for Education. Available from: https:// www.fnde.gov.br/index.php/programas/pnae. (accessed on may 24, 2019). Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., et al. (2011). Solutions for a cultivated planet. Nature, 478, 337–342. https://doi. org/10.1038/nature10452. Gama-Rodrigues, E. F., Nair, P. K. R., Nair, V. D., Gama-Rodrigues, A. C., Baligar, V. C., & Machado, R. C. R. (2010). Carbon storage in soil size fractions under Two cacao agroforestry systems in Bahia. Brazil. Environmental Management, 45(2), 274–283. https://doi.org/10.1007/s00267-009-9420-7. Garrastazú, M. C., Mendonça, S. D., Horokoski, T. T., Cardoso, D. J., Rosot, M. A. D., Nimmo, E. R., et al. (2015). Carbon Sequestration and Riparian Zones : Assessing the Impacts of Changing Regulatory Practices in Southern Brazil. Land use policy, 42, 329–339. Godfray, H. C. J., Beddington, J. R., Crute, I. R., Haddad, L., Lawrence, D., Muir, J. F., et al. (2010). Food security: the challenge of feeding 9 billion people. Science, 327, 812–818. https://doi.org/10.1126/science.1185383. Goglio, P., Brankatschk, G., Knudsen, M. T., Williams, A. G., & Nemecek, T. (2018). Addressing Crop Interactions within Cropping Systems in LCA. International Journal of Life Cycle Assessment, 23(9), 1735–1743. Grechi, D. C.; Lobo, H. A. S.; Martins, P. C. S.; Lunas, J. R. S. Autogestão e controle de visitantes: Voucher Unificado em Bonito, MS. In: Philippi, J. R. A.; Ruschmann, D. V. M. (Ed). Gestão Ambiental e Sustentabilidade no Turismo. Coleção Ambiental. V.9. Barueri, SP: Editora Manole, 2010.p. 913–931. Gren, I. M., & Zeleke, A. A. (2016). Policy design for forest carbon sequestration: A review of the literature. Forest Policy Economics, 70, 128–136. https://doi.org/ 10.1016/j.forpol.2016.06.008. Guillaume, T., Kotowska, M. M., Hertel, D., Knohl, A., Krashevska, V., Murtilaksono, K., Scheu, S., & Kuzyakov, Y. (2018). Carbon costs and benefits of Indonesian rainforest conversion to plantations. Nature Communications, 9(2388). https:// doi.org/10.1038/s41467-018-04755-y. Guinée, J. B. (2002). Handbook on life cycle assessment operational guide to the ISO standards. The International Journal of Life Cycle Assessment., 7, 311–313. Henriksson, P. J. G., Guinée, J. B., Heijungs, R., de Koning, A., & Green, D. M. (2014). A protocol for horizontal averaging of unit process data—including estimates for uncertainty. The International Journal of Life Cycle Assessment, 19, 429–436. Ickowitz, A., Sills, E., & de Sassi, C. (2017). Estimating Smallholder Opportunity Costs of REDD+: A Pantropical Analysis from Households to Carbon and Back. World Development, 95, 15–26. https://doi.org/10.1016/j.worlddev.2017.02.022. ILCD, 2010. ILCD Handbook, International Reference Life Cycle Data System, General guide for Life Cycle Assessment - Detailed guidance, Constraints. doi:10.2788/ 38479. INCRA (2017) – Instituto Nacional de Colonização e Reforma Agrária. Incra nos Estados - Informações gerais sobre os assentamentos da Reforma Agrária. Available from: http://painel.incra.gov.br/sistemas/index.php (accessed on November 30, 2018). IBF (2017) – Instituto Brasileiro de Florestas. Utilização de tubetes na produção de mudas. Available from: https://www.ibflorestas.org.br/conteudo/blog/1103utilizacao-detubetes-na-producao-de-mudas.html. (accessed on November 01, 2017). IBGE (2010) – Instituto Brasileiro de Geografia Estatística. População residente, por situação do domicílio e sexo, segundo as Grandes Regiões e as Unidades da Federação – 2010. Available from: https://censo2010.ibge.gov.br/sinopse/index. php?dados=11&uf=00. (accessed on November 01, 2017). IPCC (2006). Guidelines for national greenhouse gas inventories 2006: Agriculture, forestry and other land use. v. 4. chapter 4. Foresty land. IPCC (2013). Climate Change: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. [s.l.] Cambridge University Press, New York, 2013. ISO (2006). International Standart Organization. 14040:2006 (E). Environmental Management e Life Cycle Assessment e Principles and Framework. International Organization of Standardization, Geneva, Switzerland. ISO (2006). International Standart Organization. 14044:2006 Environmental management - Life cycle assessment - Requirements and guidelines. Environmental management - Life cycle assessment - Principles and framework, p. 46. Iwata, B. D., Leite, L. F. C., Araujo, A. S. F., Nunes, L. A. P. L., Gehring, C., & Campos, L. P. (2012). Agroforestry systems and its effects on chemical attributes of an Ultisol in the ‘‘Cerrado” of Piaui State, Brazil. Revista Brasileira Engenharia Agrícola e Ambiental, 16, 730–738. https://doi.org/10.1590/S1415-43662012000700005. Jagoret, P., Kwesseu, J., Messie, C., Michel-Dounias, I., & Malézieux, E. (2014). Farmers’ assessment of the use value of agrobiodiversity in complex cocoa


agroforestry systems in central Cameroon. Agroforestry Systems, 88, 983–1000. https://doi.org/10.1007/s10457-014-9698-1. Jindal, R., Kerr, J. M., & Carter, S. (2012). Reducing Poverty Through Carbon Forestry? Impacts of the N’hambita Community Carbon Project in Mozambique. World Development, 40(10), 2123–2135. https://doi.org/10.1016/j.worlddev.2012.05.003. Jose, S. (2009). Agroforestry for ecosystem services and environmental benefits: An overview. Agroforestry Systems, 76(1), 1–10. https://doi.org/10.1007/s10457009-9229-7. Jung, S., Rasmussen, L. V., Watkins, C., Newton, P., & Agrawal, A. (2017). Brazil’s National Environmental Registry of Rural properties: Implications for livelihoods. Ecological Economics, 136, 53–61. https://doi.org/10.1016/j. ecolecon.2017.02.004. Kansanga, M. M., & Luginaah, I. (2019). Agrarian livelihoods under siege: Carbon forestry, tenure constraints and the rise of capitalist forest enclosures in Ghana. World Development, 113, 131–142. https://doi.org/10.1016/ j.worlddev.2018.09.002. Ketterings, Q. M., Coe, R., Van Noordwijk, M., Ambagau, Y., & Palm, C. A. (2001). Reducing uncertain in the use of allometric biomass equation for predciting above-ground tree biomass in mixed secondary forests. Forest Ecology Management., 146, 199–209. https://doi.org/10.1016/S0378-1127(00)00460-6. Kilian, B., Hettinga, J., Jiménez, G. A., Molina, S., & White, A. (2012). Case study on Dole’s carbon-neutral fruits. Journal Business Research, 65(12), 1800–1810. https://doi.org/10.1016/j.jbusres.2011.10.040. Kim, D. G., Kirschbaum, M. U. F., & Beedy, T. L. (2016). Carbon sequestration and net emissions of CH4and N2O under agroforestry: Synthesizing available data and suggestions for future studies. Agriculture Ecosystem Environment, 226(16), 65–78. https://doi.org/10.1016/j.agee.2016.04.011. Leakey, R. (1996). Definition of agroforestry revisited. Agroforestry Today, 8(1), 5–7. https://doi.org/10.1016/B978-0-12-805356-0.00001-5. Lemaire, G., Franzluebbers, A., Carvalho, P. C. de F., & Dedieu, B. (2014). Integrated crop–livestock systems: Strategies to achieve synergy between agricultural production and environmental quality. Agriculture Ecosystem Environment, 190, 4–8. https://doi.org/10.1016/j.agee.2013.08.009. Lobell, D. B., Schlenker, W., & Costa-Roberts, J. (2011). Climate trends and global crop production since 1980. Science, 333, 616–620. Lobell, D. B., & Field, C. B. (2007). Global scale climate–crop yield relationships and the impacts of recent warming. Environment Research Lett, 2 014002, 7. https:// doi.org/10.1088/1748-9326/2/1/014002. Macedo, A. C. (1993). Produção de mudas em viveiros agroflorestais, espécies nativas. São Paulo: Governo do Estado de São Paulo; Secretaria do Meio Ambiente; Fundação Florestal, 1993. 21 p. MAPA (2017). Ministério da Agricultura, Pecuária e abastecimento. Objetivos, Metas e Diretrizes. Available from: http://www.agricultura.gov.br/ assuntos/sustentabilidade/plano-abc/objetivos-e-diretrizes. (accessed on February 14, 2017). Martinelli, G. do C., Schlindwein, M. M., Padovan, M. P., & Gimenes, R. M. T. (2019). Decreasing uncertainties and reversing paradigms on the economic performance of agroforestry systems in Brazil. Land Use Policy, 80, 274–286. https://doi.org/10.1016/j.landusepol.2018.09.019. Matthews, R. B., van Noordwijk, M., Lambin, E., Meyfroidt, P., Gupta, J., Verchot, L., et al. (2014). Implementing REDD + (Reducing Emissions from Deforestation and Degradation): Evidence on Governance, Evaluation and Impacts from the REDD-ALERT Project. Mitigation and Adaptation Strategies for Global Change, 19 (6), 907–925. https://doi.org/10.1007/s11027-014-9578-z. Mbow, C., Smith, P., Skole, D., Duguma, L., & Bustamante, M. (2014). Achieving mitigation and adaptation to climate change through sustainable agroforestry practices in Africa. Current Opinion in Environmental Sustainability, 6, 8–17. https://doi.org/10.1016/j.cosust.2013.09.002. Medina, G., Almeida, C., Novaes, E., Godar, J., & Pokorny, B. (2015). Development conditions for family farming: Lessons from brazil. World Development, 74, 386–396. https://doi.org/10.1016/j.worlddev.2015.05.023. MMA (2018). Ministério do Meio Ambiente. O que é REDD+. Available from: http:// redd.mma.gov.br/pt/pub-apresentacoes/item/82-o-que-e-redd. (accessed on January 19, 2018). Mokany, K., Raison, J. R., & Prokushkin, A. S. (2006). Critical analysis of root: shoot ratios in terrestrial biomes. Global Change Biology, 12, 84–96. Monroe, P. H. M., Gama-Rodrigues, E. F., Gama-Rodrigues, A. C., & Marques, J. R. B. (2016). Soil carbon stocks and origin under different cacao agroforestry systems in Southern Bahia, Brazil. Agriculture Ecosystem Environment, 221(1), 99–108. https://doi.org/10.1016/j.agee.2016.01.022. Mori-Clement, Y. (2019). Impacts of CDM projects on sustainable development: Improving living standards across Brazilian municipalities? World Development, 113, 222–236. https://doi.org/10.1016/j.worlddev.2018.06.014. Murdiyarso, D., Brockhaus, M., Sunderlin, W. D., & Verchot, L. (2012). Some lessons learned from the first generation of REDD+ activities. Current Opinion in Environmental Sustainability, 4(6), 678–685. https://doi.org/10.1016/ j.cosust.2012.10.014. Nair, P. K. R. (1993). An introduction to agroforestry. An Introduction to Agroforestry. https://doi.org/10.1016/0378-1127(95)90008-X. Nair, P. K. R., Kumar, B. M., & Nair, V. D. (2009). Agroforestry as a strategy for carbon sequestration. Journal of Plant Nutrition Soil Science, 172(1), 10–23. https://doi. org/10.1002/jpln.200800030. Nair, P. K. R., Nair, V. D., Kumar, B. M., & Showalter, J. M. (2010). Carbon sequestration in agroforestry systems. Advances in Agronomy, 108, 237–307. https://doi.org/10.1016/S0065-2113(10)08005-3.


G.C. Martinelli et al. / World Development 122 (2019) 339–348

Nascimento, J. S. Estudos multidisciplinares em arranjos agroflorestais biodiversos na região Sudoeste de Mato Grosso do Sul. (2016). 128 p. Dissertação (Mestrado em agronegócios) – Universidade Federal da Grande Dourados, Dourados. 2016. Available from: http://files.ufgd.edu.br/arquivos/arquivos/78/MESTRADOAGRONEGOCIOS/ESTUDOS%20MULTICIPLINARES%20EM%20ARRANJOS% 20AGROFLORESTAIS%20BIODIVERSOS%20NA%20REGI%C3%83O%20SUDESTE% 20DE%20MATO%20GROSSO%20DO%20SUL.pdf. (accessed on March 6, 2017). Nemecek, T., Dubois, D., Huguenin-Elie, O., & Gaillard, G. (2011). Life cycle assessment of Swiss farming systems: I. Integrated and organic farming. Agriculture Systems, 104(3), 217–232. https://doi.org/10.1016/j. agsy.2010.10.002. Nemecek, T., Kägi, T. (2007). Life Cycle Inventories of Agricultural Production Systems. Available from: https://db.ecoinvent.org/reports/15_Agriculture.pdf. (accessed on March 6, 2017). Ness, B., Urbel-Piirsalu, E., Anderberg, S., & Olsson, L. (2007). Categorising tools for sustainability assessment. Ecological Economics., 60(3), 498–508. https://doi. org/10.1016/j.ecolecon.2006.07.023. Nicholson, S. E. (2014). Spatial teleconnections in African rainfall: A comparison of 19th and 20th century patterns. The Holocene, 24, 1840–1848. https://doi.org/ 10.1177/0959683614551230. Nunoo, I., & Owusu, V. (2015). Comparative analysis on financial viability of cocoa agroforestry systems in Ghana. Environment Development Sustainability, 19(1), 83–98. https://doi.org/10.1007/s10668-015-9733-z. Oliveira, M. C., Ogata, R. S., Andrade, G. A., Santos, D. S., Souza, R. M., Guimarães, T. G., et al. (2016). Manual de viveiro e produção de mudas: espécies arbóreas nativas do Cerrado. Editora Rede de Sementes do Cerrado, 124. Paolotti, L., Boggia, A., Castellini, C., Rocchi, L., & Rosati, A. (2016). Combining livestock and tree crops to improve sustainability in agriculture: a case study using the life cycle assessment (LCA) approach. Journal of Cleaner Production, 131, 351–363. https://doi.org/10.1016/j.jclepro.2016.05.024. Ramos, H. M. N., Vasconcelos, S. S., Kato, O. R., & Castellani, D. C. (2018). Above- and belowground carbon stocks of two organic, agroforestry-based oil palm production systems in eastern Amazonia. Agroforestry Systems, 92(2), 221–227. https://doi.org/10.1007/s10457-017-0131-4. Rasmussen, L. V., Watkins, C., & Agrawal, A. (2017). Forest contributions to livelihoods in changing agriculture-forest landscapes. Forest Policy Economics, 84, 1–8. https://doi.org/10.1016/j.forpol.2017.04.010. Raucci, G. S., Moreira, C. S., Alves, P. A., Mello, F. F. C., Frazão, L. D. A., Cerri, C. E. P., et al. (2015). Greenhouse gas assessment of Brazilian soybean production: A case study of Mato Grosso State. Journal of Cleaner Production, 96(1), 418–425. https://doi.org/10.1016/j.jclepro.2014.02.064. Reed, J., van Vianen, J., Foli, S., Clendenning, J., Yang, K., MacDonald, M., et al. (2017). Trees for life: The ecosystem service contribution of trees to food production and livelihoods in the tropics. Forest Policy Economics, 84, 62–71. https://doi.org/ 10.1016/j.forpol.2017.01.012. Reynolds, T. W. (2012). Institutional determinants of success among forestry-based carbon sequestration projects in sub-saharan Africa. World Development, 40(3), 542–554. https://doi.org/10.1016/j.worlddev.2011.09.001. Rocha, G. P., Fernandes, L. A., Cabacinha, C. D., Lopes, I. D. P., Ribeiro, J. M., Frazão, L. A., et al. (2014). Characterization and carbon storage of agroforestry systems in brazilian savannas of Minas Gerais, Brazil (In Portuguese). Ciência Rural, 44, 1197–1203. https://doi.org/10.1590/0103-8478cr20130804. Roscoe, R., Buurman, P., Velthorst, E. J., & Vasconcellos, C. A. (2001). Soil organic matter dynamics in density and particle size fractions as revealed by the 13Cr12C isotopic ratio in a Cerrado’soxisol. Geoderma, 104 Zˇ2001, 185–202. Roy, P., Nei, D., Orikasa, T., Xu, Q., Okadome, H., Nakamura, N., et al. (2009). A review of life cycle assessment (LCA) on some food products. Journal of food engineering., 90(1), 1–10. https://doi.org/10.1016/j.jfoodeng.2008.06.016. Ruviaro, C. F., Gianezini, M., Brandão, F. S., Winck, C. A., & Dewes, H. (2012). Life cycle assessment in Brazilian agriculture facing worldwide trends. Journal of Cleaner Production, 28, 9–24. https://doi.org/10.1016/j.jclepro.2011.10.015. Sala, S., Farioli, F., & Zamagni, A. (2013). Life cycle sustainability assessment in the context of sustainability science progress (part 2). The International Journal of Life Cycle Assessment, 18, 1686–1697. https://doi.org/10.1007/s11367-0120509-5. Salton, J. C., Mercante, F. M., Tomazi, M., Zanatta, J. A., Concenço, G., Silva, W. M., et al. (2014). Integrated crop-livestock system in tropical Brazil: Toward a sustainable production system. Agriculture Ecosystem Environment, 190, 70–79. https://doi.org/10.1016/j.agee.2013.09.023. Schaefer, F., & Blanke, M. (2014). Opportunities and challenges of carbon footprint, climate or CO2 labelling for horticultural products. Erwerbs-Obstbau, 56(2), 73–80. https://doi.org/10.1007/s10341-014-0206-6.

Schau, E. M., & Fet, A. M. (2008). LCA studies of food products as background for environmental product declarations. The International Journal of Life Cycle Assessment, 13(3), 255–264. https://doi.org/10.1065/lca2007.12.372. Scherr, S. J. (1995). Economic factors in farmer adoption of agroforestry: Patterns observed in Western Kenya. World Development, 23(5), 787–804. https://doi. org/10.1016/0305-750X(95)00005-W. SEEG (2017) - Sistema de Estimativas de Emissões de Gases de Efeito Estufa. Emissões do Brasil sobem 9% em 2016, 2017. Available from: http://www. observatoriodoclima.eco.br/wpcontent/uploads/2017/10/seeg2017presskit_ FINAL.pdf. (accesse March 6, 2018). Shikuku, K. M., Winowiecki, L., Twyman, J., Eitzinger, A., Perez, J. G., Mwongera, C., et al. (2017). Smallholder farmers ’ attitudes and determinants of adaptation to climate risks in East Africa. Climate Risk Management, 16, 234–245. Simelton, E. S., Catacutan, D. C., Dao, T. C., Dam, B. V., & Le, T. D. (2017). Factors constraining and enabling agroforestry adoption in Viet Nam: A multi-level policy analysis. Agroforestry Systems, 91(1), 51–67. https://doi.org/10.1007/ s10457-016-9906-2. Smith, P., M. Bustamante, Ahammad, H., Clark, H., Dong, H., Elsiddig, E.A., Haberl, H., Harper, R., House, J., Jafari, M., Masera, O., C. Mbow, N. H. Ravindranath, C. W. Rice, C. Robledo Abad, A. Romanovskaya, F. Sperling, Tubiello, F. (2014). Agriculture, Forestry and Other Land Use (AFOLU). Clim. Chang. Mitig. Clim. Chang. Contrib. Work. Gr. III to Fifth Assess. Rep. Intergov. Panel Clim. Chang. [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, 811–922. doi:10.1016/j.phrs.2011.03.002. Sonne, E. (2006). Greenhouse gas emissions from forestry operations: A life cycle assessment. Journal of Environmental Sciences, 35(4), 1439–1450. https://doi. org/10.2134/jeq2005.0159. Suminah, N., Sulistyantara, B., & Budiarti, T. (2017). Analysis of green space characteristic effect to the comfort microclimate in the simple flats in Jakarta. IOP Conf. Ser.: Earth Environ. Sci., 91, 012017. https://doi.org/10.1088/17551315/91/1/012017. Sunderlin, W. D., Larson, A. M., Duchelle, A. E., Resosudarmo, I. A. P., Huynh, T. B., Awono, A., et al. (2014). How are REDD+ proponents addressing tenure problems? evidence from brazil, cameroon, tanzania, indonesia, and vietnam. World Development, 55, 37–52. https://doi.org/10.1016/j.worlddev.2013.01.013. Thangata, P. H., & Hildebrand, P. E. (2012). Carbon stock and sequestration potential of agroforestry systems in smallholder agroecosystems of sub-Saharan Africa: Mechanisms for ‘‘reducing emissions from deforestation and forest degradation” (REDD+). Agriculture Ecosystem Environment, 158, 172–183. https://doi.org/10.1016/j.agee.2012.06.007. Tilman, D., Hill, J., & Lehman, C. (2006). Carbon-negative biofuels from low-input high-diversity grassland biomass. Science, 314(5805), 1598–1600. https://doi. org/10.1126/science.1133306. Torralba, M., Fagerholm, N., Burgess, P. J., Moreno, G., & Plieninger, T. (2016). Do European agroforestry systems enhance biodiversity and ecosystem services? A meta-analysis. Agriculture Ecosystem Environment, 230, 150–161. https://doi. org/10.1016/j.agee.2016.06.002. Utomo, B., Prawoto, A. A., Bonnet, S., Bangviwat, A., & Gheewala, S. H. (2016). Environmental performance of cocoa production from monoculture and agroforestry systems in Indonesia. Journal of Cleaner Production, 134(Part B), 583–591. https://doi.org/10.1016/j.jclepro.2015.08.102. Vinyes, E., Gasol, C. M., & Asin, L. (2015). Life Cycle Assessment of multiyear peach production. Journal of Cleaner Production, 104, 68–79. https://doi.org/10.1016/j. jclepro.2015.05.041. Wittman, H., & Blesh, J. (2017). Food sovereignty and fome zero: Connecting public food procurement programmes to sustainable rural development in Brazil. Journal Agrarian Change, 17(1), 81–105. https://doi.org/10.1111/joac.12131. Wood, S. A., Jina, A. S., Jain, M., Kristjanson, P., & Defries, R. S. (2014). Smallholder farmer cropping decisions related to climate variability across multiple regions. Global Environment Change, 25, 163–172. World Bank (2010). Brazil - Formoso River Integrated Watershed Management and Protection Project: procurement plan. Available from: http://documents.worldbank.org/curated/pt/400031468232503705/BrasilManejo-Integrado-da-Bacia-Hidrogr%C3%A1fica-do-Rio-Formoso-BonitoMS-GEF-Planejamento-Anual-de-Aquisi%C3%A7%C3%B5es. (accessed on December 10, 2018). ZEE/MS (2009) - Zoneamento ecológico-econômico do estado de Mato Grosso do Sul. LEI N° 3.839, de 28 de dezembro de 2009. Available from: http://193.43.36. 109/docs/pdf/bra116233AnnexI.pdf. (accessed on December 10, 2017).