CC

ETCa

b

c

ARRAA

KBCCTTF

1

he

(

0h

Agriculture, Ecosystems and Environment 173 (2013) 46– 57

Contents lists available at SciVerse ScienceDirect

Agriculture, Ecosystems and Environment

jo ur nal home p age: www.elsev ier .com/ locate /agee

arbon stocks and cocoa yields in agroforestry systems ofentral America

duardo Somarribaa,∗, Rolando Cerdaa, Luis Orozcoa, Miguel Cifuentesa, Héctor Dávilaa,ania Espina, Henry Mavisoya, Guadalupe Ávilaa, Estefany Alvaradoa, Verónica Povedaa,arlos Astorgaa, Eduardo Saya, Olivier Deheuvelsb,c

CATIE, DID, 7170, Cartago, Turrialba 30501, Costa RicaCIRAD, UMR System, F-34070 Montpellier, FranceCATIE, PAAS, CR-7170 Turrialba, Costa Rica

a r t i c l e i n f o

rticle history:eceived 13 August 2012eceived in revised form 3 April 2013ccepted 15 April 2013vailable online 16 May 2013

eywords:iomassertificationlimate changeimberrade-offorest

a b s t r a c t

The cocoa tree (Theobroma cacao L.) is cultivated typically in agroforestry systems in close associationwith a rich list of tree species and other useful plants on the same plot. Cocoa based agroforestry systemsare credited for stocking significant amounts of carbon and hence have the potential to mitigate climatechange. Since cocoa yields decrease non-linearly with increasing shade, a need is to design optimal cocoaagroforestry systems with high yields and high carbon stocks. We estimated the carbon stocked in anetwork of 229 permanent sample plots in cacao-based agroforestry systems and natural forests in fiveCentral American countries. Carbon stocks were fractioned by both system compartments (aboveground,roots, soil, litter, dead wood – fine and coarse, and total) and tree use/form (cocoa, timber, fruit, bananas,shade and ornamentals, and palms). Cocoa plantations were assigned to a five-class typology and testedfor independence with growing region using contingency analysis. Most Central American cocoa plan-tations had mixed or productive shade canopies. Only 4% of cocoa plantations were full sun or rustic(cocoa under thinned natural forest). Cocoa tree density was low (548 ± 192 trees ha−1). Total carbon(soil + biomass + dead biomass) was 117 ± 47 Mg ha−1, with 51 Mg ha−1 in the soil and 49 Mg ha−1 (42%of total carbon) in aboveground biomass (cocoa and canopy trees). Cocoa trees accumulated 9 Mg C ha−1

(18% of carbon in aboveground biomass). Timber and fruit trees stored 65% of aboveground carbon. Theannual rate of accumulation of carbon in aboveground biomass ranged between 1.3 and 2.6 Mg C ha−1 y−1.Trade-offs between carbon levels and yields were explored qualitatively using functional relationshipsdocumented in the scientific and technical literature, and expert knowledge. We argue that it is possibleto design cocoa-based AFS with good yields (cocoa and shade canopy) and high carbon stock levels. Thebotanical composition of the shade canopy provides a large set of morphological and functional traitsthat can be used to optimize shade canopy design. Our results offer Central American cocoa producers a

rigorous estimate of carbon stocks in their cocoa plantations. This knowledge may help them to certifyand sell their cocoa, timber, fruits and other goods to niche markets with good prices. Our results willalso assist governments and the private sector in (i) designing better legal, institutional and policy frame-works, local and national, promoting an agriculture with trees and (ii) contributing to the developmentof the national monitoring, reporting and verification systems required by the international community

men

to access funding and pay

. Introduction

The atmospheric concentration of CO2 and other green-ouse gases increased by 70% between 1970 and 2004 (Solomont al., 2007). Carbon accumulates in the atmosphere at a rate

∗ Corresponding author. Tel.: +506 25 58 25 93; fax: +506 25 56 30 18.E-mail addresses: eduardo.somarriba56@gmail.com, esomarri@catie.ac.cr

E. Somarriba).

167-8809/$ – see front matter © 2013 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.agee.2013.04.013

t for ecosystem services.© 2013 Elsevier B.V. All rights reserved.

of 3.5 × 109 tons a year, due mostly to fossil fuel consumptionand the conversion of tropical forests into land for agricultureand pasture (Paustian et al., 2000). Industry and energy sectors(transport, industrial processes, electricity, and heat generation)are responsible for approximately 65% of all emissions. Landuse change and agriculture are responsible for 18% and 14%,

respectively (WRI, 2005). There are incentives to emit less andcapture more greenhouse gases, such as the Joint Implementationand Clean Development Mechanisms, REDD+ (Reduced Emissionsfrom Deforestation and Forest Degradation), and voluntary carbon

E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57 47

eas wh

mcr

smsrbmA2iaWcscpl2do2

(2atdulaeh

2

2

ti

Fig. 1. Name and location of the cocoa growing ar

arkets (Miles and Kapos, 2008; FAO, 2010). Cocoa (Theobromaacao L.) is cultivated in agroforestry systems, i.e. together with aich list of tree species and other useful plants on the same plot.

Cocoa based agroforestry systems are credited for stockingignificant amounts of carbon and hence have the potential toitigate climate change. Carbon stocks in shaded agroforestry

ystems with perennial crops—such as coffee (Coffea arabica L.),ubber (Hevea brasiliensis (HBK) Muell.-Arg.), and cocoa—may varyetween 12 and 228 Mg ha−1 and could help to mitigate cli-ate change (Winjum et al., 1992; Schroeder, 1994; Dixon, 1995;lbrecht and Kandji, 2003; Montagnini and Nair, 2004; Nair et al.,009). In Central America, 24,000 ha of cocoa are grown without

norganic inputs or pesticides, plantations are small (0.25–3.0 ha)nd yield only 250 kg dry cocoa ha−1 y−1 (Deheuvels et al., 2012;helan et al., 2007; Somarriba et al., 2009). Central American

ocoa agroforestry systems have high plant species richness andtructural complexity (Deheuvels et al., 2012), product diversifi-ation for self-consumption and sale (Dalquist et al., 2007), andermanent soil cover and large amounts of organic matter. These

ater conditions promote soil and water conservation (Adejumo,005; Verchot et al., 2007; Binternagel et al., 2010). Taxonomicallyiverse shaded cocoa plantations share many features usually rec-mmended to adapt farming to climate change (Smit and Skinner,002).

Cocoa yields decrease non-linearly with increasing shadeZuidema et al., 2005; Stephan-Dewenter et al., 2007; Wade et al.,010; Gockowski and Sonwa, 2011), and shade in turn increases –lbeit not deterministically – with carbon stock level. This raiseshe question whether optimal cocoa agroforestry systems can beesigned that simultaneously produce high yields (cocoa and prod-cts from the shade canopy species) and retain high carbon stock

evels. We quantified carbon stocks in Central American cocoagroforestry systems and local forests patches, and qualitativelyxplored the trade-offs of maintaining both high carbon levels andigh crop yields.

. Materials and methods

.1. Definitions, terms and concepts

We use the following definitions: A cocoa growing area is theerritory where farms having cocoa plantations are located. A farms the land unit (in a single block or not) managed by the family

ere our study was conducted in Central America.

or enterprise, which typically includes several cropping systems,one of which may be cocoa. A cocoa plantation is a single block ofland, of variable size and form, dedicated to cultivating cocoa withor without other associated plants. A plot is a 50 m × 20 m repre-sentative sample area within the cocoa plantation. A plot may bedivided into sub-plots. A cocoa plantation has two components:cocoa and shade canopy (or simply, the canopy). The cocoa compo-nent includes all cocoa plants. The canopy component includes allnon-cocoa plants taller than cocoa trees. A cocoa plantation undershade trees is a cocoa based agroforestry system (cocoa AFS). Asyoung cocoa trees grow in height and develop their crowns, upperleaves shade those underneath, producing self-shading. The site isthe set of biophysical conditions (soil, climate, biology and localculture) that determines growth and yield of cocoa and canopycomponents.

2.2. Description of cocoa plantations and sample plots

We sampled 229 cocoa plantations in six cocoa growing areasin five Central American countries (Fig. 1). In each cocoa growingarea, we established a network of permanent sample plots locatedin 36–40 cocoa-based AFS and in 3–4 mature or secondary naturalforest patches, as control. The natural forest present in the areaat the time of sampling may be a degraded version of the originalnative primary forest at the site. Cocoa-based AFS in each growingarea were selected in order to sample as much variability aspossible in terms of farm typology and biophysical conditions.Further details of the criteria used to develop the research networkare given in Deheuvels et al. (2012) and Deheuvels (2011).

2.3. Field measurements and data analysis

Tree biomass was estimated using locally derived allometricequations (Table 1).

The carbon content was 0.5 of dry biomass (IPCC, 2003b). Carbonper plot was fractioned into: (i) system’s compartments [above-ground, litter (leaves and fine branches ≤2 cm diameter), coarse(>10 cm) and fine (>2 and <10 cm) dead wood, coarse (>2 mm indiameter) and fine roots (<2 mm in diameter), soil, total] and (ii)

plant type: cocoa, timber trees, fruit and medicinal trees, othershade and ornamental trees, bananas, and palm trees. We measuredcarbon in soil organic matter, litter, soil bulk density, fine roots den-sity, and fine dead wood in composite samples of 10 sub-samples

48 E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57

Table 1Allometric equations used to estimate carbon in aboveground biomass and coarse roots in Central American cocoa plantations.

Species or plant type Equation or formula Source

Theobroma cacao Log B = (−1.684 + 2.158 * Log(d30) + 0.892 * Log(alt)) CATIE (unpublished)Cordia alliodora Log B = (−0.94 + 1.32 * Log(dbh) + 1.14 * Log(alt)) CATIE (unpublished)Bactris gasipaes B = 0.74 * alt2 Szott et al. (1993)Other timber trees B = (21.3–6.95 * (dbh) + 0.74 * (dbh2)) Brown and Iverson (1992)Other fruit trees Log B = (−1.11 + 2.64 * Log(dbh)) CATIE (unpublished)Other palms B = 4.5 + 7.7 * alt Frangi and Lugo (1985)Coarse roots B = exp[−1.0587 + 0.8836 * ln(AB)] Cairns et al. (1997)

B (1.3 m

ptWwFlbm

fcbogcSobcw

(U(o(ie

Musacea 1.5 kg/m height

: biomass (kg); Log: logarithm base 10; dbh: trunk diameter (cm) at breast height

er plot. Coarse dead wood was measured on two perpendicularransects (50 and 20 m, respectively) traced on the sample plot (Van

agner, 1968; IPCC, 2003b). Carbon content in soil, fine roots, deadood and litter were determined by combustion (Thermoffinigan,

lash EA 1112 series; MacDiken, 1997). The annual rate of accumu-ation of aboveground carbon (cocoa and canopy) was estimatedoth by using plantation age as indicated by farmers, and by re-easuring ten sample plots in Waslala, Nicaragua.A multivariate Principal Component Analysis (PCA) was per-

ormed on our 229 cocoa plantations sample for biomass, carbonontent and accumulation rate for each plant type (cocoa, tim-er trees, fruit and medicinal trees, palm trees, other shade andrnamental trees, and Musacea) and in each compartment (above-round: aerial, litter, coarse and fine dead wood; belowground:oarse and fine roots, soil). This PCA was performed with the Info-tat software (Di Rienzo et al., 2012) to give a descriptive overviewf the global dataset and to identify correlations to be testedetween variables and between countries. Differences betweenocoa-growing areas in terms of carbon stocks were then testedith ANOVA and LSD Fisher tests with a 95% confidence interval.

We calculated the gross monetary value of current carbon stockstotal and aboveground) and accumulation rates using a price ofS$ 5 per ton of CO2 (CO2 = C * 3.67) in the voluntary markets

Seeberg-Elverfeldt et al., 2009; Hamilton et al., 2010). Although

ther authors propose US$ 1.2 per CO2 ton in voluntary marketsGockowski and Sonwa, 2011), average agroforestry credit pricesncreased from US$ 5 to 10 between 2009 and 2010 (Peters-Stanleyt al., 2011).

05

1015202530354045505560657075808590

0,2 0,4 0, 6 0, 8 1, 0 1,2 1, 4 1, 6 1, 8 2,0

Plan

t spe

cies

rich

ness

Sampled

Fig. 2. Rarefaction curves for shade canopy plant species in 22

Tanaka and Yamaguchi (1972)

); d30: trunk diameter at 30 cm; alt: total height (m); AB: aboveground biomass.

Central American cocoa plantations were classified accordingto a five-class, modified version of the typology proposed by Riceand Greenberg (2000). Our cocoa plantation typology included:(1) cocoa without shade; (2) cocoa with specialized shade (e.g.shade from service legume trees such as various species of Gliri-cidia, Inga, Leucaena, Erythrina, Albizia); (3) cocoa with productiveshade (e.g. cocoa with a mono-specific canopy of coconut, fruit,banana, or timber species); (4) cocoa with mixed shade; and (5)cocoa with rustic shade (cocoa planted under thinned natural for-est), known as “cabrucas” in Brazil (Sambuichi, 2002). Because, ingeneral, shade levels increase with decreasing crop managementintensity, other authors have suggested using canopy cover as anindicator of cocoa management intensity (Stephan-Dewenter et al.,2007; Clough et al., 2011; Deheuvels, 2011). We tested the hypoth-esis that cocoa farm typologies were similar in all cocoa growingareas by contingency analysis (X2 5%).

3. Results

3.1. Soil and site characteristics of the sample

Cocoa plots were located in rainy (1700–4000 mm y−1), warmareas (24–25 ◦C), at <500 m altitude, in valleys (flat terrain) and hills

(hillsides), on inceptisol (valleys) and ultisol (hills) soils. On aver-age, cocoa soils had medium to low fertility, pH between 5.0 and6.5, carbon between 2 and 7%, little P and normal to low amounts ofCa and K. Cocoa plantations were 1.6 ha (0.1–9.0) in size, used local

2, 2 2, 4 2, 6 2,8 3, 0 3, 2 3, 4 3, 6 3, 8 4, 0

area (ha)

PANA MA

NICARAGUACOSTA RICA

HONDURAS

GUATEMALACost a Sur

GUATEMALAAlta Verapaz

9 cocoa-based agroforestry systems in Central America.

E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57 49

Fig. 3. Principal Component Analysis conducted on 229 cocoa-based agroforestry systems in Panama, Costa Rica, Nicaragua, Honduras and Guatemala. The quality of thecorrelations for biomass, carbon content and accumulation rate in each plant type (cocoa, timber trees, fruit and medicinal trees, palm trees, other shade and ornamental trees,and Musacea) and in each compartment (aboveground: aerial, litter, coarse and fine dead wood; belowground: coarse and fine roots, soil) is shown on the first 2 principalcomponents (58.2% of total variability); age: number of years since creation of the cocoa plantation; area: surface of the cocoa plantation; CCoarseRoots: carbon in coarseroots; CCoarseWood: carbon in coarse dead wood; Ccocoa: carbon in cocoa trees; CFineRoots: carbon in fine roots; CFineWood: carbon in fine dead wood; CFruitMed: carbonin fruit and medicinal trees; CLeafLitter: carbon in leaf litter; Cmusa: carbon in Musacea; Cothers: carbon in other only-shade trees; Cpalm: carbon in Palmacea; Csoil: carboni Densd nsity

a

hf

3

atwCebopKLcs(

3

stAcss

pdtt

tf

n soil; CTimber: carbon in timer trees; CocoaDens: density of cocoa trees; FruitMedensity of other only-shade trees; PalmDens: density of palm trees; TimberDens: deerial biomass.

ybrid cocoa varieties, and were between 18 and 30 years old; aew plantations were >40 years old.

.2. Botanical composition of the sample

Rarefaction curves of canopy species, using 1000 m2 plots and total of 3.6 ha inventoried per cocoa growing region showedhat these cocoa plantations contained between 40 and 80 species,ith noticeable differences between cocoa growing areas (Fig. 2).anopy species were either spontaneous or planted, managed andxploited for timber, fruit or firewood, and may include several tim-er species—such as Cordia alliodora (Ruiz and Pavón) Oken, Cedreladorata L., Terminalia oblonga Exell); palm species (Iriartea spp., inarticular), and several fruit tree species, such as Bactris gasipaesunth, Cocos nucifera L., Nephelium lappaceum L., Mangifera indica., Pouteria sapota (Jacq.) H.E. Moore and Stearn, and Persea ameri-ana Mill. The most commonly used legume species were Gliricidiaepium (Jacq.) Kunth ex. Walp, Inga spp. and Leucaena leucocephalaLam.) de Wil (unpublished data).

.3. Overview of the correlations in the sample

The first two axes of the PCA contain 58.2% of the variation in theample (Fig. 3). Cocoa producing regions separated into three dis-inct groups: in group 1, cocoa plantations in Nicaragua, Guatemalalta Verapaz and Honduras are associated with steep slopes, highocoa planting density, high carbon stock in cocoa trees, low carbontock in shade canopy plants, low species richness, and low carbontock in soil and leaf litter.

In group 2, Panama and Costa Rica are associated with cocoalantations at low altitude, high plant species richness, high abun-ance of bananas, palm, fruit and medicinal trees. Cocoa AFS in

hese two countries tend to stock more carbon in banana, palm andimber trees, and much less in cocoa trees.

The Guatemala Costa Sur region clearly differentiated as a dis-inct group 3, with old cocoa plantation, with high carbon stocks inruit, medicinal and shade-only trees, and in soil and leaf litter.

: density of fruit and medicinal trees; MusaDens: density of Musacea; OthersDens:of timber trees; TotalCacuRate: total carbon accumulation rate; TotalBiomass: total

3.4. Plant density and cocoa plantation typology

The average plant density in the plots was 866 plants ha−1,including 545 cocoa trees ha−1, 117 banana stems ha−1,104 timber trees ha−1, 52 fruit trees ha−1, and 47 palms and othertrees ha−1 (Table 2). Bananas (90%) and plantains (10%) were fre-quent in Nicaragua, Costa Rica and Panama (150–240 stems ha−1),but rare in Guatemala and Honduras (2–40 stems ha−1). CentralAmerican cocoa plantations have a total basal area of 23 m2 ha−1,with cocoa contributing 11 m2 ha−1, timber trees (6 m2 ha−1) andthe rest of plant types (palms, bananas, fruit trees, and other) anadditional 6 m2 ha−1 (Table 2).

Forty-six percent of Central American cocoa plantations hadmixed shade canopies; 37% had a productive shade cover. Only3–4% of all cocoa plantations were cultivated either without shadeor under rustic shade (Table 3). Cocoa plantation typologies andgrowing areas were not independent (p < 0.0001). For example, rus-tic and full sun plantations were found only in Guatemala; cocoaplantations with mixed shade were common in all Central Ameri-can countries.

3.5. Carbon stocks

Central American cocoa-based AFS stocked, on average,117 ± 47 Mg ha−1 of total carbon, with wide differences amongplots (46–333 Mg C ha−1). Carbon in aboveground biomass (cocoaand canopy) was 49 ± 35 Mg C ha−1 (Table 4).

The frequency distributions of total and carbon in abovegroundbiomass were slightly asymmetrically positive and moderately lep-tokurtic, signaling that means are good indicators of the centraltendency of the data (Fig. 4).

Carbon stocks differed widely between growing areas. Thehighest level of total carbon was found in Guatemala-CostaSur (155 Mg C ha−1), and the lowest in Nicaragua (93 Mg C ha−1).

Aboveground biomass contained 42% of total carbon (Table 4). Theannual rate of accumulation of carbon in aboveground biomassvaried with plantation age, with an average of 2.6 Mg C ha−1 y−1,respectively (Table 4). The rate of carbon accumulation was high

50 E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57

Table 2Density and basal area for cocoa and shade canopy in Central American cocoa-based agroforestry systems, 2011.

Nicaragua Honduras Guatemala Alta Verapaz Costa Rica Panama Guatemala Costa Sur Average

Density (trees ha−1)Timber trees 42 ± 52a 91 ± 99b 170 ± 91d 119 ± 84bc 134 ± 77cd 88 ± 98b 104 ± 92Fruit trees 60 ± 57bc 35 ± 65ab 14 ± 23a 84 ± 63c 64 ± 148bc 48 ± 49abc 52 ± 81Other trees 24 ± 29ab 18 ± 28a 36 ± 43bc 42 ± 58c 15 ± 21a 20 ± 30ab 25 ± 37Palms 8 ± 25ab 37 ± 83c 1.43 ± 5.5a 43 ± 48c 24 ± 34bc 22 ± 29bc 22 ± 45Bananas 158 ± 152b 42 ± 74a 0.57 ± 2.0a 193 ± 261bc 240 ± 163c 31 ± 42a 117 ± 169Cocoa 562 ± 98b 583 ± 205b 604 ± 128b 591 ± 218b 588 ± 215b 335 ± 148a 545 ± 192Total 855 ± 190b 808 ± 295b 826 ± 156b 1071 ± 242c 1065 ± 323c 544 ± 199a 866 ± 296

Basal area (m2 ha−1)Timber trees 2.2 ± 2.9a 6.3 ± 5.9b 7.1 ± 3.5b 8.2 ± 5.6b 7.5 ± 5.1b 8.0 ± 7.8b 6.4 ± 5.8Fruit trees 3.1 ± 3.5cd 1.4 ± 3.0ab 0.5 ± 1.0a 1.9 ± 1.7bc 1.2 ± 1.5ab 4.3 ± 4.1d 2.1 ± 3.0Other trees 1.1 ± 1.6a 1.1 ± 3.1a 1.1 ± 1.5a 0.9 ± 2.2a 1.8 ± 3.6ab 3.0 ± 6.1b 1.5 ± 3.3Palms 0.2 ± 0.6a 0.6 ± 1.6a 0.4 ± 1.6a 0.9 ± 1.2a 0.6 ± 0.9a 2.6 ± 3.5b 0.8 ± 1.9Bananas 2.7 ± 2.7b 0.7 ± 1.3a 0.02 ± 0.1a 3.4 ± 4.6bc 4.3 ± 2.9c 0.5 ± 0.7a 2.1 ± 2.9Cocoa 10.7 ± 5.3b 12.8 ± 5.9c 14.2 ± 4.7c 10.2 ± 4.3ab 8.2 ± 4.1a 8.6 ± 3.2a 10.7 ± 5.1Total 19.9 ± 6.2a 22.9 ± 10.1ab 23.3 ± 7.2bc 25.5 ± 7.4bc 23.6 ± 6.2bc 27.5 ± 14.5c 23.6 ± 8.3

Different letters along rows indicate significant differences among countries (LSD Fisher, p < 0.05).

Table 3Number cocoa-based agroforestry systems sampled in each of the five types typology and in each Central American country, 2011.

Country Without shade Specialized shade Productive shade Mixed Rustic Total

Nicaragua 0 2 25 22 0 49Guatemala Alta Vera Paz 0 21 0 14 0 35Honduras 0 1 18 14 0 33Costa Rica 0 0 16 20 0 36Panama 0 0 21 19 0 40Guatemala Costa Sur 3 0 5 17 11 36

Total 3 24 85 106 11 229

Table 4Carbon stored per compartment, plantation age and carbon storage rates in Central American cocoa-based agroforestry systems, 2011.

Carbon stored (Mg ha−1) in eachcompartment

Nicaragua Honduras Guatemala AltaVerapaz

Costa Rica Panama GuatemalaCosta Sur

Average

Soil 48.3 ± 14.7b 33.3 ± 11.5a 52.8 ± 10.3bc 49.3 ± 8.5b 56.9 ± 13.2c 64.1 ± 13.4d 51.0 ± 15.2Aboveground biomass 33.1 ± 19.5a 45.1 ± 29.0abc 39.4 ± 19.4ab 52.7 ± 21.7bc 56.7 ± 47.4c 74.4 ± 47.0d 49.2 ± 34.9Coarse roots 6.9 ± 3.6ab 9.4 ± 5.4bc 6.6 ± 3.6a 9.3 ± 3.6bc 11.5 ± 8.3cd 13.4 ± 8.0d 9.4 ± 6.2Fine roots 3.8 ± 2.5c 1.3 ± 0.8a 1.4 ± 1.1a 1.9 ± 0.9ab 2.1 ± 0.9b 1.6 ± 0.8ab 2.1 ± 1.7Coarse dead wood 0.01 ± 0.06a 6.2 ± 4.8c 3.7 ± 5.1b 6.2 ± 5.1c 3.2 ± 4.9b 0.02 ± 0.07a 3.0 ± 4.7Fine dead wood 0.3 ± 0.1b 0.1 ± 0.1a 1.2 ± 0.1d 1.2 ± 0.5d 0.7 ± 0.4c 0.3 ± 0.1b 0.6 ± 0.5Litter 0.3 ± 0.1a 0.8 ± 0.4bc 0.4 ± 0.2ab 1.2 ± 0.4d 0.9 ± 0.3c 3.6 ± 1.8e 1.1 ± 1.3Total 93 ± 30a 96 ± 37a 106 ± 25ab 122 ± 24bc 132 ± 60c 155 ± 58d 117 ± 47Age (years) 20.3 ± 6.7ab 20.5 ± 6.5ab 18.1 ± 8.4a 24.9 ± 14.5bc 26.9 ± 6.1cd 30.8 ± 20.2d 23.5 ± 12Total C rate (Mg ha−1 y−1)a 5.4 ± 3.4a 5.6 ± 4.7a 7.9 ± 5.3b 6.9 ± 4.3ab 5.3 ± 3.3a 7.9 ± 6.2b 6.4 ± 4.6Aboveground biomass C rate

(Mg ha−1 y−1)1.9 ± 1.6a 2.6 ± 2.7ab 2.6 ± 1.9ab 3.0 ± 1.9bc 2.2 ± 1.8ab 3.7 ± 3.7c 2.6 ± 2.4

a Over-estimates the real carbon accumulation rate in the plot, because we do not know

Fig. 4. Frequency distributions, mean, asymmetry and kurtosis for abovegroundcarbon in Central American cocoa plantations (n = 229).

how much soil carbon was present at the establishment of the cocoa plantation.

in young plantations AFS (<10 years) and decreased with age(Fig. 5).

Annual accumulation rate of aboveground carbon estimatedby re-measurement of plots in Nicaragua, was estimated at1.3 Mg C ha−1 y−1.

Timber and fruit trees stored 32 Mg C ha−1, equivalent to 64% ofcarbon in aboveground biomass. Cocoa trees stored 9 Mg C ha−1,equal to 18% of carbon in aboveground biomass. In nearly allcountries, most aboveground biomass carbon was concentratedin timber trees. Only in Nicaragua carbon aboveground biomasswas mainly stored in fruit trees (Persea americana, Pouteria sapota,Mangifera indica, Inga spp., Citrus spp.). Bananas and palm treesstored only 4% of carbon in aboveground biomass irrespective of

growing area (Table 5).

Some site and soil variables (area, apparent density, pH, K and Ncontent) correlated significantly with total and aboveground car-bon levels, but correlation coefficients were less than 0.30.

E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57 51

Table 5Carbon found in aboveground biomass per plant type and per country in 229 Central American cocoa-based agroforestry systems, 2011.

Carbon C in abovegroundbiomass (Mg ha−1)

Nicaragua Guatemala AltaVerapaz

Honduras Costa Rica Panama GuatemalaCosta Sur

Average

Timber 6.9 ± 12.8a 22.9 ± 12.9b 21.5 ± 19.3b 27.7 ± 17.3b 31.6 ± 34.7c 30.9 ± 33.3b 22.8 ± 24.8Fruit trees 11.6 ± 17.1b 1.8 ± 4.3a 7.5 ± 17.0ab 8.1 ± 8.3ab 3.0 ± 4.0a 19.7 ± 25.1c 8.7 ± 16.0Cocoa 9.8 ± 5.8b 9.6 ± 4.8b 10.5 ± 5.4b 8.6 ± 5.2ab 7.0 ± 4.0a 8.4 ± 4.4ab 9.0 ± 5.1Others 4.3 ± 8.3ab 3.6 ± 5.4ab 4.2 ± 12.1ab 2.9 ± 8.9a 12.9 ± 33.6c 11.7 ± 24.5bc 6.6 ± 18.8Palms 0.6 ± 1.7a 1.5 ± 6.4a 0.9 ± 2.3a 4.6 ± 7.7b 1.6 ± 2.4a 1.7 ± 2.1a 1.8 ± 4.5Musacea 0.3 ± 0.1a 0.0 ± 0.0a 0.5 ± 1.1b 0.8 ± 1.1b 0.8 ± 0.5b 0.1 ± 0.3a 0.3 ± 0.7

Total 33.5 ± 20a 39.4 ± 19ab 45.1 ± 29abc 52.7 ± 22bc 56.9 ± 47c 72.5 ± 47d 49.2 ± 35

Different letters along rows indicate significant differences among countries (LSD Fisher,

Fc

pwgo4

TM

M

ig. 5. Accumulation rate of carbon in aboveground biomass in Central Americanocoa agroforestry systems: (A) total = cocoa + shade canopy and (B) in cocoa trees.

The monetary value of carbon stocked in Central American cocoalantations is modest. For example, 117 tons of total carbon are

−1

orth 2152 US$ ha . The monetary value of carbon in above-round biomass is only 920 US$ ha−1. If only the accumulation ratef aboveground carbon is valued, cocoa plantations would yield9 US$ ha−1 y−1 (Table 6).

able 6onetary value of carbon dioxide stored and accumulation rate per country in 229 Centr

CO2 rates and monetary values Nicaragua Guatemala Alta V

CO2 in aboveground biomass (Mg ha−1) 121 143

CO2 rate in aboveground biomass (Mg ha−1 year−1) 7 10

CO2 value in aboveground biomass (US$) 605 716

CO2 rate value in aboveground biomass (US$ year−1) 35 48

g CO2 = Mg C × 3.67; US$ = Mg CO2 × 5 us$ [Mg CO2]−1.

p < 0.05).

4. Discussion

4.1. Comparing the carbon stocks in Central American cocoaplantations with other sites

Forests are the main atmospheric CO2 sink on Earth. The car-bon stock of the local climax forest depends on the ecologicalconditions (rainfall, temperature, soil, local flora and fauna) thatdetermine tree growth. Most cacao trees in the world are grownbetween 18◦ N and 18◦ S latitude (Schmitz and Shapiro, 2012), inhumid forest areas with rainfall between 1200 and 2800 mm yr−1,mean annual temperature between 20 and 28 ◦C, without frosts,and on a variety of mid-textured, medium to high fertility soils(Wood and Lass, 2001). Humid climax forests within the ecologi-cal range of cocoa (such as natural climax forests in the Amazonia,Central America, Mata Atlantica in Brazil, Indonesia, Malaysia andGhana) store on average 180 Mg C ha−1, with variations between75 and 275 Mg C ha−1 (Brown et al., 1991; Kotto-Same et al., 1997;Clark and Clark, 2000; Woomer et al., 2000; Duguma et al., 2001;Cummings et al., 2002; Chave et al., 2003; DeWalt and Chave, 2004;Hoshizaki et al., 2004; Rolim et al., 2005; Smiley and Kroschel, 2008;Alves Luciana et al., 2010; Chiti et al., 2010; Girardin et al., 2010;Ibrahima et al., 2010; Lindner, 2010; Wade et al., 2010; Baralotoet al., 2011; de Paula et al., 2011; Metzker et al., 2011; Morel et al.,2011). Cocoa is also grown at a few dry forest locations, with rain-fall between 800–1100 mm y−1. Dry forests of Venezuela (Delaneyet al., 1997), Mexico (Jaramillo et al., 2003), South and SoutheastAsia (Brown et al., 1991), and Madagascar (Raherison and Grouzis,2005), store between 27 and 63 Mg ha−1 of carbon in their above-ground biomass.

The transformation of primary forests into cocoa plantationsentails a drastic reduction of forest carbon to give room and createlight and air circulation conditions adequate for cocoa production.In Indonesia, the transformation of primary forests into cocoa AFSdecreased forest carbon by 75–88% (Stephan-Dewenter et al., 2007;Smiley and Kroschel, 2008). In Central and West Africa, the conver-

sion of natural forests into cocoa plantations resulted in a 50% lossof biomass (Duguma et al., 2001). In Cameroon, out of the originalforest’s 204 Mg C ha−1 stored in aboveground biomass, rustic cocoaplantation retained 126 Mg C ha−1, that is, 38% of the forest carbon

al American cocoa-based agroforestry systems, 2011.

erapaz Honduras Costa Rica Panama Guatemala Costa Sur Average

165 194 209 272 18410 11 8 14 10

826 972 1046 1358 92048 54 40 71 49

5 ystem

we2tl>t<oi1mAg(

tp

c9pBbt1csi(aBi2breaeSa2

itisbFibeite

itpc1tpRg(

2 E. Somarriba et al. / Agriculture, Ecos

as lost (Kotto-Same et al., 1997). Other estimates from West Africastablish forest carbon losses at 60–75% (Gockowski and Sonwa,011). In Ghana, carbon losses caused by clearing primary forestso plant cocoa varied between 15 and 75%, depending on the typo-ogy of the cocoa plantation. Traditional cocoa plantations with25% shade cover retained 131 Mg C ha−1 of the 155 Mg ha−1 ofhe local primary forest, while intensive cocoa plantations with25% shade retained 39 Mg ha−1 (Wade et al., 2010). The 32 Mg ha−1

f carbon retained by cocoa plantations with Erythrina fusca Lourn Bahia, Brazil (Gama-Rodrigues et al., 2011) represent scarcely8% of the carbon in primary forest of the “Mata Atlantica”, esti-ated between 100 and 237 Mg ha−1 (Lindner, 2010). Centralmerican cocoa plantations retained only 49 Mg C ha−1 in above-round biomass, representing 27% of forest aboveground carbon180 Mg ha−1).

Total and aboveground carbon in Central American cocoa plan-ations estimated in this study fall within ranges measured in otherarts of the world (Table 7).

The 49 Mg ha−1 of aboveground carbon in Central Americanocoa plantations are considerably lower than the average of5 Mg C ha−1 reported by Albrecht and Kandji (2003), but com-arable to cocoa plantations with specialized E. fusca shade inahia, Brazil, which accumulated 32 Mg C ha−1 in abovegroundiomass (Gama-Rodrigues et al., 2011). Mixed-shade cocoa plan-ations in the Peruvian Amazon, at 250–450 m altitude and000–1500 mm y−1 rainfall, stock 40–45 Mg ha−1 of abovegroundarbon (Concha et al., 2007). Hybrid cocoa plantations with mono-pecific Cordia alliodora shade stored 43–62 Mg ha−1 in 25 yearsn Panama (Ortiz et al., 2008), 60 Mg ha−1 in Turrialba, Costa RicaBeer et al., 1990) and 49 Mg ha−1 in Caldas, Colombia (Aristizabalnd Guerra, 2002). Commercial rubber-cocoa mixed cropping inahia (Brazil) stored 82 Mg ha−1 in aboveground carbon, includ-

ng 68 Mg ha−1 in rubber and 3.8 Mg ha−1 in cocoa (Cotta et al.,008). African cocoa plantations appear to store more abovegroundiomass carbon than their American counterparts. For example,ustic shade (Kotto-Same et al., 1997) and mixed shade (Dugumat al., 2001) cocoa plantations in Cameroon stored 125 Mg C ha−1 inboveground biomass. However, other estimates for West Africanstablish aboveground biomass at 89 Mg C ha−1 (Gockowski andonwa, 2011). In Ghana, aboveground carbon varied between 39nd 131 Mg C ha−1, depending on cocoa farm typology (Wade et al.,010).

Carbon in Central American cocoa-based AFS is stocked mainlyn the soil and in aboveground biomass (cocoa + shade canopyrees). The amount of carbon in soil (51 Mg ha−1) was higher thann 30 year-old, mixed shade cocoa plantations in Ghana, whichtocked 41 Mg C ha−1 (Dawoe et al., 2010). In Ghana, soil car-on content decreased with increased cocoa tree density (Ofori-rimpong et al., 2010). Unfortunately, most studies on soil carbonn cocoa plantation soils are not directly comparable to our studyecause they measured different soil profiles (Isaac et al., 2005; Ritat al., 2011). There is evidence that soil carbon may be significantlyncreased, especially during the first ten years of development ofhe cocoa AFS (Beer et al., 1990; Albrecht and Kandji, 2003; Isaact al., 2005).

Carbon stored in cocoa tress under mixed shade canopiesn Central American plantations (9 Mg ha−1) compares well tohe 10.5 Mg C ha−1 stocked in an eight years old, full sun cocoalantations in Ghana (Isaac et al., 2007). Central Americanocoa plantations (rainfall of 2300–2600 mm y−1) maintain barely.1 Mg C ha−1 in the litter, while in Ghana (1300–1850 mm y−1)hey store 2–3 Mg C ha−1 (Dawoe et al., 2010). In Bahia, Brazil, cocoa

lantations under E. fusca shade store 2.7 Mg C ha−1 in litter (Gama-odrigues et al., 2011), while commercial associations of 6 year-oldrafted cocoa and 30 year-old rubber accumulated 1.67 Mg C ha−1

Cotta et al., 2008).

s and Environment 173 (2013) 46– 57

Accumulation rates of aboveground carbon in Central Ameri-can cocoa AFS (1.3–2.6 Mg C ha−1) are similar to the 1–2 Mg C ha−1

reported for several cocoa plantations worldwide (Table 7), butlower than the 6 Mg C ha−1 reported for cocoa plantations withmono-specific C. alliodora and Erythrina poeppigiana (Walp.) O.F.Cook in Costa Rica (Beer et al., 1990), and rustic cocoa plantationsin Cameroon (Duguma et al., 2001).

4.2. Balancing carbon stocks and yields

In the search for cocoa agroforestry designs that optimally solvethe trade-offs between high yields and high carbon stocks a setof key questions must be addressed: Can natural forests be mini-mally degraded when converted into cocoa plantations? Are lossesof forest carbon, the allocation of carbon between soil and veg-etation, and between cocoa and shade canopy trees determinedby the ecological conditions of the site, or vary depending on cli-mate and soil? Can a maximum carbon stock compatible withfarmers’ objectives be reached for each cocoa plantation typo-logy? To evaluate the effects of ecological conditions on thesetrade-offs, a global study of the relevant literature combined withexpert knowledge and field work is needed. In what follows weexplore qualitatively the relationships, and alternatives for man-aging the trade-offs, between carbon stocks and yields in cocoaplantations.

Is it possible to design cocoa plantations with large stocks of car-bon in both the cocoa (Ck) and canopy (Cc) compartments that alsoproduce high yields from both cocoa (Yk) and canopy (Yc) com-partments? Current knowledge in crop management provides afirst glance at the interactions and functional relationships betweenthese four variables:

1. The effects of Ck on Yk has been the subject of research seekingto determine the optimal cocoa tree density needed to achievemaximum cocoa yield per hectare (Lockwood and Yina, 1996;Dias et al., 2000). A detailed analysis of density–yield relation-ship in cocoa is outside the scope of this paper, although we doknow that Yk increases with density—and Ck along with it—untilit peaks at the optimal density and then experiences a moderatedecrease at very high densities (Fig. 6a).

2. Carbon levels in cocoa (Ck) are not expected to have an effecton canopy yields (Yc) (Fig. 6b). A as consequence, differencesin yields between cocoa plantations will depend on system’sdesign, management, and other factors.

3. The relationship between Cc and Yk is well-known both in theory(Zuidema et al., 2005; de Almeida and Valle, 2007) and practice(Stephan-Dewenter et al., 2007; Wade et al., 2010; Gockowskiand Sonwa, 2011): cocoa yield (Yk) decreases in a non-linearway with increased shade—and Cc along with it—(Fig. 6c).

4. It is expected that Yc increases asymptotically with increasingCc (Fig. 6d). However, if instead of total outputs from the canopy(for both people and for nature) we look at useful output forpeople, Yc may be expected to peak at an intermediate Cc level,and then decrease slightly with increasing Cc.

After exploring the relationships between carbon levels andyields, we now need to explore the relationships between Cc andCk in the five cocoa plantation typologies. In Fig. 7, we propose ahypothetical preliminary distribution of Ck and Cc per typology,based on the following arguments:

Although cocoa is planted at high densities in full sun cocoaplantations (1600–2000 plants ha−1), Ck is not the maximum

attainable because the cocoa trees are regularly and heavily pruned(Lockwood and Yina, 1996; Souza et al., 2009).

Maximum Ck is expected to occur in specialized-shade cocoaplantations and decrease as Cc increases with the cocoa typology.

E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57 53

Table 7Carbon stocks in compartments of cocoa agroforestry systems in tropical regions around the world.

Region Temperature (◦C) Rainfall (mm) Type of agroforestry system Age (years) Compartment Mg C ha−1 Source

Central America 25 1700–4000 Mixed shade 24

Aboveground biomass 49.2 ± 34.9

This studyAnnual rate 2.6 ± 2.4Cocoa biomass 9.0 ± 5.1Annual cocoa rate 0.5 ± 0.4

Bahia, Brazil26 1500

Cocoa/Erythrina fusca30

Aboveground biomass 32

1Annual rate 1.1

Cocoa cabrucaAboveground biomass 33Annual rate 1.1

25 1500Cocoa/Heveabrasiliensis

34Aboveground biomass 82

2Annual rate 2.4

Amazonas, Peru 25 1500Cocoa/timber/fruittrees

20Aboveground biomass 30

3

Annual rate 1.5

12Aboveground biomass 34Annual rate 2.8

5Aboveground biomass 13Annual rate 2.6

Caldas, Colombia 23 2250 Cocoa/musa/Cordiaalliodora

13 Aboveground biomass 49 4Annual rate 4.3

Bocas del Toro, Panama 27 3000 Cocoa/Cordia alliodora 25 Aboveground biomass 62 5Annual rate 2.5

Turrialba, Costa Rica 24 2500–3000 Cocoa/Cordia alliodora 10 Aboveground biomass 60 6Annual rate 6.0

East Ghana 24–29 1200–1600

Traditional cocoa(>25% shade)

50

Aboveground biomass 131

7Annual rate 2.6

Intensive cocoa (<25%shade)

Aboveground biomass 39Annual rate 0.8

West Ghana 26 1100

Shadeless cocoa

8

Aboveground biomass 10

8

Annual rate 1.3

Cocoa-AlbiziaAboveground biomass 18Annual rate 2.3

Cocoa/MiliciaAboveground biomass 19Annual rate 2.3

Cocoa/NewbouldiaAboveground biomass 14Annual rate 1.8

Sefwi Wiawso, Ghana 26 1050 Multilayer cocoa

2Aboveground biomass 5

9

Annual rate 2.5

15Aboveground biomass 54Annual rate 3.6

25Aboveground biomass 81Annual rate 3.2

Cameroon sd sd Rustic cocoa 26Aboveground biomass 125

10Annual rate 4.8

Southeast Cameroon 21 1550Cocoa/timber

40

Aboveground biomass 89

11Annual rate 2.2

Shadeless cocoaAboveground biomass 49Annual rate 1.2

Sulawesi, Indonesia 21 1550 Cocoa/Gliricidia sp. 15Aboveground biomass 31

12Annual rate 2.1Central America 25 1700–4000 Mixed shade 24 Soil (0–20 cm) 51 ± 15 This studySoutheast Cameroon 21 1550 Cocoa/timber Shadeless cocoa 40 Soil (0–20 cm) 43 11

Ghana sd 1500 Mixed shade 19Soil (0–15 cm) 25

13Soil (15–30 cm) 19Soil (30–45 cm) 17

Sefwi Wiawso, Ghana 26 1050 Multilayer cocoa2

Soil (0–15 cm)23

915 1825 18

Bahia, Brazil 26 1500

Cocoa/Erythrina fusca 30

Soil (0–10 cm) 40

1,15

Soil (10–30 cm) 38Soil (30–60 cm) 33Soil (60–100 cm) 28

Cocoa cabruca 30

Soil (0–10 cm) 58Soil (10–30 cm) 50Soil (30–60 cm) 37Soil (60–100 cm) 27

Central America 25 1700–4000 Mixed shade 24 Litter 1.1 ± 1.3 This study

West Ghana 27 1300–1850 Mixed cocoa3 Litter 2

1415 330 3

Bahia, Brazil26 1500 Cocoa/Erythrina fuscaCocoa cabruca 30 Litter 2.7 125 1500 Cocoa/Hevea brasiliensis 34 Litter 1.7 2

Source: 1: Gama-Rodrigues et al., 2011; 2: Cotta et al., 2008; 3: Concha et al., 2007; 4: Aristizabal and Guerra, 2002; 5: Ortiz et al., 2008; 6: Beer et al., 1990; 7: Wade et al.,2010; 8: Isaac et al., 2007; 9: Isaac et al., 2005; 10: Duguma et al., 2001; 11: Gockowski and Sonwa, 2011; 12: Smiley and Kroschel, 2008; 13: Ofori-Frimpong et al., 2010; 14:Dawoe et al., 2010; 15: Gama-Rodrigues et al., 2010.Note: Carbon accumulation rates were calculated based on inventories and plantation age as reported by each author. The sources did not report soil and residual vegetationcarbon inventories at the moment of the cocoa-based AFS establishment.

54 E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57

Fig. 6. Qualitative relationships between levels of aboveground C in cocoa (Ck) and

Fig. 7. Carbon levels and expected yields for the cocoa and the canopy componentsand for each type of cocoa-based agroforestry systems.

in shade canopy trees (Cc), and yields of cocoa (Yk) and shade canopy (Yc).

This pattern is apparently confirmed by carbon distribution incocoa plantations with Gliricidia sepium in Indonesia (Smileyand Kroschel, 2008) and cocoa plantations with E. fusca shadein Bahia, Brazil (Gama-Rodrigues et al., 2011). Cocoa and canopycarbon distribution data in the 229 cocoa plantations measuredby us in Central America (most of them under mixed canopiesand low cocoa plant density) seem to adjust to this hypotheticaldistribution, as well.

Maximum Yk is expected to occur in full sun cocoa plantations,and then decrease with increases in Cc in the cocoa typologies.There is evidence for this. In Ghana, a cocoa intensification gradientvaried aboveground biomass carbon between 39 and 131 Mg ha−1

(Wade et al., 2010). Similar results were observed in an intensi-fication gradient in Sulawesi, Indonesia (Stephan-Dewenter et al.,2007).

Yc is nil in full sun cocoa, peaks in cocoa plantations with pro-ductive (Cotta et al., 2008) and mixed shade, and decreases inrustic ones (Gama-Rodrigues et al., 2011). Rustic canopies typi-cally include a mix of valuable and non-commercial tree species(Sambuichi, 2002).

The analysis above assumes that carbon level is a good pre-dictors of yield, which may not always be the case. Two cocoaplantations may have the same canopy carbon level, but in Plan-tation 1 concentrated in a few, very tall trees, and in Plantation2 distributed in many, small, short trees. Plantations 1 and 2will have significant differences in the pattern of transmission ofsolar radiation inside the cocoa plantation and may result in sig-nificant differences in cocoa yield. In yet another example, twoplantations with the same canopy carbon level may have radicallydifferent botanical compositions resulting again in very differentpatterns of transmission of solar radiation into the plantation andpossibly in cocoa yields. Canopy species have an array of mor-

phological (e.g. leaf size and morphology, root systems, etc.) andfunctional attributes (e.g. leaf fall patterns) that drastically influ-ence the transmission of solar radiation into the cocoa plantation,thereby affecting the growth and yield of cocoa, and altering the

E. Somarriba et al. / Agriculture, Ecosystems and Environment 173 (2013) 46– 57 55

Table 8Standards for tandem-type certification, including considerations about amounts of stored carbon.

Standard Mechanism Elements Online source

VCM CDM C S B

The climate, community and Biodiversity Alliance (CCB) X X X X X http://www.climate-standards.org/index.htmlVerified Carbon Standard (VCS) X X http://v-c-s.org/The gold standard X X X X X http://www.cdmgoldstandard.org/Social Carbon Standard X X X X http://www.socialcarbon.org/Forest stewardship council (FSC) X X X X http://www.fsc.org/77.htmlAmerican Carbon Registry Standard (ACRS) X X X X X http://www.americancarbonregistry.org/Carbco Platinum Carbon Standard X X X X http://www.cquestor.com/Carbon Fix Standard (CFS) X X X X http://www.carbonfix.info/EPA Climate Leaders Offset Guidance X X http://www.epa.gov/Panda Standard X X X X http://www.pandastandard.org/Plan Vivo X X X X http://www.planvivo.org/standard/VER+ Standard X X X http://www.tuev-sued.de/Chicago Climate Exchange (CCX) X X https://www.theice.com/ccx.jhtmlGreen-e Climate X X http://www.green-e.org/WRI/WBCSD GHG Protocol for Project Accounting X X X http://www.ghgprotocol.org/

V S: so

md

cicba(Sp((dhswdiappOt2

va(mperi22http2plst

Rain Forest Alliance X X

CM: voluntary carbon markets; CDM: clean development mechanisms; C: carbon;

icroclimate that is so determinant to the life cycles of pest andiseases that reduce yields.

The manipulation of the morphological and functional traits ofanopy species has been used to optimize shade canopy designn coffee (Bellow and Muschler, 1999; Linkimer et al., 2002) andould be used in cocoa to both maintain high yields and car-on stocks. To stock high levels of carbon in the plot withoutdversely affecting cocoa yields, one could select tree species with1) tall, cylindrical and thick stems—a tree form that may be calledequoia—like Terminalia ivorensis A. Chev. in West African cocoalantations. Large trees store most of forest aboveground biomassLindner, 2010); tall trees cast a “lighter” shade than short trees;2) small canopies and light foliage (like Albizia spp.; (3) large,eep, thick roots (Nair et al., 2009); and (4) rapid growth andigh-density timber; (5) inverted phenology which would be ofpecial interest (e.g. Faidherbia albida (Delile) A. Chev. in Africa,hich loses foliage during the rainy season and keeps it during thery season). This inverted phenology behavior has been observed

n Dalbergia glomerata Hemsley (a highly valuable timber) useds shade over cacao in Honduras (Aroldo Dubón, FHIA, Honduras,ersonal communication, 2011). It seems possible to design cocoalantations with high carbon stock levels and good cocoa yields.ther authors have reached similar conclusions for cocoa plan-

ations in Indonesia and Ghana (Clough et al., 2011; Wade et al.,010).

The contribution of cocoa to sustainable production and the pro-ision of ecosystem services (including carbon sequestration tobate climate change) at the landscape level has been exploredat least conceptually) in terms of the dichotomy between pro-

oting intensive cocoa production to free natural forest areas forure conservation (land-sparing strategy) and promoting mixed,nvironmentally friendly cocoa agroforestry systems, which mayequire a larger area due to smaller yields (wildlife-friendly farm-ng strategy) but could reduce deforestation (Montagnini and Nair,004; Clough et al., 2011; Tscharntke et al., 2011; Wade et al.,010). To reduce deforestation and loss of natural forests, authorsave proposed to transform rustic cocoa into cocoa with produc-ive shade (e.g. cocoa – timber systems), a controlled intensificationhat would nonetheless reduce biodiversity and ecological com-lexity (Stephan-Dewenter et al., 2007; Gockowski and Sonwa,011). In Bahia, Brazil, a large cocoa-growing territory encom-

assing more than 500,000 ha of rustic cocoa (a wildlife-friendly

andscape) and a few remnants of protected mature forest, inten-ive production (land sparing strategy) is not attractive becausehere is no more natural forest left to lose (Cotta et al., 2006).

X X X http://www.rainforest-alliance.org/

cial impacts; B: environmental impacts (biodiversity, land use, reforestation).

In this region, the key question is how to increase rustic cocoayield without sacrificing its biodiversity and high total carbon stock(Schroth et al., 2011). Central American cocoa plantations con-form to a wildlife-friendly farming strategy, because 51% are usingmixed or rustic shade. Only 11% of Central American cocoa planta-tions are intensively managed either at full sun or with specializedshade.

Our results offer Central American cocoa producers a rigorousestimate of carbon stocks in their cocoa plantations. Several stud-ies show that, for these small producers (who must organize intolarger groups to accumulate a marketable amount of carbon certifi-cates), voluntary markets seem to be the most appropriate (Milesand Kapos, 2008; Somarriba et al., 2009; Hamilton et al., 2010; FAO,2010). Large and small cocoa producers may choose among severalvoluntary market-compatible standards (Table 8).

Tandem standards, which consider climate change, socialjustice and ecological sustainability production aspects (organic orlow-input, biodiversity-friendly, etc.) seem appropriate for smallfarmers (Somarriba et al., 2009). Additionally, tandem standardspoint toward sustainable cocoa production, in line with the strate-gies of the cocoa industry (http://www.worldcocoafoundation.org/sustainability-principles-and-goals/; http://www.mars.com/global/commitments/sustainability/cocoa-sustainability.aspx;http://www.mars.com/global/principle-in-action/cocoa-certification.aspx; Millard, 2011).

The results from our study will help cocoa farmers’ orga-nizations to sell certified agroforestry products (cocoa, banana,timber, fruit, carbon sequestration and other ecosystem ser-vices) in market niches with better prices. Some possibilitiesinclude (1) sustainable timber, Forest Stewardship Council pro-tocol (www.fsc.org); (2) REDD+ offers access to payments forcarbon sequestration (Miles and Kapos, 2008); and (3) the ClimateSmart Agriculture program, supporting initiatives that enhancefood security, reduce vulnerability, mitigate and adapt to cli-mate change (www.fao.org/climatechange/climatesmart/en/; FAO,2010). The results and data gathered by our research could alsoassist governments and the private sector in (1) designing bet-ter legal, institutional and policy frameworks, local and national,promoting an agriculture with trees (Albrecht and Kandji, 2003;Seeberg-Elverfeldt et al., 2009; Wade et al., 2010; FAO, 2010;Somarriba et al., 2012a,b); and (2) contributing to the development

of national monitoring, reporting and verification systems requiredby the international community to access funding and payment forecosystem services (Angelsen et al., 2009; Intergovernmental Panelon Climate Change, 2003a).

5 ystem

5

ymshytld

pgCfaacct

A

tBnAAIGcdtmAvDpC

R

A

A

A

A

A

B

B

B

B

6 E. Somarriba et al. / Agriculture, Ecos

. Conclusion

It is possible to design cocoa-based AFS that provide both goodields (cocoa and shade canopy) and high carbon densities. Theanipulation of morphological and functional traits of canopy

pecies may be used to optimize shade canopy design. To stockigh levels of carbon in the plot without adversely affecting cocoaields, one could select tree species with (1) tall, cylindrical andhick stems (a “sequoia” type of tree); (2) small canopies and small,ight foliage; (3) large, deep, thick roots; (4) rapid growth and high-ensity timber; and (5) inverted phenology.

Inventories and carbon storage rates in Central American cocoalantations are significant and similar to those in other cocoa-rowing regions around the world. The sale of carbon stored inentral American cocoa can generate a modest income for cocoa

armers. We expect that our results help governments, private firmsnd producer organizations to formulate climate change adaptationnd abatement strategies, access payments for ecosystem services,ertify and obtain better prices for other products derived fromocoa plantations (cocoa, fruits, timber, etc.), and to improve sus-ainable cocoa production.

cknowledgements

We would like to thank the support provided by field assis-ants from COCABO (Cooperativa de Servicios Múltiples de Cacaoocatorena, Panamá), ACOMUITA (Asociación de Mujeres Indíge-as de Talamanca, Costa Rica), CACAONICA (Cooperativa de Serviciogroforestal y de Comercialización de Cacao, Waslala, Nicaragua),PROCACAHO (Asociación de productores de cacao de Honduras),

nstituto agroecológico bilingüe Fray Domingo de Vico, Cahabón,uatemala; ASECAN (Asociación de sembradores de cacao de lauenca del Nahualapa, Guatemala) and APROCA (Asociación de pro-uctores de sur occidente de Guatemala). We would also like tohank Ignacio Rodriguez Arias for is valuable help in the field in Tala-

anca (Costa Rica). Jenny Ordónez, Bruno Rapidel, Goetz Schroth,ntonio Carlos Gama-Rodríguez and anonymous reviewers pro-ided valuable comments on the manuscript. Alejandra Villota andavid Calvache, from the University of Narino, Colombia, helpedrepare tables, figures and bibliography. Research was funded byATIE/MAP/PCC.

eferences

dejumo, T.O., 2005. Crop protection strategies for major diseases of cocoa, coffeeand cashew in Nigeria. Afr. J. Biotechnol. 4 (2), 143–150.

lbrecht, A., Kandji, S.T., 2003. Carbon sequestration in tropical agroforestry sys-tems. Agric. Ecosyst. Environ. 99, 15–27.

lves Luciana, F., Vieira Simone, A., Scaranello Marcos, A., 2010. Forest structureand live aboveground biomass variation along an elevational gradient of tropicalAtlantic moist forest (Brazil). Forest Ecol. Manag. 260 (5), 679–691.

ngelsen, A., Brockhaus, M., Kanninen, M., Sills, E., Sunderlin, W.D., Wertz-Kanounnikoff, S. (Eds.), 2009. Realising REDD+: National Strategy and PolicyOptions. Cifor, Bogor.

ristizabal, J., Guerra, A., 2002. Estimación de la tasa de fijación de C en el sistemaagroforestal Nogal Cafetero (Cordia alliodora) – Cacao (Theobroma cacao L.) –Plátano (Musa paradisiaca). Univ. Distrital “Francisco José de Caldas” Fac. Med.Amb. y Rec. Nat., Bogota.

araloto, C., Rabaud, D., Molto, Q., Blanc, L., Fortunel, C., Hérault, B., Dávila, N.,Mesones, I., Ríos, M., Valderrama, E., Fine, P.V.A., 2011. Disentangling stand andenvironmental correlates of aboveground biomass in Amazonian Forests. Glob.Change Biol. 17 (8), 2677–2688.

eer, J., Bonnemann, A., Chavez, W., Fassbender, H.W., Imbach, A.C., Martel, I., 1990.Modelling agroforestry systems of cacao (Theobroma cacao) with laurel (Cordiaalliodora) or poro (Erythrina poeppigiana) in Costa Rica. V. Productivity indices,organic material models and sustainability over ten years. Agrofor. Syst. 12,229–249.

ellow, J.G., Muschler, R.G., 1999. Screening for promising tree associates for cof-fee in Central America. In: Jiménez, F., Beer, J. (Eds.), Multi-strata AgroforestrySystems with Perennial Crops. CATIE, Turrialba, pp. 171–174.

internagel, N.B., Juhrbrandt, J., Koch, S., Purnomo, M., Schwarze, S., Barkmann, J.,Faust, H., 2010. Adaptation to climate change in Indonesia – livelihood strategies

s and Environment 173 (2013) 46– 57

of rural households in the face of ENSO related droughts. Env. Sci. Eng. 2,351–375.

Brown, S., Iverson, L.R., 1992. Biomass estimates for tropical forests. World Res. Rev.4 (3), 366–383.

Brown, S., Gillespie, A.J.R., Lugo, A.E., 1991. Biomass of tropical forests of south andsoutheast Asia. Can. J. For. Res. 21, 111–117.

Cairns, M.A., Brown, S., Helmer, E.H., Baungardner, G.A., 1997. Root biomass alloca-tion in the world’s upland forests. Oecologia 111, 1–11.

Chave, J., Condit, R., Lao, S., Caspersen, J.P., Foster, R.M., Hubbell, S.P., 2003. Spatialand temporal variation of biomass in a tropical forest: results from a large censusplot in Panama. J. Ecol. 91, 240–252.

Chiti, T., Certini, G., Grieco, E., Valentini, R., 2010. The role of soil in storing car-bon in tropical rainforests: the case of Ankasa Park, Ghana. Plant Soil 331 (1),453–461.

Clark, D.B., Clark, D.A., 2000. Landscape-scale variation in forest structure andbiomass in a tropical rainforest. Forest Ecol. Manag. 137, 185–198.

Clough, Y., Barkmann, J., Juhrbandt, J., Kessler, M., Wanger, T.C., Anshary, A., Buchori,D., Cicuzza, D., Darras, K., Putra, D., Erasmi, S., Pitopang, R., Schmidt, C., Schulze,C.H., Seidel, Steffan-Dewenter, I., Stenchly, K., Vidal, S., Weist, M., Wielgoss, A.C.,Tscharntke, T., 2011. Combining high biodiversity with high yields in tropicalagroforests. PNAS 108, 8311–8316.

Concha, J., Alegre, J., Pocomucha, V., 2007. Determinación de las reservas de Cen la biomasa aérea de sistemas agroforestales de Theobroma cacao, L. en eldepartamento de San Martín, Perú. Ecol. Appl. 6, 75–82.

Cotta, M., Goncalves, L., de Paiva, H.N., Soares, C.P.B., Virgens Filho, A. de C., Valverde,S.R., 2008. Quantificacao de biomassa e geracao de certificados de emissoesreduzidas no consorcio seringueira – cacau. Árvore 32 (6), 969–978.

Cotta, M., Gonc alves, L., Valverde, S., Nogueira, H., Virgens, A., Lopes, M., 2006.Análise econômica do consorcio seringueira – cacau para gerac ão de certificadosde emissões reduzidas. Árvore 30 (6), 969–979.

Cummings, D.L., Kauffman, J.B., Perry, D.A., Hughes, R.F., 2002. Aboveground biomassand structure of rainforests in the southwestern Brazilian Amazon. Forest Ecol.Manag. 163, 293–307.

Dalquist, R.M., Whelan, M.P., Winowiecki, L., Polidoro, B., Candela, S., Harvey, C.A.,Wulfhorst, J.D., McDaniel, P.A., Bosque-Pérez, N.A., 2007. Incorporating liveli-hoods in biodiversity conservation: a case study of cacao agroforestry systemsin Talamanca, Costa Rica. Biodivers. Conserv. 16, 2311–2333.

Dawoe, E.K., Isaac, M.E., Quashie-Sam, J., 2010. Litterfall and litter nutrient dynamicsunder cocoa ecosystems in lowland humid Ghana. Plant Soil 330, 55–64.

de Almeida, A.A.F., Valle, R., 2007. Ecophysiology of the cacao tree. Braz. J. Plant.Physiol. 19 (4), 425–448.

de Paula, M.D., Costa, C.P.A., Tabarelli, M., 2011. Carbon storage in fragmented land-scape of Atlantic forest: the role played by edge-affected habitats and emergenttrees. Trop. Conserv. Sci. 4 (3), 349–358.

Deheuvels, O., 2011. Compromis entre productivité et biodiversité sur un gradi-ent d’intensité de gestion de systèmes agroforestiers à base de cacaoyers deTalamanca, Costa Rica. SupAgro, Montpellier.

Deheuvels, O., Avelino, J., Somarriba, E., Malezieux, E., 2012. Vegetation structureand productivity in cocoa-based agroforestry systems in Talamanca, Costa Rica.Agric. Ecosyst. Environ. 149, 181–188.

Delaney, M., Brown, S., Lugo, A.E., Torres-Lezama, A., Bello-Quintero, N., 1997. Thedistribution of organic carbon in major components of forests located in five lifezones of Venezuela. J. Trop. Ecol. 13, 697–708.

DeWalt, S.J., Chave, J., 2004. Structure and biomass of four lowland neotropicalforest. Biotropica 36 (1), 7–19.

Dias, L.A.S., Santos, M.M., Santos, A.O.S., Almeida, C.M.V.C., Cruz, D.C., Carneiro, P.C.S.,2000. Effect of planting density on yield and incidence of witches broom diseasein a Young plantation of hybrid cacao trees. Exp. Agric. 36, 501–508.

Di Rienzo, J.A., Casanoves, F., Balzarini, M.G., Gonzalez, L., Tablada, M., Robledo, C.W.,InfoStat versión 2012. Grupo InfoStat, FCA, Universidad Nacional de Córdoba,Argentina. URL: http://www.infostat.com.ar

Dixon, R.K., 1995. Agroforestry systems: sources or sinks of greenhouse gases?Agrofor. Syst. 31, 99–116.

Duguma, B., Gockowski, J., Bakala, J., 2001. Smallholder cacao (Theobroma cacao,Linn.) cultivation in agroforestry systems of West and Central Africa: challengesand opportunities. Agrofor. Syst. 51, 177–188.

FAO, 2010. Climate-smart agriculture. In: Policies, Practices and Financing for FoodSecurity, Adaptation and Mitigation. FAO, Rome.

Frangi, J.L., Lugo, A.E., 1985. Ecosystem dynamics of a subtropical floodplain forest.Ecol. Monogr. 55, 351–369.

Gama-Rodrigues, E.F., Gama-Rodrigues, A.C., Nair, P.K.R., 2011. Soil carbon seques-tration in cacao Agroforestry Systems: a case study from Bahia, Brazil. In: Kumar,B.M., Nair, P.K.R. (Eds.), Carbon Sequestration Potential of Agroforestry Systems:Opportunities and Challenges. Advances in Agroforestry 8. Springer-Science,New York, pp. 85–99.

Gama-Rodrigues, E., Nair, P.K.R., Nair, V.D., Gama-Rodrigues, A.C., Baligar, V.,Machado, R.C.R., 2010. Carbon storage in soil size fractions under two cacaoagroforestry systems in Bahia, Brazil. J. Environ. Manag. 45, 274–283.

Girardin, C.A.J., Malhi, Y., Aragao, L.E.O.C., Mamani, M., Huaraca-Huasco, W., Durand,L., Feeley, K.J., Rapp, J., Silva-Espejo, J.E., Silman, M., Salinas, N., Whittaker, R.J.,2010. Net primary productivity allocation and cycling of carbon along a trop-

ical forest elevational transect in the Peruvian Andes. Glob. Change Biol. 16,3176–3192.

Gockowski, J., Sonwa, D., 2011. Cocoa intensification scenarios and their predictedimpact on CO2 emissions, biodiversity conservation, and rural livelihoods in theGuinea rain forest of West Africa. Environ. Manage. 48, 307–321.

ystem

H

H

I

I

I

I

I

J

K

L

L

L

M

M

M

M

M

M

N

O

O

P

P

R

R

R

R

S

E. Somarriba et al. / Agriculture, Ecos

amilton, K., Sjardin, M., Peters-Stanley, M., Marcello, T., 2010. Building bridges:state of the voluntary carbon markets 2010. Ecosystems Marketplace andBloomberg New Energy Finance, USA.

oshizaki, K., Niiyama, K., Kimura, K., Yamashita, T., Bekku, Y., Okuda, T., Quah, E.S.,Supardi, N., 2004. Temporal and spatial variation of forest biomass in relationto stand dynamics in a mature, lowland tropical rainforest, Malaysia. Ecol. Res.19, 357–363.

brahima, A., Mvondoze, A., Ntonga, J.C., 2010. Aboveground biomass and nutrientaccumulation in the tropical rainforest of southern Cameroon: effects of logging.Cameroon J. Exp. Biol. 6 (1), 49–62.

ntergovernmental Panel on Climate Change, 2003a. Climate change 2000: SynthesisReport. IPCC Third Assessment Report, WMO UNEP, Geneva.

ntergovernmental Panel on Climate Change, 2003b. Good Practice Guidance forLand Use, Land-Use Change and Forestry. IGES, Kanagawa.

saac, M.E., Gordon, A.M., Thevathasan, N., Oppong, S.K., Quashie-Sam, J., 2005.Temporal changes in soil carbon and nitrogen in west African multistrata

agroforestry systems: a chronosequence of pools and fluxes. Agrofor. Syst. 65,23–31.

saac, M.E., Timmer, V.R., Quashie-Sam, S.J., 2007. Shade tree effects in an 8-year oldcocoa agroforestry system: biomass and nutrient diagnosis of Theobroma cacaoby vector analysis. Nutr. Cycl. Agroecosyst. 78, 155–165.

aramillo, V.J., Kauffman, J.B., Rentería-Rodríguez, L., Cummings, D.L., Ellingson, L.J.,2003. Biomass, carbon, and nitrogen pools in Mexican tropical dry forest land-scapes. Ecosystem 6, 609–629.

otto-Same, J., Woomer, P.L., Mounkan, A., Zapfack, L., 1997. Carbon dynamics inslash-and-bum agriculture and land use alternatives of the humid forest zonein Cameroon. Agric. Ecosyst. Environ. 65, 245–256.

indner, A., 2010. Biomass storage and stand structure in a conservation unit in theAtlantic Rainforest—the role of big trees. Ecol. Eng. 36, 1769–1773.

inkimer, M., Muschler, R., Benjamin, T., Harvey, C., 2002. Árboles nativos para diver-sificar cafetales en la zona Atlántica de Costa Rica. Agrofor. Amér. 9 (35–36),37–43.

ockwood, G., Yina, J.P.T., 1996. Yields of cocoa clones in response to planting densityin Malaysia. Exp. Agric. 32, 41–47.

acDiken, K., 1997. A guide to monitoring carbon storage in forestry and agro-forestry projects. Winrock International, Arlington.

etzker, R., Spósito, T.C., Martins, M.T.F., Horta, M.B., García, Q.S., 2011. For-est dynamics and carbon stocks in Rio Doce State Park, an Atlantic rainforesthotspot. Curr. Sci. 100 (12), 1855–1862.

iles, L., Kapos, V., 2008. Reducing greenhouse gas emissions from defor-estation and forest degradation: global land-use implications. Science 320,1454–1455.

illard, E., 2011. Incorporating agroforestry approaches into commodity valuechains. Environ. Manage. 48, 365–377.

ontagnini, F., Nair, F.P.K.R., 2004. Carbon sequestration: an underex-ploited environmental benefit of agroforestry systems. Agrofor. Syst. 61,281–295.

orel, A.C., Saatchi, S.S., Malhi, Y., Berry, N.J., Banin, L., Burslem, D., Nilus, R., Ong,R.C., 2011. Estimating above ground biomass in forest and oil palm plantationin Sabah, Malaysian Borneo, using ALOS PALSAR data. Forest Ecol. Manag. 262(9), 1786–1798.

air, P.K.R., Kumar, B.M., Nair, V.D., 2009. Agroforestry as a strategy for carbonsequestration. J. Plant Nutr. Soil Sci. 172, 10–23.

fori-Frimpong, K., Afrifa, A.A., Acquaye, A., 2010. Impact of shade and cocoa plantdensities on soil organic carbon sequestration rates in a cocoa growing soil ofGhana. Afric. J. Environ. Sci. Technol. 4 (9), 621–624.

rtiz, A., Riascos, L., Somarriba, E., 2008. Almacenamiento y tasas de fijación debiomasa y C en sistemas agroforestales de cacao (Theobroma cacao) y laurel(Cordia alliodora). Agrofor. Amér. 46, 26–30.

austian, K., Six, J., Elliott, E.T., Hunt, H.W., 2000. Management options for reducingCO2 emissions from agricultural soils. Biogeochemistry 48, 147–163.

eters-Stanley, M., Hamilton, K., Marcello, T., Sjardin, M., 2011. Back to the Future:State of the Voluntary Carbon Markets 2011. Ecosystem Market Place ForestTrends Association and Bloomberg New Energy Finance, USA.

aherison, S.M., Grouzis, M., 2005. Plant biomass, nutrient concentration and nutri-ent storage in a tropical dry forest in the south-west of Madagascar. Plant Ecol.180, 33–45.

ice, R., Greenberg, R., 2000. Cacao cultivation and the conservation of biologicaldiversity. Ambio 29, 167–173.

ita, J.C.O., Gama-Rodrigues, E.F., Gama-Rodrigues, A.C., Polidoro, J.C., Machado,R.C.R., Baligar, V.C., 2011. C and N content in density fractions of whole soiland soil size fraction under cacao agroforestry systems and natural forest inBahia, Brazil. Environ. Manage. 48 (1), 134–141.

olim, S.G., Henrique, R.M.J., Nascimento, H.E.M., do Couto, H.T.Z., Chambers,J.Q., 2005. Biomass changes in an Atlantic tropical moist forest. The ENSO

effect in permanent sample plots over a 22-year period. Oecologia 142,238–246.

ambuichi, R.H.S., 2002. Fitossociologia e diversidade de especies arbóreas emcabruca (mata Atlantica raleada sobre plantac ao de cacau) na regiao sul da Bahía,Brasil. Acta Bot. Brasil. 16 (1), 89–101.

s and Environment 173 (2013) 46– 57 57

Schmitz, H., Shapiro, H.Y., 2012. The future of chocolate. Sci. Am. 2012, 60–65.Schroeder, P., 1994. Carbon storage benefits of agroforestry systems. Agrofor. Syst.

27, 89–97.Schroth, G., Faria, D., Araujo, M., Bede, L., van Bael, S.A., Cassano, C.R., Oliveira, L.C.,

Delabie, J.H.C., 2011. Conservation in tropical landscape mosaics: the case of thecacao landscape of southern Bahia, Brazil. Biodivers. Conserv. 20, 1635–1654.

Seeberg-Elverfeldt, C., Schwarze, S., Zeller, M., 2009. Payments for environmentalservices – carbon finance options for smallholders’ agroforestry in Indonesia.Int. J. Commons 3, 108–130.

Smiley, G.L., Kroschel, J., 2008. Temporal change in carbon stocks of cocoa – Gliricidiaagroforests in Central Sulawesi, Indonesia. Agrofor. Syst. 73, 219–231.

Smit, B., Skinner, M.W., 2002. Adaptation options in agriculture to climate change:a typology. Mitig. Adapt. Strat. Glob. Change 7, 85–114.

Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M.,Miller, H.L. (Eds.), 2007. Climate Change 2007: The physical science basis. Con-tribution of IPCC Working Group I to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change, Cambridge Univ. Press, USA.

Somarriba, E., Andrade, H., Segura, M., Villalobos, M., 2008. ¿Cómo fijar C atmosférico,fijarlo y venderlo para complementar los ingresos de productores indígenas deCosta Rica? Agrofor. Amér. 46, 81–88.

Somarriba, E., Beer, J., Orihuela, J.A., Andrade, H., Cerda, R., DeClerck, F., Detlefsen, G.,Escalante, M., Giraldo, L.A., Ibrahim, M.A., Krishnamurthy, L., Mena, V.E., Mora,J.R., Orozco, L., Scheelje, M., Campos, J.J., 2012b. Mainstreaming agroforestry inLatin AmericaA, Advances in Agroforestry. In: Nair, P.K.R., Garrity, D.P. (Eds.),Agroforestry: the way forward. Springer, USA, 9: 429-453.

Somarriba, E., Villalobos, M., Orozco, L., 2009. Cocoa in Central America. GRO-CocoaBull. 14 (November), 5–9.

Souza, C.A.S., dos Santos Dias, L.A., Aguilar, M.A.G., Sonegheti, S., Oliveira, J., AndradeCosta, J.L., 2009. Cacao yield in different planting densities. Braz. Arch. Biol.Technol. 52 (6), 1313–1320.

Stephan-Dewenter, I., Kesslerc, M., Barkmannc, J., Bosa, M., Buchorig, D., Erasmih,S., Fausth, H., Geroldh, G., Glenke, K., Gradsteind, S.R., Guhardjai, E., Harteveldd,M., Herteld, D., Höhna, P., Kappash, M., Köhlerh, S., Leuschnerd, C., Maertensj,M., Marggrafe, R., Migge-Kleiank, S., Mogeai, J., Pitopangl, R., Schaeferk, M.,Schwarzem, S., Spornd, S.G., Steingrebek, A., Tjitrosoedirdjoi, S.S., Tjitrosoemi-toi, S., Tweleh, A., Weberh, R., Woltmannk, L., Zellerm, M.N., Tscharntkea, T.,2007. Tradeoffs between income, biodiversity, and ecosystem functioning dur-ing tropical rainforest conversion and agroforestry intensification. PNAS 104(12), 4973–4978.

Szott, L.T., Arévalo-López, L.A., Pérez, J., 1993. Allometric relationships in Pijuayo(Bactris gasipaes H.B.K.). In: Mora-Urpí, J., Szott, L.T., Murillo, M., Patino, V.M.(Eds.), Congreso Internacional sobre Biología, Agronomía e Industrialización delPijuayo. San José, pp. 91–114.

Tanaka, A., Yamaguchi, 1972. Producción de materia seca, componentes delrendimiento y rendimiento del grano de maíz. Colegio de postgraduados,Chapingo.

Tscharntke, T., Clough, Y., Bhagwat, S.A., Buchori, D., Faust, H., Hertel, D., lscher,D.H., Juhrbandt, J., Kessler, M., Perfecto, I., Scherber, C., Schroth, G., Veldkamp,E., Wanger, T.C., 2011. Multifunctional shade-tree management in tropical agro-forestry landscapes. J. Appl. Ecol. 48, 619–629.

Van Wagner, C.E., 1968. The line intersect method in forest fuel sampling. ForestSci. 14, 20–26.

Verchot, L.V., Van Noordwijk, M., Kandji, S., Tomich, T., Ong, C., Albrecht, A.,Mackensen, J., Bantilan, C., Anupama, K.V., Palm, C., 2007. Climate change: link-ing adaptation and mitigation through agroforestry. Mitig. Adapt. Strat. Glob.Change 12, 901–918.

Wade, A.S.I., Asase, A., Hadley, P., Mason, J., Ofori-Frimpong, K., Preece, D., Spring,N., Norris, K., 2010. Management strategies for maximizing carbon storage andtree species diversity in cocoa-growing landscapes. Agric. Ecosyst. Environ. 138,324–334.

Whelan, M., Dahlquist, R., Winowiecki, L., Polidoro, B., Candela, S., Harvey, C.,Wulfhorst, J., McDaniel, P., Bosque-Pérez, N., 2007. Incorporating livelihoodsapproach for biodiversity conservation: a case study in cocoa agroforestry sys-tems in Talamanca, Costa Rica. Biodivers. Conserv. 16, 2311–2333.

Winjum, J.K., Dixon, R.K., Schroeder, P.E., 1992. Estimating the global potential offorest and agroforest management practices to sequester carbon. Water Air SoilPollut. 64, 213–223.

Wood, G.A.R., Lass, R.A., 2001. Cocoa, 4th ed. Blackwell Science, Oxford.Woomer, P.L., Palm, C.A., Alegre, J., Castilla, C., Cordeiro, D.G., Hairiah, K., Kotto-Same,

J., Moukam, A., Riese, A., Rodrigues, V., van Noordwijk, M., 2000. Slash-and-burneffects on carbon stocks in the humid tropics. In: Lal, R., Kimble, J.M., Stewart, B.A.(Eds.), Global Climate Change and Tropical Ecosystems. CRC Press, Boca Raton,pp. 99–115.

World Resources Institute, 2005. Climate Analysis Indicator Tool (CAIT), Navi-gating the Numbers: Greenhouse Gas Data and International Climate Policy.

www.lowcarboneconomy.com/Resources/UserImages/06-prob wri-flowchart009Original.jpg (accessed July 2012).

Zuidema, P.A., Leffelaar, P.A., Gerritsma, W., Mommer, L., Anten, N.P.R., 2005. A phys-iological production model for cocoa (Theobroma cacao): model presentation,validation and application. Agric. Syst. 84 (2), 195–225.