Sustainability of holistic and conventional cattle ranching in the seasonally dry tropics of Chiapas, Mexico

Agricultural Systems 120 (2013) 38–48

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Sustainability of holistic and conventional cattle ranching in the seasonally dry tropics of Chiapas, Mexico Bruce G. Ferguson a,⇑, Stewart A.W. Diemont a,b, Rigoberto Alfaro-Arguello a, Jay F. Martin c, José Nahed-Toral a, David Álvarez-Solís a, René Pinto-Ruíz d a Departmento de Agroecología, El Colegio de La Frontera Sur, Carretera Panamericana y Periférico Sur s/n, María Auxiliadora San Cristóbal de Las Casas, Chiapas, San Cristóbal de Las Casas, Chiapas, CP 29290, Mexico b Department of Environmental Resources Engineering, State University of New York, College of Environmental Science and Forestry, 1 Forestry Drive, Syracuse, NY 13210, USA c Department of Food, Agricultural, and Biological Engineering, Ecological Engineering Program, The Ohio State University, 590 Woody Hayes Dr., Columbus, OH 43210, USA d Facultad de Ciencias Agronómicas, Universidad Autónoma de Chiapas, Apdo. Postal 63, Villaflores, Chiapas CP 30470, Mexico

a r t i c l e

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Article history: Received 30 September 2012 Received in revised form 11 March 2013 Accepted 12 May 2013 Available online 18 June 2013 Keywords: Dairy farming Ecological restoration Farmer-to-farmer training Fire Rotational grazing Silvopastoral systems

a b s t r a c t Conventional cattle ranching in the lowlands of Chiapas, Mexico typically employs extensive grazing, annual pasture burns and frequent applications of agrochemicals, threatening biodiversity and long-term productivity. A small group of innovative ranchers in the Central Valleys are converting to holistic management through careful land-use planning, rotational grazing, diversified forage, and diminished use of purchased inputs. We compared the sustainability of 18 conventional and seven holistic, dual-purpose ranches, using three sets of sustainability metrics. First, we combined semistructured interviews and field observations to better describe the two productions systems and to calculate an ‘‘Organic Conversion Index’’ (OCI), combining economic, social, technological and environmental indicators. Holistic ranchers have more pasture divisions, higher grazing pressure, greater lengths of time between pasture burns, greater milk productivity, larger forest reserves, lower cow and calf mortality, purchase less hay and feed, and use less herbicides and pesticides than their conventional neighbors (T-tests and Fisher’s Exact Tests; all p < 0.05). OCI was greater (T-test, p < 0.0005) for holistic ranches (81.8 ± 4.6% compliance with organic standards), than for conventional ranches (32.1 ± 9.0% compliance), with holistic ranches demonstrating superiority for nine of ten OCI indicators. Second, drawing on data from the same interviews, we conducted ‘‘emergy’’ analysis to quantify the embodied energy of inputs, outputs and sustainability of the ranching systems. The Emergy Yield Ratio, an index of a systems emergy throughput relative to the emergy in purchased inputs, was marginally higher in holistic ranches (T-test; p = 0.07), but became significant when only ranches P40 ha were analyzed (p = 0.04) and when government assistance (mostly in the form of machinery) was removed from the calculations (p = 0.008). Holistic ranches exhibited marginally higher Emergy Sustainability Indices, a measure of system yield relative to environmental impact, for all ranches combined (p = 0.07) and for ranches P 40 ha (p = 0.06). Third, we sampled vegetation and soils on seven holistic and seven conventional ranches. We found higher soil respiration, deeper topsoil, increased earthworm presence, more tightly closed herbaceous canopies (all p < 0.05), and marginally greater forage availability (p = 0.053) in holistic ranches. Other variables, including soil compaction, soil chemistry and pasture tree cover, did not differ significantly between groups. These data are a snapshot of long, complex processes. Nonetheless, these complementary metrics combine to suggest that holistic management strategies are leading to greater ecological and economic sustainability. This production model merits further study for potential broader application as well as greater attention from decision makers concerned with ranching and the environment. Ó 2013 Elsevier Ltd. All rights reserved.

1. Introduction Livestock production is among the fastest growing economic sectors in the developing world (Delgado et al., 1999; Steinfeld ⇑ Corresponding author. Tel.: +52 967 674 9000x1406; fax: +52 967 674 9021. E-mail address: [email protected] (B.G. Ferguson). 0308-521X/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.agsy.2013.05.005

et al., 2006) and constitutes a pillar of the rural economy in Chiapas (Jiménez Ferrer et al., 2003). Raising livestock contributes to the food sovereignty of farm families and is a savings strategy for small producers that allows them to confront emergencies and better capitalize on their production systems (Delgado et al., 1999; Jiménez Ferrer et al., 2003; Kaimowitz, 1996). Extensive ranching is also attractive to large producers as labor costs are low in

B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

relation to the land area managed (Hecht, 1993; Kaimowitz, 1996; White et al., 2001). Cattle ranching in tropical Latin America has been based largely on extensive monocultures of grass, a production model poorly suited to the region (Murgueitio et al., 2011; Sánchez et al., 2000). These artificial grasslands are inefficient and fragile, exhibiting low productivity and nutritional value while being highly susceptible to soil and pasture degradation, especially when subjected to over- or under-grazing (Van Soest, 1982; Savory and Butterfield, 1999; Serrão and Toledo, 1990; Szott et al., 2000). This deficiency is particularly marked during the dry season, when ranchers must allow livestock to forage over a larger area and/or increase feed supplements (Szott et al., 2000), increasing their negative impact. Frequent burns exacerbate pasture degradation and threats to the surrounding landscape. Pasture burns provide multiple shortterm benefits, including elimination of unpalatable plants and lignified grass, promotion of tender new grass growth, a pulse of nutrients released into the soil and control of herbivorous insects, plant pathogens and ticks (Savory and Butterfield, 1999; Villanueva Avalos et al., 2008). However, burns can also diminish soil fertility and the structural and biological diversity of the plant community (Savory and Butterfield, 1999; Vieira and Scariot, 2006). These fires often get out of control, burning neighboring forests and farms (Román-Cuesta et al., 2003). The combination of low productivity, rapid degradation and fire contributes to the extensive nature of tropical cattle ranching, and its association with deforestation and biodiversity loss (FAO/EMBRAPA, 2001; Murgueitio et al., 2011; Villafuerte et al., 1997). Soil and pasture degradation and biodiversity loss lead to increased dependence on herbicides, pesticides, fertilizers and feed supplements, which in turn reduces profit margins. In the face of these limitations, a small group of dual-purpose (milk and meat) ranchers in the Central Valleys of Chiapas have turned to the holistic management (HM) decision-making framework described by Savory and Butterfield (1999). Under HM, management decisions are based upon relationships among the landscape (including wild and managed biodiversity, water, soil and other resources), people (farmers and ranchers and their families, neighbors, suppliers, customers, advisers, regulators and so on), the broader community in which they live, and the services available in that community. In ‘‘brittle’’ environments like our study area, where humidity is particularly uneven throughout the year, HM advocates managing high densities of large herding animals to produce heavy grazing and trampling impact for brief periods at appropriate intervals. With support and training from FIRA (Avalos Flores et al., 1996), visiting Cuban extensionists and faculty at the Autonomous University of Chiapas, the ten ranchers formed an ‘‘Intensive, Technical Grazing’’ club (‘‘PIT Las Villas’’) in 1994. Seven of the original club members continue to practice HM. Core elements of their management strategy include: holistic decision making, farmer-to-farmer training, Voisin-style rotational grazing (Voisin, 1959), reduction in the frequency of burns, major reductions in agrochemical use, careful record keeping, diversification of forage resources and maintenance of forest reserves. Proponents of HM present empirical evidence of its potential for simultaneously improving productivity and protecting the environment (Savory and Butterfield, 1999, www.holisticmanagement.org). However HM has not been widely studied from a scientific perspective and findings have been contradictory (Teague et al., 2011). To evaluate HM’s sustainability, we compared the ranches of the members of PIT Las Villas with those of their ‘‘conventional’’ neighbors using three sets of metrics: compliance with organic standards used to calculate an Organic Conversion Index (OCI), emergy analysis of inputs, outputs and overall

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sustainability, and measurement of vegetation diversity and soil parameters that indicate system health. 2. Materials and methods 2.1. Study sites and participants We worked on ranches in the communities of Cuahtémoc, La Sirena, Joaquín Miguel Gutiérrez, Villa Hidalgo, and Dr. Domingo Chanona in the Villaflores Municipality and Emiliano Zapata and Revolución Mexicana in the Villacorzo Municipality. These sites are located between 540 and 580 masl, between 16°100 and 16°140 N, and between 93°02 and 93°160 W (Fig. 1). This area, in the Frailesca region of the Central Valleys of Chiapas, is classified as hot and humid but has a marked dry season (INEGI, 2011). The dominant native vegetation is tropical deciduous forest; selva baja caducifolia in the Rzedowski (1981) classification (SEPLAN, 2000). Average annual temperature is 24.9 °C and precipitation is 1168 mm per year. Alluvial and colluvial soils dominate (INEGI, 2011). Participating ranchers included all seven members of the ‘‘Club de Pastoreo Intensivo Las Villas’’ who are still practicing HM (holistic ranchers or the HM group), having modified their management as a result of short courses and the exchange of experiences among ranchers. Eighteen conventional ranchers (conventional ranchers or the CM group), chosen from the membership of the local ranchers’ associations for their proximity to the holistic ranches and their willingness to contribute to the research, served as a comparison group. 2.2. Sampling 2.2.1. Description of the production systems and their approximation to the organic model We conducted semistructured interviews (Vela, 2001) with the 25 participating ranchers between June and September 2007 to document resource use, productivity, and management techniques within their cattle production systems. Except where a longerterm focus was appropriate, we requested information specific to the previous calendar year. As one indication of sustainability, we integrated technological, economic, environmental and social information to calculate organic conversion indices (OCI) for each farm. The OCI was based upon international organic standards (UE, 1991; IFOAM, 2005) and the consensus of a group of experts (Nahed et al., 2009; Mena et al., 2012). It consists of 10 composite indicators, including feeding management, pasture management, weed control, pest control, and animal well-being. Each indicator is scored from 0 to 100%, weighted according to its importance in the organic standards, and finally all of the indicators are averaged to obtain the overall OCI. 2.2.2. Emergy analysis We have published detailed methods and findings of our emergy analysis in Agricultural Systems (Alfaro-Arguello et al., 2010), and summarize them here to facilitate understanding of the suite of methods employed. Emergy analysis evaluates diverse flows of energy and materials through systems using common units (solar emjoules, sej) to provide a broad view of the impact of management choices on sustainability. This is accomplished by converting all aspects of a material or product’s embodied energy into solar emjoules (sej). Conversion of other embodied energy measures to sej, through previously calculated conversion factors, permits all inputs to the system to be quantified, allowing meaningful evaluation of entire systems. Important outcomes of emergy analysis

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B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

Fig. 1. Study area with locations of ranches where vegetation and soils were sampled (map produced by Laboratorio de Informacion Geográfica, El Colegio de la Frontera Sur).

are measurements of resource use efficiency and environmental impact, including the Emergy Yield Ratio (EYR), the Environmental Loading Ratio (ELR) and the Emergy Sustainability Index (ESI). The EYR is a measure of the emergy the system receives from local renewable or non-renewable sources and purchased inputs relative to the emergy input purchased from the broader economy. The ELR is the ratio of non-renewable to renewable resource consumption. ESI, the ratio of EYR to ELR, balances the yield of the system in emergy terms against the impact of the system on the environment (Brown and Ulgiati, 1997). Thus ESI differentiates more sustainable systems from less, by accounting for the environmental load when examining the emergy output. Based on interviews, we constructed a generalized scheme of the inputs, outputs and stores of energy on the ranches (Fig. 2). Questions were incorporated into our semistructured interviews to quantify each element of the emergy diagram for each ranch. Local climate data was obtained from SAGARPA, the agriculture and livestock secretariat. 2.2.3. Evaluation of pasture vegetation and soils The survey data was complemented with a set of measurements quantifying several indicators of soil and pasture health. Between May and August, 2007, the first months of the rainy season, we sampled the seven holistic ranches and seven conventional ranches. We selected larger conventional ranches to minimize differences in ranch size between the groups. To further maximize

comparability among ranches, we sampled only pastures dominated by African star grass (Cynodon plectostachyus) the most commonly planted pasture grass in the region. At each ranch, we sampled two pastures; one freshly grazed, and the other approaching the maximum recovery period allowed by each rancher’s grazing system (26.6 ± 14.9 d in the conventional systems and 26.4 ± 4.8 d in the holistic systems). Following Herrick et al. (2005), we sampled soil and vegetation along three transects, measuring a total of 150 m and radiating from a central point in each pasture. By default, transect length and angles between transects were equal, but were modified when necessary to adapt to the shape of the pasture. Transects began 5 m from the central point to avoid overlapping measurements and the effects of trampling. In smaller pastures, some transects ended at fence lines. 2.2.3.1. Vegetation cover and diversity. The herbaceous stratum of the vegetation was characterized utilizing the line-point intercept method (Herrick et al., 2005). Sampling points were distributed uniformly along the three transects to achieve a sampling intensity of 150 points/pasture sampled. At each point, we dropped a thin, 1 m rod vertically to the ground and recorded the soil cover at the rod tip as well as the plant species touching the rod in the lower (<50 cm) and upper (50–100 cm) canopy of the herbaceous layer. Along the same linear transects, we applied the gap intercept method (Herrick et al., 2005) to quantify gaps in the herbaceous

B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

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Fig. 2. Generalized emergy diagram of ranching systems in the Frailesca region of Chiapas, Mexico.

canopy. As an indicator of susceptibility to wind erosion, we recorded the beginning and end of each patch of exposed soil >20 cm intersected by the transect using a vertical projection from the herbaceous canopy to the soil surface. We also measured patches of exposed soil at ground level >20 cm as an indicator of susceptibility to water erosion and weed invasion. Woody vegetation was censused using six m wide belt transects (Mostacedo and Fredericksen, 2000; Herrick et al., 2005) along these same lines (900 m2/pasture), recording species, height, DBH (for individuals P1 cm dbh) and crown projection area over the transect for each individual P25 cm tall. Based upon these data, we calculated woody stem density and basal area of each species. 2.2.3.2. Available forage. We estimated forage availability using the comparative yield method (Haydock and Shaw, 1975). For each pasture, we selected five 50  50 cm reference quadrats to define the full range of forage conditions. Following the sample size recommendations of Mostacedo and Fredericksen (2000), we visually estimated pasture availability in 30 randomly placed quadrats by assigning each a value from one to five according to the reference quadrat to which its biomass was most similar. Aboveground biomass from each reference quadrat was harvested, dried at 28 °C, and weighed. We then calculated a weighted average of the dry weight of available forage by multiplying the number of visual sampling quadrats assigned to each reference quadrat,by the biomass of that reference quadrat and dividing by 30. 2.2.3.3. Soil sampling and analysis. We took 28 subsamples from each pasture using a 35 mm diam. soil corer at a depth of 20 cm, in a zigzag pattern along the same transects used for vegetation sampling. We combined these subsamples in a composite soil sample for each pasture that we then air dried and sieved (<2 mm for all the analyses; <0.5 mm for organic matter and total N). Samples

were analyzed for apparent bulk density (cylinder), texture (Bouyoucos hydrometer method), organic matter (wet digestion of Walkley and Black), total N (micro-Kjeldahl), pH (1:2 soil/water ratio), electrical conductivity (1:50 soil/water ratio), extractable P (NaHCO3 0.5 M, pH 8.5) and exchangeable potassium (ammonium acetate 1 N pH 7). Management can be expected to have little influence on soil texture on the decadal scale relevant to this study. Thus any differences in soil texture between management types would indicate differences existing prior to adoption of HM. We measured depth of soil horizons in one 30 cm cubic soil pit in each pasture. We counted earthworms and white grubs in soil removed from these same pits. We took 200 g samples from the pits for soil microbial respiration analysis. We air dried the samples, sieved them through 2 mm mesh, and quantified CO2 production using Stotzky’s (1965) method. Analyses were performed at the El Colegio de la Frontera Sur laboratory in San Cristóbal de Las Casas, in accordance with Mexican standards (Norma Oficial Mexicana NOM-021-RECNAT-2000). 2.2.3.4. Statistical analysis. We performed T-tests to compare continuous, descriptive variables, organic conversion indicators, emergy indices, resource use, and the density and basal area of tree and shrub species between ranch types. Where variances were unequal (alpha = 0.05), we applied T-tests for unequal variance. We used Fisher’s Exact Test to identify differences between ranch types for binomial descriptive data. The relationship of emergy indices to resource use and management techniques was examined using Pearson’s linear regression and ANOVA. For variables that could be affected by the rest period of the pastures (erosibility, invasibility, ground cover, available grass forage, and soil parameters), we applied repeated measures ANOVA’s to look for differences between ranch types and rest periods. When data did not meet the sphericity criterion, we report F and p values using the Greenhouse–Geisser

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correction. We report statistics for ranch type-rest period interaction only for the single variable for which the interaction was significant. We performed all analyses using SPSS 12 and 14.

3. Results 3.1. Ranch descriptions and OCI 3.1.1. Descriptive data As is typical for the region, most of the participating ranchers produce animals for both milk and meat, including cattle that are shipped from the state live for fattening elsewhere. One of the holistic ranchers is recognized for his skill as a livestock breeder and boosts profits by sale of breeding stock and semen. Most of the holistic ranchers are members of a cooperative that produces the feed supplement they use (Albafrai), using mostly inputs that they grow themselves. Two of the holistic ranches studied essentially act as intermediaries, purchasing cattle from local producers, fattening them for a few weeks or months, and then exporting them directly to the United States. These ranches have high cattle turnover, use more feed supplements, and enjoy higher profits than the rest of the ranches; consequently, their business and production models differ in important ways from the other holistic ranchers. For this reason, we excluded them from elements of the analysis for which they were outliers (Table 1). As Table 1 indicates, holistic ranches differ from conventional ranches in many ways. Holistic ranchers have more land and pasture area, and dedicate more of their pastures to CT-115 (a Pennisetum purpureum variety developed in Cuba for cutting or forage banks), and more of their land to forests. They use electric fences more often, have more pasture divisions/ha, run larger herds, apply greater grazing pressure, provide more feed supplement, and depend less on baled hay. They also apply less herbicide, have gone without burning for longer periods, and have lower mortality of calves and cows than conventional ranches (Table 1). The measured differences stem from the HM approach. For instance, holis-

tic ranchers described forests as productive land, and two of them have registered forest management plans that allow for rotational timber harvests. One rancher mentioned that he leaves his hills forested to protect the springs that irrigate his pastures below. Another allowed forests to regenerate to protect a riparian area. They also mentioned use and conservation of trees in pastures, including guanacastle (Enterolobium cyclocarpum), guava (Psidium guajava), caulote (Guazuma ulmifolia), and espino blanco (Acacia farnesiana). Holistic ranchers, in contrast with most of their conventional counterparts, noted the presence on their land of wildlife including wild boars, deer, ocelots, and anteaters and actively protect these animals. On average, holistic ranches are substantially more productive and profitable than conventional ranches, but because of the variability in these economic data, the only statistically significant difference (p = 0.026) was for milk productivity. Expenses on a unit area basis were about the same for the two groups. Variation in profitability among ranches may be largely a result of differing livelihood strategies. For some ranch owners the ranch is a primary source of work and income, while others work off-farm, investing much less time and effort in their ranches. 3.1.2. Organic conversion index Holistic ranches had higher and less variable weighted organic conversion indices (OCI) than the CM ranches (Table 2; T-test, p < 0.0005). OCI was positively related to ranch size when all ranches were pooled (linear regression; R2 = 0.43, p < 0.0005). However this relationship disappeared when conventional and holistic ranches were analyzed separately (R2 = 0.034, p = 0.46 and R2 = 0.033, p = 0.70, respectively) and can therefore be attributed to differences between the two groups other than production scale. Holistic ranches were substantially closer than conventional ranches to meeting organic standards for nine of the ten groups of criteria that comprise the OCI, and these differences were statistically significant (Table 2). Many of the differences detected relate to contrasting approaches to pasture management. Pastures on

Table 1 Descriptive data for ranches and ranchers and t-tests for differences between conventional (n = 18) and holistic (n = 7) ranches. For binomial data (t statistics not reported), p values are for Fisher’s Exact Test. Bold type indicates significant differences between ranch types.

Formal education (yr) Cattle ranching experience (yr) Holistic ranching experience (yr) Ranch size (ha) Annual crops (% of ranch area) Star grass (% of ranch area) CT115 (% of ranch area) Pasture area (ha, w/o CT 115)) Divisions/ha of pasture Electric fence use (%) Herd size (AU) Grazing pressure (AU/ha pasture) Hay bales purchased (T/yr) Feed per AU (kg/yr)a Time since last burn (yr) Herbicide use (L/ha) Pesticide use in pastures (L/ha) Calf mortality (%/yr) Cow mortality (%/yr) Forest area (% of ranch) Forest management plan (%) Milk productivity ((L/ha pasture)/yr)a Live weight gain ((kg/ha)/yr) Expenses/ha (pesos/yr)a Profit/ha (pesos/yr)a Net ranch profit (pesos/yra a

Conventional ( x± s.d.)

Holistic ( x ± s.d.)

t

p

10.5 ± 5.2 28.1 ± 10.2 0.0 ± 0.0 38.3 ± 18.3 0.4 ± 1.2 38.4 ± 22.8 0.8 ± 1.7 34.9 ± 17.7 0.3 ± 0.1 38.9 ± 50.2 58.6 ± 39.2 1.9 ± 0.9 144 ± 123 321 ± 271 2.0 ± 1.6 0.8 ± 0.3 0.036 ± 0.095 7.0 ± 2.9 4.9 ± 3.2 7.0 ± 5.9 0.0 ± 0.0 1760 ± 1909 262 ± 372 5116 ± 3647 3829 ± 8372 141,117 ± 351,501

13.0 ± 3.2 33.1 ± 11.8 10.1 ± 2.3 88.3 ± 42.9 4.4 ± 7.7 22.5 ± 5.8 17.7 ± 13.1 66.0 ± 30.9 1.8 ± 0.9 100.0 ± 0.0 203.6 ± 113.5 3.2 ± 1.3 0.0 ± 0.0 830 ± 127 19.4 ± 9.2 0.0 ± 0.1 0.0 ± 0.0 2.4 ± 0.9 1.1 ± 0.2 19.8 ± 10.5 28.6 ± 48.8 4310 ± 2771 1084 ± 1527 5270 ± 1850 10,972 ± 7908 1,273,871 ± 1,647,928

1.17 1.06 11.83 2.98 1.39 1.80 3.40 2.51 3.61

0.253 0.300 <0.0005 0.021 0.266 0.085 0.014 0.038 0.011 0.008 0.014 0.007 <0.0005 0.001 0.002 <0.0005 <0.0005 <0.0005 <0.0005 0.001 0.070 0.026 0.21 0.201 0.103 0.200

Denotes data that exclude two holistic ranches that export live cattle directly to the United States.

2.57 2.93 4.95 4.02 5.00 6.43 27.0 4.06 4.95 3.04 2.40 1.43 1.71 1.53

B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

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Table 2 Organic conversion indices and their component indicators. Descriptions typify practices of the majority of ranchers in each category. Bold text indicates significant differences between ranch types. Nahed et al. (2009) and Mena et al. (2012) explain the indicators, their constituent variables and their weighting. Indicator

Conventional ( x ± s.d.)

Livestock nutrition

59.7 ± 12.5

96.4 ± 9.4

Pasture management

28.9 ± 14.1

85.7 ± 25.1

Soil fertility management

11.1 ± 32.3

Weed control in pastures and crops

0.0±0.0

Holistic ( x ± s.d.)

100.0 ± 0.0 85.7 ± 37.8

T

p

Description (B = Both, C = Conventional; H = Holistic)

6.98

<0.0005

5.66

0.001

7.18

<0.0005

6.00

0.001

B: grazing C: commercial feed, chicken manure H: locally-sourced feed C: extensive grass monocultures H: rotational grazing, legumes, fodder trees C: chemical fertilizers H: manure collected and spread, grazing management C: herbicides, burns H: grazing management, selective manual weeding C: insecticides, burns H: grazing management, forage diversity B: internal parasite treatment, chemical tick control, allopathy C: obligatory vaccinations (50%) H: obligatory vaccinations, new animals quarantined B: locally adapted breeds, natural breeding C: inadequate space, grazing time, water, food H: adequate space, grazing time, water, food; juvenile dehorning B: cattle free of brucellosis, tuberculosis C: inadequate milking parlor hygiene; hormones, antibiotics, pesticides may taint products H: good milking parlor hygiene; products free of hormones, antibiotics, pesticides B: no organic commercialization C: little training,planning or record keeping for organic production H: training, planning and record keeping for organic production

Pest control in pastures and crops

11.1 ± 32.3

100.0 ± 0.0

7.18

<0.0005

Veterinary care, prophylaxis

31.3 ± 24.0

62.5 ± 0.0

5.53

<0.0005

Breeds and breeding Animal welfare

97.2 ± 11.8 26.9 ± 30.9

100.0 ± 0.0 88.1 ± 8.1

0.62 7.76

0.544 <0.0005

Food safety

51.4 ± 16.0

100.0 ± 0.0

12.91

<0.0005

2.2 ± 6.5

40.0 ± 0.0

15.25

<0.0005

32.1 ± 9.0

81.8 ± 4.6

13.73

<0.0005

Ecological administration

Weighted organic conversion indexa

conventional ranches are typically extensive grass monocultures, while holistic ranchers practice rotational grazing and diversify fodder with legumes and forage trees. CT-115 is a key resource on the holistic ranches. Its deep roots maintain forage production even in the dry season, reducing the need for purchased feed or larger grazing areas. Holistic ranchers are experimenting with polycropping CT-115 with fodder trees and herbaceous legumes. Conventional ranchers use chemical fertilizers, while holistic ranchers rely exclusively on manure and careful grazing management to maintain soil fertility. While conventional ranchers use herbicides and fire to control weed invasion, holistic ranchers prevent weeds through careful grazing management, removing only those plants that cattle do not eat or that scratch their udders. Only one holistic rancher uses herbicide, which he applies selectively. Conventional ranchers control pasture and crop pests including spittlebugs (Aeneolamia postica, Cercopidae), grass loopers (Mocis latipes, Noctuidae), cutworms (Agrotis ypsilon, Noctuidae) and cabbage loopers (Trichoplusia ni, Noctuidae) with pesticides. Holistic ranches control pasture and crop pests by maintaining greater forage diversity. For example, a cabbage looper outbreak that occurred during our field season devastated African star grass pastures in the region, but holistic ranchers fell back upon their stands of CT 115 which was protected by the pubescence of its leaves. At least one rancher also achieved some degree of control by sending his cattle into pasture divisions along the advancing front of the outbreak where they trampled the caterpillars and competed with them for grass. Approaches to livestock nutrition, health and well being also differ between ranch types. While animals on both types of ranches get most of their food by grazing, conventional ranches rely more heavily on commercial concentrates and chicken manure for animal feed. The holistic ranchers also offer supplemental feed, but this is produced from grains, soy and molasses from their own farms and other local sources. Although holistic ranchers express

some skepticism with regard to livestock vaccinations, they comply with minimal vaccination requirements, as do half of the conventional ranchers interviewed. Holistic ranchers also protect their herds by placing newly acquired or sick animals in quarantine, a practice adopted by only a third of conventional ranchers. Most ranchers from both groups treat their animals for internal parasites on an appropriate schedule. Both groups rely upon allopathic medicine to treat sick animals and upon chemical control for ticks. None of the ranchers interviewed uses herbal or other alternative remedies. All of the ranches use breeds appropriate to the region, particularly brown Swiss or brown Swiss crossed with Cebu or other breeds. They rely principally upon natural breeding and renew their breeding stock regularly. These facts account for their nearly identical breeds and breeding scores in the OCI metric. In contrast with most conventional producers, holistic ranchers provide adequate space and protection from inclement weather for their livestock, and dehorn calves to minimize injuries. All holistic ranchers and more than half of conventional ranchers provide adequate infrastructure for provision of food and water. Few ranchers in either group allow their calves access to maternal milk for sufficient time to meet organic standards; many holistic ranchers wean their calves just after they have consumed the colostrum. Ensuring food safety is another area in which holistic ranchers set themselves apart, meeting all of the relevant standards. By contrast, only 22% of conventional ranchers provide adequate hygiene in their milking facilities, and none can demonstrate that his or her products are free of hormones, antibiotics and pesticides. Neither group of ranchers performs well according to criteria for ecological ranch administration. The higher scores of the holistic ranchers stem from the training they have received in organic production and how they monitor aspects of their ranches relevant to organic production. However neither group participates in organic or other markets that ensure preferential prices for ecologically oriented production.

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3.2. Emergy analysis Initial emergy analysis revealed tendencies toward greater resource use efficiency (EYR) and sustainability (ESI) in the holistic ranches, but because of high variances we found no significant differences (Alfaro-Arguello et al., 2010; Table 3). Although emergy calculations are normalized for land area, the difference in mean ranch size between holistic and conventional ranches might have introduced a bias in the tendencies we observed. To minimize potential ranch size effects, we repeated the analysis excluding the nine conventional ranches under 40 ha. The remaining nine conventional and seven holistic systems did not differ in size (p = 0.11), and displayed similar tendencies in emergy indices to those observed in the initial analysis. In fact, when we compared similarly sized systems, the tendency toward greater EYR for holistic ranches became significant because of reduced variance within the conventional group (Table 3). A more detailed assessment of resource use indicated that government assistance in the form of machinery dominated the purchased resources (F) in holistic systems and contributed significantly to variance within the group. To better understand the influence of government assistance on sustainability, we repeated the emergy analysis without government assistance. The result was a wider sustainability gap between holistic and conventional ranches, with significant differences for both EYR and ESI (p = 0.008 and 0.01, respectively). With government assistance, F in conventional and holistic systems is statistically equivalent (Alfaro-Arguello et al., 2010). When government assistance is removed, labor dominates the purchased resources in holistic systems. In conventional systems, labor, nitrogen fertilizer, and cattle feed play roughly equal roles in the purchased components of the system. We presented detailed findings of the emergy analysis in AlfaroArguello et al. (2010). 3.3. Vegetation and soil sampling Line-point intercept data revealed no significant differences in bare soil or in cover of individual species between holistic and conventional ranches (repeated measures ANOVAs; all p > 0.1). Table 4 lists cover by species on the two ranch types and in the two vegetation layers sampled (0–50 and 50–100 cm). The comparative yield method found marginally more forage availability on holistic pastures than conventional pastures (Table 5a). There was significantly more forage available on rested pastures than on freshly grazed pastures (F1,12 = 34.51, p < 0.0005) and no significant interaction between management type and rest period. The gap intercept method found more space between plants in conventional than in holistic ranches at both the ground and herbaceous canopy levels (Table 5a). For the ground level measurements, there were also significant effects of rest period (a larger percentage of gaps in recently grazed pasture; F1,12 = 5.76,

p = 0.034) and of rest period-management interaction (F1,12 = 6.78, p = 0.023). Subsequent independent-sample T-tests for ground-level vegetation gaps found no significant differences between rest periods for conventional or holistic pastures, and significant management effects only for freshly grazed pastures, where conventional pastures exhibited a larger percentage of gaps (Table 5b). Basal area of trees (Table 6) in holistic pastures averaged 51% greater than in conventional pastures, while woody stem density averaged 3.59 times greater in holistic pastures. These differences were particularly marked for leguminous species. However variance among ranches was high and the differences were not statistically significant, either for all species pooled or for individual species (T-tests; all p > 0.1). The area directly under tree or shrub canopies averaged 1722 ± 1361 m2/ha on conventional ranches and 1606 ± 1639 m2/ha on holistic ranches. Most physical soil properties (penetrability, bulk density, texture) did not differ between ranch types (Table 7), although holistic ranches had significantly thicker A horizons than conventional ranches (F1,12 = 7.98, p = 0.015). Soil chemical properties (pH, P, OM, total N, CEC) did not differ between ranch types (Table 7). Among biological indicators, both microbial respiration rate (F1,12 = 13.5, p = 0.003) and the presence of earthworms (F1,12 = 9.72, p = 0.009) were significantly greater in the soils of holistic ranches, while the presence of white grubs did not differ between ranch types. 4. Discussion Murgueitio et al. (2011) call for a new production paradigm for Latin American cattle ranching based upon increasing plant diversity and biomass, protecting and restoring soils, protecting water resources and increasing livestock productivity. The holistic ranchers in our study exemplify one pathway toward sustainable cattle ranching. They appear to have achieved important advances in ecological and economic sustainability as measured by a variety of indicators. We found significant advantages of holistic over conventional management (p < 0.05) in frequency of pasture burns, purchased feed, hay and herbicide, cow and calf mortality, forest cover, milk productivity (Table 1), compliance with organic production standards (Table 2), some emergy indices (Table 3), herbaceous cover (Table 5), topsoil depth, and soil biological activity (Table 7). For many other indicators (e.g. profits, tree cover, available forage), variation within each group was high and we did not discover significant differences. Conventional ranches were not superior for any indicator. However productivity and stocking density data for intensive silvopastoral systems (Murgueitio et al., 2011) suggest that holistic ranchers could further boost production by increasing woody plant density and further diversification of pasture grasses. Intensive silvopastoral systems have >10,000 trees and shrubs per ha, compared to an average of <700 on the holistic ranches’ star grass pastures. Their milk productivity can be more than double that of the HM ranches participating in our study.

Table 3 Results of T-tests comparing emergy indices between conventional and holistic ranches (Alfaro-Arguello et al., 2010.). Bold text indicates significant differences. Ranch type

n

Emergy yield ratiio

Environmental loading ratio

Emergy sustainability index

 x± s.d.

p

 x± s.d.

p

 x± s.d.

p

All ranches

Conventional Holistic

18 7

1.6 ± 0.3 2.0 ± 0.5

0.07

2.6 ± 1.8 1.8 ± 1.2

0.27

1.0 ± 0.7 1.6 ± 0.9

0.07

Ranches P40 ha

Conventional Holistic

9 7

1.6 ± 0.2 2 ± 0.5

0.04

2.6 ± 1.3 1.8 ± 1.2

0.21

0.74 ± 0.4 1.6 ± 0.9

0.06

All ranches, govt. assistance excluded from indices

Conventional Holistic

18 7

1.7 ± 0.4 2.2 ± 0.4

0.008

2.2 ± 1.4 1.2 ± 0.3

0.09

1.1 ± 0.73 2.0 ± 0.74

0.01

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B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

Table 4 Ground cover by layer and ranch type as measured by the line-point intercept method. There were no statistically significant differences between management strategies for any species (p > 0.1). Values for the two pastures sampled at each ranch were averaged before calculating standard deviations (N = 7 for each ranch type). Family

Species

% Cover (mean ± s.d.) 0–50 cm layer

50–100 cm layer

Conventional Convolvulaceae Cucurbitaceae Cyperaceae Euphorbiaceae Fabaceae

Lamiaceae Malvaceae Nyctaginaceae Poaceae

Solanaceae

Ipomoea triloba Cucurbita sp. Cyperus odoratus Euphorbia heterophylla Euphorbia hirta Arachis pintoi Calopogonium coeruleum Mimosa albida Mimosa sp. Lippia graveolens Sida acuta Boerhavia erecta Brachiaria mutica Cenchrus echinatus Cynodon dactylon Cynodon plectostachyus Epicampes macroura Hyparrhenia rufa Leptochloa filiformes Opizia stolonifera Urochloa brizantha Physalis pubescens No vegetation Total number of species

0.1 + 0.3 0.1 ± 0.2 0.0 ± 0.1 0.1 ± 0.3 0.1 ± 0.2

2.2 ± 3.1 0.1 ± 0.4 0.1 ± 0.3 0.9 + 2.4 0.2 ± 0.4 1.7 ± 4.4 1.7 ± 4.2

Holistic

Conventional

0.1 ± 0.2

0.0 ± 0.1

0.4 ± 1.0 0.3 ± 0.9 0.2 ± 0.4 0.7 ± 1.6 0.6 ± 0.8 0.0 ± 0.1 0.0 ± 0.1 0.5 ± 0.9 2.2 ± 2.3 0.2 ± 0.6

1.5 ± 2.6

0.5 ± 0.6 2.0 ± 4.7 0.2 ± 0.3

10.0 ± 12.2

82.5 ± 16.3

4.9 ± 6.2 0.5 ± 1.3 0.2 ± 0.5 86.4 ± 11.2

13

17

Holistic

0.0 ± 0.1

0.3 ± 0.6

0.1 ± 0.3

0.2 ± 0.3

0.0 ± 0.1 2.4 + 4.1 79.3 ± 15.4

0.0 ± 0.1 0.5 ± 0.8 0.1 ± 0.3

7.0 ± 9.8

92.5 ± 14.8 0.1 ± 0.4 0.6 ± 0.9 0.0 ± 0.1 5.1 ± 11.8 0.1 ± 0.4 0.0 ± 0.1 0.8 ± 1.7

11

11

3.4 ± 5.5 0.0 ± 0.1 5.6 ± 6.9

Table 5 Pasture indicators. (a) Repeated measures ANOVA’s for forage availability and gaps in the herbaceous canopy and ground cover as measured by the comparative yield method and the gap intersect method respectively. Forage availability was greater (p < 0.0005) and ground level vegetation gaps less prevalent (p = 0.034) in rested than in freshly grazed pastures, while rest period had no effect on gaps in the herbaceous canopy (p = 0.54). The interaction between ranch type and rest period was significant for ground-level gaps (p = 0.034) but not for canopy gaps (p = 0.64) or forage availability (p = 0.28). Bold type indicates significant differences. (b) Independent sample t-tests for ground level gaps elucidate the significant management-rest period interaction for ground-level vegetation gaps. Bold type indicates significant differences. (a) Indicator

Conventional ( x% ± s.d.)

Holistic ( x% ± s.d.)

F1,12

p

Forage availability (kg/ha) Ground-level gaps (%) Herbaceous canopy gaps (%)

24,852 ± 4653 8.82 ± 9.83 9.54 ± 5.36

36,277 ± 13,304 0.10 ± 0.16 0.75 ± 1.02

4.60 5.51 18.16

0.053 0.034 0.001

(b) Ground-level gaps (%) ( x ± s.d.)

Conventional Holistic T12 p

Rested

Grazed

6.5 ± 10.2 0.2 ± 0.3 1.63 0.154

11.1 ± 10.1 0.0 ± 0.0 2.93 0.026

The range of indicators we used to explore the sustainability of the ranches provided complementary insights regarding system function and the benefits and weaknesses of HM as practiced by the members of PIT Las Villas. While meeting organic standards is not an explicit goal of most of the HM or CM ranchers, OCI indicators such as livestock nutrition, pasture management, soil fertility and weed and pest control are all relevant to ecological and economic sustainability. The HM group achieved an OCI of 81.8%, and the CM group 32.1% (Table 2). By comparison, Nahed et al. (2009), using the same set of indicators, found OCI’s ranging from 53.3% to 61.3% for groups of small-scale, agrosilvopastoralists in three regions of Chiapas. One of the weak points (62.5% compliance) for the HM ranchers was veterinary care, in large part due to their continued reliance on chemical control for ticks. Another low score for the HM group (40% compliance) was for ‘‘ecological administration,’’ mainly because they have made few advances in seeking ‘‘green’’ market niches for their products. However their

T12

p

0.86 1.55

0.408 0.172

high overall OCI’s indicate that the HM ranchers are close to meeting organic standards, presenting an opportunity to increase their economic advantage. Of the metrics we calculated, emergy accounting provides the broadest view of sustainability. Environmental Loading Ratios close to two, as found in both groups of ranches (Alfaro-Arguello et al., 2010; Table 3), indicate relatively low impacts that can be absorbed within the system area (Brown and Ulgiati, 1997). Emergy Sustainability Indices were greater than one for both the holistic and conventional systems (though not the large conventional systems analyzed separately), indicating that these ranches are net providers of emergy to the economy when properly accounting for environmental impact. Although PIT Las Villas was formed in part thanks to support from government agencies, government assistance in the form of farm equipment decreased sustainability as measured in emergy terms. These findings suggest that programs concerned with sustainability would do well to focus less

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B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

Table 6 Density (of individuals P25 cm tall) and basal area (of individuals P1 cm dbh) of woody species in transects. Values for the two pastures sampled at each ranch were averaged before calculating standard deviations (N = 7 for each ranch type). Family

Species

Annonaceae

Annona purpurea Annona reticulata Thevetia peruviana Gilibertia arborea Verbesina punctata Vernonia condensata Bignoniaceae aesculifolia Tabebuia pentaphylla Tabebuia rosea Bursera simaruba Licania arborea Calophyllum brasiliense Cochlospermum vitifolium Curatella americana Jatropha curcas Acacia cornigera Acacia pennatula Andira inermis Bauhinia ungulata Caesalpinia velutina Diphysa robinioides Dussia cuscatlanica Enterolobium cyclocarpum Erythrina goldmanii Gliricidia sepium Hymenaea courbaril Lonchocarpus rugosus Machaerium biovulatum Pithecellobium dulce Platymiscium dimorphandrum Casearia nitida Byrsonima crassifolia Sida rhombifolia Cedrela odorata Ficus cookii Psidium guajava Psidium sartorianum Pisonia macranthocarpa Calycophyllum candidisimum Genipa americana Salix chilensis Solanum torvum Guazuma ulmifolia TOTAL

Apocynaceae Araliaceae Asteraceae Bignoniaceae

Burseraceae Chrysobalanaceae Clusiaceae Cochlospermaceae Dilleniaceae Euphorbeaceae Fabaceae

Flacourtiaceae Malpighiaceae Malvaceae Meliaceae Moraceae Myrtaceae Nyctaginaceae Rubiaceae Salicaceae Solanaceae Sterculiaceae

Number of species detected

Basal area (m2/ha) ( x ± s.d.)

Individuals/ha ( x ± s.d.)

Conventional

Conventional

0.06 ± 0.15 0.04 ± 0.10 0.06 ± 0.15 0.02 ± 0.07 0.04 ± 0.11 1.53 ± 2.47 0.50 ± 1.31 0.15 ± 0.39 0.22 ± 0.59 0.06 ± 0.16 0.06 ± 0.11 0.09 ± 0.23

0.56 ± 1.48 0.37 ± 0.92

0.15 ± 0.30 0.36 ± 0.65

Holistic 0.11 ± 0.29

0.01 ± 0.02 0.03 ± 0.09 0.01 ± 0.03 0.67 ± 1.65 0.01 ± 0.02 0.26 ± 0.59 0.37 ± 0.98 0.01 ± 0.04

0.68 ± 1.14 0.57 ± 0.87 <0.01

Holistic 0.79 ± 2.10 9.52 ± 25.20

0.79 ± 2.10 0.79 ± 2.10 1.59 ± 2.71

53.17 ± 91.50 15.87 ± 25.75 0.79 ± 2.10 11.11 ± 17.86 37.30 ± 89.05 2.38 ± 4.37 0.79 ± 2.10 0.79 ± 2.10

2.38 ± 4.37 1.59 ± 4.20 5.56 ± 6.42 0.79 ± 2.10 5.56 ± 12.42 0.79 ± 2.10 0.79 ± 2.10 25.40 ± 34.52 20.63 ± 26.58 3.97 ± 5.28

1.52 ± 4.02 0.45 ± 0.77 0.02 ± 0.06 0.59 ± 1.48 0.04 ± 0.10 0.23 ± 0.62 0.46 ± 1.20 0.31 ± 0.81

29.37 ± 45.67 1.59 ± 4.20

0.77 ± 1.71 0.13 ± 0.26 <0.01 0.05 ± 0.12

2.38 ± 6.30 7.14 ± 11.88 1.59 ± 2.71 2.38 ± 4.37

104.76 ± 221.56 78.57 ± 98.36 15.08 ± 20.21 1.58 ± 4.20 5.56 ± 14.70 3.17 ± 8.40 16.67 ± 27.40 8.73 ± 23.10 55.56 ± 101.33 0.79 ± 2.10 41.27 ± 76.16 2.38 ± 4.37 0.79 ± 2.10 7.94 ± 13.93 76.98 ± 128.52 34.92 ± 74.17 3.17 ± 6.30 0.79 ± 2.10 2.38 ± 6.30 11.11 ± 20.54

11.11 ± 19.25

0.02 ± 0.04 0.90 ± 2.37 0.09 ± 0.23 0.03 ± 0.09 0.08 ± 0.20 0.48 ± 0.76

0.64 ± 1.69 0.01 ± 0.04

0.79 ± 2.10 11.90 ± 19.90 0.79 ± 2.10 3.97 ± 6.18 0.79 ± 2.10 3.17 ± 4.37

8.73 ± 10.57 11.11 ± 20.54 3.97 ± 8.31

0.51 ± 0.78 4.93 ± 2.97

1.10 ± 2.13 7.42 ± 6.90

38.89 ± 68.87 186.51 ± 178.73

1.58 ± 4.20 0.79 ± 2.1 62.70 ± 103.28 692.06 ± 837.61

21

29

27

36

Table 7 Repeated measures ANOVA’s for soil indicators. Neither pasture rest period nor ranch type-rest period interactions were significant factors for any response variable and are not reported. Standard deviations are for data averaged between rest periods. Bold type indicates significant differences between ranch types for a given variable. Indicator

Conventional ( x ± s.d.)

Holistic ( x ± s.d.)

F1,12

p

A horizon depth (cm) Penetrability, soil surface (kg/cm2) Horizontal penetrability, A horizon (kg/cm2) Sand (%) Silt (%) Clay (%) Bulk density (g/cm3) pH P (mg/kg) Organic material (%) Total N (%) Cation exchange capacity (cmol/kg) Respiration ((kgCO2/ha)/day)) Earthworm presence (%) White grub presence (%)

18.6 ± 8.9 0.82 ± 0.19 0.55 ± 0.17 54.1 ± 9.6 28.0 ± 6.2 17.9 ± 5.3 1.37 ± 0.10 5.49 ± 0.49 35.3 ± 30.2 3.11 ± 0.64 0.15 ± 0.03 19.1 ± 5.1 4.98 ± 0.66 14.3 ± 37.8 14.3 ± 24.4

28.8 ± 3.2 0.98 ± 0.32 0.71 ± 0.32 52.4 ± 8.8 27.1 ± 5.7 20.5 ± 3.3 1.31 ± 0.05 5.66 ± 0.53 59.9 ± 43.9 3.33 ± 0.89 0.17 ± 0.05 19.8 ± 5.9 6.68 ± 1.04 78.6 ± 39.3 0.0 ± 0.0

7.98 0.07 1.32 0.12 0.07 1.19 2.21 0.42 1.49 0.29 0.78 0.06 13.50 9.72 2.40

0.015 0.792 0.273 0.736 0.793 0.297 0.163 0.530 0.245 0.601 0.395 0.811 0.003 0.009 0.147

on expensive, purchased machinery and other emergy intensive inputs. In this case, technical support, particularly farmer-to-farmer

training (Holt-Gimenez, 2005) and simple technologies appear to have been the drivers of the transition to HM. These kinds of inter-

B.G. Ferguson et al. / Agricultural Systems 120 (2013) 38–48

ventions may be more appropriate and effective targets for subsidies and assistance. Our vegetation and soil data provide concrete evidence suggesting that HM is augmenting conservation values on the land. Although differences were not significant, we found on average 71% more woody basal area and 271% more woody stems on holistic ranches (Table 6), suggesting that HM is increasing tree cover. We also found significantly deeper topsoil on the holistic ranches (Table 7), consistent with the assertion of one holistic rancher that in the 40 years since he took over his ranch and stopped burning, he has accumulated some 25 cm of dark, rich soil on top of the red clay layer he inherited. Our data are also consistent with the common claim that by building soil, HM can contribute significantly to carbon sequestration. Because of potential confounding variables, we have couched our conclusions with respect to the benefits of HM in cautious terms. The members of PIT Las Villas were self-selected and even before their training in HM and rational grazing they were likely atypical in important aspects. The holistic ranches, for example, are larger on average than the conventional ranches we sampled. Although we took steps to control for ranch size in our analysis, scale effects may have influenced our data. Moreover, along with their economic advantages, the holistic ranchers appear to be politically better connected than most of their neighbors. One, for example, is a former mayor who now holds an important post within the Chiapas Rural Development Secretariat. Also, although not a statistically significant difference, the HM group averaged 2.5 years more formal education than the CM group. Their wealth, political savvy and education may have permitted the HM group to leverage support for innovation on their ranches, and helped them to take full advantage of available training and technical assistance. This likely explains the difference in average ranch size between the two groups. It remains to be seen whether smaller, less connected, less educated ranchers could achieve the same success as the HM group in this study. Most of the HM tools we mention here, including holistic decision making, farmer-to-farmer training, elimination of burning, reduced agrochemical use, record keeping and diversification of forage resources, are likely scale-neutral or perhaps more easily adopted by small producers. Others, however, including rotational grazing with electric fences and the maintenance of forest reserves, could be relatively more costly to implement at a smaller scale. Furthermore, those with less land to spare may find the risk of failure prohibitive, limiting their disposition to try new techniques and technologies. Small holders, many of them ejido1 members, many of them indigenous, are an increasingly important component of Chiapas’ livestock sector (Alemán Santillán et al., 2007). These ranchers typically manage a few ha or less of pasture (much less than the both HM and CM groups in our study), often on marginal land at the agricultural frontier. Identifying sustainable production strategies for these small, impoverished ranchers is a conservation and development priority for the state. On the other hand, the holistic ranches we worked on are small compared to latifundios found elsewhere in Latin America (Hecht, 1993; Kaimowitz, 1996). These large ranchers often have other, larger sources of income and are most interested in staking a claim to the land or in maximizing their short-term returns. HM may not make sense in the context of this entrepreneurial logic. Other large holders, however, are in ranching for the long term (Kaimowitz, 1996) and might be attracted to the potential of HM’s, and silvopastoral systems in general, to improve productivity (Cubbage et al., 2012; Murgueitio et al., 2011).

1 Ejidos are the collective land tenure regime established under Mexico’s postrevolutionary constitutional reforms.

47

While we acknowledge that ranch size, political connectedness and other confounding variables may account for some of the differences between our HM and CM groups, we also recognize that our methodology likely underestimated the relative benefits of HM in several ways. Although the focus of HM is whole systems and their interactions with other whole systems (Savory and Butterfield, 1999), we sought comparability among ranches by sampling plant communities and soil in a single component of these systems; pastures dominated by star grass. Holistic ranchers continuously seek to diversify their resource base, introducing and selecting for a wealth of herbaceous and woody forage plants in diverse combinations. Many of these were ignored by our sampling scheme. Similarly, differences in tree cover were not significantly different between the star grass pastures of the HM and CM ranchers, but when fencerows and forest reserves are taken into account, tree cover is undoubtedly greater on the HM ranches. We quantified the social and economic success of the ranches using conventional indictors such as productivity and profit, but HM also focuses on goals such as quality of life and risk management. The diversification of resources and products, part of this strategy, confers resilience upon the holistic ranches. The response of the holistic ranchers to the cabbage looper outbreak (Section 3.1.2) is an excellent example. Ranchers attributed that outbreak to an interruption in the onset of the rainy season. In the face of climate change, strategies that allow farmers and ranchers to confront unusual or extreme weather and its consequences will become an increasingly important aspect of sustainability (Altieri and Koohafkan, 2008; Murgueitio et al., 2011). Experiences such as that of PIT Las Villas may encourage other ranchers, large and small, to try rational grazing and HM, and justify government support for such strategies. Further investigation will be necessary to identify context-appropriate technology, training and support mechanisms. Further research could also help us more fully understand how, and in which contexts, HM is beneficial. Quantifying the ecological benefits of HM for landscape connectivity, wildlife habitat, fire prevention, nutrient cycling, climate change mitigation and soil and watershed protection (Murgueitio et al., 2011) may help justify investment in HM. Stratified sampling at the ranch scale would better describe system components, their planned and associated biodiversity and their soils. Longitudinal studies of ranchers converting to HM would help to document more conclusively the impacts of HM on the land and its managers. Top priorities for research in support of HM in our study region are agroecological methods of tick prevention and control and the development of better markets for the high quality products of these ranches. The applicability of HM in less ‘‘brittle’’ environments would also be an important avenue to explore. The suite of practices employed by members of PIT Las Villas seem appropriate for the humid tropics as well, though perhaps their benefits would be less pronounced than in the seasonally-dry tropics. Despite these knowledge gaps, we argue that there is sufficient evidence of the benefits HM and more intensive silvopastoral systems from this and other studies (Cubbage et al., 2012; Murgueitio et al., 2011) to justify aggressive promotion of transition from conventional ranching. Financial and knowledge barriers typically slow adoption of such systems (Murgueitio et al., 2011) and both are likely to be significant for chiapanecan ranchers. Financial barriers could be overcome if agencies charged with agriculture and forestry production as well as conservation could coordinate their efforts and orient existing subsidies toward the paradigm shift to sustainable ranching. Knowledge barriers may be more significant, because managing a low-external-input, complex system requires sophisticated planning and observation for adaptive management as well as access to information. Furthermore, agricultural extension services in Mexico were largely dismantled under structural

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adjustment policies (Bello, 2008). Currently, local ranchers unions and groups of ranchers supported by the agricultural secretariat called ‘‘grupos ganaderos de validación y transferencia de tecnología’’ or ‘‘GGAVATTs’’ (Galindo Gonzalez, 2009) may be the structures best adapted for overcoming knowledge barriers. An additional challenge is likely to be shortage of labor in rural areas. HM and intensive silvopastoral systems require more labor than conventional ranching (Murgueitio et al., 2006), and in recent years the Mexican countryside has witnessed an exodus of small farmers and laborers to cities and to the United States (García-Barrios et al., 2009). Both ranchers and government agencies have a role to play in creating attractive living and working conditions for ranch hands. Acknowledgements This work was carried out with financial support from the European Commission through the ReForLan Project, INCO-DEV contract PL 032132, and from the Mexican Consejo Nacional de Ciencia y Tecnología and El Colegio de la Frontera Sur through a postdoctoral fellowship for SAWD and a graduate fellowship for R.A.A. We thank the ranchers who shared their time and knowledge and allowed us to sample their vegetation and soils. Laura Rubio, Lesvia Domínguez, Carlos Sánchez, Wilder Grajales, Juan López, Jesús Carmona and Miguel López helped in the field and laboratory. Miguel Martínez Icó and Henry Castañeda helped with plant identification. Alejandro Flores contributed to data base design. The GIS lab (LAIGE) at ECOSUR produced the maps. Two anonymous reviewers provided suggestions that strengthened the manuscript. References Alemán Santillán, T., Ferguson, B.G., Jiménez Ferrer, G., Gómez Castro, H., Carmona Muñoz, I., Nahed Toral, J., 2007. Ganadería extensiva en regiones tropicales: el caso de Chiapas. In: Alemán Santillán, T., Ferguson, B.G., Medina Jonapá, F.J. (Eds.), Ganadería, Desarrollo y Ambiente: Una Visión para Chiapas. El Colegio de la Frontera Sur, Tapachula, Chiapas, México, pp. 18–39. Alfaro-Arguello, R., Diemont, S.A.W., Ferguson, B.G., Martin, J.F., Nahed-Toral, J., David Álvarez-Solís, J., Ruíz, R.P., 2010. Steps toward sustainable ranching: an emergy evaluation of conventional and holistic management in Chiapas, Mexico. Agric. Syst. 103, 639–646. Altieri, M.A., Koohafkan, P., 2008. Enduring Farms: Climate Change, Smallholders and Traditional Farming Communities. Third World Network, Penang, Malaysia. Avalos Flores, L., González Camacho, J.E., Carrizales Guevara, A., 1996. Pastoreo intensivo tecnificado en zonas tropicales. FIRA Fideicomisos Instituidos en Relación con la Agricultura Boletín Informativo, vol. XXIX, Núm. 287 Morelia, Michoacán, México. Bello, W., 2008. Manufacturing a Food Crisis. The Nation. May 15, 2008. thenation.com/article/manufacturing-food-crisis (accessed 10.03.13). Brown, M., Ulgiati, S., 1997. Emergy-based indices and ratios to evaluate sustainability: monitoring economies and technology toward environmentally sound innovation. Ecol. Eng. 9, 51–69. Cubbage, F., Balmelli, G., Bussoni, A., Noellemeyer, E., Pachas, A., Fassola, H., Colcombet, L., Rossner, B., Frey, G., Dube, F., Lopes de Silva, M., Stevenson, H., Hamilton, J., Hubbard, W., 2012. Comparing silvopastoral systems and prospects in eight regions of the world. Agrofor. Syst. 86, 303–314. Delgado, C.M. Rosegrant, M.W., Steinfeld, H., Ehui, S.C., Courbios, C., 1999. Livestock to 2020: The Next Food Revolution. Food, Agriculture and the Environment Discussion Paper 28, IFPRI-FAO-ILRI, Washington. FAO/EMBRAPA, 2001. Protección de los Recursos Naturales en Sistemas Ganaderos: Los Sistemas Agroforestales pecuarios en América Latina. FAO, Juiz de Fora, MG, Brasil. Galindo Gonzalez, S., 2009. Social Dynamics and Access to Social Capital of GGAVATT Participants in Veracruz, Mexico. Ph.D. Thesis, University of Florida, 2009, 179 pages. García-Barrios, L., Galván-Miyoshi, Y., Valdivieso-Pérez, A., Masera, O.R., Bocco, G., Vandermeer, J., 2009. Neotropical forest conservation, agricultural intensification, and rural out-migration: the Mexican expereience. BioScience 59, 863–873. Haydock, K., Shaw, N., 1975. The comparative yield method for estimating dry matter yield of pasture. Aust. J. Exp. Agric. 15, 663–670. Hecht, S.B., 1993. The logic of livestock and deforestation in Amazonia. BioScience 43, 687–695. Herrick, J.E., Van Zee, J.W., Havstad, K.M., Burkett, L.M., Whitford, W.G., 2005. Monitoring Manual for Grassland, Shrubland and Savanna Ecosystems. Volume I: Quick Start. USDA-ARS Jornada Experimental Range.

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