Ecological Applications, 21(5), 2011, pp. 1557–1572 Ó 2011 by the Ecological Society of America
Balancing shifting cultivation and forest conservation: lessons from a ‘‘sustainable landscape’’ in southeastern Mexico SARAH PAULE DALLE,1,4 MARI´A T. PULIDO,2
AND
SYLVIE
DE
BLOIS1,3,5
1
Department of Plant Science, Macdonald Campus of McGill University, 21 111 Lakeshore, Ste-Anne-de-Bellevue, Que´bec H9X 3V9 Canada 2 Centro de Investigaciones Biolo´gicas, Universidad Auto´noma del Estado de Hidalgo, Ciudad Universitaria, Carretera Pachuca-Tulancingo, km. 4.5, Colonia Carboneras, Mineral de la Reforma, Hidalgo C.P. 42184 Me´xico 3 McGill School of Environment, Macdonald Campus of McGill University, 21 111 Lakeshore, Ste-Anne-de-Bellevue, Que´bec H9X 3V9 Canada
Abstract. Shifting cultivation is often perceived to be a threat to forests, but it is also central to the culture and livelihoods of millions of people worldwide. Balancing agriculture and forest conservation requires knowledge of how agricultural land uses evolve in landscapes with forest conservation initiatives. Based on a case study from Quintana Roo, Mexico, and remote sensing data, we investigated land use and land cover change (LUCC) in relation to accessibility (from main settlement and road) in search of evidence for agricultural expansion and/or intensification after the initiation of a community forestry program in 1986. Intensification was through a shortening of the fallow period. Defining the sampling space as a function of human needs and accessibility to agricultural resources was critical to ensure a user-centered perspective of the landscape. The composition of the accessible landscape changed substantially between 1976 and 1997. Over the 21-year period studied, the local population saw the accessible landscape transformed from a heterogeneous array of different successional stages including mature forests to a landscape dominated by young fallows. We detected a dynamic characterized by intensification of shifting cultivation in the most accessible areas with milpas being felled more and more from young fallows in spite of a preference for felling secondary forests. We argue that the resulting landscape provides a poorer resource base for sustaining agricultural livelihoods and discuss ways in which agricultural change could be better addressed through participatory land use planning. Balancing agricultural production and forest conservation will become even more important in a context of intense negotiations for carbon credits, an emerging market that is likely to drive future land changes worldwide. Key words: accessibility; agricultural expansion; agricultural intensification; community forestry; forest conservation; livelihoods; milpa; Plan Piloto Forestal; sustainability; trade-offs; tropical deforestation; Yucatec Maya.
INTRODUCTION How do agricultural systems evolve in areas with forest conservation initiatives? This is a crucial question for highly biodiverse regions of the world where shifting cultivation systems must sustain increasing demands as a result of ever-growing populations, new market opportunities, or changing aspirations (Ramakrishnan 1992, Brookfield 2001, Finegan and Nasi 2004). In these regions, the success of conservation initiatives is often measured in terms of forest retention (e.g., Jackson et al. 1998, Gautam et al. 2002, Smith 2003, Bray et al. 2004, Dalle et al. 2006), with less attention being paid to the fate of agriculture. Yet to fully assess the trade-offs Manuscript received 7 April 2010; revised 27 September 2010; accepted 22 October 2011. Corresponding Editor: V. C. Radeloff. 4 Present address: USC Canada, 56 Sparks Street, Suite 705, Ottawa, Ontario K1P 5B1 Canada. 5 Corresponding author. E-mail:
[email protected]
resulting from land use decisions and conservation policies, we need to understand not only how agriculture drives forest dynamics, but also how agriculture responds to forest conservation in space and time (Turner et al. 2001, DeFries et al. 2004, Nelson et al. 2009). Understanding the dynamics of agricultural change (or agricultural trajectories) is an important dimension of sustainability and a necessary first step to evaluating land-management strategies in relation to local livelihoods (Dougill et al. 2001, Raquez and Lambin 2006, Fischer et al. 2008). To answer increasing demand for agricultural products, shifting cultivators either extend agricultural frontiers (agricultural expansion) or increase returns on existing cropland (intensification) (Kates et al. 1993, Turner and Ali 1996, Laney 2002). Expansion involves bringing previously uncultivated lands under crop production, and in shifting cultivation systems it is commonly reported as posing a threat to forests, as these are felled for agriculture (Geist and Lambin 2002,
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Lawrence et al. 2007, Diemont and Martin 2009). Community-based conservation strategies have responded to this threat by promoting alternative economic activities, such as the setting aside of permanent forest areas, the production of non-timber forest products, or eco-tourism that depends on forest (Salafsky et al. 2001, Al-Sayed and Al-Langawi 2003, Plummer and Fitzgibbon 2004). As for intensification, it involves changes in management of existing cropland in order to increase returns in relation to inputs (e.g., labor, capital, technology, or time) (Laney 2002). In shifting cultivation systems, this typically occurs first by a shortening of the fallow period (Kellman and Tackaberry 1997, Laney 2002), but may be followed by changes in cropping patterns, management practices (tilling, increased weeding) or inputs (inorganic fertilizers, herbicides, irrigation; Laney 2002, Keys and McConnell 2005). Intensification is perceived to be positive when it protects valuable land (e.g., reducing expansion into forests) or increases productivity or incomes (Green et al. 2005), but negative if management practices damage soils, pollute water, compromise long-term agricultural productivity or nutrient cycles, or cause loss of ecosystem services or of agrobiodiversity (Matson et al. 1997, Lawrence et al. 2007). Balancing agriculture with forest conservation remains therefore a crucial challenge to achieve sustainability (Knoke et al. 2009). Here, we assess agricultural trajectories in a spatially complex shifting cultivation landscape with institutionalized forest conservation to contribute to the integration of research and policy aimed at balancing forest conservation and agriculture. Dominated by Yucatec Maya communities, the Central Quintana Roo region of Mexico includes one of the most extensive stretches of tropical forest in Mesoamerica (Vester et al. 2007) and sustains some of the lowest annual rates of forest loss (between 0.1% and 0.7% per year; Bray et al. 2004, Dura´n et al. 2005, Dalle et al. 2006, Ellis and PorterBolland 2008) in tropical Mexico (regional average of 1.9% per year; Cairns et al. 2000). This has been attributed to a number of factors, including the Mexican agrarian reform (1930s–1990s) that granted community control of large tracts of valuable forests, as well as norms upheld since at least the 1950s (see Dalle et al. 2006) by Maya communities protecting areas used for commercial timbers and for chicle, a commercially important non-timber forest product. An important state-wide institutional support for conservation initiatives has been provided by a community forestry program (Plan Piloto Forestal [PPF]) initiated in 1986 and implemented by 64 communities on over 500 000 ha (Kiernan and Freese 1997, Merino Pe´rez 1997, Flachsenberg and Galletti 1998, Galletti 1998). The high rate of forest retention has prompted the suggestion that the Zona Maya represents a ‘‘sustainable landscape’’ (Bray et al. 2003, 2004) and that communitybased forestry is more efficient than nature reserves in
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conserving forests (Dura´n et al. 2005, Ellis and PorterBolland 2008). This is significant in a region that is thought to have been managed continuously by humans for at least 3000 years (Colunga-GarciaMarı´ n and Zizumbo-Villarreal 2004). Sustainability, however, must pertain also to agricultural land uses on which the livelihood and culture of the Maya communities still largely depend (Murphy 1990, Hostettler 1996, Re Cruz 1996). As in many other parts of Mexico (Alcorn 1981, Toledo et al. 2003, Klooster 2005), Yucatec Maya livelihoods are based on a ‘‘multiple use strategy,’’ which relies on the availability of up to 300–500 cultivated and uncultivated plant and animal species (Teran and Rasmussen 1995, Barrera-Bassols and Toledo 2005, Toledo et al. 2008). Access to a diverse landscape is a key component to this strategy and management practices often contribute to maintaining or increasing both the diversity and accessibility of key resources (Alcorn 1981, Berkes et al. 2000, Turner et al. 2003). This is the case of long-cycle fallowing, which generates a mosaic of different successional stages (Finegan and Nasi 2004). However, the setting aside of large permanent forest areas outside areas managed for agriculture, while reducing agricultural expansion, could lead to intensification in the remaining agricultural zones, with the potential for negative impacts on the diversity, availability, and productivity of key resources (Murphy 1990). Within this context, the specific objectives of our study were to (1) quantify land use and land cover change (LUCC) in relation to accessibility, before and after the initiation of the community forestry program in 1986, and (2) detect whether the agricultural trajectories observed after 1986 were consistent with patterns of agricultural intensification. Taking into account accessibility was critical to adopt a user-centered perspective of the landscape, in which access to agricultural resources is considered a key component of the Maya multiple-use strategy. It also allowed us to account for the fact that land use and land cover changes in the region is related to distance to roads or human settlements (Bray et al. 2004) and therefore we expected agricultural intensification to increase with increasing accessibility. We used remote sensing data to detect land cover changes predicted for expansion or intensification (Table 1). An increase in the conversion of forest that had not been recently used for agriculture and a subsequent increase in successional vegetation, as cropped land is let to fallow, was seen as evidence for expansion (Moran et al. 1994, Skole et al. 1994, Smith et al. 1999). Field studies suggested that the main intensification strategy in this area would be a shortening of the fallow period (Dalle and De Blois 2006, Lawrence et al. 2007). Intensification, via a reduction in the fallow period, was therefore identified by an increase in the felling of younger fallows and a decrease in the cover of secondary forests, since fallow periods are not
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TABLE 1. Working definitions of agricultural expansion and intensification, the associated land dynamics expected, and the land cover changes used to identify them.
Strategy
Definition
Agricultural expansion
cultivation of lands not used for agriculture in recent history
Agricultural intensification
increase in returns to land through reduction in fallow period
Expected land dynamics conversion of mature forests to milpa; reduction in the proportion of mature forests in the landscape; increase in secondary forests and fallows shorter fallow periods; progressive elimination of preferred land cover (SF); increase in younger fallows
Land cover changes examined transition Mi_MF; decline in proportion of MF; increase in proportion of YF and SFà increase in proportion Mi_YF, decrease Mi_Mi, Mi_SF, Mi_MF; decrease in proportion of SF; increase in proportion of YF
Temporal frame restricted to the last 100 years, when the Caste War ended and the current settlement pattern was established (Hostettler 1996). à See Table 2 for definition of abbreviations for land covers and transitions.
long enough to ensure replacement of older vegetation (Metzger 2003, Finegan and Nasi 2004, Garcı´ a-Frapolli et al. 2007). This research was part of a broader study on land change and resource management (Dalle 2006, Dalle and De Blois 2006, Dalle et al. 2006, Pulido 2006, Pulido and Caballero 2006) with two authors (S. P. Dalle and M. T. Pulido) each spending approximately 12 months between 2001 and 2004 living and working in the study area. The preparation of the remote sensing data, as well as other analyses and interpretation thus greatly benefit from an in-depth understanding of agricultural practices and of the social and cultural context of the study region, gained through ecological studies, participatory observation, and interviews. Insights from this study have relevance for the management of tropical areas that are characterized by peasant economies, forest conservation initiatives and culturally important agricultural land uses (e.g., buffer zones of protected areas, indigenous territories, and extractive reserves). The potential overspill effects of forest conservation on agricultural livelihoods highlighted by our research should also be carefully considered in the context of carbon credits, payments for ecosystem services and other strategies for reducing emissions from deforestation and forest degradation. METHODOLOGY Study area Research was carried out in the Ejido X-Maben, a 730-km2 territory (Fig. 1). The karstic terrain is flat to slightly undulating with elevation less than 30 m above sea level, with thin, limestone-derived soils (mostly lithosols and rendzinas), and a system of underground drainage systems and sinkholes (Universidad Auto´noma de Yucata´n 1999). Average annual temperature is 268C, while average annual precipitation is approximately 1200 mm/year (Universidad Auto´noma de Yucata´n 1999), with a marked dry season occurring from
FIG. 1. Locational map of Ejido X-Maben, Mexico, indicating the main villages, roads, and the area analyzed (based on accessibility) for 1976 and for 1988–1997.
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January to April (Flores and Espejel Carvajal 1994, Pennington and Sarukha´n 1998). The vegetation is described as medium semi-deciduous tropical forest (selva mediana subperenifolia) in the Mexican classification system (Flores and Espejel Carvajal 1994, Universidad Auto´noma de Yucata´n 1999) or as tropical dry forest in the Holdridge system (White and Darwin 1995). These forests have a maximum stature of about 15 m and shed near 25% of their foliage in the dry season. Several inundated vegetation types are found in small extensions, on gley soils, particularly in the eastern part of the ejido forming part of the permanent forest area. The population of X-Maben is nearly entirely Yucatec Maya. There are 10 settlements within X-Maben. The main village, Se˜nor, is located along the highway, 30 km from the municipal capital, Felipe Carrillo Puerto (Fig. 1). Since 1970, the population of X-Maben more than doubled (from 1363 in 1970 to 2849 in 2000), but this growth was concentrated in Se˜nor (from 939 in 1970, or 69% of the ejido population, to 2362, or 83% of the population, in 2000; Secretarı´ a de Industrı´ a y Comercio 1971, INEGI 2000). The other settlements all had populations of less than 200 during the same period. In Mexico, the ejido is a form of collective land tenure in which a group of ejidatarios (usually male household heads) is granted usufruct rights by the federal government. The X-Maben ejido petition was initiated in 1936 and finalized in 1955, with a grant to 159 ejidatarios (Hostettler 1996). The land grant included large tracts of forested areas that were managed by the Maya for extraction of chicle (Hostettler 1996). In 2000, the ejido had approximately 492 ejidatarios, 800 hijos de ejidatarios (married sons of ejidatarios), and around 30 pobladores (heads of migrant households) (Catalino Cau Diaz, personal communication). While all households can use land for milpa, collection of fuelwood, and other resources, only ejidatarios have voting rights in the ejido assembly. Until recently (2010), X-Maben had not entered ‘‘Procede,’’ a government program to implement the 1992 ejido reforms that allow communal agricultural land to be parceled out and rented or sold by ejidatarios (Cornelius and Myhre 1998). As a result, X-Maben continues to be managed by the ejido assembly as common property. Agriculture is primarily centered around ‘‘milpa,’’ a polyculture of maize, beans, and squash (Teran and Rasmussen 1995), with other crops (e.g., gourds, watermelon, tubers) sometimes intercropped. In Quintana Roo (as well as many other parts of Mesoamerica), milpa is practiced as a shifting cultivation system and in X-Maben fallow periods range from five to 20–30 years. Use of inorganic fertilizers, promoted by government agencies, has become widespread in the region, irrespective of fallow period (S. P. Dalle and M. T. Pulido, personal observations). Nearly all households in X-Maben manage milpa and use wild plant resources, such as fuelwood, thatch, and other
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construction materials from the shifting cultivation mosaic (Murphy 1990, Hostettler 1996, Dalle 2006). There is some small-scale horticulture, citrus production, and cattle ranching, but this is very limited in extent while wage labor is a more important source of cash income (Pulido 2006). This contrasts with other parts of the Southern or Northern Yucatan peninsula, where chili production, intensive horticulture, and cattle ranching have higher economic importance and largely drive land use dynamics (Humphries 1993, Caballero 1994, Abizaid and Coomes 2004, Geoghegan et al. 2005, Ellis and Porter-Bolland 2008). In 1986, X-Maben’s ejido assembly voted to enter the state-wide community forestry program. With support from a regional producer’s organization (Organizacio´n de Ejidos Productores Forestales de la Zona Maya [OEPFZM]), the ejido developed management plans for the commercial extraction of tropical timbers on an estimated 40 000 ha (55%) of their territory (Murphy 1990, Merino Pe´rez 1997). Compared to other ejidos supported by OEPFZM, the commercial value of XMaben’s timber resources is considered moderate (Merino Pe´rez 1997). In a previous paper, we examined LUCC in X-Maben between 1976 and 1997 at the scale of the entire ejido (730 km2) and reported the territory to be dominated by mature forests (76–80% of land cover) with very low rates of net mature forest loss (0.6–0.7% per year), largely attributed to forest protection by community norms (Dalle et al. 2006). The present paper focuses on agricultural dynamics within the most accessible areas of X-Maben used for milpa (;200 km2 area of the same territory, see details in Statistical procedures), outside of the large swaths of forest protected by community norms (Appendix A). Data set and image processing The data set analyzed in this paper consisted of five land cover maps derived from the following satellite images: 12 February 1976 (Landsat 2-MSS), 16 December 1988 (Landsat 4-TM), 16 February 1991 (Landsat 5-TM), 31 January 1997 (Landsat 5-TM), and 9 February 2000 (Landsat 5-TM). These images were all taken during the dry season (therefore minimizing phenological differences) and were selected due to the relatively cloud-free coverage over the study area. The images were all georeferenced with respect to a Landsat7-ETM image from 21 April 2000 (this last image had been georeferenced using topographic maps in the context of the 2000 National Forest Inventory of Mexico) with a 30 3 30 m pixel size, achieving a root mean square error of near 0.5 pixels for all images (range ¼ 0.48–0.54 pixels). A post-classification comparison approach was used to detect land cover changes (Mas 1999). For each of the 1976, 1988, 1997, and 2000 images, an unsupervised classification (ISODATA method in ENVI version 3.5 [ITT Visual Information Solutions, Boulder, Colorado,
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TABLE 2. Codes used and description of (a) land covers identified in satellite images from 1976, 1988, and 1997; and (b) transitions used to estimate fallow periods in 1991 and 2000. Code
Description
a) Land covers in 1976, 1988, and 1997 land cover maps (Analysis 1) Mi milpas, pastures, horticultural plots, other open areas YF young fallows and secondary vegetation between 2 and 9 years SF secondary forests, 10–25 years MF mature forests .25 years; includes some areas of burned forests (e.g., from fires escaping milpas) b) Transitions calculated from image pairs (1988/1991 and 1997/ 2000) to estimate fallow periods (Analysis 2)à Mi_Mi milpa/open areas in t1 classified as milpa in t2§ (milpa cultivated continuously for 2–3 years) Mi_YF young fallow in t1 classified as milpa in t2§ (milpa felled from young fallow) Mi_SF secondary forest in t1 classified as milpa in t2§ (milpa felled from secondary forest) Mi_MF mature forest in t1 classified as milpa in t2§ (milpa felled from mature forest) Village and roads were also classified in this category, but pixels corresponding to these covers were excluded from the data set. à For each image pair, t1 is the earlier image and t2 is the later image. § Pixels known to correspond to pastures or horticultural plots (i.e., permanent agricultural land uses) were removed from the 1991 and 2000 images, since the objective of Analysis 2 was to examine changes in fallow periods in the shifting cultivation system.
USA) was used to identify spectrally similar areas for training sites, which were then used to perform a supervised classification with a maximum likelihood algorithm. Interpretation of the land covers/land uses associated to each of these training sites was made by comparing the unsupervised classification to several data sources. These included (1) 468 GPS points taken in different vegetation types in X-Maben between June and December 2002, (2) a series of six color aerial photographs taken during the National Forest Inventory of Mexico in November 2000, covering an area of approximately 4.5 km2 each, and (3) nine black and white digital orthophotos (from 1998 and 2000) obtained from INEGI (Aguascalientes, Mexico), which together cover the entire ejido. Field interpretation of the land cover associated with each GPS point as well as that of the color aerial photos were performed with assistants from X-Maben very knowledgeable of the land use history of the sites. Detailed information on the cultivation history of 26 milpas used as sites for vegetation sampling in 2003 in a related study was also employed (see Dalle et al. 2006). Once associated with a given land cover, the separability of the training sites for each image was tested using the Jeffries-Matusita and the transformed divergence indices. For each image, training sites with very low separability (,1.0) were combined, while those with moderate separability were revised in order to improve their separability (minimum separability was 1.7). The final set of training sites defined for each image was then used in a maximum likelihood supervised classification. Finally, a majority analysis was applied, which eliminates unclassified or isolated pixels by assigning them to the land cover class to which the majority of surrounding pixels are classified.
A total of eight land cover classes were identified, four of which are analyzed in this paper: milpa/open areas (Mi ), young fallows (YF), secondary forests (SF), and mature forests (MF; Table 2). All pixels classified as one of the remaining land cover classes (clouds/cloud shadows, water, wetlands, roads, or urban areas) in any of the images were excluded from the data set. This represented ;2% of pixels. The 1991 image was obtained later in the study, for use in the 1988/1991 change map of Analysis 2 (see details in Statistical procedures). In this analysis, only milpa covers were needed from the 1991 and 2000 images. Since experience with the other four images had indicated that milpa/open areas were easily identified with the initial unsupervised classification, no supervised classification was performed for the 1991 image. For 2000, the milpa/ open area land cover was extracted from the supervised classification. In both cases, all non-milpa covers (pastures, horticultural plots) were removed. These were easily identified by their permanent nature and based on our extensive field knowledge of the study area. In addition to image processing and classification, we used field data collected in April 2004 to conduct an accuracy assessment of the most recent image (2000). A stratified sampling design based on accessibility was used to randomly select a total of 27 sites where four pixels distributed in a 270 3 270 m square were groundtruthed. This design provided land cover information for a total of 108 pixels and resulted in an estimated overall accuracy of 0.81 6 0.4 (mean 6 SE; for more details, see Dalle et al. 2006). The assessment showed that most errors were either boundary errors or due to ambiguities at the threshold between classes (e.g., between YF and SF or SF and MF, etc). The milpa/ open areas category could not be verified due to the small sample size (n ¼ 8) obtained for this cover class; it
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TABLE 3. Estimated accessibility and travel time from Se˜nor for the seven buffers used as the covariable ACCESS in analyses of land cover changes. ACCESS buffer
Estimated travel time from Se˜nor (minutes)
0 1 2 3 4 5 6 7
,7 7–18 19–30 31–42 43–54 55–66 67–78 79–90
The area corresponding to access buffer 0 was not analyzed since land cover changes there were more related to urban expansion than to agricultural practices.
was, however, very easily identified during image processing, which contributes to increase our confidence in their classification. It was not possible to verify the older images with recent field data, due to constant changes in the shifting cultivation landscape. However, as these images were classified using the same procedures as 2000, we assume that they have a similar level of accuracy. Statistical procedures We conducted three distinct sets of analyses to answer our research questions. The 1976, 1988, and 1997 images were used to detect and quantify land changes in the accessible landscape before and after the initiation in 1986 of the PPF (Analysis 1). Image pairs (1988/1991 and 1997/2000) were used to detect changes in fallow periods from 1991 to 2000 (Analysis 2). A third analysis was done to test an important assumption of our analytical framework, namely that 10–20-year-old secondary forests, when available, are preferred over other vegetation types for milpa (Analysis 3). The land changes observed were interpreted according to our framework for expansion or intensification (Table 1). A flow chart showing the land cover classes derived from each image and how they were used in the analyses is presented in Appendix B. Since we aimed to quantify land changes in relation to accessibility, particularly to access resources important to local livelihoods, we focused our analyses on areas accessible within 90 minutes of travel from the main village Se˜nor (Fig. 1 and Appendix A). Referred to herein as the ‘‘accessible landscape,’’ this included all the major areas within the ejido commonly used for milpa, hunting, and gathering (S. P. Dalle and M. T. Pulido, personal observations). The areas excluded consisted of the large extensions of mature forest used primarily for timber management and chicle extraction. Accessibility was estimated by an index that assumed travel by bicycle along roads at 12 km/h, and travel by foot at 4 km/h along paths from these major roads. This reflected the main transport habit observed during the study period for the majority of the population. A new graded road
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was built after 1976 between Se˜nor and San Antonio, following a preexisting foot path. Being easily transited by bicycle, this new road increased the extent of the ‘‘accessible landscape’’ for the majority of inhabitants (15 533 ha for 1976 vs. 20 234 ha for 1988, 1997; Fig. 1 and Appendix A). Since our focus was on land change relative to accessibility, we chose to analyze areas comparable in terms of their relative accessibility for the three time periods. In Analysis 1, we compared the proportion of four land covers (Mi, YF, SF, and MF) over time (1976, 1988, and 1997, YEAR) and within areas defined by accessibility (ACCESS) using an analysis of covariance (ANCOVA). The covariable ACCESS consisted of seven buffer zones, each representing ;11 minutes of travel from Se˜nor, based on the accessibility index (Table 3). This scale was used since preliminary Moran’s I tests indicated the lack of any significant autocorrelation. As these buffers were of increasing surface areas, we sampled each land cover map within each buffer using equal sample sizes. For Analysis 1, the dependent variables (proportion of land cover) were obtained by randomly sampling 800 pixels within each buffer zone and calculating the proportion corresponding to each land/cover. The residuals of the ANCOVA models were tested for autocorrelation, normality, and homogeneity of variance among groups using the Moran’s I, KolmogorovSmirnov, and Levene tests, respectively. Significant deviations (P , 0.05) were found for one model only (young fallows: significant deviation for homogeneity of variance). To correct for this, the arcsine transformation was applied to the data, since this transformation is appropriate for proportions (Legendre and Legendre 1998:42). ANCOVAs and tests for normality and homogeneity of variance were performed using the GLM procedure in SAS version 9.1 (SAS Institute 2002), whereas the Moran’s I test was conducted using the spdep package of R, version 2.3.1 (R Development Core Team 2006). For models with a significant (P , 0.10) YEAR 3 ACCESS term, group (YEAR) effects were tested with the Johnson-Neyman (J-N) procedure (Potthoff 1964, Rogosa 1980, D’Alonzo 2004). This allowed us to identify the regions of the covariable for which significant group (YEAR) differences existed. The procedure was first developed for comparing models with one covariable and two groups (e.g., D’Alonzo 2004). Details on how this test was extended for threegroup ANCOVA are provided in Appendix C. When interaction terms were not significant (P . 0.10), they were removed from the model. The ANCOVA was then run again, and any remaining nonsignificant (P . 0.10) terms were also removed to obtain the most parsimonious model. In Analysis 2, we carried out a similar ANCOVA to assess changes in fallow periods as evidenced by more milpa cover being felled from young fallows. In this
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TABLE 4. Results of ANCOVA to test for changes in the proportion of land cover in relation to accessibility (ACCESS) and time (YEAR ¼ 1976, 1988, 1997). Type III SS
F
P
R2
Proportion milpa/open areas (Mi ) Full model 5 ACCESS 1 YEAR 2 ACCESS 3 YEAR 2 Error 15
0.0704 0.0372 0.0295 0.0166 0.0077
27.56 72.75 28.81 16.25
,0.0001 ,0.0001 ,0.0001 0.0002
0.902
Proportion young fallow (YF) Full model 5 ACCESS 1 YEAR 2 ACCESS 3 YEAR 2 Error 15
0.6698 0.3231 0.1998 0.0458 0.0246
81.76 197.20 60.96 13.97
,0.0001 ,0.0001 ,0.0001 0.0004
0.965
Proportion secondary forest (SF) Full model 5 ACCESS 1 YEAR 2 ACCESS 3 YEAR 2 Error 15
0.0678 0.0388 0.0033 0.0048 0.0079
25.81 59.00 3.16 4.55
,0.0001 ,0.0001 0.0718 0.0286
0.899
Proportion mature forest (MF) Full model 3 ACCESS 1 YEAR 2 Error 17
1.2430 0.9185 0.3245 0.0464
151.64 336.16 59.38
,0.0001 ,0.0001 ,0.0001
0.964
Factor
df
case, image pairs from 1988/1991 and 1997/2000 were used to estimate the dependent variable (fallow period). An overlay operation was used to calculate the proportion of milpa cover at t2 that was classified as Mi, YF, SF, and MF at t1, where t1 is the earlier image and t2 is the later image in each image pair. The resulting variables (Mi_Mi, Mi_YF, Mi_SF, Mi_MF) are defined in Table 2. Because the time lag in each stacked pair (3 years) was shorter than the minimum fallow period (5 years, based on our field observations), we assumed that the land cover at t1 was a good indicator of the type of vegetation that had been felled for milpa in t2. Because of the relatively small area covered by milpa, 100 pixels out of all milpa pixels available were randomly sampled from each buffer zone. The same procedures as described above were used to test for autocorrelation, normality and homogeneity of variance among groups. Significant deviation from the assumption of homogeneity of variance among groups was found in one model (Mi_Mi ). The arcsine transformation was not sufficient to correct for this deviation. Given that there was no significant relationship with the co-variable ACCESS in this model, we therefore used the nonparametric KruskallWallis to test for differences among years. In Analysis 3, we verified the assumption that farmers preferred felling secondary forests for milpa, by adapting a method used by Hayes et al. (2002). We constructed scatterplots comparing the proportion of each land cover at t1 (1988 and 1997) that ended up as milpa at t2 (1991 and 2000) with the proportion at which this land cover was available at t1. A 1:1 line in the scatterplots represented the null hypothesis of no
preference for felling the land cover type (land cover felled at the proportion at which it is available). Land covers that were preferred for milpa were expected to be felled in a higher proportion than their relative availability, while those that are avoided were expected to be felled at a proportion less than their relative availability. A one-sample t test on the mean residual of each scatterplot served to determine significant deviations from the null hypothesis of no preference (mean residual ¼ 0). Data were tested for normality using the Kolmogorov-Smirnov test, and where significant (P , 0.05) deviations were found, data was log-transformed to achieve normality. RESULTS Analysis 1: Changes in land cover 1976–1997 The composition of the accessible landscape changed substantially between 1976 and 1997, especially in the most accessible zones (Appendix D). The ANCOVA models were all highly significant, explaining between 89.9% and 96.4% of variance in the land cover trends (Table 4). All land covers were spatially structured, with MF being more abundant with increasing distance from the village, whereas the opposite was true for Mi, YF, and SF (Fig. 2). YF became particularly abundant in the most accessible areas, explaining the significant YEAR 3 ACCESS interaction (Fig. 3b). The cover of MF decreased uniformly across the landscape (Fig. 2d), with no significant YEAR 3 ACCESS interaction detected (Table 4). For SF, cover increased evenly across accessibility zones in 1976–1988, but in 1988–1997 this trend continued only in the less
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FIG. 2. Interaction plots from ANCOVAs on land cover composition, for (a) milpa (Mi), (b) young fallows (YF), (c) secondary forests (SF), and (d) mature forests (MF) (Analysis 1). Johnson-Neyman (J-N) regions of significance are indicated for plots with significant interaction terms (note that ‘‘All ACCESS’’ refers only to the range of the co-variable included in the study). The variable ACCESS consists of seven buffer zones, each representing ;11 minutes of travel from Se˜nor, based on the accessibility index (Table 3).
accessible areas (ACCESS . 5.4; Fig. 2c). The significant YEAR 3 ACCESS interaction term thus indicates a qualitative change in the land dynamic, shifting from increase in SF to no change. A similar shifting dynamic is observed in the case of milpa/open areas. From 1976 to 1988, Mi declined sharply in the most accessible zones (ACCESS , 4), due to the abandonment of a large (;1000 ha) pasture that existed as part of a cattle ranching project near Se˜nor (in ACCESS buffers 1–3) in the 1970s. By 1978 the project was abandoned, and the pasture was let to fallow to be subsequently used for milpa (S. P. Dalle and M. T. Pulido, personal observations). From 1988 to 1997, Mi continued to decrease, with a decline of approximately 3.6% throughout the study area (Fig. 2a).
Analysis 2: Changes in fallow periods Over the study area, milpa cover in X-Maben was derived predominantly from MF (42% in 1991 and 38% in 2000), followed by SF, YF, and Mi. From 1991 to 2000, the most notable changes are for milpas felled from young fallows (Mi_YF), which increased from 20% to 29% of milpa cover and for Mi_Mi, which decreased from 10% to 1%. The ANCOVA models of changes in fallow periods were all significant (Table 5), although they explained less of the variance (between 31.6% and 79.6%) in fallow periods than those performed on land covers. This could be due to the fact that we estimated fallow periods using a land cover transition, which introduces more error into the models.
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FIG. 3. Interaction plots from ANCOVAs on the proportion of milpas in t2 felled from different land covers in t1: (a) milpa, (b) young fallows, (c) secondary forests, and (d) mature forests (Analysis 2). The Johnson-Neyman region of significance is indicated for plots with significant interaction terms.
In the case of milpa cover derived from YF (Mi_YF), a significant ACCESS 3 YEAR interaction was detected (Table 5), with significant increases occurring in areas closer to Se˜nor only (ACCESS , 2.4; Fig. 3b). In these areas, Mi_YF nearly doubled. This increase is consistent with the hypothesis of shorter fallow periods in these parts of the landscape. Milpas derived from ‘‘milpa/open areas’’ (Mi_Mi; interpreted here as milpas cropped for two or three consecutive cycles) was the only land cover in this study that was not spatially structured (Fig. 3a). The KruskallWallis test revealed a significant temporal trend, with less milpa cover being derived from Mi in 2000 as compared to 1991 (v2 ¼ 9.9531, df ¼ 1, P ¼ 0.0016). Field observations and discussions with local farmers indicate that milpas that are cropped for several consecutive years tend to be felled first from older vegetation, since
they have lower weed loads. The decline in consecutively cropped milpas may thus reflect a decline in felling of older vegetation, providing additional support for the hypothesis of shorter fallow periods. Alternatively, this result might be an artifact from the different procedure used to classify the 1991 image (unsupervised classification) vs. the other images (see Appendix B). For milpas derived from older forests (Mi_SF and Mi_MF), no significant temporal change was detected. In these two models, only the relationship with ACCESS was significant, mirroring the spatial trends for SF and MF (Figs. 2c and d and 3c and d). Analysis 3: Preferences in land covers felled for milpa Fig. 4 shows the scatterplots for each land cover of the proportion available at t1 vs. the proportion of milpa at t2 felled from the land cover. The 1:1 line in these plots
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SARAH PAULE DALLE ET AL.
TABLE 5. Results of ANCOVA analyses to test for changes in the proportion of milpa derived from different land covers (an estimate of fallow periods) in relation to accessibility (ACCESS) and time (YEAR ¼ 1991, 2000). R2
Factor
df
Type III SS
F
Proportion Mi_YF Full model ACCESS YEAR ACCESS 3 YEAR Error
3 1 1 1 10
0.3054 0.2379 0.0648 0.0418 0.0779
13.07 30.55 8.32 5.37
0.0009 0.0003 0.0162 0.0430
0.796
Proportion Mi_SF Full model ACCESS Error
1 1 12
0.0306 0.0306 0.0662
5.55 5.55
0.0363 0.0363
0.316
Proportion Mi_MF Full model ACCESS Error
1 1 12
0.4322 0.4322 0.1474
35.18 35.18
,0.0001 ,0.0001
0.746
P
Note: Mi_Mi was analyzed with a nonparametric test (see Fig. 3).
indicates the null hypothesis of no preference for the land cover. Significantly positive deviations from this null hypothesis were found for secondary forests in both time periods. For milpas felled from young fallows (Mi_YF) or that are consecutively cropped (Mi_Mi ), a significant avoidance was detected in the 1997–2000 time period only, whereas in 1988–1991 these covers were felled in proportion to their availability. No significant preference or avoidance was found for mature forests in either time period.
DISCUSSION In Central Quintana Roo, previous research has demonstrated very low rates of net forest loss at both the regional (Bray et al. 2004, Dura´n et al. 2005, Ellis and Porter-Bolland 2008) and the ejido scales (Dalle et al. 2006), due to the conservation of large tracts of community forests for chicle and timber extraction. Yet, as our findings illustrate, these high levels of forest conservation mask important land use/cover changes,
FIG. 4. Changes in felling preferences from (a–d) 1991 to (e–h) 2000 (Analysis 3). Scatterplots show the proportion of Mi, YF, SF, and MF felled for milpa in t2 relative to the proportion available in t1, in relation to a 1:1 line. Statistics from one-sample t tests are shown when significant differences were found in the mean residual (in all cases df ¼ 6). Positive mean residuals indicate significant preference for the land cover, whereas negative mean residuals indicate significant avoidance. For each image pair, t1 is the earlier image and t2 is the later image.
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that become apparent when defining the sampling ‘‘space’’ as a function of human needs and accessibility to agricultural resources. Indeed, over the 21-year period studied, the local population saw the accessible landscape transformed from a heterogeneous array of different successional stages including mature forests to a landscape dominated by young fallows. Such changes have a number of consequences for the availability and productivity of wild and cultivated resources. For example, our research has shown that fuelwood, which in Quintana Roo is harvested from deadwood in mature forests and from spared stumps and trees in the milpa, has become scarce due to declines in the accessibility of mature forests and as a result of the predominance of short-fallow milpas that provide far less fuelwood than long-fallow milpas (Dalle 2006, Dalle and De Blois 2006). Similarly, the accessible landscape is poor in the availability of thatch derived from the palm Sabal yapa, which is much more productive in mature forest than younger secondary forest (Pulido 2006, Pulido and Caballero 2006). The productivity of the milpa can also be affected since short-fallow shifting cultivation is associated with higher weed loads (Staver 1991, de Rouw 1995, Fujisaka et al. 2000) and repeated and/or short cycles have been linked to poor dispersal and establishment of pioneer trees and other species that promote efficient fallows (Metzger 2003, Lawrence et al. 2005, Dalle and De Blois 2006). These types of impacts were often articulated by local people during our research as they recounted how the ejido had changed over time. Our analysis of agricultural trajectories helps elucidate some of the land use practices (agricultural expansion and intensification) that contributed to these observed land cover changes in different parts of the accessible landscape. In areas within 30 minutes travel from Sen˜ or, all mature forests, other than those remaining in village reserves (10% of land cover), had been eliminated indicating that in these areas, the agricultural frontier had essentially closed by 1997. Fallow cycles were shortened, with the majority of milpa cover being derived from young fallows by 2000, and no additional secondary forests were generated. The significant avoidance of felling young fallows in 2000 reveals that the reduction in fallow periods was a reflection of the scarcity of preferred secondary forests, rather than a preference for young fallows. The resulting landscape, dominated by young fallows, mirrors the patterns reported by Metzger (2003) for short-fallow landscapes in the Amazon, and reflects trends of intensification widespread in shifting cultivation systems (Ramakrishnan 1992, Kellman and Tackaberry 1997, Brookfield 2001). Thus, intensification, while taking pressure off forests in outlying areas, led to an impoverishment of the shifting cultivation landscape within accessible areas. In the more distant parts of the accessible landscape (especially . 1 hour travel from Se˜nor), we observed a
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decline in mature forests as these are felled for milpa, combined with an increase in secondary forests and fallows, a dynamic that is more consistent with agricultural expansion (Table 1). Because our analytical approach does not allow us to distinguish old fallows (.25 years) from forests that have not been used for milpa (at least within living memory), it is also possible that the conversion of mature forests to milpa could be indicative of long-fallow cycles (e.g., . 25 years) rather than agricultural expansion. However, in the long-fallow situation, one would expect equilibrium dynamics with stable overall land cover composition (Metzger 2002), rather than the increases in the proportion of young fallows and secondary forests that we observed. The hypothesis of agricultural expansion is further supported by our finding that secondary forests were preferred for milpa, while mature forests were felled in the proportion they were encountered. This suggests that mature forests were only felled as a means to open up ‘‘new’’ land, i.e., as a means of expansion, to be subsequently managed with shorter fallow periods. This finding indicates that 11 years after the establishment of the PPF, the agricultural frontier was not entirely closed in these more distant parts, although potential for further expansion was greatly limited, with much of the remaining forest protected under community norms (Dalle et al. 2006). These patterns of agricultural expansion and intensification can be considered proximate drivers of land cover change, which in turn are the result of a complex set of underlying drivers (Keys and McConnell 2005). At the outset of this study, we postulated that forest conservation would be a driver of intensification. Our results indicate that a process of intensification did occur following the implementation of the PPF, a process that was accompanied by the expansion of community norms protecting valuable forest types (Dalle et al. 2006). This finding is supported by Bray et al. (2004)’s study of 50 ejidos in Central Quintana Roo, which reported that older ejidos, with greater timber volumes had a significantly lower probability of deforestation from 1984–2000, suggesting that the PPF contributed to halting agricultural expansion. While these findings suggest a link between forest conservation and intensification, it is not possible to firmly establish a causal relationship. Indeed, other processes also occurred during the study period that likely contributed to the observed land use/cover changes. For example, the strong demographic growth and concentration in Se˜nor (see Study area) is most certainly an important driver of both the agricultural expansion and intensification observed in the ejido. A regional trend toward economic diversification, with increased importance of wage labor and off-farm economic activities (Murphy 1990:150, Hostettler 1996:345) may also have encouraged felling of the more accessible young fallows, as families have less time to travel to the milpa (S. P. Dalle and M. T. Pulido,
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personal observations). Changes in agricultural policies (especially in relation to NAFTA and declines in maize prices) and the progressive increase in the proportion of non-ejidatarios are other factors that have influenced land use practices in Mexico. More in-depth research linking underlying drivers and decision-making processes to land use and land cover changes (e.g., Geoghegan et al. 2001, Klepeis and Vance 2003, Abizaid and Coomes 2004) is required to identify the relative importance of forest conservation with respect to these and other factors in driving the expansion–intensification dynamics in central Quintana Roo. Implications for sustainable land management Our findings have several important implications for sustainable land management. First, the fact that secondary forests are preferred over mature forests for milpa suggests that shifting cultivation in this area is largely fallow based, as is also the case in some parts of the Southern Yucatan peninsula (Lawrence et al. 2004), and will not compete with mature forests providing that there is sufficient fallow land to sustain agricultural activities. Land management approaches must therefore ensure access to secondary forests to maintain midlength fallow cycles and reduce some negative impacts of intensification. Second, specific conservation measures are needed to maintain mature forests within the agricultural matrix of this shifting cultivation system. Maya communities have developed a number of community norms to protect mature forests and these have been respected even in relatively accessible parts of the landscape (Dalle et al. 2006). However, with the exception of a few village reserves close to Se˜nor, this has not been enough to maintain a diverse matrix within the accessible areas and these reserves were reported by villagers to be very heavily harvested. Third, and perhaps most important, our data provide evidence that at the time the PPF was initiated (1986), significant land use and land cover changes were occurring in areas most accessible to the majority of the ejido population. As a state-wide program, the PPF was an opportunity to improve land management in the state and the program was effective in helping communities increase economic benefits from the forest and to strengthen incentives for forest conservation (Bray et al. 2004, Dalle et al. 2006). Yet, by focusing on the management of commercial timbers in the permanent forest areas, the PPF was a missed opportunity to address the land use/land cover changes affecting the areas most used for agriculture, hunting and gathering of noncommercial forest products. The lack of attention to agriculture and noncommercial forest uses is not unique to the PPF. For example, research from Asia has highlighted how gathering of fuelwood and forage have been prohibited from a number of community forests in India and Nepal, leading to increased hardship on women and other less
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powerful groups who are poorly represented in the community forest decision-making bodies (Mehta and Kellert 1998, Agarwal 2001, Gupte 2004). Walker (2005) has further argued that community forestry lobbies in Thailand, while aiming to secure community tenure to government reserve lands, have overlooked the need to secure agricultural land rights. To overcome these shortcomings, community forestry and other forest-based economic activities need to be considered within the broader context of local livelihoods. One important way this can be done is through participatory land use planning, taking into account the diverse management objectives and interests (e.g., Bocco et al. 2000, Velazquez et al. 2001, Anta Fonseca et al. 2006). This indeed can be an important policy tool to bring together different stakeholders to address conflicting interests and trade-offs in management scenarios (Zurayk et al. 2001). In X-Maben, such an approach could have entailed several elements including (1) protection of more forests and hedgerows (e.g., Remmers and de Koeijer 1992) within the agricultural area; (2) improved access to productive agricultural lands further from Se˜nor in order to maintain as much as possible the mid-length fallow cycles preferred for milpa; (3) development of locally adapted strategies to maintain milpa productivity (Pascual 2005, Eastmond and Faust 2006) and to manage important resources, such as fuelwood and thatch. Methodological strengths, limitations, and recommendations for future research Studies of agricultural intensification are typically based on on-farm surveys of agricultural practices, but these are rarely linked to broader patterns of land use/ cover change. By using remote sensing data we were able to provide an analysis of agricultural trajectories at the landscape scale, contributing to a better understanding of at least the proximate drivers of land use/cover change. To do so, we derived indicators (Table 1) from existing understanding of land cover change in shifting cultivation systems that could be examined with remote sensing data. This was practical for several reasons: (1) intensification was occurring mainly in terms of changes in the fallow period, rather than through technological changes; (2) shifting cultivation was the dominant land use in the study area; and (3) we had knowledge of, and were able to test, the preferred fallow period. Given similar conditions, the indicators used here could be adapted and applied to other study regions. Laney (2002, 2004), using a case study from Madagascar in a region with a mix of fallow-based and permanent agriculture, provides an example of modeling more complex intensification dynamics. One limitation of our study was the accuracy assessment, in particular for the older images. While it is recognized that conducting a rigorous field-based accuracy assessment is generally challenging (Foody 2002), this is especially true for tropical shifting
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cultivation landscapes with dense regenerating vegetation making access to randomly selected points difficult. Also, the constantly shifting nature of land cover makes it inappropriate to verify past status from current field conditions. Meticulous classification of land use/land cover for earlier maps often depends on the availability of other sources of historical data, which, if they are scarce, can in turn result in a lack of independent data for further testing the accuracy of the maps produced. In this study, our thorough classification approach included visiting sites whose land use history was known to specific informants and recall of significant events for which dates could be verified (e.g., marriages, hurricanes) to identify sites that had been cultivated that year. While such an in-depth classification approach can increase the confidence in maps, it cannot replace an extensive field-based accuracy assessment. Given the importance of land use/cover studies in tropical landscapes, we encourage further development of methods adapted to these challenging contexts. Despite this limitation, our analyses demonstrated strong, plausible, and consistent trends in land cover change over space and time. Overall, the effect of classification errors is limited by the fact that our analysis relied mostly on comparisons of land cover proportions over time and not on land cover transitions. The exception is for Analysis 2 where the estimation of vegetation felled (i.e., fallow period) was based on a transition, which introduced more error into our models. An alternative for future research may be to use Metzger (2002)’s approach for estimating fallow periods, which is based on the frequency of disturbance, calculated from an annual or biannual time series of satellite images. Conclusions This research has highlighted the need for integrated land management approaches that balance both agriculture and forest conservation. In recent years, the organization supporting the PPF in the Zona Maya (OEPFZM) is increasingly attempting to move toward such an approach (V. Santos, personal communication): a lesson that we hope will be heeded by nascent community-based conservation initiatives in the future. The specific links between forest conservation and agricultural livelihoods should also be carefully considered in other forms of forest protection, including the intense negotiations for carbon credits, an emerging market that is likely to drive future land changes worldwide. ACKNOWLEDGMENTS We extend special thanks to the people of Ejido X-Maben for their collaboration in this study and for sharing their knowledge, experience, and friendship with us throughout our stay in Se˜nor. Julia Murphy’s insightful pioneering work in XMaben provided an important inspiration for this study. We are grateful to Jean-Franc¸ois Mas for guidance in the preparation of the land cover maps, to Jeanine Rhemtulla and Reto Schmucki for helpful advice on the statistical procedures, and
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to Hewa Saranadasa for advice on using the Johnson-Neyman procedure and for writing the SAS code. Javier Caballero and Timothy Johns provided guidance and supervision throughout the research. Comments from three anonymous reviewers greatly improved the quality of the manuscript. The fieldwork for this study was supported by a Doctoral Research Award from the International Development Research Centre (Ottawa). We also acknowledge funding from the Fonds Que´becois de Recherches sur la Nature et les Technologies, the Natural Science and Engineering Research Council of Canada, the Celanese Canada Internationalist program, and the Secretarı´ a de Relaciones Exteriores (Mexico). LITERATURE CITED Abizaid, C., and O. T. Coomes. 2004. Land use and forest fallowing dynamics in seasonally dry tropical forests of the southern Yucatan Peninsula, Mexico. Land Use Policy 21:71–84. Agarwal, B. 2001. Participatory exclusions, community forestry, and gender: an analysis for South Asia and a conceptual framework. World Development 29:1623–1648. Alcorn, J. B. 1981. Huastec noncrop resource management: implications for prehistoric rain forest management. Human Ecology 9:395–417. Al-Sayed, M., and A. Al-Langawi. 2003. Biological resources conservation through ecotourism development. Journal of Arid Environments 54:225–236. Anta Fonseca, S., A. V. Areola Mu˜noz, M. A. Gonza´lez Ortiz, and J. Acosta Gonza´lez, editors. 2006. Ordenamiento territorial comunitario. Instituto Nacional de Ecologı´ aSemarnat, Me´xico D.F, Me´xico. Barrera-Bassols, N., and V. M. Toledo. 2005. Ethnoecology of the Yucatec Maya: symbolism, knowledge and management of natural resources. Journal of Latin American Geography 4:9–41. Berkes, F., J. Colding, and C. Folke. 2000. Rediscovery of traditional ecological knowledge as adaptive management. Ecological Applications 10:1251–1262. Bocco, G., A. Vela´zquez, and A. Torres. 2000. Ciencia, comunidades indı´ genas y manejo de recursos naturales. Un caso de investigacio´n participativa en Me´xico. Interciencia 25:64–70. Bray, D. B., E. A. Ellis, N. Armijo-Canto, and C. T. Beck. 2004. The institutional drivers of sustainable landscapes: a case study of the ‘‘Mayan Zone’’ in Quintana Roo, Mexico. Land Use Policy 21:333–346. Bray, D. B., L. Merino-Perez, P. Negreros-Castillo, G. SeguraWarnholtz, J. M. Torres-Rojo, and H. F. M. Vester. 2003. Mexico’s community-managed forests as a global model for sustainable landscapes. Conservation Biology 17:672–677. Brookfield, H. 2001. Exploring agrodiversity. Columbia University Press, New York, New York, USA. Caballero, J. 1994. Use and management of Sabal Palms among the Maya of Yucatan. Dissertation. University of California, Berkeley, California, USA. Cairns, M. A., P. K. Haggerty, R. Alvarez, B. H. J. de Jong, and I. Olmsted. 2000. Tropical Mexico’s recent land-use change: a region’s contribution to the global carbon cycle. Ecological Applications 10:1426–1441. Colunga-GarciaMarı´ n, P., and D. Zizumbo-Villarreal. 2004. Domestication of plants in Maya Lowlands. Economic Botany 58:S101–S110. Cornelius, W. A., and D. Myhre, editors. 1998. The transformation of rural Mexico. reforming the ejido sector. University of California, San Diego, California, USA. Dalle, S. P. 2006. Landscape dynamics and management of wild plant resources in shifting cultivation systems: a case study from a forest ejido in the Maya Zone of Quintana Roo, Mexico. Ph.D. thesis, McGill University, Montre´al, Que´bec, Canada.
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APPENDIX A Land cover maps of Ejido X-Maben from 1976, 1988, and 1997 (Ecological Archives A021-073-A1).
APPENDIX B Schematic representation of image processing steps and land cover classes used in Analyses 1–3 (Ecological Archives A021-073-A2).
APPENDIX C Procedure used to estimate group differences in ANCOVAs with significant interaction terms (Ecological Archives A021-073-A3).
APPENDIX D Bar graphs of land cover composition vs. accessibility for three time periods (Ecological Archives A021-073-A4).
