Forest dynamics and the importance of place in western Honduras

Applied Geography 29 (2009) 91–110

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Forest dynamics and the importance of place in western Honduras Danny Redo a, *, J.O. Joby Bass b, Andrew C. Millington a a b

Department of Geography, Texas A&M University, 810 O&M Building, College Station, TX 77843, USA Department of Geography and Geology, Box 5051, The University of Southern Mississippi, Hattiesburg, MS 39406, USA

a b s t r a c t Keywords: Honduras Site selection Forest transition Landscape ecology Remote sensing Land-use and land-cover change

Analyses of landscape change using remotely sensed satellite imagery constitute a large component of forest transition research, allowing for assessments of large areas. In the western highlands of Honduras is an area of complex forest dynamics (w45,000 ha) that has seen significant forest regeneration in recent years. However, analysis of the larger region (w500,000 ha) shows net forest loss. The comparative aspects highlight the importance of site selection and scale in forest transition analysis, a process often ignored in the land-use and land-cover change (LULCC) and forest transition literature. Results also highlight the importance of analyzing human-induced fragmentation at a variety of selected sites and a range of spatial scales, and producing quality, accurate forest cover and change maps. Ó 2008 Elsevier Ltd. All rights reserved.

Introduction The relationship between humans and forests has been the focus of much scholarly attention (e.g. Geist & Lambin, 2002; Lambin, Geist, & Lepers, 2003; Lepers et al., 2005; Williams, 2002) as societies’ imprint on land cover continues to expand. Emphasis is placed on deforestation, but over the last two decades, scholars have highlighted forest transition (FT) areas all over the world (Andre, 1998; Bass, 2004, 2005, 2006; Byers, 2000; Foster, 1992; Foster & Rosenzweig, 2003; Gillmor, 2001; Kauppi et al., 2006; Klooster, 2000, 2003; Mather, 1992, 2001, 2004; Perz & Skole, 2003; Petek, 2001; Staaland, Holand, Nellemann, & Smith, 1998; Thomlinson, Serrano, Lo´pezdel, Aide, & Zimmerman, 1996; Tucker & Southworth, 2005). A thorough discussion of FT theory is beyond the scope of this paper, but in its simplest form it implies that over time, forest area declines, reaches a base level and stabilizes, and then expands (often resembling a U-shaped curve) due to factors such as technological advances and an increase in agricultural productivity, changes in resource perception, rural abandonment and outmigration, economic growth, increased demand for timber, industrialization, the strengthening of sociopolitical institutions and urbanization (Bhattarai & Hammig, 2001; Erhardt-Martinez, Crenshaw, & Jenkins, 2002; Grainger, 1995; Mather, 1992, 2006; Perz, 2007). This literature, however, has rarely or only peripherally considered the importance of changing scales of analysis and site selection (i.e. choice of study area), though exceptions can be found in the works of Hecht and Rudel (Hecht, 2002; Hecht, Kandel, Gomes, Cuellar, & Rosa, 2006; Rudel, 2001; Rudel, Bates, & Machinguiashi, 2002; Rudel et al., 2005; Rudel, Pe´rez-Lugo, & Zichal, 2000). Many people view the humid tropics as landscapes of deforestation, but in painting that picture we rely on the multitude of studies that have been undertaken (e.g. Table 1) where the choice of study area or place was not considered deeply. In a recent debate between Perz and Walker in the Professional Geographer (60 [1]), the former author states that there ‘‘remains a need for more analytical discussion of how the processes [of forest transition] are similar and different across

* Corresponding author. Tel.: þ1 601 434 6006. E-mail address: [email protected] (D. Redo). 0143-6228/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.apgeog.2008.07.007

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Table 1 Forest change detection studies from Central America and Mexico. Purpose

Forest change

Methodology

Central America – MAB Corridor

Determine the amount of forest and clearance rate in the Mesoamerican Biological Corridor

Mean annual clearing rate of 0.58% per year

Hybrid method (unsupervised and supervised classification, cluster busting and post-class editing)

13,367,500

Belize – entire country

Report deforestation rates from 1990 to 2000

36,000 ha of forest cover lost

2,280,000

Belize – Toledo District

Document forest change from 1975 to 1999

Aggregate forest loss of w10% or 36,000 ha

10% stratified random sample of Landsat scenes Unsupervised classification and sub-pixel algorithms

Costa Rica – entire country

Report deforestation rates from 1990 to 2000

16,000 ha of forest cover lost

Costa Rica – entire country

Analyze primary forest change from 1940 to 1983 Link an inventory of deforestation to possible driving forces from 1952 to 1984 Produce maps of forest cover and deforestation from 1986 to 1997 Report rates of deforestation and fragmentation inside and outside protected areas from 1976 to 1996 Estimate forest cover change between 1986 and 1991

Primary forest declined from 67% of the landscape to 17% Forest cover declined from 84.4% of the landscape to 5.7%

10% stratified random sample of Landsat scenes Digitized and overlaid in a GIS

Costa Rica – Turrialba Volcano

Costa Rica – entire country Costa Rica – Sarapiqui region (La Selva)

Costa Rica – 50% of the country (mostly central valley and adjacent highlands) Costa Rica – Osa Peninsula

Costa Rica – Limon Province

Deforestation rates were less than 1% from 1986 to 1997 Forest cover declined from 55 to 34%

Forest area decreased by 225,000 ha

Assess extent and fragmentation in Corcovado National Park from 1979 to 1997

Forest declined from 97% of the landscape to 89%

See Tropical Science Center (1998)

Between 1986 and 1997, 54,830 ha was deforested (8% of the 1986 forest cover)

Overlaid aerial photos using a monoplotting program NA

Supervised classification and ‘‘in-pair processing’’ (checking for spurious polygons) Digitized and overlaid in a GIS

Classified into 5 categories using ‘‘in-pair processing’’ (checking for spurious polygons) See Tropical Science Center (1998)

Study area (ha)

Platform

Resolution

Authors

Landsat TM

30 m

Sader, Hayes, Irwin, and Saatchi (2001) and Sader et al. (2004)

Landsat TM and ETMþ

30 m

FAO (2003)

Landsat MSS and ETMþ

30–60 m

Emch et al. (2005)

5,110,000

Landsat TM and ETMþ

30 m

FAO (2003)

5,110,000

Airphotos

1:1,000,000

Sader and Joyce (1988)

39,500

Airphotos

1:20,000– 1:80,000

Veldkamp et al. (1992)

Landsat TM

30 m

Tropical Science Center (TSC) (1998)

Landsat MSS and TM

30 m

Sa´nchez-Azofeifa, QuesadaMateo, Gonzalez-Quesada, Dayanandan, and Bawa (1999)

Landsat TM, airphotos, and ground data

30 m; 1:250,000

Sa´nchez-Azofeifa, Harris, and Skole (2001)

109,300

Landsat MSS and TM

30 m

Sa´nchez-Azofeifa, Rivard, Calvo, and Moorthy (2002)

918,800

Landsat TM

30 m

Van Laake and Sa´nchezAzofeifa (2004)

442,100

5,110,000

98,600

5,110,000

D. Redo et al. / Applied Geography 29 (2009) 91–110

Location

Report deforestation rates from 1990 to 2000

7,000 ha of forest cover lost

10% stratified random sample of Landsat scenes

2,072,000

Landsat TM and ETMþ

30 m

FAO (2003)

Guatemala – entire country

Report deforestation rates from 1990 to 2000

54,000 ha of forest cover lost

10,843,000

Landsat TM and ETMþ

30 m

FAO (2003)

Guatemala – Maya Biosphere Reserve (Peten)

Monitor forest change from 1986 to 1997

513,816

Landsat TM

30 m

Sader, Hayes, Hepinstall, et al. (2001)

Guatemala – Maya Biosphere Reserve (Peten) Guatemala – Municipality of San Jose La Arada, Chiquimala

Analyze forest clearance and regrowth from 1974 to 1997 Observe changes in a common property forest from 1954 to 1996

Annual deforestation rates increased from 0.04 to 0.23% (1986– 1993); from 1993 to 1997 rates were 0.33–0.36% Annual average rate of clearance was 0.16%

10% stratified random sample of Landsat scenes Unsupervised classification of NDVI time-series

Unsupervised classification of NDVI time-series Forest inventories and change detection

513,816

Landsat MSS and TM

30 m

Hayes and Sader (2001) and Hayes et al. (2002)

3000

Aerial photography

1:83,333

Holder (2004)

Honduras – entire country

Report deforestation rates from 1990 to 2000

59,000 ha of forest cover lost

11,189,000

Landsat TM and ETMþ

30 m

FAO (2003)

Honduras – La Lima watershed Honduras – approximately half of the Department of Lempira (including Celaque National Park)

Analyze landscape change from 1955 to 1995 Map forest resurgence (among many others) from 1987 to 1996

Aggregate forest loss of 19% Forest cover increased 459 ha

950

Aerial photography Landsat TM and ETMþ

1:20,000– 1:50,000 30 m

Honduras – Cordillera Nombre de Dios

Logistic regression analysis was used to determine variables associated with forest loss for the time periods 1954–1965 and 1977– 1978

Deforestation rates were between 13.8 and 17.4% depending on the statistical figure employed

RS and GIS

NA

Topographic maps and aerial photography

1:40,000, 1:50,000, 1:60,000,

Kammerbauer and Ardon (1999) Southworth and Tucker (2001), Southworth, Nagendra, and Tucker (2002), Munroe et al. (2002), Nagendra et al. (2003), Southworth et al. (2004), and Munroe, Southworth, and Tucker (2004) Ludeke et al. (1990)

Mexico – entire country

Report deforestation rates from 1990 to 2000

631,000 ha of forest cover lost

197,254,500

Landsat TM and ETMþ

30 m

FAO (2003)

Mexico – Los Tuxtlas

Develop maps of rainforest distribution in a portion of Veracruz from 1967 to 1986

85,000

Ground data, aerial photographs, and Landsat TM

30 m

Dirzo and Garcia (1992)

Mexico – Lacandonia

Calculate rates of deforestation to assess conservation status from 1974 to 1991

Annual deforestation rates averaged between 4.2 and 4.3%; 84% of the original forest cover removed Nearly 20,000 ha of forest lost

10% stratified random sample of Landsat scenes Maps were digitized and overlaid in a GIS

Non-supervised classification of 38 randomly selected quadrats

ca. 60,000

Landsat MSS, TM, and airphotos

60 m

Mendoza and Dirzo (1999)

14.4% reduction of forest cover

10% stratified random sample of Landsat scenes GIS and change detection RS and GIS to create forest change trajectories

90,884

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El Salvador – entire country

(continued on next page) 93

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Table 1 (continued) Purpose

Forest change

Methodology

Mexico – Chiapas (Huistan and Chanal municipalities)

Monitor forest change from 1974 to 1990

Maximum likelihood classifier

Mexico – Lake Patzcuaro

Mapping forest extent from 1960 to 1990

Annual deforestation rates were 1.58% (1974–1984) and 2.13% (1984–1990) 12% of the landscape returned to forest

Mexico – Majahual coastal system

Detect land-cover changes

Mexico – Terminos lagoon (Campeche)

Document deforestation from 1974 to 1991

Supervised classification and change matrices GIS model

Mexico – entire country

Quantification and spatial characterization of land-use change from 1976 to 2000 Depict land-use change from 1980 to 2001

From 1973 to 1997, forest decreased 2.4% annually From 1974 to 1986 and from 1986 to 1991, deforestation rates were 2.2 and 5.3%, respectively Mexico lost 8,410,000 ha of forest in the last quarter century

Mexico – Oaxaca

5.4% of primary and secondary forest was lost, in addition to significant degradation

Study area (ha)

Platform

Resolution

Authors

Landsat TM

30 m

Ochoa-Gaona and Gonza´lez-Espinosa (2000)

8090

B&W aerial photographs

1:20,000– 1:50,000

460,540

Landsat MSS and TM

60 m

Michoacan State Forest Agency (from Klooster, 2000) Berlinga-Robles and RuizLuna (2002)

NA

NA

NA

Mas and Puig (2001)

Maps were overlaid in a GIS to generate change matrices

197,254,500

Digital maps

1:250,000

Mas et al. (2002)

Satellite images were printed at 1:250,000 scale and then overlaid with vector land-cover types Historical documents and statistics

9,000,000

Airphotos, Landsat ETMþ, and ground data

1:250,000

Vela´quez et al. (2003)

NA

NA

Bray and Klepeis (2005)

69,628

NA

NA

Mexico – eastern and southern Yucatan and Lacandon rainforest

Analyze forest histories from 1985 to 2003

In 1970s, secondary forest was 0.2%; in 1990s, secondary forest was 18.2%

Nicaragua – entire country

Report deforestation rates from 1990 to 2000

117,000 ha of forest cover lost

10% stratified random sample of Landsat scenes

12,140,000

Landsat TM and ETMþ

30 m

FAO (2003)

Panama – entire country

Report deforestation rates from 1990 to 2000

52,000 ha of forest cover lost

7,443,000

Landsat TM and ETMþ

30 m

FAO (2003)

Panama – Darie´n Park

Determine if road improvements (e.g. paving) cause deforestation

Forest cover declined 10% from 1987 to 1997

10% stratified random sample of Landsat scenes Spatially explicit economic model

1,625,800

NA

NA

Dames and Moore Engineering (from Nelson, De Pinto, Harris, & Stone, 2004)

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Location

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cases, what commonalities emerge, and when different processes nonetheless yield similar outcomes’’ (Perz, 2008, p. 142). We also argue that an assessment of how processes are analogous and dissimilar at different spatial scales within the same region are also vitally important as different processes operate at different spatial and temporal scales (Perz, 2007, 2008), but at what spatial scale of analysis can land-use change scientists be confident that changes observed are characteristic of a range of places? Does changing the study area size influence the observed forest transition? Walker contends that comparing the dynamics of change at varying spatial scales (e.g. backyard woodlot compared to the Amazon or Europe) defies any attempt at generalization (Walker, 2008, p. 138). But what about change between adjacent areas and more similar spatial scales? Does a comparison lose its shape only when compared at the extreme ends of the spatial spectrum? In an attempt to answer these questions and contribute to the recent debate set forth by Perz and Walker, this paper offers a comparative analysis of forest decline–regrowth in western Honduras. Using satellite imagery, landscape metrics and field observations, we assess spatial patterns of forest cover change and the drivers underpinning change in different sized areas in western Honduras. By analyzing forest cover change in four small sample areas of western Honduras, we encountered two different dynamics – deforestation and regeneration – suggesting that a forest transition may be underway. More importantly, looked at together these four areas remind us that the forest dynamic within relatively small areas varies and that extrapolating forest trends on the evidence of too few places is risky (e.g. Klooster, 2003). At the turn of the 21st century, concerns about forest loss and fragmentation in the tropics are commonplace. Significant research has been published on forest change in Central America and though pockets of reforestation have been identified, the overwhelming trend is forest loss (Table 1). Typical of this is Honduras, where some studies have noted increases in forest cover (e.g. Bass, 2004, 2006; Southworth & Tucker, 2001) while others have noted a decline (e.g. FAO, 2000; Kammerbauer & Ardon, 1999; UNESCO, 1991–1992; WRI, 1998). This study also contributes to this body of research, but provides a unique viewpoint in that several areas in Honduras have been analyzed instead of a single site. We have investigated forest cover change in the relatively unstudied departments of Intibuca and La Paz, a region with a forest–agriculture matrix that is experiencing dynamic forest conversion in western Honduras. Deforestation in Honduras After 1945, rates of deforestation in Central America likely surpassed any experienced during the pre- and post-Conquest eras (GEF, 2005; Williams, 1986), with the exception of the central Mayan lowlands (Allen & Barnes, 1985). During the 1990s, the Central American isthmus was considered to be one of the world’s most heavily deforested regions (Carr & Bilsborrow, 2000, 2005; FAO, 2000), despite reported reforestation in El Salvador and Mexico (Hecht et al., 2006; Klooster, 2000). Forest loss during the last four decades in Central America has been estimated at 300,000–431,000 ha annually (Castro, Sa´nchezAzofeifa, & Rivard, 2003; FAO, 2003). Honduras, the poorest (DeWalt, Stonich, & Hamilton, 1993; Paniagua, Kammerbauer, Avedillo, & Andrews, 1999) and most heavily forested country (4,600,000–5,400,000 ha) (FAO, 2000; WRI, 1998) in Central America, follows this trend. UNESCO (1991–1992) estimated that Honduras lost 14.5% of its total forest from 1968 to 1988. Much of this has been attributed to cotton, cattle, shrimp and melon ‘booms’ (DeWalt et al., 1993; Stonich, 1993, 1995; Williams, 1986) in Choluteca and Olancho, as well as banana cultivation in the Sula Valley and logging throughout the country (Contreras-Hermosilla, 2000). Losses continue into the twenty-first century (FAO, 2003). Honduras contains several ecological regions and has substantial ethnic diversity. Consequently, forest conditions vary throughout the country. The pine–oak forests of the interior of western Honduras are a crucial link in the Mesoamerican Biological Corridor, a project designed to connect protected areas in southern Mexico and Central America (Sader, Chowdhury, Schneider, & Turner, 2004; Zimmerer, Galt, & Buck, 2004). It is also considered an Endemic Bird Area (Powell, Palminteri, Locklin, & Schipper, 2001). Despite the fact that tropical dry1 forests cover approximately 50% of Central America, the interior remains poorly understood and their original extent is much diminished (Murphy & Lugo, 1995; Nagendra, Southworth, & Tucker, 2003). The western highlands are a dynamic region in which forests and soils are under increasing human pressure. Exploitation by logging and milpa agriculture reduce forest cover on steep slopes and lead to high erosion rates on the region’s shallow soils. As this study shows, large tracts of once intact forest have become increasingly isolated and fragmented in recent years. Study area This study focuses on two departments in the western highlands – Intibuca and La Paz (Fig. 1). Both are land-locked with a combined area of w500,000 ha. They cover approximately 37% of the western highlands and share borders with five Honduran Departments and a porous border with El Salvador. The departmental populations for Intibuca and La Paz were 179,872 and 156,560, respectively, in the 2001 census (Instituto Nacional Estadistica, 2001). Population growth rates between 1988 and 2001 were 44 and 25% (Direccı´on General de Estadistica y Censos, 1988).

1 Evans (1999) uses the 800 mm (31.5 in) isohyet as the contrariety between wet and dry forests, with seasonality and drought being the most distinctive feature of a subtropical and tropical dry forest (Bullock, Mooney, & Medina, 1995).

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Fig. 1. Departments of Intibuca and La Paz and the subsets used in analysis.

The landscape is rugged. Mountains average between 600 and 1500 m.a.s.l. (Pineda Portillo, 1984), though they can reach 2500 m.a.s.l., with 30–60 slopes (Ericksen, McSweeney, & Madison, 2002; Stonich, 1989; Tucker, 1999). Incised rivers create isolated, intermontane valley pockets at 300–900 m.a.s.l., which range in width from 3 to 7 km (Jansen, 1998; West & Augelli, 1989). The two largest in the study area are the Otoro valley and part of the Comoyagua valley, which contain the region’s two major cities (La Esperanza and La Paz) and a relatively high density transportation network. Generally, however, the rugged terrain and poor road network in some areas of these two departments make them relatively inaccessible. With the exception of narrow slivers of alluvial soils in valley bottoms, the mountain soils are highly mineralized, acidic and nutrient-poor (Holder, 2004; Parsons, 1976; West & Augelli, 1989). Land utilization is principally hillside subsistence agriculture – milpa2 – of maize, beans and squash (Barreto & Hartkamp, 1999) for household consumption, as well as cattle rearing and cash crop (coffee and vegetable) cultivation. Large swaths of western and central Honduras are still covered by large, contiguous patches of pine–oak forests, but much of it, of course, having been transformed by human agency (Powell et al., 2001). Dominant species include Pinus oocarpa and Quercus spp. at lower elevations, and Pinus pseudostrobus and Liquidambar styraciflua at higher altitudes. P. oocarpa and P. pseudostrobus thrive on acidic soils (Styles & McCarter, 1988), and oaks tend to grow on deeper soils (Pineda Portillo, 1984). Even though Pinus is clearly dominant, there is evidence that most of the lower slopes and valley bottoms might have been covered in deciduous broadleaf forest prior to human settlement (Denevan, 1961; Johannessen, 1963). At high elevations, patches of broadleaf cloud forest survive though people have slowly been clearing it for agriculture over many decades (West, 1998). The western highlands are a dynamic and complex region whose forests and soils have become increasingly pressured by a variety of political and economic trends from local to global scales. During the period covered by this study, western Honduras – like many places throughout the world – witnessed dramatic change. Modernization, urbanization, and improvements in communication and transportation infrastructures were

2 Milpa (field) is a common agricultural system known throughout MesoAmerica where maize is planted in conjunction with up to a dozen crops, but more frequently beans and squash (Mann, 2005, pp. 197–198). In Honduras, however, squash is not as common.

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spreading through the country on the heels of reforms that took place between the 1960s and 1980s (see Euraque, 1996). Untold numbers of non-governmental organizations were working on issues at multiple scales throughout the country. Economic diversification was continuing to expand, changing both lifeways and land surfaces. Conservation was gaining visibility as a public concern. In 1974, with the economic and professional assistance of Germany, the United States, and the United Nations Program for Development, Honduras formed the Corporacion Hondurena de Desarollo Forestal (COHDEFOR) (AFE-COHDEFOR, 1996; Sandoval-Corea, 2000). Initially, attention went mostly to industrialization and commercialization of the country’s forests. Toward the late 1980s, a larger ecological movement began to take hold, expressing interest in conservation, protection of resources, biodiversity, and ecosystem management. Reforestation began to receive attention, as did the formation of protected areas, causing approximately 24% of the country to be eventually put under a variety of forms of protected status, ranging from national parks to forest reserves to inhabited forest areas with regulations on their use (AFE-COHDEFOR, 1996, pp. 150–153; Sandoval-Corea, 2000, p. 279). What particularly marks this period is the increasing global coordination of environmental awareness. Honduras formed the Secretaria de Estado en el Despacho del Ambiente in 1993. In the same year, the Congress passed laws that, officially at least, assured the protection of the environment and guaranteed that forests would be protected, managed, and, if need be, replanted, formally ‘concretizing’ the growing global preoccupation with the environment (Sandoval-Corea, 2000, pp. 280–284). Coincidentally, these concerns grew with involvement by foreign agencies, mostly non-governmental organizations (NGOs) (see AFE-COHDEFOR, 1996, pp. 39, 155, 185, 199; Sandoval-Corea, 2000, pp. 287, 331–315, 409–414). Social and educational programs were put in place throughout the country, largely with the help of, if not directed by, foreign interests from the United States or Europe (AFE-COHDEFOR, 1996, p. 185; Sandoval-Corea, 2000, pp. 298–302). The context for conditions on the ground in Honduras during the years that separate this study’s data sources provides important perspectives on understanding why changes take place. As Catherine Tucker (2008) recently showed, a thorough example of how understanding social and economic processes at different scales helps inform notions on what causes change. Methods Change detection was undertaken on a Landsat 5 (TM) image acquired on December 7, 1987, and a Landsat 7 (ETMþ) image from March 29, 2000. Both images were acquired during the dry season on days clear of atmospheric haze enabling forest cover to be easily discerned from surrounding non-forest land uses, and to reduce inter-image differences between sun angle and azimuth, soil moisture and atmospheric transmission. Radiometric corrections were not conducted since a binary forest/ non-forest classification scheme was used and since the objective of this study was to identify forest decline–regrowth and not monitor land-cover change (Sader, Hayes, Hepinstall, Coan, & Soza, 2001, p. 1941). Also, radiometric correction atmospheric scattering was not an issue on the dates imagery was acquired. Black and white aerial photographs from 1992 (scale ¼ 1:40,000) and visual interpretation were used to identify representative training sites in forest (F) and non-forest (NF) areas. Forest cover data sets for 1987 and 2000 were produced using a maximum likelihood supervised classification rule. The forest class incorporated pine–oak and broadleaf forests, and early to late stages of secondary regrowth. Recent clear-cuts, permanent open areas, residential/urban areas, agricultural land, grassland, wetlands, and water bodies were included in the non-forest class (NF). Two forest/non-forest maps were produced for both images, and a binary change/no change analysis output matrix was created with four change classes from 1987 to 2000: no forest change (F / F), areas that were deforested over the 13-year period (F / NF), areas that became reforested (NF / F), and no non-forest change (NF / NF). Shapefiles of roads, rivers, urban centers, and wildlife/biological refuges were overlaid on the cover and change maps in a GIS using the original satellite imagery, aerial photography, and topographic maps in order to further enhance the spatial direction of change relative to other cover types. Due to the large size of the study area and its mountainous topography, accuracy was determined by visually interpreting the land cover from the original satellite images (Cushman & Wallin, 2000; Zheng, Wallin, & Hao, 1997) at 250 randomly sampled points for Intibuca and La Paz and 200 ground control points for each of the four subsets used for analysis. These were compared with the classified maps. Accuracy was lower for Intibuca and La Paz across both years compared to the four, smaller subsets (Table 2). For each of the four subsets, accuracy ranged from 78 to 86%. Little cloud cover was present, therefore most error can be attributed to shadows cast on southeastern-facing slopes. In addition, all errors that are reported are correlated to error of commission. For example, some pixels that were classified as forest should have been associated with the non-forest class.

Landscape metrics Landscape metrics were calculated from each of the forest and non-forest maps using Patch Analyst 3.1 (ArcView Extension) in order to analyze changes in landscape composition and configuration through time (Griffith, Stehman, & Loveland, 2003; Walsh, Evans, & Turner, 2004). The landscape and patch indices used in this study are partially redundant but have the potential to illustrate different aspects of the landscape (Southworth, Tucker, & Munroe, 2004):

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Table 2 Accuracy assessment for forest and non-forest images (1987 and 2000). Class

Number of points

Producer’s accuracy (%)

User’s accuracy (%)

I/LP – 1987

F NF

126 126

76.19 69.05

71.11 74.36

I/LP – 2000

F NF

126 126

76.98 69.84

71.85 75.21

Subset 1 – 1987

F NF

103 97

84.47 79.38

79.82 83.52

Subset 1 – 2000

F NF

103 97

87.38 79.39

82.57 84.62

Subset 2 – 1987

F NF

103 97

83.50 79.38

78.90 84.62

Subset 2 – 2000

F NF

103 97

84.47 81.44

79.82 86.81

Subset 3 – 1987

F NF

103 97

84.47 77.32

79.82 82.42

Subset 3 – 2000

F NF

104 96

84.62 78.13

80.73 82.42

Subset 4 – 1987

F NF

103 97

87.38 79.38

82.57 84.62

Subset 4 – 2000

F NF

103 97

89.32 77.32

84.40 82.42

(1) Class area (CA): coverage of forest and non-forest classes (ha); (2) Percentage of landscape (percent land): percentage of landscape occupied by each patch type; (3) Number of patches (NP): the total number of patches in each class; (4) Mean patch size (MPS): average patch size for each category (ha); (5) Area-weighted mean shape index (AWMSI): a dimensionless index of patch size which equals 1 for a perfectly square patch and increases when patches become more complex in shape; (6) Fractal dimension (FD): measures the geographic dimension of patches in a landscape with values ranging from 1 to 2 (Kojima et al., 2006). A value of 1 implies a straight line or regular patch shape while a value of 2 implies a square shape or more complex patch shape (Chen, Wang, Fu, & Qiu, 2001). Values closer to 1.4 will have short, jagged edges; values closer to 1.8 will take on a stair-stepped pattern resembling geometric shapes. The metrics were chosen to provide insights into the types of landscape change occurring and some of the driving forces change (Griffith et al., 2003). TLA, CA, and % land are area metrics that quantify landscape structure or composition at the landscape and class levels. NP and MPS are related patch-level metrics which are used to represent the number and average size of patches in each class type (McGarigal & Marks, 1995); they are also used to indicate forest fragmentation (Franklin & Forman, 1987; Millington, Velez, & Bradley, 2003). AWMSI and FD allow for an analysis of shape complexity and potential human impact. Results Forest dynamics in Intibuca and La Paz At the scale of the two departments (referred to as I/LP), forest cover decreased from 50.4% in 1987 to 36.6% in 2000 (Table 3). This is equivalent to a loss of 68,769 ha or a net of loss of 27.7% in 13 years (Table 4). Clear patterns of spatial change were found to be heterogeneous and scattered; that is, deforestation had predominately occurred around the periphery of settlements and roads. The greatest deforestation occurred along the border between Intibuca and neighboring Santa Barbara Department to the north, and along the Otoro River. Nonetheless, scattered and small areas of forest loss occurred in areas that had been contiguous forest in 1987. For example, patches of forest loss occurred at high elevations many kilometers from the nearest paved or dirt road. These we ascribe to clearance along foot paths and mule tracks which are not included on the GIS layers. Reforestation was also localized and concentrated in similar locations to deforested areas.

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Table 3 Proportion of areas studied under forest and non-forest in 1987 and 2000, and the net change in forest between 1987 and 2000. Area (ha)

I/LP Intibuca La Paz Subset 1 Subset 2 Subset 3 Subset 4

1987

498,846 281,191 217,655 44,680 44,680 44,680 44,680

2000

Net forest change

Forest (%)

Non-forest (%)

Forest (%)

Non-forest (%)

(ha)

(%)

50.4 54.1 45.6 55.0 86.5 53.0 41.7

49.6 45.9 54.3 45.0 13.5 47.0 58.3

36.6 39.9 32.3 43.5 68.0 64.9 26.4

63.4 60.1 67.7 56.5 32.0 35.1 75.4

68,769 39,732 29,061 3934 7582 þ5336 6112

27.7 26.1 29.2 21.6 21.3 þ22.5 36.6

Minus value signifies a forest loss overall between 1987 and 2000, and a positive sign signifies reforestation overall.

Landscape metrics reveal extensive forest fragmentation during the study period (Table 5). The number of forest patches increased by 100% while mean forest patch size decreased by nearly 65%, indicating that forest cover had been dissected and more fine-grained. Large contiguous forest patches that existed in 1987 had fragmented into numerous scattered and isolated patches by 2000. The AWMSI and FD showed little change for the forest class. As anticipated, the non-forest class showed the opposite trend in all metrics, except for FD which remained relatively constant (Table 5). Slightly more non-forest patches had developed by 2000 than in 1987 and patch size increased on average 2 ha suggesting the addition of new logging sites and farms, and the expansion of existing non-forest patches (e.g. increases in urban areas) (Turner, Pearson, Bolstad, & Wear, 2003). AWMSI for the non-forest class changed considerably suggesting that non-forest patch shapes had become more complex or convoluted. This result is counter to other research which suggests that human-induced changes generally result in patches with straighter boundaries (Griffith et al., 2003; White, Harrod, Romme, & Betancourt, 1995). The overall landscape pattern for I/LP in 2000 demonstrates that it was more complex, irregular, and fragmented than in 1987. This may be due to the fact that forest clearance is characterized by small irregular fields typical of swidden agriculture (Fox, Krummel, Yarnasarn, Ekasingh, & Podger, 1995; Jansen, 1998; Pfeffer, Schlelhas, DeGloria, & Gomez, 2005) though small-scale logging activities and urbanization cannot be ruled out. FD for the non-forest classes at both spatial scales remained constant during the 13 years (1.03–1.05), suggesting a human-induced edge simplification (natural boundaries usually have irregular boundaries and an FD greater than 1.05).

Forest dynamics in the subsets Subsets 1, 2, and 4 all show a decrease in forest cover over the 13-year time period with net forest losses of 21.6, 21.3, and 36.6%, respectively (Table 3). Areas of reforestation are present in each case, but forest losses greatly outweighed gains (Table 4). In all three areas reforestation and deforestation are concentrated along the margins of previously established settlements, roads, and rivers (Figs. 2 and 3). Additionally, the density of non-forest patches increased in non-forest areas. Basically, forest transition has occurred in areas where access is relatively easy (spatial inertia or accretive growth as seen in Ludeke, Maggio, & Reid, 1990; Mertens & Lambin, 2000; Mundia & Aniya, 2005). Subset 3 shows an increase in forest cover from 53 to 64.9% (Table 3). This represents a net forest gain of 22% (5376 ha) between 1987 and 2000. Reforestation exhibited a spatial pattern similar to the other subsets, i.e. most reforested were easily accessible (Fig. 2). Deforestation appears to be concentrated in the southwestern portion of the image, which could potentially be the result of random sample demarcations. In this subscene, deforestation, like reforestation, occurred along the periphery of non-forest (mainly agricultural) areas, but unlike regrowth also occurred along rivers. Area and size metrics for Subsets 1, 3 and 4, indicate that a well-connected non-forest matrix dominated each area in 1987 with forest cover being fragmented and isolated (Table 5). In Subset 1, the number of forest patches increased from 1987 to 2000 while patch size decreased. This is indicative of increasing forest fragmentation, with forest patches merging and

Table 4 Forest and non-forest change matrix for Intibuca and La Paz and the four subsets from 1987 and 2000. Direction of change (1987–2000) Study area

I/LP Intibuca La Paz Subset 1 Subset 2 Subset 3 Subset 4

Area (ha)

498,846 281,191 217,655 44,680 44,680 44,680 44,680

F/F

F / NF

NF / F

NF / NF

Area (ha)

% of Land

Area (ha)

% of Land

Area (ha)

% of Land

Area (ha)

% of Land

161,370 101,528 59,814 27,155 9656 20,843 9666

32.35 36.11 27.48 60.78 21.61 46.6 29.51

90,097 50,519 39,555 9410 9235 2859 9215

18.06 17.96 18.17 21.06 20.67 6.4 9.36

21,328 10,787 10,493 1297 3103 8196 3103

4.28 3.84 4.82 2.90 6.94 18.4 42.98

226,051 118,357 107,793 6818 22,686 12,782 22,696

45.31 42.09 49.53 15.26 50.78 28.6 18.15

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I/LP (498,846 ha) Forest Metricsa CA (ha) % Land NP MPS (ha) FD AWMSI a

1987 251,467 50 20,862 12.05 1.05 90.45

Subset 1 (44,680 ha) Non-forest

2000 182,638 36 43,524 4.2 1.04 83.89

1987 247,319 50 26,555 9.32 1.05 65.06

For a description of metrics, see text.

Forest 2000 316,148 64 27,688 11.42 1.05 117.68

1987 22,039 55 1627 13.55 1.05 35.98

2000 17,402 43 3859 4.51 1.05 42.16

Subset 2 (44,680 ha)

Non-forest

Forest

1987 17,971 45 2822 6.37 1.05 29.73

1987 34,632 87 476 72.76 1.04 20.86

2000 22,608 57 2115 10.69 1.05 59.65

2000 27,223 68 1647 16.53 1.04 45.06

Subset 3 (44,680 ha)

Non-forest

Forest

1987 5378 13 3091 1.74 1.05 12.62

1987 23,760 53 4674 5.08 1.4 36.97

2000 12,787 32 5030 2.54 1.05 21.33

2000 29,234 65 5511 5.3 1.4 43.88

Subset 4 (44,680 ha)

Non-forest

Forest

1987 20,920 47 5323 3.93 1.4 14.22

1987 16,705 41 2279 7.33 1.05 32.09

2000 15,446 35 10,054 1.54 1.4 8.84

Non-forest 2000 10,594 26 5752 1.84 1.05 14.14

1987 23,305 49 1739 13.40 1.05 36.64

2000 29,416 74 1126 26.12 1.04 48.81

D. Redo et al. / Applied Geography 29 (2009) 91–110

Table 5 Forest (F) and Non-forest (NF) pattern analysis for Intibuca and La Paz and the four subsets from 1987 and 2000.

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Fig. 2. Change maps for the two departments and four subsets (1987–2000).

becoming larger (Fig. 4). In Subsets 2 and 4, forest cover also became increasingly fragmented between 1987 and 2000. The trends in Subset 3 were quite different compared to the other subsets. The number of forest patches increased by 17% from 1987 to 2000 and patch size increased by 4%, suggesting that ‘new’ forest patches had established themselves in areas disconnected from existing forest patches (Fig. 4). The non-forest category changed considerably. The number of non-forest patches nearly doubled from 5323 to 10,054 (an 88% increase) and their mean size decreased from 3.93 to 1.54 ha. Although the number of non-forest patches in Subset 3 almost doubled, the decrease in non-forest patch size was enough to lead to a net loss of the non-forest area. In all four subsets, AWMSI changed considerably for both forest and non-forest classes since the largest patches are weighted more heavily than smaller patches in calculating the average patch shape for the class or landscape levels (McGarigal & Marks, 1995) (Table 5). Subsets 1 and 2 show an increase in AWMSI values for both forest and non-forest classes. In Subset 4, the AWMSI of forest patches decreased over time suggesting that patch shape had become increasingly more complex over time. In Subset 3, AWMSI values for forest patches increased while non-forest values declined, this supports the notion that forest patches had become both larger and more spatially complex. Non-forest patches, conversely, had become smaller with simpler shapes. Fractal dimension remained fairly constant for all four subsets for both classes, indicating that the overall complexity of the landscape had changed little in 13 years. Interestingly, the FD values for the forest and non-forest classes in Subset 3 (1.4) were much higher than the other three subsets and for I/LP (where values ranged from 1.03 to 1.05).

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Fig. 3. A portion of the departmental scale 1987–2000 change map showing forest removal on the periphery of established settlements and along rivers.

We suggest this reflects the very rugged topography in this region and observed low population densities between the towns of Marcala and La Esperanza. Though the difference between values of 1.03–1.05 and may appear small, FDs are constrained between 1 and 2 and this 35–36% difference is significant (Kojima et al., 2006). Discussion Overall, the analyses showed that the forest dynamics in one subset differed significantly from those at the departmental level, and in the other three subsets have similar trends. Both Intibuca and La Paz show overall forest losses between 1987 and 2000, three of the four subsets within the departments also experienced forest loss, but a fourth indicates an overall gain in forest. Specifically, in this subset forest cover increased by 22% – a gain of 5376 ha – between 1987 and 2000, mainly through the merger of previously fragmented forest patches, but also through the formation of new forest patches. This is in direct contrast to the overall picture for the two departments, which showed a 27.7% decline, and the other three, same-size subsets which had overall forest losses of 21.0 to 36.6%. In the case of the two departments, and the three subsets, forest fragmentation increased during the period studied; whereas in Subset 3, metrics indicate fragmentation decreased. Why in a region that shows such clear evidence of forest loss do the results from some of the smallest units analyzed mirror the overall picture, whilst for another they are the opposite? The forest loss and gains in Intibuca and La Paz Departments were anticipated and are comparable to other studies conducted in similar size areas in the region (Table 6). The aggregate forest loss (13.7% over 13 years) compares favorably to 8.1% over 25 years in southern Belize (Emch, Quinn, Peterson, & Alexander, 2005). The annual deforestation rate was far greater than that for the Maya Biosphere Reserve (Hayes & Sader, 2001; Hayes, Sader, & Schwartz, 2002; Sader, Hayes, Hepinstall, et al., 2001) as would be expected, but lower than for the unprotected Majahual coastline in the Yucatan peninsula

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Fig. 4. The top pair of images shows fragmentation of forest patches (green) by non-forest cover types (light blue) in the west of Subset 1. The bottom pair of images shows the merging of small forest patches (green) to larger, contiguous forest patches in the southwest portion of Subset 3.

(Berlinga-Robles & Ruiz-Luna, 2002). Comparing areas of similar size to the four subsets that were analyzed was also possible, although only two such areas were discovered (Table 7). Approximately three times as much of forest was lost around Volca´n Turrialba (Veldkamp, Weitz, Staritsky, & Huising, 1992) than in Subsets 1, 2 and 4 from this study, but the time period of analysis was also far longer, dating back to the early 1950s – the start of modern deforestation in Central America. We argue that if our analysis carried out in Intibuca and La Paz was extended back to the 1950s, very high proportional forest loss would also be found because deforestation rates vary over time and are often greatest early in a forest clearance sequence (Bradley & Millington, 2008). Therefore comparing annual deforestation rates in these three subsets with those from Huistan and Chanal municipalities in Chiapas (Ochoa-Gaona & Gonza´lez-Espinosa, 2000) may be more illuminating. There annual deforestation rates varied from 1.58 to 2.8% in ten and six year periods, respectively, compared to 1.2–2.52% in the three subsets which showed overall forest losses in western Honduras. However, neither of the areas in Costa Rica or Mexico showed an overall gain in forest cover as was the case with Subset 3 which spans Intibuca and La Paz Departments. It would appear that scale – in this study represented by size of study area – is a weak predictor of the area that is deforested and also of annual deforestation rates. If it were a better predictor, we might have expected deforested areas and rates in the smaller areas to be significantly different – either less or more – than the rates in larger areas because of the generalization phenomenon that is well known in remote sensing and cartography. The length of time over which forest dynamics are studied, and at which stage of economic development land colonization is studied, are a stronger influence on rates and amounts of forest loss: although the evidence we present here is tentative. More important in this analysis, however, is the location of the study site, i.e. the influence of place on forest dynamics. Forest losses for Honduras are mainly reported by international organizations, and the data used are reported to organizations such as FAO by the Honduras government. These range from 59,000 ha of forest lost between 1990 and 2000 to 100,000 ha lost between 1992 and 1993 (FAO, 2003). Other estimates (e.g. Nations & Komer, 1982; UNESCO, 1991–1992) are more difficult to compare. These data, particularly those reported in the FAO, 2000 Forest Assessment, are difficult to use comparatively and are error prone (Grainger, 2007). Nonetheless the trend projected by these statistics is one of forest loss, and in this respect Intibuca and La Paz Departments and three of the subsets appear to conform to a ‘data norm’ for Honduras.

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Table 6 Comparison of studies conducted in similar size areas of Intibuca and La Paz (w500,000 ha) in Central America and Mexico. Location

Study area (ha)

Belize – Toledo District

442,100

Guatemala – Maya Biosphere Reserve (Peten)

513,816

Increased from 0.04 to 0.23% between 1986 and 1993 Ranged from 0.33 to 0.36% between 1993and 1997

Sader, Hayes, Hepinstall, et al. (2001)

Guatemala – Maya Biosphere Reserve (Peten) Mexico – Majahual coastal system Honduras – Intibuca and La Paz Departments

513,816

0.16% between start year and end year 2.4% between 1973 and 1997

Hayes and Sader (2001) and Hayes et al. (2002) Berlinga-Robles and Ruiz-Luna (2002) This study

460,540 498,846

Annual deforestation rate

1.06% between 1987 and 2000 La Paz: 1.03% Intibuca: 1.08%

Aggregate forest loss

Authors

Aggregate forest loss of 36,000 ha or 8.1% between start year and end year

Emch et al. (2005)

Aggregate forest loss of 68,793 ha or 13.7% between 1987 and 2000 La Paz: 13.3%, Intibuca: 14.1%

This picture is complicated by the fact that little is known about the status of forests in other departments in Honduras, and the lack of studies of areas around 50,000 ha – the size of the subsets – in the country. An exception is Lempira Department, which with an area of 90,884 ha is smaller than either Intibuca (281,191 ha) or La Paz (217,655 ha), where Southworth and Tucker (2001) calculated an overall gain in forest cover between 1987 and 1996 of 459 ha or 5.1%. This suggests that reforestation is occurring in some parts of Honduras, and might indicate that a forest transition is underway. However, these indications are masked by the national and international dialogues about tropical deforestation. Intriguingly, Bass (2004) has found further evidence of reforestation in parts of Choluteca, Comoyagua, El Paraiso, Francisco Moraza´n and Valle Departments in Honduras, as well as Lempira, from repeat photography over a 44-year period between 1957 and 2001. According to Kok (2004), deforestation is dominant in the department of Olancho, but even here there is localized reforestation. Most importantly from this paper’s perspective Bass (2006) also found evidence of reforestation in Intibuca and La Paz Departments. It appears then that, although the national ‘picture’ is Honduras is one of deforestation, when departments are examined in detail the overall ‘picture’ may be one of deforestation, as is the case in Intibuca and La Paz, or reforestation, as is the case of Lempira. Downscaling further, pockets of reforestation can even be found in departments with an overall deforestation trajectory, such as I/LP (Fig. 2). The human drivers of forest change are multi-scalar and complex (Kok, 2004; Mather, Fairbairn, & Needle, 1999) but given the rarity of significant exogenous environmental factors in western Honduras between 1987 and 2000 (except for Hurricane Mitch), we argue that it is human-induced drivers linked to proximate causes of deforestation and reforestation that are responsible for the local effects illustrated in our research. Using a drivers and proximate causes approach we reflect on why the departments

Table 7 Comparison of studies conducted in similar size areas of the four subsets (w45,000 ha) in Central America and Mexico. Location

Study area (ha)

Annual deforestation rate

Costa Rica – around Volcan Turrialba

39,500

Mexico – Huistan and Chanal municipalities in Chiapas Province

69,628

1.58% between 1974 and 1984 2.8% between 1984 and 1990

Honduras – Intibuca Dept, Subset 1

44,680

1.23% between 1987 and 2000

Honduras – Intibuca Dept, Subset 2

44,680

1.50% between 1987 and 2000

Honduras – Intibuca and La Paz Depts, Subset 3

44,680

1.73% between 1974 and 1984 (forest gain)

Honduras – La Paz Dept, Subset 4

44,680

2.52% between 1987 and 2000

Aggregate forest loss

Authors

Aggregate forest loss of 31,086 ha or 78.7% between 1952 and 1984

Veldkamp et al. (1992)

Ochoa-Gaona and Gonza´lez-Espinosa (2000) Aggregate forest loss of 3934 ha or 21.6% between 1987 and 2000 Aggregate forest loss of 7582 ha or 21.3% between 1987 and 2000 Aggregate forest gain of 5336 ha or 22.5% between 1987 and 2000 Aggregate forest loss of 6112 ha or 36.6% between 1987 and 2000

This study

This study

This study

This study

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and the four subsets show different deforestation narratives, and argue that the construction of place based on drivers and proximate causes is essential before generalizing results from deforestation and reforestation research more widely. Deforestation It is clear that deforestation dominates these two departments, as it does for three of the four subsets. Populations have nearly doubled in the last two decades in Intibuca and La Paz (Direccı´on General de Estadistica y Censos, 1988; Instituto Nacional Estadistica, 2001). However, population growth by itself is a too simplistic and reductionist explanation, and leads us to a Malthusian trap (cf. Carr, Suter, & Barbieri, 2005 and studies therein). DeWalt et al. (1993) showed that population growth was not a major driver of change in southern Honduras, concluding that deforestation and land degradation were the result of the activities of large landowners and the unequal distribution of land; a conclusion supported by Brockett (1988), Jansen (1998) and Stonich (1989, 1992). Whatever the case, it is the complex set of activities that the population undertakes, rather than growth itself, which have been identified as the drivers and proximate causes of deforestation. A major issue confronting forests in Honduras, as elsewhere in Central America, is illegal logging (Contreras-Hermosilla, 2000, 2003; Richards, Wells, Gatto, Contreras-Hermosilla, & Pommier, 2003). Enforcement of timber extraction controls, particularly in remote areas, is ineffective. The tools at the disposal of enforcement agencies are few, penalties are negligible, and they are under-funded and under-resourced. Their lack of effectiveness is compounded by corruption and the fear of retaliation (Contreras-Hermosilla, 2003; Sunderlin & Rodriguez, 1996). With ineffective enforcement and disproportionately low penalties, illegal logging is worth the risk and a major proximate cause of forest loss in western Honduras. Why illegal logging is so important in western Honduras is strongly linked to the political situation and markets in El Salvador. The demand for construction timber from neighboring El Salvador (Fig. 1) has been very high for at least twenty years and is fuelled by post-Civil War reconstruction, and rebuilding after Hurricane Mitch in 1998 and two major earthquakes in 2001 (Contreras-Hermosilla, 2003; Richards et al., 2003). Richards et al. (2003) argue that the extensive pine forests of southwestern Honduras (Intibuca, La Paz and Lempira Departments) have met much of this demand. There is, of course, also internal demand for construction timber as the population grows, not least in Intibuca and La Paz Departments. Further demand in Intibuca and La Paz is created by domestic consumption. Oak is preferentially collected as a cooking fuel, and pine for firing pottery. It is estimated that between 70 and 90% of households in Honduras use wood as their primary fuel for cooking (Stonich, 1989). However, many households collect fuelwood by gathering dead branches from the forest floor or selectively cutting branches. Damage to oaks therefore might not be that great, especially if the trees are allowed to regenerate. It is therefore probable that domestic fuelwood collection from oaks is not as significant a cause of forest loss as illegal logging, although long-term damage in terms of forest degradation may be serious (Holder, 2004). Traditional pottery production, which is common in the western highlands, requires large amounts of pinewood to sustain the high temperatures required in kilns (Tucker, 1999). Pinewood is normally extracted from common property forests, and it is a major cause of forest loss because pines do not regenerate like oaks. Moreover, it is an essential component of household incomes as selling pottery is a major source of income for women, and provides extra income to pay for household outgoings associated with health care and education. Cattle ranching has been an important activity in Intibuca and La Paz ever since the 1950s and 1960s – the ‘golden age for cattle’ in Honduras. However, after the 1960s the focus of cattle production shifted to the north coast, and Olancho and Gracias a Dios Departments. Agricultural census data show that the number of cattle increased 27.7% between 1954 and 1994 in Intibuca, but the area under pasture declined by 3.1% suggesting a trend toward intensification (RDH, 1954, 1968, 1978, 1994). In La Paz the change was less marked, the cattle population declined by 4.04% and the area under pasture was unchanged. These data suggest that cattle ranching has not been a major cause of deforestation between 1987 and 2000 as little forest will have been converted to pasture in that time; though it could have led to reforestation, especially in Intibuca Department. The role of land tenure in the operation of these drivers and proximate causes is important. Land tenure in Honduras is still rooted in the property rights model of 19th century Spain. Land is generally domino pleno (i.e. full control by mestizos) or publicly owned by the state on which indigenous and poor mestizo squat (Fandino, 1993): some common forests are recognized (Tucker, 1999). Most forest loss occurs on common forests or land controlled by the state. Tucker (1999) argued that common property rights in neighboring department of Lempira allowed people to extract forest resources such as resin and fuelwood with few restrictions as well as to graze cattle at will, and that decisions made by owners of private land (domino pleno) made land tenure irrelevant. Our evidence suggests that their findings are applicable to Intibuca and La Paz. Reforestation Whilst logging, and to a lesser degree fuelwood collection for the pottery industry, are the main proximate causes of deforestation throughout Intibuca and La Paz, they do not explain the reforestation trend that dominated Subset 3 between 1987 and 2000 which also is responsible for the patches of reforestation scattered throughout the two departments. Different proximate causes and drivers of deforestation explain this trend. Cultivation of traditional shade-grown coffee – the main cash crop in western Honduras – leaves the forest canopy intact during cultivation or landowners will plant shade trees. In the context of this discussion any increase in shade-coffee cultivation will be evident as a trend in reforestation. Passive airborne and satellite sensors are unable to detect differences between radiance values of shade-coffee canopies and those of forest because they are either statistically similar or appear

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Fig. 5. A conceptual model showing how the drivers and proximate causes of deforestation and reforestation in western Honduras relate to the construction of place.

similar to slightly thinned forests (Castro et al., 2003; Sader, Hayes, Hepinstall, et al., 2001).3 In fact, GEF (2005) comment that rustic systems of shade-coffee sometimes resemble ‘natural’ forest. It is probable that at least some of the reforestation dynamic found in parts of the two departments is due to the uptake of shade-coffee by farmers. Whether this is reforestation or the expansion of agroforestry systems is a moot point. In Lempira, Munroe, Southworth, and Tucker (2002) found that ‘‘farmers responded favorably to national incentives to expand coffee production because credit for coffee farmers has become more readily available even for those who do not have private land titles.’’ However, unlike Intibuca and La Paz, shade-coffee is not grown in Lempira and sun-coffee cultivation is the main proximate cause of deforestation in that department (Southworth & Tucker 2001). Blackman, Albers, Sartorio, and Crooks (2003) have found that land close to large towns with coffee markets and urban centers is less likely to be cleared, but converted to shade-coffee because the net returns from this agroforestry system are more advantageous than farming other types of cultivation. Logic suggests that around urban centers in Intibuca and La Paz shade-coffee cultivation may be an important proximate cause of reforestation, driven by the international market for coffee. Bass (2006) has noted an increase in tree cover due to shade-coffee around the important coffee center of Marcala in Subset 3, where the number of coffee fincas increased by 947% between 1954 and 2002. This subset witnessed a 22.5% increase in ‘forest’ cover between 1987 and 2000. Many people view the humid tropics as landscapes of deforestation, but in painting that picture we rely on the multitude of studies that have been undertaken (e.g. Table 1) where the choice of study area or place was not considered deeply. By analyzing forest cover change in four sample areas of western Honduras, we encountered two different dynamics – deforestation and regeneration – suggesting that a forest transition may be underway. More importantly, looked at together these four areas remind us that the forest dynamic within relatively small areas varies and that extrapolating forest trends on the evidence of too few places are risky (e.g. Klooster, 2003). This is important. The proximate causes and their drivers are stimulating change, and

3 It should also be noted that it is difficult to detect low regrowth association with forest fallow in a mountainous environment where fields can often be small and irregular. For the purposes of this study, low regrowth will be included in the discussion of forest regeneration.

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are taking place in specific, local ways and within specific, local contexts resulting from particular combinations of multi-scalar processes. Understanding these processes and their distinct local manifestations is the challenge in understanding patterns of change, and how society might respond. In Fig. 5 we have attempted a conceptual model to show how the drivers and proximate causes of deforestation and reforestation in western Honduras relate to the construction of place. Conclusion This research shows the interplay of space and the time period of a study are important in analyzing forest dynamics in western Honduras and, we argue, all studies of forest dynamics. Geographical scale, represented by the size of the study area, is weakly related to the annual rate of deforestation and the proportion of a landscape deforested in Central America; but because of the relatively small number of comparable studies in the region this conclusion is tentative. It is also counterintuitive in terms of map generalization theory, which suggests that small geographical areas that are subsets of larger areas would show higher and lower rates of forest loss (or gain) than the larger areas. Even more tentative is the suggestion in the discussion that deforestation rates and the amount of an area deforested are dependent on when, in the time frame of economic development they were sampled, and the length of the time period sampled. Far less tentative, however, is the conclusion that the geographical locality or place that is sampled is paramount in determining the rate of forest loss, and even whether there is an overall gain or loss of forest cover. It is clear in this study that Subset 3 shows a radically different forest dynamic over 13 years to the other three subsets and to the bigger area that it was drawn from. Evidence suggests that agricultural intensification and the focus on shade-coffee production around Marcala in this subset is due a particular mix and concentration of proximate causes of deforestation and reforestation. These proximate causes are an integral part of the construction of place in ‘Marcala/Subset 3’ and are at the heart of what place means in the context of forest dynamics research. More intriguing is the possibility that drivers of forest dynamics, with their more distant origins, may be part of the construction of place at ‘Marcala/Subset 3’. Generally, studies of forest dynamics – be they deforestation or the forest transition – pay scant regard to the construction of place, though it is inherent in all studies. Perz (2007) counters this trend. The ignorance of site selection as a construct makes for poor geography: of more concern for the non-geographers who undertake this work, is that it provides a very unstable foundation on which to build general theory. Acknowledgements Danny Redo would like to thank his former advisors and colleagues at the University of Southern Mississippi as well as those in the Human–Environment Group at Texas A&M University, particularly Christian Brannstrom, for their valuable advice during this paper’s revision. References AFE-COHDEFOR. (1996). Analisis del Sub-Sector Forestal de Honduras. Tegucigalpa: Cooperacion Hondurena-Alemana, Programa Social Forestal. Allen, J. C., & Barnes, D. F. (1985). The causes of deforestation in developing countries. Annals of the Association of American Geographers, 75(2), 163–184. Andre, M. (1998). Depopulation, land-use change and landscape transformation in the French Massif Central. Ambio, 27(4), 351–353. Barreto, H. J., & Hartkamp, A. D. (1999). Analysis of maize production in Honduras: Linking census data to environmental variables through GIS. (pp. 1–22). NRG-GIS Series 99-02. Mexico, D.F.: CIMMYT. Bass, J. O. (2004). More trees in the tropics. Area, 36(1), 19–32. Bass, J. O. (2005). Message in the plaza: landscape, landscaping, and a forest discourse. Geographical Review, 95(4), 556–577. Bass, J. O. (2006). Forty years and more trees: coffee production and landscape change in western Honduras. Southeastern Geographer, 46(1), 41–65. Berlinga-Robles, C. A., & Ruiz-Luna, A. (2002). Land use mapping and change detection in the coastal zone of northwest Mexico using remote sensing technology. Journal of Coastal Research, 18(3), 514–522. Bhattarai, M., & Hammig, M. (2001). Institutions and the environmental Kuznets curve for deforestation: a crosscountry analysis for Latin America, Africa and Asia. World Development, 29(6), 995–1010. Blackman, A., Albers, H., Sartorio, B. A., & Crooks, L. (2003). Land cover in a managed forest ecosystem: Mexican shade coffee. Washington, DC: Resources for the Future. Bradley, A. V., & Millington, A. C. (2008). Coca and colonists: quantifying and explaining forest clearance under coca and anti-narcotics policy regimes. Ecology and Society, 13(1), 31. [online]. Bray, D. B., & Klepeis, P. (2005). Deforestation, forest transitions, and institutions for sustainability in southeastern Mexico, 1900–2000. Environment and History, 11, 195–223. Brockett, C. D. (1988). Land, power, and poverty: Agrarian transformation and political conflict in Central America. Boston, MA: Unwin Hyman Publishing. Bullock, S. H., Mooney, H. A., & Medina, E. (1995). Seasonally dry tropical forests. Cambridge, UK: Cambridge University Press. Byers, A. C. (2000). Contemporary landscape change in the Huascara´n National Park and buffer zone, Cordillera Blanca, Peru. Mountain Research and Development, 20(1), 52–63. Carr, D., & Bilsborrow, R. E. (2000). Population and land use/cover change: a regional comparison between Central America and South America. Journal of Geography Education, 43, 7–16. Carr, D., & Bilsborrow, R. E. (2005). Forest clearing among farm households in the Maya Biosphere Reserve. The Professional Geographer, 57(2), 157–168. Carr, D., Suter, L., & Barbieri, A. (2005). Population dynamics and tropical deforestation: state of the debate and conceptual challenges. Population and Environment, 27(1), 89–113. Castro, K. L., Sa´nchez-Azofeifa, G. A., & Rivard, B. (2003). Monitoring secondary tropical forests using space-borne data: implications for Central America. International Journal of Remote Sensing, 24(9), 1853–1894. Chen, L., Wang, J., Fu, B., & Qiu, Y. (2001). Land-use change in a small catchment of northern Loess Plateau, China. Agriculture, Ecosystems and Environment, 86(2), 163–172. Contreras-Hermosilla, A. (2000). The underlying causes of forest decline. Center for International Forestry Research (CIFOR). Occasional Paper 30, 1–23.

108

D. Redo et al. / Applied Geography 29 (2009) 91–110

Contreras-Hermosilla, A. (2003). Barriers to legality in the forest sectors of Honduras and Nicaragua. UK Overseas Development Institute (ORI), 1–5. Cushman, S. A., & Wallin, D. O. (2000). Rates and patterns of landscape change in the central Sikhote-alin mountains, Russian Far East. Landscape Ecology, 15(7), 643–659. Denevan, W. M. (1961). The upland pine forests of Nicaragua: A study in cultural plant geography. Berkeley, CA: University of California Press. DeWalt, B. R., Stonich, S. C., & Hamilton, S. L. (1993). Honduras: population, inequality, and resource destruction. In C. L. Jolly, & B. B. Torrey (Eds.), Population and land use in developing countries: Report of a workshop (pp. 106–123). Washington, DC: National Academic Press. Direccı´on General de Estadistica y Censos. (1988). Caracteristicas geograficas, migratorias y sociales de la poblacion por departmento. In: Censo nacional de poblacion, 1988, Tomo II. Tegucigalpa: Honduras. Dirzo, R., & Garcia, M. C. (1992). Rates of deforestation in Los Tuxtlas, a neo-tropical area in southeast Mexico. Conservation Biology, 6(1), 84–90. Emch, M., Quinn, J. W., Peterson, M., & Alexander, M. (2005). Forest cover change in the Toledo District, Belize from 1975 to 1999: a remote sensing approach. The Professional Geographer, 57(2), 256–267. Erhardt-Martinez, K., Crenshaw, E. M., & Jenkins, J. C. (2002). Deforestation and the environmental Kuznets curve: a cross-national investigation of intervening mechanisms. Social Science Quarterly, 83(1), 226–243. Ericksen, P. J., McSweeney, K., & Madison, F. W. (2002). Accessing linkages and sustainable land management for hillside agro-systems in Central Honduras: analysis of intermediate and catchment scale indicators. Agriculture, Ecosystems and Environment, 91(1), 295–311. Euraque, D. A. (1996). Reinterpreting the Banana Republic: Region and state in Honduras, 1870–1972. Chapel Hill, NC: The University of North Carolina Press. Evans, J. (1999). Planted forests of the wet and dry tropics: their variety, nature, and significance. New Forests, 17, 25–36. Fandino, M. (1993). Land titling and peasant differentiation in Honduras. Latin American Perspectives, 20(2), 45–53. FAO (Food and Agriculture Organization of the United Nations). (2000). Global forest resources assessment 2000 (chapter 35: Central America and Mexico), corporate document repository, forestry department. Rome: FAO. FAO (Food and Agriculture Organization of the United Nations). (2003). The state of the world’s forests, FAO corporate document repository, forestry department. Rome: FAO. Foster, A. D., & Rosenzweig, M. R. (2003). Economic growth and the rise of forests. The Quarterly Journal of Economics, 118(2), 601–637. Foster, D. R. (1992). Land use history (1730–1990) and vegetation dynamics in central New England, USA. Journal of Ecology, 80, 753–772. Fox, J., Krummel, J., Yarnasarn, S., Ekasingh, M., & Podger, N. (1995). Land use and landscape dynamics in northern Thailand: assessing change in three upland watersheds. Ambio, 24(6), 328–334. Franklin, J. F., & Forman, R. T. T. (1987). Creating landscape patterns by forest cutting: ecological consequences and principles. Landscape Ecology, 1(1), 5–18. GEF (The Global Environment Facility). (2005). El Salvador: Promotion of biodiversity conservation within coffee landscapes. Medium-sized project brief. Washington, DC: GEF. http://www.gefonline.org/projectDetails.cfm?projID¼466. Accessed 17.07.07. Geist, H. J., & Lambin, E. F. (2002). Proximate causes and underlying driving forces of tropical deforestation. BioSicence, 52(2), 143–150. Gillmor, D. A. (2001). Spatial patterns of land use and land cover change: processes, causes and consequences in the Republic of Ireland. In R. B. Singh, J. Fox, & Y. Himiyama (Eds.), Land use and land cover change (pp. 37–50). Enfield, NH: Science Publishers, Inc. Grainger, A. (1995). The forest transition: an alternative approach. Area, 27(3), 242–251. Grainger, A. (2007). The influence of end-users on the temporal consistency of an international statistical process: the case of tropical forest statistics. Journal of Official Statistics, 23(4), 553–592. Griffith, J. A., Stehman, S. V., & Loveland, T. R. (2003). Landscape trends in Mid-Atlantic and Southeastern United States ecoregions. Environmental Management, 32(5), 572–588. Hayes, D. J., & Sader, S. A. (2001). Comparison of change-detection techniques for monitoring tropical forest clearing and vegetation re-growth in a time series. Photogrammetric Engineering and Remote Sensing, 67(9), 1067–1075. Hayes, D. J., Sader, S. A., & Schwartz, N. B. (2002). Analyzing a forest conversion history database to explore the spatial and temporal characteristics of land cover change in Guatemala’s Maya Biosphere Reserve. Landscape Ecology, 17(4), 299–314. Hecht, S. B. (2002). Invisible forests: the political ecology of forest resurgence in El Salvador. In R. Peet, & M.Watts. (Eds.), Liberation ecologies: Environment, development, and social movements (2nd ed.). (pp. 64–103) London, England:: Routledge. Hecht, S. B., Kandel, S., Gomes, I., Cuellar, N., & Rosa, H. (2006). Globalization, forest resurgence, and environmental politics in El Salvador. World Development, 34(2), 308–323. Holder, C. D. (2004). Changes in structure and cover of a common property pine forest in Guatemala, 1954–1996. Environmental Conservation, 31(1), 22–29. Instituto Nacional Estadistica. Honduras. (2001). Censo Nacional de Poblacion yVivienda. http://www.ine-hn.org. Accessed 15.04.04. Jansen, K. (1998). Political ecology, mountain agriculture, and knowledge in Honduras. Amsterdam, Netherlands: Thela Publishers. Johannessen, C. L. (1963). Savannas of interior Honduras. Berkeley and Los Angeles, CA: University of California Press. Kammerbauer, J., & Ardon, C. (1999). Land-use dynamics and landscape change pattern in a typical watershed in the hillside region of central Honduras. Agriculture, Ecosystems and Environment, 75(1), 93–100. Kauppi, P. E., Ausubel, J. H., Fang, J., Mather, A. S., Sedjo, R. A., & Waggoner, P. E. (2006). Returning forests analyzed with the forest identity. Proceedings of the National Academy of Sciences of the United States of America, 103(46), 17574–17579. Klooster, D. (2000). Beyond deforestation: the social context of forest change in two indigenous communities in highland Mexico. Journal of Latin American Geography, 26, 47–59. Klooster, D. (2003). Forest transitions in Mexico: institutions and forests in a globalized countryside. The Professional Geographer, 55(2), 227–237. Kojima, N., Laba, M., Velez Liendo, X. M., Bradley, A. V., Millington, A. C., & Baveye, P. (2006). Causes of the apparent scale independence of fractal indexes associated with forest fragmentation in Bolivia. ISPRS Journal of Photogrammetry and Remote Sensing, 61(2), 84–94. Kok, K. (2004). The role of population in understanding Honduran land use patterns. Journal of Environmental Management, 72(1–2), 73–89. Lambin, E. F., Geist, H. J., & Lepers, E. (2003). Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environmental Resources, 28, 205–241. Lepers, E., Lambin, E. F., Janetos, A. C., DeFries, R., Achard, F., Ramankutty, N., et al. (2005). A synthesis of information on rapid land-cover change for the period 1981–2000. BioScience, 55(2), 115–124. Ludeke, A. K., Maggio, R. C., & Reid, L. M. (1990). An analysis of anthropogenic deforestation using logistic regression and GIS. Journal of Environmental Management, 31, 247–259. McGarigal, K., & Marks, B. J. (1995). FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure. General Technical Report PNW-GTR-351. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Mann, C. C. (2005). 1491: New revelations of the Americas before Columbus. New York, NY: Alfred A. Knopf. Mas, J. F., & Puig, H. (2001). Modalites de la deforestation dans le sud-ouest de l’Etat de Campeche, Mexico. Canadian Journal of Forest Research, 31, 1280–1288. Mas, J. F., Vela´zquez, A., Dı´az, J. R., Mayorga, R., Alca´ntara, C., Castro, R., et al. (2002). Assessing forest resources in Mexico: wall-to-wall land use/cover mapping. Photogrammetric Engineering and Remote Sensing, 68(10), 966–988. Mather, A. S. (1992). The forest transition. Area, 24(4), 367–379. Mather, A. S. (2001). The transition from deforestation to reforestation in Europe. In A. Angelsen, & D. Kaimowitz (Eds.), Agricultural technologies and tropical deforestation (pp. 35–52). Wallingford, UK: CABI Publishing. Mather, A. S. (2004). Forest transition theory and the reforesting of Scotland. Scottish Geographical Journal, 120(11), 83–98. Mather, A. S. (2006). Forest transition. In H. Geist (Ed.), Our earth’s changing land: An encyclopedia of land-use and land-cover change (pp. 241–246). London, England/Westport, CT: Greenwood Press. Mather, A. S., Fairbairn, J., & Needle, C. L. (1999). The course and drivers of the forest transition: the case of France. Journal of Rural Studies, 15(1), 65–90.

D. Redo et al. / Applied Geography 29 (2009) 91–110

109

Mendoza, E., & Dirzo, R. (1999). Deforestation in Lacandonia (southeast Mexico): evidence for the declaration of the northernmost tropical hot-spot. Conservation Biology, 8(12), 1621–1641. Mertens, B., & Lambin, E. F. (2000). Land-cover-change trajectories in Southern Cameroon. Annals of the Association of American Geographers, 90(3), 467–494. Millington, A. C., Velez, L. M. V., & Bradley, A. V. (2003). Scale dependence in multitemporal mapping of forest fragmentation in Bolivia: implications for explaining temporal trends in landscape ecology and applications to biodiversity conservation. ISPRS Journal of Photogrammetry and Remote Sensing, 57(4), 289–299. Mundia, C. N., & Aniya, M. (2005). Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. International Journal of Remote Sensing, 26(13), 2831–2849. Munroe, D. K., Southworth, J., & Tucker, C. M. (2002). The dynamics of land-cover change in western Honduras: exploring spatial and temporal complexity. Agricultural Economics, 27(3), 355–369. Munroe, D. K., Southworth, J., & Tucker, C. M. (2004). Modeling spatially and temporally complex land-cover change: the case of western Honduras. The Professional Geographer, 56(4), 544–559. Murphy, P. G., & Lugo, A. E. (1995). Dry forests of Central America and the Caribbean. In S. H. Bullock, H. A. Mooney, & E. Medina (Eds.), Seasonally dry tropical forests (pp. 9–34). Cambridge, UK: Cambridge University Press. Nagendra, H., Southworth, J., & Tucker, C. (2003). Accessibility as a determinant of landscape transformation in western Honduras: linking pattern and process. Landscape Ecology, 18(2), 141–158. Nations, J. D., & Komer, D. I. (1982). Indians, immigrants, and beef exports: deforestation in Central America. Cultural Survival Quarterly, 6(2), 8–12. Nelson, G., De Pinto, A., Harris, V., & Stone, S. (2004). Land use and road improvements: a spatial perspective. International Regional Science Review, 27(3), 297–325. Ochoa-Gaona, S., & Gonza´lez-Espinosa, M. (2000). Land use and deforestation in the highlands of Chiapas, Mexico. Applied Geography, 20(1), 17–42. Paniagua, A., Kammerbauer, J., Avedillo, M., & Andrews, A. M. (1999). Relationship of soil characteristics to vegetation successions on a sequence of degraded and rehabilitated soils in Honduras. Agriculture, Ecosystems and Environment, 72(3), 215–225. Parsons, J. J. (1976). Forest to pasture: development or destruction. Revista de Biologı´a Tropical, 21(Suppl. 1), 121–138. Perz, S. G. (2007). Grand theory and context-specificity in the study of forest dynamics: forest transition theory and other directions. The Professional Geographer, 59(1), 105–114. Perz, S. G. (2008). Forest transitions, environmental social theory, and land science research: reply to Walker. The Professional Geographer, 60(1), 141–145. Perz, S. G., & Skole, D. L. (2003). Secondary forest expansion in the Brazilian Amazon and the refinement of forest transition theory. Society and Natural Resources, 16, 277–294. Petek, F. (2001). Land use changes in Gorenjsko. In R. B. Singh, J. Fox, & Y. Himiyama (Eds.), Land use and land cover change (pp. 125–138). Enfield, NH: Science Publishers, Inc. Pfeffer, M. J., Schlelhas, J. W., DeGloria, S. D., & Gomez, J. (2005). Population, conservation, and land use change in Honduras. Agriculture, Ecosystems and Environment, 110(1–2), 14–28. Pineda Portillo, N. (1984). Geografia de Honduras (2nd ed.). Tegucigalpa, Honduras: Editorial ESP. Powell, G., Palminteri, S., Locklin, C., & Schipper, J. (2001). Central American pine–oak forests. World Wildlife Fund, National Geographic. RDH, Repu´blica de Honduras. (1954). Primer censo agropecuario 1952. San Salvador: Ministerio de Gobernacio´n, Direccio´n General de Estadı´sticas y Censos. Litografı´a e Imprenta Lud Dreikorn. RDH, Repu´blica de Honduras. (1968). Segundo censo nacional agropecuario 1965–66. Tegucigalpa: Secretaria de Economı´a y Hacienda, Direccio´n General de Estadı´sticas y Censos. RDH, Repu´blica de Honduras. (1978). Censo nacional agropecuario 1974. Tegucigalpa: Ministerio de Economı´a, Direccio´n General de Estadı´sticas y Censos. RDH, Repu´blica de Honduras. (1994). IV censo nacional agropecuario 1993. Tegucigalpa: Secretaria de Planificacio´n, Coordinacio´n y Presupuesto y Secretaria de Recursos Naturales. Richards, M., Wells, A., Gatto, F. D., Contreras-Hermosilla, A., & Pommier, D. (2003). Impacts of illegality and barriers to legality: a diagnostic analysis of illegal logging in Honduras and Nicaragua. International Forestry Review, 5(3), 282–292. Rudel, T. K. (2001). Did a green revolution restore the forests of the American South? In A. Angelsen, & D. Kaimowitz (Eds.), Agricultural technologies and tropical deforestation (pp. 53–68) Wallingford, UK: CABI Publishing. Rudel, T. K., Bates, D., & Machinguiashi, R. (2002). A tropical forest transition? Agricultural change, out-migration, and secondary forests in the Ecuadorian Amazon. Annals of the Association of American Geographers, 92(1), 87–102. Rudel, T. K., Coomes, O. T., Moran, E., Achard, F., Angelsen, A., Xu, J., et al. (2005). Forest transitions: towards a global understanding of land use change. Global Environmental Change, 15(1), 23–31. Rudel, T. K., Pe´rez-Lugo, M., & Zichal, H. (2000). When fields revert to forest: development and spontaneous reforestation in post-war Puerto Rico. The Professional Geographer, 52(3), 386–397. Sader, S. A., Chowdhury, R. R., Schneider, L. C., & Turner, B. L., II (2004). Forest change and human driving forces in Central America. In G. Gutman, A. C. Janetos, C. O. Justice, E. F. Moran, J. F. Mustard, R. R. Rindfuss, D. Skole, B. L. Turner, II, & M. A. Cochrane (Eds.), Land change science: Observing, monitoring and understanding trajectories of change on the earth’s surface (pp. 57–76). Dordrecht, Netherlands: Kluwer Academic Publishers. Sader, S. A., Hayes, D. J., Hepinstall, J. A., Coan, M., & Soza, C. (2001). Forest change monitoring of a remote biosphere reserve. International Journal of Remote Sensing, 22(10), 1937–1950. Sader, S. A., Hayes, D. J., Irwin, D. E., & Saatchi, S. S. (2001). Preliminary forest cover change estimates for Central America (1990’s), with reference to the proposed Mesoamerican Biological Corridor. In Proceedings of the (2001) annual conference of the American Society of Photogrammetric Engineering and Remote Sensing. St. Louis, Missouri. Sader, S. A., & Joyce, A. T. (1988). Deforestation rates and trends in Costa Rica, 1940–1983. Biotropica, 20(1), 11–19. Sa´nchez-Azofeifa, G. A., Harris, R. C., & Skole, D. L. (2001). Deforestation in Costa Rica: a quantitative analysis using remote sensing imagery. Biotropica, 33(3), 378–384. Sa´nchez-Azofeifa, G. A., Quesada-Mateo, C., Gonzalez-Quesada, P., Dayanandan, S., & Bawa, K. S. (1999). Protected areas and conservation of biodiversity in the tropics. Conservation Biology, 13(2), 407–411. Sa´nchez-Azofeifa, G. A., Rivard, B., Calvo, J., & Moorthy, I. (2002). Dynamics of tropical deforestation around national parks. Mountain Research and Development, 22(4), 352–358. Sandoval-Corea, R. (2000). Honduras: su gente, su tierra y su bosque. Tegucigalpa: Graficentro Editores. Southworth, J., Nagendra, H., & Tucker, C. M. (2002). Fragmentation of a landscape: incorporating landscape metrics into satellite analyses of land-cover change. Landscape Research, 27(3), 253–269. Southworth, J., & Tucker, C. M. (2001). The influence of accessibility, local institutions, and socioeconomic factors on forest cover change in the mountains of western Honduras. Mountain Research and Development, 21(3), 276–283. Southworth, J., Tucker, C. M., & Munroe, D. (2004). Modeling spatially and temporally complex land-cover change: the case of western Honduras. The Professional Geographer, 56(4), 544–559. Staaland, H., Holand, Ø, Nellemann, C., & Smith, M. (1998). Time scale for forest regrowth: abandoned grazing and agricultural areas in southern Norway. Ambio, 27(6), 456–460. Stonich, S. C. (1989). The dynamics of social processes and environmental destruction: a Central American case study. Population and Development Review, 15(2), 269–296. Stonich, S. C. (1992). Struggling with Honduran poverty: the environmental consequences of natural resource-based development and rural transformations. World Development, 20(3), 385–399.

110

D. Redo et al. / Applied Geography 29 (2009) 91–110

Stonich, S. C. (1993). ‘‘I Am Destroying the Land!’’: The political ecology of poverty and environmental destruction in Honduras. Boulder: Westview Press. Stonich, S. C. (1995). Development, rural impoverishment, and environmental destruction in Honduras. In M. Painter, & W. H. Durham (Eds.), The social causes of environmental destruction in Latin America (pp. 63–99). Ann Arbor, MI: University of Michigan Press. Styles, B. T., & McCarter, P. S. (1988). The botany, ecology, distribution and conservation of Pinus patula ssp. tecunumanii in the Republic of Honduras. CEIBA, 29, 3–30. Sunderlin, W. D., & Rodriguez, J. A. (1996). Cattle, broadleaf forests and the agricultural modernization law of Honduras. (pp. 1–33). CIFOR (Center for International Forestry Research) Occasional Paper No. 7(E). Thomlinson, J. R., Serrano, M. I., Lo´pez, T., Aide, M., & Zimmerman, J. K. (1996). Land-use dynamics in a post-agricultural Puerto Rican landscape (1936– 1988). Biotropica, 28(4a), 525–536. Tropical Science Center (1998). San Jose, Costa Rica. Available from: http://www.cct.or.cr/en/menu_cct.html. Accessed 25.03.05. Tucker, C. M. (1999). Private versus common property forests: forest conditions and tenure in a Honduran community. Human Ecology, 27(2), 201–230. Tucker, C. M. (2008). Changing forests: Collective action, common property, and coffee in Honduras. Berlin: Springer Press. Tucker, C. M., & Southworth, J. (2005). Processes of forest change at the local and landscape levels in Honduras and Guatemala. In E. F. Moran, & E. Ostrom (Eds.), Seeing the forest and the trees: Human–environment interactions in forest ecosystems (pp. 253–277). Cambridge, MA: MIT Press. Turner, M. G., Pearson, S. M., Bolstad, P., & Wear, D. N. (2003). Effects of land-cover change on spatial pattern of forest communities in the Southern Appalachian mountains (USA). Landscape Ecology, 18(5), 449–464. UNESCO Institute for Statistics (United Nations Educational, Scientific and Cultural Organization). (1991–1992). UNESCO statistical yearbook 1985–1993. Washington, DC. Van Laake, P. E., & Sa´nchez-Azofeifa, G. A. (2004). Focus on deforestation: zooming in on hotspots in highly fragmented ecosystems in Costa Rica. Agriculture, Ecosystems and Environment, 102(1), 3–15. Vela´quez, A., Dura´n, E., Ramı´rez, I., Mas, J. F., Bocco, G., Ramı´rez, G., et al. (2003). Land use-cover change processes in highly biodiverse areas: the case of Oaxaca, Mexico. Global Environmental Change, 13(3), 175–184. Veldkamp, E., Weitz, A. M., Staritsky, I. G., & Huising, E. J. (1992). Deforestation trends in the Atlantic zone of Costa Rica: a case study. Landscape Degradation and Rehabilitation, 3(2), 71–84. Walker, R. (2008). Forest transition: without complexity, without scale. The Professional Geographer, 60(1), 136–140. Walsh, S. J., Evans, T. P., & Turner, B. L., II (2004). Population–environment interactions with an emphasis on land use/land cover dynamics and the role of technology. In S. D. Brunn, S. L. Cutter, & J. W. Harrigton, Jr. (Eds.), Geography and technology (pp. 491–519). Dordrecht, Netherlands: Kluwer Academic Publishers. West, R. C. (1998). The Lenca Indians of Honduras: a study in ethnography. In R. C. West (Ed.), Latin American geography: Historical–geographical essays, 1941–1998, Vol. 35. Baton Rouge, LA: Geoscience and Man Publications. West, R. C., & Augelli, J. P. (1989). Middle America: Its land and peoples. Englewood Cliffs, NJ: Prentice Hall. White, P. S., Harrod, J., Romme, W. H., & Betancourt, J. (1995). Disturbance and temporal dynamics. In R. C. Szaro, N. C. Johnson, W. T. Sexton, & A. J. Malk (Eds.), Ecological stewardship: A common reference for ecosystem management (pp. 281–312). New York, NY: Elsevier Science. Williams, M. (2002). Deforesting the earth: From prehistory to global crisis. Chicago, IL: The University of Chicago Press. Williams, R. G. (1986). Export agriculture and the crisis in Central America. Chapel Hill, NC: University of North Carolina Press. World Resources Institute (WRI). (1998). World resources (1998–1999): A guide to the global environment. New York, NY: Oxford University Press. Zheng, D., Wallin, D. O., & Hao, Z. (1997). Rates and patterns of landscape change between 1972 and 1988 in the Changbai mountain area of China and North Korea. Landscape Ecology, 12(4), 241–254. Zimmerer, K. S., Galt, R. E., & Buck, M. V. (2004). Globalization and multi-spatial trends in the coverage of protected-area conservation (1980–2000). Ambio, 33(8), 520–529.