TEMPORAL PATTERNS OF DEFORESTATION AND FRAGMENTATION IN LOWLAND BOLIVIA: IMPLICATIONS FOR CLIMATE CHANGE

Supplementary material

Jesús N. Pinto-Ledezma (1, 2, 3), Mary Laura Rivero Mamani (1)

  1. Departamento de Ecología, Museo de Historia Natural Noel Kempff Mercado, Universidad Autónoma Gabriel René Moreno, Av. Irala 565, CC. 2489, Santa Cruz de la Sierra-Bolivia.
  2. Carreras de Biología y Ciencias Ambientales, Universidad Autónoma Gabriel René Moreno, El Vallecito Km. 9 carretera al Norte, CC. 702, Santa Cruz de la Sierra-Bolivia.
  3. Correspondence author:

INTRODUCTION

The aim of this supplementary material is to complement the section “Study area and Methods” of the main paper by furnishing: i- a more comprehensive description of the study area, namely Lowland Bolivia and Chiquitanía and 2- more details on image processing, on methods and metrics that were employed to analyze deforestation and defragmentation .

STUDY AREA AND METHODS

Lowland Bolivia

The most recent classifications (Navarro and Maldonado 2002, Ibisch and Merida 2003) recognize several different Amazonian forest types (inundated, pre-Andean, Beni-Santa Cruz), Chiquitano dry forest, Gran Chaco dry forest, and Serrano-Chaco forest. The region also contains numerous savanna habitats, which are essentially western outliers of the Cerrado biome of central Brazil (Killeen 1997), or are similar to the inundated savannas of the Gran Pantanal to the southeast.

The Chiquitanía

The Chiquitano dry forest is a term used to describe a complex of forest communities that occur across the climatic transition described above (Killeen et al. 1998), representing what is probably the largest extant patch of what is now broadly recognized as the Neotropical seasonal dry tropical forest complex (Prado and Gibbs 1993, Prado2000, Killeen et al. 2006). The Chiquitano dry forest ranges from completely deciduous in the south to semi-deciduous in the north, while the degree of deciduousness in the intervening areas is highly variable depending on the amount of precipitation that falls within any given year at any given place.

The Chiquitano dry forest is located in the central region of the eastern Bolivian lowlands (Department of Santa Cruz). This ecoregion is bordered on the west and north by the Amazon and to the south by the Chaco (Olson et al. 2001). Approximately 9% (101,769 km2) of the land surface of Bolivia is comprised of Chiquitano dry forest. Topographically the Chiquitano dry forest is represented by plains, hills, and low mountains (including Precambian shield inselbergs). Elevation ranges from 100 to 1400 meters. The annual average temperatures range from 21-28º C, with a minimum of 3º C due to the southerly winds (surazos). Annual average precipitation, locally variable, ranges from 600-2300, with approximately 3-8 dry months (Olson et al. 2001).

Forest habitats are composed of closed canopy deciduous forest, which are dominated by extremely hard-wooded species with a large potential economic value in international timber markets (Killeen et al. 1998). However, the forests and savannas of the Chiquitanía are coming under increasing threat from land use change, due in part to regional initiatives in the energy and transportation sectors (PRIME 2000). Recently recognized as a unique ecoregion, the Chiquitano dry forest has become the focus of conservation initiatives because it is one of the best-preserved dry forest ecosystems in the world (Olson et al 2001).

Image processing

To analyze the spatial and temporal patterns of deforestation and fragmentation in the Chiquitanía, a set of five mosaics of Landsat scenes (pre1976, 1986, 1992, 2001, and 2008).were used. This image set is adapted from previous studies in the Bolivian lowlands (see Steininger et al. 2001, Killeen et al. 2007 and Gobernación de Santa Cruz 2009). The last period (2008), is based on a mosaic of fourteen Landsat images: TM and ETM. These images were georeferenced with a RMS error of 0.3 pixels. The image classification process was applied using the unsupervised module program Isodata v9.2 Erdas Imagine (Leica Geosystems 2006). The classification process was conducted using 10 iterations and a convergence threshold of 0.95% to produce a raster with 125 spectral classes. The spectral classes were grouped into classes based on thematic similarity spectral coverage rates (Killeen et al. 2007, Pinto-Ledezma and Ruiz 2010).

Priortotheclassification,the authors conductedtwo visits to the fieldin JulyandAugust2009,wheregeo-referenced dataofthemaintypesof coverage were collected(N =475).Theprimarycoveragesinthe field wereidentified as: Forest (Amazonian and Chiquitano dry forest), Non-forest (Savannas, Cerrado, and Chaco woodland), Deforested (urban areas, human settlements, agricultural areas, and cultivated pastures for cattle grazing, Water, and Wetlands. We usedthefield dataforasupervised classification, and these datawere usedtoestablishtraining areaswith aminimum of70pixels(sensuEastman), using themaximum likelihood classifier(Maximum Likelihood) ofErdasImaginev9.2(Leica Geosystems, 2006).

The classesresultingfromthe five studyperiodswere groupedintoforest, savannaanddeforested, creating five map mosaics withthreethematic classes.

Finally, theaccuracy oftheclassificationfor thefirst fourstudy periodswerebasedonstudiesofSteiningeretal.(2001) andKilleenetal (2007), where forestshadan accuracyof90%, deforested98%, andsavanna75%, ofwhich5% was mistakenforforestregeneration. For the last period (2008), the overall classification accuracies were: forest 92%, savanna 86%, and deforested 95% (Congalton and Green 2009).

Deforestation and fragmentation analysis methodology

The term “deforestation” is used when there is a replacement of natural cover (forest and savannas) by cultivated pastures, agricultural fields, urban areas and/or human settlements (Dirzo and Garcia 1992, Pinto-Ledezma and Ruiz 2010). The term “fragmentation” refers to a disruption in the continuity of natural covers (Lord and Norton 1990), and the subdivision of landscapes into smaller units (Laberty and Gibbs 2007).

For the calculation of deforestation rates (r) we use the methodology proposed by Puyravaud (2003), which is an expression of compound interest and does not underestimate the annual deforestation rate when changes are very large and fast (Puyravaud 2003). In this sense, the rates of deforestation were calculated for the five periods (pre1976, 1986, 1992, 2001, and 2008), using the year 1950 as a basis to calculate the first period (Bethell 2008).

Quantification and comparison of the spatial configuration of natural covers (forest and savanna) was conducted based on the set key landscape metric (Forman 1995, Gavier and Bucher 2004, Pinto-Ledezma and Ruiz 2010). We calculate six landscape metrics at the class level because this level better represented the pattern and distribution of land cover and land use (Pan et al. 2004), and report these data for the central Chiquitanía (i.e., San Julián district). The selected metrics include percentage of landscape (PLAND), number of patches (NP), mean patch size (MPS), patch density (PD), mean nearest neighbor distance (MNN), interspersion and juxtaposition index (IJI), and dispersion index (DI) (McGarigal et al. 2002).

Description of the selected metrics for the analysis of forest and savanna fragmentation

The percentage of landscape is defined as the percentage of natural covers in the study area, and the number of patches is defined as the total of patches of the corresponding cover. The mean patch size indicates the average size of all patches in the landscape. The progressive reduction of size is a key component in the process of fragmentation. Patch Density, a fundamental but limiting aspect of landscape pattern, is defined as the number of patches per unit area, which facilitates comparisons among landscapes of varying size. Patch density is a good indicator of fragmentation (McGarigal et al. 2002, Smith et al. 2009); however, it is often of limited value for interpretation itself, as it conveys no information about the size and spatial distribution of patches (McGarigal et al. 2002). The mean nearest neighbor distance, the average distance between forest and savanna patches, and that of nearest neighboring forest and savanna patches, reflect the spatial arrangement of these natural covers. The interspersion and juxtaposition index provides information about the spatial configuration of landscape patches in their surroundings, and the degree of intermixing of patches is based on the number of classes and patch adjacencies (Gustafson and Parker 1992, McGarigal et al. 2002). High values of this index (e.g. 100) occur in landscapes where patch types are distributed with equal distance (as adjacency with other patches), while low values (e.g. 0.0) are characteristic of poorly interspersed landscapes (i.e. patches are randomly distributed) (McGarigal et al. 2002, Smith et al. 2009). Finally, the dispersion index refers to the tendency for patches to be regular or continuously distributed with respect to others, and reflects the spatial distribution of fragments in the landscape. The values of this index range between 0.0 and 2.4, as follows: if the index value is equal to 1, the patches are randomly distributed, if it is less than 1, the patches are aggregated, and if greater than 1, the fragments are distributed regularly (Forman and Godron 1986, McGarigal et al. 2002).

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