Robert Zomer
Center for Spatial Technologies
and Remote Sensing (CSTARS)
Dept.. of Land, Air, and Water Resources
University of California
Davis, CA 95616 USA
rjzomer@ucdavis.edu
Low elevation riparian forests found within the Middle Hills of Nepal are both essential biological habitat and important resources for local subsistence farmers. Forming networks of habitat patches within the primarily agricultural matrix of the Middle Hills, these forests are repositories of a rich biological diversity. Dynamics of forest change along riparian corridors were investigated within the newly established Makalu Barun National Park Conservation Area of eastern Nepal, based upon a comparison of remote sensing data over a twenty year interval. Multispectral analysis and a supervised classification of Landsat TM (1992) and Landsat MSS (1972) data estimates approximately 7,000 ha. of low elevation riparian forests within the study area. Change detection analysis estimates based upon the respective supervised classifications reveal little significant change in extent of the tropical and subtropical zone riparian forests. More impact was evident towards the upper elevational limits of the study area. Approx. 300 ha loss of cover within areas previously designated as forest within the LRMP Landuse Map is estimated, constituting a 4% net loss since 1972. For all areas in the study area, a net loss of forest of 11% is estimated. Landuse is shown to be highly dynamic, with significant internal trading between landuse classes. The important role of riparian corridors in biodiversity conservation within the Middle Hills of east Nepal is discussed. Further research on biodiversity within these patches, and a specific recognition of the value of remnant riparian forests within the landscape and rural economy, are required if conservation goals for the eastern Nepal Himalaya are to be met.
Tables and Figures:
Cut deep into the Middle Hills of eastern Nepal Himalaya, a system of low elevation riparian corridors extends tropical climatic conditions far into the high Himalaya. Remnant tropical and subtropical forest vegetation along these riparian corridors provide important biological habitat for numerous rare and endangered species (Cronin 1979, Shrestha 1989, Jackson et al 1990, Shrestha et al 1990) within an increasingly monotypic and cover-poor landscape. Remnant forest vegetation forms networks of habitat patches which are essential for numerous indigenous and migrating wildlife species. These forests contain a large number of rare and endangered plant species, for example Podocarpus nerifolius, Cyca pectinata, Talauma hodgsonii, Cyathea spinulosa, and Pandanus nepalensis. (Shrestha et al, 1990). The occurrence of these forests is essential for many tropical birds and mammals, many of which are at considerable risk throughout the eastern Himalaya (Jackson et al. 1990). Rare large mammals reported to occur in this habitat type include clouded leopard, assamese monkey, leopard cat, golden cat, otters, and spotted linsang. Rare or protected bird species include the purple cochloa, rose-ringed parakeet, Blyth’s kingfisher, deep-blue kingfisher, blue-naped pitta, pale blue flycatcher, sultan tit, silver-eared mesia, black-spotted yellow tit, and the white-necked yuhina.
The vital role of forests within the mountain farming system, and the dependence upon fertility transfer from forest to agricultural fields to maintain agricultural production, is well described (Mahat 1987; Mahat et al 1987; Ives and Messerli 1989; Metz 1994). Within the agricultural zone of the Middle Hills, remnant patches of riparian vegetation constitute important resources for local subsistence agriculturalists, providing fodder, fuelwood, medicinal or other useful plant materials, and timber. Equally important to the sustainability of the mountain farming system, dense vegetation cover within the steep and highly erosive gullies and ravines to which these stands are confined provides important ecosystem and soil stabilizing functions (Zomer and Menke 1992). These forests are often fragmented or heavily impacted (Shrestha 1989, Shrestha et al 1990). Local farmers apparently recognize the important conservation value of protecting the most marginal areas and vulnerable riparian sites, however population growth and resource scarcity often put heavy demands on these areas. Many of these sites are often highly utilized or, in some cases, semi-managed. Increased demands upon these systems, with associated fragmentation and/or degradation of riparian forests, have resulted through improved access, e.g. particularly in the case of extension of new roads along the river corridors.
Tropical and subtropical monsoonal rain forests, located along the upper reaches of the Arun River, represent both ecologically and economically important repositories of regionally endangered biological diversity. Approximately 7000 hectares of these forest types occur within the boundaries of the MBCA (LRMP 1986).The importance of riparian vegetation within the mountain landscape is generally recognized, particularly in relation to wildlife habitat, dispersal and migration (Carleson et al., 1991; Harris 1984), refugia (Meave et al. 1991; Dix et al. 1997), and streamside management (Moyle et al. 1996). However, relatively few hectares of these hill-variant tropical and subtropical forest types are found within protected areas of Nepal (Hunter and Yonzon, 1993).
This current paper reports on a detailed landscape-level analysis of landuse and cover change in relation to the status of tropical and subtropical riparian forests within the Makalu Barun Conservation Area. A comparison of classified satellite remote sensing datasets is used to describe both spatial and temporal dynamics of forest change. A time interval of approximately 20 years, leading up to the establishment of the MBCA in 1992, is evaluated for both impacts upon forests and increase of tree cover on agricultural lands. Landscape and forest fragmentation metrics are used to evaluate current status of remnant forests. Extent, fragmentation, and recent historic change within tropical riparian forest stands within the MBCA are analyzed within the context of the dynamic nature of mountain farming systems as found in east Nepal.
STUDY SITE
The study area lies along the upper reaches of the Arun River of the eastern Nepal Himalaya, within the area now designated as the Makalu Barun Conservation Area (MBCA) (Fig. 1). The MBCA, established in 1991 by Dept. of National Parks and Wildlife Conservation, H.M.G. Nepal, lies on the edge of the vast and relatively undisturbed Makalu Barun National Park (MBNP). Envisioned as a buffer zone for the nearly 1500 sq. km. of uninhabited area designated as restricted National Park, the surrounding MBCA supports a population of approximately 40,000 inhabitants, mostly subsistence agriculturalists. These farmers, with an average farm size of approximately .5 hectare, depend heavily on local forest resources. Many of these agriculturalists also depend upon resources extracted from adjacent forests, or communal grazing lands, now within Park boundaries. The MBCA was instituted to mitigate and enhance conservation of the designated national park area through community-based resource management and development assistance (Sherpa et al. 1990: MBCP Task Force 1990).
Low elevation riparian corridors within the eastern Himalaya are generally referred to as being within the "tropical" bioclimatic zone if below 1000 m asl (Shrestha, 1989), or the "subtropical" if below 2000 m asl. Although geographically outside of the tropics (Latitude: 27° 30’ North), orographic blocking of cold winter air from central Asia allows tropical climatic conditions to prevail along the deeply cut river valleys. This tropical/subtropical zone is frost free, with average monthly mean temperatures above 18° C. throughout the year for elevations below 1000 m. Precipitation within this region of eastern Nepal is generally is high, and highly seasonal with most of the annual precipitation falling during the relatively long summer monsoon. Mean annual rainfall at the nearest weather station (Num) exceeded 4000 mm. Spatial distribution of precipitation is highly variable, and strongly influenced by orographic effects associated with the complex mountainous terrain. The upper Arun River corridor exhibits attributes common to "dry valleys" (Schwienfurth 1984), with upslope valley winds carrying moisture away from the lower slopes. Cloud forests with very mesic conditions are found on slopes above 2000m, where rising moist air forms belts of clouds, often leaving clear skies in the middle of wider valleys. Valley bottoms receive substantially less precipitation than upslope areas, and very little precipitation during the extended dry season.
In the eastern Nepal Himalaya, the main zone of cereal cultivation overlies the tropical and subtropical bioclimatic zones. Many of the native forests in these zones have been cleared for rice terraces (khet) and/or upland maize (bari), particularly in the less rugged areas. Some cultivation of rice and maize is found on terraces immediately adjacent the Arun, however, the tropical zone is generally not as intensively cultivated as the subtropical zone. Although most farmers reside at slightly higher elevations, possibly due to comfort or disease considerations, this zone is quite clearly integrated into the intensive mountain farming system. It is common for subtropical zone farmers to also have fields at lower elevations. This vertical zonation is partly due to a fragmentation of landholdings, but is also widely regarded as an adaptation of the mountain agricultural system to climatic differentiation associated with the altitudinal gradient. Livestock are generally rotated to graze stubble on lower fields during the winter, and are grazed in, or fed fodder from, nearby forest and riparian patches.
Near the bottoms of the steep and deeply cut river corridors in this region, slopes tend to be steep, and soils rocky, due to active steam cutting processes, and the unstable and erodable geologic substrate associated with the lower middle hills of the eastern Himalaya (Selby, 1988). Geomorphologic processes are accentuated here by sustained periods of intense precipitation, with frequent disturbance within riparian corridors due to seasonally swollen rivers and monsoonal downpours. Consequently, river- and stream-side zones are often left uncultivated, with vegetation in a semi-wild state. These lush and dense patches of remnant forest provide access to fuelwood, fodder, and other valuable resources for local subsistence agriculturalists. Access to these resources is integral to the local mountain farming systems. Ives and Messerli (1989) outline the important inter-relationship of agriculture and forests in the Nepal Himalaya. The mountain farming system is dependent upon a transfer of fertility from forest to farm, usually mediated by livestock and the collection of fodder. It is estimated that three to five hectare of forest are required to sustain the long-term fertility of one hectare of cereal production (Ives and Messerli, 1989). Recently farmers have responded to diminishing forests by inter-planting more trees on their farms (Gilmore and Nurse, 1991).
Forest types and vegetation of the eastern Nepal is renown for high levels of both species and community diversity (Hooker 1852, Singh and Singh 1987, Shrestha 1989). Low elevation riparian corridors within the MBCA are described as containing significant and important biodiversity and forest habitat (Jackson et al. 1990; Shrestha, 1989; Shrestha et al 1990). This point was highlighted at the time of establishment of the MBCA (MBCP Task Force 1990), as the study site lies adjacent to the proposed (but now defunct) Arun III Hydroelectric Project (Kattelmann 1990). Descriptions of forests of the Arun Basin include, among others, Hara (1966), Stainton (1972), Dobremez (1976), Oshawa (1983), and LRMP (1986). Lower elevational forests, specifically of MBCA, have been described by Oshawa (1983), Shrestha (1989), Shrestha et al (1990); and Carpenter and Zomer (1996). Three major formations were identified within the study area by Zomer et al. (1998a):
1.) Dipterocarpus forest, dominated by Shorea robusta, characterizes the tropical zone. It is found intermixed with palms, cycads, tree ferns, bananas, etc, below 800 m in the MBCA.
2.) Low montane needle-leaf forest, dominated by Pinus roxburghii, is relatively scare in the Arun Basin (Shrestha, 1989), and is mostly limited, within the MBCA, to a relatively xeric site above the confluence of the Sankuwa and Arun rivers.
3.) Low-montane evergreen broadleaf seasonal rain forest, prevalent throughout the Arun Basin, and referred to as Schima - Castanopsis forest, is characteristic of the subtropical bioclimatic zone. Lower ecotonal variants of this formation are found within the MBCA to well below 600 m, and form important components of the riparian vegetation of the tropical zone.
METHODS:
Field Studies
Surveys and fieldwork for this study were carried out in collaboration with the Wildlands Studies Program, San Francisco State University Extended Education. Six field expeditions conducted between 1991 and 1994 surveyed forest vegetation within the greater MBNPCA and its environs (Carpenter and Zomer, 1996). Site characteristics and vegetation data were sampled on 256 forest quadrats in a stratified random manner, of which 30 quadrats fall within the currently described forest types . Five community types, within three forest formations, were identified: Sal forest, Chir Pine, and three Subtropical Evergreen Broadleaf communities (includes riparian sub-types). A detailed quantitative analysis of the community ecology of these tropical zone riparian forest communities is presented in Zomer et al. (1998a). Additionally, a set of georeferenced ground-control points (GCP’s; n = 33) was selected within a stratified set of landuse types. Landuse and/or cover type within the immediate and general vicinity were qualitatively described. Site descriptions for both quadrats and GCP’s included an estimation of use and impacts by grazing, woodcutting, and fodder collection. The nature and extent of these landuse activities were categorized based upon observation and (when possible) informal interviews.
Non-differentially corrected Global Positioning System (GPS) receivers were used to georeference all plots and GCP’s. External antennas on 10 m collapsible fiberglass poles were used under closed canopy, or among tall trees, to improve satellite reception. Elevation was estimated by altimeter and a clinometer was used to sight slope angle and estimate canopy height.
Image Processing and Remote Sensing Analysis:
Two sets of satellite imagery, acquired approximately twenty years apart, were classified and compared to determine the extent, spatial distribution, and recent change of contemporary tropical and subtropical forests within the MBCA. The remote sensing based datasets include:
1.) Landsat TM seven-band scene acquired September 23, 1992, obtained in LSWOG format (level 1A data resampled to 25 x 25 m cell size) from the EOSAT Corp.
2.) Landsat MSS four-band scene acquired November 7, 1972, obtained in NLAPS format, (level 1A preprocessing, orbit-oriented, nearest neighbor resampled, 25 m cell size) from the Eros Data Center.
3.) Digital elevation model (DEM) of the study area. This was extracted from stereo SPOT imagery using a procedure described in Zomer et al (1998b).
All datasets were georeferenced to the Nepal GIS 1:250,000 Database (ICIMOD 1996), i.e. UTM, Zone 45, Everest 1830 Spheroid. Each satellite image was orthorectified to the extracted DEM, using EASI/PACE v.6.2 Satellite Orthorectification (SORTHO) software (PCI Inc.) . Results were compared with the various datasets found within, or derived from, the Nepal GIS 1:250,000 Database (ICIMOD 1996), including a DEM previously generated from the topographic contour layer (HMG 1984) using the TOPOGRID function within ARC/INFO - GRID (ESRI Inc.). Accuracy of georegistration was found to be significantly improved with orthorectification (Zomer et al, 1998b).
The multispectral analysis included calculation of the normalized difference vegetation index (NDVI) for each image. A visually enhanced RGB composite image was produced for each of the datasets. The supervised classification of the imagery relied on a set of pre-selected image classes identified within this enhanced RGB composite image. Training sites were selected based upon the field survey and the georeferenced field data. In order to compensate for the pronounced effects of topography within the Middle Hills of Nepal (Millette et al, 1995), image classes and their respective training sites, were chosen separately on sunny and shaded slopes. A Bayesian maximum likelihood supervised classification (confidence interval 95%) was performed on all spectral bands plus the NDVI to obtain the best results for each image class. Sunny and shaded slope variants of each image class were combined afterward to represent the aggregated class. In order that the full extent of the deeply entrenched tropical corridors might be mapped, the satellite imagery was clipped to include the tropical and subtropical zones, i.e. up to 2000 meters, as found within the boundaries of the MBCA. Four elevational zones of 500 meters each, spanning the altitudinal range of the study area, were used to provide a detailed breakdown of the analysis by elevation. Results are given in hectares, and relative to: the percent of the elevational zone (% Zone); the percent of the total study area (%Total_Area); the percent of all area classified as forest in 1972 (%MSS_Forest); and the percent of all area classified as forest in 1992 (% TM_Forest).
Landscape and Forest Fragmentation
The FRAGSTATS spatial pattern analysis program version 2.0 (McGarigal and Marks 1994) was used to analyze current landscape-level forest fragmentation. The Landsat TM (1992) classified image was prepared by setting all image classes not relevant to the fragmentation analysis to background values. The analysis was preformed using the public domain UNIX raster version of the FRAGSTATS software. Landscape measures selected for analysis and interpretation fall into five main categories (McGarigal and Marks 1994; Hargis et al, 1998):
1.) Area metrics are used to quantify landscape composition. Descriptive statistics representing area at the patch, class and landscape levels are reported.
2.) Patch metrics are used to represent landscape configuration. . Descriptive statistics representing the number or density of patches, the average size of patches, and the variation in patch size at the class and landscape levels are reported.
3.) Edge metrics are used to represent landscape configuration, and are considered a measure of ecologically important edge effects. Edge density standardizes total edge to a per unit area basis that facilitates relative comparison.
4.) Nearest neighbor metrics are used to quantify landscape configuration, and are calculated at the class and landscape level. Mean nearest neighbor distance (MNN) is computed for patches belonging to each of the respective classes, and for all patches in the landscape. Nearest-neighbor standard deviation (NNSD) is used as measure of patch dispersion.
5.) Contagion / interspersion metrics are used to represent patch interspersion and juxtaposition at the class and landscape levels. Contagion (O'Neill et al. 1988, Li and Reynolds 1993) measures both patch type interspersion and spatial dispersion within patch types. Interspersion and juxtaposition index directly measures patch interspersion and is independent of dispersion.
The FRAGSTATS manual (McGarigal and Marks 1994) gives a overview of use and interpretation of these measures. Utility , interpretation and potential range of these landscape metrics in response to various types of landscapes is reviewed by Hargis et al. (1998). Algorithms used to calculate metrics are listed in Appendix C of the FRAGSTATS manual (McGarigal and Marks 1994).
Landuse and Land Cover Change
The change detection analysis compared contemporary tree cover, as estimated by the classified Landsat TM (1992) data, to historical tree cover, as estimated by the Landsat MSS (1972) classified image. The two classified images were compared to iterate all combinations of change between the two dates. Two classes of change are reported; forest to agriculture, and agriculture to forest. The forest class was defined to include all significant tree cover, as detected within the respective datasets. Since most land in the study area which is not directly farmed is most likely grazed, the agriculture class was defined to include all other image classes except bare rock and river, e.g. grazing land and agricultural scrub. Results of the change detection analysis were compared with the LRMP Landuse Map (1978), as digitized within the Nepal GIS 1/250 Database (ICIMOD 1996). Two main categories of change are investigated based upon two aggregated LRMP landuse designations: 1.) change in tree cover within forested areas, and 2.) change in tree cover within agricultural areas. Forest and agriculture classes are aggregated for the LRMP as described above.
RESULTS
Visual analysis of the Landsat TM scene from 1992, based upon an overlay of the forest classes on the enhanced false color imagery (Fig. 2), reveals a landscape pattern typical of the relatively heavily populated Middle Hills of the eastern Himalaya. Forest fragments are clustered along the steep riparian corridors of tributaries, and along the banks of the Arun, interspersed by agricultural landuses, including terraced and non-terrraced cropping areas, grazing land, and agricultural scrub. Tree cover appears relatively contiguous along the major tributaries, and forms a patchy corridor finely articulated along the riparian network. Several conspicuous breaks in cover (agricultural zones) are evident on the less steep slopes along the west side of the Arun corridor.
The supervised classification of the 1992 TM imagery was able to distinguish two main lower elevation forest formation types: tropical semi-deciduous monsoonal forest (defined to include Sal and Chir Pine community types) and subtropical evergreen hill forest (see Chapter 1). Separation between classes examined within crossplots of various band combinations. Separation was found to be especially good between agriculture and forest classes. All thirty sampled forest quadrats were classified correctly in the supervised classification.
Forest represents 26 percent of all area below 2000 m, with agriculture making up 32%. Forest is estimated to occur on approx. 7132 ha classified into two broad forest classes (Table 1). Tropical forest comprised 29% of the total areas classified as forest within the TM scene (% TM_Forest), with the subtropical forest class comprising 71%. Tropical forest (2080 ha) occupied more than 40% of all area below 500 m , with the majority (1178 ha) found between 500 and 1000 m. The tropical forest formation showed a distinct northern latitudinal limit at approximately 27° 34’, consistent with reports by Shrestha et al (1990). Subtropical evergreen forest (5052 ha.) was found primarily above 1000 m, with a substantial presence in the upper tropical zone between 500 and 1000 m (575 ha; 16% of zone). There is very little agricultural landuse in the lower tropical zone, extending from 345 m to 500 m (3 ha, 3 %of zone), with more than 90 % of total area classified as agriculture (8656 ha) occurring above 1000 m. Agriculture occupied more than 40% of the lower subtropical zone (1000 -1500 m), and almost 30 % of the upper subtropical zone (1500 - 2000 m). Less than 600 ha of agricultural landuse types occurred below 1000 m.
Landscape metrics were evaluated for the study area based upon the 1992 Landsat TM, and were not compared to the 1972 data due to the sensitivity of these measurements to scale and resolution of the imagery. Metrics are given for the landscape as a whole (Table 2) and broken down by landuse class (Table 3). At the landscape level, the largest patch represented approximately 6% of the total landscape, with an average patch density of 79 patches per ha. Edge density was 114 m per ha for the landscape as a whole, with agriculture having the highest edge density (101 m / ha) and tropical monsoonal forest the least (52 m / ha). Likewise, agriculture had the greatest mean patch size (1.7 ha), followed by evergreen hill forest (1.2 ha) and tropical monsoonal forest (0.7 ha). Mean nearest neighbor distance was closest for agriculture (39 m), and furthest for tropical monsoonal forest (51 m).
The supervised classification of the 1972 Landsat MSS data (Bayesian maximum likelihood cover class estimation at the 95% confidence level) was not able to distinguished between the tropical and subtropical forest classes, and consequently all forest (i.e. tree cover or high biomass) classes were aggregated into one forest class (Fig. 3). Visual inspection shows a rough congruency with the classified TM image, given the lower resolution of the MSS data. The MSS data had significantly more unclassified area. Forest classes represent approx. 28 percent of all area below 2000 m, with agriculture occupying approx. 20 percent.
Total forest cover in the classified 1992 data was approximately 12 % less than in the classified 1972 data. Change detection analysis of forest cover (Fig. 4) reveals substantial forest loss at higher elevations and the upper margins of the study area, while gains in tree cover appear at relatively lower elevations. Within areas designated as a forest types in the LRMP Landuse map (Fig 5), 628 ha of forest have been converted to agriculture, comprising more than 8% of forest extent in 1972 (Table 4). Within this same area, almost 300 ha. are shown as having gained substantial tree cover, representing an increase of more than 4 %. The resulting net loss of forest within the LRMP designated forest zone was 4 %. Within areas designated as agricultural in the LRMP Landuse map, 1282 ha have lost substantial tree cover, comprising a loss of almost 17 % of all forest in 1972 (Table 5). Within this same area, 680 ha are shown as having gained tree cover, representing an increase of almost 10 %. The resulting net loss of forest within the LRMP designated agricultural areas was 7 %. Net loss of low elevation forest for the study area was 11 %
DISCUSSION
Extent and spatial distribution of current forest cover below 2000m in the MBCA indicates that closed canopy tree cover is now mostly restricted to riparian corridors and the slopes of associated gullies and ravines. However, within the highly articulated and complex topography of the study area, this network of remnant patches continues to represent an essentially contiguous corridor with a significant diversity of associated habitats and plant communities. Upland subtropical evergreen (non-riparian) forest community types appear to have been the most impacted by recent conversion to intensive agricultural uses. Although intensity of cultivation within the MBCA has increased, most riparian zones along the tributaries of the Arun still remain heavily vegetated. The dendritic pattern associated with the distribution of remnant low elevation forests indicates that, for the most part, the important ecosystem and watershed conservation functions associated with riparian zone vegetation are generally being maintained within the existing mountain farming system. Increases in population inevitably will put increasing pressures on remaining patches.
The highly articulated landscape, and dissection of the narrow riparian corridors by their streams, is a major factor influencing the evaluation of landscape metrics. Since forest classes were not limited to riparian types, but included all significant tree cover, landscape metrics report on impacts upon forest, and not the spatial distribution of riparian forests within the landscape per se. Small patch size, with a similarly small mean distance to nearest neighbor, can be indicative of highly disturbed landscapes (McGargical and Marks 1994; Hargis et al 1998). In this case, the highly articulated mountain riparian topography is likely a major influence on patch size, as is natural disturbance within the riparian zone. This is confirmed by the relatively small mean distance to nearest neighbor values. In simulated landscapes, tightly aggregated patches were found to produce the same values as landscapes with high disturbance (Hargis et al 1998). However, because the linear nature of the deeply cut corridors limits dispersion and migration of both plant and animal species, even relatively limited fragmentation with corridors can be significant, although impact is species specific. Within the study area, low elevation riparian forests form a fairly contiguous network, and intermingle at their upper margins with the densely covered and extensive areas of oak, hemlock, and fir forests of the upland National Park area. This spatial continuity enhances both their value to seasonally migrating species, and their resilience to periodic disturbance. Significant portions of these remnant forests, however, are highly disturbed, or consist of secondary successional regrowth following disturbance. Besides direct grazing, and fodder and fuelwood collection, disturbance by fire and/or swidden agricultural activities were observed as significant factors within the remaining forested areas.
The abundance of habitat edge is important to many ecological phenomena (Harris, 1984). High edge densities associated with highly articulated landscapes have been found to enhance both species and community diversity (Quinn and Harrison, 1988). An increase in habitat edge is a primary outcome of habitat fragmentation (Hargis et al. 1998). By this measure, agricultural areas had the greatest level of fragmentation. This is likely a reflection of the small farm size, and the spatial adaptation of a myriad of small farmers to the complex matrix of the mountain agricultural landscape, a pattern which is easily observable on the ground. Likewise, tropical forests are more tightly aggregated along the riparian zones, forming a fairly extensive contiguous network, and are less interspersed within the agricultural matrix, partly a result of physiographically delineated landuse boundaries along the upper edges of the narrow ravines and gorges.
Change Detection Analysis
The comparison of the classified 1992 Landsat TM supervised classification with the classification derived from the 1972 Landsat MSS data shows that overall forests have been significantly impacted by conversion to agriculture during the period leading up to the establishment of the MBCP in 1992. The comparative analysis, however, is confounded by the coarser spatial resolution of the Landsat MSS data, and it’s more limited spectral bandwidth compared to the Landsat TM data. This was especially true for the lower resolution MSS data, where tree cover was easily confused with other high biomass sites, e.g. bamboo or agricultural scrub. The intricate complexity of the farming landscape, a highly differentiated cropping calendar, and small farm and field size, further confound classification of landuse and cover within the Middle Hills (Millette et al, 1995). The Landsat MSS classification in particular was not able to achieve a fine discrimination of forest cover type classes, i.e. compared to the TM imagery. To accommodate this incongruity, and to facilitate the comparative analysis, all forest classes in the MSS classification were aggregated into a single inclusive forest class.
Areas which were previously designated as forest types in the LRMP LandUse Map are reported separately in the final estimates of forest to agriculture conversion. This estimate shows relatively little change in the overall extent or the pattern of spatial distribution for LRMP designated forested areas. Very little change was detected in the tropical zone below 1000 m. The tropical zone exhibited a slight net increase of forest cover, attributed to abandonment of marginal low elevation terraces. Interviews revealed that several regenerating sites were on terraces fairly recently abandoned due to out-migration to the Terai. Several sites within this zone showed evidence of being formerly terraced.
Estimates considering both agricultural and forest areas of the MBCA suggest that increases in tree cover are a direct response to diminishing forests within the more highly impacted subtropical zone. The majority of forest loss appears at the upper margin of this suptropical zone, perhaps indicating a movement further up onto more marginal upland slopes. Overall results of this study reflect the dynamic nature of vegetation within both the landscape and the mountain farming system (Ives and Messerli, 1989, Virgo and Subba, 1994, Schreir et al, 1994 ). A high degree of both temporal and spatial heterogeneity of landuse and vegetation dynamics is revealed in both the quantitative and spatial analysis. Results differ somewhat compared to studies of land-use change in the lower Arun (Virgo and Subba, 1994) and in the hills of the western and central regions of Nepal (Gilmour and Nurse 1991; Fox 1993). These studies detected no statistically significant changes (over a similar time interval), but considerable internal trading between landuse categories was evident. Schrier et al (1994) reported similar results, however, also detecting significant internal trading of landuse categories. The relatively recent expansion of agricultural activities is one likely explanation for the relatively high rate of forest loss within the study area.
Conclusions:
Analysis of landuse and cover change processes within the MBCA suggest that remaining riparian stands are under pressure, and are subject to disturbance and degradation. It is likely that this is even more so for the higher population density areas of the lower Arun Basin. Evidence that overall extent of low elevation forests with the MBCA has decreased in the period from 1972 to 1992 indicates substantial conversion to agricultural landuses. The relatively intact cover along riparian corridors is evidence that the importance of these ecosystem functions are generally recognized locally. Complete loss of forest stands occurred primarily within the subtropical non-riparian forests of the MBCA. Loss of spatially limited but ecologically significant stands within the monotypic agricultural landscape further increases the significance of remaining riparian zones.
The ecological and economic significance of remnant riparian forest within the landscape and the mountain farming system create a unique conservation challenge for managers, policy-makers, and researchers interested in regional or landscape level approaches to biodiversity management. Within the context of the MBCA, the importance of these forests and the biodiversity resources they represent are now explicitly recognized (Jackson et al 1990; Sherpa et al. 1990; Shrestha et al 1990; MBCP Task Force 1990) Nevertheless, as these forests are not within the protected area of the MBNP, their management is indirect. A "biodiversity management pocket" approach which delineates, prioritizes and recognizes especially important pockets of biodiversity has been suggested a possible conservation approach (Jackson et al 1990; MBCP Task Force 1990). Recent initiatives to increase tree cover on farmers fields are likely to produce the most immediate results, by taking resource gathering pressure off of easily accessible riparian zones. However, increasing population and livestock numbers threaten riparian forest with degradation and local extinction throughout the Middle Hills of east Nepal. On this regional level, conservation and biodiversity management confronts several challenges. Spatially discrete patches within roughly contiguous corridors, interspersed within a primarily agricultural landscape, do not easily lend themselves to protection within the national park or protected area conservation model. Community forestry (Gilmore and Fisher 1991) on a local level has proven an effective model for other similarly restricted forests in the Middle Hills, but has not specifically addressed the role of biodiversity conservation or wildlife habitat. Further research on biodiversity and wildlife habitat relationships within these patches, and a specific recognition of the value of remnant riparian forests within the landscape and rural economy, are required if conservation goals for the eastern Nepal Himalaya are to be met.
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