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Spatial alteration of fragmented landscape in evergreen and semi- evergreen rainforest: A case study in Chittagong Hill Tracts, Bangladesh

Mamnun M, Hossen S. 2021. Spatial alteration of fragmented landscape in evergreen and semi-evergreen rainforest: A case study in Chittagong Hill Tracts, Bangladesh. Asian J For 5: 17-27. The principal aim of the study was to explore the level of fragmentation and underlying drivers in forests of Bandarban Sadar Upazila, Chittagong Division, Bangladesh from 1988-2018. The ArcGIS v10.5 and ERDAS Imagine v15 software were used to process satellite imageries and assess quantitative data. The study revealed that the area under forest land decreased very rapidly; it was lost about 7165.13 ha and the annual destruction rate was 17.92%. The edge density of forest area and agricultural crops rapidly increased from 1988-2018, while barren land and waterbodies were almost consistent. Forest land became fragmented as its total edge area increased by 275.87% from 16469.6 km in 1988 to 61905 km in 2018. There was gradual decline in Shannon Diversity Index from 1988 (1.004), 2003 (0.878), and 2018 (0.615). Among the different factors, agro-horticultural plantation was the main factor for reduction in landscape diversity. This analytic study would help policymakers take necessary steps for sustainable forest management.


INTRODUCTION
Tropical rainforests cover only 7% of the earth's land surface, however, they have highest amount of species diversity and almost 50% of the world's wildlife (Tchoumbou et al. 2020). Tropical forests are one of the most momentous carbon sinks and store about 25% of terrestrial carbon (Zapfack et al. 2020). Species extension, climate change is the most acute problem in tropical forests (Harper et al. 2007, Echeverria et al. 2008. Huge areas of these evergreen rainforests are dilapidated due to deforestation, fragmentation, over-exploitation, and climate change which also vary from region to region (Bhusal et al. 1998, Morris 2010). An estimation says that every individual day 130 plants, animal and insect species are lost due to deforestation. In the last 40 years, 20% of the Amazon rainforests have been lost. Fragmented landscape narrates habitat loss and alteration of spatial characteristics and configuration switch which brings about a lot of physical and biological changes in a forest environment (Hansen et al. 2001, Jha et al. 2005. This results in an extreme level of edge effects into remaining fragmented forests area and there observed strong differences in habitat near the edge and away from edges (Donovan et al. 1997, Broadbent et al. 2008. The effects of habitat fragmentation on species richness are often predicted by the landscape matrix (Öckinger et al. 2012). Within the last century, increasing the level of fragmentation associated with the rapid change of land-use practices, has made the landscape a crucial and auxiliary scale of studies of wildlife ecology and forest management (Rodewald 2003). Landscape metrics are effectively applied during a sort of situation including the measurement of environmental change, landscape change, and forest fragmentation measurement (Hansen et al. 2001). Spatial or landscape metrics can measure the numerous aspects of the land cover/land-use pattern including composition, spatial configuration, and spatial neighborhood of the land cover/land-use or landscape during a given area (Kowe et al. 2015). Different types of matrix are utilized in forest fragmentation study, among them the most common metrics used to analyze forest fragmentation at the category or patch type-level include Number of Patches, Mean Patch Size, Patch Shape, Edge Density/Total Edge Distance, Mean Core Area, Patch Density, Fractal Dimension, Interpatch Distance and Interspersion and Juxtaposition (Hansen et al. 2001).
As one of the forest-poor countries in the world, Bangladesh has 10.96% forest resources and it is struggling to conserve it (Baten et al. 2010). Among them, 4.54% of the country's total forest are evergreen and semi-evergreen forest cover, Chittagong Hill Tracts included in this category. Like other mountainous regions of Asia, Chittagong Hill Tracts (CHT) of Bangladesh are also facing an acute level of degradation especially in recent four decades, natural resources have been exploited enormously to inappropriate land-use system such as shifting cultivation associated with incendiary fires, population pressure, the encroachment of reserve forests, soil erosion, agroforestry practices, and commercial teak plantation (Rasul et al. 2004;Rasul and Thapa 2006;Biswas et al. 2012). The aim of the study was to explore the level of fragmentation in forests of Bandarban Sadar Upazila, Chittagong Hill Tracts; based on fragmentation matrices besides elucidating drivers related to fragmentation. The result of the study will give a thought about the fragmentation and underlying drivers in hill tracts which can help the government, organizations associated with natural resources management, policymakers and another researcher to take necessary steps for sustainable management in the future.

Description of the study area
The study area was Bandarban Sadar Upazila District, Chittagong Division, Bangladesh located at 21°55' and 22°22' N and 92°08' and 92°20' E, having an area of about 501.99 sq km. The Upazila is bounded by Rajasthali Upazila on the North, Lama Upazila on the South, Rowangchhari and Ruma Upazilas on the East, and Rangunia, Satkania and Lohagara Upazilas on the West and is bordered by Cox's Bazar, Chittagong, Rangamati and Khagrachari. On the other side of the 129 km, international border lies Chin and Arakan provinces of Myanmar. It consists of 5 unions namely Rajbila Union, Kuhalong Union, Bandarban Sadar Union, Swalak, and Tankabati ( Figure 1).

Digital data collection and processing
It was used multi-temporal satellite imagery data that are provided by USGS (United States Geological Survey) for Landsat 8 OLI-TIRS (Operational Land Imager/ Thermal Infrared Sensor), Landsat 5 TM (Thematic  Mapper) for 2018, 2003, and 1988 for visual image interpretation, land-use identification and land-use classification. To urge cloud-free satellite imagery, winter season was selected (November-February) to get accurate data for classification. The spatial resolution of Landsat 2 was 60 m and 30 m for Landsat 5 and 8 (Table 1). Landsat 8 raw image constitutes 11 bands and only 5,4,3 bands for Landsat 8 and 4,3,2 bands for both Landsat 5 and Landsat 2 were used. Composite layer of these 3 bands was created in Arc GIS 10.5, the pictures were then projected and clipped by using subset tools using the shapefile of Bandarban Sadar Upazila. A complete of 47290.05 hectares (ha) of land was estimated for the entire Bandarban Sadar Upazila after supervised image classification by using ERDAS Imagine v15.

Land-use and land cover change detection process
During June 2018-December 2018, a field survey was directed within the study area to record specific land-use categories according to their latitude and longitude. A total of 500 GPS point locations were taken by using convenient sampling. The land-use of study area was classified into 5 groups including croplands, Barren lands, Settlements, Waterbodies and Forest areas. The collected land-use data were used to determine the color tone of 2018 Landsat 8 images while training dataset. Afterward, maximum likelihood classification (MLC) was used for LULC assessment. After land-use classification, forest areas from supervised classification were exported to raster through spatial analysis tools in Arc GIS 10.5 and converted from raster to polygon in Arc map 10.5.  Landscape configuration changes and fragmentation analysis FRAGSTATS and Patch analysts programs were used to explore the landscape patches and modeling of attributes related to patches. This spatial pattern analysis software finds use in determining habitat modeling for biodiversity conservation and forest management. Vector polygon data/ raster-based data derived from the years 2018, 2003, and 1988 were given as input metrics for measuring and quantifying landscape characteristics and their changes in growth dynamics (Table 2).

Probability mapping using satellite imagery and topographic variables to analyze landscape diversity
A probability map was made to classify different agrohorticultural practices within the study area. The probability map mainly represents the high suitability of environmental conditions for the subsequent practices. For tree species classification probability mapping primarily optical multispectral sensor like Landsat images are used and in the next steps second (the topographic variables) from a digital elevation model (DEM) is used and geographical information systems (GIS) data from study area is applied to make the probability map more accurate. For the first set of variables, a Landsat 8 image from USGS earth explorer was used ( Figure 2). Table 2. Quantifying changes in landscape configuration and composition for fragmentation analysis (class-level metrics)

Parameter Equation Meaning
Number To derive the topographic variables, the Global Digital Elevation Model (GDEM) version 2 data with a resolution of 30 m was obtained from the advanced spaceborne thermal emission and reflection radiometer (ASTER) that is operated by the National Aeronautics and Space Administration (NASA). By applying topographic variables, the logistic probability model was calculated, whose accuracy is more than the forest inventory maps (Chianga et al. 2016). For the study, temperature, slope, aspect, chlorophyll and entropy map of the study area was also used. Field level survey data for ground truth inventory map was overlapped upon entropy map and in this way, probability map for various agro-horticultural practices and artificial plantations of the study area was prepared. After observing the classification result and comparing it with the tree species inventory, the foremost dominant practices within the study area were found to be Teak plantation. In the study area, 7 main vegetation types viz. agroforestry, horticultural, artificial fast-growing forest tree species plantation, teak plantation, jhum cultivation, homestead forestry, bamboo were found at the study site.

Relative changes of land-use in Bandarban Sadar Upazila
Land-use mapping of Bandarban Sadar Upazila provided spatial distribution of land-use categories and land-use changes over the past 30 years (Figure 3). Table 3 and Table 4 show relative changes in Bandarban Sadar Upazila land-use from 1988-2018. Three trends were noticed from the results viz (i) area under Barren land and Settlements continuously increased from 2.53% and 1.57% respectively, during 1988 to 10.42% and 5.33% respectively, during 2018; (ii) Forest areas were continuously declined from 84.56% in 1988 to 69.41% in 2018; (iii) while % cover of agricultural crops peaked in 2003 (13.66%) from 1988 (8.06%) and again decreased to 11.74% in 2018 and % cover of waterbody decreased to 2.72% in 2003 from 3.28% in 1988, however, it again increased to 3.10% in 2018.    Figure 4).

Metrics calculation
Classified LULC images of 1988, 2003 and 2018 were used as inputs in patch analyst extension software of Arc GIS 10.5 to calculate and analyze conversant landscape metrics for each class.

Edge density
Edge density is an indicator of landscape configuration for fragmentation analysis (class-level metrics). The study revealed that the edge density of forest area and agricultural crops rapidly increased from 1988-2018, while barren land and waterbodies were almost consistent. At the same time period, edge density of the settlement decreased swiftly. This indicates that forest and agricultural crop land were converted into settlement and urbanization ( Figure 5).

Class area
Class area indicates the sum of areas of all patches belonging to a particular landscape class. From 1988 to 2003 class area of forest increased rapidly, but it decreased slightly in 2018. On the other hand, from 1988-2003 patch area of settlement was decreased drastically and remained unchanged till 2018. Similarly, the total patch areas of forest land were increased and settlement was decreased. Meanwhile, total patch areas of barren land, agricultural land, and waterbody did not change significantly ( Figure 6).

Land-use area (ha)-2018 Sum of area (ha)
Column labels

Landscape configuration and fragmentation analysis Spatial variation in land-use fragmentation
Land cover/land-use fragmentation varied with each land cover/land-use type as evident from the mean perimeter-area ratio (MPAR) of patches, mean patch size (MPS) and total edge (TE) represented in Table 6. A more fragmented land cover/land-use pattern is generally associated with a decrease of the MPAR and an increase in total edge and MPS. Forest land became fragmented as its total edge area increased by 275.87% from 16469.6 km in 1988 to 61905 km in 2018 and the MPS increased 31290.05 ha. On the other hand, the mean perimeter area ratio was declined from 1060.26 ha in 1988 to 188.48 ha in 2018.
The total edge of settlement declined 37.14% from 1988 to 2018 while MPS of settlement decreased by 37487.11 ha from 1988-2018, whereas the MPAR increased by 896.23% (Table 6). It can be concluded that the fragmentation area of the total forest patch was increased and fragmented patch of settlement was decreased and forest was converted to settlement and other land cover types. Smaller patches of settlement have become inter-connected and large portion of land cover has transformed to settlement (Figure 8).
Other classes of land cover also have changed with time. The total edge area of agricultural crops and MPS was increased by 260.88% and 364.45% respectively, and MPAR was decreased by 22.3%, indicating the impact of fragmentation on agricultural crop land between1988-2018. In the case of the waterbody, it was found that the MPAR was increased by 6.34% and total edge area increased from 5557.23 km in 1988 to 11646.7 km in 2018 (Table 6). Table 7 illustrates that the largest percentage of areaweighted mean shape index (AWMSI) of settlement was increased by 150.27% from 1988-2018. The argument behind these can be linked to rapid forest destruction associated with agricultural intensification, shifting cultivation, unplanned settlement pattern in the study area. Due to the unplanned settlement, more complex and irregular shapes of settlement areas were created.

Changes in patch shape complexity of land cover/land-use categories
Similarly, the AWMPFD value (% of change) for settlement from 1988-2018 was 12.50% that represents the increase in new irregular settlement patterns and the complex built-up patch shapes. Although, other practices like barren land, agricultural land, waterbody, and forest were less complex in irregularity from1988-2018 (Table 7).
AWMSI value for forest area was declined by 18.26% and AWMPFD value by 7.56% from 1988-2018. The forest patches became more irregular, exposed edges, extremely fragmented and the values indicate complex heterogeneous shapes due to human influence. Barren land patches, a number of which were located in open fields and agricultural activities, increased in AWMSI value by 7.35% and decreased in AWMPFD value by 0.59% leading to relatively simple circular shapes. The patches of Agricultural land's AWMSI increased (67.46%) between 1988 to 2018, and its AWMPFD values did not change for the same period. The AWMSI and AWMPFD values of waterbodies increased by 49.29% and 1.20% respectively between 1988 to 2018 (Table 7).    59 -0.13 -7.56 This finding expresses that, forest destruction destroys valuable natural resources of the study areas. As in the current case swift collapse of evergreen and semievergreen forest area was recorded between 1988-2018. Increase in settlement can be considered a main reason behind this. People's from different areas migrate in Chittagong Hill Tracts and for settlement. Chittagong Hill Tracts areas has also seen establishment of different organizations, school, colleges, industries etc. And the corresponding increase in population has led to rapid forest destruction. Forest and agricultural areas were thus converted into settlements and divided into many smaller patch areas which led to the increase of AWMSI and AWMPFD of settlement areas.

Landscape diversity and probability distribution model for different agro-horticultural practices and artificial plantation
The decrease in Shannon's Diversity Index (SHDI) and Shannon Evenness Index (SHEI) from 1988 to 2018 (Table  8) indicates decrease in landscape heterogeneity and evenness. This was contrary to the expectation that decrease in forest land would cause reduction in landscape diversity. It can be concluded that once the huge landscape diversity of Chittagong Hill Tracts, Bandarban gradually declined with the passage of time and deforestation and fragmentation (Table 8). The gradual decrease in SHEI from 1988-2018 also indicates that the classes of map units were not uniformly distributed in the study area reflecting the differences in sizes of certain land cover/land-use on the landscape with some practices dominating others at the landscape level.
In 2018, agro-horticultural plantation was the main cause for reducing landscape diversity. Natural forest was replaced by human-modified plantation of teak, horticultural practices, agroforestry practices etc. To classify different Agro-horticultural practices, probability distribution map was generated using satellite imagery and topographic variables with Arc GIS10.5.
The maximum amount of land was found to be deployed for teak (Tectona grandis) plantation (Figure 9). After teak plantation, agroforestry was practiced, and together were the top two causes of natural forest destruction. Homestead plantation and horticultural practices occupied additionally outsized portion of Bandarban Sadar Upazila. Though the percentage of jhum cultivation was not high, it spread vastly across all Upazila. Fast-growing tree species were planted by the government through different plantation programs. Naturally, different types of bamboos were found in all hilly areas and were also planted artificially in some places.
In conclusion, it can be enunciated that spatial/ landscape metrics are useful tools to narrate the landscape structure with various aspects especially in fragmentation analysis. Bandarban Sadar Upazila has been undergoing exaggerated deforestation and degradation since the beginning of 1988 due to habitat destruction, fragmentation, shifting cultivation, over-exploitation, encroachment, and agroforestry practices. An enormous amount of forest land and semi-natural vegetation were converted to other land cover types. The increase in population, as well as settlement and urbanization, made forested areas more complex in shape and fragmented. Increasing heterogeneity and fragmentation of habitat were identified through landscape metrics for 1988, 2003, and 2018. The growth pattern of fragmented patches, uniformity, and irregularity, and change in shape complexity was illustrated by using AWMSI and AWMPFD in this study.
Rapid conversion of forest area into agro-horticultural area in an unplanned and unauthorized way, aggravated by intensified shifting cultivation as supported by AWMSI and AWMPFD measurements, gives an urgent message to policy-makers about the extent of rapid fragmentation and natural forest loss in the area. It was also noticed that, spatial configuration changes (as indicated by change in the number of patches, MPS, and total edge) the diversity of landscape. From 1988-2018, forest area decreased swiftly and decreased SHDI and SHEI index. Further, it can be said that settlement expansion, agroforestry practices, and artificial plantation in hilly areas increased fragmentation extent and reduce natural biodiversity.  This study tries to draw attention to rapid fragmentation, biodiversity loss, and poor management of natural resources which has driven vast areas of previously forest land now turned to unplanned settlements, barren hills, or agro-horticultural practices. Appropriate intervention from concerned authorities is required to save remnant natural evergreen and semi-evergreen forest of Bandarban Sadar Upazila, Chittagong Hill Tracts, Bangladesh.