Materials and Method

Study Area

The Western Ghats, a rare repository of endemic flora and fauna is one of the 35 hotspots of global biodiversity and a home to diverse social, religious and linguistic group. Uttara Kannada district located in the central Western Ghats (Fig. 1) lies between 13.769°–15.732°N and 74.124°–75.169°E covering approximately an area of 10, 291 km². The region has the distinction of having highest forest area (80.48%) in Karnataka State, India, and has been undergoing severe anthropogenic pressures impacting biogeochemistry, hydrology, food security, climate and socio-economic systems. The district has varied geographical features with thick forest, perennial rivers and abundant flora, fauna. It has the unique distinction of having 3 agro-climatic zones and for the regional administrative purpose, the district is further divided into 11 taluks (also known as tehsil or mandal is an agglomeration of villages). The coastal region, which has hot humid climate and rainfall, varies between 3000 and 4500 mm. The Sahyadri interior region of the Western Ghats (500–1000 m high)is very humid to the south (rainfall varies from 4000 to 5500 mm). The plains are regions of transition, which are drier (rainfall varies between 1500 and 2000 mm).

Method

Local hotspots of biodiversity or ESRs in the district are prioritized considering biological (terrestrial and aquatic flora and fauna, estuarine biodiversity), ecological (diversity, endemism, conservation reserve), geo-climatic (altitude, slope, rainfall), renewable energy prospects (bio, solar, wind), social (population, forest-dwelling communities) as outlined in Fig. 2. The study area has been divided into 5¹ 5¹ equal area grids (168) covering approximately 9 9 km² (Fig. 3) for prioritizing ESR.

Table 1 lists the weightages assigned to each variable of various themes consider- ing the minimal impact on the landscape and also to prioritize conservation regions for future planning. The weightages were assigned iteratively across the landscape with varied themes for a development solution and monitoring.

Developing a weightage metric score analysis requires knowledge of multidis- ciplines [16], and planning integrates the present and future needs in the landscape [17], and weightage is given by

Conservation and Sustainable Management … 369

Weightage = Σⁿ_i=1W_iV_i

where n is the number of data sets (variables), V_i is the value associated with criterion i, and W_i is the weight associated with that criterion. Table 1 expresses the theme- wise decision variable considered with their level of significance, ranked between 1 and 10. Value 10 corresponds to highest priority for conservation, whereas 7, 5 and 3 correspond to high, moderate and low levels of prioritization. Assigning weightages based on individual proxy based extensively on GIS techniques has proved to be the most effective for prioritizing ESR. Visualization of levels of ESR helps the decision- makers in opting eco-friendly development measures. A detailed database has been created for various themes covering all aspects from land to estuarine ecosystem. The theme-wise description given below highlights the consideration of variables for study and their significance in conservation priority.

Table 1 Various themes considered and their weightages

FC–forest cover; IF–interior forest cover; END–endemic; NEND–non-endemic; BM–biomass; SD–supply to demand ratio; WA–water availability

Land

Land uses based on the analysis of remote sensing data were considered, and grids were prioritized based on the proportion forest cover [18]. Forest fragmentation statistics is computed as per the standard protocol [18, 19]. The interior forest cover refers to the undisturbed core forest patches that aid in preserving the structure of the ecosystem while enhancing its functional aspects.

Ecology

Field investigations were carried out in 116 sample transects (Fig. 4) for data on the plant species diversity, basal area, biomass, estimates of carbon sequestration, per- centage of evergreenness and Western Ghats endemism and about the distribution of threatened species, etc. Along a transect length ranging up to 180 m, quadrats

each of 20 20 m were laid alternatively on the right and left, for tree study (min- imum girth of 30 cm at girth at breast height (GBH) or 130 cm height from the ground), keeping intervals of 20 m length between successive quadrats. A number of quadrats per transect depended on species–area curve, and most transects had a maximum of five quadrats. Within each tree quadrat, at two diagonal corners, two sub-quadrats of 5 m 5 m were laid for shrubs and tree saplings (<30 cm girth). Within each of these two herb layer quadrats, 1 m² area each was also laid down for herbs and tree seedlings. Supplementary data were compiled through the review of published literature, unpublished datasets and ground-based surveys other than transects. Approaches adopted in documenting flora and fauna are outlined by earlier studies [20].

The health of ecosystem and its significance is derived based on the key vari- ables—endemism, floral diversity, evergreenness, etc., for evolving the composite conservation index. Tree species diversity is another measure calculated using Shannon’s diversity index (H¹). H¹ is given by Eq. (H)^' = -Σⁿ_i=1(P_i)lnP_i

where i is the proportion of the species relative to the total number of species (p_i) multiplied by the natural logarithm of this proportion (ln p_i) and the final product

multiplied by 1. The Shannon index ranges typically from 1.5 to 3.5 and rarely reaches 4.5. Higher diversity range was assigned higher weightage for conservation.

Faunal diversity is another surrogate variable used to assess the eco-sensitivity of a region. The region is storehouse of endemic fauna, in which occurrence of endemic species increases in the undulating terrains of upper Ghats. Species richness and endemism are two key attributes of biodiversity that reflect the complexity and uniqueness of natural ecosystems [4, 23]. The setting of regional conservation prior- ities based on combinations of modelling individual endemic species’ distributions, evaluating regional concentrations of species richness and using complementarity of areas by maximizing inclusion of species in the overall system is most appro- priate [24]. A set of criteria for prioritizing the regions has been prepared based on field investigation, interaction with stakeholders (researchers working in this region, forest officials, local people, subject experts).

Mammals are well represented in this chain of mountains, and many endemic birds are found in all other places of the district. Conservation Reserves (CR) are being established under the framework of Protected Areas (PA) under the Wildlife (Protection) Amendment Act of 2002. CRs are typically buffer zones or connectors and migration corridors between National Parks, Wildlife Sanctuaries and reserved protected forests in the district. These reserves protect habitats that are under pri- vate ownership also, through active stakeholder participation. The biological diver- sity in these zones like National parks, Sanctuaries (Anshi Dandeli Tiger reserve (ADTR)), botanical gardens (Shalmala Riparian Ecosystem Conservation Reserve, Aghanashini LTM Conservation Reserve, Hornbill Conservation Reserve, Attiveri Bird Sanctuary), zoological gardens hosts threatened (rare, vulnerable, endangered) flora/fauna. Higher weightage is assigned for CRs.

Biomass

Biomass is another important indicator of forest health and reveals its role in a global carbon sink. Most of the Uttara Kannada district is located in the high rainfall zone, except Mundgod and eastern parts of Haliyal and Yellapura support trees with higher biomass. Details of biomass quantification, flora and fauna diversity are available in the literature [16, http://wgbis.ces.iisc.ernet.in/biodiversity/database_new/]. The analysis has calculated total standing biomass of forest’s vegetation [25, 26] based on field data and remote sensing data. Transect-wise basal area per hectare was estimated using allometric equations.

Geo-Climatic Variables

Geo-climate plays a major role in determining the speed of recovery (lag-time) of a landscape (and the ecosystem that governs it), and the studies reveal that variables such as altitude (elevation, slope, rainfall), easterly aspect, steepness and longer dry seasons have a significant role in local ecology [27]. The patterns of altitude,

slope and rainfall bring about the sensitivity, heterogeneity, complexity of climate, soil, vegetation, land use, land cover in connection with socio-economic interac- tions [28, 29]. The elevation map is generated using Cartosat DEM of 1 arc-second resolution. Areas with steep slopes and high altitudes are likely to be eroded more easily, and hence vulnerable to natural erosion or landslides, need to be considered as least resilient and hence environmentally sensitive zones areas. The analysis has considered that the slopes and altitudes can be normalized within each grid from 0 (least average slope or lowest average altitude) to 10 (high slope and high alti- tude) and assigned to the grids. The slope map is generated from DEM dataset using Geographical Resources Analysis Support System (GRASS)—http://wgbis.ces.iisc. ernet.in/grass/index.html)—free and open-source tool.

Hydrology provides a fundamental basis for understanding material flows, envi- ronmental quality and stream ecosystem in a basin [30]. Conservation of high bio- diversity forest landscapes is justified on the basis of hydrological benefits—in par- ticular, reduction of flooding hazards for downstream floodplain populations [31]. Point-based daily rainfall data from various rain gauge stations in and around the study area between 1901 and 2010 were considered for analysis of rainfall [20, 32]. The rainfall data used for the study were obtained from Department of Statistics, Government of Karnataka; Indian metrological data (IMD), Government of India. Rainfall trend analysis was done for selected rain gauge stations to assess the vari- ability of rainfall at different locations in the study area. Monthly monitoring of hydrological parameters reveals that streams in the catchments with undisturbed pri- mary forest (evergreen to semi-evergreen and moist deciduous forests with spatial extent >60% in the respective catchment) cover have reduced run-off as compared to catchments with disturbed/altered forest covers. Run-off and thus erosion from monoculture plantation forests were higher from that of natural forests. Forested catchment has higher rates of infiltration as soil is more permeable due to enhanced microbial activities with higher amounts of organic matter in the forest floor. Streams with undisturbed forest cover (vegetation of native species) in the catchment showed a good amount of dry season flow. Native forests in the catchment aid as sponge retaining the water, while allowing infiltration during monsoon, which are steadily released during the lean season. Compared to this, streams in the catchment dom- inated by agricultural and monoculture plantations (of Eucalyptus sp. and Acacia auriculiformis) are seasonal with water availability ranging between 4 and 6 months. The grids where water is available during all months in a year (perennial flow) are assigned higher values.

Energy

Dependence on the conventional energy resources for electricity generation is eroding the natural resources at faster rate by causing a significant adverse effect on ecology by producing enormous quantities of by products including nuclear waste and carbon dioxide. Improving energy efficiency, switch over to renewable sources of energy and de-linking economic development from energy consumption (particularly of fossil fuels) is essential for sustainable development of a region. Potential of renewable energy sources is assessed (Solar, Wind, Bioenergy) month-wise and captured the variations [33–35]. The solar energy datasets are derived based on NASA’s Surface Meteorology and Solar Energy (SSE) methodology. The solar energy is available greater than 10 months with higher potential. The availability of wind energy and its characteristics of Uttara Kannada District have been analysed based on primary data collected from India Meteorological Department (IMD) observatories. Wind energy conversion systems would be most effective during the period May to August. Energy pattern factor (EPF) and power densities are computed which show that the coastal taluks such as Karwar, Ankola and Kumta have good wind potential [34]. The house- holds’ survey carried out to understand the spatio-temporal patterns in the domestic fuelwood consumption reveals that 82–90% of the households still depend on fuel- wood and agro-residues. Analyses of sector-wise contribution in the energy surplus zones show that horticulture residues contribute in the central dry zone, southern transition zone and the coastal zone, while in the hilly zone, forests contribute more towards the available bioenergy [35]. The adaptation of green technologies would aid in cutting down carbon footprint. Weightages are assigned based on the level and quantum of availability of energy from renewable resources.

Social Aspects

Forest Rights Act 2006, Government of India, seeks to recognize and vest the for- est rights and occupation in forest land in forest-dwelling Scheduled Tribes and other traditional forest dwellers who have been residing in forests for generations but whose rights could not be recorded. Forest-dwelling communities (tribes) of the district are mapped at village level, and the grids with tribal population are assigned higher weightage. In the regional planning, demographic aspect is essential to many applications across the science and policy domains including assessment of human vulnerability to environmental changes. Land degradation is due to population pres- sure which leads to intense land-use conversions without proper management prac- tices. Increase in population density will lead to the increasing exploitation of natural resources and the resulting loss of species and ecosystem richness, nature conserva- tion [36]. Village-wise population density is computed considering 2011 population census data (http://censusindia.gov.in). Population density per sq. km is considered as one of the influencing social factors for prioritization, and the grids with lower population density are assigned higher weightage. The need for combining nature conservation with social aspect is to emphasize receiving a livelihood from natural resources and participation in enriching biodiversity.

Estuarine Diversity

Estuarine ecosystems are biologically productive, socio-economically vital and aes- thetically attractive, while providing food and shelter for many vital biotic species, and some are commercially very important [37]. West coast estuaries of the district were assessed based on productivity, biodiversity and human pressure [38–40]. The analysis has identified the mangroves at species level using remote sensing data with field-based measurements. Estuarine productivity based on goods and services of the district [38] brings out the disparity in productivity and diversity between the neighbouring estuaries due to major human intervention in the form of construction of hydroelectric projects in upstream. Estuaries were given weightages based on the productivity and diversity.

SDSS Framework

SDSS integrates the scientific data in addressing the problems and provides appropri- ate solutions for sustainable utilization of the resources. OGC provide standardized interface specifications to support geospatial data sharing and interoperability among Web-based GIS systems (Fig. 4). SDSS Server GIS framework (i) is used remotely as data management done by the researchers and administrators, (ii) provides access to functionality via Web protocols such as the OGC Web Processing Service and

(iii) allows the users to access the data and enter input parameters. Web-mapping API such as Openstreet Maps which is one of the popular Web-mapping application programming interfaces (APIs) and Bhuvan (http://bhuvan.nrsc.gov.in), WMS layers are used in our framework, and other examples are Google Maps (http://maps.google. co.in), Yahoo! Maps (http://maps.yahoo.com) or Bing Maps (http://bing.com/maps). The online user will be able to access the graphical user interface (http://10.58.20. 79/ol3/ukwms.html) and choose the different map layers [41]. When the request is received, the Web server communicates with the GeoServer to retrieve the map layers as a service which will be fetched from the database and a response is sent to the user through the GUI. The user will be able to visualize the information on the maps.