Biodiversity assessment at landscape level - CiteSeerX

ROY & BEHERA

Tropical Ecology 43(1): 151-171, 2002 © International Society for Tropical Ecology

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ISSN 0564-3295

Biodiversity assessment at landscape level P.S. ROY & M.D. BEHERA

Indian Institute of Remote Sensing (NRSA), Dehradun 248001, India Abstract: Biodiversity is dynamic in nature; species and their populations are in a constant state of evolutionary change. The changes, as well as human-induced modifications of biodiversity, must be thought against the background of its 3.5 billion years history. The discrepancy between field knowledge and predictions; the applicability of the model to continual situations, where ecosystem fragmentation and consequent area loss is the important consideration and various methods for predicting biodiversity distribution have been discussed here. The utility of landscape ecological principles for biodiversity characterization has been described. Use of satellite remote sensing, geographic information system (GIS) and global positioning system (GPS) techniques for assessing the disturbed and biologically-rich sites by many researchers have been highlighted. Satellite-derived vegetation map and various landscape ecological parameters (viz., patch shape, patch size, number of patches, porosity, fragmentation, interspersion and juxtaposition) were analyzed by various authors to characterize various habitat ecosystems. The present approach of prioritizing the biodiversity rich sites has the advantage of integrating spatial and non-spatial information with horizontal relationships and thus provides clue for conservation prioritization. Under the behest of Department of Biotechnology and Department of Space, Government of India, landscape ecological approach is being used to characterize the biologically-rich areas in six regions of the country i.e., north-east India, western Himalaya, western Ghats, Andaman and Nicobar islands, eastern and central India. A case study for the state of Arunachal Pradesh has been discussed in detail. The potential applications of the database prepared as a result of the inventory have been described. This method of biodiversity characterization has the following advantages over the traditional method of inventory e.g. (i) has an ecological basis since many ecological components are considered (ii) all the components have precise positional (locational) representation on earth surface. In the days of pilferage of bioresources and in the backdrop of intellectual property right issues, a quick and effective geospatial technique for characterizing biodiversity at landscape level will go a long way in conservation and judicious management of bioresources. Resumen: La biodiversidad tiene una naturaleza dinámica; las especies y sus poblaciones están en un estado constante de cambio evolutivo. Se debe pensar en los cambios y las modificaciones de la biodiversidad inducidas por los seres humanos a la luz de sus 3,500 millones de años de historia. Se discuten la discrepancia entre el conocimiento de campo y las predicciones, la aplicabilidad del modelo a situaciones continuas, donde la fragmentación de los ecosistemas y la consecuente pérdida de área es la consideración importante, así como varios métodos para la predicción de la biodiversidad. Se describe la utilidad de los principios de la ecología del paisaje en la caracterización de la biodiversidad. Se enfatiza el uso de técnicas de percepción remota satelital, sistemas de información geográfica (SIG) y sistemas de posicionamiento global (GPS) en la evaluación hecha por numerosos investigadores de los sitios perturbados y los biológicamente ricos. Varios autores analizaron un mapa de vegetación obtenido de información satelital, así como varios parámetros ecológicos del paisaje (p.ej., forma del fragmento, tamaño Address of Correspondence: P.S. Roy, Indian Institute of Remote Sensing (NRSA), 4, Kalidas Road, P.O. Box – 135, Dehradun UA 248001, India. Tel: +91-135-744583, 744518; Fax: +91-135-741987; Email: [email protected]

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BIODIVERSITY ASSESSMENT

del fragmento, número de fragmentos, porosidad, fragmentación, entremezclado y yuxtaposición) con el fin de caracterizar varios ecosistemas de hábitat. El presente enfoque para asignar prioridades a los sitios ricos en biodiversidad tiene la ventaja de integrar información espacial y no espacial con relaciones horizontales, y por lo tanto ofrece claves para la asignación de estas prioridades en la conservación. Por disposición de los Departamentos de Biotecnología y de Espacio, Gobierno de la India, el enfoque de la ecología de paisaje está siendo utilizado para caracterizar áreas biológicamente ricas en seis regiones del país, i.e., el noreste de la India, el Himalaya occidental, los Ghats occidentales, las islas Andaman y Nicobar, y la India oriental y central. Se discute en detalle un estudio de caso para el estado de Arunachal Pradesh. Se describen las aplicaciones potenciales de la base de datos obtenida como resultado del inventario. Este método para caracterizar la biodiversidad tiene las siguientes ventajas sobre los métodos de inventario tradicionales: (i) tiene una base ecológica ya que se consideran muchos componentes ecológicos, y (ii) todos los componentes tienen una representación de posición (localidad) en la superficie de la tierra. En los días de saqueo de recursos bióticos y teniendo como telón de fondo la cuestión del derecho de propiedad intelectual, una técnica geoespacial rápida y efectiva para caracterizar la biodiversidad a nivel de paisaje llegará muy lejos en la conservación y el manejo sensato de los recursos bióticos. Resumo: Na natureza a biodiversidade é dinâmica; as espécies e as suas populações estão em constante mudança evolutiva. As mudanças na biodiversidade, e incluindo as induzidas pelo homem, devem ser consideradas em relação ao pano de fundo dos seus 3,5 milhões de anos de história. A discrepância entre o conhecimento de campo e as predições; a aplicabilidade do modelo de situações de continuidade, onde a fragmentação do ecossistema e perdas consequentes de área são considerações importantes, e os vários métodos para predição da biodiversidade são discutidos. A utilidade dos princípios da ecologia da paisagem para a caracterização da biodiversidade é descrita. O uso, por muitos investigadores, da detecção remota por satélite, do sistema de informação geográfica (SIG) e das técnicas do sistema de posicionamento global (GPS) para avaliação dos distúrbios em estação biologicamente ricas têm sido evidenciadas. Mapas de vegetação baseados na informação de satélite bem como de vários parâmetros ecológicos da paisagem (configuração e tamanho das manchas, número das manchas, porosidade e fragmentação, intercepção e justaposição) foram analisados por vários autores para caracterizar os vários habitats dos ecossistemas. A abordagem da priorização presente da biodiversidade de estações ricas tem a vantagem de integrar informação espacial e não espacial, com relações horizontais, e providenciar, dessa maneira, chaves para priorização da conservação. Sob comando do Departamento de Biotecnologia e Departamento do Espaço do Governo da Índia, foi usada uma abordagem com base na ecologia da paisagem para caracterizar as áreas biologicamente ricas em seis regiões do país, i.e., noroeste da Índia, Himalaias ocidentais e Ghates ocidentais e das ilhas de Andaman e Nicobar, Índia oriental e central. Um estudo de caso para o Estado de Arunachal Pradesh é discutido em detalhe. As aplicações detalhadas da base de dados preparada em resultado do inventário é descrita. Este método de caracterização da biodiversidade apresenta as seguintes vantagens sobre o método tradicional: (i) tem uma base ecológica, dado que muitas componentes ecológicas são consideradas; (ii) todas as componentes estão georeferenciadas. Nos dias em que os biorecursos são rapinados e a propriedade intelectual é sonegação, uma rápida e efectiva técnica geoespacial para caracterização da biodiversidade ao nível da paisagem tem uma larga aplicação na conservação e gestão judiciosa dos biorecursos.

Key words:

Biological richness, conservation prioritization, disturbance regimes, fragmentation, Geographic Information System, remote sensing.

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Introduction Biodiversity refers to the quality, range or extent of differences between the biological entities in a given set. Thus it would be the diversity of all life and is a characteristic or property of nature, not an entity or a resource. This covers the total range of variation in and variability among systems and organisms, at the regional, landscape, ecosystem and habitat levels, at the various organism levels, down to species, populations and individuals. It also covers the complex shades of structural and functional relationships within and between these different levels of organisations (Fig. 1), including human action, and their origin and evolution in space and time domain. Darwin’s (1859) theory of evolution by descent made sense of the natural patterns observed in the variation between organisms. Through natural selection, these heritable changes may spread throughout the population and over time can lead to the production of new linkages closely similar to their relatives. Such lineage diversification produces strictly hierarchical pattern. Roughly 4.5 billion years of biotic evolution has led to an enormous diversity of living forms on earth. Biodiversity often decreases with distance from source populations, and is most constrained by dispersal in areas that are surrounded by dis-

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similar habitats (Colinvaux 1993). It is becoming evident that patterns of diversity in natural settings showing strong ecological correlation may reflect history rather than the product of ecological equilibrium of species diversity determined by the outcome of species interactions. The decrease in diversity by decrease in distance may in part reflect the relative edge, geographical extent and different historical patterns of barrier formation and consequent biotic disruptions. Distributional studies of biodiversity patterns show that each region has had a unique phylogenetic, geographic and ecological history that has set contemporary biodiversity.

Biodiversity Assessment: Indian Initiatives Botanical Survey of India (BSI) and Zoological Survey of India (ZSI) have been involved in survey and exploration of flora and fauna present in the country (1983). The Red Data Book enlists the IUCN categories of plants and animals occurring in various parts of the nation (Nayar & Shastri 1987). Government of India has been involved in launching various projects from time to time for inventorying and preserving the biological database viz., Project on Study, Survey and Conservation of Endangered Plants (POSSCEP), National Biodiversity Strategy and Action Plan (NBSAP).

Biosphere Biome Landscape Ecosystem Community Population Species Fig. 1. A structurally distinct geographical space, which is kilometers wide is called a landscape. Biosphere is the limited zone of life on earth.

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However, a lot of database has been developed out of these studies. But the important components lacked in these studies are (a) lack of proper documentation and database retrieval system (b) lack of spatial (locational) information on IUCN plant categories (c) absence of time-period study to assess the change etc. In a most recent attempt to map bio-geographical regions, Rodgers & Panwar (1988) attempted to define the bio-geographical regions of India and mapped ten bio-geographical zones. The Wildlife Institute of India has converted these regions on to Survey of India (SOI) digital database. An established method of biodiversity conservation is the protected area concept, which lacks many integral components. It was observed that the process of selecting protected areas and determining a protection category was arbitrary, unsystematic and inconsistent. Protected areas were also not placed in any rational system of regional land use planning. As a result, even densely settled areas were designated as national parks and many important biodiversity areas were not included in the network (Kothari et al. 1989). Most obvious causes of biodiversity loss in India have been habitat loss, over-exploitation, and introduction of invasive species and lack of national land use policy.

Characterizing biodiversity Biodiversity characterization involves two different processes, the observational and characterization of the main units of variation (genes, species and ecosystems) and the quantification of variation within and between them. In reality, they are part of the same process; the analysis of pattern defines the unit and characterization of their variation. Characterization of biodiversity depends critically on the work of three scientific disciplines i.e., taxonomy, ecology and genetics. Organisms occur in an intricate spatial mosaic classified on a world scale into biogeographic zones, biomes, ecoregions and oceanic realms, and at a variety of smaller scales within landscape into ecosystems and communities. The biodiversity at landscape level can be characterized by measures of species richness, species diversity, taxic diversity and functional diversity (Roy & Behera 2000). Hence, assessment of characterization units and techniques leave rather a dissected view of biodiversity at different levels of description. The remote predictors or surrogates often play very sig-

nificant role to measure richness. The habitat surrogates including classification of vegetation, details on the physical environment, factors determining the biodiversity loss in a spatial context may be of practical information value and could reduce sampling intensity. This information base could also guide detailed sampling on the ground. These larger scale surrogates include entire functional system and are more likely to promote population viability in the ecosystem. In conservation, this is likely to differ with earlier measures of ecological diversity formulated with the narrower aim of representing differences in abundance among species, exploring distribution of resources within community. If the value of biodiversity to a conservationist is associated with its use to people then this ought to be separated carefully from issues of rarity, viability and threat. If the biodiversity value is associated with richness in a currency of characters of organism then the higher level of biological organization (or environmental factors affecting its distribution) will have to be used in surrogate measures. Choosing a surrogate level from this scale is a compromise between the precision of the measure on the one hand, and the availability of the data and the cost of data compilation on the other. Higher-level surrogates should have the additional advantage of implicitly integrating more of the functional processes that favour viability. The taxonomic inventories in the past have only been able to reach partial level of understanding the richness. Hence this should be a top down and bottom up approach together (Fig. 2).

Landscape ecology A landscape addresses a number of technical issues e.g., managing large datasets, scaling processes among different spatial and temporal scales and the whole concept of ‘ecosystem management’ include many of the tenants of landscape ecology. Ecological systems do not exist as discrete units but represent different parts of a natural continum in the form of landscape. It can also be considered as higher level of biological complexity and immensely useful for understanding various complex processes. Landscape ecology allows studying these processes on different scales and time. The relatively new discipline of landscape ecology provides insight into both landscape diversity and species diversity and suggests a theoretical and practical basis for conservation planning. The

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Approach (Existing) 1

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Approach (Proposed) 2

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Time Consuming High extinction rate ? Overtaking inventory process Stratified approach Extrapolation on large landscapes Systematic Monitoring Spatial Environmental Database

Landscape 1 ach pro p A

Ecosystem Community

Population 2 ach o r p Ap

Species Genes

Hierarchy of Biological Organisation Fig. 2. Hierarchy of biological organization.

management should thus focus on the ecosystems that contain these species and on the landscapes in which ecosystems are found. There are three basic characteristics of landscapes that affect their diversity: structure, function and dynamics (Forman & Godron 1986). The patch is the basic unit of the landscape structure; the characteristics of patches and the spatial relationships among patches are important components of the landscape (Lidicker 1995). The distribution of energy, material and species among patches differing in size, shape, abundance and configuration are particularly important to patterns in diversity at the landscape scale. Landscape dynamics include characteristics of structure and function both in order to examine changes in pattern and processes over time. The conservation of biodiversity requires understanding of all three elements, including the effects of human activities on the system. Landscape composition can be measured in ways analogous to measurements of species composition (Romme 1982). The most

straight forward approach is landscape richness i.e. the number of different patch types in a landscape. Another approach includes the relative abundance or dominance of different patch types along with richness. Measurements of landscape diversity are analogous to common measurements of species diversity (Whittaker 1977, 1995). Different patch types provide different habitats and species composition, thus one might expect that the total number of species in a landscape would increase as landscape richness increases (Burnett et al. 1998). Landscape level approach also addresses the changes that might be expected in biodiversity as a result of anthropogenic activity and also the complementary issue of how changes in biodiversity will affect the functioning of biological systems (Franklin 2001). Patch description A patch is relatively homogenous nonlinear area that differs from its surroundings. The definition and identification of individual patches and

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their boundaries are important steps in characterizing the structure of a landscape. Most methods of patch identification combine qualitative and quantitative approaches. Turner et al. (1993) provided quantitative techniques to group similar cells into homogenous patches or to identify repeating patterns across landscape. These methods include moving window analysis and satellite image to characterize landscapes with sharp transitions. Once the patches in a landscape have been identified, there are many ways to describe and quantify them (Peter et al. 2001; Ritters et al. 1995). The patch size and shape are the most understood landscape characteristics with species diversity. The relationship between patch size and species richness goes well beyond the familiar species-area curve (Fig. 3). Fragmentation

No. of Species

Fragmentation of landscape results in geographical isolation and the probability of recolonisation strongly depends on the distance of fragments from the main core and on the quality of the surrounding habitat. Fragmentation study takes into account connectivity (corridors), presence of ecotones, the meta population structure etc. It in-

creases the vulnerability of these patches to external disturbance with threat on the survival of these patches and on the supporting biodiversity (Nilson & Grelsson 1995). Fragmentation is one of the most severe processes to depress biodiversity (Farina 1998). Large fragments have more species, are less distributed and have lower road access than smaller fragments. Severity of tropical forests fragmentation has been studied with respect to distance effects, fragment size, edge effects and biotic changes (Bierregaard et al. 1992; Ravan & Roy 1997). The corridors are physical and functional connectivity to allow the movement of plant species and fauna. They are severely affected due to fragmentation (Villard & Taylor 1994; Villard et al. 1995). It is also observed that habitat requirement for sensitive species are specific to area size and surrounding characters (Bancroft et al. 1995). Fragments having edges of dense shrubby vegetation that prevent alien species from entering, although at the same time these warm edges are attractive to alien species (Brothers & Spingarn 1992). Despite these negative effects, fragments are better than nothing (Turner & Corlett 1996). Fragmentation of the terrestrial habitats is wide-

Patch Area Fig. 3. Species Area Curve showing the increase in species number with increasing patch size tending towards a regional limit (Peter et al. 2001).

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spread in most parts of the world, and its negative effects have been well-documented (Saunders & Ingram 1987). Matrix is the most connected element and structural attribute. Hence in landscape perspective, matrix and patches are the elements that are used while considering fragmentation in a landscape (Baudry 1984; Wien 1994). Using the neighborhood concept, it is possible to measure the relative size and isolation of the patches. Environmental patchiness can reflect a mosaic of soil types, topographic conditions, microclimate and successful stages after recovery from disturbance (Lambeck & Saunders 1993). The functional relationships of patchiness with species diversity are due to (a) dependence of species diversity on physical substrate; (b) interspecies dependence; (c) species interactions within communities; (d) incidental species relations; and (e) dynamics of a landscape.

The landscape way – world goes? The structured, spatially explicit approach for describing, analysing and evaluating the distribution of vegetation, species composition of heath and mire in Northern Ireland was based on multivariate land classification and field sampling (Millsopp et al. 1997). Forman & Godron (1986) observed three landscape characteristics i.e., structure, function and change. Several studies have suggested that the landscape have critical threshold at which ecological processes will show dramatic qualitative changes (Gardner et al. 1989; O’ Neill et al. 1989; Turner 1989). Godron (1991) has documented that remote sensing gives a perspective horizontal view and helps in delineating different landscape elements and their spatial characteristics. McGarigal & Marks (1995) have documented that the patch density and mean patch size serve as fragmentation indices for comparison between two time periods. The role of patch connectiveness on the dispersal and spatio-temporal distribution of a small tree dwelling bird and also revealing the presence of birds being significantly related to the length of suitable patches has been dealt by Farina (1998). Patch size can influence floral and faunal composition and richness. Small patches of forest tend to have a greater proportion of edge to interior than large patches and thus are more likely to harbour exotic or weedy species (Levenson 1981). Fuller et al. (1998) combined field surveys of plants and animals with satellite re-

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mote sensing of broad vegetation types to map biodiversity and thereby helped plan conservation in Sango Bay area in Uganda. Debinski et al. (1999) had used remotely sensed data and GIS to categorize habitats, and then determined the relationship between remotely sensed habitat categorizations and species distribution patterns. Many workers had studied on the patterns of species richness in biogeographical, ecological or habitat space biology (Pinaka 1966; Richerson & Lum 1980; Rohde 1992). Relationships between richness patterns and various ecological, geographical or other factors have been dealt in by many workers (Currie 1993). The accuracy and validity of modeling geographical patterns of species richness are critical factors in distinguishing and understanding the so called hotspots of biodiversity (Roy et al. 1993). Few studies have been done in India to establish relationship between the disturbance and the biological richness of the landscape elements. (Pandey & Shukla 1999; Roy et al. 1997; Roy & Tomar 2000). Menon & Bawa (1997) have also found the role of remote sensing, geographic information system and landscape analysis for biodiversity conservation in western Ghats using geospatial modeling approach. The study, however, only considered habitat fragmentation and did not include many other important landscape parameters. A horizontal relationship between the various spatial units at different spatial scale to study the homogeneity, heterogeneity and causative mechanisms have been established by Ravan & Roy (1995) during their landscape dynamics study of Madhav National Park in India. Ramesh et al. (1997) have attempted a vegetation-based approach for biodiversity gap analysis. This approach takes into account the extent of deforestation, distribution of forest/vegetation types, patchiness, and species diversity for each forest/vegetation type and uniqueness of the habitats. The study, however, did not take into account human induced disturbance sources. Nagendra & Gadgil (1999) attempted to investigate relationship of various landscape elements on the basis of field observation. They found that the landscape elements significantly support distinctive sets of species of flowering plants. However, the study did not analyze landscape based ecological parameters in a spatial context. They also could not integrate field data with satellite derived vegetation maps. Roy & Tomar (2000) used geospatial techniques to char-

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acterize biodiversity at landscape level in Meghalaya. The pioneering attempt took into account environmental complexity, habitat and its attributes and disturbance regimes to model the spatial variation in biological richness. The importance of the study lied in the fact that it can help in prioritizing sites in conservation and also facilitate monitoring the perturbations of the richness of the landscape as a function of space and time. Behera (2000a) mapped the biologically-rich areas in Subansiri district of Arunachal Pradesh and observed that much of the biologically-rich areas were lying in the sub-tropical zone. Behera et al. (unpublished) attempted to validate the findings and observed that fragmentation has got significant impact on species diversity.

Community analysis Inventorying and analyzing vegetation cover is the most practical way of tracking biodiversity. Information on species is crucial before they are lost forever. Article 7 of the United Nations Convention on Environment and Development requires signatory parties to ‘identify components of biodiversity importance conservation and sustainable use and monitor, through sampling and other techniques, the components of biological units identified. Chapter 15.6 calls for the development of ‘methodologies with a view to undertake systematic sampling and evaluation on a national basis of the components of biological diversity identified by means of country studies’ and to initiate or further develop methodologies and begin or continue work on surveys at the appropriate level on the status of ecosystems and establish baseline information on biological resources. Studies of specimens collected during inventories yield data useful for resolving the phylogenetic relationships of species, which in turn, are essential for building predictive classification systems and permit the estimation of character diversity for comparison of biota (Williams et al. 1995). These relationships can be used to help prioritise areas for conservation or other land management decisions. Species inventories provide the foundation for future industrial applications, particularly those associated with bioprospecting (Behera et al. 2000b; Reid et al. 1993).

Is biodiversity related to disturbance? Disturbance is a common and widespread phenomenon in nature and may be defined as a discrete event along the passage of time that modifies landscape, ecosystem, community and population structure (Pickett & White 1985). Fragmentation has a strong influence on the dynamics and fate of the material and energy moving across a landscape. Disturbance regimes and their impact on communities and landscape can be well understood by analyzing spatial and temporal architecture of disturbance (Moloney & Levin 1996). Severe disturbance or even a prolonged absence of disturbance generally has depressing effect on biodiversity, but intermediate disturbance seems to enhance diversity in a system (Pickett & White 1985). The capacity of the landscape to incorporate human disturbance is overwhelmed and the disturbance process is transformed into a stress process, which reduces biodiversity. The disturbance regimes can be measured by using different indices i.e., degree of fragmentation, fractal dimension, contagion, juxtaposition, evenness and patchiness (Li & Reynolds 1994).

Biodiversity conservation planning at the landscape level – why? To preserve species diversity most effectively, management plans must preserve the habitats and landscape structure needed by the target species, rather than simply preserving the species in isolation from the larger, potentially changing environment. Management practices aimed directly at a particular species run the risk of losing ecosystem functions that might actually be crucial for the target species, but that were unknown when the management plan was created. Furthermore, maximizing benefits for one species may threaten others. The ideal is to preserve overall ecosystem health, including species diversity. Given the large number of species on the planet, it is impossible, or at best impractical, to manage for every one of them. Instead, conservation biologists are now trying to identify ways to simplify the task of landscape level management. The primary requirements to evolve such an approach would be: • Determination of disturbance regimes; • Knowledge on spatial distribution of biological richness;

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Determination of the optimum size of conservation areas; and Identification of set of focal species, sensitive to particular landscape structure and function.

Geospatial tool – how does it help? Landscape ecology has evolved as an operational tool with the availability of geospatial modeling techniques. Space may be considered as ‘the final frontier for ecological theory’ (Karieva 1994) spacing or spatial arrangement is a scaled property of living organisms, from individuals to populations, communities and meta-communities. It is the ecological replay of an organism to nonuniform distribution of resources (habitat suitability) and to inter and intra-specific competition in space and time. This is the central dogma of landscape ecology. Spacing depends mainly on resource availability. Plants react to resource availability by arranging themselves in a finite and predictable pattern. Satellite remote sensing Acquisition of images of earth from space has opened new frontiers in mapping. The multispectral satellite images provide definitions of vegetation patches, which are related to phenological types, gregarious formations and communities occurring in unique environmental setup (Behera 1999). The temporal images help in monitoring all back processes a landscape has experienced (Delcourt & Delcourt 1988). Such an approach allows monitoring the forest condition and degradation processes (Roy & Behera 2000). The images also provide digital mosaic of the spatial arrangement of land cover and vegetation types amenable to computer processing (Coulson et al. 1990 ; Chuvieco 1999). The other approach to analyze the landscape pattern properties is based on nominal scale classified maps. These maps can also be analyzed using various indices quantitatively, which measure the heterogeneity of landscape within a specific radius. Diversity and dominance are well known examples of those indices (Baker & Cai 1992). They are ordinarily computed from samples of relatively homogenous cover types, named patches. Size, shapes, perimeter, connectivity, orientation, presence of corridors, visibility or diversity of patches are critical variables for describing the landscape mosaic. Not much work has been done towards analysis of these variables

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from satellite images. Analysis of landscape fragmentation (Turner et al. 1993) has been common goals in the use of satellite data for landscape pattern analysis. It has recently been shown that these clumps (also known as ‘geographic windows’) are more suitable to describe spatial patterns than the standard moving windows of fixed sizes (Dillworth et al. 1994). In Indian context, Menon & Bawa (1997) have used remote sensing and GIS technologies for biodiversity conservation following landscape ecology and spatial analysis approach. In 1996, Kasturirangan et al. 1996 have forecasted that applications to biodiversity conservation is one of the areas in which remote sensing will play a role in the future. Geographic information system (GIS) GIS provides the way to overlay different ‘layers’ of data: the ecological conditions, the actual vegetation physiognomy and human pressure indices (e.g., as deduced from the density of population or road network). It helps to assess disturbance levels; the spatial distribution of several species in order to determine biodiversity hotspots; past and present maps for monitoring land cover and land use changes. It provides possibilities to extrapolate observations e.g., to automatically define and map the potential area of a given species and to compare it with the locations where, it has been actually observed; or to combine different data sets for defining the potential list of species for a given forest type. GIS provides a database structure for efficiently storing and managing ecosystem-related data over large regions. It enables aggregation and dis-aggregation of data between regional, landscape and plot scales. It also assists in location of study plots and/or ecologically sensitive areas. GIS supports spatial statistical analysis of ecological distributions. It improves remote sensing information extraction capabilities, and provides input data/parameters for ecosystem modelling. The data generated through ground truthing and integration of related attributes when used in GIS application result into significant features of biodiversity and genetic resources. Global positioning system A GPS is a satellite-based positioning system operated by the U.S. Department of Defense (DoD). GPS allows the collection of information about the geographical position of any location using a network of satellites. It has a great potential

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in landscape ecology, as well as in many other related disciplines requiring geographic locations of the objects in the landscape (Farina 1998). Coupled with GIS, it acts as a powerful tool to describe the geographical characteristics of ecological systems. A practical use of GPS has been in locating the sample plots and this information was used for mapping and spatio-statistical analysis (Behera et al. 2000c).

Biodiversity conservation priority – setting the right criteria? The complexity priority setting varies considerably due to complexity of biodiversity and the number of ways of valuing it. Among the biological criteria are richness (the number of species or ecosystems in given area), rarity, threat (degree of harm or danger), distinctiveness (how much a species differs from its nearest relative), representiveness (how closely an area represents a defined ecosystem) and function (the degree to which a species or ecosystem affects the ability of other species or ecosystems to persist). Some priority setting approaches use social, policy and institutional criteria as well. Utility, the most common nonbiological criteria, points to biodiversity elements of known or potential use to humankind. Feasibility, often paramount in deciding how to allocate conservation resources, may be political, economic, logistical or institutional terms. Considering the biological criteria, areas can be identified where the actions are most likely to succeed. However, with increased recognition the social, policy and institutional factors are crucial for conserving biodiversity. Ecological approaches for setting priorities for biodiversity conservation generally seek to protect most of the species within conservation areas that are representative of a region’s natural habitat. Ecosystem approaches for identifying conservation priorities use multiple criteria such as species richness, endemism, abundance, uniqueness and representativeness, as well as considerations of the physical environment, ecological processes and disturbance regimes that help to define the ecosystem.

Baseline data on biodiversity at landscape level The goals and scales of inventorying and monitoring programs may change with time. Hence, the

baseline data at landscape level should be sufficiently robust to accommodate changes. It should be based on robust samples enabling calibration for future rapid biodiversity assessment. Landscapes contain all levels of the biological hierarchy, from ecosystem to species and genes that are targeted for biodiversity inventories and conservation. The present effort to characterize vegetation cover, fragmentation, disturbance and biological richness across the landscape is organized in the form of Biodiversity Information System (BIS) (Fig. 4). The field samples of key ecological characters have been used for geospatial extrapolation. The species database has been linked with above spatial details. The BIS allows to identify gap areas, species / habitat relationship and helps in biodiversity conservation planning by setting priority areas. Such database coupled with detailed sitespecific field inventories helps in identifying areas for bioprospecting. The assessment of biological rich areas brings out distinctiveness of the landscapes as driven by pattern of richness, endemism, biological corridors, community composition and diversity. The analysis made also presents full range of distinct natural communities and ecological status at landscape level. The landscape capable of maintaining the viable population species, sustain important ecological processes and services that maintain biodiversity are also mapped. This information is of valued importance in rugged, inhospitable region throughout northeastern region. Such areas remain by and large under explored. The results presented here could form the basic guideline to plan flora and faunal future inventories. The focus should be to cover varied landscapes differing based on vegetation types, disturbance regimes and BR. Such an approach allows to build habitat factors like biophysical environment, landscape indices and disturbance regimes which allow monitoring changes taking place over a time in biodiversity regimes. Understanding of species habitat relationships, inventorying patterns, multivariate modeling of long-term datasets allows to formulate and test the hypothesis. The dataset could also allow monitoring and forecasting changes through extinction models using multi-temporal data. Such modeling can help in impact of global change in different landscapes. Finally the approach can be extended to study species diversity and genetic variability in biologically rich sites for prioritizing focus on bioprospecting.

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Availability Distributed Spatial Data Satellite Remote Sensing & Geo-spatial Modeling PRIMARY OUTPUTS

Biological Richness Disturbance Index Fragmentation Vegetation Type

Species Database

ANCILLARY INFORMATION FSI (Forest Cover Map)

NON SPATIAL INFORMATION

Wildlife Institute Of India (Biogeographical zones of India)

Red Data Book (BSI) French Institute Database Field Database

Digital Elevation Model Drainage Digital Chart World Settlement+ Roads (DCW)

Published Flora Endemic Species

Identification of Biological Gap Area Species + Habitat Relationaships Biodiversity Conservation Planning Bioprospecting Zonation Fig. 4. Biological Information System (BIS).

Biodiversity characterization at landscape level in Arunachal Pradesh – fulfills the information need? The rich species diversity which characterizes the flora of north-eastern region of India is largely attributable to the diverse geographical area, varied topography, climate and soil variability, immigration and colonization of plant species from widely different territories and is a transitional zone between India, Indo-Malayan and IndoChinese biogeographical zones as well as the confluence of the Himalayan region with peninsular India (Rao 1994). Forest of Arunachal Pradesh in northeastern region of India with such rich biodiversity is disappearing at an alarming rate mainly due to anthropogenic activities. Irreversible changes and deterioration of ecosystems are caused not only by the extensive destruction of natural habitats but also by direct extermination of many important species of fauna and flora meeting various human needs and greeds. Jhum or shifting cultivation, which is widely practiced in hills of Arunachal, is also a causing factor in the depletion of biodiversity. Application of recent ad-

vances of space technology and their integration with biodiveristy studies to different levels and data generation for setting criteria and priorities are provided below.

Methods Mapping at macro level The satellite data of IRS-1C/1D have been used to extract the vegetation types, considering forest phenology and optimal season. Regional level mapping was carried out for the preparation of ecological zone map using IRS-WiFS data (Wide Field Sensor) with a capability of covering large area in single instantaneous field of view (IFOV). It has a potential for monitoring the phenological fluxes of largely forested landscape at regional level. Integration of maximum NDVI was evaluated for monitoring the seasonal changes in vegetation. This was found as an excellent source of data for understanding the land dynamic processes and human interventions in the region, which was taken as one of the inputs in mapping disturbance regimes.

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Mapping at meso level IRS – 1C/1D LISS-III digital data were used for classification. The entire state of Arunachal Pradesh is covered in 21 scenes. The scenes were geometrically corrected (Root Mean Square Error < 0.002 – 0.007) and then mosaiced. With the help of Survey of India (SOI) digital boundary the state area was extracted. Pre-processing (radiometric and atmospheric correction) of data was done prior to classification. Digital classification was carried out through hybrid classification (supervised and unsupervised techniques) approach using ERDAS Imagine software. Finally classified map of the study area was prepared on 1:250 000 scale. Intensive ground truth data was collected prior to classification by repetitive field visits. Various vegetation classes mapped are as follows: tropical evergreen, tropical semi-evergreen, moist mixed deciduous, sub-tropical evergreen, temperate broadleaved, conifers, sub-alpine and alpine scrub, bamAdvantage: Precision as a measure of character diversity

boo mixed, abandoned jhum, degraded, Dipterocarpus, Hollock, Pine, fir, Rhododendron, Riverain and grass land. Various non-forest classes mapped are dry river bed/sand, agriculture, fallow/barren land, river/water body, settlement/habitation, shadow, snow and cloud. This classified information has been used to delineate the spatial extent of forest (Fig. 5).

Field data generation Stratified random sampling and nested quadrat approach was followed for carrying out community analysis after a reconnaissance survey in various districts of the state (Anon. 1998). Size of the quadrat was determined through species-areacurve. Phytosociological data viz. relative frequency, relative density and relative dominance have been calculated to compute the importance value index (IVI) for each stratum. The IVI has been utilized to calculate species richness using

Advantage:Inexpensive A scale of surrogacy survey & units more inclusive for a value currency of character diversity of viability enhancing process

Low

High

‘Ecosystem richness’ ?

Environmental surrogates

Climate class richness Terrain class richness

Environmental / Assemblage surrogates

Substrate class richness Landscape class richness Habitat class richness

Assemblage surrogates

‘Community class richness’ Vegetation class richness Higher taxon richness

Taxonomic surrogates

Species/subspecies richness Taxonomic/phylogenetic subtree length

Molecular surrogates

Expressed gene richness

High

Low Source: Paul Williams, 2000

Fig. 5. Vegetation Type/ Land use Map of Arunachal Pradesh.

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the Shannon-Wiener index. The field data was collected to derive biodiversity value on the basis of importance index, forest density and economic value. These parameters have ultimately been used to ordinate the vegetation types (Behera 2000a; Roy & Tomar 2000).

Landscape characterization Satellite images were used to generate the vegetation type map. Digitally classified product with different landscape parameters (porosity, fragmentation, interspersion, juxtaposition, patch characteristics) were generated and analysed. Using these different characters along with proximity inputs (roads and settlements) were used to derive disturbance index (DI) map. To fulfill the requirement of landscape analysis, Bio_CAP that is a Geospatial Semi-Expert package was developed using GIS package (Arc/Info), Image Processing (ERDAS) and C/C++(Anon. 1999). Disturbance = Index

∫

fragmentation, patchiness, interspersion, porosity, biotic disturbance buffer, juxtaposition

Biodiversity characterization The biological richness at landscape is determined as a function of ecosystem uniqueness, species diversity, biodiversity value, terrain complexity and disturbance. The main parameters like EU, H, BD etc., come from ground based observations in various vegetation types specially ecosystem uniqueness is derived with the help of species database query shell which is based on IUCN categorization scheme. Terrain complexity is derived from the terrain through DEM. The biological richness values have been used for scaling the region or area for potential biodiversity prospect zones (Fig. 6). Biological richness = index

∫

ecosystem uniqueness, species diversity, biodiversity value, terrain complexity and disturbance index

Result and discussion Vegetation mapping The entire state of Arunachal Pradesh was covered in 21 LISS-III scenes of IRS-1C/1D satel-

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lites. Due to the radiometric variation between individual scenes, they were classified separately and then mosaiced using the previously stored ground control points (GCPs) to obtain the final classified map for the entire state. The vegetation cover type map was prepared by using digital classification following hybrid approach.

Community analysis Highest Shannon-Weiner diversity was observed in subtropical evergreen forest followed by temperate broadleaved and tropical evergreen forest. Total number of families, genera and species of plants were found to be highest in tropical semievergreen forest.

Disturbance index The landscape parameters were finally integrated to derive disturbance index map of the state (Fig. 7). Assigning different intra-class weights to various indices has simulated disturbance index after performing normalization. Disturbance index image obtained gives a clear picture of both anthropogenic and natural disturbances and their spatial extent in various levels. The map shall be useful for managers and decision makers for various planning and enforcing conservation measures.

Biological richness mapping The mapping of biological richness carried out in Subansiri district of Arunachal Pradesh (Behera 2000) revealed that sub-tropical evergreen forest zone is highly rich biologically followed by tropical semi-evergreen forest environment (Fig. 8). The biological richness map shows a clear pattern, which cannot be judged without a critical understanding of the whole spectrum of phenomenon responsible for it. The results of the present study characterize biodiversity at landscape level for bioprospecting and conservation. This work aims at developing reversal process of deforestation and degradation in northeastern region by setting conservation priorities. The information system evolved through multicriteria analysis in GIS facilitates the following: • Rapid assessment for monitoring biodiversity loss and/or gain • Assess nature of habitat and disturbance regimes;

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Evolve species – habitat relationship; Mapping biological richness and gap analysis; and • Prioritizing conservation and bioprospecting sites. Following are the areas where the database would have direct use.

Highlights of the work The status of information and ongoing practical aspects of the integrated studies using recent techniques of remote sensing, GIS and GPS provided following features: • Biodiversity is generally greatest in the oldest ecosystems. It changes across environmental gradients like, latitude, altitude, depth, aridity etc. The habitat definitions in the form of vegetation cover types

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will allow ‘what to look where’. The disturbance regimes assessed across the landscape will allow focusing on the ecosystems, which are under ‘stress’. Hence if the field survey indicates that the region is important habitat for a species for bioprospecting, the ‘stress’ factor needs to be removed/reduced. Biological Richness Index (BR) asserts the areas, which should be treated as priority in decision-making and management level for conservation of biodiversity. The Gap Analysis carried out on maps will guide mangement and decision making for bioprospecting. All plant species have a basic requirement of its ecological optima in particular habitat or niche within range of tolerance and requirement. Habitat identification and

Fig. 9. Genetic diversity vs. Species diversity.

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economic importance of the species can be useful input for bioprospecting and biodiversity conservation. Biological rich areas are those habitats where landscape ecological conditions are favorable for natural speciation and evolutionary process. These areas can be expected to be in equilibrium where species can occur, grow and evolve in natural conditions. Each species requires a specific ecological niche (minimum/optimum area for its survival, evolution, gene exchange). Analysis of landscape parameters like habitat fragmentation, patchiness, interspersion and juxtaposition have shown impact on the definition of the limits in different habitats. Greater the variety of types of habitat, the greater is diversity of the species. Diversity also increases with expanding architectural complexity of the physical habitat. Management of contaguous (large), intact and juxtaposed patches of high diversity in any landscape should draw first attention for conservation. The ground inventories on species/ genetic diversity should further decide on priorities. The patches having higher biological diversity at landscape level will be subject for more intensive ground inventories for assessing species/genetic diversity. The patches with genetic and species diversity should draw first attention followed by patches of high species and/or genetic diversity. Most of the species growing in the natural conditions have some sociological association with the species – environment complex and in general have fairly well defined niches. Similar ecological conditions in different geographical location bear similar biodiversity if not the same. But they will have differences at genetic level. The vegetation cover types, their composition, association, latitude, altitude, fragmentation levels, inferences on possible corridors and species database compliment the information needs. Based on the existing literature about the occurrence of the valuable threatened species (BSI Red Data Book and field data of the present and subsequent studies), its

habitat can be examined in terms of its landscape requirements of the species. Once the comprehensive species database is established, potential species distribution and occurrence maps can be generated. Integrated gene marking techniques can help in preparing the location - species – environment complexes. Such information base can be of immense value for bioprospecting. • It is expected that the maps will be strategically used for planning detailed ground level inventories of flora and fauna by premier institutions like Botanical Survey of India, Zoological Survey of India, State forest departments and Wildlife Institute of India. The region wise maps can also be used for redefining ecological zones required for biodiversity conservation. Hence, it may be concluded that not ‘either-or’ but a hybrid approach (both ground sampling and satellite tool) play a major role in assessing biodiversity at landscape level.

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