Landscape Analysis 2002

7/28/2019 Landscape Analysis 2002

1/21

ROY & BEHERA 151

Tropical Ecology43(1): 151-171, 2002 ISSN 0564-3295 International Society for Tropical Ecology

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 con-stant state of evolutionary change. The changes, as well as human-induced modifications ofbiodiversity, must be thought against the background of its 3.5 billion years history. The dis-crepancy between field knowledge and predictions; the applicability of the model to continualsituations, where ecosystem fragmentation and consequent area loss is the important consid-eration and various methods for predicting biodiversity distribution have been discussed here.

The utility of landscape ecological principles for biodiversity characterization has been de-scribed. Use of satellite remote sensing, geographic information system (GIS) and global posi-tioning system (GPS) techniques for assessing the disturbed and biologically-rich sites by manyresearchers have been highlighted. Satellite-derived vegetation map and various landscapeecological parameters (viz., patch shape, patch size, number of patches, porosity, fragmenta-tion, interspersion and juxtaposition) were analyzed by various authors to characterize varioushabitat ecosystems. The present approach of prioritizing the biodiversity rich sites has the ad-vantage of integrating spatial and non-spatial information with horizontal relationships andthus provides clue for conservation prioritization. Under the behest of Department of Biotech-nology and Department of Space, Government of India, landscape ecological approach is beingused to characterize the biologically-rich areas in six regions of the country i.e., north-east In-dia, western Himalaya, western Ghats, Andaman and Nicobar islands, eastern and central In-dia. 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. Thismethod of biodiversity characterization has the following advantages over the traditionalmethod of inventory e.g. (i) has an ecological basis since many ecological components are con-sidered (ii) all the components have precise positional (locational) representation on earth sur-face. In the days of pilferage of bioresources and in the backdrop of intellectual property rightissues, a quick and effective geospatial technique for characterizing biodiversity at landscapelevel will go a long way in conservation and judicious management of bioresources.

Resumen: La biodiversidad tiene una naturaleza dinmica; las especies y sus poblacionesestn en un estado constante de cambio evolutivo. Se debe pensar en los cambios y las modifi-caciones de la biodiversidad inducidas por los seres humanos a la luz de sus 3,500 millones deaos de historia. Se discuten la discrepancia entre el conocimiento de campo y las predicciones,la aplicabilidad del modelo a situaciones continuas, donde la fragmentacin de los ecosistemasy la consecuente prdida de rea es la consideracin importante, as como varios mtodos para

la prediccin de la biodiversidad. Se describe la utilidad de los principios de la ecologa delpaisaje en la caracterizacin de la biodiversidad. Se enfatiza el uso de tcnicas de percepcinremota satelital, sistemas de informacin geogrfica (SIG) y sistemas de posicionamiento global(GPS) en la evaluacin hecha por numerosos investigadores de los sitios perturbados y losbiolgicamente ricos. Varios autores analizaron un mapa de vegetacin obtenido de informacinsatelital, as como varios parmetros ecolgicos del paisaje (p.ej., forma del fragmento, tamao

ddress 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]


2/21

152 BIODIVERSITY ASSESSMENT

del fragmento, nmero de fragmentos, porosidad, fragmentacin, entremezclado y yuxtaposi-cin) con el fin de caracterizar varios ecosistemas de hbitat. El presente enfoque para asignarprioridades a los sitios ricos en biodiversidad tiene la ventaja de integrar informacin espacialy no espacial con relaciones horizontales, y por lo tanto ofrece claves para la asignacin de es-

tas prioridades en la conservacin. Por disposicin de los Departamentos de Biotecnologa y deEspacio, Gobierno de la India, el enfoque de la ecologa de paisaje est siendo utilizado paracaracterizar reas biolgicamente ricas en seis regiones del pas, i.e., el noreste de la India, elHimalaya occidental, los Ghats occidentales, las islas Andaman y Nicobar, y la India oriental ycentral. Se discute en detalle un estudio de caso para el estado de Arunachal Pradesh. Se de-scriben las aplicaciones potenciales de la base de datos obtenida como resultado del inventario.Este mtodo para caracterizar la biodiversidad tiene las siguientes ventajas sobre los mtodosde inventario tradicionales: (i) tiene una base ecolgica ya que se consideran muchos compo-nentes ecolgicos, y (ii) todos los componentes tienen una representacin de posicin (localidad)en la superficie de la tierra. En los das de saqueo de recursos biticos y teniendo como teln defondo la cuestin del derecho de propiedad intelectual, una tcnica geoespacial rpida y efectivapara caracterizar la biodiversidad a nivel de paisaje llegar muy lejos en la conservacin y elmanejo sensato de los recursos biticos.

Resumo: Na natureza a biodiversidade dinmica; as espcies e as suas populaes estoem constante mudana evolutiva. As mudanas na biodiversidade, e incluindo as induzidaspelo homem, devem ser consideradas em relao ao pano de fundo dos seus 3,5 milhes de anosde histria. A discrepncia entre o conhecimento de campo e as predies; a aplicabilidade domodelo de situaes de continuidade, onde a fragmentao do ecossistema e perdas conse-quentes de rea so consideraes importantes, e os vrios mtodos para predio da biodiver-sidade so discutidos. A utilidade dos princpios da ecologia da paisagem para a caracterizaoda biodiversidade descrita. O uso, por muitos investigadores, da deteco remota por satlite,do sistema de informao geogrfica (SIG) e das tcnicas do sistema de posicionamento global(GPS) para avaliao dos distrbios em estao biologicamente ricas tm sido evidenciadas.Mapas de vegetao baseados na informao de satlite bem como de vrios parmetrosecolgicos da paisagem (configurao e tamanho das manchas, nmero das manchas, porosi-dade e fragmentao, intercepo e justaposio) foram analisados por vrios autores para

caracterizar os vrios habitats dos ecossistemas. A abordagem da priorizao presente da bio-diversidade de estaes ricas tem a vantagem de integrar informao espacial e no espacial,com relaes horizontais, e providenciar, dessa maneira, chaves para priorizao da conserva-o. Sob comando do Departamento de Biotecnologia e Departamento do Espao do Governo dandia, foi usada uma abordagem com base na ecologia da paisagem para caracterizar as reasbiologicamente ricas em seis regies do pas, i.e., noroeste da ndia, Himalaias ocidentais eGhates ocidentais e das ilhas de Andaman e Nicobar, ndia oriental e central. Um estudo decaso para o Estado de Arunachal Pradesh discutido em detalhe. As aplicaes detalhadas dabase de dados preparada em resultado do inventrio descrita. Este mtodo de caracterizaoda biodiversidade apresenta as seguintes vantagens sobre o mtodo tradicional: (i) tem umabase ecolgica, dado que muitas componentes ecolgicas so consideradas; (ii) todas as compo-nentes esto georeferenciadas. Nos dias em que os biorecursos so rapinados e a propriedadeintelectual sonegao, uma rpida e efectiva tcnica geoespacial para caracterizao da biodi-versidade ao nvel da paisagem tem uma larga aplicao na conservao e gesto judiciosa dosbiorecursos.

Key words: Biological richness, conservation prioritization, disturbance regimes, fragmentation, Geo-graphic Information System, remote sensing.


3/21

ROY & BEHERA 153

Introduction

Biodiversity refers to the quality, range or ex-tent of differences between the biological entitiesin a given set. Thus it would be the diversity of alllife and is a characteristic or property of nature,not an entity or a resource. This covers the totalrange of variation in and variability among sys-tems and organisms, at the regional, landscape,ecosystem and habitat levels, at the various organ-ism levels, down to species, populations and indi-viduals. It also covers the complex shades of struc-tural and functional relationships within and be-tween these different levels of organisations (Fig.1), including human action, and their origin andevolution in space and time domain. Darwins(1859) theory of evolution by descent made sense ofthe natural patterns observed in the variation be-tween organisms. Through natural selection, theseheritable changes may spread throughout thepopulation and over time can lead to the produc-tion of new linkages closely similar to their rela-tives. Such lineage diversification produces strictlyhierarchical pattern. Roughly 4.5 billion years ofbiotic evolution has led to an enormous diversity ofliving forms on earth.

Biodiversity often decreases with distancefrom source populations, and is most constrainedby dispersal in areas that are surrounded by dis-

similar habitats (Colinvaux 1993). It is becomingevident that patterns of diversity in natural set-tings showing strong ecological correlation mayreflect history rather than the product of ecological

equilibrium of species diversity determined by theoutcome of species interactions. The decrease indiversity by decrease in distance may in part re-flect the relative edge, geographical extent anddifferent historical patterns of barrier formationand consequent biotic disruptions. Distributionalstudies of biodiversity patterns show that each re-gion has had a unique phylogenetic, geographicand ecological history that has set contemporarybiodiversity.

Biodiversity Assessment: Indian Initiatives

Botanical Survey of India (BSI) and ZoologicalSurvey of India (ZSI) have been involved in surveyand exploration of flora and fauna present in thecountry (1983). The Red Data Book enlists theIUCN categories of plants and animals occurringin various parts of the nation (Nayar & Shastri1987). Government of India has been involved inlaunching various projects from time to time forinventorying and preserving the biological data-base viz., Project on Study, Survey and Conserva-tion of Endangered Plants (POSSCEP), NationalBiodiversity 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. Bio-sphere is the limited zone of life on earth.


4/21


However, a lot of database has been developed outof these studies. But the important componentslacked in these studies are (a) lack of properdocumentation and database retrieval system (b)

lack of spatial (locational) information on IUCNplant categories (c) absence of time-period study toassess the change etc. In a most recent attempt tomap bio-geographical regions, Rodgers & Panwar(1988) attempted to define the bio-geographicalregions of India and mapped ten bio-geographicalzones. The Wildlife Institute of India has con-verted these regions on to Survey of India (SOI)digital database. An established method of biodi-versity conservation is the protected area concept,which lacks many integral components. It was ob-served that the process of selecting protected areasand determining a protection category was arbi-

trary, unsystematic and inconsistent. Protectedareas were also not placed in any rational systemof regional land use planning. As a result, evendensely settled areas were designated as nationalparks and many important biodiversity areas werenot included in the network (Kothari et al. 1989).Most obvious causes of biodiversity loss in Indiahave been habitat loss, over-exploitation, and in-troduction of invasive species and lack of nationalland use policy.

Characterizing biodiversity

Biodiversity characterization involves two dif-ferent processes, the observational and characteri-zation of the main units of variation (genes, spe-cies and ecosystems) and the quantification ofvariation within and between them. In reality,they are part of the same process; the analysis ofpattern defines the unit and characterization oftheir variation. Characterization of biodiversitydepends critically on the work of three scientificdisciplines i.e., taxonomy, ecology andgenetics. Or-ganisms occur in an intricate spatial mosaic classi-fied on a world scale into biogeographic zones, bi-omes, ecoregions and oceanic realms, and at a va-

riety of smaller scales within landscape into eco-systems and communities. The biodiversity atlandscape level can be characterized by measuresof species richness, species diversity, taxic diver-sity and functional diversity (Roy & Behera 2000).Hence, assessment of characterization units andtechniques leave rather a dissected view of biodi-versity at different levels of description. The re-mote predictors or surrogates often play very sig-

nificant role to measure richness. The habitat sur-rogates including classification of vegetation, de-tails on the physical environment, factors deter-mining the biodiversity loss in a spatial context

may be of practical information value and couldreduce sampling intensity. This information basecould also guide detailed sampling on the ground.These larger scale surrogates include entire func-tional system and are more likely to promote popu-lation viability in the ecosystem. In conservation,this is likely to differ with earlier measures of eco-logical diversity formulated with the narrower aimof representing differences in abundance amongspecies, exploring distribution of resources withincommunity. If the value of biodiversity to a conser-vationist is associated with its use to people thenthis ought to be separated carefully from issues of

rarity, viability and threat. If the biodiversityvalue is associated with richness in a currency ofcharacters of organism then the higher level of bio-logical organization (or environmental factors af-fecting its distribution) will have to be used in sur-rogate measures. Choosing a surrogate level fromthis scale is a compromise between the precision ofthe measure on the one hand, and the availabilityof the data and the cost of data compilation on theother. Higher-level surrogates should have the ad-ditional advantage of implicitly integrating more ofthe functional processes that favour viability. Thetaxonomic inventories in the past have only been

able to reach partial level of understanding therichness. Hence this should be a top down andbottom up approach together (Fig. 2).

Landscape ecology

A landscape addresses a number of technicalissues e.g., managing large datasets, scaling proc-esses among different spatial and temporal scalesand the whole concept of ecosystem managementinclude many of the tenants of landscape ecology.Ecological systems do not exist as discrete unitsbut represent different parts of a natural continum

in the form of landscape. It can also be consideredas higher level of biological complexity and im-mensely useful for understanding various complexprocesses. Landscape ecology allows studyingthese processes on different scales and time. Therelatively new discipline of landscape ecology pro-vides insight into both landscape diversity andspecies diversity and suggests a theoretical andpractical basis for conservation planning. The


5/21

ROY & BEHERA 155

management should thus focus on the ecosystemsthat contain these species and on the landscapes inwhich ecosystems are found.

There are three basic characteristics of land-scapes that affect their diversity: structure, func-tion and dynamics (Forman & Godron 1986). The

patch is the basic unit of the landscape structure;the characteristics of patches and the spatial rela-tionships among patches are important compo-nents of the landscape (Lidicker 1995). The distri-bution of energy, material and species amongpatches differing in size, shape, abundance andconfiguration are particularly important to pat-

terns in diversity at the landscape scale. Land-scape dynamics include characteristics of structureand function both in order to examine changes inpattern and processes over time. The conservationof biodiversity requires understanding of all threeelements, including the effects of human activitieson the system. Landscape composition can bemeasured in ways analogous to measurements ofspecies composition (Romme 1982). The most

straight forward approach is landscape richnessi.e. the number of different patch types in a land-scape. Another approach includes the relativeabundance or dominance of different patch typesalong with richness. Measurements of landscapediversity are analogous to common measurementsof species diversity (Whittaker 1977, 1995). Differ-ent patch types provide different habitats and spe-cies composition, thus one might expect that thetotal number of species in a landscape would in-crease as landscape richness increases (Burnett etal. 1998).Landscape level approach also addressesthe changes that might be expected in biodiversity

as a result of anthropogenic activity and also thecomplementary issue of how changes in biodiver-sity will affect the functioning of biological systems(Franklin 2001).

Patch description

A patch is relatively homogenous nonlineararea that differs from its surroundings. The defini-tion and identification of individual patches and

Genes

Species

Population

Community

Ecosystem

Landscape

Appro

ach2

Appro

ach1

Hierarchy of Biological Organisation

Approach (Existing) 1 : Time Consuming

High extinction rate ? Overtaking inventory process

Approach (Proposed) 2 : Stratified approach

Extrapolation on large landscapesSystematic Monitoring

Spatial Environmental Database

Fig. 2. Hierarchy of biological organization.


6/21


their boundaries are important steps in character-izing the structure of a landscape. Most methods ofpatch identification combine qualitative and quan-titative approaches. Turner et al. (1993) provided

quantitative techniques to group similar cells intohomogenous patches or to identify repeating pat-terns across landscape. These methods includemoving window analysis and satellite image tocharacterize landscapes with sharp transitions.Once the patches in a landscape have been identi-fied, there are many ways to describe and quantifythem (Peter et al. 2001; Ritters et al. 1995). Thepatch size and shape are the most understoodlandscape characteristics with species diversity.The relationship between patch size and speciesrichness goes well beyond the familiar species-areacurve (Fig. 3).

Fragmentation

Fragmentation of landscape results in geo-graphical isolation and the probability of recoloni-sation strongly depends on the distance of frag-ments from the main core and on the quality of thesurrounding habitat. Fragmentation study takesinto account connectivity (corridors), presence ofecotones, the meta population structure etc. It in-

creases the vulnerability of these patches to exter-nal disturbance with threat on the survival ofthese 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 accessthan smaller fragments. Severity of tropical forestsfragmentation has been studied with respect todistance effects, fragment size, edge effects andbiotic changes (Bierregaard et al. 1992; Ravan &Roy 1997). The corridors are physical and func-tional connectivity to allow the movement of plantspecies and fauna. They are severely affected dueto fragmentation (Villard & Taylor 1994; Villard etal. 1995). It is also observed that habitat require-ment for sensitive species are specific to area size

and surrounding characters (Bancroft et al. 1995).Fragments having edges of dense shrubby vegeta-tion that prevent alien species from entering, al-though at the same time these warm edges areattractive to alien species (Brothers & Spingarn1992). Despite these negative effects, fragmentsare better than nothing (Turner & Corlett 1996).Fragmentation of the terrestrial habitats is wide-

Patch Area

No

.o

fSpe

cie

s

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


7/21

ROY & BEHERA 157

spread in most parts of the world, and its negativeeffects have been well-documented (Saunders &Ingram 1987). Matrix is the most connected ele-ment and structural attribute. Hence in landscape

perspective, matrix and patches are the elementsthat are used while considering fragmentation in alandscape (Baudry 1984; Wien 1994). Using theneighborhood concept, it is possible to measure therelative size and isolation of the patches. Envi-ronmental patchiness can reflect a mosaic of soiltypes, topographic conditions, microclimate andsuccessful stages after recovery from disturbance(Lambeck & Saunders 1993). The functional rela-tionships of patchiness with species diversity aredue to (a) dependence of species diversity on physi-cal substrate; (b) interspecies dependence; (c) spe-cies interactions within communities; (d) inciden-

tal species relations; and (e) dynamics of a land-scape.

The landscape way world goes?

The structured, spatially explicit approach fordescribing, analysing and evaluating the distribu-tion of vegetation, species composition of heathand mire in Northern Ireland was based on multi-variate land classification and field sampling(Millsopp et al. 1997). Forman & Godron (1986)observed three landscape characteristics i.e., struc-ture, function and change. Several studies have

suggested that the landscape have critical thresh-old at which ecological processes will show dra-matic qualitative changes (Gardner et al. 1989; ONeill et al. 1989; Turner 1989). Godron (1991) hasdocumented that remote sensing gives a perspec-tive horizontal view and helps in delineating dif-ferent landscape elements and their spatial char-acteristics. McGarigal & Marks (1995) have docu-mented that the patch density and mean patchsize serve as fragmentation indices for comparisonbetween two time periods. The role of patch con-nectiveness on the dispersal and spatio-temporaldistribution of a small tree dwelling bird and also

revealing the presence of birds being significantlyrelated to the length of suitable patches has beendealt by Farina (1998). Patch size can influencefloral and faunal composition and richness. Smallpatches of forest tend to have a greater proportionof edge to interior than large patches and thus aremore likely to harbour exotic or weedy species(Levenson 1981). Fuller et al. (1998) combined fieldsurveys of plants and animals with satellite re-

mote sensing of broad vegetation types to map bio-diversity and thereby helped plan conservation inSango Bay area in Uganda. Debinski et al. (1999)had used remotely sensed data and GIS to catego-

rize habitats, and then determined the relation-ship between remotely sensed habitat categoriza-tions and species distribution patterns. Manyworkers had studied on the patterns of speciesrichness in biogeographical, ecological or habitatspace biology (Pinaka 1966; Richerson & Lum1980; Rohde 1992). Relationships between richnesspatterns and various ecological, geographical orother factors have been dealt in by many workers(Currie 1993). The accuracy and validity of model-ing geographical patterns of species richness arecritical factors in distinguishing and understand-ing the so called hotspots of biodiversity (Roy et al.

1993).Few studies have been done in India to estab-

lish relationship between the disturbance and thebiological richness of the landscape elements.(Pandey & Shukla 1999; Roy et al. 1997; Roy &Tomar 2000). Menon & Bawa (1997) have alsofound the role of remote sensing, geographic in-formation system and landscape analysis for biodi-versity conservation in western Ghats using geo-spatial modeling approach. The study, however,only considered habitat fragmentation and did notinclude many other important landscape parame-ters. A horizontal relationship between the various

spatial units at different spatial scale to study thehomogeneity, heterogeneity and causative mecha-nisms have been established by Ravan & Roy(1995) during their landscape dynamics study ofMadhav National Park in India. Ramesh et al.(1997) have attempted a vegetation-based ap-proach for biodiversity gap analysis. This approachtakes into account the extent of deforestation, dis-tribution of forest/vegetation types, patchiness,and species diversity for each forest/vegetationtype and uniqueness of the habitats. The study,however, did not take into account human induceddisturbance sources. Nagendra & Gadgil (1999)

attempted to investigate relationship of variouslandscape elements on the basis of field observa-tion. They found that the landscape elements sig-nificantly support distinctive sets of species offlowering plants. However, the study did not ana-lyze landscape based ecological parameters in aspatial context. They also could not integrate fielddata with satellite derived vegetation maps. Roy &Tomar (2000) used geospatial techniques to char-


8/21


acterize biodiversity at landscape level in Megha-laya. The pioneering attempt took into accountenvironmental complexity, habitat and its attrib-utes and disturbance regimes to model the spatial

variation in biological richness. The importance ofthe study lied in the fact that it can help in priori-tizing sites in conservation and also facilitatemonitoring the perturbations of the richness of thelandscape as a function of space and time. Behera(2000a) mapped the biologically-rich areas inSubansiri district of Arunachal Pradesh and ob-served that much of the biologically-rich areaswere lying in the sub-tropical zone. Behera et al.(unpublished) attempted to validate the findingsand observed that fragmentation has got signifi-cant impact on species diversity.

Community analysis

Inventorying and analyzing vegetation cover isthe most practical way of tracking biodiversity.Information on species is crucial before they arelost forever. Article 7 of the United Nations Con-vention on Environment and Development re-quires signatory parties to identify components ofbiodiversity importance conservation and sustain-able use and monitor, through sampling and othertechniques, the components of biological unitsidentified. Chapter 15.6 calls for the developmentof methodologies with a view to undertake sys-

tematic sampling and evaluation on a national ba-sis of the components of biological diversity identi-fied by means of country studies and to initiate orfurther develop methodologies and begin or con-tinue work on surveys at the appropriate level onthe status of ecosystems and establish baselineinformation on biological resources. Studies ofspecimens collected during inventories yield datauseful for resolving the phylogenetic relationshipsof species, which in turn, are essential for buildingpredictive classification systems and permit theestimation of character diversity for comparison ofbiota (Williams et al. 1995). These relationships

can be used to help prioritise areas for conserva-tion or other land management decisions. Speciesinventories provide the foundation for future in-dustrial applications, particularly those associatedwith bioprospecting (Behera et al. 2000b; Reid etal. 1993).

Is biodiversity related to disturbance?

Disturbance is a common and widespread phe-nomenon in nature and may be defined as a dis-

crete event along the passage of time that modifieslandscape, ecosystem, community and populationstructure (Pickett & White 1985). Fragmentationhas a strong influence on the dynamics and fate ofthe material and energy moving across a land-scape. Disturbance regimes and their impact oncommunities and landscape can be well understoodby analyzing spatial and temporal architecture ofdisturbance (Moloney & Levin 1996). Severe dis-turbance or even a prolonged absence of distur-bance generally has depressing effect on biodiver-sity, but intermediate disturbance seems to en-hance diversity in a system (Pickett & White

1985). The capacity of the landscape to incorporatehuman disturbance is overwhelmed and the dis-turbance process is transformed into a stress proc-ess, which reduces biodiversity. The disturbanceregimes can be measured by using different indicesi.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 isola-tion from the larger, potentially changing envi-ronment. Management practices aimed directly ata particular species run the risk of losing ecosys-tem functions that might actually be crucial for thetarget species, but that were unknown when themanagement plan was created. Furthermore,maximizing benefits for one species may threatenothers. The ideal is to preserve overall ecosystemhealth, including species diversity. Given the largenumber of species on the planet, it is impossible, orat best impractical, to manage for every one of

them. Instead, conservation biologists are now try-ing to identify ways to simplify the task of land-scape level management. The primary require-ments to evolve such an approach would be:

Determination of disturbance regimes; Knowledge on spatial distribution of bio-

logical richness;


9/21

ROY & BEHERA 159

Determination of the optimum size of con-servation areas; and

Identification of set of focal species, sensi-tive to particular landscape structure and

function.

Geospatial tool how does it help?

Landscape ecology has evolved as an opera-tional tool with the availability of geospatial mod-eling techniques. Space may be considered as the

final frontier for ecological theory (Karieva 1994)spacing or spatial arrangement is a scaled prop-erty of living organisms, from individuals to popu-lations, communities and meta-communities. It isthe ecological replay of an organism to non-uniform distribution of resources (habitat suitabil-

ity) and to inter and intra-specific competition inspace and time. This is the central dogma of land-scape ecology. Spacing depends mainly on resourceavailability. Plants react to resource availabilityby arranging themselves in a finite and predictablepattern.

Satellite remote sensing

Acquisition of images of earth from space hasopened new frontiers in mapping. The multispectralsatellite images provide definitions of vegetationpatches, which are related to phenological types,gregarious formations and communities occurringin unique environmental setup (Behera 1999). Thetemporal images help in monitoring all back proc-esses a landscape has experienced (Delcourt & Del-court 1988). Such an approach allows monitoringthe forest condition and degradation processes (Roy& Behera 2000). The images also provide digitalmosaic of the spatial arrangement of land cover andvegetation types amenable to computer processing(Coulson et al. 1990 ; Chuvieco 1999). The other ap-proach to analyze the landscape pattern propertiesis based on nominal scale classified maps. Thesemaps can also be analyzed using various indicesquantitatively, which measure the heterogeneity oflandscape within a specific radius. Diversity anddominance are well known examples of those indi-ces (Baker & Cai 1992). They are ordinarily com-puted from samples of relatively homogenous covertypes, named patches. Size, shapes, perimeter, con-nectivity, orientation, presence of corridors, visibil-ity or diversity of patches are critical variables fordescribing the landscape mosaic. Not much workhas been done towards analysis of these variables

from satellite images. Analysis of landscape frag-mentation (Turner et al. 1993) has been commongoals in the use of satellite data for landscape pat-tern analysis. It has recently been shown that these

clumps (also known as geographic windows) aremore suitable to describe spatial patterns than thestandard moving windows of fixed sizes (Dillworthet al. 1994). In Indian context, Menon & Bawa(1997) have used remote sensing and GIS technolo-gies for biodiversity conservation following land-scape ecology and spatial analysis approach. In1996, Kasturirangan et al. 1996 have forecastedthat applications to biodiversity conservation is oneof the areas in which remote sensing will play a rolein the future.

Geographic information system (GIS)

GIS provides the way to overlay different lay-ers of data: the ecological conditions, the actualvegetation physiognomy and human pressure indi-ces (e.g., as deduced from the density of populationor road network). It helps to assess disturbancelevels; the spatial distribution of several species inorder to determine biodiversity hotspots; past andpresent maps for monitoring land cover and landuse changes. It provides possibilities to extrapolateobservations e.g., to automatically define and mapthe potential area of a given species and to com-pare it with the locations where, it has been actu-ally observed; or to combine different data sets for

defining the potential list of species for a given for-est type. GIS provides a database structure for ef-ficiently storing and managing ecosystem-relateddata over large regions. It enables aggregation anddis-aggregation of data between regional, land-scape and plot scales. It also assists in location ofstudy plots and/or ecologically sensitive areas. GISsupports spatial statistical analysis of ecologicaldistributions. It improves remote sensing informa-tion extraction capabilities, and provides inputdata/parameters for ecosystem modelling. Thedata generated through ground truthing and inte-gration of related attributes when used in GIS ap-

plication result into significant features of biodi-versity and genetic resources.

Global positioning system

A GPS is a satellite-based positioning systemoperated by the U.S. Department of Defense(DoD). GPS allows the collection of informationabout the geographical position of any location us-ing a network of satellites. It has a great potential


10/21


in landscape ecology, as well as in many other re-lated disciplines requiring geographic locations ofthe objects in the landscape (Farina 1998). Cou-pled with GIS, it acts as a powerful tool to describe

the geographical characteristics of ecological sys-tems. A practical use of GPS has been in locatingthe sample plots and this information was used formapping and spatio-statistical analysis (Behera etal. 2000c).

Biodiversity conservation priority setting

the right criteria?

The complexity priority setting varies consid-erably due to complexity of biodiversity and thenumber of ways of valuing it. Among the biologicalcriteria are richness (the numberof species or eco-

systems in given area), rarity, threat (degree ofharm or danger), distinctiveness (how much a spe-cies differs from its nearest relative), representive-ness (how closely an area represents a defined eco-system) andfunction (the degree to which a speciesor ecosystem affects the ability of other species orecosystems to persist). Some priority setting ap-proaches use social, policy and institutional crite-ria as well. Utility, the most common non-biological criteria, points to biodiversity elementsof known or potential use to humankind. Feasibil-ity, often paramount in deciding how to allocateconservation resources, may be political, economic,

logistical or institutional terms. Considering thebiological criteria, areas can be identified wherethe actions are most likely to succeed. However,with increased recognition the social, policy andinstitutional factors are crucial for conserving bio-diversity. Ecological approaches for setting priori-ties for biodiversity conservation generally seek toprotect most of the species within conservationareas that are representative of a regions naturalhabitat. Ecosystem approaches for identifying con-servation priorities use multiple criteria such asspecies richness, endemism, abundance, unique-ness and representativeness, as well as considera-

tions of the physical environment, ecological proc-esses and disturbance regimes that help to definethe ecosystem.

Baseline data on biodiversity at landscape

level

The goals and scales of inventorying and moni-toring programs may change with time. Hence, the

baseline data at landscape level should be suffi-ciently robust to accommodate changes. It shouldbe based on robust samples enabling calibrationfor future rapid biodiversity assessment. Land-

scapes contain all levels of the biological hierarchy,from ecosystem to species and genes that are tar-geted for biodiversity inventories and conserva-tion. The present effort to characterize vegetationcover, fragmentation, disturbance and biologicalrichness across the landscape is organized in theform of Biodiversity Information System (BIS)(Fig. 4). The field samples of key ecological charac-ters have been used for geospatial extrapolation.The species database has been linked with abovespatial details. The BIS allows to identify gap ar-eas, species / habitat relationship and helps in bio-diversity conservation planning by setting priority

areas. Such database coupled with detailed site-specific field inventories helps in identifying areasfor bioprospecting.

The assessment of biological rich areas bringsout distinctiveness of the landscapes as driven bypattern of richness, endemism, biological corridors,community composition and diversity. The analy-sis made also presents full range of distinct natu-ral communities and ecological status at landscapelevel. The landscape capable of maintaining theviable population species, sustain important eco-logical processes and services that maintain biodi-versity are also mapped. This information is of

valued importance in rugged, inhospitable regionthroughout northeastern region. Such areas re-main by and large under explored. The resultspresented here could form the basic guideline toplan flora and faunal future inventories. The focusshould be to cover varied landscapes differingbased on vegetation types, disturbance regimesand BR. Such an approach allows to build habitatfactors like biophysical environment, landscapeindices and disturbance regimes which allow moni-toring changes taking place over a time in biodi-versity regimes. Understanding of species habitatrelationships, inventorying patterns, multivariate

modeling of long-term datasets allows to formulateand test the hypothesis. The dataset could alsoallow monitoring and forecasting changes throughextinction models using multi-temporal data. Suchmodeling can help in impact of global change indifferent landscapes. Finally the approach can beextended to study species diversity and geneticvariability in biologically rich sites for prioritizingfocus on bioprospecting.


11/21

ROY & BEHERA 161

Biodiversity characterization at landscape

level in Arunachal Pradesh fulfills the in-

formation need?The rich species diversity which characterizes

the flora of north-eastern region of India is largelyattributable to the diverse geographical area, var-ied topography, climate and soil variability, immi-gration and colonization of plant species fromwidely different territories and is a transitionalzone between India, Indo-Malayan and Indo-Chinese biogeographical zones as well as the con-fluence of the Himalayan region with peninsularIndia (Rao 1994). Forest of Arunachal Pradesh innortheastern region of India with such rich biodi-versity is disappearing at an alarming rate mainly

due to anthropogenic activities. Irreversiblechanges and deterioration of ecosystems arecaused not only by the extensive destruction ofnatural habitats but also by direct exterminationof many important species of fauna and flora meet-ing various human needs and greeds. Jhum orshifting cultivation, which is widely practiced inhills of Arunachal, is also a causing factor in thedepletion of biodiversity. Application of recent ad-

vances of space technology and their integrationwith biodiveristy studies to different levels anddata generation for setting criteria and prioritiesare provided below.

Methods

Mapping at macro level

The satellite data of IRS-1C/1D have been usedto extract the vegetation types, considering forestphenology and optimal season. Regional levelmapping was carried out for the preparation ofecological zone map using IRS-WiFS data (WideField Sensor) with a capability of covering largearea in single instantaneous field of view (IFOV).

It has a potential for monitoring the phenologicalfluxes of largely forested landscape at regionallevel. Integration of maximum NDVI was evalu-ated for monitoring the seasonal changes in vege-tation. This was found as an excellent source ofdata for understanding the land dynamic processesand human interventions in the region, which wastaken as one of the inputs in mapping disturbanceregimes.

Satellite Remote Sensing &Geo-spatial Modeling

Availability Distributed Spatial Data

Species Database

Identification of Biological Gap AreaSpecies + Habitat RelationashipsBiodiversity Conservation PlanningBioprospecting Zonation

Biological RichnessDisturbance Index

Vegetation Type

Fragmentation

PRIMARY OUTPUTS

Digital Elevation Model

DrainageDigital Chart World

Settlement+ Roads (DCW)

Wildlife Institute Of India(Biogeographical zones of India)

FSI (Forest Cover Map)

ANCILLARY INFORMATION

NON SPATIAL INFORMATION

Red Data Book (BSI)

Field Database

PublishedFlora

Endemic Species

French Institute Database

Fig. 4. Biological Information System (BIS).


12/21


Mapping at meso levelIRS 1C/1D LISS-III digital data were used

for classification. The entire state of Arunachal

Pradesh is covered in 21 scenes. The scenes weregeometrically corrected (Root Mean Square Error< 0.002 0.007) and then mosaiced. With the helpof Survey of India (SOI) digital boundary the statearea was extracted. Pre-processing (radiometricand atmospheric correction) of data was done priorto classification. Digital classification was carriedout through hybrid classification (supervised andunsupervised techniques) approach using ERDASImagine software. Finally classified map of thestudy area was prepared on 1:250 000 scale. Inten-sive ground truth data was collected prior to classi-fication by repetitive field visits. Various vegeta-

tion classes mapped are as follows: tropical ever-green, tropical semi-evergreen, moist mixed de-ciduous, sub-tropical evergreen, temperate broad-leaved, conifers, sub-alpine and alpine scrub, bam-

boo mixed, abandoned jhum, degraded, Diptero-carpus, Hollock, Pine, fir, Rhododendron, Riverainand grass land. Various non-forest classes mappedare dry river bed/sand, agriculture, fallow/barren

land, river/water body, settlement/habitation,shadow, snow and cloud. This classified informa-tion has been used to delineate the spatial extentof forest (Fig. 5).

Field data generation

Stratified random sampling and nested quad-rat approach was followed for carrying out com-munity analysis after a reconnaissance survey invarious districts of the state (Anon. 1998). Size ofthe quadrat was determined through species-area-curve. Phytosociological data viz. relative fre-

quency, relative density and relative dominancehave been calculated to compute the importancevalue index (IVI) for each stratum. The IVI hasbeen utilized to calculate species richness using

High Low

Ecosystem richness ?

Climate class richness

Terrain class richness

Substrate class richness

Landscape class richness

Habitat class richness

Community class richness

Vegetation class richness

Higher taxon richness

Species/subspecies richness

Taxonomic/phylogeneticsubtree length

Expressed gene richness

Environmental surrogates

Environmental /Assemblage surrogates

Assemblage surrogates

Taxonomic surrogates

Molecular surrogates

Low

Advantage:Precision as a measureof character diversity

A scale of surrogacyfor a value currencyof character diversity

Advantage:Inexpensivesurvey & units more inclusiveof viability enhancing process

High

Source: Paul Williams, 2000

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


13/21

ROY & BEHERA 163

the Shannon-Wiener index. The field data was col-lected to derive biodiversity value on the basis ofimportance index, forest density and economicvalue. These parameters have ultimately been

used to ordinate the vegetation types (Behera2000a; Roy & Tomar 2000).

Landscape characterization

Satellite images were used to generate thevegetation type map. Digitally classified productwith different landscape parameters (porosity,fragmentation, interspersion, juxtaposition, patchcharacteristics) were generated and analysed. Us-ing these different characters along with proximityinputs (roads and settlements) were used to derivedisturbance index (DI) map. To fulfill the require-

ment of landscape analysis, Bio_CAP that is aGeospatial Semi-Expert package was developedusing GIS package (Arc/Info), Image Processing(ERDAS) and C/C++(Anon. 1999).

DisturbanceIndex

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

Biodiversity characterization

The biological richness at landscape is deter-mined as a function of ecosystem uniqueness, spe-cies diversity, biodiversity value, terrain complex-ity and disturbance. The main parameters like EU,H, BD etc., come from ground based observationsin various vegetation types specially ecosystemuniqueness is derived with the help of species da-tabase query shell which is based on IUCN catego-rization scheme. Terrain complexity is derivedfrom the terrain through DEM. The biologicalrichness values have been used for scaling the re-gion or area for potential biodiversity prospectzones (Fig. 6).

Biologicalrichnessindex

=

ecosystem uniqueness, speciesdiversity, biodiversity value,

terrain complexity anddisturbance index

Result and discussion

Vegetation mapping

The entire state of Arunachal Pradesh wascovered in 21 LISS-III scenes of IRS-1C/1D satel-

lites. Due to the radiometric variation betweenindividual scenes, they were classified separatelyand then mosaiced using the previously storedground control points (GCPs) to obtain the final

classified map for the entire state. The vegetationcover type map was prepared by using digital clas-sification following hybrid approach.

Community analysis

Highest Shannon-Weiner diversity was ob-served in subtropical evergreen forest followed bytemperate broadleaved and tropical evergreen for-est. Total number of families, genera and species ofplants were found to be highest in tropical semi-evergreen forest.

Disturbance indexThe landscape parameters were finally inte-

grated to derive disturbance index map of the state(Fig. 7). Assigning different intra-class weights tovarious indices has simulated disturbance indexafter performing normalization. Disturbance indeximage obtained gives a clear picture of both an-thropogenic and natural disturbances and theirspatial extent in various levels. The map shall beuseful for managers and decision makers for vari-ous planning and enforcing conservation meas-ures.

Biological richness mapping

The mapping ofbiological richness carried outin Subansiri district of Arunachal Pradesh (Behera2000) revealed that sub-tropical evergreen forestzone is highly rich biologically followed by tropicalsemi-evergreen forest environment (Fig. 8). Thebiological richness map shows a clear pattern,which cannot be judged without a critical under-standing of the whole spectrum of phenomenonresponsible for it.

The results of the present study characterizebiodiversity at landscape level for bioprospecting and

conservation. This work aims at developing reversalprocess of deforestation and degradation in north-eastern region by setting conservation priorities. Theinformation system evolved through multicriteriaanalysis in GIS facilitates the following:

Rapid assessment for monitoring biodiver-sity loss and/or gain

Assess nature of habitat and disturbanceregimes;


14/21



15/21

ROY & BEHERA 165


16/21



17/21

ROY & BEHERA 167

Evolve species habitat relationship; Mapping biological richness and gap

analysis; and Prioritizing conservation and bioprospect-

ing sites.Following are the areas where the database

would have direct use.

Highlights of the work

The status of information and ongoing practi-cal aspects of the integrated studies using recenttechniques of remote sensing, GIS and GPS pro-vided following features:

Biodiversity is generally greatest in theoldest ecosystems. It changes across envi-ronmental gradients like, latitude, alti-

tude, depth, aridity etc. The habitat defini-tions in the form of vegetation cover types

will allow what to look where. The distur-bance regimes assessed across the land-scape will allow focusing on the ecosys-tems, which are under stress. Hence if

the field survey indicates that the region isimportant habitat for a species for bio-prospecting, the stress factor needs to beremoved/reduced.

Biological Richness Index (BR) asserts theareas, which should be treated as priorityin decision-making and management levelfor conservation of biodiversity. The Gap

Analysis carried out on maps will guidemangement and decision making for bio-prospecting.

All plant species have a basic requirementof its ecological optima in particular habi-

tat or niche within range of tolerance andrequirement. Habitat identification and

Fig. 9. Genetic diversity vs. Species diversity.


18/21


economic importance of the species can beuseful input for bioprospecting and biodi-versity conservation.

Biological rich areas are those habitatswhere landscape ecological conditions arefavorable for natural speciation and evolu-tionary process. These areas can be ex-pected to be in equilibrium where speciescan occur, grow and evolve in natural con-ditions.

Each species requires a specific ecologicalniche (minimum/optimum area for its sur-vival, evolution, gene exchange). Analysisof landscape parameters like habitat frag-mentation, patchiness, interspersion andjuxtaposition have shown impact on thedefinition of the limits in different habi-

tats. Greater the variety of types of habi-tat, the greater is diversity of the species.Diversity also increases with expandingarchitectural complexity of the physicalhabitat.

Management of contaguous (large), intactand juxtaposed patches of high diversity inany landscape should draw first attentionfor conservation. The ground inventorieson species/ genetic diversity should furtherdecide on priorities. The patches havinghigher biological diversity at landscapelevel will be subject for more intensive

ground inventories for assessing spe-cies/genetic diversity. The patches withgenetic and species diversity should drawfirst attention followed by patches of highspecies and/or genetic diversity.

Most of the species growing in the naturalconditions have some sociological associa-tion with the species environment com-plex and in general have fairly well definedniches. Similar ecological conditions in dif-ferent geographical location bear similarbiodiversity if not the same. But they willhave differences at genetic level. The vege-

tation cover types, their composition, asso-ciation, latitude, altitude, fragmentationlevels, inferences on possible corridors andspecies database compliment the informa-tion needs.

Based on the existing literature about theoccurrence of the valuable threatened spe-cies (BSI Red Data Book and field data ofthe present and subsequent studies), its

habitat can be examined in terms of itslandscape requirements of the species.Once the comprehensive species databaseis established, potential species distribu-

tion and occurrence maps can be gener-ated. Integrated gene marking techniquescan help in preparing the location - species environment complexes. Such informa-tion base can be of immense value for bio-prospecting.

It is expected that the maps will be strate-gically used for planning detailed groundlevel inventories of flora and fauna bypremier institutions like Botanical Surveyof India, Zoological Survey of India, Stateforest departments and Wildlife Instituteof India. The region wise maps can also be

used for redefining ecological zones re-quired for biodiversity conservation.

Hence, it may be concluded that not either-orbut a hybrid approach (both ground sampling andsatellite tool) play a major role in assessing biodi-versity at landscape level.

References

Anonymous. 1998. Biodiversity Characterization atLandscape Level using Geographic Information Sys-

tem. Project Manual, Indian Institute of RemoteSensing. Dehradun.

Anonymous. 1999. Bio_CAP User Manual for LandscapeAnalysis and Modeling Biological Richness. IndianInstitute of Remote Sensing. Dehradun

Baker, W.L. & Y. Cai. 1992. The role programs for mul-tiscale analysis of landscape structure using theGRASS geographic information system. LandscapeEcology7: 291-302.

Bancroft, G.T., A.M. Strong, M. Carrington. 1995. Defor-estation and its affects on foresting birds in theFlorida Keys. Conservation Biology9: 835-844.

Baudry, J. 1984. Effects of landscape structures on bio-logical communities: the case of hedgerow networklandscapes. Proceedings of International Seminar.

IALE Methodology in Landscape Ecological Re-search and Planning. Roskilde, Denmark, 15-19October 1984. Vol. I: 55-65.

Behera, M.D. 1999. Remote sensing and environment.Employment News24: 1-2.

Behera, M.D. 2000a. Biodiversity Characterization atLandscape Level in Subansiri District of Arunachal

Pradesh (Eastern Himalaya) Using Remote Sensing

and GIS. Ph.D. Thesis.Gurukul Kangri University,Hardwar.


19/21

ROY & BEHERA 169

Behera, M.D., S. Srivastava, S.P.S. Kushwaha & P.S.Roy. 2000b. Stratification and mapping of Taxusbaccata L. bearing forests in Talle Valley using re-mote sensing and GIS. Current Science 78: 1008-

1013.Behera, M.D., C. Jeganathan, S. Srivastava, S.P.S.

Kushwaha & P.S. Roy. 2000c. Utility of GPS in clas-sification accuracy assessment. Current Science79:1996-1700.

Bierregaard, R.O.J. 1992. The biological dynamics oftropical rainforest fragments.Bioscience42:859-866.

Botanical Survey of India. 1983. Flora and Vegetation ofIndia An Outline. Botanical Survey of India,Howrah.

Brothers, T.S. & A. Spingarn. 1992. Forest fragmenta-tion and alien plant invasion of central Indiana oldgroth forests. Conservation Biology6: 91-100.

Burnett, M.B., J. August, J. Brown & K.T. Killingbeck.1998. The influence of geomorphological heterogene-ity on biodiversity: A patch-scale perspective. Con-servation Biology12:363-370.

Chuvieco, E. 1999. Measuring changes in landscape pat-tern from satellite images: short-term effects of fireon spatial diversity. International Journal of Re-mote Sensing20: 2331-2346.

Colinvaux, P. 1993. Ecology. 2nd Edition. John Wiley,New York.

Coulson, R.N., C.N. Lovelady, R.O. Flamm, S.L. Sprad-ling & M.C. Saunders. 1990. Intelligent geographicinformation systems for natural resource manage-ment. pp. 173-172. In: M.G. Turner & R.H. Gadner

(eds.) Quantitative Methods in Landscape Ecology.Ecological Studies-82 NewYork: Springler-Verlag.

Currie, D.J. 1993. Energy and large-scale patterns ofanimal and plant species richness. The AmericanNaturalist137: 27-49.

Darwin, C. 1859. On the Origin of Species by Means ofNatural Selection. John Murray, London.

Debinski, D.M., M.E. Jakubauskas & K. Kindscher.1999. A remote sensing and GIS based model ofhabitats and biodiversity in the greater Yellowstoneecosystem. International Journal of Remote Sensing20: 3281-3292.

Delcourt, H.R. & P.A. Delcourt. 1988. Quaternary land-scape ecology: relevant scales in space and time.Landscape Ecology 2: 23-44.

Dillworth, M.E., J.L. Whistler & J.W. Merchant. 1994.Measuring landscape structure using geographicand geometric windows. Photogrammetric Engineer-ing and Remote Sensing60: 1215-1224.

Farina, A. 1998. Principles and Methods in LandscapeEcology. Chapman & Hall, London.

Forman, R.T.T. & M. Godron. 1986. Landscape Ecology.John Wiley and Sons, New York.

Franklin, J. F. 2001. Preserving biodiversity: species,ecosystems, or landscapes? Ecological Applications3: 202205.

Fuller, R.M., G.B. Groom, S. Mugisha, P. Ipulet, D.

Pomeror, A. Katende, R. Bailey & R. Ogutu-Ohwayo. 1998. The integration of field survey andremote sensing for biodiversity assessment: a casestudy in the tropical forests and wetlands of SangoBay, Uganda.Biological Conservation86: 379-391.

Gardner, R.H., R.V. O`Neill, M.G. Turner & V.H. Dale.1989. Quantifying scale dependant effects of animalmovements with simple percolation models. Land-scape Ecology3: 217-227.

Gordon, B.B. 1991. Seasonal and annual carbon fluxesin a Boreal forest landscapes. Journal of Geophysi-cal Research96: 17329-17338.

Hajra, P.K., D.M. Verma & G.S. Giri. 1996. Materials forthe Flora of Arunachal Pradesh Vol-I. Botanical Sur-vey of India, P-8, Barbourne Road, Calcutta, India.

IIRS, 2001. Biodiversity Characterisation at LandscapeLevel, Project Report, IIRS, Dehradun.

Kareiva, P. 1994. Space: the final frontier for ecologicaltheory. Ecology95: 1

Kasturirangan, K., R. Aravamundan, B.L. Deekshatulu,G. Joshep & M.G. Chandrasekhar. 1996. Indian re-mote sensing satellite (IRS)-IC-The beginning of anew era. Current Science70: 495-500.

Kothari. A., P. Pandey, S. Singh & D. Variava. 1989.Management of National Parks and Sanctuaries in

India. A Status Report, Environmental Studies Di-vision, Indian Institute of Public Administration,

New Delhi.Lambeck, R.J. & D.A. Saunders. 1993. The role of

patchiness in reconstructed Wheatbelt landscapes.pp. 153-161. In: D. Saunders, R. W.F. Loraunce, &P. Ehrlich, (eds.) Nature Conservation 3: Recon-struction of Fragmented Ecosystems. Sydney, SurreyBeeatty Sons.

Levenson, J.B. 1981. Woodlots as biogeographic islandsin Southeastern Wisconsin. pp. 13-39. In: R.L. Bur-gess & D. M. Sharpe (eds.) Forest Islands in Man-Dominated Landscapes. New York, Springer-Verlag.

Li, H. & J.F. Reynolds. 1994. A simulation experiment toquantify spatial heterogeneity in categorical map.Ecology75:36-55.

Lidicker, W.Z. Jr. 1995. The landscape concept: some-thing old, something new. pp. 3-19. In: W.Z.Lidicker Jr. (ed.) Landscape approaches in mam-malian ecology and conservation. University ofMinnesota Press, Minneapolis.

McGarigal, K. & B. Marks. 1995. FRAGSTATS: SpatialAnalysis Program for Quantifying Landscape Struc-

ture. U.S. Department of Agriculture Forest Service,General Technical Report PNW-GTR-351.


20/21


Menon, S & K.S. Bawa. 1997. Application of geographicinformation systems, remote sensing and landscapeecology approach to biodiversity conservation in theWestern ghats. Current Science73: 134-145.

Millsopp, C.A., A. Cameron & J.H. McAdam. 1997.Landscape monitoring in environmentally sensitiveareas in northern Irelands. pp. 321-324. In: A. Coo-per & J. Power (eds.) Proceedings of the Sixth An-nual IALE (UK) Conference. University of Ulster,Coleraine, Northern Ireland.

Moloney, K.A. & S.A. Levin. 1996. The effect of distur-bance architecture on Landscape- level populationdynamics. Ecology77: 375-394.

Nagendra, H. & M. Gadgil. 1999. Biodiversity assess-ment at multiple scales: Linking remotely senseddata with field information, Proceedings of NationalAcademy of Sciences 96: 9154-9158.

Nayar, N. P. & A.R.K. Sastry. 1987. Red Data Book ofIndian Plants. Vol. I. Howrah: Botanical Survey ofIndia.

Nilsson, C. & G. Grelsson. 1995. The fragility of ecosys-tems: a review. Journal of Applied Ecology32: 677-692.

O`Neill, R. V., A.R. Johnson & A.W. King. 1989. A hier-archical framework for the analysis of scale. Land-scape Ecology3:193-205.

Pandey, S.K. & R.P. Shukla. 1999. Plant diversity andcommunity patterns along the disturbance gradientin plantation forests of sal (Shorea robusta Garten.).Current Science77: 814-818.

Peter, D.P., C. Sarah & C. Goslee. 2001. Landscape di-

versity. pp. 645-658. In: S.A. Levin (ed.) Encyclope-dia of Biodiversity. Academic Press, New York.

Pickett, S.T.A. & P.S. White. 1985. The Ecology of Natu-ral Disturbance and Patch Dynamics. AcademicPress, London.

Pinaka, E. R. 1966. Latitudinal gradients in space diver-sity: a review of concepts. The American Naturalist100: 33-46.

Ramesh, B.R., S. Menon & K.S. Bawa. 1997. A vegeta-tion-based to approach to biodiversity gap analysisin the Agastymalai region. Western Ghats, India.Ambio26: 529-536.

Rao, R.R. 1994.Biodiversity in India: Floristics Aspects.Bishen Singh Mahendra Pal Singh, Dehradun.

Ravan, S.A. & P.S. Roy. 1995. Landscape ecologicalanalysis of a disturbance gradient using geo-graphic information system in the Madhav Na-tional Park, Madhya Pradesh. Current Science68:309-315.

Ravan, S.A. & P.S. Roy. 1997. Satellite remote sensingfor ecological analysis of forested landscape. PlantEcology. 131:129-141.

Reid, W., J. McNely, D. Tunstall, D. Bryant & M. Wino-grad. 1993. Biodiversity Indicators for Policy-Makers. World Resources Institute, Washington,DC.

Richerson, P.J. & K.L. Lum. 1980. Patterns of plant spe-cies diversity in California: relation to weather andtopography. The American Naturalist116: 504-527.

Ritters, K.H., R.V. O`Neill, C.T. Hunsaker, J.D. Wick-ham, D.H. Yankee, S.P. Timmins, K.B. Jones & B.L.Jackson. 1995. A factor analysis of landscape pat-tern and structure matrices. Landscape Ecology10:23-29.

Rodgers, W.A. & S.H. Panwar. 1988. Biogeographicalclassification of India. New Forest, Dehra Dun, In-dia.

Rohde, K. 1992. Latitudinal gradients in species diver-sity: the search for the primary cause. Oikos 65:514-527.

Romme, W. 1982. Fire and landscape diversity in subalpine forests of Yellowstone National Park. Eco-logical Monograph52:199-221.

Roy, P.S. & M.D. Behera. 2000. Perspectives of biodiver-sity characterization from space, Employment News25: 1-2.

Roy, P.S., S. Singh & M.C. Porwal. 1993. Characteriza-tion of ecological parameters in tropical forest com-munity a remote sensing approach. Photonirva-chak21:127-149.

Roy, P.S. & S. Tomar. 2000. Biodiversity characteriza-tion at landscape level using geospatial modelingtechnique.Biological Conservation95:95-109.

Roy, P.S., S. Tomar & C. Jegannathan. 1997. Biodiver-sity characterization at landscape level using re-mote sensing. NNRMS BulletinB21: 12-18.

Saunders, D.A. & J.A. Ingram. 1987. Factors affectingsurvival of breeding populations of Carnaby,s cock-too Calyptorhyncus funereus latirostris in remnantsof native vegetation. pp. 249-258. In: D.A. Saunders,G.W. Arnold, A.A. Burbidge & A.J.M. Hopkins,(eds.) Nature Conservation: The Role of Remnantsin Native Vegetation. Beatty and Sons, Sydney.

Turner, I. M. & R.T. Corlett. 1996. The conservation ofsmall isolated fragments of lowland tropical rainforest. TREE11: 330-333.

Turner, M. G. 1989. Landscape ecology: the effect of pat-tern on process. Annual Review of Ecology and Sys-tematics20: 171-197.

Turner, M. G., R.H. Gardener, V.H. Dale & R.V. O`Neill.1993. A revised concept of landscape equilibrium:disturbance and stability on scaled landscapes.Landscape Ecology8: 213-227.

Villard, M.A. & P.D. Taylor. 1994. Tolerance to habitatfragmentation influences the colonization of newhabitat by forest birds. Oecologia98: 393-401.


21/21

ROY & BEHERA 171

Villard, M.A., G. Merriam & B.A. Maurer. 1995. Dynam-ics in subdivided populations of neurotropical mi-gratory birds in a fragmented temperate forest.Ecology 76: 27-40.

White, P.S. & T.A. Pickett. 1985. Natural disturabanceand patch dynamics: an introduction. pp. In: T.A.Pickett, & P. White (eds.) The Ecology of NaturalDisturbance and Patch Dynamics. Academic Press,Orlando.

Whittaker, R.H. 1977. Evolution of species diversity inland communities. Evolutionary Biology10: 1-67.

Whittaker, R.H. 1995. Communities and Ecosystems.2nd Edition. Mac-Millan Publishing Co., New York.

Wiens, J.A. 1994. Habitat fragmentation: island vs.landscape perspectives on bird conservation. Ibis

137: S97-S104.Williams, P.H., K.J. Gaston & C.J. Humphries. 1995. Do

conservationists and molecular biologists value thedifferences between organisms in the same way?Biodiversity Letters2: 67-78.

Documents

Landscape Analysis 2002