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Ecological Indicators 11 (2011) 220–229

Contents lists available at ScienceDirect

Ecological Indicators

journa l homepage: www.e lsev ier .com/ locate /eco l ind

eview

egional Index of Ecological Integrity: A need for sustainable management ofatural resources

ohammad Imam Hasan Rezaa,b,∗, Saiful Arif Abdullaha,1

Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor Darul Ehsan, MalaysiaDepartment of Botany, University of Chittagong, Chittagong 4331, Bangladesh

r t i c l e i n f o

rticle history:eceived 15 December 2009eceived in revised form 22 July 2010ccepted 22 August 2010

eywords:nthropogenic disturbancesonservation planning

a b s t r a c t

An ecosystem is a complex composition of physical, chemical and biological components. This com-plex system remains in a healthy state if the system can maintain the ecological equilibrium among itscomponents. Anthropogenic disturbances are the prime stressors that affect this equilibrium through cre-ating fragmentation, ecosystem sensitivity, loosening landscape connectivity and disrupting ecologicalintegrity. As different types of ecosystem are interconnected, a comprehensive monitoring and evaluat-ing criteria is needed for measuring its integrity at regional level for conservation planning. A RegionalIndex of Ecological Integrity can be a suitable approach for sustainable management of regional ecosys-

olicy/managementepresentativenessegional scalepatial processes

tem. Therefore, this paper presents (i) the characteristics of ecological integrity, (ii) the spatial processesinduced by anthropogenic stressors and (iii) an approach to develop a composite Regional Index of Eco-logical Integrity (RIEI). The prime objective is to establish a thought and a way to develop a compositeindex of ecological integrity at the regional level. Here, we demonstrate different compositional, struc-tural and functional indicators/indices related to fragmentation, representativeness of protected area,ecosystem sensitivity, and landscape connectivity for the development of a Regional Index of Ecological

Integrity (RIEI).

© 2010 Elsevier Ltd. All rights reserved.

ontents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2202. The characteristics of ecological integrity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2213. Changes in spatial processes due to anthropogenic pressures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2224. The approaches for combating the challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222

4.1. Regional Index of Ecological Integrity (RIEI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2234.2. The work plan for developing an effective RIEI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224

4.2.1. Fragmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2254.2.2. Representativeness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2254.2.3. Ecosystem sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2264.2.4. Landscape connectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

4.3. Calculation and final index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2265. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228

∗ Corresponding author at: Institute for Environment and Development (LESTARI),niversiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor Darul Ehsan, Malaysia.el.: +60 3 8921 4161; fax: +60 3 8925 5104.

E-mail addresses: reza mih@hotmail.com, rezamih@gmail.com (M.I.H. Reza),aiful arif2002@yahoo.com (S.A. Abdullah).

1 Tel.: +60 3 8921 4151; fax: +60 3 8925 5104.

470-160X/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.oi:10.1016/j.ecolind.2010.08.010

1. Introduction

In many parts of the world, ecological integrity has becomea popular approach for conservation planning (Westra et al.,2000; Manuel-Navarrete et al., 2004; Borja et al., 2009). Ecologicalintegrity can be defined as the capacity to support and maintain thebalanced and integrated ecosystem in a particular region (Karr and

ogical Indicators 11 (2011) 220–229 221

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Fig. 1. Self-organization components of a typical ecosystem for the evaluation ofecological integrity. Exergy trapped by the system which used to generate structureand modified energy drives the different functional processes. Anthropogenic activ-ities putting pressure on the window of viability. It may decrease energy capture,storage capacity, cycling, efficiency, heterogeneity and accelerate nutrient loss andwill decrease ecological integrity. If spatial processes like fragmentation, ecosys-tem sensitivity, landscape connectivity of this ecosystem can be measured thus

M.I.H. Reza, S.A. Abdullah / Ecol

udley, 1981; Karr, 1996; Parrish et al., 2003). It is also considereds a capacity and an indication of the degree of self-organizationMüller et al., 2000). Originating from the ethical concept put for-arded by Leopold (1949), ecological integrity has been measured

o assess ecological condition of aquatic and terrestrial ecosystemsAndreasen et al., 2001; Zampella et al., 2006; Hargiss et al., 2008).cological integrity has emerged as a fundamental basis for themplementation of natural resource protection, for example, thelean Water Act (CWA) in 1972 in the United States (Barbour et al.,000) and the Austrian Water Act in 1990 (Moog and Chovanec,000).

The general problem of all ecological analyses and sustainableanagement decision processes is the complexity of the ecosys-

ems (Müller et al., 2000), particularly in the tropics where theiratural forests are losing rapidly (Laurance, 1999; Laurance etl., 2004; Curran et al., 2004). Moreover, due to restricted accesso modern information and communication technologies, localecision makers rely on the expertise of local academics, forestanagers, cattle breeders and/or farmers (Kampichler et al., 2010).

n this context, an approach for the development of an index ofcological integrity has been undertaken to simplify the sustain-ble management paradigm. Many approaches have been proposedor the development of indices of ecological integrity (e.g. Karrnd Chu, 1999; Angermeier and Davideanu, 2004; Ortega et al.,004; Solimini et al., 2008; Rothrock et al., 2008; Borja et al., 2009),ut they are applied to very specific areas of aquatic or terres-rial ecosystems. Till date there is no ecological integrity index toepresent the entire region comprising both aquatic and terres-rial ecosystems (Slocombe, 1992; Andreasen et al., 2001; Borja etl., 2009). Moreover, biodiversity conservation in multi-functional,uman-dominated landscapes needs a coherent, large-scale spa-ial structure of ecosystems (Opdam et al., 2006) where differentypes of ecosystems are nested side by side in a regional contextBailey, 1996). Therefore, it may be justified to measure ecologicalntegrity at regional scale to get a complete picture of ecosystemomposition, structure and function.

While many researchers have suggested the need for a suit-ble index at regional level (Andreasen et al., 2001; Borja et al.,009), thus far no effort has been undertaken to develop suchn approach. Nevertheless, understanding the characteristics ofcological integrity and spatial processes associated with anthro-ogenic stressors is crucial and prerequisite to developing an indexf ecological integrity at the regional level. Therefore, this paperresents (i) the characteristics of ecological integrity, (ii) the spatialrocesses induced by anthropogenic pressures and (iii) an approacho develop a composite Regional Index of Ecological Integrity (RIEI).he prime objective is to establish a thought and a way to developcomposite index of ecological integrity at the regional level.

To achieve the objective, this paper begins with a discussion onhe characteristics of ecological integrity in regional context. Here,e tried to identify the components of ecological integrity, how

ts capacity is related to compositional, structural and functionalttributes of an ecological system and also, their relationship withelf-organization of an ecosystem. In the following section, we dis-uss specifically the spatial processes induced by anthropogenictressors. In this part, we consider the spatial processes that areuitable for assessment of ecological integrity at regional level. Thiss followed by a work plan to develop an approach for Regionalndex of Ecological Integrity (RIEI), and finally some conclusionsre drawn.

. The characteristics of ecological integrity

Leopold (1949) was a pioneer in defining ecological integrity asA thing is right when it tends to preserve the integrity, stability

ecological integrity can also be measured.

Modified after Müller et al. (2000).

and beauty of the biotic community. It is wrong when it tends oth-erwise”. He did not give a clear definition of the term ‘integrity’ inhis article on land ethics, but he initiated a thought on sustainabil-ity. Later the concept was clarified by several works, specifically byKarr and his co-workers (Karr, 1981; Karr and Dudley, 1981; Karrand Chu, 1999), where they defined ecological integrity as “the abil-ity of an ecosystem to support and maintain a balanced, adaptivecommunity of organisms having a species composition, diversity,and functional organization comparable to that of a natural habitatof a region”.

By this definition, the features of ecological integrity includeecosystem health, resilience and self-organizing capacity (seeJoergensen, 1992; Müller, 1998, 2005). This is the feature of a nat-ural ecosystem. An ecosystem is an open system where exergy(total available energy radiated by the solar system to the earth)is entrapped by the system and transferred within metabolic reac-tions (e.g. respiration, heat export) (see Fig. 1). Self-organizedecological systems try to build up ordered structures and storethe imported exergy within biomass, detritus and information (e.g.genetic information), which can be indicated by structural diver-sities (Joergensen, 2000). In a disturbance-free environment, thesystem will advance to a more complicated state of heterogene-ity, increasing species richness and rising in connectedness, andmany other ecological attributes will follow a similar trajectory(sensu maturity of ecosystem, see Odum, 1969). This complexitycan be characterized as the complex chemical, biological, and socialinteractions in an ecological system (Colwell, 1998), which developthrough the multiplicity of interconnected relationships and levels(Ascher, 2001) (see also Fig. 1). So, there is a significant rela-tionship among compositional, structural and functional attributesof an ecosystem. During these synergetic processes, creation ofmacro-structures from microscopic disorder leads to the forma-tion of emergent properties and gradient (Müller, 2005). Thus, the

features of ecological integrity also include ecosystem functions,ecosystem thermodynamics, gradient degradation and ecologicalorientors (Müller and Leupelt, 1998; Joergensen, 2000). Therefore,careful selection of indictors from compositional, structural and

222 M.I.H. Reza, S.A. Abdullah / Ecological Indicators 11 (2011) 220–229

vel. Di

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Fig. 2. Structural characteristics of ecological integrity at regional le

unctional attributes of ecosystem can successfully represent thecological state and integrity of a region.

. Changes in spatial processes due to anthropogenicressures

Several spatial processes occur because of anthropogenicctivities like agriculture, logging, aquaculture and urbanizationAbdullah and Nakagoshi, 2006, 2007; Riley, 2007) (Fig. 2). Suchrocesses are synchronized and proliferated according to the spa-ial and temporal nature and volume of the pressures (Nitschke,008). The initial spatial process to affect naturalness is fragmen-ation of habitat. Habitat fragmentation affects compositional asell as structural and functional aspects of ecosystem (Harris,

984; Franklin and Forman, 1987; Arroyo-Rodriguez et al., 2007).ts effects lead to changes in species composition, community struc-ure, population dynamics, behavior, breeding success and a rangef ecological and ecosystem processes (Laurance et al., 2002; Fahrig,003; Opdam and Wascher, 2004; Henry et al., 2007), for exam-le, pollination, decomposition, nutrient cycling, seed dispersalnd predation (Harrison and Bruna, 1999). Habitat fragmentationestroys links or connectivity between patches of habitat (Fahrignd Merriam, 1994; Foppen et al., 1999); both of its structural con-ectivity (e.g. increasing number of patches, reduction in patchize, distance between patches) as well as functional connectivitydispersal ability of organisms as response to the discrete patches)Taylor et al., 1993; With et al., 1997; Tischendorf and Fahrig, 2000).oss of connectivity may cause loss of genetic diversity (Gibbs,001), create barrier to dispersal (Cramer et al., 2007; Haddad andaum, 1999), species extinction (Foppen et al., 1999; Donovan andlather, 2002) and disruption of biotic interactions (Kruess andscharntke, 2000). Fragmentation and loss of connectivity reducehe quality of the habitat, which eventually increases sensitivity to

isturbances (Nell, 2008). The particular habitat becomes an envi-onmentally sensitive area which loses its ecological capability toupport flora and fauna.

The combination of fragmentation, loss of connectivity andncreasing sensitivity represents the vulnerability of the ecosystem

fferent spatial processes show their impacts on ecological integrity.

(see Penghua et al., 2007). Vulnerability is the state of susceptibilityto harm from exposure to stresses associated with environmen-tal and social change and from the absence of capacity to adopt(IPCC, 2001; Tyler et al., 2007). Severe anthropogenic disturbancesespecially intensive land use change makes the species and alsotheir habitat vulnerable (e.g. White et al., 1999; Jackson et al.,2004; Metzger et al., 2006; Mercer et al., 2007). To protect thenatural landscape from further degradation and to conserve bio-diversity, a protected area system has been established (Timko andInnes, 2009). Policy and management are responsible to determinehabitat representativeness in the protected area system. How-ever, in most cases, the habitats in a particular area or region areless represented by the protected area system (Armenteras et al.,2003; DeFries et al., 2005; Timko and Innes, 2009). All these createdegradation and decrease the capacity of self-organization of theecological system and hamper the integrity of the system (Fig. 2).

4. The approaches for combating the challenges

The components of ecological integrity include ecosystemhealth, biodiversity, sustainability, stability, naturalness, wilder-ness and beauty (Barbour et al., 2000; Andreasen et al., 2001)(see Fig. 3). Ecosystems with high integrity should be relativelyresistant to environmental changes and stresses (Andreasen et al.,2001). Despite some debates and criticism over the last two decades(Soule and Lease, 1995; O’Neill, 2000), the concept of ecologicalintegrity is considered reliable for conservation of natural ecosys-tems (Barbour et al., 2000; Andreasen et al., 2001; Ortega et al.,2004).

It is impossible to measure all the potential components in anecosystem. For example, no two species exist in the same nicheand no single species should be expected to represent the con-dition of an entire ecosystem (Cairns and Van der Shalie, 1980).

Ecological integrity is generally tested with several indictors thatrepresent components of the structural, compositional and func-tional attributes of an ecosystem (Karr, 1981; Noss, 1999; Carignanand Villard, 2002; Müller, 2005). However, in most cases the assess-ment is difficult to understand by the public and stakeholders. In

M.I.H. Reza, S.A. Abdullah / Ecological

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ig. 3. Typical component feature of ecological integrity (biodiversity and beautyepresents stability, sustainability, naturalness, and wilderness).

his circumstance, a composite index can provide a general featuref ecological integrity of an ecosystem (Andreasen et al., 2001). Ineveloping the composite index, many indicators are selected toepresent various components of the ecosystem (e.g. Karr and Chu,999; Andreasen et al., 2001; Carignan and Villard, 2002). Nev-rtheless, prior to this process, it is a prerequisite to review andonstruct the characteristics of the index whether it represents allhe attributes of the ecosystem comprehensively.

.1. Regional Index of Ecological Integrity (RIEI)

A Regional Index of Ecological Integrity must represent theital attributes of the regional ecosystems. Though a set of indi-ators may vary according to the region, the selection must beased on the general characteristics of the regional ecological

ntegrity. This selection process is a vital part in the develop-ent of such index where stakeholders, decision makers and landangers closely need to cooperate with scientists. Andreasen et al.

2001) outlined six characteristics of an effective index of ecologi-al integrity for terrestrial ecosystems, which include multi-scaled,rounded in natural history, relevant and helpful, flexible, mea-urable and comprehensive. Earlier, Riley (2000) also suggestedome properties for index of ecological integrity. These are uni-ersality, probability, sensitivity to changes, simple, inexpensive,nalyzable with existing historical dates, and have wide use. Con-idering all these suggestions with those of Dale and Beyeler (2001)nd the Convention on Biological Diversity (1999), we suggest a setf characteristics for an RIEI (Table 1).

The characteristics of the RIEI are described below:

Multi-scaled: A dynamic and complex ecological system is theorganization of flows, storages and regulations of energy, matter,substances and information. To understand their general featuresand validate the implicit models, ecological components fromcompositional, structural and functional attributes have to betaken into account (Müller, 2005). In a regional context, althoughthe suite of indices may vary from site to site and also region toregion, they are suitable tools to represent the state of complexorganization of ecosystems (Müller et al., 2000). Thus, a RegionalIndex of Ecological Integrity must consider multi-scales to mea-sure the ecological states of a region (see O’Neill et al., 1989;Andreasen et al., 2001).Grounded in history and succession: Both organisms and theirhabitat, successional state, environmental consequences mustfit with the selection of indicators (Carignan and Villard, 2002).

Furthermore, Grumbine (1994) highlighted on maintenanceevolutionary and ecological processes. Considering all the sug-gestions and studies, selection of representing indicators mustrelate histories of organisms, evolution, population dynamics,importance on existence (e.g. endangered, endemism, etc.), and

Indicators 11 (2011) 220–229 223

fitness to the environmental changes. Therefore, the followingcategories need to be considered in the indicator selection fordeveloping a Regional Index of Ecological Integrity.1. Natural history of organisms,2. history of successional attributes and evolution,3. conservation importance (e.g. endangered, endemic, threat-

ened), and4. adaptations to environmental changes.

• Relevant and helpful: For the effectiveness of such effort, the indexmust address endpoints and values that society relates to, such asspiritual, cultural, religious, and esthetic values (see Jüdes, 1998).Ecosystem goods and services (water quality, air quality, floodmitigation, waste treatment), and recreational values and com-mercial values (potentialities of fisheries, timber, tourism andrelated business) (Andreasen et al., 2001) are examples of bene-fits that can accrue from the effort. People (e.g. stakeholders anddecision makers) must understand and realize that the approachis helpful for them with both short-term and long-lasting facilitiesand services (Bossel, 1998).

• Simple and flexible: An index of ecological integrity will be effec-tive if it is simple and understandable to the public, decisionmakers and stakeholders of different hierarchies as they willbe involved in implementation (Andreasen et al., 2001). Theremust be some awareness and capacity building programmes to bearranged to make the people competent to handle such RegionalIndex of Ecological Integrity. So, it must be simple and under-standable for all the personnel involved (Convention on BiologicalDiversity, 1999). Particularly this effort is needed for a regionalscale as the approach required a long-lasting period and a publicinvolvement is important. Moreover, the index must be flexibleto accommodate new relevant information to make the approachfit with the changes (Dale and Beyeler, 2001).

• Adjustable: A regional landscape is wide and every ecosystemwithin it is interconnected by ecological attributes, e.g. compo-sitional, structural, and functional (Müller, 2005). Furthermore,the structural, compositional and functional components of theregion have a long interactive chain with the other region of itssurrounding. That is why a Regional Index of Ecological Integrityshould be adjustable with its surrounding ecoregions by eco-logical and landscape attributes (Riley, 2000). Uses of airborne,satellite data for measuring different components of the indexhave the ability to adjust ecological attributes in a wider range.Remote sensing and GIS technology will make the task easier anduser friendly.

• Measurable and cost-effective: The index will be a measurable one.Land managers and decision makers must know how to use itand interpret the results. Capacity building programme can makethe land managers competent to handle different techniques andalso to measure the index. However, it will be cost-effective toquantify using experts from outside (Convention on BiologicalDiversity, 1999; Riley, 2000). Changes in the ecological attributescan be accommodated with the approach.

• Policy relevance: For an effective index of ecological integrity inthe regional scale, a set of indicators must reflect policy rele-vant perspectives. There must be indication for policy relevance,progress towards policy targets, and understandability of theindicators (EEA, 2005).

• Comprehensive: A useful Regional Index of Ecological Integritymust be comprehensive, considering compositional, struc-tural and functional attributes of the ecosystems (Noss, 1990;Lindenmayer and Franklin, 2002; Müller, 2005). For each candi-

date metric, the important point(s) to consider in the selectionprocess as listed in Table 2 must be taken into account. Thoughthe traditional approach for environmental management is basedon structural attributes, but an effective approach must be linkedwith functional ecosystem features, such as energy and matter

224 M.I.H. Reza, S.A. Abdullah / Ecological Indicators 11 (2011) 220–229

Table 1Comparison of the modified characteristics of a proposed Regional Index of Ecological Integrity (RIEI) with Riley (2000) and Andreasen et al. (2001) proposed indices forlandscape level.

Riley (2000) Andreasen et al. (2001) Our proposal for RIEI

1. Universal 1. Multi-scaled 1. Multi-scaled2. Portable 2. Grounded in natural history 2. Grounded in history and succession3. Sensitive to changes 3. Relevant and helpful • Natural history of organisms4. Simple 4. Flexible • History of successional attributes and evolution5. Inexpensive 5. Measurable • Conservation importance (e.g. endangered, endemic)6. Adjustable with historical data 6. Comprehensive • Adaptations to environmental changes7. Wide use • Composition 3. Relevant and helpful

• Structure 4. Simple and flexible• Function 5. Measurable and cost-effective

6. Adjustable7. Policy relevance8. Comprehensive

• Composition• Structure• Function

Table 2Critical points to evaluate a candidate metric.

Candidates/category Important information for consideration

Components of ecological integrity Whether the components suited with the basics of ecological systems?e.g. composition, structure, and function

Scale Is the metric sufficiently addressing the regional aspects?Is temporal scale is sufficient to address historical and ecological attributes?

Comprehensive Do the components sufficiently represent the vital aspects of regional system, both spatial and temporal?

Relevance Whether the metrics relevant with the objectives of the assessment?

Usefulness Are all the components selected as candidate metrics able to represent the vital and important characteristics ofregional ecological integrity? They must relate to the science, policy, ethics and belief of the particular region

Aquatic/terrestrial Does the metric provide information on the linkage between terrestrial and aquatic ecosystems in the region?

Feasibility and measurability Can the metric be quantified using available scientific technology?Does it cost-efficient and easy to handle, and have sufficient longevity?Whether the baseline data is available (from national, regional or international source) and can store for long-term?Whether some capacity building programme can make the stakeholder competent to use it?Will the relevant agency be able to handle continuous monitoring programme?Is/are the endpoint(s) meet the expectations of the specific objectives?

etric

endpo

r

1

2

Ease of interpretation Are changes and results in the m

Adjustability Whether the measurability andwith the adjacent ecoregions?

flow and cycling, storage and losses, information dynamics andresource utilization (Müller et al., 2000).

Some of the important indicators which can be considered asepresentatives of these three components are listed below:

. Composition: Compositional features represent an ecosystemand a set of vital species can give the scenario of that particu-lar area (Noss, 1990). These metrics focus on biological entitieslike keystone species that dominate ecosystem processes, sen-sitive species or threatened species. Selection of candidates ishighly context-dependent and must vary from region to region.Furthermore, expert biological knowledge and natural historyis important for appropriate judgment (Andreasen et al., 2001;Karr and Chu, 1999). Focal species, indicator species, keystonespecies, exotic or invasive species, and endangered species canbe considered as suitable compositional metrics.

. Structure: Indices based on habitat measurements (structural)might be more cost-effective than the indices based on organ-

isms (compositional). Several landscape metrics can be usedto quantify the structural condition in a region. For exampletotal number of patches, mean patch size, mean patch distance,patch size standard deviation, shape index, and proximity index.The functional relationship among patches defined as landscape

value can be interpreted by the public and decision maker?

ints of the metric is adjustable and meaningful in interpretation and evaluation

connectivity (Taylor et al., 1993; With et al., 1997). It can be mea-sured in two aspects; structural and functional. The former isbased on landscape structure and the later considers organism’sbehavioral responses to landscape elements. In addition to thebasic spatial pattern, structural metrics might also include per-cent cover and habitat available for indicator species (Andreasenet al., 2001), which can make a relationship with structural andcompositional variables.

3. Function: Functional metrics concerns vital processes, such asbiogeochemical, hydrological, ecological and evolutionary pro-cesses. They may be classified as biotic, abiotic or combination ofbiotic and abiotic processes. Some potential functional candidatemetrics for regional scale are listed as follows:

(i) Biotic: competition, biomagnifications, predation.(ii) Abiotic: soil erosion, soil acidification, land forms.

(iii) Combined: succession, biodegradation, decomposition.

4.2. The work plan for developing an effective RIEI

Selection of appropriate indices in the development of aRegional Index of Ecological Integrity requires very careful judg-ment. We consider four major components to evaluate theecological integrity that are mostly relevant to structural, func-tional and compositional aspects of the regional ecological system

M.I.H. Reza, S.A. Abdullah / Ecological Indicators 11 (2011) 220–229 225

Table 3Suggested set of metrics with useful tools for the development of RIEI.

Major components Set of metrics/indicators Scale/useful tools

Fragmentation Number of patches, patch density, total patch area,mean patch size, patch perimeter, mean patch corearea, patch shape index, mean nearest neighbour

FRAGSTATS,a V-LATEb in GIS platform

Representativeness Percent representation of the surrounding ecosystem,percent representation of total area of same ecosystemin the region

According to the World Conservation Union

Ecosystem sensitivity Forest interior, riparian area, buffer zones, gap withinpatches, relative road density

Landscape Analysis in ArcGIS 9x

Sensitivity of soil erosion, land desertification, soilacidification, salinity or siltation

USLE, USDA, UNEP proposed methodology

Landscape connectivity Structural connectivity: patch cohesion, proximityindex, nearest neighbour distance, fractal dimension

Landscape indices in FRAGSTATS or V-LATE

Functional connectivity: graph theory, using According to Bunn et al. (2000) and Ferrari et

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a FRAGSTATS (http://www.umass.edu/landeco/research/fragstats/fragstats.html)b V-LATE (http://arcscripts.esri.com/details.asp?dbid=13898).

see Fig. 4). Moreover, remotely sensed data or other digitizedata which have been proposed as candidate indices have a bet-er chance to suit with the index due to its broader aspects andvailability (Andreasen et al., 2001). Furthermore, ability of rela-ively fast acquisition, accommodating capability of different layerse.g. climate, geology, physiography, soil, hydrology, vegetation,nd biogeography), outstanding performance in visualization, suit-bility to cope with GIS technology make this data very useful toolve the complexity of such ecological analyses (Chuvieco, 1999;howdhury, 2006). Table 3 represents some selected indices thatan be used to quantify different aspects of the proposed RIEI.owever, one needs to select a set of indices directly relevant

o a target region and the set may differ according to differ-nces in regional ecological compositions. Moreover, the followingub-sections describe in more detail how we can use the majoromponents in analyzing different indices.

.2.1. FragmentationFragmentation measures, both spatially and temporally, the

xtent of anthropogenic pressures on the regional natural condi-

ion. There are several indices that measure the degree of landscaperagmentation, such as density of patch, mean patch size, patcherimeter and patch shape index. Fragmentation of landscape cane measured from the value 0 to 1, where 0 indicates the land-

ig. 4. Schematic flow chart showing different components chosen for the devel-pment of Regional Index of Ecological Integrity (RIEI). Fragmentation, ecosystemensitivity, connectivity and representativeness of protected areas are the com-onent indicators of stressors on the regional ecosystems. Ecological integrity ofregion can be measured using different indices related to their qualitative and

uantitative attributes.

al. (2007); using ArcRstats or CS22 software

scape has not been destroyed at all and 1 implies the landscape hasbeen totally destroyed. The degree of fragmentation which can becalculated for landscape is as follows (Penghua et al., 2007):

FR = MPSNf − 1

Nc

where FR is the fragmentation for the landscape, MPS is the meanpatch size which is calculated by the average area of all patchesdivided by the minimum patch area in landscapes. Nf stands forthe total number of patches in the landscape; and Nc is the ratioof the whole area of landscape to the area of minimum patch size.Furthermore, effect of fragmentation on key species can also bemeasured and eventually accommodate with the candidate met-rics. So, fragmentation indices represent structural phenomenonas well as their relations with the compositional attributes too.

4.2.2. RepresentativenessRepresentativeness of protected areas will quantify the status

and effectiveness of policy, management and planning for sustain-able environment and development [emphasized by EEA (2005)for policy relevance]. To quantify the representativeness of pro-tected areas, an ecosystem map of the target region has to bedeveloped. An ecosystem map is a vital part to represent ecolog-ical pattern and processes in a region which enables the use ofecosystem occurrences as a robust spatial unit of analysis for varietyof applications, including conservation planning, climate changeeffects, resource management, and analyses of the economic valueof ecosystem benefits (see http://rmgsc.cr.usgs.gov/ecosystems/,and also http://www.earthobservations.org/). So, the ecosystemswill be geospatially delineated as facets of the landscape generatedthrough biophysical stratification by bioclimate, biogeography,lithology, landforms, surface moisture, and land cover. Once anecosystem map is being developed, it has to be overlaid with adigitized map of the protected areas of that region. The ecosys-tem composition of the protected areas and their representationof coverage as a percentage compared to the total area of relatedecosystem in the study area can be calculated. Generally, if 10%of a certain ecosystem is protected, it can be considered as well-represented in the protected area system (World ConservationUnion, 1992; World Resources Institute, 1994; Noss, 1996). Repre-

sentativeness of protected areas must be compared, both spatiallyand temporally, with the degree of fragmentation. Otherwise,current representation status of an ecosystem may show higherpercent of representation than the previous status of that ecosys-tem in a fragmented landscape. Representativeness of a protected

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rea can be calculated with following formula:

Pi = Pi

Le× 100

here RPi stands for representativeness of protected area i; Pi rep-esents the total area for the protected area i and Le is the total landrea of that particular ecosystem subjected to the representationy the protected area i. This index basically represents policy andanagement perspectives. Moreover, it also represents the feature

nd dynamics of the regional ecosystems.

.2.3. Ecosystem sensitivityEcosystem sensitivity indices can be another source of indicators

hich can be interpreted with the landscape pattern and may giveconsiderable explanation of anthropogenic disturbance regime.

ensitivity to land desertification, soil erosion, soil acidification,alinity or siltation can be measured. For example, sensitivity to soilrosion can be measured based on the Universal Soil Loss EquationUSLE), which is an erosion model that predicts soil loss as a func-ion of soil erodibility (K-factor), as well as topographic, rainfall,egetation cover, and management factor. A soil erosion classifica-ion needs to be developed for the region and then the sensitivity ofoil erosion (weathering) can be measured through the followingPenghua et al., 2007):

Wi =n∑

j=1

Bij

BiSij

here SWi stands for the sensitivity to soil erosion of the landscapeype i; Bij represents the area that landscape i distributes on j sensi-ive level of soil erosion. Bj is the whole area of landscape type i; Sijs the weight of landscape type j to i sensitive level of soil erosion; js the sensitive level of soil erosion; i is landscape type; and n is theotal number of landscape types. On the other hand, some land-cape indices such as, forest interior, riparian area, buffer zones,elative road density can also be measured and after weighting theyan be used for the sensitivity analysis (Canaan Valley Institute,001). A sensitivity map can be developed through using Analyticierarchy Process (AHP) in the GIS platform (weighted overlay)hich can give a spatially explicit feature of the ecosystem sensi-

ivity (Saaty and Vargas, 1991). So, this component represents vitalrocesses and also their relation with compositional and structuralttributes in the regional scale.

.2.4. Landscape connectivityLandscape connectivity is ‘the degree to which the landscape

acilitates or impedes movement of organisms among resourceatches’ (Taylor et al., 1993). Natural and human induced damageo habitats can alter spatial relationships between habitat patches.herefore, the susceptibility of spatial relationships to patch lossnd associated degradation to connectivity is an important factoretermining ecological integrity of a region (Matisziw and Murray,009). However, landscape connectivity can be measured in twospects, structural and functional.

Structural connectivity: Structural connectivity is often measuredusing the Euclidian shortest distance. It has been successfullyused in the quantification of simple to complex landscape con-nectivity features (Moilanen and Nieminen, 2002). The following

formula can be used for the measurement of structural connec-tivity (Moilanen and Hanski, 2001)

S =n∑

i=1

Aci

∑j /= 1

D(dij, ˛)Abj

Indicators 11 (2011) 220–229

where Ai is the area of patch i (=1, 2, . . . , n); parameters b and crepresent scale area, patch i being the target and patch j beingthe source of migration; D(dij, ˛) scales the effect of distance onmigration rate; dij is the distance between patches i and j and ˛is a vector of species-specific parameters describing the dispersalability of the species. This formula can be modified according tothe need of assessment (Kindlmann and Burel, 2008).

• Functional connectivity: Functional connectivity considers thebehavioral responses of organisms to landscape pattern. It canbe measured as mean probability of moving between pairsof patches that is known as emigration and dispersal success(Tischendorf and Fahrig, 2000; Taylor et al., 2006). Graph the-ory often is used to quantify functional connectivity (Bunn et al.,2000; Ferrari et al., 2007). It is a multidirectional graph represen-tation that allows for multiple pathways between nodes (patches)and, which may be a realistic depiction of connectivity with ref-erence to the actual movement of wildlife.

Ti =n∑

k=1

WikAk

(Ai

A

)

where Ti represents functional connectivity; Ai is the area ofthe focal patch (or fragment), Ak is the area of a single patchin the study area; A is the mean area of all patches, andWik describes the interaction between patch k and all otherpatches i. Moreover, recently developed software, for example,ArcRstats (http://www.nicholas.duke.edu/geospatial) or ConeforSensinode 2.2 (CS22) (http://www.conefor.udl.es/) can be usedto quantify connectivity using a graph theoretical approach. Theyidentify the least cost paths among core habitat areas from whichnetwork centrality metrics can be calculated. ArcRstats (version0.7, released 27.06.2006) required two inputs, habitat patches(e.g. core areas) and a cumulative distance surface (see Urbanand Keitt, 2001; Goetz et al., 2009).

4.3. Calculation and final index

Developing a single value through integrating all the metricsis the final step of the proposed RIEI. This step is a vital part of thewhole index which will simply represent the feature of the regionalecosystem. All indices from the major components (e.g. fragmenta-tion, landscape connectivity) are weighted in the final calculation.Principal component analysis (PCA) can be a suitable tool for reduc-tion of metrics and also to reduce the redundant information inorder to avoid unnecessary complexity and redundancy. However,in some cases semantic analysis or choice of indicators accord-ing to the expert judgment may be applied. Multivariate analysisis another statistical tool to choose suitable metrics from thelist.

Indices from each major component will be measured and theywill be calculated for individual indices. For example, indices fromthe landscape connectivity would be weighted and standardizedfrom which suitable indices will be selected (considering Table 2).Then, they would be used to calculate connectivity index, which isscored between 0 and 4 (where 4 is excellent and 0 is the worst).Similarly, other components can be developed into an index fortheir own category. Degrading components can be calibrated such away that scoring is reversed to weight in a similar fashion [e.g. from0 to 4 (where 4 is not degraded and 0 indicates fully degraded)].However, selection of metrics based on expert opinion, experts are

human being, and their decisions are influenced by personal expe-rience, institution, heuristics and bias (Kampichler et al., 2010).Uncertainty or vagueness of rating the importance of every possibleexplanatory variable might motivate the experts to choose a highnumber of indicators. A sensitivity analysis can be used to assess

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he sensitivity of the index to the weights used for each index. Theensitivity can be checked by calculating a coefficient of sensitivityCS) based on the standard economic concept of elasticity, that is,he percentage change in the output for a given percentage changen an input (Mansfield, 1985). The calculation of the coefficient ofensitivity is as follows (see Abdullah and Nakagoshi, 2007):

S = (XIj − XIi)/XIi(WTjk − WTik)/WTik

here XI is a measured index value, WT is the adjusted value ofeight given to the respective metrics, i and j represent the initial

nd adjusted values, respectively, and k represents the indicatoromponent. If the value of coefficient of sensitivity is less than one,hen the XI value (output) is considered to be robust to changes inhe weight of metric component (input).

Finally, Regional Index of Ecological Integrity can be measuredsing the formula:

IEI = ˛ FI + ˇ SI + � CI + ı RI

here RIEI is the Regional Index of Ecological Integrity, FI, SI, CI,nd RI stand for fragmentation index, sensitivity index, connec-ivity index and representativeness index, respectively; ˛, ˇ, � ,nd ı represent weight for the values. Weighting for such valueill derive from their relative importance to ecological integrity

nd also related to the management objectives of the region. Theemaining variables of the final index are simple and straightfor-ard, and understandable having no math anxiety.

The sensitivity of RIEI to the weight component can be measuredsing the same procedure as the single indices of fragmentation,ensitivity, connectivity and representativeness. However, spa-ially explicit mapping of each component index and a final index

ight give a real feature which may be easily interpreted by theand managers and stakeholders. Moreover, an additional repre-entation like pie chart or other graphic features can be constructedf it needs to demonstrate the exact scenario in some cases, espe-ially in the case of the vital individual features. For example, datarom endangered species or eutrophication of water body.

Testing of metrics is a necessary step in choosing appropri-te methodology for the index. Moreover, it is also necessary tovaluate its performance through applying the index in a num-er of sites, ranging from undisturbed to degraded areas. Simplestethod is required for analysis, because the index must commu-

icate to decision makers and the public. Though, there might berisk of avoidance of some potential problems of the real-world

pplication which may not be calculated through the proposedophisticated approach. These problems can be solved through aesting for a period of time. Critical questions of utility and feasi-ility can be answered and limitations can be sorted. And, througholving such questions, limitations and problems, the index couldet reliability and applicability.

. Conclusions

Ecosystem will continue to degrade unless we take proper policyeasures for preventive and restorative strategies to achieve the

ealth and integrity of regional ecosystems (Rio Declaration, 1992;ranklin, 1993; Rapport et al., 1998). Under such circumstances anndex of ecological integrity, which needs to be developed, mightive a valuable support to the policy makers for sustainable man-gement of natural resources (Andreasen et al., 2001; Müller, 2005;

iemeijr and de Groot, 2008). In fact, during the last decade, thereave been substantial scientific advances in the development of

ndices, with an attempt to measure the ecosystem integrity (Borjat al., 2009). Though many of them are successful for some smallcale area, but no index of ecological integrity exists up to date for

Indicators 11 (2011) 220–229 227

a regional level comprising both terrestrial and aquatic ecosystems(Slocombe, 1992; Andreasen et al., 2001; Borja et al., 2009).

The proposed Regional Index of Ecological Integrity (RIEI) is anattempt to develop a suitable approach for assessing ecological con-dition at regional level. This effort tries to include a possible setof indicators to make the index multi-scaled, but useful, simple,flexible and comprehensive on the one hand, and it will be measur-able, cost-effective and policy relevant on the other. In this context,understandability of the approach was emphasized as land man-agers and policy makers will be the primary customers (Andreasenet al., 2001).

In this approach, indicators or indices from four majorcomponents, i.e. fragmentation, ecosystem sensitivity, landscapeconnectivity and representativeness of protected areas were sug-gested. The combination of landscape pattern (e.g. fragmentationand connectivity) and ecosystem sensitivity is able to representecological vulnerability of a region (Penghua et al., 2007). So,we do not measure vulnerability separately which will simplifythe approach and will make the process comparatively easier tomeasure. The proposed indicators are representing the composi-tional, structural and functional attributes of ecosystem; moreover,representativeness of protected areas represents policy and man-agement perspectives. Most of the indicator/indices under theproposed components should be based on remotely sensed satel-lite data and other digitized data which might be suitable for thedevelopment of the index (Andreasen et al., 2001; Ortega et al.,2004; Borja et al., 2009). Modern and available techniques can beused to quantify the indices (for example, GIS softwares). Further-more, a number of newly required indices can be incorporated inthe index due to changing circumstances, which may make theindex measurable, flexible and adjustable. Representativeness ofprotected area will cover the policy relevance features which con-stitute an important part of indicators for sustainable management(EEA, 2005). The proposed index is combining both landscape andenvironmental attributes for ecological integrity thus it is broaderthan many other approaches for biological integrity (also suggestedby Stevenson and Pan, 1999; Zampella et al., 2006).

Practically, it must be mentioned that all the various compo-nents of an ecosystems cannot be encapsulated within a singleindex (Price et al., 1999). So, there is a risk of ignoring some impor-tant issues in the region through this methodology. Because theindex emphasizes the simplicity and understandability as it mustcommunicate to decision makers and the public. However, careful-ness in selection procedure may minimize the risk. On the otherhand, it is expected that the index should be bulletproof, and theindex would have to be site, problem and scale-specific (Andreasenet al., 2001). The task is difficult as there are a lot of expectations tomeet for such an index (Karr and Chu, 1999) but at the same timegrowing demand for it may make the task effective (Barbour et al.,2000).

In conclusion, this paper has outlined a possible way to developa Regional Index of Ecological Integrity which might be a usefultool for decision makers for sustainable management of naturalresources at regional level. The challenges are also worth consider-ing so as to develop such an index because there is no value of theapproach without involvement of land managers and stakeholders.They may need instant result, though there is a lack of consensus onthe concept and feasibility of a regional index. But, the beginningof research and testing on such index may attract them and alsomay build a basis of reliability of RIEI. A continuous effort will beneeded to validate and incorporate changing features in the index.

A long-lasting research work on ecological attributes can give a pos-itive input to the index. Local universities have the opportunity andcapability to play a positive role in such perspectives. Therefore, thiseffort may be included in similar efforts in sustainable managementof natural resources, particularly in the regional context.

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28 M.I.H. Reza, S.A. Abdullah / Eco

cknowledgements

The authors would like to thank two anonymous reviewers forany constructive comments, suggestions and insights to improve

his manuscript. We are very much thankful to the Ministry ofcience, Technology and Innovation (MOSTI), Malaysia for theirupport and funding for this research work through the researchroject: Science Fund 04-01-02 SF-0378 entitled “Landscape Eco-

ogical Assessment of Protected Areas in Peninsular Malaysia forustainable Management Planning”.

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