Conservation Managementin a Changing World

Albert S. van Jaarsveld*, Guy F. Midgley, Robert J. Scholesand Belinda Reyers

AIACC Working Paper No. 1December 2003

*Corresponding Author. Email address: asvanj@sun.ac.za

An electronic publication of the AIACC project available at www.aiaccproject.org.

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CONSERVATION MANAGEMENT IN A CHANGING WORLD1

Albert S. van Jaarsveld1, Guy F. Midgley2, Robert J. Scholes3 and Belinda Reyers1

1Department of Zoology, University of Stellenbosch, Private Bag X1, Stellenbosch 7602, South Africa. E-mail:asvanj@sun.ac.za; breyers@sun.ac.za

2Climate Change Research Group, Ecology and Conservation, National Botanical Institute, Private Bag X7,Claremont, 7735, Cape Town, South Africa. E-mail: midgley@nbict.nbi.ac.za

3CSIR Division of Water, Environment and Forest Technology, Box 395, Pretoria 0001, South Africa. E-mail:bscholes@csir.co.za

ABSTRACT

Much of modern conservation practice emanates from a preservationist agenda that is poorly equipped to addressmany of the realities confronting the discipline. The challenges confronted by conservation practitioners andplanners in a rapidly changing and complex world require a more explicitly defined risk management approach. Theprimary threats to biodiversity are understood, and include: anthropogenic land transformation, climate change,invasive species and over-exploitation. Proximate shifts in biodiversity distribution patterns will also alter the valueof existing conservation estates. Although systematic conservation planning traditionally adopts a static view of life,innovations to incorporate altered biodiversity distribution scenarios explicitly into planning frameworks are rapidlydeveloping. Despite this sensitivity to the dynamics of the biodiversity estate, conservation planning does not yetfully encapsulate the complexity of the task at hand. We propose that the adoption of a risk assessment approach tosystematic conservation planning can strengthen its impact and value. This will require a capacity to translatebiodiversity value and threat statements into common currencies for assessing both the conservation value ofplanning units as well as the probability of their loss. Risk assessment, by virtue of its use of the notion ofprobability provides one potential tool for achieving this objective while expanding the ability of the discipline todeal with uncertainty, a critical need when faced by threats such as climate change.

INTRODUCTION

The conservation of existing biodiversity patterns and processes is considered a sufficiently daunting task byconservation biologists (Margules & Pressey 2000; Pimm 2002). However, the realities of our modern world implythat conservation should be tackled against the backdrop of changing land uses and other human mediatedecosystem changes, including climate change (Cowling 1999; Hannah et al. 2002). This increased complexity raisesthe challenges posed to the discipline of conservation biology considerably and means that we will increasingly bedealing with a moving, complex and adaptive system.

Although the bulk of conservation planning to date has adopted a more static view (see Margules & Pressey2000), conservation planners are not blind to the dynamic nature of the challenge facing the discipline. A number ofmore recent developments in the field have made important strides towards establishing a more coherent frameworkfor conserving a dynamic biodiversity estate. These initiatives have focused largely on representing biodiversitypatterns, biodiversity processes (ecological and evolutionary) and altered species distribution patterns. Thesedevelopments will be reviewed, together with a brief explanation of the state of the art and the most salient featuresof these recent advances. This will serve as an introduction to a conceptual barrier confronting the discipline thatneeds to be resolved in order to continue the current rate of progress. We propose that a more explicit riskassessment approach towards conservation planning may add significant impetus to this rapidly developingdiscipline.

It is not possible to cover the full spectrum of conservation management in a single paper, but the principlesand issues emphasized here will hopefully illustrate the main challenges in taking a dynamic view of the future.

1 Reprinted from N. Allsopp, A.R. Palmer, S.J. Milton, K.P. Kirkman, G.I.H. Kerley, C.R. Hurt, and C.J. Brown,editors, Proceedings of the VIIth International Rangelands Congress, 26th July – 1st August 2003, Durban, SouthAfrica, ISBN Number: 0-958-45348-9, with permission from the publisher. This paper reports on results fromresearch supported in part by grant number AF04 from the AIACC project.

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PRINCIPLES OF SYSTEMATIC CONSERVATION PLANNING

The principles and advantages of systematic conservation planning are now well documented in the literature (forreviews see Pressey et al. 1993; Ferrier 1999; Margules & Pressey 2000). In short, systematic conservation planningis a ‘minimum set’ procedure that aims to represent chosen biodiversity features as conservation goals. It providesplanners with numerous options for achieving these conservation goals (flexibility) and for prioritising areas of highconservation value (irreplaceability). All of this can be accomplished on an interactive platform increasingly used bydecision makers to review the consequences of land-use permutations across planning regions (e.g. C-Plan software- Pressey 1998; Cowling and Pressey in press). Systematic conservation planning follows six distinct stages(Margules & Pressey 2000):

• Compile biodiversity data for planning region• Identify conservation goals• Review existing protected area network• Select additional conservation areas• Implement conservation areas• Maintain the required attributes of conservation areas

The stages are used in an iterative manner to maximize the representation and persistence of biodiversity features.The goal of representation is always limited by the availability of information, the choices of biodiversity surrogatesand the specified conservation goals. However, representation is not a sufficient basis for a reserve network. Designfeatures that maintain natural processes and viable populations (e.g. size, connectivity, gene flow) are typicallyincluded to ensure the persistence of biodiversity features within identified networks (Noss et al. 2002). In addition,external threats are also actively avoided when identifying protected area networks (Margules & Pressey 2000;Wessels et al. 2003). Another and intermediate objective is to retain biodiversity features in the landscape untilreserves can formally be established. It may take years or even decades for conservation network blueprints tobecome fully implemented (Cowling et al. 1999). The relationship between the conservation value of sites (theirirreplaceability) and their vulnerability to external threats can be used to determine the most appropriateimplementation sequence to maximize the retention of biodiversity features in the landscape prior to final networkimplementation (Pressey et al. 1996; Cowling et al. 1999; Pressey & Taffs 2001; Noss et al. 2002 – see Fig. 1).

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Figure 1. A traditional biodiversity irreplaceability and vulnerability trade-off space generated using C-plan software (Pressey1998) within the Gariep Basin of South Africa. The figure illustrates the vulnerability to land use change of the grids as well astheir value in reaching a conservation goal of representing 10% of the pre-European extent of the vegetation types. Thevulnerability to land use change is determined by the grid cells average suitability for dryland cultivation from 1 not suitable to 7very suitable. Those areas that are highly irreplaceable and most vulnerable are usually prioritized for rapid implementation.

Representing biodiversity features

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The types of biodiversity features included in conservation goal setting exercises are also continually expanding.Initially the focus was almost exclusively on the conservation of identified biodiversity patterns such as species orvegetation types (Kirkpatrick 1983; Margules et al. 1988; Rebelo & Siegfried 1992; Pressey et al. 1993; Lombard1995). More recently biodiversity features that represent ecological and evolutionary processes (Moritz & Faith1998; Cowling et al. 1999; Fairbanks et al. 2000; Desmet et al. 2002; Rouget et al. in press) or even viablepopulations of species (Noss et al. 2002) have been incorporated. For example, Cowling et al. (1999) used a varietyof spatial surrogates for important ecological and evolutionary processes in the Succulent Karoo, South Africa.These included sand movement corridors, untransformed river basins, edaphically differentiated habitats, minordrainage basins in a quartz field and climatic gradients. In another study of avian distributions in KwaZulu-Natal(South Africa), Fairbanks et al. (2001) used climate variables to identify gradients in growing season temperatureand rainfall seasonality as well as an aridity gradient across the province. These environmental variables were foundto affect bird assemblage structure across the region. Subsequently, a systematic conservation planning approachthat preferentially samples species in areas along these environmental gradients and at points where high speciesturnovers were encountered was used. This was aimed at representing important ecological transition zones and theirlikely future movements under conditions of climate change (Fig. 2).

Figure 2. (a) calculated Morans’ I spatial autocorrelation values along two environmental gradients in KwaZulu-Natal, (b)species richness conservation area selection output, and (c) species richness and beta-diversity algorithm output that selects forareas of high species turnover along environmental gradients (from Fairbanks et al. 2001).

This continual expansion of the types of biodiversity features included in systematic conservation planning is part ofthe natural progression of the discipline (Cowling & Pressey in press), and is ultimately aimed at capturing the fullcomplexity of nature’s hierarchy (Noss 1994) in protected area systems. The expansion of the variable typesincorporated into systematic conservation planning exercises is inevitable and necessary, and we can expect thistrend to continue into the future.

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DEALING WITH BIODIVERSITY THREATS

The avoidance of potential biodiversity threats where appropriate (Chown et al. in press; Wessels et al. 2003; Reyersin press) or prioritizing areas where threats are most pressing (Pressey et al. 1995; Freitag et al. 1998; Cowling et al.1999; Pressey & Taffs 2001) are both important elements of a goal oriented strategic conservation plan. Moreover,the types of threats faced by the global biodiversity estate are well documented and have not deviated significantlyfrom the original “evil quartet” (Diamond 1975), namely habitat change, overkill, invasive species and chains ofextinction. The most significant addition to this list is possibly climate change that acts as a catalyst for many of theabove changes in biodiversity distributions (see Walther et al. 2002; Parmesam & Yohe 2003; Root et al. 2003).Procedures and methods for assessing the threats to species have been established for some time (IUCN 1994) andcontinue to evolve (Gardenförs 2001). Procedures for assessing the threats posed by landscape changes are nowfrequently employed (Balmford et al. 2002; Wessels et al. 2003; Chown et al. in press). Considering theanthropogenic nature of the threats to biodiversity also implies that there should be some overlap between humanand biodiversity land-use requirements. This suggested overlap has been confirmed in both broad scale and finescale studies (Balmford et al. 2001; Chown et al. in press). These studies confirm that both humans and otherspecies tend to select areas of high rainfall and high primary productivity across African landscapes. This suggeststhat threat avoidance is not always going to be easy and underscores why the rapid conservation of areas of highconservation value (irreplaceable) and vulnerable biodiversity features is an essential conservation tactic (Pressey &Taffs 2001).

The numerous guises of biodiversity threats pose a particular challenge to conservation planning (Cowlinget al. 1999). For example, threats may be species specific (e.g. demographic drivers, threatened breeding sites), theymay transform landscapes (agriculture and forestry) or disrupt ecosystem or evolutionary processes (migratoryroutes, flooding regimes, gene flow). This broad range of biodiversity threats that have to be captured in a planningexercise, and the very specific manner in which each of these impact on biodiversity features from across nature’shierarchy (Noss 1994), means that we soon transcend the ability of simplistic vulnerability statements to capture themultidimensional concept of “biodiversity threat” or vulnerability. The scope of this problem increases rapidly whenthe complexity of biodiversity features incorporated into systematic conservation goals is increased (e.g. pattern andprocess). The challenge precipitated by this emergent complexity when the sampled features are increased forms thefocus of this paper.

However, despite these problems, threat is systematically treated in conservation planning exercises. Thealgorithms employed to identify potential reserve networks are now capable of avoiding identified threats (e.g.stands of alien vegetation or transformed landscapes – Wessels et al. 2000) as well as potential future threats such asareas that contain significant stands of unused arable land or land with mining potential (Wessels et al. 2003; Reyersin press). But mechanisms for dealing effectively with more complex notions and permutations of biodiversity threatwhen setting conservation goals still evade us (see Noss et al. 2002). Cowling et al. (1999) previously articulatedthis dilemma:

“When conservation goals deal with both pattern and process, as is the case here, there are no establishedways of comparing the risks of alternative approaches to implementation. For example, how should the

outright loss of five RDB [Red Data Book] species or a 20% loss of the target for a land type be comparedto the effect of a new mine covering 100 ha or a sand corridor, or the narrowing of a migratory pathway

for ungulates.” (from Cowling et al. 1999)

The essence of this problem lies in the different “currencies:” that are used to express and measure these variousbiodiversity threats and vulnerabilities. One potential solution is to find a common biodiversity currency; not atrivial or new challenge. The attempts by resource economists to translate all of biodiversity into a single monetaryvalue assessment have progressed in interesting and innovative ways (see Costanza et al. 1999). However, skepticsremain unconvinced that this approach will lead to significant advances (Pimm 1999). Considering the problemsassociated with developing a common currency approach for biodiversity we suggest that an alternative route toresolving this multidimensional biodiversity threat currency problem in conservation goal setting exists, namely theadoption of a risk assessment approach. But first, we will briefly demonstrate the nature of this emergentmultidimensional biodiversity threat problem, with reference to a particular biodiversity threat: climate change.

THE CONSERVATION OF MOVING TARGETS

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The relative stability of global climate during the last few millennia of the Holocene, the short history of humantechnological society, and the short duration of human lifespan together provide a false impression of a relativelystable natural environment within which conservation efforts are embedded. The analysis of atmosphericcomposition and global temperature derived from deep ice cores (Petit et al. 1999) has shattered that illusion, butthis revolution in understanding has not yet been effectively incorporated in the theory and practice of conservation.In essence, the Holocene represents an unusually warm and stable climate in relation to the past two million years atleast (the Pleistocene), during which this and other similar warm interludes tended to last only some thousands ofyears between glacial periods lasting several tens of thousands of years.

Much evidence now suggests that biota responded globally most rapidly to these extensive climate changesby shifting geographic range (Graham & Grimm 1990, Hewitt 2000). It appears that species from areas of high ratesof past climate change possess a high degree of vagility (Dynesius & Jansson 2000). A corollary to this is thatecosystems as we know them may represent fairly transient combinations of species, as species respondindividualistically to climatic changes. Therefore, conservation efforts aimed at ensuring the long-term persistenceof biodiversity may vainly seek to capture a moving target, especially if the chief tool is a system of protected areaswith fixed borders.

It is possible that human induced increases in atmospheric CO2 and the state of the earths orbit will preventa return to glacial conditions for several tens of thousands of years into the future (Loutre & Burger 2000), but theprojected rate of CO2 increase and final projected level could alter climate as significantly as it changed between thecoolest period of the Pleistocene and the current warm Holocene conditions. At the same time, human activities aretransforming landscapes and rendering them far less permeable to species migration. Moreover, the introduction ofalien and invasive species by humans is resulting in devastating landscape transformations (Richardson et al. 1996)and drastic changes in community composition. Following present patterns (Balmford et al. 2000; Chown et al. inpress), both humans and other species are likely to prefer highly productive landscapes for settlement after climatechange. Collectively, these factors constrain our ability to ensure species persistence through time within the bordersof a static protected areas system, and presents conservation with possibly the most significant challenge in itshistory.

But climate and atmospheric changes remain in their own right powerful and pervasive threats tobiodiversity globally. Recent comprehensive reviews have concluded that even the relatively small shift in globaltemperature of + 0.6ºC in the past century have been sufficient to shift species ranges per decade by 6 km polewardsor 6m upwards in elevation (Parmesan & Yohe 2003). Some attempts to model the impact of future temperature riseand rainfall change have yielded noteworthy range shifts (Peterson et al. 2002, Midgley et al. 2002; Erasmus et al.2002).

Given the uncertainties strongly inherent in models of future climate change at a regional scale, it is not yetpossible to model individual species range shifts with sufficient confidence to guide comprehensive spatialconservation plans which account for climate change. However, there is enough evidence now from observationalstudies and theoretical understanding, that observations and general predictions of upward and poleward range shiftscould usefully inform decisions on protected areas placement and the design of corridors linking protected areas.Local knowledge regarding climatic refugia (i.e. azonally cool and moist situations) could also provide a usefulfocus for targeted conservation land acquisition.

Conservation planners may also ultimately be faced with decisions regarding species relocations to ensuretheir survival in nature. Projected range changes are large enough in some species to suggest that an assisted rangeshift is the only realistic way of ensuring species persistence in nature. This will pose a significant ethical andscientific dilemma – when is it preferable to establish a viable population in a novel range, or retain it only in ex situcollections or gene banks? Either way – the cost of intensive interventions such as this in a large enough number ofspecies, and the necessary subsequent monitoring, will certainly challenge the resources (both financial and human)available to conservationists.

Furthermore, rising CO2 itself may transform ecosystems into the future. Atmospheric CO2 has probablybeen at its historically lowest levels during the earth’s Pleistocene period, and this has almost certainly constrainedthe success of plant species that invest heavily in carbon-rich compounds and support structures. Thus trees wouldhave been highly constrained, while carbon-efficient growth forms like C4 grasses would have flourished. One of themost characteristic ecosystems of the tropics, namely savannas, comprise mixtures of trees and grasses in a dynamicequilibrium that may be tipped in the favour of trees with increasing CO2 (Bond & Midgley 2000). However,managers of such ecosystems may be able to employ carefully timed fires to retard or prevent the establishment oftrees at the expense of grasses in such systems.

Changes in climate and atmospheric composition therefore pose new and challenging questions forconservation science. The manner in which this single threat affects biodiversity resources appears to be highly

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complex, with species responses likely to be of an individual nature and species dispersal through corridors oraltered landscapes also constrained in a species-specific manner. Altered ecosystem and evolutionary processes orthe secondary response of species to these still appear speculative, but may even require assisted speciestranslocations and active landscape management to achieve conservation goals. From a conservation planningperspective we simply do not have the tools for dealing with such a variety of species-specific reactions, complexrelations or even unpredictable spatial responses. Thus, we urgently need an ability to synthesize these myriadinteractions into a spatially explicit framework for conservation planning, which expresses the relative threats orvulnerabilities in a common currency to facilitate a rational prioritization of interventions.

TOWARDS RISK ASSESSMENT IN CONSERVATION PLANNING

A risk assessment approach differs from a traditional threat assessment or vulnerability approach in the sense thatrisk management decisions are typically based on the product of the likelihood of an event occurring combined withan evaluation of the consequences of an event (Kammen & Hassenzahl 1999 - see Equation 1).

Risk = likelihood x consequences (Eq. 1)

This means that if we are interested in pursuing a risk assessment approach in conservation planning we need toconsistently express traditional biodiversity threat and vulnerability statements, e.g. historic rates of vegetationtransformation or species extinctions, into statements about the conservation value of sites and the likelihood orprobability of potential sites being lost in future. This is no simple task but in essence it translates the above equationinto a spatially explicit biodiversity risk statement (Equation 2):

Biodiversity risk to a site = probability of site loss x conservation value of site (Eq. 2)

Expressing conservation value in terms of irreplaceability

To date, risk assessment has only partially been employed in conservation planning. For example, Red Data Bookassessments are primarily threat driven and translate these threat assessments into likelihood or probability ofextinction measures (IUCN 2001). However, all species are traditionally treated as equals and no value judgmentsabout the possible consequences of the loss of particular species are made. This approach has been questioned(Vane-Wright et al. 1994; Freitag et al. 1998; Harcourt & Parks 2003; Keith et al. in review) and a morecomprehensive risk assessment approach is not feasible without incorporating an evaluation of the consequences ofspecific species losses (e.g. phylogenetic weighting). Moreover, for species at risk, these extinction measures are notnormally translated into site-specific conservation value statements. For example, what is the conservation value of aspecific site in terms of preventing the possible extinction of species A? The proportion of the viable populationrange contained in a site could potentially be used to formulate a site-specific conservation value statement for eachspecies (e.g. irreplaceability –see Noss et al. 2002). Here the area required by a viable population would be theconservation target and proportional contributions are translated into irreplaceability values. It is also possible toadopt either a RDB listing or some other conservation value statement, such as phylogenetic rarity, as criteria forincluding species in a list of species that require a spatially explicit irreplaceability surface in any particular planningdomain. Ecosystem processes can also be treated in a similar manner to individual species and it should beconceptually feasible to provide irreplaceability surfaces for any type of biodiversity feature from nature’s hierarchyof structure, composition and function. Here appropriate species-specific or process design criteria (migrationroutes, dispersal routes, breeding sites, flow regimes etc.) together with appropriate conservation targets wouldalways be the point of departure for developing appropriate irreplaceability surfaces (see Noss et al. 2002).

In the field of conservation planning combined threat/vulnerability and conservation value assessments(consequences) are routinely employed for certain types of biodiversity variables such as vegetation types andspecies. Consequently this field already applies a partial risk assessment approach. The main shortcoming being thatvulnerability assessments are not usually expressed as probability of loss statements (Pressey & Taffs 2001), butrather as suitability for alternative land uses.

Probability as a common currency for expressing site-specific biodiversity threat or vulnerability

As demonstrated previously, conservation planning has made some progress in terms of identifying potential threatsto biodiversity when designing conservation area networks. However, these biodiversity threats or vulnerabilities are

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measured and expressed in very different ways. For instance, the inherent suitability of land for commercialpurposes (such as crop production, mining or forestry) are typically used to score or rank sites in terms of theirrelative vulnerabilities (Pressey & Taffs 2001; Reyers in press). Thus, these vulnerability assessments are notemployed consistently. The most vulnerable areas are sometimes identified using arbitrary thresholds (Wessels et al.2003) or a continuum of vulnerability scores (Pressey & Taffs 2001; Rouget et al. in press b). In addition, a sharperdistinction between the use of historic threat patterns and future threats would be helpful. We concur with Rouget etal. (in press b) that historic threat patterns (species at risk of extinction and highly transformed vegetation types) arebetter suited for formulating conservation targets, whereas future threats are more useful for evaluating the risks oflosing new sites. Moreover, these vulnerabilities are usually not expressed in terms of a probability of losingindividual sites, although they are frequently come conceptually very close (e.g. percentage conversion of a landunit – Rouget et al. in press b). As multiple agents threaten most land parcels we also feel that a multi-threatapproach would be most advantageous (Rouget et al. in press b). We propose that the integration of multiple threatscan best be achieved when we employ a probabilistic risk assessment framework.

The use of standard risk assessment tools such as stock-flow models, more mechanistic cause and effectmodels, cost-benefit analysis and statistical models (Kamen & Hassenzahl 1999; Rouget et al. in press b) can beused to translate biodiversity threat or vulnerability statements into statements that express the probability of losingpotential conservation sites. The outcome should be a probability statement that will allow us to evaluate the risksassociated with the loss of a particular parcel of land threatened by multiple threats. This is possible as probability ofloss statements are essentially unit free and can be added across multiple threats. Similary, conservation value iscaptured by the notion of irreplaceability in a unit free manner, and is expressed as a ratio or relative contributiontowards a predetermined conservation goal or target (Margules & Pressey 2000; Pressey et al. 1994; Noss et al.2002).

Consequently, our suggested solution to the common currency dilemma is not to try and find a commoncurrency for biodiversity features per se, but to resort to the use of common currencies for expressing conservationvalue (irreplaceability) and future biodiversity threats (probability of loss). The dilemma posed by Cowling et al.(1999) about weighing up the consequences of “losing 5 Red Data species against a 20% loss of a land type”,becomes a very different question. It now becomes a simple matter of prioritizing land parcels that are considered athighest cumulative risk of being lost to a multitude of threats and which contain the most additive conservationvalue across the considered features. This addition process can be dealt with using a simple arithmetic manner (seeNoss et al. 2002 for a conservation value example Fig. 3a) or in a multidimensional manner (Fig. 3b).

Considering the difficulties experienced with the implementation of conservation plans, mainly due to theselection of sites that are unlikely to be conserved for any one of a variety of potential socio-economic or politicalreasons (Cowling and Pressey in press), it is also possible to depict the probability of a particular site being used forconservation in outputs like figure 3. Simply varying the sizes of the data points in a proportional manner can dothis. However, there are no established ways of determining the probability of sites actually being implemented onceidentified in a conservation plan. It is likely that such probabilities will be affected by variables such as current landuse and tenure systems. This implementation dimension requires considerable work to help us define appropriateways of treating socio-economic and political uncertainties in land-use planning.

(a) Priority conservation sites

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Figure 3. The most appropriate approach towards using a biodiversity value versus the risk of loss framework for prioritizingconservation sites may be determined by the question posed by the investigators (a) a simplistic additive example whereirreplaceability and likelihood of loss statements are summed across the selected biodiversity variables, or (b) a multi-dimensional approach where ecosystem pattern and process irreplaceability were considered independently against the likelihoodof grid cell loss. A three-dimensional plot of grid cells within the Gariep Basin illustrating their conservation value and theirprobability of loss. Their conservation value is illustrated in terms of both their pattern and process irreplaceability while theirprobability of loss was derived from the rates at which land was degraded historically in each grid cell and projecting thisforward. Only grid cells with irreplaceability values above 0.2 are illustrated in order to improve display clarity.

Dealing with uncertainty and complexity in conservation planning

A fundamental assumption of the above approach is that we can treat conservation value and conservation threat in asimplistic additive and unit free manner. However the complexity of biodiversity, here viewed as a multivariate andmulti-scale condition (Noss 1994), suggests that this is unlikely. This complexity places a number of options beforeconservation practitioners, including (Kammen & Hassenzahl 1999):

a. make arbitrary decisions about the biodiversity features to include. This option may be largely data drivenand requires surrogacy assumptions for features not included in the analysis. Much of existing conservationplanning follows this approach (for example see van Jaarsveld et al. 1998);

b. agree on a common index that transcends scales and that can accommodate best possible regional datasets.Surrogacy assumptions would also be required here (see Reyers & James 1999);

c. develop a detailed understanding of the relationships between biodiversity feature types and/or hierarchicallevels (e.g. mammals and invertebrates; landscapes and species). Surrogacy assumptions not required asrelationships are incorporated into planning models. It is unlikely that conservation biology will achievethis level of understanding in the near future;

d. employ risk assessment tools to determine and explore the relationships between variables. Standard riskassessment procedures may be used when good data are available, however, when a large degree ofuncertainty is involved Bayesian belief networks may be most appropriate. Bayesian analysis is essentiallya “common sense reduced to numbers” approach (Pendock & Sears 2003) and can be used to translatealmost any level of understanding or knowledge into probability statements using Bayes’ theorem.

Numerous risk assessment tools exist and can be used to prioritise interventions in the field of conservation biology.Some of these do require considerable understanding and data about the risks involved. However, this is not arequirement as risk assessment can also effectively be done using minimal data and even limited levels ofunderstanding (Kamen & Hassenzahl 1999). One such an approach is Bayesian probability assessment. Bayesianapproaches are useful for dealing with uncertainty and when the information is highly dependent on the state or“information” available to the observer, a situation likely to apply in conservation planning. Bayes’ theorem allows

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the calculation of conditional belief systems. In practice it states, that if A and B are propositions, then P(A) is a realnumber between 0 and 1 which donates the strength of one’s belief in A as a probability statement. In this regard wecan even define joint probabilities [probability of A and B = P(AB)] or even conditional probabilities [P(A|B) is theconditional probability of A given that evidence exists that B is true] - (Pendock & Sears 2003). Bayes’ theorem alsoallows the explicit calculation of conditional probabilities so that:

P(A|B) = P(A)P(B|A)/P(B) (Eq. 3)

Conditional probabilities are then defined and are indicative of relationships between variables, i.e. P(A|B). Ifrelationships are uncertain trial models may be explored and the most likely one implemented (Pendock & Sears2003). Such probability assessments can also be adjusted as novel information becomes available to the observer,e.g. likely impacts on conservation value of sites if new populations of threatened species are discovered.The incremental nature of the Bayesian approach is particularly well suited for developing a more comprehensiveframework for conservation planning, since it allows us to incorporate all forms of scientific and localunderstanding, it can cope with uncertainty in ecosystem relationships, and the system is iterative (Kammen &Hassenzahl 1999). Figure 4 provides a hypothetical Bayesian belief network for conservation planning in theWestern Cape, South Africa. A network of conditional probabilities between variables then takes us a step closertowards defining the relationships between variables in complex systems without the a detailed mechanisticunderstanding (Wade 2000). Bayesian belief networks can also be adapted to local conditions using the bestavailable data and can even incorporate local knowledge about the relationships between parameters. Consequently,we feel that in order for conservation planning to take its logical next step it is important that we strengthen ourcapacity to:

a. formulate comparable biodiversity value statements for all biodiversity variables (compositional, structuraland functional – Noss 1994) using the common currency of site-specific “irreplaceability values” (Presseyet al. 1994);

b. express all biodiversity threats using a common currency of the “probability of losing” specific planningunits from a planning domain;

c. deploy existing methods for determining priority conservation sites (Pressey &Taffs 2001; Noss et al.2002) using site-specific conservation value together with likelihood of site loss statements, and

d. develop an integrated risk assessment approach for improving our understanding and quantifying obscurerelationships in complex biological systems (Seife 2003).

Dryland agriculturePresent 70%Absent 30%

Habitat lossTrue 50%False 50%

Urban –industrial complexPresent 35% Absent 65% Invasive plant

species Present 20% Absent 80%

Species extinctionsTrue 50% False 50%

Reduced MARTrue 50% False 50%

Altered fire regimesTrue 40%False 60%

Figure 4. A hypothetical Bayesian conservation threat belief network for a lowland fynbos system in the Western Cape, SouthAfrica.

WHY RISK ASSESSMENT IN CONSERVATION PLANNING?

The challenges faced by the conservation community have distinct similarities with an existing tension betweenengineers and risk assessment practitioners. Probabilistic risk assessment (PRA) is well suited and is sometimesused in the engineering and business environments to gain insights into the likely failure of complex systems (Seife2003). Typically, engineers are not very fond of the risk assessment approach as they prefer to incorporate sufficient“safety margins” into their designed systems – “make it twice as strong to be sure”. This fail safe approach is alsoemployed by the conservation community when they are faced with uncertainty or having to make judgments aboutcomplex ecosystem impacts. One lesson that the engineering fraternity have learnt, however, is that making sure that

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each component in a complex system is sufficiently robust provides little information or guarantee about thelikelihood of complex system failures, e.g. space shuttles, and can even lead to a false sense of security. The effortthat the conservation community invests in ensuring the safety of species (Red Data Book approach – IUCN 2001)or to conserve biodiversity patterns is an obvious analogy.

If we are to progress beyond a simplistic understanding of the complex ecosystems we are attempting tomanage and conserve we will have to resort to using a more comprehensive risk assessment approach inconservation planning. This means improving our ability to make statements about complex biological systems andto pursue an understanding of the critical elements or the relationships of those systems. The existing “black art” ofecosystem and conservation management (Caughley 1994) can therefore realistically be replaced with a morepragmatic and systematic approach (Seife 2003).

What are the major advantages that a risk assessment approach provides? Besides its ability to detectcritical elements or those most crucial for ecosystem functioning (conservation value?), it should be rememberedthat it is the relative risks that are of importance in a risk assessment exercise. This allows one to focus attention onthese relevant or critical elements to better direct scarce resources. Risk assessment will also allow us to identifythose ecosystem elements or processes/services that are most likely to be lost to any particular ecosystem threat.

Despite these potential advantages, PRA does also have its limitations, including our inability to capture allelements of a complex system, overlooking a possible source of failure or the interdependencies of these failures(Seife 2003). It is therefore important that we manage the expectations from such an alternative approach. However,in order to carry out PRA, it is important that all conditional and joint dependencies between parameters of interestin a complex system, should also be expressed in a “common currency”. The common currency used in riskassessment is the likelihood or the probability of an event occurring. This means that all likely sources of ecosystemfailure or loses of biodiversity features need to be translated into probability statements, not an easy task given ourpresent level of ecosystem understanding. However, provided the principle of a common currency is pursued withvigour, the integration of understanding using standard risk assessment tools is achievable.

CONCLUSION

This overview suggests that the current dual assessment approach of looking at biodiversity vulnerability andconservation value should be adapted to more explicitly incorporate a biodiversity risk assessment framework. Thisusage of the common currencies of probabilities and irreplaceability together with the incorporation of biodiversityvariables from across natures’ complex hierarchy can strengthen systematic conservation planning procedures.Moreover, by adopting a stronger risk assessment approach, conservation planning will be in a better position to dealwith complexity and uncertainty. This is in contrast with the rather ad hoc approach presently used to deal withissues such as data availability, surrogacy measures or uncertain relationships between biodiversity variables.Explicit probability statements can be derived when good data are available using normal statistical procedures orusing more flexible and less conventional analytical frameworks such as Bayesian statistical approaches. The needfor planning in the face of uncertain futures is probably inevitable. Consequently we need to learn to deal with thisreality rather than succumb to the temptation of reverting to ad hoc approaches to conservation planning.

ACKNOWLEGEMENTS

We would like to thank the National Research Foundation, the National Botanical Institute, the Council for Scientific andIndustrial Research and the University of Stellenbosch for financial and logistic support. We would also like to thank RichardCowling for commenting on drafts of this manuscript and Louise Erasmus for assisting with the development of the fynbosBayesian belief network.

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