AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS
Aquatic Conserv: Mar. Freshw. Ecosyst. 18: 969–983 (2008)
Published online 23 April 2008 in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/aqc.902
Key biodiversity areas as globally significant target sites for the
conservation of marine biological diversity
GRAHAM J. EDGARa,b,c,*, PENNY F. LANGHAMMERa, GERRY ALLENd,
THOMAS M. BROOKSa,e, JULIET BRODIEf, WILLIAM CROSSEa, NAAMAL DE SILVAa,
LINCOLN D. C. FISHPOOLg, MATTHEW N. FOSTERa, DAVID H. KNOXh, JOHN E. MCCOSKERi,
ROGER MCMANUSa, ALAN J. K. MILLARj and ROBINSON MUGOk,l
aConservation International, 2011 Crystal Drive, Ste 500, Arlington, Virginia 22202, USA
bTasmanian Aquaculture and Fisheries Institute, University of Tasmania, GPO Box 252-49 Hobart, Tasmania 7001, Australia
cCharles Darwin Foundation, Puerto Ayora, Galapagos, Ecuador
dDepartment of Aquatic Zoology, Western Australian Museum, Locked Bag 49, Welshpool DC, Perth,
Western Australia 6986, Australia
eSchool of Geography and Environmental Studies, University of Tasmania, GPO Box 252-78, Hobart, Tasmania 7001, Australia
fDepartment of Botany, Natural History Museum, Cromwell Road, London SW7 5BD, UK
gBirdLife International , Wellbrook Court, Girton Road, Cambridge CB3 0NA, UK
hConservation International, Kirstenbosch National Botanical Garden, Private Bag x7, Claremont 7735, South Africa
iCalifornia Academy of Sciences, San Francisco, California 94118, USA
jRoyal Botanic Gardens Sydney, Mrs Macquaries Road, Sydney, NSW 2000, Australia
kKenya Marine & Fisheries Research Institute, English Point, Silos Road, Mkomani, P.O. Box 81651-80100
Mombasa, Kenya
lGraduate School of Fisheries Sciences, Hakkaido University, 3-1-1 Minato-cho,
Hakodate 041-8611, Japan
ABSTRACT
1. Recent approaches to the planning of marine protected area (MPA) networks for biodiversity conservation
often stress the need for a representative coverage of habitat types while aiming to minimize impacts on resource
users. As typified by planning for the Australian South-east Marine Region, this strategy can be manipulated by
political processes, with consequent biased siting of MPAs. Networks thus created frequently possess relatively
low value for biodiversity conservation, despite significant costs in establishment and maintenance.
2. Such biases can be minimized through application of the data-driven and species-based concept of key
biodiversity areas (KBAs).
3. By mapping locations of threatened species and populations that are highly aggregated in time or space, the
KBA process allows marine sites of global biodiversity significance to be systematically identified as priority
*Correspondence to: Graham J. Edgar, Tasmanian Aquaculture and Fisheries Institute, University of Tasmania, GPO Box 252-49
Hobart, Tasmania 7001, Australia. E-mail: g.edgar@utas.edu.au
Copyright # 2008 John Wiley & Sons, Ltd.

conservation targets. Here, the value of KBAs for marine conservation planning is outlined, and guidelines and
provisional criteria for their application provided.
Copyright # 2008 John Wiley & Sons, Ltd.
KEY WORDS: endemism; marine protected area; MPA; IUCN Red List; systematic conservation planning; threatened species
INTRODUCTION
As threats to biodiversity increase, conservation managers and
donor organisations require increasingly sophisticated tools
for decision-making; above all, ways to prioritize conservation
actions that are efficient, accountable and transparent. At the
global scale, the ‘biodiversity hotspots’ approach (Myers et al.,
2000) provides an example of the way that data-driven
analyses can assist prioritization of conservation actions and
significantly leverage new conservation dollars (Brooks et al.,
2006). At regional and local scales, progress towards a data-
driven approach to conservation is most evident in site
planning, which is now central to much conservation action
across the world (Margules and Pressey, 2000).
While species are the predominant units of biodiversity, time
and resources are not available to conserve species one-by-one
(Ehrlich, 1992). The conservation of important sites with
associated habitats as protected areas or through other
safeguard mechanisms is therefore generally seen as the best
strategy to maintain biodiversity (Bruner et al., 2001; Brooks
et al., 2004; Pressey, 2004). This is implicit, for example, in
the call from the 5th IUCNWorld Parks Congress to: ‘Maximize
representation and persistence of biodiversity in comprehensive
protected area networks, focusing especially on threatened and
under-protected ecosystems and species globally threatened
with extinction’ (www.iucn.org/themes/wcpa/wpc2003/english/
outputs/durban/cbdmessage.htm). Threat reduction and addi-
tional conservation actions are clearly also necessary (Cicin-Sain
and Belfiore, 2005); nevertheless, even for species that are wide-
ranging across landscapes and seascapes, protected areas often
serve as ‘anchors’ for conservation strategies involving ecological
networks or corridors.
Central to conservation planning is the question: ‘How can
the locations of protected areas be best identified?’ This
question is particularly pertinent within the field of marine
planning given increasing recognition of the extent of
deterioration in the marine environment and the potential
importance of the role of marine protected areas (MPAs)
(Roberts and Hawkins, 1999; Dulvy et al., 2003; Glover and
Earle, 2004; Worm et al., 2006). The issue is also intertwined
with social and political considerations, given that intense
pressure is often placed on decision-makers to minimize
perceived impacts of new protected areas on existing users
(Davis, 1981; Lynch, 2006).
To provide the most effective outcomes, and to offset
pressures of partisan stakeholders, efficient systems of
identifying and prioritizing candidates for protected sites are
required. Ideally, such systems should be quantitative and
explicit, while also understandable to stakeholder groups and
non-scientific decision-makers. Here, we briefly review the
representative habitat approach typically used in planning
networks of MPAs for biodiversity conservation, and highlight
a serious shortcoming.
To help overcome current limitations in the development of
MPA networks, we also outline the key biodiversity area
(KBA) concept, where sites of global conservation significance
that are, or can potentially be, managed for conservation are
identified using the principles of vulnerability and
irreplaceability (Eken et al., 2004; Langhammer et al., 2007).
Vulnerable sites are those holding one or more globally
threatened species while irreplaceable sites are those holding a
significant proportion of the global population of a species.
The term ‘site’ in the KBA context refers to a landscape or
seascape unit that (i) can be delimited on maps, (ii) encompasses
the important habitat used by the species of conservation
concern, and (iii) can actually or potentially be managed as a
single unit for conservation. Following this definition, KBAs
can vary greatly in size, each possessing a site boundary that
corresponds to the most practical conservation unit, where
contiguous habitat, local management units, and the potential
for significant gene flow among populations are all considered.
In the marine context a KBA will often, but not always, be
effectively safeguarded as anMPA. The choice of an appropriate
conservation tactic will depend on the best mechanism to protect
the target species within a given KBA. Managed fishery or
tourism sites may in some instances provide better protection for
a KBA than provided by MPA designation, particularly if the
alternative strategy promotes local ownership and allows more
effective control of illegal exploitation.
Within the conservation managers’ toolbox, KBAs provide
an important tool alongside strategies currently used to
safeguard representative habitats, to protect individual
species from idiosyncratic threats, and to reduce broad-scale
pressures and threats affecting wide-ranging species. While
further testing is necessary, the incorporation of a KBA
approach into marine conservation planning should ensure
that MPAs and other site conservation tactics are targeted
towards the places where they are most necessary to prevent
species’ extinctions.
G.J. EDGAR ET AL.970
Copyright # 2008 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 18: 969–983 (2008)
DOI: 10.1002/aqc

LIMITATIONS OF CURRENT MARINE
CONSERVATION PLANNING METHODS
Despite recognition that site protection is fundamental to
conservation, national systems of protected areas, including
MPAs, are far from systematic in their coverage (Rodrigues
et al., 2004; Mora et al., 2006). Gaps and redundancies in the
distribution of protected sites result not only in inefficiency but
failure to protect important biodiversity (Margules and
Pressey, 2000).
Since pioneering work two decades ago (Kirkpatrick, 1983),
a number of tools for identifying and prioritizing sites of
conservation significance have been proposed or are currently
under development (Pressey, 2004). These include reserve
selection algorithms that use a complementarity approach to
maximize the range of conservation targets such as habitats or
species to be protected within a protected area network of given
size (Beger et al., 2003; Leslie et al., 2003; Stewart et al., 2003).
While conservation planning tools have progressed most
rapidly in terrestrial systems, data-driven procedures are also
increasingly used when defining frameworks for marine
conservation planning (Roff and Taylor, 2000; Roff and
Evans, 2002; Roff et al., 2003), and to assist the development
of systematic networks of MPAs (Ward et al., 1999; Sala et al.,
2002; Beger et al., 2003; Roberts et al., 2003; Stewart et al.,
2003; Campagna et al., 2007).
Planning of MPA networks to conserve biodiversity has
relied heavily to date on the concept of representation} the
need to encompass a wide range of different habitat types (e.g.
ANZECC, 1999). Thus, MPA planning typically involves
division of a seascape into mappable units such as bioregions
and habitats, with stakeholder-driven processes then applied to
select representative subsets of each of the mapped units for
protection. A major limitation of this process is that it often,
although not always (e.g. in the terrestrial realm, Cowling et al.,
2003), overlooks vulnerability} recognition that some sites
hold species that are at higher risk of extinction and require
prioritized conservation action (Margules and Pressey, 2000).
A compounding problem of current MPA selection processes
is that outcomes are affected by biases associated with
stakeholder input. During negotiations over MPA
establishment and boundaries, stakeholders who utilize local
resources (e.g. fisheries, tourism, oil extraction) typically know
where those resources are concentrated, and attempt to keep
such areas out of protected area networks (Lynch, 2006). By
contrast, the conservation sector rarely has accurate information
on the most important sites for conservation, resulting in areas
of low conservation value often ending up designated as
‘representative’ areas within finalized MPA systems.
MPA networks derived through such negotiations can
possess reduced value for biodiversity conservation and
involve large costs in terms of forgone opportunities to
create more effective MPA networks for the same total
cost. This situation parallels terrestrial conservation planning
of the last century when alpine regions, deserts and other areas
with little resource value were disproportionately designated
national parks} the so-called ‘worthless lands’ scenario
(Runte, 1977; Pressey, 1994), in the sense that lands
allocated to conservation often possessed negligible economic
value other than for tourism.
Biases in MPA location develop at the local level during
face-to-face negotiations between stakeholders, and can also
be formalized at regional levels within government-mandated
MPA selection strategies. The Galapagos Marine Reserve
(GMR) provides an example of a network of sanctuary zones
developed using a bottom-up, stakeholder-driven process with
substantial bias. In Galapagos, sanctuary zones were identified
following a series of face-to-face meetings involving
representatives of fishing, tourism, conservation, science and
management sectors that extended over 12 months and
culminated in an extended boat cruise to finalize zone
boundaries (Heylings et al., 2002; Edgar et al., 2008).
Negotiations followed guidelines outlined in the GMR
Management plan, which called for the development of a
network of conservation zones that included representative
habitats, rather than species, within recognized Galapagos
bioregions.
At the commencement of negotiations, the Galapagos
artisanal fishing sector advocated that no areas be excluded
from fishing, while the science and conservation sector
proposed 36% of the coast as ‘no-take’ zones. Consensual
agreement was eventually reached on a total of 14 ‘no-take’
conservation zones (6% of the coast) and 62 small ‘no-take’
tourism zones that were also regarded as possessing high
conservation value (additional 11% of coast). Because the
fishing sector would not agree to sanctuary zones in important
fishery areas, almost all conservation zones were located along
coasts with little fishery resources or with limited commercial
diver access. Sites with known concentrations of sharks were
included within tourism zones.
The environmental outcome of these negotiations was
quantified during archipelago-wide surveys of resources at
the conclusion of negotiations (Edgar et al., 2004). Mean
densities of major fishery species (sea cucumbers and spiny
lobsters) were about three times higher in areas agreed to
remain open for fishing compared to conservation zones, a
consequence of fishers vetoing all conservation zones proposed
for resource rich areas. Areas agreed as tourism zones
possessed sharks} the major dive tourism resource}with
mean densities five times higher than in conservation zones.
An example of bias that is formally embedded in MPA
selection is the process used recently by the Australian
Government to delineate MPAs in its South-east Marine
Region, one of the largest MPA networks worldwide,
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encompassing 226 155 km2 of seabed. The government agency
responsible for this process initially consulted with
stakeholders and then distributed a draft set of MPA zones
for public comment. The specific criteria used to identify
MPAs proposed in the initial draft were not clearly enunciated
but appear to have been: (i) a wide range of habitat types
should be included; and (ii) existing and prospective petroleum
leases and fishing grounds should be avoided. Only one
proposed MPA overlapped with a petroleum lease, while
several had boundaries contiguous with petroleum leases
(Figure 1(A); Buxton et al., 2006).
The fishing sector lobbied strongly during the public
consultation phase that all sites with significant commercial
fishing activity should not be included within MPAs because of
social and economic costs, or, if this was not possible, then pre-
existing fishing methods should be allowed to continue within
protected zones (Buxton et al., 2006). Zoning amendments
requested by fishers were largely accommodated (Figure 1(B)),
allowing the Australian Minister for the Environment and
Heritage to announce (5 May 2006: http://www.deh.gov.au/
minister/env/2006/mr05may06.html) ‘We have made more than
20 adjustments to boundaries and zoning that will reduce the
impact on commercial fishing by more than 90 per cent. . . . The
new MPA network will not prevent prospective oil and gas
areas from being explored and developed.’ Implicit in this
statement is the assumption that a useful and comprehensive
MPA network can be developed, and threats to biodiversity
addressed, with negligible change to existing activity.
Although a total of 8% of the continental shelf in the South-
east Marine Region is to be recognized as MPAs of one form
or another, and 42% of the total MPA area comprises ‘no-
fishing’ sanctuary zones, only one sanctuary zone is located on
the continental shelf (ca 0.4% of regional shelf waters) within
the MPA network (http://www.deh.gov.au/coasts/mpa/
southeast/index.html). Longlining, charter fishing and
aquaculture are permitted in almost all sections of MPAs on
the continental shelf and slope, while sanctuary zones are
located almost exclusively in abyssal areas >1500m depth.
Scallop dredging, the fishing activity within the region that is
recognized to cause most environmental harm (Kaiser et al.,
2006), is not affected by the new zoning scheme (Stump and
Sansom, 2006). Sites of recognized conservation significance
have not been included in fully protected zones, such as the
highly productive Bonney Upwelling where Endangered blue
whales (Balaenoptera musculus) congregate.
Thus, despite the impressive appearance and size of this
MPA network on paper, human activity will continue virtually
unchanged across the Australian seascape. Major conservation
benefits arising from the new MPA network with respect to
existing activities are negligible, despite clear evidence that
marine biodiversity within the region has already declined
substantially over the past century (Edgar and Samson, 2004;
Edgar et al., 2005).
Rather than representing a failure of the representation
approach to marine planning, the above example could also be
regarded as an example of political opportunism producing
poor conservation outcomes that are promoted as a great
advance to a poorly-informed public; however, such
manipulation is assisted by the latitude available to policy
makers in defining which habitat types require representative
coverage. Very little scientific information exists on which
physical surrogates are most effective at delineating habitat or
ecosystem types in conservation planning. Consequently,
planners can credibly place emphasis on, for example, a
division of the seascape into geomorphological units over a
division based on primary productivity, water temperature,
wave energy, current strength, or depth, whereas these latter
factors, or others including history, may predominantly
influence species’ distributions.
This source of potential bias is likely to diminish with spatial
scale (R.L. Pressey, pers. commun.). At broad regional scales,
marine planners possess enormous flexibility in the siting of
protected areas to achieve representation targets, hence
lobbying by extractive interests can readily divert
conservation attention away from areas and species most
under threat. At finer scales, planners possess less spatial
flexibility relative to the scale of exploited resources, and
avoidance of such areas becomes more difficult.
KEY BIODIVERSITY AREAS AS PRIORITY SITE
CONSERVATION TARGETS
To redress stakeholder-associated biases in MPA selection,
conservation managers require an objective protocol to
identify sites of highest significance for biodiversity
conservation. The ‘Key Biodiversity Area’ (KBA) approach
fills this need (Eken et al., 2004; Langhammer et al., 2007),
providing a complement to existing methodologies that
identify and select representative marine areas for protection
within MPA networks.
KBA methods are based on the rationale that the extinction
of any species represents a loss of global significance.
Biodiversity clearly declines at the species and genetic levels
following extinction. It can also decline at the ecosystem level,
depending on the ecological role of lost species. KBAs are
selected using standardized, globally-applicable criteria based
on species vulnerability and site irreplaceability (Margules and
Pressey, 2000). A KBA site meeting the vulnerability criterion
comprises the confirmed locality of a Critically Endangered or
Endangered species, or more than
30 individuals of a
Vulnerable species (following the IUCN Red List categories
G.J. EDGAR ET AL.972
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DOI: 10.1002/aqc

and criteria; IUCN, 2001), while an irreplaceable KBA
comprises the location of a significant proportion of the
global population of a species (Eken et al., 2004; Langhammer
et al., 2007).
The KBA approach developed from quantitative criteria
pioneered by the BirdLife International partnership for the
designation of globally significant ‘Important Bird Areas’.
More than 10 000 Important Bird Areas, the avian subset of
KBAs, have been identified in over 170 countries and
territories (BirdLife International, 2004a).
KBAs are also widely used for the conservation of plants,
mammals, amphibians and other vertebrate taxa. Sites
encompassing the only known localities for highly-threatened
species} the ‘Alliance for Zero Extinction’ (AZE) sites (Ricketts
et al., 2005)} comprise a subset of KBAs. A total of 595 AZE
sites based on mammals, birds, amphibians, tortoises, crocodiles,
iguanas and conifers, with a median size of 120km2, have been
identified globally to date (Ricketts et al., 2005).
Sites that uniquely contain particular threatened species
should be regarded as the most urgent subset of sites required
Figure 1. (A) Boundaries initially proposed for MPAs in the South-east Marine Region of Australia with ‘no-take’ sanctuary zones and with zones
of limited permitted fishing. (B) Finalized MPA zone boundaries for the South-east Marine Region. Filled arrows indicate locations identified by the
fishing industry as important for commercial fisheries after public dissemination of proposed zones depicted in (A). Open arrow indicates sole
sanctuary zone present on continental shelf. Petroleum exploration leases (Figure 1(A)), the continental shelf break (black line) and Exclusive
Economic Zone boundary (grey line) are also shown. Data largely from Buxton et al. (2006)
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within networks of MPAs that follow ‘CAR’ principles
of complementarity, adequacy and representativeness
(ANZECC, 1998). For an MPA network to be totally
representative and comprehensive it must include all sites
with species that are confined to a single site. When single-site
species face a high level of threat (i.e. are listed as CR or EN on
the Red List), then sites that contain such species clearly
represent the most urgent conservation priorities for inclusion
within MPA networks. No alternatives in space exist to
safeguard these threatened species within a network, and
neither can management intervention be postponed for the
future as the species may have become extinct by that time.
Other KBA sites need management intervention less
urgently, but, if extinction risk is to be minimized, represent
higher conservation priorities than sites with widely-
distributed non-threatened taxa. A fully comprehensive and
representative network of MPAs could nevertheless also
include sites in this latter category, particularly in wilderness
regions, in order to minimize the slide of species from non-
threatened to threatened status.
A further likely benefit of the KBA process additional to its
role in safeguarding well-researched species is to protect sites
that include critical habitats for poorly-known threatened
species. This benefit is outlined using the hypothetical example
illustrated in Figure 2, where the two sides of the figure
represent changes in a mosaic of different ‘ecosystem units’
distributed across the seascape from the recent past to the
present. The term ‘ecosystem unit’ is used to refer to a spatial
mapping unit that reflects habitats or assemblages, with species
composition within each unit most similar to that in units of
similar shading.
For the seascape represented by Figure 2, the primary target
for safeguarding at present is the hatched ecosystem unit ‘A’,
given that the total area of this ecosystem unit has declined by
more than 90% over the period of analysis. If current threats
continue, then this unit could disappear from the seascape,
with extinction of associated species. Hatched unit A may
comprise, for example, seabed habitat threatened by trawling,
shallow rocky reef ecosystem transformed by cascading fishing
effects associated with the removal of large predators,
upwelling cells affected by climate change, estuaries
influenced by pollutants draining from catchments, or
seagrass beds affected by eutrophication. While knowledge of
the type of threat is necessary when attempting to ameliorate
it, this information is not necessary when identifying
conservation priority areas using such a mapping approach.
A secondary priority for protection in this example is the
small white unit at right centre (marked B), which currently
possesses a stable area but is unique within the seascape.
Because of its small size and lack of replication, a localized
threat acting stochastically, or negative external influences
encroaching inside the limited habitat boundary, could cause
extinction of species associated with this unit.
In practice, such a direct mapping approach can rarely be
used to identify priority ecosystem units for several reasons.
First, marine habitats are out of sight, hence mapping over
large spatial scales relies on remote sensing, and ecosystem
units often have poorly-resolved or fuzzy boundaries (Bruce
et al., 1997). Second, habitat boundaries can be important
biodiversity features in their own right, including frontal areas
in offshore habitats (Malakoff, 2004; Campagna et al., 2007).
Third, detailed ‘before’ data, such as shown at left in the
hypothetical example, are rarely, if ever, available (Dayton
et al., 1998). Fourth, ‘ecosystem units’ (or habitats,
assemblages, etc.) are not homogeneous entities and are
affected by history. The universe of environmental variables
operating in the marine environment (e.g. sediment type,
seabed structural heterogeneity, bedrock geology, wave
exposure, currents, salinity, turbidity, depth, and
concentrations of oxygen, nitrates, phosphates, silicates and
iron) trend in different but interacting directions, and affect
each species differently. Consequently, any habitat map should
be regarded as a highly simplified representation, with the
distribution of few, if any, species defined by sharp, mapped
habitat boundaries (Brooks et al., 2004).
Given these limitations, the KBA approach arguably
provides the best available mechanism to identify ecosystem
units of highest conservation priority. While data relating to
species distributions are patchy and also suffer many of the
limitations outlined above for habitat data, ‘before’
information and complete spatial data sets are not necessary
for KBA planning.
For the hypothetical example above, populations of species
closely associated with hatched ecosystem A in Figure 2,
and confined to the region mapped, will have declined greatly
in recent years, triggering threatened species status for those
species when criteria associated with the IUCN Red List of
Figure 2. Changes in distribution of ecosystem units from the
recent past to present
G.J. EDGAR ET AL.974
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DOI: 10.1002/aqc

Threatened Species (hereafter Red List) are applied. By
plotting the localities where threatened taxa are known
to occur, it should be possible to identify the hatched
areas because of the presence of one or more species with
rapidly declining populations. Thus, the location of threatened
species can provide a surrogate for threatened habitats, which
in turn may provide a surrogate for other (unknown)
threatened species. Moreover, by assessing the known
localities for species with highly restricted ranges, it should
also be possible to locate sites analogous to the small white
ecosystem unit B.
A prediction of the hypothesis that remnant areas of
relatively undisturbed habitat provide a refuge for multiple
species with declining populations is that sedentary threatened
marine species are not randomly distributed across the
seascape, but will tend to co-exist in a restricted number of
sites. This prediction is supported by the limited data available.
A map of all localities where threatened endemic Tasmanian
fish and sea stars have been recorded in the past 30 years, for
example, indicates that threatened marine species are not
randomly distributed (Figure 3). Large areas of coast lack
threatened taxa, including the northern half of the island,
whereas over 80% of known localities with threatened species
are positioned within a 100 km span off the south-eastern
coast. Three species occur in very close proximity at the
encircled location.
MARINE KEY BIODIVERSITY AREAS
Criteria used to identify key biodiversity areas
KBAs are designated for species that regularly occur at a site
and that will benefit from conservation and management
actions undertaken at the site (Eken et al., 2004). Sites may be
included in a KBA network where the species’ occurrence is
seasonal (e.g. for breeding or feeding) or episodic; however,
Figure 3. Localities at which endemic Tasmanian marine fish and invertebrate species listed as threatened under the Australian Conservation and
Biodiversity Protection Act and Tasmanian Threatened Species Protection Act have been recorded during the past 30 years
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instances of vagrancy or marginal occurrence and historical
records are excluded.
KBA criteria currently applied in terrestrial situations need
some modification to work most effectively at marine sites
because of differences between terrestrial and marine realms
(Steele, 1985; Carr et al., 2003), including greater connectivity
and faster turnover rates of marine systems, and the three-
dimensional nature of marine habitats. In addition,
comparatively few data are available on the distribution of,
and threats to, marine taxa.
As an initial step to address the perceived need for modified
marine criteria, a ‘Marine KBA Development Workshop’ was
held in Washington DC on 1–3 August 2005, involving authors
of this paper and
30 others closely involved in marine
conservation planning and science. The goal of the workshop
was to examine criteria used to identify terrestrial KBAs to
determine whether they need adaptation for marine situations;
Table 1 lists the marine KBA criteria that were consensually
agreed by workshop participants. They are based on KBA
criteria applied to date, mainly in terrestrial environments,
with slight adaptation to facilitate marine application. While
some initial testing has been undertaken in the Galapagos
Marine Reserve (Edgar et al., 2008), criteria and thresholds
included in Table 1 are provisional, and are proposed within
the evolving process for establishing agreed-upon thresholds
for KBA criteria (Eken et al., 2004). They need field-testing to
ensure that the number of KBAs identified in practice is
appropriate and reasonable, and that species for which site-
scale conservation is important are not overlooked.
Vulnerability criterion associated with globally threatened
species
The IUCN Red List provides an appropriate quantitative
standard for measuring extinction risk among species (IUCN,
2001). The Red List recognizes three groups of threatened
species with decreasing levels of vulnerability: Critically
Endangered (CR), Endangered (EN) and Vulnerable (VU)
species. Other categories are applied for species regarded as
Extinct (EX), Extinct in the Wild (EW), Near Threatened
(NT), Least Concern (LC) and Data Deficient (DD).
Threatened species are categorized on the basis of
standardized thresholds related to population size,
population trends, distributional range, and persistence of
threats. For example, a species with a population that has
declined by >80% over the past 10 years in the face of
persisting threats is categorized as CR.
One major shortcoming of the current Red List is that few
marine species have been assessed, and these taxa are heavily
biased towards large, charismatic, wide-ranging vertebrates
(Rodrigues et al., 2006). Only 19 benthic marine invertebrates
(twelve molluscs, four crustaceans, one polychaete, two
cnidarians) and one marine plant have been assessed as
threatened and entered on the 2006 IUCN Red List, surely an
insignificant proportion of the number that is actually
threatened (Millar, 2003; Edgar et al., 2005).
Some threatened marine fish, invertebrates and seaweeds
are, however, recognized at national and state levels.
Any species endemic to an assessment region that is
evaluated using the required Red List process and meets
threatened species criteria should be included in the
application of the vulnerability criterion for KBAs. Within
Australia, for example, the NSW Fisheries Management
Act 1994 lists six marine fishes and two algal species as
Vulnerable, Endangered or Extinct (http://www.fisheries.nsw.
gov.au/threatened species/threatened species), while threatened
species schedules of the Tasmanian Threatened Species
Protection Act include four marine fishes, three seastars, one
seaweed and one gastropod (http://www.dpiw.tas.gov.au/
inter.nsf/WebPages/SJON-58K8WK?open). Nevertheless, such
listings are incomplete even in comparatively well-studied
regions such as Australia, and they are absent for most
nations and states.
Table 1. Criteria and thresholds provisionally considered appropriate for the identification of marine KBAs
Criterion Sub-criteria Provisional thresholds for triggering KBA status
Vulnerability Regular presence of a single individual for
Critically
Regular occurrence of a globally threatened
species (according to the IUCN Red List) at
the site
Endangered (CR) and Endangered (EN) species;
regular presence of 30 individuals or 10 pairs for
Vulnerable species (VU)
Irreplaceability (a) Restricted-range species Species with a global range less than 100 000km2;
5% of global population at site
Site holds X% of a species0 global population
at any stage of the species0 lifecycle
(b) Species with large but clumped
distributions
5% of global population at site
(c) Globally significant congregations 1% of global population seasonally present at site
(d) Globally significant source populations Site is responsible for maintaining 1% of global
population
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The development of effective KBA networks clearly requires
threat assessment of sedentary species in addition to the
charismatic taxa already included on the IUCN Red List
(Edgar et al., in review). Species currently recognized as
threatened may prove a somewhat unusual subset of all species
because of the inclusion of many wide-ranging species such as
whales and tuna that require broad-scale (national and global)
action to address threats such as longlining, as well as
management of sites where animals aggregate to feed, mate
or spawn.
The low number of marine species with global threat
assessments to date should be overcome through the
acceleration of the IUCN Global Marine Species Assessment
(GMSA; http://www.sci.odu.edu/gmsa/), which aims to
systematically assess the Red List threat status of all species
within major marine taxonomic groups such as sharks and
rays, reef fish, corals, kelps and seagrasses. Both the GMSA
and the Census of Marine Life (O’Dor, 2004) will also play an
urgently needed role in the coordination, capture, and
management of existing marine biodiversity data, further
assisting the Red Listing process. Centralization of new and
existing species data will better facilitate the assessment of a
species’ threatened status using standard criteria associated
with extinction risk. To ensure this process remains rigorous
and comprehensive, close collaboration is needed between
taxonomic experts, regional data providers and assessors.
Irreplaceability criteria associated with species
concentrations in space or time
KBAs can be identified using irreplaceability criteria for: (a)
species with highly restricted global ranges (‘range-restricted’
or ‘endemic’ species); (b) species with highly clustered
distributions (‘clumped’ species); (c) species that temporarily
aggregate in particular sites (‘congregatory’ species); or (d)
species with small sub-populations that are responsible for
generating a significant proportion of recruitment (‘source’
species). Following conventions recognized for terrestrial KBA
identification, provisional percentage thresholds for these
categories are proposed (Table 1).
Until more detailed global analyses of species ranges are
completed, the initial set of species with sites to be considered
under the ‘restricted-range’ criterion are those with mapped
extent of occurrence or EOO (sensu IUCN, 2001) of less than
100 000 km2. A greater distributional area is applied here
compared to the 50 000 km2 used to define restricted-range
species in terrestrial situations (Langhammer et al., 2007)
because of the greater mean range size for marine species.
Approximately 3% and 4% of Indo-Pacific reef coral and reef
fish species, respectively, are defined as range-restricted using
the 50 000 km2 EOO threshold, and 3% and 9%, using the
100 000 km2 threshold (G. Allen, unpublished data; Hughes
et al., 2002; Allen, 2007). This compares with approximately
25% of all bird and mammal species, and 60% of amphibian
species, that fall within the 50 000 km2 EOO used for terrestrial
taxa (Eken et al., 2004). The occurrence in a site of,
provisionally, 5% of the population (or range) of a
‘restricted-range’ species would be required to trigger the
identification of a KBA under this criterion (Table 1).
Participants at the marine KBA workshop suggested that
the area of continental shelf be used in calculations of EOO for
species with mapped distributions that appear as long coastal
strings. This technicality was considered necessary for coastal
species with linear distributions that are difficult to quantify
realistically in terms of area, most notably intertidal species
distributed along continental margins. Larval dispersal of most
coastal marine species extends seawards, with the shelf break
used here to define the offshore distributional boundary for
such species.
A second class of species that may trigger the irreplaceability
criterion comprises those species that are widely distributed
but have clumped distributions in parts of their range. In other
words, large numbers of individuals may be concentrated in a
single or few sites while the rest of the species is widely
dispersed. Species with large extent of occurrence but small
area of occupancy can trigger this criterion. A provisional
threshold of 5% of the global population should trigger a
KBA for such species (Table 1), paralleling the threshold for
restricted-range species. An example is Guerney’s sea pen
Ptilosarcus gurneyi, which is distributed along the US west
coast from the Gulf of Alaska to southern California, but with
very high concentrations in Puget Sound (Birkeland, 1974).
Species with such wide distributions should only be considered
after other KBA criteria have been evaluated, given that most
species with clumped distributions are concentrated in an area
for only part of the year and should therefore also trigger the
congregatory criterion.
KBAs for congregatory species include: (a) assembly sites
where large numbers of individuals gather at the same time
(e.g. feeding, breeding and spawning sites); and (b) bottleneck
sites traversed by many individuals in the same season (e.g.
migratory sites). To meet the KBA sub-criterion for
congregations, a site must hold a significant proportion of
the global population of a congregatory species on a regular
basis. Based on the 1% thresholds in wide use under the
Ramsar Convention (BirdLife International, 2002) and
regional flyway initiatives (Asia-Pacific Migratory Waterbird
Conservation Committee, 2001) a provisional threshold of 1%
of the global population of a species is proposed. This
threshold requires further testing, especially in comparison
with a 5% threshold.
In conformity with Red List criteria, calculations of
population size are based on the number of mature
individuals, excluding individuals that will never produce
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new recruits to the global population (e.g. dioecious
individuals reproductively isolated from other individuals, or
individuals that produce larvae that drift offshore and are all
lost). In contrast to sites with plants and animals that generate
no new recruits, and hence are not considered as KBAs, some
marine sites make a disproportionately high contribution to
recruitment elsewhere. Such source sites should be designated
as KBAs when they contribute >1% of recruits to the global
population of the species, regardless of whether the total adult
population is clumped or not. Recognition of source sites is
necessary to safeguard sites such as the waters around
particular Caribbean islands that generate the majority of
juvenile spiny lobster recruitment to islands across the wider
region (Stockhausen et al., 2000).
An anomaly within the methodology developed for
terrestrial KBA identification, and inherited by the
provisional thresholds outlined here, is that a much smaller
proportion of the total population is sufficient to trigger a
KBA for species that aggregate seasonally (1%) compared to
spatially (5%). This can be supported on the grounds that it
has worked well so far in the terrestrial context. However, it
could also be argued that these thresholds should be reversed
in marine systems because restricted-range species face greater
extinction risk from localized stochastic threats. Threats that
are distributed at scales 5100 000 km2 may fully overlap the
distribution of a restricted-range species and therefore threaten
the total population with extinction if precautionary
management measures are not enacted. By contrast,
congregatory species with populations that are widely
distributed but not currently threatened (i.e. potentially able
to trigger KBA irreplaceability but not vulnerability criteria)
are less likely to become extinct as a consequence of threats
that are localized in time and space. The difference between
thresholds for congregatory and restricted-range taxa clearly
needs to be assessed in practice as a matter of urgency, then
standardized if appropriate within ongoing processes to refine
standard KBA methodology.
An additional irreplaceability criterion relating to
‘Bioregionally-restricted assemblages’ has been applied to
terrestrial sites that hold ‘a significant proportion of the
group of species whose distributions are restricted to a biome
or to a subdivision of it’ (Eken et al., 2004). This criterion has
not been used as widely in identifying KBAs as the two criteria
described above. Its usage evolved from Important Bird Area
(IBA) and Important Plant Area (IPA) criteria (Eken et al.,
2004), although these in turn differ in some respects. For IBAs,
this criterion has been defined as: ‘a significant component of
the group of species whose distributions are largely or wholly
confined to one biome’ (Fishpool and Evans, 2001). For IPAs,
this criterion covers two situations, either: ‘an exceptionally
rich flora in a regional context in relation to its biogeographic
zone’, or ‘an outstanding example of a habitat or vegetation
type of global or regional plant conservation and botanical
importance’ (Plant Diversity Challenge, 2004).
Given that the bioregionally-restricted criterion has not been
widely applied for a range of animal taxa in the terrestrial
context and is still regarded as under development, we suggest
that it be postponed from application to marine sites for the
present. An informed decision on the application of this
criterion and appropriate thresholds requires: (i) the
exploration of methodologies that have been used to classify
species assemblages and define biomes; (ii) analysis of different
bioregional classifications applied in the marine context; and,
importantly, (iii) the identification of important aspects of
marine biodiversity that are not captured through application
of the other criteria.
Regional testing of KBA criteria
To date, three main tests of KBA criteria in the marine
environment have been conducted. First, application of KBA
criteria described in this paper has been trialled within the
Galapagos Marine Reserve, as described in the associated
paper (Edgar et al., 2008). A total of 38KBAs were identified
along the Galapagos coastline using the vulnerability criterion,
comprising ca 10% of the total inshore area.
Second, although marine algae in the UK have received very
little direct conservation attention, three IPA criteria have
recently been applied to marine algae (Brodie et al., in press):
(A) significant populations of one or more species that are of
global or European conservation concern; (B) an exceptionally
rich flora in a European context in relation to its
biogeographical zone; (C) an outstanding example of a
habitat type of global or European plant conservation and
botanical importance. Criterion A falls within KBA guidelines
outlined here for species endemic to the Europe region, while
Criteria B and C largely relate to the bioregionally-restricted
assemblage criteria as applied to terrestrial KBAs.
Over 83 UK sites were suggested by members of the British
Phycological Society as possible candidate IPAs, nine of which
have been considered for possible European IPA designation.
While the application of IPA criterion C of outstanding
examples of habitat types was relatively uncomplicated, given
that most relevant habitats, including maerl beds, chalk and eel
grass beds at the UK level and reefs at the European level
already had conservation legislation, the application of criteria
A and B was less straightforward. This largely reflected the
lack of verifiable data, hence a pragmatic approach was needed
to apply criteria that were developed primarily with terrestrial
organisms in mind. A novel approach was devised utilizing
specimens from the algal herbarium and distribution maps.
For criterion A, a list of species with limited distribution was
made and then refined by specialists. This rare species list
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provided the basis for assessing species as potential Red List
candidates.
Until recently, the inclusion of seabirds in BirdLife
International’s IBA programme has been largely confined to
the identification and protection of terrestrial sites where more
than threshold numbers are present on a regular basis, such as
at nesting colonies, foraging grounds, and roosting locations.
The programme is, however, undergoing extension into the
marine realm, where four different ‘types’ of marine IBA are
being explored. The initial focus is on delimiting seaward
extensions to boundaries of existing IBAs designated for
seabird breeding colonies, to include the colonies’ adjacent
foraging areas. In addition, it is likely that IBAs will be readily
and increasingly identified for inshore concentrations of non-
breeding seabirds, such as seaduck, whose distributions are
largely circumscribed by water depth and access to sedentary
benthic food resources. Straits, headlands and other places
that act as migratory bottlenecks, through and around which
large numbers of seabirds funnel seasonally, will also be
identified. Finally, and most challenging of all, work is
underway to examine ways of identifying and delineating
IBAs for the key foraging areas of pelagic species. These
studies utilize information provided by satellite tracking
(BirdLife International, 2004b), combined with at-sea
observations and other data sources, in order to develop and
test criteria by which offshore IBAs may identified.
The process of identification of marine KBAs for a full
range of taxa has recently commenced through projects
undertaken by participants of the marine KBA workshop,
and others, in the Eastern Tropical Pacific, Philippines,
Indonesia, Madagascar, Australia, Brazil, Melanesia and
Polynesia, thereby providing a vital opportunity for
adaptively testing thresholds and criteria.
Outstanding issues associated with key biodiversity areas
Development of an optimal KBA methodology represents an
ongoing challenge, both in order to reduce subjectivity
associated with KBA identification, delineation and
prioritization, and also to facilitate implementation of KBA
and MPA networks with relevant stakeholders (Knight et al.,
2007). While subjectivity is less than with methodologies based
on the use of abstract habitat types as proxies, the KBA
process involves several challenges, most significantly because:
(i) species distributional datasets are inevitably imperfect,
hence KBA networks will also be imperfect, with a bias
towards well-studied sites;
(ii) irreplaceability thresholds are often difficult to apply in
practice because of the scarcity of good population data
at the global and site levels, making it near impossible to
accurately estimate the percentage of the global
population present at many sites;
(iii) some threatened species, such as the napoleon wrasse
Cheilinus undulatus (Donaldson and Sadovy, 2001) and
green turtle Chelonia mydas (Edgar et al., 2008), occur
widely, potentially creating a situation whereby the majority
of the global coastline is designated within KBAs; and
(iv) boundaries of KBAs can potentially be manipulated by
sectoral interests to achieve particular aims, with, in the
extreme situation, the existence of some KBAs dependent
on whether boundaries are drawn to encompass a
sufficient target population to trigger thresholds.
With respect to the first of these challenges, KBA networks
should be regarded as adaptive systems that will improve
through time as new data become available. Protection of a
site where a threatened species is known to occur, or which
possesses a high concentration of the known global
population, should be undertaken without delay regardless
of the possible but uncertain existence of individuals in under-
studied areas. If research later indicates that a species is more
widely distributed than initially believed, then existing and
potential KBAs involving that species should be re-evaluated,
and conservation resources directed to KBAs reallocated if
appropriate. An alternate strategy involving the protection of
sites where the existence of threatened species is predicted but
uncertain will, in many cases, result in overconfidence that
species are adequately safeguarded.
In cases where population data are poor and the second
challenge applies, proxies such as global percentage of suitable
habitat or range polygons for all sites at which the species is
known to occur can be used to generate proportionate
population estimates. These estimates should subsequently be
refined as better data become available.
The third challenge, that the KBA process will be debased if
all localities with confirmed records of widely-distributed
threatened species are recognized as KBAs, is partly
alleviated through the exclusion of sites with vagrant
occurrence of individuals, or less than 30 individuals of VU
species. Nevertheless, if application of thresholds outlined in
Table 1 in multiple regions is found to trigger an excessively
high number of KBAs, then thresholds will need to be adjusted
upwards to trigger fewer KBAs. Such a modification was
suggested by Edgar et al. (2008), who recommended that
marine KBAs not be recognised for wide-ranging EN and VU
species that are well represented in existing KBAs, unless at
least 1% of the global population is present at a site.
The fourth challenge relates to the variable potential size of
KBAs, with dimensions depending on the scale of local
management units and the extent of habitat considered
necessary to safeguard populations of species that trigger the
KBA. Boundaries of marine KBAs may follow habitat edges,
depth contours, existing or potential MPA boundaries,
exclusive economic zone or seabed-tenure borders, or other
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features, depending on the needs of the species that trigger the
KBA. Although methods for working through various
contrasting KBA delineation scenarios are outlined in
Langhammer et al. (2007), the development of standardized
globally-consistent methods for delineating KBAs would
greatly reduce subjectivity in boundary delineation.
In many cases, appropriate KBA boundaries are self-
evident, such as for species endemic to small islands, existing
MPAs, or individual estuaries. In other cases, decisions may
involve consideration of appropriate habitat or management
unit boundaries, and whether to aggregate multiple localities
with known species occurrence into a single KBA or to
consider different localities as separate KBAs.
A long-term strategy for standardizing decision rules
requires, first, identification of appropriate boundaries for
numerous KBAs on a case-by-case basis. Information on the
processes most often used to define individual KBA
boundaries should then be integrated into generalized
decision rules. This delineation process would be greatly
assisted if facilitated by an international agency or a
consortium with a mandate to maintain global KBA
standards and to recommend useful changes to criteria and
thresholds, in the same way that the Red List process is
facilitated by the IUCN.
Standardized methods also need to be developed for ranking
KBAs with respect to their priority for conservation
intervention and investment. A non-prioritized network of
KBAs has value in terms of providing a focal set of sites for
conservation action, local ownership, and building institutional
capacity; however, managers and conservation financiers
additionally require information on such factors as cost of
protection, level of local and government support, vulnerability
of site to external threats, ecosystem services presently and
potentially generated, and conservation value of each KBA.
Decision rules to prioritize the need for conservation action
among KBAs will greatly assist this process.
Alliance for Zero Extinction sites, which represent known
places where extinctions are imminent unless immediate
conservation action is taken (Ricketts et al., 2005), comprise
the highest priority set of KBAs with respect to conservation
intervention. Other likely prioritization rules, in no set order
and all else being equal, are: (i) KBAs with the greatest
proportion of the global population of a threatened or
aggregating species have highest priority, (ii) KBA sites
identified for Critically-Endangered (CR) species have higher
priority than sites identified for Endangered (EN) species,
which have higher priority than sites for Vulnerable (VU)
species; (iii) KBAs identified to safeguard a species not
protected elsewhere have highest priority; (iv) KBAs
safeguarding more than one species have higher priority than
sites identified for a single species; (v) KBA sites that are highly
vulnerable to known threats have higher priority than sites
lacking apparent threats if a large percentage of the global
population of threatened or aggregating species utilize that site
(i.e. it is highly irreplaceable; Langhammer et al., 2007); and
(vi) KBAs identified to protect species with significant
ecological roles, such as keystone or habitat-forming species,
have high priority.
Algorithms such as MARXAN (Ball and Possingham, 2000)
are available to maximize site complementarity (category iii
above) and site representation (category iv) in MPA networks;
however, additional decision rules are needed to incorporate
species vulnerability (categories (i) and (ii)), site vulnerability
(category (v)) and ecological interaction strength (category
(vi)) into the prioritization framework. Decision rules
based on interactions between the six categories above are
particularly needed, such as: ‘Is an MPA with 90% of the
population of two EN species a higher conservation priority
than an MPA with 50% of the population of a CR species?’
Such questions are best answered by quantifying relationships
between threat and extinction risk.
An issue related to the prioritization of KBAs is the
identification of representation targets within MPA networks
using reserve selection algorithms. KBAs represent an essential
component of any representative MPA network because of
their irreplaceability, hence should be identified as an initial
step if networks are to be complementary, adequate and
representative. Clearly, if a KBA is designated for a species not
found elsewhere, then that site is a necessary component within
any fully representative network.
Although a number of outstanding issues associated with
development of KBA networks remain, as discussed above, the
variety of benefits provided by KBAs should not be
underestimated. The following strengths indicate that the
role of KBAs in systematic MPA planning should be
overwhelmingly positive:
(i) KBAs are founded on previous initiatives (e.g.
Important Bird Areas, Alliance for Zero Extinction),
hence existing de facto KBAs have already been
identified in many countries.
(ii) KBAs consider all taxonomic groups for which data
exist.
(iii) KBAs target all known biodiversity that would benefit
from conservation activities undertaken at the scale of
individual sites.
(iv) KBAs can be based on any species-level data, allowing
the KBA process to begin immediately with iterative
updating as more data become available.
(v) KBA identification relies on inexpensive and
straightforward procedures that can typically be
completed within a short timeframe.
(vi) Leadership and ownership of the KBA process occurs at
local (or sometimes national or regional) levels, but
G.J. EDGAR ET AL.980
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follows global standards and criteria that allow
comparability and consistency.
Local leadership is important because allocation of resources
to protect KBAs will inevitably involve subjectivity in terms of
tradeoffs between perceived needs, threats, benefits and costs,
regardless of the availability of sophisticated analytical tools.
Because these tradeoffs are best understood locally, and
stakeholder ownership is critical to the success of protected
areas, identification and implementation of the KBA process
is best achieved through activities undertaken at local and
national levels. Local activities should include monitoring,
which is integral to any implementation strategy given that
improved boundary delineation and more effective species
protection depend heavily on an understanding of population
trends for those species whose presence triggers a KBA.
Development of KBA networks involves feedback at many
levels. On the one hand, KBA criteria will need to be modified
if found deficient in the protection of threatened or aggregating
species, while remaining simple and globally consistent. On the
other, individual KBAs and KBA networks must adapt to
changing environmental conditions and data availability. This
is particularly important in the current era of global
environmental change, when a major challenge is to foresee
fragmentation of biota at existing locations through
extirpation, emigration and immigration. Thus, marine KBA
networks will inevitably evolve through time, as is also the case
with terrestrial KBAs. Sites will be added to the network as new
data on threats and species distribution become available, and,
in cases of the delisting of threatened species, or local
extirpation or populations decline below trigger values, sites
will also occasionally lose KBA status.
CONCLUSIONS
The data-driven and species-based KBA concept allows
systematic identification and conservation of sites of global
biodiversity significance through application of simple criteria.
This concept fills a critical need to incorporate species
vulnerability into MPA planning, and should prove useful
for overcoming deficiencies in current planning strategies.
KBA criteria have been largely applied to date in terrestrial
situations, and require some further modification to work
effectively in marine situations because of the generally larger
distributional ranges of marine taxa, the linear distributions of
many coastal species when mapped at regional scales, and a
paucity of observational data for marine plants and animals.
Criteria and thresholds to identify marine KBAs provisionally
outlined in this paper require testing as a matter of urgency, as
do decision rules for delineating KBA boundaries, and for
prioritizing conservation action amongst sites. Nevertheless,
although the thresholds proposed here are provisional, marine
sites have already been identified as KBAs that are globally
significant and that represent clear targets for conservation
action. Once an initial set of KBAs have been identified in a
region, conservation activities should begin as soon as
possible, rather than waiting for criteria to be finalized or a
full network of sites identified.
ACKNOWLEDGEMENTS
We greatly appreciate opinions and contributions to the paper
provided by the rest of the participants at the Marine KBA
Development Workshop}Hari Balasubramanian, Jamie
Bechtel, Robert Bensted-Smith, Mauricio Cervantes, Dan
Costa, Guilherme Dutra, Sylvia Earle, Mark Erdmann,
Claude Gascon, Arlo Hemphill, Scott Henderson, Brian
Hutchinson, Roger James, Jennifer Jeffers, Thomas Lacher,
Sheila McKenna, Rod Mast, Emily Pidgeon, Ketut Putra,
Marco Quesada, Mags Quibilan, Philippe Razafinjatovo,
Simon Stuart, Sue Taei, Sheila Vergara, Charlie Veron, Fred
Wells and Kristen Williams. The project was made possible by
grants provided by the Walton Family Foundation, the
Gordon and Betty Moore Foundation (through the Marine
Management Area Science project), and the Global Marine
Division of Conservation International, with additional
support to GJE provided by the Australian Research
Council. We thank Ray Murphy for data used in Figure 3,
Vanessa Lucieer for base maps, and John Croxall, Tim Lynch,
Bob Pressey, Jamie Kirkpatrick and an anonymous reviewer
for comments on the draft manuscript.
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