Supplementary material
Appendix S1. Prioritization approaches in practice: What are they used for?
Legal status
Even though threatened species lists are not designed for species prioritization, often these
are used straightforwardly to assign legal protection status to species. Some countries have
developed their own prioritization schemes specifically for that purpose (some examples in
de Grammont and Cuaron 2006).
Identifying focal species for conservation action
The simplest form of prioritization is to identify as focal species only the ones that are of
conservation interest, while ignoring the other species. For example, only threatened, rare,
endemic or keystone species may be considered (Ceballos and Ehrlich 2006). However,
often the use of a specific group is due to assumed surrogate relationships with other
species (e.g., Das et al. 2006), rather than to preference for one group over the others.
Assigning conservation targets
Targets for conservation, usually as percentage of individuals, populations or distribution to
be protected, can be assigned differently according to species priorities. Targets are
frequently assigned based on threat category or various forms of rarity, but more specific
population parameters can also be used when available (Pressey et al. 2003).
Species weights in systematic conservation planning
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Certain reserve selection approaches allow for the use of differential species weights. These
approaches operate in terms of maximization of “conservation value” across selected sites,
which depends on the weights of the species that occur at the sites (Arponen et al. 2005;
Early and Thomas 2007; Kremen et al. 2008), rather than relying on mere species richness
and fixed targets.
Maximizing persistence of diversity directly in systematic conservation planning
This can be seen as prioritization in the sense that species contribute differentially to total
diversity. Any diversity measure can be incorporated directly in the objective function in
systematic conservation planning, for example phylogenetic diversity (Polasky et al. 2001;
Forest et al. 2007). In practice, reserve sites are selected in order to maximize the
(persistence of the) diversity measure instead of maximizing species richness (see also Fig.
1).
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Appendix S2. Assessing extinction risk
Some examples of methods for assessing extinction risk, that have then been used to assign
conservation priorities. More comprehensive reviews of assessing extinction risk are
Andelman et al. (2004) and DeGrammont and Cuaron (2006).
IUCN Red List (IUCN 2001)
A rule-based system. The oldest (1966) of threat classification systems, but has been
frequently updated. The scheme is applicable to all macro-fauna and flora. Created for
global scale use, but guidelines for application at regional levels were published in 2003. It is
considered the most robust system (de Grammont and Cuaron 2006) because it uses
quantitative criteria which are based on population biology (life history, habitat
requirements, abundance, distribution, threats, any specified management options of that
species). The threat categories are defined only in terms of extinction risk over explicit,
increasing time periods. The list itself is produced by a network of over 7000 species
experts.
Being the most widely applied system, it has provoked much discussion. It has been
criticized and praised even for the same qualities: Being rule-based implies low data
requirements, but also that it does not take advantage of all available data – a species that
nearly fulfils several criteria for being classified as endangered is in the same category with a
species that barely meets one criterion for being vulnerable (Mace et al. 2006). Another
positive feature of a rule-based system is that it is explicit about which features of a species
led to its listing (Mace et al. 2006). It also provides guidance on how to deal with uncertainty
when applying the criteria (see also Akçakaya et al. 2000; Regan et al. 2000).
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Criteria include: Population size and size reduction, extent of occurrence or area of
occupancy, quantitative analysis of extinction risk, degree of fragmentation, extreme
population fluctuations, and skewed population structure.
Risk categories: extinct (EX), extinct in the wild (EW), critically endangered (CR), endangered
(EN), vulnerable (V), near threatened (NT), least concern (LC)
NatureServe Conservation Status (NatureServe 2008)
A rule-based system, with the difference to the IUCN scheme that all criteria are taken into
account in classification. It is applicable at any geographical scale, and to communities and
ecosystems in addition to species. Most criteria are defined numerically, and data
requirements are high, although both empirical data and expert opinion can be used as data
inputs.
Criteria include: number and condition of occurrences, population size, range extent, area of
occupancy, short- and long-term trends in all above mentioned factors, threats (scope,
severity, and immediacy), intrinsic vulnerability, number of protected and managed
occurrences, and environmental specificity.
Risk categories: critically imperilled, imperilled, vulnerable to extirpation or extinction,
apparently secure, and demonstrably widespread, abundant and secure (and a number of
additional categories for special cases such as species of only historical occurrence or with
insufficient information).
Conservation Priority Index (Cofré and Marquet 1999)
4
A point scoring method. Applicable at all geographical scales, although initially created for
national use (Chile). It differs from the previous systems also in that it is mostly based on
(anthropogenic) threats and species intrinsic characteristics instead of population trend
data, which the authors claim are often hard to acquire. Consequently, it evaluates potential
vulnerability rather than actual extinction risk (de Grammont and Cuaron 2006). It is not a
pure threat assessment technique but a prioritization scheme that combines for example
“taxonomic singularity” with extinction risk. It is flexible regarding data requirements (some
criteria are quantitative, some not), but also problematic in that some criteria are
redundant.
Criteria include: number of ecoregions where species is found, geographic distribution
within Chile, local abundance, degree of endemism, taxonomic singularity, body mass,
presence on IUCN list, effect of human activities, and degree of protection.
Risk categories: No categories. Species are assigned a “priority index” which is the sum of
scores for all criteria, ranging from zero to 27, with species scoring at least 12 considered as
priority.
Appendix S3. Combining different criteria
This appendix does not attempt to cover the extensive literature on multi-criteria analyses
that can and often do combine species-level criteria with any other kinds of criteria, ranging
from reserve connectivity to cultural heritage value. These are reviewed elsewhere (Moffett
and Sarkar 2006). Instead, I give a few examples of typical ways of combining different
species-level criteria into a single score or objective.
5
Additive scoring approaches
Species scores are (often weighted) sums of scores given based on different criteria. One of
the most comprehensive approaches regarding the criteria used is Marsh et al. (2007):
Extinction risk, consequences of extinction (including factors such as uniqueness of
ecological role, genetic and taxonomic uniqueness) and potential for successful recovery
(including knowledge of and capacity to control threatening processes, costs of conservation
action and biological recovery potential). Other examples include e.g. Cofré and Marquet
(1999) and Keith et al. (2007). Summing of scores is problematic because criteria may be
correlated and some factors therefore “inflated”, and for instance, if a species has zero
potential of recovery, it may still receive a relatively high score due to high impact of its
extinction.
Multiplicative scoring approaches
Multiplication implies that all criteria are important and do not independently influence
species’ priority, for example, only the species which are both unique and in need of
protection receive high weights, and neither criterion alone is enough. Multiplying an
indicator of extinction risk with a proxy of uniqueness is essentially an estimate of expected
loss if no conservation actions are taken. Arponen et al. (2005) derive species weights by
multiplying a “taxonomic uniqueness” score with a threat score (a weighted sum of scores
derived from Red List classifications and a measure of national rarity). Also the EDGE score
(Isaac et al., 2007) falls within this category. See also the approaches to evaluate expected
loss of biodiversity by Witting and Loeschke (1995) and Redding and Mooers (2006). This
way only the species which are both unique and in need of protection receive high weights,
and neither criterion alone is enough.
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Species’ contribution to “future expected diversity”
Weitzman’s (1998) species ranking index gives the contribution of a species to “future
expected diversity”. It maximizes numbers of features (genes) across species taking account
of probabilities of extinction and costs of changing them, as well as species “utility”
estimations (species value per se, irrelevant from a biodiversity viewpoint). Regarding how
species uniqueness is considered, this measure does not differ essentially from previous
approaches (e.g., Faith 1992). This approach combines costs and effectiveness of
conservation actions, and species’ dissimilarities, but ignores differential quantities of
features carried by species. The approach has recently been further refined and applied by
Joseph et al. (2009) by the name “Project Prioritization Protocol” to produce rankings of
species-specific conservation projects. Approaches to solving this computationally difficult
problem are discussed in Hartmann and Steel (2006).
Species’ differential contribution to conservation benefit in systematic conservation
prioritization
Instead of producing species scores or rankings, or ranking of conservation projects, species’
differential contribution to conservation benefit can be directly accounted for in systematic
conservation prioritization (see also Appendix S1 and Fig. 1). Mace et al. (2006) maximize
the number of species surviving. This approach combines costs and effectiveness of
conservation actions, but ignores species’ differential contribution to total diversity
(uniqueness). Others maximize phylogenetic diversity considering also number or area of
reserves as surrogate for conservation costs, but ignore need and effectiveness of
protection (Polasky et al. 2001; Forest et al. 2007)
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References
Akçakaya HR, Ferson SS, Burgman MA, Keith DA, Mace GM, Todd CR (2000) Making consistent IUCN
classifications under uncertainty. Conserv. Biol. 14: 1001-1013
Andelman SJ, Groves C, Regan HM (2004) A review of protocols for selecting species at risk in the
context of US Forest Service viability assessments. Acta Oecol. 26: 75-83
Arponen A, Heikkinen RK, Thomas CD, Moilanen A (2005) The Value of Biodiversity in Reserve
Selection: Representation, Species Weighting, and Benefit Functions. Conserv. Biol. 19:
2009-2014
Ceballos G, Ehrlich PR (2006) Global mammal distributions, biodiversity hotspots, and conservation.
Proceedings of the National Academy of Sciences 103: 19374-19379
Cofré H, Marquet PA (1999) Conservation status, rarity, and geographic priorities for conservation of
Chilean mammals: an assessment. Biol. Conserv. 88: 53-68
Das A, Krishnaswamy J, Bawa KS, Kiran MC, Srinivas V, Kumar NS, Karanth KU (2006) Prioritisation of
conservation areas in the Western Ghats, India. Biol. Conserv. 133: 16-31
de Grammont PC, Cuaron AD (2006) An evaluation of threatened species categorization systems
used on the American continent. Conserv. Biol. 20: 14-27
Early R, Thomas CD (2007) Multispecies conservation planning: identifying landscapes for the
conservation of viable populations using local and continental species priorities. J. Appl. Ecol.
44: 253-262
Faith DP (1992) Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61: 1-10
Forest F, Grenyer R, Rouget M, Davies TJ, Cowling RM, Faith DP, Balmford A, Manning JC, Proches S,
van der Bank M, Reeves G, Hedderson TAJ, Savolainen V (2007) Preserving the evolutionary
potential of floras in biodiversity hotspots. Nature 445: 757-760
Hartmann K, Steel M (2006) Maximizing Phylogenetic Diversity in Biodiversity Conservation: Greedy
Solutions to the Noah's Ark Problem. Syst. Biol. 55: 644 - 651
International Union for Conservation of Nature (2001). IUCN Red List categories and criteria version
3.1.
Joseph LN, Maloney RF, Possingham HP (2009) Optimal allocation of resources among threatened
species: a Project Prioritization Protocol. Conserv. Biol. 23: 328-338
Keith M, Chimimba CT, Reyers B, van Jaarsveld AS (2007) A comparative analysis of components
incorporated in conservation priority assessments: a case study based on South African
species of terrestrial mammals. Afr. Zool. 42: 97-111
Kremen C, Cameron A, Moilanen A, Phillips SJ, Thomas CD, Beentje H, Dransfield J, Fisher BL, Glaw F,
Good TC, Harper GJ, Hijmans RJ, Lees DC, Louis E, Jr., Nussbaum RA, Raxworthy CJ,
Razafimpahanana A, Schatz GE, Vences M, Vieites DR, Wright PC, Zjhra ML (2008) Aligning
Conservation Priorities Across Taxa in Madagascar with High-Resolution Planning Tools.
Science 320: 222-226
Mace GM, Possingham H, Leader-Williams N (2006) Prioritizing choices in conservation. In:
Macdonald D, Service K (eds) Key topics in conservation biology, 1st edn. Blackwell
Publishing, pp. 17-34
Marsh H, Dennis A, Hines H, Kutt A, McDonald K, Weber E, Williams S, Winter J (2007) Optimizing
allocation of management resources for wildlife. Conserv. Biol. 21: 387-399
Moffett A, Sarkar S (2006) Incorporating multiple criteria into the design of conservation area
networks: a minireview with recommendations. Divers. Distrib. 12: 125-137
NatureServe (2008). NatureServe Conservation Status.
8
Polasky S, Csuti B, Vossler CA, Meyers SM (2001) A comparison of taxonomic distinctness versus
richness as criteria for setting conservation priorities for North American birds. Biol. Conserv.
97: 99-105
Pressey RL, Cowling RM, Rouget M (2003) Formulating conservation targets for biodiversity pattern
and process in the Cape Floristic Region, South Africa. Biol. Conserv. 112: 99-127
Redding DW, Mooers AO (2006) Incorporating Evolutionary Measures into Conservation
Prioritization. Conserv. Biol. 20: 1670-1678
Regan HM, Colyvan M, Burgman MA (2000) A proposal for fuzzy International Union for the
Conservation of Nature (IUCN) categories and criteria. Biol. Conserv. 92: 101-108
Weitzman ML (1998) The Noah's Ark problem. Econometrica 66: 1279-1298
Witting L, Loeschke V (1995) The optimization of biodiversity conservation. Biol. Conserv. 71: 205207
9