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322 2016, VOL. 92, No3 — THE FORESTRY CHRONICLE
A review of applications of the six-step method
of systematic conservation planning
by Yolanda F. Wiersma1,* and Darren J.H. Sleep2
ABSTRACT
Systematic Conservation Planning (SCP) is an approach to protected areas planning that follows a step-by-step process.
Recent reviews have examined the use of key “biogeographic-concepts”, but an assessment of their use or effectiveness has
not been done. We conducted a review of the literature on SCP to assess how the 6-step approach considers these con-
cepts. Most of the 127 papers we reviewed varied in their application of SCP steps. Our findings suggest that protected
areas plans are not effectively achieving conservation goals. Only six papers considered data uncertainty. Twenty papers
used so-called “data free” conservation targets without clear rationales, and which have been shown to under-represent
natural features. The median size of planning units applied (2500 ha) is too small to meet minimum area requirements
for many species. We show how an examination of the variation in the ways that SCP is applied helps to identify best prac-
tices for achieving conservation effectiveness and efficiency. However, very few SCP efforts have been implemented, mak-
ing it difficult to assess their effectiveness or efficiency in practice. Detailed examination of how SCP is implemented (per-
haps focused on a specific region) can lead to a better understanding of how best to achieve large-scale conservation goals.
Key words: Systematic Conservation Planning, 6-step biogeographic-concepts, protected areas
RÉSUMÉ
La planification systématique de la conservation systématique (PSCS) consiste enest une approche méthode utilisée dans
la planification des territoires protégés qui suit s’appuie sur une démarche séquentielle. Des études récentes se sont penchée-
sont étudié sur l’emploi dess plus importants « «concepts biogéographiques »» clés, mais aucune évaluation de son leur uti-
lisation ou de son leur efficacité n’a encore jamais été faiteréalisée. Nous avons dons effectué une revue de la littératureana-
lyse documentaire portant sur la PCS afin d’évaluer comment cette approche en 6 étapes tient tenait compte de ces concepts.
La plupart des 127 articles que nous avons étudiés parcourus affichaient montraient une certainegrande variabilité dans
l’utilisation des étapes de la PCS. Nos résultats laissent entendre voir que les plans pour ldes territoires protégés n’atteignent
pas les objectifs de conservation. Seulement six articles ont abordé l’incertitude entourant les données. Vingt articles ont
utilisé des objectifs de conservation soi-disantdits « «non rattachéssans à des données » et sans justification précise et qui
se sont révélés àavérés sous-représenter les caractéristiques naturelles. La taille médiane des unités de planification étudiées
(2500 ha) est trop petite pour répondre aux exigences de superficie minimale de plusieurs espèces. Nous indiquons mon-
trons comment comment une étude de l’examen de la variation danse l’application de la PCS permet d’identifier les
meilleures pratiques qui contribueront à l’atteinte de permettant d’atteindre l’efficacité efficience et l’efficacité efficience en
matière de conservation. Cependant, il y a eu peu de bien peu de projets de PCS ont été mis en œuvrecomplets, ce qui rend
difficile d’évaluer une évaluation pratique de leur efficacité efficience ou de leur efficienceefficacité dans la pratique. Une
étude détaillée sur la façon d’implanter la PCS (peut- être en se concentrant sur une région donnée) permettrait d’obtenir
une meilleure compréhension de la démarche à suivre pour atteindre les objectifs de conservation à grande échelle.
Mots-clés: planification de la conservation systématique, six étapes des concepts biogéographiques en six étapes, terri-
toires protégés
1Department of Biology, Memorial University, St. John’s, Newfoundland and Labrador, A1B 3X9, Canada *corresponding author:
ywiersma@mun.ca
2National Council for Air and Stream Improvement, P.O. Box 1036, Stn B, Montreal, Québec, H3B 3K5, Canada
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2016, VOL. 92, No3 — THE FORESTRY CHRONICLE 323
Introduction
Landscapes maintained and managed as protected areas are
intended to protect special ecological spaces or values (water-
sheds, critical habitat for threatened species), or to act as reserves
to maintain biodiversity (Duinker et al. 2010). In some cases,
protected areas may have other uses as well, such as the preser-
vation of natural or semi-natural benchmarks for contrast with
developed areas (Arcese and Sinclair 1997), or the maintenance
of landscape types that are difficult to maintain on intensely
managed landscapes. In these cases, protected areas may be con-
sidered a complimentary land use to natural resource manage-
ment such as forestry, agriculture or grazing. Protected areas, as
well as other types of land use may also provide aesthetic, recre-
ational or educational values (Dearden 1995).
The way in which protected areas are established to meet
conservation objectives has evolved from its initial focus on
the designation of single sites of exceptional aesthetic, recre-
ation, or biodiversity value (Runte 2010). Systematic Conser-
vation Planning (SCP) has emerged as an approach to iden-
tify sites for protected areas and facilitate decision-making
with an emphasis on the use of protected areas as a key tool in
biodiversity conservation. However, we contend that land-use
planning for protected areas (SCP) is not as rigorous as plan-
ning within other natural resource sectors (e.g., forestry),
mainly due to inconsistencies in the ways that key concepts
and steps in SCP are applied. While some variation in appli-
cation may be expected due to regional contexts, our concern
is that inconsistencies can lead to misunderstanding between
practitioners, lack of clarity on best practices, and reduced
effectiveness and efficiency of conservation initiatives.
SCP concepts were popularized with the publication of a
paper in Nature (Margules and Pressey 2000) and a special
issue on the topic in Biological Conservation (Cowling and
Pressey 2003), and resulted in a “period of expansion” of SCP
(Kukkala and Moilanen 2013: 446). Based on these early con-
cepts, Margules and Pressey (2000) outlined six key steps for
SCP (Table 1). These were later expanded upon by others to
provide details on the step of goal setting (Step 2; Tear et al.
2005) and to refine and expand the other steps (Gaston et al.
2002, Margules et al. 2002, Sarkar 2005, Wilson et al. 2005,
Pressey and Bottrill 2009, Sarkar and Illoldi-Rangel
2010).The literature on SCP has proliferated in the past two
decades (see Fig. 1 in Kukkala and Moilanen 2013).
Despite increased conservation literature on protected
areas design, threats to biodiversity persist and losses con-
tinue (McKee et al. 2004), and recent papers have called for
increases in protected areas globally (Venter et al. 2014,
Larsen et al. 2015). Thus, consistency around how to best
make decisions on the identification of priority areas for con-
servation is important. In their concluding paragraph,
Kukkala and Moilanen (2013: 460) ask “Are the operational
definitions of these concepts clear and applicable in real-
world planning?” Our work is motivated by this statement.
We conducted an in-depth review of 127 papers that docu-
ment application of SCP concepts to assess whether and how
application of SCP varies globally. Although variation in
application is to be expected due to variation between sites
(e.g., tropical vs. temperate), we were interested in whether
there is variation due to lack of clarity in the way SCP steps
and concepts are applied.
Although there is a large body of peer-reviewed literature
on SCP, including several reviews (Justus and Sarkar 2002,
Pressey et al. 2007, Sarkar 2012, Kukkala and Moilanen 2013)
and a book (Moilanen et al. 2009), there has been little work
comparing and contrasting how SCP is applied around the
globe. SCP has been widely embraced, but the steps outlined
by Margules and Pressey (2000) have not always been applied
in the same ways. We are not aware of any systematic exami-
nation of which aspects of SCP (e.g., targets, study area and
planning unit type/size, tools, methods) best achieve effective
conservation outcomes (but see Van Teeffelen et al. 2012).
A thorough evaluation of the effectiveness of SCP is out-
side the scope of this review. Rather, here we conducted an
assessment of the peer-reviewed literature to compare and
contrast how the original six steps of SCP as outlined by Mar-
gules and Pressey (2000) have been operationalized around
the world. Our review is not intended to comment on the util-
ity of the original six steps themselves (which, as pointed out
above, have been updated several times), but rather to exam-
ine the variety of ways in which the steps and underlying con-
cepts have been interpreted and applied as a means to evalu-
ate the way they are operationalized. We structured our
review around the original six steps of SCP (Margules and
Pressey 2000) although it is important to note that in real-
world conservation planning these steps are not necessarily
directional. We have listed the original six steps from Mar-
gules and Pressey (2000), and juxtaposed these with the key
concepts from Kukkala and Moilanen (2013) that are perti-
nent to each step (Table 1). Thus, the purpose of this review is
to compare and contrast how SCP steps have been applied in
the real world, and to assess whether and how individual ini-
tiatives have addressed some of the uncertainties inherent in
the application of each of the steps and key concepts. Specifi-
cally, we evaluated: (1) the number and type of conservation
features used in SCP (along with the degree to which uncer-
tainties in data and validity as surrogates were evaluated); (2)
the different types of goals and targets used to inform SCP; (3)
the types of evaluation strategies applied to assess existing
protected areas; (4) the range of tools applied to carry out
SCP; (5) the degree to which implementation strategies are
documented; and, (6) how projects carry out evaluations of
the effectiveness of SCP.
Methods
Terminology
In a recent comprehensive review of the SCP literature,
Kukkala and Moilanen (2013) identified and examined 12
Yolanda F. Wiersma Darren J.H. Sleep
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324 2016, VOL. 92, No3 — THE FORESTRY CHRONICLE
Table 1.
Key SCP Concepts
Systematic Conservation Planning (SCP) Steps (Kukkala & Moilanen 2013)
(Margules & Pressey 2000) for consideration Findings from this Review
1. Compile data on the biodiversity of the planning region.
• Review existing data and decide on which data sets • The conservation plan will be • Most plans use whatever data are
are sufficiently consistent to serve as surrogates for limited at the outset by how available without a rigorous
biodiversity across the region. comprehensive the biodiversity evaluation of their ecological
data are. importance.
• If time allows, collect new data to augment or replace
some existing data sets • It will be important to consider • Species are often presumed to be
how representative the features for surrogates (i.e., representative
• Collect information on the localities of species which there are data are of the of) for other elements of the
considered to be rare and/or threatened in the region wider suite of biodiversity features. ecosystem, without sufficient
(these are likely to be missed or under-represented in testing.
conservation areas selected only on the basis of land • Data on species that may be under
classes such as vegetation types). threat might be of particular • Common features and species
relevance. are used more in planning than
rare ones; where rare species are
included, they are not always
threatened.
2. Identify conservation goals for the planning region.
• Set quantitative conservation targets for species, • An evaluation of the adequacy of • Targets are often data-free and
vegetation types or other features (for example, at targets for achieving goals is not evaluated as to whether they
least three occurrences of each species, 1500 ha of necessary. are adequate for the region.
each vegetation type, or specific targets tailored to
the conservation needs of individual features). Despite • Targets are usually devised to • The literature suggests that there
inevitable subjectivity in their formulation, the value ensure representation of the bio- is no universal target; goals and
of such goals is in their explicitness. diversity features for which there targets should be specific to each
are data. project.
• Identify qualitative targets or preferences (for example,
as far as possible, new conservation areas should
have minimal previous disturbance from grazing
or logging).
3. Review existing conservation areas.
• Measure the extent to which quantitative targets for • Inclusion of existing poor-quality • Few plans rigorously evaluate
representation and design have been met my existing conservation areas may carry high existing protected areas, even
conservation areas. cost though there is good evidence to
support criteria (e.g., size, intact-
• Identify the imminence of threat to under-represented • How vulnerable existing conser- ness) for protected areas that
features such as species or vegetation types, and the vation areas are will influence the will promote biodiversity
threats posed to areas that will be important in selection of additional area. conservation.
securing satisfactory design targets.
4. Select additional conservation sites.
• Regard established conservation areas as “constraints” • Algorithms and decision-support • There are many tools and strate-
or focal points for the design of an expanded system. software often incorporate gies to carry out conservation
principles of complementarity. planning; most are based on
• Identify preliminary sets of new conservation areas concepts of efficiency and
for consideration as additions to established areas. • Selection processes are designed complementarity.
Options for doing this include reserve selection to maximize efficiency.
algorithms or decision-support software to allow • A comparison of software pack-
stakeholders to design expanded systems that achieve ages (of which there are several)
regional conservation goals subject to constraints such was beyond the scope of the
as existing reserves, acquisition budgets, or limits on paper.
feasible opportunity costs for other land uses.
• Modern computing has ren-
dered moot the debate between
using heuristic vs. optimization
algorithms.
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2016, VOL. 92, No3 — THE FORESTRY CHRONICLE 325
core concepts of SCP (adequacy, comprehensiveness, repre-
sentativeness, representation, complementarity, threat, vul-
nerability, efficiency, effectiveness, irreplaceability, replace-
ment cost, flexibility) and suggested that while some are
well-defined, others have conflicting definitions and usage in
the literature. Thus, for clarity, we outline the meaning of
terms as we use them in this review. When we refer to the
“design” of protected areas networks, we refer to a formalized
strategy or method to identify potential protected areas
within a larger region (where “region” can refer to an individ-
ual country or natural or political subdivisions thereof). “Net-
works” refers to multiple protected areas (also referred to as
the “network set”) within a defined spatial region that either
have physical or ecological connectedness (to facilitate flow of
organisms and processes) and/or are designed in concert with
each other within a region to concomitantly meet a larger
conservation goal.
We adopt terminology more common in the Australian
and South African literature on SCP and also used in Mar-
gules and Pressey (2000) which differs from terms used else-
where (Groves 2003). Thus we use “goal” to mean the overall
purpose of the conservation effort. In this case, the goal of all
the SCP efforts discussed in the reviewed papers is to achieve
biodiversity conservation; however, in individual papers the
goal may be more specific, such as the conservation of threat-
ened vertebrates or of endemic plants within a defined region.
We use the term “conservation feature” to mean the entity
that is the focus of conservation in a particular study; other
papers, e.g., Groves 2003, use the term “biodiversity target” or
“conservation target” to mean the entity of conservation
interest, and Margules and Pressey (2000) refer to such data
as “surrogates for biodiversity”. Here “conservation target”
refers to the desired level of conservation in the final reserve
network. This can be expressed in a variety of ways (see dis-
cussion of Step 2 below). Common examples of conservation
targets are specified minimum number of populations of the
conservation feature, or a minimum level of representation of
particular habitat types.
Literature Search
To carry out our analysis we conducted a literature search
using the Scopus database. We searched the following search
strings sequentially: “systematic conservation planning”,
“reserve design” OR “protected area design”, and “reserve
network”. The sequential search yielded some duplicate find-
ings which were removed, but searching “reserve network”
yielded a different set than “reserve design” and thus this
sequential search was necessary. We also searched the terms
“reserve” OR “protected area” in combination with (i.e., log-
ical operator AND) the terms “hotspots” and “gap analysis”,
since these terms represent early strategies applied in SCP.
We did not search on the above terms without quotes,
(although this yielded a larger number of articles, for exam-
ple a search on “systematic conservation planning” without
quotes yielded over 500 articles) because many of these were
about conservation and/or planning, and not specifically on
Table 1 (continued)
Key SCP Concepts
Systematic Conservation Planning (SCP) Steps (Kukkala & Moilanen 2013)
(Margules & Pressey 2000) for consideration Findings from this Review
5. Implement conservation actions
• Decide on the most appropriate or feasible form of •The degree of irreplaceability of •There is very little description of
management to be applied to individual areas (some particular sites should also inform plans which have been fully
management approaches will be fallbacks from the prioritization. implemented.
preferred option)
• How easy it is to implement the • Implementation requires think-
•If one or more selected areas prove to be unexpectedly conservation plan may depend in ing about dimensions beyond
degraded or difficult to protect, return to stage 4 and part on the inherent flexibility of scientific/ecological ones;
look for alternatives. the plan. including economic, social and
political contexts.
• Decide on the relative timing of conservation manage-
ment when resources are insufficient to implement
the whole system in the short term (usually).
6. Maintain the required values of conservation areas
• Set conservation goals at the level of individual • With long-term monitoring, it will •There are no descriptions of case
conservation areas (for example, maintain seral habitats be possible to evaluate the effec- studies where conservation plans
for one or more species for which the area is important). tiveness of the conservation have been implemented and
Ideally, these goals will acknowledge the particular network. monitored for their effectiveness.
values of the area in the context of the whole system.
• Implement management actions and zonings in and
around each area to achieve the goals.
• Monitor key indicators that will reflect the success of
management actions or zonings in achieving goals.
Modify management as required.
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326 2016, VOL. 92, No3 — THE FORESTRY CHRONICLE
SCP in the sense in which we wanted to focus. We also did
not choose to use the names of specific tools (e.g., “Marxan”
or “Zonation”) as keywords in our initial search. Although
searches on these terms yielded a large number of articles,
our goal was to assess the way SCP strategies were applied,
not specific tools. We conducted forward and back citation
searches to find additional articles and included papers from
around the world. We selected articles that described real-
world data (that is, simulation modelling and conceptual
papers were excluded) and met at least one of the following
criteria of SCP: 1) the plan included quantitative targets; 2)
the focus of the paper was on improving methods for identi-
fying and/or establishing networks of reserves for conserva-
tion; 3) the paper identified a list of con-
servation features; and, 4) there was some
sort of systematic approach (e.g., an algo-
rithm, an optimization tool, complemen-
tarity principles) to selecting sites. Theo-
retical papers that used hypothetical data
for the purposes of illustrating principles
of SCP were not included in the database.
We also excluded reviews of SCP con-
cepts, critiques of previous work, and
meta-analyses. We did not consider
papers that only discussed effectiveness or
management of existing protected areas.
We further excluded papers dealing with
conservation planning in freshwater and
marine areas. Freshwater and marine con-
servation planning is an important and
growing area of work. However, the terres-
trial and aquatic/marine environments
differ dramatically both biophysically and
in terms of political jurisdictions, which
means that approaches to planning and
implementation will be very different than
in terrestrial realms (Hansen et al. 2011).
Although we are using the Margules and
Pressey (2000) paper to frame this review,
we searched for papers from all available
dates (up to December 31, 2013), since the
literature on systematic conservation
planning dates back to the 1980s (Kukkala
and Moilanen 2013). We did not include
any ‘grey literature’, even though many
organizations (e.g., the Nature Conser-
vancy) publish conservation planning
documents. It can be difficult to get a full
representation of the grey literature from
academic search indices, and our review is
intended to be illustrative of the variation
of applications of SCP concepts rather
than comprehensive. Despite these limita-
tions, we feel the sample of papers is suffi-
ciently representative to allow us to make
broad inferences.
Our final database contained 127
papers (see supplementary material S.1
available only in the on-line version of this
paper). We read each paper closely to
extract data relevant to the steps in SCP
(Table 1). Where the information was
available, we recorded data on the type and size of the study
area, the type and size of the planning units, the species or fea-
tures for which conservation areas were being planned, the
type of conservation targets applied, and the tools used. Not
all papers included details on all of the data in which we were
interested, and we were not able to follow up with individual
authors to try to obtain missing data. We included data from
all studies which were carried out in the same location, since
in some cases there were subtle differences in aspects of each
study (e.g., method, biodiversity target). Some of the papers
we reviewed contained information from studies in multiple
locations; in these cases we used data from all study sites.
Table 2. Types of data used as conservation features in 127 papers in literature
review. The total of the count column is greater than 127 because some papers
made use of multiple sets of conservation features (e.g., birds and mammals).
Mean
number of S.D. Count
species/ species/ (number
Conservation Feature features features of papers)
Broad species variables
species in a specific habitata1095 2248.5 5
invertebratesb158 137.1 3
vertebratesb799 1415.5 6
plantsc1387 2173.5 23
listed speciesd185 308.1 18
Specific groupings of species variables (taxonomic classes)
Amphibians 115 156.1 7
Birds 227 229.2 26
Fish 46 n/a 1
Herptiles 88 62.2 2
Mammals 387 1158.6 28
Reptiles 19 17.4 5
Highly specific groups of species variables (taxonomic groupings)
Bats 4 n/a 1
Beetles 127 63.3 3
Bryophytes 47 n/a 1
Butterflies 122 131.8 7
Carnivores 4 n/a 1
Dragonflies 367 315.1 4
Molluscs 47 n/a 1
Raptors 3.5 3.5 2
Salamanders 11 n/a 1
Trees 367 304.3 4
Environmental variables
sites of interest 1963 3322.9 3
environmental parameters 16 3.0 4
vegetation classes/land cover 204 444.9 33
Wetlands 5 n/a 1
aThis includes paper that examined for example “beach species”, “fen species” and included plants and animals.
b“Invertebrates” and “Vertebrates” indicates papers that made uses of a suite of species from different classes or
families; rather than a specific subgroup (e.g., butterflies, birds).
c“Plants” indicates papers that made use of a wide range of plant species, or in some cases specific species/sub-
groups (e.g., orchids).
dListed species” indicates papers where the species used for analysis was listed (e.g., IUCN Red-List, or
national species-at-risk status) or otherwise identified as “at risk” of extinction, regardless of taxa). Some of
these were further subset into the following taxonomic groups: amphibians (1), listed birds (3), dragonflies (1),
herptiles (1), invertebrates (1), mammals (2), plants (3) and vertebrates (1). These are not double-counted in
the table and are summarized in the text of the paper.
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Results
Conservation features
Step 1 (Margules and Pressey 2000) outlines the critical role
that data play in SCP. The conservation features (i.e., surro-
gates for biodiversity) used in the papers we surveyed fall into
two broad categories: species and environmental variables
(Table 2). The latter can include biotic data such as vegetation
communities or land cover types as well as abiotic data such
as elevation, productivity, and climate which are commonly
used as proxies for ecological regions and/or ecosystems
(Margules and Pressey 2000, Williams et al. 2002). Kukkala
and Moilanen (2013) stress that comprehensiveness of the
data considered is important. Individual research papers var-
ied in their comprehensiveness (Fig. 1). Of the 127 papers, 86
used a single feature category, while 41 were more compre-
hensive and made use of more than one conservation feature
category. In addition, while many papers used a broad taxo-
nomic group from their region for each particular conserva-
tion feature category (e.g., all vascular plant species), some
papers used more narrowly defined (yet highly diverse) taxo-
nomic groups as conservation feature
categories (e.g., beetles, butterflies), and
yet others used a very small set of
species within a particular category.
Ten papers developed SCPs using only a
single species and an additional 27
papers used five or fewer species/ele-
ments (Fig. 1).
Only six papers explicitly
addressed any aspects of uncertainty in
species distribution data used, such as
spatial or temporal accuracy (Flather et
al. 1997, McCarthy et al. 2006, Chen
and Bi 2007, Gove et al. 2008, Carvalho
et al. 2010, Hermoso and Kennard
2012). Of the 127 articles reviewed,
vegetation/land cover classes were the
conservation feature most commonly
used, followed by mammals, birds and
plant species (Fig. 2). Vegetation/land
cover likely was the most common
because it can be obtained for a broad region via remote
sensing, while using plant species (or other species groups)
requires on-the-ground surveys, although some type of satel-
lite data can carry a high cost.
Goals and targets
Step 2 in Margules and Pressey (2000) emphasizes the impor-
tance of goals and targets. Eighty-seven of the papers used
quantitative targets in SCP; of these, 20 used a blanket per-
centage target, ranging from 1% to 75% of total land area
(mean 20%, s.d. 22%). These are examples of ‘data-free’ tar-
gets (Svancara et al. 2005), in that they are not based on any
particular empirical investigation and so likely are not ade-
quate. Six papers used the well-known “10%” or “12%” targets
that came out of the World Parks Congress (McNeely and
Miller 1984) and the Brundtland Commission (WCED 1987).
Thirteen papers we reviewed focused on maximizing repre-
sentation of species and/or features with a minimum amount
of area. The majority of these (8) aimed to have every species
represented at least once, while three set targets of intervals
Fig. 1. Count of 127 papers based on the number of conserva-
tion features (e.g., landcover type or ecosystem) or species
included in the study.
Fig. 2. Count of number of different species, by different taxo-
nomic groupings, which are included in 127 papers on system-
atic conservation planning.
Table 3. Minimum, maximum, mean and median size (in hectares) of planning units
by type used in 127 papers on systematic conservation planning.
Type of
planning unitaMinimum Maximum Mean Median Countb
Ecologicalc0.4 190 000 000 12 000 000 2750 17
Hexagon 10 64 000 13 031 750 8
Square 0.25 1 300 000 139 425 6500 33
Other polygond0.2 899 100 56 040 1600 24
Pixel 0.25 1 826 400 151 838 552 27
aPlanning units are defined as the units of analysis used as “building blocks” in the site prioritization.
bCounts sum to a number larger than the number of papers represented in the table, since some papers presented
results with different types and sizes of planning units. As well, the number of papers represented here is different
from that in other tables because of differences in details on study area and planning unit size that were provided
in individual papers.
cEcologically-defined planning units include natural patches of habitat (e.g., forest stands) or physiographic units
(e.g., watersheds).
d“Other polygon” refers to irregular polygons that are not defined ecologically, and may include counties, existing
protected areas, or land ownership parcels.
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328 2016, VOL. 92, No3 — THE FORESTRY CHRONICLE
from 1–6 representations of each species (Margules et al.
1988, Rodrigues et al. 2000a, Bonn and Gaston 2005) and
two suggested representation should be as high as 10
instances (Heikkinen 2002, Simaika and Samways 2009).
Evaluation of existing protected areas
Most studies did not detail how existing protected areas
were assessed (Step 3; Margules and Pressey 2000), so we
used planning units described in SCP methods as indicative
of what authors thought were adequate requirements for a
single protected area. The median size of the planning units
in our literature review (2500 ha) was much smaller than
what most of the literature recommends for ecological via-
bility (Table 3). Planning units were ecologically-defined
(e.g., watersheds, catchments) in only 17 of the papers
(Table 3), and the others were squares, pixels, or hexagons
(and hence not likely to reflect realistic or effective reserve
boundaries).
Tools applied in SCP
The addition of new conservation areas is Step 4 in Mar-
gules and Pressey (2000) and a large variety of software tools
have been developed to carry out SCP. Nearly all of these
incorporate the concepts of complementarity and efficiency.
Seventy-two papers reviewed described a particular soft-
ware tool (Table 4), the majority of which were Marxan,
C-Plan, Zonation, and optimization algorithms (linear or
integer programming).
Implementation plans
Only seven of the papers contained conservation plans that
were at least partly implemented (or expressed intent to do
so), which is step 5 in Margules and Pressey (2000). In our
review, 19 papers explicitly included social and/or economic
factors in their analysis. In papers that consider economic
aspects of reserve design, costs are often simplified in terms of
land area without accounting for variation in real estate
prices. Others model trade-offs, in terms of other benefits
such as alternative land uses, identify areas that are productive
for forestry or other activities (Faith and Walker 2002). We are
aware of only two papers where cost-benefit trade-offs
included real-world estimates of net-present value (NPV) of
forest harvests as a potential cost to a conservation plan (Per-
hans et al. 2008, Schnider et al. 2010).
Evaluation of effectiveness
Only seven of the papers actually documented any kind of
systematic conservation plan that was at least partially
implemented or expressed intent to do so. None included a
comprehensive assessment of how well the plan achieved
stated goals. Thus, we cannot evaluate the operationaliza-
tion of this step in detail. Margules and Pressey (2000)
emphasize that this final (6th) step is of fundamental impor-
tance, yet we could not find examples that illustrate how this
step is carried out.
Discussion
Below we provide additional discussion of the results of our
literature survey of the six steps in SCP as well as recommen-
dations for practitioners considering implementing SCP.
Step 1: Compile data on the biodiversity of the planning region
Of the conservation features chosen, mammals were the most
frequent taxonomic group and the second-most common
conservation feature after vegetation categories (identified
using remotely-sensed data). This is not surprising since
mammals are large, charismatic, and well-studied. Mammals
may also serve as area-sensitive umbrella species (see discus-
sion on the use of surrogate species below). Birds are the third
most prominent group as they are often well-surveyed given
the levels of amateur birders and the existence of long-term
data sets across broad spatial extents (Sullivan et al. 2009).
The variation in the number of conservation features used
across all papers indicates that comprehensiveness of data was
variable, although it is obviously impossible to have data for
all biodiversity or conservation features within a region
(Kukkala and Moilanen 2013). Thus, it is important to know
how well the conservation features used in SCP act as surro-
gates for biodiversity patterns. In many cases researchers are
constrained by available data and thus forced to use limited
sets of conservation features, which may or may not affect
representativeness. In other words, if the conservation fea-
tures used are good surrogates for biodiversity, then biodiver-
sity will be well represented within the resulting conservation
network. In our review, only 34 papers explicitly indicated
that the species used in the SCP was serving as some sort of
Table 4. Summary of tools used in Systematic Conservation
Planning based on a survey of 72 papers that made use of
computer software or analytical techniques (indicated by ital-
ics) ordered from most to least frequent. For specific soft-
ware packages, the source is given, if available. There are
multiple software packages that can be used for optimization,
statistical and GIS analysis, so these are listed as n/a.
Tool CountaSource
Marxan 19 University of Queensland,
Australia
statistical models 14 n/a
Zonation 10 University of Helsinki
optimization algorithms 9n/a
(linear and integer)
C-Plan 7 Environmental Decisions Group
ResNet 4 University of Texas at Austin
GIS-based 3n/a
CONSERVE 2 no longer available
WORLDMAP 2 Natural History Museum, UK
CODA 1 no longer available
Decision-analysis 1n/a
DIVERSITY 1 no longer available
GARP 1 no longer available
LARCH 1 Wageningen University
MinPatch 1 Durrell Institute of Conservation
and Ecology
RESERVE 1 See Briers RA (2002)
TARGET 1 See Barton et al. (2004)
aCount indicates the number of papers which specified use of the tool and sums to a
larger number than the sample of papers because some papers presented work using
more than one tool.
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2016, VOL. 92, No3 — THE FORESTRY CHRONICLE 329
surrogate species (a term used to collectively describe key-
stone, indicator, focal, flagship, and umbrella species; for a
review see Caro and O’Doherty 1999). However, only a hand-
ful of the 34 papers that used surrogates assessed the effective-
ness of these in the context of their particular reserve design.
In East Africa, Caro (2003) found that large mammals were
effective umbrella species, and across Canada, Warman et al.
(2004) found that richness of one taxonomic group (e.g.,
birds, mammals, reptiles, amphibians) was well-correlated
with that of others. However, the utility of surrogate species
has been postulated to be highly scale-dependent. For exam-
ple, some authors have found surrogates to be ineffective in
small areas (Caro et al. 2004), but effective in larger areas if
minimum representation of the surrogate was met (Garson et
al. 2002). Effectiveness as a surrogate may also vary across
background taxa (Roberge et al. 2008). In a comprehensive
review of 575 surrogacy tests from 19 studies, Rodrigues and
Brooks (2007) evaluated the effectiveness of protected areas
designed using surrogate species data for representing target
taxa and found a positive but weak surrogacy effect. They
found a number of papers where surrogacy was shown not to
be effective, but also a great deal of variation in terms of which
taxonomic group were more effective surrogates, and how
surrogacy was defined (Rodrigues and Brooks 2007).
Many SCPs use range map data which delineate “extent of
occurrence” as opposed to “area of occupancy” (Gaston and
Fuller 2009). Species distribution data carries uncertainties
along different dimensions of data quality, including accu-
racy, precision, and timeliness. For example, both extent of
occurrence and areas of occupancy maps can have limitations
(Williams et al. 2002, Fleishmann et al. 2006, Rondinini et al.
2006) due to errors in species identification, sampling biases
(e.g., over representation of areas near roads; see Williams et
al. 2012) and temporal gaps. Such errors and limitations have
been shown to affect conservation planning and assessment
(Habib et al. 2003, Gaston and Fuller 2009, Loehle and Sleep
2015). Of the six papers that addressed any aspects of uncer-
tainty in the data (Flather et al. 1997, McCarthy et al. 2006,
Chen and Bi 2007, Gove et al. 2008, Carvalho et al. 2010,
Hermoso and Kennard 2012), all found that outcomes were
sensitive to variations in data quality. Sensitivity analyses
are a highly recommended step to assess how plans respond
to variation in data in order to increase confidence in the
final product.
A further consideration when selecting conservation fea-
tures should be the threats to species or landscapes (Margules
and Pressey 2000, Deguise and Kerr 2006, Kukkala and
Moilanen 2013). Within our database, 18 papers made use of
threatened species in conservation planning (Table 2). When
considering rare, threatened and listed species, it is important
to consider the reasons behind species rarity. Some species are
naturally rare and thus may not necessarily need to be prior-
itized in conservation strategies (Drever et al. 2012, Strittholt
and Leroux 2012). It is also important to distinguish between
assessing threats of extinction to rare species and identifying
species that are conservation priorities but may or may not
actually be threatened (e.g., “listed species”; Mace and Lande
1991). Further, when conservation planning happens within
politically bounded regions, species may be identified as rare
because they are occurring at the edge of their range (Drever
et al. 2012). Thus SCP within politically-bounded regions
may inflate the importance of some rare species that may be
abundant elsewhere, as was demonstrated for birds in South
Africa (Rodrigues and Gaston 2002). Of the papers we
reviewed, 110 clearly defined the study region (the rest simply
specified an approximate region); of these 53 used an ecolog-
ically-defined study region and 57 a politically-defined one.
Recommendations
Care should be taken when choosing conservation features. If
features are chosen to be surrogate species, there should be
some certainty about what they are a surrogate for, and
whether they are an effective surrogate across the study
region. Species or environmental features should not be
included in the SCP just because data are available; if these
have little ecological relevance, then the resulting conserva-
tion network will not be very relevant for conservation.
Step 2: Identify conservation goals and targets for the planning
region
Identification of conservation goals is a key step in SCP.
Indeed, Tear et al. (2005) expanded on this single step to
develop a list of standards and principles for goal setting.
Margules and Pressey (2000) outline some examples of con-
servation goals such as minimum numbers of occurrences of
each species or minimum conserved area. To ensure conser-
vation goals are achieved, adequate quantitative and opera-
tional targets should be selected (Kukkala and Moilanen
2013). However, evaluating adequacy of targets is complex.
Not surprisingly, data-free percentage targets (expressed as a
percentage of the target region’s land area) were the most
commonly used. These are popular with policy-makers and
environmental groups because they offer a clear objective and
can be easily measured (Noss et al. 2012). However, the risk
with data-free targets is that the amount advocated may either
be inadequate to meet biodiversity conservation objectives, or
inefficient by conserving amounts far in excess of what is
needed. In the 1990s, a World Wildlife Fund-led campaign
advocated a 12% target for protection of lands within Canada
(Hummel 1995); more recently environmental groups have
suggested that the targets should be closer to 50% of total land
area (CPAWS 2008, Badiou et al. 2013, Wells et al. 2014). The
50% target has been advocated by Locke (2013) who based his
evidence on an editorial by Noss et al. (2012). However, the
percentage target data presented in Noss et al. (2012) varies
widely, and even data from individual studies have large con-
fidence limits around their estimate. There is no empirical
evidence to support the claim that any fixed percentage of
land target is sufficient to adequately conserve biodiversity.
Svancara et al. (2005) reviewed 159 articles that proposed
conservation targets and found that the “data-free” (or policy-
driven) targets were generally smaller than those based on
empirical analysis.
Evidence-based targets (those that emerge from an
assessment of the conservation requirements for a given suite
of species in a given region) range from ~ 33%–99% of total
land area (Margules et al. 1988, Ryti 1992, Noss 1993, 1996;
Saetersdal et al. 1993, Soulé and Sanjayan, 1998, Svancara et
al. 2005, Noss et al. 2012). These targets aim to achieve repre-
sentation of the full suite of biodiversity in a region. It is clear,
however, that there is a great deal of uncertainty in the litera-
ture as to what an appropriate target value should be (Noss et
al. 2012, Wilhere et al. 2012). It is likely that there is no uni-
versally-applicable percentage target to indicate how much
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330 2016, VOL. 92, No3 — THE FORESTRY CHRONICLE
protected area is “enough” to meet representation objectives
for effective biodiversity conservation. Our review suggests
that the value is context-dependent and is contingent on a
number of issues, including scale (both grain and extent) and
diversity levels (alpha, beta, and gamma), environmental vari-
ability, and the specific conservation goals and anthropogenic
threats involved. Sensitivity of representation targets to con-
servation design was also demonstrated empirically by Justus
et al. (2008) who suggested that targets should be based on
functional relationships between the area for conservation
and distribution of species. Only six of the papers we
reviewed specified variable targets, with higher targets speci-
fied for the rare habitats and/or species.
Whether these targets for species representation are ade-
quate to ensure population persistence is unknown; only one
paper in our dataset tried to set targets for minimum num-
bers of individuals based on minimum viable population esti-
mates (Kerley et al. 2003). The issue of persistence is one that
has been extensively discussed in the literature, and which is
not adequately addressed with representation targets
(Rodrigues et al. 2000a, 2000b, Cabeza and Moilanen 2003,
Kerley et al. 2003, Pressey et al. 2003, Solomon et al. 2003,
Wiersma and Nudds 2006, Smith et al. 2010). If planning
units are designed to meet minimum size thresholds for
species persistence (Pressey and Logan 1998, Wiersma and
Nudds 2006), or if the selection algorithms are modified to
constrain sites to be of a minimum size and/or to be mini-
mally fragmented (Moilanen and Wintle 2007, Smith et al.
2010), then representation and persistence goals might be
adequate. However, only seven papers we reviewed (Pressey
and Logan 1998, Gaston et al. 2002, McCarthy et al. 2006,
Wiersma and Nudds 2006, Moilanen and Wintle 2007, Smith
et al. 2010) used planning units that met some kind of mini-
mum size criterion.
Recommendations
Although convenient, data-free conservation targets are not
effective tools for conserving more complicated aspects of the
environment such as species diversity and persistence, ecosys-
tem representation, or biodiversity as a whole. The applica-
tion of data-free targets may result in significant inefficiencies
in conservation planning with largely unknown costs, both to
society and to biodiversity, particularly where protected areas
of higher order (IUCN classes I–IV) exclude future manage-
ment options to redress the effects of natural disturbance or
future potential effects of climate change. Although relatively
simple to measure and promote, data-free targets do not lead
to either a reduction in uncertainty or provide mechanistic
explanations for relationships between land use activities and
biological diversity, both of which are important to improve
conservation planning over the long-term. Thus, data-free
targets should be avoided.
Step 3: Review existing conservation areas
Margules and Pressey (2000) outline the need to review the
extent to which conservation targets are met by existing pro-
tected areas. For example, one basic criterion with which to
assess existing protected areas may be whether or not they are
sufficiently large to conserve biodiversity in the long-term.
The minimum size for a reserve is an important considera-
tion, and can be estimated using principles from island biog-
raphy theory (Gurd et al. 2001) or minimum viable popula-
tion analysis (Landry et al. 2001, Reed et al. 2003, Kujala et al.
2011). Other approaches use species-area or species-density
relationships to estimate minimum area requirements
(Desmet and Cowling 2004, McCoy and Mushinksy 2007) or
combine island biogeography principles with a landscape
ecology approach (Harcourt et al. 2001, Parks and Harcourt
2002, Wiersma et al. 2004, Wiersma and Simonson 2010).
Ecological processes can also be considered, such as mini-
mum dynamic areas (Pickett and Thompson 1978, Hunter
1993, Leroux et al. 2007a, 2007b) that estimate the minimum
area needed to ensure that essential ecological processes and
disturbances can continue to take place unhindered.
Although much of the literature cited above is focused on
determining requirements for a single site, incorporating
these size guidelines into systematic reserve design will help
to simultaneously address issues of representation and per-
sistence (Gaston et al. 2002, McCarthy et al. 2006, Wiersma
and Nudds 2006, Smith et al. 2010). The estimates of mini-
mum reserve size are dependent on the specific region and
taxa under consideration. Most research suggests these
should be on the order of thousands or tens of thousands of
square kilometres (100 000 to 1 000 000 hectares) to be eco-
logically effective in the event that the surrounding habitat
matrix becomes completely altered, which is much larger
than the median planning unit size (2500 hectares) found
across papers reviewed here. The growing field of conserva-
tion biogeography (e.g., Mendenhall et al. 2014) can con-
tribute usefully to analysing these issues.
Another criterion that should be considered when carry-
ing out this step is the degree of vulnerability of existing pro-
tected areas. More vulnerable sites may carry higher inclu-
sion costs in the long run (Kukkala and Moilanen 2013),
especially if that vulnerability means they will likely need to
be replaced after loss. However, if a highly vulnerable site is
also the only occurrence of a particular rare feature, then it
may be important for prioritization. One way vulnerability
has been qualified is through the use of relative “intactness”
of existing protected areas. “Intactness” is a term that is com-
monly related to both fragmentation and habitat loss, but is
also a more holistic term that includes any alteration that is
anthropogenic in nature, whether or not there is an ecologi-
cal effect (NCASI 2011). Intactness, usually measured using
a variety of satellite imagery, ancillary data, or expert opin-
ion, may be considered as a factor inside existing protected
areas (e.g., roads, tourist areas), or beyond the boundaries of
protected areas, relating to the effects that the surrounding
matrix may have on their ability to continue to conserve bio-
diversity (Parks and Harcourt 2002, Wiersma et al. 2004).
However, using intactness as a criterion for protected area
design is complicated, in that the concept encompasses a
range of factors and considerations, both ecological and
social, making it challenging to define an empirical metric
for measurement (NCASI 2011).
Recommendations
Not all protected areas are equal. Existing protected areas
should be rigorously evaluated against scientifically defensible
(and regionally-appropriate) criteria for size, intactness and
overall effectiveness for meeting conservation goals. If they
are not effective, it may be inefficient to include them as part
of a regional conservation area network.
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Step 4: Select additional conservation areas
There are a variety of tools and software employed to carry
out SCP; most are based on considering sets of multiple-pro-
tected areas within a network simultaneously. This comple-
mentarity-based approach was developed with the idea that
an effective reserve network was the set of protected areas that
efficiently represented the full suite of biological and ecologi-
cal features (Kirkpatrick 1983, Margules et al. 1988) by cap-
turing as many features as possible within the smallest
amount of land possible. Therefore, by being more efficient,
more land is available for other types of use. Early work used
heuristic algorithms to maximize network efficiency (Pressey
and Nicholls 1989), but later advances in computing power
gave rise to the use of optimization algorithms (Rodrigues et
al. 2000c, Williams et al. 2004, Moilanen et al. 2009). The
main debate in the literature on the issue of tools to apply to
SCP has (until recently) hinged on the merits of using heuris-
tic vs. optimization algorithms.
Heuristic algorithms follow a set of step-wise rules to
iteratively add protected areas to a network set. Commonly-
applied rules are based on richness (i.e., sites with high species
richness are selected first) or rarity (i.e., sites containing a
high number of rare species are selected first). At each step,
the principle of complementarity is applied. Thus, the next
site selected is complementary to the ones already in the set in
that it maximizes the number of new species/features added
to the set. In this way, redundancies are avoided, and the set
as a whole is as efficient as possible. Most papers we examined
operationalized efficiency simply in terms of number of sites,
but in reality sites may have different costs which can affect
the likelihood of implementation (see step 5 below).
Proponents of optimization algorithms (also known as
integer or linear programming techniques) argue that heuris-
tic algorithms can only achieve a near-optimal solution
(Rodrigues et al. 2000c) and thus are not maximally efficient.
Optimization is either based on finding the minimum num-
ber of sites for a given number of occurrences (the “location
set covering problem”, Church et al. 1996; also known as the
“species set covering problem”, ReVelle et al. 2002) or on using
a fixed amount of area, and optimizing the location of the set
of sites to maximize the number of species or features cap-
tured (the “maximal covering location problem”, Church et al.
1996; also known as the “maximal covering species problem”,
ReVelle et al. 2002). Until very recently, computing power
limited the use of optimizing algorithms, since the large data
sets commonly used in reserve design resulted in inefficient
computing time to effectively assist planning (Strange et al.
2006). However, this is no longer an issue (Vanderkam et al.
2007, Billionnet 2011).
Recommendations
Many of the software packages listed in Table 4 were custom-
developed for a specific project. Thus, it is difficult to evalu-
ate them against a suite of criteria (e.g., efficiency, user-friend-
liness, comprehensive, flexibility). MARXAN is the most
widely used software and has various options for reserve
selection algorithms. It also provides user-friendly output in
the form of maps and graphs. Like most of the tools in Table
4, MARXAN is open-source, and has an active online com-
munity which provides peer-support. However, other soft-
ware and techniques (e.g., statistical or GIS analyses) may
function just as well in other contexts. Users should let their
research question or management problem dictate which
software package would be most effective rather than chose a
tool because it appears to be the most widely used.
Step 5: Implement conservation actions
In theory, a key concept that can help inform decisions about
which areas to prioritize is that of irreplaceability (Kukkala
and Moilanen 2013). However, in practice we were unable to
adequately assess how irreplaceability is operationalized in
the context of implementing SCP, as only a few papers had
any reference to implementation plans. Knight et al. (2008)
document a similar lack of implementation and contend that
it is due to a gap between knowledge and implementation.
Protected areas establishment usually happens within govern-
ment agencies, but sometimes can happen through Environ-
mental Non-Governmental Organization-led initiatives (e.g.,
conservation easements). This can lead to challenges because
the planning carried out without decision-makers may oper-
ate in a vacuum (Game et al. 2013). They identified this and
five other common “mistakes” that can have a negative effect
on the implementation of conservation plans. Additionally,
implementation of protected areas once their locations have
been identified through systematic conservation planning is a
long process that also involves social, political, and economic
dimensions, and some of the perceived gap may be due to
delays within these arenas. Thus, there is a need to adopt a
high degree of flexibility (Kukkala and Moilanen 2013).
Although rarely done, it is possible to build the temporal
aspect of lags between planning and implementation into
SCPs to explicitly model flexibility (Meir et al. 2004, Spring et
al. 2010). Some papers have model species and environmen-
tal dynamics to assess whether the static conservation sce-
nario will be effective through time (Leroux et al. 2007a, Har-
tig and Drechsler 2008, Spring et al. 2010, Johst et al. 2011,
Rubio et al. 2012), while others have suggested strategies for
implementation (Knight et al. 2006a, 2006b). This sort of
modelling can also be incorporated to model some of the
uncertainties mentioned in steps 1–3 above, and assess the
potential impact of these uncertainties on planning out-
comes.
In the real world, conservation planning must be flexible
enough take into account social and economic aspects and
competing land uses. SCP was designed as a tool for assessing
scenarios that can then be used to support decision-making
across multiple sectors, land uses and social economic
dynamics (Pressey et al. 2007, Kukkala and Moilanen 2013).
Some researchers have suggested that, for real-world conser-
vation planning, consideration of economic costs should be
more important than biological assessments (e.g., Carwar-
dine et al. 2010, Knight et al. 2011). Outside of the SCP liter-
ature, bio-economic trade-offs have been modelled to opti-
mize NPV against different amounts of conservation reserves
(Knoke and Moog 2005, Schneider et al. 2010) or to compare
NPV of timber against ecosystem goods and services values
of forest stands (Knoke and Weber 2006, Knoke et al. 2009,
Schneider et al. 2010). Such methods might profitably be
applied to SCP.
Recommendations
Implementation is the most difficult stage of SCP, since it
requires interacting with decision-makers, land-owners and
other stakeholders. The addition of research incorporating
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332 2016, VOL. 92, No3 — THE FORESTRY CHRONICLE
economic modelling or research on human dimensions may
increase the ability to rigorously evaluate and defend a partic-
ular plan. This stage of SCP requires that practitioners have
skills in collaborative decision making, negotiation and con-
flict resolution.
Step 6: Maintain the required values of the conservation areas
Margules and Pressey (2000) emphasized that planning is an
iterative process and does not stop once protected areas are in
place. They point out that management of protected areas
needs to be continually assessed to ensure they are maintain-
ing conservation values. They also point out the importance
of monitoring key indicators to ensure management effective-
ness. However, in their review of key concepts, Kukkala and
Moilanen (2013) suggest that effectiveness is not a completely
straightforward metric. Jones et al. (2009) outline a concep-
tual approach to monitor land use and land cover in and
around protected areas using remote sensing data. Joppa et al.
(2008) provide a review of methods to evaluate success of
protected areas in the tropics.
Recommendations
Standards for effectiveness are a necessary component of
monitoring. These are not yet well-developed, and thus the
focus of future research should be the development of stan-
dards and metrics for evaluating the effectiveness of both
individual protected areas, but more importantly for system-
atic conservation plans and networks of protected areas. An
examination of the grey literature might provide additional
examples of implementation which could be informative.
Conclusions
SCP is an important tool in the development of effective and
efficient protected areas which are an important aspect for
helping to halt the loss of biodiversity globally, and maintain-
ing the ecosystems, unique landscape features, and other soci-
etal values on the landscape. However, SCP is a relatively new
endeavor. This novelty as a conservation tool is exemplified
by the range and diversity of approaches and interpretations
of basic SCP documented in this paper.
The limitations and uncertainties illustrated by this review
do not mean that there is no room in SCP for qualitative or
socially-derived criteria or features; indeed additional
research on the utility of these strategies is needed. Relatively
simple preservation of unique landscape features, archaeolog-
ically important areas, and other societal values remains an
important aspect of SCP, and measuring the success of such
preservation actions may be more straightforward. In some
cases, a simple “yes or no” determination as to whether or not
those values remain on the landscape will suffice. In contrast,
some ecosystem functions and services (clean water, clean
air), although difficult to conceptualize, remain important
aspects for conservation even when empirically-derived rela-
tionships may be less well developed. Relatively arbitrary tar-
gets may suffice in the short-term, e.g., the 30% equivalent
clearcut area for watershed disturbance (Government of
British Columbia 1996) while longer-term research efforts
reduce uncertainty regarding the ecological effects of man-
agement. Further work is required to inform SCP initiatives
regarding the cause and effect relationships between land uses
and long-term ecosystem functions. As well, future research
should develop tools and techniques that can model the
impact that uncertainty in data, targets and design compo-
nents can have on the final plan.
Overall, our review highlights the variation with which
strategic conservation planning (SCP) steps are applied, as
well as some of the uncertainty inherent in implementing
these steps. This is not surprising, given the lack of clarity in
the definitions of key SCP concepts described by Kukkala and
Moilanen (2013). Efforts to standardize concepts and prac-
tices will lead to greater consistency in the application of
actual on-the-ground conservation planning and will ulti-
mately result in effective conservation of biodiversity.
Acknowledgements
Thanks to S. Leroux and several anonymous reviewers for
helpful comments on earlier versions of this manuscript.
Much of this work was completed while Yolanda Wiersma
was a visiting researcher at the Institute of Forest Manage-
ment at the Technical University of Munich, and she thanks
colleagues there, particularly A. Hahn and T. Knoke, for help-
ful discussions. We thank M. Fahmy for his assistance in
preparing the supplemental material. Funding for this work
was provided by the National Council for Air and Stream
Improvement, Inc., who also provided impetus for the review
and helpful feedback (K. Vice).
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AuthorPrimary Year PeriodicalTitle Vol Issue
Alagador & Cerdeira 2007 Biological Conservation 137 2
Andrew et al. 2011 Biological Conservation 144 12
Andrew et al. 2012 Biological Conservation 146 1
Araujo 1999 Diversity and Distributions 5 4
Arponen et al. 2007 Conservation Biology 21 2
Averill-Murray 2013 Herpetological Conservation and Biodiversity 8 1
Barbosa et L. 2010 Conservation Biolgy 24 5
Beazley et al. 2005 Ecological Applications 15 6
Bedward et al. 1992 Biological Conservation 62 2
Belbin 1993 Biological Conservation 66 3
Betrus et al. 2005 J Environmental Management 74 1
Bino et al. 2013 Austral Ecology 38 4
Bonn & Gaston 2005 Biodiversity and Conservation 14 5
Boyce et al. 2002 Journal of Bioscience 27 4
Briers 2002 Biological Conservation 103 1
Bruinderink et al. 2003 Conservation Biology 17 2
Burns et al. 2013 Biological Conservation 158
Cabeza 2003 Ecology Letters 6 7
Camm et al. 2002 Operations Research 50 6
Cardillo et al. 2006 PNAS 103 11
Caro 2003 Animal Conservation 6 2
Carroll et al. 2001 Ecological Applications 11 4
Carvalho et al. 2010 Biological Conservation 143 2
Carwardine et al. 2007 Biodiversity and Conservation 16 1
Ceballos & Ehrlich 2006 PNAS 103 51
Chen & Bi 2007 Current Science 92 4
Clark&Slusher 2000 Landscape Ecology 15 1
Cowling et al. 2003 Biological Conservation 112 1-2
Cumming et al. 1996 Ecography 19 2
D'Amen 2013 Animal Conservation 16 4
Desmet & Cowling 2004 Ecology & Society 9 2
Di Minin 2013 PLoS One 8 8
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Dobson et al. 2001 Ecological Applications 11 4
Dockerty et al. 2003 Global Environmental Change 13 2
Dunk et al. 2006 Diversity and Distributions 12 4
Faith & Walker 2002 Journal of Bioscience 27 4
Faleiro 2013 Biological Conservation 158 -
Faleiro & Loyola 2013 Diversity and Distributions 19 8
Fleishman et al. 2001 Ecological Applications 11 5
Freudenburger et al. 2013 Biodiversity &Conservation 22 5
Galetti et al. 2009 Biological Conservation 142 6
Gao et al 2013 Landscape Ecology 28 10
Gordon et al. 2013 Ecological Modelling 249 -
Gove et al. 2008 Biodiversity and Conservation 17 4
Grant & Samways 2011 Biological Conservation 144 2
Grelle et al. 2010 Natureza & Conservacoa 8 1
Hannah et al. 2007 Frontiers in Ecology and Environment 5 3
Harris et al. 2014 Estuarine, Coastal and Shelf Science 150
Heikkinen 2002 Biodiversity and Conservation 11 11
Hermoso & Kennard 2012 Biological Conservation 147 1
Hernandez-Manrique et al. 2012 Biodiversity and Conservation 21 8
Hoctor et al. 2000 Conservation Biology 14 4
Hornberg et al. 1998 BioScience 48 10
Huber et al. 2010 The Professional Geographer 62 3
Jaffre et al. 1998 Biodiversity and Conservation 7 1
Jantke et al. 2013 Environmental Conservation 40 1
Jenkins et al. 2013 PNAS 110 28
Justus et al. 2008 Conservation Biology 22 3
Kareksela et al. 2013 Conservation Biology 27 6
Kati et al. 2004 Biological Conservation 120 4
Kerley et al. 2003 Biological Conservation 112 1-2
Klein et al. 2009 Ecological Applications 19 1
Kohlmann et al. 2007 Zootaxa 1457
Krupnick & Kress 2003 Biodiversity and Conservation 12 11
Lachat & Butler 2009 Environmental Management 44 1
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Landry et al. 2001 The George Wright Forum 18
Lentini et al. 2013 Conservation Biology 27 4
Leroux et al. 2007a Ecological Applications 17 7
Leroux et al. 2007b Biological Conservation 138 3-4
Levin et al. 2013 Biological Conservation 158
Loyola et al. 2013 Biodiversity &Conservation 22 2
Loyola et al. 2007 Diversity and Distributions 13 4
Maiorano et al. 2006 Biological Conservation 133 4
Marfil-Daza 2013 Animal Conservation 16 1
Margules et al. 1988 Biological Conservation 43 1
Marignani & Blasi 2012 Biodiversity and Conservation 21 7
Martin & Ferrier 2013 Ardeola 60 1
Mateo et al. 2013 Biological Conservation 160
McCarthy et al. 2006 The American Naturalist 167 5
McCoy & Mushinsky 2007 Ecology 88 6
Mikkonen & Moilanen 2013 Environmental Science andolicy 27
Moilanen & Wintle 2007 Conservation Biology 21 2
Moilanen&Wintle 2006 Biological Conservation 129 3
Mokany et al. 2013 Journal of Applied Ecology 50 2
Nicholson et al. 2006 Ecology Letters 9 9
Parks & Harcourt 2002 Conservation Biology 16 3
Pearce et al. 2008 Biological Conservation 141 4
Pressey & Logan 1995 Conservation Biology 9 6
Pressey & Logan` 1998 Biological Conservation 85 3
Pressey & Nicholls 1989b Biological Conservation 50 1-4
Pressey &Nicholls 1989 Biological Conservation 50 1-4
Pressey et al. 2000 Biological Conservation 96 1
Pressey etal. 2003 Biological Conservation 112 1-2
Pryke and Samways 2008 Biodiversity and Conservation 17 12
Ramage 2013 Biodiversity and Cinservation 22 3
Rayfield et al. 2008 Biological Conservation 141 2
Rayfield et al. 2009 ecological Modelling 220 5
Reyers et al. 2000 Proc Royal Soc B 267 1442
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Rogers et al. 2013 Biological Conservation 110 5
Rothley & Rae 2005 Env Monitoring and Assessment 10 2
Rouget et al. 2003 Diversity and Distributions 9 3
Rouget et al. 2003 Biological Conservation 1112 1-2
Rubio et al. 2012 Forest Systems 21 2
Sarakinos et al. 2001 Biodiversity and Conservation 10 9
Sarkar et al. 2008 Biodiversity and Conservation 17 10
Schleupner & Schneider 2013 Land Use Policy 30 1
Schneider et al. 2007 PLoS One 211
Scott et al. 2001 Biodiversity and Conservation 10 8
Sergio et al. 2006 J Applied Ecology 43 6
Shriner et al. 2006 Ecological Applications 16 5
Siitonen et al. 2002 Conservation Biology 16 5
Simaika & Samways 2009 Biological Conservation 142 3
Simaika et al. 2013 Biological Conservation 157
Smith et al. 2010 Biological Conservation 143 11
Solomon et al. 2003 Biodiversity and Conservation 12 12
Spring et al. 2010 Conservation Biology 24 3
Steinitz et al. 2005 Conservation Biology 19 6
Vellak et al. 2010 Biodiversity and Conservation 19 5
Villalobos et al. 2013 Biological Conservation 158
Vimal et al. 2011 Biodiversity and Conservation 20 3
Warman et al. 2004 Conservation Biology 18 3
Wiersma & Nudds 2006 Biodiversity and Conservation 15 14
Wiersma & Nudds 2009 Biological Conservation 142 8
Wilhere et al. 2008 Biological Conservation 141 3
Williams et al. 1996 Conservation Biology 10 1
Wu et al. 2013 Zoological Studies 52 1
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Page ArticleTitle
254-262 Designing spatially-explicit reserve networks in the presence of mandatory sites!
2891-2901 Patterns of protection and threats along productivity gradients in Canada
97-107 Identification of de facto protected areas in boreal Canada
151-163 Distribution patterns of biodiversity and the design of a representative reserve network in Portugal
527-533 Area-based refinement for selection of reserve sites with the benefit-function approach
1-15 Conserving population linkages for the Mojave desert tortoise (Gopherus agassizii)
1378-1387 Use of coarse-resolution models of species' distributions to guide local conservation inferences!!
2192-2208 Biodiversity considerations in conservation system planning: Map-based approach for Nova Scotia, Canada
115-125 A new approach for selecting fully representative reserve networks: addressing efficiency, reserve design and land suitability with an iterative analysis
223-230 Environmental representativeness: Regional partitioning and reserve selection!
79-87 Cross-taxonomic potential and spatial transferability of an umbrella species index
393-404 Improving bioregional frameworks for conservation by including mammal distributions
1083-1100 Capturing biodiversity: Selecting priority areas for conservation using different criteria
385-392 Bet-hedging applications for conservation
77-83 Incorporating connectivity into reserve selection procedures
549-557 Designing a coherent ecological network for large mammals in northwestern Europe
14-25 A modeling framework for life history-based conservation planning!
665-672 Habitat loss and connectivity of reserve networks in probability approaches to reserve design
946-955+1076 Nature reserve site selection to maximize expected species covered
4157-4161 Latent extinction risk and the future battlegrounds of mammal conservation
171-181 Umbrella species: Critique and lessons from East Africa!
961-980 Carnivores as focal species for conservation planning in the Rocky Mountain region
426-438 Simulating the effects of using different types of species distribution data in reserve selection
245-258 Conservation planning with irreplaceability: Does the method matter?!!
19374-19379
Global mammal distributions, biodiversity hotspots, and conservation
480-489 Biogeography and hotspots of amphibian species of China: Implications to reserve selection and conservation!
75-84 Using spatial analysis to drive reserve design: A case study of a national wildlife refuge in Indiana and Illinois (USA)!
191-216 A conservation plan for a global biodiversity hotspot - The Cape Floristic Region, South Africa
162-180 Boreal mixedwood forests may have no "representative" areas: Some implications for reserve design
370-378 Protected areas and insect conservation: Questioning the effectiveness of Natura 2000 network for saproxylic beetles in Italy
11 Using the species-area relationship to set baseline targets for conservation
e71788
Creating larger and better connected protected areas enhances the persistence of big game species in the Maputaland-Pondoland-Albany biodiversity hotspot
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1019-1026 Synoptic tinkering: Integrating strategies for large-scale conservation
125-135 Climate change and nature reserves: Examining the potential impacts, with examples from Great Britain!!
434-442 Evaluating reserves for species richness and representation in northern California
393-407 The role of trade-offs in biodiversity conservation planning: Linking local management, regional planning and global conservation efforts
248-257 Defining spatial conservation priorities in the face of land-use and climate change
977-987
Socioeconomic and political trade-offs in biodiversity conservation: A case study of the Cerrado Biodiversity Hotspot, Brazil!
1489-1501 Empirical validation of a method for umbrella species selection
1255-1281 Nature conservation: Priority-setting needs a global change
1229-1241 Priority areas for the conservation of Atlantic forest large mammals
1949-1959 Identifying functionally connected habitat compartments with a novel regionalization technique
19-25 Simulating the value of collaboration in multi-actor conservation planning
817-831 The importance of species range attributes and reserve configuration for the conservation of angiosperm diversity in Western Australia
772-781 Micro-hotspot determination and buffer zone value for Odonata in a globally significant biosphere reserve
46-53 Reserve selection based on vegetation in the Brazilian Atlantic Forest!
131-138 Protected area needs in a changing climate
45-577 Setting conservation targets for sandy beach ecosystems
1939-1958 Complementarity and other key criteria in the conservation of herb-rich forests in Finland
52-59 Uncertainty in coarse conservation assessments hinders the efficient achievement of conservation goals
2127-2137 Using local autocorrelation analysis to identify conservation areas: An example considering threatened invertebrate species in Spain
984-1000 Indentifying a linked reserve system using a regional landscape approach: The Florida ecological network
795-802 Boreal swamp forests: Biodiversity 'hotspots' in an impoverished forest landscape
409-425 Boundaries make a difference: The effects of spatial and temporal parameters on conservation planning
109-135 Threatened plants of New Caledonia: Is the system of protected areas adequate?
37-47 Benefits of earth observation data for conservation planning in the case of European wetland biodiversity
E2602-2610 Global patterns of terrestrial vertebrate diversity and conservation.
673-682 Influence of representation targets on the total area of conservation-area networks
1294-1303 Use of inverse spatial conservation prioritization to avoid biological diversity loss outside protected areas
471-480 Hotspots, complementarity or representativeness? Designing optimal small-scale reserves for biodiversity conservation
169-190 Options for the conservation of large and medium-sized mammals in the Cape Floristic Region hotspot, South Africa
206-217 Incorporating ecological and evolutionary processes into continental-scale conservation planning
1-34 Biodiversity, conservation, and hotspot atlas of Costa Rica: A dung beetle perspective (Coleoptera: Scarabaeidae: Scarabaeinae)
2237-2253
Hotspots and ecoregions: A test of conservation priorities using taxonomic data
105-118 Identifying conservation and restoration priorities for saproxylic and old-growth forest species: A case study in Switzerland!
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13-237 Sizes of Canadian national parks and the viability of large mammal populations: policy implications
796-807 Effect of planning for connectivity on linear reserve networks
1954-1966 Accounting for system dynamics in reserve design
464-473 Minimum dynamic reserves: A framework for determining reserve size in ecosystems structured by large disturbances!
371-383 A framework for systematic conservation planning and management of Mediterranean landscapes
483-495 A straightforward conceptual approach for evaluating spatial conservation priorities under climate change!
389-396 Endemic vertebrates are the most effective surrogates for identifying conservation priorities among Brazilian ecoregions
455-473 Gap analysis of terrestrial vertebrates in Italy: Priorities for conservation planning in a human dominated landscape
60-68 Do hot spots of breeding birds serve as surrogate hot spots of wintering birds? An example from central Spain
63-76 Selecting networks of reserves to maximise biological diversity
1853-1864 Looking for important plant areas: Selection based on criteria, complementarity, or both?
15-28 Assessing biodiversity distribution using diurnal raptors in Andalusia, southern Spain
150-161 A new spin on a compositionalist predictive modelling framework for conservation planning: A tropical case study in Ecuador!
717-727 Logic for designing nature reserves for multiple species
1401-1407 Estimates of minimum patch size depend on the method of estimation and the condition of the habitat!
11-20 Identification of top priority areas and management landscapes from a national Natura 2000 network
355-364 The boundary-quality penalty: A quantitative method for approximating species responses to fragmentation in reserve selection
427-434 Uncertainty analysis favours selection of spatially aggregated reserve networks
519-527 Comparing habitat configuration strategies for retaining biodiversity under climate change
1049-1060 A new method for conservation planning for the persistence of multiple species
800-808 Reserve size, local human density, and mammalian extinctions in U.S. protected areas
908-924 Prioritizing avian conservation areas for the Yellowstone to Yukon Region of North America
1506-1517 Reserve coverage and requirements in relation to partitioning and generalization of land classes: Analysis for western New South Wales
305-319 Size of selection units for future reserves and its influence on actual vs targeted representation of features: A case study in western New South Wales!
263-278 Application of a numerical algorithm to the selection of reserves in semi-arid New South Wales
199-218 Efficiency in conservation evaluation: Scoring versus iterative approaches
55-82 Using abiotic data for conservation assessments over extensive regions: Quantitative methods applied across New South Wales, Australia
99-127 Formulating conservation targets for biodiversity pattern and process in the Cape Floristic Region, South Africa
3027-3043 Conservation of invertebrate biodiversity on a mountain in a global biodiversity hotspot, Cape Floral Region
789-801 Optimized Floating Refugia: A new strategy for species conservation in production forest landscapes
438-449 Comparing static versus dynamic protected areas in the Québec boreal forest
725-733 Incorporating consumer-resource spatial interactions in reserve design
505-513 Complementarity as a biodiversity indicator strategy
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1750-1755 Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries
107-113 Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection!
191-210 Identifying spatial components of ecological and evolutionary processes for regional conservation planning in the Cape Floristic Region, South Africa
129-145 The current configuration of protected areas in the Cape Floristic Region, South Africa - Reservation bias and representation of biodiversity patterns and processes
223-235 Sustaining forest landscape connectivity under different land cover change scenarios
1419-1472 Area prioritization for biodiversity conservation in Québec on the basis of species distributions: A preliminary analysis
2495-2511 Conservation of freshwater fish resources of India: New approaches, assessment and challenges
604-614 Allocation of European wetland restoration options for systematic conservation planning
e1171 Prior exposure to uninfected mosquitoes enhances mortality in naturally-transmitted West Nile virus infection
1297-1301 Representation of natural vegetation in protected areas: Capturing the geographic range
1049-1055 Ecologically justified charisma: Preservation of top predators delivers biodiversity conservation
1660-1673 Reserve networks based on richness hotspots and representation vary with scale
1398-1408 Method for selection of old-forest reserves!
638-651 Reserve selection using Red Listed taxa in three global biodiversity hotspots: Dragonflies in South Africa
245-254 Continental-scale conservation prioritization of African dragonflies
2525-2531
An approach for ensuring minimum protected area size in systematic conservation planning
2435-2441 Conservation targets for viable species assemblages?
691-700 Building a regionally connected reserve network in a changing and uncertain world
1978-1988 Predicting regional patterns of similarity in species composition for conservation planning
1353-1364 Vascular plant and bryophytes species representation in the protected areas network on the national scale
313-320 Range-diversity plots for conservation assessments: Using richness and rarity in priority setting
531-543 The sensitivity of gap analysis to conservation targets
656-666 Sensitivity of systematic reserve selection to decisions about scale, biological data, and targets: Case study from southern British Columbia
4555-4567 Conservation targets for viable species assemblages in Canada: are percentage targets appropriate?
1639-1646 Efficiency and effectiveness in representative reserve design in Canada: The contribution of existing protected areas
770-781 Average optimacity: An index to guide site prioritization for biodiversity conservation
155-174 A comparison of richness hotspots, rarity hotspots, and complementary areas for conserving diversity of British birds
29 Hotspot analysis of Taiwanese breeding birds to determine gaps in the protected area network
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Biodiversity considerations in conservation system planning: Map-based approach for Nova Scotia, Canada
A new approach for selecting fully representative reserve networks: addressing efficiency, reserve design and land suitability with an iterative analysis
Biogeography and hotspots of amphibian species of China: Implications to reserve selection and conservation!
Using spatial analysis to drive reserve design: A case study of a national wildlife refuge in Indiana and Illinois (USA)!
Protected areas and insect conservation: Questioning the effectiveness of Natura 2000 network for saproxylic beetles in Italy
Creating larger and better connected protected areas enhances the persistence of big game species in the Maputaland-Pondoland-Albany biodiversity hotspot
The Forestry Chronicle Downloaded from pubs.cif-ifc.org by CSP Staff on 09/12/16
For personal use only.
Climate change and nature reserves: Examining the potential impacts, with examples from Great Britain!!
The role of trade-offs in biodiversity conservation planning: Linking local management, regional planning and global conservation efforts
Socioeconomic and political trade-offs in biodiversity conservation: A case study of the Cerrado Biodiversity Hotspot, Brazil!
The importance of species range attributes and reserve configuration for the conservation of angiosperm diversity in Western Australia
Micro-hotspot determination and buffer zone value for Odonata in a globally significant biosphere reserve
Uncertainty in coarse conservation assessments hinders the efficient achievement of conservation goals
Using local autocorrelation analysis to identify conservation areas: An example considering threatened invertebrate species in Spain
Indentifying a linked reserve system using a regional landscape approach: The Florida ecological network
Boundaries make a difference: The effects of spatial and temporal parameters on conservation planning
Benefits of earth observation data for conservation planning in the case of European wetland biodiversity
Use of inverse spatial conservation prioritization to avoid biological diversity loss outside protected areas
Hotspots, complementarity or representativeness? Designing optimal small-scale reserves for biodiversity conservation
Options for the conservation of large and medium-sized mammals in the Cape Floristic Region hotspot, South Africa
Biodiversity, conservation, and hotspot atlas of Costa Rica: A dung beetle perspective (Coleoptera: Scarabaeidae: Scarabaeinae)
Identifying conservation and restoration priorities for saproxylic and old-growth forest species: A case study in Switzerland!
The Forestry Chronicle Downloaded from pubs.cif-ifc.org by CSP Staff on 09/12/16
For personal use only.
Minimum dynamic reserves: A framework for determining reserve size in ecosystems structured by large disturbances!
A straightforward conceptual approach for evaluating spatial conservation priorities under climate change!
Endemic vertebrates are the most effective surrogates for identifying conservation priorities among Brazilian ecoregions
Gap analysis of terrestrial vertebrates in Italy: Priorities for conservation planning in a human dominated landscape
Do hot spots of breeding birds serve as surrogate hot spots of wintering birds? An example from central Spain
A new spin on a compositionalist predictive modelling framework for conservation planning: A tropical case study in Ecuador!
Estimates of minimum patch size depend on the method of estimation and the condition of the habitat!
The boundary-quality penalty: A quantitative method for approximating species responses to fragmentation in reserve selection
Reserve coverage and requirements in relation to partitioning and generalization of land classes: Analysis for western New South Wales
Size of selection units for future reserves and its influence on actual vs targeted representation of features: A case study in western New South Wales!
Using abiotic data for conservation assessments over extensive regions: Quantitative methods applied across New South Wales, Australia
Formulating conservation targets for biodiversity pattern and process in the Cape Floristic Region, South Africa
Conservation of invertebrate biodiversity on a mountain in a global biodiversity hotspot, Cape Floral Region
The Forestry Chronicle Downloaded from pubs.cif-ifc.org by CSP Staff on 09/12/16
For personal use only.
Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries
Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection!
Identifying spatial components of ecological and evolutionary processes for regional conservation planning in the Cape Floristic Region, South Africa
The current configuration of protected areas in the Cape Floristic Region, South Africa - Reservation bias and representation of biodiversity patterns and processes
Area prioritization for biodiversity conservation in Québec on the basis of species distributions: A preliminary analysis
Prior exposure to uninfected mosquitoes enhances mortality in naturally-transmitted West Nile virus infection
Reserve selection using Red Listed taxa in three global biodiversity hotspots: Dragonflies in South Africa
Vascular plant and bryophytes species representation in the protected areas network on the national scale
Sensitivity of systematic reserve selection to decisions about scale, biological data, and targets: Case study from southern British Columbia
Efficiency and effectiveness in representative reserve design in Canada: The contribution of existing protected areas
A comparison of richness hotspots, rarity hotspots, and complementary areas for conserving diversity of British birds
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