BIODIVERSITYRESEARCH

Edge artefacts and lost performance innational versus continental conservationpriority areasAtte Moilanen1*, Barbara J. Anderson2, Anni Arponen1,

Federico M. Pouzols1 and Chris D. Thomas2

1Department of Biosciences, P.O. Box 65

(Viikinkaari 1), University of Helsinki, FI-

00014 Helsinki, Finland, 2Department of

Biology, Wentworth Way, University of York,

York, YO10 5DD, UK

*Correspondence: Atte Moilanen, Department

of Biosciences, FI-00014 University of

Helsinki, P.O. Box 65 (Viikinkaari 1),

Helsinki, Finland.

E-mail: atte.moilanen@helsinki.fi

ABSTRACT

Aim Global conservation policies, such as the Convention on Biological Diver-

sity (CBD) decision to aim for the protection of 17% of the area of terrestrial

ecosystems by 2020, are typically realized at national levels. We investigate the

difference between continentally coordinated conservation versus nationally

devolved conservation, in a manner relevant for the Nagoya resolution.

Location The terrestrial areas of the Western Hemisphere.

Methods We used IUCN distribution data for 8463 species of mammals, birds

and amphibians in the Western Hemisphere. We investigated the consequences

of prioritizing land at a continental scale, versus analysing priorities within each

country separately. Spatial prioritization was performed using the ZONATION

software, which produces a complementarity-based hierarchical priority ranking

across the area of interest.

Results We found that coordinated continent-wide priorities achieved > 50%

higher mean protection levels than national analyses for the top 17% of land.

National prioritizations also result in spatial priority patterns that can be con-

sidered as artefacts at the continental scale: in bands of high-priority land con-

centrated at terrestrial political boundaries, such as at low-latitude edges of

temperate zone countries. We find that this edge artefact also correlates with

the present distribution of conservation areas, with the density of conservation

areas within 50 km of a national border being > 50% higher than the density

of conservation areas away from national borders.

Main conclusions The means by which national priorities are integrated with

continental or global conservation prioritization will have considerable influ-

ence on how much is achieved by the CBD resolution. Focus on national spe-

cies distributions and priorities will result in lost performance because of

emphasis on nationally rare species that are comparatively common elsewhere.

National borders intersect species distributions (and possibly diversity gradi-

ents), leading to clustering of nationally rare species and priority areas close to

the border.

Keywords

Administrative units, conservation target, Convention on Biological Diversity,

coordinated conservation, spatial conservation prioritization, ZONATION

software.

INTRODUCTION

International conservation strategies and priorities are fre-

quently devolved to national governments and conservation

organizations for their implementation. This facilitates deliv-

ery within national legal systems and allows international

priorities to be adjusted to the needs of local biological and

human communities. Conservation priorities are currently

DOI: 10.1111/ddi.12000ª 2012 Blackwell Publishing Ltd http://wileyonlinelibrary.com/journal/ddi 1

Diversity and Distributions, (Diversity Distrib.) (2012) 1–13A

Jou

rnal

of

Cons

erva

tion

Bio

geog

raph

yD

iver

sity

and

Dis

trib

utio

ns

particularly relevant with respect to the implementation of

the resolutions of the tenth Conference of Parties to the

Convention on Biological Diversity, which was held on Octo-

ber 2010 in Nagoya, Japan. It was decided that biodiversity

loss should be halted and that biodiversity should be valued,

conserved, restored, wisely used and shared equitably, main-

taining ecosystem services, sustaining a healthy planet and

delivering benefits essential for all people (Normile, 2010;

UNEP/CBD, 2010; Harrop, 2011). Global efforts towards a

sustainable environment will be investigated further in the

Rio + 20 conference (UNCSD, 2012).

It has long been argued that the prior 10% global conser-

vation target was inadequate, in part because of inefficient

site selection whereby existing protected areas are often

located in low-productivity and inaccessible regions, leading

to imbalances in the representation of different ecosystems in

the global protected area network (Rodrigues et al., 2004;

Gaston et al., 2008; Fuller et al., 2010). One of the most

prominent vehicles of action arising from the Nagoya meet-

ing was Target 11, a decision to increase the area of terres-

trial ecosystems protected to 17% globally (Harrop, 2011).

This target has already been partway met in terms of area, as

the present global percentage of protected area has increased

to over 12% (McDonald & Boucher, 2011). Nevertheless,

given prior massive imbalances in protection levels across

biomes, there necessarily remains much need for expanded

protection measures (Jenkins & Joppa, 2009). The Nagoya

meeting also called for conservation ‘decision-making [to be]

based on sound science’ (UNEP/CBD, 2010) – in the context

of the 17% target, how can priority areas for conservation be

selected efficiently to protect the maximum amount of

biodiversity possible in a given area?

The requirement of equitability suggests that conservation

effort should take place in all countries (UNEP/CBD, 2010),

but previous work suggests that globally planned conservation

would be more efficient than locally distributed conservation

effort. Soutullo & Gudynas (2006) investigated protection of

bioregions across the countries of South America and found

that regionally coordinated conservation would be more effi-

cient than national decision-making. Much of the Earth’s

unprotected biodiversity lies in global priority areas identified

by conservation NGOs, which also suggests a need for globally

coordinated action (Soutullo et al., 2008). In the USA, a spa-

tially explicit study found that representing mammal species in

all states separately required ten times the area than represent-

ing species nationally (Vazquez et al., 2008). Coordinated con-

servation of amphibians, reptiles and fish around the

Mediterranean would have been 45%more efficient than unco-

ordinated conservation (Kark et al., 2009). Coordinated con-

servation at European wetlands would have been 30% more

efficient than uncoordinated effort (Jantke & Schneider, 2010).

Going beyond international and national, Pajaro et al.

(2010) find that policy development related to marine pro-

tected areas occurs at three levels: international, national and

local, with information feedback and conflict resolution

between levels needed. It has also been suggested that marine

conservation planning should be integrated with broader

marine spatial planning and ocean zoning to avoid failure of

conservation effort (Agardy et al., 2011). Inside a country,

Strange et al. (2006) investigated conservation within Den-

mark and found that nationally coordinated conservation

could be up to 20 times more efficient than regionally

devolved effort. They suggest that in economic and biodiver-

sity terms, it can largely be a win–win situation to set a com-

mon goal, to develop priority strategies and to coordinate

actions at higher rather than at lower levels of administra-

tion. Chiarucci et al. (2008) investigated patterns of species

composition across the European Natura 2000 network and

found that ecosystem-level complementarity of areas is criti-

cal for the performance of the network – and achieving such

complementarity at the European scale requires coordinated

conservation effort. Indeed, in Europe, conservation has been

moving towards a higher level of international coordination

(Cogalniceanu & Cogalniceanu, 2010). Taking a more eco-

nomical perspective, White et al. (2012) found that manage-

ment of ecosystem services that is coordinated across

interacting sectors and stakeholders may produce more than

double the societal gains that what can be expected from

uncoordinated effort (White et al., 2012). In the Nether-

lands, collective contracts allow neighbouring land managers

to coordinate environmental management at the landscape

rather than the farm-scale, reducing costs and increasing

participation rates in conservation (Franks, 2011).

Following the Nagoya call for a science-based approach, we

here present new spatially explicit large-scale analyses that con-

trast national and continental targeting of conservation, specif-

ically in the context of the 17% terrestrial conservation

coverage target. We use ‘continental’ as a shorthand for anal-

yses where priorities are evaluated in a coordinated manner

across one or more continents – here, North, Central and

South America, and associated islands were used as a single

entity for analysis. We use ‘national’ as a shorthand for analy-

ses across the same overall geographical region, but where

independent priorities are devolved, and hence set indepen-

dently for each country within these continents. We in particu-

lar focus on what can be achieved with 17% of land when it is

selected in a continentally efficient manner, compared to selec-

tion that emphasizes approximately equal conservation efforts

across all countries. We also focus on what happens around

the borders of countries, as previous work has shown that the

boundary of the planning region influences both the total area

needed to meet conservation goals and the spatial location of

suggested additions to conservation area networks (Huber

et al., 2010). The same general principles and issues identified

here apply to levels of selection other than 17%.

METHODS

Data

We undertook a continental-scale priority ranking analysis

for the terrestrial areas of the Western Hemisphere. Analysis

2 Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd

A. Moilanen et al.

was based on the distributions of 2928 amphibians from the

world amphibian data (IUCN, Conservation International, &

NatureServe, 2006), 1642 mammals from the world mammal

data (IUCN, 2009), and information on 3893 bird species

obtained from Ridgely et al. (2007). The distribution poly-

gons of the amphibian and mammal species were converted

into equal-area presence–absence occupancy grids (World

Behrmann projection, datum WGS 1984; 50 km 9 50 km

rectangular grid cells), using the ‘Vector to Grid’ function in

ARCGIS/ARCINFO 9.2 (ESRI, Redlands, CA, USA). Marine

species and grid cells were excluded from this analysis.

Islands that were too small to include the centre point of

even one grid cell were also excluded. We calculated existing

levels of protection for each grid cell by calculating the frac-

tion of the grid cell covered by land designated as IUCN cat-

egories I-IV protection levels, using the IUCN & UNEP,

2010 data (IUCN & UNEP, 2010).

Analysis methods

We used a publicly available spatial conservation prioritiza-

tion method and software, ZONATION, to produce large-scale

conservation priority rankings (Moilanen et al., 2005; Arpo-

nen et al., 2012). The principles of these analyses used here

have been described in detail elsewhere, and the software and

documentation are freely publicly available (Moilanen et al.,

2005, 2011a,b). In the analyses presented here, we evaluate

the efficiency with which (and locations where) species could

be protected, although we could also consider other entities

of importance, such as ecosystem services (Moilanen et al.,

2011a).

Verbally described, spatial priority ranking by Zonation

takes a series of units, here equal-area grid cells, and itera-

tively ranks them in order, from lowest to highest priority,

based on the representation of biodiversity and other infor-

mation from those cells. Normally, this method is applied to

all of the cells in one region (e.g. country), for example, to

identify the most important locations for conservation. Here,

we use an analysis variant that effectively joins multiple con-

servation prioritization analyses, one global and one for each

administrative sub-region (Moilanen & Arponen, 2011). This

analysis is best understood by examining an intermediate

equation that defines how conservation value is handled

during the ranking process (Moilanen & Arponen, 2011):

VðSÞ ¼ qX

j

Vglobalj Sð Þ þ ð1� qÞ

X

A

X

j

V localjA ðSÞ

¼ qX

j

wGj f

Gj RjðSÞ� �þ ð1� qÞ

X

A

GA

X

j

wLjAfjA RjAðSÞ

� �:

(1)

This equation gives conservation value V() as a function

of a set of areas, S. Value is combined from two compo-

nents, a global (here continental) one and a local (national)

one, the balance between which is tuned by parameter q. In

this equation, weights (w), benefit functions (f) or represen-

tation (R) are indexed by administrative sub-region (index

A), by species (j), and for global (G) and local (L) compo-

nents. During iterative ranking, change in conservation value

V(S) is evaluated for loss of each grid cell remaining in S,

and the cell that leads to smallest loss is chosen for removal

next. Starting from the full landscape and iteratively mini-

mizing loss leads to a ranking that identifies least important

grid cells at low ranks and successively more valuable cells

are retained for higher ranks.

Features relevant for the present analysis include: (1) set-

ting q = 0 produces an analysis where rankings for individual

countries are effectively independent from the rankings of

other countries – this is our national analysis. (2) Setting

q = 1 results in an analysis where only global considerations

influence the ranking – this is our continental analysis. (3)

An intermediate q between 0 and 1 produces a compromise

analysis that combines global and local considerations. After

generating a ranking, we can identify its top 17% (or any

other percentage) of cells, corresponding to the Nagoya Tar-

get. The top 17% can also be identified separately from

within each country, equivalent to national devolution of

Target 11. With respect to the compromise solution, the one

we used effectively allows deviation from the per-country

17% to allow higher emphasis on species-rich tropical

regions. A different kind of compromise would be to select

17% for each country, but to do so based on continental pri-

orities. This result could be obtained by picking the highest-

ranked 17% of cells for each country from the continental

analyses.

We repeated each of the above analyses (continental,

national, compromise) using two major Zonation analysis

variants, the additive benefit function (ABF) and core-area

Zonation (CAZ) (Moilanen et al., 2005, 2011a). ABF and

CAZ represent conceptually different views of conservation

value, and hence, the analyses complement each other. ABF

favours grid cells that contain large numbers of localized spe-

cies (summing value across species), combined with a species

–area approach to minimize extinction rates (Moilanen et al.,

2011a). The ABF power function was set to zj = 0.25 for all

species, typical of species–area curves. CAZ considers each

species separately, securing high-quality locations for all spe-

cies, even when they occur in otherwise species-poor regions

(Moilanen et al., 2005, 2011a). Technically, differences

between ABF and CAZ manifest in different across-species

aggregation structures and different benefit functions in

equation 1; see e.g. Moilanen et al. (2011a).

With respect to parameter values, we treated all species as

equal, with species weights wj = 1.0 for all species j, both

locally and globally. [Note that even when equally weighted,

Zonation emphasizes narrow-range and shrinking range spe-

cies because of iterative range-size normalization employed

in computations, maintaining a balance across all features all

through the ranking (Moilanen et al., 2005, 2011a).] The

weights of countries were set equal to the area of the country

(Table 1) and normalized to sum to 1 (Moilanen & Arpo-

nen, 2011). We used q = 0.003 (ABF) and q = 0.001 (CAZ)

Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd 3

National edge artefacts in spatial conservation

in the compromise analyses, as values that achieved approxi-

mately intermediate performance between continental coor-

dinated and national analyses (q = 0.5 does not imply an

analysis that is exactly balanced between global and local

units as the interpretation of q is case-specific and depends,

among other things, on the weights given to countries – see

Moilanen & Arponen, 2011).

The present work bears superficial resemblance to those

employing the ‘maximum coverage principle’ in reserve

selection (Camm et al., 2002; Margules & Sarkar, 2007).

These studies employ optimization to maximize the number

of (species-level) representation targets that can be satisfied

given limited resources and concentrate only on the best

parts of the study area. Zonation represents very different

principles to those employed in target-based systematic con-

servation planning. The continuous ranking of locations

(lowest to highest value) that we produce does not require

us to set a priori area or species targets or to concentrate

only on the ‘best cells’ (Moilanen et al., 2005). It is practi-

cally and quantitatively advantageous that targets need not

be set separately for 8463 features (species) in each of the 32

countries (Di Minin & Moilanen, 2012). Nonetheless, we can

still derive the locations of the ‘best’ 17% once the analysis is

complete, facilitating interpretation in the context of the

Nagoya resolutions.

RESULTS

Spatial prioritization at the continental-scale results in most

high-priority areas being located at low latitudes and often

in montane and insular regions (Fig. 1a,b). When analyses

are carried out in each country separately, priority areas are

evenly distributed among countries, the red and orange col-

ours identifying the top 17% within each country separately

(Fig. 1c,d). Most of Central America and countries along

the Andes receive high conservation priorities in continen-

tal-scale analyses (Table 1) but, by definition, only 17%

of their land would be prioritized within national-level

Table 1 Statistics about countries included in this study, arranged according to the global CAZ analysis (by percentage of country

assigned to top 17%). Statistics are not shown for the national solutions because 17% of each country will be included in its top 17%.

The column ‘CBD’ shows whether the country is a member of the Convention on Biological Diversity, with consequent implications on

the implementation of the Nagoya resolutions in the country

Country No. of cells

% of cells of the country in top 17% fraction

CBD member

ABF CAZ

Continental Compromise Continental Compromise

Haiti 4 100.0 50.0 100.0 50.0 No

Jamaica 2 100.0 100.0 100.0 100.0 No

Costa Rica 17 100.0 82.4 100.0 47.1 Yes

Puerto Rico 2 100.0 100.0 100.0 100.0 No

Panama 20 100.0 80.0 95.0 40.0 Yes

Ecuador 87 100.0 72.4 86.2 31.0 Yes

Cuba 29 100.0 37.9 79.3 37.9 Yes

Dominican Rep. 17 100.0 52.9 76.5 35.3 Yes

Guatemala 43 72.1 37.2 69.8 34.9 Yes

Honduras 43 86.0 32.6 67.4 23.3 Yes

Belize 8 100.0 12.5 62.5 0.0 Yes

Peru 495 67.1 37.6 44.2 25.3 Yes

Chile 223 30.5 9.9 38.1 12.1 No

Nicaragua 42 88.1 19.0 38.1 7.1 Yes

Colombia 438 42.5 36.8 37.7 24.9 Yes

French Guiana 32 87.5 15.6 37.5 6.3 No

Mexico 727 38.4 24.2 37.4 27.1 Yes

Venezuela 355 41.1 24.2 33.5 20.3 Yes

Uruguay 72 19.4 5.6 29.2 4.2 Yes

El Salvador 7 100.0 28.6 28.6 14.3 Yes

Suriname 59 44.1 10.2 25.4 6.8 Yes

Bolivia 435 26.9 22.8 25.3 14.5 Yes

Argentina 1101 13.2 13.4 20.4 17.3 No

Guyana 82 26.8 14.6 18.3 4.9 Yes

Brazil 3348 16.6 26.4 15.2 22.5 Yes

Paraguay 160 10.6 8.8 13.1 1.3 Yes

United States 3578 8.0 11.3 11.9 17.9 No

Canada 3463 0.4 4.7 2.4 7.1 No

4 Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd

A. Moilanen et al.

analyses. Prioritizations that simultaneously implement joint

continental and national priorities generate intermediate

patterns (Fig. 2, Table 1). ABF and CAZ analyses lead to

similar conclusions, albeit with a ‘spottier’ distribution

within the CAZ solutions (Figs 1 & 2), implying that while

most species could be efficiently protected by large semi-

continuous conservation areas, there are species that only

occur in relatively species-poor regions critical for few

species only.

National-scale analyses result in major artefacts because of

the imposition of political boundaries. This is particularly

striking along the border between Canada and the contigu-

ous USA, where adjacent cells that contain virtually identical

biotas are top 17% cells on the Canadian side of the border

but in some cases bottom 17% cells in the USA (Fig. 1). The

thermal-latitudinal diversity gradient results, in this case, in

similar biotas having high priority in Canada but low prior-

ity in the USA. Fundamentally, the cause of this artefact is

that species that are rare in one country (say, Canada) are

abundant in another (say, USA). Similar effects are seen at

other temperate zone borders, particularly the USA–Mexico

border, and to some extent in northern Argentina, where the

national-scale analyses cluster priority areas near the coun-

tries’ low-latitude borders. These artefacts extend to the tro-

pics, with national-level analyses, for example, showing

increased representation close to the geographical borders of

Brazil (e.g. in the north with French Guiana and in the west

with Peru). In each case, areas are identified that are nation-

ally more important than they would be at a continental

scale.

(a) (b)

(c) (d)

Figure 1 Conservation prioritization for the Western Hemisphere based on amphibians, mammals and birds. We show results for

continental ABF and CAZ analyses (a and b), and national ABF and CAZ analyses (c and d). The continental prioritizations have

treated the entire Western Hemisphere as one planning unit, with the oranges and reds identifying the highest priority 17% of land

across the entire region. The devolved, national analyses are based on the national distributions of species, with oranges and reds

identifying the highest priority 17% of land within each country, ignoring the distributions of species elsewhere in North and South

America. ABF places higher emphasis on species richness than CAZ, which aims at the inclusion of high-quality areas for all species

even when they occur in otherwise species-poor regions.

Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd 5

National edge artefacts in spatial conservation

Zonation performance curves quantify the fractions of spe-

cies’ distributions (here averaged across species) that are cov-

ered at any stage of the priority ranking. These show that

continental-scale analyses are most efficient, and national-

only analyses are least efficient, at delivering species-level glo-

bal biodiversity targets (Fig. 3). ABF is on average more effi-

cient than CAZ (Fig. 3), but the latter increases the cover

given to localized species that occur in low-diversity regions

(a result that may be desired but is not visible in averaged

performance curves). Considering the top 17% of the land

alone, ABF delivers 66%, and CAZ 60.5%, of the distribution

areas (averaged across species) of Western Hemisphere mam-

mals, birds and amphibians in the continental-scale analyses

(Fig. 3). Because a random selection of 17% of area would

by statistical necessity provide 17% mean coverage across

species, it follows that efficient continental selections are 3.9

and 3.6 times as effective as selecting land at random, for

ABF and CAZ, respectively. The continental ABF analysis

provides an upper limit to the biodiversity that could poten-

tially be obtained in 17% of the terrestrial area (Figs 1 & 3).

In contrast, the national ABF or CAZ solutions provide only

42% and 39% mean coverage across species distributions.

While ABF compromise performance falls smoothly between

continental and national analyses, the CAZ compromise

solution performs poorly, particularly in identifying the top

10% of the land surface (Fig. 3). This somewhat surprising

result is because the CAZ compromise must retain high-

quality locations for all species both locally and globally,

which requirement is more stringent than providing only

continental or national coverage. In effect, covering all

nationally or continentally rare species leads to losses in

mean conservation levels across all species as a whole.

(a) (b)

Figure 2 Combined continental + national compromise prioritizations for ABF (a) and CAZ (b). By varying the relative weight given

to the continental component, it is possible to generate an effectively continuous range of compromise solutions between the continental

and national solutions (Fig. 1).

Figure 3 The Zonation performance curves corresponding to

the priority maps of Figures 1 and 2. These curves report the

mean (across species) fraction of the distribution of each species

retained as a function of fraction of land reserved for protection.

Of these curves, the continental ABF solution is most efficient: it

is able to retain the highest fraction of species distributions,

implying high return on investment in areas belonging to high

ABF ranking cells. CAZ produces slightly lower mean

performance, compared to ABF, because CAZ gives higher

protection levels to species occurring in relatively species-poor

areas. All variants of local (national) prioritization lose

efficiency. This is because conservation priorities are relocated

from endemic- and species-rich tropical and montane regions to

relatively species-poor areas closer to the poles. Differences in

conservation efficiency between methods are substantial: for

example, national-level CAZ analysis provides < 40% mean

coverage across all species within the top 17% of the land,

whereas continental ABF provides ~66% coverage.

6 Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd

A. Moilanen et al.

We tested the stability of our analyses to changes in spe-

cies data by two approaches. First, we considered the robust-

ness of conclusions to choice of taxonomic group (see

Appendix S1 in Supporting Information), finding that our

main conclusions do not change. For example, very strong

bands of high-priority land are present in national analyses

and absent in continental analyses along all of the borders

where this artefact was identified by the main analyses

(Fig. 1; Fig. S1, Fig. S2, Fig. S3). In contrast to previous

work (Kark et al., 2009), the edge artefact is also present for

amphibians for both temperate zone and tropical borders.

These separate analyses also identify that some regions are of

high priority for all three taxonomic groups. Such areas

include the Atlantic rain forest of Brazil, southern parts of

Mexico, the spine of the Andes and parts of the west coast

of USA. Some regions are of higher significance for individ-

ual taxa, but most of the areas that are priorities for one of

the taxonomic groups are also prioritized for at least one of

the other groups (Table S1; e.g. Hispaniola is relatively more

important for birds and amphibians than for mammals, and

the Amazon River corridor emerges more strongly for birds

and mammals than for amphibians). Continental analyses

consistently place higher priority on large areas of Central

America, on the west coast of USA and on areas of South

America expanding either side of and down the spine of

the Andes, whereas national analyses tend to redistribute

priorities towards national boundaries.

We also tested the stability of our analyses to the number

of species included using sensitivity analysis. The basic con-

tinental and national ABF and CAZ analyses (Fig. 1) were

replicated 10 times taking a random 50% sample of the

full 8463 species. It was found that the top 17% fractions

of the landscape on average overlapped to a degree of

84.8% (national ABF; SD = 0.45%), 85.3% (continental

ABF; SD = 0.37%), 69.8% (national CAZ; SD = 1.6%) and

72.8% (continental CAZ; SD = 1.2%). Thus, coordinated

continental-scale analyses were robust to the particular

species included.

We also examined the relationship between the ranking of

locations in the Zonation analyses and the distribution of

actual protected areas (PAs), defined as existing IUCN cate-

gory I-IV PAs. PAs are not very efficiently placed by these

criteria: the very highest priority grid cells according to

Zonation ranks do have slightly higher fractions protection

than land overall, but conservation areas are also widely

located across lowest ranked areas (Fig. 4). Only approxi-

mately 10% of the top 5% of land is protected, indicating

that any unprotected natural or semi-natural habitat within

Figure 4 Average fraction of grid cells protected compared to priority rank in the present Zonation analyses (with 1% intervals on

x-axis). Rank 99–100 corresponds to the top 1% and rank 0–1 to the least important 1%.

Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd 7

National edge artefacts in spatial conservation

the top-priority cells could be considered for protection as

the world works towards fulfilling the Nagoya 17% target.

The virtual lack of correlation between continental-scale

ranked priorities and existing PAs (Fig. 4) indicates, and

agrees with prior evaluations (Gaston et al., 2008), that con-

servation designation is inefficient (from a biodiversity per-

spective), although of course PAs are likely be situated in

better-than-average habitat inside each cell.

The role of national priorities in past PA selection can be

seen in two ways. First, there are stronger (albeit still quite

weak) correlations between national priority ranks and the

designation of PAs, than for continental priorities (Fig. 4).

Furthermore, the relationship is stronger for (the overall less

efficient) CAZ, suggesting an emphasis on prioritizing indi-

vidual species. Second, existing PAs disproportionately clus-

ter around country boundaries. Comparison of the top 17%

areas (as defined by the ABF or CAZ analyses) against the

distribution of present protected areas identifies areas where

conservation would be highly efficient at the continental level

(yellow–orange colour, Fig. 5a,b). The artefact that national

priorities cluster around terrestrial borders between countries

(Fig. 5c,d) is seen by the concentration of top 17% priority

cells around country borders (Fig. 6). Bias towards borders

is actually also seen in the present distribution of IUCN cate-

gory I-IV protected areas: 11.9% of the continents’ PA land

currently falls within border cells, which comprised only

7.7% of the continental land surface in our analysis.

DISCUSSION

The CBD Nagoya Target 11 has again raised the profile of

where best to protect ecosystems, leading to choices of where

protected areas (PAs) and other conservation-related land

designations and actions (e.g. conservation easements)

(a) (b)

(c) (d)

Figure 5 Potential for expanded conservation measures. Colours from yellow to red show the fraction of land currently protected in

the top 17% areas of priority rankings. The greyscale shows the fraction of land already protected in areas that do not belong to top

17% regions. Colours in light yellow and orange show areas that belong to top 17% ranks but where present conservation coverage is

below 2%. Results are shown both for the ABF and CAZ, continental and national analyses corresponding to Fig. 1.

8 Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd

A. Moilanen et al.

should best be located. One, but only one, of the consider-

ations is where biodiversity can be conserved most effec-

tively, as a cultural ecosystem service in its own right, and

for its contributions to other ecosystem goods and services

and their resilience. The analyses presented here contribute

to this aspect of decision-making and need to be judged

alongside a number of other social, economic and political

interests (Ceballos & Ehrlich, 2006; Wilson et al., 2007; Nel-

son et al., 2009; Eklund et al., 2011). Given that decisions

that flow from CBD targets, including legislative designation

of PAs, are commonly devolved to individual countries, each

country must judge how best to balance national versus

international interests in the implementation of targets. The

results in this article highlight that this choice, as applied to

the mammal, bird and amphibian biota of the New World,

has major implications as to where priority areas lie, as well

as for the overall efficiency of conservation strategies. While

the targets discussed in Nagoya were determined in a collab-

orative process, each country may still act independently to

achieve the target within its national boundaries, which will

likely lead to redundancy and inefficiency in conservation

efforts. Prior evidence from conservation biogeography sug-

gests that the need for additional conservation differs greatly

across biomes and countries, also suggesting that equal

national conservation area targets may be ecologically ineffi-

cient (e.g. Jenkins & Joppa, 2009; Schuldt & Assmann, 2010;

Marinesque et al., 2012). In this study, the coordinated, con-

tinental-scale analyses delivered over one and a half times

the conservation value (measured as the average fraction of

species’ ranges protected) of the nationally devolved analyses.

National-scale decision-making can potentially assign high

priorities to locations that are unusual in that country but of

low international importance. The analyses we present show

that national-only prioritization is inefficient at protecting

biodiversity internationally, but that this can be improved

somewhat in ‘compromise’ solutions that take both national

and international interests into account. However, the results

point not just to overall inefficiencies of fully devolved deci-

sion-making, but also to major artefacts. Country-level prior-

itization may result in the clustering of highly ranked areas

near to political boundaries. This observation was previously

made by Vazquez et al. (2008) for mammals of North Amer-

ica, but is strikingly visible across the larger area analysed in

the present work. There are two other studies that have

investigated national versus coordinated conservation. Jantke

& Schneider (2010) did not observe high priorities close to

geographical boundaries, probably because the environment

analysed, wetlands of Europe, has a very fragmented distribu-

tion. Neither were national edge artefacts observed in

another study that used data about distributions of amphibi-

ans, reptiles, freshwater fish and land cover types around the

Mediterranean basin (Kark et al., 2009). Our results suggest

that these artefacts are strong, that they apply to tropical

national boundaries as well as to those in the temperate zone

(Fig. 1), and that they seriously reduce the overall efficiency

of conservation strategies.

The clustering of national, but not international, priorities

near political boundaries arises because arbitrarily located

country boundaries (from the perspective of biodiversity) cut

across the geographical ranges of species. Hence, a single

Figure 6 Distributions of Zonation priority ranks at grid cells adjacent to national terrestrial borders between countries. Points are in

one per cent bins, by Zonation rank. In the continental analyses, the highest 17% conservation-value (rank 83–100) cells are no more

likely than mid-ranking cells to occur close to political borders. In contrast, high ranks are disproportionately associated with borders in

national analyses. The very lowest ranks do not occur at borders in the continental analyses because they are located in comparatively

species-poor areas of northern Canada where there are no national borders.

Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd 9

National edge artefacts in spatial conservation

species may be localized near to the geographical edge of one

country (where national conservation agencies may prioritize

it), but potentially widespread in another country. If so

desired, boundary effects might be partially compensated in

national analysis by prioritizing the conservation of interna-

tionally rare or endangered species within countries. Never-

theless, the boundary artefact will still arise if nationally, but

not internationally, rare species are also prioritized within

countries (Fig. 2). Although our analyses involved the distri-

butions of species, similar considerations apply to designa-

tions based on nationally (but not internationally) rare

habitats, ecosystems, and in some cases, ecosystem goods

and services. On the other hand, the higher density of pres-

ent IUCN protected areas near boundaries of countries

might be influenced by additional factors. Observations from

economic and institutional geography suggest that patterns

of comparatively low habitat degradation may be found

along the no-man’s land of border zones, making nature

conservation in those areas attractive (Dudley et al., 2002).

Nonetheless, it is important to recognize that the boundary

effects reported here result in an overall reduction in conser-

vation efficiency, at a continental scale.

We tested the robustness of our results in by considering

the taxonomic groups (mammals, birds, amphibians) sepa-

rately and found that the same general issues were relevant.

The taxa largely shared the similar priority areas, and the

boundary effects were as prominent within each group as it

had been for the combined analysis (online Appendix). We

also tested the stability of our analyses by replicating them

using 50% subsamples of the original data and found that

conclusions remained unchanged. It is possible though, that

addition of new higher taxa, such as plants or insects, could

change priority patterns more significantly, particularly if

they differ in environmental constraints and/or average geo-

graphical range sizes. The expectation was that ABF analyses

should be comparatively stable, as they are more focused on

species richness and allow for some compensation between

species (Moilanen, 2007). This expectation was borne out by

the sensitivity analysis. Overall, ABF top areas (Fig. 1a) show

a remarkable degree of connectedness at this coarse resolu-

tion, suggesting that the highlighted areas would be critical

for continental-scale green ‘infrastructure’ (Tzoulas et al.,

2007). In contrast, the CAZ analyses are somewhat more sen-

sitive to the identities of individual species, as they have an

aim of securing high-quality locations for all species. This

makes CAZ analyses less stable at the national scale (see

Results) because the discovery/addition of new species can

generate new ‘nationally rare’ species, that shift the priority

areas towards those (usually border) areas. The same conclu-

sion extrapolates to traditional systematic conservation plan-

ning, which is focused on implementation of conservation

and cost-efficient covering of species-specific representation

targets (e.g. Margules & Sarkar, 2007; Pressey & Bottrill,

2008; Sarkar & Illoldi-Rangel, 2010).

It is important to ask what data conservation prioritization

should be based on (e.g. Margules & Sarkar, 2007; Wilson

et al., 2007; Boitani et al., 2011). It would be desirable to

include additional taxa, such as plants and insects, in future

analyses but the overall concentration of priority areas in

Middle America, the Andes, and the Atlantic forest of Brazil

are important for a wide range of taxa (Grenyer et al., 2006;

Lamoreux et al., 2006). Given the nature of the biodiversity

data, we restricted our analyses to 50-km resolution, but our

general conclusions (relative efficiencies of country- and

international-level analyses and displacement of priority areas

towards political boundaries) are robust to resolution. How-

ever, the 50-km resolution is not sufficient to select sites for

on-the-ground targeting of conservation action (Hurlbert &

White, 2005; Orme et al., 2006; Hurlbert & Jetz, 2007; Jetz

et al., 2007; Hermoso & Kennard, 2012). Rather, highly

ranking 50-km grid cells represent regions within which to

search for specific locations to protect. A series of additional

considerations will become important at this stage, including

identifying undisturbed ecosystems and habitat types that

contain the highest value species. Within these regions,

socio-political concerns and human-caused factors will influ-

ence operational conservation decisions (Ceballos & Ehrlich,

2006; Knight et al., 2006; Eklund et al., 2011; Rondinini

et al., 2011; Wilson et al., 2011). These include implementa-

tion costs, opportunity costs and needs of alternative land

uses (Pressey et al., 2007; Wilson et al., 2007, 2011; Moilanen

et al., 2011a; Rondinini et al., 2011), threats and vulnerabil-

ity (Brooks et al., 2006; Wilson et al., 2006, 2011; Pressey

et al., 2007; Rondinini et al., 2011) and ecosystem services

(Naidoo et al., 2006; Nelson et al., 2009; UNEP/CBD, 2010),

which are prominent in the Nagoya resolution. Notwith-

standing these additional considerations, we note that only a

small amount (~10%) of the top 17% of the current land

surface is currently protected by IUCN category I-IV pro-

tected areas (Figs 4 & 5), so there is undoubtedly scope to

select at least some further areas for conservation within

these 50-km regions.

The Nagoya convention relies substantially on voluntary

conservation action, in which decisions reflect the outcome

of multiple competing interests and pressures (Harrop &

Pritchard, 2011). Most of these decisions will take place at a

regional, national or sub-national level. The combined conti-

nental and local analyses presented here have the potential to

increase the efficiency of decision-making by enabling coun-

try-level decision-making to take place in the context of

international priorities and preferably for nations whose land

is of relatively low conservation priority to help support con-

servation delivery in countries where the need is greatest. In

terms of conservation implications, the present work strongly

suggests that large-scale coordination of conservation efforts

in response of the Nagoya treaty would be highly desirable,

instead of prioritization based on national distributions of

biodiversity features. Focus on national-level protection of

species will lead to significantly reduced conservation effec-

tiveness at the global scale. Our results also confirm that

national species-based conservation priorities would tend to

concentrate close to terrestrial boundaries between countries.

10 Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd

A. Moilanen et al.

This outcome can be expected even without any special

ecological factors elevating priorities around borders. Rather,

such edge effects are an unavoidable consequence of national

boundaries crossing large-scale patterns of species distribu-

tions, leaving some species rare just at one side of the

border.

ACKNOWLEDGEMENTS

A.M. and F. M.-P. thank the ERC-StG project GEDA (grant

260393) for financial support. B.J.A. and C.D.T. thank NERC

for financial support. A.A. thanks the Academy of Finland

grant #250126 and EU FP7 project SCALES #226852 for

support. We thank Aija Kukkala and Johanna Kuustera for

technical assistance.

REFERENCES

Agardy, T., di Sciara, G.N. & Christie, P. (2011) Mind the

gap Addressing the shortcomings of marine protected areas

through large scale marine spatial planning. Marine Policy,

35, 226–232.

Arponen, A., Lehtomaki, J., Leppanen, J., Tomppo, E. &

Moilanen, A. (2012) Effects of connectivity and spatial res-

olution of analyses on conservation prioritization across

large extents. Conservation Biology, 26, 294–304.

Boitani, L., Maiorano, L., Baisero, D., Falcucci, A., Visconti,

P. & Rondinini, C. (2011) What spatial data do we need to

develop global mammal conservation strategies? Philosophi-

cal Transactions of the Royal Society of London B, 366, SI

2623–2632.

Brooks, T.M., Mittermeier, R.A., da Fonseca, G.A.B., Gerlach,

J., Hoffmann, M., Lamoreux, J.F., Mittermeier, C.G., Pil-

grim, J.D. & Rodrigues, A.S.L. (2006) Global biodiversity

conservation priorities. Science, 313, 58–61.

Camm, J.D., Norman, S.K., Polasky, S. & Solow, A.R. (2002)

Nature reserve site selection to maximize expected species

covered. Operations Research, 50, 946–955.

Ceballos, G. & Ehrlich, P.R. (2006) Global mammal distribu-

tions, biodiversity hotspots, and conservation. Proceedings

of the National Academy of Sciences USA, 103, 19374–

19379.

Chiarucci, A., Bacaro, G. & Rocchini, D. (2008) Quantifying

plant species diversity in a Natura 2000 network: Old ideas

and new proposals. Biological Conservation, 141, 2608–2618.

Cogalniceanu, D. & Cogalniceanu, G.C. (2010) An enlarged

European Union challenges priority settings in conserva-

tion. Biodiversity and Conservation, 19, 1471–1483.

Di Minin, E. & Moilanen, A. (2012) Empirical evidence for

reduced protection levels across biodiversity features from

target-based conservation planning. Biological Conservation,

153, 187–191.

Dudley, J.P., Ginsberg, J.R., Plumptre, A.J., Hart, J.A. &

Campos, L.C. (2002) Effects of war and civil strife on wild-

life and wildlife habitats. Conservation Biology, 16, 319–329.

Eklund, J., Arponen, A., Visconti, P. & Cabeza, M. (2011)

Governance factors in the identification of global conserva-

tion priorities for mammals. Philosophical Transactions of

the Royal Society B, 366, SI 2661–2669.

Franks, J.R. (2011) The collective provision of environmental

goods: a discussion of contractual issues. Journal of Envi-

ronmental Planning and Management, 54, 637–660.

Fuller, R.A., McDonald-Madden, E., Wilson, K.A., Carwar-

dine, J., Grantham, H.S., Watson, J.E.M., Klein, C.J.,

Green, D.C. & Possingham, H.P. (2010) Replacing under-

performing protected areas achieves better conservation

outcomes. Nature, 466, 365–367.

Gaston, K.J., Jackson, S.E., Cantu-Salazar, L. & Cruz-Pinon,

G. (2008) The ecological performance of protected areas.

Annual Review of Ecology, Evolution, and Systematics, 39, 93

–113.

Grenyer, R., Orme, C.D.L., Jackson, S.F., Thomas, G.H.,

Davies, R.G., Davies, T.J., Jones, K.E., Olson, V.A., Ridgely,

R.S., Rasmussen, P.C., Ding, T.S., Bennett, P.M., Black-

burn, T.M., Gaston, K.J., Gittleman, J.L. & Owens, I.P.F.

(2006) Global distribution and conservation of rare and

threatened vertebrates. Nature, 444, 93–96.

Harrop, S.R. (2011) Living in harmony with nature? Out-

comes of the 2010 Nagoya conference of the convention

on biological diversity Journal of Environmental Law, 23,

117–128.

Harrop, S.R. & Pritchard, D.J. (2011) A hard instrument

goes soft: the implications of the convention on biological

diversity’s current trajectory. Global Environmental Change,

21, SI474–SI480.

Hermoso, V. & Kennard, M.J. (2012) Uncertainty in coarse

conservation assessments hinders the efficient achievement

of conservation goals. Biological Conservation, 147, 52–59.

Huber, P.R., Greco, S.E. & Thorne, J.H. (2010) Boundaries

make a difference: the effects of spatial and temporal

parameters on conservation planning. Professional Geogra-

pher, 62, 409–425.

Hurlbert, A.H. & Jetz, W. (2007) Species richness, hotspots,

and the scale dependence of range maps in ecology and

conservation. Proceedings of the National Academy of Sci-

ences USA, 104, 13384–13389.

Hurlbert, A.H. & White, E.P. (2005) Disparity between range

map- and survey-based analyses of species richness: patterns,

processes and implications. Ecology Letters, 8, 319–327.

IUCN. (2009) IUCN red list of threatened species. Version

2009.1, Available at: http://www.iucnredlist.org (accessed 5

May 2010).

IUCN, Conservation International, and NatureServe (2006)

Global amphibian assessment. Available at www.globalam-

phibians.org, version 1.1. (accessed 8 May 2008).

IUCN & UNEP. (2010) The World Database on Protected

Areas (WDPA). UNEP-WCMC, Cambridge, UK. www.pro-

tectedplanet.net. (accessed 13 March 2011).

Jantke, K. & Schneider, U.A. (2010) Multiple-species conser-

vation planning for European wetlands with different

Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd 11

National edge artefacts in spatial conservation

degrees of coordination. Biological Conservation, 143, 1812–

1821.

Jenkins, C.N. & Joppa, L. (2009) Expansion of the global ter-

restrial protected area system. Biological Conservation, 142,

2166–2174.

Jetz, W., Sekercioglu, C.H. & Watson, J.E.M. (2007) Ecologi-

cal correlates and conservation implications of overestimat-

ing species geographic ranges. Conservation Biology, 22, 140

–150.

Kark, S., Levin, N., Grantham, H.S. & Possingham, H.P.

(2009) Between-country collaboration and consideration of

costs increase conservation planning efficiency in the Medi-

terranean Basin. Proceedings of the National Academy of Sci-

ences USA, 106, 15368–15373.

Knight, A.T., Cowling, R.M. & Campbell, B.M. (2006) An

operational model for implementing conservation action.

Conservation Biology, 20, 408–419.

Lamoreux, J.F., Morrison, J.C., Ricketts, T.H., Olson, D.M.,

Dinerstein, E., McKnight, M.W. & Shugart, H.H. (2006)

Global tests of biodiversity concordance and the impor-

tance of endemism. Nature, 440, 212–214.

Margules, C.R. & Sarkar, S.. (2007) Systematic conservation

planning. Cambridge University Press, Cambridge, UK.

Marinesque, S., Kaplan, D.M. & Rodwell, L.D. (2012) Global

implementation of marine protected areas: Is the develop-

ing world being left behind? Marine Policy, 36, 727–737.

McDonald, R.I. & Boucher, T.M. (2011) Global development

and the future of the protected area strategy. Biological

Conservation, 144, 383–392.

Moilanen, A. (2007) Landscape Zonation, benefit functions

and target-based planning: Unifying reserve selection stra-

tegies. Biological Conservation, 134, 571–579.

Moilanen, A. & Arponen, A. (2011) Administrative regions

in conservation: balancing local priorities with regional to

global preferences in spatial planning. Biological Conserva-

tion, 144, 1719–1725.

Moilanen, A., Franco, A.M.A., Early, R., Fox, R., Wintle, B.

& Thomas, C.D. (2005) Prioritising multiple–use land-

scapes for conservation: methods for large multi–species

planning problems. Philosophical Transactions of the Royal

Society of London B, 272, 1885–1891.

Moilanen, A., Anderson, B.J., Eigenbrod, F., Heinemeyer, A.,

Roy, D.B., Gillings, S., Armsworth, P.R., Gaston, K.J. &

Thomas, C.D. (2011a) Balancing alternative land uses in

conservation prioritization. Ecological Applications, 21, 1419

–1426.

Moilanen, A., Leathwick, J.R. & Quinn, J.M. (2011b) Spatial

prioritization of conservation management. Conservation

Letters, 4, 383–393.

Naidoo, R., Balmford, A., Costanza, R., Fisher, B., Green, R.

E., Lehner, B., Malcolm, T.R. & Ricketts, T.H. (2006) Glo-

bal mapping of ecosystem services and conservation priori-

ties. Proceedings of the National Academy of Sciences USA,

105, 9495–9500.

Nelson, E., Mendoza, G., Regetz, J., Polasky, S., Tallis, H.,

Cameron, D.R., Chan, K.M.A., Daily, G.C., Goldstein, J.,

Kareiva, P.M., Lonsdorf, E., Naidoo, R., Ricketts, T.H. &

Shaw, M.R. (2009) Modeling multiple ecosystem services,

biodiversity conservation, commodity production, and

tradeoffs at landscape scales. Frontiers in Ecology and the

Environment, 7, 4–11.

Normile, D. (2010) UN biodiversity summit yields welcome

and unexpected progress. Science, 330, 742–743.

Orme, C.D.L., Davies, R.G., Olson, V.A., Thomas, G.H.,

Ding, T.S., Rasmussen, P.C., Ridgely, R.S., Stattersfield, A.

J., Bennett, P.M. & Owens, I.P.F. (2006) Global patterns of

geographic range size in birds. PLoS Biology, 4, e208.

Pajaro, M.G., Mulrennan, M.E. & Vincent, A.C.J. (2010)

Toward an integrated marine protected areas policy: con-

necting the global to the local. Environment Development

and Sustainability, 12, 945–965.

Pressey, R.L. & Bottrill, M.C. (2008) Opportunism, threats,

and the evolution of systematic conservation planning.

Conservation Biology, 22, 1340–1345.

Pressey, R.L., Cabeza, M., Watts, M.E., Cowling, R.M. &

Wilson, K.A. (2007) Conservation planning in a changing

world. Trends in Ecology and Evolution, 22, 583–592.

Ridgely, R.S., Allnutt, T.F., Brooks, T., McNicol, D.K., Mehl-

man, D.W., Young, B.E. & Zook, J.R. (2007) Digital Distri-

bution Maps of the Birds of the Western Hemisphere, version

3.0. NatureServe, Arlington, Virginia, USA.

Rodrigues, A.S.L., Andelman, S. J., Bakarr, M. I., Boitani, L.,

Brooks, T. M., Cowling, R. M., Fishpool, L. D. C., da

Fonseca, G. A. B., Gaston, K. J., Hoffmann, M., Long, J. S.,

Marquet, P. A., Pilgrim, J. D., Pressey, R. L., Schipper, J.,

Sechrest, W., Stuart, S. N., Underhill, L.G., Waller, R. W.,

Watts, M. E. J. & Yan, X. (2004) Effectiveness of the global

protected area network in representing species diversity.

Nature, 428, 640–643.

Rondinini, C., Rodrigues, A.S.L. & Boitani, L.. (2011) The

key elements of a comprehensive global mammal conserva-

tion strategy. Philosophical Transactions of the Royal Society

of London B, 366 (S1) 2591–2597.

Sarkar, S. & Illoldi-Rangel, P. (2010) Systematic conservation

planning: an updated protocol. Natureza & Conservacao, 8,

19–26.

Schuldt, A. & Assmann, T. (2010) Invertebrate diversity and

national responsibility for species conservation across Eur-

ope – a multi-taxon approach. Biological Conservation, 143,

2747–2756.

Soutullo, A. & Gudynas, E. (2006) How effective is the

MERCOSUR’s network of protected areas in representing

South America’s ecoregions? Oryx, 40, 112–116.

Soutullo, A., De Castro, M. & Urios, V. (2008) Linking polit-

ical and scientifically derived targets for global biodiversity

conservation: implications for the expansion of the global

network of protected areas. Diversity and Distributions, 14,

604–613.

Strange, N., Rahbek, C., Jepsen, J.K. & Lund, M.P. (2006)

Using farmland prices to evaluate cost-efficiency of

national versus regional reserve selection in Denmark. Bio-

logical Conservation, 128, 455–466.

12 Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd

A. Moilanen et al.

Tzoulas, K., Korpela, K., Venn, S., Yli-Pelkonen, V., Kazmi-

erczak, A., Niemela, J. & James, P. (2007) Promoting eco-

system and human health in urban areas using Green

Infrastructure: a literature review. Landscape Urban Plan, 8,

167–178.

UNCSD (2012). Available at: http://www.uncsd2012.org/

(accessed 12 June 2012).

UNEP/CBD. (2010) Available at: http://www.cbd.int/doc/

decisions/COP-10/cop-10-dec-02-en.pdf. (accessed 10 May

2011).

Vazquez, L.B., Rodriguez, P. & Arita, H.T. (2008) Conserva-

tion planning in a subdivided world. Biodiversity Conserva-

tion, 17, 1367–1377.

White, C., Costello, C., Kendall, B.E. & Brown, C.J. (2012)

The value of coordinated management of interacting eco-

system services. Ecology Letters, 15, 509–519.

Wilson, K.A., McBride, M.F., Bode, M. & Possingham, H.P.

(2006) Prioritizing global conservation efforts. Nature, 440,

337–340.

Wilson, K.A., Underwood, E.C., Morrison, S.A., Klausmeyer,

K.R., Murdoch, W.W., Reyers, B., Wardell-Johnson, G.,

Marquet, P.A., Rundel, P.W., McBride, M.F., Pressey, R.L.,

Bode, M., Hoekstra, J.M., Andelman, S., Looker, M., Rond-

inini, C., Kareiva, P., Shaw, M.R. & Possingham, H.P.

(2007) Conserving biodiversity efficiently: what to do,

where, and when. PLoS Biology, 5, 1850–1861.

Wilson, K.A., Evans, M.C., Di Marco, M., Green, D.C., Boi-

tani, L., Possingham, H.P., Chiozza, F. & Rondinini, C..

(2011) Prioritizing conservation investments for mammal

species globally. Philosophical Transactions of the Royal

Society of London B, 366 (S1) 2670–2680.

SUPPORTING INFORMATION

Additional Supporting Information may be found in the

online version of this article:

Appendix S1 Separate analyses for major taxa; mammals,

birds, and amphibians.

Figure S1 Conservation prioritization for the western hemi-

sphere based on mammals only, corresponding to the all-

taxa analysis of the main paper (Fig. 1).

Figure S2 Conservation prioritization for the western hemi-

sphere based on birds only, corresponding to the all-taxa

analysis of the main paper (Fig. 1).

Figure S3 Conservation prioritization for the western hemi-

sphere based on amphibians only, corresponding to the all-

taxa analysis of the main paper (Fig. 1).

Figure S4 Mean performance curves for per-taxa analyses of

Figures S1, S2 and S3; for (a) ABF, (b) CAZ.

Table S1 Overlap of the top and bottom 17% of area in the

separate analyses for mammals, birds and amphibians.

As a service to our authors and readers, this journal provides

supporting information supplied by the authors. Such mate-

rials are peer-reviewed and may be re-organized for online

delivery, but are not copy-edited or typeset. Technical sup-

port issues arising from supporting information (other than

missing files) should be addressed to the authors.

BIOSKETCH

Atte Moilanen is a Professor of Conservation Decision Anal-

ysis, working at the Finnish Centre of Excellence in Meta-

population Biology, Dept. Biosciences, University of

Helsinki. His research group is working on biodiversity con-

servation informatics, with a focus on development of con-

cepts, methods, analyses and software, primarily for spatial

conservation planning, but also for conservation resource

allocation in general.

Author contributions: A.M. and C.D.T. conceived the ideas;

B.J.A. and A.A. obtained the data; A.A. and B.J. analysed the

data; F.M.P. contributed to analysis methods and software

development and A.M. and C.D.T. led the writing.

Editor: Rafael Loyola

Diversity and Distributions, 1–13, ª 2012 Blackwell Publishing Ltd 13

National edge artefacts in spatial conservation