problem-solving in conservation biology and wildlife management (gibbs/problem-solving in...

CHAPTER 29

Priority Setting: WhereAround the Globe ShouldWe Invest OurConservation Efforts?

James P. Gibbs

In the global effort to curb losses of biological diversity, many internationalconservation organizations try to set priorities for which regions should receivethe relatively scarce resources available for conservation efforts. Organizations mayset priorities for resource investment at global and regional, as well as local scales.Since it is impossible to measure and monitor all biodiversity even at a local scale,they choose surrogates as criteria for setting priorities. Common criteria includespecies richness (total number of species in an area), number of endemic species, andlevel of threat to species. They generally select species for which there is adequatedata (mostly larger vertebrates) and assume that these surrogates represent otheraspects of an area’s biodiversity.

Areas chosen for global conservation effort generally have unusually large num-bers of species, particularly endemic ones. Conservation International identifiesglobal ‘‘hotspots’’ where species are numerous, often endemic, and under threat.Examples include the Caribbean Islands, the Caucasus Mountains, Madagascar andthe Indian Ocean Islands, New Caledonia, Polynesia-Micronesia and many otherregions (Figure 29.1).

How does one go about the process of identifying countries or regions in termsof relative immediacy of need for resources and assistance? It can be a complexundertaking, but many of the techniques used can be applied at the global, regional,or local level. One attempt was made by Dinerstein and Wikramanayake (1993) whocontrasted biodiversity security with threat to prioritize 23 Indo-Pacific countries(Figure 29.2). More specifically they used estimates of the extent of protected areas(in some sense ‘‘biodiversity security’’) and deforestation (in some sense ‘‘biodiver-sity threat’’) to classify each country into four categories: well protected but withlittle forest outside protected areas (category I), well protected and with extensiveforest remaining outside protected areas (category II), poorly protected but withextensive forest outside protected areas (category III), and poorly protected andwith little forest outside protected areas (category IV, Figure 29.2). Category IVcountries, i.e. those with little protected area and high rates of habitat loss,might qualify as those requiring the most urgent action. Conversely, category I

Gibbs / Problem-Solving in Conservation Biology 9781405152877_4_029 Final Proof page 279 11.10.2007 2:14pm Compositor Name: PAnanthi

Problem-Solving in Conservation Biology and Wildlife Management: Exercises for Class, Field, and LaboratoryJames P. Gibbs, Malcolm L. Hunter, and Eleanor J. Sterling© 2008 James P. Gibbs, Malcolm L. Hunter, Jr., and Eleanor J. Sterling ISBN: 978-1-405-15287-7

Fig.

29.1

Th

irty

-fo

ur

bio

div

ersi

tyh

ots

po

tsid

enti

fied

by

the

con

serv

atio

no

rgan

izat

ion

Co

nse

rvat

ion

Inte

rnat

ion

alan

du

sed

inth

ato

rgan

izat

ion

’sco

nse

rvat

ion

pla

nn

ing

effo

rts.

Sou

rce:

Co

nse

rvat

ion

Inte

rnat

ion

al:

ww

w.b

iod

iver

sity

ho

tsp

ots

.org

.


280

Policy

and

Organ

ization

countries might seem to require the least attention and category II and category IIIcountries were best candidates for moving to category I status as quickly as possible.This analysis could also be expanded to include other considerations, such as theamount of corruption prevalent in a particular country or region, that country orregion’s political stability and its level of economic development. Similarly, theamount of diversity found in each country might also have been evaluated, that is,by considering the number of endemic species present as well as those potentiallyor actually at risk.

Different organizations and individuals will approach this complicated prioritizationproblem differently depending on their objectives and constraints. It is much morethan an academic exercise; these prioritization efforts affect where funding andassistance will flow with tangible effects on people and wild species in differentparts of the world. What would you do if you had to make these decisions?

Objective

. To identify the top priority ‘‘hotspots’’ for allocating resources for conservation.

25

20

15

10

5

00 10 20 30 40

Percent of unprotected forest remaining in 10 years

Per

cent

of

coun

try

prot

ecte

d

50 60 70 80 90

Sri Lanka

Thailand

TaiwanNepal

Pakistan

IndiaVietnam

ChinaPhilippines

BangladeshCambodia

MyanmarLaos Fiji

Papua New GuineaNew Caledonia

VanuaiuSolomon

is

Malaysia

Tonga

Brunei

Bhutan

Indonesia

II I

IIIIV

Fig. 29.2 Approach used by Dinerstein and Wikramanayake (1993) to prioritize conservationefforts among 23 Indo-Pacific countries. Countries were placed into four categories as follows:I. Countries with a relatively large percentage (> 4%) of forests under formal protectionand that will have a high proportion (> 20%) of unprotected forested areas left in 10 years;II. Countries with a relatively large percentage of forest (> 4%) under formal protection,but that will have little (< 20%) unprotected forests left in 10 years; III. Countries with arelatively low percentage (< 4%) of forests presently protected and that under current defor-estation rates these countries will still retain a large proportion (> 20%) of their unprotectedforests in 10 years; IV. Countries with a relatively low proportion (< 4%) of forests presentlyprotected and little forest remaining.

281

Prio

ritySettin

g

Ch

29

Prio

ritySettin

g


Procedures

Hotspot Data

In order to explore one of the global priority setting strategies, current data on 34global biodiversity ‘‘hotspots’’ as identified and compiled by Conservation Inter-national are provided (Table 29.1). The data provide a rich set of information abouteach hotspot and include: its original extent, how much of the original vegetation ofthe hotspot remains, the estimated number of endemic plant and endemic threa-tened bird, mammal, and amphibian species found in the hotspot, the number ofrecorded species extinctions in the hotspot, the human population density thereand estimates of the aggregate area protected as well as the aggregate area in types ofprotected areas categories regarded by the IUCN as being afforded higher levelsof protection (Categories I–IV). (An electronic form of these data is provided for youto download at this book’s website.)

The Problem

Your task is relatively simple – identify the top priority ‘‘hotspots’’ for allocatingresources for conservation. How will you carry out this task? There are many waysto approach this problem and there is no single or correct answer.

You need to devise some form of ranking system; the rationale for the approach youchoose should be outlined and articulated clearly. Start, then, with conceptualizingwhat factors you think are most indicative of impending threats to biological diver-sity in a given ‘‘hotspot.’’ Also consider the intrinsic value of a particular ‘‘hotspot’’ interms of the biodiversity it harbors. What are the critical factors to consider?

Establishing Ranking Criteria

Once you have identified relevant criteria to consider, how will you contrast ‘‘hot-spots’’ in relation to these criteria? You should do this with an objective, data-basedapproach with your rationale clearly articulated. Note that in comparing among‘‘hotspots’’ you may need to synthesize some new variables. Once you have identi-fied your primary variables, how will you analyze the data to derive robust indicatorsthat are also relatively few in number so that they can be communicated easilyto your audience? Dinerstein and Wikramanayake’s (1993) efforts depicted inFigure 29.2 are based on a two-axis, four-category system that is simultaneously auseful analytical and communication device. For starters, you might similarly iden-tify just two primary axes and follow their approach. But if you are feeling ambitiousyou might consider three or more axes along which to array each ‘‘hotspot.’’Remember you will need to defend your approach and show that you used allavailable data to best effect.

Manipulating the Data

One approach to making sense of the large amount of data presented in Table 29.1 isto use criteria matrices to set priorities. Several methods for setting priorities havebeen developed that use various criteria. Most of these systems combine criteria ofrarity/richness and threat. You can design your own system, identifying criteria that

282

Policy

and

Organ

ization


Tab

le29.1

Th

est

atu

san

dat

trib

ute

so

f34

glo

bal

bio

div

ersi

tyh

ots

po

tsas

def

ined

by

the

con

serv

atio

no

rgan

izat

ion

.C

on

serv

atio

nIn

tern

atio

nal

(so

urc

e:w

ww

.bio

div

ersi

tyh

ots

po

ts.o

rg)

Ho

tsp

ot

ori

gin

alex

ten

t(k

m2)

Ho

tsp

ot

vege

tati

on

rem

ain

ing

(km

2)

En

dem

icp

lan

tsp

ecie

s

En

dem

icth

reat

ened

bir

ds

En

dem

icth

reat

ened

mam

mal

s

En

dem

icth

reat

ened

amp

hib

ian

s

Ext

inct

spec

ies

(rec

ord

edsi

nce

1500

)

Hu

man

po

pu

lati

on

den

sity

(peo

ple=km

2)

Are

ap

rote

cted

(km

2)

Are

ap

rote

cted

(km

2)

inC

ateg

ori

esI–

IV

Car

ibb

ean

isla

nd

s229,

549

22,9

556,

550

4818

143

3815

529

,605

16,3

06C

auca

sus

532,

658

143,

818

1,60

00

22

068

42,7

2135

,538

Mad

agas

car

and

the

Ind

ian

Oce

anis

lan

ds

600

,461

60,0

4611

,600

5751

6145

3218

,482

14,6

64

New

Cal

edo

nia

18,

972

5,12

22,

432

73

01

114,

192

497

Po

lyn

esia

–Mic

ron

esia

47,2

3910

,015

3,07

490

81

4359

2,43

62,

088

Cap

eF

lori

stic

Pro

vin

ce78,5

55

15,7

116,

210

01

71

5110

,859

10,1

54E

aste

rnM

elan

esia

nis

lan

ds

99,

384

29,8

153,

000

3320

56

135,

677

0E

aste

rnA

fro

mo

nta

ne

99,

384

29,8

153,

000

3320

56

135,

677

0S

ucc

ule

nt

Kar

oo

102,6

91

29,7

802,

439

01

11

42,

567

1,89

0W

este

rnG

hat

s–S

riL

anka

189,6

11

43,6

113,

049

1014

8720

261

26,1

3021

,259

Mo

un

tain

so

fS

ou

thw

est

Ch

ina

262,

446

20,9

963,

500

23

30

3214

,034

4,27

3N

ewZ

eala

nd

270

,197

59,4

431,

865

633

423

1474

,260

59,7

94M

apu

tala

nd

–Po

nd

ola

nd

–A

lban

y274

,136

67,1

631,

900

02

60

7023

,051

20,3

22

Tu

mb

es-C

ho

co-M

agd

alen

a274

,597

65,9

032,

750

217

84

5134

,338

18,8

14C

oas

tal

fore

sts

of

Eas

tern

Afr

ica

291,2

5029

,125

1,75

02

64

052

50,8

8911

,343

Cal

ifo

rnia

Flo

rist

icP

rovi

nce

293,

804

73,4

512,

124

45

82

121

108,

715

30,0

02P

hil

lip

ines

297,1

7920

,803

6,09

156

4748

227

332

,404

18,0

60W

alla

cea

338

,494

50,7

741,

500

4944

73

8124

,387

19,7

02

(Con

tinu

ed)

Ch

29

Prio

ritySettin

g


Tab

le29.1

(Con

tinu

ed)

So

uth

wes

tA

ust

rali

a356,

717

107,

015

2,94

83

63

25

38,3

7938

,258

Jap

an373

,490

74,6

981,

950

1021

197

336

62,0

2521

,918

Ch

ilea

nw

inte

rra

infa

ll–

Val

div

ian

fore

sts

397

,142

119,

143

1,95

76

515

037

50,7

4544

,388

Mad

rean

pin

e-o

akw

oo

dla

nd

s461,

265

92,2

533,

975

72

361

3227

,361

8,90

0

Gu

inea

nfo

rest

so

fW

est

Afr

ica

620,3

14

93,0

471,

800

3135

490

137

108,

104

18,8

80

Him

alay

a74

1,7

0618

5,42

73,

160

84

40

123

112,

578

77,7

39M

ou

nta

ins

of

Cen

tral

Asi

a863

,362

172,

672

1,50

00

31

042

59,5

6358

,605

Iran

o-A

nat

oli

an89

9,7

7313

4,96

62,

500

03

20

5856

,193

25,7

83M

eso

amer

ica

1,1

30,0

1922

6,00

42,

941

3129

232

772

142,

103

63,9

02S

un

dal

and

1,501,

063

100,

571

15,0

0043

6059

415

317

9,72

377

,408

Tro

pic

alA

nd

es1,

542,

644

385,

661

15,0

0011

014

363

237

246,

871

121,

650

Ho

rno

fA

fric

a1,

659,

363

82,9

682,

750

98

11

2314

5,32

251

,229

Cer

rad

o2,0

31,9

90

438,

910

4,40

010

42

013

111,

051

28,7

36M

edit

erra

nea

nB

asin

2,0

85,2

92

98,0

0911

,700

911

145

111

90,2

4228

,751

Atl

anti

cfo

rest

1,2

33,8

75

99,9

448

5521

141

8750

,370

22,7

82In

do

-Bu

rma

2,3

73,0

57

118,

653

718

2535

113

423

5,75

813

2,28

3


are most important in your view. A matrix approach is most useful when dealing witha large number of criteria to be incorporated when you wish to weight each criterionindividually.

Here is an example of a criteria matrix to set priorities using data for a subset ofjust three of the ‘‘hotspots’’ listed in Table 29.1. Let’s assume that you have decidedthat your primary axes of interest are the degree of ‘‘threat’’ and intrinsic ‘‘import-ance’’ to global biodiversity. For ‘‘threat’’ you decide you are most concerned withthe percentage of the original vegetation remaining that is strictly protected (some-thing you calculate from Hotspot Vegetation Remaining (km2) and Area Protected(km2) in Categories I–IV in Table 29.1) as well as human density (assuming thatincreasing numbers of humans pose a greater threat). You might also assume thesetwo factors are of equal consideration so you apply an equal weight to them (here ¼ 1,but it can be any equivalent values). The actual ratings of each variable times theimportance weight you assigned (r � w) summed together equals the overall score for‘‘threat.’’ A similar process is applied to ‘‘importance.’’ In this case, you have assumedthat endemic plant species richness is of equal importance to that represented by allthreatened endemic vertebrates (birds, mammals and amphibians) so you apply aweight of 1 for plants and 0.333 for each vertebrate group (you could have also applied3 to the plants and 1 to each vertebrate group and gotten the same results). Make surein all cases that your weight is consistent with what you wish it to reflect, e.g., higherweights should indicate greater importance or threat. Summing across the rxw scoresfor each criterion you get an over ‘‘importance’’ score for each ‘‘hotspot’’ relative tothe others ‘‘hotspots.’’ Table 29.2 indicates how this is done for a small subset of sites.

Table 29.2 Sample calculations as an example of a criteria matrix to set prioritiesusing data for a subset of just three ‘‘hotspots’’ listed in Table 29.1; for data that havenot been converted to fractions of the maximum value observed in any hotspot.

Criterionweighting

Caribbeanislands Caucasus

Madagascarand the IndianOcean islands

Criterion Rating w� r Rating w� r Rating w� r

Threat index

% Remaining vegetationstrictly protected1

1.0 71.0 71.0 24.7 24.7 24.4 24.4

Human populationdensity (people=km2)

1.0 155.0 155.0 68.0 68.0 32.0 32.0

Total threat score 226.0 92.7 56.4

Importance index

Endemic plant species 1.0 6 550 6 550.0 1600 1 600.0 11 600 11 600.0Endemic threatened birds 0.3 48 16.0 0 0.0 57 19.0Endemic threatened

mammals0.3 18 6.0 2 0.7 51 17.0

Endemic threatenedamphibians

0.3 143 47.6 2 0.7 61 20.3

Total importance score 6 619.6 1 601.3 11 656

1 calculated from Hotspot vegetation remaining (km2)/Area protected (km2) in CategoriesI–IV�100.

285

Prio

ritySettin

g

Ch

29

Prio

ritySettin

g


As a final recommendation, we suggest dividing the values from Table 29.1 by themaximum value observed in any given hotspot so that data are converted to fractions(0–1) of the maximum. For example, divide endemic threatened birds for all hotspotsby 110 (the maximum value observed [in the Tropical Andes]). This way all param-eters will vary by the same amount and your weights can then function properly.(If you didn’t do this conversion then, for example, the number of plant specieswill overwhelm the other parameters simply because it represents the largest valuesand would influence the sum of the products the most). This approach is portrayedin Table 29.3.

Last, you can plot these scores for the three countries in a bi-variate plot as didDinerstein and Wikramanayake (1993) and you get Figure 29.3.

The final step is to apply your ranking system to all 34 hotspots. You caneventually identify the category IV countries by determining the median value ofall hotspots for each axis and determining which hotspots fall below the medianvalues for each axis you evaluate. This is a convenient way to categorize ‘‘hotspots’’and identify the priority ones with the category systems used by Dinersteinand Wikramanayake (1993). You may well decide on another approach. Anyapproach is fine as long as it is logical, it is well documented, and it stands up toreview by your peers.

Expected Products

. A presentation (in written, verbal, or presentation form as your instructor prefers)of the rationale and associated methods you used for prioritizing the 34 hotspots

. A list and short description of the priority hotspots that you identified andexplanation of why they merit this distinction

. Responses in a form indicated by your instructor to the Discussion questionsbelow.

Discussion

1 What other kinds of data needs might improve the ranking process? Where wouldyou secure them?

2 Were the same hotspots prioritized by all parties working on this problem? If,not, why not? Whose approach is best?

3 Is the ‘‘hotspots’’ approach the ‘‘silver bullet’’ strategy for conserving most speciesfor least cost? Are all taxa equally represented? Can a few well-studied groups ofhigher plants and vertebrate animals serve as surrogates for the many other groupsnot included in these assessments?

4 What do you think should be the priority criteria: where species diversity is greatest,areas faced with imminent destruction, or large intact ecosystems? Or shouldwe not prioritize at all given that nature everywhere benefits from conservation?

5 What is the next step in terms of getting your results integrated into the policyprocess? How actually do international conservation groups implement thesekinds of analyses?

286

Policy

and

Organ

ization


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 0.5 1 2.521.5Threat Index

Impo

rtan

ce I

ndex

CaribbeanIslands

Caucasus

Madagascar and theIndian OceanIslands

Fig. 29.3 Final ‘‘threats’’ and ‘‘importance’’ scores from Table 29.2 for Caribbean islands,Caucasus, and Madagascar and the Indian Ocean islands, portrayed as a bi-variate plot.

Table 29.3 Sample calculations as an example of a criteria matrix to set prioritiesusing data adjusted as proportions for a subset of just three ‘‘hotspots’’ listed inTable 29.1.

Criterionweighting

Caribbeanislands Caucasus

Madagascarand the IndianOcean islands

Criterion Rating w� r Rating w� r Rating w� r

Threat index

% Remaining vegetationstrictly protected1

1.0 1.0 1.0 0.3 0.3 0.3 0.3

Human population density(people=km2)

1.0 1.0 1.0 0.4 0.4 0.2 0.2

Total threat score 2.0 0.8 0.6

Importance index

Endemic plant species 1.0 0.6 0.6 0.1 0.1 1.0 1.0Endemic threatened birds 0.3 0.8 0.3 0.0 0.0 1.0 0.3Endemic threatened

mammals0.3 0.4 0.1 0.0 0.0 1.0 0.3

Endemic threatenedamphibians

0.3 1.0 0.3 0.0 0.0 0.4 0.1

Total importance score 1.3 0.2 1.8

1 calculated from Hotspot vegetation remaining (km2)/Area protected (km2) in CategoriesI–IV�100.

287

Prio

ritySettin

g

Ch

29

Prio

ritySettin

g


Making It Happen

Prioritization of regions at the global scale is done primarily to guide to policy-makers and conservation financiers. This said, the concepts of site prioritizationoutlined here still apply at the local level where an individual can be quite effective.In your region (e.g. county, province, etc.) where do you think conservationresources would best be expended? How would you tackle the problem on a locallevel? On a related note, these approaches to prioritization apply in many contexts inconservation biology, what species to emphasize or what ecological indicators tomonitor, and the approaches outlined here will apply in those contexts as well.

Further Resources

Two good overviews of the ‘‘hotspots’’ concept are Myers et al. (2000) andReid (1998) and one applied to the marine realm (Roberts et al. 2002). A recentelaboration of some of the challenges of identifying biodiversity hotspots formultiple taxa is Oertli et al. (2005). For an overview of Conservation International’sattempt to inventory and classify biodiversity hotspots around the world, see:www.biodiversityhotspots.org.

288

Policy

and

Organ

ization


problem-solving in conservation biology and wildlife management (gibbs/problem-solving in...

Documents