Putting ecosystem services

on the map

Taylor Ricketts

Conservation Science Program, World Wildlife Fund – U.S.

• 25 people• 10 PhDs• 11 Masters

• Plus• Interns• Students• Post-docs

Dual Roles1. Research

2. Advisors to WWF Programs

Conservation Science Program, WWF

Natural processes through which ecosystems sustain and fulfill human life.

Ecosystem Services

• Links nature to human welfare• New motivation, funding for conservation• Poorly understood

Year

1990

1995

2000

2005

Pap

ers

publ

ishe

d

0

50

100

150

200

250

"Ecosystem service*"

Growing attention

Three projects

Number of services

Spa

tial s

cale

Millennium Assessment

12

3

Pollination case study

Pollination meta-analysis

Natural Capital Project

• 2/3 of crops require it

• Honeybee declines

• Can wild bees to do the job?

• Value of their habitats?

coffee

tomatoapple

Crop pollination

What is value of native habitats as sources of pollinators to surrounding crops?

1. Does pollinator activity decline with distance from native habitats?

2. Does this decline influence yields?

Questions

0 1 2 km

S

N

Near

Near

Med.

Med.

Far

Distance # sites

Near (<100m) 4

Mid (0.8 km) 4

Far (1.6 km) 4

Design

• Timed observations

• Diversity, visitation rate

Pollinator activity

near medium far0

1

2

3

4

5

6

7

8

9

10

Distance class

Visitation rate

ANOVA: p < 0.001

a

b

b

Apis mellifera

near medium far0

200

400

600

800

1000

1200

Distance class

ANOVA: p < 0.001

Pollen depositiona

bb

Yield experiments

Two treatments

1. Open(ambient pollination)

2. Hand-pollinated(ensure sufficient

pollination)

Question: are ambient pollination levels sufficient?

Possible results:

Experimental logic

Hand = OpenSufficient

Hand > OpenNot sufficient

Re

sid

ua

l s

ee

d m

as

s (

g)

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

Re

sid

ua

l s

ee

d m

as

s (

g)

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

Hand

Open

Results: seed mass

Distance class

Near Medium Far

Res

idu

al s

eed

mas

s (g

)

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

Hand-pollinated

Open

ANOVADistance: nsTreatment: nsD x T: p=0.004

**

Questions:

1. Does pollinator activity decline with distance from forest?

• YES

• Ricketts, Cons Bio 2004

2. Does this decline influence coffee yields?

• YES

• ~20% decrease beyond 1km

• Ricketts et al., PNAS 2004

near medium far0

1

2

3

4

5

6

7

8

9

10

Distance class

Distance class

Near Medium Far

Res

idu

al s

eed

mas

s (g

)

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

Hand-pollinated

Open

Value of pollination services

n

s

Numbers we need

• Forest effects 1 km

• Yield beyond 1km 17.8 fa*/ha

• Yield within 1km 21.5 fa/ha

• Net income $35/fa

* fanega = 200 liters

1.0 km

(far)

Marginal change in forest

1.0 km

Loss of area near forest: 480 ha

Loss of income: $62,000

1.0 km

Are forests undervalued?

Environmental Service Payments– Carbon sequestration– Hydrological services– Scenic beauty

– Biodiversity $42/ha/year

Pollination service value– $62,000 / 157 ha =

$395/ha/year

Underestimate:

other services, other farms

Three projects

19

Number of services

Spa

tial s

cale

Millennium Assessment

12

Pollination case study

Pollination meta-analysis

How general is coffee result?

23 studies• 18 published, in press• 5 in review, preparation Any general lessons?

16 crops• Almond• Atemoya• Canola (2)• Tomato• Watermelon (3)• Coffee (3)• Eggplant• Field Bean• Grapefruit• Kiwifruit• Longan• Macadamia (2)• Muskmelon• Oil palm• Passion fruit• Sunflower (2) 10 countries

Exponential decay model

Distance

Nat

ive

visi

tati

on

P = α * e(β*D) • α : intercept• β : decay rate

All studies (visitation)

Hierarchical Bayesian modeling

“ Mean β “

Pro

bab

ility

• Estimates probability distribution of

“mean β,“ given all studies

•α estimated separately for each study

• Better fits = more influence

• Stochastic sampling approach (WinBUGS)

• Flat priors

Native visitation rates

• Number of visits / flower / minute

• Both means and certainties vary

Decay rate (β)

Overall mean β

Pro

bab

ility

P = 0.004

Ricketts et al. 2008. Ecol. Letters.

Overall effect of distance

Point of 50% decline:

668m (395-1727m)

Distance (m)

Nat

ive

visi

tati

on

Pollinator richness (19 studies)

Point of 50% decline:

1507m (921-3332m)

• shallower decline

• species present, but lower abundances

Distance (m)

Ric

hn

ess

Overall mean β

Pro

bab

ility

P = 0.002

Fruit or seed set (12 studies)

Point of 50% decline:

26,826m (5038-NA)

• No overall decline detected

• sufficient pollination at low abundances

• crops self-compatible• experiments difficult Distance (m)

Fru

it/s

eed

setOverall mean β

Pro

bab

ility

P = 0.162

How does this help?

Ecology• Search for general patterns in

nature• Landscape effects on pollination

Conservation• Map ecosystem services• Inform landscape planning• Predict effects of land use change

Three projects

Number of services

Spa

tial s

cale

Millennium Assessment

12

3

Pollination case study

Pollination meta-analysis

Natural Capital Project “Landscape level quantification of economic values of entire bundles of ecosystem services under alternative management

regimes” -Carpenter et al. Science. 2006.

Most policy relevance

The Natural Capital Project

– Develop tools to map, value ecosystem services

– Test & apply tools in critical ecoregions

– Support policies to maintain / pay for services

– Change the way ecosystems are viewed

InVEST

31Questions for InVEST

– What places provide the most ecosystem services?

– How would a proposed logging project affect different ecosystem services and biodiversity?

– What landscape pattern would optimize ecosystem services now and under likely scenarios?

– Who should pay whom under a proposed ‘PES’ program, and how much?

Biodiversity

Pollination

Carbon Storage, Sequest.

Timber & NTFP Production

Water quality

Water quantity and timing

Agricultural production

Recreation / Tourism

Cultural and Non-use

InVESTB

uilt

so fa

r

33Tiered Approach

Tier 1 Tier 2

Doable anywhere (?)

Relative scores

Simple Complex

Models

Data(typical)

(typical)

More detail

Absolute estimates

Pollination model

Pollinator source abundance

Fly to pollinate crops

Effect on crop yield

Distribute value to source A

A A

Y

P

Kremen, et al. 2007. Ecology LettersLonsdorf, et al. 2009. Annals of Botany

Testing in Costa Rica

Source abundanceContribution to coffee yieldSource value

Validating model results

y = 67.599Ln(x) + 179.53R2 = 0.842p < 0.001

0

20

40

60

80

100

120

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Ob

serv

ed a

bu

nd

ance

Farm abundance score

y = 518.46Ln(x) + 1787.8R2 = 0.3044

p=0.063

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Ob

serv

ed p

olle

n d

epos

itio

n

Farm Abundance Score

y = 79.366Ln(x) + 381.53R2 = 0.5457

p <0.001

0

50

100

150

200

250

300

350

400

450

0 0.05 0.1 0.15 0.2 0.25 0.3

Ob

serv

ed a

bu

nd

ance

Farm Abundance Score

y = 647.66Ln(x) + 2879.3R2 = 0.6053

p<0.001

0

500

1000

1500

2000

2500

3000

3500

0 0.05 0.1 0.15 0.2 0.25 0.3

Ob

serv

ed p

olle

n d

epos

itio

n

Farm Abundance Score

y = -0.0267Ln(x) - 0.0203R2 = 0.182

p = 0.17

0

0.02

0.04

0.06

0.08

0.1

0.12

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Ove

rall

pol

len

lim

itat

ion

(se

ed m

ass)

Farm Abundance Score

Predicted on-farm abundance

Obs

erve

d on

-far

m a

bund

ance

• Good fits• Simple model• Simple data (experts)

Lonsdorf, et al. 2009. Annals of Botany

Upper Yangtze

EasternArc Mtns

SierraNevada

Four Demonstration Sites

Hawai’i

• test, refine InVEST with field partners and experts• support conservation goals

“Valuing the Arc”

Early results

Water yield~f(rain, ET, topo, soils)

Carbon storage~f(storage/ha, harvest, decay)

Charcoal harvest~f(stock/ha, access, protection)

InVEST interface

http://invest.ecoinformatics.org

Kareiva, et al. (in prep). Theory and Practice of Ecosystem Services. Oxford.

Engaging people

How does this help?

• Locate win-win areas for conservation

• Target payments for services

• Engage those deciding things

• Demonstrate economic importance of nature

• Connect conservation to people

www.naturalcapitalproject.orgwww.valuingthearc.org

Putting ES on the map

Number of services

Spa

tial s

cale

Millennium Assessment

12

3

Pollination case study

Pollination meta-analysis

Natural Capital Project

44

Thanks…NatCap / Valuing the Arc

Andrew BalmfordNeil Burgess

Gretchen DailyBrendan FisherPeter KareivaEric Lonsdorf

Guillermo MendozaShadrack Mwakalila

Robin NaidooErik Nelson

Nasser OlweroSteve Polasky

Jim RegetzMathieu RougetRuth SwetnamHeather Tallis

Buzz ThompsonKerry TurnerSue White

Michael Wright…

SupportNSF-NCEAS

NASALeverhulme Trust

Packard FoundationMacArthur Foundation

Moore FoundationSummit Foundation

Roger and Vicki SantPeter and Helen Bing

…

PollinationPaul EhrlichJaime FlorezGeoff Heal

David InouyeAilene Kane

Claire KremenMaya Hayden

Charles Michener Brad Reed

David RoubikNeal Williams

OTSFinca Santa Fe

The Fallas family…

Three possibilities

• 1. Apis arrival time– Stigmas receptive only a few hours– Arrive later in far sites?

2. Apis behavior– Move less among plants?– Able to fill corbiculae with fewer

visits?

3. Hand-pollination treatments– Damage or “clog” stigmas?– Yields lower than potential?

Near Intermediate Far

Res

idual

fru

it s

et (fr

uit/fl

ow

ers)

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

a

b

bb

c

near medium far bag hand0

500

1000

1500

3000

4000

open manipulated

Pollen manipulations

Decisions

Ecosystems

ServicesValue

Production functions

Daily et al. in press.Frontiers in Ecology & Evolution

Valuation

Incentives & Restrictions

Information

Scenarios & actions

Institutions

Big picture

Policy / Finance• How use information?• PES, gov programs• WRI collaborations?

InVEST