EcoMathsThe Numbers of Life (and Death)

Professor Corey J. A. BradshawTHE ENVIRONMENT INSTITUTE, University of Adelaide

South Australian Research & Development Institute

•> 4 million protists

•16600 protozoa

•75000-300000 helminth parasites

•1.5 million fungi

•320000 plants

•4-6 million arthropods

•> 6500 amphibians

•> 30000 fishes

•10000 birds

•> 5000 mammals

99 % of ALL species that have ever existed...

EXTINCTspecies lifespan = 1-10 M years

Ordovician (490-443 MYA)

Devonian (417-354 MYA)

Permian (299-250 MYA)

Triassic (251-200 MYA)

Cretaceous (146-64 MYA)

Anthropoceneextinction rate 100-10000× background

Crutzen 2002 Nature 415:23; Bradshaw & Brook 2009 J Cosmol 2:221-229© T

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•1,011,000 km2 lost 2000-2005 (3.1 %; 0.6 %/year)•highest in boreal biome (60 %)•humid tropics next (Brazil, Indonesia, Malaysia)•dry tropics next highest (Australia, Brazil,

Argentina)•N.A. greatest proportional lost by continent•Nationally, Brazil, Canada, Indonesia, DR Congo

•21 % of all known mammals•30 % of all known

amphibians•12 % of all known birds•35 % of conifers & cycads•17 % of sharks•27 % of reef-building corals

threatened with extinction

IUCN RED LIST OF THREATENED SPECIES www.iucnredlist.org

•3366 spp

•life history (reproduction, fecundity, body size, habit)

•ecological (range size)

•environment (temperature, precipitation, human density)

• threat ~ X1 + X2 + X3… (Order/Family)

•decline ~ …

Correlates of extinction

Sodhi et al. 2008 PLoS One 3:e1636

Sodhi et al. 2008 PLoS One 3:e1636

Sodhi et al. 2008 PLoS One 3:e1636

range (number of FAO Fishing Areas),

• risk for sharks with small range size

•similar for teleosts with slightly larger ranges

habitat • threat risk for reef sharks• and for pelagic teleosts

environmental temperature regime

• risk for deepwater sharks• risk deepwater teleosts

Field et al. 2009 Advances in Marine Biology 56:275-363

Bradshaw et al. 2008 J Ecol 96:869-883

Bradshaw et al. 2008J Ecol 96:869-883

deforestation, soil erosion, sediment & nutrient loading

destructive fishing practices

overfishing

invasive species and starfish outbreaks

bleaching

Mellin et al. 2010 Glob Ecol Biogeog 19:212

3.0 ± 0.42.2 ± 0.4

1.5 ± 0.3

Reef area Reef isolation

3.1 ± 0.42.0 ± 0.31.7 ± 0.3

Mellin et al. In press Ecology

Mellin et al. In press Ecology

1. habitat destruction

2. over-exploitation

3. introduced species

4. extinction cascades

Diamond 1984 Extinctions Chicago University Press

Evil quartet

Broo

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-460

1. habitat destruction

2. over-exploitation

3. introduced species

4. extinction cascades

5. climate change

Evil quintet

6. synergies

Evil sextet

Brook et al. 2008 Trends Ecol Evol 25:453-460

© Millennium Ecosystem Assessment

justification to maintain healthy ecosystems is intangible because it seems unrelated to personal well-being

• reduce desertification• maintain soils• crop pollination• seed dispersal• food provision• water purification• fuel provision• fibre provision• climate regulation• flood regulation• disease regulation• waste decomposition/detoxification• nutrient cycling• soil formation• primary production• pharmaceutical sources• cultural appreciation (aesthetic, spiritual, educational, recreational…)

• €50 billion lost/year• land-based ecosystem loss €545 billion by 2010

• > €14 trillion/year lost by 2050

Cost of Policy Inaction (COPI):The case of not meeting the 2010 biodiversity target.

European Commission

€153 billion/year

fisheries: €50 billion/year

Bradshaw et al. 2007 Glob Change Biol 13:2379-2395

1990-2000• ~100,000 people killed• 320 million people displaced• total reported damages > US$1151 billion

•decades of warning

•human population 6.8 B; 9-10 B by 2050

•competition for resources – famine, wars

•loss of basic ecosystem services

•fundamental worldwide shifts in policy required

•identifying relative country degradation

–highlight nations needing assistance

–better-performing nations as model governance structures

City Development Index www.unchs.org

Ecological Footprint www.footprintnetwork.org

Environmental Performance Index epi.yale.edu

Environmental Sustainability Index sedac.ciesin.columbia.edu

Genuine Savings Index worldbank.org

Human Development Index hdr.undp.org

Living Planet Index www.panda.org

Well-Being Index www.well-beingindex.com

Environmental Impact Rank

Böhringer & Joachim 2007 Ecol Econ 63:1-8

•inability to describe complexity of ‘sustainability’

•not comprehensive

•mix environmental, economic and health data

•often subjective combinations, weightings, normalisation

•not available for large sample of nations

•not consistent

•natural forest loss2005-1990 D/ha

•natural habitat conversionhuman-modified landcover/total landcover

•marine captures1990-2005 fish, whales, seals/EEZ km

•fertiliser useNPK/ha arable land

•water pollutionbiochemical oxygen demand/total renewable water resources

•carbon emissionsforestry, land-use change, fossil fuels/km2

•biodiversity threatRed List threatened birds, mammals, amphibians/listed species

Bradshaw et al. 2010 PLoS One 5:e10440

NFL NHC MC FU WP BT CE RANK

128 5 91 1 4 63 1 10.6

23 61 20 17 21 29 5 20.4

- 198 112 20 3 - 7 24.8

128 197 114 11 1 - 8 25.1

87 87 18 21 29 13 6 25.2

128 5 91 1 4 63 1 10.6

Bradshaw et al. 2010 PLoS One 5:e10440

1 Singapore 179 Cape Verde

2 Rep Korea 178 Cent Afr Rep

3 Qatar 177 Swaziland

4 Kuwait 176 Antig & Barb5 Japan 175 Niger6 Thailand 174 Grenada7 Bahrain 173 Samoa8 Malaysia 172 Tonga9 Philippines 171 Djibouti

10 Netherlands 170 Tajikistan11 Denmark 169 Bhutan12 Sri Lanka 168 Chad13 Indonesia 167 Vanuatu14 Israel 166 Mali15 Bangladesh 165 Kazakhstan16 Malta 164 Gabon17 China 163 Turkmenistan18 New Zealand 162 Lesotho19 Iceland 161 Suriname20 Honduras 160 Eritrea

“I anticipate that the anti-science crowd will be screeching and howling with indignation when they read this one.”

“This is such BS, China is WAY worse then the U.S.”

“This researcher is a waste ...”

“This article is crap.”

“Can we really depend on some study when the Chinese could have funded this or maybe some group who was angry at the US and Brazil for whatever? I highly doubt the accuracy of the findings. Looks like the Treehuggers are at it again.”

“Shame on you Australia !!! I guess your dying great Barrior [sic] reef is America's fault too!!!!”

“here we go again. I'm so frickin' sick of these watermelons (green on the outside, red (communist) on the inside) treehuggers. The only f*^king green I care about is made of paper and folds.”

1 Brazil

2 USA

3 China

4 Indonesia

5 Japan6 Mexico

7 India8 Russia9 Australia

10 Peru

11 Argentina12 Canada13 Malaysia14 Myanmar15 Ukraine

16 Thailand17 Philippines

18 France19 South Africa

20 Colombia

POPULATION

WEALTH

GOVERNANCE

+

impa

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0 50 100 150 200

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Governance quality rank

Pro

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Gross National Income rank

Ab

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Total population rank

Pro

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0 50 100 150 200

0

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Population density rank

0 50 100 150 200

0

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Population growth rank

Pro

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Gross National Income rank

A B

C D

- im

pact

+ im

pact

+ people - people

+ growth - growth

- im

pact

poorer wealthier

- quality + quality poorer wealthier

+ density - density

- im

pact

+ im

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E F

Bradshaw et al. 2010 PLoS One 5:e10440

Bradshaw et al. 2010 PLoS One 5:e10440

per capita prosperity

envi

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ENVIRONMENTAL

KUZNETS CURVE

Bradshaw et al. 2010 PLoS One 5:e10440

1 10 100

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intercept

per capita PPP-adjusted GNI

Pro

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1 10 100

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per capita PPP-adjusted GNI

Ab

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- im

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+ im

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- im

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+ im

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poorer wealthier

poorer wealthier

A

B

Bradshaw et al. 2010 PLoS One 5:e10440

© http://tropicaltoxic.blogspot.com

Does a sick environment make sick people?

•physician-assessed morbidity declines with more green spaces near Dutch patients

Maas et al. 2009 J Epidemiol Comm Health 63:967-973

•dioxin-poisoning accident in Milan – increased circulatory disease, lymphoma, pulmonary disease & diabetes 25 years later

Consonni et al. 2008 Am J Epidemiol 167:847-858

•low water quality, poor sanitation & indoor air pollution from household solid fuels increased child mortality and reduced life expectancy in Mexico

Stevens et al. 2009 Proc Natl Acad Sci USA 105:16860-16865

•malaria-vector mosquito bite rates 278× higher in deforested sites in Amazon

Vittor et al. 2006 Am J Trop Med Hyg 74:3-11

•Anopheline mosquito density after deforestation in 60% of 60 studies over past century; 70 % of cases incidence of malaria

Yasuoka & Levins 2007 Am J Trop Med Hyg 76:450-460

Human health: World Health Organization Global Burden of Disease database

Environment: - Environmental Combination Index (adapted from Yale Env Performance Index)

- Proportional Environmental Impact rank (Bradshaw et al. 2010 PLoS One 5:e10440)- natural habitat conversion proportion (Global Land Cover 2000 dataset)- air/water quality (Yale Environmental Performance Index)- NPK fertiliser use/area arable land (FAOSTAT database)- CO2 emissions (Climate Analysis Indicators tool)

Control: - human population size (United Nations Common Database)

- purchasing-power parity-adjusted GNI (World Resources Institute)- health expenditure (WHO Statistical Information System)

DATA

Human health: WHO Global Burden of Disease database

• Disability-Adjusted Life Years (DALY) - years of life lost due to premature mortality and healthy years of life lost due to disability

• Infant Mortality (male) – 2004 mortality per 1000 live births

• Life Expectancy at birth (male) – 2004

• Diarrhoea deaths among children < 5 years (2000)

• Malaria deaths among children < 5 years (2000)

• Deaths due to Cardiovascular Disease (2002 age-standardised per 10,000)

• Deaths due to Cancers (2002 age-standardised per 10,000)

DATA

http://epi.yale.edu

10 % ECI mINFM 7.0/1000 live births mLE 1.9 years

• extinction must be inferred from record of sightings/collections

• when a species becomes increasingly rare before extinction, might persist unseen for many years

• so the time of last sighting often poor estimate of extinction date

Roberts & Solow 2003 Nature 426:245

present pastx x x xx x x?? xx x x

• optimal linear estimation• joint distribution of k same Weibull form regardless

of parent distribution• estimated extinction time q

• L: symmetric k×k matrix

• n: Estimated shape parameter of joint Weibull distribution of k

Roberts & Solow 2003 Nature 426:245

present pastx x x xx x x

qxx x x

kTTTT ...321

k

iiiTa

1

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ij

ji

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2

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k

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TT

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11000 12000 13000 14000

YBP

• maximum likelihood to account for radio carbon dating error

• assume true ages U independent/uniformly distributed over (b1,g1) where b1 = extinction date

• PDF of Xj:

Solow et al. 2006 PNAS 103:7351

present pastx x x xx x x

b1 xx x x

jjj UX

11

11

)(

jj

j

xx

xf

11000 12000 13000 14000

YBP

• but... previous sighting rate important• length of period since last sighting informative• given previous sighting rate(n/tn), probability of next

sighting

• where p drops below threshold with increasing T-tn, TE inferred

McInerny et al. 2006 Conserv Biol 20:562

present pastx x x xx x x

TE xx x x

ntT

nt

np

1

5 10 15 20 25 30

10900

11000

11100

11200

11300

11400

11500

samples

Te

• but... TE depends on number of samples in ‘final’ period• declining influence of dates within time since last sighting• sequentially recalculated TE, weighting by cumulative distance

from T1

present pastx x x xx x x

TE xx x xT1

10000 15000 20000 25000 30000 35000 40000

YBP

IS1 IS2 IS3 IS4 IS5 IS6 IS7 IS8 IS9 IS10

Mammoth Equus S.Horse

Bison

C.BearSF.Bear

Neand

extinctions - constrained

P(rand overlap) = 0.09

© Moronail.net

© WWF

corey.bradshaw@adelaide.edu.au

www.adelaide.edu.au/directory/corey.bradshaw

ConservationBytes.com

• Barry Brook University of Adelaide• Alan Cooper University of Adelaide• Camille Mellin University of Adelaide/AIMS• Mark Meekan AIMS• Iain Field Macquarie University• Xingli Giam Princeton University• Navjot S. Sodhi National University of Singapore• Tony McMichael Australian National University

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