1. Peter Søgaard Jørgensen, Scott P Carroll,
Michael T Kinnison, R Ford Dennison, Bruce
Tabashnik, Carl Bergstrom, Sharon Y Strauss,
Peter D Gluckman, Tom B Smith
Applying evolutionary biology to
address global challenges
@ STOCKHOLM RESILIENCE CENTRE, JUNE 23 2014

2. Personal background
– University of Copenhagen, PhD 2014 (defense June 30)
• Center for Macroecology Evolution and Climate
– University of California – Berkeley (2011/12)
– University of California – Davis (2008/09)
• Macroecology of environmental change response
– Climate change impacts on European and North American
breeding birds
– Validating historical inference from present data
• Applied evolutionary biology
• Integration of disciplines such as ecology and economics
• Co-founder of the International Network of Next-
Generation Ecologists

3. Outline
• Applied Evolutionary Biology?
• Global Evolutionary Challenges
• Applied evolutionary biology to address global
challenges

4. History of a field
• DARWIN AND APPLIED EVOLUTION (1859)
• MEDICINE (1970’s,1994)
• UNWANTED ANTHROPOGENIC EVOLUTION (2001)
• AGRICULTURE (2003)
• ENVIRONMENT (2008)

5. NEW ENEMIES
• Antibiotic resistance
• Drug resistance
• Pesticide resistance
NEW TOOLS
• Genetic engineering
• Genomics

7. THE GREAT ACCELERATION
Steffen et al.
2011 AMBIO

8. Economic costs of inadvertent
evolution
Palumbi 2001

9. Palumbi Science 2001, Cooper and Shlaes Nature 2011

10. Post antibiotics era in 87 days…?
Nature 472, 32 (07 April 2011)
Cooper and Shlaes Nature 2011

11. What’s missing
• Dichotomy of applied evolution
– Only rapidly evolving species
• Lack of framework for manipulations,
solutions?
– Narrow solution-oriented focus
– Naïve solution context
– Ignoring interdependencies linkages between
economic sectors
– Socio-economic factors?

12. Bringing a multidisciplinary team together
to build on Palumbi’s landmark
• Heron Island Summit 2010 (vid.)

13. Outline of Palumbi +10 years
1. Global challenges
2. The conundrum of applied evolutionary biology
3. Fundamental manipulations
4. Four main-strategies of applied evolutionary biology
5. From implementation to prospects
6. Addressing evolution across management sectors
7. Implementing solutions (through the eyes of Ostrom)
8. Post 2015 agenda

14. Global challenges
Contemporary evolution in unwanted species
• Antibiotic (drug) resistance
– Greatest medicinal challenge
• Pesticide resistance
– 11000 cases, 1000 species of insects
Phenotype-environment mismatch in valued species
• Chronic human life-style disease
– Such as “type 2” diabetes, estimated ~1% global GDP
• Human caused biodiversity decline
– Earth sixth mass extinction

15. log(generation time)
log(populationsize)
Conservation
Biology:
CONTEMPORARY
EVOLUTION
Crops
Livestock
Medicine:
Human
epithelia
Medicine:
Human
bone marrow
All:
Viral &
microbial
pathogens,
mutualists,
commensal
s
Agriculture &
Natural resources:
Multicellular
pests,
weeds,
invasive
species
Medicine:
Human
neurons
Medicine:
Human
fat cells
Annual
organisms
Trees
All:
Pollinators
Medicine:
Humans
PHENOTYPE-
ENVIRONMENT
MISMATCH
1) The conundrum of applied
evolutionary biology

16. RECOGNIZING MISMATCH AND
CONTEMPORARY EVOLUTION
• ENVIRONMENT

17. RECOGNIZING MISMATCH AND
CONTEMPORARY EVOLUTION
• HEALTH

18. RECOGNIZING MISMATCH AND
CONTEMPORARY EVOLUTION
• FOOD

19. Genotype Manipulation Developmental Manipulation
Phenotype
Distribution
Genotype
Distribution
Optimum
Phenotype
Range
a)
b) c) d)
Manipulation
of Mismatch
Frequency
Trait Value
Mismatch
Environment Manipulation
2) Three fundamental manipulations

20. 3) Four main-strategies of applied
evolutionary biology
Control pests, pathogens, invading species by…
• …slowing unwanted evolution
• …reducing adversary fitness
Protect desirable populations by…
• …reducing phenotype environment mismatch
• …increasing group performance

21. Control pests, pathogens, invading
species by…
FOOD HEALTH ENVIRONMENT

22. Protect desirable populations by…
FOOD HEALTH ENVIRONMENT

23. 5) From implementation to prospects
• Environmental alignment to protect
valued species
• Genomic manipulation to improve
valued species
• Slowing unwanted evolution w/
environmental heterogeneity
• Choosing population sources for
translocation and restoration
• Managing group vs. individual fitness
for desired outcomes
Implementation stage
Experimental stage

24. Environmental alignment to secure
biodiversity and human health
• In conservation biology and environmental
management [Widely implemented]
– Management of wild populations
– Management of captive populations
• In treatment of human life-style disease [Increasing
attention]
– Palaeo diet
– Genomics
– Phenotypic data
– Exposome
Environment Manipulation

25. Altering genomes for improved food
security and human health
• Artificial selection, genetic engineering [Widely
implemented]
– Old art of artificial selection
– Genetically engineered crops
– Using genetic markers to guide artificial selection
– Selection and engineering for drought/flood tolerance
• Gene therapy and genomic replacement in humans
[Increasing attention]
– Gene therapy – failing to make it into market
– Frontiers!? Mt genome replacement and ???
Genotype Manipulation

26. Using environmental heterogeneity to
delay resistance evolution
• The refuge strategy in agricultural biocontrol
efforts
• Transfer to marine biodiversity, fisheries,
cancer treatment
Gatenby Nature 2009

27. Choosing population sources to
anticipate climate change
• Moving biodiversity prevent future
extinctions?
• Review of assisted migration in agriculture,
and forestry?

28. Exploiting group versus individual
performance in crops and livestock
• Selecting for cooperative traits
– [so far a mainly a prospect]

29. 6) Addressing evolution across
management sectors

30. Interconnected problems
• Emerging diseases
– Antibiotic resistance
– Flu outbreaks
– Wildlife zoonoses
• Agriculture
– Pesticides as selective agents in humans and
environment
– Gene flow / hybridzation with wild species
– Conservation of wild crop relatives to maintain
evolutionary potential
– Land use conflicts on a crowded planet

32. 7) Implementing solutions in
socio-ecological systems
Ostrom Science 2009

33. Tragedy of commons?
PRONE TO SELF-ORGANIZATION
• Small-scale
• Few users
• Distinguishable units
• Medium productivity
• Highly predictable
• Low mobility
• Small number stakeholders
• High reliance
• Norms
• Leadership
• Knowledge
LESS PRONE TO
SELF-ORGANIZATION
• Large-scale
• Many users
• Non-visible differences
• High-low productivity
• Low predictability
• Medium-High mobility
• Large number of stakeholders
• High-medium reliance
• Norms?
• Leadership?
• Knowledge?
REFLECTS MANY CHALLENGES OF APPLIED
EVOLUTIONARY BIOLOGY AND CALLS FOR COMBINED
TOP-DOWN AND BOTTOM-UP IMPLEMENTATION
Ostrom Science 2009

34. 8) Applied Evolution &
Millennium Development Goals
Strong evolutionary component
•Eradicating extreme poverty and hunger
•Reducing child mortality rates
•Improving maternal health
•Combatting HIV/AIDS, malaria, and other diseases
•Ensuring environmental sustainability

35. POST 2015 AGENDA?
(before proposal of 17 SDGs)
Griggs et al. 2013

36. POST 2015 AGENDA
Griggs et al. 2013

37. Applied Evolutionary Biology &
the Post 2015 agenda?
• Goal 1: Thriving lives and livelihoods
• Goal 2: Sustainable food security
• Goal 3: Secure sustainable water
• Goal 4: Universal clean energy
• Goal 5: Healthy and productive ecosystems
• Goal 6: Governance for sustainable societies

38. Goal 1: Thriving lives and livelihoods
• Reduce chronic lifestyle disease through environmental
alignment of human lifestyle.
• Reduce environmental levels of human toxicants
through application of reduced selection response
techniques* to pesticides/biocides.
• Apply reduced selection response techniques to
maintain long-term efficacy of antimicrobials and avert
the antibiotics crisis.
• Reconcile individual and group incentives in health
systems to reduce virulence and resistance of emerging
and re-emerging pathogens.

39. Goal 2: Sustainable food security
• Increase crop yield through continued selection of
varieties and improved access to these.
• Prolong efficacy of pesticides and artificially
selected or GE crops through reduced selection
response techniques.
• Improve yields through integration of group
selection in production of novel crop varieties.
• Reduce climate change impact by choosing crop
varieties resilient to drought, flooding and other
extremes.

40. Goal 3: Secure sustainable water
• Increase water security through use of
reduced selection response techniques to
water polluting pesticides/biocides
• Use genetic manipulation to produce crop
varieties with improved water economy.

41. Goal 4: Universal clean energy
• Improve biofuels through genetic
manipulation with the aim to reduce CO2
emissions and land area for energy
production.
• Assess risks and benefits of synthetic
organisms for biofuel production taking taking
gene flow, land use and property rights issues
into account.

42. Goal 5: Healthy and productive
ecosystems
• Reduce biodiversity extinction rates through
environmental alignment and genetic
manipulation of fitness.
• Retain naturalness of captive biodiversity through
environmental alignment.
• Choose pre-adapted or high diversity sources for
increased habitat restoration success.
• Avoid collapse and protect genetic diversity of
aquatic resources through non-selective
harvesting strategies informed by early warning
signals.

43. Goal 6: Governance for sustainable
societies
• Incorporate externalities from rapid evolution
as well as the loss of evolutionary history and
potential into green accounting for sustainable
governance of the earth system.
• Coordinate strategies of SDG’s in a coupled
systems framework to reduce conflicts from
inadvertent contemporary evolution and
phenotype-environment mismatch.

44. Thank you!