How to keep up with the literature? How to stop the loss of biodiversity? How to study/predict/manageglobal change effects on agrodiversity? How to achieve interdisciplinarity? How to involve stakeholders? How to learn from network theory? What can we learn from biogeography?

1. Outstanding challenges
in the study of
seed exchange networks in
agrobiodiversity conservation
Marco Pautasso
marpauta at gmail.com
CEFE, CNRS, 14 May 2012

2. Seed exchange networks: defining the terms
Intra-European Trade
Organic seed of Ornamental Plants (2003)

3. The talk is partly based on this review of the literature

4. Challenge nr 1: how to keep up with the literature?
A selection of
recent reviews
on agro-
biodiversity
conservation
and/or seed
exchange
networks
from Pautasso
et al. (2012)
Agr Sust Dev

5. NETSEED-CESAB
Agrobiodiversité et réseaux sociaux
Une approche interdisciplinaire pour analyser
comment les systèmes semenciers locaux
agissent sur la diversité des plantes
domestiquées
NETSEED
FRB-CESAB

6. Challenge nr 2: how to stop the loss of biodiversity?
aggregated indicators of
A) species’ population trends, habitat extent and
condition, and community composition
B) ecological footprint, nitrogen deposition,
alien species, overexploitation and climatic impacts
C) protected area extent and biodiversity coverage,
responses to invasive alien species, sustainable
forest management and biodiversity-related aid
6000
5000 Web of Science papers
number of papers
4000
on biodiversity
3000
2000
1000
0
Butchart et al. (2010) Science 1990 1995 2000 2005 2010

7. CESAB (Centre
for Synthesis
and Analysis of
Biodiversity data)
Technopole de
l’Arbois (~ Aix
en Provence)
3rd Call for CESAB Working Groups
(deadline pre-registration 25 May 2012,
deadline for submission end of June 2012)

8. Average time spent travelling in the UK (1930s-1990s)
Schulz (2004)
Population &
Environment

9. [CO2]
from MacKay (2008) Sustainable Energy – without the Hot Air

10. Average temperature α [CO2] (a reminder)
Shakun
et al
(2012)
Nature

11. Carbon emissions of conservation biologists
Fox et al. (2009) Frontiers in the Ecology and the Environment

12. Sustainable transport of seed
(sorghum?) in Kathwana market, Kenya
Picture: Christian Leclerc
(CIRAD, Montpellier)

13. Seed potato sources
in Kenya, Uganda and Ethiopia
Gildemacher et al. (2009) A description of seed potato systems in
Kenya, Uganda and Ethiopia. American Journal of Potato Research

14. Maize seed sources in Mexico
Bellon et al. (2011) Assessing the vulnerability of traditional maize seed
systems in Mexico to climate change. PNAS

15. Challenge nr 3. How to study/predict/manage
global change effects on agrodiversity?
Pautasso et al. (2012) Agronomy for Sustainable Development

16. Challenge nr 4. How to achieve interdisciplinarity?
Kiss et al. (2010) Can epidemic models describe
the diffusion of topics across disciplines? Journal of Informetrics

17. Hypothetical network of interdisciplinary collaborations
among scientists interested in seed exchange networks
Pautasso et al. (2012) Agronomy for Sustainable Development

18. Challenge nr 5. Involving stakeholders
Pautasso et al. (2012) European Journal of Plant Pathology

19. Network analysis of barley seed flows in Ethiopia
Abay et al. (2011)
Plant Genetic Resources – Characterization and Utilization

20. Network analysis of barley seed flows in Ethiopia
N nodes = 186, N links = 210 data from: Abay et al. (2011)
node ID links in links out
218 1 0
314 0 1
135 2 1
120 1 1
…
100 6
number of incoming links
incoming
number of nodes
80 5
links
4
60 outgoing
links 3
40 2
20 1
0
0
0 2 4 6 8
1 2 3 4 5 6
number of links number of outgoing links

21. Network structure and correlation between links in and out
one-way
random
uncorrelated
local
scale-free
two-ways
small-world
modified from:
Keeling & Eames (2005) Interface

22. Some recent applications of network theory
Network pictures from: NATURAL
Newman (2003)
SIAM Review food webs
cell
metabolism
neural Food web of Little Rock
networks Lake, Wisconsin, US
ant nests sexual
partnerships
DISEASE
SPREAD
family
innovation networks
Internet flows co-authorship HIV
structure railway urban road nets spread
electrical networks networks network
power grids telephone calls
WWW
computing airport Internet E-mail
committees
grids networks software maps patterns
TECHNOLOGICAL SOCIAL
Moslonka-Lefebvre et al. (2011) Phytopathology

23. Challenge nr 6. How to learn from network theory?
Network Seed exchange
epidemiology networks
Elements moving
thanks to a network pathogens/ seeds, varieties/
of contacts human beings farmers
through aware
Diffusion happens inadvertently
decisions
Main aim of minimizing preserving
applied research disease spread agrobiodiversity
Picture from
Kaluza et al. (2010)
Interface

24. Simple model of spread and establishment in a network
SIS deterministic model, 100 Nodes, fixed structure, absence/presence continuum
P [i (x, t)] = Σ { pp * P [i (x, t-1)] + pt * P [i (y, t-1)]}
node 1 2 3 4 5 6 7 8 … 100
step 1
pp probability of pt probability of
persistence transmission
step 2
step 3
…
step n
Moslonka-Lefebvre et al. (2011) Phytopathology

25. Lower invasion threshold for scale-free networks with
positive correlation between in- and out-degree
1.00
local
probability of persistence
random
0.75 small-world
INVASION
scale-free (two-way)
scale-free (uncorrelated)
0.50 scale-free (one way)
0.25
0.00
0.00 0.25 0.50 0.75 1.00
NO INVASION probability of transmission
from: Moslonka-Lefebvre et al. (2011) Phytopathology

26. Lower epidemic threshold for two-way scale-free networks
(unless networks are sparsely connected)
N replicates = 100;
error bars are St. Dev.;
different letters show
sign. different means
at p < 0.05
from: Moslonka-Lefebvre et al. (2009) Journal of Theoretical Biology

27. 100 100
75
(local) 75
(sw)
(N of nodes with invasion status > 0.01) 50 50
25 25
0 0
0 25 50 75 100 0 25 50 75 100
final size of invasion
100 100
(rand)
75 75
(sf2)
50 50
25 25
0 0
0 25 50 75 100 0 25 50 75 100
100 100
75
(sf0) 75 (sf1)
50 50
25 25
0 0
0 25 50 75 100 0 25 50 75 100
starting node of the invasion

28. 2.0 3.0
1.5
local 2.5 sw
across all nodes (+0.01 for sf networks) 2.0
sum at equilibrium of invasion status
1.0 1.5
1.0
0.5
0.5
0.0 0.0
0 1 2 3 4 5 6 0 2 4 6 8
3.0 1.0
2.5 rand sf2 (log-log)
2.0
1.5 0.0
1.0
0.5
0.0 -1.0
-1 0 1 2 3
0 2 4 6 8 10 12
2.0
2.0
1.5 sf0 (log-log) 1.5
sf1 (log-log)
1.0 1.0
0.5 0.5
0.0 0.0
-0.5 -0.5
-1.0 -1.0
0.0 0.5 1.0 1.5 2.0 0.0 0.2 0.4 0.6 0.8 1.0
n of links from starting node n of links from starting node

29. Correlation of invasion final size with out-degree of
starting node increases with network connectivity
from: Pautasso
et al. (2010)
Ecological N replicates = 100; error bars are St. Dev.;
Complexity different letters show sign. different means at p < 0.05

30. Network analysis of barley seed flows in Ethiopia
100
10 100
12
80
Buket 10
80
8 Bolenta
Mugulat Buket
Aynalem Bolenta
Mugulat
Melfa
number of nodes
number of nodes
number of nodes
Habes 8 Aynalem
Melfa
number of nodes
Adinefas
60
6 Adinefas
Habes
60 Habes
Adinefas
Melfa Adinefas
Habes
Aynalem
6 Melfa
Aynalem
Mugulat
Bolenta
40
4 Buket
bridges 40 Mugulat
Bolenta
Buket
bridges
4
20 20
2 2
0
0 00
1 2 3 4 5 6 1 2 3 4 5 6
1 number of outgoing5links6
2 3 4 1 number of incoming links6
2 3 4 5
number of incoming links
number of outgoing links
data from: Abay et al. (2011)

31. Network analysis of barley seed flows in Ethiopia
4 6 4 4
n = 11, y = -0.25x + 1.91 n = 14 n = 16
n = 11, y = 0.32x + 1.48
2
R = 0.29, p = 0.09 5 2
R = 0.32, p = 0.07
3 3 3
4
2 3 2 2
2
number of incoming links
1 1 1
1
0 0
0 0
0 1 2 3 4
0 2 4 6 8 0 2 4 6 0 1 2 3 4 5
3 4 4 4
n = 92, y = -0.37x + 0.80 n=9 n = 19 n = 14, y = 0.32x + 1.33
2 2
R = 0.20, p < 0.01 R = 0.21, p = 0.10
3 3 3
2
2 2 2
1
1 1 1
0
0 0 0
0 1 2 3 4 0 1 2 3 4
0 1 2 3 4 0 2 4 6
number of outgoing links data from: Abay et al. (2011)

32. What is an organization?
Butts (2009) Revisiting the foundations of network analysis. Science

33. Network metrics as a function of sampling intensity
Dormann et
al. (2009) The
Open
Ecology
Journal

34. Network analysis of barley seed flows in Ethiopia
Abay et al. (2011)
Plant Genetic Resources – Characterization and Utilization

35. Orbis terrarum, Marcus Vipsanius Agrippa, ~27 a.C.
from http://www.arqweb.com/vitrum/orbis22.asp

36. from Jeger et al. 2011

37. Living collections of the world’s botanical gardens
(c)
(a) (c)
log10 spp richness (n)
(d) (yr)
(b) Size of countries reflects n of botanic gardens
(d)
b from: http://www.worldmapper.org/
a, c & d: from: Pautasso & Parmentier (2007) Botanica Helvetica

38. Botanic vs. linguistic diversity
Burnside et al. (2011) Biological Reviews

39. Species-people correlation in Europe
plants birds
from Araujo (2003) spp
Global Ecology &
Biogeography people

40. Invasion biogeography of Sudden Oak Death
Trace forward/back zipcode
Positive (Phytophthora ramorum) site
Hold released
from: McKelvey et al.
(2007)
Source: United States Department of Agriculture, 2004 SOD Science
Symposium III
Animal and Plant Health Inspection Service, Plant Protection and Quarantine

41. Phytophthora ramorum in the UK and Europe
From: UK Forestry Commission (Feb 2012) and EFSA Plant Health Panel (2011)

42. Species richness of human parasitic and infectious
diseases as a function of latitude
Burnside et al. (2011) Human macroecology: linking pattern
and process in big-picture human ecology. Biological Reviews

43. Challenge nr 7. What can we learn from biogeography?
Freeman (2011) Domesticated crop richness in human subsistence cultivation systems:
a test of macroecological and economic determinants. Global Ecology & Biogeography

44. Scenarios to anticipate challenges to biodiversity,
landscapes and public engagement with nature
1) Connect
for Life
2) Go for
Growth
3) Keep it
Local
4) Succeed
Kass et al. (2012)
through Journal of Applied
Science Ecology

45. A proposed model of on-farm plant genetic conservation
Selection of
target taxa On farm conservation
Project commission Phase 1: Project Planning and Establishment
• Identification of project site(s)
Ecogeographic survey
• Project sustainability
Development of •Identification of project partners
conservation objectives
• Formulation
of project activities
Field exploration
Phase 2: Project Management and Monitoring
• Initiation of project activities
• Monitoring activities
Conservation products • Review of project activities
Product deposition and Phase 3: Diversity Utilisation
dissemination • Traditional, general and
Characterization / professional utilization
evaluation
• Links to ex situ conservation,
Plant genetic resource research and education
utilization
redrawn from: Maxted et al. (2002) Towards a methodology for on-farm
conservation of plant genetic resources. Genetic Resources and Crop Evolution

46. Challenge nr 8. How to identify research priorities?

47. Identifying research priorities and emerging issues

48. Identifying research priorities and emerging issues
Grierson et al. (2011)

49. Seven means of identifying research priorities
(they are neither mutually exclusive nor exhaustive)
(i) reflection by individual workshop participants,
(ii) reviews of the peer-reviewed and gray literature
by individual workshop participants,
(iii) informal discussions between workshop
participants and colleagues,
(iv) use of email, blogs, tweets, Facebook, and other
electronic mechanisms for social networking,
(v) facilitating a workshop with colleagues,
(vi) assigning students to generate material as a class
assignment,
and (vii) an interactive website.
Sutherland et al. (2011) Methods in Ecology & Evolution

50. Question requirements…
(i) answerable through a realistic research design,
(ii) that have a factual answer that does not depend on value judgments,
(iii) that address important gaps in knowledge,
(iv) of a spatial and temporal scope that reasonably could be addressed by
a research team,
(v) not formulated as a general topic area,
(vi) not answerable with it all depends, (vii) except if questioning a precise
statement (‘does the earth go round the sun?’)
(vii) should not be answerable by yes or no (i.e. not ‘is X better for
biodiversity than Y’),
(viii) if related to impact and interventions, contains a subject, an
intervention, and a measurable outcome.
An ideal question suggests the design of research that is required to answer it
or can be envisioned as translating the question into directly testable
research hypotheses. Sutherland et al. (2011)
Methods in Ecology & Evolution

51. Challenge nr 9. How to promote
a diversity of research methods?
Pautasso et
al. (2012)
Agr Sust
Dev

52. Three results from recent game theory studies
1. cooperation is more
likely to persist in an Droz et al. (2009)
European
interacting population Physical Journal B
if cooperating
individuals are mobile
2. cooperation benefits
from diversity in the
number of social Santos et al. (2009)
interactions and in the Journal of
Theoretical Biology
choice of role models
to imitate
3. higher amount of Kaplan et al. (2012)
exchanges in high Proceedings of the
Royal Society B
variance environments

53. Summary of challenges
1. Keeping up with the literature
2. Stopping biodiversity loss
3. Global change interactions
4. Interdisciplinarity
5. Involving stakeholders
6. Network theory
7. Large-scale picture
8. Identifying research priorities
9. Diversity of methods

54. Don’t miss the ISE sessions S28 and S10
on Thursday 24 May at the Botanical Institute
13th Congress of the International Society of Ethnobiology,
20-25 May 2012, Montpellier
“Cultural diversity and biological diversity for sustainable
development: exploring the past to build up the future”

55. A forum of 25 researchers selected by the
European Commission in April 2012
http://voice.euraxess.org/
Please send your suggestions!
marpauta at gmail.com

56. Samedi 19 Mai,
Mas Drevon, Montpellier, 17h

57. Acknowledgements
Diego
Kevin
Fontaneto,
Gaston,
Mike McKinney, Verbania
Cornwall Ingrid
Knoxville
Susanne Fritz, Parmentier,
Frankfurt Brussels
Peter
Weisberg, Glen Powell, Mathieu
Wye Moslonka- Mike Jeger, Caroline Lorenzo
Reno Pecher,
Lefebvre, Paris Silwood Marini,
Bozen Uppsala
Ottmar Alessandro
Birgit & Florian Schlick- Chiarucci, Tom
Holdenrieder, Claude Steck,
Harwood,
Zurich Freiburg i.B. Steiner, Innsbruck Siena Canberra

58. Life cycle assessment for walnut seedling production
Cambria & Pierangeli (2011) A life cycle assessment case study for walnut tree
(Juglans regia L.) seedlings production. International Journal of Life Cycle Assessment

59. Life cycle assessments of the US food system
Heller & Keoleian (2003) Assessing the sustainability of the US food
system: a life cycle perspective. Agricultural Systems

60. Genetic structure of a rice landrace in Northern Thailand
Pusadee et al. (2009) Genetic structure and isolation by distance
in a landrace of Thai rice. PNAS

61. Regression model of n of spp per homegarden, Peru
Perrault-Archmibault & Coomes (2008) Distribution of agrobiodiversity in home gardens
along the Corrientes river, Peruvian Amazon. Economic Botany

62. „Wealth“ Biogeographical patterns
of the living collections
GDP SPP of the world’s botanic gardens
„combined“
Hypothesis: Rich countries have rich gardens
GDP
AGE
„Garden“
LAT SPP POP
AGE SPP
AREA
FLORA
AREA
Hyp.: There‘s a combination of processes
Hyp.: Garden characteristics matter most
„Flora“
LAT
SPP
FLORA
Hyp.: Diverse garden mirror a rich country flora Golding et al. (2010) Annals of Botany

63. „Wealth“ Biogeographical patterns
.48
R² = .22
of the living collections
GDP SPP of the world’s botanic gardens
„combined“
„Garden“ GDP
.30
AGE
.68 .28
R² = .21
R² = .44
.43 .19
AGE SPP LAT SPP POP
-.59 .31
.21 -.11
AREA AREA
FLORA
Significant at alpha 0.05
„Flora“
LAT .47
R² = .22 Non-significant; P > 0.05
-.55
.01
SPP
FLORA Golding et al. (2010) Annals of Botany