This document discusses using open data and meta-analysis to help with ecological and evolutionary synthesis. It describes how data from various sources like published studies, unpublished datasets, and metadata can be gathered and synthesized. Challenges include incomplete or unavailable data as well as differences in data collection and reporting. Case studies on topics like genetic change rates, divorce in birds, microbe communities, and soil carbon stocks demonstrate searching for relevant open data, screening datasets for usability, and analyzing data to answer research questions. The document advocates for open science to improve data sharing and the robustness of synthesis results.

1. From pedigrees, through divorce, to microbes and CO2:
how can fast growing data-landscape help ecological
and evolutionary synthesis?
Warsaw talk, 11/10/2017
By Antica Culina
Netherlands Institute of Ecology

2. Knowledge (data)
generators
DATA-SET
ECOSYSTEM
STUDY
ECOSYSTEM
Synthesis
Summarise, general conclusions,
test hypothesis, guide future
research, inform decision making
and interventions..
Users
Policy makers,
researchers,
public…

3. Meta-analysis
• statistically rigorous synthesis of research conducted on a certain
topic
• weighting the overall evidence for the effect of interest
• testing for biological drivers of observed patterns
• identifying methodological flaws (e.g. study design)
• highlighting the areas of interest for future work in the field

4. Antica Culina, #scidata16, 26 Oct 2016 4
Collect
data
Calculate
effect
sizes
Statitical
analysis
 search for studies
screen studies
extract info needed for effect size
contact the authors
calculate r
transform it to Zr
calculate the variance
random effects: control for dependencies
heterogeneity in ES: biological and
methodological moderators
Test and correct for biases

5. 5

6. Open Science

9. Data Ecosystem
Unpublished
datasets
Published
studies
Unpublished
studies
Metadata
Published
datasets

10. Data Ecosystem

11. Knowledge (data)
generators
DATA-SET
ECOSYSTEM
STUDY
ECOSYSTEM
Synthesis: Summarise, general conclusions,
test hypothesis, guide future research. Users
Policy makers,
researchers, public…
DESCRIBE:
• Where is it?
• How ‘good’ is it?
• How prone to
extinction is it?
• What are the problems in
using data-sets
EVALUATE:
• What difference does this bring?
SUGEST EFFECTIVE
FINDING/USE OF DATA-SETS

13. We want to know:
1) How does environment act on selection and heritability to
determine the rate of genetic change?
2) Is within season divorce adaptive in monogamous birds?
3) How are metanotroph communities structured by their
environment?
4) How will soil carbon stocks fall under warming?
And more interesting questions (see our project website!)
At the same time we want to use these case studies to learn about the
potentials and problems of the DATA landscape

14. Environment
14
Breeders equation: R = h2 x S
Case study 1: the rate of genetic change

15. Standardized spring temperature
Heritability
Selection
15

16. 16
Selection Differential on Birthweight against
Environmental Quality
Estimated Maternal Genetic Variance across
Environments

17. 17
Data do we need to answer our question:
ID Mother Father
1) Pedigree
+ 3) Environment
2) Traite

18. 18
Where to find datasets?
Data are usually in:
- Data repository
- Data journal
- Supplement of a publication
- Personal website
https://ckan-ecoevo.d4science.org

19. 19
We searched:
Europe PMC, DataCite, BASE, OpenAIRE, ScienceSerach, DataOne Mercury search,
Web of Science Data Citation Index, Scielo, Research Data Australia, DLI Service,
Dryad Digital Repository, Data MED
We can use a pedigree if:
(i) the pedigree file could potentially be used
(ii) the pedigree contained a sufficient number of individuals
(iii)individuals in the pedigree also had information on a phenotype on which
selection could act
(iv)there was potential, natural environmental variation in the phenotype (this
excluded all laboratory populations)
(v) the associated phenotype file contained at least six years of data
(vi)there were no additional issues

20. Antica Culina, #scidata16, 26 Oct 2016 20
Data Cite search
308 datasets excluded as
irrelevant
Screen abstract and title
Detailed screening
Datasets excluded as they are
not possible to use (state why)
Remove datasets belonging
to the same data-package
37 datasets from the same
package
4 datasets excluded as
irrelevant
Can dataset be used?

21. Antica Culina, #scidata16, 26 Oct 2016 21
N populations = 71
N species = 50
N populations = 14
N species = 9
amphibia
2%
birds
36%
fish
10%
insect
14%
mammals
32%
reptile
4%
mollusk
2%
Starting dataset:
Final dataset: amphibia
0%
birds
78%
mammals
11%
reptile
11%

22. Is within-season divorce adaptive for breeding success
• Between season divorce is: Culina et al. 2015 (Biol reviews)
 Triggered by low breeding success  Leads to improvement in BS (for females)

23. NO
Screen abstract and
title and deduplicate
1846
Across 13 databses
7
+45 references
cited in these

25. 10 studies; 35 ES
11 studies; 46 ES

26. Data there (out of 163 studies)
NO
Clarity of information provided
(67 ES)
included after
contacting the
author
46%
exlcuded
6%
possible to
include straight
away
48%

27. before
after
-0.4 -0.2 0 0.2
Effect size of divorce and breeding success

28. Breedingsuccescomponent Effect size of adptivness of divorce to breeding success
between sexes

29. Microbes
How are methanotroph
communities structured by their
environment?

30. Methane oxidation
CH4 Sources
methane oxidizing communities
CH4 + O2 -> CO2
We need:
 Open metagenome data
 Community structure
 pH
 T, C, N

31. 0
2000
4000
6000
8000
10000
12000
0
1000
2000
3000
4000
2008 2009 2010 2011 2012 2013 2014 2015 2016
cumulative
#soilsamples
year
soil samples that became publicly
available
JGI MG RAST EBI CUMULATIVE
What we found?
0
20
40
60
80
100
T pH Total N orgC
%oftotalsoilmetagenomes
Metadata % of total soil metagenomes
MG-RAST EBI
Open metagenome data
Community structure
pH, T
• C, N

32. + Other issues
Example N concentration
46%
15%
31%
8%
no units % mg/kg NO3 mg/L

33. Preliminary analysis
93 samples used
980 samples discarded
• temperature
• pH
9%
91%
pH reported
not reported

34. • for two decades, scientists have been concerned that warming would
stimulate the loss of carbon into the atmosphere, speeding up the rate of
climate change
• data focused on changes in respiration rates
• only a few had looked at net changes in carbon stocks
What is needed
• data from many sites on the ‘amount of carbon stored’ in ’ambient’ and
‘warmed’ plots around the world to calculate the ’difference’ for each site
• extract climate and soil data from each of these locations using GIS to
model the effects of warming to project it for the rest of the world
Quantify how soil carbon stocks will fall under
global warming

35. set the target of
50 studies to give
a strong
regression design
Of thousands of
experiments, only 6
reported changes in
C stocks
Only 2 open
access datasets,
and neither had
the necessary
location info
Emailed PIs for
raw data and got
access to 51 sites
in 6 months

36. Crowther et al. (2016). Nature
Background

38. 38
Some conclusions:
• Open Science is the FUTURE
• Ingredients are there (more and more of them)
• But, there are still issues
• Great potential to provide new opportunities for meta-analysis,
and improve robustness and quality of the results
• We all need to provide and use data to improve on the current
state for the better future of ecology

39. 39
A big thank to
Prof. Marcel Visser
Jip Ramakers
Dr. Annelies Veraart
Dr. Dedmer Van de Waal
Dr. Tom Crowther
Andrea Aldas Vargas
Mandy Velthuist
Mike Aaldering
Ilona van den Berg
Contact and more info:
A.Culina@nioo.knaw.nl
@antica_c
Meta analysis meets Open Science Project
https://nioo.knaw.nl/en/meta-analysis-meets-open-science
Also, sign up for our workshop
http://www.geurts.online/apply
https://nioo.knaw.nl/en/open-science-tools-data-technologies-
efficient-ecological-evolutionary-research