the use of meta-analysis to address ecological questions: an example using litter decomposition in...
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The use of meta-analysis to address
ecological questions: an example using
litter decomposition in streams
Verónica Ferreira [email protected]
17th September 2015
Metal contamination of streams
(USGS)
Litter decomposition is a key process in forest streams
(scheme adapted from Cummnis & Klug, 1979; Vannote et al., 1980; Wallace et al., 1997; Gulis & Suberkropp, 2003)
Riparian vegetation
Shading
Limited primary production (PP)
Litter input
High respiration (R)
Heterotrophic system (R>PP)
metalsmetals
y = 1E-80e0.0932x
R² = 0.979
0
10
20
30
40
1970 1980 1990 2000 2010
Cu
mu
lative
no
. stu
die
s
Year
Studies addressing the effect of metal contamination on litter decomposition in ‘streams’
0.00
0.02
0.04
0.06
0.08
0.10
0.00 0.02 0.04 0.06 0.08 0.10
Dec
om
po
siti
on
rate
(kin
d-1
) at
IMP
Decomposition rate(k in d-1) at REF
Traditional narrative review
No strict criteria for selection of studies
Usually does not attempt to locate all relevant studies
Usually does not describe why certain studies are included
and others excluded
Often does not assess study quality
High degree of subjectivity
Low repeatability
Low efficiency in handling a large number of studies
Limited ability to deal with variation in study outcomes
(Petticrew, 2001; Koricheva, 2014)
(Petticrew, 2001; Borenstein et al., 2009; Koricheva et al., 2013)
Question/hyphotesis clearly defined
Intensive and extensive literature search to locate all relevant studies
Inclusion/exclusion criteria clearly defined
Critical appraisal of studies
Statistical synthesis (e.g. meta-analysis)
Discussion and conclusion based on the most precise studies
Data extraction
Quantitative systematic review
Meta-analysis: a statistical approach
(Lipsey & Wilson, 2000; Nakagawa & Santos, 2012; Koricheva, 2013)
Combines results from different studies on the same topic, taking into account their precision, in order to draw a general conclusion and to evaluate the consistency among study findings.
It applies only to empirical research studies using quantitative measurement of variables and reporting descriptive or inferential statistics to summarize the data.
It allows to answer the following questions:
What is the combined magnitude of the effect under study?
Is the overall effect significantly different from zero?
Do any characteristics of the studies influence the magnitude of the observed effect?
Which are the gaps in the research?
When is meta-analysis most useful?
There is large amount of empirical studies available
The results vary across studies
The expected magnitude of the effect is weak and difficult to identify in individual studies
The sample size of individual studies is limited
Hypotheses are difficult to test in individual studies
Research gaps need to be identified
Does metal contamination affect litter decomposition in streams?
What is the magnitude and direction of the effect?
Is the magnitude and direction of this effect dependent on methodology or
environmental conditions?
Literature survey
Scope:
Time frame:
Type of studies:
Languages:
Search paths:
Studies addressing the effect of chronic anthropogenic metal contamination on litter decomposition in running waters*
January 1970 – October 2014
Studies published in the mainstream*
English*
Personal literature data bases; journal indices; Google Scholar; reference lists in primary studies and in review papers
Selection of relevant studies
133 REF – IMP pairs derived from 38 studies
Address the effect of chronic anthropogenic metal contamination on litter decomposition in running waters*
Report decomposition (any unit)
of natural litter
from allochthonous origin
in at least one reference and one impacted condition (REF – IMP pair)
Report sample size
Report a measure of variation (not strictly necessary!)
Data extraction
Decomposition:
Variation:
Sample size:
Moderators:
k in d–1 k in dd–1 Mass remaining Mass loss
SD, SE, CL SD
n
Publication year Study type Type of metal in laboratory studies Origin of contamination in field studies Mine type pH Type of decomposer community Litter type Litter identity
k in d–1
Effect size
(Hedges et al., 1999; Borenstein et al., 2009)
Hedges’ g:
Associated variance (Vg) – sampling error:
df = n1 + n2 – 2
Ι g Ι = 0.2, small effect Ι g Ι = 0.5, medium effect Ι g Ι = 0.8, large effect
0.0 0.5 1.0 1.5 2.0 2.5
Response ratio ( 95 % CL)
Study A
Study B
Study C
Study D
Overall mean
0.0 0.5 1.0 1.5 2.0 2.5
Response ratio ( 95 % CL)
Study A
Study B
Study C
Study D
Overall mean Hedges’ g –1.0 –0.5 0.0 0.5 1.0 1.5 0.0 0.5 1.0 1.5 2.0 2.5
Response ratio ( 95 % CL)
Study A
Study B
Study C
Study D
Overall mean
0.0 0.5 1.0 1.5 2.0 2.5
Response ratio ( 95 % CL)
Study A
Study B
Study C
Study D
Overall mean
Meta-analysis
Weighed random-effects model:
Cumulative meta-analysis
Subgroup analyses
Meta-regressions
Publication bias
Sensitivity analyses
(Viechtbauer, 2010; Koricheva et al., 2013)
metafor
Structure of the data base
Large experiment with
133 REF – IMP stream pairs
and > 6 000 litter bags
#papers: 38#cases: 133
#laboratory : 52
#field : 81
#manipulative: 6
#correlative: 75
#Acer: 9#Alnus: 3#Populus: 1#Quercus: 5#Salix: 1
#Ag mine: 2#As mine: 4#Au mine: 8#metal mine: 4#pyrite mine: 7
#leaves: 25
#Ag: 5#Al: 6#Cd: 5
#Cu: 2#Cu+Zn: 17#Fe: 2#Mixture: 1#Mn: 2#Zn: 12
#leaves: 6#circumneutral: 2#na: 4
#total: 2#microbial: 4
#mixture: 4#na: 2
#coal mine: 35#mine drainage: 3#motorway: 10#tip top mine: 2#metal mine:25
#acidic: 14#circumneutral: 13#na: 8
#microbial: 1#total: 34
#leaves: 29
#wood: 6
#Acer: 7#Alnus: 6#Melicytus: 1
#Nothofagus: 3#Platanus: 5#Quercus: 4#Salix: 3
#Betula: 3#Nothofagus: 3
#microbial: 6
#total: 19
#Alnus: 3#Quercus: 3
#acidic: 1#circumneutral: 8#na: 16
#papers: 38#cases: 133
#laboratory : 52
#field : 81
#manipulative: 6
#correlative: 75
#Acer: 9#Alnus: 3#Populus: 1#Quercus: 5#Salix: 1
#Ag mine: 2#As mine: 4#Au mine: 8#metal mine: 4#pyrite mine: 7
#leaves: 25
#Ag: 5#Al: 6#Cd: 5
#Cu: 2#Cu+Zn: 17#Fe: 2#Mixture: 1#Mn: 2#Zn: 12
#leaves: 6#circumneutral: 2#na: 4
#total: 2#microbial: 4
#mixture: 4#na: 2
#coal mine: 35#mine drainage: 3#motorway: 10#tip top mine: 2#metal mine:25
#acidic: 14#circumneutral: 13#na: 8
#microbial: 1#total: 34
#leaves: 29
#wood: 6
#Acer: 7#Alnus: 6#Melicytus: 1
#Nothofagus: 3#Platanus: 5#Quercus: 4#Salix: 3
#Betula: 3#Nothofagus: 3
#microbial: 6
#total: 19
#Alnus: 3#Quercus: 3
#acidic: 1#circumneutral: 8#na: 16
Q1: Does metal contamination affect litter decomposition in running waters?
Yes!
Hedges’ g = – 0.813
Strong inhibition!
No publication bias!
(Nfs > 8000 effect sizes)
Cumulative meta-analysis
In the last 10 years, the accumulated evidence allowed to increase the precision of the estimate and to reveal a significant inhibition of litter decomposition with metal contamination! Until 2004 (13 studies) there was no evidence of a significant effect of metal contamination on litter decomposition!
Q2: Do the magnitude and direction of the metal contamiantion effect differ between types of studies?
(Niyogi et al., 2001)
(Roussel et al., 2008)
Q3: Are the magnitude and direction of the metal contamination effect in laboratory studies influenced by the identity of the metal?
Q4: Are the magnitude and direction of the metal contamination effect in field studies influenced by origin of the metal contamination?
Q5: Do the magnitude and direction of the metal contamination effect depend on pH or litter type and identity in coal mine studies?
Q6: Do the magnitude and direction of the metal contamination effect depend on mine type, community type or litter identity in metal mine studies?
Conclusions
Litter decomposition is strongly inhibited by chronic anthropogenic metal contamination. This effect seems to be more dependent on the nature of the contamination than on the nature of the substrate and decomposers.
Future research:
Investigate the role of litter identity and community type in moderating the response of litter decomposition to metal contamination.
Investigate the effect of nanometals litter decomposition.
Investigate the combined effects of metal contamination and changes in other environmental conditions (multiple stressors).
Acknowledgements
Many authors provided information that was not included in the primary studies.