The use of meta-analysis to address ecological questions: an example using litter decomposition in streams

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


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


Study A

Study B

Study C

Study D

Overall mean

0.0 0.5 1.0 1.5 2.0 2.5


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


#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


#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


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.

Science

The use of meta-analysis to address ecological questions: an example using litter decomposition in streams