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A.E. Eycott et al. 2010. The impact of the matrix on species movement: systematic review and meta-analysis
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2. Methodology
2.1 Data search
We used a systematic review technique that was originally developed for conservation and
environmental management from the medical evidence review model (Pullin & Stewart, 2006).
Systematic review strives to minimise error and bias through an exhaustive search of peerreviewed
journal publications, grey literature and unpublished research findings.
Full details of the systematic review methodology and search terms can be found
atwww.environmentalevidence.org/SR43.html. In summary, we aimed to select all articles
(including grey literature and web-published data) that presented original, empirical data on
measured emigration rates from habitat patches where two or more matrix types were directly
compared in a controlled experiment or through a single survey. We excluded studies which
measured emigration indirectly, for example by distribution patterns, or where the patches were
too small to support a single individual (e.g. Castellon & Sieving, 2006). We also were unable
to include those papers from which raw emigration rates could not be extracted and the authors
of which did not respond to our request for the original data.
2.2 Data synthesis
Matrix types were classified as ‘more favourable’ or ‘less favourable’. This was decided using
the classification by the author of each study. In all but one case, the matrix type that was
assumed to be more favourable was that most structurally similar to the habitat patch, the
exception (Goodwin & Fahrig, 2002) being more ambiguous.
In order to combine the outcomes of different studies, all the data were converted to a single
measure that describes the magnitude of the effect of the study treatment. In this case the
'treatment' is the matrix type. We used risk ratios as the measure of the size of the effect. The
risk ratio is the multiplication of the risk that occurs in a ‘treated’ group relative to a control
group. In this case, the ‘treatment’ was the more similar matrix and the ‘control’ the less similar
matrix. If the chance of movement is reduced by a more favourable matrix, the risk ratio will be
less than one; if it increases the chance of individual movement, the risk ratio will be greater
than one.
‘Number needed to treat’ (NNT) can more intuitively illustrate the effect of a 'treatment'. NNT
is defined as the expected number of individuals who need to receive the experimental
‘treatment’ (the permeable matrix) rather than the control (the less permeable matrix) in order
for one additional individual to either incur (or avoid) an event in a given time frame.
The risk ratio was calculated individually for each homogeneous subgroup in a study, e.g. ‘all
the tests performed on species x over a distance of 250 m’. Calculated risk ratios were pooled
across studies to generate an overall weighted average risk ratio within a random effects model
(DerSimonian & Laird, 1986). The estimate of heterogeneity (variation in risk among studies)
was taken from the Mantel-Haenszel model.
2.3 Covariate analysis
We looked at the impact of five different factors on the study risk ratio: distance, duration,
contrast, choice and taxon. Distance and duration were investigated using meta-regression.
Contrast, choice and taxon were investigated using subgroup analysis, where the meta-analysis
Forest Landscapes and Global Change-New Frontiers in Management, Conservation and Restoration. Proceedings of the IUFRO Landscape Ecology
Working Group International Conference, September 21-27, 2010, Bragança, Portugal. J.C. Azevedo, M. Feliciano, J. Castro & M.A. Pinto (eds.)
2010, Instituto Politécnico de Bragança, Bragança, Portugal.