Searches for literature
Most of the evidence on which the proposed systematic review is to be based will be selected from the recently compiled systematic map of biodiversity impacts of roadside management [21]. The systematic map is based on literature searches using 13 publication databases, four search engines and about 40 specialist websites and literature reviews. The majority of these searches were performed in October–December 2015.
When deciding whether an article included in the systematic map is also eligible for inclusion in the proposed review, we will use the criteria described in the next section. This set of inclusion criteria is a more restrictive version of that used for the systematic map.
To identify more recently-published literature on the specific topic of the systematic review, we will also perform a search update, using the following subset of the search terms used for the systematic map:
- Population
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roadside*, “road side*”, (road* AND (verge* OR edge*)), roundabout*, “traffic island*”, “median strip*”, “central reservation*”, boulevard*, parkway*, (avenue* AND tree*)
- Outcomes
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*diversity, species, abundance, vegetation
The terms within the ‘population’ and ‘outcomes’ categories will be combined using the Boolean operator ‘OR’. The two categories will then be combined using the Boolean operator ‘AND’. An asterisk (*) is a ‘wildcard’ that represents any group of characters, including no character.
The search update will cover literature published in 2015 or later, which means that we expect it to add a fairly limited number of articles. When making literature searches for the systematic map, moreover, we found that about 90% of recent studies eventually included as relevant had been identified through Scopus and/or Transport Research International Documentation (TRID). Therefore, we consider it sufficient to base the search update on these two resources, with a complementary search in Google Scholar. When searching in Google Scholar, we will examine the first 200 hits (based on relevance) for appropriate data. No language or document type restrictions will be applied.
Article screening and study inclusion criteria
Articles identified during the search update will be evaluated for inclusion at three successive levels. First, they will be assessed by title. Next, each article found to be potentially relevant on the basis of title will be judged for inclusion on the basis of abstract. Finally, each article found to be potentially relevant on the basis of abstract will be judged for inclusion based on the full text. At all stages of this screening process, the reviewer will tend towards inclusion in cases of uncertainty. The screening will be performed by reviewers who participated in the main screening of studies for the systematic map and who are therefore well acquainted with the relevant literature and with the criteria for inclusion. The screening of articles from the search update can be seen as a continuation of the main screening, for which detailed, multi-level consistency checking was performed. Articles identified by the primary reviewer as potentially utilisable based on the full text will also be assessed by a second reviewer, and reviewers will not assess studies authored by themselves. Final decisions on whether to include doubtful cases will be taken by the review team as a whole.
A list of studies rejected on the basis of full-text assessment will be provided in an appendix together with the reasons for exclusion.
In order to be included in the review, studies included in the systematic map or identified during the search update must pass each of the following criteria:
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Relevant subjects: Roadsides anywhere in the world. A roadside is defined as the unpaved zone of a road that is exposed to roadside management.
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Relevant types of intervention: Maintenance or restoration of roadsides based on non-chemical vegetation removal such as mowing, grazing, burning, clearance of shrubs and saplings, coppicing, pruning, or mechanical removal of invasive plants.
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Relevant type of comparator: Non-intervention or alternative forms of the interventions.
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Relevant types of outcome: Measures of functional/taxonomic diversity of vascular plants or invertebrates (including abundance of assemblages and single species). Ratings of intervention effects based on visual assessments of vegetation vitality will not considered to be relevant.
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Relevant type of study: Primary field studies (reviews and other secondary compilations will not be included). Comparisons can in principle be made both temporally and spatially. Studies with a ‘BA’ (Before/After) design compare data collected at the same site prior to and following an intervention. Other studies may be based on comparison of different parts of a roadside, some that have been subject to a certain kind of management and some that have not. These may be termed as ‘CI’ (Comparator/Intervention) studies, or ‘BACI’ (Before/After/Comparator/Intervention) if they present data collected both before and after the intervention.
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Language: Full text written in English, Danish, Dutch, French, German, Norwegian, Spanish or Swedish.
Study quality assessment
Studies that have passed the relevance criteria described above will be subject to critical appraisal: Based on assessments of their clarity and susceptibility to bias, they will be categorised as having high or low validity (with regard to our review question).
Studies will be excluded from the review due to low validity if any of the following factors apply:
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No true replication (interventions not replicated)
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Intervention and comparator sites not well-matched (sites significantly different before intervention)
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Severely confounding factors present (e.g. additional treatments carried out at the intervention sites but not at the comparator sites)
The first two of these criteria deal with susceptibility to selection bias, whereas the last one deals with performance bias, as defined by the CEE guidelines [23]. The guidelines also list two other kinds of bias: detection bias and attrition bias [23]. We will address detection bias at full-text screening by excluding studies that only report simple ‘ratings’ of intervention effects based on visual assessments of vegetation vitality (see above), whereas attrition bias is not relevant to our review question—the interventions considered could not lead to systematic differences in attrition between intervention and control plots.
We will also exclude studies that are unclear to such an extent that their validity cannot be judged, for instance due to absence of key information on study design. More specifically, we will categorise a study as having unclear validity if any of the following factors apply:
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Methodological description insufficient (e.g. not clear to what extent the study was actually conducted at roadsides)
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Intervention data cannot be interpreted (e.g. since they consist of post hoc records such as ‘evidence of mowing’)
If none of the above five factors apply, the study will be considered to have high validity.
Detailed reasoning concerning critical appraisal will be recorded in a transparent manner. The quality of each study will be assessed by one reviewer and double-checked by another one. Reviewers will not assess studies authored by themselves. Final decisions on how to judge doubtful cases will be taken by the review team as a whole.
A list of studies rejected on the basis of quality assessment will be provided in an appendix together with the reasons for exclusion.
Data extraction strategy
Mean outcomes and measures of variation and uncertainty (standard deviation, standard error, confidence intervals) will be extracted from tables and graphs, using image analysis software (WebPlotDigitizer) when necessary. Where multi-year series of outcomes are available, we will extract all data and use either cross-year means or, if there are sufficient studies, look for time trends in responses. Data on interventions and other potential effect modifiers will also be extracted from the included articles. All extracted data will be double-checked by a second reviewer.
It may in some cases be useful to ask authors of relevant articles to supply data in digital format. This will primarily be done for articles less than 10 years old where useful data have been published in graphs from which they are difficult to extract accurately enough, or when it is known or assumed that considerable amounts of relevant but unpublished data may be available in addition to the published results. If raw data are provided, summary statistics will be calculated by us. Extracted data records will be made available as an additional file.
Potential effect modifiers and reasons for heterogeneity
To the extent that data are available, the following potential effect modifiers will be considered and recorded:
Roadside data
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Type, timing and intensity/frequency of roadside management
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Goals of the management (e.g. conservation/restoration of biodiversity)
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Roadside manager
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Width, aspect and slope of roadside
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Type and structure of roadside vegetation
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Soil type
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Nutrient status of the soil
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Shading, e.g. by trees
Road data
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Road type (width, type of surface)
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Time elapsed since the road (or roadside) was constructed
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Traffic (no. of vehicles per day)
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Road maintenance (e.g. salting, gritting, dust control, snow clearance)
Study setting
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Geographical coordinates
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Altitude
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Mean annual temperature and precipitation
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Vegetation, land use and history of land use in the surroundings of the road
Study design
Data on geographical coordinates, altitude and climate will be searched for in external sources if not available in the included articles. A final list of modifiers and causes of heterogeneity to be recorded will be established as the review proceeds.
Data synthesis and presentation
A narrative synthesis of data from all studies included in the review will describe the quality of the results along with the study findings. Tables will be produced to summarise these results. The findings in our systematic map also indicate that sufficiently many studies report similar kinds of outcome such that meta-analysis will be possible in some cases. In these cases effect sizes (mainly standardised mean differences) will be calculated, weighted appropriately and analysed using random-effects models. Meta-regressions or subgroup analysis of categories of studies will be performed where a sufficient number of studies report common sources of heterogeneity. Analysis of sensitivity and publication bias will be carried out where possible. Overall management effects will be presented visually in plots of mean effect sizes and variance. Any major knowledge gaps identified by the review will be highlighted and discussed. Details of the quantitative analysis will only be known when full texts have been assessed for their contents and validity.