Search strategy
We will search for relevant studies using Web of Science and Scopus databases, using the search terms listed below. The search terms for macroalgal blooms will be combined with the other terms using the Boolean operator ‘AND’. The search terms for ecosystem structure, biogeochemical cycling, and productivity will be separated using the Boolean operator ‘OR’ and then combined within a set of outer brackets.
Terms for macroalgal blooms
((( Enteromorpha OR Ulva OR ulvoid OR Ulvaria OR Gracilaria OR "Pilayella littoralis" OR Cladophora OR Chaetomorpha OR Pylaiella OR Ectocarpus OR Lobophora OR wrack) AND ( bloom* OR outbreak OR proliferation OR overabundance)) OR "green tide" OR " macroalgal bloom*" OR " seaweed bloom*" OR "macroalgal accumulation*" OR "accumulation* of macroalga*" OR "alga* mat" OR "alga* mats" OR "macroalgal mat*" OR "accumulation* of algae" OR "drifting alga*" OR "drifting macroalg*" OR "nuisance macroalga*" OR "ephemeral alga*" OR "opportunistic alga*" OR (("Alga* bloom*" OR "alga* outbreak*" OR "Nuisance alga*") AND (wrack OR seaweed OR macroalga* OR Enteromorpha OR Ulva OR Ulvaria OR Gracilaria OR Pilayella OR Cladophora OR Chaetomorpha OR Pylaiella OR Ectocarpus OR Lobophora))).
Terms for ecosystem structure
(hysteresis OR "tipping point" OR "alternat* state" OR "alternat* stable state" OR "phase shift" OR "regime shift" OR "species richness" OR diversity OR "community structure" OR evenness OR "Shannon-Weaver" OR "Shannon-Weiner" OR "Shannon index" OR "Simpson Index" OR "abundance-biomass curve*" OR "species abundance distribution*").
Terms for biogeochemical cycling, flows of energy and materials
("Energy flow*" OR "Energy flux*" OR "Flow* of energy" OR "Flux* of energy" OR biogeochemical OR "Nutrient cycl*" OR "cycling of nutrient*" OR "Nutrient dynamics" OR "nutrient flux*" OR "Nutrient flow*" OR "Flow* of nutrient*" OR "Flux* of nutrient*" OR "cycling of carbon" OR "carbon cycl*" OR "carbon stor*" OR "carbon flow*" OR "carbon flux*" OR "flow* of carbon" OR "flux* of carbon" OR "cycling of sul*ur" OR "Sul*ur cycl*" OR "Flow* of sul*ur" OR "flux* of sul*ur" OR "sul*ur flux*" OR "sul*ur flow*" OR "Hydrogen sul*ide" OR "cycling of nitrogen" OR "nitrogen cycl*" OR "Flow* of nitrogen" OR "flux* of nitrogen" OR "nitrogen flux*" OR "nitrogen flow*" OR denitrification OR "cycling of phosphorus" OR " phosphorus cycl*" OR "Flow* of phosphorus" OR "flux* of phosphorus" OR "phosphorus flux*" OR "phosphorus flow*" OR "cycling of oxygen" OR " oxygen cycl*" OR "Flow* of oxygen" OR "flux* of oxygen" OR "oxygen flux*" OR "oxygen flow*" OR anoxi* OR hypoxi* OR bioturbation OR grazing OR foraging OR herbivory OR predation).
Terms for productivity and abundance
("primary product*" OR "secondary product*" OR "carbon fixation" OR "community respiration" OR "ecosystem respiration" OR "community metabolism" OR "ecosystem metabolism" OR "abundance of benthic" OR "productivity of benthic" OR "benthic biomass" OR "biomass of benthic" OR "benthic metabolism" OR "benthic respiration" OR (( abundance* OR biomass* OR productivity OR mortalit* OR survival OR growth OR cover OR densit*) AND ( fauna* OR animal OR infauna* OR epifauna* OR fish OR macroinvertebrate OR invertebrate OR macrofauna* OR mesofauna* OR meiofauna* OR epibenthic OR seagrass OR eelgrass OR Cymodocea OR Zostera OR Posidonia OR seaweed OR macroalgal OR macroalgae OR fish* OR bird* OR seabird OR shorebird))).
Study inclusion criteria
We will evaluate studies for inclusion at three successive levels, based on whether their populations, interventions, comparators, outcomes, and study types are considered relevant (see inclusion criteria below). First we will evaluate the titles, and remove spurious citations. Next, we will evaluate the abstracts. Several members of the review team will independently assess a subset of the studies (~10%), and a multi-rater Kappa statistic relating to the assessments will be calculated. If the statistic indicates that reviewers are inconsistent in their assessment (| < 0.5), discrepancies will be discussed and the inclusion criteria will be clarified or modified. Finally, we will evaluate the remaining studies at full text. If it is not clear whether a study meets our inclusion criteria at one of the levels of screening, it will be evaluated at the next level. The inclusion criteria we will use are as follows:
Relevant populations
Any ecosystems or ecosystem component (excluding coral reefs) affected by marine or brackish-water macroalgal blooms, including but not limited to:
Coastal, estuarine, and lagoon ecosystems
Seagrasses, algae, invertebrates, fish, and birds
Benthic, demersal, and pelagic components
Relevant interventions
"Natural" blooms of ephemeral macroalgae and mats of macroalgae
Manipulations of the abundance of an outbreaking macroalgal species (either direct manipulations or indirect manipulation made by changing nutrient levels, grazing intensity, etc.)
Relevant comparators
Experimental comparisons of "treatment" (bloom present) and "control" (bloom absent) conditions
Experimental and observational time series where the abundance of a bloom-forming species varies
Comparisons of areas with and without blooms from observational studies
For the purposes of this review, we define macroalgal blooms as rapid, temporary, increases in macroalgal abundance. We will specifically search for studies of algal genera well-known to cause macroalgal blooms in temperate and subtropical waters, including Cladophora, Ulva (Enteromorpha), Ulvaria, Pylaiella (Pilayella; sometimes mistaken for Ectocarpus), Gracilaria, and Chaetomorpha. However, we will also include studies examining blooms or mats of other species.
Relevant outcomes
We will begin by searching for studies examining the effect of macroalgal outbreaks on a broad range of outcomes. The resources available to carry out this review are limited, so we may later decide to exclude studies examining some of these outcomes. This decision will be based on the number of studies found for different outcomes, not the apparent magnitude or direction of effects. Initially we will search for studies on:
1. Structure and diversity of communities or community components
– Species richness (numbers of species observed)
– Univariate diversity or evenness indices (Shannon’s, Simpson’s, Pielou’s, etc)
– Abundance, biomass, density or cover of ecosystem components.
2. Ecosystem functions
– Productivity of the ecosystem or ecosystem components, measured as carbon fixation, respiration rate or other appropriate productivity measurements.
– Flows of energy or material between ecosystems or ecosystem components. For example, grazing or predation rates and measurements of ecosystem subsidies
– Biogeochemical cycling of nitrogen, phosphorus, carbon, oxygen, and sulphur, including both static and dynamic measures (e.g. static- nitrogen pool, dynamic- denitrification rate)
Relevant study types
– Manipulative experiments conducted in the field or laboratory
– Observational studies carried out in the field
We will consider studies from any time period. We will include grey literature and non-english studies if we find them following our general search strategy. However, we will not make additional, specific efforts to search for grey literature or non-english literature because we do not believe that we have adequate time or resources to do so in a thorough, unbiased, and systematic way. Non-significant results are often not published in scientific journals, but they might be more likely to appear in the grey literature. Our decision not to conduct grey-literature-specific searches could increase the chance that our results will be influenced by publication bias. Thus, we plan to evaluate and report on the potential effects of publication bias on our results as part of the review process.
Potential effect modifiers and reasons for heterogeneity
– We expect that the effects of macroalgal blooms may vary according to the following factors:
– Type of outcome (variable measured, ecosystem component, etc.)
– Type of ecosystem or habitat affected
– Features of blooms including species, size, magnitude, and duration
– Features of studies such as setting (lab vs. field), spatial scale, and timing of sampling (time since bloom started or ended)
– Region (i.e. different large marine ecosystems)
– Background ecosystem productivity
– Exposure (water movement, currents), temperature other physical or chemical parameters
Study quality assessment
Studies that meet the inclusion criteria will be assessed in terms of their susceptibility to bias, and the appropriateness of the study design in terms of estimating responses at the ecosystem scale. Each study will be classified along a number of dimensions:
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a)
Study setting – i) lab or ii) field
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b)
Study type – i) manipulative experiment or ii) observational
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c)
Appropriateness of controls- - i) appropriate ii) inappropriate iii) unclear
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d)
Replication – i) replicated or ii) unreplicated
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e)
Allocation of replicates – i) randomization ii) haphazard iii) other
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f)
Replication appropriateness - i) appropriate ii) inappropriate iii) unclear
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g)
Size of replicates – i) bay/bloom scale or larger ii) > 1 m2 iii) < 1 m2
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h)
Study extent – i) multiple blooms ii) full bloom iii) sub-bloom
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i)
Confounding factors - - i) present ii) not present iii) unclear
In addition to categorizing studies in this way, more specific details relating to each classification, such as the actual replicate size or the justification for considering replication appropriate or inappropriate, will be recorded and tabulated (See Additional file 1).
Determining whether controls are appropriate will be a subjective judgement, but the following criteria will be considered:
– do the controls appear to be spatially/temporally independent of the affected areas?
– are controls and affected areas sufficiently similar (consider, for example habitat and substrate type, degree of exposure, salinity, proximity to human activities).
If clear evidence is available in the paper that all of these criteria are met, then the controls should be considered valid, if there is evidence of failure to meet either of these criteria, the controls should be considered invalid and if it is not possible to make a proper assessment based on the information provided, then the study will be classified as ‘unclear’ in this regard.
If the authors refer to the replicates as being assigned randomly, or make reference to use of a random number table or random number generator, they will be classified as being randomly assigned. If the authors refer to the allocation as haphazard, or make reference to a procedure such as throwing a quadrat over their shoulder, allocation will be classified as 'haphazard'. All others methods will be classified as 'other', and described so that their susceptibility to bias can be assessed.
Determining whether or not replication has been carried out appropriately will be a subjective judgement, made after considering whether the replicates appear to be independent of one another in space and time (are they interspersed geographically, spread sufficiently in time, etc.). If the reviewer finds that the replicates are not independent, replication will be considered 'inappropriate'. If it is not possible to judge, the study will be classified as ‘unclear’.
The dimensions of study quality will later be evaluated as potential effect modifiers in the meta-analysis. This will allow us to assess the influence of different aspects of study quality and design on the outcome of studies investigating macroalgal outbreaks. We are particularly interested in knowing whether lower quality studies are biased in a particular direction. Understanding this will strengthen our ability to make recommendations regarding the design of future studies. If particular dimensions of study quality are found to bias the outcome of studies, we will base our conclusions regarding the effects of macroalgal outbreaks on an analysis of studies classified in the category deemed to be of higher quality.
Data extraction strategy
In addition to being categorized in terms of aspects of study quality, studies that meet the inclusion criteria will be described in terms of their:
– Region (from US National Oceanic and Atmospheric Administration large marine ecosystem list)
– Geographic coordinates (field studies only)
– Dates (start and end dates, sampling dates)
– Habitat type (e.g. rocky subtidal, beach, open coast, lagoon)
– Aims/focus
– Study design (beyond those aspects covered in quality assessment)
– Response variables measured
Information on all of the outcome measures listed above will be extracted from relevant papers. Summary statistics (mean, standard deviation, standard error, confidence intervals) will be extracted from tables and graphs, using image analysis software when necessary. If raw data are provided rather than summary statistics, these will be extracted and the summary statistics will be calculated. Information on potential confounding variables or effect modifiers will also be extracted. Dates and location data may be used to obtain estimates of additional effect-modifying variables from other data sources (e.g. digital maps of sea surface temperature, primary productivity, potential solar radiation). If the required data cannot be extracted from the paper, the authors will be contacted and asked to provide it. A number of reviewers will independently extract data from different papers, but a subset of papers will be processed by all reviewers to verify that data extraction is consistent and repeatable.
Data synthesis and presentation
The review will first present the number and type of studies that cover the impact of blooms on each of the different outcome measures of interest (i.e. diversity, species richness, productivity of different parts of the ecosystem and nutrient cycling of different nutrients). Where sufficient data on the same outcome measure are available, a meta-analysis will be conducted. Where different measures of the same outcome can be meaningfully combined in a single effect, we will do so using standardised response measures (e.g. log response ratios). Initially, information from all studies of a given outcome will be combined, and a random-effects meta-analysis will be used to estimate effect sizes. Subgroup analysis or meta-regression will be conducted to assess the impact of study quality categories, different outcome measurements and other potential effect modifiers where possible.