Abstract:

This dataset was generated from a data synthesis of 5 mesocosm experiments conducted by Alabama Center for Ecological Resilience (ACER) researchers that evaluated the effect of biodiversity on oil effects in coastal ecosystems. This dataset is compromised of the elements (i.e., mean, sample size and variance) from each experiment required to conduct a formal meta-analysis of these results. Biodiversity – including genetic, species or functional – can enhance community stability in response to environmental fluctuations or disturbance that are either natural or human-induced. Initial findings from the Deepwater Horizon oil spill found that ecological impacts on coastal ecosystems varied greatly across habitat-type and trophic groups. To date, few studies have tested the influence of local biodiversity on these responses; however, each ACER sub-group conducted mesocosm experiments to evaluate whether biodiversity increased the resistance and/or resilience of coastal ecosystems to oil and dispersant disturbance. These experiments tested diversity effects across a range of habitats – from intertidal wetlands to pelagic open water – and across taxonomic groups (from microbes to fishes). Therefore, our data set is set up to assess how the diversity-disturbance relationship varied across trophic levels, the type of biodiversity tested (e.g. genetic vs. taxonomic), and response metrics including population- (e.g. survival, growth), community- (e.g., secondary production, predation rates) and ecosystem-level processes (e.g. bioturbation, denitrification).

Suggested Citation:

Zerebecki, Robyn A., Kenneth L. Heck, Jr., and John F. Valentine. 2020. A synthesis of mesocosm experiments results addressing the role of biodiversity on the resistance of coastal ecosystems to oil disturbance. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/YMJP922A

Purpose:

The purpose of this dataset was to examine if biodiversity can increase the resistance and resilience of nearshore coastal ecosystems in the northern Gulf of Mexico due to oil exposure.

Data Parameters and Units:

All data are in one datasheet Study Info Author = first author’s surname Year.conduct = year study was conducted or if published, publication date (2015-2016; 2016; 2017) Study = separate number assigned to each individual study (1; 2; 3; 4; 5) Exp.no = Letter representing the experiment within a study that has multiple experiments or treatments (corresponds on the Other.treatment.level column) (A; B; C; D; E; F) Resp.no = response number in row (corresponds with Response type column) within each study Time.no= time when response measured (dur; intermediate; end) GRIIDC = GRIIDC Unique Dataset Identifiers (UDIs) for each experiment Rep.id = concatenate of study, Exp.no, Resp.no to give unique identifier Info of Treatment in each row Oil Exposure Trmt = Oil, dispersant or both were exposed to (oil; oil +dispersant) Oil exposure concentration = concentration of oil (or dispersant, dispersant + oil) being tested (if multiple levels tested in experiment). NA if there were not multiple levels tested, and instead the concentration is in the Oil Amount column. Diversity Treatment = monoculture (averaged), max monoculture (best or least affected monoculture in oiling treatment) or polyculture (averaged) Polyculture.Level = number of species or genotypes in polyculture treatment. NA if not a polyculture treatment in Diversity Treatment as no levels existed. Max Mono Treatment = identification (species or genotype) of the max (best) monoculture treatment; best monoculture was recorded as the monoculture (on average) that was least affected by oil exposure. NA if not a max.mono in Diversity Treatment as not applicable. Diversity Info Div.cat = category of diversity manipulated (i.e. taxonomic, genetic or functional) # Poly.treat = # of polyculture levels tested in study Poly.Levels = description of polyculture levels (i.e. 2 species, 4 species, etc.) div.design = additive vs. substitutive Broad taxa classification = phylum (animal or plant) of target organisms manipulated More specific classification = class or order of target organisms Species = genus and species of manipulated/target organism Target response species = species that response was measured on Oiling Info (If ? in any oiling info column, this variable was unclear from GRIIDC, and/or publication) # oil.levels = # oil exposure levels manipulated in the study Oil levels = list of oil levels used in study Oil Amount = amount of oil exposed to in study Dispersant = Yes or No dispersant treatments included in study dispersant.trmt = Dispersant only, or Dispersant + Oil Disp. amount = amount of dispersant exposed to in study Oil.type = source of oil Disp.type = source of dispersant Oil.weathered = was oil weathered prior to addition – yes or no oiling.method = pulse or press oiling Experimental Design info (If NA in any column design/other trmt column, means that experiment only had diversity and oiling treatments, and no additional experimental treatments) Other.treatments = additional treatments beside oiling and diversity. Or if multiple types of diversity manipulated within experiment, those are indicated here as well. #treatment.levels = # of levels of other treatments Other.treat.level = Description of other treatment level in the experiment Exp.type = mesocosm or microcosm (beakers), & indoor/outdoor Season = season experiment conducted during other.treat.level = other treatment level for response in this row Response Properties Response.type = actual response variable data in the row Response.cat = more specific category of response (i.e. fitness, growth, predation, etc.) Response.level = Population, community or ecosystem level response Response units = actual units of the response variable (i.e. density, proportion survived) Duration = experiment duration (total) in days If.oil.pulse.timesince = units of time since oil exposure (if pulse exposure) in days # times Sample = # of dependent replicates sampled throughout the experiment duration Time.response = time point of response measured in row Response to oiling Mean.oiling = mean response to oiling treatment Sd.oiling = standard deviation of response to oiling treatment n.oiling = sample size in oiling treatment Mean.no.oiling = mean response to no oiling treatment Sd.no.oiling = standard deviation of response to no oiling treatment n.no.oiling = sample size in no oiling treatment Meta-analysis Response (Please find the parameters and their formulas in attached Word document or jpeg document "Metadata_response_parameters.") LRR (log response ratio to oiling) = LN((Mean.oiling)/( Mean.no.oiling)) Hedge d = effect size Var Hd = variance of effect size Notes = any other information about how calculated means or Hd for the response variables.

Methods:

Literature based, laboratory, and synthesis of lab mesocosm experiments

Individual Files: