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Dryad

Negative effect of turbidity on prey capture for both visual and non-visual aquatic predators

Cite this dataset

Ortega, Jean et al. (2020). Negative effect of turbidity on prey capture for both visual and non-visual aquatic predators [Dataset]. Dryad. https://doi.org/10.5061/dryad.qbzkh18fq

Abstract

1. Turbidity plays an important role in aquatic predator-prey interactions. Increases in turbidity are expected to reduce prey capture rates, especially for visually oriented predators. However, there is also evidence indicating that turbidity may have little or no effect on predation rates. 2. Here, we conducted a systematic review and meta-analysis of the relationship between turbidity and capture rate. We explored possible sources of heterogeneity in the effect sizes (capture strategy, predator’s body size, relative eye size and turbidity range in the experiments) while controlling for the dependence among effects sizes and phylogenetic relationships among predator species. 3. We found a consistent negative effect of turbidity on prey capture and that turbidity range (manipulated in the experiments) was the main factor accounting for between-study variation in effect sizes. Also, capture rates of both visually and non-visually oriented predators decreased with an increase in turbidity. In addition, for visually oriented fish predators, the relative eye size did not influence the effect sizes. 4. Despite the paucity of studies for some groups of aquatic predators (mainly in tropical regions), we provide corroborative evidence that turbidity is a critical environmental factor controlling predator-prey interactions. This result is especially relevant considering that changes in turbidity is a human-induced pervasive environmental alteration resulted from, among other mechanisms, runoff after deforestation, eutrophication or oligotrophication in reservoir cascades, which imply changes in predator-prey interactions.

Methods

This dataset was collected following a systematic review protocol. We performed a systematic search on the Web of Science database, Scopus and Google Scholar on January, 31th 2018, using the following set of keywords and Boolean operators: ("predation rate*" OR "consumpt* rate*" OR "ingest* rate*" OR "forag* success") AND ("turbidit*" OR "transparen*" OR "sediment*"). The systematic search was performed in the "topic" field in Web of Science. In Scopus, the search was restricted to the document type “Article” and to the subject area “Agricultural and Biological Sciences” on “Title, Abstract and keywords”. Google Scholar search involved the use of a single combination of each keyword relating predation to turbidity with singular terms in the Scholar Google. For instance, “predation rate, turbidity”, “predation rate, sediment” or “foraging success, transparency”.

We found 1995 studies using our search queries and after screening the reference lists of two related meta-analyses (i.e., Chapman et al. (2014) and Wenger et al. (2017)). We evaluated the abstract of 1319 studies, after deleting the duplicates. We excluded 1191 studies which were (i) out of the scope of our meta-analysis, (ii) not published in English, Spanish or Portuguese (language restrictions), or (iii) did not present enough data. Then, we evaluated the full-text of the remaining 128 studies. After this step, we excluded 68 studies because, among other reasons, they were out of the scope of the meta-analysis or they did not present enough data (even after contacting the corresponding authors). We also did not consider studies that measure predation rates on frozen, dead or artificial food.

We compiled information on sample size, measures of central tendency (mean and median) and dispersion (standard deviation, standard error, range, and confidence intervals) in studies comparing a control group to one or more experimental groups. From studies that assessed the relationship between turbidity and predation rates using turbidity as a continuous variable, we compiled information on sample size and the correlation measure (Pearson correlations and coefficients of determination).

From each study, we recorded predator and prey species identities. Then, based on the literature, we recorded whether the predator species is mainly guided by visual or non-visual cues. We compiled the size of the eye of visually oriented predators (eye diameter in relation to total body length; only for fish species) by photos available in technical reports, articles and the FishBase repository. We also recorded the average size (in cm) of the predators and the range of turbidity (in nephelometric units; NTU) manipulated in each experiment.

Inside the R script file there are specific functions for effect size computation and conversions.

Usage notes

This dataset is composed of three files:

- "Supplementary Material 1_Turbidity.xls" is a dataplan with a list of studies returned from the systematic review protocol, raw data from the studies, data formated for analysis, and a list of references consulted for predator traits. Details on the content of each spreadsheet and the meaning of each column can be found in the "Metadata" plan.

- "phylo_pred.csv" is a matrix to build phylogenetic relations between predator species.

- "Script_Ortega et al_JAE_Turbidity meta_analysis" is a R script file for data analysis.

Missing values are coded as "NA" or as blank cells in "List of studies" plan.

Funding

National Council for Scientific and Technological Development, Award: 168522/2017-9