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Indirect effects shape epifauna habitat


Ndhlovu, Aldwin (2022), Indirect effects shape epifauna habitat, Dryad, Dataset,


We tested the response of algal epifauna to the direct effects of predation and the indirect consequences of habitat change due to grazing and nutrient supply through upwelling using an abundant intertidal rhodophyte, Gelidium pristoides. We ran a mid-shore field experiment at four sites (two upwelling sites interspersed with two non-upwelling sites) along 450 km of the south coast of South Africa. The experiment was started in June 2014 and ran until June 2015. Four treatments (predator exclusion, grazer exclusion, control, and procedural control) set out in a block design (n = 5) were monitored monthly for algal cover for the first 6 months and every 2 months for the last 6 months. Epifaunal abundance, species composition, algal cover, and algal architectural complexity (measured using fractal geometry) were assessed after 12 months. Predation had no significant effect on epifaunal abundances, while upwelling interacted with treatment. Grazing reduced the architectural complexity of algae, with increased fractal dimensions in the absence of grazers, and also reduced algal cover at all sites, though the latter effect was only significant for upwelling sites. Epifaunal community composition was not significantly affected by the presence of herbivores or predators but differed amongst sites independently of upwelling; sites were more similar to nearby sites than those farther away. In contrast, total epifaunal abundance was significantly affected by grazing, when normalized to algal cover. Grazing reduced the cover of algae, thus epifaunal abundances were not affected by the direct top-down effects of predation but did respond to the indirect effects of grazing on habitat availability and quality. Our results indicate that epifaunal communities can be strongly influenced by the indirect consequences of biotic interactions.


The dataset was collected this study were used to distinguish upwelling and non-upwelling sites. Data for algal cover were used to assess the influence of treatment (fixed, 4 levels), upwelling (fixed, 2 levels) and site (nested in upwelling, random, four levels) on percentage algal cover. This was done at the start of the experiment (no significant effects of any factor or interaction) and again towards the end of the experiment. Analyses of the epifauna were based on data collected at the end of the experiment when all plots were destructively sampled. We used the same nested design to test the effects of treatment, upwelling and site on: epifaunal abundance (i.e., total number of epifaunal individuals) in each plot and density of epifauna per unit algal cover (number of epifauna per cm² of algal cover) in each plot. Analyses were performed using Statistica 12 (StatSoft), with alpha = 0.05.

Usage Notes

The readme file contains an explanation of each of the variables in the dataset and its measurement units. Information on how the measurements were done can be found in the associated manuscript referenced above. Funding This work was supported by the South African Research Chairs Initiative of the Department of Science and Technology and the National Research Foundation (grant number 64801) to CDM.


Rhodes University, Award: 64801