Archive data for: Loss of predation risk from apex predators can exacerbate marine tropicalization caused by extreme climatic events ...

• Main Authors: Nowicki, Robert, Thomson, Jordan, Fourqurean, James, Wirsing, Aaron, Heithaus, Michael
• Format: Dataset
• Language: English
• Published: Dryad 2020
• Subjects: FOS: Biological sciences; Antarc*
• Online Access: https://dx.doi.org/10.5061/dryad.59zw3r261; https://datadryad.org/stash/dataset/doi:10.5061/dryad.59zw3r261

1. Extreme climatic events (ECEs) and predator removal represent some of the most widespread stressors to ecosystems. Though species interactions can alter ecological effects of climate change (and vice versa), it is less understood whether, when, and how predator removal can interact with ECEs to exacerbate their effects. Understanding the circumstances under which such interactions might occur is critical because predator loss is widespread and ECEs can generate rapid phase shifts in ecosystems which can ultimately lead to tropicalization. 2. Our goal was to determine whether loss of predation risk may be an important mechanism governing ecosystem responses to extreme events, and whether the effects of such events, such as tropicalization, can occur even when species range shifts do not. Specifically, our goal was to experimentally simulate loss of an apex predator, the tiger shark (Galeocerdo cuvier) effects on a recently damaged seagrass ecosystem of Shark Bay, Australia by applying documented changes to ... : This dataset was collected over 16 months from 2013-2014 in degraded seagrass beds of Shark Bay, Western Australia. Each row refers to a visit to an experimental plot, each measuring 3x3m and consisting of three main macrophyte types: the seagrasses Amphibolis antarctica and Halodule uninervis as well as benthic macroalgae. At each plot, percent cover was assessed via diver by using a single 60 cm quadrat overlaid on the plot in a 5 x 5 pattern to cover the entire plot. Because each quadrat measurement is strongly correlated in space to others within the same plot, the percent cover across all 25 quadrats was averaged to generate a single percent cover value for each macrophye group in the plot. As such, each row contains the average percent cover in that plot for that time point. Later columns also group the data collected in a specific month by treatment group, and by treatment x bank subgroup. The data are otherwise unprocessed; full details can be found in the methods of the manuscript. There is also a ...