Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Data Files
• Supplemental Files
• Related Publications
• Related Datasets
• Parameters
• Project Information
• Funding

See "Related Datasets" section for other datasets to be published in Ng & Gaylord (2025, in-prep).  These datasets are also listed on the "Related-Resource" page for that results publication https://www.bco-dmo.org/related-resource/948176
​
All datasets in this project can be viewed from the "Dataset Collections" of the project page https://www.bco-dmo.org/project/712799

Of particular note are :

Dataset: Fear behavior with predators: Tegula in the presence of Cancer crab cues
https://www.bco-dmo.org/dataset/948210

Dataset: Fear behavior with predators: Tegula in the presence of Pisaster cues
https://www.bco-dmo.org/dataset/948216

* The supplemental file "Fear_behavior_with_predators_analysis_package.zip" is attached to BCO-DMO datasets 948204 (this dataset), 948210, and 948216.  The analysis package includes raw data and analysis R-scripts for all three datasets.
 

To examine the intensity of anti-predatory behavior of both Tegula funebralis and Nucella lamellosa, we measured the proportion of time individual snails spend above the waterline in the presence and absence of their predator species, Pisaster ochraceus and Cancer productus. Data from this experiment are used to calculate estimated predation rates for snails that do not behaviorally respond to their predators, which are used to determine the impact anti-predatory responses have on the strength of trophic cascades. The experiment was conducted within laboratory mesocosms at Bodega Marine Lab in 2018 and 2019.

Pisaster ochraceus, Cancer productus, and Tegula funebralis were collected along the coastline of Sonoma County, California in 2018. Both Pisaster and Tegula were sampled at Carmet Beach (38.372172 N, -123.076438 W), and the Cancer crabs were gathered subtidally from Doran Beach (38.309334 N, -123.048703 W). Nucella lamellosa were collected at Washington Park in Anacortes, Washington (48.502190 N, -122.691865 W) in July 2019.

We measured the behavior of both Nucella and Tegula in the presence and absence of their respective predators. We established 20 mesocosms (33cm x 20cm x 11.5cm) each with 10 Tegula that were provided with Ulva sp. ad libitum. Half of the mesocosms were exposed to Pisaster cue and the other 10 to just seawater. Predator exposure was accomplished by placing an individual Pisaster in a separate container, and then allowing cue generated by it to flow into the appropriate mesocosms. Pisaster were fed an individual Tegula once a week. Over a period of 14 days, we measured the number of snails either above or below the water line. Ulva sp. was included in the experiment in case its presence affected the snails’ decision to leave the water. We used the same procedure with Cancer to estimate Tegula’s behavioral response to them. We also used an analogous procedure to estimate Nucella’s behavioral response to Pisaster, with the exception that only five snails were used in each mesocosm due to the larger sizes of individuals of this snail species, and a small rock with Balanus glandula replaced Ulva as the basal resource.

Because a subset of our Nucella displayed morphological inducible defenses from the induction period, we also crossed the Pisaster cue treatment with the induced morphology treatment such that of the 10 mesocosms experiencing Pisaster cues, half of them contained induced Nucella and the other half had non-induced Nucella. Of the 10 mesocosms with no predator cue, half had induced Nucella and the other half had non-induced individuals.

To test the effect of predator cue on the snails’ behavior, we conducted a logistic regression on the proportion of snails in and out of the water line with container as a random effect. For Nucella, we also added induced morphology as a predictor along with its interaction with Pisaster cue, but because both terms were non-significant, we removed them from the final model. In addition, we added the containers they were housed in during the induction period as an additional random effect.

Organism identifiers (taxonomic names used in dataset metadata):

Scientific Name, Life Science Identifier (LSID)
Tegula funebralis, urn:lsid:marinespecies.org:taxname:534190
Nucella lamellosa, urn:lsid:marinespecies.org:taxname:404218
Pisaster ochraceus,urn:lsid:marinespecies.org:taxname:240755
Cancer productus,urn:lsid:marinespecies.org:taxname:440382
Ulva sp., urn:lsid:marinespecies.org:taxname:144296
Balanus glandula, urn:lsid:marinespecies.org:taxname:394848

See "Supplemental Files" for analysis package (R-language).

* Raw data and analysis R-scripts for three related datasets were packaged into the supplemental file Fear_behavior_with_predators_analysis_package.zip (no modifications to files). The zip file was attached to all three datasets (BCO-DMO datasets 948204, 948210, 948216).

* Data table from submitted file "Nucella behavior data.csv" was imported into the BCO-DMO data system for this dataset (948204). Table will appear on this dataset page as Data File:
948204_v1_fear-behavior_nucella.csv (with other download format options).

* Column "Date" renamed to "Date_local", and "Time" renamed to "Time_local". [US/Pacific local time]

* New column "ISO_DateTime_UTC" added by combining "Date_local" and "Time_local" with timezone conversion to UTC in ISO 8601 format.

* Bounding box for dataset determined by sampling locations provided and location of experiment at Bodega Bay Marine Laboratory (38.3180548,-123.0743098).

* Any column names with characters other than letters, numbers and underscores were renamed to meet BCO-DMO naming conventions designed to support broad re-use by a variety of research tools and scripting languages. [Only numbers, letters, and underscores.  Can not start with a number]

Missing Data Identifiers:
* In the BCO-DMO data system missing data identifiers are displayed according to the format of data you access. For example, in csv files it will be blank (null) values. In Matlab .mat files it will be NaN values. When viewing data online at BCO-DMO, the missing value will be shown as blank (null) values.

* Taxonomic identifiers added to the metadata (Life Science Identifiers (LSID)). Names matched using the World Register of Marine Species (WoRMS) on 2024-01-02.

NSF Award Abstract:
The absorption of human-produced carbon dioxide into the world's oceans is altering the chemistry of seawater, including decreasing its pH. Such changes, collectively called "ocean acidification", are expected to influence numerous types of sea creatures. This project examines how shifts in ocean pH affect animal behavior and thus interactions among species. It uses a case study system that involves sea star predators, snail grazers that they eat, and seaweeds consumed by the latter. The rocky-shore habitats where these organisms live have a long history of attention, and new findings from this work will further extend an already-large body of marine ecological knowledge. The project provides support for graduate and undergraduate students, including underrepresented students from a nearby community college. The project underpins the development of a new educational module for local K-12 schools. Findings will moreover be communicated to the public through the use of short film documentaries, as well as through established relationships with policy, management, and industry groups, and contacts with the media.

Ocean acidification is a global-scale perturbation. Most research on the topic, however, has examined effects on single species operating in isolation, leaving interactions among species underexplored. This project confronts this knowledge gap by considering how ocean acidification may shift predator-prey relationships through altered behavior. It targets as a model system sea stars, their gastropod grazer prey, and macoalgae consumed by the latter, via four lines of inquiry. 1) The project examines the functional response of the focal taxa to altered seawater chemistry, using experiments that target up to 16 discrete levels of pH. This experimental design is essential for identifying nonlinearities and tipping points. 2) The project addresses both consumptive and non-consumptive components of direct and indirect species interactions. The capacity of ocean acidification to influence such links is poorly known, and better understanding of this issue is a recognized priority. 3) The project combines controlled laboratory experiments with field trials that exploit tide pools and their unique pH signatures as natural mesocosms. Field tests of ocean acidification effects are relatively rare and are sorely needed. 4) A final research phase expands upon the above three components to address effects of ocean acidification on multiple additional taxa that interact in rocky intertidal systems, to provide a broad database that may have utility for future experiments or modeling.