| Contributors | Affiliation | Role |
|---|---|---|
| Menge, Bruce A. | Oregon State University (OSU) | Principal Investigator |
| Gravem, Sarah | Oregon State University (OSU) | Co-Principal Investigator |
| York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
The purpose of this experiment is to test the recovery rates of rocky intertidal communities to single or repeated disturbance and thereby measure the succession and resilience of the community, respectively. We initiated the experiment series in the low zone in 2011 by haphazardly locating, then permanently marking five pairs of 0.5 x 0.5 m low intertidal plots. In spring/early summer each year from 2011- 2024, we photographed, then cleared one plot of each pair of all macrobiota, including macrophytes and sessile invertebrates ('removal plots'). Adjacent uncleared reference plots were left intact (controls). We also added succession plots in the early 2020s that were cleared once and allowed to recover (succession plots). Removals were allowed to recover without further intrusion for 12 mo, when they were photographed and recleared for the next year's observations. Plot locations did not change. Mid and high experiments were added in the early 2020s as well to compare how recovery and resilience differed between intertidal zones.
Percent cover of each species was estimated by inspecting photographs. The 0.5 x 0.5 m quadrats were subdivided into 0.1x0.1m subquadrats, each consisting of 4% cover. Abundances of each taxon were estimated by eye for each subquadrat, and totals were obtained by adding across all 25 subquadrats. We grouped species into functional groups for analysis (see Supplemental Files for taxon ids and more category information):
NA
* Sheet 1 "PE_PhotoPlots_Matrix_2024-04-17" of submitted file "BCODMO_PE_PhotoPlots_Matrix_2025-06-23_SAG.xlsx" was imported into the BCO-DMO data system for this dataset. Values "NA" imported as missing data values. Table will appear as Data File: 990951_v1_photoplot-species.csv (along with other download format options).
* Two unnamed columns in the table named "Comment1" and "Comment2"
* Sheet 2 "FunctionalGroups" and Sheet 4 "Notes" of "BCODMO_PE_PhotoPlots_Matrix_2025-06-23_SAG.xlsx" were added directly to the Methods & Sampling metadata section.
* Table within BCODMO_SiteList_STARS_2023-04-11_SAG.xlsx added as supplemental file sitelist_stars.csv
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.
* Column names adjusted to conform to 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]
* Date converted to ISO 8601 format
* Table of functional group name, column in dataset, and the SciNames included in the group were added as a supplemental file (functional_group_scinames_and_ids.csv) by parsing information provided Sheet 2 "FunctionalGroups" and Sheet 4 "Notes" of "BCODMO_PE_PhotoPlots_Matrix_2025-06-23_SAG.xlsx."
Taxon ids AphiaID and LSID were added from the World Register of Marine Species (lookup was on 2026-01-26).
Notes on SciNames and matching:
Alaria is an accepted taxon for two separate organisms. The usage in this dataset was matched to Alaria Greville, 1830 (urn:lsid:marinespecies.org:taxname:144194) that is a kelp not the Alaria that is a worm "Alaria esculenta (Linnaeus) Greville, 1830" urn:lsid:marinespecies.org:taxname:145716 (since this is in the kelp category).
Typos in scinames corrected (from->to):
Balanus nubilis
Balanus nubilus (urn:lsid:marinespecies.org:taxname:594745)
Corallina vancourveriensis
Corallina vancouveriensis (urn:lsid:marinespecies.org:taxname:494902)
| Parameter | Description | Units |
| PhotoID | Identifier for each photo showing SiteCode, Zone, Replicate, Treatment, and PhotoDate. E.g. BB_L_1_R_2011-06-02 | unitless |
| PlotID | Identifier for each photo showing SiteCode, Zone, Replicate, Treatment. E.g. BB_L_1_R | unitless |
| Project | PE for PreEmption Project | unitless |
| State | State experiment performed. All Oregon | unitless |
| Region | Region experiment performed. All Oregon | unitless |
| Cape | Cape experiment performed (Foulweather, Perpetua, Blanco) | unitless |
| SiteCode_STARS | Abbreviated Site Code | unitless |
| Site | Site Name | unitless |
| Latitude | Latitude of Site | decimal degrees |
| Longitude | Longitude of Site | decimal degrees |
| Zone | Zone of Plot (High, Medium, Low) | unitless |
| Rep | Replicate. Each replicate has one of each treatment and is clustered in space (1 to 5). | unitless |
| Treat | Detailed treatment of the plot (C = Control, never cleared; S = Sucession, cleared one time; R = Removal, plot cleared annually) | unitless |
| RepTreat | Combined Rep and Treat. E.g. 1_S or 3_C | unitless |
| PhotoDate | Date photo taken | unitless |
| Year | Year photo taken | unitless |
| Month | Month photo taken | unitless |
| Day | Day photo taken | unitless |
| Survey | Identifier for each survey showing SiteCode, Project, Date E.g. BB_PreEmption_2011-06-02 | unitless |
| YearRemovalStart | Year clearance started. Usually clearances are in spring and plots are monitored until the following spring | unitless |
| YearRemovalEnd | Year clearance ended. Usually clearances are in spring and plots are monitored until the following spring | unitless |
| YearNumber | Sequetion year of project. Year 1 is 2011 | unitless |
| YearRange | Years spanned from spring to spring | unitless |
| RemovalDate | Date clearance started. Usually clearances are in spring and plots are monitored until the following spring | unitless |
| DaysElapsed | Days since clearance started for the site (even if plot wasn't cleared). | days |
| Method | All data types are % cover | unitless |
| Bare_space | % cover of this species category | percent (%) |
| Mussels | % cover of this species category | percent (%) |
| Semibalanus | % cover of this species category | percent (%) |
| Balanus_glandula | % cover of this species category | percent (%) |
| Chthamalus | % cover of this species category | percent (%) |
| Gooseneck_barnacles | % cover of this species category | percent (%) |
| Anemones | % cover of this species category | percent (%) |
| Worms | % cover of this species category | percent (%) |
| Colonial_sessile_inverts | % cover of this species category | percent (%) |
| Coralline_crusts | % cover of this species category | percent (%) |
| Algal_crusts | % cover of this species category | percent (%) |
| Articulated_corallines | % cover of this species category | percent (%) |
| Red_blades | % cover of this species category | percent (%) |
| Red_filamentous | % cover of this species category | percent (%) |
| Red_turfs | % cover of this species category | percent (%) |
| Fucoids | % cover of this species category | percent (%) |
| Kelp | % cover of this species category | percent (%) |
| Surfgrass | % cover of this species category | percent (%) |
| Ulva | % cover of this species category | percent (%) |
| Other_green_algae | % cover of this species category | percent (%) |
| Diatoms | % cover of this species category | percent (%) |
| Total_cover | Summed % cover for plot. Usually equals 100 unless part of plot was not analyzed (glare, shadow, etc.) | percent (%) |
| Comment1 | Comment 1 | unitless |
| Comment2 | Comment 2 | unitless |
NSF abstract:
In recent decades, ocean ecosystems, long thought to be immune to change, have undergone disruptions to their structure, diversity, and geographic range, yet the actual underlying reasons for such changes in oceanic biota are often unclear. Coastal intertidal zones (i.e., the shore between high and low tides) have long served as important ecological model systems because of advantages in accessibility and ease of observation, occupancy by easily studied and manipulated organisms of relatively short lifespans, and exposure to often severe environmental conditions. This research will address the stability of a well-known rocky shore system along the Oregon and California coasts. Prior long-term research indicates that, although casual observation suggests these systems are stable, in fact, they may be on the cusp of shifting into another state, losing iconic organisms like mussels and sea stars, and becoming dominated by seaweeds. These changes might be comparable to losing trees and large predators from terrestrial systems. This study would result in the training of undergraduates and graduate students, including individuals from under-represented groups. Additionally, this study would include outreach to the general public.
The researchers will focus particularly on impacts of increasing and more variable warming on community recovery. For example, climate oscillations (e.g., El Niño), coastal upwelling, and particularly temperature have all changed in recent decades in ways leading to increased stress on intertidal biota. In apparent response, coastal ecosystems evidently have become less productive, organismal performance (growth, reproduction) has declined, and key dynamical processes (species interactions) have weakened. The new research will pursue these strong hints of an impending “tipping point” by (1) continuing the projects that led to the insights of increasing instability, (2) adding new projects that will pinpoint ecological changes, and (3) expanding the region of work to include locations in California. Research will assess whether or not sea stars recover from wasting disease, experimentally test if species interactions are indeed weakening, quantify the annual inputs of new prey and changes in abundance, diversity, stability, and resilience of intertidal communities, and document changes in the physical environment. Using field observations and experiments, the research will provide insight into impacts of environmental change, particularly warming, on the future of coastal ecosystems, and more generally, into possible future states of Earth’s ecosystems. Using these data, we will test the hypothesis that direct and indirect effects of climate change are driving, or may drive these systems into new, alternative states.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
| Funding Source | Award |
|---|---|
| NSF Division of Environmental Biology (NSF DEB) |