Table of Contents

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

This time series is part of the LTREB project listed on this page (Award DEB-2050017) and was supported by the prior awards listed in the “Awards” section on this page.

SSWD = Sea star wasting disease

Our studies took place at eight sites along the Oregon coast spanning ~260 km from 44.5N to 42.75N latitude (Fig. 1, Table S1 of Gravem et al (2025)). All are predominantly rocky shores with relatively gentle slopes and have typical patterns of zonation, with a high-intertidal zone dominated by barnacles and fucoid algae, a mid-intertidal zone dominated by mussels, and a low-intertidal zone with a diverse assemblage of macrophytes and sessile invertebrates.

Belt Transects

Because of the importance of Pisaster in influencing community structure through its consumption of mussels and other prey, in 2000-2001 we initiated a program of ~twice-annual belt transects to quantify sea star size structure and density at each site. Surveys generally occurred in spring (April or May) and summer (July, August, or September), but in some years surveys were more or less frequent. Belt transects were replicated (n = 5) in 2 x 5 or 2 x 10 m rectangular areas (plots or belts) sampled below the bottom edge of mussel beds in the same location each year, with plot size enlarged to 2 x10m at years or sites when Pisaster abundance was low. Belt replicates were spaced throughout the defined study site to capture the density of Pisaster just below mussel beds. In each belt, researchers carefully searched for and collected all sea stars present and then wet weighed and measured arm lengths (madreporite to tip of opposite arm). Sea stars were often abundant, so when we reached the threshold of 200 animals in site and sample date, we finished that transect, then discontinued weighing and measuring in subsequent transects. Instead, we counted the remaining sea stars in these transects to capture densities. When sea stars were sparse, we surveyed additional transects (up to 10 total) to assess size structure of 200 animals where possible, but these additional transects were not used for density calculations since they were not replicated over time. After measurements, all sea stars were returned to their respective belt plots. Overall, we performed 440 surveys over 24 years at these 8 sites, which included 1,582 transects and measurements of 143,241 individual sea stars.

We calculated density as the count in each plot divided by plot area, which we calculated separately for each life stage for measured animals (see below). We calculated average size in each transect as the average wet weight. Since time constraints, the SSWD pandemic, or field scale failure sometimes forced us to measure only arm lengths but not weights, we developed an equation for estimating weights based on lengths as [wet weight in grams = 0.417 * (arm length in cm)^2.574]. We calculated biomass density as the total weight of animals per meter² in each transect. This is a potentially more accurate measure of ecological importance since Pisaster can vary several orders of magnitude in size and since potential predation rates and top-down control of mussels can increase dramatically as sea stars grow.

Sea Star Wasting Surveys and Disease Phases

In 2014-2015, when the pandemic was at outbreak levels in Oregon, we quantified disease occurrence using frequent (biweekly to monthly) surveys at each site. For disease frequency surveys, we searched a large area (100s of m²) within the study site for all sea stars. We recorded if the animal was apparently healthy or not, and if not, recorded the symptom(s), including lesions, deflation, arm loss, arm twisting, losing grip and disintegration. We calculated percent diseased as the percent of the total animals that exhibited any SSWD symptom. After 2015, disease occurrence mostly was quantified in the belt transects supplemented by periodic wider surveys as above. Since we had never observed a prior outbreak of SSWD nor instances of disease symptoms, we assumed pre-SSWD percent diseased was 0.

Using our disease frequency and demographic data, we divided the SSWD outbreak into 4 phases, with Pre-SSWD (or Pre-wasting) as before 2014, During outbreak as 2014 when symptoms peaked, Post-SSWD (or Post-wasting) as 2015-2020 when small outbreaks continued to occur and adult populations were clearly still low, and Current as 2021-2024 when adult populations had begun to recover at several sites (though small outbreaks continued to occur). 

Categorization of Life Stages

We categorized different life stages of Pisaster into recruits (which we sometimes split into young-of-year recruits and older recruits), juveniles, and adults. Post-larval individuals (several weeks or months old) were not targeted by our surveys. We defined ‘young-of-year (YOY) recruits’ ranging in size from 0.01 to 1 g wet weight and 3 to 14 mm arm length.  We define older recruits as individuals of 1 to 5 g wet weight, ~1.4 to 2.6 cm in arm length, and based on our size structure histograms are ~2-3 years old. We defined juveniles as individuals 5 to 80 g and ~2.6 to 7.7 cm arm length (this corresponds to roughly 2-6 years old) and defined adults as >80g, and >7.7cm arm length.

See associated paper - Gravem and Menge 2025. Metapopulation-scale resilience to disease-induced mass mortality in a keystone predator: From stasis to instability. Ecosphere. 2025;16:e70426. DOI: 10.1002/ecs2.70426

* Sheet BT_Density of submitted file "BCODMO_BTMasterAnnot_2000-2024_2025-03-06_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: 990963_v1_belt-transect_density.csv (along with other download format options).

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.

Supplemental Files:

* Validation Lists extracted from sheet ValidationList in BCODMO_BTMasterAnnot_2000-2024_2025-03-06_SAG.xlsx. Reformatted to not imply this is a table but rather unique lists of controlled vocabulary elements the study used.

* Table within BCODMO_SiteList_STARS_2023-04-11_SAG.xlsx added as supplemental file sitelist_stars.csv

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.