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Technical Summary

STUDY TITLE: Cross-Shelf Habitat Suitability Modeling

REPORT TITLE: Cross-Shelf Habitat Suitability Modeling for Benthic Macrofauna

OCS STUDY NUMBER: BOEM 2020-008

NUMBER OF PAGES: 71

CONTRACT NUMBER: M16AC00014

SPONSORING OCS REGION: Pacific

APPLICABLE PLANNING AREAS: Northern California, Washington-Oregon

FISCAL YEARS OF PROJECT FUNDING: FY 2016: $104,833; FY 2017: $35,167; FY 2018: $20,815; 

FY 2019: $0; FY 2020: $0

CUMULATIVE PROJECT COST: $160,815

COMPLETION DATE OF REPORT: February 2020

PROJECT MANAGER: Sarah K. Henkel, Ph.D.

AFFILIATION OF PROJECT MANAGER: Oregon State University, Hatfield Marine Science Center

ADDRESS: Oregon State University, Hatfield Marine Science Center, 2030 SE Marine Science Drive, 

Newport, OR 97365

PRINCIPAL INVESTIGATOR: Sarah K Henkel, Ph.D.

KEY WORDS: assemblages, benthic, biogeography, classification, California, continental shelf, 

continental slope, eastern Pacific, grain size, habitat characterization, habitat suitability model, 

invertebrates, infauna, macrofauna, Oregon, Pacific Northwest, unconsolidated sediment habitats

BRIEF ABSTRACT: Offshore the Pacific Northwest, we sampled macrofauna (i.e. infauna) species in 

waters 20 to 525 m to create cross-shelf habitat characterizations based on species groupings

(assemblages) and correlated to environmental parameters. The depth break of ~90 m was the first major 

environmental variable that correlated with major differences among macrofaunal assemblages among 

our stations and was followed by breaks at 200, 221, and 445 m. We found sediment parameters (percent 

fines, grain size, and total organic carbon) secondary and nearly as statistically important as depth. The 

information derived from this study starts to describe unconsolidated seafloor habitats and invertebrate 

communities in the Pacific Northwest; data collated can be used for future modelling applications.

BACKGROUND: Most seafloor habitats consist of unconsolidated sediments where macrofaunal 

(infaunal) invertebrate species serve as links between primary productivity and higher trophic levels 

(Snelgrove et al. 1998; Kędra et al. 2015). These invertebrates can be useful in defining unconsolidated 

sediment habitats because species represent long-term environmental conditions (Elliot 1994), both 

responding to and affecting local sedimentary processes and flow (Gray 1974, Rhoads 1974, Aller and 

Aller 1998, Friedrichs and Graf 2009). Macrofauna-based assessment indices are utilized worldwide to 

evaluate the overall condition or health of benthic habitats in a variety of regulatory or disturbance 

assessment contexts (e.g., waste water discharge, dredged material disposal) around the world (Gillett et 

al. 2015; Diaz et al. 2004). Despite the wide-use of assessment indices in water-quality based coastal 

regulation, the use of macrofauna to classify benthic habitats for informing planning applications is not 
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always possible nor done consistently (Reiss et al. 2015). US Federal laws and regulations specifically 

state the importance of benthic habitats on the continental shelf, and macrofauna-based analyses can 

assist with planning for groundfisheries (Thrush and Dayton 2002), fish farming (Tomassetti and Porrello

2005), and renewable energy (Etnoyer and Morgan 2003). In particular, the Outer Continental Shelf 

Lands Act states the need to characterize and monitor benthic habitats in areas potentially impacted by 

energy development. In this study we conducted macrofauna community analysis and correlated it with 

environmental covariates as an approach for applied decision-making at the regional scale needed for 

planning applications of the US west coast seafloor.

OBJECTIVES: The purpose of this study was to understand how macrofauna are distributed in relation to 

physical factors across the shelf and the upper slope and classify sedimentary benthic habitats as defined 

by the macrofaunal organisms. We specifically sought to (1) determine thresholds in physical parameters 

that correlated with macrofaunal assemblage differences in order to classify seafloor habitats in a 

biologically relevant way; and (2) coalesce macrofauna abundances and environmental data for the US 

west coast continental shelf and upper slope from multiple sources into a single database to use as inputs 

to habitat suitability models for a subset of the macrofauna species or other future applications.

METHODS: For the first objective to create cross-shelf habitat characterizations in the Pacific Northwest, 

404 seafloor samples from Grays Harbor, Washington (47.0 °N) south to Mendocino, California (39.5 °N) 

collected between 2012 and 2016 and ranging from 20 to 525 m deep were used. Samples were 

collected with a modified Grey-O’Hara 0.1 m2 box core, sieved through a 1.0 millimeter (mm) mesh 

screen, and identified. At most stations vertical water-column profiles were taken of conductivity, 

temperature, dissolved oxygen, and pH. Sediments were analyzed to determine mean and median grain 

size and percent fines (silt/clay). Approximately one quarter (n = 110) of the sediment samples were 

analyzed for percent total organic carbon (TOC) and total nitrogen (TN). A Bray-Curtis similarity matrix 

was created from 378 stations (outliers removed) to create a dendrogram, by agglomerative cluster

analysis with group-average linking and the Similarity Profiles (SIMPROF) procedure, to identify 

significant clusters based only from similarities in macrofaunal abundance. To determine which measured 

environmental factors “best” described the distribution of macrofaunal invertebrates across the study 

region, the BIO-ENV (BEST) procedure was used to find the subset of environmental variables with the 

strongest Spearman rank correlations to the macrofauna observed among the samples. We used 

LINKTREE procedure in PRIMER 6 to assess which of the variables that correlated with the species 

assemblage patterns could be used to delineate habitat types. The LINKTREE procedure is a form of 

constrained cluster analysis involving a divisive partition of the biotic community samples into ever smaller 

groups in which each biological division has an 'explanation' in terms of a threshold in one of the 

environmental variables (Clarke et al. 2008). We explored which combination of physical variables yielded 

the most parsimonious LINKTREE (i.e., the fewest number of splits using the fewest number of 

parameters) by creating LINKTREEs using each of the physical parameters individually, in groups, and

with all the potential predictors.

A second objective was to provide macrofaunal abundance and environmental data from multiple 

datasets along the US west coast. We determined which species were characteristic of the habitats 

classified and choose those present throughout the study region. Additionally, we included species that 

comprise a wide range of tolerance/sensitivities to pollution. Finally, we included seven species modeled 

previously in the region.

RESULTS: Organism abundances at the Pacific Northwest stations ranged from 10 to 542 individuals per 

0.1 m2 sample, and richness ranged from 5 to 64 taxa. In total, 757 taxa were identified and included for 

analysis, most to the species level. Overall, both organism abundance and sample richness declined 

significantly (p < 0.001) with depth while numerical species richness (number of taxa per number of 

individuals per grab) significantly increased (p < 0.001) with depth. The BEST match between the 

biological data and the environmental data for which we had complete coverage used just two variables: 

depth and median grain size, with a rather high correlation (r = 0.643). Using latitude, depth, and median 

grain size in the LINKTREE analysis resulted in the smallest tree (71 splits) using the fewest variables.

We grouped the 72 termini of the LINKTREE into 12 major habitats based on a cut-off of 25% dissimilarity 

among benthic assemblages. The first major split in the LINKTREE was associated with a depth break at 
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89 m. We classified the shallower side of this split as mid- and inner- (shallower than 42.5 m) shelf 

habitats. On the mid-shelf, there was a latitude split at 42° N, which is essentially the Oregon-California

border. Deeper than 90 m, a subsequent break was detected at 200 m, distinguishing the outer shelf from 

the slope. On the shelf, while further distinctions among macrofaunal assemblages were related to 

sediment characteristics – primarily median grain size – the biologically relevant breaks in grain size 

differed between the mid- and outer-shelf. Deeper than 200 m, subsequent breaks were detected at 

~220 m and 445 m. On the slope, percent fines and TOC increased with depth with median grain size, 

temperature, oxygen, and pH decreasing, making it challenging to determine the actual drivers for 

assemblage differences across slope depths.

For the second objective, of gathering macrofauna data for future habitat suitability models, 13 distinct 

data sets were combined spanning from 1994 to 2016 and from 15 to 535 m deep for a total of 1835 

records. All records contained macrofaunal count data, station location, depth, and at least percent fines 

for the sediment. Some datasets had additional physical data. Forty-five taxa were selected as the final 

list recommended for future habitat suitability modeling and the National Centers for Coastal Ocean 

Science built habitat suitability models reported under a separate BOEM report under Interagency 

Agreement Number M16PG00014.

CONCLUSIONS: We used differences in species assemblages to find meaningful breaks in more easily 

measured environmental data in order to develop habitat classifications. This study classified the 

macrofaunal communities of the Pacific Northwest continental shelf and upper slope soft bottom into 12 

habitats representing key depth and sediment-related breaks in macrofaunal community composition. Our 

results are consistent with the pattern of depth-related macrofauna assemblages throughout the 

California Current, supported by several studies in different parts of the California Current spanning over 

30 years. Sediment characteristics were important parameters not just on the inner to mid-shelf, but also 

further across the shelf and down the slope. The two most unique macrofauna-derived habitats in the 

Pacific northwest are the mud-based seafloor offshore northern California (63 m average depth), and the 

sandy sediments offshore central Oregon (34 m average depth). The deeper waters were structured 

similarly to the inner and mid shelf groups, having three grain size groups and lower separation latitudinal 

breaks within four outer shelf and three slope groups. For marine planning, these results can be used to 

set expectations of what macrofaunal species are likely to occur in particular habitat types. In classifying 

these habitats, we can create a context for describing the current communities in the region for soft 

bottom; a region undergoing changes in ocean hydrology, changes in bottom trawling pressure, and of 

growing interest for energy development projects. Establishing a soft bottom characterization for the 

Pacific Northwest offshore will aid in the increasingly standardized and quantitative assessments of 

impacts.

STUDY PRODUCTS:

1. BOEM final report: Henkel SK, Gilbane L, Phillips AJ, Gillett DJ. 2020. Cross-shelf habitat 

suitability modeling for benthic macrofauna. Camarillo (CA): US Department of the Interior, 

Bureau of Ocean Energy Management. OCS Study BOEM 2020-008. 71 p.

2. BOEM technical summary (this document)

3. Final database biology and environmental databases: Access Database 

‘HenkelCollatedNorthPtC’ contains station locations, macrofauna, and environmental data from 

Grays Harbor, Washington (47.0 °N) south to Point Conception, California (34.5 oN). Datasets 

were provided by Henkel SK, U.S. Environmental Protection Agency, Army Corps of Engineers, 

San Francisco Public Utility Commission, Moss Landing Marine Laboratories Benthic Lab, City of 

Morro Bay, and Cayucos Sanitary District Offshore Monitoring and Reporting Program. Database 

includes samples collected in the same location at multiple time points for Oregon and offshore 

San Francisco Bay and Monterey Bay. Not all datasets were used in all associated analyses.

4. ArcGIS polygon of study footprint and map package of 404 sample locations for Chapter 3 

collected primarily by Henkel SK extending from Grays Harbor, Washington (47.0 °N) south to 

Fort Bragg, California (39.3 oN).
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MAP SHOWING AREA OF STUDY

Macrofaunal grab samples (n = 404) gathered for habitat classification in the Pacific Northwest.