Content uploaded by Chris Goldfinger
Author content
All content in this area was uploaded by Chris Goldfinger on Nov 29, 2014
Content may be subject to copyright.
OCS Study
BOEM 2014-662
US Department of the Interior
Bureau of Ocean Energy Management
Pacific OCS Region
Benthic Habitat Characterization
Offshore the Pacific Northwest
Volume 2: Evaluation of Continental
Shelf Benthic Communities
OCS Study
BOEM 2014-662
Benthic Habitat Characterization
Offshore the Pacific Northwest
Volume 2: Evaluation of Continental
Shelf Benthic Communities
Authors
S.K. Henkel, C. Goldfinger, C. Romsos, L.G. Hemery,
A. Havron, K. Politano
Prepared under BOEM Award
M10AC20002 (CFDA No.) 15.423
by
Oregon State University
Corvallis, OR 97331
US Department of the Interior
Bureau of Ocean Energy Management
Pacific OCS Region
November 24, 2014
4
DISCLAIMER
!
Study collaboration and funding were provided by the US Department of the Interior, Bureau of Ocean
Energy Management, Environmental Studies Program, Washington, DC, under Agreement Number
M10AC20002 (CFDA No.) 15.423. This report has been technically reviewed by BOEM and it has been
approved for publication. The views and conclusions contained in this document are those of the authors
and should not be interpreted as representing the opinions or policies of the US Government, nor does
mention of trade names or commercial products constitute endorsement or recommendation for use.
!
REPORT AVAILABILITY
To download a PDF file of this Gulf of Mexico OCS Region report, go to the US Department of the
Interior, Bureau of Ocean Energy Management, Environmental Studies Program Information System
website and search on OCS Study BOEM 2014-662.
This report can be viewed at select Federal Depository Libraries. It can also be obtained from the National
Technical Information Service; the contact information is below.
US Department of Commerce
National Technical Information Service
5301 Shawnee Rd.
Springfield, VA 22312
Phone: (703) 605-6000, 1 (800) 553-6847
Fax: (703) 605-6900
Website: http://www.ntis.gov/
!
CITATION
!
Henkel, SK, Goldfinger C, et al. 2014. Benthic Habitat Characterization Offshore the Pacific Northwest
Volume 2: Evaluation of Continental Shelf Benthic Communities. US Dept. of the Interior,
Bureau of Ocean Energy Management, Pacific OCS Region. OCS Study BOEM 2014-662. 218
pp.
Contributing Authors
T. Lee, S. Labou
Acknowledgements
The captains and crews of the R/V Pacific Storm, R/V Elakha, Miss Linda, Derek M. Baylis. Marine
Applied Research and Exploration, David Evans and Associates.
5
Survey of Benthic Communities near Potential Renewable Energy Sites
Offshore the Pacific Northwest
!"#$%&"'()*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*,!
)(-.)/*&0&"%&1"%"/2*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*,!
$"/&/".3*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*,!
%456*78*94:;<=5*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*>!
%456*78*/?@A=5*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*B!
&@@<=C4?647D5*?DE*&F<7DGH5*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*IJ!
,+*-?66=<D5*78*1=D6K4F*'=:?L"DC=<6=@ < ?6 = *M ? @ 46? 6*& 5 57 F 4? 647 D 5 *N) . 0*)=O7 <6 P*+++++++++++++++++++++++++++++++++++++*IQ!
4.1!Introduction!and!Background!...........................................................................................................!12!
4.1.1!Study!Purpose!and!Objectives!...................................................................................................................!13!
4.2!Methods!...........................................................................................................................................!13!
4.2.1!Study!Sites!.................................................................................................................................................!13!
4.2.2!Video!Analyses!..........................................................................................................................................!16!
4.2.3!Segment!Area!and!Taxon!Density!..............................................................................................................!17!
4.2.4!Statistical!Analyses!....................................................................................................................................!18!
4.3!Results!..............................................................................................................................................!18!
4.3.1!Site!Characteristics!....................................................................................................................................!18!
4.3.2!Community!Structure!................................................................................................................................!20!
4.4!Discussion!.........................................................................................................................................!32!
4.4.1!Conclusions!................................................................................................................................................!35!
4.4.2!Next!Steps!..................................................................................................................................................!36!
4.5!Literature!Cited!................................................................................................................................!36!
R+! 1=D6K4F*'?F<78?;D?*!456<4@;647D5*?DE*M?@46?6*&557F4?647D5*++++++++++++++++++++++++++++++++++++++++++++++++++++++++*,I!
5.1!Introduction!and!Background!...........................................................................................................!41!
5.1.1!Study!Purpose!and!Objectives!...................................................................................................................!42!
5.2!Methods!...........................................................................................................................................!42!
5.2.1!New!Sample!Collection!..............................................................................................................................!42!
5.2.2!Sample!Processing!.....................................................................................................................................!44!
5.2.3!Processing!of!Historical!Data!.....................................................................................................................!45!
5.2.4!Data!Analysis!.............................................................................................................................................!45!
5.3!Results!..............................................................................................................................................!48!
5.3.1!BOEM!Survey!Data!....................................................................................................................................!48!
5.3.2!EPA!Data!....................................................................................................................................................!52!
5.3.3!EPA!and!BOEM!comparison!.......................................................................................................................!56!
5.3.4!Linking!Biological!and!Physical!Patterns!....................................................................................................!57!
5.4!Discussion!.........................................................................................................................................!62!
6
5.4.1!Conclusions!................................................................................................................................................!64!
5.4.2!Next!Steps!..................................................................................................................................................!65!
5.5!Literature!Cited!................................................................................................................................!67!
S+*1?G=54?D*'7E=A4D:*78*'?F<78?;D?*)=O7<6*++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ *>I!
6.1!Introduction!and!Background!...........................................................................................................!71!
6.1.1!Purpose!and!Objectives!.............................................................................................................................!72!
6.2!Methods!...........................................................................................................................................!73!
6.2.1!Overview!...................................................................................................................................................!73!
6.2.2!Components!of!a!Bayesian!Network!.........................................................................................................!77!
6.2.3!Variable!Selection!......................................................................................................................................!79!
6.2.4!Development!of!Model!Structure!.............................................................................................................!80!
6.2.5!Model!Parameterization!............................................................................................................................!85!
6.2.6!Model!Calibration,!Selection,!and!Prediction!............................................................................................!86!
6.2.7!HSP!Bayesian!Net!Model!Outputs!.............................................................................................................!88!
6.2.8!Field!Validation!..........................................................................................................................................!88!
6.3!Results!..............................................................................................................................................!89!
6.3.1!Bivalvia!......................................................................................................................................................!91!
6.3.2!Gastropoda!................................................................................................................................................!96!
6.3.3!Polychaeta!...............................................................................................................................................!101!
6.4!Discussion!.......................................................................................................................................!107!
6.4.1!Interpreting!Results!.................................................................................................................................!107!
6.4.2!Limitations!...............................................................................................................................................!108!
6.4.3!Recommendations!...................................................................................................................................!108!
6.4.4!Conclusions!..............................................................................................................................................!110!
6.5!Next!steps:!Application!of!methods!to!preliminary!glass!sponge!habitat!model!...........................!110!
6.5.1!Introduction!.............................................................................................................................................!110!
6.5.2!Methods!..................................................................................................................................................!111!
6.5.3!Preliminary!Results!..................................................................................................................................!113!
6.5.4!Discussion!................................................................................................................................................ !116!
6.6!Literature!Cited!..............................................................................................................................!116!
&OO=DE4T*,+*#;OOA=H=D6?<G*'?6=<4?A*87<*).0*)=O7<6*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*IIB!
&OO=DE4T*R+*#;OOA=H=D6?<G*'?6=<4?A*87<*'?F<78?;D?*)=O7<6*++++++++++++++++++++++++++++++++ +++++++++++++++++++++++++++*IQS!
&OO=DE4T*S+*1=D6K4F*'?F<78?;D?*'7E=A5U*#O=F4=5*)=5O7D5=*M4567:<?H5V*1?G=54?D*1=A4=8*3=6W7<X5V*
?DE*'7E=A*YOE?6=*?DE*3=W*#O=F4=5*&OOA4F?647D*"D56<;F647D5*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*ISR!
&OO=DE4T*>+*!?6?*-<7E;F65*?DE*!456<4@;647D*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*QJ>!
/=FKD4F?A*#;HH?<G*+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++*QJB!
7
List of Figures
Figure!1.!Location!of!the!three!ROV!and!Delta!study!areas!.......................................................................!14!
Figure!2.!Tracklines!of!station!covered!during!the!ROV!surveys!at!Grays!Bank!(A),!Siltcoos!Reef!(B)!and!
Bandon\Arago!(C)!.......................................................................................................................................!16!
Figure!3.!Proportion!of!substratum!patch!types!per!study!site!.................................................................!19!
Figure!4.!Abundances!of!benthic!macroinvertebrate!phyla!at!the!study!sites!...........................................!22!
Figure!5.!Two\dimensional!nonmetric!multidimensional!scaling!(nMDS)!ordination!of!the!patch!types!
based!on!invertebrate!community!data!from!the!ROV!Hammerhead!survey!forming!4!distinct!habitat!
types!(MM ,!M x,!cR ,!rR)!with !som e!site!d ifferen ce s!resu lting!in!6!tota l!group s!.........................................!23!
Figure!6.!Diversity!indices!(mean!±SD)!for!each!habitat!type!an d!m e m b ersh ip!fro m !the !Tu key !test!for!
ROV!sites!(left)!and!!"#$%!sites!(right)!........................................................................................................!25!
Figure!7.!Two\dimensional!nonmetric!multidimensional!scaling!(nMDS)!ordination!of!the!patch!types!
based!on!invertebrate!community!data!from!the!!"#$%!survey!forming!four!distinct!habitat!types!(MM,!
Mx,!R,!F)!with!some!site!differences!..........................................................................................................!29!
Figure!8.!Box!core!stations!sampled!in!2010!(yellow)!and!2012!(red)!across!eight!sites!...........................!43!
Figure!9.!BOEM!box!core!stations!sampled!in!2010!(blue)!and!EPA!stations!sampled!in!2003!(red)!.........!46!
Figure!10.!nMDS!plot!of!BOEM!(2010!&!2012)!and!within\region!EP A!sta tion s!(2 00 3)!.............................!47!
Figure!11.!Proportions!of!major!taxa!at!each!site!surveyed!for!the!BOEM!project!from!northern!California!
(two!left!sights),!offsh ore !of!O reg on !(ne xt!five!site s),!and !W as hin gto n!(G ray s!H arb or)!............................!49!
Figure!12.!Proportions!of!major!taxa!within!the!selected!areas!of!the!EPA!dataset!grouped!by!state!.....!52!
Figure!13.!Cluster!analysis!of!the!regional!EPA!stations!(n!=!79)!based!on!macrofaunal!densities!............!54!
Figure!14.!Bivalve!densities!from!EPA!stations!(red!bars)!that!fell!near!2010!BOEM!sites!(blue!bars)!......!57!
Figure!15.!LINKTREE!grouping!and!physical!characteristics!of!BOEM!stations!developed!using!the!BEST!
correlating!(%!gravel,!%!sand,!median!grain!size,!and!depth)!environmental!variables.!Y\axis!shows!the!
percent!similarity!(%B)!...............................................................................................................................!59!
Figure!16.!LINKTREE!grouping!and!physical!characteristics!of!EPA!stations!developed!using!the!BEST!
correlating!(%!sand ,!dep th,!TO C ,!and !latitud e………………………………………………………………………………………..60
Figure!17.!nMDS!ordination!of!BOEM!stations!..........................................................................................!61!
Figure!18.!nMDS!ordination!of!EPA!stations!..............................................................................................!61!
Figure!19.!Benthic!macrofauna!species!chosen!for!habitat!suitability!models!..........................................!73!
Figure!20.!Diagram!of!the!process!used!to!create!Bayesian!Network\based!model!for!seven!benthic!
macrofauna!species!....................................................................................................................................!74!
Figure!21.!Principles!of!Parsimony!............................................................................................................. !75!
Figure!22.!Study!region!..............................................................................................................................!76!
Figure!23.!A!sample!Bayesian!network!modeling!structure!.......................................................................!77!
Figure!24.!Bayesian!Network!Conditional!Probability!Table!(CPT)!.............................................................!78!
Figure!25.!Integrating!absent/present!probabilities!..................................................................................!79!
Figure!26.!Supervised!Discretization!(Left)!and!Equal!Frequency!Discretization!(Right)!techniques!to!
select!breakpoints!and!state!parameters!for!bu ilding !the!H SP !M o de l!(Top !Left)!......................................!81!
Figure!27.!Naïve!Bayesian!Network!............................................................................................................!82!
Figure!28.!Tree!Augmented!Naïve!Bayesian!Network!................................................................................!83!
8
Figure!29.!Supervised!Net!Link!Structure!...................................................................................................!83!
Figure!30.!Regional!raster!and!local!in!situ!variables!.................................................................................!84!
Figure!31.!Example!of!a!re\useable!and!updateable!Bayesian!network!for!benthic!macrofauna!living!
within!marine!sediment!.............................................................................................................................!85!
Figure!32.!Confusion!Matrix!that!is!used!to!calculate!the!confusion!matrix!error!rate!.............................!86!
Figure!33.!Graphical!representation!of!the!Four\Fold!Cross!Validation!process!........................................!87!
Figure!34.!Study!area!of!field!validation!.....................................................................................................!89!
Figure!35.!Overall!Model!Comparison!of!True!Skill!Statistic!(TSS)!performance!scores!.............................!90!
Figure!36.!&'()*+,(-%.,"//(0%$%!..................................................................................................................!93!
Figure!37.!1))202#%.$")2(,!.........................................................................................................................!95!
Figure!38.!&3,$/(,.4%2,%+%$%!......................................................................................................................!97!
Figure!39.!5%##(%)%'.+30)%!........................................................................................................................!100!
Figure!40.!6%4"#*)%.7"/8"#"3(!.................................................................................................................!102!
Figure!41.!9)2+:(,.(/(-",0"),!...................................................................................................................!104!
Figure!42.!;$"/)%+,(,.<*,,*/!......................................................................................................................!106!
Figure!43.!Dictyonine!glass!sponge!species!..............................................................................................!111!
Figure!44.!Newport!embayment!offshore!of!Oregon!...............................................................................!112!
Figure!45.!Preliminary!Bayesian!network!for!dictyonine!sponge!group!..................................................!113!
Figure!46.!Habitat!Suitability!Probability!(HSP)!Map!of!the!Dictyonine!sponge!group!............................!115!
Figure!47.!Example!of!a!mud\mud!(MM)!patch!(from!Siltcoos)!...............................................................!119!
Figure!48.!Example!of!a!mud\gravel!(MG)!patch!(from!Grays!Bank)!........................................................!119!
Figure!49.!Example!of!a!mud\pebble!(MP)!patch!(from!Bandon\Arago)!..................................................!120!
Figure!50.!Example!of!a!cobble\mud!(CM)!patch!(from!Bandon\Arago)!..................................................!120!
Figure!51.!Example!of!a!mud\boulder!(MB)!patch!(from!Siltcoos)!...........................................................!121!
Figure!52.!Example!of!a!flat!rock\mud!(FM)!patch!(from!Ban do n \Arago)!................................................!121!
Figure!53.!Example!of!a!ridge!rock\mud!(RM)!patch!(from!Bandon\Arago)!.............................................!122!
Figure!54.!Example!of!a!cobble\gravel!(CG)!patch!(from!Bandon\Arago)!................................................!122!
Figure!55.!Depth!(m)!at!the!eight!study!sites!...........................................................................................!126!
Figure!56.!Percent!gravel!(>!2!mm)!at!the!8!study!sites!...........................................................................!126!
Figure!57.!Percent!sand!(62.5!um!\!2!mm)!at!the!8!study!sites!................................................................!127!
Figure!58.!Percent!silt/clay!(fraction!<!62.5!um)!at!the!8!study!sites!.......................................................!127!
Figure!59.!Percent!(by!weight)!total!organic!carbon!at!the!8!study!sites!.................................................!128!
Figure!60.!Percent!(by!weight)!to tal!nitro ge n!at!th e!8!stu dy !sites!...........................................................!128!
Figure!61.!Temperature!(degrees!Celcius)!at!the!eight!study!sites!..........................................................!129!
Figure!62.!Dissolved!oxygen!(mg/mL)!at!the!8!study!sites!.......................................................................!129!
Figure!63.!Macrofauna!indices!for!the!BOEM!dataset!compared!to!depth!.............................................!130!
Figure!64.!Macrofauna!indices!for!the!BOEM!dataset!compared!to!median!grain!size!...........................!130!
Figure!65.!Macrofauna!groups!at!Grays!Bank!as!determined!by!cluster!and!SIMPROF!analyses!............!131!
Figure!66.!Macrofauna!groups!at!Nehalem!as!determined!by!cluster!and!SIMPROF!analyses!................!132!
9
Figure!67.!Macrofauna!groups!as!determined!by!cluster!and!SIMPROF!analyses!at!Newport!................!133!
Figure!68.!Macrofauna!groups!at!Cape!Perpetua!as!determined!by!cluster!and!SIMPROF!analyses!......!134!
Figure!69.!Macrofauna!groups!at!Siltcoos!as!determined!by!cluster!and!SIMPROF!analyses!..................!135!
Figure!70.!Macrofauna!groups!at!Bandon\Arago!as!determined!by!cluster!and!SIMPROF!analyses!.......!136!
Figure!71.!Macrofauna!groups!at!Eureka!as!determined!by!cluster!and!SIMPROF!analyses!...................!137!
Figure!72.!Macrofauna!groups!at!the!Northern!San!Andreas!Fault!site!as!determined!by!cluster!and!
SIMPROF!analyses!....................................................................................................................................!138!
Figure!73.!Macrofauna!groups!in!Washington!state!as!determined!by!cluster!and!SIMPROF!analyses!on !
the!EPA!datas et!........................................................................................................................................!139!
Figure!74.!Macrofauna!groups!in!Oregon!as!determined!by!cluster!and!SIMPROF!analyses!on!the!EPA!
dataset!.....................................................................................................................................................!140!
Figure!75.!Macrofauna!groups!in!northern!California!as!determined!by!cluster!and!SIMPROF!analyses!on!
the!EPA!datas et!........................................................................................................................................!141!
!
List of Tables
!
Table!1.!Metadata!associated!with!the!ROV!stations!and!!"#$%!dives!for!all!three!sites!...........................!18!
Table!2.!Total!count!of!patches!of!each!substratum!type!observed!and!analyzed!at!each!site,!sorted!by!
descending!occurrence!across!all!six!sites!.................................................................................................!20!
Table!3.!Total!number!of!mega\invertebrate!taxa!and!individuals!per!phylum!across!all!sites!in!the!!"#$%!
and!ROV!stations!........................................................................................................................................!21!
Table!4.!General!habitat!codes!determined!by!analysis!of!ROV!and!!"#$%!datasets!.................................!24!
Table!5.!Pairwise!comparisons!and!significance!of!major!groupings!of!substrate!patch!types!into!habitat!
types!based!o n!ide ntity!an d !den sities!of!m eg a\invertebr at es !w it h in!t h e!p a tc h !ty pe s !..............................!24!
Table!6.!Percent!dissimilarity!between!assemblages!characteristic!of!the!hab it at !typ e s !by !th e !S IMPER!
analyses!on!ROV!=%>>"/:"%-!dataset!.....................................................................................................!24!
Table!7.!Within!each!major!habitat!type,!assemblage!characteristics!determined!by!the!SIMPER!analysis!
on!the!ROV!dataset!....................................................................................................................................!26!
Table!8.!Dissimilarities!between!mixed!mud\rock!(Mx)!habita ts!at!Ba nd on \ Arago!(BA)!versus!Grays!
Bank/Siltcoos!(GBSC)!in!the!ROV!surveys!...................................................................................................!26!
Table!9.!Dissimilarities!between!consolidated!rock!(cR)!and!rubble!rock!(rR)!habitat!types!from!RO V!
surveys!.......................................................................................................................................................!27!
Table!10.!Pairwise!comparisons!and!significance!of!major!groupings!of!!"#$%!substrate!patch!types!into!
habitat!types!based!on!identity!and!densities!of!mega\inverteb ra te s!within!pa tc h !ty pe s !........................!29!
Table!11.!Percent!dissimilarity!between!assemblages!characteristic!of!the!habitat!types!by!the!SIMPER!
analyses!on!!"#$%.dataset!..........................................................................................................................!30!
Table!12.!Within!each!major!habitat!type,!assemblage!characteristics!determined!by!the!SIMPER!analysis!
on!the!!"#$%!dataset!...................................................................................................................................!30!
Table!13.!Dissimilarities!of!rock!habitat!types!between!and!within!!"#$%!sites!Siltcoos!(SC),!Bandon\Arago!
(BA)!and!Gra ys!B an k!(G B) !...........................................................................................................................!31!
Table!14.!Depth!and!site!distribution!of!sampling!stations!........................................................................!44!
Table!15.!Habitat!and!diversity!metrics!for!the!eight!BOEM!sites!(upper!table)!and!three!EPA!states!
(lower!table)!...............................................................................................................................................!48!
10
Table!16.!Average!physical!parameters!of!the!two!major!clusters!of!stations!(based!on!macrofaunal!
species!abundances)!in!the!EPA!dataset!....................................................................................................!53!
Table!17.!Species!that!are!abundant!in!one!cluster!but!rare!or!absent!in!the!other!for!the!EPA!dataset!.!55!
Table!18.!Steps!for!calcu lat ing !ex p ec te d !va lue s!(X)!of!nodes!dis play ed !in!Figure!23!................................!78!
Table!19.!Environmental!variables!considered!for!Benthic!Macrofauna!Model!for!Habitat!Suitability!
Analysis!.......................................................................................................................................................!80!
Table!20.!Performance!Metrics!..................................................................................................................!86!
Table!21.!Performance!Metrics!of!HSP!model!for!&'()*+,(-%.,"//(0%$%!....................................................!91!
Table!22.!Performance!Metrics!of!the!HSP!model!for!1))202#%.$")2(,!.....................................................!94!
Table!23.!Performance!Metrics!of!the!HSP!model!for!&3,$/(,.4%2,%+%$%!..................................................!96!
Table!24.!Performance!Metrics!of!HSP!model!for!5%##(%)%'.+30)%!............................................................!99!
Table!25.!Performance!Metrics!of!the!HSP!model!for!6%4"#*)%.7"/8"#"3(!.............................................!101!
Table!26.!Performance!Metrics!of!the!HSP!model!for!9)2+:(,.(/(-",0"),!...............................................!103!
Table!27.!Performance!Metrics!of!the!HSP!model!for!;$"/)%,+(,.<*,,*/!..................................................!105!
Table!28.!Prediction!success!reported!as!a!percent!occurrence!..............................................................!114!
Table!29.!Total!raw!count!of!macroinvertebrate!taxa!across!all!six!sites!in!the!!"#$%!and!ROV!
=%>>"/:"%-!stations!..............................................................................................................................!123!
Table!30.!Distinct!groupings!of!BOEM!sampling!stations!as!determined!by!the!Similarity!of!Profile!
(SIMPRO F)!te st!w ith!ch arac teristics !spe cies !from !th e!SIMPER!test !.........................................................!142!
Table!31.!Distinct!groupings!of!EPA!sampling!stations!and!abundances!of!characteristic!species!as!
determined!by!the!Similarity!of!Profile!(SIMPROF)!test!along!with!characteristic!species!from!the!SIMPER!
test!...........................................................................................................................................................!146!
Table!32.!LINKTREE!analysis!group!letter!code!of!BOEM!stations!............................................................!148!
Table!33.!LINKTREE!analysis!group!letter!code!of!EPA!stations.!..............................................................!150!
Table!34.!Total!abundances!of!all!identified!worm!taxa!at!each!site!.......................................................!153!
Table!35.!Total!abundance!of!all!identified!molluscan!taxa!at!each!site.!.................................................!158!
Table!36.!Total!abundance!of!all!identified!arthropod!taxa!at!each!site!.................................................. !161!
Table!37.!Total!abundance!of!all!‘other’!taxa!at!each!site!........................................................................!163!
Abbreviations and Acronyms
AT&SML Active Tectonics and Seafloor Mapping Lab
BOEM Bureau of Ocean Energy Management
CEOAS College of Earth Ocean and Atmospheric Sciences
CMECS Coastal and Marine Ecological Classification Standard
COR Contracting Officer’s Representative
CSE Council of Science Editors
CTD Conductivity, Temperature, Depth
DOI US Department of the Interior
EFH Essential Fish Habitat
11
EIS Environmental Impact Statement
EPA US Environmental Protection Agency
ESP Environmental Studies Program
ESPIS Environmental Studies Program Information System
FRAM Fisheries Resource Analysis and Monitoring
GIS Geographic Information System
GPS Global Positioning System
HMSC Hatfield Marine Science Center
IMU Inertial Motion Unit
MMI Marine Mammal Institute
MHK Marine Hydrokinetic
MLC Maximum Likelihood Classification
NAMSS National Archive of Marine Seismic Surveys
NGDC National Geophysical Data Center
NMFS National Marine Fisheries Service
NNMREC Northwest National Marine Renewable Energy Center
NOAA National Oceanic and Atmospheric Administration
NSF National Science Foundation
OCNMS Olympic Coast National Marine Sanctuary
OCS Outer Continental Shelf
ODFW Oregon Department of Fish and Wildlife
ONR Office of Naval Research
OSU Oregon State University
PO Project Officer
PMEC Pacific Marine Energy Center
RMS Root Mean Square
ROV Remotely Operated Vehicle
SETS South Energy Test Site
SGH Surficial Geologic Habitat
SWMP State Waters Mapping Program
TPI Topographic Position Index
USGS United States Geological Survey
VRM Vector Ruggedness Measure
WEC Wave Energy Capture
12
4. Patterns of Benthic Mega-Invertebrate Habitat Associations (ROV
Report)
4.1 Introduction and Background
Although the oceans provide a variety of valuable goods and services, societies sometimes fail consider
the damage that such resource exploitation may cause to marine ecosystems over time (Jackson et al.
2001). Examples of anthropogenic impacts and over-exploitations of these ecosystems are numerous, and
hard continental shelves and rocky reefs are among marine ecosystems the most impacted (Lotze et al.
2006; Halpern et al. 2008). Fisheries using bottom gear such as trawls and dredges are by far the most
damaging for the seafloor, acting like forest clear-cutting (Watling and Norse 1998). Due to technological
improvements during the last decades, bottom-fishing gears are now used from polar to tropical waters on
every type of seafloor; only few places on the world’s continental shelves remaining non-impacted
(Watling and Norse 1998; Halpern et al. 2008). Other human uses of the oceans like aquaculture, mining
or tourism activities threaten continental shelf ecosystems (Rossi 2013) and their effects, both direct and
indirect, are synergistic (Jackson et al. 2001; Kaplan et al. 2013). Although the intensity and extent of
effects on seafloor communities by marine renewable energy developments, like wave energy or offshore
wind farms are as yet uncharacterized (Henkel et al. 2014) past studies of oil platforms have shown that
these installations can affect invertebrate communities locally by providing surface for fouling
invertebrates to establish, and in some cases, facilitating species invasions (Page et al. 2006). Wave
and/or wind installations could similarly alter the habitat since they could act as artificial reefs with large
surface area for new colonies of sessile invertebrates to establish (Wolfson et al. 1979). In addition,
bringing new colonies of sessile invertebrates could also alter the ecological niches and change food web
dynamics (Langhamer et al. 2009).
One of the major threats to continental shelf ecosystems is a reduction of habitat complexity and
heterogeneity by damage to or smothering of slow-growing structure-building organisms like sponges or
gorgonians (Watling and Norse 1998; Kaiser et al. 2006; Sheehan et al. 2013), typically found on rocky
outcrop, as well as damage to or sedimentation of a rocky outcrop or reef itself. The preferred wave
energy installation sites are sedimentary habitats with flat or low relief. As currents flow around installed
devices, greater volumes of sediments will be sent into the water column, possibly exposing nearby rocky
habitats to increasing sedimentation. Increasing sedimentation in some coral reefs have shown to exert
negative effects by smothering the colonies, which reduces recruitment, decreases net productivity, and
decreases calcification (Rogers 1990). If the rate of sedimentation on nearby reefs increased due to
offshore installations, this could pose a threat to sponges, gorgonians, and crinoids, as their colonies could
be smothered by increased sedimentation rates. Habitat heterogeneity can be a major driver of variability
in the abundance and diversity of marine species (Benedetti-Cecchi and Cinelli 1995; García-Charton et
al. 2004), supporting global species diversity by increasing niche availability and community complexity
and facilitating the formation of distinct species assemblages (Cerame-Vivas and Gray 1966; García-
Charton et al. 2004; McClain and Barry 2010).
The Pacific Northwest (PNW) continental shelf, especially the northern part (i.e. off Oregon and
Washington), is mostly characterized by mud and gravel habitats, but rocky outcrops and reefs occur in
several areas (Romsos et al. 2007), supporting structure-building invertebrates that increase the habitat
complexity of the seafloor (Strom 2006). This region has a long history of fisheries with a variety of fleets
using bottom gears dedicated to groundfishes, dermersal rockfishes, crabs and shrimps. Moreover, it is
becoming a focus area for offshore wave and wind energy installations on the continental shelf and slope.
However, despite the abundance (and some documentation) of invertebrate bycatch, little is known about
mega-invertebrate assemblages on this part of the continental shelf. Hixon and Tissot (2007) and Hannah
et al. (2010, 2013) compared trawled versus untrawled mud assemblages at two location sites on the
Oregon continental shelf, and Tissot et al. (2007) described the invertebrate and fish assemblages at a
single outer continental shelf reef off Oregon. Only Strom (2006) has summarized the distribution of
13
structure-forming invertebrates at multiple sites along the continental margin off Oregon. Off southern
California, different invertebrate assemblages have been distinguished based on the physical structure of
the habitats: habitats composed of high-relief consolidated rocky outcrops are associated with greater
densities of sessile and structure-forming mega-invertebrates including sponges and gorgonians while
habitats composed of unconsolidated fine sediments are associated with motile mega-invertebrates
including sea stars, crustaceans, bivalves, and sea cucumbers (Allen and Moore 1996; Allen et al. 1997;
Stull et al. 1999; Tissot et al. 2006). Large sized, structure-forming mega-invertebrates such as sponges,
corals, crinoids, and basket stars have been suggested to provide shelter and additional resources for both
fish and other invertebrates by increasing the availability of microhabitats through their large surface area
(Tissot et al. 2006).
4.1.1 Study Purpose and Objectives
The purpose of this study was to distinguish mega-invertebrate communities living on or near
consolidated rocky outcrops across the Pacific Northwest. The objectives of this study were to determine
first if it is possible to distinguish finer resolution habitat differentiation (beyond high-relief and
unconsolidated sediment classification groups) based on substrate types; and second, to characterize the
diversity and composition of mega-invertebrates found in those habitats. We hypothesized that mega-
invertebrate assemblages found on pure mud substrata differ from assemblages found on mud mixed with
rocks (hereafter called mixed mud-rock), which in turn differ from assemblages living in habitats
primarily composed of rocks. Within rocky habitats we hypothesized that the slope of the rock (i.e. flat
versus ridge rock) and the cover (i.e. consolidated rock with a cover of unconsolidated smaller rocks,
hereafter called rubble, versus a cover of sediment veneer or no cover) affect the composition of
associated epifauna. To test these hypotheses, we separately analyzed two sets of underwater video
footage from three different sampling areas along the Washington (Grays Bank) and Oregon (Siltcoos
Reef and Bandon-Arago) coasts, identifying and enumerating the sessile and motile mega-invertebrates
from the images, and characterizing the encountered substratum types. The primary footage analyzed for
this project was collected in 2011-2012 via ROV with a sampling plan purposefully designed to cover a
maximum diversity of available habitats at study sites with regularly spaced stations comprised of three
parallel transects. Additionally, we analyzed footage from the mid to early 1990’s collected via the
submersible Delta, consisting of long dives focused on the sediment and rock structure but not on the
benthic invertebrates inhabiting these reefs, so the speed and the height of the submersible varied which is
not ideal for mega-invertebrate identification and enumeration. The observations from the two studies
thus were not directly compared; we sought to determine if the habitat distinctions and invertebrate
assemblage associations determined via the systematic ROV surveys were similarly distinguished in the
more ‘exploratory’ Delta dives.
4.2 Methods
4.2.1 Study Sites
Our study comprises two series of data: a first series of dives from the early to mid-1990s, and a series of
more recent dives (2011-2012) (Figure 1). In the early to mid-1990s, Oregon State University geologists
surveyed the seafloor at sites from Washington to northern California using a manned-submersible, Delta,
to explore regions of tectonic and faulting activities off Oregon and Washington coast and to visually
confirm and complement the geological structures highlighted by sidescan sonar and seismic reflection
data (Goldfinger et al. 1997). The submersible was equipped with a Hi-8 camera attached on the starboard
side, sizing lasers, depth, and temperature sensors. We reviewed 19 geologic survey dives from three sites
that had not been fully reviewed for invertebrate counts and identification: Grays Bank (GB, n= 4,
offshore of Grays Harbor, Washington, September 1994), Siltcoos Reef (SC, n = 7, offshore of
Charleston, Oregon, September 1995), and Bandon-Arago (BA, n = 8, offshore Bandon, Oregon;
September 1993).
14
Figure 1. Location of the three ROV and Delta study areas
Tracklines are overlain on surficial lithologic habitats on the Pacific Northwest continental shelf, listed with
the number of ROV stations (black lines) and Delta dives (red lines) per site.
In late August 2011 and September 2012, we used the remotely operated vehicle (ROV), Hammerhead, a
modified deep-ocean Phantom, to survey habitat and mega-invertebrates at the same three sites: Grays
Bank (n = 14; Figure 2A) and Siltcoos Reef (n = 10; Figure 2B) in 2011, and Bandon-Arago (n = 12;
Figure 2C) in 2012. For this survey, the Grays Bank stations were on a reef shallower than the one
surveyed in 1994; at Siltcoos Reef, ROV stations were slightly further south but overlapped with the
stations from 1995; at Bandon-Arago, the northern ROV stations were very close to (but shallower) the
stations from 1993 (Table 1). Each ROV station was composed of three transects, each approximately 250
meters long separated 250 meters apart), along which the ROV was kept at a regular speed and a regular
height from the bottom to provide images of good quality to identify and enumerate the mega-
invertebrates. The ROV was equipped with two cameras attached at the front of the ROV: one facing
downward and perpendicular to the sea surface, and the other camera facing outward, angled roughly 30
degrees from the dorsal surface of the ROV. The ROV was equipped with sizing lasers for both cameras,
a CTD that measured depth (meters), temperature (Celsius), and salinity (PSU) continuously, and was
integrated with a navigation system that measured latitude and longitude every second.
15
16
Figure 2. Tracklines of station covered during the ROV surveys at Grays Bank (A), Siltcoos Reef
(B) and Bandon-Arago (C)
The bathymetry color shading is at the same scale for the three maps (red = shallow, green = deep).
4.2.2 Video Analyses
Each video was watched a minimum of three times: one for substratum identification, one for sessile
mega-invertebrate identification and enumeration, one for motile mega-invertebrate identification and
enumeration. Only benthic epifauna and some endofauna taxa showing recognizable body parts above the
sediment were recorded. In the ROV Hammerhead footage, both the outward and downward facing
cameras were used to identify substratum patches and invertebrates. Since one camera faced downward at
a fixed angle from the vehicle, all footage viewed by the downward-facing camera was considered “on-
transect” and this view was used to count the invertebrates. Generally, video analysis followed guidelines
established by Tissot (2008). Each invertebrate entry was accompanied with a time code that was used to
determine in which substratum patch a particular invertebrate was found.
In the Delta videos, the “on-transect” designation was used to lessen the effects of changing transect
widths by variation of seafloor elevations and the height of the submersible off the seafloor with the side-
mounted camera providing an oblique view (Strom 2006). “On-transect” was defined as the seafloor
appearing below the sizing lasers on the screen; thus, substratum patch identification and invertebrate
counts were based on what appeared below the lasers. Substratum patches were identified first then
invertebrates were identified within each substratum patch. Based on the average height of the camera off
the seafloor and the distance between the sizing lasers and the submersible, the transect width for Delta
stations was estimated at 2 meters.
17
Substratum: Substratum patches were identified based on the grain size class and, for consolidated rocks,
relief angle, with the start and end times of each substratum patch recorded. Each substratum patch was
coded with two letters; the first letter indicated the primary substratum (comprising 50-80% of the
duration of the patch) and the second letter indicated the secondary substratum (comprising 20-50% of the
duration of the patch): R for ridge rock (angle >30°), F for flat rock (distinguishable from surrounding
sediment, angle <30°), B for boulder (> 25.5 cm), C for cobble (6.5 – 25.5 cm), P for pebble (2 – 6.5 cm),
G for gravel (4 mm - 2 cm), and M for mud (not distinguished from sand), refined from Stein et al.
(1992). If the substratum patch was comprised of two substrata in equal proportions, the patch was coded
with the first letter indicating the substratum with larger grain size. If a patch was comprised over 80% of
a single substratum type the patch was coded with the same two letters (e.g. MM). See figures in
Appendix 4 for screen grabs of example patch types.
Sessile mega-invertebrate: Sessile invertebrates taller than 5 cm were identified and enumerated, as
recommended by Riedl (1971) and Tissot et al. (2006) because smaller individuals were difficult to see
and identify on the images. Sponges and gorgonians, difficult to identify on video, were characterized
based on their morphology and sometimes color (e.g., branching sponge, shelf sponge, branching red
gorgonian). Encrusting ascidians and bryozoans, impossible to distinguish on video from encrusting
sponges, were all gathered under the name shelf sponge, while possible branching bryozoans were
counted as branching sponges. These two names thus describe a life form more than a systematic group.
Motile mega-invertebrate: Motile invertebrates taller than 5 cm were identified to the lowest possible
taxonomic level and enumerated. Some taxa were only identified to the family or genus level, since many
species in these families / genera have overlapping morphological features and are difficult to distinguish
without specimens to analyze. When the abundance of motile invertebrates was high, one to three
additional viewings were needed to identify and enumerate all the individuals. In the Bandon-Arago (BA)
2012 footage, small orange brittle stars were too abundant to be counted all along each transect and were
only enumerated every 30 seconds.
While reviewing video footage recorded during these two surveys, several identifications were not able to
reach the species level without actual specimens to check and dissect for diagnostic morphological
characters. For example, the different species of the sea star genera Henricia and Solaster are impossible
to differentiate without a clear check of the aboral plates, the adambulacral spines and the pedicellariae
(Lambert 2000; C. Mah, pers. comm.); thus all the encountered individuals were listed as Henricia sp.
and Solaster sp. respectively. Species identification is nearly impossible on video and still images for
organisms like sponges, as shapes vary a lot within a species and sponges are usually identified on the
structure of their spicules. In the present work, all round-shaped sponges were gathered as a morphologic
group under the name “ball sponges”, except a common yellow one, which was called “yellow ball
sponge” and could be related to the species Tethya aurantia or T. californiana. The branching and
encrusting organisms were difficult to enumerate and discriminate between sponges, bryozoans, and
colonial ascidians (in the case of encrusting organisms). All the encountered individuals were counted by
tufts (for branching forms) or patches (for encrusting forms) and gathered as functional groups under the
names “branching sponge” and “shelf sponges” respectively, even if these groups included more than just
sponge species. These taxonomic limits do not allow us to be extremely precise on the identity of some of
the characteristic species for each assemblage but it gives an idea of the type of organisms and could
encourage going back to those habitats to sample these organisms, particularly the sessile invertebrates,
and identify them to species.
4.2.3 Segment Area and Taxon Density
The ROV Hammerhead was integrated with a navigation system that was used to calculate the transect
width and approximate the distance traveled every second (ranging from 0.001 to 1.36 meters traveled in
a second, depending on speed of the ROV and the support vessel). Based on the transect width per second
(dependent on the height of the ROV above the seafloor) and the distance it traveled from the previous
18
second, the transect area covered was determined for every second. Therefore, the area of each substratum
patch was calculated by adding all area entries from one second after the start time of the segment to the
end time of the patch. The density (individuals/m
2
) of each taxon per substratum patch was calculated by
dividing the sum of a particular invertebrate taxon count by the total area the ROV had covered along this
substratum patch. The Delta was not equipped with a navigator beam so the area covered by each
substratum patch was derived from the average speed of 0.75 knots, or 0.38 m.s
-1
(Strom 2006). The
transect width being fixed at 2 m, the substratum patch area was calculated by multiplying the total time
of the segment by the average speed and the patch width. The density of each invertebrate taxon per
substratum patch was then calculated as the number of each invertebrate taxon divided by the patch area.
4.2.4 Statistical Analyses
Analyses were performed for the Delta and ROV Hammerhead datasets separately. The sample units
considered here were the different patch types in a whole site: data from all the same substratum patches
were pooled at the site level. Only patch types observed longer than one minute in total for a whole site
were kept in the analyses. A matrix of Bray-Curtis similarities between patch types was calculated on log-
transformed density (# individuals/m
2
) data. Nonmetric multidimensional scaling (nMDS), analyses of
similarities (ANOSIM), SIMPER, and DIVERSE were performed using PRIMER 6
th
Edition (Clarke and
Gorley 2006). The nMDS analysis plotted sample units (patch types) on a two-dimensional ordination
plane based on taxa composition similarities and dissimilarities. Groups of patch types (hereafter ‘habitat
types’) were discerned from the nMDS plot and an ANOSIM was performed to test the strengths of
similarities within and differences between these habitat type groups, using permutation and
randomization methods on the resemblance matrix. SIMPER (Similarity of Percentage) was used to
determine which taxa and their densities contributed to defining each group and the percent contribution
of each defining taxon. DIVERSE was used to calculate the diversity indices (average number of taxa S,
average density N, Pielou’s evenness J’) on the untransformed abundances for each habitat group, and a
series of ANOVAs and Tukey’s HSD tests was performed in the open-source software R (R Development
Core Team 2013) to test whether or not the indices were significantly different among habitat groups.
4.3 Results
4.3.1 Site Characteristics
The six sites showed slightly different physical characteristics (Table 1). Bandon-Arago (BA) 2012 and
Grays Bank (GB) 2011 were the shallowest, while Grays Bank 1994 was the deepest and the three others
were at a similar depth range. The temperature was the coldest at the northern deep stations (GB 1994).
The temperature at SC was colder in 1995 than in 2011 and the same trend was observed at BA. The
salinity was not recorded during the Delta dives but no bathymetric or latitudinal variation in salinity was
noticed in the ROV surveys.
Table 1. Metadata associated with the ROV stations and Delta dives for all three sites
GB = Grays Bank, SC = Siltcoos Reef, BA = Bandon-Arago. Average duration (n) is the average time per
transect for the ROV data and per dive for the Delta data with the total number of transects/dives.
Depth (m)
Temp. (°C)
Salinity (PSU)
Avg. duration (n)
Total area surveyed
Year
ROV
GB
55 - 82
7.25 - 7.33
33.76 - 33.83
13:48 ± 02:46 (42)
225,321 m
2
2011
SC
97 - 119
7.75 - 7.92
33.84 - 33.88
17:49 ± 04:46 (30)
213,043 m
2
2011
BA
54 - 68
8.29 - 8.94
33.72 - 33.78
17:59 ± 03:11 (36)
147,607 m
2
2012
Delta
GB
167 - 204
6.45 - 6.61
-
85:18 ± 15:38 (4)
13,074 m
2
1994
SC
108 - 120
7.39 - 7.42
-
86:05 ± 24:15 (7)
23,175 m
2
1995
BA
85 - 116
7.75 - 8.11
-
86:27 ± 35:45 (8)
25,363 m
2
1993
19
Figure 3. Proportion of substratum patch types per study site
A total of 18 and 28 different substratum patch types were identified in the Delta and ROV stations
respectively. Considerably greater areas were covered by the ROV surveys (Table 1), contributing to the
greater numbers of patch types observed. From 8 to 19 substratum patch types were found per site;
however depending on the site, up to eight substratum types were not analyzed because of durations
shorter than a minute. The fewest different substratum patch types were observed and analyzed at Siltcoos
Reef in both years (5, 6), intermediate patch type diversity was observed and analyzed at Grays Bank in
both years (12, 11), and the greatest numbers of substratum patch types were observed and analyzed at
Bandon-Arago in both years (14, 17) (Table 2). Substratum types that were found in large proportion
across all sites were ridge rock-mud (average = 30%), mud-mud and flat rock-mud (average = 19% each),
and ridge rock-ridge rock (average = 14%) (Figure 3). Twelve substratum types were found only once
across all six sites, like cobble - gravel found only at BA 2012; four of these lasted less than a minute and
were removed before the analyses.
20
Table 2. Total count of patches of each substratum type observed and analyzed at each site,
sorted by descending occurrence across all six sites
Substratum patch types are shown as two letter codes in first column and survey across the top. The
fewest different substratum patch types were observed at Siltcoos Reef (SC) in both years (5, 6). The
most diversity of substratum patch types was observed at Bandon-Arago (BA) in both years (14, 17).
Patches seen for less than one minute are excluded.
GB 1994
GB 2011
SC 1995
SC 2011
BA 1993
BA 2012
RM
76
146
390
125
281
80
FM
21
108
36
35
183
213
RR
27
107
3
172
50
2
MM
68
71
12
101
22
37
BM
-
-
-
-
-
145
MG
-
72
-
-
-
17
MC
44
-
-
-
17
25
RB
3
3
27
8
21
-
CM
-
-
-
-
1
54
MB
11
-
-
-
4
34
FB
-
-
-
1
44
-
RP
7
3
-
-
30
-
FP
-
-
-
-
35
-
MP
7
3
-
-
-
21
RC
4
6
-
-
13
-
FC
-
-
-
-
22
-
GM
-
8
-
-
-
9
PM
-
-
-
-
-
13
RG
3
8
-
-
-
-
FF
-
-
-
-
6
-
CB
-
-
-
-
-
4
FG
4
-
-
-
-
-
CG
-
-
-
-
-
3
PB
-
-
-
-
-
3
BC
-
-
-
-
-
2
PG
-
-
-
-
-
2
B = boulder, C = cobble, F = flat rock, G = gravel, M = mud, P = pebble, R = ridge rock.
4.3.2 Community Structure
A total of 91 taxa representing eight phyla were found across all six sites (Table 3 and Appendix 4), with
more taxa recognized and individuals counted in footage from the ROV survey than the Delta survey. The
phyla Porifera, Echinodermata and Cnidaria together comprised over 91% of all the invertebrates
encountered in the ROV survey and over 99% in the Delta survey, Echinodermata being the most
abundant in ROV and Porifera in Delta (Table 3). Porifera and Echinodermata were the most abundant at
21
BA (both years), the high numbers of Echinoderms driven by many Florometra serratissima observed in
1993 and the highly abundant small orange brittle stars and greater numbers of small sea cucumbers
observed in 2012; cnidaria were the most abundant at GB 2011 (Figure 4).
Table 3. Total number of mega-invertebrate taxa and individuals per phylum across all sites in the
Delta and ROV stations
Includes total counted (n = 252,884) and each phylum’s percent contribution to the total count; details of
taxa are given in Appendix 4.
Taxon
GB
1994
GB
2011
SC
1995
SC
2011
BA
1993
BA
2012
Total
%
ANNELIDA
N taxa
0
0
0
0
0
2
2
N individuals
0
0
0
0
0
83
83
0.03
ARTHROPODA
N taxa
3
8
3
6
0
8
9
N individuals
140
698
14
5388
0
102
6342
2.51
CHORDATA
N taxa
1
1
1
1
1
1
1
N individuals
1
212
1
48
4
1976
2242
0.89
CNIDARIA
N taxa
6
13
8
10
8
11
17
N individuals
1754
12592
3307
5133
6285
6736
35807
14.16
ECHINODERMATA
N taxa
16
22
18
26
17
24
32
N individuals
3178
8562
2625
14043
40522
31249
100179
39.61
MOLLUSCA
N taxa
2
12
1
6
1
10
12
N individuals
4
257
5
90
1
2543
2900
1.15
NEMERTEA
N taxa
0
1
0
1
0
1
1
N individuals
0
12
0
5
0
4
21
0.01
PORIFERA
N taxa
7
11
7
7
6
13
17
N individuals
2797
5561
1232
6692
52598
36430
105310
41.64
GRAND TOTAL NO. OF TAXA
91
GRAND TOTAL NO. OF INDIVIDUALS
252884
22
Figure 4. Abundances of benthic macroinvertebrate phyla at the study sites
4.3.2.1. Assemblages Inferred from the ROV Hammerhead Dataset
Based on their taxa composition, six habitat types (groups of patch types hosting similar invertebrate
taxa) were identified on two ordination plans of the nMDS for the ROV dataset (Figure 5). The groups
(hereafter ‘habitat types’) were mostly organized by substratum characteristics (e.g. pure mud, mixed
mud-rock, consolidated/rubble rock) and subsequently by sites. Unconsolidated sediment patches from
the sites split into three groups: group MM-GBSC consisted of pure mud (not distinguished from sand)
patches from GB and SC; group Mx-GBSC was made of mixed mud-rock patches from GB and SC; and
group Mx-BA gathered pure and mixed mud-rock patches from BA only. Rock-based patches clustered
into two main groups: cR made of consolidated rocks, both bare and covered with a veneer of mud (BM,
FM, RM, RR), from the three sites; and group rR made of rubble rocks (e.g. BC, FB, RG) from the three
sites. Group PG (pebble-gravel), is a patch type found only at BA in a single transect and will not be
discussed further. Table 4 identifies which substratum patch types are grouped into each of the five
described habitat types.
The ANOSIM performed on these six groups demonstrated significant differences in the taxa
compositions overall between the habitat types (Global R statistic = 0.700, with a significance level of
0.1%). In the pairwise test, comparisons were considered reliable when more than ten permutations were
possible. Nine of the 12 possible pairwise comparisons showed significant differences between groups
(Table 5). The non-significant pairwise comparisons were MM-GBSC vs. Mx-GBSC (6.7%) and PG vs.
other groups. However, this was not surprising because of the low number of permutations possible for
these pairwise comparisons. Despite these few non-significant ANOSIM comparisons, the SIMPER
analysis gave a high percent of dissimilarity between each pairwise comparison, ranging from 70.81% to
99.47% of difference in the taxa composition of the groups (Table 6). Significant differences also were
found among the various habitat types based on the univariate analyses of number of taxa (S), density
(N), and evenness (J’) (Figure 6).
23
Figure 5. Two-dimensional nonmetric multidimensional scaling (nMDS) ordination of the patch
types based on invertebrate community data from the ROV Hammerhead survey forming 4 distinct
habitat types (MM, Mx, cR, rR) with some site differences resulting in 6 total groups
Groups distinguished with dotted lines were tested using ANOSIM to investigate within group similarity
and between group dissimilarities. MM = pure mud at Grays Bank and Siltcoos Reef, Mx-GBSC = mixed
mud-rock at Grays Bank and Siltcoos Reef, Mx-BA = mixed mud-rock at Bandon-Arago, cR =
consolidated rocks, rR = rubble rocks, PG = pebble – gravel (found only at BA).
24
Table 4. General habitat codes determined by analysis of ROV and Delta datasets
The two-letter code patch types that are aggregated into each of the habitat codes are listed along with a
general description of the habitat type.
Habitat
Code
Substrate Types
Included
Description
MM
MM
Pure mud/sand (distinct at Grays Bank and Siltcoos, not a unique
habitat at Bandon-Arago) for Delta and ROV sites.
Mx
MG, MP, MC, MB, GM,
PM, CM
Mud mixed with small rocks or boulders (when mud primary) for
Delta and ROV sites. BA distinguished from GB & SC.
cR
FM, RM, RR, BM
Consolidated rock (flat or ridge), bare or covered with a thin layer
of sediment, includes BM (boulders primary) for ROV sites
rR
RG, RP, RC, RB, FB,
PB, CB, CG, BC
Rubble rocks, includes mixed smaller rocks (e.g. gravel, pebble)
as well as consolidated rock (flat and ridge) and boulders covered
with smaller rocks for ROV sites
R/F-BA
RR, RM, RP, RC, RB,
FF, FM, FP, FC, FB,
All patch types with consolidated rock (ridge or flat) as primary
substrata for Delta observations at Bandon-Arago
R/F-SC
FF, RM, RB, FM
All patch types with consolidated rock (ridge or flat) as primary
substrata for Delta observations at Siltcoos
R-GB
RR, RM, RG, RP, RC,
RB
All patch types with ridge rock as primary substrata for Delta
observations at Grays Bank
F-GB
FM, FG
All patch types with flat rock as primary substrata for Delta
observations at Grays Bank
Table 5. Pairwise comparisons and significance of major groupings of substrate patch types into
habitat types based on identity and densities of mega-invertebrates within the patch types
ANOSIM performed on the habitat types (Table 4) derived from the nMDS analyses of patch types of
ROV Hammerhead dataset (Figure 5). Upper matrix is the R-values of the test; lower matrix is the
associated p-value (in percent). Pebble Gravel group (PG) was excluded from ROV dataset because the
habitat type represented a single group.
ROV
Global R = 0.700
p \ R
cR
Mx-BA
rR
MM
Mx-GBSC
cR
0.337
0.829
0.828
0.892
Mx-BA
0.5
0.548
1
0.921
rR
0.1
0.1
0.994
0.692
MM
1.5
2.2
1.3
0.714
Mx-GBSC
0.1
0.2
0.3
6.7
Table 6. Percent dissimilarity between assemblages characteristic of the habitat types by the
SIMPER analyses on ROV Hammerhead dataset
ROV
cR
Mx-BA
rR
MM
Mx-GBSC
Mx-BA
70.81
rR
90.47
77.74
MM
91.91
93.54
95.64
Mx-GBSC
95.24
93.18
86.17
93.33
PG
99.47
98.37
96.38
99.19
93.90
25
Figure 6. Diversity indices (mean ±SD) for each habitat type and membership from the Tukey test
for ROV sites (left) and Delta sites (right)
Top left = ROV’s number of species (ANOVA p-value < 0.001), mid left = ROV’s density (ANOVA p-value
= 0.007), bottom left = ROV’s Pielou’s evenness (ANOVA p-value = 0.003), top right = Delta’s number of
species (ANOVA p-value = 0.072), mid right = Delta’s density (ANOVA p-value = < 0.001), bottom right =
Delta’s Pielou’s evenness (ANOVA p-value = 0.005).
While there were no significant differences in diversity or density of organisms (Figure 6) among the
identified mud habitats (pure versus mixed mud-rock from the various sites), we did detect some trends
and were able to identify what members of the assemblages distinguished them. Pure mud at GB & SC
(33 % similar) showed a medium number of taxa and a high density of individuals with a significantly
lower Pielou’s evenness than all the other habitat types. Pure mud habitat was characterized by high
density of burrowing brittle stars and Subselliflorae (sea whips). Mixed mud-rock habitats at GB and SC
showed lower number of taxa and density of individuals than the same habitat types at BA and were
characterized by medium to high abundance of anemones and low abundance of sponges with the lowest
within group similarity (16 %; Table 7). Mixed mud-rock habitats at BA (which included pure mud at this
site; patches 46 % similar) showed a medium number of taxa, a low density of individuals (Figure 6) and
were characterized by many of the same taxa as the consolidated rocks (minus the anemones and squat
lobsters) but in much lower densities. What made the two mixed mud-rock assemblages 93.18%
dissimilar (Table 6) was the higher density of several echinoderm species (particularly the previously
mentioned small orange brittle stars and sea cucumbers as well as sea stars), sponges, branching
gorgonians and tunicates at BA than GB and SC, and a higher density of sea anemones at GB and SC than
BA (Table 8).
26
Table 7. Within each major habitat type, assemblage characteristics determined by the SIMPER
analysis on the ROV dataset
% Sim = percent of similarity of patches within a habitat type, Av den = average density of the taxon
within that habitat type, Cum % = cumulated percent of contributions of the species to the characterization
of a the habitat type.
Habitat Type
% Sim
Species
Av den
Cum %
Pure Mud
(MM-GBSC)
32.88
Burrowing brittle star
2.57
63.59
Subselliflorae
1.13
85.48
Mixed mud-rock
GB & SC
(Mx-GBSC)
16.03
Stomphia coccinea
0.28
30.86
Metridium farcimen
0.09
49.84
Urticina spp.
0.11
68.74
Shelf sponge
0.02
81.94
Mixed mud-rock
BA (Mx-BA)
46.03
Shelf sponge
1.00
35.91
Branching sponge
0.52
49.01
Small orange brittle star
0.51
58.79
Mediaster aequalis
0.24
65.91
Branching red gorgonian
0.26
72.63
Parastichopus californicus
0.23
78.95
Cucumaria spp.
0.14
82.73
Consolidated
Rocks
(cR)
37.13
Shelf sponge
1.60
19.34
Branching sponge
1.56
31.93
Branching red gorgonian
1.35
44.46
Small orange brittle star
1.57
54.28
Metridium farcimen
0.72
61.28
Parastichopus californicus
0.57
66.58
Munida quadrispina
0.50
71.81
Mediaster aequalis
0.56
75.70
Foliose sponge
0.62
78.59
Henricia spp.
0.42
81.40
Rubble Rocks
(rR)
35.83
Shelf sponge
0.22
56.68
Parastichopus californicus
0.05
71.67
Branching sponge
0.04
82.04
Table 8. Dissimilarities between mixed mud-rock (Mx) habitats at Bandon-Arago (BA) versus
Grays Bank/Siltcoos (GBSC) in the ROV surveys
Av den = average density of the species within a particular rock habitat type and Cum % = cumulated
percent of contribution of the species in the dissimilarity between the two rock habitat types
Average dissimilarity = 93.18
Species
Mx-BA
Av den
Mx-GBSC
Av den
Cum %
Shelf sponge
1.0
0.0
24.2
Branching sponge
0.5
0.0
34.7
Small orange brittle star
0.5
0.0
44.4
Stomphia coccinea
0.0
0.3
50.7
Branching red gorgonian
0.3
0.0
56.2
27
Mediaster aequalis
0.2
0.0
61.5
Parastichopus californicus
0.2
0.0
66.3
Metridium farcimen
0.1
0.1
70.1
Urticina spp.
0.1
0.1
73.4
Cucumaria spp.
0.1
0.0
76.4
Foliose sponge
0.2
0.0
79.4
Transparent tunicate
0.2
0.0
82.4
Table 9. Dissimilarities between consolidated rock (cR) and rubble rock (rR) habitat types from
ROV surveys
Av den = average density of the species within a particular rock habitat type and Cum % = cumulated
percent of contribution of the species in the dissimilarity between the two rock habitat types
Percent dissimilarity = 90.47
Species
cR
Av den
rR
Av den
Cum %
Shelf sponge
1.60
0.22
12.07
Small orange brittle star
1.57
0.01
22.88
Branching sponge
1.56
0.04
33.19
Branching red gorgonian
1.35
0.03
42.39
Munida quadrispina
0.50
0.03
48.06
Metridium farcimen
0.72
0.03
53.49
Parastichopus californicus
0.57
0.05
57.28
Foliose sponge
0.62
0.01
61.00
Mediaster aequalis
0.56
0.01
64.57
Single stalk red gorgonian
0.38
0.00