Marine Science Institute

University of California Santa Barbara

Who we are

Robert Miller, David Siegel, Craig Carlson, Daniel Reed, BS

Manjunath, Deborah Iglesias-Rodriguez, Doug McCauley, Milton Love

Principal/Associate Investigators

UCSB

Florida State University

USGSKevin Lafferty

UCSD - SIO

John Hildebrand

Andrew Thompson

NOAA – NMFS SWFSC

Andrew Rassweiler

Partners

Plumes and Blooms (NASA)

BOEM Pacific Region

Santa Barbara Coastal LTER (NSF)

Channel Islands National Marine Sanctuary

Southern California Coastal Water Research Project

Southern California Coastal Ocean Observing

System (SCCOOS)

Channel Islands National Park

Gray Whales Count

CalCOFI

1. Provide data to inform managers and society about

patterns of biodiversity across taxa, space, and time

• Integrate existing data

• Develop new methods & products

2. Build a framework to facilitate MBON development under

diverse circumstances

MBON Prototype:

Progress, by Taxonomic Group

Measurement Class:

D: Occurrence (EBV “distribution”)

A: abundance or density (EBV “abundance”)

Focus on time series oldest: 35 yrs youngest: 18 yrs

14 Data packages published

stable, immutablewith DOI

Spanning taxa from microbes to whales

Net Environmental Benefit Analysis of offshore platform decommissioning alternatives

Users:

– US Bureau of Ocean Energy Management

– CA State Lands Commission

– Petroleum industry (e.g. Exxon, Chevron, Venoco)

Leave in

place Partial

Removal

Total

Removal

Meyer-Gutbrod et al., in prephttps://meyer-gutbrod.shinyapps.io/Decommissioning_WebApp/

• Platform structures are dominated by rockfish

• If removed, sites will return to mud inhabited by soft bottom species such as flatfish

• Removal of 24 platforms will result in the loss of 28,700 kg of fish biomass, and an additional loss of 4,700 kg of annual fish production

Comparing platform decommissioning scenarios

Meyer-Gutbrod et al. In prep.

Webinization of Condition Reports

How does biodiversity affect ecosystem function and

stability?

However, most empirical and theoretical studies which have investigated ecological

variability and its relation with biodiversity have focused on local scales

Understanding the factors that dampen variability of biomass production is

a core concept of Ecology

Species diversity begets stability

Asynchronous species

dynamics trumped

asynchronous spatial

dynamics to stabilize

metacommunity

biomass in the kelp

forest understory

10

Real-world ecosystems are complex: from populations of single species to

multi-species communities to metapopulations and metacommunities

Lamy et al. 2019, Ecology, Wang et al. 2019, Ecography

Recommendation: data

integration and management

needs science involvement

Typical machine learning

Engineer required

throughout

Time consuming

(months)

Only works on

specific type of

dataTrain & test

Select classifier

Select features

Images

annotations

BenefitsGeneralizes to your data

Fully automated - no feature selection

High accuracy

LeveragesScalable services

Annotation system

Cluster processing

Fast classification on GPUs

Deep learning

New Products: Deep learning for image analysis

|

Image management & annotation |

Model building & usage |

Identification & segmentation|

Recommendation: machine

learning requires time but

saves work in the long run

New Products: AcousticsAcoustic Detection of Marine Mammals

Blue Whale

D-callT

ota

l D

ete

ctio

ns p

er W

ee

k

Jul09 Jan10 Jul10 Jan11 Jul11 Jan12 Jul12 Jan13 Jul13 Jan14 Jul14 Jan15 Jul15 Jan16 Jul16 Jan170

1.1288

2.2577x 10

4

0

50

100

Pe

rce

nta

ge

of

Eff

ort

pe

r W

ee

k

Tota

l D

ete

ctio

ns p

er

We

ek

Jul09 Jan10 Jul10 Jan11 Jul11 Jan12 Jul12 Jan13 Jul13 Jan14 Jul14 Jan15 Jul15 Jan16 Jul16 Jan170

9937.5

19875

0

50

100

Pe

rce

nta

ge

of

Eff

ort

pe

r W

ee

k

Site H

Site N

Seasonal patterns of blue whale song

New Products: Remote SensingPhytoplankton functional diversity

Phytoplankton pigment community clusters define five clusters

Catlett and Siegel, 2018.

Bio-optically modeled PFTs give us the links to PACE/ESBG

350 400 450 500 550 600 650 700Wavelength [nm]

-0.02

-0.01

0

0.01

0.02

0.03

0.04

a' p

h(6

) coe

ffic

ients

[A

(6)]

fo

r F

uco

(a)Mean95% C.I.

350 400 450 500 550 600 650 700

Wavelength [nm]

-0.05

-0.04

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.04

a'' p

h(6

) co

eff

icie

nts

[B

(6)]

for

Fu

co

(b)

Prediction of fucoxanthin

(diatom marker) from

optical derivative spectra

Works well - r2 = 0.86

Similar performance for

other marker pigments’

Requires info from the

entire spectrum

Bio-Optical Model Extends Biomarker Pigment Time Series

*Catlett et al., in prep.

Model Retrievals R2

TChlb (green algae) 0.815

HexFuco (haptophytes) 0.733

Fuco (diatoms) 0.856

Perid (dinoflagellates) 0.887

Zea (picoplankton) 0.541Pigment EOF Mode 1 (Early

upwelling mixed bloom) 0.884Pigment EOF Mode 2

(Diatoms vs. mixed nano-/pico-plankton) 0.852

Pigment EOF Mode 3 (Pico-plankton vs. haptophytes) 0.454

Pigment EOF Mode 4 (Dinoflagellates vs. mixed

diatoms/haptophytes) 0.809

PFTs and Climate• Investigating PFT associations with climate

1997-2015

• SBC dinoflagellate blooms associated with low or negative NPGO + MEI

• Hypothesis: climate-driven variations in surface-ocean circulation drive variations in PFTs– Low/negative NPGO = weaker equatorward

flows in Cal Current, dino-rich SoCal Bight waters can be transported North into SBC to seed blooms

– Low/negative MEI = weak El Nino/La Nina provides favorable conditions for dinoblooms

*Catlett et al. preliminary

97 99 01 03 05 07 09 11 13 15

Year

-2

-1

0

1

2

3

NP

GO

/ME

I

0

1

2

Peri

din

in

NPGO

MEI

Perid

PFTs and Surface Ocean Circulation

• ROMS particle trajectory modeling used to quantify water mass origins for each PnB cruise

• Particles released back in time from the PnB transect (red), count how many originated in each box (blue)

• ~30% increase in proportion of particles from Box 7 for dino blooms relative to diatom or no bloom

• (Climate-driven) surface ocean circulation may be important in biodiversity monitoring

*Catlett, Siegel, Simons, et al, preliminary1 2 3 4 5 6 7 8

Origin Box Number

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

Diffe

ren

ce

in

Pro

po

rtio

n o

f P

art

icle

s

Dino minus no bloom

Diatom minus no bloom

15 day advection time

Dino-rich SoCal

Bight

Diatom-rich Cal.

Current

Formation, Development, and Propagation of a

Coastal Coccolithophore Bloom

VIIRS 2015-06-05

Matson et al. (in press) JGR Oceans

No

bloom

Growing

Bloom

Senescing

Bloom

Genomic Links with Pigment PFTs + Bio-optics

• Correspondence is found in genomic & pigment PFTs

• Seasonality evident in PFTs

• Work on-going to pull apart the Eukgenomic data

*Catlett et al., preliminary

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8Seq. Rel. Abundance (Bacillariophyta)

-2

0

2

Lo

g1

0(F

uco

Co

nce

ntr

atio

n)

0

0.5

1

Dia

tom

% C

HL

(C

HE

MT

AX

)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8Seq. Rel. Abundance (Dinophyta)

0

0.5

Pe

rid C

oncen

tration

0

0.5

Din

ofla

ge

llate

% C

HL

(C

HE

MT

AX

)

Genomics Pigments

Fall-Winter

Spring

Upwelling

Spring Bloom

Summer-

Fall

Fall-

WinterSpring Upwelling

Spring

BloomSummer-

Fall

Recommendation:

Determine remotely sensible

and validated PFTs

New Products: Remote Sensing

a.

b.

c.

Min

imu

m

Em

erg

en

ce

Ag

e (

d)

Chl:C

(mg

mg

-1)

Bio

ma

ss

(kg

m-2

)

April June August+

500 m

Kelp condition, age, and forest extent

Bell & Siegel in prepBell et al. L&O 2018

PIs: Siegel, Bell, Cavanaugh, Miller, Nidzieko, Nelson, Reed

Aerial extent: color imagery

NIR

Re

flecta

nce

(Bio

ma

ss)

Low

High

Bell et al. in prep

Biomass and condition: multispectral

25

Giant kelp creates a diverse ecosystem

Lamy et al. Ecology in review

Giant kelp increases biodiversity through physical engineering

Giant kelp stability indirectly stabilizes the community via its effect on biodiversity

Miller et al. 2018, Proc. Royal Soc. B.,Castorani et al. 2018 Ecology

Recommendation: focus on

dynamics of foundation

species (best with RS!)

New Products: GenomicsMicrobial diversity & community structure

Eu

rya

rch

ae

ota

: M

ari

ne

Gro

up

II

Th

au

ma

rch

ae

ota

: N

itro

so

pu

milu

s

Ac

tin

ob

acte

ria:

OC

S1

55

Fla

vo

ba

cte

ria

: P

ola

rib

ac

ter

Fla

vo

bac

teri

a:

NS

4

Fla

vo

bac

teri

a:

NS

5

De

ferr

ibac

tere

s:

SA

R4

06

SA

R11 S

urf

ace

1

SA

R11 S

urf

ace

2

SA

R11

De

ep

1

Ro

se

ob

ac

ter

NA

C11

-7

Ro

se

ob

ac

ter

DC

5-8

0-3

Ro

seo

ba

cte

r O

CT

Oth

er

Rh

od

ob

ac

tera

ce

a

OC

S11

6

SA

R11

6

Nit

ros

pin

a

SA

R32

4 (

Ma

rin

e g

rou

p B

)

SA

R9

2

OM

60(N

OR

5)

Ps

eu

do

sp

iril

lum

SA

R8

6

Verr

uc

om

icro

bia

: M

B11C

04

Oth

er,

<0

.1%

-10

-5-5

-4

-3

-2

-1

0

1

2

35

10

Lo

g2-f

old

rati

o t

o e

xp

ecte

d

V4

V4-5 V3-4

V1-2

Alphaproteobacteria Deltaproteobacteria Gammaproteobacteria

Mock community deviation from expected

abundance with four different primer sets:

Ordination plots of the same marine time-series

samples sequenced with four primer sets

Wear et al. 2018

Phytoplankton Genomics Method Validation

• Mock communities revealed unexpected issue with common methods

• Outliers correspond to specific primer indices used for sample multiplexing that dramatically reduce accuracy + precision

*Catlett et al., 2019, submitted, Environmental Microbiology

Rela

tive A

bundance

Recommendation: method

validation is critical for

genomic surveys

Environmental DNA captures the fine scale and hierarchical

spatial structure of kelp forest fish communities

Spatially stratified sampling of 49 water samples on 27

transects across 11 rocky reefs

Sheephead

Senorita

Blacksmith Garibaldi

Visual Survey

(2001-2019 SBC

LTER)

eDNA

(12S)

Kelp bass

Leopard sharkLingcod

Japanese pilchard

Engraulis spp.

White shark

Barred

surfperch

Lizardfish

Lamy et al., in prep.

Lafferty et. al 2018, Frontiers Mar. Sci.

eDNA and Acoustic Telemetry Detection of Great White Sharks

Recommendation: eDNA

useful especially for known

targets

For each method:- Rarify biodiversity to 100

individuals observed - Calculate associated

confidence intervals (CI)- Uncertainty is CI/mean

Uncertainty-effort curves:- Randomly subsample

replicates- Calculate expected CI

and uncertainty

0D = Richness, 1D ≈Shannon Diversity, 1D ≈Simpson Diversity

Information about biodiversity

management actions and outcomes

Sampling method 2

Sampling method 1

Comparing the efficiency of alternative methods of monitoring biodiversity

Biodiversity information:status of rare speciesrichness and evennessTrends in abundanceSpatial patterns of diversity

√

0D(richness)

1D(~Shannon)

2D(~Simpson)

Pow

er t

o d

etec

t 2

5%

ch

ange

in b

iod

iver

sity

Sampling Effort (diver hours)

Compare power to detect change:

0D(richness)

1D(~Shannon)

2D(~Simpson)

Un

cert

ain

ty (

CI/

mea

n)

Sampling Effort (diver hours)

Compare sampling efficiency across methods:

Program Development

Recommendation: MBON

support should be

competitive but predictable

SBC MBON: by the numbers

• Publications: 47

• Undergraduate Students: 67

• Graduate students: 17

• Postdocs: 7