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Deep-Sea Research I 53 (2006) 1044–1060
www.elsevier.com/locate/dsr
Spatial patterns of zooplankton and nekton in a hydrothermally
active axial valley on Juan de Fuca Ridge
Kristina Skeboa, Verena Tunnicliffea,, Irene Garcia Berdealb, H. Paul Johnsonb
a
Department of Biology, University of Victoria, P.O. Box 3080, Victoria, BC, Canada V8W 3N5
School of Oceanography, University of Washington, PO Box 357940, Seattle, WA 98195-7940, USA
b
Received 20 June 2005; received in revised form 1 March 2006; accepted 21 March 2006
Available online 23 May 2006
Abstract
Zooplankton and nekton at 2000 m depth in the axial valley of Endeavour Segment, Juan de Fuca Ridge, show marked
variability in abundances in a plane at 20 m above bottom. A remotely operated vehicle flew a gridded rectangle
3.2 0.5 km that included two large high-temperature and two small low-temperature vent fields. Numbers of
zooplankton, jellyfish, shrimp and fish were recorded with a video camera, and the abundance patterns were examined
with the program SADIEr. Each organism group displayed a distinctive distribution pattern. Abundance gaps over the
high-temperature fields were significant and, for the more abundant copepods, were related to the locations of individual
smokers. Pelagic shrimp and macrourid fish abundances were correlated and concentrated around the northern high
temperature field. Distinct aggregations of zooplankton and nekton were correlated with the fluid indicators from both the
low temperature diffuse effluent and the focused high temperature vents. Patterns were likely established by organism
choice that forms aggregations and gaps, and by physical processes that entrain passive particles near vigorous smoker
plumes. While enhanced plankton and nekton numbers were not observed over the vent fields, overall abundances in the
axial valley may be sustained by production transported from the vent fields on the seafloor.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: Plankton patterns; Horizontal profile; Hydrothermal vents; Axial valley; Endeavour Segment; Juan de Fuca Ridge
1. Introduction
Fluids from hydrothermal vents enter seawater
through a range of conduits that vary from focused
flows emitted from high-temperature vents to
diffuse flows from low-temperature sources. The
neutrally buoyant plumes that overlie the axial high
temperature vents have attracted many studies
related to their physical and chemical behaviour,
Corresponding author. Tel.: +1 250 721 7135;
fax: +1 250 721 7120.
E-mail address: [email protected] (V. Tunnicliffe).
0967-0637/$ - see front matter r 2006 Elsevier Ltd. All rights reserved.
doi:10.1016/j.dsr.2006.03.001
and to the associated biota. Plumes from high
temperature sources disperse laterally once they
reach seawater of equal density, between 100 and
400 m above the seafloor (Baker et al., 1995). In
contrast to the sharp upper plume boundary, lower
levels of the neutrally buoyant plume are ill-defined
(Thurnherr and Richards, 2001). In the lower
10–50 m above bottom, a layer with properties
intermediate between seawater and vent fluid may
form, and the relative mixing of fluids from diffuse
vents and ambient seawater is highly variable
(Lavelle and Wetzler, 1999). This bottom layer
may show reduced stratification that facilitates the
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K. Skebo et al. / Deep-Sea Research I 53 (2006) 1044–1060
vertical transport of particles either emitted from
vents or resuspended from the bottom (Pruis, 2004).
Tidally dominated bottom currents redistribute
particulates near the seafloor where dispersion
dynamics differ markedly from the upper plume
(Lavelle and Wetzler, 1999).
Reduced compounds in plume fluids can provide
an energy source for microbes, mainly through
oxidation reactions. Plume and epiplume zooplankton at Endeavour Segment of Juan de Fuca Ridge
feed on a mix of organic carbon from plume
production and transported vent production
(Cowen et al., 2001). Organic matter produced
both within the crustal reservoir underlying the
seafloor and at hydrothermal vent orifices is
advected vertically; entrainment of organic particulates and in-plume microbial production add more
carbon. Carbon export via the vertical plume and
its horizontal dispersion may be an important
pathway to distribute hydrothermally produced
carbon into the ocean (Tunnicliffe et al., 2003).
Increased plankton concentrations occur near hydrothermal vents in some locations (Kaartvedt
et al., 1994; Berg and Van Dover, 1987). High
concentrations of crustaceans and gelatinous zooplankton are found in a ‘‘deep scattering layer’’
above the Endeavour Segment plume at 300 m
above the seafloor (Burd and Thomson, 1995,
2000). However, elsewhere, enhanced plankton
abundances over the high temperature plumes are
not always evident or are limited to a few taxa
(Vinogradov et al., 2003).
Hydrothermal effluent may also present adverse
biological conditions: toxic reduced compounds,
high turbulence, and sharp gradients in temperature, salinity and particle flux (Kaartvedt et al.,
1994). Zooplankton can respond to subtle gradients
in physical and chemical conditions, thus creating
patches, gaps and zones of high abundance (e.g.
Mianzan and Guerrero, 2000; Sabatini and Martos,
2002.) It is likely that zooplankton and nekton in
the deep sea can detect near-by hydrothermal
plumes, especially in an environment of otherwise
low variability. Whether they respond to hydrothermal effluent remains unclear. Because repeated
net tows in the deep ocean are difficult and costly
(Raffaelli et al., 2003), visual methods are advantageous. Visual data yield finer resolution on distributions of zooplankton and, in conjunction with
environmental information, can identify animal
responses to different water masses (Gallager
et al., 1996). Visually acquired data also allow
1045
examination of the nature of patchiness (Kolasa and
Rollo, 1991; Pinel-Alloul, 1995).
Our study of imagery examines the spatial
patterns and abundances of zooplankton and
nekton in the near-bottom water over the Endeavour Segment axial valley floor. The large area grid
encompassed several hydrothermal vent fields, and
included the surrounding non-venting areas of
exposed basaltic valley floor. The major study
objective was to document zooplankton and nekton
abundance patterns in a plane draped at a constant
20 m altitude over the Endeavour axial rift valley.
The basic hypotheses of the study were: (i) that
observed dispersion patterns would not differ from
random and (ii) any significant geographic patterns
identified would not differ among major taxon
groups. We seek to understand whether near
bottom pelagic populations show behavioural or
abundance responses to the presence of extensive
hydrothermal venting on the seafloor.
2. Methods
2.1. Study site
Endeavour Segment (471560 –580 N, 1291060 W) is
located on northern Juan de Fuca Ridge. The
hydrothermally active portion of the 1-km wide
axial valley includes a 3-km region in which several
vent fields occur (Fig. 1) along a linear strike of
about 0201 True. The northern High Rise Field is
characterized by high temperature vents located on
an uplifted horst and a moderate extent of diffuse
venting over a 210 135 m area. Clam Bed Field,
roughly 200 74 m, is a small field with primarily
diffuse (o30 1C) venting with a single smoker
(o215 1C). Raven Field, discovered during the
collection of these data, is a small field located on
the western bounding fault of the valley, 95 30 m
in area with only diffuse vents. Main Field (about
500 140 m) is characterized by over 100 high
temperature vents, many emitting fluid in excess of
360 1C (Butterfield et al., 1994). Extensive low
temperature diffuse venting occurs along the length
of the field. The 1.5-km stretch of basaltic seafloor
separating Raven from Clam Bed is hydrothermally
inactive. No major venting is known along the west
wall of the Endeavour valley or directly to the east
of Main and High Rise fields.
Mean currents within the 100 m deep axial valley
are typically northward along-strike at speeds
between 1 and 5 cm s1 (Thomson et al., 2003).
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K. Skebo et al. / Deep-Sea Research I 53 (2006) 1044–1060
Fig. 1. Bathymetry of sampled area with submersible tracks overlaid. Upper inset shows location of Endeavour Segment off the west coast
of Canada. Lower inset shows cross-section of Endeavour Segment. Venting within the valley is confined to the western half of the segment
near the west wall; thus the survey does not extend into the eastern side of the valley floor.
Superimposed on these mean flows are predominantly tidal oscillatory motions of several cm s1;
the relative strength of prevailing versus tidal flows
determines the strength of flow reversals. Both
Thomson et al. (2003) and Garcia Berdeal et al.
(2006) describe highly variable flows at heights over
50 m above bottom (mab), while currents at 20 mab
and below show little rotation away from the strike
of the axial valley and few flow reversals.
2.2. Data collection
The remotely operated vehicle JASON flew a
systematic 3.2 0.5-km survey grid of 12 lines at
20 mab during a 3-day period from 0850 h GMT 1
October 2000–0050 h GMT 4 October 2000 (64 h).
Configuration of the grid was dictated by the
orientation of the valley walls. The study area lies
against the western wall, and extends eastward to
the centre of the axial valley. Thus, the 20 mab plane
is tilted as the western boundary lies over shallower
terrain (Fig. 1). The purpose of the grid was to map
heat fluxes from the seafloor (Johnson et al., 2002)
with this plankton study as a secondary objective.
Submersible speed ranged from 0.12 to 0.25 m s1,
and lines were spaced by 50 m. All odd numbered
lines were flown from south to north, and even
numbered lines from north to south (Fig. 1). Lines
10–12 were flown subsequent to line 9, but were
spatially nearer to line 1. Occasional off-course and
speed variable (at line beginnings) segments were
not used yielding a total transect distance of
34,430 m.
The colour video camera mounted on the brow of
the submersible remained in the same position
during the survey. The camera focused on organisms and particles in the water column located
directly in front of the submersible with a focal
depth down to 0.5 m. The field of view was scaled by
holding the 30 cm diameter hoop in front of the
ROV briefly for calibration. Copepods were identified near to the camera over an area of 0.23 m2.
Jellyfish and shrimp were verified within this same
area. Table 1 lists the estimated water volumes
examined. The fish, especially macrourids, were
distinguishable at greater distances; therefore, it was
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Table 1
Average abundances of each organism group over vent fields, between fields and elsewhere in the axial valley
Vent field
Between-fields
Far-field
All study area
Volume (m3)
Copepods (#/m3)
Jellyfish (#/m3)
Shrimp (#/
100 m3)
Zoarcid (#/
1000 m2)
Macrourid (#/
1000 m2)
694
1047
6154
7895
1.6
3
2.6
2.6
0.3
0.5
0.6
0.6
2.9
3.8
4.9
4.6
0.09
0.02
0.16
0.14
0.06
0.02
0.07
0.06
Note that fish abundances are reported as numbers over area of ground beneath the survey assuming a maximum 4 m across in the field of
view. The invertebrate groups are reported in densities in observed water volumes.
not possible to scale the viewing area. An estimated
field of view of 4 m across is used to calculate
abundances for comparison to other studies. Because the viewing area does not change, exact
calibration is not necessary to generate the pattern
analyses.
Animals were distinguished on high-resolution
(Hi8) video by form and behaviour. Size and motion
often hindered complete identification of all species
so analyses were based on generic groups rather
than on specific taxonomic levels. Crustacean
zooplankton included copepods, euphausiids and
amphipods, while gelatinous plankton included
medusae, siphonophores, ctenophores, salps, larvaceans and rare heteropods. Copepods were distinguished from particulates by distinctive motions.
An object was not included if it could not be
identified confidently as an organism. Time of
encounter with each animal was recorded. Videos
were watched in order surveyed, and the first 20 h
were re-examined to ensure consistency of counts
and identification. One observer recorded all visual
data. Accuracy of video counts was checked with
occasional re-runs of 5 min segments; re-counts fell
within 5% of the original.
A simultaneous net tow allowed identification of
zooplankton species. The net (125-mm mesh) was
held about 1 m below the submersible by the
manipulator for the duration of the survey. However, as the net occasionally billowed in front of the
camera, it probably did not fish well. The sample
was preserved in 70% ethanol, and all specimens
were identified. Environmental data were collected
using a Seabird CTD and a SeaTech transmissometer, and are reported as theta anomaly (1C),
salinity and light transmissivity (percentage of light
transmitted between two sensors 25-cm apart).
Potential temperature (y) anomaly is the difference
between the potential temperature measured within
the sample area and that at an off-axis location
10-km east of the ridge on the same density surface.
2.3. Data analysis
Video, navigation and environmental data were
collected simultaneously. Navigation coordinates
(x–y) were generated by merging integrated vehicle
velocity with fixes every 20 s from GPS-located
bottom transponders. Although instrument and
video data were generated in a continuous stream,
for analysis they were grouped into contiguous bins
(or grains) using the programme Matlabr. To
examine the scale on which patterns are manifest,
data were grouped into several category sizes based
on the distance that the submersible traveled.
‘‘Extent’’ is the area sampled (i.e. total area or
subsections of the total sampled area), and ‘‘grain
size’’ is the size of the sample units that determines
the resolution (Kolasa and Rollo, 1991; Legendre
and Legendre, 1998). All data were initially binned
into four grain sizes to determine the representation
for each taxon that best reflects organism density
and motility; a larger grain size may better capture
the dispersion of larger organisms. Grain sizes were
based on time intervals along the submersible track
(1, 5, 15 and 30 min) which were equivalent to
distances over ground of 10, 55, 165 and 335 m.
Grouped data were assigned to one of three areas:
‘‘vent field’’ (the mid-point of an observed bin lies
within a designated vent field along lines 1–3),
‘‘between-field’’ (portions of lines 1, 2 and 3
in the region between the two main vent fields)
and ‘‘far-field’’ (elsewhere in the axial valley, not
proximal to the major fields).
A single-factor ANOVA with a post-hoc Tukey
test assessed the hypothesis of no differences in
organism abundances among the three areas. For all
tests, a significance level of a ¼ 0:05 was used.
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K. Skebo et al. / Deep-Sea Research I 53 (2006) 1044–1060
Spatial data mapping is highly recommended for
examining patterns and for interpreting analyses
(Pielou, 1977; Legendre and Legendre, 1998; Perry
et al., 2002). Contour maps (Surferr, Golden
Software) of abundances and environmental data
were created to visualize spatial patterns using
kriging to interpolate between data points. To
verify this data visualization, contour maps were
also generated using results from the SADIE
analyses (below).
Point pattern analysis is useful to determine if the
geographic distribution of data points (e.g. counts)
is random, and to describe the pattern thus to infer
the causative process (Legendre and Legendre,
1998). Neighbouring data points along lines likely
relate more closely than points between lines
(anisotropy) because of the predominantly alongstrike current and closer temporal collection. Spatial
autocorrelation values were calculated along each
transect line for environmental and organism data.
Data were de-trended, and lines were assigned into
over-vent (lines 1–3), west-of-vents (lines 4–9) or
east-of-vents (lines 10–12) groups. The de-correlation scale is used to determine the number of
independent events (e.g. patch size) and, therefore,
the number of degrees of freedom in a sample
(Emery and Thomson, 1997). By dividing the total
length of the sample area (3.4 km) by the decorrelation distance, the number of independent
events (degrees of freedom) over the entire sample
area was calculated. Significance of autocorrelation
values was calculated following the method of
Lueck and Wolk (1999).
2.4. Pattern analysis
The randomness of the spatial distribution
pattern was assessed for each group of organisms
by examining how much re-ordering is necessary to
generate a uniform distribution. Degree of clustering in spatially referenced counts of organisms at
different extents and grain sizes is based on a
randomization test (Perry, 1994, 2003) executed
in the software SADIE (Spatial Analysis Distance IndicEs,r Kelvin F. Conrad, 2002, available
from http://www.rothamsted.ac.uk/pie/sadie/SADIE_
home_page_1.htm). For a comprehensive discussion
of SADIE methods and uses, see Perry (1994) and
the software website. We used SADIE to describe
local variation of spatial pattern, and to test
significance of clustering. SADIE tests significance
of clustering by measuring spatial pattern locally at
each sampled unit. An iterative transportation
algorithm moves each count from its current
position to one in which the final distribution of
counts is uniform. SADIE calculates distance to
uniformity (Dobs) as the sum of the distances moved
by each count from the observed arrangement to a
uniform arrangement. SADIE then randomly assigns positions for the same number of counts as in
the observed sample. Using the transport procedure, the total distance for each set of randomly
generated counts is generated as Drand. After 5967
permutations, an average Drand is calculated. The
probability that the observed data are no more
aggregated than expected from a random permutation of the counts is calculated such that probability
prand ¼ R/S where R is the number of permutations
where Drand4Dobs, and S is the total number of
random permutations (5967 in every case). A
prando0.05 indicates that the observed arrangement
is likely aggregated. An aggregation index (Ia)
describes the degree of spatial aggregation in the
dataset, and facilitates comparison among datasets:
Ia ¼
Dobs
,
Ea
where Ea is the average and Drand or D1rand þ
D2rand þ D3rand þ þ DSrand Þ=SÞ, the average of the
individual Drand/S. Values of Ia41 are aggregated;
values close to 1 indicate randomness, and values of
Iao1 indicate uniformity. The program also examines significance of groups of clustered or dispersed
counts. Results are presented as patch (vi) or gap (vj)
cluster indices. Values 41.50 (vi) and o1.50 (vj)
typically represent a sample unit with a clustering
index that is significantly different from random
spatial patterns.
The sample area as a whole was analysed using
the 165 m grain size for nekton. Because SADIE can
process only fewer than 500 records, the sample area
was divided into smaller sampling units when using
the 55 m grain for other taxa. In this case, multiple,
overlapping extents were examined to ensure that
the patterns detected were not simply a product of
the extent at which counts were analyzed. Within
individual vent fields, 10 m grain sizes were examined to determine small-scale cluster patterns of
copepods. SADIE generates continuously distributed data points in its calculation of Ia, and these
data were used to create contour maps. While
Surferr created maps using binned data that were
better for display (see Section 3), the confirmation
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K. Skebo et al. / Deep-Sea Research I 53 (2006) 1044–1060
of pattern by SADIE maps is supported by greater
statistical rigour.
2.5. Correlation analyses
Cross-correlation was used to assess relationships
between autocorrelated variables (copepod abundance
with theta anomaly, salinity and transmissivity).
Because two data sets are used, cross-correlation is
not symmetrical, so correlation values were calculated
in opposite directions (i.e. one data set moves ‘‘up’’ or
‘down’ with respect to the other data set, producing a
different distribution of correlation coefficients).
Abundances of neither jellyfish nor nekton groups
were autocorrelated; Pearson’s product moment
correlation coefficient (r) tested the relationships of
these abundances with the environmental variables.
3. Results
3.1. Organism abundances
The hand-held net collected a larger fraction of
copepods than was observed on videos (Table 2).
Only one jellyfish, but neither larger crustaceans nor
fish, were captured. Copepods in the net sample
consisted primarily of miscellaneous calanoid copepodites (29%), peocilostomatoids (mostly Oncaea
sp. 20%), Aetideopsis rostrata (15%) and NeocalaTable 2
Comparison of video and net tow data taken simultaneously over
entire survey area
Taxon
Crustacean zooplankton subtotal
Copepod
Euphausiid
Amphipod
Gelatinous zooplankton
Nekton subtotal
Shrimp
Zoarcid fish
Macrourid fish
Tomopterid polychaetes
Cephalopods
Unknown/othera
Total
Video
Net tow
Count
%
Count
%
20,385
20,023
329
33
4413
683
360
223
100
6
5
1630
27,122
75
73.8
1.2
0.1
16.3
2.5
1.3
0.8
0.4
o0.1
o0.1
6
469
465
1
3
1
0
0
0
0
0
0
39
509
92.1
99.2
0.2
0.6
0.2
0
0
0
0
0
0
7.7
Total abundances for each group of organisms are listed. Relative
abundances for each group are given as percentage. Italic
typeface indicates generic grouping.
a
Indicates indistinguishable organisms in videos, or benthic
organisms in net tow sample.
1049
nus plumchrus (6%). The most abundant vent
copepod was the siphonostome Stygiopontius quadrispinosus (2%).
Many pelagic shrimp seen on the videos resembled the Hymenodora gracilis reported by Burd
and Thomson (1995) in net tows 300 m above these
vents. The zoarcid fish adopted the characteristic
head-down coiled tail posture of Melanostigma
pammela, but another smaller species was also
present. Rattail fish included species of Coryphenoides and Nezumia, but firm identification was not
often possible. Water clarity was very high, although
cloudy water occurred in brief segments directly over
smoker vent orifices. Depth of field may be smaller
in cloudy water leading to a possible underestimate
of organisms such as copepods, but these sequences
were rare. Average encounter frequency over 64 h
was one organism every 7 s; because copepods were
distinguished mostly by movement, this number is
an underestimate. Overall visible organism abundance was about 3.2 individuals m3 (Table 1).
A smaller grain size is more useful for detecting
pattern in abundances; however, optimal grain may
differ in animal groups with different densities,
behaviours and swimming capabilities. Encounter
frequency for each organism group was calculated
for each of four grains. There was a probability of
observing at least one shrimp, zoarcid and macrourid in any 165 m portion of the transect; thus, this
grain was the minimum used. On average, 55 m
grains capture over five jellyfish. The crustacean
zooplankton (hereafter called ‘‘copepods’’) was
abundant enough to stand examination at a 10 m
grain over vent fields, but a 55 m grain was needed
to compare with jellyfish in the larger extent. All
organisms show a greater average abundance in
areas distant from smoker fields (Table 2). Abundances of copepods per 55 m grain are significantly
different among all three areas in Table 2 (ANOVA
F ¼ 28.5, df ¼ 679, po0:01), while jellyfish differences are significant for (i) vent field versus far-field
and (ii) between-field versus far-field.
3.2. Spatial patterns of organisms
The contour plot of copepod abundance data
reveals notable gaps over the smoker fields (Main
and High Rise) with a relative increase between the
fields (Figs. 2(A) and (B)). Abundances are significantly higher over Clam Bed than the smoker
fields (ANOVA, F ¼ 8.59, df ¼ 236, po0:01).
Autocorrelation among observations is significant
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K. Skebo et al. / Deep-Sea Research I 53 (2006) 1044–1060
Fig. 2. Copepod zooplankton dispersion over the Endeavour axial valley. Map axes are metres in the navigation grid. (A) Contour plots
of copepod abundance at 20 mab throughout whole sample area using 55 m grain. Insets illustrate copepod abundance at 10 m grain over
High Rise and Main Fields. Black dots are positions of black smoker chimneys. Scale bar indicates number of animals per 55-m grain. (B)
Variation in copepod abundance along the length of the sample area; distance is along the 0201 trend from SW to NE. Data are from all
transect lines. (C) Spatial autocorrelogram of copepod abundance along-lines (transect lines). Error bars ¼ 7standard error (SE). Lines
1–3 pass over vent fields and thus are grouped as ‘‘vent,’’ lines 4–9 are grouped as ‘‘west’’ (west-of-vent field lines) and lines 10–12 are
grouped as ‘east’ (east-of-vent field lines). Plot begins at lag ¼ 1. Horizontal lines indicate lower and upper bounds of the 95% confidence
interval for the correlation coefficient distribution.
under 165 m along ‘vent’ lines. The negative peak at
800–1000 m (Fig. 2(C)) includes comparisons of the
low counts around the two smoker fields with high
counts near the middle of the sample area, while the
positive correlation peak at 2000 m includes comparisons between High Rise and Main Fields. No
additional structure is evident when lag size is
decreased. On average, de-correlation of copepod
abundances occurs at about 570 m which yields
about six independent events per line or 72 (6 12
lines) over the whole area. Decreasing the grain size
does not increase the number of independent events,
while neither the 165 m nor 335 m grains detects all
the independent events. Thus, the 55 m grain size is
the most efficient in detecting copepod pattern in
this study.
The patchiness observed in zooplankton distribution appeared to be real, and non-random. Aggregation analysis with SADIE tested the significance
of the gaps and patches seen in the contour maps
(Table 3). The middle third of the sample area, with
the highest copepod abundance, is the least patchy
(Ia ¼ 1.6). The southern third of the area has
high and significant gap and patch indices reflecting
the high variability in this region (Fig. 2). Observed
clustering is significant at all extents; gaps and
patches at, and between, the vent fields are
significantly different from a random dispersion of
counts. Contour maps of organism distributions
using SADIE aggregation data verified locations of
patches and gaps figured in kriged contour maps
using count data. Based on SADIE analysis,
copepod dispersion over Clam Bed was random
when examined at a finer grain within the vent
fields. However, clustering values at High Rise
(Ia ¼ 1.88) and Main (Ia ¼ 1.64) were significant.
Gaps relate closely to positions of the individual
smoker chimneys (Fig. 2(A) insets). In both fields,
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Table 3
Summary of SADIE clustering statistics
Group
Extent
North 1/3
Copepods
Jellyfish
Mid 1/3
South 1/3
Ia
Avg vi
Avg vj
Ia
Avg vi
Avg vj
Ia
Avg vi
Avg vj
2.062
1.903
1.9
1.753
1.951
1.913
1.607
1.791
1.633
1.577
1.608
1.761
2.957
2.885
2.898
2.549
3.046
2.95
Whole area
Shrimp
Zoarcids
Macrourids
Ia
Avg vi
Avg vj
2.97
2.162
2.818
2.366
1.896
2.399
3.132
2.106
2.898
Copepods and jellyfish are analyzed at three extents using 55 m grain. Nekton groups are analyzed over entire extent using 165 m grain.
Ia ¼ index of aggregation (strength of clustering in gaps and patches). Probability (Pa) that clustering is not significantly different from
random is o0.05 for all Ia values. vi ¼ gap cluster index and vj ¼ patch cluster index. Only average gap and patch clustering indices are
shown. All vi and vj values are significant (po0.05).
patch cluster indices differed significantly from
random ðpo0:05Þ.
Overall, jellyfish dispersion pattern has distinct
absences in the south and in the central core of the
study area (Fig. 3(A)). Highest abundances occur
along the edges—particularly toward the middle of
the axial valley (Fig. 3(B)). There is little along-line
structure, and spatial autocorrelation along lines is
low (Fig. 3(C)). Patches and gaps are significant,
and most pronounced in the southern third of the
study area (Table 3). The three nekton groups show
different spatial patterns. Shrimp abundance increases toward the north (Pearson’s r ¼ 0:19,
po0:001), and is higher around High Rise and
Clam Bed (Fig. 4(A)). Zoarcid fish show a slight
increase
toward
the
south
(Pearson’s
r ¼ 0:15; po0:02). Macrourid fish are relatively
more abundant in the north half, especially over
Clam Bed, but are virtually absent from Main Field
and surrounding area (Fig. 4(B)). Nekton show
significant clustering throughout the entire sample
area. The degree to which abundances of taxonomic
groups covaried was examined with simple correlations (Table 4). Over the entire sample area, the
copepod and jellyfish groups are significantly
correlated at two grains; both groups also show
significant correlation with zoarcids. Shrimp and
macrourids form a second group of association as
they correlate with each other, but with no other
group.
3.3. Water characteristics at 20 m above bottom
Environmental sensors detected significantly variable water structure within the plane 20 m above the
bottom. We examine variability at the 55 m grain
over the whole area for the best comparison to
copepod data. Potential temperature range at
20 mab is 1.73–2.70 1C. Anomalies range from
0.018 to 0.55 1C. Water in the study area was
generally warmer relative to the standard 10-km offaxis at the same depth. Pronounced positive
theta anomalies occur over the two smoker fields
(Fig. 5(A)). Greater detail of the smoker fields
illustrates the correspondence of theta anomaly with
smoker positions (Fig. 5(A) inset). At the time of
observation near the west wall, temperature anomalies were relatively high. Salinity varied over a
hundredth of a unit (Fig. 5(B))—sufficient to
distinguish a north–south salinity gradient that
follows bathymetry (Fig. 1). Additionally, locations
of the two large high temperature fields and Clam
Bed were distinguishable by a decrease in light
transmissivity (Fig. 5(C)).
Water characteristics over the vent fields show
great variability compared to lines over far-field
areas (Fig. 6). All three water properties register
vent locations on Line 2 (Fig. 6(A)), although with
widely ranging values. A salinity high over Raven is
pronounced, while bottom water over the High Rise
Field exhibits a relative decrease. A slight decrease
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Fig. 3. Gelatinous zooplankton dispersion over the Endeavour axial valley. (A) Contour plots of jellyfish abundance at 20 mab
throughout whole sample area using 55 m grains. Scale indicates jellyfish abundance in each grain. There is a notable depletion in the
centre of the study area and over the vent fields. Scale bar indicates number of animals per 55-m grain. (B) Variation in jellyfish abundance
across the axial valley; abundance per 55 m segment. Data are plotted from west (line 9) to east (line 12) covering a distance of about
550 m. (C) Spatial autocorrelogram of jellyfish abundance along-lines (transect lines). Error bars (often smaller than data dots) are 7SE.
Lines 1–3 are grouped as ‘vent’, lines 4–9 are grouped as ‘west’ (west-of-vent field lines) and lines 10–12 are grouped as ‘east’ (east-of-vent
field lines). Plot begins at lag ¼ 1. Horizontal lines indicate lower and upper bounds of the 95% confidence interval for the correlation
coefficient distribution.
in transmissivity occurs at the south end of line 8
(Fig. 6(B)) west of Main Field. Autocorrelations run
for each transect generated three groupings of
transect lines with different correlation characteristics for both theta anomaly and transmissivity.
Lines that are east and west of the vent fields show
autocorrelation behaviour distinct from each other,
and from the three intervening transect lines that
traverse the vent fields. Maximum distance for
significant correlation of adjacent points (averaged
over 55 m) for any line is 250 m. Theta anomaly
and salinity show no significant cross-correlation
along vent lines, however, theta anomaly and
transmissivity along lines 1, 2 and 3 have significant
negative cross-correlation up to lags of 275 m.
Significant correlation distances are shorter over
the western lines (about 110 m) compared to eastern
lines (about 650 m) suggesting greater variability to
the west.
3.4. Correlation of plankton and water
characteristics
Maximum counts of copepods occur at low theta
anomalies (0.02–0.04 1C on Fig. 7(A)). Abundance
and theta anomaly on Line 2 display inverse
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Fig. 4. Abundances of larger nekton above the Endeavour axial valley calculated using 165 m grain. Counts of organisms are grouped into
three classes: (1) one organism of that group seen in 165 m; (2–4) two to four organisms seen in 165 m; and (5–10) five to ten organisms seen
in 165 m. (A) Shrimp abundances are higher in the northern half of the study area. (B) The two fish groups show different patterns with
zoarcids more abundant in the south and macrourids more abundant in the north.
variation (Fig. 7(B)). Copepods show significant
negative correlation with theta anomaly up to
distances of 165 m along vent lines (Fig. 7(C))
whether data are shifted positively or negatively
with respect to each other. No significant correlation is evident along either set of non-vent lines.
Copepods show no significant correlation to salinity, but the response to light transmission is
positively correlated. A finer grain (10 m) examination of abundances over the three larger vent fields
shows similar relationships: theta anomaly over
High Rise (Pearson r ¼ 0:41; po0:01) and MEF
(r ¼ 0:21, po0:05), and transmissivity over High
Rise (r ¼ 0:37, po0:01) and Clam Bed (r ¼ 0:33,
po0:05) are correlated to copepod abundance.
Abundances of other organism groups show little
or no autocorrelation so linear correlation coefficients were used (Table 4). Jellyfish abundance is
positively correlated with light transmission—both
were higher in the middle of the valley floor on the
eastern side of the study area. The strongest
association among the nekton lay in the zoarcid
negative response to theta anomaly and positive
response to light transmission. The aggregation of
macrourids in the northern part of the study area is
reflected in the negative correlation with salinity.
4. Discussion
A major advantage of visual plankton surveys
over net tows is the fine resolution in spatial pattern
that is possible on a variety of scales. Imaging
techniques work well in the deep sea where
particulate load is low and near bottom where
plankton nets cannot be used. Visual surveys record
fragile organisms normally absent in net tows
such as many gelatinous zooplankton and nekton
(Vereshchaka and Vinogradov, 1999). However,
limitations of lower resolution video cameras and
lighting preclude the detection of smaller, quiescent
organisms. Species confirmations are generally not
possible, and organism groupings are lumped
despite possible variability in functional groups of
organisms. For studies that concentrate on small
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Table 4
Summary of correlations of organism dispersion (A) with biotic
and abiotic variables over the entire extent and (B) among abiotic
variables using 55 m grain (df ¼ 72);**pp0.01
Jellyfish
(A)
Biotic biotic
Copepod
Jellyfish
Shrimp
Zoarcid
Shrimp
0.575**
0.097
—
0.053
—
—
—
—
Zoarcid
Macrourid
0.291** 0.038
0.241** 0.02
0.003
0.275**
—
0.053
Abiotic biotic
Theta anomaly
0.025
0.034 0.178**
0.193**
Salinity
0.132
0.142*
0.024
0.205**
Light transmissivity
0.239**
0.017
0.222** 0.081
(B)
Abiotic abiotic
Theta anomaly
Salinity
Salinity
Transmissivity
0.509**
0.726**
0.382**
For all biotic correlations, df ¼ 208. For abiotic correlations,
jellyfish are assessed using 55 m grain (df ¼ 72) with degrees of
freedom calculated by dividing the length of the sample area
(3.4 km) by the number of independent events per line (6) as
determined from autocorrelograms. For abiotic correlations,
nekton are assessed at 165 m grain (df ¼ 208); *pp0.05;
**pp0.01.
zooplankton, submersible mounted video plankton
recorders (VPR) yield better definition (e.g., Gallager et al., 2004). The wide-view camera approach
used in our study also detected larger animals that a
VPR would not sample. A series of net tows
executed in another study at this site detected
spatial patterns in copepods similar to those
reported here (K. Skebo, unpubl. data), indicating
that imagery detected this group well despite the
lack of distinction within the group. Larger nekton,
including jellyfish, are rare in deep-sea near-bottom
net tows (Wishner, 1980). Burd and Thomson
(1995, 2000) report 25 tows below 1700 m depth
near the Endeavour vent fields in which jellyfish
abundances were under 1.5% and fish abundances
were 0.1% of total fauna. In our video results, these
numbers are 17% and 1.2%. Video captures a
higher representation of deep ocean gelatinous
plankton abundances. Avoidance of the vehicle by
fish may occur, although macrourids appear less
affected (Mahaut et al., 1990).
The estimated plankton abundances at 20 mab in
the Endeavour axial valley are similar to those
obtained in other studies. In three short tows
between 5 and 25 mab in the East Pacific Rise axial
valley, Berg and Van Dover (1987) captured an
average of 3.1 individuals m3 of which half are
Fig. 5. Contour maps of environmental conditions of water layer 20 mab over the whole sample area. Data are averaged over
approximately 55 m of observations for comparison with copepod dispersion. The survey strip covers two-thirds of the valley floor up to
the base of the western wall. (A) Theta (scale in in 1C potential temperature) anomaly: highest anomalies are evident over the two smoker
fields. Insets at 10 m grain illustrate localized influences of individual smokers (black dots). (B) Salinity variation is pronounced with a
north–south gradient. (C) Water clarity (scale in % light transmission) is lowest over the smoker fields.
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Fig. 6. Environmental conditions are notably different along two transect lines. (A) Line 2 passes over all vent fields yielding high
variability in all measured parameters. (B) Line 8 lies second furthest to the west away from the vent fields. The drifting hydrothermal
plume is recorded by the more conservative tracer, transmissivity.
copepods and none is larger nekton. In ten vertical
tows between 2150 and 1800 m depth over the
Endeavour Segment, Burd and Thomson (2000)
report an average of 5.4 individuals m3 (range
0.7–10.0). Because of slow vehicle speeds, our net
captured too poorly during the long tow for direct
comparison, but the video records a survey average
of 3.2 individuals m3. Because we counted only
moving ‘particles’, this value is an underestimate.
Visual records in the 50 m above MidAtlantic Ridge
vents yield less than 0.1 jellyfish m3 (Vinogradov
and Shushkina, 2002). The Endeavour Ridge Segment, however, supports higher jellyfish abundances
both in the full water column (Burd and Thomson,
2000) and at 20 mab where densities are 0.6 m3.
Few of the netted organisms at 20 mab were ventrelated of which all were siphonostome copepods; a
similar low proportion of these copepods is reported
by Berg and Van Dover (1987) above East Pacific
Rise vents. The abundant vent organisms over
Mid Atlantic Ridge fields are alvinocarid shrimp
(Vereshchaka and Vinogradov, 2002), a taxon not
present at Juan de Fuca vents. Macrourid abundances in the plane at 20 mab are about 0.5–1.0 per
1000 m2 (projected onto a flat bottom). While this
density is about five times less than observations
on the continental shelf (e.g. Coggan et al., 1999),
it is much higher than trawl estimates in the
temperate abyssal plain. Priede and Merrett (1998)
report macrourid densities between 0.025 (Madiera
Abyssal Plain) and 0.2 (Porcupine Abyssal Plain)
per 1000 m2.
4.1. Presence of patterns
Plankton dispersion patterns are highly variable
in the axial valley both within an organism group
and among groups. Data contouring delivers useful
visualizations, and spatial autocorrelation explores
internal patterns. However, only if structure is not
random can we move to examining the underlying
causes of pattern (Diggle, 1983; Legendre and
Legendre, 1998). The SADIE approach provides
statistical support for observed clustering; in this
study, the observed patches and gaps in dispersion
of all groups were non-random. The most obvious
result is that there are fewer organisms over the
large high temperature vent fields where gaps in
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Fig. 7. Relationship between theta anomaly and zooplankton abundance at 20 mab. (A) Scatterplot of abundances and anomaly
determined from 55 m grain. Symbols identify the values found in different areas over the valley floor. (B) Relationship of abundance and
anomaly with respect to distance along line 2. Copepods (open circles) decrease over the major smoker fields where theta anomaly (filled
circles) increases. (C) Cross-correlogram of copepod abundance and theta anomaly along transect lines 1, 2 and 3. Negative and positive
refer to the sign of the lag distance k. Error bars ¼ 7SE. Horizontal lines indicate lower 2.5 percentiles and upper 97.5 percentiles of
distribution of correlation coefficients. Values above and below bounding lines are significantly different from zero.
both crustacean and gelatinous zooplankton abundances are pronounced. The second major result is
that each organism group displays a distinctive
distribution pattern. Maximum abundance for cope-
pods lies in the area between vent fields, for jellyfish
on the lateral edges of the study region (middle of the
valley and western wall), for shrimp and macrourids
in the north and for zoarcids in the south.
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Water characteristics also show large spatial
variability that relates to the overall valley-scale
mean flow and to localized vent plume behaviour.
Data collection time was much longer than tidal
cycles—the static picture of Fig. 5 does not
represent sustained conditions. Mean bottom currents are thought to be driven by the buoyancy flux
and further constrained by bottom topography
(Thomson et al., 2003). The strong southern in-flow
to the axial valley is evident in gradients of both the
temperature anomaly and salinity from South to
North with cooler, denser water in the southern
central valley. Current records near Main Field
show a relatively strong steady northward flow at
depths 20 mab and below, such that flow reversals
are rare since tidal influences are comparatively
weak (Thomson et al., 2003; Garcia Berdeal et al.,
2006). A moored current meter record taken at
15 mab between HiRise and Main Endeavour
during this survey shows northeastward along-strike
daily mean currents of about 5 cm s1 (Veirs, 2003).
In 2002, velocities at 20 mab in the central valley
southwest of Main Field were bottom-intensified to
over 5 cm s1 in the same direction (Garcia Berdeal
et al., 2006). These flows imply progressive tidal
displacement of about 360 m. Thus, plankton
patterns are unlikely to be confused by periodic
reversing bottom water currents.
The vertical fluid flux from hydrothermal sources
imparts a marked signature to both the theta
anomaly and transmissivity maps of the survey
conducted near the height of high temperature
smoker orifices in the two large fields. Ascending
high temperature water passes through the plane at
20 mab to form the neutrally buoyant plume
100–300 m higher in the water column. It is unlikely
that the large ‘‘holes’’ in zooplankton centered over
the smoker fields are due to passive entrainment of
lower layer particles into the rising plume. Only
fluid within 15–30 m of smokers is likely to be
vertically entrained into this buoyant flux (Trivett,
1994; McDuff, 1995). Effluent from diffuse low
temperature vents forms a discrete plume hugging
the bottom in a low stability layer with a small
buoyancy frequency (M.J. Pruis and H.P. Johnson,
unpubl. data). During this survey, we intersected
only the lower stem of the high temperature plumes
that are manifest as intense temperature anomalies
at the vent field scale. An additional feature of the
heat distribution is warming in the western boundary of the study area. Because the bottom rises at
the base of the axial wall (producing a tilted survey
1057
plane), the ROV environmental sensors may have
intercepted water advected westward from the high
temperature plumes at a height above bottom where
some cross-valley flow occurs.
4.2. Causes of patterns
The observed biotic patterns likely result from a
combination of local flow dynamics, differing
responses to perceived stimuli and some inter-taxon
interactions. Zooplankton are less abundant in
areas where the vent effluent signature, especially
the conservative particle tracer transmissivity, is the
strongest. At least two mechanisms cause gap
formation: passive dispersal of zooplankton by
turbulent plumes and active avoidance by evasive
swimming. At the smoker scale, there could be a
passive depletion of plankton ‘particles’ by entrainment into the rising effluent. At 20 mab, rising fluid
jets from high temperature vents may exceed
10 cm s1 (Little et al., 1987). Near such turbulence,
copepods begin to resemble passive particles
(Gallager et al., 2004) where smaller species with
limited mobility can be aggregated or dispersed by
advective processes (Barry and Dayton, 1991).
However, the lower plume stems exhibit a cyclonic
rotation (Thomson et al., 2005) that should tend to
concentrate particles like zooplankton in the lower
waters. The size of the copepod abundance gaps
over the two smoker fields reflects a much larger
area of plankton response in which active evasion
may be operating. In lower turbulence conditions,
zooplankton distribution differs substantially from
that of inert particles, and individual copepod
movements can affect overall population dispersal
(Mauchline, 1998; Buskey et al., 2002). Because
copepods can forage using chemoreception (Mauchline, 1998), they can probably detect and avoid
adverse conditions such as toxic reducing chemical
species in vent effluent.
Copepod abundance increases away from vents to
form aggregations. Thomson et al. (1992) and
Mullineaux et al. (1995) report a decrease in
copepod abundance in the core of the neutrally
buoyant plume, but an increase in the layers above.
A copepod may detect vent effluent using temperature gradients, chemical species or particulate
concentrations. Zooplankton in a very stable and
uniform environment, such as the abyssal depths,
may be more sensitive to small changes in water
characteristics than zooplankton at the surface or
mid-depths. Individuals may be responding to
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changes in temperature on micro-scales, but the net
effect is seen on larger scales (tens of metres). Our
survey showed no localized attraction of zooplankton to vent areas, with the exception of a single 55 m
segment over Clam Bed. Within the vicinity of the
vent fields, microbial productivity is enhanced
above background levels (Cowen and German,
2003). Copepods in the neutrally buoyant plume
apparently use chemosynthetic products such as
bacteria (Burd et al., 2002). Thus, over low
temperature effluent, a copepod aggregation may
form to use a greater food source in the absence of
the high particulate and chemical load of the
smokers. It is unclear whether the overall zooplankton population of the hydrothermally active axial
valley is elevated in comparison to normal seafloor;
resolution of this question awaits a parallel study on
the abyssal plain.
Jellyfish distribution patterns are likely driven
both by attraction to copepod aggregations and by
avoidance of vent effluent in a fashion similar to
that in the overlying plume (Burd and Thomson,
2000). Weak-swimming jellyfish may avoid rapidly
changing conditions near vent field by remaining in
the middle of the valley where conditions are most
constant. Several of the observed species, such as
Crossota, Pantachogon and Halicreas, are found at
similar depths in the northwest Pacific (Vinogradov
and Shushkina, 2002). Zoarcid fish show similar
dispersion patterns, and may move toward copepod
concentrations as a food source (Janssen et al.,
2000), while jellyfish may be significant predators on
juvenile zoarcids. The co-occurrence of pelagic
shrimp and macrourid fish in the northern area
was noted in a previous year during a pilot study of
plankton dispersion (V. Tunnicliffe, pers. obs.)
suggesting stable populations that congregate near
High Rise Field and/or avoid the southern water
inflow. Benthic animals form a major part of the
diet of northeast Pacific macrourids, especially as
juveniles (Drazen et al., 2001). As the unsedimented
and exposed basalts of the spreading axis support
few organisms except directly adjacent to hydrothermal vents, the relatively large macrourid population likely depends on occasional foraging at vents
(observed by Tunnicliffe et al., 1990) plus a pelagic
diet known to include shrimp (Drazen et al., 2001).
Distinct aggregations of zooplankton and nekton
are correlated with the fluid indicators from both
the low temperature diffuse effluent and the focused
high temperature vents. The processes that control
the observed zooplankton dispersion patterns likely
include both active response to, and passive
entrainment by, vent effluent. Shrimp, eelpouts
and rattails represent the bulk of the biomass
present within the axial valley, and may be
enhanced relative to normal abyssal densities. Time
series observations of these organism patterns
would be useful to determine if the observations
of the Endeavour Valley are sustained, quasipermanent populations, and if zooplankton abundances fluctuate as the hydrothermal activity within
the valley varies with episodes of tectonic and
magmatic activity (Johnson et al., 2000; Lilley et al.,
2003). While a large increase in zooplankton
biomass within the water column adjacent to
hydrothermal vent fields was not evident from our
survey, the extended axial valley of the Endeavour
Segment fosters robust populations of zooplankton
and nekton. There are many locations on the global
seafloor where fluid outflows transport a variety of
subseafloor products. This study describes one
example of how subseafloor processes influence the
pattern of plankton distribution in the overlying
water.
Acknowledgements
The skillful vehicle control by the JASON ROV
pilots during this survey is gratefully recognized. We
also thank T. Bjorklund and J. Rose for technical
assistance. A. Bates, S. Hautala, J. Marcus, G.
Yahel and R. Yahel commented on data interpretations. This work was funded by Grants from
NSERC Canada (to VT) and NSF USA
(OCE9911523 and OCE0085615 to HPJ). A pilot
study was funded by Fisheries and Oceans Canada.
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Further reading
Wetzler, M.A., Lavelle, J.W., Cannon, G.A., Baker, E.T., 1998.
Variability of temperature and currents measured near Pipe
Organ hydrothermal vent site. Marine Geophysical Researches 20, 505–516.