Download Impact of trawling on benthic marine organisms off the Greenlandic

Irina Chemshirova
Impact of trawling on benthic marine organisms off the Greenlandic
shelf, 200 to 600 meters depth
Abstract
Mobile fishing gear directly impacts the seabed by both removing target organisms and
reducing the habitat complexity of the benthos. This is due to the extensive contact gear
has with the seabed. Camera surveys have been used in order to quantify the effect of
trawling for the Northern shrimp (Pandalus borealis) on the benthos. Soft substrata
have been found to be more sensitive to trawling. This is likely to be due to the
frequency at which they are exploited. The diversity of hard substrata has been found
to increase with trawling intensity. It is possible that hard substrata is only moderately
disturbed hence increasing in diversity. The sensitivity of Vulnerable Marine Organisms
(main habitat builders) was highlighted by their rapid decline with trawling intensity.
Overall trawling affects the benthic organisms negatively. Their responses should be
taken into consideration when fisheries management plans are developed.
Introduction
The marine benthos is composed of very diverse bottom-dwelling organisms
(Poore & Wilson, 1993). This is especially interesting since the benthic zone offers a
dark, cold habitat, lacking in resources (Snelgrove, Blackburn & Hutchings, 1998).
Nevertheless Appeltans et al., (2012) estimate that there could be 687, 255 benthic
species worldwide. Many of them are key in a range of ecological processes, from
nutrient cycling to bioturbation (destabilising sediment by mixing it, regulating the
amount of oxygen present) (Andersen & Kristensen, 1992, Solan et al., 2004). The
benthos has also been shown to contribute to the upwelling of iron, a nutrient vital for
phytoplankton productivity (Johnson, Chavez & Friederich, 1999).
However, the benthic ecosystems have been put under increasing pressure by
pollution, ocean acidification, and habitat degradation (Widdicombe & Spicer, 2008,
Thrush & Dayton, 2002b, Burd, 2002). Fishing, more specifically fishing activities that
have contact the seabed such as trawling. It is one of the main factors contributing to
habitat degradation. Trawling for the Northern shrimp, Pandalus borealis is an extensive
1
Trawling Impact on the Greenlandic Benthos
practice in the West Greenland. The main type of trawl used there is the otter trawl. It
consists of two trawl doors (can weigh several tonnes) which keep the net open and are
dragged along the seabed at an angle. It is estimated that these can penetrate up to
15cm into soft sediment even if they have metal shoes attached which aim to limit this
(Jennings & Kaiser, 1998). As trawling technology has advanced, the repercussions for
the benthic habitat have grown (Hall, 1999). The damage to the benthos increases with
depth at which the gear is operated, its weight, the speed it is towed and the amount of
contact with the seabed. For example, gear designed for deep sea trawling is heavier,
thus it will be towed for a longer time period at a slower speed. Therefore the contact
with the seabed will be prolonged. This will ultimately lead to greater damage of the
benthos (Halpern et al., 2007, Thrush & Dayton, 2002b).
Any fishing gear which has such contact with the seabed will cause disturbance
of the benthos. Natural disruption is essential in order to avoid the dominance of one
species. However it is important that it does not exceed the re-colonisation capacity of
the community. Areas which are subjected to frequent natural disturbance are likely to
be more resilient to fishing disturbance (Thrush & Dayton, 2002b). Natural disturbance
events decrease in frequency with depth. Therefore community vulnerability increases
with depth (Collie, Escanero & Valentine, 2000).
Trawling disturbance has both long-term and short-term effects on the benthos.
The most obvious short-term effect is the removal of organisms in the form of bycatch
i.e. the non-target organisms and the target organism (P. borealis). Furthermore
removal of organisms may have an effect on the ecosystem’s function. This usually
occurs when a species is still present but in such low density that it can no longer
adequately perform its function (Thrush & Dayton, 2002a). Indirect mortality, through
contact with fishing gear has shown to be more damaging than bycatch (Jenkins,
Beukers-Stewart & Brand, 2001).
Ball, Fox & Munday (2000) investigated the effects of a demersal lobster fishery
in the northwest of the Irish Sea. They found that diversity metrics (such as the Shannon
Index and species richness) drop rapidly 24 hours after fishing, this was more apparent
in their shallower sites.
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Irina Chemshirova
The long-term effects of trawling have been compared with those of terrestrial
forest clearing (Watling & Norse, 1998). Trawling reduces the habitat complexity of the
benthos. This occurs because the substrate is homogenised i.e. becomes more uniform.
Habitat-building organisms such as corals are quite sensitive to disturbance. Upright
organisms (a major feature of a complex habitat) provide better feeding opportunities
for suspension feeders. It has been shown that current speeds increase dramatically
only a few centimetres from the sea floor. Hence suspension feeders are likely to
encounter more food in a more complex habitat (Caddy, 1973).
A complex habitat also provides a refuge for vulnerable species or organisms in
vulnerable life stages i.e. juveniles. For example Atlantic cod recruitment rates have
been found to increase with more heterogeneous habitat (Kaiser et al., 2000).
The species composition of the community may also alter with time. Kaiser et al. (2000)
have found scavengers to dominate areas which have been subject to extreme fishing
disturbance.
The composition of the benthos often differs with substrate. Therefore
communities are likely to react differently to disturbance. Collie, Escanero and
Valentine (2000) discovered that those on gravel substrate are more sensitive to
trawling than those on sandy and muddy terrains.
Quantifying the observed effects of trawling is especially challenging because
data is often incomplete. Frequently findings are more specific to local areas and cannot
be applied to wide geographic ranges. Garcia, Ragnarsson and Eiríksson (2006) state
that the effects of fishing are much more severe at the beginning of the exploitation of
an area. Thus a community is already modified before being investigated. Therefore the
full impact of the disturbance is not apparent.
The aim of this investigation is to quantify the effect of trawling on the diversity
observed in still images taken of the Greenlandic benthos.
3
Trawling Impact on the Greenlandic Benthos
Methods
This was addressed by photographing the seabed at locations which have experienced
varied
fishing
disturbance
off
the
West
coast
of
Greenland
(Figure
1).
Credit: Chris Yesson
Figure 1: Map showing the locations surveyed along the west Greenlandic
coast and the level of trawling there.
Camera surveys
The surveys were carried out aboard M/T Paamiut. The cruises surveyed the
areas between Aasiaat and Nuuk in 2011 and then between Nuuk and Qaqortoq in 2012
(Figure 1). The camera equipment was provided by the Greenland Climate Research
Centre,
Greenland Institute
of Natural Resources
(GINR).
It
consisted of:
a camera (DSC-10000 Digital Ocean Imaging Systems (DOIS), USA) placed in waterproof
housing that can withstand up to 2, 000 meters depth; a flash unit (200W-S Remote
Head Strobe Model3831, DOIS, USA) tape was applied to the flash in order to improve
image quality by reducing backscatter; a battery unit for the flash and a flash trigger.
The flash was operated by adding a weight to the trigger. Therefore when the weight
4
Irina Chemshirova
hits the sea bottom the flash is triggered and thus the seafloor is exposed allowing for
an image to be taken.
All of this equipment was mounted on a frame (see Figure 2). The frame was
reinforced with additional weight
at the bottom. This overcomes currents, which
otherwise tend to drag the apparatus. Rulers were also added to the frame in order to
give a concept of scale to the organisms in the images. For detailed camera settings see
Appendix 1.
Flash
trigger
Flash
battery
Camera in
housing
Flash
Additional
weight
Trigger weight
Credit: Kirsty Kemp
Figure 2: Camera apparatus mounted on frame
The survey station locations were chosen based on the fishing impact using a
qGIS map (Figure 1). This map was developed based on logbook data for 1986-2010
provided by the Greenland Fishery and Licence Control. The fishing data consists of
trawling effort for five year periods between 1986 and 2010.
Upon arriving at the location the camera apparatus was deployed using a winch
wire, off a platform located at the starboard side of the vessel (Figure 3).
The following was recorded at each sampling station – Start and Finish Latitude and
Longitude, Depth1 , Wire Out2 and Time. On each camera drop the sea bottom was
1
seabed depth directly under the vessel, recorded by the ship’s sounding system
5
Trawling Impact on the Greenlandic Benthos
detected by monitoring the wire for loss of tension. After detecting bottom the frame
was raised up by 10-20 meters. It was lowered again after 1 minute to allow for settling
of any disturbed sediment and to allow for the ship to drift. This ensured that different
area was captured with each camera drop.
The camera apparatus was lowered a total of ten times per station, thus giving a
total of ten images of the seafloor. The area of the seafloor recorded in each image is
0.3m2(Kemp, 2011).
Credit: Julius Nielsen
Figure 3: Deployment of camera
Image processing
The images collected on the cruises were then processed at the Institute of
Zoology, London. The images from the 2012 cruise were processed by Poppy Simon as
part of an MSci project (Simon, 2013). The identifications of organisms made by her
served as a guide to the processing of the 2011 images (Appendix 2).
A combination of identification guides and expert websites were used to confirm
the classification of the organisms (Picton & National Museums of Northern Ireland,
2013, Telnes, 2013, Gibson, Hextall & Rogers, 2001, Hayward, Nelson-Smith & Shields,
2001, Sars, 1899). All of this was used to compile an independent guide specific to the
study system (Appendix 3). The initial aim for the 2011 processing was to identify
2
the amount of winch wire used when deploying the camera to the seabed
6
Irina Chemshirova
organisms to Family level. This proved too time-consuming, except for Starfish and
Polychaete worms. The identifications were further confirmed by experts at Marine
Ecological Surveys in Bath whilst partaking in a marine taxonomy course.
Substrate was classified as hard or soft for each station (Figure 4). A station was
categorised as being hard substrate when rocks, pebbles and shells were present
(Figure 4A). Stations classed as soft substrate mainly consisted of mud and sand (Figure
4B).
Figure 4: Substrate classification. A-hard, B-soft.
Not all images were of sufficient quality for processing i.e. they were blurry.
Therefore some were excluded from the analysis as the identifications made could be
unreliable. In order to control for image quality, each image was given a rating of high,
medium or low (Appendix 4).
The best available images were chosen from each station (low quality images
were not included in the analysis). A total of five images were used per station in order
7
Trawling Impact on the Greenlandic Benthos
to maximise the quality of the images used and maintain consistency throughout the
stations.
Analysis
Fishing impact data was available as start and end trawl times and locations for
all Greenlandic shrimp trawl vessels. As many trawls do not proceed in a straight line,
the most representative measure of impact was found to be trawl duration rather than
distance. The trawling impact was measured in cumulative minutes trawled aggregated
over a grid of 3.5 x 3.5 km, for both 5 year and 25 year periods (pers. comm. Yesson,
2013). The trawling impact was treated as a continuous explanatory variable.
A Shapiro-Wilks normality test was carried out on the data for the total trawling
impact (25 year period). It showed that it was not distributed normally (W=0.78
p<0.001). The data was then log-transformed but it still failed the normality test.
Therefore a Box-Cox transformation was applied using the following formula (Box &
Cox, 1964):
The value of λ was calculated to be 0.18.
This was also carried out for the five year periods of fishing impact. A log
transformation was deemed more suitable for the normal distribution of the data as the
value of λ was -0.02. Only two five-year periods were analysed in more depth, 19861990 and 2006-2010. This is because they make it possible to determine if the system is
recovering from fishing disturbance. From the image dataset, Station 201149 was
excluded from further analysis. It was identified as an outlier due to the fact that it was
the shallowest station at 68m. This was further confirmed when diagnostic plots were
carried
out
on
the
initial
regression
8
analysis
(Figure
5).
Irina Chemshirova
2
Residuals vs Leverage
0
-1
-2
Standardized residuals
1
201106
201248
201149
Cook's distance
0.00
0.01
0.02
0.03
0.04
0.05
0.06
Leverage
lm(shannon49 ~ fishing.trans.allno49)
Figure 5: Diagnostic plot showing which data points have the most influence on the model.
The station in itself was unique in terms of the large density of brittle stars observed
(Figure 6).
9
Trawling Impact on the Greenlandic Benthos
An assessment of completeness of sampling was made examining species
accumulation curves for our sampling stations (Ugland, Gray & Ellingsen, 2003). The
Shannon-Weiner Index measures both the richness and evenness of the community.
This explanatory variable was continuous. A high value means that the community is
both species rich and is not dominated by any one particular taxon (Shannon, 1948).
The number of individuals and number of brittle stars were calculated in order
to compare with the diversity indices. These are discrete count data, however they were
treated as continuous variables in the analysis. This data was log transformed in the
regression analysis.
The same calculations were carried out on a subset of the taxa. These were
deemed Vulnerable Marine Organisms (VMOs) based on a report by FAO on
management of deep sea fisheries (Food and Agriculture Organisation of the United
Nations (FAO), 2009). This allows us to compare how organisms thought to be sensitive
to disturbance respond to trawling. All of these were treated as the response variable in
further analysis.
As both variables were continuous a linear regression was used to further
analyse the data. It allowed us to determine if there is a linear relationship, between
trawling impact and diversity.
A 3d scatter plot was also generated in order to determine if there were any
stations which could be classified as recovering from fishing. This returned too few
stations in order to pursue further analysis. All analysis was performed using the
statistics software R (R Core Team, 2013) using the packages vegan, MASS and
scatterplot3d.
10
Irina Chemshirova
Results
A total of 80 stations from both years were analysed. In total of 44 taxa
identified, with 41 in the analysis set. Three additional taxa were found in low quality
images.
A Shapiro – Wilks test was performed on the total trawling impact data. After
box-cox transformation the data set still failed the test (W=0.95, p<0.01). Nevertheless
the data was more normally distributed than before so the transformation was used.
The species accumulation curves (Figure 7) show that the sampling effort
accounts for most of the species present. The jacknife estimate predicted that there
20
0
10
Species
30
40
should be 45 species (SE=2), whilst we found 41.
0
20
40
60
80
Sites
Figure 7: Shows that the species number is reaching the asymptote with increased sampling effort.
The linear regressions showed that diversity metrics generally declined with
increased trawling (Figure 8, Appendix 5, and Table 1). Notable exception is the
Shannon index for hard substrata sites as it increases with greater trawling disturbance
(Figure 8). When examining the diversity metrics for the VMOs the decline with
trawling is more apparent (Appendix 6 & 7, Table 2). Recovery sites were identified as
ones with no fishing impact in the last 5 year period (2006-2010) but high levels of
fishing in the first 5 year period (1986-1991). The 3D scatter plot produced showed that
there are very few recovery sites (Figure 9). Brittle stars also decline with trawling
(Appendix 8, Table 3).
11
1.5
1.0
Substrata
0.5
Shannon Index
2.0
2.5
Trawling Impact on the Greenlandic Benthos
0.0
hard
soft
both
A
0
10
20
30
40
50
B
2.5
1.5
2.0
2
0.5
Substrata
hard
soft
both
0.0
0.0
hard
soft
both
0
1.0
Shannon Index
1.5
1.0
Substrata
0.5
Shannon Index
2.0
2.5
Total Trawling Impact
4
6
8
10
0
2
4
6
8
10
C log(Trawling Impact 2006-2010)(mins)
log(Trawling Impact 1986-1990)(mins)
Figure 8: A: Showing the relationship between Shannon diversity and trawling impact. Diversity decreases as a
function of trawling impact for both substrata (Table 1). B: Showing the relationship between trawling impact for
1986 to 1990 and Shannon diversity index. Diversity is declining with increased trawling for both substrata (Table 1).
C: Showing the relationship for the latest trawling period (2006-2010) and Shannon diversity. Increased trawling has
a negative impact on diversity for both substrata (Table 1).
12
Irina Chemshirova
Table 1: Calculated linear regression statistics on the relationship between trawling impact and diversity measures
for all the taxa recorded (•p<0.1, *p<0.05, **p<0.01, ***p<0.001).
Response
Slope
variable
estimate
d.f.
R2
t
Shannon Index
Total Trawling (Figure 8A)
Substrata
Hard
0.009*
42
0.13
2.50
Soft
-0.03**
34
0.26
-3.42
Both
-0.01*
78
0.06
-2.31
Trawling Period 1986-1990 (Figure 8B)
Substrata
Hard
0.06***
42
0.32
4.40
Soft
-0.02
34
0.02
-0.76
Both
-0.02
78
0.03
-1.46
Trawling Period 2006-2010 (Figure 8C)
Substrata
Hard
0.04*
42
0.20
3.24
Soft
-0.05
34
0.06
-1.47
Both
-0.04*
78
0.08
-2.59
No. individuals (Appendix 5)
Total Trawling
Substrata
Hard
-0.02**
42
0.14
-2.63
Soft
-0.05
34
0.05
-1.39
Both
-0.06***
78
0.22
-4.60
Trawling Period 1986-1990
Substrata
Hard
-0.03
42
0.03
-1.21
Soft
-0.12
34
0.08
-1.67
Both
-0.23***
78
0.27
-5.40
Trawling Period 1986-1990
Substrata
13
Trawling Impact on the Greenlandic Benthos
Hard
-0.08**
42
0.20
-3.25
Soft
-0.17*
34
0.14
-2.35
Both
-0.27***
78
0.42
-7.56
14
Irina Chemshirova
Table 2: Linear regression statistics on the relationship between trawling impact and diversity measures for
Vulnerable Marine Organisms (•p<0.1, *p<0.05, **p<0.01, ***p<0.001).
Response Slope
variable
d.f.
R2
t
estimate
Shannon Index (Appendix 6)
Total Trawling
Substrata
Hard
-0.004
42
0.04
-1.38
Soft
-0.04*
34
0.13
-2.26
Both
-0.02***
78
0.20
-4.46
Trawling Period 1986-1990
Substrata
Hard
0.003
42
0.001 0.22
Soft
-0.06**
34
0.19
-2.84
Both
-0.06***
78
0.24
-4.96
Trawling Period 2006-2010
Substrata
Hard
0.0003
42
10-6
0.02
Soft
-0.07**
34
0.25
-3.39
Both
-0.07***
78
0.31
-5.97
No. individuals (Appendix 7)
Total Trawling
Substrata
Hard
-0.009
42
0.04
-1.24
Soft
-0.07***
34
0.23
-3.17
Both
-0.07***
78
0.24
-4.90
Trawling Period 1986-1990
Substrata
Hard
-0.06•
42
0.08
-1.89
Soft
-0.19**
34
0.23
-2.84
Both
-0.07**
78
0.23
-3.17
Trawling Period 2006-2010
Substrata
Hard
-0.06•
42
0.09
-1.99
15
Trawling Impact on the Greenlandic Benthos
Soft
-0.20**
34
0.22
-3.07
Both
-0.32***
78
0.44
-7.75
Table 3: Linear regression statistics on the relationship between trawling impact and the number of brittle stars
found at each station (•p<0.1, *p<0.05, **p<0.01, ***p<0.001).
Response
Slope
variable
estimate
d.f.
R2
t
Total Trawling (Appendix 8)
Substrata
Hard
-0.03*
42
0.14
-2.62
Soft
-0.04*
34
0.13
-2.21
Both
-0.07***
78
0.28
-5.44
Trawling Period 1986-1990
Substrata
Hard
-0.12*
42
0.11
-2.32
Soft
-0.14*
34
0.15
-2.46
Both
-0.26***
78
0.35
-6.44
Trawling Period 2006-2010
Substrata
Hard
-0.11*
42
0.12
-2.40
Soft
-0.16*
34
0.17
-2.65
Both
-0.28***
78
0.42
-7.50
16
10
8
0.5
6
4
0.0
2
log(Trawling Impact 2006-2010) (mins)
1.5
12
1.0
Shannon Index
2.0
2.5
3.0
Irina Chemshirova
0
0
2
4
6
8
10
12
log(Trawling Impact 1986-1990) (mins)
Figure 9: Showing the potential recovery stations in red, based on the relationship between the first and last fishing
period and their respective Shannon diversity.
17
Trawling Impact on the Greenlandic Benthos
Discussion
The number of taxa we found was consistent with similar studies. Mac Donald et.
al. (2010) discovered 51 taxa at 900m depth. They also took physical samples at their
study sites, which would have allowed them to sample more of the infaunal community.
There is evidence of trawling impacting the diversity of the benthos. All of the diversity
metrics show that soft substrata sites have been more severely affected. Kaiser et al.
(2006) have also found these communities are quite vulnerable and their recovery may
take years. The soft substrata are more frequently disturbed by trawling activities.
Therefore they are not given enough time to recover before they are disturbed again
(Kaiser et al., 2006). Furthermore the soft sediments are more prone to resuspension.
This may lead to the smothering of the benthos and anaerobic conditions which often
hinder the settlement of the larvae of many organisms (Jones, 1992). It is also possible
that the extent of the diversity of the soft-bottom sites has been under-recorded due to
the burrowing behaviour of many of the organisms there. Simpson and Watling (2006)
recorded burrow density and size. Whilst we recorded the number of visible burrows
and animal trails we did not perform any statistical analysis on them. It would be
interesting to develop this further and measure how trawling is impacting this infaunal
habitat structure.
The hard substrata sites on the other hand, have responded positively to
trawling when considering Shannon’s Index. This kind of substrata is less frequently
disturbed and his community has low levels of natural disturbance due to its depth.
Therefore trawling could be increasing the diversity by acting as an intermediate
disturbance. Thus removing the some of the slow growing species which are better at
competing for resources and giving a chance for the rapidly colonising species to settle
instead (Blanchard et al., 2004). This is further confirmed by Figure 9. It shows that
intermediate amount of trawling (in brown, regardless of substrata) has the similar
diversity to sites which haven’t been trawled for a very long period of time (in red).
However when considering the number of individuals found at hard substrata stations a
decline was observed. This was consistent with findings by Freese et al. (1999).
Therefore it could be that the Shannon Index is not suitable for measuring the diversity
with our current level of classification (i.e. most are identified to variable taxonomic
levels, none to species).
18
Irina Chemshirova
Most studies have reported that trawling has no long term effects on soft
substrata (Simpson & Watling, 2006, Sparks-McConkey & Watling, 2001, Kaiser et al.,
1998). However all of them have simulated trawling disturbance. They state that the
level of disturbance they subjected the benthos to is not as intensive as commercial
trawling. Therefore it is possible that the long term effects we have seen here are due to
the extensive and frequent exploitation of soft-bottom sites. Smith, Papadopoulou &
Diliberto, (2000) have found that recovery is much slower when surveying sites which
are being trawled commercially. They also state that the four months recovery period is
not enough to counter the negative effects of trawling.
The declines of Vulnerable Marine Organisms were more evident across both
substrata. These taxa are more sensitive to disturbance (MacDonald et al., 1996). Also
they are usually long-lived and reach a relatively large size when undisturbed.
Therefore larger individuals are usually more susceptible to trawling damage as there is
a greater chance of impact with the fishing gear (Bergman & van Santbrink, 2000).
This coincides with the findings of McConnaughey, Mier & Dew (2000), where there is
greater diversity and numbers of sedentary taxa (i.e. soft corals, sponges, ascidians,
bryozoans) in untrawled areas. Simpson & Watling (2006) and Prena et al. (1999) also
found that trawling affects sponges and corals to a greater extent than other organisms.
Trawling has been shown to generally cause a shift in the community from
habitat-building organisms (like the VMOs) to mobile and burrowing organisms which
are more capable in dealing with continuous trawling pressure (De Juan, Demestre &
Sanchez, 2011). Furthermore some models estimate that sponges and corals may take
up to several decades to recover from trawling damage. This is mainly due to their slow
growth and limited dispersal (Rooper et al., 2011, McConnaughey, Mier & Dew, 2000).
In many studies, brittle stars are shown to be more numerous in trawled areas
and to actively scavenge on the remains of damaged benthic organisms (Groenewold &
Fonds, 2000). However we found that they are strongly decreasing in numbers across
all substrata. This could be due to the scavenging assemblages being quite transient (24
to 48 hours) and form shortly after a trawling event has occurred (Bergmann et al.,
2002). Therefore our current trawling data is not sufficient to detect these abundance
changes as it does not overlap with our camera data.
19
Trawling Impact on the Greenlandic Benthos
Soft substrata organisms may be more susceptible to trawling than previously
thought. This can be attributed to the frequency at which they face disturbance. The
overall effect of trawling on hard substrata is not entirely clear. It is likely that with
increased trawling intensity the diversity levels would be similar to those we found for
soft substrata.
We highlight the need for consistent taxonomic level identification (i.e. all
individuals
counted
to
be
recorded
at
only
order
or
family
level).
This study may aid in the outlining of sustainable management plans for the
Greenlandic shrimp fishery. If they prove successful, they can be implemented on a
wider scale. Furthermore these findings may serve as a basis of creating a policy
framework which may benefit in increasing the nation’s economic and environmental
capital.
Acknowledgements:
Many thanks to Andrew Croft Memorial Fund and Percy Sladen Memorial Fund for
making my participation in the field collection of this project possible.
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Appendix 1: Detailed Camera settings used for image capture
Shutter speed
1/100 sec
Distance bottom
80 cm
frame to camera lens
Focus distance
70 cm (manual)
F-stop
11
Programme
Manual (M)
WB
Flash
ISO
100
(Kemp, 2011)
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Trawling Impact on the Greenlandic Benthos
Appendix 2: Taxa found in the surveys from 2011 and 2012. Taxa designated as VMOs have been highlighted.
Taxa
Total
Soft Coral
197
Sea fans/pens
3
Anemones
117
Zoanthids
906
Hydroids
584
Stylasterina
1479
Asteriidae
4
Pterasteridae
5
Echinasteridae
15
Solasteridae
5
Goniasteridae
9
Astropectinidae
2
Starfish (other)
1
Brittle stars
5461
Sea urchins
50
Sea cucumbers
142
Crinoids
45
Encrusting Sponges
460
Massive Sponges
1646
Arborescent Sponges 229
Sabellidae
713
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Eunicidae
636
Serpulidae
299
Aphroditidae
0
Polynoidae
1
Decapoda
51
Amphipoda
0
Isopoda
76
Sea Spiders
12
Gastropoda
39
Chitons
43
Bivalves
208
Scaphopoda
8
Sepioida
0
Octopoda
2
Terebratulida
161
Erect Bryozoans
944
Encrusting Bryozans
1203
Soft Bryozoans
142
Ascidians
3978
Rajiformes
1
Scorpaeniformes
1
Peciformes
4
Pleunectiformes
3
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Trawling Impact on the Greenlandic Benthos
Appendix 4: Image quality classification
An image classified as high quality
An image classified as medium quality
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An image classified as low quality
29
Trawling Impact on the Greenlandic Benthos
4
3
2
log(No. of individuals)
5
6
7
Appendix 5: Linear Regression Graphs - Number of individuals vs Trawling Impact
Substrate type
1
hard
soft
0
10
20
30
40
50
0
2
6
5
4
3
Substrate type
hard
soft
1
hard
soft
2
log(No. of individuals)
6
5
4
3
2
Substrate type
1
log(No. of individuals)
7
7
Total Trawling Impact
4
6
8
0
10
2
4
6
8
10
log(Trawling Impact 2006-2010)(mins)
log(Trawling Impact 1986-1990)(mins)
30
0.5
1.0
Shannon Index VMOs
1.5
Irina Chemshirova
Appendix 6: Linear Regression Graphs VMO Shannon vs Trawling Impact
Substrate type
0.0
hard
soft
0
10
20
30
40
50
1.5
1.0
Substrate ty pe
hard
sof t
0.0
hard
sof t
0.5
Shannon Index VMOs
1.5
1.0
0.5
Substrate ty pe
0.0
Shannon Index VMOs
Total Trawling Impact
0
2
4
6
8
0
10
2
4
6
8
10
log(Trawling Impact 2006-2010)(mins)
log(Trawling Impact 1986-1990)(mins)
31
Trawling Impact on the Greenlandic Benthos
4
3
2
1
log(No. of VMO individuals)
5
6
Appendix 7: Linear Regression Graphs VMO Number of individuals vs Trawling Impact
Substrate type
0
hard
soft
0
10
20
30
40
50
hard
soft
0
2
4
6
8
6
5
4
3
2
1
Substrate type
hard
soft
0
log(No. VMO of individuals)
6
5
4
3
2
1
Substrate type
0
log(No. of VMO individuals)
Total Trawling Impact
0
10
2
4
6
8
10
log(Trawling Impact 2006-2010)(mins)
log(Trawling Impact 1986-1990)(mins)
32
1
2
3
4
log(No. of Brittle stars)
5
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Irina Chemshirova
Appendix 8: Linear Regression Graphs Number of Brittle stars vs Trawling Impact
Substrate type
0
hard
soft
0
10
20
30
40
50
4
3
2
Substrate ty pe
1
hard
sof t
5
log(No. of Brittle stars)
6
6
5
4
3
2
1
Substrate ty pe
hard
sof t
0
0
log(No. of Brittle stars)
Total Trawling Impact
0
2
4
6
8
10
0
log(Trawling Impact 1986-1990)(mins)
2
4
6
8
10
log(Trawling Impact 2006-2010)(mins)
33