Edited by: Trevor John Willis, University of Portsmouth, United Kingdom
Reviewed by: Silvia De Juan Mohan, Instituto de Ciencias del Mar (ICM), Spain; Peter J. Auster, University of Connecticut and Mystic Aquarium, United States
This article was submitted to Marine Conservation and Sustainability, a section of the journal Frontiers in Marine Science
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Marine benthic habitats are modified by a number of human-related disturbances. When these disturbances occur at large scales over areas of high environmental variability, it is difficult to assess impacts using metrics such as species richness or individual species distributions because of varying species-specific responses to environmental drivers (e.g., exposure, sediment, temperature). Impact assessment can also be problematic when assessed at broad spatial scales because of regional heterogeneity of species pools. Even when effects on individual species can be detected, it is difficult to upscale from individual species to ecosystem scale effects. Here, we use a functional group approach to assess broad scale patterns in ecological processes with respect to fishing and environmental drivers. We used data from field surveys of benthic communities from two large, widely separated areas in New Zealand’s EEZ (Chatham Rise and Challenger Plateau). We assigned 828 taxonomic units (most identified to species) into functional groups related to important ecosystem processes and likely sensitivity to, and recovery from, fishing disturbance to the seafloor. These included: opportunistic early colonists; substrate stabilisers (e.g., tube mat formers); substrate destabilisers; shell hash-creating species; emergent epifauna; burrowers; and predators and scavengers. Effects of fishing disturbance on benthic functional composition were observed, even at this broad spatial scale. Responses varied between functional groups, with some being tolerant of fishing impacts and others showing rapid declines with minimal fishing effort. The use of a functional group approach facilitates assessment of impacts across regions and species, allowing for improved generalisations of impacts to inform management and decision making.
Assessment of impacts of human and natural disturbances on seafloor communities is challenging (
Functional group approaches are a potential tool to elucidate the roles of particular species in maintaining ecosystem structure and function across regionally heterogeneous species pools, and inform generalisations about the scales of disturbance at which diverse communities can persist (
The analysis of biological traits has proved to be a useful approach, highlighting community responses which are difficult to detect using an individual or key species approach, due to high natural spatial and temporal variability in individual species abundance (e.g.,
Physical disturbances to the seafloor by fishing trawls and dredges can modify habitats and reduce biodiversity and productivity through their effects on a range of species, including those that provide biogenic structure (e.g., sponges, tubeworms, anemones), or modify the sediment (
Here, we use an extensive dataset of benthic faunal distributions covering > 200,000 km2 on Chatham Rise and Challenger Plateau, New Zealand, to investigate the suitability of a functional group approach to determining impacts of bottom fishing disturbance on benthic communities. We investigate patterns of abundance of individuals within functional groups in relation to fishing effort at broad spatial scales, as well as with physical correlates of natural disturbance and other environmental drivers that may be influencing abundance. Eight functional groups were defined through expert elicitation, representing key aspects of the way organisms in seafloor communities modify their environment and interact with each other, and how they would respond to and recover from disturbance to the seafloor (
Chatham Rise is east of New Zealand in the Pacific Ocean, while Challenger Plateau is in the Tasman Sea, to the west of New Zealand. Both regions were sampled as part of Ocean Survey 20/20 voyages that surveyed extensive areas (>200,000 km2) of New Zealand’s EEZ (
Sites sampled for benthic invertebrate assemblages across Chatham Rise (East of the South Island) and Challenger Plateau (West of the North Island) during Ocean Survey 20/20 voyages TAN0705 and TAN0707. Filled dots were sampled with both DTIS video and SEL epibenthic sleds; open circles were sampled with DTIS video only.
Video transect data (
Environmental variables were available for a range of metrics from the New Zealand Marine Environments Classification database (Table
Environmental variables available for Chatham Rise and Challenger Plateau.
Variable | Description | Reference | Mean | Median | Max | Min |
---|---|---|---|---|---|---|
Tidal current | Maximum depth–averaged tidal current velocity (m s-1) was calculated from the NIWA Tide Model and interpolated across the EEZ classification grid. | 0.19 | 0.18 | 0.76 | 0.03 | |
Seabed slope | Seabed slope was calculated from multi-beam analysis as the rate of change of slope for each cell (25 m × 25 m) and computed for each grid cell by analysis of the surrounding cells in the bathymetry grid. | 0.72 | 0.42 | 5.81 | 0.01 | |
Seabed roughness | Multi-beam bathymetry was used to develop a rugosity grid as a measure of roughness and complexity of the seafloor based on standard deviation of depths in a 3 × 3 cell neighbourhood. | 10.23 | 6.14 | 71.49 | 0.17 | |
Primary productivity (VGPM) | Satellite ocean colour data during the period 1997–2006 was used to estimate primary productivity using the Vertically Generalised Production Model (VGPM). | 590.7 | 587.7 | 838.1 | 402.3 | |
Depth | Maximum depth (m) at each station was estimated from ship-board multi-beam sonar. | 747 | 662 | 1950 | 64 | |
Sediment grain size from core samples | Sediment samples were collected by multi-corer and by pipe dredges attached to the epibenthic sled. Sediment grain size composition was determined from oven-dried sub-samples by sieving (sand and gravel fractions: >500 mm, 250–500 mm, 125–250 mm, 63–125 mm) and by Sedigraph techniques to calculate mud content (silt and clay fractions < 63 mm). Values presented are percent mud content. | 48.3 | 46.7 | 97.9 | 0 | |
Sediment grain size from video observations | Sediments were also characterised from visual observations in DTIS Video transects. Visually identified categories included bedrock, boulders, cobbles, pebbles, gravel, sand, muddy sediment, coral rubble, epifauna (high density), epifauna (low density), shell hash, and shell-coral hash. Values presented are percent muddy sediment. | 84.6 | 100 | 100 | 0 |
Extensive areas of Chatham Rise and parts of Challenger Plateau are commercially fished. Data on the intensity and frequency of bottom trawling by commercial fishing vessels were sourced from the New Zealand Ministry for Primary Industries for the 16 years from 1989–1990 to 2004–2005 at depths to 1600 m, the maximum recorded trawl depth in the region during this period (
Fishing effort was generally lower on Challenger Plateau than on Chatham Rise (
Fishing effort classes for Ocean Survey 20/20 Chatham Rise and Challenger Plateau datasets used to compare functional group abundance at site replicates.
Stratum | Cumulative fishing effort (% of total seascape disturbed over 16 years, 1990–2005) | Annual fishing effort (% of total seascape disturbed per annum) | Number of site replicates (Chatham sites) | Number of site replicates (Challenger sites) |
---|---|---|---|---|
Absent | 0 | 0 | 7 | 14 |
Very low | 0.01–1.00 | 0.01–0.06 | 46 | 8 |
Low | 1.01–5.00 | 0.06–0.31 | 22 | 8 |
Medium | 5.01–25.00 | 0.31–1.56 | 17 | 8 |
High | 25.01–57.80 | 1.56–3.61 | 6 | 4 |
Functional groups were selected through expert elicitation (as described in
General description of fauna classified under eight conceptual functional groups based on key functional traitmodalities.
Functional group | Typical taxa | Traits used to derive group membership |
||||||||
---|---|---|---|---|---|---|---|---|---|---|
Mobility (R,E) | Feeding (E) | Longevity (R) | Size (R,E) | Habitat structure (E) | Living position in sediment (R) | Form (R,E) | Sediment moving (E) | |||
1 |
Opportunistic early colonists – limited substrate disturbance | Sedentary species (e.g., paraonid and capitellid polychaetes) | Sedentary or only moving within fixed tube structure | Deposit feeding | Short-lived | Small (0.5 – 5 mm longest dimension, exclusive) | n/a | Top 2 cm | n/a | Surface mixing |
2 |
Opportunistic early colonists – considerable |
Mobile deposit feeders and small scavengers (e.g., phoxocephalid amphipods and other small crustaceans) | Limited free movement, e.g., withdrawal into sediment; OR Freely motile in or on sediment | Deposit feeding | Short-lived | Small (0.5 – 5 mm longest dimension, exclusive) | n/a | Top 2 cm | n/a | Surface mixing |
3 |
Substrate stabilisers (Tube mat formers) | Tube mat forming polychaetes (e.g., spionid, sabellid and chaetopterid polychaetes) and tube-building amphipods (e.g., |
Sedentary or only moving within fixed tube structure | Deposit feeding OR Suspension feeding | Intermediate or long-lived | n/a | Tube | n/a | n/a | Surface (top 2 cm)-to-deep (>2 cm deep) OR Deep-to-surface |
4 |
Substrate |
Spatangoid echinoids (e.g., |
Freely motile in or on sediment | Deposit feeding | Intermediate-lived | Medium (5–20 mm longest dimension, exclusive) | n/a | Top 2 cm | n/a | Surface mixing |
5 |
Shell hash-creating species | Bivalves, gastropods | n/a | n/a | n/a | n/a | n/a | n/a | Contains calcium carbonate | n/a |
6 |
Late colonisers – emergent epifauna | Sponges, bryozoans, sea pens, sea whips, ascidians, gorgonians – primarily sedentary suspension feeders | Sedentary or only moving within fixed tube structure | Suspension feeding | Long lived | Medium (5–20 mm longest dimension, exclusive) OR Large (≥20 mm longest dimension) | n/a | Protruding above sediment surface; OR Attached to other animals or small hard surfaces | n/a | n/a |
7 |
Late colonisers – burrowers | Shrimps, crabs, large burrowing polychaetes | Limited free movement, e.g., withdrawal into sediment; OR Freely motile in or on sediment | n/a | n/a | Medium (5-20 mm longest dimension, exclusive) OR Large (≥20 mm longest dimension) | Permanent burrow | Deeper than 2 cm | n/a | Deep-to-surface; OR Deep mixing |
8 |
Predators and scavengers | Starfish, crabs, hermit crabs, large-bodied predatory worms | Freely motile in or on sediment | Predator OR scavenger | n/a | Large (≥20 mm longest dimension) | n/a | Protruding above sediment surface; or Top 2 cm | n/a | n/a |
Fuzzy coding (e.g.,
Recognising the benefits and limitations of both DTIS and SEL datasets at enumerating all functional groups (see Results), we combined data from both sampling methods to derive functional group composition at each sampling location. Relative abundances of functional groups at each site were calculated by summing abundance across all species allocated to each functional group at a site, calculated independently for DTIS and SEL samples. For sites at which both DTIS and SEL were used (
The effect of trawling on the abundances of individual functional groups was investigated. As a linear response was not expected for all functional groups, and sampling locations were distributed unequally across the fishing effort gradient observed in the regions, a categorical variable of fishing intensity was developed, using five classes based on visual analysis of data clusters of trawl effort. Fishing classes represented a gradient from no fishing (‘absent’, 0%) and very low (0.01 – 1% cumulative fishing effort within a cell over 16 years of available trawl data), to high fishing (rates of 25–57% of the area in a cell trawled within a 16 year period; Table
Potential drivers of functional communities including both fishing metrics and environmental drivers were examined using canonical ordination (DISTLM; Primer software version 6 plus PERMANOVA;
In general, SEL datasets sampled a larger total number of taxa than DTIS, with more diversity of taxa within functional groups. Relative proportional abundances of each functional group were typically similar for those sites that were sampled using both DTIS and SEL, though taxonomic differentiation was typically higher in SEL with taxonomic entities typically identified to species, whereas DTIS methods allowed for identification to functional group, but not always to species (i.e., orange globulous sponge #1). In functional group 6 (emergent epifauna), for example, more than 100 individual taxa were recorded from DTIS samples, but more than 200 were recorded from SEL samples. Functional groups differed in relative abundance with 156 and 298 individual taxa (typically species) enumerated for group 4 and 6, respectively. In particular, small-bodied taxa (primarily groups 1 and 2) were poorly enumerated in both SEL and DTIS data, resulting in few taxa being classified to these two smaller, opportunistic functional groups (Table
Response to fishing disturbance differed between the eight functional groups, generally supporting our hypotheses (Figure
Abundance of each functional group for the Ocean Survey 20/20 offshore dataset for different fishing effort classes. Abundance values for groups 4 and 6 are plotted on the secondary y axis. Error bars represent one standard error.
Variability of abundances within each functional group was also affected by fishing disturbance (Table
Coefficient of variation (CV) between fishing effort classes and functional group abundance.
Functional group CV | ||||||
---|---|---|---|---|---|---|
Fishing effort class (% of total seascape disturbed over 16 years) | 3 | 4 | 5 | 6 | 7 | 8 |
Absent (0) | 259.3 | 548.6 | 154.6 | 541.8 | 137.9 | 109.2 |
Very low (0.01–1.00) | 301.1 | 527.1 | 210.5 | 259.9 | 136.0 | 132.1 |
Low (1.49–7.26) | 227.9 | 314.5 | 249.7 | 218.5 | 100.0 | 136.6 |
Medium (8.00–13.65) | 246.3 | 281.5 | 145.3 | 161.3 | 77.0 | 151.0 |
High (16.27–34.37) | 109.2 | 106.8 | 98.1 | 28.7 | 69.9 | 144.3 |
Not surprisingly, abundances of the six functional groups showed complex and non-linear patterns with respect to individual environmental variables (Figures
Abundance of each functional group for the Ocean Survey 20/20 offshore dataset for environmental variables:
Only minor amounts of overall variability in functional composition were explained by the environmental variables and the continuous fishing effort data used in the ordinations, with 3 and 7.5% of the variability explained for the full dataset and for the sediment data subset, respectively. However, in both cases, fishing effort data was significantly related to variation in functional community composition. For the full dataset, the only variables selected by the DISTLM to explain the variability in functional composition were proportion of the area swept by trawling over 16 years and the maximum count of fishing trawls in a cell over the same time period. For the sediment data subset, six variables were selected: maximum depth; proportion of the area swept by trawling over 16 years; total area swept by trawling over the same time period; sand; mud; and tidal current. Forcing the model to only use the fishing effort related variables (proportion of area swept and total area swept) resulted in 3% explained, the same amount as for the full dataset. A forward selection procedure, restricted to the six variables, selected sand first (1.2% explained), followed by mud (3.3%), total area swept (0.9%), proportion swept (1.4%), depth (0.07%) and finally tidal current (0.02%). These results suggest overlapping effects between fishing effort and the other variables and between tidal current, depth and the other variables. However, the overlap between fishing effort and the other variables was small as the difference between the amount explained when only fishing effort variables were used (3%) was little different to that when the other variables were allowed to be selected first [0.9% (total area swept) + 1.4% (proportion swept) = 2.3% cf. 3%].
Our results suggest that we can use functional groups to generalise predictions of the impacts of seafloor trawling disturbance across benthic communities within diverse seafloor communities across broad geographic regions. Even with potentially confounding factors of high environmental variability (depth, sediment, exposure) and differing regional species pools, the functional group approach resulted in fishing effort being selected as an important predictor of benthic functional group composition in New Zealand’s EEZ. The low percent explanation is not uncommon in multivariate ordination techniques, due to (i) the inclusion of a large gradient across both fishing and environmental variability, and (ii) the limited number of samples, including both intrusive (benthic sled) and non-intrusive (video) sampling methods (
Our analyses suggest shifts in functional composition with increased fishing effort, with largest declines in functional groups representing emergent epifauna and substrate destabilisers (e.g., surface burrowers like
These different functional responses and reductions in functional groups at different levels of fishing effort suggest increased functional homogenisation with disturbance, as less tolerant functional groups are excluded with increasing rates of disturbance, and functional diversity is reduced (
Declines in abundance and composition of particular functional groups support broad generalisations about the effects of fishing on ecosystem functions. Emergent epifauna showed the largest declines with increasing fishing effort, and declines in this group would be predicted to result in declines in biogenic habitat structure, the provision of settlement habitat and refuge sites from predation, modification of biogeochemical processes and exchanges, modification of flows, and sediment stabilisation (
Others have shown significant environmental drivers that are associated with either sensitivity or resilience to seafloor disturbance (
High resolution spatial data on fishing activity have been available since 1989 for the study areas but commercial bottom-contact trawl fishing goes back to the early 1970s (
The functional group approach is useful and provides a first, high-level, analysis showing effects of bottom contact trawl fisheries. Some challenges in our broad analysis include the minimal replication across the full range of fishing disturbance in the benthic datasets, and low replication of samples within coarser sediment regions. Despite these factors, our results still indicate significant impacts of fishing effort, and the lack of coarse sediments being selected as an important predictor suggests this will not be a major factor affecting our ability to detect fishing impacts. Others have suggested (e.g.,
The sampling methodology did not accurately represent all functional groups, particularly smaller opportunistic taxa. We combined video and infaunal (epibenthic sled) sampling to allow us to obtain broader scale information on more widely distributed, larger taxa such as epifauna, while concurrently collecting adequate data to quantify abundance of smaller, infaunal taxa, but recognise that our infaunal sampling (mesh = 25 mm) was not sufficient to estimate abundance of small, opportunistic species. Regardless, our analysis, conducted with both intrusive (benthic sled) and non-intrusive (video) sampling techniques provides indications of validity of using remote techniques to determine benthic community structure and potential responses to impacts across both large spatial scales, and in deep areas where remote sampling is the most cost-effective option.
The conceptual functional groups used here represent broadly applicable functional roles important for assessing impacts on and recovery from seafloor disturbances, and also ecosystem processes that affect integrity. As such they would be useful to apply to a variety of situations and the results should be easily transferable to different regions where functional trait data are available. The responses to disturbance we observed within functional groups across broad spatial scales and regional species pools suggests that we can populate a conceptual model of a generalised recovery trajectory in order to advance our understanding of the role of disturbance on marine community dynamics, as is indeed our intention (
CL and JH developed the conceptual design and performed the statistical analyses. KC and FS assisted with data collation and preparation of tables and figures. DB, JH, and IT designed the initial OS 20/20 sampling strategy. CL drafted the manuscript, assisted by DB, FS, IT, and JH.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank Mary Livingston and the Ministry for Primary Industries, Biodiversity Research Advisory Group, for supporting this research, and for constructive advice throughout this project.