The impacts of two Antarctic stations in different regions, on marine sediment macrofaunal communities were compared: McMurdo, a very large station in the Ross Sea; and Casey, a more typical small station in East Antarctica. Community structure and diversity were compared along a gradient of anthropogenic disturbance from heavily contaminated to uncontaminated locations. We examined some of the inherent problems in comparing data from unrelated studies, such as different sampling methods, spatial and temporal scales of sampling and taxonomic uncertainty. These issues generated specific biases which were taken into account when interpreting patterns. Control sites in the two regions had very different communities but both were dominated by crustaceans. Community responses to anthropogenic disturbance (sediment contamination by metals, oils and sewage) were also different. At McMurdo the proportion of crustaceans decreased in disturbed areas and polychaetes became dominant, whereas at Casey, crustaceans increased in response to disturbance, largely through an increase in amphipods. Despite differing overall community responses there were some common elements. Ostracods, cumaceans and echinoderms were sensitive to disturbance in both regions. Capitellid, dorvelleid and orbiniid polychaetes were indicative of disturbed sites. Amphipods, isopods and tanaids had different responses at each station. Biodiversity and taxonomic distinctness were significantly lower at disturbed locations in both regions. The size of the impact, however, was not related to the level of contamination, with a larger reduction in biodiversity at Casey, the smaller, less polluted station. The impacts of small stations, with low to moderate levels of contamination, can thus be as great as those of large or heavily contaminated stations. Regional broad scale environmental influences may be important in determining the composition of communities and thus their response to disturbance, but there are some generalizations regarding responses which will aid future management of stations.
Citation: Stark JS, Kim SL, Oliver JS (2014) Anthropogenic Disturbance and Biodiversity of Marine Benthic Communities in Antarctica: A Regional Comparison. PLoS ONE 9(6): e98802. https://doi.org/10.1371/journal.pone.0098802
Editor: James P. Meador, Northwest Fisheries Science Center, NOAA Fisheries, United States of America
Received: October 28, 2013; Accepted: May 6, 2014; Published: June 11, 2014
Copyright: © 2014 Stark et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Work at Casey Station was supported by the Australian Antarctic Division (www.antarctica.gov.au/) under AAS project 2201. Work at McMurdo Station was supported by the National Science Foundation under Grant Nos. DPP 8914858, OPP 97961111, OPP 9615849, OPP 59088 and OPP 0126399. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Understanding the ecological consequences of disturbance from Antarctic stations is important in the management and prevention of environmental impacts. A total of 31 countries operate 82 seasonal or year-round research stations in Antarctica , the majority of which are located in coastal areas , , however, currently there is little known of the impacts of these stations on marine environments. Clearer understanding of the way in which Antarctic coastal ecosystems respond to disturbance, together with proven methods for detecting impacts and assessing biodiversity, will aid operators and policy makers attempting to improve environmental management of research stations. Although the response of benthic communities to disturbance has been well studied in tropical and temperate regions, these cannot necessarily be generalized to polar regions. Countries managing stations need the ability to easily assess their potential impacts and understand them in a Antarctic-wide context. This includes assessing local biodiversity in comparison to regional and Antarctic wide biodiversity and how it is impacted. An understanding of the relative size or nature of an impact will aid in decisions regarding its management or remediation. The remediation of environmental damage, and marine spatial protection and management, have both been identified as high priority issues by the Committee for Environmental Protection (CEP) of the Antarctic Treaty Consultative Parties (ATCP) . The need for assessment of biodiversity in regional planning has also been highlighted by recent international endorsements of marine protected areas (MPA) as a management tool, such as by the World Summit on Sustainable Development  and the World Parks Congress . The Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR), together with the CEP, have made a commitment to work towards creation of an MPA network in Antarctica. This study aims to increase our understanding of the way in which Antarctic coastal benthic communities respond to anthropogenic disturbance and improve approaches to the detection and assessment of the size and nature of impacts of Antarctic stations. We also examine the regional assessment and comparison of biodiversity, a key component in MPA planning.
Most stations are located in coastal ice free areas , , which are biologically important as habitats for terrestrial plants (e.g. moss and lichen), breeding birds (e.g. penguins and petrels) and highly diverse coastal marine ecosystems, particularly of benthic communities , . Coastal ice-free land comprises less than 0.01% of the continent  and correspondingly, coastal shallow water marine ecosystems are rare in Antarctica. Shallow water habitats are isolated by large expanses of continental ice, glaciers, ice shelves and deep water and can be considered as “islands” in their lack of connection to each other. Genetic research indicates highly limited connectivity between these areas for some species –. Activities associated with stations known to cause environmental impacts include fuel and oil spills, landfill and marine waste disposal sites, and sewage and wastewater disposal. As stations are generally situated very close to the coast for ease of access, these activities can cause impacts on marine benthic communities , . Thus environmental impacts in these areas, even if only local in scale and limited to the vicinity of Antarctic stations, will have implications greater than might at first appear to be the case in an Antarctic-wide context. This is due to stations being located in habitat that is rare, isolated and biologically important. Antarctic benthic communities are particularly vulnerable to environmental impacts due to their slow recovery from disturbance, the high proportion of brooding and poorly dispersing species , and the highly variable spatio-temporal nature of primary production . Many stations have been established for up to 50 years and with the number of bases and tourism on the increase these ecosystems will come under increasing pressure. Antarctic marine ecosystems are forecast to be particularly vulnerable to climate change , –, which may further exacerbate potential impacts of stations.
Environmental impact research in Antarctic coastal marine habitats has been done extensively at two stations: McMurdo (USA) in the Ross Sea; and Casey (Australia) in East Antarctica. These stations are of similar ages, established around the International Geophysical Year (IGY) in the late 1950’s, however, in most other aspects they are very different. McMurdo is atypical of Antarctic stations: it is very large (population 200–1500 people), it has had activities not found elsewhere in Antarctica (e.g. a nuclear power station, military base) and in places it is as highly polluted as industrial harbours in other parts of the world –, and in these aspects it is unique. Casey is more representative of the majority of stations: it is small (15–75 people) with less infrastructure, and pollution levels are much lower than McMurdo , . Marine environmental impacts have been detected at both stations , , –. Environmental impact and biodiversity assessments are expensive and time consuming, particularly in Antarctica. Antarctic marine benthic research is generally fragmented, patchy in distribution, limited in extent and focused on small areas adjacent to or nearby each nation’s area of operations or station locations. This is due to the isolation of Antarctic stations on “islands” of ice-free rock and their operation by different countries. Opportunities to sample widely around Antarctica concurrently, using the same methods and sampling design, are unlikely and thus the only realistic way comparisons of regional response to human impacts can be made is with existing data from different studies . Comparing data from different studies is hampered by a range of issues as research is conducted for different reasons by scientists from different countries, using differing methodologies, sampling designs, processing and identification, and at different spatial and temporal scales –.
Measurement of diversity, commonly recorded as species richness, is central to ecological theory and conservation strategies and is affected by spatial scale and sampling effort , , . Description and comparison of community diversity is best done in a well defined spatial framework , . Some of the difficulties in comparing biodiversity assessments from different studies can be avoided or reconciled by using species-area relationships and species accumulation and rarefaction curves , . Comparing species-area curves from different studies requires a common or standardized sampling unit , . Sample based and individual based rarefaction methods allow the meaningful comparison of standardized datasets , . Thus when attempting comparisons it is vital to understand the limitations inherent in the data and its interpretation. Some of these issues associated with comparing biodiversity estimates from different studies have been examined by various authors –, , .
This study compares soft-sediment infaunal communities near McMurdo and Casey using previously unrelated studies to explore the nature and extent of responses of soft-sediment communities to anthropogenic contamination and disturbance in Antarctica. We examine issues of methodological bias, sampling effort, taxonomic uncertainty in comparisons of different studies, and effects of spatial scale on measures of biodiversity. We describe responses to anthropogenic disturbance of communities at species and higher taxonomic levels, effects on biodiversity, identify potential indicator organisms and compare the relative size of impacts at each station. This information will enable more rapid assessment and early detection of environmental impacts at other Antarctic Stations, leading to improved environmental management.
Materials and Methods
Casey station is situated in the Windmill Islands in East Antarctica at 66° 17′S, 110° 32′E (Fig. 1). The data used for the Casey region comes from a survey done in the summer of 1997/98. Sampling design and details can be found in Stark et al. . In summary: samples were taken by divers using hand held cores (10 cm diam.×15 cm long), inserted into the sediment up to 10 cm; samples were taken from 9 locations over an 8 week period between October and December 1998 with a hierarchical spatially nested sampling design with 3 scales (plots = 10 s of metres, sites = 100 s of metres and locations = 1000 s of metres); 16 samples were taken at each location (4 replicates within a 2 m diam. plot, 2 plots within a site, 2 sites within a location); one location was sampled twice over the sampling period; there were a total of 160 samples used in this data set (Table 1); samples were sieved on a 1 mm mesh and sorted; a subset (4 locations) were sieved and sorted at 0.5 mm; taxa were identified to species, or morphospecies where identifications were uncertain or could not be reliably made.
McMurdo Station is situated on Ross Island at 77° 51′S, 166° 40′E in the Ross Sea. The data used for McMurdo comes from a ten year period of sampling from 1988 to 1998. Sampling details can be found in Lenihan and Oliver . In summary samples were taken by divers with a hand held corer (10 cm diameter) from 8 locations, generally with a minimum of 6 replicate cores per location with some locations sampled at several water depths (Table 1). In total there were 325 samples used in this data set. Samples were sieved on a 0.5 mm mesh and identified to species or morphospecies where identifications were uncertain or could not be reliably made.
All necessary permits were obtained for the described field studies. Collections from Casey were approved by the Commonwealth of Australia under the Antarctic Marine Living Resources Act 1981, under permit AMLR 98/10. No special permits are required for invertebrate collections from McMurdo.
In this study we compare numerical species richness within a specified spatial framework, which takes into account sampling effort and the spatial extent of sampling, which have been shown to be important in comparisons of biodiversity , . We have used the following terminology from Gray  to distinguish spatial scales of comparison and sample size, relating to numerical species richness (SR).
- Point species richness: SRP The species richness (number of species) of a single sampling unit.
- Sample species richness: SRS The species richness of a number of sampling units from a site of defined area.
- Large area species richness: SRL The species richness of a large area which includes a variety of habitats and assemblages.
- Habitat species richness: SRH The species richness of a defined habitat.
We also used species-area curves to compare species richness in both regions and at control and disturbed locations. In addition to species accumulation curves based on the number of species observed we employ several non-parametric asymptotic estimators of species richness (Chao-2, Jacknife-1 and Jacknife-2) to estimate the likely lower-bounds of overall species richness in each region. These methods are currently regarded as the most suitable for estimating the minimum number of species in an assemblage ,  and are particularly useful where the observed species richness curves have not reached an asymptote . Species accumulation/rarefaction curves were calculated using the program PRIMER (V 6.1.13).
A wide variety of indices have been used to describe the two components of species diversity: richness and evenness. We use observed species richness and species-area plots, which show the actual number of species living in a range of comparable areas, regardless of any statistical relationships between the number of species and number of individuals. We have chosen not to use the commonly utilised index H’ (the Shannon-Wiener index) due to well documented criticism of the difficulty in biological interpretation , – and non-suitability for environmental quality assessment . We have also avoided use of the evenness index J as it is derived from H’. Instead we employ Simpson’s index, λ,  as it is relatively unaffected by sample size, is more intuitively meaningful and has greater utility in a range of contexts, as reviewed by Magurran  and assessed by other authors , –.
Sampling Bias from Mesh Size
The potential effects of using a 1 mm sieve as opposed to a 0.5 mm sieve are underestimates of species richness and abundance in samples sieved using a 1 mm screen. We compared 4 locations (16 replicates per location) at Casey using both mesh sizes. Abundance was on average 1.49 (0.11 SE) times greater per sample in 0.5 mm samples (range: 1.21–1.75). Species richness was on average 1.17 (0.03 SE) times greater on a per sample basis using a 0.5 mm mesh (range: 1.11–1.25). When species richness was considered cumulatively, per location (4 locations, n = 16 per location), this effect was reduced with a mean of 1.10 (0.06 SE) times greater number of species per location using a 0.5 mm mesh (Fig. 2). This effect of mesh size was further reduced when species richness was calculated cumulatively over all 4 locations (n = 64), with only 1.05 times more species on a 0.5 mm mesh (Fig. 2). Thus, as the sample size increases, the difference in the cumulative number of species captured on a 1 mm vs. 0.5 mm mesh decreases. On an even larger data set, such as the 160 samples from Casey used in this study, we assume that the sample bias on species richness would be negligible.
In many regions of the world, particularly remote and difficult to access areas such as Antarctica, there remains great taxonomic uncertainty and a paucity of taxonomic resources such as identification keys. In addition, modern taxonomic tools such as DNA sequencing are revealing a wide degree of cryptic speciation among otherwise nearly identical species, and there are numerous examples from Antarctica , , . A large degree of uncertainty exists in identification of whole communities of taxa to species level when comparing species sampled in different studies, without the direct matching of actual specimens from different regions, particularly when morphospecies identifications are used when species cannot be reliably identified. We did not compare community patterns in the same analysis using species level identifications. The infaunal species from each station were identified by different scientists in different countries and no direct comparisons of individual species were made to confirm the same identities. To overcome this, a higher level of taxonomic resolution was used, as there is far less uncertainty in identifications at higher levels. In comparisons of assemblage patterns and their response to anthropogenic impacts, the two assemblages were directly compared at the level of family, and for some taxa a higher taxonomic unit was used such as order or class. Thus the assemblage response to disturbance in each region is presented at the family level. This has been shown to be as effective as species level identifications for detecting impacts , .
We define disturbance for the purposes of this paper as being of anthropogenic origin, such as pollution. We did not include natural disturbances such as ice scour, as the sites used in this study were selected, within each region, to be as similar as possible with respect to physical characteristics such as duration of ice cover and exposure to ice scour. The sites used in this study are ice covered for most of the year, being ice free for only short periods of 2 to 8 weeks in late summer (e.g. ) and with some sites ice covered year round in some years. Thus they are largely protected from the impacts of ice scour from floating sea ice and ice bergs. In addition, no sites were shallower than 6 m depth or within 50 m of shore and thus not in the zone of ice foot scour e.g. .
Casey and McMurdo have very different histories, although both areas have been occupied continuously for a similar period. Different levels of contamination have occurred at each station, largely a result of their different sizes, but the general types of activities at each station are similar such as waste disposal, hydrocarbon contamination from leaks and spills, and sewage disposal. Waste disposal sites located on or very close to the shoreline were perhaps the most significant source of contamination at both stations, but sewage outfalls are also a significant source of organic enrichment and contaminants at each station. Contamination of the marine environment has been well documented at McMurdo , –, , ,  and Casey , , , , , .
The disturbed sites at Casey include Brown Bay, which is adjacent to a waste landfill site that operated for a period of 22 years (1965–1986). Waste disposed here consisted of building materials, metal, waste oil, chemicals, machinery and equipment, electronic components and food wastes . Waste was also bulldozed into the bay and this remains on the seabed in Brown Bay. The marine environment adjacent to the Casey Wharf has been subjected to a range of disturbance including a large fuel spill in 1991 , physical disturbance from the propeller wash of boats and the seabed is also strewn with rubbish and metallic items dropped from resupply vessels. A sewage outfall discharges secondarily treated wastewater into Shannon Bay and for some periods over summer the treatment system is bypassed due to limited treatment capacity. The site of Wilkes is adjacent to another abandoned waste disposal site at the former station of Wilkes, which operated from 1957 until 1969.
At McMurdo the disturbed sites include Winter Quarters Bay (WQB), the ice-dock site of fuel and cargo resupply activities, adjacent to the mechanical workshops as well as a landfill waste disposal site situated on the foreshore the bay which operated between 1955 and the late 1980’s. Waste was also doused with fuel and burnt on the site as well as being deposited onto the sea ice . WQB has a long history of contamination and the McMurdo wastewater outfall is also a known source of organic enrichment and chemical contamination , , , . The wastewater outfall discharged untreated effluent until 2003 when a secondary treatment plant was installed .
Data on contaminant levels in marine sediments are largely taken from other studies. Different methods were used to measure metals (Casey , McMurdo ) but comparison among stations takes methodological biases into account. At McMurdo a strong acid (conc. HNO3) digest was used on the sediments , while at Casey both a strong acid (conc. HNO3+ conc. HF)  and a weak acid (1 M HCl) partial digest were utilised .
Different methods were also used to measure organic carbon in sediments in each region. At Casey a loss-on-ignition method was used and a correction factor (division by 1.8) was applied to convert from total organic matter to give an estimate of % organic carbon –, as organic carbon is closely correlated with weight loss on ignition. There is some controversy in the literature, however, regarding the appropriate conversion factor –, and thus the value of 1.8 used here is intended to provide an approximation of the relative organic carbon concentrations and not an exact measure. Organic carbon in McMurdo sediments was determined by an elemental carbon analyser as detailed in . The redox potential discontinuity layer (RPD) was estimated by divers while sampling at Casey sites. Citations for methods for all other contaminants measured are given where data are used.
A set of simple criteria were used to classify species as potentially useful indicators of anthropogenic disturbance in Antarctica: 1) Opportunist taxa – those consistently more abundant at disturbed sites than controls, or occasionally very dominant at disturbed and/or only low abundances at control; 2) Sensitive taxa - found commonly at control sites (but not necessarily abundantly) but not found at disturbed sites, or extremely rarely.
Simpson dominance, taxonomic diversity (TDΔ), taxonomic distinctness (TDΔ*) and average taxonomic distinctness (TDΔ+) were calculated according to ,  using the program PRIMER V6.1.13. Differences in taxonomic diversity between control, intermediate and disturbed locations were tested using univariate PERMANOVA , , based on a Euclidean distance similarity matrix and a 2 factor design with disturbance (3 levels) and locations nested within disturbance for each region separately. Univariate PERMANOVA is a permutation based analogue of traditional ANOVA and gives equivalent results, but caters for unbalanced designs by offering a choice for the type of sums of squares used for partitioning, and there are no assumptions regarding the distribution of variables .
To test hypotheses regarding differences between macrofaunal communities at control, disturbed and intermediate locations, a range of multivariate methods were used including ANOSIM tests for differences between groups, distances between group centroids and MDS and PCO ordinations, which were all based on Bray-Curtis similarity matrices of square root transformed abundance data, calculated using PRIMER.
Comparison of Anthropogenic Disturbance
Direct comparison of contaminant levels between the stations is difficult as different sampling, analytical and assessment methods have been used at each station, with only patchy measurement of some contaminants, particularly at Casey. At each station there is a range of contamination and individual sites can be nominally classified into groups which are broadly representative of their contamination status at each station (Table 1): control (uncontaminated background levels), intermediate (moderate local contamination in comparison to background or the highest local levels) or disturbed (highest levels of local contamination). For example, sediment metal levels show a pattern of the three groups (Fig. 3). We used these three broad contamination classifications (control, intermediate and disturbed) to compare the response of macrobenthic communities to anthropogenic disturbance at each station. We also combined the intermediate and disturbed groups together for some analysis in comparison with the control groups. These groups are only meant to be indicative of contamination levels against background (control) levels within each region and do not indicate similar levels of disturbance in inter-station comparisons. Contamination levels at Casey are generally lower and are not in the same range as McMurdo. The known history of each site was also used to contribute to the classification of sites into these 3 groups.
Organic carbon content and metal concentrations in marine sediments at Casey and McMurdo Stations. Note different scales for copper (Cu) and cadmium (Cd) in each region. Data for Casey are from  and ; data from McMurdo are from , , . Pb = lead; Zn = zinc; OBB = O’Brien Bay; BB = Brown Bay; WQB = Winter Quarters Bay.
At Casey the most contaminated sites are those adjacent to the old waste disposal site in Brown Bay (Brown Bay Inner, Middle) and the Casey Wharf. The sites classified as intermediate disturbance at Casey are: Shannon Bay, adjacent to the wastewater outfall; Wilkes, adjacent to another abandoned waste disposal site; and Brown Bay Outer. Several control sites are used in comparison to these including four sites in O’Brien Bay and a single site in Newcomb Bay: Newcomb Corner (Figure 1, Table 1, Table 2).
At McMurdo the most contaminated sites are those in Winter Quarters Bay (WQB) and adjacent to the sewage outfall. Two sites downstream of the outfall, Outfall South A and B are classified here as intermediate disturbance. Several control sites were used in comparisons including Cape Armitage, Cinder Cones and the station wharf (Jetty).
One of the most routinely assessed measures of environmental contamination is trace metals in marine sediments. Metals have been measured at both stations but with different methods, making direct comparison difficult. Strong acid digests break down mineral phases in the sediment and are often used because they are highly reproducible, however they typically only identify the most intense local contamination . Some metals are frequently not identified as being above background when they may in reality be anthropogenically elevated, producing a Type II statistical error. A weak acid partial extraction gives an estimate of the bioavailable metal fraction in marine sediments and targets the labile mineral phases, sorbed to grains or in the pore water , , . A strong acid extraction will give much higher results than a weak acid partial-extraction, up to and greater than an order of magnitude difference depending on the metal measured .
A comparison of lead, copper, zinc and cadmium concentrations from Casey and McMurdo demonstrates the nominal classification into control, intermediate and disturbed groups at each station (Fig. 3), and also shows the difference when using the strong or partial digests at Casey. Thus the strong acid digest may obscure low levels of anthropogenic contamination at McMurdo. Direct comparison of strong digests between regions shows that McMurdo (HNO3) has greater concentrations of metals at contaminated sites than at Casey contaminated sites, even though a stronger digest was used at Casey (HNO3+ HF). While metal concentrations appear higher, a proportion of this would be metals tightly bound in the mineral matrix and not available to biota. However, even taking this into consideration concentrations are higher at McMurdo, for example, lead at contaminated sites is up to ∼5x the controls, while at Casey using a strong digest it is only ∼3x the controls (Fig. 3). This is likely to be an underestimate of the difference between the two stations as a stronger digest was used for Casey than McMurdo. Using partial digest data from Casey, lead at disturbed sites is up to ∼180x background levels.
The contamination at both stations also includes hydrocarbons and organic contaminants  (Table 2). Although the same contaminants were not measured at both stations, these data provide further evidence of the nominal disturbance classifications within each region. For example the Casey outfall at Shannon Bay has higher levels of organic carbon, copper and cadmium than controls (Fig. 3, Table 2). There is no organic contaminant data available from Casey, although some preliminary sampling indicates polybrominated diphenyl ether (PBDE) levels at the outfall site, Shannon Bay, are well above background (unpublished data). PBDEs were detected in wastewater effluent and marine sediments around Davis station, another Australian Station of similar size and history to Casey . Disturbed sites at McMurdo have a range of other contaminants including PCBs (WQB and outfall) and PBDEs at the outfall (Table 2).
The other major form of contamination at each station is organic enrichment, primarily from sewage outfalls. The quantity of organic carbon in sediments is greater overall at Casey than at McMurdo when control sites are compared (Fig. 3). While the methods used in each region to determine carbon content are different, they are unlikely to be the cause of the difference between regions. At control sites at Casey carbon levels are 3 to 4 times higher than at McMurdo. Enrichment can be seen at the disturbed sites in both regions and is highest at the outfall at McMurdo and also high at the site of Casey’s outfall (Shannon Bay) and in Brown Bay adjacent to the former waste disposal site (Fig. 3). The redox potential discontinuity layer (RPD) at Brown Bay and Shannon Bay were also very shallow (<1 cm), while at the control sites they were deeper (≥5 cm), indicating anaerobic conditions and further evidence of elevated organic carbon content. The organic enrichment factor caused by the sewage outfall at each station is similar, ca. 3× background at McMurdo and ca. 2× background at Casey, with ca. 3× at the waste disposal site (Fig. 3).
Comparison of Biodiversity
Observed species richness (S-obs) is greater at Casey than McMurdo, despite lesser sampling effort, but neither set of curves has reached an asymptote. (Fig. 4A). There is a very clear difference in S-obs between control and disturbed locations at both stations, and the disturbed locations at McMurdo have the lowest species richness overall. Sampling effort is also greater at disturbed locations in both regions. Non-parametric estimators of species richness were also used to compare each region. All three methods, Chao-2, Jacknife-1 and Jacknife-2 show similar patterns to S-obs, but with a greater total number of species, with estimates of 120 to 130 at Casey and 80 to 90 species at McMurdo (Fig. 4A). These non-parametric estimators are influenced by the sampling design, as seen in the declining smoothed curves for Chao-2 and Jacknife-2, a result of the fact that the implicit assumption of these methods, that all samples are effectively interchangeable within the region, is not actually true. Because these are heterogeneous sets of locations (within each region), once a certain number of samples have been reached (around 100), further samples are not from new locations but are replicates from within locations and the encounter rate of new species declines sharply. The spatially hierarchical nature of the sampling design, particularly at Casey (Locations, Sites, Plots, replicates within Plots), illustrates the difference between locations in the number and identity of species.
A) Species accumulation curves for Casey and McMurdo regions, and control and disturbed locations within each region. B) Rank/abundance plots for macrofaunal communities from control and disturbed locations at Casey and McMurdo.
This effect of spatial scale can also be seen in a comparison of the observed number of species found at increasing spatial scales, from replicates to region. At the smallest scale, the point scale (replicate cores within a location) species richness (SRP) was variable and lower at Casey than McMurdo (Fig. 5, Table 3), but at this scale the comparison is biased by the underestimate at Casey due to the 1 mm sieve used. This difference is reduced when SR is examined at the sample scale (SRS - replicates pooled within each location) and nullified at the large sample scale (SRL) (Fig. 5). At the habitat scale (SRH) Casey surpasses McMurdo (Fig. 5). This is an understimate biased by the lesser total sampling effort at Casey. Species richness was also greater at control than disturbed locations in both regions, which was more apparent above the point scale.
Species richness at increasing spatial scales in each region. Different symbols represent different locations, blue symbols represent control locations, clear symbols disturbed locations, star symbol represents largest scale in each region (SRH, control and disturbed combined). Numbers in brackets indicate number of replicates in sample. SRP = Point (replicate) species richness, SRS = sample (combined replicates for location) species richness, SRL = large sample species richness, SRH = habitat species richness.
A comparison of species richness by major taxonomic groups indicates some clear differences between Casey and McMurdo. At Casey there are more species of polychaetes and most arthropod groups including isopods, ostracods, tanaids and cumaceans than at McMurdo, but no difference in the number of gammarid, mollusc or echinoderm species (Fig. 6).
Comparison of taxonomic diversity in each region, based on the total number of species found in cores, McMurdo n = 325, Casey n = 160.
Taxonomic diversity (Δ), taxonomic distinctness (Δ*) and average taxonomic distinctness (Δ+) were in most cases significantly greater at control than disturbed locations (ANOVA: p = 0.0001) in both regions, at both the average point scale and pooled over the large area scale (Fig. 7, Table 4). In general controls were not significantly different from intermediate sites, nor were intermediate different from disturbed, with a few exceptions (Fig. 7). This was due to very large differences between locations within the control, intermediate and disturbed groups. However at the extreme ends of the disturbance gradient, controls had greater taxonomic diversity than disturbed locations. Also the Δ+ did not show an effect of disturbance at the large area scale (Fig. 7). This indicates that over all disturbed and intermediate sites the average taxonomic distance between two randomly selected species is not different. Areas classified as intermediate or disturbed were not significantly different from each other at either scale. The effect of sampling effort on species richness (S-obs) and taxonomic diversity (Δ) can be seen in the large difference in S-obs from the point to the large area scales, but with very little change in taxonomic distinctness indices from point to large area scales. Species richness (SR) was greater over the largest scale at Casey, however, taxonomic diversity indices were greater at McMurdo than Casey, indicating greater relatedness among species at Casey or a broader range of taxa at McMurdo.
Comparison of taxonomic distinctness indices in each region. SR = species richness, Δ = taxonomic diversity (takes account of species abundances), Δ* = taxonomic distinctness, Δ+ = average taxonomic distinctness (based on presence-absence only), which equates to the average taxonomic distinctness between two randomly selected species.
Contrasting patterns of the distribution of individuals among species between Casey and McMurdo and control and disturbed sites can be seen in a Whittaker plot of rank abundance (Fig. 4B). There is a clear difference in evenness of control assemblages with a steeper line for McMurdo (higher dominance) than Casey (more even), and a clear difference between control and disturbed assemblages at each station. The Casey and McMurdo disturbed assemblages have the steepest slopes (Fig. 4B), which are characteristic of an environmental impact . A comparison of dominance using Simpson’s dominance index (λ) indicated significant variability in dominance among locations (Table 3) in both regions, but that in general dominance was greater at disturbed locations (Fig. 8C, D). Pooled reference locations at Casey had a slightly lower dominance (λ = 0.10) than McMurdo (λ = 0.13), but pooled disturbed locations had similar values in each region (Table 3). Dominance also decreased with increasing spatial scale, and was generally largest at the point scale (mean per core at each location), less at the sample scale for each location and lowest at the large area scale for pooled control locations and disturbed locations (Table 3). We observed a significant positive non-linear relationship between the number of individuals and the number of species, that appeared to be different for control and disturbed locations, particularly at Casey (Fig. 8A, B), far more so than at McMurdo. There was also a significant negative correlation between the number of species and dominance per sample, with control samples having generally lower dominance, particularly at Casey.
A & B) The relationship between the number of species and number of individuals in each region; C & D) The relationship between the number of species and dominance in each region. Blue symbols represent control samples, red symbols represent disturbed samples. Type of function used to fit trendline indicated following R2 value.
Comparison of Community Patterns
Both stations show significant differences in infaunal communities at the species level along a contamination/disturbance gradient, with strong differences between control and disturbed locations (Fig. 9A, B). Differences between control and disturbed locations were more distinct at Casey, with a high level of within-location similarity (clustering of samples in locations in MDS ordination, Fig. 9B) and distinct differences among locations (clearly separated location clusters in MDS ordination), particularly among control locations. At McMurdo there was less separation of different locations in the species level MDS, with more of a gradual change in communities along the contamination gradient (Fig. 9A). This may reflect the higher levels of contamination at McMurdo, as there is a greater spectrum of contamination from control to disturbed with a set of locations that are intermediate in their levels of contamination. This is seen in the species level MDS with the intermediate disturbance locations clustering very closely to the controls (Fig. 9A, B). Additionally it may be influenced by the greater sampling effort at McMurdo and the influence of temporal variation on communities over 10 years.
A & B) MDS ordinations of macrofaunal communities at Casey region species level (A) and McMurdo region species level (B); C) Combined family level MDS ordination of macrofaunal communities at Casey and McMurdo, showing control, intermediate and disturbed groups within each region; D) PCO plot of distances among group centroids in C to show relative effect size. Based on square root transformed abundances and Bray-Curtis similarities. PCO1 = 50.8% of total variation, PCO2 = 27.3% of total variation.
Casey and McMurdo community patterns were compared directly using family level taxonomic resolution (Fig. 9C). Infaunal communities were different between the two regions with very clear separation between control groups in the MDS ordination (Fig. 9C), indicating that at the family level Casey and McMurdo have different assemblages. The effect of disturbance is also apparent with intermediate and disturbed communities significantly different from controls, but with a response that is in the same plane in the MDS ordination (Fig. 9C). Thus although Casey and McMurdo had differing starting points (as represented in control communities), there were some similarities in the nature of the response in each region at the community level. Intermediately contaminated sites tended to sit in between control and disturbed sites, indicating there is a gradient of response to contaminants, although the varied response of the intermediate category is indicative of its nominal classification. Some locations classified as intermediate more closely resemble disturbed, and some, controls. Importantly the community response to the contamination gradient seen at the species level (Fig. 9A, B) is also apparent at the family level (Fig. 9C).
Two metrics were used to measure the size of the response to disturbance at each station, ANOSIM and distances between group centroids (calculated from the resemblance matrix). Control communities in both regions were compared to intermediate and disturbed groups separately and both regions showed a similar pattern, but the magnitude of the response to contamination/disturbance at Casey was slightly greater than at McMurdo (Table 5). A PCO ordination of distances among group centroids demonstrates a larger difference between control and disturbed at Casey than McMurdo (Fig. 9D). The intermediate group was more distinct from controls at Casey than McMurdo. The size of the difference between the disturbed group at Casey and disturbed group at McMurdo is also similar to the size difference between the control groups in each region, providing further evidence that the degree of the impact is similar at each station (Table 5). The control groups in each region, however, are less variable than the disturbed group, with the intermediate groups least variable overall, probably reflecting the fewer locations (samples) in this category (Table 6).
At the phylum level the differences between Casey and McMurdo are due to the relative proportions of polychaetes and crustaceans (Table 7, Fig. 10). Crustaceans dominate the control communities in both regions but are far more dominant at Casey, whereas polychaetes are a relatively minor component of the Casey community but are prominent at McMurdo (Fig. 10). The effect of disturbance, however, is very different in each region. At Casey crustaceans become more dominant, whereas at McMurdo they become less abundant and polychaetes dominate disturbed communities. At McMurdo the proportion of polychaetes is much greater at disturbed locations than controls, whereas at Casey it is very similar at disturbed and control locations (Table 7). Of the crustaceans at Casey, it is the proportion of amphipods which has the greatest change, increasing from an average of 20.7% (SE 6%) of the community at controls to 61.2% (SE 6.9%) at disturbed locations (Fig. 10). The proportion of isopods also increased slightly at disturbed locations in both regions. Ostracods and cumaceans, however, decrease in proportion at disturbed locations in both regions. The proportion of tanaids is approximately the same at both control and disturbed locations at Casey and decreases from control to disturbed at McMurdo. At McMurdo the proportion of all crustacean groups is lower at disturbed locations than controls, except for isopods, which is similar in both (Table 7). Echinoderms decrease slightly at disturbed locations although proportions are generally very low. There is no clear trend for bivalves or gastropods as proportions are very small (Table 7).
Relative proportions of polychaetes and crustaceans in infaunal assemblages at Casey and McMurdo, split into control and disturbed locations.
Relative abundance is more difficult to compare between the two regions due to the differing sieve mesh sizes used, which underestimates abundance at Casey in comparison to McMurdo. However some relative patterns of abundance are very clear. At McMurdo total abundances were greatest at control sites but at disturbed sites at Casey (Fig. 11). Even if applying a correction factor of 1.5 to Casey estimates (based on the Casey subset sorted at both mesh sizes, see Methods), abundances at the Casey controls are much lower than McMurdo. At disturbed sites however, abundances are similar (Fig. 11), and after applying a 1.5×mesh correction, abundances at disturbed sites at Casey would be greater than McMurdo (excepting several large peaks of abundance at some intermediate disturbance sites at McMurdo). Total abundance of crustaceans shows a similar pattern of differences, with generally greater abundances at McMurdo controls than Casey (after correction for mesh size) and greater abundances at Casey disturbed than McMurdo (even without the correction) (Fig. 11). Amphipods show an incredible difference in abundance at disturbed sites between the two regions, with huge abundances recorded at Casey, which would be even larger with a 0.5 mm mesh. Abundances of amphipods are similar at controls in both regions. Thus, at Casey amphipods increase from control to disturbed while at McMurdo they decrease (Fig. 11). In contrast polychaetes are far more abundant at McMurdo, and although they comprise a greater proportion of disturbed communities they are less abundant than at control and intermediate sites (Fig. 11). Polychaete abundances at Casey, however, are greatest at the disturbed and intermediate sites. Ostracods, cumaceans, tanaids and isopods are far more abundant at McMurdo than Casey, even allowing for a mesh size correction. Ostracods and cumaceans both show the same pattern of greater abundance at control sites in both regions (Fig. 11).
Comparison of mean abundance per core for major taxonomic groups at Casey and McMurdo. Note Casey data based on 1
There were several taxa which could be considered potentially useful indicators of disturbance in Antarctic soft-sediment assemblages (Table 8). At the species and family level there were some similarities in the taxa comprising control and disturbed assemblages at Casey and McMurdo, for example cumaceans and ostracods both were more abundant at controls than disturbed sites in both regions (Table 8). At disturbed sites there were also similar taxa present, in particular three polychaete families (Table 8). Thus even though there were big differences in overall assemblage composition, there were similar characteristic taxa in control and disturbed assemblages in both regions. There were also some contrasting patterns for some taxa, for example amphipods of the genus Orchomenella were very abundant at disturbed sites at Casey but extremely rare at McMurdo disturbed sites and in low abundances at controls.
Antarctic research stations have the potential to severely impact marine benthic communities. The accumulation of contaminants in marine sediments causes changes in community composition and loss of biodiversity. Responses of benthic communities to anthropogenic disturbance show some regional differences, largely due to differing regional community composition. There are, however, some common responses and species which are potential indicators of, or sensitive to, disturbance which may aid in the rapid detection of impacts in other areas. Assessing the relative impact of stations depends on a clear understanding of sampling effort and potential methodological biases. Such impact assessments will lead to improved environmental management and inform decisions regarding potential remediation actions, while contributing to a better understanding of regional biodiversity for conservation and management purposes.
At both Casey and McMurdo there is clear evidence of human impacts in macrobenthic communities, with contamination of marine sediments matched with differences in community composition, reduced biodiversity and characteristic indicator taxa. A common feature in response to disturbance in both regions was reduced diversity at disturbed sites, whether measured as observed species richness, estimated total species richness or taxonomic diversity/distinctness. Contamination clearly has an impact on biodiversity in Antarctic soft sediment communities as has previously been demonstrated at Casey . The nature of the community response, however, is quite different in each region. The response of macrofaunal communities at McMurdo was similar to that seen in other parts of the world , with an increase in the proportion of polychaetes to become the dominant component at McMurdo (disturbed sites range 46–82%, mean 68±6%), whereas they decreased at Casey (disturbed sites range 0.2–65%, mean 11±9%). Globally, polychaetes are known to characterise contaminated sediments, whether influenced by organic enrichment or other contaminants such as metals –. At McMurdo the disturbed sites are organically enriched but they are also contaminated with anthropogenic pollutants such as metals and hydrocarbons , , . Some polychaete species are tolerant to pollutants and can produce detoxifying secondary metabolites and proteins in response to contaminants –. These responses are usually confined to several families of polychaetes with opportunistic life histories, and at McMurdo the prominent families at disturbed sites included dorvelleids, capitellids, orbiniids, cirratulids and hesionids, which were also seen to respond positively in experimental manipulations of organic matter , . While an increase in the proportion of polychaetes was not seen at Casey, there were several polychaete families characteristic of disturbed sites in both regions (Table 8), including Capitellidae, Dorvelleidae and Orbiniidae. These families have been found to dominate or have increased abundances in disturbed areas in other regions , – including the Arctic . Abundances of these three families increased at some disturbed sites at Casey but overall polychaetes at Casey did not respond in the manner described in other regions and studies. This may be due to their low abundances and regionally low representation in the community, with potentially only a small pool of source populations to recruit from. Local recruitment is likely to be the dominant source and have a strong influence on assemblage composition (e.g. ). Isolation by regional oceanographic currents, such as has been shown at McMurdo , may also contribute to dominance of local recruitment.
A major difference in the response to disturbance was in the proportion of crustaceans, which decreased at disturbed sites at McMurdo but increased at Casey, mainly due to amphipods. Experiments by Lenihan et al.  at McMurdo showed that in general crustaceans were negatively affected by increasing metal (Cu) concentrations and this has also been observed in other experimental work –. Lenihan et al.  also demonstrated a decrease in crustaceans in response to increasing organic enrichment. Oakden et al.  described behavioural avoidance by phoxacephalid amphipods to sediment organically enriched by sewage effluent. This difference in crustacean response between the two stations may relate to the levels of contamination, with McMurdo having generally higher concentrations of contaminants. It may also reflect the generally greater dominance of crustaceans in Casey communities. Of the amphipods at Casey it was the family Lyssianassidae that had highest abundances at disturbed compared to control sites. Lyssianassid amphipods are known scavengers  and respond positively to organic enrichment in the deep sea – and have been found in large abundances in disturbed areas in the Arctic . Stable isotope ratios of nitrogen indicate that lyssianassids found at Casey are at an intermediate trophic level comprising deposit feeders and scavengers , . The increase in the abundance and proportion of lyssianassids at Casey may be a response to increased organic carbon content of sediments at disturbed sites. As metal concentrations are generally lower at Casey than McMurdo, lyssianassids may not be challenged by the above-background levels of metals present in the sediments at Casey. Alternatively other contaminants present at McMurdo, such as persistent organic compounds , may not be present at Casey, although this remains to be tested.
Some taxa showed a similar sensitivity to contamination in both regions, being either absent from contaminated sites or in very low abundances. Cumaceans and ostracods are two examples, and may prove to be effective indicators of disturbance in Antarctica. Whether it is a response common to all Antarctic cumacean and ostracod species remains to be determined. In other parts of the world cumaceans, for example, have been found to be both sensitive to disturbance such as organic enrichment  as well as indicative of these conditions , depending on the species. Ostracods, however, are generally sensitive to pollution and disturbance in marine habitats  and our results support this. Echinoderms were also significantly reduced in abundance or absent from disturbed sites and previous Antarctic work has found them to be negatively affected by metals but to increase in response to organic enrichment . There were also other similarities in the fauna comprising the control communities in the two regions. Several amphipod families characterised the control assemblages including Oedicerotidae, Lyssianassidae and the phoxacephalid species Heterophoxus videns. Other taxa characteristic of control communities in both regions included cumaceans, philomedid ostracods, oligochaetes, Rissoidae gastropods and cirratulid polychaetes (Table 8).
One of the aims of this study was to identify potentially useful indicator species whose general utility could be in tested in future work or used in the development of indices or biocriteria to assess environmental conditions. Biological assessment criteria are increasingly being used to assess ecological impacts in estuarine and coastal ecosystems in other regions of the world, e.g. by the US Environmental Protection Agency  and the European Water Framework Directive , , of which benthic invertebrates are a key component . The development of such methods in Antarctica is in its very early days as knowledge of the fauna and their responses to the environment is very limited. It is of great importance, however, that attempts are made to identify common responses and potential indicators to disturbance. Further field studies from other regions of Antarctica are needed to test such generalizations, in addition to species specific ecotoxicological studies assessing tolerance or sensitivities to contaminants . Very little is known of the pollution tolerance or adaptation to pollution for Antarctic marine invertebrates and field observations are limited.
This study found that small Antarctic stations such as Casey can have impacts of equal or greater severity on marine benthic communities as large, more disturbed and contaminated stations such as McMurdo. McMurdo has a much larger human population and some sites are considered to be as contaminated as heavily industrialized estuaries in other parts of the world . However the magnitude of the response to disturbance in each region is fairly similar, if not larger at Casey compared to McMurdo. Casey has a greater loss of biodiversity at its disturbed sites than McMurdo, although McMurdo has a greater level of dominance than at Casey. McMurdo is atypical and almost unique in comparison to other Antarctic stations. Casey is more representative of the size of many Antarctic stations. On the basis of the findings of this study it is likely many coastal Antarctic research stations have some level of environmental impact on local marine ecosystems. It is too early to propose that the size of the impacts at all coastal stations would be similar, but clearly even comparatively low levels of contamination and disturbance could cause large effects as demonstrated in this study. This study provides evidence that Antarctic marine benthic communities may be particularly sensitive to disturbance.
The Casey and McMurdo regions have considerably different soft-sediment macrobenthic communities, primarily in the relative proportions of polychaetes and crustaceans. McMurdo is more typical of macrobenthic assemblages worldwide, with a larger proportion of polychaetes (control sites at McMurdo 26–38%, mean 32±3%) compared to Casey (controls 2–30%, mean 13±10%). Polychaetes tend to dominate soft sediment assemblages globally, usually comprising at least 30–60% of total abundance –. Casey is unusual in its almost complete numerical dominance by crustaceans (controls 54–89%, mean = 74±11%), whereas they were less dominant at McMurdo (controls 42–57%, mean 51±5%).
The unusual community composition at Casey may be due to large scale regional processes. Antarctic nearshore benthic ecosystems have highly seasonal primary production and are thought to be food limited . Regional hydrographic conditions around McMurdo are fairly well described and it is an area considered to be relatively eutrophic due to the current flowing into the eastern side of McMurdo Sound, bringing with it the spring phytoplankton bloom from further north , . These eutrophic conditions may account for the extremely high abundances (up to 250,000 individuals m−1) recorded at reference locations in the McMurdo region. In contrast little is known of regional hydrographic conditions around Casey. Casey has greater sediment organic carbon content than McMurdo, which has been confirmed in other studies , and indicates a highly productive ecosystem with possibly greater food availability for benthic fauna. Casey is also further north than McMurdo on an area of Antarctic coastline which is more open, and sea ice breaks out in some areas over winter and earlier in summer than McMurdo (although not at the sites used in this study), which may also contribute to higher in-situ primary production. The Windmill Islands/Casey region is situated in Vincennes Bay, which is a katabatic polynya  that may enhance primary production in the region. The distinct differences between macrofaunal communities at Casey and McMurdo may be related to these broad scale oceanographic differences. The unusual community composition at Casey (dominance by crustaceans), however, is unlikely to be related to local environmental properties such as sediment type as they are similar to other regions of Antarctica. There is nothing outwardly unusual in local physical environmental conditions to indicate any potential cause for such unusual phyletic composition at Casey. One possible biological and habitat difference between the two regions is the presence of macroalgae. The Casey region has large areas of macroalgal habitat in areas which have less sea ice (these areas were not part of this study), whereas McMurdo has very little or no macroalgal cover, due to longer ice cover over the region and less available light as it is further south. The addition of this major food source in the Casey region ,  may have profound influences on benthic community composition and diversity. The positive influence of primary productivity on Antarctic benthos has been emphasised by several studies , , with sediment carbon content increasing β-diversity within locations . Food quality may also be important as the proportion of nitrogen in sediments has been shown to be important at regional scales .
While the two areas may have some differences in primary production levels and ice cover at a regional scale, the actual sites used in this study at both regions have similar levels of ice cover duration and therefore are likely to have similar levels of physical disturbance by ice. Ice scour has not been quantified at the locations in this study but our observations indicate that they have similar ice duration affording them similar levels of protection from scour, which has been shown to be a major structuring force in other areas of Antarctica such as the Peninsula region , . The sites used at Casey represent the far end of an ice cover gradient which extends from sites with no ice for long periods of the year (excluded from this study) to sites covered by ice for most of the year , which were used in this study. There is less of a gradient at McMurdo and most sites are similar in their duration of ice cover and are at the ice-covered end of the Casey spectrum.
At the regional level and within regions at scales greater than 1 km, Casey is more diverse than McMurdo, as measured by numerical species richness, however, indices of taxonomic distinctness , ,  were greater at McMurdo suggesting greater taxonomic diversity. These measures, which describe the path length or average taxonomic distance between two randomly selected organisms through the phylogeny (Δ and Δ* based on quantitative data, and average taxonomic distinctness Δ+, based on presence/absence), have been suggested by Warwick and Clarke  as being more easily comparable measures of biodiversity due to their lack of dependence on sampling effort or differences in taxonomic rigor. A greater taxonomic distinctness at McMurdo indicates greater taxonomic diversity or less relatedness among all species overall, or a wider spread of diversity across phylogenies. One possible explanation for this is the broader range of depths at McMurdo, with closer proximity of nearshore, shallow water habitats to deep shelf habitats and ice shelves. McMurdo is also at higher latitude than Casey which may contribute to a greater range of physical environmental conditions and a wider range of adaptations and thus taxonomic diversity. Habitat diversity has been found to have a positive effect on β-diversity in Antarctic infaunal communities . Taxonomic distinctness, however, cannot be seen as a substitute for species richness, but as an additional piece of information on species diversity, and Casey has a greater number of species overall than McMurdo, with less sampling effort. Warwick and Clarke  found that Δ+ is also useful in identifying degraded habitats and at the point scale at Casey and McMurdo this appears to be the case, however at the scale of large area, there is no difference between control and intermediate or disturbed habitats. This may be due to the differing nature of the disturbances across sites, affecting different fauna at different sites, but when all disturbed sites are combined this effect is nullified.
There is much to be gained in comparisons involving data from different studies, including the ability to make generalizations and increase overall understanding of ecological responses to environmental changes. The opportunity to sample widely separated regions using the same methods, at similar times and for a single unified purpose are exceedingly rare and difficult to organize, involving different countries, funding bodies and logistic operations. An alternative method is to opportunistically use the results from independent studies. Comparisons of environmental impacts using community data from different studies will usually encounter a range of difficulties, for example, due to differing sampling methods, but as demonstrated here, as long as potential sources of bias are identified, valid comparisons are possible.
Sampling effort is a major consideration in inter-study comparisons. Sampling effort, either the total number of samples taken or the total cumulative area they represent, has a strong influence on estimates of species richness. In regional comparisons using different studies, sampling effort and species richness can easily be assessed by comparisons of species-area curves. Species richness should ideally be compared as close to the asymptote of species-area curves as possible , however if sampling effort is unequal this may not be possible, but if one or more curves in the comparison is nearing an asymptote a valid comparison can be made. Casey’s greater diversity and the strong effect of disturbance on diversity are best demonstrated in these curves. Diversity is likely to be underestimated at Casey due to the greater sampling effort at McMurdo, comprising a longer period of time and greater number of samples. Importantly the Casey and McMurdo samples cover a similar spatial extent, as this can have a large effect on estimates of species diversity . Realistic community description for comparisons among samples, community patches, and different communities is best done in a known spatial context . At small spatial scales (the point and sample level) McMurdo appears to be more diverse, but this may be due in part to underestimation of point-scale diversity at Casey with a larger mesh size (1 mm vs. 0.5 mm). Above this scale however, we have demonstrated that mesh size effects are unlikely to be significant. Previous work at Casey has demonstrated that community patterns were the same when using either 1 mm or 0.5 mm data . Thus the fauna passing through a 1 mm sieve are only smaller individuals, not different species, but due to the larger number of individuals more species are encountered at a point (core) or sample (group of cores at a site) scale. Casey’s greater diversity thus is even more significant when considering the lesser sampling effort than at McMurdo.
Another potential confounding factor in comparisons of impacts is species level identifications of highly diverse macrofauna, particularly when working in regions where there is a paucity of taxonomic information or resources such as Antarctica. One approach to dealing with this challenge is the use of coarser taxonomic resolution, such as family as opposed to species. Using coarser levels there is less chance of incorrectly identifying particular taxa, whereas at the species level there is often great uncertainty, particularly when considering the recent spate of cryptic species being described in this area –. In general there is little loss of community information when moving from species to family level when examining patterns related to environmental gradients or habitat heterogeneity , . We demonstrate that the same is true for the Antarctic, whereby patterns of community composition in response to anthropogenic contamination gradients were preserved when going from species to family level.
Direct comparison of contaminant levels should be done with caution due to the different analytical methods used. For example sediment metal data based on a total extraction may actually obscure some low level anthropogenic contamination and this is highly likely to be the case at McMurdo. Research done at Casey comparing these two methods indicated a varying degree of difference depending on the metal examined, for example copper concentrations in total digests were approximately twice those observed in partial digests . However copper levels in total digests at Casey contaminated sites are still well below levels seen at McMurdo at contaminated sites. Standardized approaches to measuring contaminants in sediments are recommended, although unlikely to occur in the short term due to the historical nature of measurements within regions. This highlights the importance of studies which compare the effects of different methodologies on measuring contaminants, enabling inter-study comparisons to be made of disturbance levels. The relative effects of contaminants between regions are not solely related to contaminant concentrations, however, but also depend on other physical and biological factors.
We would like to thank the many people involved in collecting, sorting, identifying and curating the samples in this study. For Casey samples: Martin Riddle, Glenn Johnstone, Paul Goldsworthy, Ian Snape, Gillian Anderson, Susan Doust, Jim Lowry, Garry Wilson, Winston Ponder. For McMurdo samples: Kathleen Conlan, Kamille Hammerstrom, Ed Hendrycks, Judy Fournier, Rob Robbins, Steven Rupp, Jennifer Fisher, Dan Malone, Aaron Carlisle, Jim Oakden, Peter Slattery, Craig Lewis, Mike Donnellan, Jonna Engel, and Elizabeth Gibbs. We also thank the many students at Moss Landing Marine Laboratories (California), Vanier College (Quebec), Queen’s University (Ontario), and Trent University (Ontario) who extracted and rough sorted specimens.
Conceived and designed the experiments: JS SK JO. Performed the experiments: JS SK JO. Analyzed the data: JS. Contributed reagents/materials/analysis tools: JS SK JO. Wrote the paper: JS SK JO.
- 1. COMNAP (2013) Antarctic Facilities List 15th May 2013. https://www.comnap.aq/Information/SitePages/Home.aspx: Council of Managers of National Antarctic Programs.
- 2. Gröndahl F, Sidenmark J, Thomsen A (2009) Survey of Waste Water Disposal Practices at Antarctic Research Stations. Polar Research 28: 298–306.
- 3. Tin T, Lamers M, Liggett D, Maher PT, Hughes KA (2014) Setting the Scene: Human Activities, Environmental Impacts and Governance Arrangements in Antarctica. In: Tin T, Liggett D, Maher PT, Lamers M, editors. Antarctic Futures: Springer Netherlands. 1–24.
- 4. CEP (2013) CEP Five-Year Work Plan adopted at the XVth CEP Meeting at Hobart. XXXVI Antarctic Treaty Consultative Meeting. Brussels.
- 5. United Nations (2002) Report of the World Summit on Sustainable Development. www.johannesburgsummit.org.
- 6. IUCN (2004) Recommendations from the 4th World Parks Congress. www.iucn.org/themes/wcpa/wpc2003.
- 7. Dayton PK, Mordida BJ, Bacon F (1994) Polar marine communities. American Zoologist 34: 90–99.
- 8. Clarke A, Johnston NM (2003) Antarctic marine benthic diversity. Oceanography and Marine Biology: An Annual Review 41: 47–114.
- 9. Snape I, Riddle MJ, Stark JS, Cole CM, King CK, et al. (2001) Management and remediation of contaminated sites at Casey Station, Antarctica. Polar Record 37: 199–214.
- 10. Baird HP, Miller KJ, Stark JS (2011) Evidence of hidden biodiversity, ongoing speciation and diverse patterns of genetic structure in giant Antarctic amphipods. Molecular Ecology 20: 3439–3454.
- 11. Baird HP, Miller KJ, Stark JS (2012) Genetic population structure in the Antarctic benthos: insights from the widespread amphipod, Orchomenella franklini. PLoS ONE 7(3): e34363.
- 12. Thatje S (2012) Effects of Capability for Dispersal on the Evolution of Diversity in Antarctic Benthos. Integrative and Comparative Biology 52: 470–482.
- 13. Lenihan HS, Oliver JS (1995) Anthropogenic and natural disturbances to marine benthic communities in Antarctica. Ecological Applications 5(2): 311–326.
- 14. Aronson RB, Thatje S, McClintock JB, Hughes KA (2011) Anthropogenic impacts on marine ecosystems in Antarctica. Annals of the New York Academy of Sciences 1223: 82–107.
- 15. Thrush SF, Hewitt JE, Cummings VJ, Norkko A, Chiantore M (2010) β-Diversity and Species Accumulation in Antarctic Coastal Benthos: Influence of Habitat, Distance and Productivity on Ecological Connectivity. PLoS ONE 5: e11899.
- 16. Thomas DN (2004) Frozen oceans: the floating world of pack ice. London: Natural History Museum. 224 p.
- 17. Lohrer AM, Cummings VJ, Thrush SF (2013) Altered Sea Ice Thickness and Permanence Affects Benthic Ecosystem Functioning in Coastal Antarctica. Ecosystems 16: 224–236.
- 18. Smetacek V, Nicol S (2005) Polar ocean ecosystems in a changing world. Nature 437: 362–368.
- 19. Lenihan HS, Oliver JS, Oakden JM, Stephenson MD (1990) Intense and localized benthic marine pollution around McMurdo Station, Antarctica. Marine Pollution Bulletin 21: 422–430.
- 20. Hale RC, Kim SL, Harvey E, La Guardia MJ, Mainor TM, et al. (2008) Antarctic Research Bases: Local Sources of Polybrominated Diphenyl Ether (PBDE) Flame Retardants. Environmental Science & Technology 42: 1452–1457.
- 21. Risebrough RW, de Lappe BW, Younghans-Haug C (1990) PCB and PCT contamination in Winter Quarters Bay, Antarctica. Marine Pollution Bulletin 21: 523–529.
- 22. Kennicutt MC, Klein A, Montagna P, Sweet S, Wade T, et al. (2010) Temporal and spatial patterns of anthropogenic disturbance at McMurdo Station, Antarctica. Environmental Research Letters 5.
- 23. Stark JS, Riddle MJ, Snape I, Scouller RC (2003) Human impacts in Antarctic marine soft-sediment assemblages: correlations between multivariate biological patterns and environmental variables. Estuarine, Coastal and Shelf Science 56: 717–734.
- 24. Stark JS, Snape I, Riddle MJ, Stark SC (2005) Constraints on spatial variability in soft-sediment communities affected by contamination from an Antarctic waste disposal site. Marine Pollution Bulletin 50: 276–290.
- 25. Lenihan HS (1992) Benthic marine pollution around McMurdo Station, Antarctica: a summary of findings. Marine Pollution Bulletin 25(9–12): 318–323.
- 26. Conlan KE, Kim SL, Lenihan HS, Oliver JS (2004) Benthic changes during 10 years of organic enrichment by McMurdo Station, Antarctica. Marine Pollution Bulletin 49: 43–60.
- 27. Conlan KE, Rau GH, Kvitek RG (2006) δ13C and δ15N shifts in benthic invertebrates exposed to sewage from McMurdo Station, Antarctica. Marine Pollution Bulletin 52: 1695–1707.
- 28. Stark JS, Riddle MJ, Simpson RD (2003) Human impacts in soft-sediment assemblages at Casey Station, East Antarctica: spatial variation, taxonomic resolution and data transformation. Austral Ecology 28: 287–304.
- 29. Stark JS, Riddle MJ, Smith SDA (2004) Influence of an Antarctic waste dump on recruitment to near-shore marine soft-sediment assemblages. Marine Ecology Progress Series 276: 53–70.
- 30. van Gemerden BS, Etienne RS, Olff H, Hommel PWFM, van Langevelde F (2005) Reconciling methodologically different biodiversity assessments. Ecological Applications 15: 1747–1760.
- 31. Gotelli NJ, Colwell RK (2001) Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecology Letters 4: 379.
- 32. Bonar SA, Fehmi JS, Mercado-Silva N (2011) An overview of sampling issues in species diversity and abundance surveys. In: Magurran AE, McGill BJ, editors. Biological diversity: frontiers in measurement and assessment: Oxford University Press Oxford. 11–24.
- 33. Gotelli NJ, Colwell RK (2011) Estimating species richness. In: Magurran AE, McGill BJ, editors. Biological diversity: frontiers in measurement and assessment. Oxford: Oxford University Press. 39–54.
- 34. Scheiner SM, Cox SB, Willig M, Mittelbach GG, Osenberg C, et al. (2000) Species richness, species–area curves and Simpson’s paradox. Evolutionary Ecology Research 2: 791–802.
- 35. Oliver J, Hammerstrom K, McPhee-Shaw E, Slattery P, Oakden J, et al. (2011) High species density patterns in macrofaunal invertebrate communities in the marine benthos. Marine Ecology 32: 278–288.
- 36. Gray JS (2000) The measurement of marine species diversity, with an application to the benthic fauna of the Norwegian continental shelf. Journal of Experimental Marine Biology and Ecology 250: 23–49.
- 37. Scheiner SM (2003) Six types of species-area curves. Global Ecology and Biogeography 12: 441–447.
- 38. Magurran AE, McGill BJ (2011) Biological diversity: frontiers in measurement and assessment: Oxford University Press Oxford.
- 39. Walther BA, Moore JL (2005) The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28: 815–829.
- 40. Hurlbert SH (1971) The non-concept of species diversity: a critique and alternative parameters. Ecology 52: 577–586.
- 41. Goodman D (1975) The Theory of Diversity-Stability Relationships in Ecology. The Quarterly Review of Biology 50: 237–266.
- 42. Magurran AE (2004) Measuring Biological Diversity. Malden, MA: Blackwell Publishing. 256 p.
- 43. Gray JS (1979) Pollution induced changes in populations. Philosophical Transactions of the Royal Society, Series B 286: 546–561.
- 44. Simpson EH (1949) Measurement of Diversity. Nature 163: 688.
- 45. Lande R, DeVries PJ, Walla TR (2000) When species accumulation curves intersect: implications for ranking diversity using small samples. Oikos 89: 601–605.
- 46. May RM (1975) Patterns of species abundance and diversity. In: Cody ML, Diamond JM, editors. Ecology and Evolution of Communities. Cambridge, MA: Harvard University Press. 81–120.
- 47. Pielou EC (1975) Ecological diversity. New York: John Wiley. 165 p.
- 48. Brandt A, Gooday AJ, Brandão SN, Brix S, Brökeland W, et al. (2007) First insights into the biodiversity and biogeography of the Southern Ocean deep sea. Nature 447: 307–311.
- 49. Linse K, Cope T, Lörz A-N, Sands C (2007) Is the Scotia Sea a centre of Antarctic marine diversification? Some evidence of cryptic speciation in the circum-Antarctic bivalve Lissarca notorcadensis (Arcoidea: Philobryidae). Polar Biology 30: 1059–1068.
- 50. Warwick RM (1988) Analysis of community attributes of the macrobenthos of Frierfjord/Langesundfjord at taxonomic levels higher than species. Marine Ecology Progress Series 46: 167–170.
- 51. Warwick RM (1988) The level of taxonomic discrimination required to detect pollution effects on marine benthic communities. Marine Pollution Bulletin 19: 259–268.
- 52. Clark GF, Stark JS, Johnston EL, Runcie JW, Goldsworthy PM, et al. (2013) Light-driven tipping points in polar ecosystems. Global Change Biology 19: 3749–3761.
- 53. Barnes DKA (1999) The influence of ice on polar nearshore benthos. Journal of the Marine Biological Association of the United Kingdom 79: 401–407.
- 54. Howington JP, McFeters GA, Barry JP, Smith JJ (1992) Distribution of the McMurdo Station sewage plume. Marine Pollution Bulletin 25: 324–327.
- 55. Kennicutt MCII, McDonald SJ, Seranico JL, Boothe P, Oliver J, et al. (1995) Human contamination of the marine environment - Arthur Harbor and McMurdo Sound, Antarctica. Environmental Science and Technology 29: 1279–1287.
- 56. Duquesne S, Riddle MJ (2002) Biological monitoring of heavy metal contamination in coastal waters in the vicinity of Casey Station, Windmill Islands, East Antarctica. Polar Biology 25: 206–215.
- 57. Stark JS, Snape I, Riddle MJ (2006) Abandoned waste disposal sites in Antarctica: monitoring remediation outcomes and limitations at Casey Station. Ecological Management and Restoration 7: 21–31.
- 58. Crockett AB, White GJ (1997) Comprehensive Characterization Report on Winter Quarters Bay, Mcmurdo Station, Antarctica. Idaho Falls, ID, USA: Idaho National Engineering Lab.
- 59. Conlan KE, Rau GH, McFeters GA, Kvitek RG (2000) Influence of McMurdo Station sewage on Antarctic marine benthos: evidence from stable isotopes, bacteria, and biotic indices. In: Davison W H-WC, Broady P, editor. Antarctic Ecosystems: Models for Wider Ecological Understanding. Christchurch: New Zealand Natural Sciences. 315–318.
- 60. Conlan KE, Kim SL, Thurber AR, Hendrycks E (2010) Benthic changes at McMurdo Station, Antarctica following local sewage treatment and regional iceberg-mediated productivity decline. Marine Pollution Bulletin 60: 419–432.
- 61. Scouller RC, Snape I, Stark JS, Gore DB (2006) Evaluation of geochemical methods for the discrimination of metal contamination in Antarctic marine sediments: a case study from Casey Station, East Antarctica. Chemosphere 65: 294–309.
- 62. Heiri O, Lotter AF, Lemcke G (2001) Loss on ignition as a method for estimating organic and carbonate content in sediments: reproducibility and comparability of results. Journal of Paleolimnology 25: 101–110.
- 63. Nelson DW, Sommers LE (1996) Total carbon, organic carbon, and organic matter. In: Sparks DL, Page, A L., Helmke, P A., Loeppert, R H., Soltanpour, P N., Tabatabai, M A., Johnston, C T., Sumner, M E., editor. Methods of soil analysis Part 3 - chemical methods. Madison, WI, USA: Soil Science Society of America, Inc., American Society of Agronomy, Inc. 961–1010.
- 64. Wang Q, Li Y, Wang Y (2011) Optimizing the weight loss-on-ignition methodology to quantify organic and carbonate carbon of sediments from diverse sources. Environmental Monitoring and Assessment 174: 241–257.
- 65. Leong LS, Tanner PA (1999) Comparison of Methods for Determination of Organic Carbon in Marine Sediment. Marine Pollution Bulletin 38: 875–879.
- 66. Sleutel S, De Neve S, Singier B, Hofman G (2007) Quantification of Organic Carbon in Soils: A Comparison of Methodologies and Assessment of the Carbon Content of Organic Matter. Communications in Soil Science and Plant Analysis 38: 2647–2657.
- 67. Sutherland RA (1998) Loss-on-ignition estimates of organic matter and relationships to organic carbon in fluvial bed sediments. Hydrobiologia 389: 153–167.
- 68. Clarke KR, Warwick RM (1998) A taxonomic distinctness index and its statistical properties. Journal of Applied Ecology 35: 523–531.
- 69. Clarke KR, Warwick RM (2001) A further biodiversity index applicable to species lists: variation in taxonomic distinctness. Marine Ecology Progress Series 216: 265–278.
- 70. Anderson MJ (2001) A new method of non-parametric multivariate analysis of variance. Austral Ecology 26: 32–46.
- 71. Anderson MJ (2001) Permutation tests for univariate or multivariate analysis of variance and regression. Canadian Journal of Fisheries and Aquatic Sciences 58: 626–639.
- 72. Anderson MJ, Gorley RN, Clarke KR (2008) PERMANOVA+ for PRIMER: Guide to software and statistical methods. Plymouth, UK: PRIMER-E.
- 73. Weimin Y, Batley GE, Ahsanullah M (1992) The ability of sediment extractants to measure the bioavailability of metals to three marine invertebrates. The Science of the Total Environment 125: 67–84.
- 74. Simpson SL, Batley GE, Chariton AE, Stauber JL, King CK, et al. (2005) Handbook for sediment quality assessment. Bangor, NSW: CSIRO. 126 p.
- 75. Stark JS, Riddle M, Snape I, King C, Smith J, et al. (2011) Environmental impact assessment of the Davis Station wastewater outfall. Kingston, Tasmania: Australian Antarctic Division.
- 76. Krebs CJ (1999) Ecological methodology. New York: Harper & Row.
- 77. Pearson TH, Rosenberg R (1978) Macrobenthic succession in relation to organic enrichment and pollution of the marine environment. Oceanography and Marine Biology Annual Review 16: 229–311.
- 78. Hall JA, Frid CLJ, Gill ME (1997) The response of estuarine fish and benthos to an increasing discharge of sewage effluent. Marine Pollution Bulletin 34(7): 527–535.
- 79. Rosenberg R (2001) Marine benthic faunal successional stages and related sedimentary activity. Scientia Marina 65: 107–119.
- 80. Lenihan HS, Peterson CH, Kim SL, Conlan KE, Fairey R, et al. (2003) Variation in marine benthic community composition allows discrimination of multiple stressors. Marine Ecology Progress Series 261: 63–73.
- 81. Durou C, Mouneyrac C, Amiard-Triquet C (2005) Tolerance to metals and assessment of energy reserves in the polychaete Nereis diversicolor in clean and contaminated estuaries. Environmental Toxicology 20: 23–31.
- 82. Mouneyrac C, Mastain O, Amiard JC, Amiard-Triquet C, Beaunier P, et al. (2003) Trace-metal detoxification and tolerance of the estuarine worm Hediste diversicolor chronically exposed in their environment. Marine Biology 143: 731–744.
- 83. Dean HK (2008) The use of polychaetes (Annelida) as indicator species of marine pollution: a review. Rev Biol Trop 56: 11–38.
- 84. Kim S, Hammerstom KK, Conlan KE, Thurber AR (2010) Polar Ecosystem Dynamics: Recovery of Communities from Organic Enrichment in McMurdo Sound, Antarctica. Integrative and Comparative Biology 50: 1031–1040.
- 85. Conlan KE, Lenihan HS, Kvitek RG, Oliver JS (1998) Ice scour disturbance to benthic communities in the Canadian high Arctic. Marine Ecology-Progress Series 166: 1–16.
- 86. Tomassetti P, Porrello S (2005) Polychaetes as indicators of marine fish farm organic enrichment. Aquaculture International 13: 109–128.
- 87. Rosenberg R, Blomqvist M, Nilsson CH, Cederwall H, Dimming A (2004) Marine quality assessment by use of benthic species-abundance distributions: a proposed new protocol within the European Union Water Framework Directive. Marine Pollution Bulletin 49: 728–739.
- 88. Stull JK, Haydock CI, Smith RW, Montagne DE (1986) Long-term changes in the benthic community on the coastal shelf of Palos Verdes, Southern California. Marine Biology 91: 539–511.
- 89. Weisberg SB, Thompson B, Ranasinghe JA, Montagne DE, Cadien DB, et al. (2008) The level of agreement among experts applying best professional judgment to assess the condition of benthic infaunal communities. Ecological Indicators 8: 389–394.
- 90. Holte B, Dahle S, Gulliksen B, Næs K (1996) Some macrofaunal effects of local pollution and glacier-induced sedimentation, with indicative chemical analyses, in the sediments of two Arctic fjords. Polar Biology 16: 549–557.
- 91. Osman RW, Whitlatch RB (1998) Local control of recruitment in an epifaunal community and the consequences to colonization processes. Hydrobiologia 375–376: 113–123.
- 92. Dayton PK, Oliver JS (1977) Antarctic soft-bottom benthos in oligotrophic and eutrophic environments. Science 197: 55–58.
- 93. Stark JS (1998) Effects of copper on macrobenthic assemblages in soft-sediments: a laboratory experimental study. Ecotoxicology 7(3): 161–173.
- 94. Morrisey DJ, Underwood AJ, Howitt L (1996) Effects of copper on the faunas of marine soft sediments: a field experimental study. Marine Biology 125: 199–213.
- 95. Oakden JM, Oliver JS, Flegal AR (1984) Behavioral responses of a phoxocephalid amphipod to organic enrichment and trace metals in sediment. Marine Ecology Progress Series 14: 253–257.
- 96. Slattery PN, Oliver JS (1986) Scavenging and other feeding habits of Lysianassid amphipods (Orchomene spp.) from McMurdo Sound, Antarctica. Polar Biology 6: 171–177.
- 97. Lundsten L, Schlining KL, Frasier K, Johnson SB, Kuhnz LA, et al. (2010) Time-series analysis of six whale-fall communities in Monterey Canyon, California, USA. Deep Sea Research Part I: Oceanographic Research Papers 57: 1573–1584.
- 98. Shulenberger E, Hessler RR (1974) Scavenging abyssal benthic amphipods trapped under oligotrophic central North Pacific Gyre waters. Marine Biology 28: 185–187.
- 99. Busdosh M, Robilliard GA, Tarbox K, Beehler CL (1982) Chemoreception in an arctic amphipod crustacean: A field study. Journal of Experimental Marine Biology and Ecology 62: 261–269.
- 100. Gillies CL, Stark JS, Johnstone GJ, Smith SDA (2012) Carbon flow and trophic structure of an Antarctic coastal benthic community as determined by δ13C and δ15N. Estuarine, Coastal and Shelf Science 97: 44–57.
- 101. Gillies CL, Stark JS, Johnstone GJ, Smith SDA (2013) Establishing a food web model for coastal Antarctic benthic communities: a case study from the Vestfold Hills. Marine Ecology Progress Series 478: 27–41.
- 102. de-la-Ossa-Carretero JA, Del-Pilar-Ruso Y, Giménez-Casalduero F, Sánchez-Lizaso JL (2011) Assessing reliable indicators to sewage pollution in coastal soft-bottom communities. Environmental Monitoring and Assessment 184: 2133–2149.
- 103. Corbera J, Cardell MJ (1995) Cumaceans as indicators of eutrophication on soft bottoms. Scientia Marina 59: 63–69.
- 104. Ruiz F, Abad M, Bodergat AM, Carbonel P, Rodríguez-Lázaro J, et al. (2005) Marine and brackish-water ostracods as sentinels of anthropogenic impacts. Earth-Science Reviews 72: 89–111.
- 105. Gibson GR, Bowman ML, Gerritsen J, Snyder BD (2000) Estuarine and Coastal Marine Waters: Bioassessment and Biocriteria Technical Guidance. Office of Water, Washington, DC: US Environmental Protection Agency.
- 106. Borja A, Dauer DM (2008) Assessing the environmental quality status in estuarine and coastal systems: Comparing methodologies and indices. Ecological Indicators 8: 331–337.
- 107. Borja A, Miles A, Occhipinti-Ambrogi A, Berg T (2009) Current status of macroinvertebrate methods used for assessing the quality of European marine waters: implementing the Water Framework Directive. Hydrobiologia 633: 181–196.
- 108. Chapman PM, Riddle MJ (2003) Missing and needed: polar marine ecotoxicology. Marine Pollution Bulletin 46: 927–928.
- 109. Morrisey DJ, Underwood AJ, Howitt L, Stark JS (1992) Temporal variation in soft sediment benthos. Journal of Experimental Marine Biology and Ecology 164: 233–245.
- 110. Schlacher TA, Newell P, Clavier J, SchlacherHoenlinger MA, Chevillon C, et al. (1998) Soft-sediment benthic community structure in a coral reef lagoon – the prominence of spatial heterogeneity and ‘spot endemism’. Marine Ecology Progress Series 174: 159–174.
- 111. Stark JS (1998) Heavy metal pollution and macrobenthic assemblages in soft-sediments in two Sydney estuaries, Australia. Journal of Marine and Freshwater Research 49: 533–540.
- 112. Ellingsen KE (2001) Biodiversity of a continental shelf soft-sediment macrobenthos community. Marine Ecology Progress Series 218: 1–15.
- 113. Noren K, Lindegarth M (2005) Spatial, temporal and interactive variability of infauna in Swedish coastal sediments. Journal of Experimental Marine Biology and Ecology 317: 53–68.
- 114. Woodin SA (1974) Polychaete abundance patterns in a marine soft sediment environment: The importance of biological interactions. Ecological Monographs 44: 171–187.
- 115. Barry JP (1988) Hydrographic patterns in McMurdo Sound, Antarctica and their relationship to local benthic communities. Polar Biology 8: 377–391.
- 116. Gasparon M, Ehrler K, Matschullat J, Melles M (2007) Temporal and spatial variability of geochemical backgrounds in the Windmill Islands, East Antarctica: Implications for climatic changes and human impacts. Applied Geochemistry 22: 888–905.
- 117. Cotton JH, Michael KJ (1994) The monitoring of katabatic wind-coastal polynya interaction using AVHRR imagery. Antarctic Science 6: 537–540.
- 118. Smale DA (2008) Continuous benthic community change along a depth gradient in Antarctic shallows: evidence of patchiness but not zonation. Polar Biology 31: 189–198.
- 119. Barnes DKA, Brockington S (2003) Zoobenthic biodiversity, biomass and abundance at Adelaide Island, Antarctica. Marine Ecology Progress Series 249: 145–155.
- 120. Warwick RM, Clarke KR (1995) New ‘biodiversity’ measures reveal a decrease in taxonomic distictness with increasing stress. Marine Ecology Progress Series 129: 301–305.
- 121. Warwick RM, Clarke KR (2001) Practical measures of marine biodiversity based on relatedness of species. Oceanography and Marine Biology: an Annual Review 39: 207–231.
- 122. Warwick RM, Clarke KR (1998) Taxonomic distinctness and environmental assessment. Journal of Applied Ecology 35: 532–543.
- 123. Thompson B, Riddle MJ, Stark JS (2003) Cost efficient methods for marine pollution monitoring at Casey Station, East Antarctica: the choice of sieve mesh-size and taxonomic resolution. Marine Pollution Bulletin 46: 232–243.
- 124. Gutt J, Sirenko BI, Smirnov IS, Arntz WE (2004) How many macrozoobenthic species might inhabit the Antarctic shelf? Antarctic Science 16: 11–16.
- 125. Raupach MJ, Malyutina M, Brandt A, Wägele J-W (2007) Molecular data reveal a highly diverse species flock within the munnopsoid deep-sea isopod Betamorpha fusiformis (Barnard, 1920) (Crustacea: Isopoda: Asellota) in the Southern Ocean. Deep Sea Research Part II: Topical Studies in Oceanography 54: 1820–1830.
- 126. Held C, Wägele J-W (2005) Cryptic speciation in the giant Antarctic isopod Glyptonotus antarcticus (Isopoda: Valvifera: Chaetiliidae). Scientia Marina 69: 175–181.
- 127. Vanderklift MA, Ward TJ, Jacoby CA (1996) Effect of reducing taxonomic resolution on ordinations to detect pollution induced gradients in macrobenthic assemblages. Marine Ecology Progress Series 136: 137–145.