CC BY
14Russian Journal of Nematology, 2012, 20 (2), 127-140
Temporal dynamics in nematode biodiversity and community structure at an experimental open ocean aquaculture site, Gulf of Maine, uSa
1 12 Eyualem Abebe , Matthew Joseph and Wim Bert
'Department of Biology and Marine Environmental Science, Elizabeth City State University, 1704 Weeksville Rd, Jenkins Science Center, Room 421, Elizabeth City, NC 27909, USA; e-mail: Ebabebe@mail.ecsu.edu ^Department of Biology, Nematology Unit, Ghent University, Ledeganckstraat 35, 9000 Ghent, Belgium
Accepted for publication 20 November 2011
Summary. We investigated nematode biodiversity and community structure during two time periods, 2002 and 2006, at four sites in the Gulf of Maine within the vicinity of an experimental open ocean aquaculture site. Here we present our findings of this first long-term temporal study in the area on changes in biodiversity and nematode community structure. Our results showed that, over a period of four years, nematode biodiversity declined significantly and nematode community structure changed drastically. Temporal changes were most pronounced but not restricted to the close vicinity of the open ocean aquaculture; sites that were considered control for other and ongoing macrofaunal monitoring also showed a considerable temporal decline in nematode biodiversity. Nematode communities changed so drastically that they grouped closely with multivariate analysis based on year of sampling rather than locality. A better grasp of long term biodiversity and community dynamics may give us a more realistic view of benthic ecology in light of the use of meiofauna as indicators of environmental change. Key words: Environmental impact, Gulf of Maine; meiofauana; nematode community dynamics; Northwestern Atlantic; open ocean aquaculture; temporal dynamics.
In the past two decades, coastal marine habitats have become sites of expansion of an intensive fish cage farming industry (open ocean aquaculture) (Grego et al., 2009; Read and Fernandes, 2003). With this expansion has arisen a concern for the coastal marine environment, and for the industry to be sustainable, it has become necessary to address those environmental concerns ( Wu, 1995, Carroll et al., 2003; Read and Fernandes, 2003; Cole et al, 2009; Grego et al, 2009; Wild-Allen et al, 2010;).
Dissolved and particulate organic compounds in the form of faeces and food and excretory inorganic products such as ammonia, medicines and antifoulants are some of the residues of fish farms impacting coastal marine environments (Read & Fernandes, 2003). However, organic matter accumulation is reported to have a disproportionately high impact in modifying the sediment environment in fish farms (GESAMP, 1990; Karakassis et al., 1998) affecting the structure and characteristics of benthic communities including meiofauna (Mazzola et al., 1999; Sutherland et al., 2007; Mirto et al, 2010; Grego et al., 2009;). Direct measurements of
physicochemical or abiotic variables may not provide a complete picture of the environmental consequences of contaminants. Contaminants may bioaccumulate or toxicity may be observed even at an undetectably low contaminant concentration. Consequently, changes in population parameters or individual attributes are often preferred as indicators of environmental change (Carignan & Villard, 2002; Goodsell et al., 2009). Carignan & Villard (2002) reviewed previous work and summarised desirable organismal attributes for researchers to consider in choosing potential indicators of environmental change. These include the ability to provide early warning of a natural response and continuous assessment over a wide range and intensity of stress.
The methods used to evaluate and monitor the impact of aquaculture on the environment vary. Some use a combination of faunal analysis, sediment profile imagery, sediment chemistry analysis, microbial analysis and diving surveys (Carroll et al., 2003; Crawford et al., 2003). Most often, macrofauna are the preferred group used to evaluate the environmental impact of fish farms ( Grizzle et al., 2003; Brooks et al., 2006). To a
limited extent, meiofauna have also been used to evaluate environmental change, including those related to fish farms (Gyedu-Ababio et al., 1999; Mazzola et al., 1999; Mirto et al., 2002; Danovaro et al., 2004; Grego et al., 2009).
Nematodes are numerically the most abundant component of the meiofauna ( McIntyre, 1969; Platt & Warwick, 1980; Heip et al., 1985; Vezzulli et al, 2008; Mirto et al, 2010) and exhibit extreme diversity in aquatic sediments (Lambshead, 1993, 2004).The high diversity of nematode communities and the high degree of variation in their response to disturbance is such that it enables some species to persist in extremely stressed habitats that otherwise would reduce macrofaunal communities to a handful of species or eliminate them altogether (Heip et al, 1988; Zullini, 1976). Nematodes also are closely associated with the sediment and interstitial water and have a short generation time that enables them to react to sediment disturbance quickly. Furthermore, their sensitivity as indicators of change in sediment health in relation to heavy metals and organic carbon has already been demonstrated (Gyedu-Ababio & Baird, 2006).
This study is a continuation of an investigation of nematode communities within the vicinity of an open ocean aquaculture experimental site (Eyualem Abebe et al., 2004) established in 1997 by the University of New Hampshire for the production of cod, haddock, halibut, and flounder in the Gulf of Maine, USA. The cage started functioning in 1999, and its fish stock grew to about 4,600 in 2002. Ongoing required environmental monitoring at the site employed regular analysis of physicochemical parameters of the water column, sediment surface study using video imagery, and the study of macroinvertebrates. These monitoring efforts consistently reported the absence of environmental impact between 2002 and 2006 (Ward & Bub, 2001, 2005; Ward et al, 2006).
Independent from ongoing environmental studies, in 2002 we began investigating the meiofaunal communities with a focus on nematodes by selecting four stations (two within the impact zone and two control sites). In 2002, the cage was functioning at its minimum capacity (4,600 fish), and our results showed an insignificant difference in diversity or community structure among the nematode communities of the sampled four sites, indicating the absence of environmental impact (Eyualem Abebe et al, 2004). Therefore, we considered the 2002 data as the baseline for future nematode community studies (Eyualem Abebe et al, 2004).
The immediate and evident changes in the benthos in relation to open ocean aquaculture have
been investigated (Mirto et al, 2002). However, detailed investigations on the effect of fish farms on nematode assemblages are rare (Mirto et al., 2002). To our knowledge, long-term temporal studies spanning four years on changes in biodiversity and nematode community structure in relation to the influence of open ocean aquaculture are nonexistent.
The objective of this study was to investigate temporal changes in nematode communities that might have occurred in association with the further increase in fish stock to 50,000 at the open ocean aquaculture site over four years (2006). We hypothesised that should there be an environmental impact from the byproducts of the open ocean aquaculture activities, 1) nematodes at the impact sites would show pronounced temporal changes compared with 2002 in diversity and community structure, 2) assuming designated impact zone reflects level of dispersion of biodeposition, there would be a significant difference in diversity and community structure between the control and impact sites.
70 44 70°40'
Fig. 1. Location of the study site in the Gulf of Maine. Inset: the open ocean aquaculture experimental site (dotted line) and the four sampling sites
MATERIALS AND METHODS
The study area. The Gulf of Maine, on the northeastern coast of the USA (Fig. 1), is a semi-enclosed body of water and one of the most biologically productive regions in the world. Within
the Gulf, the state of New Hampshire was evaluating the feasibility of open ocean aquaculture in two fish cages at a demonstration field site located ~12 km from the coast. We use the term "open ocean aquaculture" simply because the experimental programme was referred to as such by the group working on it and we would like to maintain consistency for ease of communication although the site is coastal. Also this term is used with 'fish farm' interchangeably.
The permit area was rectangular in shape 506 m north to south by 240 m east to west (Figure 1). Fish cages were suspended within the water column and did not reach the sediment. An eight sampling site (sites 1-8), macrofauna-based environmental monitoring study started since the beginning of the experiment. Of the eight sites, four were control sites and from the remaining four, three were considered within the impact zone (Site 2, 4 & 7) and one (Site 5) within a buffering zone (Ward et al., 2001). For our study, for reasons of feasibility and time limitations, we limited sampling to a total of four sites: one within the direct impact of the fish cage, two control and one buffer. Site 4 was within the perimeter of the experimental field site. The other two sites (2 and 6) were considered control sites. Site 2 was 700 m west of the cage, and Site 6 was located about 700 m east of the impact area (Figure 1). Site 5 was about 300 m east of Site 4, and Site 6 in turn was located about 500 m east of Site 5. During our 2002 sampling, the two fish cages held less than 10% (~1600 halibut and 3000 cod) of the total number of fish expected to be grown when in full operation (Eyualem Abebe, 2004).
The sampling area was largely composed of low organic (3%), muddy sand, and the sediment type in the area was continuous across these sampling sites. Water depth and specific sediment characteristics of the sites are given in Table 1.
Sample processing and data analysis. Samples were taken in a Wildco box sampler which were subsequently subsampled (one per site) with Perspex cores (diam. 3.6 cm) on-board University of New Hampshire (UNH) RV Gulf Challenger, transported to UNH in a cooled container and were
extracted following the centrifugal-floatation technique using Ludox, i.e. 50% silicasol colloid solution, and were retained using a 38 ^m sieve. Nematodes were fixed in warm (65 °C) 5% formaldehyde and transferred to anhydrous glycerin according to Seinhorst (1959). Permanent slides were prepared following Cobb (1918) or using glass slides.
In 2002, for each of the four sites, approximately 260 randomly picked individuals were identified to the genus level. In 2006, for each of the four sites, approximately 100 randomly picked individuals were identified to the genus level (except for Site 6 where the total number of worms found was lower than 100). To render data comparability, the rarefaction index was calculated using two methods for a sample size of 91 (Heck et al., 1975; Sanders, 1968). This method eliminates calculation biases emanating from differing sample sizes.
Diversity numbers (Hill, 1973) of the order 0, 1, 2, and were calculated following the
recommendation by Heip et al. (1988). Diversity profiles are visualised using ^-dominance curves (Lambshead et al., 1983). The maturity index (MI) was calculated following Bongers et al. (1991). Nematodes were classified per trophic group according to Wieser's (1953) original grouping.
Data were analysed using a combination of multivariate and univariate methods. Temporal density differences between the 2002 and 2006 samples, diversity indices, and the MI were analysed as the differences between pairs with a non-parametric Wilcoxon-Signed-Rank Test using StatXact 5 (Cytel software). Although the normality and homogeneity of variances did not differ significantly from the normal distribution and we may have opted for parametric tests (e.g. a paired t-test), a non-parametric test was used (and thus reducing the statistical power) because of the low number of samples. For multivariate analysis, a similarity matrix was constructed using the Bray-Curtis measure of similarity on square-root transformed data. An ordination analysis using group average sorting was carried out with multidimensional scaling ordination (MDS).
Table 1. Water depth, coordinates and sediment characteristics of the four sampling sites. LOI = organic content (loss-on-ignition).
Site Depth(m) Latitude Longitude LOI (%) %Gravel %Sand %Mud
Site 2 50.5 428 56.632' 708 38.456' 1.79 2 78 20
Site 4 52.7 428 56.633' 708 37.862' 1.68 1 80 19
Site 5 54.3 428 56.615' 708 37.682' 1.93 0 81 19
Site 6 56.7 428 56.630' 708 37.285' 2.44 0 70 30
Fig. 2. Genus-level taxon accumulation for the Gulf of Maine.
SIMPER analysis was used to determine which species were most responsible for the differences seen between the two sampling years (2002 vs 2006). An analysis of similarities (ANOSIM) was applied to assess significant differences in the nematode species composition between these two sampling years. The ANOSIM compares the ranked dissimilarities between years. The resulting R value lies between 0 and 1. R has an absolute interpretation of its value that is more meaningful than its statistical significance (especially for few replicates in each group). Classification of the sampling sites was done using a group average clustering algorithm. MDS, ANOSIM, SIMPER test and cluster analysis were done using the PRIMER v5.0 software package (Clarck & Gorley, 2001).
RESULTS
A total of 1,558 individuals were indentified from the four sites sampled in 2002 and 2006. We recorded a total of 89 genera (Table 2) of which five taxa could be tentatively identified only to the closest known groups. The genus-level taxon accumulation curve for the Gulf of Maine even after the collection of 1558 individuals did not reach an asymptote (Fig. 2), indicating that nematode inventory at the genus level in the Gulf of Maine at these sites is far from complete. Sabatieria and Setosabatieria were the most dominant overall and together with Terschellengia were present at all sites in both years. SIMPER identified Setosabatieria as the genus with the highest contribution for the 2002 sites (5.4%), while Sabatieria was the genus with the highest contribution for 2006 (20.5%). The average nematode density in the sampling area decreased from 906 in 2002 to 457 ind. 10 cm-2 in
2006 (Fig. 3). Thirty-seven genera from 2002 were not retrieved in 2006, and from those genera not recorded in 2006, Actinonema, Aegialoalaimus, Microlaimus, Paralongicyatholaimus and Rhabdodemania were relatively abundant (> 16 ind. 10 cm-2) in 2002. Desmodora was the only genus that was abundantly present in all locations in 2002 and maintained a comparable density at one site (Site 6) in 2006.
In the 2006 sample, we recorded 19 taxa that were not encountered in 2002. The relative abundance of those newly recorded taxa was low (< 2% for most except Thalassironus that had 4.8% relative abundance), and the following 13 had one or two individuals only: Choanolaimus, Cyartonema, Disconema, Dolicholaimus, Gammanema, Innocuonema, Mesacanthion, Metadesmolaimus, Moralaixia, Neochromadora, Odontophoroides, Polygastrophora and Spirinia. From those taxa encountered in both sampling years, only the genus Dorylaimopsis increased considerably in density from 2002 to 2006.
A summary of the diversity parameters is given in Table 3. The total number of genera (N0) significantly decreased in all sites in 2006 compared to 2002. N0 ranged between 44 and 47 in 2002, while only 14 (Site 4) to maximum 27 genera (Site 2) were found in the five sampled sites in 2006. We observed a significant temporal decline in the Shannon-Wiener diversity index (H; Figure 3) at all sites. The Shannon entropy (H') and Simpson's diversity (1-D) indices for Sites 4 and 5 showed the highest decrease in the number of genera and diversity indices values. Other Hill's diversity numbers (N1, N2 and NM) also decreased in 2006 compared to 2002, except for an increase in N in Site 6 (2006). The lowest diversity (H; H') was observed
Table 2. Relative abundance (percent) of genera in 2002 and 2006 for each of the four sampling sites.
Site 2 Site 4 Site 5 Site 6
Taxa 2002 2006 2002 2006 2002 2006 2002 2006
Acantholaimus - - - - 0.4 - - -
Actinonema 3.2 - 1.1 - 1.2 - 0.8 -
Aegialoalaimus 1.8 - 4.5 - 2.3 - 4.2 -
Aponema - - 0.4 - - - - -
Alaimella - 0.8 0.4 - - - - -
Amphimonhystera - - - - 0.4 - 0.4 -
Araeolaimus - - - - 0.4 - - -
Ascolaimus - - - - - - 0.4 -
Axonolaimus 1.8 0.8 0.4 - 0.8 - 0.8 -
Belbolla 0.7 0.8 - 1.0 1.2 2.0 - -
Calmicrolaimus - - 0.4 - 0.4 - - -
Camacolaimus 0.4 - - - 2.3 - 1.1 -
Campylaimus 0.4 0.8 0.4 - - - 1.1 -
Cervonema - 1.6 0.4 - 0.4 - - 2.9
Choanolaimus - - - 1.0 - - - -
Comesa 1.8 - 0.4 - - - - -
Chromadora 1.1 - - - - - - -
Chromadorina cf. 1.1 - - - - - - -
Cytolaimium 1.1 - - - 0.8 - - -
Cyartonema - 0.8 - - - - - -
Cyatholaimus 0.4 - - - - - 0.4 -
Daptonema 2.1 0.8 1.1 2.0 3.5 - 4.5 -
Desmodora 3.2 - 10.9 - 6.6 - 5.3 5.9
Desmoscolex 0.4 - - - - - - -
Dichromadora 0.4 - - - - - - -
Diplopeltoides cf - - 0.4 - 0.4 2.0 - -
Disconema - - - - - - - 2.9
Dolicholaimus - - - - - 1.0 - -
Dorylaimopsis 1.8 16.3 - 23.0 1.6 - 1.9 -
Enoplid - 0.8 - - - - - -
Enoploides 1.1 0.8 0.4 - 0.8 2.0 - -
Filitonchus 0.4 - 0.4 - 0.4 - 0.4 -
Gammanema - - - - - 1.0 - -
Halalaimus 2.1 1.6 0.4 1.0 0.8 - 1.1 2.9
Halaphanolaimus - - 0.4 - - - - -
Halichoanolaimus cf. - - - - - - 0.4 -
Hopperia 0.4 - 1.1 1.0 0.8 4.0 - -
Innocuonema - 0.8 - - - - - -
Laimella - - 0.4 - - - 0.4 8.8
Leptolaimid - - - - - 1.0 - -
Leptolaimoides 0.4 - - - - - - -
Leptolaimus cf 0.4 3.9 2.3 - 1.2 - 5.3 11.8
Table 2. Relative abundance (percent) of genera in 2002 and 2006 for each of the four sampling sites (continued.)
Site 2 Site 4 Site 5 Site 6
Taxa 2002 2006 2002 2006 2002 2006 2002 2006
Linhystera cf. - - - - - - 0.4 2.9
Mesacanthion - 0.8 - - - - - -
Metadesmolaimus - 0.8 - - - - - -
Metalinhomoeus 9.9 - 6.4 - 5.0 - 3.4 -
Microlaimus 2.8 - 9.0 - 1.6 - 5.7 -
Molgolaimus 2.8 - 0.4 - 0.4 - - -
Moralaixia - 1.6 - - - - - -
Neochromadora - - - 2.0 - - - -
Neotonchus 1.4 0.8 1.1 - 1.2 - 0.4 -
Odontophora 3.5 0.8 7.1 - 5.8 2.0 1.9 5.9
Odontophoroides - 0.8 - - - - - -
Oncholaimus 0.7 - 0.4 - 0.4 - 0.4 -
Paracanthonchus - - - - - - 0.4 -
Paracomesoma - - - - 0.4 - - -
Paralinhomoeus - - 0.4 - - - 0.8 -
Paralongicyatholaimus 3.2 - 2.3 - 1.6 - 0.8 -
Paramonohystera 0.4 - 0.4 - 0.4 - 2.3 -
Paramesacanthion 1.4 0.8 1.1 - 1.9 5.0 - -
Parasphaerolaimus - - - 3.0 0.4 5.0 1.1 -
Pareurystomina 0.4 - - - 0.4 - 0.4 -
Phanoderma 3.2 - - - - - 0.4 -
Plectid - 0.8 - - - - - -
Polygastrophora - - - - - - - 2.9
Pselionema - - 0.8 - - - - -
Quadricoma 0.7 - 0.4 - 1.6 - 0.8 2.9
Rhabdodemania 1.8 - 0.8 - 2.3 - 1.9 -
Rhabditid - 0.8 - - - - - -
Richtersia 7.4 - 10.5 - 5.4 - 5.3 17.6
Sabatieria 11.7 21.7 4.9 4- 16.3 38.0 18.1 2.9
Setosabatieria 11.0 29.5 11.7 5.0 12.2 29.0 12.5 17.6
Siphonolaimus 0.7 - 1.1 - 4.3 1.0 1.5 -
Southerniella cf. - - 0.4 - 0.4 - 0.4 -
Sphaerolaimus - 4.7 1.1 4.0 0.4 1.0 0.8 -
Spirinia - - - 1.0 - - - -
Unknown Sphaerolaimid - - - - 0.4 - - -
Steineria 0.4 - 0.4 - - - 0.8 -
Terschellengia 0.7 5.4 1.9 14.0 1.2 4.0 3.0 2.9
Thalassironus - - - - - - - 2.9
Thalassomonhystera 0.7 0.8 0.8 - - - - -
Theristus - - 0.4 - - - 0.8 -
Trefusia - - - - 0.4 - 0.8 -
Tricoma 6.7 - 8.6 - 2.7 - 5.3 -
Tricotheristus 0.7 - 0.8 - 0.4 - - 5.9
Unidentified - - - 2.0 - - - -
Viscosia 0.7 - 0.4 - 1.2 - - -
Wieseria - - - - - - 0.4 -
Fig. 3. Diversity, expressed as the Shannon-Wiener index (H) and abundance (ind. 10 cm"2) per site and per year; dashed lines indicate the open ocean aquaculture site. Diagrams are plotted on a simplified sampling map.
Fig. 4. K-dominance curves for four sites in 2002 and 2006.
in 2006 in the sampling site closest to the fish cages (Site 4). In addition, evenness decreased in 2006, although not significantly, except for Site 6 K-dominance curves of 2006 samples run consistently above those of 2002 (Figure 4). This indicates that overall evenness, as a measure of an aspect of diversity, is clearly different among the temporally separated nematode communities: those communities got less diverse in 2006 compared to 2002. The MI index also temporally decreased significantly; the average MI value decreased from 2.66 in 2002 to 2.30 in 2006. The highest MI values (2.7) were observed in 2002 in the aquaculture area (Site 4) and also in the control site (Site 2). The lowest MI value (2.1) was recorded in 2006 in the site closest to the fish cage (Site 4). The rarefaction values EG(91), calculated to make diversity data comparable in the face of varying sample sizes in the compared studies, revealed a distinct decrease from 2002 to 2006 (Table 3). The total Gulf of Maine biological diversity estimated through rarefaction EG(91) temporally decreased from 30.9 to 15.4. The rarefaction values decreased most in the aquaculture area (Sites 4 and 5); these values in 2006 were only about half of what we reported in 2002.
The temporal trend of functional group composition over the two periods was not unequivocal (Fig. 5). The most dominant group, the non-selective deposit feeders that comprised on average 47% of the feeding types, decreased in Sites 2 and 6 but increased in Sites 4 and 5. The relative proportion of selective deposit feeders increased in Sites 2, 5 and 6 from about 21% in 2002 to about 27% in 2006 but decreased from 22% to only 7% in the site closest to the fish cage—Site 4. Epistrate feeders decreased in all sites, except Site 6, from about 28% in 2002 to about 19% in 2006. Omnivore predators slightly increased (Sites 4 and 5) or decreased in Site 2 and disappeared in Site 6. The overall measure of this functional diversity, i.e., the trophic diversity index, varied within the range of 0.30 up to 0.47; the index showed a slight increase closest to the fish cage, Sites 4 and 5, but slightly decreased further away from the fish cage, Sites 2 and 6.
MDS ordination analysis clearly showed that the nematode communities of the four sites were more closely grouped based on the year of sampling instead of the sampling locations (Fig. 6). The 2002 samples were positioned very close to each other at the bottom right corner of the MDS plot while the 2006 samples were positioned from the bottom left corner to the upper right corner. ANOSIM also indicated a significant difference between 2002 and
Table 3. Diversity parameters of nematode communities in 2002 and 2006 in the Gulf of Maine. Rarefaction index EG(91) was calculated using Heck et al. (1975)
Site 2 Site 4 Site 5 Site 6 Overall average Significance
2002 2006 2002 2006 2002 2006 2002 2006 2002 2006 2002 vs. 2006
Shannon-Wiener Diversity (H) 3,25 2,29 3,03 1,83 3,19 1,91 3,09 2,51 3,14 2,14 p<0.05
Shannon Entropy (H') 4,70 3,29 4,37 2,64 4,61 2,75 4,47 3,62 4,54 3,086 p<0.05
Simpson's Diversity (D) 0,06 0,17 0,07 0,24 0,07 0,24 0,07 0,10 0,07 0,19 p<0.05
Simpson's Diversity (1-D) 0,94 0,83 0,93 0,77 0,93 0,76 0,93 0,90 0,93 0,82 p<0.05
Evenness 0,85 0,69 0,78 0,69 0,83 X1 0,82 0,91 0,82 0,76 Data missing
Trophic Diversity Index 0,36 0,33 0,34 0,47 0,30 0,35 0,37 0,36 0,34 0,38 NS
Rarefaction values ES(91) 31,0 21,4 26,6 13,5 30,7 15,5 28,8 X1 30.8 15.4 Data missing
Hill's Diversity Numbers
N0 (Species Richness) 46 27 45 14 47 16 44 16 45 18,2 p<0.05
N1 25,8 9,9 20,7 6,2 24,2 6,7 22,0 12,3 23,2 8,8 p<0.05
N2 (Simpson's Reciprocal Diversity ) 17,5 5,9 14,9 4,2 15,1 2,6 13,7 9,8 15,3 5,6 p<0.05
N„ 8,3 3,4 8,5 3,2 6,0 2,6 5,4 5,7 7,1 3,7 NS (p=0.07)
Maturity index 2,7 2,2 2,7 2,0 2,6 2,2 2,6 2,6 2,7 2,3 p<0.05
Abundance (per 10 cm2) 839 132 608 1131 1293 375 884 193 906 457 NS (p=0.07)
Sample size (identified individuals) 283 129 264 100 258 100 265 34 267 91
Mata absent
Fig. 5. Community functional group composition for the analyzed sites in 2002 and 2006.
2006 (P = 0.029), with an R value of 0.54, that corresponds to a clear difference between the two groups with possible overlap (Clarck and Gorley, 2001). SIMPER analyses indicated an average dissimilarity between the nematode genera of 2002 and 2006 of 66.9%. Clustering based on community composition also indicated a higher similarity between the sampling year than between sites (Fig. 7), the 2002 samples are distinctly similar, while Site 6 (2006 sample) was the most different from all the other sites.
Stress: 0.04 *2002 □ 2006 Site 2D Site 6 □
Site 4D
□ Site 5 Site5*-*£ite6 Site 2W * Site 4
Fig. 6. Output of nonmetric multi-dimensional scaling (MDS) on square root-transformed species from four sites in 2002 and in 2006 based on Bray-Curtis measure of similarity.
Fig. 7. Result of clustering based on entire community composition from four samples in 2002 and 2006 using group average clustering.
DISCUSSION
Environmental degradation related to open ocean fish farms has been widely reported (Cole et al., 2009). In addition, the immediate and evident changes that result from fish farm biodeposition
specific to the benthos have been documented: reduced conditions, eutrophication and changes in the structures of microbial and meiofaunal assemblages (Mirto et al., 2002). Nevertheless, reports also show the overall response of meiofaunal communities to fish farm biodeposition to be variable depending on sediment vegetation cover: meiofaunal communities in non-vegetated sites respond to biodeposition more than those in sediments with vegetation cover (Mirto et al, 2010). The fish farm addressed in our study, located about 12 miles offshore in the Gulf of Maine, USA, was at about 50 m water depth (Eyualem Abebe et al, 2004; Ward et al., 2001). The absence of any vegetation eliminates any real or perceived buffering factor to the impacts of biodeposition at our study site.
Despite the relatively rich literature on changes in benthic communities in relation to fish farms ( Mazzola et al, 1999; Karakassis et al., 2000; Mirto et al, 2000, 2002; Sutherland et al, 2007; Papageorgiou et al., 2009; Grego et al., 2009;), long-term investigations on the dynamics of meiofaunal and particularly nematode biodiversity and community structure over a period of several years, to our knowledge, are nonexistent.
Our study revealed a significant, temporal reduction of nematode diversity and a change in nematode community structure. Differences between the nematode assemblages from the two sampling years were evident from the clear separation on the MDS ordination plot. Other analysis confirmed that the communities changed so drastically that temporal factors were more important than spatial proximity, although in the cluster analysis the distinction between the two sets of samples (2002 and 2006) was not completely clear-cut (Fig. 7). The nematode community structure changes observed in the Gulf of Maine may reflect the expected impacts of fish cage biodeposition. For example, Dorylaimopsis was the only genus that drastically increased in abundance in the current study presumably in reaction to an increase in sediment composition. Reports by Gyedu-Ababio & Baird (2006) and Mirto et al. (2002) also showed this genus prefers organic polluted sediments. To a lesser extent, Sabatieria and Terschellingia also increased in relative abundance temporally; Sabatieria especially was the most dominant genus in almost all sites and showed an increase in abundance temporally. These two genera were associated with high organic pollution and low redox potential (Moreno et al., 2010). By contrast, similar to what Mirto et al. (2002) reported in the western Mediterranean, Setosabatieria
increased in abundance in all the sites we studied but declined in abundance at the potentially most impacted site (Site 4). Our results also agree with those of Moreno et al. (2010) in that genera generally considered sensitive, such as Microlaimus, Oncholaimus, Quadricoma, Richtersia, and Tricoma (Moreno et al, 2010), declined in abundance. Although we did not conduct any heavy metal analysis, Paralongicyatholaimus, a genus whose decline was associated with an increased load of copper (Moreno et al., 2009), also declined in abundance in the Gulf of Maine samples.
The declines in diversity and the maturity index were the most pronounced aspects of the temporal differences we recorded. With the exception of the trophic diversity index, all indices indicated a temporal decrease in diversity in all sites. This was also confirmed by the ^-dominance curves of 2006 samples that run consistently above those of 2002. Over the four-year period, the sites closest to the fish farm impact zone (Sites 4 and 5) showed the highest decline in the number of genera and calculated diversity indices, indicating the spatial impact of the fish cage biodeposition. Similar results were obtained for the MI; we observed a temporal decrease for all sites with the highest decrease at the Site 4 that was under the potential direct impact of the fish cage. Together these results suggest an evident combinational effect of time of impact and distance from the impact zone.
The impact of fish cage organic enrichment on nematode abundance in the literature is equivocal. Most studies show nematodes display a significantly reduced density, diversity, and richness in sediments beneath fish farms (Mazzola et al., 1999; La Rosa et al., 2001; Mirto et al, 2002; Sutherland et al, 2007; Moreno et al., 2008;) including in microcosm experiments (Gyedu-Ababio & Baird, 2006). Others reported more indirect associations of organic enrichment with meiofauna by measuring impact using distance from the fish cage as an indicator, i.e., without reporting on organic enrichment itself (Duplisea & Hargrave, 1996). However, a smaller number of studies reported that the distance from fish cages did not affect the average abundance of nematodes (Grego et al, 2009; Vezzulli et al, 2008). Distance from the fish cage may be considered a sufficiently valid predictor of organic enrichment. Previous studies (Carroll et al, 2003) have demonstrated that samples from under fish cages had significantly higher total organic carbon than the reference sites, and the authors reported "indications" that the elevated organic level in those sediments were direct results of fish farm operations. Contrary to most studies, Mirto et al.
(2010) studied four regions in the Mediterranean Sea and reported an increase in nematode abundance beneath the cages in vegetated sediments in Cyprus and non-vegetated sediments in Italy.
A look at macrofaunal studies shows a similar inconclusive pattern in the results: some reports showed, though sediment-specific, the abundance and biomass of macrofauna under the cages (impacted sites) to be higher than at the control sites (Karakassis et al., 2000), while others reported little variability in macrofauna species number and abundance between the impacted and the reference stations (Apostolaki et al, 2007). These discrepancies, whether in meiofauna or macrofaunal studies, could arise from the fact that hitherto studies did not dissect byproduct factors of fish cage processes that potentially impact nematode communities, and the results could be idiosyncratic impacts on the respective communities (Pusceddu & Danovaro, 2009; Pusceddu et al., 2007).
The clear temporal changes in nematode assemblages we described above were not evident in relation to the functional group composition of the communities we investigated: the distribution of feeding types and the trophic index of diversity did not show a uniform and clear-cut trend. Similarly, Mirto et al. (2002), in his study of a fish farm in the western Mediterranean Sea, reported a discrepancy between functional diversity and the other indices: the presence of a clear pattern in the diversity indices and maturity index but the absence of a pattern in functional diversity. This could suggest that the impact of biodeposition from the fish cage on nematodes was not selective toward specific functional groups. However, Mirto et al. (2002) also indicated the possibility that Wieser's (1953) feeding type classification adopted for functional group analysis may not reflect the actual trophic structure and the functional role of specific groups of nematodes (Moens et al., 1999).
Most remarkable in the current study is that the temporal changes in nematode density and community structure were not restricted to the close vicinity of the fish farm impact zone. The temporal decline in diversity we observed was most pronounced below or in the close vicinity of the cage (Sites 4 and 5). However, the two outermost sites (Site 2 in the west and Site 6 in the east), which were considered control sites for macrofaunal monitoring and were situated about 700 m away from the centre of the cage, showed a considerable temporal decline in diversity. The initial design of the environmental monitoring and the designation of sampling sites as an impact zone or control in the currently studied fish cage was proposed for
macrofaunal groups (Grizzle et al., 2001; Ward et al., 2001). However, reports elsewhere have shown meiobenthos to be more sensitive to interactions between physical disturbance and organic enrichment than macrobenthos (Austen & Widdicombe, 2006).
Although negative effects have been reported extending up to 1.2 km from a fish farm, most aquaculture effect studies have been carried out on small spatial scales, i.e., around a particular cage or fish farm site (Karakassis et al., 2000; Sutherland et al, 2007; Vezzulli et al, 2008; Grego et al, 2009). Our study documents potential relatively large-scale effects as opposed to impacts solely under cages and agree with findings of Pohle et al. (2001). The latter was one of the few studies that attempted to monitor regional rather than site-specific impacts. The analysis indicated increased biological stress on the benthic community (macrobenthos), suggesting that major environmental alterations took place in the studied bay on the Canadian coast. Those effects were at distances of at least more than 200 m from any fish farm in that area. Larger-scale effects also agree with Posceddu et al. (2007, 2009), who pointed out that quantitative and qualitative changes in the organic loads of the sediments that arise from intensive aquaculture are dependent upon the ecological context and are not predictable based on only fish-farm attributes and hydrodynamic regimes. Posceddu et al. (2007) observed downward fluxes that did not change significantly as the distance from the cages increased to distances close to 1000 m. Adopting the downward fluxes as a proxy of the potential spatial extent of fish-farm impact, Posceddu et al. (2007) proposed 2 km as an acceptable, conservative, distance between fish farms and any benthic system traditionally considered as vulnerable. Marba et al. (2006) observed the absence of evidence of the impact of fish farms on vertical rhizome growth at a distance greater than 800 m, whereas others (La Rosa et al., 2001; Mirto et al, 2002, 2010), based on a preliminary investigation, used 1 km as the appropriate distance from the cage for non-impacted, control sites. Furthermore, Pitta et al. (2005) have recommended a wider spatial scale of study than previously used for investigating environmental impacts on fish farms.
Methods differ in sensitivity in detecting more subtle effects at greater distances from the cages (Carroll et al., 2003). Visual and sediment chemistry parameters (pH, sulphide and redox potential) revealed marked deviations from the normal situation within a relatively localised area around the farm sites, and severe effects were restricted to
an area within a 10-m radius. Quantitative faunal analysis proved to be a more sensitive method in detecting environmental effects from the cage groups and environmental effects were detected more than 50 m from the fish farm of the cages (Carroll et al., 2003). Our result corroborates the sensitivity of faunal bio-indicators, and especially the potential of meiofauna to reveal aquaculture impact. Despite the fact that our data lend support to an extended effect of open ocean aquaculture in time and space than previously thought, we caution against use of our findings as a confirmation of the impact of fish farm because of the lack of temporal physico-chemical environmental data. Relevant environmental data would be key in confirming the significance of our study. Our results demonstrate a potential impact that, however, needs more temporal investigations to elucidate observed changes in the context of what environmental factors are key in causing them.
Limitation of the data set. Our study of the individual sites was done using only single cores taken from a box corer in each site. Boucher & Lambshead (1995) pointed out that 'in marine nematology, it is traditional to standardise for number of specimens because of the area sampled by a corer is usually considered sufficiently large to obtain a representative sample.' Nonetheless, it remains that replication enhances the precision of estimates by reducing unnecessary 'noise' in the data and permits testing (Hurlbert, 1984).We have standardised sample size through the rarefaction technique (Sanders, 1968; Lambshead, 2003) and this accords our data comparability to similar studies. The preconditions of comparability, however, are not limited only to similar sample size; instead it also includes the difficult issue of standardisation of the taxonomy, and we have also attempted to address it in this study by providing images of those worms at www.nemtol.unh.edu.
CONCLUSIONS
Our results showed, over a four-year period, a significant, temporal reduction in nematode diversity and a change in nematode community structure. These temporal changes were most pronounced but not restricted to the close vicinity of the fish farm impact zone; in addition, sites 700 m away from the centre of the cage considered control sites for macrofaunal monitoring showed a considerable temporal decline in diversity. Multivariate analysis confirmed that communities have changed so drastically that they are more related based on the time of sampling than locality.
The current study, based on nematode assemblages, indicates a potentially, more extended, effect of open ocean aquaculture than previously thought, in time and space.
ACKNOWLEDGEMENT
Eyualem Abebe was supported in part by the US Army Research Laboratory and US Army Research Office under Contract number W911NF-08-1-0402, and US National Science Foundation Award Number 0808632. We thank Jennifer Greene for collecting the sediment samples.
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Резюме. Биологическое разнообразие нематод и их популяционную структуру исследовали на четырех участках вблизи зоны аквакультуры в заливе Мэн открытого океана на протяжении двух периодов в 2002 и 2006 годах. Представлены результаты долговременных наблюдений, которые показывают существенное сниижение биологического разнообразия и изменения в популяционной структуре. Эти изменения были наиболее выражены в зонах аквакультуры открытого океана, хотя и не приурочены исключительно к этим зонам. Участки, рассматривавшиеся в качестве контрольных при наблюдениях за макрофауной, также показали существенное снижение биологического разнообразия. Нематодные сообщества изменились за период наблюдений столь существенно, что многовариантный анализ показывал большее сходство между различными сообществами одного года, нежели между одними и теми же местами сбора проб в разные годы. Авторы полагают, что лучшее понимание долговременных изменений в биологическом разнообразии и изменениях в популяционой структуре мейобентоса позволит сформировать более реалистичный взгляд на использование мейофауны как индикатора экологических изменений.
