Estuarine macrobenthos respond to a variety of environmental gradients such as sediment type and salinity, and organic enrichment. A relatively new influence, organic loading from suspended bivalve culture, has the potential to alter this response. A study on soft-bottom macrobenthic communities was carried out in the Richibucto estuary (46°4 0′N, 64°50′W), New Brunswick, Canada, with samples collected from 18 stations in late September and early October 2006. The site consisted of a large tidal channel originating upstream in a small river. The channel was punctuated by bag culture of oysters along its length. A total of 88 species were recorded. The mean values of abundance, species richness, and diversity (H′) of macrofauna were 11,199 ind. m −2 (ranged from 4,371 to 19,930 ind. m −2 ), 23.4 species grab −1 and 3.29 grab −1 , respectively. In general species richness and H′ increased from the upper estuary to the estuarine mouth. Multivariate analyses clearly exhibited the spatial distribution in community structure, which coincided with the locations along the estuary (the upper, the lower and the mouth), as well as inside and outside the channel. Species richness and diversity H′ showed strong positive correlations with salinity (21.2-25.2 ppt), and abundance was positively correlated with water depth (1.0-4.5 m). Abundance and species richness were negatively correlated with both of silt-clay fraction (3.3-24.8%) and sorting (σ I ). Species richness was also negatively correlated with organic content (1.9-12.7%). The BIO-ENV analyses identified silt-clay fraction, σ I and salinity as the major environmental variable combination influencing the macrofaunal patterns, and siltclay fraction as the single best-correlated variable.

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This study sought to understand the performance of arctic treatment systems and the impact of wastewater effluent on benthic invertebrate communities in arctic receiving water habitats. Effluent quality and benthic impacts were monitored in the receiving water of five communities across Nunavut that differed in the type and level of treatment achieved by wastewater infrastructure, the volume of effluent and receiving water mixing environment. We detected minimal impacts to benthic communities (<225 m linear distance from the effluent source) in four out of the five communities (Grise Fiord, Kugaaruk, Pond Inlet, and Pangnirtung), where the population was <2000 people. In these small communities impacts were characterized by increases or decreases in species richness, diversity, evenness, and density, and some differences in benthic species composition. This was in contrast to benthic sediments in Iqaluit (population 6699), which were devoid of benthic fauna up to 580 m from the effluent source in response to sediment anoxia. Variation in benthic community response between sampling locations was attributed primarily to differences in effluent volume, with effluent quality and receiving water hydrodynamics playing secondary roles. The results of this study will help to inform the development of northern specific treatment performance standards which will aid in prioritizing community wastewater system upgrades in arctic communities.

Sea surface temperature (SST) and salinity (SSS) are essential variables at the ocean and atmosphere interface when considering risk factors for disease in farmed and wild fish stocks. Ecological research has witnessed a recent trend in use of digital and satellite technologies, including remote-sensing tools. We explored spatial coverage of remotely-sensed SST and SSS data and compared them with in situ measurements of water temperatures and salinity, which led to suggested adjustments to the remotely-sensed data for its use in aquaculture research. The in situ data were from farms and wild surveillance sites in coastal British Columbia, Canada, from 2003 to 2016. Concurrent SST and SSS values were extracted from remotely-sensed products and compared with 20,513 and 20,038 in situ records for water temperature and salinity, respectively, from 232 different sites. Among nine SST products evaluated, the UKMO OSTIA SST (UK Meteorological Office) had the highest retrieval, and highest concordance correlation coefficient (0.86), highest index of agreement (0.93), fewest missing values, and smallest mean and SD values for bias, when compared to in situ measurements. A mixed linear regression model with UKMO OSTIA SST as the predictor for in situ measurements estimated an adjustment coefficient of 0.89 • C for UKMO OSTIA SST. None of the three SSS products evaluated provided appropriate corresponding values for in situ sites, suggesting that spatial coverage for the study area is currently lacking. This study demonstrates that, among SST products, UKMO OSTIA SST is currently best suited for aquaculture studies in coastal BC. The near real-time availability of these data with the estimated adjustment would allow their use in forecast models, surveillance of pathogens, and the creation of risk maps.

Accurate maps representing seagrass spatial distribution are essential components for effective monitoring and management of coastal vegetated habitats. Satellite and acoustic remote sensing provide valuable spatial data for seagrass mapping, though few studies have evaluated the complementarity of these methods. In this study, the complementarity of seagrass mapping was assessed through comparison of acoustic and satellite remote-sensing data sets. QuickBird ® satellite imagery representing the seagrass landscape of the Richibucto estuary, New Brunswick, Canada, was classified through an object-based procedure and evaluated against a single-beam sonar data set. Acoustic percentage cover values were classified into binary presence/absence format through the application of a decision threshold, allowing comparison with satellite data using the error matrix and derived metrics. Though the binary satellite classification resulted in relatively high accuracy compared with independent ground reference data, agreement between satellite and acoustic data sets was limited. Local differences in seagrass prevalence and patchiness affected classification accuracy, highlighting the potential for under-or overestimating seagrass cover when applying bay-scale classification to areas with different landscape structure. These results emphasize the importance of landscape context in seagrass mapping. Satellite and acoustic remote sensing were seen to fundamentally differ in their depiction of the landscape. Comparison of multiple remote-sensing methods allowed for assessment of complementarity as well as ecologically relevant insight to seagrass spatial dynamics, with implications for mapping and monitoring of seagrass habitats.