Seagrass meadows are among the most productive and diverse marine ecosystems, providing essential structure, functions, and services. They are also among the most impacted by human activities and in urgent need of better management and protection. In Canada, eelgrass ( Zostera marina) meadows are found along the Atlantic, Pacific, and Arctic coasts, and thus occur across a wide range of biogeographic conditions. Here, we synthesize knowledge of eelgrass ecosystems across Canada’s coasts, highlighting commonalities and differences in environmental conditions, plant, habitat, and community structure, as well as current trends and human impacts. Across regions, eelgrass life history, phenology, and general species assemblages are similar. However, distinct regional differences occur in environmental conditions, particularly with water temperature and nutrient availability. There is considerable variation in the types and strengths of human activities among regions. The impacts of coastal development are prevalent in all regions, while other impacts are of concern for specific regions, e.g., nutrient loading in the Atlantic and impacts from the logging industry in the Pacific. In addition, climate change represents a growing threat to eelgrass meadows. We review current management and conservation efforts and discuss the implications of observed differences from coast to coast to coast.

Satellite images are an effective tool for the detection of phytoplankton blooms, since they cause striking changes in water color. Bloom intensity can be expressed in terms of chlorophyll-a concentration. Previous studies suggest the use of Landsat TM4/TM3 reflectance ratio to retrieve surface chlorophyll-a concentration from aquatic systems. In this study we assumed that a remote sensing trophic state index can be applied to investigate how changes in HRT along the hydrologic year affect the spatial distribution of the phytoplankton blooms at Ibitinga's reservoir surface. For that, we formulated two objectives: (1) apply a semi-empirical model which uses this reflectance ratio to map chlorophyll-a concentration at Ibitinga reservoir along the 2005 hydrologic year and (2) assess how changes in hydraulic residence time (HRT) affect the spatial distribution of phytoplankton blooms at Ibitinga Reservoir. The study site was chosen because previous studies reported seasonal changes in the reservoir limnology which might be related to the reservoir seasonality and hydrodynamics. Six Landsat/TM images were acquired over Ibitinga reservoir during 2005 and water flow measurements provided by the Brazilian Electric System National Operator -ONS were used to compute the reservoir´s residence time, which varied from 5.37 to 52.39 days during 2005. The HRT in the date of image acquisition was then compared to the distribution of chlorophyll-a in the reservoir. The results showed that the HRT increasing implies the increasing of the reservoir surface occupied by phytoplankton blooms.Keywords: Landsat TM4/TM3 band ratios, chlorophyll-a, phytoplankton bloom, hydraulic residence time.Efeito de variações no tempo de residência hidráulica sobre a ocorrência de florações de fitoplâncton: estudo de caso no Reservatório de Ibitinga (SP) com o uso de imagens Landsat/TM ResumoAs imagens de satélite são frequentemente usadas para a identificação de florações de fitoplâncton porque sua presença causa mudanças significativas na cor da água. A abundância das florações pode ser quantificada por medidas de concentração de clorofila-a. Diversos estudos sugerem o uso da razão de reflectância das bandas TM4/TM3 Landsat, para determinar as concentrações de clorofila-a em sistemas aquáticos. Este trabalho tem como objetivos: (1) Palavras-chave: razões entre bandas TM4/TM3, clorofila-a, florações de fitoplancton, residência hidráulica.

We used a three-dimensional model to assess the dynamics of diffusive carbon dioxide flux (F(CO2)) from a hydroelectric reservoir located at Amazon rainforest. Our results showed that for the studied periods (2013 summer/wet and winter/dry seasons) the surface averaged F(CO2) presented similar behaviors, with regular emissions peaks. The mean daily surface averaged F(CO2) showed no significant difference between the seasons (p>0.01), with values around -1338mg Cm-2day-1 (summer/wet) and -1395mg Cm-2day-1 (winter/dry). At diel scale, the F(CO2) was large during the night and morning and low during the afternoon in both seasons. Regarding its spatial distribution, the F(CO2) showed to be more heterogeneous during the summer/wet than during the winter/dry season. The highest F(CO2) were observed at transition zone (-300mg Cm-2h-1) during summer and at littoral zone (-55mg Cm-2h-1) during the winter. The total CO2 emitted by the reservoir along 2013 year was estimated to be 1.1Tg C year-1. By extrapolating our results we found that the total carbon emitted by all Amazonian reservoirs can be around 7Tg C year-1, which is 22% lower than the previous published estimate. This significant difference should not be neglected in the carbon inventories since the carbon emission is a key factor when comparing the environmental impacts of different sources of electricity generation and can influences decision makers in the selection of the more appropriate source of electricity and, in case of hydroelectricity, the geographical position of the reservoirs.

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In most coastal waters, riverine inputs of suspended particulate matter (SPM) and colored dissolved organic matter (CDOM) are the primary optically active constituents. Moderate- and high-resolution satellite optical sensors, such as the Operational Land Imager (OLI) on Landsat-8 and the MultiSpectral Instrument (MSI) on Sentinel-2, offer a synoptic view at high spatial resolution (10–30 m) with weekly revisits allowing the study of coastal dynamics (e.g., river plumes and sediment re-suspension events). Accurate estimations of CDOM and SPM from space require regionally tuned bio-optical algorithms. Using an in situ dataset of CDOM, SPM, and optical properties (both apparent and inherent) from various field campaigns carried out in the coastal waters of the estuary and Gulf of St. Lawrence (EGSL) and eastern James Bay (JB) (N = 347), we developed regional algorithms for OLI and MSI sensors. We found that CDOM absorption at 440 nm [ag (440)] can be retrieved using the red-to-green band ratio for both EGSL and JB. In contrast, the SPM algorithm required regional adjustments due to significant differences in mass-specific inherent optical properties. Finally, the application of regional algorithms to satellite images from OLI and MSI indicated that the atmospheric correction (AC) algorithm C2RCC gives the most accurate remote-sensing reflectance (Rrs) absolute values. However, the ACOLITE algorithm gives the best results for CDOM estimation (almost null bias; median symmetric accuracy of 45% and R2 of 0.78) as it preserved the Rrs spectral shape, while tending to yield positively bias SPM (88%). We conclude that the choice of the algorithm depends on the parameter of interest.