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12 results for “submerged aquatic vegetation”
CVPIA Predation Contact Point Study - 2022: The impact of submerged aquatic vegetation removal on fish predation in a tidal river channel
Proliferation of non-native submerged aquatic vegetation (SAV) has the potential to cause widespread ecosystem changes, and has been attributed to declines in native fish populations around the world. One pathway for these declines is non-native SAV may render ecosystems more hospitable to fish predator species by creating habitat structure, by altering lower trophic food webs, or by affecting predator-prey interactions. It is presumed that non-native vegetation removal will generally favor native fish, however, fish community responses to SAV removals are not well understood. Using a field-based Before-After-Control-Impact study design, we measured the impact of manual SAV removals on short-term changes in predator abundance, predation risk on juvenile Chinook salmon ( Oncorhynchus tshawytscha ; a native fish of management concern), and the aerobic scope of predator and prey in California’s Sacramento-San Joaquin Delta. We found that, while SAV removals decreased abundances of the most common SAV-associated predator, largemouth bass ( Micropterus salmoides ), they resulted in higher predation risk of tethered prey, likely due to the removal of refuge habitat and the immigration of an open-water predator, striped bass ( Morone saxatilis ). SAV removals also buffered against a seasonal decline in environmental oxygen supply, increasing the aerobic scope of juvenile Chinook salmon and largemouth bass; whether such gains for prey would outweigh the persistent aerobic advantage of predators is an open question. While limited in spatial and temporal scope, this study has put into question any short-term benefits of small-scale SAV removal efforts for native fish populations, especially in areas where open-water predator species are abundant.
Data on submerged aquatic vegetation and its water environment in Lake Saint-Pierre, Saint Lawrence River, from 2012 to 2016
<p>This dataset is the result of a large collaborative work lead by the GRIL from 2012 to 2015 on a submerged aquatic vegetation meadow located downstream of two agricultural tributaries (Saint-François and Yamaska rivers) in Lake Saint-Pierre, a fluvial lake of the Saint Lawrence River. The data describe plants (as rake biomass and echosounding) and their environment, including water chemistry, current velocity as well as light, temperature and instantaneous meteo. Only echosounding data are available in 2016 and sediments were collected in 2015. Data are organized as a relational database and the GRIL_LSP_database.png provides keys and links between tables as well as data format. Data are in the tables mesure_integree, mesure_spatiale, mesure_verticale, plante_biomass_taxon, plante_recolte, plante_in_situ. The other tables are metadata about spatiotemporal locations and reported measures. Additional data (e.g. zooplankton, sediments) should eventually be made available and associated to this overall GRIL dataset.</p>
Submerged aquatic vegetation and nitrogen retention data from 2012 to 2017 in lake Saint-Pierre, Saint Lawrence River
<p>Here we provide seven datasets that describes plant biomass (2012 to 2016), environmental variables and nitrogen retention time series (2012 to 2016) in a submerged aquatic vegetation (SAV) meadow at the confluence of two agricultural tributaries (Saint-François and Yamaska) with the St. Lawrence River in southern Lake Saint-Pierre.</p> <p>Version 2 adds the dataset 6 and 7.</p> <p>The seven datasets are:</p> <p>1) Growing season (June 21 to September 22) daily environmental variables (water level, water temperature, light, tributaries input, and SAV biomass indicator)</p> <p>2) Mean SAV biomass measured using rake or quadrat samples in the meadow</p> <p>3) Modelled daily nitrate tributary inputs to the SAV bed</p> <p>4) Daily nitrate output to the SAV bed estimated from a sensor</p> <p>5) Daily nitrate budget</p> <p>6) Hourly nitrate output to the SAV bed and signal decomposition from ensemble empirical mode decomposition (EEMD)</p> <p>7) Hourly dissolved oxygen and gas exchange velocities at the SAV bed outflow for 2016</p> <p>Original data comes from Lake Saint-Pierre, either from publicly available government agencies data, from a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal) or from Christiane Hudon (ECCC). Data were created for an article on climate-driven variation in nitrogen retention, led by Morgan Botrel and supervisor Roxane Maranger, with Christiane Hudon, James B. Heffernan and Pascale M. Biron (https://doi.org/10.1029/2022WR032678).</p>
Simulated submerged aquatic vegetation spectral signatures under different water quality conditions using Hydrolight
<p>Reflectance spectra were simulated using the Hydrolight radiative transfer model (Sequoia Scientific, Bellevue, WA) for four different submerged macrophyte species under a range of water quality conditions at two different depths. We used the four-component case-2 model with spectral reflectance of four submerged species, Egeria densa, Ceratophyllum demersum, Cabomba caroliniana, and Stukenia pectinata. These four reflectance spectra were calculated from the median of 10 measurements of the canopies of the representative species placed in clear tap-water made with a handheld ASD FieldSpec Pro spectrometer. Total suspended solids concentration was varied from 1 to 40 g·m<sup>−3</sup>, chlorophyll-a concentration was varied from 0.5 to 50 mg·m<sup>−3</sup>, and colored dissolved organic matter (CDOM) was varied from 0.25 to 3.5 m<sup>−1</sup>. A total of 4,742 spectra were simulated for all four species and a mud substrate at two different depths, 1 m and 5 m, and for optically deep water.</p>
Submerged aquatic vegetation biomass from the Saint Lawrence River (2006-2016) to compare estimation from quadrat-diver technique to rake collection and echosounding
<p>Here we provide 4 datasets that describes 1) the comparison between quadrat and rake collected biomass (QR), 2) the comparison of rake biomass and biovolume, a biomass proxy derived from echosounding (RE), 3) a validation dataset that confronts quadrat measurements to quadrat prediction measured from echosounding using two intercalibration equations (derived from QR and RE datasets), and 4) a whole-system biomass estimation comparing biomass predicted from echosounding and from rake.</p> <p>Original data comes from the Saint Lawrence River, mainly from Lac Saint-Pierre, but for the QR dataset also from Lac Saint-François and Lac Saint-Louis. Data from the QR (2006-2009) and validation dataset (2016) were collected by Christiane Hudon, Environment and Climate Change Canada, while the RE dataset and part of the validation dataset were collected as part of a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal). Data were created for an article on a method to estimate SAV biomass, led by Morgan Botrel and supervisor Roxane Maranger, with co-supervisor Christiane Hudon and Pascale Biron.</p> <p>For the second version, the data is more clearly organized in the four categories mentioned above. Additionally, revised prediction equations were applied which modifies results used in the validation and whole-system datasets (dataset 2 and 4). Equations are presented in the associated publication:</p> <p>Botrel, M., C. Hudon, P.M. Biron, R. Maranger. Combining quadrat, rake and echosounding to estimate submerged aquatic vegetation biomass at the ecosystem scale. Limnology & Oceanography: Methods. Accepted (as of 2023/02/08)</p>
Dataset for: African manatee (Trichechus senegalensis) habitat suitability at Lake Ossa, Cameroon using trophic state models and predictions of submerged aquatic vegetation
<p>See research article here: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.8202</p> <p>Aim: The present study aims at investigating the past and current trophic status of Lake Ossa and evaluating its potential impact on African manatee health.</p> <p>Location: Lake Ossa is known as a refuge for the threatened African manatees in Cameroon. Little information exists on the water quality and health of the ecosystem as reflected by its chemical and biological characteristics.</p> <p>Methods: Aquatic biotic and abiotic parameters including water clarity, nitrogen, phosphorous and chlorophyll concentrations were measured monthly during four months at each of 18 water sampling stations evenly distributed across the lake. These parameters were then compared with historical values obtained from the literature to examine the dynamic trophic state of Lake Ossa.</p> <p>Results: Results indicate that Lake Ossa’s trophic state parameters doubled in only three decades (from 1985 to 2016), moving from a mesotrophic to a eutrophic state. The decreasing nutrient gradient moving from the mouth of the lake (in the south) to the north indicates that the flow of the adjacent Sanaga River is the primary source of nutrient input. Further analysis suggests that the poor transparency of the lake is not associated with chlorophyll concentrations but rather with the suspended sediments brought-in by the Sanaga River. Consequently, our model demonstrated that despite nutrient enrichment, less than 5% of the lake bottom surface sustained submerged aquatic vegetation. Thus, shoreline emergent vegetation is the primary food available for the local manatee population. During the dry season, water recedes drastically and disconnects from the dominant shoreline emergent vegetation, decreasing accessibility for manatees.</p> <p>Main conclusions: The current study revealed major environmental concerns (eutrophication and sedimentation) that may negatively impact habitat quality for manatees. Efficient land use and water management across the entire watershed may be necessary to mitigate such issues.</p>
Infauna shift trait-productivity relationships in submerged aquatic vegetation communities
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Submerged aquatic vegetation, water quality (pH, salinity, and turbidity) and waterfowl abundance data from 1991-2017 in Back Bay, Virginia
<p><span>Back Bay, Virginia, has been documented as an important foraging area for waterfowl since at least the mid-1800s. Expansive submerged plant beds historically supported diverse assemblages of non-breeding waterfowl, however coastal development and other anthropogenic influences have since led to fluctuations in submerged aquatic vegetation (SAV) and an associated decline in waterfowl abundance in the bay. To gain insight into the effects of environmental drivers on waterfowl foraging guilds, our study explores the effects of SAV frequency and water quality on the abundance of dabbling ducks, diving ducks, and swans and geese in Back Bay. We use 8 years of SAV, water quality, and waterfowl monitoring data collected by state and federal agencies to model the effects of salinity, turbidity, pH, and percent frequency of SAV on the relative abundance of waterfowl by foraging guild in Back Bay. The appropriateness of the data and reasonability of the preliminary results were then evaluated through semi-structured interviews with 11 local informants representing state, federal, and non-governmental organizations. Quantitative results indicated that dabbling ducks are affected differently than other guilds by water quality and percent frequency of SAV. Thematic analysis of the interview data revealed a number of potential explanations for the model results, as well as highlighted areas of uncertainty in need of further research. In a test of face validity, participants demonstrated a significant degree of belief in turbidity, salinity, and SAV as drivers of waterfowl abundance, but were not convinced by the potential effects of pH as demonstrated by the model. This mixed methods study provides insights that could potentially influence the management and conservation of non-breeding waterfowl populations by challenging the assumption that particular environmental conditions serve all foraging groups equally.</span></p>
Evaluating impacts of non-native submerged aquatic vegetation on native nekton
<p>These data accompany the publication of the same name. We performed a quantitative meta-analysis to quantify impacts of non-native submerged aquatic vegetation on native crabs, fishes, and shrimps in coastal, estuarine, and marine systems. We found that nekton abundance, species richness, and biomass were the most assessed metrics of nekton performance. We extracted data from 35 studies and evaluated 11 response metrics related to inter-specific facilitation, restricting our analysis to studies that compared at least one of these metrics in nekton from co-occurring native and non-native SAV habitats in marine, coastal, or estuarine systems.</p>
Submerged aquatic vegetation, water quality (pH, salinity, and turbidity) and waterfowl abundance data from 1991-2017 in Back Bay, Virginia
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Data on global trends and drivers of submerged aquatic vegetation quantities in lakes
<p>This dataset describes trends and drivers of submerged aquatic vegetation quantities in lakes. The database was compiled through a literature synthesis and is the object of a published article. The sav_trend_dbstructure.png describes the database structure.</p> <p>The publication below detail the methodology used to assemble the dataset.</p> <p>Botrel, M. & R. Maranger. 2023. Global historical trends and drivers of submerged aquatic vegetation quantities in lakes. Global Change Biology. 29, 2493– 2509. <a href="https://doi.org/10.1111/gcb.16619">https://doi.org/10.1111/gcb.16619</a></p> <p> </p>
Danish coastal submerged aquatic vegetation 2018
<p>Submerged aquatic vegetation (SAV) mapped with Copernicus Sentinel-2 MSI 10 meter imagery for the Danish coast. Mapping is based on images mainly from April/May 2018. Habitat classification categories are: 1: Unvegetated soft substrate (Sand); 2: Sparse vegetation; 3: Dense vegetation; 4: No data.</p> <p>The map has been developed to capture SAV distributions at the national Danish scale and is less appropriate for local exploration. For a more detailed map of smaller regions, it is recommended to source a local map made with data and models specifically selected and trained for those areas, to ensure the highest level of detail and accuracy. The map shows "Submerged aquatic vegetation SAV" that is, seagrass + macroalgae (and possibly some mussels and stones here and there as well).</p> <p>Note that for the satellite-based approach to be effective, the sea floor must be visible in the satellite imagery. Consequently, the achievable depth for mapping relies on environmental conditions such as cloud coverage, turbidity and water roughness. Typically, it is not possible to detect the eelgrass depth limits in Denmark with satellite imagery. To “see” as deep as possible, for the mapping spring images were used, as Danish waters tend to have better water quality at the beginning of the year, even though the vegetation can spread further during the growing season.</p> <p>The categories “sparse vegetation” and “dense vegetation” do not cover a well-defined percentage coverage but are based on visual interpretation of satellite images and orthophotos.</p> <p>Data portal for free download for private and non-commercial use: https://marine-vegetation.satlas.dk/</p> <p>For more information visit</p> <ul> <li><a href="https://eo.dhigroup.com/projects/mapping_submerged_coastal_vegetation/">https://eo.dhigroup.com/projects/mapping_submerged_coastal_vegetation/</a></li> <li><a href="https://youtu.be/_xAa858qg70">https://youtu.be/_xAa858qg70</a></li> </ul>
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