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155 results for “great lakes”
Indigenous Peoples and environmental research and monitoring within the Laurentian Great Lakes Basin: A systematic map
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Data from: Individual weight estimates for Great Lakes benthic invertebrates
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Quantifying methane emissions from Laurentian Great Lakes estuaries using in situ measurements, remote sensing and machine learning
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Data for: Aquatic connectivity treatments increase fish and macroinvertebrate use of Typha invaded Great Lakes coastal wetlands
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Data from: Muskrat disturbances and their analogues reduce invasive plant dominance within a Great Lakes coastal wetland
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The conservation genetics of Iris lacustris (Dwarf Lake Iris), a Great Lakes endemic
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Data from: Climate connectivity of the bobcat in the Great Lakes region
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Human impacts on Great Lakes walleye Sander vitreus structure, diversity, and local adaptation
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Watershed shapes for the Great Lakes Runoff Inter-comparison Project for Lake Erie (GRIP-E)
<p>This dataset provides the shapefiles of the 46 calibration and 7 validation watersheds used within the Great Lakes Runoff Inter-comparison Project for Lake Erie (GRIP-E).</p> <p>The watersheds draining towards the following WSC and USGS gauge stations have been used for:</p> <p><strong>1a. calibration of objective 1</strong> (low-human impact)<br> (28 stations in total; 13 of them in both objective 1 and 2)<br> 02GA010 02GA018 02GA038 02GA047 02GB007<br> 02GC002 02GC010 02GC018 02GD004 02GE007<br> 02GG002 02GG003 02GG006 02GG009 02GG013<br> 04159492 04159900 04160600 04161820 04164000<br> 04165500 04166100 04177000 04196800 04197100<br> 04207200 04208504 04213000</p> <p><strong>1b. calibration of objective 2</strong> (most-downstream gauges closest to Lake Erie)<br> (31 stations in total; 13 of them in both objective 1 and 2)<br> 02GB001 02GB007 02GC002 02GC007 02GC018<br> 02GC026 02GE007 02GG003 02GG009 02GG013<br> 04159900 04160600 04165500 04166500 04174500<br> 04176500 04177000 04193500 04195820 04198000<br> 04199000 04199500 04200500 04208504 04209000<br> 04212100 04213000 04213500 04214500 04215000<br> 04215500</p> <p><strong>2. (spatial) validation</strong><br> (7 stations in total)<br> 02GE003 04167000 04168000 04185000 04195500<br> 04201500 04208000</p> <p>===============================================================</p> <p>These data have been derived under the Great Lakes Runoff Intercomparison Project for Lake Erie (GRIP-E) led by Juliane Mai and Bryan Tolson (both University of Waterloo) and funded under the Integrated Modelling Program for Canada (IMPC) within the Global Water Futures program.</p>
mHM_UFZ gridded simulations for the Great Lakes Runoff Inter-comparison Project for Lake Erie
<p>This dataset provides gridded model simulations in netcdf format over the Lake Erie using the mHM model (Samaniego, et al., 2010, Kumar et al, 2013), done within the Great Lakes Runoff Inter-comparison Project for Lake Erie (GRIP-E).</p> <p>Model code is available under: <a href="https://git.ufz.de/mhm/mhm">https://git.ufz.de/mhm/mhm</a>, revision number: 8271b54</p> <p>Domain boundaries (WGS84 system): lon_min = -86.0, lon_max = -78.0, lat_min = 40.0, lat_max = 45.0</p> <p>Model variables are simulated at spatial grid of 0.125deg x 0.125deg, daily time step. </p> <p>Simulation period: 01 Jan 2011 - 31 Dec 2014 (with 1year -2010- warm-up)</p> <p>Meteorological input data, see Mai et al. 2020 (in prep)</p> <p>Following model variables are provided for two mHM_parameter.nml realizations (*obj1 and *obj2, as defined in Mai et al. 2020 in prep). </p> <p>double <strong>snowpack</strong>(time, northing, easting) ;<br> snowpack:long_name = "depth of snowpack" ;<br> snowpack:unit = "mm" ;<br> double <strong>SM_Lall</strong>(time, northing, easting) ;<br> SM_Lall:long_name = "average soil moisture over all layers" ;<br> SM_Lall:unit = "mm mm-1" ;<br> double <strong>unsatSTW</strong>(time, northing, easting) ;<br> unsatSTW:long_name = "reservoir of unsaturated zone" ;<br> unsatSTW:unit = "mm" ;<br> double <strong>satSTW</strong>(time, northing, easting) ;<br> satSTW:long_name = "water level in groundwater reservoir" ;<br> satSTW:unit = "mm" ;<br> double <strong>aET</strong>(time, northing, easting) ;<br> aET:long_name = "actual Evapotranspiration" ;<br> aET:unit = "mm d-1" ;<br> double <strong>Q</strong>(time, northing, easting) ;<br> Q:long_name = "total runoff generated by every cell" ;<br> Q:unit = "mm d-1" ;<br> double <strong>QD</strong>(time, northing, easting) ;<br> QD:long_name = "direct runoff generated by every cell (runoffSeal)" ;<br> QD:unit = "mm d-1" ;<br> double <strong>QIf</strong>(time, northing, easting) ;<br> QIf:long_name = "fast interflow generated by every cell (fastRunoff)" ;<br> QIf:unit = "mm d-1" ;<br> double <strong>QIs</strong>(time, northing, easting) ;<br> QIs:long_name = "slow interflow generated by every cell (slowRunoff)" ;<br> QIs:unit = "mm d-1" ;<br> double <strong>QB</strong>(time, northing, easting) ;<br> QB:long_name = "baseflow generated by every cell" ;<br> QB:unit = "mm d-1" ;<br> double <strong>recharge</strong>(time, northing, easting) ;<br> recharge:long_name = "groundwater recharge" ;<br> recharge:unit = "mm d-1" ;</p> <p>===============================================================</p> <p>These data and model runs have been performed under the Great Lakes Runoff Intercomparison Project for Lake Erie (GRIP-E) led by Juliane Mai and Bryan Tolson (both University of Waterloo) and funded under the Integrated Modelling Program for Canada (IMPC) within the Global Water Futures program. This work has received funding from the Initiative and Networking Fund of the Helmholtz Association through the project Advanced Earth System Modelling Capacity (ESM) (<a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/www.esm-project.net">www.esm-project.net</a>).</p>
Data from: Phenotypic, ecological and genomic variation in common bully (Gobiomorphus cotidianus) populations along depth gradients in New Zealand's Southern Great Lakes
<p>Depth gradients in lakes are often key drivers of population divergence and speciation in fishes. New Zealand has many deep lakes but no known profundal specialist fishes or cases of intralacustrine speciation. We sampled a native benthic fish, the common bully, from 5–90 m depth in four South Island lakes, to test for morphological, ecological, or genetic differentiation associated with depth. Deeper fish consistently had narrower bodies, while other morphological traits showed variable relationships with depth. Carbon and nitrogen stable isotope values of fish increased with depth, largely tracking isotopic trends with depth of benthic invertebrate prey. Genotyping-by-sequencing showed some genome-wide differentiation between two of the lakes, but no evidence for within-lake genetic structuring along depth gradients. These results indicate that individual bullies associate with shallower or deeper habitats within their lifetimes, but we found no evidence of progress toward genetic divergence within lakes. The apparent lack of intralacustrine genetic divergence in New Zealand's fishes may be explained by a combination of environmental factors and constraints intrinsic to its marine-derived freshwater fish fauna.</p>
Data from: A century of intermittent eco-evolutionary feedbacks resulted in novel trait combinations in invasive great lakes Alewives (Alosa pseudoharengus)
<p>Species introductions provide opportunities to quantify rates and patterns of evolutionary change in response to novel environments. Alewives (<em>Alosa pseudoharengus</em>) are native to the East Coast of North America where they ascend coastal rivers to spawn in lakes, and then return to the ocean. Some populations have become landlocked within the last 350 years and diverged phenotypically from their ancestral marine population. More recently alewives were introduced to the Laurentian Great Lakes (~150 years ago), but these populations have not been compared to East Coast anadromous and landlocked populations. We quantified 95 years of evolution in foraging traits and overall body shape of Great Lakes alewives and compared patterns of phenotypic evolution of Great Lakes alewives to East Coast anadromous and landlocked populations. Our results suggest that gill raker spacing in Great Lakes alewives has evolved in a dynamic pattern that is consistent with responses to strong but intermittent eco-evolutionary feedbacks with zooplankton size. Following their initial colonization of Lakes Ontario and Michigan, dense alewife populations likely depleted large-bodied zooplankton, which drove a decrease in alewife gill raker spacing. However, the introduction of large, non-native zooplankton to the Great Lakes in later decades resulted in an increase in gill raker spacing, and present-day Great Lakes alewives have gill raker spacing patterns that are similar to the ancestral East Coast anadromous population. Conversely, contemporary Great Lakes alewife populations possess a gape width consistent with East Coast landlocked populations. Body shape showed remarkable parallel evolution with East Coast landlocked populations, likely due to a shared response to the loss of long-distance movement or migrations. Our results suggest the colonization of a new environment and cessation of migration can result in rapid parallel evolution in some traits, but contingency also plays a role, and a dynamic ecosystem can also yield novel trait combinations.</p>
Datasets relating (i) A wetland fish multimetric index to variation in agricultural stress among Laurentian Great Lakes coastal wetlands, (ii) Cyanobacteria biomass to total phosphorus concentrations among Canadian lakes
<p>We present two datasets of biological responses against environmental stresses. In the first dataset, the biological response and environmental stress variables are fish multimetric index of community health and agricultural stress, respectively, in watersheds draining to Laurentian Great Lakes. In the second dataset, the biological response and environmental stress variables are cyanobacterial biomass and total phosphorus, respectively, in Canadian Lakes.</p>
Data from: Human-mediated and natural dispersal of an invasive fish in the eastern Great Lakes
The globally invasive Round Goby (Neogobius melanostomus) was introduced to the Great Lakes around 1990, spreading widely and becoming the dominant benthic fish in many areas. The speed and scope of this invasion is remarkable and calls into question conventional secondary spread models and scenarios. We utilized 9 microsatellites to identify large-scale genetic structure in Round Goby populations in the eastern Great Lakes, and assessed the role of colonization versus secondary transport and dispersal in developing this structure. We identified three clusters, corresponding with Lake Huron, eastern Lake Erie, and western Lake Erie plus eastern Lake Ontario, along with three highly-divergent populations. Bottleneck analysis identified founder effects in two divergent populations. Regression analyses of isolation-by-distance and allelic richness vs. distance from the initial invasion site were consistent with limited migration. However, some populations in eastern Lake Erie and Lake Ontario showed anomalously low genetic distance from the original site of colonization, consistent with secondary transport of large numbers of individuals via ballast water. Genetic structure of Round Goby in the Great Lakes principally resulted from long-distance secondary transport via ballast water with additional movement of individual via bait buckets and natural dispersal. The success of Round Gobies represents an interesting model for colonization characterization; however, those same attributes present significant challenges for conservation and fisheries management. Current management likely prevents many new species from arriving in the Great Lakes, but fails to address the transport of species within the lakes after they arrive; an issue of clear and pressing importance.
Data from: Coalescent models characterize sources and demographic history of recent round goby colonization of Great Lakes and inland waters
The establishment and spread of aquatic invasive species is ecologically and economically harmful and a source of conservation concern internationally. Processes of species invasion have traditionally been inferred from observational data of species presence/absence and relative abundance. However, genetic-based approaches can provide valuable sources of inference. Restriction-site associated DNA sequencing was used to identify and genotype single nucleotide polymorphism (SNP) loci for Round Gobies (Neogobius melanostomus) (N=440) from 18 sampling locations in the Great Lakes and in three Michigan, USA drainages (Flint, Au Sable, and Cheboygan River basins). Sampled rivers differed in size, accessibility, and physical characteristics including man-made dispersal barriers. Population levels of genetic diversity and inter-population variance in SNP allele frequency were used in coalescence-based Approximate Bayesian Computation (ABC) to statistically compare models representing competing hypotheses regarding source population, post-colonization dispersal, and demographic history in the Great Lakes and inland waters. Results indicate different patterns of colonization across the three drainages. In the Flint River, models indicate a strong population bottleneck (< 3% of contemporary effective population size) and a single founding event from Saginaw Bay led to the colonization of inland river segments. In the Au Sable River, analyses could not distinguish potential source populations, but supported models indicated multiple introductions from one source population. In the Cheboygan River, supported models indicated that colonization likely proceeded from east (Lake Huron source) to west among inland locales sampled in the system. Despite the recent occupancy of Great Lakes and inland habitats, large numbers of loci analyzed in an ABC framework enable statistically supported identification of source populations and reconstruction of the direction of inland spread and demographic history following establishment. Information from analyses can direct management actions to limit the spread of invasive species from identified sources and most probable vectors into additional inland aquatic habitats.
Data from: Environmental DNA detection of rare and invasive fish species in two Great Lakes tributaries
The extraction and characterization of DNA from aquatic environmental samples offers an alternative, non-invasive approach for the detection of rare species. Environmental DNA, coupled with PCR and next-generation sequencing ("metabarcoding"), has proven to be very sensitive for the detection of rare aquatic species. Our study used a custom designed group-specific primer set and next-generation sequencing for the detection of three species at risk; (Eastern Sand Darter, Ammocrypta pellucida; Northern Madtom, Noturus stigmosus; and Silver Shiner, Notropis photogenis), one invasive species (Round Goby, Neogobius melanostomus) and an additional 78 native species from two large Great Lakes tributary rivers in southern Ontario, Canada; the Grand River and the Sydenham River. Out of 82 fish species detected in both rivers using capture-based and eDNA methods, our eDNA method detected 86.2% and 72.0% of the fish species in the Grand River and the Sydenham River, respectively, which included our four target species. Our analyses also identified significant positive and negative species co-occurrence patterns between our target species and other identified species. Our results demonstrate that eDNA metabarcoding that targets the fish community as well as individual species of interest provides a better understanding of factors affecting the target species spatial distribution in an ecosystem than possible with only target species data. Additionally, eDNA is easily implemented as an initial survey tool, or alongside capture-based methods, for improved mapping of species distribution patterns.
FIGURE 4. Moraria hudsoni n in A new species of Moraria (Crustacea: Copepoda: Harpacticoida) from the Laurentian Great Lakes
FIGURE 4. Moraria hudsoni n. sp., female. A, Left leg 1 and coupler; B, right leg 2 and coupler; C, left leg 3, coupler, and right leg 3 endopodite; D, leg 4; E, leg 5 (arrow indicates 6th seta, present in holotype female but not in most individuals examined).
FIGURE 3. Moraria hudsoni n in A new species of Moraria (Crustacea: Copepoda: Harpacticoida) from the Laurentian Great Lakes
FIGURE 3. Moraria hudsoni n. sp., female. A, Abdomen, ventral view; B, caudal ramus, lateral view; C, anal operculum and caudal rami, dorsal view; D, caudal ramus, ventral view; E, antennule; F, antenna; G, antennal exopodite, enlarged; H, mandible; I, maxilla; J, maxilliped.
FIGURE 6. Moraria hudsoni n in A new species of Moraria (Crustacea: Copepoda: Harpacticoida) from the Laurentian Great Lakes
FIGURE 6. Moraria hudsoni n. sp., male. A, antennule; B, leg 2 endopodite, frontal; C, leg 2 endopodite, lateraloblique view, showing terminal setae; D, leg 3 endopodite; E, right leg 4 endopodite of allotype specimen, lateraloblique view; F, left leg 4 endopodite of allotype specimen, frontal view; G, terminal spine of leg 4 endopodite of allotype specimen, oblique view, enlarged; H, leg 5.
FIGURE 5. Moraria hudsoni n in A new species of Moraria (Crustacea: Copepoda: Harpacticoida) from the Laurentian Great Lakes
FIGURE 5. Moraria hudsoni n. sp., male. A, habitus, lateral view (longest terminal caudal seta shown separately); B, habitus, dorsal view; C, urosome, ventral view. Scale bar applies to all figures.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.