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40 results for “lake characteristics”
Satellite derived secchi disk depth and other lake and landscape characteristics in Wisconsin, USA, 1991 - 2012
This data supports the following publication: Rose, K.C., S.R. Greb, M. Diebel, and M.G. Turner. Annual precipitation as a regulator of spatial and temporal drivers of lake water clarity. Ecological Applications. The data uses satellite remotely sensed estimates of Secchi disk depth (Landsat imagery), landscape features, and lake characteristics to understand how and why lakes vary and respond to different drivers through time and space. The data were produced by the authors and their collaborators, as acknowledged in the manuscript. The Secchi disk depth data span the time period 1991-2012.
Microbial Community Composition in Lakes - Taxonomic/Ecological characteristics of the sample at North Temperate Lakes LTER 2000 - 2007
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by a combination of taxonomic and ecological characteristics of the sample allows the user to retrieve sample information [sample IDs, sample dates, lake information (region, type, size, depth) and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites)] and clone information [clone IDs, sequence data, and characteristics of the sequence (length, chimera status, accession number, taxonomic affiliation)]. The data can be filtered by ecological characteristics of the sample [lake name, sample date, lake information (region, type, size, depth)] and taxonomic characteristics of the community members [clone ID, ARISA fragment length (raw or binned), and/or taxonomic characteristics (Phylum and Phylum-Class)]. The output can include links to individual sample records, which contain links to the taxonomic composition of the sample inferred by dynamically matching clones to ARISA fragments in the individual sample. The output can also include links to clone records directly (though this creates a very large number of lines in the output and is not recommended). Project ID's 30 Lakes - Survey of 30 lakes in northern and southern Wisconsin. June, August and October, 2002. See http://microbes.limnology.wisc.edu/lakes30.html. Lake Characteristics. CB0000 - Time series monitoring microbial community composition in Crystal Bog. 2000-2002. CBX_02 - Food web manipulation experiment i
Microbial Community Composition in lakes - Ecological characteristics of the sample at North Temperate Lakes LTER 2002 - 2007
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by ecological characteristics of the sample allows the user to retrieve sample IDs, sample dates, lake information (region, type, size, depth) and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites). The data can be filtered by lake name, sample date, lake information (region, type, size, depth), and physical/chemical data (water temperature, clarity, pH, DOC, SUVA, TN, TP, nitrates/nitrites). The output includes links to individual sample records, which contain links to the taxonomic composition of the sample inferred by dynamically matching clones to ARISA fragments in the individual sample
Microbial Community Composition in Lakes - Taxonomic characteristics of the clones at North Temperate Lakes LTER 2000 - 2007
Microbial community composition is inferred by a combination of automated ribosomal intergenic spacer analysis (ARISA) and PCR-generated clone library analysis. Clone libraries include both the 16S rRNA gene and the 16S-23S ribosomal intergenic spacer fragment. Phylogenetic assignments for individual ARISA fragments are obtained by comparing the ARISA fragment length from each clone to all of the profiles stored in our database. We have analyzed over 3900 clones obtained from 41 lakes that represent the range of trophic types found in temperate landscapes. Querying by taxonomic characteristics of the clone allows the user to retrieve clone IDs, sequence data, and characteristics of the sequence (length, chimera status, accession number, taxonomic affiliation). The data can be filtered by clone ID, ARISA fragment length (raw or binned), and/or taxonomic characteristics (Phylum and Phylum-Class). The output includes links to individual clone records, which contain more detailed information about how the clone was generated (researcher, library ID, project ID, primer sets used, etc.).
Long-term trends and synchrony in dissolved organic matter characteristics in Wisconsin, USA lakes: quality, not quantity, is highly sensitive to climate
Dissolved organic matter (DOM) is a fundamental driver of many lake processes. In the past several decades, many lakes have exhibited a substantial increase in DOM quantity, measured as dissolved organic carbon (DOC) concentration. While increasing DOC is now widely recognized, fewer studies have sought to understand how characteristics of DOM (DOM quality) change over time. Quality can be measured in several ways, including the optical characteristics spectral slope (S275-295), spectral ratio (SR), absorbance at 254 nm (a254), and DOC-specific absorbance (SUVA; a254:DOC). However, long-term measurements of quality are not nearly as common as long-term measurements of DOC concentration. We used 24 years of DOC and absorbance data for seven lakes in the North Temperate Lakes Long Term Ecological Research site in northern Wisconsin, USA to examine temporal trends and synchrony in both DOC concentration and quality. We predicted lower SR and S275-295 and higher a254 and SUVA trends, consistent with increasing DOC and greater allochthony. DOC concentration exhibited both significant positive and negative trends among lakes. In contrast, DOC quality exhibited trends suggesting reduced allochthony or increased degradation, with significant long-term increases in SR in three lakes. Patterns and synchrony of DOM quality parameters suggest they are more responsive to climatic variations than DOC concentration. SUVA in particular tended to increase with greater moisture and decrease with drier conditions. These results demonstrate that DOC quantity and quality can exhibit different complex long-term trends and responses to climate components, with important implications for aquatic ecosystems.
Landscape Position Project at North Temperate Lakes LTER: Lake Characteristics 1998 - 2000
Parameters characterizing the chemical limnology and spatial attributes of 47 lakes were surveyed as part of the Landscape Position Project. Lake characteristics compiled here include lake area and perimeter, catchment area, mean and maximum depth, shoreline development factor, elevation and percent wetlands within catchment area. Lake order was determined using a modification of the method of Riera et al. (2000). Lake order is a numerical surrogate for groundwater influx and hydrological position along a drainage network, with the highest number indicating the lake lowest in a watershed. Lake order for each lake was determined by field visit with presence/absence of streams confirmed, not base solely on topographic maps. Riera, Joan L., John J. Magnuson, Tim K. Kratz, and Katherine E. Webster. 2000. A geomorphic template for the analysis of lake districts applied to Northern Highland Lake District, Wisconsin, U.S.A. Freshwater Biology 43:301-18. Number of sites: 49
Crossing Treeline: Bacterioplankton community composition in alpine and subalpine lakes of the Rocky Mountain southern ecoregion and associated physical and chemical characteristics
This dataset includes lake water samples collected in the summer of 2016 from 16 different mountain lakes in the Rocky mountains in both Rocky Mountain National Park and the Snowy Range of southern Wyoming. Each lake was sampled twice: once in the early summer when hydrologic connections with the surrounding terrestrial environment were high and again in the late summer when hydrologic connections were low. The main goal of the study was to compare communities of bacterioplankton in alpine and subalpine lakes to determine if communities differed across treeline as soil microbes in the surrounding terrestrial environment were. To do so, we collected water samples from the deepest point of each lake, mixed it with a surface water sample and characterized bacterioplankton communities with 16S sequencing technology. Additionally, we wanted to identify abiotic factors that may correlate with community dissimilarity and characterized a suite of chemical attributes for each lake. Lake characteristics reported included surface temperature, soluble reactive phosphorous (SRP), ammonia (NH3+), pH, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), and total dissolved organic carbon (DOC), and chlorophyll a (chl-a).
Minneapolis-St. Paul Metro Area Lakes Surface Water Quality Characteristics
Urban lakes are heavily impacted by human activities and climate variability, and they provide many ecosystem services to residents. The MSP LTER program is studying long term changes in urban lake water quality, ecology and management as part of our long term studies of urban environments. The goal of this dataset is to understand how land-use change, management, and climate have impacted urban lake biogeochemistry over time. This dataset includes parameters characterizing the long term (> 5 years) surface water quality and chemistry of 294 lakes and ponds in the Minneapolis-Saint Paul Seven County Metropolitan Area, Minnesota, USA. The dataset draws from data publicly available through the Minnesota Pollution Control Agency and data provided by individual agencies, park districts and cities. The dataset is distinct from other lake datasets because it is curated to only report a single value per lake x date x parameter, minimizing the amount of data manipulation needed before use in statistical analyses. All data come from the top two meters of the water column. In the case of multiple spatial measurements on a single lake or multiple agencies sampling the same lake on the same day, chemistry data were averaged to generate a single value. For Secchi data, the deepest reported observation on a given lake x date was used. Parameters: total phosphorus, total nitrogen, total Kjeldahl nitrogen, nitrate, nitrite, nitrate + nitrite (NOx), ammonium, chlorophyll a (corrected and not corrected for pheophytin), specific conductivity, chloride, and Secchi depth. These waterbodies are identified by their DNR Division of Water (DOW) number with minor alterations for subbasin identification. This dataset does not comprehensively represent all lentic waterbodies that have substantial water quality data in the metro area, and some included waterbodies may be considered wetlands according to state classifications. The data brought together in this database has undergone QAQC by the
LAGOS-US LOCUS v1.0: Data module of location, identifiers, and physical characteristics of lakes and their watersheds in the conterminous U.S.
This data package, LAGOS-US LOCUS v1.0, is one of the core data modules of the LAGOS-US platform that provides an extensible research-ready platform to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). This data module contains information on the location, identifiers, and physical characteristics of lakes and their watersheds. The characteristics in this module include: variables that can be obtained from GIS data such as location and geometry; variables that can be derived using GIS processing such as lake watersheds and their geometry, lake glaciation history, and lake connectivity; and commonly used identifiers from GIS and other data products useful for linking with LAGOS-US. LOCUS is based on a snapshot of the high-resolution National Hydrography Dataset product available at the initiation of the project that provided the basis for locating, identifying, and characterizing the geometry of all lakes in LAGOS-US. The database design that supports the LAGOS-US research platform was created based on several important design features. Lakes are the fundamental unit of consideration, all lakes in the spatial extent must be represented (above a minimum size) and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other 2 core data modules that are part of the LAGOS-US platform: GEO (which includes geospatial ecological context at multiple spatial and temporal scales for lakes and their watersheds) and LIMNO (in situ lake surface-water physical, chemical, and biological measurements through time) that are each found in their own data packages.
Figure 1 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 1. Spores of Myxobolus lieni (Nie & Li, 1973) (A–B) and M. varius (Achmerov, 1960) (C–D) from Hypophthalmichthys molitrix, line drawings. Scale bars = 2 μm.
Figure 2 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 2. Spores of Myxobolus lieni (Nie & Li, 1973) (A–B) and M. varius (Achmerov, 1960) (C–D) from Hypophthalmichthys molitrix, digitized images. Scale bars = 10 μm.
Figure 3 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 3. Histopathological sections of Hypophthalmichthys molitrix kidney infected by Myxobolus spp. A–C. M. lieni (Nie & Li, 1973), in the renal tubules; D. M. varius (Achmerov, 1960), in the renal interstitium. Arrows indicate the plasmodia which contains 2–4 mature myxospores. Scale bars = 10 μm.
Figure 4 in Morphological, histological and molecular characteristics of Myxobolus spp. (Cnidaria: Myxozoa) infecting the kidney of silver carp in Lake Taihu
Figure 4. Bayesian inference trees constructed with the SSU rDNA sequences. Numbers near the nodes shows the posterior probability and bootstrap values of BI and maximum likelihood (ML), respectively. Information of GenBank accession number, infection site, host and locality follows the species name. Abbreviations: B—brain; E—encephalocoele; F—fin; G—gills; GA—gill arch; GL— capillary network of the gill lamellae; H—heart; I—intestine; K—kidney; M—mesentery; MP- palate of the mouse; MC—muscle cells; SB—swim bladder; UB—urinary bladder.
Figure 2 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 2. Maxent predictions of suitable zebra mussel (Dreissena polymorpha) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
Figure 1 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 1. Physicochemical data survey lakes. Sites categorized by TPWD (at the time of this study in 2016) as "infested" (the water body has an established, reproducing population) or "positive" (zebra mussels or their larvae have been detected on more than one occasion despite lack of evidence of a fully established, reproducing population) are indicated by red triangles and included: Lakes Austin, Belton, Bridgeport, Dean Gilbert, Lavon, Lewisville, Ray Roberts, Stillhouse Hollow, Texoma, Travis, and Waco. Sites categorized by TPWD as zebra mussel "negative" are indicated by green circles and included: Lakes Aquilla, Buchanan, Georgetown, Granbury, Granger, Hubbard Creek, Inks, Lady Bird, LBJ, Limestone, Marble Falls, Palo Pinto, Pflugerville, Possum Kingdom, Proctor, and Whitney.
Figure 4 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 4. Biplot of components 1 and 2 (top) and 1 and 3 (bottom) from Principal Component Analysis of water quality variables in 27 study lakes. Variables that predominated in each component (|factor loading| ≥ 0.50) are shown on the appropriate axes. Individual lake data are represented by symbols, with open circles representing lakes without previously reported incidences of zebra mussels (absent, 16 lakes), and solid circles those known to harbor the invasive species (present, 11 lakes) at the time of sampling (October 2016). No separation between the two lake groups is evident in either of the biplots. Ca, calcium, N, nitrogen; P, phosphorous.
Figure 3 in Predicting suitable habitat for dreissenid mussel invasion in Texas based on climatic and lake physical characteristics
Figure 3. Maxent predictions of suitable quagga mussel (Dreissena bugensis) habitat in Texas. Shading indicates the logistic output of the Maxent model. Polygons represent state and national borders as well as major river basins within Texas.
Рис. 1. ЭкоΛого-географическая характеристика зоопΛанктона гиΔротермаΛьной зоны оз. Кенон в июΛе 2019 г.: А — зоогеография, Б — местообитание, В — способ переΔвижения, Г — способ питания Fig. 1. Ecological and geographic characteristics of zooplankton in the hydrothermal zone of Lake Kenon in July 2019: А — zoogeography, Б — habitat, В — type of locomotion, Г — type of feeding in Zooplankton Structure And Distribution In The Hydrothermal Zone Of Cooling Reservoirs (Trans-Baikal Territory)
Рис. 1. ЭкоΛого-географическая характеристика зоопΛанктона гиΔротермаΛьной зоны оз. Кенон в июΛе 2019 г.: А — зоогеография, Б — местообитание, В — способ переΔвижения, Г — способ питания Fig. 1. Ecological and geographic characteristics of zooplankton in the hydrothermal zone of Lake Kenon in July 2019: А — zoogeography, Б — habitat, В — type of locomotion, Г — type of feeding
Рис. 1. Карта-схема заказника «УΑыΛь» с указанием станций отбора проб зообентоса (с сайта ФГБУ «ЗаповеΑное Приамурье». URL: http://www.zapovedamur.ru/zakaznik_udyl) Fig. 1. Map-scheme of the Udyl Nature Reserve with indication of zoobenthos sampling stations (from website of the Federal State Budgetary Institution "Zapovednoe Priamurye. Available at: http://www.zapovedamur.ru/zakaznik_udyl) in Quantitative zoobenthos characteristics of the Udyl Lake basin (Udyl Nature Reserve, Khabarovsky Region)
Рис. 1. Карта-схема заказника «УΑыΛь» с указанием станций отбора проб зообентоса (с сайта ФГБУ «ЗаповеΑное Приамурье». URL: http://www.zapovedamur.ru/zakaznik_udyl) Fig. 1. Map-scheme of the Udyl Nature Reserve with indication of zoobenthos sampling stations (from website of the Federal State Budgetary Institution "Zapovednoe Priamurye. Available at: http://www.zapovedamur.ru/zakaznik_udyl)
Рис. 4. Структура сообществ зообентоса рек северного и северо-восточного побережья оз. УΑыΛь, июΛь 2021 г. Fig. 4. The structure of zoobenthos communities in the rivers of the northern and northeastern shores of Udyl Lake, July 2021 in Quantitative zoobenthos characteristics of the Udyl Lake basin (Udyl Nature Reserve, Khabarovsky Region)
Рис. 4. Структура сообществ зообентоса рек северного и северо-восточного побережья оз. УΑыΛь, июΛь 2021 г. Fig. 4. The structure of zoobenthos communities in the rivers of the northern and northeastern shores of Udyl Lake, July 2021
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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.