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47 results for “global lakes”
Global lake color dataset
<p>Lake color dataset for 147,025 global lakes. The dataset contains >5.1 million lake center surface reflectance records in the visual bands from Landsat 8 OLI sensor, as well as the estimated water color using dominant wavelength.</p>
Inputs for lake morphology in ISIMIP3 runs of the global lake sector
<p>Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). The Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) was founded for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various Representative Greenhouse Gas Concentration Pathways, all consistently bias-corrected on a 0.5° × 0.5° global grid. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.</p> <p>For a comprehensive description of ISIMIP, sectors, and protocols please see https://www.isimip.org/</p> <p>In order to simulate the impacts of climate change on lakes worldwide, the ISIMIP3 Lake Sector protocol has defined a set of lakes to be modelled by all participating lake models, as well as the basic morphometry (i.e., hypsographic curves) information for each lake. This repository includes all calculations performed to obtain the final set of lake location and mosphometry inpput information for ISIMIP3 runs. For this, available datasets on global lake extension and morphometry were used first for selecting a set of representative lakes on Earth (~40000 lakes, one for each 0.5º pixel of the normalized input/putput grid for ISIMIP across sectors), and then morphological characteristics were assigned to each representative lake using a database on global lake morphology. The final set of files constitute the input data for lake morphology and location for ISIMIP3 Lake Sector runs, which are produced in netCDF format.<br> </p>
Data from: Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats
The repeatability of adaptive radiation is expected to be scale dependent, with determinism decreasing as greater spatial separation among "replicates" leads to their increased genetic and ecological independence. Threespine stickleback (Gasterosteus aculeatus) provide an opportunity to test whether this expectation holds for the early stages of adaptive radiation -their diversification in freshwater ecosystems has been replicated many times. To better understand the repeatability of that adaptive radiation, we examined the influence of geographic scale on levels of parallel evolution by quantifying phenotypic and genetic divergence between lake and stream stickleback pairs sampled at regional (Vancouver Island) and global (North America and Europe) scales. We measured phenotypes known to show lake-stream divergence and used reduced representation genome-wide sequencing to estimate genetic divergence. We assessed the scale-dependence of parallel evolution by comparing effect sizes from multivariate models and also the direction and magnitude of lake-stream divergence vectors. At the phenotypic level, parallelism was greater at the regional than the global scale. At the genetic level, putative selected loci showed greater lake-stream parallelism at the regional than the global scale. Generally, the level of parallel evolution was low at both scales, except for some key univariate traits. Divergence vectors were often orthogonal, highlighting possible ecological and genetic constraints on parallel evolution at both scales. Overall, our results confirm that the repeatability of adaptive radiation decreases at increasing spatial scales. We suggest that greater environmental heterogeneity at larger scales imposes different selection regimes, thus generating lower repeatability of adaptive radiation at larger spatial scales.
The effect of eutrophication and global change on heterocystous cyanobacteria in freshwater lakes
<p>Eutrophication and global change have been suggested to promote cyanobacterial blooms. <em>Anabaena, Aphanizomenon and Cylindrospermopsis</em> are heterocystous genera of toxin-producing cyanobacteria. It is yet unclear how eutrophication and climate change will impact heterocystous cyanobacteria. This study investigates the effects of total nitrogen (TN), total phosphorus (TP), TN:TP ratio, temperature, pH and trophic state on the relative abundance of three heterocystous cyanobacteria, using data of 999 lakes obtained from the National Lake Assessment 2012 (NLA) of the U.S. Environmental Protection Agency (EPA). It was demonstrated that elevated TN and TP levels, as well as higher pH levels are related to higher abundance of heterocystous cyanobacteria. <em>Cylindrospermopsis</em> is correlated with TN and temperature, <em>Aphanizomenon</em> is related with TP and negatively correlated to TN:TP. All three heterocysts are correlated with pH. Eutrophication has a higher effect on the relative abundance of heterocystous cyanobacteria than the increased temperatures and increased CO<sub>2</sub> concentrations. Decreasing the concentration of nitrogen and especially phosphorus in lakes may limit the relative abundance of heterocystous cyanobacteria in fresh waters.</p>
Global LAke Surface water Temperature (GLAST): Global lakes are warming slower than surface air temperature due to accelerated evaporation
<p>This repository houses a dataset, known as the Global LAke Surface water Temperature (GLAST), which provides both temporal and spatial details at high resolution for 92,245 lakes worldwide during the period of 1981-2099, with 36% of them situated in Arctic regions. The dataset was established based on four decades (1982-2020) of Landsat satellite images and a physical model (FLake). For a comprehensive overview of the dataset's production methodology, please refer to the paper titled 'Global lakes are warming slower than surface air temperature due to accelerated evaporation' (Tong et al., 2023, Nature Water). Detailed information regarding each data file can be found in the 'readme.docx' file.</p>
Data from: Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats
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Sinking efficiency of cyanobacteria-derived particulate organic carbon from one eutrophic lake and global perspectives on carbon burial flux in subtropical shallow lakes
<p>It is the data that support the findings entitled "Sinking efficiency of cyanobacteria-derived particulate organic carbon from one eutrophic lake and global perspectives on carbon burial flux in subtropical shallow lakes” </p>
Mapping global lake dynamics reveals the emerging roles of small lakes: code and data
<p>This repository contains the relevant code and data for the paper <strong>Mapping global lake dynamics reveals the emerging roles of small lakes (</strong><a href="http://dx.doi.org/10.1038/s41467-022-33239-3">https://www.nature.com/articles/s41467-022-33239-3</a><strong>)</strong>.</p> <p>Specifically, the <strong>U-Net.zip</strong> file includes the associated codes for segmenting global lakes by using the U-Net model, and the labels used in this process. The <strong>GLAKES.zip</strong> file includes the GLAKES lake polygon product (.gdb & .shp) and the corresponding water probability-weighted area of GLAKES lakes during the three periods (1984-1999, 2000-2009, 2010-2019). Please refer to the README file in both the <strong>U-Net.zip</strong> and the <strong>GLAKES.zip </strong>file for more detailed information.</p>
Global lake surface water temperature layers
<p>In modeling species distributions and population dynamics, spatially-interpolated climatic data are often used as proxies for real, on-the-ground measurements. In shallow freshwater systems, this practice may be problematic as interpolations used for surface waters are generated from terrestrial sensor networks measuring air temperatures. Using these may therefore bias statistical estimates of species' environmental tolerances or population projections -- particularly among pleustonic and epilimnetic organisms. I used a global database of satellite-derived lake surface water temperatures (LSWT) to assess and correct for the statistical correspondence between air and LSWT as a function of atmospheric and topographic predictors, resulting in the creation of monthly high-resolution global maps of air-LSWT offsets, corresponding uncertainty measures, and derived LSWT-based bioclimatic layers for use by the scientific community.</p>
Global lake surface water temperature layers
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Data from: Suitability of Laurentian Great Lakes for invasive species based on global species distribution models and local habitat
Efficient management and prevention of species invasions requires accurate prediction of where species of concern can arrive and persist. Species distribution models provide one way to identify potentially suitable habitat by developing the relationship between climate variables and species occurrence data. However, these models when applied to freshwater invasions are complicated by two factors. The first is that the range expansions that typically occur as part of the invasion process violate standard species distribution model assumptions of data stationarity. Second, predicting potential range of freshwater aquatic species is complicated by the reliance on terrestrial climate measurements to develop occurrence relationships for species that occur in aquatic environments. To overcome these obstacles, we combined a recently developed algorithm for species distribution modeling—range bagging—with newly available aquatic habitat-specific information from the North American Great Lakes region to predict suitable habitat for three potential invasive species: golden mussel, killer shrimp, and northern snakehead. Range bagging may more accurately predict relative suitability than other methods because it focuses on the limits of the species environmental tolerances rather than central tendency or "typical" cases. Overlaying the species distribution model output with aquatic habitat-specific data then allowed for more specific predictions of areas with high suitability. Our results indicate there is suitable habitat for northern snakehead in the Great Lakes, particularly shallow coastal habitats in the lower four Great Lakes where literature suggests they will favor areas of wetland and submerged aquatic vegetation. These coastal areas also offer the highest suitability for golden mussel, but our models suggest they are marginal habitats. Globally, the Great Lakes provide the closest match to the currently invaded range of killer shrimp, but they appear to pose an intermediate risk to the region. Range bagging provided reliable predictions when assessed either by a standard test set or by tests for spatial transferability, with golden mussel being the most difficult to accurately predict. Our approach illustrates the strength of combining multiple sources of data, while reiterating the need for increased measurement of freshwater habitat at high spatial resolutions to improve the ability to predict potential invasive species.
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>
A dataset of global lake-level simulations and reconstructions since the Last Glacial Maximum
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Global acceleration of lake sediment accumulation rates associated with recent human population growth and landuse changes
<p>These datasets include the spatial coordinates and the digitized temporal rates of lake sedimentation expressed as Sediment Accumulation Rates (SAR; mm/year) and Mass Accumulation Rate (MAR; g/cm<sup>2</sup>/year) presented in Baud et al. (2021).</p> <p>Baud, A., Jenny, JP., Francus, P. and Gregory-Eaves, I. Global acceleration of lake sediment accumulation rates associated with recent human population growth and land-use changes. <em>J Paleolimnol</em> (2021). https://doi.org/10.1007/s10933-021-00217-6 </p>
Primary detection records for aquatic nonindigenous species in global estuarine and marine ecosystems and the Great Lakes
<p><strong>Aim</strong></p> <p>The introduction of aquatic non-indigenous species (ANS) has become a major driver for global changes in species biogeography. We examined spatial patterns and temporal trends of ANS detections since 1965 to inform conservation policy and management. </p> <p><strong>Location</strong></p> <p>Global</p> <p><strong>Methods</strong></p> <p>We assembled an extensive dataset of first records of detection of ANS (1965-2015) across 49 aquatic ecosystems, including the i) year of first collection, ii) population status and iii) potential pathway(s) of introduction. Data were analysed at global and regional levels to assess patterns of detection rate, richness, and transport pathways. </p> <p><strong>Results</strong></p> <p>An annual mean of 43 (± 16 S.D.) primary detections of ANS occurred – one new detection every 8.4 days for 50 years. The global rate of detections was relatively stable during 1965-1995, but increased rapidly after this time, peaking at roughly 66 primary detections per year during 2005-2010, then declining marginally. Detection rates were variable within and across regions through time. Arthropods, molluscs and fishes were the most frequently reported ANS. Most ANS were likely introduced as stowaways in ships' ballast water or biofouling, although direct evidence is typically absent. </p> <p><strong>Main conclusions</strong></p> <p>This synthesis highlights the magnitude of recent ANS detections, yet almost certainly represents an underestimate as many ANS go unreported due to limited search effort and diminishing taxonomic expertise. Temporal rates of detection are also confounded by reporting lags, likely contributing to the lower detection rate observed in recent years. There is a critical need to implement standardized, repeated methods across regions and taxa to improve the quality of global-scale comparisons and sustain core measures over longer timescales. It will be fundamental to fill in knowledge gaps given that invasion data representing broad regions of the world's oceans are not yet readily available and to maintain knowledge pipelines for adaptive management. </p>
Data from: Suitability of Laurentian Great Lakes for invasive species based on global species distribution models and local habitat
Open the record for dataset details and reuse information.
Primary detection records for aquatic nonindigenous species in global estuarine and marine ecosystems and the Great Lakes
Open the record for dataset details and reuse information.
Pre SWOT Hydrology Global Lake/Reservoir Storage Time Series V2
The Global Lake/Reservoir Storage Time Series is derived from the Surface Water Height Time Series and Surface Water Extent Mask Time Series products. The purpose of this dataset is to provide surface water storage estimates for several hundred lakes and reservoirs across the globe. These time series potentially span a 25 year time period, from late 1992 to 2017, satisfying the project goal of ESDR creation with a suitable level of quality that supports long-term trend analysis and global water dynamics models. This product is readily accessible and is of direct use to both water managers and the scientific community worldwide, and allows for improved assessment and modeling of the human impact on the global water cycle. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.
Global-Gridded Daily Methane Emissions Climatology from Lake Systems, 2003-2015
This dataset provides global gridded information on lake surface area and open water CH4 emissions at a resolution of 0.25-degree x 0.25-degree for an annual climatology representative of the average conditions from 2003 to 2015. A compilation of flux data from 575 individual lake systems and 893 aggregated flux values were used, and each flux measurement was classified into one of seven ecoclimatic types. Ice-cover-regulated emission seasonality was derived from satellite microwave observations of ice cover phenology and freeze-thaw dynamics. Global lake area was determined from the merger of HydroLAKES and Climate Change Initiative Inland-Water (CCI-IW) remote-sensing data, and lakes were classified into ecoclimatic regions to facilitate linking these types with ecosystem-specific CH4 measurements in the flux compilation. Exploratory estimates of fluxes associated with ice melt and with spring and fall water-column turnover are also included. The data are provided in NetCDF format.
Pre SWOT Hydrology Global Lake/Reservoir Surface Inland Water Height GREALM V.2
The Global Lake/Reservoir Surface Inland Water Height Time Series is derived from the G-REALM10 lake level product https://ipad.fas.usda.gov/cropexplorer/global_reservoir/ The purpose of this dataset is to provide surface water dynamics for several hundred lakes and reservoirs across the globe. These time series potentially span a 25 year time period, from late 1992 to 2017, satisfying the project goal of ESDR creation with a suitable level of quality that supports long-term trend analysis and global water dynamics models. Water level variation is also a key component required for the determination of surface water storages and fluxes. This product is readily accessible and is of direct use to both water managers and the scientific community worldwide, and allows for improved assessment and modeling of the human impact on the global water cycle. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.