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20 results for “isoscape”
Modelled isoscape data for: "Oceanographic and biogeochemical drivers cause divergent trends in the nitrogen isoscape in a changing Arctic Ocean"
<p>The data included in this repository includes the biogeochemical model output of nitrogen isotope fields. These data were generated by simulations with the NEMOv4.0 Ocean General Circulation Model, SI3 sea ice model, and Pelagic Interactions Scheme for Carbon and Ecosystem Studies version 2 (PISCESv2) biogeochemical model. Nitrogen isotopes were integrated within PISCESv2 for the purpoes of this study.</p> <p>All data here are in longitude, latitude and time cordinates. No depth coordinate is provided as all values are averaged over the upper 100 metres of the model.</p> <p> </p> <p>The file names mean the following:<br> </p> <p>ETOPO - refers to how the curvilinear, native grid of the model was re-gridded to a regular 360x180 longitude-latitude grid uisng the etopo60 coordinate system.</p> <p>JRA55 - these are the reanalysis-driven simulations, for which we used the Japanese Atmospheric Reanalysis (JRA55do).</p> <p>future - these are the emissions-driven simulations (historical from 1850-2005, then according to Representative Concentration Pathway 8.5 from 2006-2100.)</p> <p>picontrol - these are parallel to the emissions-driven simulations but do not include the increase in emissions.</p> <p>ndep - refers to if the historical increase in anthropogenic nitrogen deposition was included in the simulation</p> <p>d15Nno3 - isotopic composition of nitrate averaged over the upper 100 metres</p> <p>d15Npom - isotopic composition of particulate organic matter averaged over the upper 100 metres</p> <p>predictors - the average values of salinity, N* and particulate organic matter over the upper 100 metres</p> <p>annualave - annual averages, so that the data are inter-annual</p> <p>1970-1990ave_months - average monthy values over the period 1970-1990.</p>
Precipitation oxygen isoscape for mainland China from 1870 to 2017 generated based on data fusion and bias correction of iGCMs simulations
<p>The dataset includes the stable oxygen isotope of precipitation for the mainland of China over the 1870-2017 period, at a spatial resolution of 50-60 km and a monthly temporal resolution. In order to make full use of observations to integrate the advantages of various iGCMs, the combination of data fusion and bias correction methods are used. Some physical-based ancillary data are introduced in the fusion methods, including elevation and meteorological data, to enrich the climate and terrain information in the process of data fusion. Specifically,</p><p>(1) for the 1979-2001 period, nine simulations from six iGCMs (CAM2, GISS E, HadAM3, IsoGSM2, LMDZ4, and MIROC32) and ancillary data are fused with observations by using the CNN fusion method;</p><p>(2) for the 2002-2007 period, seven simulations from four iGCMs (GISS E, IsoGSM2, LMDZ4, and MIROC32) and ancillary data are fused by using the CNN fusion method;</p><p>(3) for the 1969-1978 period, four simulations from three iGCMs (CAM2, GISS E, and HadAM3) and ancillary data are fused by using the CNN fusion method;</p><p>(4) for the 1958-1968 and 2008-2017 periods, two iGCM simulations (CAM2 and HadAM3 for 1958-1968 and IsoGSM2 and LMDZ4 zoomed for 2008-2017) are corrected by using two BCMs, and ensemble mean (mean of four simulations) is then calculated;</p><p>(5) for the 1870-1957 period, one iGCM simulation (HadAM3) is corrected by using two BCMs, and the ensemble mean (mean of two simulations) is then calculated.</p><p>Compared with the existing iGCMs, the isoscape has high quality and stability for a large region in China at the monthly scale. However, it should be noted that the isoscape may be more reliable for the common periods of most iGCMs (1969-2007), but mediocre for other periods. </p>
Precipitation hydrogen isoscape for East China from 1969 to 2017 generated based on data fusion of iGCMs simulations
<p>The dataset includes the stable hydrogen isotope of precipitation for East China over the 1969-2017 period, at a spatial resolution of 50-60 km and a monthly temporal resolution. This dataset was built based on the Convolutional Neural Network (CNN) method, fusing observations and isotope-equipped general circulation models (iGCMs) simulations of hydrogen isotope composition. Some physical-based ancillary data are also introduced in the fusion methods, including elevation and meteorological data, to enrich the climate and terrain information in the process of data fusion.</p>
Use of historical isoscapes to develop an estuarine nutrient baseline
<p class="MsoNormal"><span>Coastal eutrophication is a prevalent threat to the healthy functioning of ecosystems globally. While degraded water quality can be detected by monitoring oxygen, nutrient concentrations, and algal abundance, establishing regulatory guidelines is complicated by a lack of baseline data (e.g., pre-Anthropocene). We use historical carbon and nitrogen isoscapes from sediment cores to reconstruct spatial and temporal changes in nutrient dynamics for a central California estuary, where development and agriculture dramatically enhanced nutrient inputs over the past century. We found strong contrasts between current sediment stable isotopes and those from the recent past, demonstrating </span>shifts exceeding those in previously studied eutrophic estuaries and <span>substantial increases in nutrient inputs. Comparisons of contemporary with historical isoscapes also revealed that nitrogen sources shifted from a marine-terrestrial gradient to amplified denitrification at the head and mouth of the estuary. Geospatial analysis of historical data suggests that an increase in fertilizer application – rather than population growth or increases in the extent of cultivated land – is chiefly responsible for increasing nutrient loads during the 20<sup>th</sup> century. This study demonstrates the ability of isotopic and stoichiometric maps to provide important perspectives on long-term shifts and spatial patterns of nutrients that can be used to improve management of nutrient pollution.</span></p>
UVic2.9-MOBI2.0+Fe-15N_13C Isoscapes Hindcast
<p>The simulations provided here are based on the model version including a dynamic, prognostic iron cycle (Somes et al. 2021), and they use the previous formulations for nitrogen and carbon isotopes (Somes et al. 2017; Schmittner et al., 2013). The model code and simulation description can be found at <a href="https://hdl.handle.net/20.500.12085/9e490d1e-4873-4eec-905b-1c470f79b01b">https://hdl.handle.net/20.500.12085/9e490d1e-4873-4eec-905b-1c470f79b01b</a>. Here we provide euphotic zone results from the North Atlantic corresponding with the associated squid data locations.</p>
Use of historical isoscapes to develop an estuarine nutrient baseline
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Data for: Bivalve δ15N isoscapes provide a baseline for urban nitrogen footprint at the edge of a World Heritage coral reef
<p>This dataframe presents the d<sup>15</sup>N signature of 348 long-lived benthic bivalves from 12 species. Individuals were trapped at 27 sites in 2012 around the Peninsula of Nouméa, New Caledonia. For each bivalve specimen, muscle tissues were dissected and stored frozen. Muscles were freeze-dried, ground into powder, and weighed in tin cups for isotopic analysis (about 1mg in 4 × 6 mm tin cups). Muscle samples were analyzed using a Thermo Delta Advantage mass spectrometer in continuous flow mode connected to a Costech Elemental Analyzer via a ConFlo IV at Union College (Schenectady, NY, USA). Ammonium sulfate [IAEA-N-2], caffeine [IAEA-600], and an in-house acetanilide were used as standards; measurements of δ<sup>15</sup>N are reported to atmospheric nitrogen. The uncertainty for δ<sup>15</sup>N measurements was ±0.15‰ based on repeated analysis of an in-house acetanilide standard.</p> <p>The data base is made of 348 raws corresponding to specimens, and 5 columns presenting an ID, the collection site, the position within the laggon , the species and the measured D15N value. </p>
Southern Sardinia Sr isoscape
<p>Sr isotope spatial distribution in southern Sardinia and the relative spatial uncertainty. The maps were obtained through a Random Forest model as described in Bataille et al., 2020.</p>
Data from: Assigning harvested waterfowl to geographic origin using feather δ2H isoscapes: What is the best analytical approach?
<p class="MsoListParagraph">Establishing links between breeding, stopover, and wintering sites for migratory species is important for their effective conservation and management. Isotopic assignment methods used to create these connections rely on the use of predictable, established relationships between the isotopic composition of environmental hydrogen and that of the non-exchangeable hydrogen in animal tissues, often in the form of a calibration equation relating feather (<em>δ</em><sup>2</sup>H<sub>f</sub>) values derived from known-origin individuals and amount-weighted long-term precipitation (<em>δ</em><sup>2</sup>H<sub>p</sub>) data. The efficacy of assigning waterfowl to moult origin using stable isotopes depends on the accuracy of these relationships and their statistical uncertainty. Most current calibrations for terrestrial species in North America are done using amount-weighted mean growing-season <em>δ</em><sup>2</sup>H<sub>p</sub> values, but the calibration relationship is less clear for aquatic and semi-aquatic species. Our objective was to critically evaluate current methods used to calibrate <em>δ</em><sup>2</sup>H<sub>p</sub> isoscapes to predicted <em>δ</em><sup>2</sup>H<sub>f</sub> values for waterfowl. Specifically, we evaluated the strength of the relationships between <em>δ</em><sup>2</sup>H<sub>p</sub> values from three commonly used isoscapes and known-origin <em>δ</em><sup>2</sup>H<sub>f</sub> values from three published and one collected as part of this study, also grouping these data into foraging guilds (dabbling vs diving ducks). </p>
Data from: Assigning harvested waterfowl to geographic origin using feather δ2H isoscapes: What is the best analytical approach?
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An ensemble machine learning bioavailable strontium isoscape for Eastern Canada
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Data from: Defining isoscapes in the Northeast Pacific as an index of ocean productivity
<p><b>Aim: </b>We modeled isoscapes in the Northeast Pacific using satellite-based data with the main objective of testing if isoscapes defined by a few key parameters can be used as a proxy for secondary productivity.</p> <p><b>Location: </b>Northeast (NE) Pacific; 46 – 60⁰N and 125 – 165⁰W.</p> <p><b>Time period: </b>From 1998 to 2017 (ongoing).</p> <p><b>Major taxa studied: </b>Zooplankton with a focus on large herbivores.</p> <p><b>Methods:</b> Approximately 280 summer zooplankton samples were analyzed for Carbon (δ<sup>13</sup>C) and Nitrogen (δ<sup>15</sup>N) stable isotope (SI) ratios. Environmental conditions experienced by zooplankton organisms were extracted from satellite, in situ sensor and model databases. A generalized additive model approach was used to explain the spatial variability of δ<sup>13</sup>C and δ<sup>15</sup>N values and predict isoscapes.</p> <p><b>Results: </b>Sea surface temperature (SST), sea level anomaly (SLA) and chlorophyll-<i>a</i> concentration emerged as the significant SI predictors. Modelled isoscapes reproduced patterns observed in δ<sup>13</sup>C and δ<sup>15</sup>N value distribution, such as a decrease from the coast to offshore. The contribution of eddies in enhancing local production in the open ocean was also well captured by the models. In the central part of the NE Pacific higher SI values were correlated with higher large copepod biomass measured by the North Pacific Continuous Plankton Recorder (CPR) survey. However, in the area off the coast of British Columbia (BC) high δ<sup>15</sup>N variability appeared to be associated with episodic intrusions of coastal waters demonstrating that caution is needed when interpreting sharp changes in SI ratios.</p> <p><b>Main conclusions: </b>While the mechanisms driving SI ratio variability are complex, we demonstrated that a few parameters used as a proxy for some of these major mechanisms are able to successfully produce isoscape models. This approach was proven useful to provide a qualitative estimate of the secondary production, which can be particularly valuable in a region where few data are available.</p>
Data from: Oxygen and carbon isoscapes for the Baltic Sea: testing their applicability in fish migration studies
Conventional tags applied to individuals have been used to investigate animal movement, but these methods require tagged individuals be recaptured. Maps of regional isotopic variability known as "isoscapes" offer potential for various applications in migration research without tagging wherein isotope values of tissues are compared to environmental isotope values. In this study, we present the spatial variability in oxygen (math formula) and dissolved inorganic carbon (δ13CDIC) isotope values of Baltic Sea water. We also provide an example of how these isoscapes can reveal locations of individual animal via spatial probability surface maps, using the high-resolution salmon otolith isotope data from salmon during their sea-feeding phase in the Baltic Sea. A clear latitudinal and vertical gradient was found for both math formula and δ13CDIC values. The difference between summer and winter in the Baltic Sea math formula values was only slight, whereas δ13CDIC values exhibited substantial seasonal variability related to algal productivity. Salmon otolith δ18Ooto and δ13Coto values showed clear differences between feeding areas and seasons. Our example demonstrates that dual isotope approach offers great potential for estimating probable fish habitats once issues in model parameterization have been resolved.
Data from: The effects of spatial scale and isoscape on consumer isotopic niche width
1. The mean and variance of ecological variables are dependent on sampling attributes such as the coverage of environmental heterogeneity (sampling extent) and spatial scale. Trophic niche width is often approximated by bulk tissue stable isotopes of C and N, i.e. the population isotopic niche. However, recent studies suggest that environmental heterogeneity (experienced by individuals) may be more important in defining the isotopic niche width than trophic variability. We hypothesised that isotopic niche width will increase monotonically with spatial scale, largely produced by environmental variation, e.g. nutrient source. 2. To refine this hypothesis, by describing the shapes of isotope scaling curves, we explored a previously published dataset describing three Chilean intertidal species representing different feeding guilds (grazing snails, suspension feeding mussel). We tested these hypotheses on a new, larger dataset describing three functionally-analogous intertidal species from Northern Ireland. We generated isotopic variance-area curves from a spatially-explicit bootstrap and investigated the scale-dependency of environment-isotope relationships, including wave exposure and sub-habitat heterogeneity. 3. Spatial scale explained 50% of the variance in population isotopic niche widths (bivariate C-N ellipse area) by simple, non-linear relationships. Finer scales (< 1 to 10 km lag) accounted for most variance. Scale dependence was strong for ẟ15N variance, of which > 40% was explained by modelling linear coefficients. A ẟ15N baseline gradient, or isoscape, dominated ẟ15N variance scaling patterns, from sheltered, terrestrially-influenced embayments to exposed, pelagic-dominated coastline. Consumer ẟ13C variance had a weaker scale-dependence, plateauing at mesoscales (> 20 km lag). 4. We show that isotopic niche width is strongly dependent on sampling spatial extent, which controls the environmental heterogeneity experienced by individual consumers. Environmental heterogeneity must be accounted for before isotopic niche width can be considered to accurately represent trophic niche width. Studies conducted at different spatial scales are likely to identify different environment-isotope relationships. 5. We recommend that spatial scale should be incorporated into sampling designs explicitly, easiest by maintaining a consistent lag distance or area within which populations are sampled. Identified isoscapes can be de-trended, where necessary.
Data from: Integrating machine learning with otolith isoscapes: reconstructing connectivity of a marine fish over four decades
<p>Stable isotopes are an important tool to uncover animal migration. Geographic natal assignments often require categorizing the spatial domain through a nominal approach, which can introduce bias given the continuous nature of these tracers. Stable isotopes predicted over a spatial gradient (i.e., isoscapes) allow a probabilistic and continuous assignment of origin across space, although applications to marine organisms remain limited. We present a new framework that integrates nominal and continuous assignment approaches by (1) developing a machine-learning multi-model ensemble classifier using Bayesian model averaging (nominal); and (2) integrating nominal predictions with continuous isoscapes to estimate the probability of origin across the spatial domain (continuous). We applied this integrated framework to predict the geographic origin of the Northwest Atlantic mackerel (<em>Scomber scombrus</em>), a migratory pelagic fish comprised of northern and southern components that have distinct spawning sites off Canada (northern contingent) and the US (southern contingent), and seasonally overlap in US fished regions. The nominal approach based on otolith carbon and oxygen stable isotopes (δ<sup>13</sup>C/δ<sup>18</sup>O) yielded high contingent classification accuracy (84.9%). Contingent assignment of unknown-origin samples revealed prevalent, yet highly varied contingent mixing levels (12.5–83.7%) within the US waters over four decades (1975–2019). Nominal predictions were integrated into mackerel-specific otolith oxygen isoscapes developed independently for Canadian and US waters. The combined approach identified geographic nursery hotspots in known spawning sites, but also detected geographic shifts over multi-decadal time scales. This framework can be applied to other marine species to understand migration and connectivity at high spatial resolution, relevant to management of unit stocks in fisheries and other conservation assessments.</p>
Data from: The effects of spatial scale and isoscape on consumer isotopic niche width
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Data from: Integrating machine learning with otolith isoscapes: reconstructing connectivity of a marine fish over four decades
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Data from: Defining isoscapes in the Northeast Pacific as an index of ocean productivity
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Data from: Oxygen and carbon isoscapes for the Baltic Sea: testing their applicability in fish migration studies
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Reproducing surface water isoscapes of δ18O and δ2H across China: A machine learning approach
<p>This dataset support this submission.</p>
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