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opencc-by-4.0Mar 2022View details →

Assessment of future wind speed and wind power changes over South Greenland using the MAR regional climate model : MAR ouptuts and KATABATA weather stations timeseries

Daliy MARv3.12 outputs and KATABATA weather stations timeseries used in : Lambin, C., Fettweis, X., Kittel, C., Fonder, M., & Ernst, D. (2022).Assessment of future wind speed and wind power changes over South Greenland using the Modèle Atmosphérique Régional regional climate model. International Journal of Climatology, 43(1),558–574. https://doi.org/10.1002/joc.7795574

opencc-by-4.0Jan 2021View details →

Fig. 2 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance

Fig. 2. Linear relationship (solid line) and 95 % confidence interval (gray area) between habitat quality predicted by the BART model (x-axis) and shell height (H in millimeters, y-axis), derived from the linear mixed model.

opencc-by-4.0Dec 2021View details →

Fig. 4. Partial dependence plot for topographic Fig. 5 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance

Fig. 4. Partial dependence plot for topographic Fig. 5. Partial dependence plot for terrain roughness wetness index (TWI). index (tri).

opencc-by-4.0Jan 2021View details →

Fig. 6 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance

Fig. 6. Partial dependence plot for pH water (phh2o). Fig. 7. Partial dependence plot for silt content (SLT).

opencc-by-4.0Aug 2021View details →

Biogeomorphic modeling to assess the resilience of tidal-marsh restoration to sea level rise and sediment supply - Supporting code and data

Code and data to reproduce figures and analyses of the paper: Gourgue, O., van Belzen, J., Schwarz, C., Vandenbruwaene, W., Vanlede, J., Belliard, J.-P., Fagherazzi, S., Bouma, T.J., van de Koppel, J., and Temmerman, S.: Biogeomorphic modeling to assess resilience of tidal marsh restoration to sea level rise and sediment supply, Earth Surf. Dynam., submitted. Standard Python dependencies: <ul> <li>GDAL</li> <li>Geopandas</li> <li>Matplotlib</li> <li>NumPy</li> <li>Rasterio</li> <li>SciPy</li> <li>Seaborn</li> <li>Shapely</li> <li>scikit-learn</li> </ul> Third-party Python dependencies: <ul> <li>Centerline (https://github.com/fitodic/centerline)</li> <li>pputils (https://github.com/pprodano/pputils)</li> <li>pysheds (https://github.com/mdbartos/pysheds)</li> </ul> In-house Python dependencies: <ul> <li>Demeter 1.0.5 (https://doi.org/10.5281/zenodo.5205258)</li> <li>OGTools 1.1 (https://doi.org/10.5281/zenodo.3994952)</li> <li>TidalGeoPro 0.1 (https://doi.org/10.5281/zenodo.5205285)</li> </ul>

opencc-by-4.0Jan 2021View details →

Fig. 3. Partial dependence plot for BIO17 in Associations Between Habitat Quality And Body Size In The Carpathian-Podolian Land Snail Vestia Turgida: Species Distribution Model Selection And Assessment Of Performance

Fig. 3. Partial dependence plot for BIO17 = Precipitation of Driest Quarter; gray area = 95 % confidence interval.

opencc-by-4.0Apr 2022View details →

Lightning Assimilation in the Weather Research and Forecasting (WRF) Model: Technique Updates and Assessment of the Applications from Regional to Hemispheric Scales

Figure 1. The data is proprietary, but it can be purchased from Vaisala Inc. (https:// <a href="http://www.vaisala.com/en/products/systems/lightning-detection">www.vaisala.com/en/products/systems/lightning-detection</a>), and the WWLLN raw data are also available for purchase at <a href="http://wwlln.net">http://wwlln.net</a>. Figure 2. Maps, data is not applicable. Figure 3. Data file: NLDN_WWLLN_Prism_Rainfall_Analysis.xlsx Figure 4. Data file: NLDN_WWLLN_METVARS_T2_Jul_2016.xlsx Figure 5. Data file: CONUSall_METOBS_q_Jul_2016.xlsx Figure 6. Data file: CONUSall_METOBS_ws_Jul_2016.xlsx Figure 7. Created using the R script: Hemi_Rain_ModelOnlyWGPM.R based on the R object files: AnnualRainFall_CFC_WRF_Hemi_BASE_*.rds, AnnualRainFall_CFC_WRF_Hemi_LTA_*.rds, and GPM_WRF_Paired_rain2Hemispheric_July2016.rds. Figure 8. Created using the R script: Hemi_Rain_Aanlysis.R based on the R object files: AnnualRainFall_CFC_WRF_Hemi_BASE_*.rds and AnnualRainFall_CFC_WRF_Hemi_LTA_*.rds. Figure 9. Data file: CPC_Model_Monthly_Prep_Hemi_Stats.xlsx Figure 10. Data file: CPC_Model_Monthly_Prep_Hemi_Stats.xlsx Figure 11. Data file: CPC_Model_Monthly_Prep_Hemi_Stats.xlsx Figure 12. Created using the R script: CreateCPCdataforUSdomain_vs_Prism.R based on the R oject files: Prism_CFC_WRF*.rds Figure 13. Data file: Hemi_lta_METOBS_T2_Jul_2016.xlsx Figure 14. Data file: Hemi_lta_METOBS_q_Jul_2016.xlsx

opencc-zeroMay 2022View details →

Data from: A hierarchical model for jointly assessing ecological and anthropogenic impacts on animal demography

1. The management of sustainable harvest of animal populations is of great ecological and conservation importance. Development of formal quantitative tools to estimate and mitigate the impacts of harvest on animal populations has positively impacted conservation efforts. 2. The vast majority of existing harvest models, however, do not simultaneously estimate ecological and harvest impacts on demographic parameters and population trends. Given that the impacts of ecological drivers are often equal to or greater than the effects of harvest, and can covary with harvest, this disconnect has the potential to lead to flawed inference. 3. In this study, we used Bayesian hierarchical models and a 43-year capture-mark-recovery dataset from 404,241 female mallards (Anas platyrhynchos) released in the North American midcontinent to estimate mallard demographic parameters. Further, we model the dynamics of waterfowl hunters and habitat, and the direct and indirect effects of anthropogenic and ecological processes on mallard demographic parameters. 4. We demonstrate that density-dependence, habitat conditions, and harvest can simultaneously impact demographic parameters of female mallards, and discuss implications for existing and future harvest management models. 5. Our results demonstrate the importance of controlling for multicollinearity among demographic drivers in harvest management models, and provide evidence for multiple mechanisms that lead to partial compensation of mallard harvest. We provide a novel model structure to assess these relationships that may allow for improved inference and prediction in future iterations of harvest management models across taxa.

opencc-by-4.0May 2022View details →

SMDRM Model for Impact Assessment

This model is the result of the training of a Convolutional Neural Network. Training datasets were tweets collected during historical floods in Sao Paulo (PT,EN) and Barcelona (ES,EN).

opencc-zeroAug 2022View details →

Population models used in: Method to assess potential magnitude of terrestrial European avian population reductions from ingestion of lead ammunition

Current estimates of terrestrial bird losses across Europe from ingestion of lead ammunition are based on uncertain or generic assumptions. A method is needed to develop defensible European-specific estimates compatible with available data that does not require long-term field studies. We propose a 2-step method using carcass data and population models. The method estimates percentage of deaths diagnosed as directly caused by lead poisoning as a lower bound and, as an upper bound, the percentage of possible deaths from sublethal lead poisoning that weakens birds, making them susceptible to death by other causes. We use these estimates to modify known population-level annual mortality. Our method also allows for potential reductions in reproduction from lead shot ingestion because reductions in survival and reproduction are entered into population models of species with life histories representative of the most groups of susceptible species. The models estimate the sustainability and potential population decreases from lead poisoning in Europe. Using the best available data, we demonstrate the method on two taxonomic groups of birds: gallinaceous birds and diurnal raptors. The direction of the population trends affects the estimate, and we incorporated such trends into the method. Our midpoint estimates of the reduction in population size of the European gallinaceous bird (< 2%) group and raptor group (2.9 – 7.7%) depend on the species life history, maximum growth rate, population trend, and if reproduction is assumed to be reduced. Our estimates can be refined as more information becomes available in countries with data gaps. We advocate use of this method to improve upon or supplement approaches currently being used. As we demonstrate, the method also can be applied to individual species of concern if enough data across countries are available.

opencc-by-4.0Nov 2022View details →

On the Application of Machine Learning Models to Assess and Predict Software Reusability

This is the dataset, results and notebook for the submission into Maltesque 2022 conference.

Fig. 6 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria

Fig. 6. Abundance (mean number of burrows/100 × 5 m transect) of S. citellus in 4 colonies in the study area in summer (for the period 2017–2021) N = Luda Yana; –– l –– = Belotrup; ---- l ---- = Panagyurski kolonii; u = Beli Manastiri

Fig. 5 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria

Fig. 5. Changes in the habitat suitability in the study area (white – not suitable, black – high suitability) of European souslik assessed by maxent modelling based on data from 2006–2018 (B) and extrapolated for the period 1985–2005 (A). The results are presented in

Fig. 3 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria

Fig. 3. Negative and positive anomalies (white and black bars) of the Mean Annual Temperature time series for the period of 1985–2018 (data from the meteorological station Sofia)

Fig. 2 in Long Term (1985-2018) Changes Of The Habitat Suitability Of European Souslik Assessed By Maxent Modelling Based On Landsat Satellite Imagery - A Case Study From A Mountain Landscape Of Central Bulgaria

Fig. 2. Changes in the number of grazing livestock in the southern central Bulgarian planning region for the period 2001–2018

opencc-zeroOct 2022View details →

Assessing predictive performance of supervised machine learning algorithms for a diamond pricing model

The diamond is 58 times harder than any other mineral in the world, and its elegance as a jewel has long been appreciated. Forecasting diamond prices is challenging due to nonlinearity in important features such as carat, cut, clarity, table, and depth. Against this backdrop, the study conducted a comparative analysis of the performance of multiple supervised machine learning models (regressors and classifiers) in predicting diamond prices. Eight supervised machine learning algorithms were evaluated in this work including Multiple Linear Regression, Linear Discriminant Analysis, eXtreme Gradient Boosting, Random Forest, k-Nearest Neighbors, Support Vector Machines, Boosted Regression and Classification Trees, and Multi-Layer Perceptron. The analysis is based on data preprocessing, exploratory data analysis (EDA), training the aforementioned models, assessing their accuracy, and interpreting their results. Based on the performance metrics values and analysis, it was discovered that eXtreme Gradient Boosting was the most optimal algorithm in both classification and regression, with a R2 score of 97.45% and an Accuracy value of 74.28%. As a result, eXtreme Gradient Boosting was recommended as the optimal regressor and classifier for forecasting the price of a diamond specimen.

opencc-zeroJun 2024View details →

Data from: In vitro to in vivo extrapolation from three-dimensional hiPSC-derived cardiac microtissues and physiologically based pharmacokinetic modeling to inform next-generation arrythmia risk assessment

Proarrhythmic cardiotoxicity remains a substantial barrier to drug development as well as a major global health challenge. In vitro human pluripotent stem cell-based new approach methodologies have been increasingly proposed and employed as alternatives to existing in vitro and in vivo models that do not accurately recapitulate human cardiac electrophysiology or cardiotoxicity risk. In this study, we expanded the capacity of our previously established three-dimensional human cardiac microtissue model to perform quantitative risk assessment by combining it with a physiologically based pharmacokinetic model, allowing a direct comparison of potentially harmful concentrations predicted in vitro to in vivo therapeutic levels. This approach enabled the measurement of concentration responses and margins of exposure for two physiologically relevant metrics of proarrhythmic risk (i.e., action potential duration and triangulation assessed by optical mapping) across concentrations spanning three orders of magnitude. The combination of both metrics enabled accurate proarrhythmic risk assessment of four compounds with a range of known proarrhythmic risk profiles (i.e., quinidine, cisapride, ranolazine, and verapamil) and demonstrated close agreement with their known clinical effects. Action potential triangulation was found to be a more sensitive metric for predicting proarrhythmic risk associated with the primary mechanism of concern for pharmaceutical-induced fatal ventricular arrhythmias, delayed cardiac repolarization due to inhibition of the rapid delayed rectifier potassium channel, or hERG channel. This study advances human induced pluripotent stem cell-based three-dimensional cardiac tissue models as new approach methodologies that enable in vitro proarrhythmic risk assessment with high precision of quantitative metrics for understanding clinically relevant cardiotoxicity.

opencc-by-4.0Nov 2024View details →

Figure 5 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics

Figure 5. Overall zebra mussel establishment risk categorization of 133 Texas water bodies based on calcium, pH, salinity, and temperature. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent. The Whittier et. al. low calcium/low risk zone delineation is shown to demonstrate level of agreement with that study, which is relatively high with some noteworthy exceptions. The Cypress, Sabine, and Neches River basins referenced in the text are the three East Texas basins with predominantly minimal risk water body categorizations.

opencc-by-4.0Nov 2024View details →

Figure 2 in A simplistic water body-specific risk assessment model for zebra mussel (Dreissena polymorpha) establishment based on physicochemical characteristics

Figure 2. pH-based zebra mussel establishment risk categorization of 133 Texas water bodies. Major water bodies not included in this study due to lack of TCEQ water quality data are shown for context of the study extent.