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Random forests as a tool for ecohydrological distribution modelling
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/9781118445112.stat03141openalex-snapshot
Generalized Additive Models
inferredcites →https://doi.org/10.1007/bf00055300openalex-snapshot
The decimal scale for releves of permanent quadrats
inferredcites →https://doi.org/10.1007/bf00162742openalex-snapshot
Historical influence of man on the riparian dynamics of a fluvial landscape
inferredcites →https://doi.org/10.1016/0006-3207(95)00119-0openalex-snapshot
Impact of hydrological changes on nature conservation areas in The Netherlands
inferredcites →https://doi.org/10.1016/0022-1694(92)90108-8openalex-snapshot
Regional changes in groundwater flow patterns and effects on groundwater composition
inferredcites →https://doi.org/10.1016/j.ecolmodel.2005.03.026openalex-snapshot
Maximum entropy modeling of species geographic distributions
inferredcites →https://doi.org/10.1016/j.ecolmodel.2005.09.007openalex-snapshot
Modelling establishment probabilities of an exotic plant, Rhododendron ponticum, invading a heterogeneous, woodland landscape using logistic regression with spatial autocorrelation
inferredcites →https://doi.org/10.1016/j.ecolmodel.2006.05.016openalex-snapshot
Effects of sample survey design on the accuracy of classification tree models in species distribution models
inferredcites →https://doi.org/10.1016/j.patrec.2005.08.011openalex-snapshot
Random Forests for land cover classification
inferredcites →https://doi.org/10.1016/s0167-8809(01)00187-6openalex-snapshot
Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA
inferredcites →https://doi.org/10.1016/s0304-3800(00)00354-9openalex-snapshot
Predictive habitat distribution models in ecology
inferredcites →https://doi.org/10.1016/s0304-3800(01)00316-7openalex-snapshot
Applications of machine learning to ecological modelling
inferredcites →https://doi.org/10.1016/s0304-3800(02)00200-4openalex-snapshot
Evaluating resource selection functions
inferredcites →https://doi.org/10.1016/s0304-3800(02)00205-3openalex-snapshot
Spatial prediction of species distribution: an interface between ecological theory and statistical modelling
inferredcites →https://doi.org/10.1016/s0304-3800(97)00062-8openalex-snapshot
A comparison of six models predicting vegetation response to hydrological habitat change
inferredcites →https://doi.org/10.1016/s0304-3800(98)00053-2openalex-snapshot
Comparison of the performance of species response models in several landscape units in the province of Noord-Holland, The Netherlands
inferredcites →https://doi.org/10.1016/s0921-8009(00)00165-8openalex-snapshot
The value of wetlands: importance of scale and landscape setting
inferredcites →https://doi.org/10.1017/s0376892997000088openalex-snapshot
A review of methods for the assessment of prediction errors in conservation presence/absence models
inferredcites →https://doi.org/10.1023/a:1008985925162openalex-snapshot
Regression and model-building in conservation biology, biogeography and ecology: The distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ models
inferredcites →https://doi.org/10.1023/a:1021346712677openalex-snapshot
Prediction of plant species distribution in lowland river valleys in Belgium: modelling species response to site conditions
inferredcites →https://doi.org/10.1029/1999wr900210openalex-snapshot
Ecohydrology: A hydrologic perspective of climate‐soil‐vegetation dynamies
inferredcites →https://doi.org/10.1046/j.1365-2664.2001.00653.xopenalex-snapshot
Exploring spatial vegetation dynamics using logistic regression and a multinomial logit model
inferredcites →https://doi.org/10.1046/j.1365-2745.2000.05262.xopenalex-snapshot
Eco‐hydrology: Plants and Water in Terrestrial and Aquatic Environments
inferredcites →https://doi.org/10.1080/00401706.1993.10485333openalex-snapshot
The Analysis of Contingency Tables
inferredcites →https://doi.org/10.1080/00401706.1997.10485141openalex-snapshot
Applied Linear Statistical Models
inferredcites →https://doi.org/10.1080/00949650410001729472openalex-snapshot
An empirical comparison of ensemble methods based on classification trees
inferredcites →https://doi.org/10.1080/01431160412331269698openalex-snapshot
Random forest classifier for remote sensing classification
inferredcites →https://doi.org/10.1093/bioinformatics/bti721openalex-snapshot
Prediction of protein–protein interactions using random decision forest framework
inferredcites →https://doi.org/10.1109/tac.1974.1100705openalex-snapshot
A new look at the statistical model identification
inferredcites →https://doi.org/10.1109/tgrs.2004.842481openalex-snapshot
Investigation of the random forest framework for classification of hyperspectral data
inferredcites →https://doi.org/10.1111/j.0021-8901.2004.00881.xopenalex-snapshot
An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo‐absence data
inferredcites →https://doi.org/10.1111/j.0021-8901.2004.00903.xopenalex-snapshot
New paradigms for modelling species distributions?
inferredcites →https://doi.org/10.1111/j.0906-7590.2005.03957.xopenalex-snapshot
Selecting thresholds of occurrence in the prediction of species distributions
inferredcites →https://doi.org/10.1111/j.1365-2664.2005.01052.xopenalex-snapshot
The continuing challenges of testing species distribution models
inferredcites →https://doi.org/10.1111/j.1365-2699.2004.01076.xopenalex-snapshot
An evaluation of methods for modelling species distributions
inferredcites →https://doi.org/10.1111/j.1461-0248.2005.00792.xopenalex-snapshot
Predicting species distribution: offering more than simple habitat models
inferredcites →https://doi.org/10.1162/089976698300017197openalex-snapshot
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
inferredcites →https://doi.org/10.1177/001316446002000104openalex-snapshot
A Coefficient of Agreement for Nominal Scales
inferredcites →https://doi.org/10.1186/1471-2105-7-3openalex-snapshot
Gene selection and classification of microarray data using random forest
inferredcites →https://doi.org/10.2307/1478985openalex-snapshot
Ecohydrological characterization of a groundwater‐fed alluvial floodplain mire
inferredcites →https://doi.org/10.2307/2258931openalex-snapshot
Reciprocal Averaging: An Eigenvector Method of Ordination
inferredcites →https://doi.org/10.2307/2259125openalex-snapshot
Freshwater Wetlands: Ecological Processes and Management Potential.
inferredcites →https://doi.org/10.2307/2484388openalex-snapshot
Freshwater Wetlands. Ecological Processes and Management Potential.
inferredcites →https://doi.org/10.2307/3001968openalex-snapshot
Individual Comparisons by Ranking Methods
inferredcites →https://doi.org/10.2307/3235801openalex-snapshot
Topographic position and water chemistry of fens in a Dutch river plain
inferredcites →https://doi.org/10.2307/3236170openalex-snapshot
Generalized additive models in plant ecology
inferredcites →https://doi.org/10.2307/3237218openalex-snapshot
Determining alternative models for vegetation response analysis: a non‐parametric approach
inferredcites →https://doi.org/10.2307/3237291openalex-snapshot
Predicting the distribution of shrub species in southern California from climate and terrain‐derived variables
inferredcites →https://doi.org/10.4324/9780203980095-12openalex-snapshot
WATER AND PLANTS IN FRESHWATER WETLANDS
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Using water sources extent during inundation as a reliable predictor for vegetation zonation in a natural wetland floodplain
inferred← citeshttps://doi.org/10.1016/j.ecolmodel.2008.12.022openalex-snapshot
Uncertainty propagation in vegetation distribution models based on ensemble classifiers
inferred← citeshttps://doi.org/10.1016/j.ecolmodel.2026.111785openalex-snapshot
Ecological modelling on its 50th anniversary: A citation analysis of the 100 most cited papers
inferred← citeshttps://doi.org/10.1016/j.ejrh.2023.101331openalex-snapshot
Evolutionary and ensemble machine learning predictive models for evaluation of water quality
inferred← citeshttps://doi.org/10.1016/j.engstruct.2019.03.105openalex-snapshot
Prediction of dynamic increase factor for steel fibre reinforced concrete using a hybrid artificial intelligence model
inferred← citeshttps://doi.org/10.1016/j.envc.2021.100421openalex-snapshot
Residual geochemical gold grade prediction using extreme gradient boosting
inferred← citeshttps://doi.org/10.1016/j.envsoft.2010.12.001openalex-snapshot
Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers
inferred← citeshttps://doi.org/10.1016/j.ese.2022.100233openalex-snapshot
Algal community structure prediction by machine learning
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.119050openalex-snapshot
Prediction of pipe failures in water supply networks for longer time periods through multi-label classification
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.128849openalex-snapshot
Enhanced prediction of NBA players’ salaries using hybrid ensemble models and multi-objective optimization techniques based on the 2022–23 season dataset
inferred← citeshttps://doi.org/10.1016/j.geoderma.2011.10.010openalex-snapshot
Uncertainty in the spatial prediction of soil texture
inferred← citeshttps://doi.org/10.1016/j.geoderma.2013.07.031openalex-snapshot
Hyper-scale digital soil mapping and soil formation analysis
inferred← citeshttps://doi.org/10.1016/j.geoderma.2014.04.036openalex-snapshot
Updating soil survey maps using random forest and conditioned Latin hypercube sampling in the loess derived soils of northern Iran
inferred← citeshttps://doi.org/10.1016/j.geoderma.2014.09.019openalex-snapshot
Machine learning for predicting soil classes in three semi-arid landscapes
inferred← citeshttps://doi.org/10.1016/j.geoderma.2016.05.014openalex-snapshot
Legacy soil maps as a covariate in digital soil mapping: A case study from Northern Iran
inferred← citeshttps://doi.org/10.1016/j.geoderma.2019.01.050openalex-snapshot
Gully headcut susceptibility modeling using functional trees, naïve Bayes tree, and random forest models
inferred← citeshttps://doi.org/10.1016/j.geoderma.2019.07.012openalex-snapshot
Teleconnections in spatial modelling
inferred← citeshttps://doi.org/10.1016/j.geoderma.2019.113939openalex-snapshot
A graded proportion method of training sample selection for updating conventional soil maps
inferred← citeshttps://doi.org/10.1016/j.geoderma.2019.114132openalex-snapshot
Tropical soil pH and sorption complex prediction via portable X-ray fluorescence spectrometry
inferred← citeshttps://doi.org/10.1016/j.geoderma.2019.114139openalex-snapshot
Assessing the effects of deforestation and intensive agriculture on the soil quality through digital soil mapping
inferred← citeshttps://doi.org/10.1016/j.geoderma.2020.114552openalex-snapshot
Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran
inferred← citeshttps://doi.org/10.1016/j.geoderma.2022.115802openalex-snapshot
Influence of legacy soil map accuracy on soil map updating with data mining methods
inferred← citeshttps://doi.org/10.1016/j.geodrs.2022.e00566openalex-snapshot
Soil organic carbon (SOC) prediction in Australian sugarcane fields using Vis–NIR spectroscopy with different model setting approaches
inferred← citeshttps://doi.org/10.1016/j.geodrs.2023.e00728openalex-snapshot
Estimating natural soil drainage classes in the Wisconsin till plain of the Midwestern U.S.A. based on lidar derived terrain indices: Evaluating prediction accuracy of multinomial logistic regression and machine learning algorithms
inferred← citeshttps://doi.org/10.1016/j.geomorph.2011.05.015openalex-snapshot
Functional soil-landscape modelling to estimate slope stability in a steep Andean mountain forest region
inferred← citeshttps://doi.org/10.1016/j.geomorph.2017.02.015openalex-snapshot
Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran
inferred← citeshttps://doi.org/10.1016/j.geomorph.2020.107331openalex-snapshot
Spatial prediction of permafrost occurrence in Sikkim Himalayas using logistic regression, random forests, support vector machines and neural networks
inferred← citeshttps://doi.org/10.1016/j.gsf.2020.03.005openalex-snapshot
Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process
inferred← citeshttps://doi.org/10.1016/j.ijhydene.2021.11.166openalex-snapshot
A semi-empirical approach and uncertainty analysis to pipes under hydrogen embrittlement degradation
inferred← citeshttps://doi.org/10.1016/j.ijpara.2008.04.007openalex-snapshot
Random forests, a novel approach for discrimination of fish populations using parasites as biological tags
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2011.11.002openalex-snapshot
An assessment of the effectiveness of a random forest classifier for land-cover classification
inferred← citeshttps://doi.org/10.1016/j.jag.2012.05.011openalex-snapshot
Random Forests as a tool for estimating uncertainty at pixel-level in SAR image classification
inferred← citeshttps://doi.org/10.1016/j.jag.2015.08.007openalex-snapshot
Polarimetric SAR decomposition parameter subset selection and their optimal dynamic range evaluation for urban area classification using Random Forest
inferred← citeshttps://doi.org/10.1016/j.jaridenv.2024.105293openalex-snapshot
An integrated approach of machine learning methods coupled with cellular automation for monitoring and forecasting of land use and land cover
inferred← citeshttps://doi.org/10.1016/j.jastp.2024.106381openalex-snapshot
Comparative assessment of empirical random forest family's model in simulating future streamflow in different basin of Sarawak, Malaysia
inferred← citeshttps://doi.org/10.1016/j.jece.2025.118003openalex-snapshot
Investigating water quality and predicting Algal density in subtropical reservoirs through machine learning
inferred← citeshttps://doi.org/10.1016/j.jenvman.2014.02.036openalex-snapshot
Motivations for rule compliance in support of forest health: Replication and extension
inferred← citeshttps://doi.org/10.1016/j.jenvman.2020.110956openalex-snapshot
Modelling water richness and habitat suitability of the wetlands and measuring their spatial linkages in mature Ganges delta of India
inferred← citeshttps://doi.org/10.1016/j.jenvman.2025.124323openalex-snapshot
Combining deep learning and machine learning techniques to track air pollution in relation to vegetation cover utilizing remotely sensed data
inferred← citeshttps://doi.org/10.1016/j.jfoodeng.2014.01.007openalex-snapshot
Modelling the relationship between peel colour and the quality of fresh mango fruit using Random Forests
inferred← citeshttps://doi.org/10.1016/j.jhazmat.2026.142468openalex-snapshot
Stress-dependent stability of microbial sulfidogenic bioremediation is governed by community assembly and evolutionary dynamics
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2014.05.049openalex-snapshot
Assessing hydrologic prediction uncertainty resulting from soft land cover classification
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2015.12.012openalex-snapshot
Applying a weighted random forests method to extract karst sinkholes from LiDAR data
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2018.07.015openalex-snapshot
Sensitivity of drought resilience-vulnerability- exposure to hydrologic ratios in contiguous United States
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2019.05.079openalex-snapshot
Evaluation of random forest and regression tree methods for estimation of mass first flush ratio in urban catchments
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2020.125826openalex-snapshot
Expected climate change impacts on rainfall erosivity over Iran based on CMIP5 climate models
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2021.126722openalex-snapshot
Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2023.130255openalex-snapshot
Quantifying the relative contributions of different flood generating mechanisms to floods across CONUS
inferred← citeshttps://doi.org/10.1016/j.jhydrol.2024.131312openalex-snapshot
Understanding the shift in drivers of terrestrial water storage decline in the central Inner Mongolian steppe over the past two decades
inferred← citeshttps://doi.org/10.1016/j.jnc.2014.01.002openalex-snapshot
Modelling habitat use of Tetrao urogallus L. in Austria for conservation issues
inferred← citeshttps://doi.org/10.1016/j.joes.2021.10.012openalex-snapshot
Durability evaluation of GFRP rebars in harsh alkaline environment using optimized tree-based random forest model
inferred← citeshttps://doi.org/10.1016/j.jsames.2025.105671openalex-snapshot
Evaluating different machine learning methods to estimate daily evapotranspiration in the Brazilian semiarid region
inferred← citeshttps://doi.org/10.1016/j.jtice.2020.03.001openalex-snapshot
Experimental measurement and compositional modeling of crude oil viscosity at reservoir conditions
inferred← citeshttps://doi.org/10.1016/j.landurbplan.2011.03.013openalex-snapshot
Avian response to urbanization in the arid riparian context of Reno, USA
inferred← citeshttps://doi.org/10.1016/j.limno.2011.09.007openalex-snapshot
Predicting fish assemblages and diversity in shallow lakes in the Yangtze River basin
inferred← citeshttps://doi.org/10.1016/j.marenvres.2017.08.009openalex-snapshot
Environmental indicators of oyster norovirus outbreaks in coastal waters
inferred← citeshttps://doi.org/10.1016/j.marpolbul.2025.119203openalex-snapshot
Machine learning classification of PAH exposure in the Antarctic limpet Nacella concinna
inferred← citeshttps://doi.org/10.1016/j.matpr.2020.07.209openalex-snapshot
Application and performance of machine learning techniques in manufacturing sector from the past two decades: A review
inferred← citeshttps://doi.org/10.1016/j.mex.2019.09.035openalex-snapshot
The use of classification and regression algorithms using the random forests method with presence-only data to model species’ distribution
inferred← citeshttps://doi.org/10.1016/j.molliq.2022.121113openalex-snapshot
Optimization and validation of drug solubility by development of advanced artificial intelligence models
inferred← citeshttps://doi.org/10.1016/j.molliq.2023.122918openalex-snapshot
Development of compositional-based models for prediction of heavy crude oil viscosity: Application in reservoir simulations
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2025.114401openalex-snapshot
The mechanical properties of recycled brick aggregate concrete at elevated temperatures: Ensemble machine learning models and experimental validation
inferred← citeshttps://doi.org/10.1016/j.oceaneng.2015.05.038openalex-snapshot
Short-term forecasting of the wave energy flux: Analogues, random forests, and physics-based models
inferred← citeshttps://doi.org/10.1016/j.oregeorev.2015.01.001openalex-snapshot
Machine learning predictive models for mineral prospectivity: An evaluation of neural networks, random forest, regression trees and support vector machines
inferred← citeshttps://doi.org/10.1016/j.patcog.2010.08.011openalex-snapshot
Mining data with random forests: A survey and results of new tests
inferred← citeshttps://doi.org/10.1016/j.pce.2025.103974openalex-snapshot
Deciphering sediment pathways: Novel integrated approaches for sediment source identification and vulnerability prediction by machine learning models in major dam catchments in Chota Nagpur plateau, India
inferred← citeshttps://doi.org/10.1016/j.petrol.2020.107037openalex-snapshot
Prediction of CO2 diffusivity in brine using white-box machine learning
inferred← citeshttps://doi.org/10.1016/j.pocean.2024.103371openalex-snapshot
Modelling global mesozooplankton biomass using machine learning
inferred← citeshttps://doi.org/10.1016/j.prevetmed.2011.03.004openalex-snapshot
Absence reduction in entomological surveillance data to improve niche-based distribution models for Culicoides imicola
inferred← citeshttps://doi.org/10.1016/j.renene.2024.122029openalex-snapshot
What are the determinants of renewable energy consumption? An application for variable selection
inferred← citeshttps://doi.org/10.1016/j.rineng.2025.107273openalex-snapshot
Random forest Regressor-driven prediction of solar still performance: A fast and accurate alternative to CFD simulations
inferred← citeshttps://doi.org/10.1016/j.rse.2014.07.004openalex-snapshot
Forested landslide detection using LiDAR data and the random forest algorithm: A case study of the Three Gorges, China
inferred← citeshttps://doi.org/10.1016/j.rse.2016.10.005openalex-snapshot
Development of methods to improve soybean yield estimation and predict plant maturity with an unmanned aerial vehicle based platform
inferred← citeshttps://doi.org/10.1016/j.rse.2025.114843openalex-snapshot
Spatial and temporal dynamics of plant water source distribution in China
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2010.04.052openalex-snapshot
Predicting assemblages and species richness of endemic fish in the upper Yangtze River
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2014.01.001openalex-snapshot
Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: A case study in an agricultural setting (Southern Spain)
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2017.10.323openalex-snapshot
Rapid prediction of total petroleum hydrocarbons concentration in contaminated soil using vis-NIR spectroscopy and regression techniques
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2018.06.389openalex-snapshot
Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2019.02.093openalex-snapshot
Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2019.02.436openalex-snapshot
Gully erosion susceptibility assessment and management of hazard-prone areas in India using different machine learning algorithms
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2019.134799openalex-snapshot
Effects of urbanization on Cd accumulation in agricultural soils: From the perspective of accessibility gradient
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2020.137249openalex-snapshot
Potential and limitations of a pilot-scale drinking water distribution system for bacterial community predictive modelling
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2020.138793openalex-snapshot
Characterizing the impacts of land use on nitrate load and water yield in an agricultural watershed in Atlantic Canada
inferred← citeshttps://doi.org/10.1016/j.scitotenv.2021.145865openalex-snapshot
Space-time modelling of groundwater level and salinity
inferred← citeshttps://doi.org/10.1016/j.scs.2025.106476openalex-snapshot
How does built environment influence outdoor jogging activities in high-density cities? New insights using machine learning from 2D/3D perspectives
inferred← citeshttps://doi.org/10.1016/j.spasta.2015.05.008openalex-snapshot
Evaluating machine learning approaches for the interpolation of monthly air temperature at Mt. Kilimanjaro, Tanzania
inferred← citeshttps://doi.org/10.1016/j.still.2019.03.006openalex-snapshot
On-line vis-NIR spectroscopy prediction of soil organic carbon using machine learning
inferred← citeshttps://doi.org/10.1016/j.vibspec.2012.05.001openalex-snapshot
Discrimination of the geographical origin of Codonopsis pilosula using near infrared diffuse reflection spectroscopy coupled with random forests and k-nearest neighbor methods
inferred← citeshttps://doi.org/10.1016/j.watres.2017.10.032openalex-snapshot
Development of genetic programming-based model for predicting oyster norovirus outbreak risks
inferred← citeshttps://doi.org/10.1016/j.watres.2020.116638openalex-snapshot
Modeling and Forecasting Vibrio Parahaemolyticus Concentrations in Oysters
inferred← citeshttps://doi.org/10.1016/j.watres.2024.121181openalex-snapshot
An optical mechanism-based deep learning approach for deriving water trophic state of China's lakes from Landsat images
inferred← citeshttps://doi.org/10.1016/j.wse.2021.10.004openalex-snapshot
A factor mining model with optimized random forest for concrete dam deformation monitoring
inferred← citeshttps://doi.org/10.1017/cbo9780511763175.004openalex-snapshot
Numerical methods for the analysis of diatom assemblage data
inferred← citeshttps://doi.org/10.1017/s0031182010000739openalex-snapshot
Discrimination of fish populations using parasites: Random Forests on a ‘predictable’ host-parasite system
inferred← citeshttps://doi.org/10.1029/2018wr023378openalex-snapshot
Inside or Outside: Quantifying Extrapolation Across River Networks
inferred← citeshttps://doi.org/10.1029/2019wr024884openalex-snapshot
Application of Machine Learning to Model Wetland Inundation Patterns Across a Large Semiarid Floodplain
inferred← citeshttps://doi.org/10.1038/s41598-019-51395-3openalex-snapshot
The relevant range of scales for multi-scale contextual spatial modelling
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