Research graph
References from Modeling Tick Populations: An Ecological Test Case for Gradient Boosted Trees. Local targets link to admitted publications; unresolved targets remain external evidence.
Comparative Ecology of Galapagos Ground Finches (Geospiza Gould): Evaluation of the Importance of Floristic Diversity and Interspecific Competition
10.2307/1942615 · 1977 · External reference
Niche Modeling of Dengue Fever Using Remotely Sensed Environmental Factors and Boosted Regression Trees
10.3390/rs9040328 · 2017 · External reference
New approaches to direct gradient analysis using environmental scalars and statistical curve-fitting procedures
10.1007/bf00039976 · 1984 · External reference
Measurement of the Realized Qualitative Niche: Environmental Niches of Five Eucalyptus Species
10.2307/1943043 · 1990 · External reference
The Crimean‐Congo haemorrhagic fever tick vector <span class="italique">Hyalomma marginatum</span> in the south of France: Modelling its distribution and determination of factors influencing its establishment in a newly invaded area
10.1111/tbed.14578 · 2022 · External reference
Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees
10.1002/ece3.6316 · 2020 · External reference
A comparative analysis of gradient boosting algorithms
10.1007/s10462-020-09896-5 · 2021 · External reference
Lyme Disease - a Tick-Borne Spirochetosis?
10.1126/science.7043737 · 1982 · External reference
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation
2010 · External reference
Random Forests for Classification in Ecology
10.1890/07-0539.1 · 2007 · External reference
Boosted Trees for Ecological Modeling and Prediction
10.1890/0012-9658(2007)88[243:btfema]2.0.co;2 · 2007 · External reference
Classification and regression trees: a powerful yet simple technique for ecological data analysis
10.1890/0012-9658(2000)081[3178:cartap]2.0.co;2 · 2000 · External reference
New types of deep neural network learning for speech recognition and related applications: an overview
10.1109/icassp.2013.6639344 · 2013 · External reference
A working guide to boosted regression trees
10.1111/j.1365-2656.2008.01390.x · 2008 · External reference
Novel methods improve prediction of species’ distributions from occurrence data
10.1111/j.2006.0906-7590.04596.x · 2006 · External reference
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time
10.1146/annurev.ecolsys.110308.120159 · 2009 · External reference
Ecological niche modeling re-examined: A case study with the Darwin's fox
10.1002/ece3.4014 · 2018 · External reference
Situating Ecology as a Big-Data Science: Current Advances, Challenges, and Solutions
10.1093/biosci/biy068 · 2018 · External reference
Predicting the zoonotic capacity of mammals to transmit SARS-CoV-2
10.1098/rspb.2021.1651 · 2021 · External reference
Greedy function approximation: A gradient boosting machine.
10.1214/aos/1013203451 · 2001 · External reference
Environmental drivers of spatiotemporal foraging intensity in fruit bats and implications for Hendra virus ecology
10.1038/s41598-018-27859-3 · 2018 · External reference
Why do tree-based models still outperform deep learning on typical tabular data?
2022 · External reference
Rodent reservoirs of future zoonotic diseases
10.1073/pnas.1501598112 · 2015 · External reference
Brain size and ecology in small mammals and primates.
10.1073/pnas.77.7.4387 · 1980 · External reference
10.1007/978-0-387-21606-5
10.1007/978-0-387-21606-5 · 2001 · External reference
Geographical and environmental factors driving the increase in the Lyme disease vector <span class="italique">Ixodes scapularis</span>
10.1890/es12-00134.1 · 2012 · External reference
Body size and metabolic rate
10.1152/physrev.1947.27.4.511 · 1947 · External reference
Will Culling White-Tailed Deer Prevent Lyme Disease?
10.1111/zph.12245 · 2016 · External reference
Physical and ecological factors explain the distribution of Ross Sea Weddell seals during the breeding season
10.3354/meps12877 · 2019 · External reference
Ecosystems and the Biosphere as Complex Adaptive Systems
10.1007/s100219900037 · 1998 · External reference
Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal
10.1038/srep44152 · 2017 · External reference
A Unified Approach to Interpreting Model Predictions
10.48550/arxiv.1705.07874 · 2017 · External reference
The role of host phenology for parasite transmission
10.1007/s12080-020-00484-5 · 2021 · External reference
Modeling Tick Populations: An Ecological Test Case for Gradient Boosting Trees. Mendeley Data, 2
10.17632/w8bp678m3f.2 · 2023 · External reference
10.1007/978-1-4899-3242-6
10.1007/978-1-4899-3242-6 · 1989 · External reference
Sexual Selection and the Risk of Extinction of Introduced Birds on Oceanic Islands
10.2307/3545671 · 1995 · External reference
A Comparative Assessment Between Three Machine Learning Models and Their Performance Comparison by Bivariate and Multivariate Statistical Methods in Groundwater Potential Mapping
10.1007/s11269-015-1114-8 · 2015 · External reference
Gradient boosting machines, a tutorial
10.3389/fnbot.2013.00021 · 2013 · External reference
Machine Learning Methods Without Tears: A Primer for Ecologists
10.1086/587826 · 2008 · External reference
Climate, Deer, Rodents, and Acorns as Determinants of Variation in Lyme-Disease Risk
10.1371/journal.pbio.0040145 · 2006 · External reference
Scikit-learn: Machine Learning in Python
2011 · External reference
Gradient Boosted Trees can deliver more than accurate ecological predictions
10.24072/pci.ecology.100532 · 2023 · External reference
Prevalence of <span class="italique">Borrelia burgdorferi</span> (Spirochaetales: Spirochaetaceae), <span class="italique">Anaplasma phagocytophilum</span> (Rickettsiales: Anaplasmataceae), and <span class="italique">Babesia microti</span> (Piroplasmida: Babesiidae) in <span class="italique">Ixodes scapularis</span> (Acari: Ixodidae) Collected From Recreational Lands in the Hudson Valley Region, New York State
10.1603/me13101 · 2014 · External reference
No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation
10.1111/2041-210x.12397 · 2015 · External reference
Predicting insect outbreaks using machine learning: A mountain pine beetle case study
10.1002/ece3.7921 · 2021 · External reference
Harnessing Deep Learning in Ecology: An Example Predicting Bark Beetle Outbreaks
10.3389/fpls.2019.01327 · 2019 · External reference
MLxtend: Providing machine learning and data science utilities and extensions to Python’s scientific computing stack
10.21105/joss.00638 · 2018 · External reference
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review
10.1162/neco_a_00990 · 2017 · External reference
Energy Constraints on Avian Distributions and Abundances
10.2307/1940431 · 1988 · External reference
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
10.1038/s42256-019-0048-x · 2019 · External reference
Explainable artificial intelligence enhances the ecological interpretability of black-box species distribution models
10.1111/ecog.05360 · 2021 · External reference
Potential Effects of Animal Activity on the Spatial Distribution of <span class="italique">Ixodes scapularis</span> and <span class="italique">Amblyomma americanum</span> (Acari: Ixodidae)
10.1603/0046-225x-30.3.568 · 2001 · External reference
A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area
10.1002/ece3.2332 · 2016 · External reference
Malaria smear positivity among Kenyan children peaks at intermediate temperatures as predicted by ecological models
10.1186/s13071-019-3547-z · 2019 · External reference
Malaria risk assessment and mapping using satellite imagery and boosted regression trees in the Peruvian Amazon
10.1038/s41598-019-51564-4 · 2019 · External reference
Human Babesiosis on Nantucket Island, USA: Description of the Vector, <span class="italique">Ixodes dammini</span>, n. sp. (Acarina: Ixodidae)
10.1093/jmedent/15.3.218 · 1979 · External reference
Global Mammal Parasite Database version 2.0
10.1002/ecy.1799 · 2017 · External reference
Kirinyuh (<span class="italique">Chromolaena odorata</span>): species distribution modeling and the potential use of fungal pathogens for its eradication
10.1088/1755-1315/762/1/012023 · 2021 · External reference
Perpetuation of the agent of human granulocytic ehrlichiosis in a deer tick-rodent cycle.
10.1073/pnas.93.12.6209 · 1996 · External reference
Productivity and sustainability influenced by biodiversity in grassland ecosystems
10.1038/379718a0 · 1996 · External reference
Estimating disease vector population size from citizen science data
10.1098/rsif.2021.0610 · External reference
Spatio-temporal variation in environmental features predicts the distribution and abundance of Ixodes scapularis
10.1016/j.ijpara.2020.10.002 · External reference
Fox sightings in a city are related to certain land use classes and sociodemographics: results from a citizen science project
10.1186/s12898-018-0207-7 · 2018 · External reference
Taxonomic affinity, habitat and seed mass strongly predict seed desiccation response: a boosted regression trees analysis based on 17539 species
10.1093/aob/mcx128 · 2018 · External reference
Generalized additive models in plant ecology
10.2307/3236170 · 1991 · External reference
Duration and Regulation of the Developmental Cycle of Ixodes dammini (Acari: Ixodidae)
10.1093/jmedent/27.2.196 · 1990 · External reference
