The following 87 publications cited the product Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 4.
| Year | Citation |
|---|---|
| 2023 | Aiello, C.M., N.L. Galloway, P.R. Prentice, N.W. Darby, D. Hughson, and C.W. Epps. 2023. Movement models and simulation reveal highway impacts and mitigation opportunities for a metapopulation-distributed species. Landscape Ecology. 38(4):1085-1103. https://doi.org/10.1007/s10980-023-01600-6 |
| 2023 | Ale, S., Q. Su, J. Singh, S. Himanshu, Y. Fan, B. Stoker, E. Gonzalez, B.R. Sapkota, C. Adams, K. Biggers, E. Kimura, and J. Wall. 2023. Development and evaluation of a decision support mobile application for cotton irrigation management. Smart Agricultural Technology. 5:100270. https://doi.org/10.1016/j.atech.2023.100270 |
| 2023 | Amirkhiz, R.G., R. John, and D.L. Swanson. 2023. A Bayesian approach for multiscale modeling of the influence of seasonal and annual habitat variation on relative abundance of ring-necked pheasant roosters. Ecological Informatics. 75:102003. https://doi.org/10.1016/j.ecoinf.2023.102003 |
| 2023 | Bennemann, C., E.R. Labelle, and J. Lussier. 2023. Influence of Tree, Stand, and Site Attributes on Hardwood Product Yield: Insights into the Acadian Forests. Forests. 14(2):182. https://doi.org/10.3390/f14020182 |
| 2023 | Bhanja, S.N., E.T. Coon, D. Lu, and S.L. Painter. 2023. Evaluation of distributed process-based hydrologic model performance using only a priori information to define model inputs. Journal of Hydrology. 618:129176. https://doi.org/10.1016/j.jhydrol.2023.129176 |
| 2023 | Buttò, V., S. Khare, P. Jain, G. de Lima Santos, and S. Rossi. 2023. Spatial patterns and climatic drivers of leaf spring phenology of maple in eastern North America. Science of The Total Environment. 857:159064. https://doi.org/10.1016/j.scitotenv.2022.159064 |
| 2023 | Celik, M.F., M.S. Isik, G. Taskin, E. Erten, and G. Camps-Valls. 2023. Explainable Artificial Intelligence for Cotton Yield Prediction With Multisource Data. IEEE Geoscience and Remote Sensing Letters. 20:1-5. https://doi.org/10.1109/LGRS.2023.3303643 |
| 2023 | Chakraborty, T., A.J. Newman, Y. Qian, A. Hsu, and G. Sheriff. 2023. Residential segregation and outdoor urban moist heat stress disparities in the United States. One Earth. 6(6):738-750. https://doi.org/10.1016/j.oneear.2023.05.016 |
| 2023 | Chu, B., R. Chen, Q. Liu, and H. Wang. 2023. Effects of High Temperature on COVID?19 Deaths in U.S. Counties. GeoHealth. 7(3). https://doi.org/10.1029/2022GH000705 |
| 2023 | Coughlan de Perez, E., H. Ganapathi, G.I.T. Masukwedza, T. Griffin, and T. Kelder. 2023. Potential for surprising heat and drought events in wheat-producing regions of USA and China. npj Climate and Atmospheric Science. 6(1). https://doi.org/10.1038/s41612-023-00361-y |
| 2023 | Eacker, D.R., A.F. Jakes, and P.F. Jones. 2023. Spatiotemporal risk factors predict landscape?scale survivorship for a northern ungulate. Ecosphere. 14(2). https://doi.org/10.1002/ecs2.4341 |
| 2023 | Emirhüseyino?lu, G., M. Shahhosseini, G. Hu, and S.M. Ryan. 2023. Validation of scenario generation for decision-making using machine learning prediction models. Optimization Letters. https://doi.org/10.1007/s11590-023-02023-7 |
| 2023 | Feng, D., H. Beck, K. Lawson, and C. Shen. 2023. The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment. Hydrology and Earth System Sciences. 27(12):2357-2373. https://doi.org/10.5194/hess-27-2357-2023 |
| 2023 | Fidan, E., J. Gray, B. Doll, and N.G. Nelson. 2023. Machine learning approach for modeling daily pluvial flood dynamics in agricultural landscapes. Environmental Modelling & Software. 167:105758. https://doi.org/10.1016/j.envsoft.2023.105758 |
| 2023 | Garretson, A., T. Cuddy, A.G. Duffy, and R.E. Forkner. 2023. Citizen science data reveal regional heterogeneity in phenological response to climate in the large milkweed bug, Oncopeltus fasciatus. Ecology and Evolution. 13(7). https://doi.org/10.1002/ece3.10213 |
| 2023 | Gaso, D.V., A. de Wit, S. de Bruin, L.A. Puntel, A.G. Berger, and L. Kooistra. 2023. Efficiency of assimilating leaf area index into a soybean model to assess within-field yield variability. European Journal of Agronomy. 143:126718. https://doi.org/10.1016/j.eja.2022.126718 |
| 2023 | Giroux-Bougard, X., E. Fluet-Chouinard, M.A. Crowley, J.A. Cardille, and M.M. Humphries. 2023. Multi-sensor detection of spring breakup phenology of Canada's lakes. Remote Sensing of Environment. 295:113656. https://doi.org/10.1016/j.rse.2023.113656 |
| 2023 | Goodling, P.J., B.J. Fleming, J. Solder, A. Soroka, and J. Raffensperger. 2023. Hydrogeologic characterization of Area B, Fort Detrick, Maryland. Scientific Investigations Report. https://doi.org/10.3133/sir20225054 |
| 2023 | Hamm, A., R.Í. Magnússon, A.J. Khattak, and A. Frampton. 2023. Continentality determines warming or cooling impact of heavy rainfall events on permafrost. Nature Communications. 14(1). https://doi.org/10.1038/s41467-023-39325-4 |
| 2023 | Haserodt, M.J., H.W. Reeves, M.G. Nielsen, L.A. Schachter, N.T. Corson-Dosch, and D.T. Feinstein. 2023. Simulation of groundwater flow at the former Badger Army Ammunition Plant, Sauk County, Wisconsin. Scientific Investigations Report. https://doi.org/10.3133/sir20235040 |
| 2023 | Hu, L., E.I. Nikolopoulos, F. Marra, and E.N. Anagnostou. 2023. Toward an improved estimation of flood frequency statistics from simulated flows. Journal of Flood Risk Management. https://doi.org/10.1111/jfr3.12891 |
| 2023 | Iverson, A.R., D.L. Humple, R.L. Cormier, and J. Hull. 2023. Land cover and NDVI are important predictors in habitat selection along migration for the Golden-crowned Sparrow, a temperate-zone migrating songbird. Movement Ecology. 11(1). https://doi.org/10.1186/s40462-022-00353-2 |
| 2023 | Katz, D.S.W., A.P. Baptist, and S.A. Batterman. 2023. Modeling airborne pollen concentrations at an urban scale with pollen release from individual trees. Aerobiologia. https://doi.org/10.1007/s10453-023-09784-9 |
| 2023 | Kemp, J., W.S. Boyd, T.M. Forstner, D. Esler, T.D. Bowman, D.C. Douglas, D. Hogan, M. McAdie, J.E. Thompson, M. Willie, and D.J. Green. 2023. Pacific Barrow’s Goldeneye refine migratory phenology in response to overwintering temperatures and annual snowmelt. Ornithology. 140(3). https://doi.org/10.1093/ornithology/ukad024 |
| 2023 | Ludwig, A., F. Rousseu, S.O. Kotchi, J. Allostry, and R.A. Fournier. 2023. Mapping the abundance of endemic mosquito-borne diseases vectors in southern Quebec. BMC Public Health. 23(1). https://doi.org/10.1186/s12889-023-15773-x |
| 2023 | McNellis, B.E., A.C. Knight, T.W. Nauman, S. Chambers, C.W. Brungard, S.E. Fick, C.G. Livensperger, S. Borthwick, and M.C. Duniway. 2023. Livestock removal increases plant cover across a heterogeneous dryland landscape on the Colorado Plateau. Environmental Research Letters. https://doi.org/10.1088/1748-9326/acb728 |
| 2023 | Mínguez, R. and S. Herrera. 2023. Spatial extreme model for rainfall depth: application to the estimation of IDF curves in the Basque country. Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-023-02440-1 |
| 2023 | Moraes, F.D., T.L. Mote, and T.C. Rasmussen. 2023. The role of physical geography on Puerto Rico’s water budget. Journal of Hydrology: Regional Studies. 47:101382. https://doi.org/10.1016/j.ejrh.2023.101382 |
| 2023 | Norris, C.E., M.J. Swallow, D. Liptzin, M. Cope, G.M. Bean, S.B. Cappellazzi, K.L. Greub, E.L. Rieke, P.W. Tracy, C.L. Morgan, and C.W. Honeycutt. 2023. Use of phospholipid fatty acid analysis as phenotypic biomarkers for soil health and the influence of management practices. Applied Soil Ecology. 185:104793. https://doi.org/10.1016/j.apsoil.2022.104793 |
| 2023 | Özgen-Xian, I., S. Molins, R.M. Johnson, Z. Xu, D. Dwivedi, R. Loritz, U. Mital, C. Ulrich, Q. Yan, and C.I. Steefel. 2023. Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions. Scientific Reports. 13(1). https://doi.org/10.1038/s41598-023-31925-w |
| 2023 | Painter, S.L., E.T. Coon, A.J. Khattak, and J.D. Jastrow. 2023. Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw. Proceedings of the National Academy of Sciences. 120(8). https://doi.org/10.1073/pnas.2212171120 |
| 2023 | Pereira, M. and B. Glisic. 2023. Detection and quantification of temperature sensor drift using probabilistic neural networks. Expert Systems with Applications. 213:118884. https://doi.org/10.1016/j.eswa.2022.118884 |
| 2023 | Ryan, A., J.F. Kocik, E.J. Atkinson, and N.B. Furey. 2023. The effects of environmental and biological factors on the length of Atlantic Salmon age?1+ parr in three Maine drainages. Transactions of the American Fisheries Society. https://doi.org/10.1002/tafs.10405 |
| 2023 | Sadra, N., M.R. Nikoo, and N. Talebbeydokhti. 2023. Non-stationary evaluation of runoff peaks in response to climate variability and land use change in Ferson Creek, Illinois, USA. Environmental Monitoring and Assessment. 195(6). https://doi.org/10.1007/s10661-023-11238-1 |
| 2023 | Saha, G.K., F. Rahmani, C. Shen, L. Li, and R. Cibin. 2023. A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds. Science of The Total Environment. 878:162930. https://doi.org/10.1016/j.scitotenv.2023.162930 |
| 2023 | Schädel, C., B. Seyednasrollah, P.J. Hanson, K. Hufkens, K.J. Pearson, J.M. Warren, and A.D. Richardson. 2023. Using long?term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models. Plant-Environment Interactions. 4(4):188-200. https://doi.org/10.1002/pei3.10118 |
| 2023 | Scher, C.L. and J.S. Clark. 2023. Species traits and observer behaviors that bias data assimilation and how to accommodate them. Ecological Applications. 33(3). https://doi.org/10.1002/eap.2815 |
| 2023 | Senay, G.B., G.E.L. Parrish, M. Schauer, M. Friedrichs, K. Khand, O. Boiko, S. Kagone, R. Dittmeier, S. Arab, and L. Ji. 2023. Improving the Operational Simplified Surface Energy Balance Evapotranspiration Model Using the Forcing and Normalizing Operation. Remote Sensing. 15(1):260. https://doi.org/10.3390/rs15010260 |
| 2023 | Suraci, J.P., T.G. Mozelewski, C.E. Littlefield, T. Nogeire McRae, A. Sorensen, and B.G. Dickson. 2023. Management of U.S. Agricultural Lands Differentially Affects Avian Habitat Connectivity. Land. 12(4):746. https://doi.org/10.3390/land12040746 |
| 2023 | Svedin, J.D., K.S. Veum, C.J. Ransom, N.R. Kitchen, and S.H. Anderson. 2023. An identified agronomic interpretation for potassium permanganate oxidizable carbon. Soil Science Society of America Journal. 87(2):291-308. https://doi.org/10.1002/saj2.20499 |
| 2023 | Vanderhoof, M.K., L. Alexander, J. Christensen, K. Solvik, P. Nieuwlandt, and M. Sagehorn. 2023. High-frequency time series comparison of Sentinel-1 and Sentinel-2 satellites for mapping open and vegetated water across the United States (2017–2021). Remote Sensing of Environment. 288:113498. https://doi.org/10.1016/j.rse.2023.113498 |
| 2023 | Wagler, B.L., R.A. Smiley, A.B. Courtemanch, D. Lutz, D. McWhirter, D. Brimeyer, P. Hnilicka, T.J. Robinson, and K.L. Monteith. 2023. Implications of forage quality for population recovery of bighorn sheep following a pneumonia epizootic. The Journal of Wildlife Management. 87(6). https://doi.org/10.1002/jwmg.22452 |
| 2023 | Worrall, G., J. Judge, K. Boote, and A. Rangarajan. 2023. In?season crop phenology using remote sensing and model?guided machine learning. Agronomy Journal. https://doi.org/10.1002/agj2.21230 |
| 2023 | Yu, R., Y. Yao, Q. Tang, C. Shao, J.B. Fisher, J. Chen, K. Jia, X. Zhang, Y. Li, K. Shang, J. Yang, L. Liu, X. Zhang, X. Guo, Z. Xie, J. Ning, J. Fan, and L. Zhang. 2023. Coupling a light use efficiency model with a machine learning-based water constraint for predicting grassland gross primary production. Agricultural and Forest Meteorology. 341:109634. https://doi.org/10.1016/j.agrformet.2023.109634 |
| 2023 | Zhang, Y., S.T. Ebelt, L. Shi, N.C. Scovronick, R.R. D'Souza, K. Steenland, and H.H. Chang. 2023. Short-term associations between warm-season ambient temperature and emergency department visits for Alzheimer's disease and related dementia in five US states. Environmental Research. 220:115176. https://doi.org/10.1016/j.envres.2022.115176 |
| 2023 | Zhao, J., T.Y. Gan, G. Zhang, and S. Zhang. 2023. Projected changes of precipitation extremes in North America using CMIP6 multi-climate model ensembles. Journal of Hydrology. 621:129598. https://doi.org/10.1016/j.jhydrol.2023.129598 |
| 2023 | Zhi, W., W. Ouyang, C. Shen, and L. Li. 2023. Temperature outweighs light and flow as the predominant driver of dissolved oxygen in US rivers. Nature Water. 1(3):249-260. https://doi.org/10.1038/s44221-023-00038-z |
| 2023 | Zou, J., M. Odening, and O. Okhrin. 2023. Plant growth stages and weather index insurance design. Annals of Actuarial Science. 1-21. https://doi.org/10.1017/S1748499523000167 |
| 2023 | Zylstra, E.R., L.J. Allison, R.C. Averill?Murray, V. Landau, N.S. Pope, and R.J. Steidl. 2023. A spatially explicit model for density that accounts for availability: a case study with |
| 2022 | Casmey, M., A. Hamann, and U.G. Hacke. 2022. Adaptation of white spruce to climatic risk environments in spring: Implications for assisted migration. Forest Ecology and Management. 525:120555. https://doi.org/10.1016/j.foreco.2022.120555 |
| 2022 | Cline, T.J., C.C. Muhlfeld, R. Kovach, R. Al-Chokhachy, D. Schmetterling, D. Whited, and A.J. Lynch. 2022. Socioeconomic resilience to climatic extremes in a freshwater fishery. Science Advances. 8(36). https://doi.org/10.1126/sciadv.abn1396 |
| 2022 | Coon, E.T., and P. Shuai. 2022. Watershed Workflow: A toolset for parameterizing data-intensive, integrated hydrologic models. Environmental Modelling & Software. 157:105502. https://doi.org/10.1016/j.envsoft.2022.105502 |
| 2022 | Danalatos, G.J.N., C. Wolter, S.V. Archontoulis, and M.J. Castellano. 2022. Nitrate losses across 29 Iowa watersheds: Measuring long?term trends in the context of interannual variability. Journal of Environmental Quality. 51(4):708-718. https://doi.org/10.1002/jeq2.20349 |
| 2022 | Dhaliwal, D.S. and M.M. Williams. 2022. Evidence of sweet corn yield losses from rising temperatures. Scientific Reports. 12(1). https://doi.org/10.1038/s41598-022-23237-2 |
| 2022 | Finkelstein, J.S., J. Monti, J.P. Masterson, and D.A. Walter. 2022. Application of a soil-water-balance model to estimate annual groundwater recharge for Long Island, New York, 1900–2019. Scientific Investigations Report. https://doi.org/10.3133/sir20215143 |
| 2022 | Glass, D.M., P.R. Prentice, A.D. Evans, and O.J. Schmitz. 2022. Local differences in maximum temperature determine water use among desert bighorn sheep populations. The Journal of Wildlife Management. 86(8). https://doi.org/10.1002/jwmg.22313 |
| 2022 | Gottlieb, A.R. and J.S. Mankin. 2022. Observing, Measuring, and Assessing the Consequences of Snow Drought. Bulletin of the American Meteorological Society. 103(4):E1041-E1060. https://doi.org/10.1175/BAMS-D-20-0243.1 |
| 2022 | Gutierrez-Avila, I. et al. 2022. Prediction of daily mean and one-hour maximum PM2.5 concentrations and applications in Central Mexico using satellite-based machine-learning models. Journal of Exposure Science & Environmental Epidemiology. https://doi.org/10.1038/s41370-022-00471-4 |
| 2022 | Hoecker, T.J. and M.G. Turner. 2022. A short-interval reburn catalyzes departures from historical structure and composition in a mesic mixed-conifer forest. Forest Ecology and Management. 504:119814. https://doi.org/10.1016/j.foreco.2021.119814 |
| 2022 | Hu, X.C., M. Dai, J.M. Sun, and E.M. Sunderland. 2022. The Utility of Machine Learning Models for Predicting Chemical Contaminants in Drinking Water: Promise, Challenges, and Opportunities. Current Environmental Health Reports. 10(1):45-60. https://doi.org/10.1007/s40572-022-00389-x |
| 2022 | Jin, T., Q. Di, W.J. Réquia, M. Danesh Yazdi, E. Castro, T. Ma, Y. Wang, H. Zhang, L. Shi, and J. Schwartz. 2022. Associations between long-term air pollution exposure and the incidence of cardiovascular diseases among American older adults. Environment International. 170:107594. https://doi.org/10.1016/j.envint.2022.107594 |
| 2022 | Jones, C., M.M. Skrip, B.J. Seliger, S. Jones, T. Wakie, Y. Takeuchi, V. Petras, A. Petrasova, and R.K. Meentemeyer. 2022. Spotted lanternfly predicted to establish in California by 2033 without preventative management. Communications Biology. 5(1). https://doi.org/10.1038/s42003-022-03447-0 |
| 2022 | Keyser, S.R., D. Fink, D. Gudex?Cross, V.C. Radeloff, J.N. Pauli, and B. Zuckerberg. 2022. Snow cover dynamics: an overlooked yet important feature of winter bird occurrence and abundance across the United States. Ecography. 2023(1). https://doi.org/10.1111/ecog.06378 |
| 2022 | Nagler, P.L., A. Barreto-Muñoz, I. Sall, M.R. Lurtz, and K. Didan. 2022. Riparian Plant Evapotranspiration and Consumptive Use for Selected Areas of the Little Colorado River Watershed on the Navajo Nation. Remote Sensing. 15(1):52. https://doi.org/10.3390/rs15010052 |
| 2022 | Petrakis, R.E., C.E. Soulard, E.K. Waller, and J.J. Walker. 2022. Analysis of Surface Water Trends for the Conterminous United States Using MODIS Satellite Data, 2003–2019. Water Resources Research. 58(6). https://doi.org/10.1029/2021WR031399 |
| 2022 | Reed, A.T., A.M. Stansfield, and K.A. Reed. 2022. Characterizing Long Island’s Extreme Precipitation and Its Relationship to Tropical Cyclones. Atmosphere. 13(7):1070. https://doi.org/10.3390/atmos13071070 |
| 2022 | Rupp, D.E., C. Daly, M.K. Doggett, J.I. Smith, and B. Steinberg. 2022. Mapping an Observation-Based Global Solar Irradiance Climatology across the Conterminous United States. Journal of Applied Meteorology and Climatology. 61(7):857-876. https://doi.org/10.1175/JAMC-D-21-0236.1 |
| 2022 | Sarzaeim, P., F. Muñoz-Arriola, and D. Jarquín. 2022. Climate and genetic data enhancement using deep learning analytics to improve maize yield predictability. Journal of Experimental Botany. 73(15):5336-5354. https://doi.org/10.1093/jxb/erac146 |
| 2022 | Smith, B.W., C.E. Soulard, J.J. Walker, and A.M. Wein. 2022. Using Landsat and MODIS satellite collections to examine extent, timing, and potential impacts of surface water inundation in California croplands. Remote Sensing Applications: Society and Environment. 28:100837. https://doi.org/10.1016/j.rsase.2022.100837 |
| 2022 | Tassone, S.J., A.F. Besterman, C.D. Buelo, D.T. Ha, J.A. Walter, and M.L. Pace. 2022. Increasing heatwave frequency in streams and rivers of the United States. Limnology and Oceanography Letters. 8(2):295-304. https://doi.org/10.1002/lol2.10284 |
| 2022 | Wang, H., Z. Dai, C.C. Trettin, K.W. Krauss, G.B. Noe, A.J. Burton, C.L. Stagg, and E.J. Ward. 2022. Modeling impacts of drought?induced salinity intrusion on carbon dynamics in tidal freshwater forested wetlands. Ecological Applications. https://doi.org/10.1002/eap.2700 |
| 2022 | Xia, Y., J.D. Watts, M.B. Machmuller, and J. Sanderman. 2022. Machine learning based estimation of field-scale daily, high resolution, multi-depth soil moisture for the Western and Midwestern United States. PeerJ. 10:e14275. https://doi.org/10.7717/peerj.14275 |
| 2022 | Yi, Y., R.H. Chen, M. Moghaddam, J.S. Kimball, B.M. Jones, R.R. Jandt, E.A. Miller, and C.E. Miller. 2022. Sensitivity of Multifrequency Polarimetric SAR Data to Postfire Permafrost Changes and Recovery Processes in Arctic Tundra. IEEE Transactions on Geoscience and Remote Sensing. 60:1-15. https://doi.org/10.1109/TGRS.2021.3125715 |
| 2021 | Cannon, A.J., H. Alford, R.R. Shrestha, M.C. Kirchmeier-Young, and M.R. Najafi. 2021. Canadian Large Ensembles Adjusted Dataset version 1 (CanLEADv1): Multivariate bias-corrected climate model outputs for terrestrial modelling and attribution studies in North America. Geoscience Data Journal. https://doi.org/10.1002/gdj3.142 |
| 2021 | Chegini, T., H.Y. Li, and L. Leung. 2021. HyRiver: Hydroclimate Data Retriever. Journal of Open Source Software. 6(66):3175. https://doi.org/10.21105/joss.03175 |
| 2021 | Clayton, L.K., K. Schaefer, M.J. Battaglia, L. Bourgeau-Chavez, J. Chen, R.H. Chen, A. Chen, K. Bakian-Dogaheh, S. Grelik, E. Jafarov, L. Liu, R.J. Michaelides, M. Moghaddam, A.D. Parsekian, A.V. Rocha, S.R. Schaefer, T. Sullivan, A. Tabatabaeenejad, K. Wang, C.J. Wilson, H.A. Zebker, T. Zhang, and Y. Zhao. 2021. Active layer thickness as a function of soil water content. Environmental Research Letters. 16(5):055028. https://doi.org/10.1088/1748-9326/abfa4c |
| 2021 | de Jesus Crespo, R. and R.E. Rogers. 2021. Habitat Segregation Patterns of Container Breeding Mosquitos: The Role of Urban Heat Islands, Vegetation Cover, and Income Disparity in Cemeteries of New Orleans. International Journal of Environmental Research and Public Health. 19(1):245. https://doi.org/10.3390/ijerph19010245 |
| 2021 | Deeds, J., A. Amirbahman, S.A. Norton, L.C. Bacon, and R.A. Hovel. 2021. Shifting baselines and cross-scale drivers of lake water clarity: Applications for lake assessment. Limnology and Oceanography. https://doi.org/10.1002/lno.11873 |
| 2021 | Fitzpatrick, L., P.J. Giambuzzi, A. Spreitzer, B. Reidy, S.M. Still, and C.R. Rollinson. 2021. Improving phenology predictions for sparsely observed species through fusion of botanical collections and citizen-science. Climate Change Ecology. 2:100032. https://doi.org/10.1016/j.ecochg.2021.100032 |
| 2021 | Fu, P., L. Hu, E.A. Ainsworth, X. Tai, S.W. Myint, W. Zhan, B.J. Blakely, and C.J. Bernacchi. 2021. Enhanced drought resistance of vegetation growth in cities due to urban heat, CO2 domes and O3 troughs. Environmental Research Letters. 16(12):124052. https://doi.org/10.1088/1748-9326/ac3b17 |
| 2021 | Li, W., Q. Xin, X. Zhou, Z. Zhang, and Y. Ruan. 2021. Comparisons of numerical phenology models and machine learning methods on predicting the spring onset of natural vegetation across the Northern Hemisphere. Ecological Indicators. 131:108126. https://doi.org/10.1016/j.ecolind.2021.108126 |
| 2021 | Mauget, S.A. and D. Mitchell-McCallister. 2021. Managing to climatology: Improving semi-arid agricultural risk management using crop models and a dense meteorological network. Q Open. 1(2): https://doi.org/10.1093/qopen/qoab013 |
| 2021 | Moro Rosso, L.H., A.F. de Borja Reis, and I.A. Ciampitti. 2021. Vertical Canopy Profile and the Impact of Branches on Soybean Seed Composition. Frontiers in Plant Science. 12: https://doi.org/10.3389/fpls.2021.725767 |
| 2021 | Qian, Y., H. Li, A. Rosenberg, Q. Li, J. Sarnat, S. Papatheodorou, J. Schwartz, D. Liang, Y. Liu, P. Liu, and L. Shi. 2021. Long-Term Exposure to Low-Level NO2 and Mortality among the Elderly Population in the Southeastern United States. Environmental Health Perspectives. 129(12): https://doi.org/10.1289/EHP9044 |
| 2021 | Smyers, S.D., M.T. Jones, L.L. Willey, T. Tadevosyan, J. Martinez, K. Cormier, and D.B. Kemmett. 2021. Calling Phenology in Rana sylvatica (Wood Frog) at High-Elevation Ponds in the White Mountains, New Hampshire. Northeastern Naturalist. 28(sp11): https://doi.org/10.1656/045.028.s1109 |
| 2021 | Tewari, A., V. Kshemkalyani, H. Kukreja, P. Menon, and R. Thomas. 2021. Application of LSTMs and HAND in Rapid Flood Inundation Mapping. 515-521. https://doi.org/10.1109/ICICCS51141.2021.9432332 |
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