Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Carlos F. Gaitan"'
Autor:
Barbara A. Muhling, Stephanie Brodie, James A. Smith, Desiree Tommasi, Carlos F. Gaitan, Elliott L. Hazen, Michael G. Jacox, Toby D. Auth, Richard D. Brodeur
Publikováno v:
Frontiers in Marine Science, Vol 7 (2020)
Spatial distributions of marine fauna are determined by complex interactions between environmental conditions and animal behaviors. As climate change leads to warmer, more acidic, and less oxygenated oceans, species are shifting away from their histo
Externí odkaz:
https://doaj.org/article/67121857d566441b8fc772fe1dbd10a1
Publikováno v:
GeoHealth, Vol 1, Iss 7, Pp 278-296 (2017)
Abstract Illness caused by pathogenic strains of Vibrio bacteria incurs significant economic and health care costs in many areas around the world. In the Chesapeake Bay, the two most problematic species are V. vulnificus and V. parahaemolyticus, whic
Externí odkaz:
https://doaj.org/article/a95b85b787eb4ea2bff660d79a1c74df
Autor:
Desiree Tommasi, James A. Smith, Elliott L. Hazen, Barbara A. Muhling, Richard D. Brodeur, Michael G. Jacox, Toby D. Auth, Carlos F. Gaitan, Stephanie Brodie
Publikováno v:
Frontiers in Marine Science, Vol 7 (2020)
Spatial distributions of marine fauna are determined by complex interactions between environmental conditions and animal behaviors. As climate change leads to warmer, more acidic, and less oxygenated oceans, species are shifting away from their histo
Autor:
Carlos F. Gaitan
As our agricultural systems are expected to sustain a population of around 10 billion by 2050, and increase their production by nearly 50% globally, agricultural producers, intermediaries, distributors, and resellers are looking at novel alternatives
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04774184cdd466d91b03118280cc86d1
https://doi.org/10.1016/b978-0-12-814895-2.00007-0
https://doi.org/10.1016/b978-0-12-814895-2.00007-0
Publikováno v:
GeoHealth, Vol 1, Iss 7, Pp 278-296 (2017)
Illness caused by pathogenic strains of Vibrio bacteria incurs significant economic and health care costs in many areas around the world. In the Chesapeake Bay, the two most problematic species are V. vulnificus and V. parahaemolyticus, which cause i
Autor:
Barbara A. Muhling, Keith W. Dixon, Charles A. Stock, Vincent S. Saba, Desiree Tommasi, Carlos F. Gaitan
Publikováno v:
Estuaries and Coasts. 41:349-372
Estuaries are productive and ecologically important ecosystems, incorporating environmental drivers from watersheds, rivers, and the coastal ocean. Climate change has potential to modify the physical properties of estuaries, with impacts on resident
Publikováno v:
Journal of Applied Meteorology and Climatology. 56:1325-1336
Increases in the frequency and intensity of extreme precipitation are projected for most U.S. regions under climate change. There is a high degree of uncertainty, however, in precipitation regime changes across the large precipitation gradient of the
Autor:
Anne M. K. Stoner, Katharine Hayhoe, Venkatramani Balaji, Carlos F. Gaitan, John R. Lanzante, Keith W. Dixon, Aparna Radhakrishnan, Mary Jo Nath
Publikováno v:
Climatic Change. 135:395-408
Empirical statistical downscaling (ESD) methods seek to refine global climate model (GCM) outputs via processes that glean information from a combination of observations and GCM simulations. They aim to create value-added climate projections by reduc
Autor:
Sarah B. Kapnick, Michael A. Alexander, Barbara A. Muhling, Sarah Gaichas, Francisco E. Werner, Desiree Tommasi, Rick Methot, J. Paige Eveson, Claire M. Spillman, Vincent S. Saba, Jason R. Hartog, Melissa A. Haltuch, Yan Xue, Isaac C. Kaplan, Rebecca G. Asch, Gabriel A. Vecchi, Roland Séférian, Kirstin K. Holsman, Samantha A. Siedlecki, Kathleen Pegion, Thomas L. Delworth, Rym Msadek, Alistair J. Hobday, C. Mark Eakin, Timothy J. Miller, Patrick Lehodey, Charles A. Stock, Patrick D. Lynch, Marion Gehlen, Trond Kristiansen, Mark R. Payne, Ryan R. Rykaczewski, Jameal F. Samhouri, Carlos F. Gaitan, Andrew J. Pershing, Malin L. Pinsky
Publikováno v:
Progress in Oceanography
Progress in Oceanography, 2017, 152, pp.15-49. ⟨10.1016/j.pocean.2016.12.011⟩
Progress in Oceanography, Elsevier, 2017, 152, pp.15-49. ⟨10.1016/j.pocean.2016.12.011⟩
Tommasi, D, Stock, C A, Hobday, A J, Methot, R, Kaplan, I C, Paige Eveson, J, Holsman, K, Miller, T J, Gaichas, S, Gehlen, M, Pershing, A, Vecchi, G A, Msadek, R, Delworth, T, Mark Eakin, C, Haltuch, M A, Séférian, R, Spillman, C M, Hartog, J R, Siedlecki, S, Samhouri, J F, Muhling, B, Asch, R G, Pinsky, M L, Saba, V S, Kapnick, S B, Gaitan, C F, Rykaczewski, R R, Alexander, M A, Xue, Y, Pegion, K V, Lynch, P, Payne, M, Kristiansen, T, Lehodey, P & Werner, F E 2017, ' Managing living marine resources in a dynamic environment: the role of seasonal to decadal climate forecasts ', Progress in Oceanography, vol. 152, pp. 15-49 . https://doi.org/10.1016/j.pocean.2016.12.011
Progress in Oceanography, 2017, 152, pp.15-49. ⟨10.1016/j.pocean.2016.12.011⟩
Progress in Oceanography, Elsevier, 2017, 152, pp.15-49. ⟨10.1016/j.pocean.2016.12.011⟩
Tommasi, D, Stock, C A, Hobday, A J, Methot, R, Kaplan, I C, Paige Eveson, J, Holsman, K, Miller, T J, Gaichas, S, Gehlen, M, Pershing, A, Vecchi, G A, Msadek, R, Delworth, T, Mark Eakin, C, Haltuch, M A, Séférian, R, Spillman, C M, Hartog, J R, Siedlecki, S, Samhouri, J F, Muhling, B, Asch, R G, Pinsky, M L, Saba, V S, Kapnick, S B, Gaitan, C F, Rykaczewski, R R, Alexander, M A, Xue, Y, Pegion, K V, Lynch, P, Payne, M, Kristiansen, T, Lehodey, P & Werner, F E 2017, ' Managing living marine resources in a dynamic environment: the role of seasonal to decadal climate forecasts ', Progress in Oceanography, vol. 152, pp. 15-49 . https://doi.org/10.1016/j.pocean.2016.12.011
Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff07a6a1ea71f3d8bb0db840acd07cc9
https://hal.science/hal-03112989/document
https://hal.science/hal-03112989/document
Publikováno v:
The Journal of Agricultural Science. 153:399-410
SUMMARYForecasting the maize yield of China's Jilin province from 1962 to 2004, with climate conditions and fertilizer as predictors, was investigated using multiple linear regression (MLR) and non-linear artificial neural network (ANN) models. Yield