СТОХАСТИЧНИ МОДЕЛИ И СОФТУЕРНИ ТЕХНОЛОГИИ В ЕКОЛОГИЧНИТЕ ИЗСЛЕДВАНИЯ
Ключови думи :
Bayesian statistics, ecological software, real-time Black Sea monitoringАбстракт
In the past years with the increaseing computing power and use of software solutions, Bayesian statistics has become a powerful alternative to traditional statistics. This paper presents the use of the Bayesian method in ecological research and environmental decision-making. Additionally, attention is to new technologies as a tool for collecting and analyzing data, as well as to the capabilities of new real-time monitoring technologies on the Black Sea.
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Литература (библиография)
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[3] Ellison Aaron M., Bayesian inference in ecology, Ecology Letters, 7, 2004, 509–520.
[4] van Gils, J. A., State-dependent Bayesian foraging on spatially auto-correlated food distributions, OIKOS, vol. 119, Issue2, February 2010, 237-244.
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[11] http://blacksea.grid.unep.ch
[12] http://www.ecostats.com/web/Biotas
[13] http://www.cebm.brown.edu/openmee/index.html
[14] https://misbs.bgports.bg/bg/climate-and-weather
[15] https://biostat-2009.soft32.com
[16] http://ntsyspc.software.informer.com
[17] www.metawinsoft.com
[2] Dall, Sasha R.X., Luc-Alain Giraldeau, Ola Olsson, John M. McNamara, David W. Stephens, Information and its use by animals in evolutionary ecology, Trends Ecol. Evol., 20, 2005, 187-193.
[3] Ellison Aaron M., Bayesian inference in ecology, Ecology Letters, 7, 2004, 509–520.
[4] van Gils, J. A., State-dependent Bayesian foraging on spatially auto-correlated food distributions, OIKOS, vol. 119, Issue2, February 2010, 237-244.
[5] Hooten M. B., N. T. Hobbs, A guide to Bayesian model selection for ecologists, Ecological monographs, vol. 85, Issue 1, February 2015, 3-28.
[6] Klomp N. I., D. G.Green, G. Fry, Roles of technology in ecology, In N. Klomp, & I. Lunt (Eds.), Frontiers in ecology: Building the links, Oxford: Elsevier, 1997, 299-309.
[7] Lehmann Anthony, Yaniss Guigoz, Nicolas Ray, Emanuele Mancosu, Karim C. Abbaspour, Elham Rouholahnejad Freund, Karin Allenbach, Andrea De Bono, Marc Fasel, Ana Gago-Silva, Roger Bär, Pierre Lacroix, Gregory Giuliani, A web platform for landuse, climate, demography, hydrology and beach erosion in the Black Sea catchment, Scientific Data, 4 July 2017, 1-15.
[8] Mislan K.A.S., Jeffrey M.Heer, Ethan P.White, Elevating The Status of Code in Ecology, Trends in Ecology & Evolution, vol. 31, Issue 1, January 2016, Pages 4-7
[9] Ovaskainen Otso, Gleb Tikhonov, Anna Norberg, F. Guillaume Blanchet, Leo Duan, David Dunson, Tomas Roslin, Nerea Abrego, How to make more out of community data? A conceptual framework and its implementation as models and software, Ecology Letters, vol. 20, Issue 5, May 2017, 561-576
[10] Wallac Byron C., Marc J. Lajeunesse, George Dietz, Issa J. Dahabreh, Thomas A. Trikalinos, Christopher H. Schmid, Jessica Gurevitch, OpenMEE: Intuitive, open‐source software for meta‐analysis in ecology and evolutionary biology, Methods in Ecology and Evolution, vol. 8, Issue 8, August 2017, 941-947.
[11] http://blacksea.grid.unep.ch
[12] http://www.ecostats.com/web/Biotas
[13] http://www.cebm.brown.edu/openmee/index.html
[14] https://misbs.bgports.bg/bg/climate-and-weather
[15] https://biostat-2009.soft32.com
[16] http://ntsyspc.software.informer.com
[17] www.metawinsoft.com
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Публикуван
2018-07-21
Брой
Раздел (Секция)
Конференция на БСУ „Синя икономика и синьо развитие“. ISBN 978-619-7126-57-0
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Статиите публикувани в списание КНК са лицензирани под Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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СТОХАСТИЧНИ МОДЕЛИ И СОФТУЕРНИ ТЕХНОЛОГИИ В ЕКОЛОГИЧНИТЕ ИЗСЛЕДВАНИЯ. (2018). КОМПЮТЪРНИ НАУКИ И КОМУНИКАЦИИ, 7(1), 93-99. https://csc.bfu.bg/index.php/CSC/article/view/213
