Przykłady interaktywnych symulacji dotyczących ochrony środowiska

1. https://worldpopulationhistory.org/map/1/mercator/1/0/25/

2. https://www.ined.fr/en/everything_about_population/population-games/tomorrow-population/

3. https://ourworldindata.org/meat-and-seafood-production-consumption

4. https://climate.nasa.gov/interactives/climate-time-machine

5. https://www.climateinteractive.org/

6. https://scied.ucar.edu/interactives

Przykłady publikacji wykorzystujących modelowanie w ochronie środowiska

1. Heesterbeek, H., R. M. Anderson, V. et al. (2015) Modeling infectious disease dynamics in the complex landscape of global health. Science 347:aaa4339.

2. Hertwich, E. G., T. Gibon, E. A. et al. (2015) Integrated life-cycle assessment of electricity-supply scenarios confirms global environmental benefit of low-carbon technologies. Proceedings of the National Academy of Sciences 112:6277-6282.

3. Lelieveld, J., J. S. Evans, M. Fnais, D. Giannadaki, and A. Pozzer. (2015) The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525:367.

4. Wilcox, C., E. Van Sebille, and B. D. Hardesty. (2015) Threat of plastic pollution to seabirds is global, pervasive, and increasing. Proceedings of the National Academy of Sciences 112:11899-11904.

5. Arntzen J. W. (2006) From descriptive to predictive distribution models: a working example with Iberian amphibians and reptiles. Frontiers in Zoology 3:8

6. Azuma T., Nakada N., Yamashita N., Tanaka H. (2015) Prediction, risk and control of anti-influenza drugs in the Yodo River Basin, Japan during seasonal and pandemic influenza using the transmission model for infectious disease. Science of the Total Environment 521–522, pp. 68–74

7. Brown M. L., Donovan T. M., Schwenk W. S., Theobald D. M. (2014) Predicting impacts of future human population growth and development on occupancy rates of forest-dependent birds. Biological Conservation. 170 pp. 311–320

8. Chang F-J., Tsai Y-H., Chen P-A., Coynel A., Vachaud G. (2015) Modelling water quality in an urban river using hydrological factors e Data driven approaches. Journal of Environmental Management 151, pp. 87-96

9. Eisenberg et al (2012). In-roads to the spread of antibiotic resistance: regional patterns of microbial transmission in northern coastal Ecuador. J. R. Soc. Interface 9 1029-1039.

10. Fechter D., Storch I. (2014) How many wolves (Canis lupus) fit into Germany? The role of assumptions in predictive rule-based habitat models for habitat generalists. PLoS ONE 9(7): e101798

11. Feio M. J., Reynoldson T. B., Ferreira V., Augusto M., Graca S. (2007) A predictive model for freshwater bioassessment (Mondego River, Portugal). Hydrobiologia 589,pp. 55–68

12. Fernández, N., Selva, N., Yuste, C., Okarma, H., Jakubiec, Z. (2012) Brown bears at the edge: Modeling habitat constrains at the periphery of the Carpathian population. Biological Conservation, 153, pp. 134-142.

13. Galetti M., Guevara R., Côrtes M. C., Fadini R., Von Matter S., Leite A. B., Labecca F., Ribeiro T., Carvalho C. S., Collevatti R. G., Pires M. M., Guimarães Jr. P. R., Brancalion P. H., Ribeiro M. C., Jordano P. (2013) Functional extinction of birds drives rapid evolutionary changes in seed size. Science 30, pp. 1086 – 1090

14. Gerland P., Raftery A. E., Ševčíková H., Li N., Gu D., Spoorenberg T., Alkema L., Fosdick B. K., Chunn J., Lalic N., Bay G., Buettner T, Heilig G. K., Wilmoth J. (2014) World population stabilization unlikely this century. Science 346 (6206), pp. 234-237 (+ supplementary materials)

15. Kennard M. J., Pusey B. J., Arthington A. H., Harch B. D., Mackay S. J. (2006) Development and application of a predictive model of freshwater fish assemblage composition to evaluate river health in eastern Australia. Hydrobiologia 572, pp. 33–57

16. Latham M. C., Latham A. D. M., Webb N. F., Mccutchen N. A., Boutin S. (2014) Can occupancy abundance models be used to monitor wolf abundance? PLoS ONE 9(7), e102982

17. Nfon, E., Armitage, J.M., Cousins, I.T. (2011) Development of a dynamic model for estimating the food web transfer of chemicals in small aquatic ecosystems. Science of the Total Environment, 409 (24), pp. 5416-5422.

18. Plotkin J. B., Potts M. D. , Yud D. W., Bunyavejchewin S., Conditf R., Fosterg R., Hubbellh S., LaFrankie J., Manokaran N., Leek H-S., Sukumar R., Nowak M. A., Ashton P. S. (2001) Predicting species diversity in tropical forests. PNAS 98 (2), pp. 10850–10854

19. Ron, S. R. (2005) Predicting the distribution of the amphibian pathogen Batrachochytrium dendrobatidis in the New World. Biotropica, 37(2), 209-221.

20. Sahlean, T. C., Gherghel, I., Papeş, M., Strugariu, A., & Zamfirescu, Ş. R. (2014) Refining climate change projections for organisms with low dispersal abilities: a case study of the Caspian whip snake. PloS one, 9(3), e91994.

21. Samso R., Blazquez J., Agullo N., Grau J., Torres R., Garcia J. (2015) Effect of bacteria density and accumulated inert solids on the effluent pollutant concentrations predicted by the constructed wetlands model BIO PORE. Ecological Engineering 80. pp.172–180

22. Santos, X., Brito, J. C., Caro, J., Abril, A. J., Lorenzo, M., Sillero, N., & Pleguezuelos, J. M. (2009). Habitat suitability, threats and conservation of isolated populations of the smooth snake (Coronella austriaca) in the southern Iberian Peninsula. Biological Conservation, 142(2), 344-352.

23. Sasina N. V., Smith J. T., Kudelsky A. V., Wright S. M. (2007) ‘‘Blind’’ testing of models for predicting the 90Sr activity concentration in river systems using post-Chernobyl monitoring data. Journal of Environmental Radioactivity 92, pp. 63e71

24. Vörösmarty, C.J., Green, P., Salisbury, J., Lammers, R.B. (2000) Global water resources: Vulnerability from climate change and population growth. Science, 289 (5477), pp. 284-288.