`a`
Mathematical Biosciences and Engineering (MBE)
 

An adaptive feedback methodology for determining information content in stable population studies
Pages: 653 - 671, Issue 4, August 2016

doi:10.3934/mbe.2016013      Abstract        References        Full text (1124.3K)           Related Articles

H. T. Banks - Center for Research in Scientific Computation, North Carolina State University, Raleigh, NC 27695-8212, United States (email)
John E. Banks - Undergraduate Research Opportunities Center (UROC), California State University, Monterey Bay, United States (email)
R. A. Everett - Center for Research in Scienti c Computation, North Carolina State University, Raleigh, NC 27695-8212, United States (email)
John D. Stark - Ecotoxicology Program, WSU Puyallup Research, Extension Center, Puyallup, WA 98371-4998, United States (email)

1 K. Adoteye, H. T. Banks, K. Cross, S. Eytcheson, K. B. Flores, G. A. LeBlanc, T. Nguyen, C. Ross, E. Smith, M. Stemkovski and S. Stokely, Statistical validation of structured population models for Daphnia magna, Mathematical Biosciences, 266 (2015), 73-84.       
2 K. Adoteye, H. T. Banks, K. B. Flores and G. A. LeBlanc, Estimation of time-varying mortality rates using continuous models for Daphnia magna, Applied Mathematical Letters, 44 (2015), 12-16.       
3 H. T. Banks, J. E. Banks, L. K. Dick and J. D. Stark, Estimation of dynamic rate parameters in insect populations undergoing sublethal exposure to pesticides, Bulletin of Mathematical Biology, 69 (2007), 2139-2180.       
4 H. T. Banks, J. E. Banks, R. Everett and J. Stark, An Adaptive Feedback Methodology for Determining Information Content in Population Studies, CRSC-TR15-12, Center for Research in Scientific Computation, N. C. State University, Raleigh, NC, November, 2015.
5 H. T. Banks, J. E. Banks, S. J. Joyner and J. D. Stark, Dynamic models for insect mortality due to exposure to insecticides, Mathematical and Computer Modeling, 48 (2008), 316-332.       
6 J. E. Banks, L. K. Dick, H. T. Banks and J. D. Stark, Time-varying vital rates in ecotoxicology: Selective pesticides and aphid population dynamics, Ecological Modeling, 210 (2008), 155-160.
7 H. T. Banks, S. Hu and W. C. Thompson, Modeling and Inverse Problems in the Presence of Uncertainty, CRC Press, New York, 2014.       
8 H. T. Banks and H. T. Tran, Mathematical and Experimental Modeling of Physical and Biological Processes, CRC Press, New York, 2009.       
9 J. R. Carey, Applied Demography for Biologists with Special Emphasis on Insects, Oxford University Press, Oxford, 1993.
10 V. E. Forbes and P. Calow, Is the per capita rate of increase a good measure of population-level effects in ecotoxicology? Environmental Toxicology and Chemistry, 18 (1999), 1544-1556.
11 V. E. Forbes and P. Calow, Extrapolation in ecological risk assessment: Balancing pragmatism and precaution in chemical controls legislation, Bioscience, 52 (2002), 249-257.
12 V. E. Forbes and P. Calow, Population growth rate as a basis for ecological risk assessment of toxic chemicals, Philosophical Transaction of the Royal Society, London, B: Biological Sciences, 357 (2002), 1299-1306.
13 N. Hanson and J. D. Stark, A comparison of simple and complex population models to reduce uncertainty in ecological risk assessments of chemicals: Example with three species of Daphnia, Ecotoxicology, 20 (2011), 1268-1276.
14 N. Hanson and J. D. Stark, Utility of population models to reduce uncertainty and increase value relevance in ecological risk assessments of pesticides: An example based on acute mortality data for Daphnids, Integrated Environmental Assessment and Management, 8 (2012), 262-270.
15 U. Hommen, J. M. Baveco, N. Galic and P. J. van den Brink, Potential application of ecological models in the European environmental risk assessment of chemicals I: review of protection goals in EU directives and regulations, Integrated Environmental Assessment and Management, 6 (2010), 325-337.
16 M. Kot, Elements of Mathematical Ecology, Cambridge University Press, Cambridge, 2001.       
17 J. D. Stark and J. E. Banks, Developing Demographic Toxicity Data: Optimizing Effort for Predicting Population Outcomes, PeerJ, submitted, 2015.

Go to top