An algorithm for data reconstruction from published articles – Application on insect life tables

References

• Bellows, T. S., Jr, Van Driesche, R. G., & Elkinton, J. S. (1992). Life-table construction and analysis in the evaluation of natural enemies. Annual Review of Entomology, 37, 587–19. doi:10.1146/annurev.en.37.010192.003103
   Web of Science ®Google Scholar
• Broyden, C. G. (1965). A class of methods for solving nonlinear simultaneous equations. Mathematics of Computation, 19, 577–593. doi:10.1090/S0025-5718-1965-0198670-6
   Web of Science ®Google Scholar
• Carey, J. R. (2001). Insect biodemography. Annual Review of Entomology, 46, 79–110. doi:10.1146/annurev.ento.46.1.79
   PubMed Web of Science ®Google Scholar
• Deevey, E. S. (1947). Life tables for natural populations of animals. The Quarterly Review of Biology, 22, 283–314. doi:10.1086/395888
   PubMed Web of Science ®Google Scholar
• Diamond, S. E., & Kingsolver, J. G. (2009). Environmental dependence of thermal reaction norms: Host plant quality can reverse the temperature-size rule. The American Naturalist, 175, 1–10. doi:10.1086/648602
   Web of Science ®Google Scholar
• Dublin, L. I., Lotka, A. J., & Spiegelman, M. (1950). Length of life (Revised ed.). JSTOR.
   Google Scholar
• Ediev, D., & Gisser, R. (2007). Reconstruction of historical series of life tables and of age-sex structures for the Austrian population in the 19th and the first half of the 20th century. Vienna Yearbook of Population Research, 2007, 327–355. doi:10.1553/populationyearbook
   Google Scholar
• Er, M. C. (1984). Sums of Fibonacci numbers by matrix methods. Fibonacci Quarterly, 22, 204–207.
   Web of Science ®Google Scholar
• Falcón, S., & Plaza, Á. (2007). The k-Fibonacci sequence and the Pascal 2-triangle. Chaos, Solitons, and Fractals, 33, 38–49. doi:10.1016/j.chaos.2006.10.022
   Web of Science ®Google Scholar
• Falcon, S., & Plaza, A. (2007). On the Fibonacci k-numbers. Chaos, Solitons, and Fractals, 32, 1615–1624. doi:10.1016/j.chaos.2006.09.022
   Web of Science ®Google Scholar
• Fand, B. B., Tonnang, H. E., Kumar, M., Kamble, A. L., & Bal, S. K. (2014). A temperature-based phenology model for predicting development, survival and population growth potential of the mealybug, Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae). Crop Protection, 55, 98–108. doi:10.1016/j.cropro.2013.10.020
   Web of Science ®Google Scholar
• Gompertz, B. (1825). On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philosophical Transactions of the Royal Society of London, 115, 513–583. doi:10.1098/rstl.1825.0026.
   Google Scholar
• Gordh, G., & Headrick, D. (2001). A dictionary of entomology. New York, NY: Oxon (CABI Publishing). ISBN 0‐85199‐291‐9 (hardcover). doi: 10.1002/mmnz.20020780210
   Google Scholar
• Haavelmo, T. (1943). The statistical implications of a system of simultaneous equations. Journal of Economic Entomology, 11(1), 1–12.
   Google Scholar
• Horadam, A. F. (1961). A generalized Fibonacci sequence. The American Mathematical Monthly, 68, 455–459. doi:10.1080/00029890.1961.11989696
   Web of Science ®Google Scholar
• Kahneman, D., Krueger, A. B., Schkade, D. A., Schwarz, N., & Stone, A. A. (2004). A survey method for characterizing daily life experience: The day reconstruction method. Science, 306, 1776–1780. doi:10.1126/science.1103572
   PubMed Web of Science ®Google Scholar
• Khadioli, N., Tonnang, Z. E. H., Muchugu, E., Ong’amo, G., Achia, T., Kipchirchir, I., … Le Ru, B. (2014a). Effect of temperature on the phenology of Chilo partellus (Swinhoe)(Lepidoptera, Crambidae); simulation and visualization of the potential future distribution of C. partellus in Africa under warmer temperatures through the development of life-table parameters. Bulletin of Entomological Research, 104, 809–822.
   Web of Science ®Google Scholar
• Khadioli, N., Tonnang, Z. E. H., Ong’amo, G., Achia, T., Kipchirchir, I., Kroschel, J., & Le Ru, B. (2014b). Effect of temperature on the life history parameters of noctuid lepidopteran stem borers, Busseola fusca and Sesamia calamistis. The Annals of Applied Biology, 165, 373–386. doi:10.1111/aab.12157
   Web of Science ®Google Scholar
• Kita, M. W. (1993). Getting the most from incomplete data: Some things are solved, others are not. Journal of Insurance Medicine, 25(2). Retrieved from https://aaimedicine.org/journal-of-insurance-medicine/jim/1993/025-02-0149.pdf
   Google Scholar
• Potter, K., Davidowitz, G., & Woods, H. A. (2009). Insect eggs protected from high temperatures by limited homeothermy of plant leaves. Journal of Experimental Biology, 212, 3448–3454. doi:10.1242/jeb.033365
   Web of Science ®Google Scholar
• Richards, O. W., Waloff, N., & Spradbery, J. P. (1960). The measurement of mortality in an insect population in which recruitment and mortality widely overlap. Oikos, 11, 306–310. doi:10.2307/3564689
   Google Scholar
• Schoolfield, R. M., Sharpe, P. J. H., & Magnuson, C. E. (1981). Non-linear regression of biological temperature-dependent rate models based on absolute reaction-rate theory. Journal of Theoretical Biology, 88, 719–731. doi:10.1016/0022-5193(81)90246-0
   PubMed Web of Science ®Google Scholar
• Sharpe, P. J., Curry, G. L., DeMichele, D. W., & Cole, C. L. (1977). Distribution model of organism development times. Journal of Theoretical Biology, 66, 21–38. doi:10.1016/0022-5193(77)90309-5
   Web of Science ®Google Scholar
• Sporleder, M., Kroschel, J., Quispe, M. R. G., & Lagnaoui, A. (2004). A temperature-based simulation model for the potato tuberworm, Phthorimaea operculella Zeller (Lepidoptera; Gelechiidae). Environmental Entomology, 33, 477–486. doi:10.1603/0046-225X-33.3.477
   Web of Science ®Google Scholar
• Stephens, M., & Donnelly, P. (2003). A comparison of bayesian methods for haplotype reconstruction from population genotype data. American Journal of Human Genetics, 73(5), 1162–1169. doi: 10.1086/379378
   PubMed Web of Science ®Google Scholar
• Stephens, M., Smith, N. J., & Donnelly, P. (2001). A new statistical method for haplotype reconstruction from population data. American Journal of Human Genetics, 68(4), 978–989. doi: 10.1086/319501
   PubMed Web of Science ®Google Scholar
• Team, R.C. 2014. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2013. ISBN 3-900051-07-0.7.
   Google Scholar
• Tonnang, H. E. Z., Carhuapoma, P., Gonzales, J. C., Juarez, H., Kroschel, J., & Sporleder, M. (2013). Insect life cycle modelling (ILCYM) software - a new tool for regional and global insect pest risk assessments under current and future climate change scenarios. Potential Invasive Pests of Agricultural Crops, 23, 412. doi: 10.1079/9781845938291.0412
   Google Scholar
• Wagner, T. L., Wu, H.-I., Sharpe, P. J., Schoolfield, R. M., & Coulson, R. N. (1984). Modeling insect development rates: A literature review and application of a biophysical model. Annals of the Entomological Society of America, 77, 208–220. doi:10.1093/aesa/77.2.208
   Web of Science ®Google Scholar
• Welch, B. L. (1937). On the z-test in randomized blocks and Latin squares. Biometrika, 29, 21–52. doi:10.1093/biomet/29.1-2.21
   Google Scholar
• Woods, H. A. (2010). Water loss and gas exchange by eggs of Manduca sexta: Trading off costs and benefits. Journal of Insect Physiology, 56, 480–487. doi:10.1016/j.jinsphys.2009.05.020
   Web of Science ®Google Scholar
• Zellner, A., & Theil, H. (1962). Three-stage least squares: Simultaneous estimation of simultaneous equations. Journal of Economic Entomology, 30, 54–78.
   Google Scholar
• Zhang, W. (1997). Some identities involving the Fibonacci numbers. Fibonacci Quarterly, 35, 225–228.
   Web of Science ®Google Scholar