A simple graphical method for displaying structured population dynamics and STdiag, its implementation in an R package
Keywords:
Demography, temporal dynamics, long-term studies, graphical displayAbstract
In demography, a detailed study of the temporal dynamics of the structure of a population is often required to better understand the processes that underline its overall dynamics and the individual’s life histories. Heatmaps, using time and structure (such as size-structure) as x and y coordinates and density as colours, are efficient tools for displaying the dynamics of a structured population. Such representations (structure-time diagrams) reveal the data at several levels, from general outlook to fine details. Despite its efficiency, this type of visual display has been scarcely used in ecology and demography. Using the example of springtail populations maintained in the laboratory and a woodlouse population studied in the field, we explain why this type of representation can be used to analyse the population dynamics of soil organisms and why it should be more widely used in demography. We also present the R package STdiag (for ‘Structure Time diagram’), an interface to complex graphical functions to easily produce and analyse such ‘structure-time diagrams’ from raw datasets. This package is available for all operating systems via R-Forge. Its syntax and options are described, discussed and illustrated using our case studies. This graphical display is a simple and efficient way to make large demographic datasets coherent and to disclose the underlying, often hidden, demographical processes.
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References
Andreev, K. F. (2000): Sex differentials in survival in the Canadian population, 1921-1997: A descriptive analysis with focus on age-specific structure. – Demographic Research 3: 1–18.
Anscombe, F. J. (1973): Graphs in statistical analysis. – The American Statistician 27: 17–21.
Baron, J. P., J. F. Le Galliard, T. Tully & R. Ferrière (2010): Cohort variation in offspring growth and survival: prenatal and postnatal factors in a late-maturing viviparous snake. – The Journal of Animal Ecology 79: 640–649.
Benton, T. G., S. J. Plaistow & T. N. Coulson (2006): Complex population dynamics and complex causation: devils, details and demography. – Proceedings of the Royal Society of London Series B, Biological Sciences 273: 1173–1181.
Benton, T. G., J. J. H. St Clair & S. J. Plaistow (2008): Maternal effects mediated by maternal age: from life histories to population dynamics. – Journal of Animal Ecology 77: 1038–1046.
Carey, J. R., L. G. Harshman, P. Liedo, H. G. Müller, J. L. Wang & Z. Zhang (2008): Longevity-fertility trade-offs in the tephritid fruit fly, Anastrepha ludens, across dietary-restriction gradients. – Aging Cell 7: 470–477.
Carey, J. R., P. Liedo, J. R. Carey, H. Müller, J. Wang & J. W. Vaupel (1998): A simple graphical technique for displaying individual fertility data and cohort survival: case study of 1000 Mediterranean Fruit Fly females. – Functional Ecology 12: 359–363.
Erlangsen, A., U. Bille-Brahe & B. Jeune (2003): Differences in suicide between the old and the oldest old. – The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 58: 314–322.
Fountain, M. T. & S. P. Hopkin (2005): Folsomia candida (Collembola): a ‘standard’ soil arthropod. – Annual Review of Entomology 50: 201–222.
Furrer, R., D. Nychka & S. Sain (2012): fields: Tools for spatial data. URL http://CRAN.R-project.org/package=fields.
Færøvig, P. J., T.Andersen & D. O. Hessen (2002): Image analysis of Daphnia populations: non-destructive determination of demography and biomass in cultures. – Freshwater Biology 47: 1956–1962.
Hassall, M. & J. M. Dangerfield (1990): Density-dependent processes in the population dynamics of Armadillidium vulgare (Isopoda: Oniscidae). – Journal of Animal Ecology, 59: 941–958.
Le Bourlot, V., T. Tully & D. Claessen (2014): Interference versus exploitative competition in the regulation of size-structured populations. – The American Naturalist 184: 609–623.
Le Galliard, J. F., J. M. Guarini & F. Gaill (2012): Sensors for ecology. Towards integrated knowledge of ecosystems. – CNRS Institut Ecologie et Environnement edn, CNRS, Paris.
Madsen, T. & R. Shine (2000): Rain, fish and snakes: climatically driven population dynamics of Arafura filesnakes in tropical Australia. – Oecologia 124: 208–215.
Mallard, F., M. Farina & T. Tully (2015): Within species variation in long-term trajectories of growth, fecundity and mortality in the Collembola Folsomia candida. – Journal of Evolutionary Biology, Epub: 1–9.
Mallard, F., V. Le Bourlot & T. Tully (2012): Automatic particle analysis as sensors for life history studies in experimental microcosms. – In: J. Le Galliard, J. M. Guarini & F. Gaill (eds): Sensors for ecology, towards integrated knowledge of ecosystems. – CNRS, Paris: 163–182.
Mallard, F., V. Le Bourlot & T. Tully (2013): An automated image analysis system to measure and count organisms in laboratory microcosms. – PloS One 8: e64387.
Marquis, O., M. Massot & J. F. Le Galliard (2008): Intergenerational effects of climate generate cohort variation in lizard reproductive performance. – Ecology 89: 2575–2583.
Mugabo, M., O. Marquis, S. Perret & J. F. Le Galliard (2010): Immediate and delayed life history effects caused by food deprivation early in life in a short-lived lizard. – Journal of Evolutionary Biology 23: 1886–1898.
Nelson, A., N. Bjornstad & T. Yamanaka (2013): Recurrent insect outbreaks caused by temperature-driven changes in system stability. – Science 341: 796–799.
Ohlberger, J., E. Edeline, L. A. Vøllestad, N. C. Stenseth & D. Claessen (2011): Temperature-driven regime shifts in the dynamics of size-structured populations. – The American Naturalist 177: 211–223.
Ohlberger, J., J. Otero, E. Edeline, I. J. Winfield, N. C. Stenseth & L. A. Vøllestad (2013): Biotic and abiotic effects on cohort size distributions in fish. – Oikos 122: 835–844.
Ozgul, A., S. Tuljapurkar, T. G. Benton, J. M. Pemberton, T. H. Clutton-Brock & T. Coulson (2009): The dynamics of phenotypic change and the shrinking sheep of St. Kilda. – Science 325: 464–467.
Plaistow, S. J. & T. G. Benton (2009): The influence of context-dependent maternal effects on population dynamics: an experimental test. – Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 364: 1049–1058.
Sarkar, D. (2008): Lattice: multivariate data visualization with R. Use R. – Springer, New York.
Schrautzer, J., A. Fichtner, A. Huckauf, L. Rasran & K. Jensen (2011): Long-term population dynamics of Dactylorhiza incarnata (L.) Soó after abandonment and re-introduction of mowing. – Flora 206: 622–630.
The R Development Core Team (2012): R: a Language and Environment for Statistical Computing. – R foundation for statistical computing, Vienna, Austria [http://www.R-project.org/].
Tufte, E. R. (1990): Envisioning information. 11th edn. – Graphics Press, Cheshire, Connecticut.
Tufte, E. R. (2001): The visual display of quantitative information. 2nd edn. – Graphics Press, Cheshire, Connecticut.
Tully, T. & R. Ferrière (2008): Reproductive flexibility: genetic variation, genetic costs and long-term evolution in a collembola. – PloS One 3: e3207.
Vaupel, J. W., B. A. Gambill & A. I. Yashin (1987): Thousands of data at a glance: shaded contour maps of demographic surfaces. – International Institute for Applied Systems Analysis, Laxenburg, Austria.
Vaupel, J. W., W. Zhenglian, K. F. Andreev & A. I. Yashin (1997): Population data at a glance: Shaded contour maps of demographic surfaces over age and time. – Odense University Press, Odense, Denmark.
Vaupel, J. W., J. R. Carey, K. Christensen, T. E. Johnson, A. I. Yashin, N. V. Holm, I. A. Iachine, V. Kannisto, A. A. Khazaeli, P. Liedo, V. D. Longo, Y. Zeng, K. G. Manton & J. W. Curtsinger (1998): Biodemographic trajectories of longevity. – Science 280: 855–860.
Venables, W. N. & B. D. Ripley (2002): Modern applied statistics with S. – Springer, New York.
Wickham, H. (2009): ggplot2: Elegant Graphics for Data Analysis. Use R. – Springer, New York.
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