Statistical Demography (Fernando Colchero)
Description
Our research is focused on two main areas: first, the development of statistical and mathematical models for demography and population dynamics; and second, the application of these models to understand the diversity of demographic and life-history strategies among primates and other species. We are particularly interested in developing inference models for demography that can be used across a broad range of species. Through comparative demographic analyses, we aim to explore how differences in demographic rates impact population dynamics and demographic senescence.
Projects
Bayesian inference methods for demography: We developed the Bayesian Survival Trajectory Analysis framework to make inference on age-specific survival when individual times of birth are missing. The approach is formalized in the R package BaSTA (Colchero et al. 2012, Colchero & Clark 2012, Colchero et al. 2021). Similarly, we are currently extending our demographic toolkit to Bayesian Fertility Trajectory Analysis (BaFTA) for inference on age-specific fertility using models developed in other disciplines.
Comparative biodemography: We use the methods developed in our group to explore the evolution of life-history strategies. For instance, we are analyzing one of the largest datasets on individual longevity from captive animals to explore the evolution of sex differences in longevity among mammals and birds. We are also studying the effect of hormonal and surgical contraception on longevity among mammals.
Evolution of Ageing: We are interested in understanding the evolutionary and proximal mechanisms that determine ageing patterns among primates and other groups.
Staff
Group Leader
Postdoc
Technical Staff
Eric Johnson
Research Assistant
Jad Daou
Relevant publications
Colchero, F. (Under review) Inference on age-specific fertility in ecology and evolution. Learning from other disciplines and improving the state of the art.
da Silva, R., D.A. Conde, A. Baudisch, F. Colchero (2022) Slow and negligible senescence among testudines challenge evolutionary theories of senescence. Science 376 (6600): 1466-1470
Vincze, O., F. Colchero, J.-F. Lemaître, D.A. Conde, S. Pavard, M. Bieuville, J.A. Teare, A.O. Urrutia, B. Ujvari, F. Thomas, M. Giraudeau (2022) Cancer risk across mammals. Nature 601(7892):263-267
Colchero, F., J.M. Aburto, E.A. Archie, C. Boesch, T. Breuer, F.A. Campos, A. Collins, D.A. Conde, M. Cords, C. Crockford, M.E. Thompson, L.M. Fedigan, C. Fichtel, M. Groenenberg, C. Hobaiter, P.M. Kappeler, R.R. Lawler, R.J. Lewis, Z.P. Machanda, M.L. Manguette, M.N. Muller, Craig Packer, R.J. Parnell, S. Perry, A.E. Pusey, M.M. Robbins, R.M. Seyfarth, J.B. Silk, J. Staerk, T.S. Stoinski, E.J. Stokes, K.B. Strier, S.C. Strum, J. Tung, F. Villavicencio, R.M. Wittig, R.W. Wrangham, K. Züberbuhler, J.W. Vaupel, S.C. Alberts (2021) The long lives of primates and the "invariant rate of aging" hypothesis. Nature Communications 12:3666
Colchero, F., W. Eckardt, T. Stoinski (2021) Evidence of demographic buffering in an endangered great ape: social buffering on immature survival and the role of refined sex-age-classes on population fitness. Journal of Animal Ecology 90(7):1701-1713
Lemaître, J.-F., V. Ronget, M. Tidière, D. Allainé, V. Berger, A. Cohas, F. Colchero, D.A. Conde, A. Liker, G. Marais, A. Scheuerlein, T. Székely, J.-M. Gaillard (2020) Sex differences in longevity and aging rates across wild mammals. PNAS 117(15):8546-8553
Colchero, F. and B.Y. Kiyakoglu (2020) Beyond the proportional frailty model: Bayesian estimation of individual heterogeneity in mortality parameters. Biometrical Journal 62(1):124-135
Staerk, J., D.A. Conde, V. Ronget, J.-F. Lemaître, J-M. Gaillard and F. Colchero (2019) Performance of generation time approximations for extinction risk assessments. Journal of Applied Ecology 56(6): 1436-1446
Colchero, F., O.R. Jones, D.A. Conde, D. Hodgson, F. Zajitschek, B.R. Schmidt, A.F. Malo, S.C. Alberts, P.H. Becker, S. Bouwhuis, A.M. Bronikowski, K.M. De Vleeschouwer, R.J. Delahay, S. Dummermuth, E. Fernández-Duque, J. Frisenvæatnge, M. Hesselsøe, S. Larson, J.-F. Lemaître, J. McDonald, D.A.W. Miller, C. O'Donnell, C. Packer, B.E. Raboy, C.J. Reading, E. Wapstra, H. Weimerskirch, G.M. While, A. Baudisch, T. Flatt, T. Coulson and J.-M. Gaillard (2019) The diversity of population responses to environmental change. Ecology Letters 22(2): 342-353
Colchero, F., R. Rau, O.R. Jones, J. Barthold, D.A. Conde, A. Lenart, L. Nemeth, A. Scheuerlein, J. Schoeley, C. Torres, V. Zarulli, J. Altmann, D.K. Brockman, A.M. Bronikowski, L.M. Fedigan, A. Pusey, T.S. Stoinski, K.B. Strier, A. Baudisch, S.C. Alberts and J.W. Vaupel (2016) The emergence of longevous populations. PNAS 113 (48): E7681-E7690
Barthold, J., A. Loveridge, D. W. Macdonald, C. Packer, F. Colchero (2016) Bayesian estimates of male and female African lion mortality for future use in population management. Journal of Applied Ecology 53: 295-304
Colchero, F. and R. Schaible (2014) Mortality as a bivariate function of age and size in indeterminate growers. Ecosphere 5(12): 161
Colchero, F., O.R. Jones and M. Rebke (2012) BaSTA: an R package for Bayesian estimation of age-specific survival from incomplete mark-recapture/recovery data with covariates. Methods in Ecology and Evolution 3: 466-470
Colchero, F. and James S. Clark (2012) Bayesian inference on age-specific survival for censored and truncated data. Journal of Animal Ecology 81: 139-149
Software
We develop R packages for demographic and comparative analyses:
- BaSTA: Bayesian Survival Trajectory Analysis. Inference on age-specific fertility for capture-mark-recapture data with truncated and censored records and for which times of birth and/or death might be missing for some individuals.
- paramDemo: parametric functions for age-specific survival and fertility. The package includes functions to calculate product limit estimators.
- CreateRproj: Functions to create an R project directory or an R package directory, allowing to start an Rstudio project and a Git repository.
- BayesPGLS: Functions to carry out Bayesian phylogenetic least squares.