USGS Professional Pages
Research Statistician (Biology)Contact Info
PublicationsJohnson, F.A., R.M. Dorazio, T.D. Castellon, J. Martin, J.O. Garcia, and J.D. Nichols. 2014. Tailoring point counts for inference about avian density: dealing with nondetection and availability. Natural Resource Modeling 27: 163-177. [Link]
Dorazio, R.M. and E.F. Connor. 2014. Estimating abundances of interacting species using morphological traits, foraging guilds, and habitat. PLoS ONE 9: e94323. [Link]
Dorazio, R.M. 2014. Accounting for imperfect detection and survey bias in statistical analysis of presence-only data. Global Ecology and Biogeography DOI: 10.1111/geb.12216. [Link]
Dorazio, R.M., J. Martin, and H.H. Edwards. 2013. Estimating abundance while accounting for rarity, correlated behavior of animals, and other sources of variation in counts. Ecology 94: 1472-1478. [Link]
Hua, F., R.J. Fletcher Jr., K.E. Sieving, and R.M. Dorazio. 2013. Too risky to settle: avian community structure changes in response to perceived predation risk on adults and offspring. Proceedings of the Royal Society B 280: 20130762. [Link]
Dorazio, R.M. 2013. Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data. PLoS ONE 8: e84017. [Link]
Royle, J.A. and R.M. Dorazio. 2012. Parameter-expanded data augmentation for Bayesian analysis of capture-recapture models. Journal of Ornithology 152 (Supplement 2): S521--S537. [Link]
Shirley, M.H., R.M. Dorazio, E. Abassery, A. Elhady, M.S. Mekki, and H.H. Asran. 2012. A sampling design and model for estimating abundance of Nile crocodiles while accounting for heterogeneity of detectability of multiple observers. Journal of Wildlife Management 76: 966--975.
Pacifici, K., R.M. Dorazio, and M.J. Conroy. 2012. A two-phase sampling design for increasing detections of rare species in occupancy surveys. Methods in Ecology and Evolution 3: 721--730.
Dorazio, R.M. 2012. Predicting the geographic distribution of a species from presence-only data subject to detection errors. Biometrics 68: 1303--1312. [Link]
Dorazio, R.M. and D. Taylor Rodriguez. 2012. A Gibbs sampler for Bayesian analysis of site-occupancy data. Methods in Ecology and Evolution 3: 1093--1098. [Link]
Dorazio, R.M., N.J. Gotelli, and A.M. Ellison. 2011. Modern methods of estimating biodiversity from presence-absence surveys. In Biodiversity Loss in a Changing Planet, O. Grillo and G. Venora (eds.), InTech, ISBN 978-953-307-707-9. [Link]
Miller, M.W, E.V. Pearlstine, R.M. Dorazio, and F.J. Mazzotti. 2011. Occupancy and abundance of wintering birds in a dynamic agricultural landscape. Journal of Wildlife Management 75: 836--847.
Fujisaki, I., F.J. Mazzotti, R.M. Dorazio, K.G. Rice, M. Cherkiss, and B. Jeffery. 2011. Estimating trend in alligator populations from nightlight survey data. Wetlands 31: 147--155.
Langtimm, C.A., R.M. Dorazio, B.M. Stith, and T.J. Doyle. 2011. New aerial survey and hierarchical model to estimate manatee abundance. Journal of Wildlife Management 75: 399--412.
Walls, S.C., J.H. Waddle, and R.M. Dorazio. 2011. Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA. Journal of Wildlife Management 75: 751--761.
Oliveira-Santos, L.G.R., R.M. Dorazio, W.M. Tomas, G. Mourao, and F.A.S. Fernandez, 2011. No evidence of interference competition among the invasive feral pig and two native peccary species in a neotropical wetland. Journal of Tropical Ecology 27: 557--561.
Dorazio, R.M., M. Kery, J.A. Royle, and M. Plattner. 2010. Models for inference in dynamic metacommunity systems. Ecology 91: 2466--2475.
Waddle, J.H., R.M. Dorazio, S.C. Walls, K.G. Rice, J. Beauchamp, M.J. Schuman, and F.J. Mazzotti. 2010. A new parameterization for estimating co-occurrence of interacting species. Ecological Applications 20: 1467–-1475.
Gotelli, N.J., R.M. Dorazio, A.M. Ellison, and G.D. Grossman. 2010. Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models. Philosophical Transactions of the Royal Society, Series B 365: 3621--3631.
Kery, M.; Royle, J.A.; Plattner, M.; Dorazio, R.M., 2009. Species richness and occupancy estimation in communities subject to temporary emigration. Ecology 90: 1279-129.
Dorazio, R.M. 2009. On selecting a prior for the precision parameter of Dirichlet process mixture models. Journal of Statistical Planning and Inference 139: 3384-3390.
Kery, M., R.M. Dorazio, L. Soldaat, A. van Strien, A. Zuiderwijk,and J.A. Royle. 2009. Trend estimation in populations with imperfect detection. Journal of Applied Ecology 46: 1163--1172.
Rota, C. T., R.J. Fletcher Jr., R.M. Dorazio, and M.G. Betts. 2009. Occupancy estimation and the closure assumption. Journal of Applied Ecology 46: 1173--1181.
Royle, J.A. and R.M. Dorazio. 2008. Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities. Academic Press, San Diego. [Link]
Dorazio, R.M., B. Mukherjee, L. Zhang, M. Ghosh, H.L. Jelks, and F. Jordan. 2008. Modeling unobserved sources of heterogeneity in animal abundance using a Dirichlet process prior. Biometrics 64: 635--644.
Jordan, F., H.L. Jelks, S.A. Bortone, and R.M. Dorazio. 2008. Comparison of visual survey and seining methods for estimating abundance of an endangered, benthic stream fish. Environmental Biology of Fishes 81: 313--319.
Royle, J.A., R.M. Dorazio, and W.A. Link. 2007. Analysis of multinomial models with unknown index using data augmentation. Journal of Computational and Graphical Statistics 16: 1--19.
Hooten, M.B., C.K. Wikle, R.M. Dorazio, and J.A. Royle. 2007. Hierarchical spatio-temporal matrix models for characterizing invasions. Biometrics 63: 558--567.
Dorazio, R.M. 2007. On the choice of statistical models for estimating occurrence and extinction from animal surveys. Ecology 88: 2773--2782.
Royle, J.A. and R.M. Dorazio. 2006. Hierarchical models of animal abundance and occurrence. Journal of Agricultural, Biological, and Environmental Statistics 11: 249--263.
Dorazio, R.M., J.A. Royle, B. Soderstrom, and A. Glimskar. 2006. Estimating species richness and accumulation by modeling species occurrence and detectability. Ecology 87: 842--854.
Dorazio, R.M. and J.A. Royle. 2005. Estimating size and composition of biological communities by modeling the occurrence of species. Journal of the American Statistical Association 100: 389--398.
Dorazio, R.M. and J.A. Royle. 2005. Rejoinder to ``The performance of mixture models in heterogeneous closed population capture-recapture.'' Biometrics 61: 874--876.
Dorazio, R.M., H.L. Jelks, and F. Jordan. 2005. Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations. Biometrics 61: 1093--1101.
Dodd, C.K. and R.M. Dorazio. 2004. Using counts to simultaneously estimate abundance and detection probabilities in a salamander community. Herpetologica 60: 468--478.
Dorazio, R.M., and F.A. Johnson. 2003. Bayesian inference and decision theory - a framework for decision making in natural resource management. Ecological Applications 13: 556--563.
Dorazio, R.M., and J.A. Royle. 2003. Mixture models for estimating the size of a closed population when capture rates vary among individuals. Biometrics 59: 351--364.
My Science Topics
Robert Dorazio is a Research Statistician at the U.S. Geological Survey's Southeast Ecological Science Center. He also holds a Courtesy Associate Professorship in the Department of Statistics at the University of Florida. His research is motivated primarily by statistical inference problems that arise in the general areas of population dynamics, community ecology, and conservation biology. In solving these problems he develops and applies novel sampling designs and novel statistical models in quantitative investigations of natural populations or communities of animals (including imperiled or declining species). He is also interested in developing the theory and practice of adaptive decision making in problems of natural resource management.
Hierarchical Modeling Book (with Andy Royle)
Published by Academic Press in 2008, this book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems.
e-book version (available to all USGS employees): http://www.sciencedirect.com/science/book/9780123740977
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