D. Nguyen, P. de Valpine, Y. Atchadé, D. Turek, N. Michaud, and C. J. Paciorek. Nested Adaptation of MCMC Algorithms.  Bayesian Analysis (advance publication).  doi:10.1214/19-BA1190.

Anderson, M. J., P. de Valpine, A. Punnett, and A.E. Miller. 2019. A pathway for multivariate analysis of ecological communities using copulas.  Ecology and Evolution 9:3276-3294.

Ponisio, L.C., P. de Valpine, L. K. M’Gonigle, and C. Kremen. 2019. Proximity of restored hedgerows interacts with local floral diversity and species’ traits to shape long‐term pollinator metacommunity dynamics.  Ecology Letters 22:1048-1060.

MacLean, S. A., A. F. Rios Dominguez, P. de Valpine, and S. R. Beissinger. 2018. A century of climate and land‐use change cause species turnover without loss of beta diversity in California’s Central Valley.  Global Change Biology 12:5882-5894.

Salazar, D., J. Lokvam, I. Mesones, M. Vásquez Pilco, J. M. Ayarza Zuñiga, P. de Valpine, and P. V. A. Fine. 2018. Origin and maintenance of chemical diversity in a species-rich tropical tree lineage. Nature Ecology & Evolution 6: 983-990. doi: 10.1038/s41559-018-0552-0.

Dougherty, E. R., P. de Valpine, C. J. Carlson, J. K. Blackburn, and W. M. Getz. 2018. Commentary to: a cross-validation-based approach for delimiting reliable home range estimates. Movement Ecology 6:10. doi:10.1186/s40462-018-0128-2

Frishkoff, L. O., P. de Valpine, and L. K. M’Gonigle. 2017.  Phylogenetic occupancy models integrate imperfect detection and phylogenetic signal to analyze community structure. Ecology, 98: 198–210. doi:10.1002/ecy.1631

Kueppers, L.M, E. Conlisk, C. Castanha, A. Moyes, M. J. Germino, P. de Valpine, M. Torn, and J. Mitton. 2017. Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest. Global Change Biology 23: 2383-2395. doi:10.1111/gcb.13561.

de Valpine, P., D. Turek, C.J. Paciorek, C. Anderson-Bergman, D. Temple Lang, and R. Bodik. 2017. Programming with models: writing statistical algorithms for general model structures with NIMBLE. Journal of Computational and Graphical Statistics 26: 403-413. doi: 10.1080/10618600.2016.1172487

Turek, D., P. de Valpine, C.J. Paciorek, and C. Anderson-Bergman. Automated Parameter Blocking for Efficient Markov Chain Monte Carlo Sampling. 2017. Bayesian Analysis 12:465-490. doi: 10.1214/16-BA1008.

Turek, D., P. de Valpine, and C.J. Paciorek. 2016. Efficient Markov Chain Monte Carlo Sampling for Hierarchical Hidden Markov Models. Environmental and Ecological Statistics 23: 549. doi:10.1007/s10651-016-0353-z

Harmon-Threatt, A. N., P. de Valpine, and C. Kremen. 2016. Estimating resource preferences of a native bumblebee: the effects of availability and use-availability models on preference estimates. Oikos 126: 633-641. doi:10.1111/oik.03550

Nuccio, E.E., J. Anderson-Furgeson, K.Y. Estera, J. Pett-Ridge, P. de Valpine, E.L. Brodie, and M.K. Firestone. 2016. Climate and edaphic controllers influence rhizosphere community assembly for a wild annual grass. Ecology 97: 1307-1318.

Knape, J. and P. de Valpine. 2016. Monte Carlo estimation of stage structured development from cohort data. Ecology 97: 992-1002.

Eitzel, M.V., M. Kelly, I. Dronova, Y. Valachovic, L. Quinn-Davidson, J. Solera, and P. de Valpine . 2016. Challenges and opportunities in synthesizing historical geospatial data using statistical models. Ecological Informatics 31: 100-111. doi:10.1016/j.ecoinf.2015.11.011.

Eitzel, M.V., J. Battles, R. York and P. de Valpine . 2015. Can’t see the trees for the forest: complex factors influence tree survival in a temperate second growth forest. Ecosphere 6(11):247. 10.1890/ES15-00105.1   See Erratum.

de Valpine, P. and Knape, J. 2015. Estimation of general multistage models from cohort data. Journal of Agricultural, Biological and Environmental Statistics 20:140-155.

Gimenez, O., S. T. Buckland, B. J. T. Morgan, N. Bez, S. Bertrand, R. Choquet, S. Dray, M. Etienne, R. Fewster, F. Gosselin, B Mérigot, P. Monestiez, J. M. Morales, F. Mortier, F. Munoz, O, Ovaskainen, S. Pavoine, R. Pradel, F. M. Schurr, L. Thomas, W. Thuiller, V. Trenkel, P. de Valpine, and R. Rexstad. 2014. Statistical ecology comes of age. Biology Letters 10: 20140698.

Ponisio, L.C., L. K. M’Gonigle , K. C. Mace , J. Palomino, P. de Valpine , and C. Kremen. 2014. Diversification practices reduce organic to conventional yield gap. Proceedings of the Royal Society of London B 282: 20141396.

de Valpine, P.,  K. Scranton, J. Knape, K. Ram, and N. J. Mills.  2014.  The importance of individual development variation in stage-structured population models.  Ecology Letters 17:1026-1038. DOI: 10.1111/ele.12290

Scranton, K.,  J. Knape, P. de Valpine. 2014. An approximate Bayesian computation approach to parameter estimation in a stochastic stage-structured population model. Ecology 95: 1418-1428.

Knape, J., K. M. Daane and P. de Valpine.  2014. Estimation of stage duration distributions and mortality under repeated cohort censuses.  Biometrics 70:346-355.

de Valpine, P.  2014.  The common sense of P values.  Ecology 95:617-621 (part of a forum on P-values in ecology).

Popescu, V. D., P. de Valpine, and R. A. Sweitzer. 2014.  Testing the consistency of wildlife data types before combining them: the case of camera traps and telemetry.  Ecology and Evolution 4: 933-943. doi: 10.1002/ece3.997

Chaplin-Kramer, R., P. de Valpine, N.J. Mills, and C. Kremen. 2013. Detecting pest control services across spatial and temporal scales.  Agriculture, Ecosystems & Environment 181: 206-121.

de Valpine, P. and A. N. Harmon-Threatt. 2013.  General models for resource use or other compositional count data using the Dirichlet-multinomial distribution.  Ecology 94:2678-2687.

Eitzel, M.,  J. Battles, R. York, J. Knape, and P. de Valpine. 2013. Estimating tree growth from complex forest monitoring data. Ecological Applications 23:1288–1296. See Errata.

Scranton, K., M. Stavrinides, N.J. Mills, and P. de Valpine.  2013. Small-Scale Intraspecific Life History Variation in Herbivorous Spider Mites (Tetranychus pacificus) Is Associated with Host Plant Cultivar.  PLoS ONE 8(9): e72980. doi:10.1371/journal.pone.0072980

Knape, J., P. Besbeas, and P. de Valpine. 2013.  Using uncertainty estimates in analyses of population time series. Ecology 94:2097-2107.

Bolker, B., B. Gardner, M. Maunder, C. Berg,  M. Brooks,  L. Comita, E. Crone, S. Cubaynes, T. Davies, P. de Valpine, J. Ford, O. Gimenez, M. Kéry, E. Kim, C. Lennert-Cody,  A. Magnusson, S. Martell, J. Nash, A. Nielsen, J. Regetz, H. Skaug, and E. Zipkin. 2013.  Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS. Methods in Ecology and Evolution: 4:501-512.

Popescu, V. D., P. de Valpine, D. Tempel, and M. Z. Peery.  2012. Estimating population impacts via dynamic occupancy analysis of Before-After Control-Impact studies.  Ecological Applications 22: 1389-1404.

Knape, J. and P. de Valpine. 2012.  Fitting complex population models by combining particle filters with Markov chain Monte Carlo.  Ecology 93: 256-263.

Knape, J. and P. de Valpine. 2012. Are patterns of density dependence in the Global Population Dynamics Database driven by uncertainty about population abundance? Ecology Letters 15: 17-23.

de Valpine, P. 2011. Frequentist analysis of hierarchical models for population dynamics and demographic data. Journal of Ornithology (EURING proceedings).  Springer Open Access (Online First)

Risk, B. B., P. de Valpine, and S. R. Beissinger. 2011. A robust-design formulation of the incidence function model of metapopulation dynamics applied to two species of rails. Ecology 92:462-474.

Nesmith, J.C.B., K. L. O’Hara, P. J. van Mantgem, and P. de Valpine.  2010. The Effects of Raking on Sugar Pine Mortality Following Prescribed Fire in Sequoia and Kings Canyon National Parks, California, USA.  Fire Ecology 6:97-116. DOI: 10.4996/fireecology.0603097

Knape, J. and P. de Valpine. 2011. Effects of weather and climate on the dynamics of animal population time series. Proceedings of the Royal Society of London B 278:987-992.  Published online Sept. 29, 2010.  doi: 10.1098/rspb.2010.1333

Ingersoll, T. E., K. W. Navo and P. de Valpine. 2010. Microclimate preferences during swarming and hibernation in the Townsend’s big-eared bat, Corynorhinus townsendii. Journal of Mammalogy 91:1242-1250. doi: 10.1644/09-MAMM-A-288.1

de Valpine, P., K. Scranton, and C. P. Ohmart. 2010. Local versus regional dynamics of managed populations: synchrony of two vineyard arthropods occurs at multiple spatial and temporal scales. Ecological Applications 20:1926-1935.

Karban, R. and P. de Valpine. 2010. Population dynamics of an Arctiid caterpillar-tachinid parasitoid system using state-space models. Journal of Animal Ecology 79:650-661.

de Valpine, P.  2009.  Stochastic development in biologically structured population models.  Ecology 90:2889-2901.  R package.

Polansky, L., P. de ValpineJ. O. Lloyd-Smith, and W. M. Getz.  2009.  Likelihood ridges and multimodality in population growth rate models.  Ecology 90:2313-2320.

de Valpine, P.  2009.  Shared challenges and common ground for Bayesian and classical analysis of hierarchical models.  Ecological Applications 19: 584-588.

de Valpine, P., H-M. Bitter, M.P.S. Brown, and J. Heller. 2009. A simulation-approximation approach to sample size planning for high-dimensional classification studies. Biostatistics 10: 424-435.  R code.

Moritz, M.A. T. J. Moody, L. J. Miles, M.M. Smith, and P. de Valpine. 2009. The fire frequency analysis branch of the pyrostatistics tree: sampling decisions and censoring in fire interval data. Environmental and ecological statistics 16: 271-289.

Polansky, L., P. de Valpine, J. O. Lloyd-Smith, and W. M. Getz.  2008.   Parameter estimation in a generalized discrete-time model of density dependence.  Theoretical Ecology 1: 221-229.

de Valpine, P., K. Cuddington, M.F. Hoopes, and J. L. Lockwood. 2008. Is spread of invasive species regulated? Using ecological theory to interpret statistical patterns.  Ecology 89: 2377-2383.

de Valpine, P., and J. M. Eadie. 2008.  Conspecific brood parasitism and population dynamics. American Naturalist  172: 547-562.

de Valpine, P. and J. A. Rosenheim.  2008. Field-scale roles of density, temperature, nitrogen, and predation on aphid population dynamics.  Ecology 89: 532-541.

de Valpine, P. 2008. Improved estimation of normalizing constants from Markov chain Monte Carlo output.  Journal of Computational & Graphical Statistics 17: 333-351.

Adler, L.S., P. de Valpine, J. Harte, and J. Call. 2007. Effects of long-term experimental warming on aphid density in the field.  Journal of the Kansas Entomological Society 80: 156-168.

de Valpine, P., and R. Hilborn. 2005. State-space likelihoods for nonlinear fisheries time-series. Canadian Journal of Fisheries and Aquatic Sciences 62: 1937-195.

de Valpine, P. 2004. Monte Carlo state-space likelihoods by weighted posterior kernel density estimation. Journal of the American Statistical Association 99:523-535.

de Valpine, P. 2003. Better inferences from population-dynamics experiments using Monte Carlo state-space likelihood methods. Ecology 84:3064-3077.

de Valpine, P. 2002. Review of methods for fitting time-series models with process and observation error, and likelihood calculations for nonlinear, non-Gaussian state-space models. Bulletin of Marine Science 70: 455-471.

de Valpine, P., and A. Hastings. 2002. Fitting population models incorporating process noise and observation error. Ecological Monographs 72:57-76.

de Valpine, P., and J. Harte. 2001. Effects of warming on a montane meadow ecosystem: how species responses comprise the ecosystem response. Ecology 82: 637-648.

de Valpine, P. 2000. A new demographic function maximized by life-history evolution. Proceedings of the Royal Society of London B 267: 357-362. (Errata)