Research


Current Projects

National Institute of Statistical Science

USGS Climate Adaptation Science Centers -- Fish habitat restoration to promote adaptation: resilience of sport fish in lakes of the Upper Midwest

Continental Limnology - Developing joint distribution models for studying the spatial patterns of continental-scale pools of lake nutrients, their environmental drivers, and identifying the role that ecological novelty affects continental-scale prediction.


Select Publications

Schliep, E.M., A.E. Gelfand, J. Abaurrea, J. As ́ın, M. A. Beamonte, A.C. Cebri ́an. (2021) Long-term spatial modeling for characteristics of extreme heat events. Journal of the Royal Statistical Society, Series A (Statistics in Society), 184(3), 1070-1092.

Schliep, E.M., T.L.J. Schafer, M. Hawkey. (2021) Distributed lag models to identify the cumulative effects of training and recovery in athletes using multivariate ordinal wellness data. Journal of Quantitative Analysis of Sports, 17(3), 241-254.

Bailey, S., G.P. Elliot, E.M. Schliep. (2021) Seasonal temperature-moisture interactions limit seedling establishment at upper treeline in the Southern Rockies. Ecosphere, 12(6), e03568.

North, J.S., E.M. Schliep, C.K. Wikle. (2021) On the spatial and temporal shift in the archetypal seasonal temperature cycle as driven by annual and semi-annual harmonics. Environmetrics, 32(6), e2665.

Schliep, E.M., S.M. Collins, S. Rojas Salazar∗, N.R. Lottig, E.M. Stanley (2020). Data fusion model to identify environmental drivers and improve estimation of total nitrogen in lakes. The Annals of Applied Statistics, 14(4), 1651-1675.

Soranno, P.A., K.S. Cheruvelil, B. Liu, Q. Wang, P.N. Tan, J. Zhou, K.B.S. King, I.M. McCullough, J. Stachelek, M. Bartley, C.T. Filstrup, E.M. Hanks, J.F. Lapierre, N.R. Lottig, E.M. Schliep, T. Wagner, K.E. Webster. (To Appear). Ecological prediction at macroscales using big data: Does sampling design matter? Ecological Applications.

Wagner, T., N.R. Lottig, M.L. Bartley, E.M. Hanks, E.M. Schliep, N.B. Wikle, K.B.S. King, I. McCullough, J Stachelek, K.S. Cheruvelil, C.T. Filstrup, J.F. Lapierre, B. Liu, N. Smith, P.A. Soranno, P.N. Tan, Q. Wang, K. Webster, J. Zhou. (2019). Increasing accuracy of lake nutrient predictions in thousands of lakes by leveraging water clarity data. Limnology and Oceanography Letters, 5(2), 228-235.

Bartley, M.L., E.M. Hanks, E.M. Schliep, P.A. Soranno, T. Wagner (2019). Identifying and characterizing extrapolation in multivariate response data. PLOS ONE, 14(12).

Stanley, E.H., S. Rojas Salazar, E.M. Schliep, N.R. Lottig, C.T. Filstrup, S.M. Collins (2019). Comparison of total nitrogen data from direct and Kjeldahl-based approaches in integrated datasets. Limnology and Oceanography: Methods, 17, 639-649.

Ramseyer Winter, Virginia, A.M. Landor, M. Teti, K. Morris, E.M. Schliep, D. Pevenhouse-Pfeiffer, E. Pekarek. (2019) Is body appreciation a mechanism of depression and anxiety? An investigation of the 3-Dimensional Body Appreciation Mapping (3D-BAM) intervention. Mental Health & Prevention, 14, 200158.

Schliep, E.M. & A.E. Gelfand (2019). Velocities for spatio-temporal point patterns. Spatial Statistics, 29, 204-225.

Schliep, E.M. (2018). “Comments on: Process modeling for slope and aspect with application to elevation data maps” by Wang et al. TEST, 27(4), 778-782.

Gelfand, A.E., E.M. Schliep (2018). Bayesian Inference and Computing for Spatial Point Patterns. NSF-CBMS Regional Conference Series in Probability and Statistics, 10, i-125. Institute of Mathematical Statistics and the American Statistical Association.

Schliep, E.M., A.E. Gelfand, J.S. Clark, R. Kays (2018). Joint Temporal Point Pattern Models for Proximate Species Occurrence in a Fixed Area Using Camera Trap Data. Journal of Agricultural, Biological, and Environmental Statistics, 23(3), 334-357.

Wagner, Tyler , E. M. Schliep. (2018). Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales. Limnology and Oceanography, 63(6), 2372-2383.

Lany, N.K., P.L. Zarnetske, E.M. Schliep, R.N. Schaeffer, C.M. Orians, D.A. Orwig, E.L. Preisser (2018). Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model. Ecology, 99(5), 1018-1023.

Schliep, E.M., A.E. Gelfand, R.M. Mitchell, M.A. Lammens, J.A. Silander (2018). Assessing the joint behavior of species traits as filtered by environment. Methods in Ecology and Evolution, 9(3), 716-727.

Schliep, E.M., N.K. Lany, P.L. Zarnetske, R.N. Schaeffer, C.M. Orians, D.A. Orwig, E.L. Preisser (2018) Joint species distribution modeling for spatio-temporal occurrence and ordinal abundance data. Global Ecology and Biogeography, 27(1), 142-155.

Schliep, E.M., A.E. Gelfand, D.M. Holland (2018). Alternating Gaussian Process Modulated Re- newal Processes for Modeling Threshold Exceedances and Durations. Stochastic Environmental Research and Risk Assessment, 32(2), 401-417.

U.S. DOE. 2018. Disturbance and Vegetation Dynamics in Earth System Models; Workshop Report, DOE/SC-0196. Office of Biological and Environmental Research, U.S. Department of Energy Office of Science.

Schliep, E.M., A.E. Gelfand, J.S. Clark, B.J. Tomasek (2017). Biomass prediction using a dnsity-dependent diameter distribution model. The Annals of Applied Statistics, 11(1), 340-361.

Taylor-Rodriguez, D., K. Kaufeld, E.M. Schliep, J.S. Clark, A.E. Gelfand (2017). Joint species distribution modeling; dimension reduction using Dirichlet processes. Bayesian Analysis, 12(4), 939-967.

Gelfand, A.E. & E.M. Schliep (2016). Spatial statistics and Gaussian processes: A Beautiful Marriage. Spatial Statistics, 18, 86-104.

Schliep, E.M., A.E. Gelfand, D.M. Holland (2015). Autoregressive spatially-varying coefficient mod- els for predicting daily PM2.5 using VIIRS satellite AOT. Advances in Statistical Climatology, Meteorology, and Oceanography, 1, 59-74.

Rundel, C., E.M. Schliep, A.E. Gelfand, D.M. Holland (2015). A Data Fusion Approach for Space- time Analysis of Speciated PM2.5. Environmetrics, 26(8), 515-525.

Schliep, E.M., A.E. Gelfand, J.S. Clark, K. Zhu (2015). Modeling change in forest biomass across the eastern US. Environmental and Ecological Statistics, 23(1), 23-41.

Schliep, E.M., A.E. Gelfand, J.S. Clark (2015). Stochastic Modeling for Velocity of Climate Change. Journal of Agricultural, Biological, and Environmental Statistics, 20(3), 323-342.

Schliep, E.M. & J.A. Hoeting (2015). Data augmentation and parameter expansion for independent or spatially correlated ordinal data. Computational Statistics & Data Analysis, 90, 1-14.

Hanks, E.M., E.M. Schliep, M.B. Hooten, J.A. Hoeting (2015). Restricted spatial regression in practice: geostatistical models, confounding, and robustness under model misspecification. Environmetrics, 26(4), 243-254.

Schliep, E.M., T.Q. Dong, A.E. Gelfand, F. Li (2014). Modeling individual tree growth by fusing diameter tape and increment core data. Environmetrics, 25(8), 610-620.

Schliep, E.M. & J.A. Hoeting (2013). Multilevel Latent Gaussian Process Model for Mixed Discrete and Continuous Multivariate Response Data. Journal of Agricultural, Biological, and Environmental Statistics, 18(4), 492-513.

Schliep, E.M., D. Cooley, S.R. Sain, J.A. Hoeting (2010). A Comparison Study of Extreme Precip- itation from Six Different Regional Climate Models via Spatial Hierarchical Modeling. Extremes, 13(2), 219-239.