Publications

Archived Data Products
Modeling Protocols

Book and Book Chapters

  1. Pederson, N., A.B. Young, A.B. Stan, U. Ariya and D. Martin-Benito. 2017. Low-hanging DendroDynamic Fruits Regarding Disturbance in Temperate, Mesic Forests. In Dendroecology: Tree-ring Analyses Applied to Ecological Studies, M. Amoroso, L. Daniels, P. Baker, J. J. Camarero, Eds. (Springer). Book details here.
  2. Trouet, V., M. Domínguez-Delmás, C. Pearson, N. Pederson, and D. Rubino. 2017. “Dendro-archeo-ecology” in North America and Europe: Re-purposing Historical Materials to Study Ancient Human-Environment Interactions. In Dendroecology: Tree-ring Analyses Applied to Ecological Studies, M. Amoroso, L. Daniels, P. Baker, J. J. Camarero, Eds. (Springer). Book details here.
  3. Dietze, M.C. 2017. Ecological Forecasting. Princeton University Press. Book details here.
  4. Hobbs, N.T. and M.B. Hooten. 2015. Bayesian Models: A Statistical Primer for Ecologists. Princeton University Press. Book details here.

Peer Reviewed Publications

2023

  1. Cogbill, C.V. 2023. Surveyor and Analyst Biases in Forest Density Estimation from United States Public Land Surveys. Ecosphere 14(8):  e4647. https://doi.org/10.1002/ecs2.4647

2022

  1. Raiho, A.M., C.J. Paciorek, S.T. Jackson, D.J. Mladenoff, J.W. Williams, J.S. McLachlan. 2022. 8000-year doubling of Midwestern forest biomass driven by population- and biome-scale processes. Science 376(6600): 1491-1495.
    https://doi.org/10.1126/science.abk3126. Get the full paper HERE.

2021

  1. D’Orangeville, L.D., Itter, M., Kneeshaw, D., Munger, J.W., Richardson, A.D., Dyer, J.M., Orwig, D.A., Pan, Y., Pederson, N. 2021. Peak radial growth of diffuse-porous species occurs during periods of lower water availability than for ring-porous and coniferous trees. Tree Physiology, tpab101. https://doi.org/10.1093/treephys/tpab101
  2. Heilman, K.A., Trouet, V.M., Belmecheri, S., Pederson, N., Berke, M.A., McLachlan, J.S. 2021. Increased water use efficiency leads to decreased precipitation sensitivity of tree growth, but is offset by high temperatures. Oecologia. https://doi.org/10.1007/s00442-021-04892-0
  3. Paciorek, C.J., C.V. Cogbill, J.A. Peters, S.J. Goring, J.W. Williams, D.J. Mladenoff, A. Dawson, J.S. McLachlan. 2021. The forests of the midwestern United States at Euro-American settlement: spatial and physical structure based on contemporaneous survey data. PLoS ONE 16(2):e0246473. https://doi.org/10.1371/journal.pone.0246473
  4. Stanke, H., Finley, A.O., Domke, G.M., Weed, A.S., MacFarlane, D.W. Accepted. Over half of western United States’ most abundant tree species in decline. Nature Communications. https://doi.org/10.1038/s41467-020-20678-z

2020

  1. Rollinson, C., Dawson, A., Raiho, A., Williams, J.W., Dietze, M.C., Hickler, T., Jackson, S.T., McLachlan, J.S., Moore, D.J.P., Poulter, B., Quaife, T., Steinkamp, J., Trachsel, M. 2020. Forest responses to last-millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity. Ecology Letters. https://doi.org/10.1111/ele.13667
  2. Rollinson, C., M. Alexander, A. Dye, D. Moore, N. Pederson, and V. Trouet. 2020. Understory trees are more climate sensitive than overstory trees in temperate mesic forests. Ecology. https://doi.org/10.1002/ecy.3264
  3. Zhang, J., Alexander, M.R., Gou, X., Deslauriers, A., Fonti, P., Zhang, F., Pederson, N. 2020. Extended xylogenesis and stem biomass production in Juniperus przewalskii Kom. during extreme late-season climatic events. Annals of Forest Science 77, 99. https://doi.org/10.1007/s13595-020-01008-1
  4. Finzi, A., et al. 2020. Carbon Budget of the Harvard Forest Long-Term Ecological Research Site: Pattern, Process and Response to Global Change. Ecological Monographs 90(4):e01423. https://doi.org/10.1002/ecm.1423
  5. McGregor, I.R., et al.. 2020. Tree height and hydraulic traits shape growth responses across droughts in a temperate broadleaf forest. New Phytologist 231(2); 601-616 https://doi.org/10.1111/nph.16996
  6. Au, T.F., et al. 2020. Demographic shifts in eastern US forests increase the impact of late-season drought on forest growth. Ecography 43(10): 1475-1486. https://doi.org/10.1111/ecog.05055
  7. Pederson, N., et al. 2020. A framework for determining population-level vulnerability to climate: evidence for growth hysteresis in Chamaecyparis thyoides along its contiguous latitudinal distribution. Frontiers in Forests and Global Change 3:39. https://doi.org/10.3389/ffgc.2020.00039
  8. Dannenberg, Matthew, Conghe Song, Erika Wise, Neil Pederson, and Daniel Bishop. 2020. Delineating environmental stresses to primary production of U.S. forests from tree rings: Effects of climate seasonality, soil, and topography. Journal of Geophysical Research: Biogeosciences, 125, e2019JG005499, doi:10.1029/2019JG005499
  9. Blakely, B.J., Rocha, A.V. & McLachalan, J.S. A Century of Forest Regrowth and Snow Loss Alters the Cooling Effect of Historical Land Use in the Upper Midwest. Ecosystems 23, 1056–1074 (2020). https://doi.org/10.1007/s10021-019-00456-9
  10. Hamlet, A.F., Patterson, T.A., Hanson, Z.J., Peters, J.A., Byun, K., Chiu,C-M., Bolster, D., McLachlan, J.S., Pavlovic, N.B., Schurr, M.R., Hellmann, J.J., Grundel, R. 2020. Assessment of Waterfowl Habitat Restoration as an Adaptive Mechanism for Water Sustainability in the Kankakee River Watershed final report to the US Fish and Wildlife Service. pp 363. https://www.sciencebase.gov/catalog/item/56c60c25e4b0946c652286ad
  11. Stahle, D.W., E.R. Cook, D.J. Burnette, M.C.A. Torbenson, I.M. Howard, D. Griffin, J.V. Diaz, B.I. Cook, P.A. Williams, E. Watson, D.J. Sauchyn, N. Pederson, C.A. Woodhouse, G.T. Pederson, D. Meko, B. Coulthard, C.J. Crawford. 2020. Dynamics, variability, and changes in seasonal precipitation reconstructions for North America. Journal of Climate, 0, Early Release.  https://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-19-0270.1
  12. Trachsel, M., Dawson, A., Paciorek, C., Williams, J., McLachlan, J., Cogbill, C., Foster, D.R., Goring, S.J., Jackson, S.T., Oswald, W.W., Shuman, B. 2020. Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States. Quaternary Research, 95, 23-42. https://doi.org/10.1017/qua.2019.81

2019

  1. Kannenberg, SA, Novick, KA, Alexander, MR, et al. 2019. Linking drought legacy effects across scales: From leaves to tree rings to ecosystems. Global Change Biology 25: 2978– 2992. https://doi.org/10.1111/gcb.14710
  2. Burke, K. D., J. W. Williams, S. Brewer, W. Finsinger, T. Giesecke, D. J. Lorenz, and A. Ordonez. 2019. Differing climatic mechanisms control transient and accumulated vegetation novelty in Europe and eastern North America. Philosophical Transactions of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rstb.2019.0218
  3. Levine, C. R., C. V. Cogbill, B. M. Collins, A. J. Larson, J. A. Lutz, M. P. North, C. M. Restaino, H. D. Safford, S. L. Stephens, and J. J. Battles. 2019. Estimating historical forest density from land-survey data: a response to Baker and Williams (2018). Ecological Applications 00(00):e01968. 10.1002/eap.1968. https://doi.org/10.1002/eap.1968
  4. Tipton, John, Hooten, M., Nolan, C., Booth, R., and McLachlan, J. 2019. Predicting unobserved climate from compositional data using multivariate Gaussian process inverse prediction. Annals of Applied Statistics 13(4): 2363-2388. https://projecteuclid.org/euclid.aoas/1574910048
  5. Hoecker, T.J. and P.E. Higuera. 2019. Forest succession and climate variability interacted to control fire activity over the last four centuries in an Alaskan boreal landscape. Landscape Ecology 34(2):227-241. https://link.springer.com/article/10.1007/s10980-018-00766-8
  6. Dawson, A., C. Paciorek, S. Goring, S.T. Jackson, J.S. McLachlan, J.W. Williams. 2019. Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States. Ecology. https://doi.org/10.1002/ecy.2856
  7. Williams, J.W., K.D. Burke, M.S. Crossley, D.A. Grant, V.C. Radeloff. 2019. Land-use and climatic causes of environmental novelty in Wisconsin since 1890. Ecological Applications 00(00):e01955. 10.1002/eap.1955
  8. Seeley, M., S. Goring, J.W. Williams. 2019. Assessing the environmental and dispersal controls of Fagus grandifolia distributions in the Great Lakes region. Journal of Biogeography 00:1-15.
  9. Nolan, C., J. Tipton, R.K. Booth, M.B. Hooten, & S.T.Jackson. 2019. Comparing and improving methods for reconstructing peatland water-table depth from testate amoebae. The Holocene 29(8): 1350-1361.
  10. Hoban, S., Dawson, A., Robinson, J.D., Smith, A.B., Strand, A.E. 2019. Inference of biogeographic history by formally integrating distinct lines of evidence: genetic, environmental niche and fossil. Ecography https://doi.org/10.1111/ecog.04327
  11. Itter, M.S., D’Orangeville, L., Dawson, A., Kneeshaw, D., Duchesne, L., Finley, A. 2019. Boreal tree growth exhibits decadal-scale ecological memory to drought and insect defoliation, but no negative response to their interaction; Journal of Ecology 107(3):1288-1301. https://doi.org/10.1111/1365-2745.13087
  12. Young AM, Higuera PE, Abatzoglou JT, Duffy PA, Hu FS. 2019. Consequences of climatic thresholds for projecting fire activity and ecological change. Global Ecology and Biogeography 38:521-532. https://doi.org/10.1111/geb.12872

2018

  1. Alexander, M.R., Rollinson, C.R., Babst, F. et al. Relative influences of multiple sources of uncertainty on cumulative and incremental tree-ring-derived aboveground biomass estimates. Trees 32, 265–276 (2018). https://doi.org/10.1007/s00468-017-1629-0
  2. Babst F, P Bodesheim, N Charney, A Friend, M Girandin, S Klesse, DJP Moore, K Seftigen, J Bjaklund, O Bouriaud, A Dawson, RJ DeRose, M Dietze, A Eckes, B Enquist, DC Frank, MD Mahecha, B Poulter, S Record, V Trouet, R Turton, Z Zhang, MEK Evans. 2018 When tree rings go global: challenges and opportunities for retro- and prospective insight. Quaternary Science Reviews 147: 1-20.
  3. Dawson, A., X. Cao, M. Chaput, E. Hopla, F. Li, M. Edwards, R. Fyfe, K. Gajewski, S. J. Goring, U. Herzschuh, F. Mazier, S. Sugita, J. W. Williams, Q. Xu, and M.-J. Gaillard. 2018. Finding the magnitude of human-induced Northern Hemisphere land-cover transformation between 6 and 0.2 ka BP. PAGES Magazine 26:34-35.
  4. Burke, K.D., J.W. Williams, M.A. Chandler, A.M. Haywood, D.J. Lunt, and B.L. Otto-Bliesner. 2018. Pliocene and Eocene provide best analogs for near-future climates. PNAS 115(52): 13288-13293.
  5. Williams, J.W., D.S. Kaufman, A. Newton, and L. von Gunte.2018. Building and harnessing open paleodata. pg 49. Past Global Changes Magazine; Building and Harnessing Open Paleodata vol. 26(2), 76. Eds: Williams JW, Newton AJ, Kaufman DS & von Gunten L.
  6. McLachlan, J.S. and the PalEON Project. 2018. Forecasting long-term ecological dynamics using open paleodata. Past Global Changes Magazine; Building and Harnessing Open Paleodata vol. 26(2), 76. Eds: Williams JW, Newton AJ, Kaufman DS & von Gunten L.
  7. Dye, A., M.R. Alexander, D. Bishop, D. Druckenbrod, N. Pederson, A. Hessl. 2018. Size-growth asymmetry is not consistently related to productivity across an eastern US temperate forest network. Oecologia.
  8. Itter, M., L. D’Orangeville, A. Dawson, D. Kneeshaw, L. Duchesne, A.O. Finley. (2018) Boreal tree growth exhibits decadal‐scale ecological memory to drought and insect defoliation, but no negative response to their interaction. Journal of Ecology.
  9. Fox, A.M., T.J. Hoar, J.L. Anderson, A.F. Arellano, W.K. Smith, M.E. Litvak, N. MacBean, D.S. Schimel, and D.J.P. Moore. 2018. Evaluation of a Data Assimilation System for Land Surface Models using CLM4.5. Journal of Advances in Modeling Earth Systems, 10.
  10. Farley, S. S., Dawson, A., Goring, S. J., and Williams, J. W. (2018) Situating ecology as a big data science: Current advances, challenges, and solutions. Bioscience.
  11. Nolan et. al. 2018. Past and future global transformation of terrestrial ecosystems under climate change. Science. 361(6405):920-923.
  12. D’Orangeville, L., J. Maxwell, D. Kneeshaw, N. Pederson, L. Duchesne, T. Logan, D. Houle, D. Arseneault, C.M. Beier, D.A. Bishop, D. Druckenbrod, S. Fraver, F. Girard, J. Halman, C. Hansen, J.L. Hart, H. Hartmann, M. Kaye, D. Leblanc, S. Manzoni, R. Ouimet, S. Rayback, C.R. Rollinson, R.P. Phillips. 2018. Drought timing and local climate determine the sensitivity of eastern temperate forests to drought. Global Change Biology, 1-13.
  13. Fer, I., R. Kelly, P.R. Moorcroft, A.D. Richardson, E.M. Cowdery, M.C. Dietze. 2018. Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation. Biogeosciences 15: 5801-5830.
  14. Cogbill, C. V., A. L. Thurman, J. W. Williams, J. Zhu, D. J. Mladenoff, and S. J. Goring. 2018. A retrospective on the accuracy and precision of plotless forest density estimators in ecological studies. Ecosphere 9(4):e02187. 10.1002/ecs2.2187
  15. Broderick, C.M., K.A. Heilman, T.A. Patterson, J.A. Peters, J.S. McLachlan. 2018 Sharp Savanna-forest Transitions in the Midwest Followed Environmental Gradients but are Absent from the Modern Landscape. The American Midland Naturalist, 180(1):1-17.

2017

  1. Marlon, J. R., Pederson, N., Nolan, C., Goring, S., Shuman, B., Robertson, A., Booth, R., Bartlein, P. J., Berke, M. A., Clifford, M., Cook, E., Dieffenbacher-Krall, A., Dietze, M. C., Hessl, A., Hubeny, J. B., Jackson, S. T., Marsicek, J., McLachlan, J., Mock, C. J., Moore, D. J. P., Nichols, J., Peteet, D., Schaefer, K., Trouet, V., Umbanhowar, C., Williams, J. W., and Yu, Z. 2017. Climatic history of the northeastern United States during the past 3000 years, Climate of the Past, 13, 1355-1379, https://doi.org/10.5194/cp-13-1355-2017, 2017.
  2. Montané, F., Fox, A. M., Arellano, A. F., MacBean, N., Alexander, M. R., Dye, A., Bishop, D. A., Trouet, V., Babst, F., Hessl, A. E., Pederson, N., Blanken, P. D., Bohrer, G., Gough, C. M., Litvak, M. E., Novick, K. A., Phillips, R. P., Wood, J. D., and Moore, D. J. P. 2017. Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools and turnover in temperate forests. Geosciences Model Development, 10, 3499-3517.
  3. Itter MS, Finley AO, Hooten MB, et al. 2017. A model-based approach to wildland fire reconstruction using sediment charcoal records. Environmetrics. 28:e2450. https://doi.org/10.1002/env.2450
  4. Young, A.M., Higuera, P.E., Duffy, P.A., and F.S. Hu. 2017. Climatic thresholds shape northern high‐latitude fire regimes and imply vulnerability to future climate change. Ecography. 40: 606-617.
  5. Feng, X., Zhu, J., Lin, P.-S., and Steen-Adams, M.M. 2017. Composite likelihood approach to the regression analysis of spatial multivariate ordinal data and spatial compositional data with exact zero values. Journal of Environmental and Ecological Statistics, 24:39-68. Abstract
  6. Levine, C.R., C.V. Cogbill, B.M. Collins, A.J. Larson, J.A. Lutz, M.P. North, C.M. Restaino, H.D. Safford, S.L. Stephens, and J.J. Battles. 2017. Evaluating a new method for reconstructing forest conditions from General Land Office survey records. Ecological Applications, 27(5), 2017, pp. 1498–1513.
  7. Itter, M.S., A.O. Finley, A.W. D’Amato, J.R. Foster and J.B. Bradford. 2017. Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics. Ecological Applications, 27:1082-1095. doi:10.1002/eap.1518. Abstract
  8. Goring, S. J., and J. W. Williams. 2017. Effect of historical land-use and climate change on tree-climate relationships in the upper Midwestern United States. Ecology Letters, 20: 461-470. doi:10.1111/ele.12747. Abstract
  9. Rollinson, C.R., Y. Liu, A. Raiho, D.J.P. Moore, J. McLachlan, D.A. Bishop, A. Dye, J. Hatala Matthes, A. Hessl, T. Hickler, N. Pederson, B. Poulter, T. Quaife, K. Schaefer, J. Steinkamp, M.C.Dietze. 2017. Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America. Global Change Biology. doi:10.1111/gcb.13626. Abstract
  10. Tipton, J., M. Hooten, S. Goring. 2017. Reconstruction of spatiotemporal temperature processes from sparse historical records using probabilistic principal component regression. Advances in Statistical Climatology, Meteorology, and Oceanography 3:1-16. doi:10.5194/ascmo-3-1-2017. Abstract

2016

  1. Goring, S.J., D.J. Mladenoff, C.V. Cogbill, S. Record, C.J. Paciorek, S.T. Jackson, M.C. Dietze, A. Dawson, J. Hatala Matthes, J.S. McLachlan, J.W. Williams. 2016. Novel and Lost Forests in the Upper Midwestern United States, From New Estimates of Settlement-Era Composition, Stem Density, and Biomass. PLoS ONE 11(12): e0151935. doi:10.1371/journal.pone.0151935. Paper
  2. Kujawa, E.R., S. Goring, A. Dawson, R. Calcote, E.C. Grimm, S.C. Hotchkiss, S.T. Jackson, E.A. Lynch, J. McLachlan, J. St-Jacques, C. Umbanhowar Jr., and J.W. Williams. 2016. The effects of anthropogenic land cover change on pollen-vegetation relationships in the American Midwest. Anthropocene 15: 60-71. Abstract
  3. Dye, A, A Barker-Plotkin, D Bishop, N Pederson, B Poulter and A Hessl. 2016. Comparing tree-ring and permanent plot estimates of aboveground net primary production in three Eastern U.S. forests. Ecosphere 7(9):e01454.10.1002/ecs2.1454. Paper
  4. Deines JM, D Williams, Q Hamlin, JS McLachlan. 2016. Changes in regional forest composition in Ohio between Euro-American settlement and the present. American Midland Naturalist 176(2): 247-271. Abstract
  5. Dawson, A., et al. 2016. Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data. Quaternary Science Reviews 137: 156-175.
    https://doi.org/10.1016/j.quascirev.2016.01.012
  6. Matthes, J.H., et al. 2016. Benchmarking historical CMIP5 plant functional types across the Upper Midwest and Northeastern United States. Journal of Geophysical Research: Biogeosciences. doi:10.1002/2015JG003175. Paper
  7. Paciorek C.J., et al. 2016. Statistically-estimated tree composition for the Northeastern United States at Euro-American Settlement. PLoS ONE 11(2): e0150087. doi:10.1371/journal.pone.0150087. Paper
  8. Tipton, J., M.B. Hooten, N. Pederson, M. Tingley, and D. Bishop. (2015). Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models. Environmetrics. DOI: 10.1002/env.2368. Abstract
  9. Marlon, J.R., Kelly, R., A-L Daniau, B. Vanniere, M.J. Power, P. Bartlein,P. Higuera, O. Blarquez, S. Brewer, T. Brucher, A. Feurdean, G. Gil-Romera, V. Iglesias, S.y. Maezumi, B. Magi, C.J.C. Mustaphi, T. Zhihai. 2016. Reconstructions of biomass burning from sediment charcoal records to improve data-model comparisons. Biogeosciences 13:3225-3244. doi:10.5194/bg-13-3225-2016. Abstract

2015

  1. Hare, Lizzy. 2015. The Anthropocene Trading Zone: The New Conservation, Big Data Ecology, and the Valuation of Nature. Environment and Society: Advances in Research 6(1):109-127.https://doi.org/10.3167/ares.2015.060107
  2. Dawson A., Austin D., Walker D., Appleton S., Gillanders B., Griffin S., Sakata C., Trouet V. (2015) A tree-ring based reconstruction of early summer precipitation in southwestern Virginia (1750-1981). Climate Research 64: 243-256. DOI 10.3354/cr01315.
  3. Bishop, D. & N. Pederson. 2015. Regional variation of rainless day frequency across a subcontinental hydroclimate gradient. Journal of Extreme Events, 2(2): 1550007. DOI: 10.1142/S2345737615500074. Abstract
  4. Pederson, N., D’Amato, A.W., Dyer, J.M., Foster, D.R., Goldblum, D., Hart, J.L., Hessl, A.E., Iverson, L.R., Jackson, S.T., Martin-Benito, D., McCarthy, B.C., McEwan, R.W., Mladenoff, D.J., Parker, A.J., Shuman, B., & Williams, J.W. (2015) Climate remains an important driver of post-European vegetation change in the eastern United States. Global Change Biology 21:2105–2110. doi: 10.1111/gcb.12779.
  5. Goring, S., et al. 2015. neotoma: A Programmatic Interface to the Neotoma Paleoecological Database; Open Quaternary. DOI: http://doi.org/10.5334/oq.ab
  6. Jackson, S.T. & J.L Blois. 2015. Community ecology in a changing environment: Perspectives from the Quaternary. Proceedings of the National Academy of Science, 112(16): 4915-4921. Abstract
  7. Hooten, M.B. & N.T. Hobbs. 2015. A guide to Bayesian model selection for ecologists. Ecological Monographs, 85: 3-28. Abstract
  8. Walsh, MK, JR Marlon, S Goring, KJ Brown, D Gavin. 2015. A regional perspective on Holocene on fire-climate-human interactions in the Pacific Northwest. Annals of the Association of American Geographers. 105(6): 1135-1157. Abstract
  9. Finley, A.O., S. Banerjee, A.E. Gelfand. 2015. spBayes for large univariate and multivariate point-referenced spatio-temporal data models. Journal of Statistical Software, 63(13):1-28. Abstract
  10. Datta, A., S. Banerjee, A.O. Finley, A.E. Gelfand. 2015. Hierarchical Nearest-Neighbor Gaussian process models for large geostatistical datasets. Journal of the American Statistical Association. DOI: 10.1080/01621459.2015.1044091. Abstract
  11. Zennaro, P., et al. 2015. Europe on fire three thousand years ago: Arson or climate?. Geophysical Research Letters, 42, 5023-2033. doi: 10.1002/2015GL064259. Paper

2014

  1. Blarquez, O., et al. 2014. Paleofire: An R package to analyse sedimentary charcoal records from the Global Charcoal Database to reconstruct past biomass burning. Computers & Geosciences, 72: 255-261. Abstract
  2. Finley, A.O, et al. 2014. Dynamic spatial regression models for space-varying forest stand tables. Environmetrics, 25: 596-609.
  3. Feng, X., et al. 2014. Composite likelihood estimation for spatial ordinal data and spatial proportional data with zero/one values. Environmetrics. 25(8):571-583. DOI: 10.1002/env.2306. Abstract
  4. Finley, A.O., S. Banerjee, and B.D. Cook. 2014. Bayesian hierarchical models for spatially misaligned data in R. Methods in Ecology and Evolution. 5(6):514-523. Abstract

Articles in a Special Issue of Frontiers in Ecology and the Environment on Macrosystem Ecology

  1. Goring, S.J., et al. 2014. Improving the culture of interdisciplinary collaboration in ecology by expanding measures of success. Frontiers in Ecology and the Environment. 12(1): 39-47. DOI: 10.1890/120370
  2. Cheruvelil KS, et al. 2014. Creating and maintaining high-performing collaborative research teams: the importance of diversity and interpersonal skills. Frontiers in Ecology and the Environment 12(1): 31-38. DOI: 10.1890/130001
  3. Heffernan JB, et al. 2014. Macrosystems ecology: understanding ecological patterns and processes at continental scales. Frontiers in Ecology and the Environment 12(1): 5-14. DOI: 10.1890/130017
  4. Levy O, et al. 2014. Approaches to advance scientific understanding of macrosystems ecology. Frontiers in Ecology and the Environment 12(1): 15-23. DOI: 10.1890/130019

2013

  1. Record, S., et al. 2013. Should species distribution models account for spatial autocorrelation? A test of model projections across eight millennia of climate change. Global Ecology and Biogeography, 22:760-771. Abstract
  2. Marsicek JP, et al. 2013. Moisture and temperature changes associated with the mid-Holocene Tsuga decline in the northeastern United States. Quaternary Science Reviews 80: 129-142.
  3. Day LT, et al. 2013. Analysis of hemlock pollen size in Holocene lake sediments from New England. Quaternary Research 79: 362-365.
  4. Swanson, A., et al. 2013. Spatial regression methods capture prediction uncertainty in species distribution model projections through time. Global Ecology and Biogeography, 22:242-251. Abstract
  5. Paciorek CJ. 2013. Spatial models for point and areal data using Markov random fields on a fine grid. Electronic Journal of Statistics 7:946-972. Abstract
  6. Clifford, M.J. & R.K. Booth. 2013. Increased fire probability of fire during late Holocene droughts in northern New England. Climate Change 119: 693-704.  Abstract
  7. Dietze, M.C., D.S. LeBauer & R. Kooper. 2013. On improving the communication between models and data. Plant, Cell & Environment, 36(9):1575-1585. Abstract

2012

  1. Goring, S.J., et al. 2012. Deposition times in the northeastern United States during the Holocene: establishing valid priors for Bayesian age models. Quaternary Science Reviews 48: 54-60. Abstract
  2. Jackson, S.T. 2012. Representation of flora and vegetation in Quaternary fossil assemblages: known and unknown knowns and unknowns. Quaternary Science Reviews 49:1-15. Abstract
  3. Kumar, J., et al. 2012. Sub-daily statistical downscaling of meteorological variables using neural networks. Procedia Computer Science 9:887-896. Abstract

Initial Paper

Paciorek, C. P. & J. S. McLachlan. 2009. Mapping Ancient Forests: Bayesian Inference for Spatio-Temporal Trends in Forest Composition Using the Fossil Pollen Proxy Record. Journal of the American Statistical Association. 104(486): 608-622. doi:10.1198/jasa.2009.0026. Abstract