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Publications
Note: the following is an incomplete list of publications that use the Ecosystem Demography model.
See also the publication group on Mendeley
Schneider FD, Longo M, Paul-Limoges E, Scholl VM, Schmid B, Morsdorf F, Pavlick RP, Schaepman ME, Schimel DS, Moorcroft PR. 2023. Remote sensing-based forest modeling reveals positive effects of functional diversity on productivity at local spatial scale. J. Geophys. Res.-Biogeosci. 128: e2023JG007421. doi:10.1029/2023JG007421.
Vieira LCdS, Manzi AO, Silva VdP, Satyamurty P, Dantas VdA, Santos AdS. 2023. Impacts of scenarios RCP4.5 and RCP8.5 on plant physiology in Tapajos National Forest in the Brazilian Amazon using the ED2.2 model. Acta Amaz. 53: 73–83. doi:10.1590/1809-4392202103184.
Antonarakis AS, Bogan SA, Goulden ML, Moorcroft PR. 2022. Impacts of the 2012–2015 Californian drought on carbon, water and energy fluxes in the Californian Sierras: Results from an imaging spectrometry-constrained terrestrial biosphere model. Glob. Change Biol. 28: 1823–1852. doi:10.1111/gcb.15995.
Hanbury-Brown AR, Powell TL, Muller-Landau HC, Wright SJ , Kueppers LM. 2022. Simulating environmentally-sensitive tree recruitment in vegetation demographic models. New Phytol. 235: 78–93. doi:10.1111/nph.18059.
Kim J, Kim Y, Kim J, Cho K, Hong J, Hong JW, Jo S, Park C , Chun JH. 2022. A transiting temperate-subtropical mixed forest: carbon cycle projection and uncertainty. Environ. Res. Lett. 17: 094010. doi:10.1088/1748-9326/ac87c0.
Larson EJL, Schiferl LD, Commane R, Munger JW, Trugman AT, Ise T, Euskirchen ES, Wofsy S, Moorcroft PR. 2022. The changing carbon balance of tundra ecosystems: results from a vertically-resolved peatland biosphere model. Environ. Res. Lett. 17: 014019. doi:10.1088/1748-9326/ac4070.
Meunier F, Verbruggen W, Verbeeck H, Peaucelle M. 2022. Low sensitivity of three terrestrial biosphere models to soil texture over the South American tropics. Geosci. Model Dev. 15: 7573–7591. doi:10.5194/gmd-15-7573-2022.
Schwartz NB, Medvigy D, Tijerin J, Pérez-Aviles D, Rivera-Polanco D, Pereira D, Vargas G. G, Werden L, Du D, Arnold L et al. 2022. Intra-annual variation in microclimatic conditions in relation to vegetation type and structure in two tropical dry forests undergoing secondary succession. Forest Ecol. Manag. 511: 120132. doi:10.1016/j.foreco.2022.120132.
Xie M, Zhu Y, Liu S, Deng D, Zhu L, Zhao M , Wang Z. 2022. Simulating the impacts of drought and warming in summer and autumn on the productivity of subtropical coniferous forests. Forests 13: 2147. doi:10.3390/f13122147.
Zhang J, Bras RL, Longo M , Heartsill Scalley T. 2022. Future hurricanes will increase palm abundance and decrease aboveground biomass in a tropical forest. Geophys. Res. Lett. 49: e2022GL100090. doi:10.1029/2022GL100090.
Zhang J, Bras RL, Longo M , Heartsill Scalley T. 2022. The impact of hurricane disturbances on a tropical forest: Implementing a palm plant functional type and hurricane disturbance module in ed2-hudi v1.0. Geosci. Model Dev. 15: 5107–5126. doi:10.5194/gmd-15-5107-2022.
Dashti H, Pandit K, Glenn NF, Shinneman DJ, Flerchinger GN, Hudak AT, de Graaf MA, Flores A, Ustin S, Ilangakoon N et al. 2021. Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area. Agric. For. Meteorol. 297: 108270. doi:10.1016/j.agrformet.2020.108270.
Kim J, Kim Y, Zona D, Oechel W, Park SJ, Lee BY, Yi Y, Erb A , Schaaf CL. 2021. Carbon response of tundra ecosystems to advancing greenup and snowmelt in Alaska. Nat. Commun. 12: 6879. doi:10.1038/s41467-021-26876-7.
Meunier F, Verbeeck H, Cowdery EM, Schnitzer SA, Smith Martin CM, Powers J, Xu X, Slot M, De Deurwaerder H, Detto M et al. 2021. Unraveling the relative role of light and water competition between lianas and trees in tropical forests: a vegetation model analysis. J. Ecol. 109: 519–540. doi:10.1111/1365-2745.13540.
Restrepo-Coupe N, Albert LP, Longo M, Baker I, Levine NM, Mercado LM, de Arau ́jo AC, Christoffersen BO, Costa MH, Fitzjarrald DR et al. 2021. Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison. Glob. Change Biol. 27: 1802–1819. doi:10.1111/gcb.15555.
Xu X, Konings AG, Longo M, Feldman A, Xu L, Saatchi S, Wu D, Wu J , Moorcroft P. 2021. Leaf surface water, not plant water stress, drives diurnal variation in tropical forest canopy water content. New Phytol. doi:10.1111/nph.17254, in press.
Longo M, Saatchi SS, Keller M, Bowman KW, Ferraz A, Moorcroft PR, Morton D, Bonal D, Brando P, Burban B et al. 2020. Impacts of degradation on water, energy, and carbon cycling of the Amazon tropical forests. J. Geophys. Res.-Biogeosci. 125: e2020JG005677. doi:10.1029/2020JG005677.
Paul-Limoges E, Wolf S, Schneider FD, Longo M, Moorcroft PR, Gharun M , Damm A. 2020. Partitioning evapotranspiration with concurrent eddy covariance measurements in a mixed forest. Agric. For. Meteorol. 280: 107786. doi:10.1016/j.agrformet.2019.107786.
Shiklomanov AN, Bond-Lamberty B, Atkins JW , Gough CM. 2020. Structure and parameter uncertainty in centennial projections of forest community structure and carbon cycling. Glob. Change Biol. 26: 6080–6096. doi:10.1111/gcb.15164.
Shiklomanov AN, Dietze MC, Fer I, Viskari T, Serbin, SP. 2020. Cutting out the middleman: Calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance. Geoscientific Model Development Discussions: 1–35. doi:10.5194/gmd-2020-324.
Berzaghi F, Longo M, Ciais P, Blake S, Bretagnolle F, Vieira S, Scaranello M, Scarascia- Mugnozza G , Doughty CE. 2019. Carbon stocks in central African forests enhanced by elephant disturbance. Nature Geosci. 12: 725–729. doi:10.1038/s41561-019-0395-6.
Bogan SA, Antonarakis AS , Moorcroft PR. 2019. Imaging spectrometry-derived estimates of re- gional ecosystem composition for the Sierra Nevada, California. Remote Sens. Environ. 228: 14–30. doi:10.1016/j.rse.2019.03.031.
di Porcia e Brugnera M, Meunier F, Longo M, Moorthy S, De Deurwaerder H, Schnitzer SA, Bonal D, Faybishenko B , Verbeeck H. 2019. Modelling the impact of liana infestation on the demography and carbon cycle of tropical forests. Glob. Change Biol. 25, 3767–3780. doi:10.1111/gcb.14769.
Farinosi F, Arias ME, Lee E, Longo M, Pereira FF, Livino A, Moorcroft PR , Briscoe J. 2019. Future climate and land use change impacts on river flows in the Tapajós basin in the Brazilian Amazon. Earth's Future 7: 993–1017. doi:10.1029/2019EF001198.
Jiang Y, Kim JB, Trugman AT, Kim Y , Still CJ. 2019. Linking tree physiological constraints with predictions of carbon and water fluxes at an old-growth coniferous forest. Ecosphere 10: e02692. doi:10.1002/ecs2.2692.
Levy-Varon JH, Batterman SA, Medvigy D, Xu X, Hall JS, van Breugel M , Hedin LO. 2019. Tropical carbon sink accelerated by symbiotic dinitrogen fixation. Nat. Commun. 10: 5637. doi:10.1038/s41467-019-13656-7.
Longo M, Knox RG, Medvigy DM, Levine NM, Dietze MC, Kim Y, Swann ALS, Zhang K, Rollinson CR, Bras RL et al. 2019. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – part 1: Model description. Geosci. Model Dev 12, 4309–4346. doi:10.5194/gmd-12-4309-2019.
Longo M, Knox RG, Levine NM, Swann ALS, Medvigy DM, Dietze MC, Kim Y, Zhang K, Bonal D, Burban B et al. 2019. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – part 2: Model evaluation for tropical South America. Geosci. Model Dev. 12: 4347--4374. doi:10.5194/gmd-12-4347-2019.
Medvigy D, Wang G, Zhu Q, Riley WJ, Trierweiler AM, Waring BG, Xu X, Powers JS. 2019. Observed variation in soil properties can drive large variation in modeled forest functioning and composition during tropical forest secondary succession. New Phytol. 223: 1820–1833. doi:10.1111/nph.15848.
Pandit K, Dashti H, Glenn NF, Flores AN, Maguire KC, Shinneman DJ, Flerchinger GN, Fellows AW. 2019. Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the northern Great Basin using the Ecosystem Demography (EDv2.2) model. Geosci. Model Dev. 12: 4585–4601. doi:10.5194/gmd-12-4585-2019.
Trugman AT, Anderegg LDL, Sperry JS, Wang Y, Venturas M , Anderegg WRL. 2019. Leveraging plant hydraulics to yield predictive and dynamic plant leaf allocation in vegetation models with climate change. Glob. Change Biol. 25: 4008–4021. doi:10.1111/gcb.14814.
Arias ME, Lee E, Farinosi F, Pereira FF, Moorcroft PR. 2018. Decoupling the effects of deforestation and climate variability in the Tapajós river basin in the Brazilian Amazon. Hydrol. Process. 32: 1648–1663. doi:10.1002/hyp.11517.
Feng X, Uriarte M, Gonzalez G, Reed S, Thompson J, Zimmerman JK, Murphy L. 2018. Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling. Glob Change Biol. 24:e213-e232. doi:10.1111/gcb.13863.
Fer I, Kelly R, Moorcroft PR, Richardson AD, Cowdery EM, Dietze MC. 2018. Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation. Biogeosciences 15:5801–5830. doi:10.5194/bg-15-5801-2018.
Fisher RA, Koven CD, Anderegg WRL, Christoffersen BO, Dietze MC, Farrior C, Holm JA, Hurtt G, Knox RG, Lawrence PJ, et al. 2018. Vegetation demographics in earth system models: a review of progress and priorities. Glob. Change Biol. 24:35–54. doi:10.1111/gcb.13910.
Lee E, Livino A, Han SC, Zhang K, Briscoe J, Kelman J, Moorcroft PR. 2018. Land cover change explains the increasing discharge of the Paraná River. Reg. Environ. Change 18:1871–1881. doi:10.1007/s10113-018-1321-y.
Longo M, Knox RG, Levine NM, Alves LF, Bonal D, Camargo PB, Fitzjarrald DR, Hayek MN, Restrepo-Coupe R, Saleska SR, et al. 2018. Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts. New Phytol. 219: 914–931. doi:10.1111/nph.15185.
Powell TL, Koven CD, Johnson DJ, Faybishenko B, Fisher RA, Knox RG, McDowell NG, Condit R, Hubbell SP, Wright SJ, et al. 2018. Variation in hydroclimate sustains tropical forest biomass and promotes functional diversity. New Phytol. 219:932–946. doi:10.1111/nph.15271.
Raczka B, Dietze MC, Serbin SP , Davis KJ. 2018. What limits predictive certainty of long-term carbon uptake? J. Geophys. Res.-Biogeosci. 123: 3570–3588. doi:10.1029/2018JG004504.
Trugman AT, Medvigy D, Hoffmann WA, Pellegrini AFA. 2018. Sensitivity of woody carbon stocks to bark investment strategy in Neotropical savannas and forests. Biogeosciences 15:233–243. doi:10.5194/bg-15-233-2018.
Pereira FF, Farinosi F, Arias ME, Lee E, Briscoe J, Moorcroft PR. 2017. Technical note: A hydrological routing scheme for the ecosystem demography model (ED2+R) tested in the Tapajós River basin in the Brazilian Amazon. Hydrol. Earth Syst. Sci. 21:4629–4648, Sep 2017. doi:10.5194/hess-21-4629-2017.
Restrepo-Coupe N, Levine NM, Christoffersen BO, Albert LP, Wu J, Costa MH, Galbraith D, Imbuzeiro H, Martins G, de Araújo AC, et al. 2017. Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison. Glob. Change Biol. 23:191–208. doi:10.1111/gcb.13442.
Rogers A, Medlyn BE, Dukes JS, Bonan G, von Caemmerer S, Dietze MC, Kattge J, Leakey ADB, Mercado LM, Niinemets U, et al. 2017. A roadmap for improving the representation of photosynthesis in earth system models. New Phytol. 213: 22–42. doi:10.1111/nph.14283.
Rollinson CR, Liu Y, Raiho A, Moore DJP, McLachlan J, Bishop DA, Dye A, Matthes JH, Hessl A, Hickler T et al. 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. Glob. Change Biol. 23: 2755–2767. doi:10.1111/gcb.13626.
Hurtt GC, Thomas RQ, Fisk JP, Dubayah RO, Sheldon SL. 2016. The impact of fine-scale disturbances on the predictability of vegetation dynamics and carbon flux. PLoS ONE 11:1–11. doi:10.1371/journal.pone.0152883.
Levine NM, Zhang K, Longo M, Baccini A, Phillips OL, Lewis SL, Alvarez E, de Andrade ACS, Brienen R, Erwin T, et al. 2016. Ecosystem heterogeneity determines the resilience of the Amazon to climate change. Proc. Natl. Acad. Sci. U. S. A. 113:793–797. doi:10.1073/pnas.1511344112.
Miller AD, Dietze MC, DeLucia EH, Anderson-Teixeira KJ. 2016. Alteration of forest succession and carbon cycling under elevated CO2. Glob. Change Biol. 22:351–363. doi:10.1111/gcb.13077.
Morton DC, Rubio J, Cook BD, Gastellu-Etchegorry JP, Longo M, Choi H, Hunter MO, Keller M. 2016. Amazon forest structure generates diurnal and seasonal variability in light utilization. Biogeosciences 12:2195–2206. doi:10.5194/bg-13-2195-2016.
Xu X, Medvigy D, Powers JS, Becknell JM, Guan K. 2016. Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests. New Phytol. 212:80–95. doi:10.1111/nph.14009.
Frasson RPdM, Bohrer G, Medvigy D, Matheny AM, Morin TH, Vogel CS, Gough CM, Maurer KD, Curtis PS. 2015. Modeling forest carbon cycle response to tree mortality: Effects of plant functional type and disturbance intensity. J. Geophys. Res.-Biogeosci. 120:2178–2193. doi:10.1002/2015JG003035.
Knox RG, Longo M, Swann ALS, Zhang K, Levine NM, Moorcroft PR, Bras RL. 2015. Hydrometeorological effects of historical land-conversion in an ecosystem-atmosphere model of Northern South America. Hydrol. Earth Syst. Sci. 19:241–273. doi:10.5194/hess-19-241-2015.
Swann ALS, Longo M, Knox RG, Lee E, Moorcroft PR. 2015. Future deforestation in the Amazon and consequences for South American climate. Agric. For. Meteorol. 214–215:12–24. doi:10.1016/j.agrformet.2015.07.006.
Rowland L, Harper A, Christoffersen BO, Galbraith DR, Imbuzeiro HMA, Powell TL, Doughty C, Levine NM, Malhi Y, Saleska SR, et al. 2015. Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses. Geosci. Model Dev. 8(4):1097–1110. doi:10.5194/gmd-8-1097-2015.
Viskari T, Hardiman B, Desai AR , Dietze MC. 2015. Model-data assimilation of multiple phenologi- cal observations to constrain and predict leaf area index. Ecol. Appl. 25: 546–558. doi:10.1890/14-0497.1.
Zhang K, Castanho ADdA, Galbraith DR, Moghim S, Levine N, Bras RL, Coe M, Costa MH, Malhi Y, Longo M, et al. 2015. The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2 and land-use. Glob. Change Biol. 21:2569–2587. doi:10.1111/gcb.12903.
Antonarakis AS. 2014. Uncertainty in initial forest structure and composition when predicting carbon dynamics in a temperate forest. Ecol. Model. 291:134–141. doi:10.1016/j.ecolmodel.2014.07.030.
Antonarakis AS, Munger JW, Moorcroft PR. 2014. Imaging spectroscopy- and lidar-derived estimates of canopy composition and structure to improve predictions of forest carbon fluxes and ecosystem dynamics. Geophys. Res. Lett. 41:2535–2542. doi:10.1002/2013GL058373.
De Kauwe MG, Medlyn BE, Zaehle S, Walker AP, Dietze MC, Wang YP, Luo Y, Jain AK, El-Masri B, Hickler T et al. 2014. Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites. New Phytol. 203: 883–899. doi:10.1111/nph.12847.
Dietze MC, Serbin SP, Davidson C, Desai AR, Feng X, Kelly R, Kooper R, LeBauer D, Mantooth J, McHenry K, Wang D. 2014. A quantitative assessment of a terrestrial biosphere model’s data needs across North American biomes. J. Geophys. Res.-Biogeosci. 119:286–300. doi:10.1002/2013JG002392.
Longo M. 2014. Amazon forest response to changes in rainfall regime: results from an individual-based dynamic vegetation model. PhD dissertation, Harvard University, Cambridge, MA. Link to PDF.
Matheny AM, Bohrer G, Stoy PC, Baker I, Black A, Desai AR, Dietze M, Gough C, Ivanov V, Jassal P, et al. 2014. Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land-surface models: an nacp analysis. J. Geophys. Res.- Biogeosci. 119:1458–1473. doi:10.1002/2014JG002623.
Walker AP, Hanson PJ, De Kauwe MG, Medlyn BE, Zaehle S, Asao S, Dietze M, Hickler T, Huntingford C, Iversen CM et al. 2014. Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration. J. Geophys. Res.-Biogeosci. 119: 937–964. doi:10.1002/2013JG002553.
Zaehle S, Medlyn BE, De Kauwe MG, Walker AP, Dietze MC, Hickler T, Luo Y, Wang YP, El-Masri B, Thornton P, et al. 2014. Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate free-air CO2 enrichment studies. New Phytol. 202:803–822. doi:10.1111/nph.12697.
De Kauwe MG, Medlyn BE, Zaehle S, Walker AP, Dietze MC, Hickler T, Jain AK, Luo Y, Parton WJ, Prentice IC et al. 2013. Forest water use and water use efficiency at elevated CO2: a model-data intercomparison at two contrasting temperate forest FACE sites. Glob. Change Biol. 19: 1759–1779. doi:10.1111/gcb.12164.
LeBauer DS, Wang D, Richter KT, Davidson CC, Dietze MC. 2013. Facilitating feedbacks between field measurements and ecosystem models. Ecol. Monogr. 83:133–154. doi:10.1890/12-0137.1.
Medvigy D, Jeong SJ, Clark KL, Skowronski NS, Schäfer KVR. 2013. Effects of seasonal variation of photosynthetic capacity on the carbon fluxes of a temperate deciduous forest. J. Geophys. Res.-Biogeosci. 118:1703–1714. doi:10.1002/2013JG002421.
Powell TL, Galbraith DR, Christoffersen BO, Harper A, Imbuzeiro HMA, Rowland L, Almeida S, Brando PM, da Costa ACL, Costa MH, et al. 2013. Confronting model predictions of carbon fluxes with measurements of Amazon forests subjected to experimental drought. New Phytol. 200:350–365. doi:10.1111/nph.12390.
Wang D, LeBauer D , Dietze M. 2013. Predicting yields of short-rotation hybrid poplar (Populus spp.) for the United States through model–data synthesis. Ecol. Appl. 23: 944–958. doi:10.1890/12-0854.1.
Keenan T, Baker I, Barr A, Ciais P, Davis K, Dietze M, Dragoni D, Gough CM, Grant R, Hollinger D et al. 2012. Terrestrial biosphere model performance for inter-annual variability of land- atmosphere CO2 exchange. Glob. Change Biol. 18: 1971–1987. doi:10.1111/j.1365-2486.2012.02678.x.
Kim Y, Knox RG, Longo M, Medvigy DM, Hutyra LR, Pyle EH, Wofsy SC, Bras RL, Moorcroft PR. 2012. Seasonal carbon dynamics and water fluxes in an Amazon rainforest. Glob. Change Biol. 18:1322–1334. doi:10.1111/j.1365-2486.2011.02629.x.
Knox RG. 2012. Land conversion in Amazonia and Northern South America; influences on regional hydrology and ecosystem response. PhD dissertation, Massachusetts Institute of Technology, Cambridge, MA. Link to PDF.
Medvigy D, Moorcroft PR. 2012. Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America. Philos. Trans. R. Soc. B-Biol. Sci. 367:222–235. doi:10.1098/rstb.2011.0253.
Richardson AD, Anderson RS, Arain MA, Barr AG, Bohrer G, Chen G, Chen JM, Ciais P, Davis KJ, Desai AR et al. 2012. Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program site synthesis. Glob. Change Biol. 18: 566–584. doi:10.1111/j.1365-2486.2011.02562.x.
Schaefer K, Schwalm CR, Williams C, Arain MA, Barr A, Chen JM, Davis KJ, Dimitrov D, Hilton TW, Hollinger DY, et al. 2012. A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis. J. Geophys. Res.-Biogeosci. 117:G03010. doi:10.1029/2012JG001960.
Antonarakis AS, Saatchi SS, Chazdon RL, Moorcroft PR. 2011. Using lidar and radar measurements to constrain predictions of forest ecosystem structure and function. Ecol. Appl. 21:1120–1137. doi:10.1890/10-0274.1.
Dietze MC, Vargas R, Richardson AD, Stoy PC, Barr AG, Anderson RS, Arain MA, Baker IT, Black TA, Chen JM, et al. 2011. Characterizing the performance of ecosystem models across time scales: A spectral analysis of the north american carbon program site-level synthesis. J. Geophys. Res.-Biogeosci. 116:G04029, Dec 2011. doi:10.1029/2011JG001661.
Albani M, Moorcroft PR, Ellison AM, Orwig DA, Foster DR. 2010. Predicting the impact of hemlock woolly adelgid on carbon dynamics of eastern United States forests. Can. J. Forest Res. 40:119–133. doi:10.1139/X09-167.
Fisher R, McDowell N, Purves D, Moorcroft P, Sitch S, Cox P, Huntingford C, Meir P, and Woodward FI. 2010. Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations. New Phytol. 187:666–681. doi:10.1111/j.1469-8137.2010.03340.x.
Hurtt GC, Fisk J, Thomas RQ, Dubayah R, Moorcroft PR, Shugart HH. 2010. Linking models and data on vegetation structure. J. Geophys. Res.-Biogeosci. 115:G00E10. doi:10.1029/2009JG000937.
Ise T, Moorcroft PR. 2010. Simulating boreal forest dynamics from perspectives of ecophysiology, resource availability, and climate change. Ecol. Res. 25:501–511. doi:10.1007/s11284-009-0680-8.
Medvigy D, Wofsy SC, Munger JW, Moorcroft PR. 2010. Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability. Proc. Natl. Acad. Sci. U. S. A. 107: 8275–8280. doi:10.1073/pnas.0912032107.
Schwalm CR, Williams CA, Schaefer K, Anderson R, Arain MA, Baker I, Barr A, Black TA, Chen G, Chen JM, et al. 2010. A model-data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis. J. Geophys. Res.-Biogeosci. 115:G00H05. doi:10.1029/2009JG001229.
Medvigy DM, Wofsy SC, Munger JW, Hollinger DY, Moorcroft PR. 2009. Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem demography model version 2. J. Geophys. Res.-Biogeosci. 114:G01002. doi:10.1029/2008JG000812.
Ise T, Dunn AL, Wofsy SC, Moorcroft PR. 2008. High sensitivity of peat decomposition to climate change through water-table feedback. Nature Geosci. 1:763–766. doi:10.1038/ngeo331.
Desai AR, Moorcroft PR, Bolstad PV, Davis KJ. 2007. Regional carbon fluxes from an ob- servationally constrained dynamic ecosystem model: Impacts of disturbance, CO2 fertilization, and heterogeneous land cover. J. Geophys. Res.-Biogeosci. 112:G01017. doi:10.1029/2006JG000264.
Albani M, Medvigy D, Hurtt GC, Moorcroft PR. 2006. The contributions of land-use change, CO2 fertilization, and climate variability to the eastern US carbon sink. Glob. Change Biol. 12:2370–2390. doi:10.1111/j.1365-2486.2006.01254.x.
Ise T, Moorcroft PR. 2006. The global-scale temperature and moisture dependencies of soil organic carbon decomposition: an analysis using a mechanistic decomposition model. Biogeochemistry 80:217–231. doi:10.1007/s10533-006-9019-5.
Medvigy DM. 2006. The state of the regional carbon cycle: results from a constrained coupled ecosystem- atmosphere model. PhD dissertation, Harvard University, Cambridge, MA.
Hurtt GC, Dubayah R, Drake J, Moorcroft PR, Pacala SW, Blair JB, Fearon MG. 2004. Beyond potential vegetation: combining lidar data and a height-structured model for carbon studies. Ecol. Appl. 14:873–883. doi:10.1890/02-5317.
Baidya Roy S, Hurtt GC, Weaver CP , Pacala SW. 2003. Impact of historical land cover change on the July climate of the United States. J. Geophys. Res.-Atmos. 108: 4793. doi:10.1029/2003JD003565.
Hurtt GC, Pacala SW, Moorcroft PR, Caspersen J, Shevliakova E, Houghton RA, Moore B. 2002. Projecting the future of the U.S. carbon sink. Proc. Natl. Acad. Sci. U. S. A. 99:1389–1394. doi:10.1073/pnas.012249999.
Moorcroft PR, Hurtt GC, Pacala SW. 2001. A method for scaling vegetation dynamics: The Ecosystem Demography model (ED). Ecol. Monogr. 71(4):557–586. doi:10.1890/0012-9615(2001)071[0557:AMFSVD]2.0.CO;2.
Hurtt GC, Moorcroft PR, Pacala SW, Levin SA. 1998. Terrestrial models and global change: challenges for the future. Glob. Change Biol. 4:581–590. doi:10.1046/j.1365-2486.1998.t01-1-00203.x.