# peerreviewed_2014.bib

@article{Teixeira_GCB_2014,
author = {Anderson-Teixeira, Kristina J. and Davies, Stuart J. and Bennett,
Amy C. and Gonzalez-Akre, Erika B. and Muller-Landau, Helene C. and
Joseph Wright, S. and Abu Salim, Kamariah and Almeyda Zambrano, Ang{\~e}lica
M. and Alonso, Alfonso and Baltzer, Jennifer L. and Basset, Yves
and Bourg, Norman A. and Broadbent, Eben N. and Brockelman, Warren
Y. and Bunyavejchewin, Sarayudh and Burslem, David F. R. P. and Butt,
Nathalie and Cao, Min and Cardenas, Dairon and Chuyong, George B.
and Clay, Keith and Cordell, Susan and Dattaraja, Handanakere S.
and Deng, Xiaobao and Detto, Matteo and Du, Xiaojun and Duque, Alvaro
and Erikson, David L. and Ewango, Corneille E.N. and Fischer, Gunter
A. and Fletcher, Christine and Foster, Robin B. and Giardina, Christian
P. and Gilbert, Gregory S. and Gunatilleke, Nimal and Gunatilleke,
Savitri and Hao, Zhanqing and Hargrove, William W. and Hart, Terese
B. and Hau, Billy C.H. and He, Fangliang and Hoffman, Forrest M.
and Howe, Robert W. and Hubbell, Stephen P. and Inman-Narahari, Faith
M. and Jansen, Patrick A. and Jiang, Mingxi and Johnson, Daniel J.
and Kanzaki, Mamoru and Kassim, Abdul Rahman and Kenfack, David and
Kibet, Staline and Kinnaird, Margaret F. and Korte, Lisa and Kral,
Kamil and Kumar, Jitendra and Larson, Andrew J. and Li, Yide and
Li, Xiankun and Liu, Shirong and Lum, Shawn K.Y. and Lutz, James
A. and Ma, Keping and Maddalena, Damian M. and Makana, Jean-Remy
and Malhi, Yadvinder and Marthews, Toby and Mat Serudin, Rafizah
and McMahon, Sean M. and McShea, William J. and Memiaghe, Her{v\
e} R. and Mi, Xiangcheng and Mizuno, Takashi and Morecroft, Michael
and Myers, Jonathan A. and Novotny, Vojtech and de Oliveira, Alexandre
A. and Ong, Perry S. and Orwig, David A. and Ostertag, Rebecca and
den Ouden, Jan and Parker, Geoffrey G. and Phillips, Richard P. and
Sack, Lawren and Sainge, Moses N. and Sang, Weiguo and Sri-ngernyuang,
Kriangsak and Sukumar, Raman and Sun, I-Fang and Sungpalee, Witchaphart
and Suresh, Hebbalalu Sathyanarayana and Tan, Sylvester and Thomas,
Sean C. and Thomas, Duncan W. and Thompson, Jill and Turner, Benjamin
L. and Uriarte, Maria and Valencia, Renato and Vallejo, Marta I.
and Vicentini, Alberto and Vr{\v s}ka, Tom{\ a}{\v s} and Wang,
Xihua and Wang, Xugao and Weiblen, George and Wolf, Amy and Xu, Han
and Yap, Sandra and Zimmerman, Jess},
title = {{CTFS-ForestGEO}: a worldwide network monitoring forests in an era
of global change},
journal = {Global Change Biology},
year = {2014},
abstract = {Global change is impacting forests worldwide, threatening biodiversity
and ecosystem services including climate regulation. Understanding
how forests respond is critical to forest conservation and climate
protection. This review describes an international network of 59
long-term forest dynamics research sites (CTFS-ForestGEO) useful
for characterizing forest responses to global change. Within very
large plots (median size 25Â ha), all stems â¥1Â cm diameter are
identified to species, mapped, and regularly recensused according
to standardized protocols. CTFS-ForestGEO spans 25Â°Sâ61Â°N latitude,
is generally representative of the range of bioclimatic, edaphic,
and topographic conditions experienced by forests worldwide, and
is the only forest monitoring network that applies a standardized
protocol to each of the world's major forest biomes. Supplementary
standardized measurements at subsets of the sites provide additional
information on plants, animals, and ecosystem and environmental variables.
CTFS-ForestGEO sites are experiencing multifaceted anthropogenic
global change pressures including warming (average 0.61Â Â°C), changes
in precipitation (up to Â±30% change), atmospheric deposition of
nitrogen and sulfur compounds (up to 3.8Â g NÂ mâ2Â yrâ1 and
3.1Â g SÂ mâ2Â yrâ1), and forest fragmentation in the surrounding
landscape (up to 88% reduced tree cover within 5Â km). The broad
suite of measurements made at CTFS-ForestGEO sites makes it possible
to investigate the complex ways in which global change is impacting
forest dynamics. Ongoing research across the CTFS-ForestGEO network
is yielding insights into how and why the forests are changing, and
continued monitoring will provide vital contributions to understanding
worldwide forest diversity and dynamics in an era of global change.},
doi = {10.1111/gcb.12712},
file = {pubs/Teixeira_GCB_2014.pdf},
issn = {1365-2486},
keywords = {biodiversity, Center for Tropical Forest Science (CTFS), climate change,
demography, forest dynamics plot, Forest Global Earth Observatory
(ForestGEO), long-term monitoring, spatial analysis},
owner = {jkumar},
timestamp = {2014.09.26},
url = {http://dx.doi.org/10.1111/gcb.12712}
}

@article{Warren_NewPhytologist_2014,
author = {Warren, Jeffrey M. and Hanson, Paul J. and Iversen, Colleen M. and
Kumar, Jitendra and Walker, Anthony P. and Wullschleger, Stan D.},
title = {Root structural and functional dynamics in terrestrial biosphere
models: evaluation and recommendations},
journal = {New Phytologist},
author = {Warren, Jeffrey and Hanson, Paul and Iversen, Colleen and Kumar,
Jitendra and Walker, Anthony and Wullschleger, Stan},
title = {Root Structural and Functional Dynamics in Terrestrial Biosphere
Models – Evaluation and Recommendations},
journal = {New Phytologist (Accepted)},
year = {2014},
file = {pubs/Warren_NewPhytologist_2014.pdf},
abstract = {
There is wide breadth of root function within ecosystems that
should be considered when modeling the terrestrial biosphere. Root
structure and function are closely associated with control of plant
water and nutrient uptake from the soil, plant carbon (C) assimilation,
partitioning and release to the soils, and control of biogeochemical
cycles through interactions within the rhizosphere. Root function
is extremely dynamic and dependent on internal plant signals, root
traits and morphology, and the physical, chemical and biotic soil
environment. While plant roots have significant structural and functional
plasticity to changing environmental conditions, their dynamics are
noticeably absent from the land component of process-based Earth
system models used to simulate global biogeochemical cycling. Their
dynamic representation in large-scale models should improve model
veracity. Here, we describe current root inclusion in models across
scales, ranging from mechanistic processes of single roots to parameterized
root processes operating at the landscape scale. With this foundation
we discuss how existing and future root functional knowledge, new
data compilation efforts, and novel modeling platforms can be leveraged
to enhance root functionality in large-scale terrestrial biosphere
models by improving parameterization within models, and introducing
new components such as dynamic root distribution and root functional
traits linked to resource extraction.},
doi = {10.1111/nph.13034},
issn = {1469-8137},
keywords = {hydraulic redistribution, nitrogen uptake, root function, root model,
root plasticity, water uptake},
owner = {jkumar},
timestamp = {2014.09.26},
url = {http://dx.doi.org/10.1111/nph.13034}
}

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@article{Hoffman_JGRB_20140201,
author = {Forrest M. Hoffman and James T. Randerson and Vivek K. Arora and Qing Bao and Patricia Cadule and Duoying Ji and Chris D. Jones and Michio Kawamiya and Samar Khatiwala and Keith Lindsay and Atsushi Obata and Elena Shevliakova and  Katharina D. Six and Jerry F. Tjiputra and Evgeny M. Volodin and Tongwen Wu},
title = {Causes and Implications of Persistent Atmospheric Carbon Dioxide Biases in {E}arth {S}ystem {M}odels},
journal = jgrb,
volume = 119,
number = 2,
pages = {141--162},
doi = {10.1002/2013JG002381},
day = 1,
month = feb,
year = 2014,
abstract = {The strength of feedbacks between a changing climate and future CO$_2$ concentrations are uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations---in which atmospheric CO$_2$ levels were computed prognostically---for historical (1850--2005) and future periods (RCP~8.5 for 2006--2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO$_2$ over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO$_2$. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO$_2$ biases and future CO$_2$ levels for the multi-model ensemble. We used this relationship to create a contemporary CO$_2$ tuned model (CCTM) estimate of the atmospheric CO$_2$ trajectory for the 21$^\textnormal{st}$ century. The CCTM yielded CO$_2$ estimates of 600 $\pm$ 14 ppm at 2060 and 947 $\pm$ 35 ppm at 2100, which were 21 ppm and 32 ppm below the multi-model mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO$_2$, CO$_2$-induced radiative forcing, and CO$_2$-induced temperature increases for the RCP~8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO$_2$ during the 21$^\textnormal{st}$ century was tied to biases that existed during the observational era, and that model differences in the representation of concentration--carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO$_2$ from Mauna Loa, our analysis suggests uncertainties in future climate projections can be reduced.}
}

@article{Lindsay_JClim_20141215,
author = {Keith Lindsay and Gordon B. Bonan and Scott C. Doney and Forrest M. Hoffman and David M. Lawrence and Matthew C. Long and Natalie M. Mahowald and J. Keith Moore and James T. Randerson and Peter E. Thornton},
title = {Preindustrial-Control and Twentieth-Century Carbon Cycle Experiments with the {E}arth System Model {CESM1(BGC)}},
journal = jclim,
volume = 27,
number = 24,
pages = {8981--9005},
doi = {10.1175/JCLI-D-12-00565.1},
day = 15,
month = dec,
year = 201,
abstract = {Version 1 of the Community Earth System Model, in the configuration where its full carbon cycle is enabled, is introduced and documented. In this configuration, the terrestrial biogeochemical model, which includes carbon?nitrogen dynamics and is present in earlier model versions, is coupled to an ocean biogeochemical model and atmospheric CO$_2$ tracers. The authors provide a description of the model, detail how preindustrial-control and twentieth-century experiments were initialized and forced, and examine the behavior of the carbon cycle in those experiments. They examine how sea- and land-to-air CO$_2$ fluxes contribute to the increase of atmospheric CO$_2$ in the twentieth century, analyze how atmospheric CO$_2$ and its surface fluxes vary on interannual time scales, including how they respond to ENSO, and describe the seasonal cycle of atmospheric CO$_2$ and its surface fluxes. While the model broadly reproduces observed aspects of the carbon cycle, there are several notable biases, including having too large of an increase in atmospheric CO$_2$ over the twentieth century and too small of a seasonal cycle of atmospheric CO$_2$ in the Northern Hemisphere. The biases are related to a weak response of the carbon cycle to climatic variations on interannual and seasonal time scales and to twentieth-century anthropogenic forcings, including rising CO$_2$, land-use change, and atmospheric deposition of nitrogen.}
}

@article{Sun_PNAS_20141104,
author = {Ying Sun and Lianhong Gu and Robert E. Dickinson and Richard J. Norby and Stephen G. Pallardy and Forrest M. Hoffman},
title = {Impact of Mesophyll Diffusion on Estimated Global Land {CO$_2$} Fertilization},
journal = pnas,
volume = 111,
number = 44,
pages = {15774--15779},
doi = {10.1073/pnas.1418075111},
day = 4,
month = nov,
year = 2014,
abstract = {In C3 plants, CO$_2$ concentrations drop considerably along mesophyll diffusion pathways from substomatal cavities to chloroplasts where CO$_2$ assimilation occurs. Global carbon cycle models have not explicitly represented this internal drawdown and therefore overestimate CO$_2$ available for carboxylation and underestimate photosynthetic responsiveness to atmospheric CO$_2$. An explicit consideration of mesophyll diffusion increases the modeled cumulative CO$_2$ fertilization effect (CFE) for global gross primary production (GPP) from 915 to 1,057~PgC for the period of 1901--2010. This increase represents a 16\% correction, which is large enough to explain the persistent overestimation of growth rates of historical atmospheric CO$_2$ by Earth system models. Without this correction, the CFE for global GPP is underestimated by 0.05~PgC/y/ppm. This finding implies that the contemporary terrestrial biosphere is more CO$_2$ limited than previously thought.}
}

@article{Wang_Biogeosci_20140407,
author = {Y. P. Wang and B. C. Chen and W. R. Wieder and M. Leite and B. E. Medlyn and M. Rasmussen and M. J. Smith and F. B. Agusto and F. M. Hoffman and Y. Q. Luo},
title = {Oscillatory Behavior of Two Nonlinear Microbial Models of Soil Carbon Decomposition},
journal = biogeosci,
volume = 11,
number = 7,
pages = {1817--1831},
doi = {10.5194/bg-11-1817-2014},
day = 7,
month = apr,
year = 2014,
abstract = {A number of nonlinear models have recently been proposed for simulating soil carbon decomposition. Their predictions of soil carbon responses to fresh litter input and warming differ significantly from conventional linear models. Using both stability analysis and numerical simulations, we showed that two of those nonlinear models (a two-pool model and a three-pool model) exhibit damped oscillatory responses to small perturbations. Stability analysis showed the frequency of oscillation is proportional to $\sqrt{\left(\epsilon^{-1} - 1\right) K_s / V_s}$ in the two-pool model, and to $\sqrt{\left(\epsilon^{-1} - 1\right) K_l / V_l}$ in the three-pool model, where $\epsilon$ is microbial growth efficiency, $K_s$ and $K_l$ are the half saturation constants of soil and litter carbon, respectively, and $V_s$ and $V_l$ are the maximal rates of carbon decomposition per unit of microbial biomass for soil and litter carbon, respectively. For both models, the oscillation has a period of between 5 and 15 years depending on other parameter values, and has smaller amplitude at soil temperatures between 0 and 15$^\circ$C. In addition, the equilibrium pool sizes of litter or soil carbon are insensitive to carbon inputs in the nonlinear model, but are proportional to carbon input in the conventional linear model. Under warming, the microbial biomass and litter carbon pools simulated by the nonlinear models can increase or decrease, depending whether $\epsilon$ varies with temperature. In contrast, the conventional linear models always simulate a decrease in both microbial and litter carbon pools with warming. Based on the evidence available, we concluded that the oscillatory behavior and insensitivity of soil carbon to carbon input are notable features in these nonlinear models that are somewhat unrealistic. We recommend that a better model for capturing the soil carbon dynamics over decadal to centennial timescales would combine the sensitivity of the conventional models to carbon influx with the flexible response to warming of the nonlinear model.}
}