Dynamic patterns of particulate matter concentration and size distribution in urban street canyons: insights into diurnal and short-term seasonal variations - Wang, X.; Chen, X.; Zhou, Z.; Teng, M.; Xiang, Y.; Peng, C.; Huang, C.; Peng, C. (Environmental Monitoring and Assessment, 2024)

Simulations show potential for reduced emissions and carbon stocks increase in boreal forests under ecosystem management - Boisvenue, C; Bergeron, Y; Bernier, P; Peng, C (Carbon Management, 2012)

Future soil organic carbon stocks in China under climate change - Wu, J.; Liu, S.; Peng, C.; Luo, Y.; Terrer, C.; Yue, C.; Peng, S.; Li, J.; Wang, B.; Shangguan, Z.; Deng, L. (Cell Reports Sustainability, 2024)

Assessing the generality and accuracy of the TRIPLEX model using in situ data of boreal forests in central Canada - Zhou, X; Peng, C; Dang, Q (Environmental Modelling & Software, 2004)

Impacts of Urbanization on Economic Development and Ecological Protection of the Wuhan City Circle, China - Li, Y.; Huang, C.; Liu, S.; Cheng, J.; Xiang, Y.; Peng, C. (Land Degradation and Development, 2024)

Vulnerability of barley yields in Québec - Epule Epule, T.; Poirier, V.; Peng, C.; Etongo, D. (Environmental Monitoring and Assessment, 2024)

Differences in fine root traits between early and late-successional tree species in a Chinese subtropical forest - Xiang, W.; Wu, W.; Tong, J.; Deng, X.; Tian, D.; Zhang, L.; Liu, C.; Peng, C. (Forestry, 2013)

Shifts in Plant Phenology Significantly Affect the Carbon Allocation in Different Plant Organs - Ren, P.; Li, P.; Zhou, X.; Liu, Z.; Tang, J.; Zhang, C.; Zou, Z.; Li, T.; Peng, C. (Ecology Letters, 2024)

Balancing Water Yield and Water Use Efficiency Between Planted and Natural Forests: A Global Analysis - Sun, S.; Xiang, W.; Ouyang, S.; Hu, Y.; Peng, C. (Global Change Biology, 2024)

Observed Vertical Dispersion Patterns of Particulate Matter in Urban Street Canyons and Dominant Influencing Factors - Wang, X.; Chen, X.; Ma, B.; Zhou, Z.; Peng, C. (Forests, 2024)

Modeling dissolved organic carbon in temperate forest soils: TRIPLEX-DOC model development and validation - Wu, H.; Peng, C.; Moore, T. R.; Hua, D.; Li, C.; Zhu, Q.; Peichl, M.; Arain, M. A.; Guo, Z. (Geoscientific Model Development, 2014)
Abstract. Even though dissolved organic carbon (DOC) is the most active carbon (C) cycling in soil organic carbon (SOC) pools, it receives little attention from the global C budget. DOC fluxes are critical to aquatic ecosystem inputs and contribute to the C balance of terrestrial ecosystems, but few ecosystem models have attempted to integrate DOC dynamics into terrestrial C cycling. This study introduces a new process-based model, TRIPLEX-DOC, that is capable of estimating DOC dynamics in forest soils by incorporating both ecological drivers and biogeochemical processes. TRIPLEX-DOC was developed from Forest-DNDC, a biogeochemical model simulating C and nitrogen (N) dynamics, coupled with a new DOC process module that predicts metabolic transformations, sorption/desorption, and DOC leaching in forest soils. The model was validated against field observations of DOC concentrations and fluxes at white pine forest stands located in southern Ontario, Canada. The model was able to simulate seasonal dynamics of DOC concentrations and the magnitudes observed within different soil layers, as well as DOC leaching in the age sequence of these forests. Additionally, TRIPLEX-DOC estimated the effect of forest harvesting on DOC leaching, with a significant increase following harvesting, illustrating that land use change is of critical importance in regulating DOC leaching in temperate forests as an important source of C input to aquatic ecosystems.

Characteristics of Meteorological Drought Evolution in the Yangtze River Basin - Bai, W.; Zhang, C.; Xiao, X.; Zou, Z.; Liu, Z.; Li, P.; Tang, J.; Li, T.; Zhou, X.; Peng, C. (Water (Switzerland), 2024)

Long-term nitrogen addition has a positive legacy effect on soil respiration in subtropical Moso bamboo forests - Li, Q.; Zhang, C.; Shi, M.; Lv, J.; Peng, C.; Zhang, J.; Chang, S.X.; Cao, T.; Li, T.; Song, X. (Geoderma, 2024)

Nocturnal peak methane flux diel patterns in rice paddy fields - Li, H.; Peng, C.; Helbig, M.; Zhao, M.; Guo, H.; Zhao, B. (Agricultural and Forest Meteorology, 2024)

Drought and warming interaction cause substantial economic losses in the carbon market potential of China's northern grasslands - Guo, J.; Li, T.; Wu, T.; Wang, Z.; Zou, Z.; Peng, C.; Zhou, X.; Li, P.; Liu, Z.; Tang, J.; Zhang, C. (Science of the Total Environment, 2024)

Biochar amendment alleviates soil microbial nitrogen and phosphorus limitation and increases soil heterotrophic respiration under long-term nitrogen input in a subtropical forest - Li, Q.; Ji, H.; Zhang, C.; Cui, Y.; Peng, C.; Chang, S.X.; Cao, T.; Shi, M.; Li, Y.; Wang, X.; Zhang, J.; Song, X. (Science of the Total Environment, 2024)

A long-term evaluation of biomass production in first and second rotations of Chinese fir plantations at the same site - Tian, D.; Xiang, W.; Chen, X.; Yan, W.; Fang, X.; Kang, W.; Dan, X.; Peng, C.; Peng, Y. (Forestry, 2011)

Determining stem biomass of Pinus massoniana L. through variations in basic density - Zhang, L.; Deng, X.; Lei, X.; Xiang, W.; Peng, C.; Lei, P.; Yan, W. (Forestry, 2012)

Photosynthesis, water use efficiency and stable carbon isotope composition are associated with anatomical properties of leaf and xylem in six poplar species - Cao, X.; Jia, J. B.; Li, H.; Li, M. C.; Luo, J.; Liang, Z. S.; Liu, T. X.; Liu, W. G.; Peng, C. H.; Luo, Z. B. (Plant Biology, 2012)
Abstract Although fast‐growing Populus species consume a large amount of water for biomass production, there are considerable variations in water use efficiency (WUE) across different poplar species. To compare differences in growth, WUE and anatomical properties of leaf and xylem and to examine the relationship between photosynthesis/WUE and anatomical properties of leaf and xylem, cuttings of six poplar species were grown in a botanical garden. The growth performance, photosynthesis, intrinsic WUE (WUE i ), stable carbon isotope composition (δ 13 C) and anatomical properties of leaf and xylem were analysed in these poplar plants. Significant differences were found in growth, photosynthesis, WUE i and anatomical properties among the examined species. Populus cathayana was the clone with the fastest growth and the lowest WUE i /δ 13 C, whereas P. × euramericana had a considerable growth increment and the highest WUE i /δ 13 C. Among the analysed poplar species, the highest total stomatal density in P. cathayana was correlated with its highest stomatal conductance (g s ) and lowest WUE i /δ 13 C. Moreover, significant correlations were observed between WUE i and abaxial stomatal density and stem vessel lumen area. These data suggest that photosynthesis, WUE i and δ 13 C are associated with leaf and xylem anatomy and there are tradeoffs between growth and WUE i . It is anticipated that some poplar species, e.g. P. × euramericana , are better candidates for water‐limited regions and others, e.g. P. cathayana , may be better for water‐abundant areas.

Chapter Eighteen Uncertainty and Sensitivity Issues in Process-based Models of Carbon and Nitrogen Cycles in Terrestrial Ecosystems - Larocque, G.R.; Bhatti, J.S.; Gordon, A.M.; Luckai, N.; Wattenbach, M.; Liu, J.; Peng, C.; Arp, P.A.; Liu, S.; Zhang, C.-F.; Komarov, A.; Grabarnik, P.; et al. (Developments in Integrated Environmental Assessment, 2008)

The North American Carbon Program Multi-scale synthesis and Terrestrial Model Intercomparison Project – Part 1: Overview and experimental design - Huntzinger, D. N.; Schwalm, C.; Michalak, A. M.; Schaefer, K.; King, A. W.; Wei, Y.; Jacobson, A.; Liu, S.; Cook, R. B.; Post, W. M.; Berthier, G.; Hayes, D.; et al. (Biogeosciences, 2013)
Abstract. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land-atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g. nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g. photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e. model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.

Modelling methane emissions from natural wetlands by development and application of the TRIPLEX-GHG model - Zhu, Q.; Liu, J.; Peng, C.; Chen, H.; Fang, X.; Jiang, H.; Yang, G.; Zhu, D.; Wang, W.; Zhou, X. (Geoscientific Model Development, 2014)
Abstract. A new process-based model TRIPLEX-GHG was developed based on the Integrated Biosphere Simulator (IBIS), coupled with a new methane (CH4) biogeochemistry module (incorporating CH4 production, oxidation, and transportation processes) and a water table module to investigate CH4 emission processes and dynamics that occur in natural wetlands. Sensitivity analysis indicates that the most sensitive parameters to evaluate CH4 emission processes from wetlands are r (defined as the CH4 to CO2 release ratio) and Q10 in the CH4 production process. These two parameters were subsequently calibrated to data obtained from 19 sites collected from approximately 35 studies across different wetlands globally. Being heterogeneously spatially distributed, r ranged from 0.1 to 0.7 with a mean value of 0.23, and the Q10 for CH4 production ranged from 1.6 to 4.5 with a mean value of 2.48. The model performed well when simulating magnitude and capturing temporal patterns in CH4 emissions from natural wetlands. Results suggest that the model is able to be applied to different wetlands under varying conditions and is also applicable for global-scale simulations.

Estimating wetland CH4 emissions on the Qinghai-Tibetan Plateau based on a processed model coupled with inundation dynamics between 1960 and 2100 - Zhang, J.; Chen, H.; Peng, C.; Huang, Y.; Wang, Y.; Liu, X.; Wang, M.; Wang, L.; Yu, D.; Zhu, Q. (Science of the Total Environment, 2024)

Evaluating the agreement between measurements and models of net ecosystem exchange at different times and timescales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis - Stoy, P. C.; Dietze, M. C.; Richardson, A. D.; Vargas, R.; Barr, A. G.; Anderson, R. S.; Arain, M. A.; Baker, I. T.; Black, T. A.; Chen, J. M.; Cook, R. B.; Gough, C. M.; et al. (Biogeosciences, 2013)
Abstract. Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model–data agreement, but usually do not identify the time and frequency patterns of model–data disagreement, leaving unclear the steps required to improve model response to environmental drivers that vary on characteristic frequencies. Wavelet coherence can quantify the times and timescales at which two time series, for example time series of models and measurements, are significantly different. We applied wavelet coherence to interpret the predictions of 20 ecosystem models from the North American Carbon Program (NACP) Site-Level Interim Synthesis when confronted with eddy-covariance-measured net ecosystem exchange (NEE) from 10 ecosystems with multiple years of available data. Models were grouped into classes with similar approaches for incorporating phenology, the calculation of NEE, the inclusion of foliar nitrogen (N), and the use of model–data fusion. Models with prescribed, rather than prognostic, phenology often fit NEE observations better on annual to interannual timescales in grassland, wetland and agricultural ecosystems. Models that calculated NEE as net primary productivity (NPP) minus heterotrophic respiration (HR) rather than gross ecosystem productivity (GPP) minus ecosystem respiration (ER) fit better on annual timescales in grassland and wetland ecosystems, but models that calculated NEE as GPP minus ER were superior on monthly to seasonal timescales in two coniferous forests. Models that incorporated foliar nitrogen (N) data were successful at capturing NEE variability on interannual (multiple year) timescales at Howland Forest, Maine. The model that employed a model–data fusion approach often, but not always, resulted in improved fit to data, suggesting that improving model parameterization is important but not the only step for improving model performance. Combined with previous findings, our results suggest that the mechanisms driving daily and annual NEE variability tend to be correctly simulated, but the magnitude of these fluxes is often erroneous, suggesting that model parameterization must be improved. Few NACP models correctly predicted fluxes on seasonal and interannual timescales where spectral energy in NEE observations tends to be low, but where phenological events, multi-year oscillations in climatological drivers, and ecosystem succession are known to be important for determining ecosystem function. Mechanistic improvements to models must be made to replicate observed NEE variability on seasonal and interannual timescales.

Common challenges for ecological modelling: Synthesis of facilitated discussions held at the symposia organized for the 2009 conference of the International Society for Ecological Modelling in Quebec City, Canada, (October 6–9, 2009) - Larocque, G.R.; Mailly, D.; Yue, T.-X.; Anand, M.; Peng, C.; Kazanci, C.; Etterson, M.; Goethals, P.; Jørgensen, S.E.; Schramski, J.R.; McIntire, E.J.B.; Marceau, D.J.; et al. (Ecological Modelling, 2011)

Incorporating weather sensitivity in inventory-based estimates of boreal forest productivity: A meta-analysis of process model results - Wang, Z.; Grant, R.F.; Arain, M.A.; Bernier, P.Y.; Chen, B.; Chen, J.M.; Govind, A.; Guindon, L.; Kurz, W.A.; Peng, C.; Price, D.T.; Stinson, G.; et al. (Ecological Modelling, 2013)

Global riverine land-to-ocean carbon export constrained by observations and multi-model assessment - Liu, M.; Raymond, P.A.; Lauerwald, R.; Zhang, Q.; Trapp-Müller, G.; Davis, K.L.; Moosdorf, N.; Xiao, C.; Middelburg, J.J.; Bouwman, A.F.; Beusen, A.H.W.; Peng, C.; et al. (Nature Geoscience, 2024)

Cold‐Season Methane Fluxes Simulated by GCP‐CH_4 Models - Ito, A.; Li, T.; Qin, Z.; Melton, J. R.; Tian, H.; Kleinen, T.; Zhang, W.; Zhang, Z.; Joos, F.; Ciais, P.; Hopcroft, P. O.; Beerling, D. J.; et al. (Geophysical Research Letters, 2023)
Abstract Cold‐season methane (CH 4 ) emissions may be poorly constrained in wetland models. We examined cold‐season CH 4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH 4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH 4 yr −1 . While summer CH 4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH 4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade −1 . Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. , Plain Language Summary Wetlands in the northern high latitudes are a major source of methane (CH 4 ) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH 4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH 4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH 4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH 4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH 4 emissions from wetlands need to be improved. , Key Points Cold‐season methane (CH 4 ) emissions simulated by 16 Global Carbon Project‐CH 4 wetland models were analyzed Most models underestimate the cold‐season emissions in comparison with observational data Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty

Critical needs to close monitoring gaps in pan-tropical wetland CH4 emissions - Zhu, Q.; Yuan, K.; Li, F.; Riley, W.J.; Hoyt, A.; Jackson, R.; McNicol, G.; Chen, M.; Knox, S.H.; Briner, O.; Beerling, D.; Gedney, N.; et al. (Environmental Research Letters, 2024)