doi:10.1007/s00376-016-5226-8

Avissar R., P. L. S. Dias, M. A. F. S. Dias, and C. Nobre, 2002: The large-scale biosphere-atmosphere experiment in Amazonia (LBA): Insights and future research needs. J. Geophys. Res.,107(D20), LBA 54-1-LBA 54-6, doi: 10.1029/ 2002JD002704.10.1029/2002JD002704

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http://onlinelibrary.wiley.com/doi/10.1029/2002JD002704/full[1] This overview summarizes general Large-Scale Atmosphere-Biosphere Experiment in Amazonia (LBA) papers and highlights some of the insights gained from these investigations and needs for future research. It complements the overview of Silva Dias et al. [2002a] , which summarizes the papers published on the joint major atmospheric mesoscale campaign in the wet season (WetAMC), which was held jointly in Rondonia with the Tropical Rainfall Measuring Mission (TRMM) validation campaign known as TRMM-LBA. It also complements the overview of Andreae et al. [2002] , which summarizes the papers describing the biogeochemical cycling of carbon, water, energy, aerosols, and trace gases resulting from the European Studies on Trace Gases and Atmospheric Chemistry, known as LBA-EUSTACH Project. The 17 papers summarized under this part of the special issue are regrouped into three main categories: (1) measurements and data sets, (2) remote sensing, and (3) modeling.

Baker I. T., L. Prihodko, A. S. Denning, M. Goulden, S. Miller, and H. R. da Rocha, 2008: Seasonal drought stress in the Amazon: Reconciling models and observations. J. Geophys. Res., 113(G1),G00B01, doi: 10.1029/2007JG000644.c8666ce516c6db68d9a5639fff7a2609

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Barlage M., X. B. Zeng, 2004: Impact of observed vegetation root distribution on seasonal global simulations of land surface processes. J. Geophys. Res., 109,D09101, doi: 10.1029/ 2003JD003847.10.1029/2003JD003847

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http://onlinelibrary.wiley.com/doi/10.1029/2003JD003847/citedbyUsing a global root distribution derived from observations, results from June to August ensemble simulations are presented. The new root distribution shifts the location of roots in the soil in most regions of the world. Root relocation depends on land use type with some roots located shallower (e.g., grasslands) and others deeper (e.g., tropical forests). Comparison of the boreal summer results of 1988 and 1993 for a control simulation and simulation with the new root distribution produces, in several regions of the world, statistically significant differences of up to 40 W/min the components of the surface energy budget. Analysis of the eastern and western United States shows statistically significant changes of over 1 K in surface air temperature and over 25 W/min surface energy components for both seasonal averages and diurnal cycles. Comparison with observations shows that the new root distribution improves the surface air temperature simulation, especially in 1993, but any precipitation improvement is statistically insignificant.

Bonan G. B., 1996: Land surface model (LSM version 1.0) for ecological, hydrological, and atmospheric studies: Technical description and user's guide. Tech. Note NCAR/TN-417-STR, National Center for Atmospheric Research, , Boulder Colo.

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http://www.osti.gov/scitech/biblio/442360This technical note describes version 1 of the LSM land surface model. In this model, land surface processes are described in terms of biophysical fluxes (latent heat, sensible heat, momentum, reflected solar radiation, emitted longwave radiation) and biochemical fluxes (CO2) that depend on the ecological and hydrologic state of the land. Consequently, ecological and hydrological sub-models are needed to simulate temporal changes in terrestrial biomass and water.

Canadell J., R. B. Jackson, J. B. Ehleringer, H. A. Mooney, O. E. Sala, and E. D. Schulze, 1996: Maximum rooting depth of vegetation types at the global scale. Oecologia,108(5), 583-595, doi: 10.1007/BF00329030.10.1007/BF00329030

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http://link.springer.com/10.1007/BF00329030The depth at which plants are able to grow roots has important implications for the whole ecosystem hydrological balance, as well as for carbon and nutrient cycling. Here we summarize what we know about the maximum rooting depth of species belonging to the major terrestrial biomes. We found 290 observations of maximum rooting depth in the literature which covered 253 woody and herbaceous species. Maximum rooting depth ranged from 0.3 m for some tundra species to 68 m for Boscia albitrunca in the central Kalahari; 194 species had roots at least 2 m deep, 50 species had roots at a depth of 5 m or more, and 22 species had roots as deep as 10 m or more. The average for the globe was 4.6±0.5 m. Maximum rooting depth by biome was 2.0±0.3 m for boreal forest. 2.1±0.2 m for cropland, 9.5±2.4 m for desert, 5.2±0.8 m for sclerophyllous shrubland and forest, 3.9±0.4 m for temperate coniferous forest, 2.9±0.2 m for temperate deciduous forest, 2.6±0.2 m for temperate grassland, 3.7±0.5 m for tropical deciduous forest, 7.3±2.8 m for tropical evergreen forest, 15.0±5.4 m for tropical grassland/savanna, and 0.5±0.1 m for tundra. Grouping all the species across biomes (except croplands) by three basic functional groups: trees, shrubs, and herbaceous plants, the maximum rooting depth was 7.0±1.2 m for trees, 5.1±0.8 m for shrubs, and 2.6±0.1 m for herbaceous plants. These data show that deep root habits are quite common in woody and herbaceous species across most of the terrestrial biomes, far deeper than the traditional view has held up to now. This finding has important implications for a better understanding of ecosystem function and its application in developing ecosystem models.

Castillo C. K. G., S. Levis, and P. Thornton, 2012: Evaluation of the new CNDV option of the Community Land Model: Effects of dynamic vegetation and interactive nitrogen on CLM4 means and variability. J.Climate, 25, 3702- 3714.10.1175/JCLI-D-11-00372.1

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http://adsabs.harvard.edu/abs/2012JCli...25.3702GThe Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon-nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography updates. CNDV simulates a reasonable present-day distribution of plant functional types but underestimates tundra vegetation cover. The CNDV simulation is compared against a CN simulation using a vegetation distribution generated by CNDV and against a carbon-only simulation with prescribed nitrogen limitation (CDV). The comparisons focus on the means and variability of carbon pools and fluxes and biophysical factors, such as albedo, surface radiation, and heat fluxes. The study assesses the relative importance of incorporating interactive nitrogen (CDV to CNDV) versus interactive biogeography (CN to CNDV) in present-day equilibrium simulations. None of the three configurations performs consistently better in simulating carbon or biophysical variables compared to observational estimates. The interactive nitrogen (N) cycle reduces annual means and interannual variability more than dynamic vegetation. Dynamic vegetation reduces seasonal variability in leaf area and, therefore, in moisture fluxes and surface albedo. The interactive N cycle has the opposite effect of enhancing seasonal variability in moisture fluxes and albedo. CNDV contains greater degrees of freedom than CN or CDV by adjusting both through nitrogen-carbon interactions and through vegetation establishment and mortality. Thus, in these equilibrium simulations, CNDV acts as a stronger "regulator" of variability compared to the other configurations. Discussed are plausible explanations for this behavior, which has been shown in past studies to improve climate simulations through better represented climate-vegetation interactions.

Chen J. L., C. R. Wilson, B. D. Tapley, Z. L. Yang, and G. Y. Niu, 2009: 2005 drought event in the Amazon River basin as measured by GRACE and estimated by climate models. J. Geophys. Res., 114,B05404, doi: 10.1029/2008JB006056.10.1029/2008JB006056

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http://onlinelibrary.wiley.com/doi/10.1029/2008JB006056/fullSatellite gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) provide new quantitative measures of the 2005 extreme drought event in the Amazon river basin, regarded as the worst in over a century. GRACE measures a significant decrease in terrestrial water storage (TWS) in the central Amazon basin in the summer of 2005, relative to the average of the 5 other summer periods in the GRACE era. In contrast, data-assimilating climate and land surface models significantly underestimate the drought intensity. GRACE measurements are consistent with accumulated precipitation data from satellite remote sensing and are also supported by in situ water-level data from river gauge stations. This study demonstrates the unique potential of satellite gravity measurements in monitoring large-scale severe drought and flooding events and in evaluating advanced climate and land surface models.

Coelho F. E., D. Or, 1999: A model for soil water and matric potential distribution under drip irrigation with water extraction by roots. Pesquisa Agropecuária Brasileira, 34, 225- 234.014e3d5c412594a0c3bb03ee32676816

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Collins D. B. G., R. L. Bras, 2007: Plant rooting strategies in water-limited ecosystems. Water Resour. Res., 43,W06407, doi: 10.1029/2006WR005541.10.1029/2006WR005541

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http://onlinelibrary.wiley.com/doi/10.1029/2006WR005541/pdfRoot depth and distribution are vital components of a plant's strategy for growth and survival in water-limited ecosystems and play significant roles in hydrologic and biogeochemical cycling. Knowledge of root profiles is invaluable in measuring and predicting ecosystem dynamics, yet data on root profiles are difficult to obtain. We developed an ecohydrological model of environmental forcing, soil moisture dynamics, and transpiration to explore dependencies of optimal rooting on edaphic, climatic, and physiological factors in water-limited ecosystems. The analysis considers individual plants with fixed biomass. Results of the optimization approach are consistent with profiles observed in nature. Optimal rooting was progressively deeper, moving from clay to loam, silt and then sand, and in wetter and cooler environments. Climates with the majority of the rainfall in winter produced deeper roots than if the rain fell in summer. Long and infrequent storms also favored deeper rooting. Plants that exhibit water stress at slight soil moisture deficiencies consistently showed deeper optimal root profiles. Silt generated the greatest sensitivity to differences in climatic and physiological parameters. The depth of rooting is governed by the depth to which water infiltrates, as influenced by soil properties and the timing and magnitude of water input and evaporative demand. These results provide a mechanistic illustration of the diversity of rooting strategies in nature.

Dickinson R. E., M. Shaikh, R. Bryant, and L. Graumlich, 1998: Interactive canopies for a climate model. J.Climate, 11, 2823- 2836.10.1175/1520-0442(1998)011<2823:ICFACM>2.0.CO;2

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http://adsabs.harvard.edu/abs/1998JCli...11.2823DClimate models depend on evapotranspiration from models of plant stomatal resistance and leaf cover, and hence they depend on a description of the response of leaf cover to temperature and soil moisture. Such a description is derived as an addition to the Biosphere-Atmosphere Transfer Scheme and tested by simulations in a climate model. Rules for carbon uptake, allocation between leaves, fine roots, and wood, and loss terms from respiration, leaf, and root turnover and cold and drought stress, are used to infer the seasonal growth of leaf area as needed in a climate model, and to provide carbon fluxes (assuming also a simple soil carbon model) and net primary productivity. The scheme is tested in an 11-yr integration with the NCAR CCM3 climate model. After a spinup period of several years, the model equilibrates to a seasonal cycle plus some interannual variability. Effects of the latter are noticeable for the Amazon. Overall, drought stress has nearly as large an effect on leaf mortality as cold stress. The leaf areas agree on average with those inferred from Normalized Difference Vegetation Index although some individual systems are either too high (grass and crops) or too low (deciduous needleleaf in Siberia) compared to the satellite data. Evergreen needleleaf forests have significantly smaller annual range and later phase than indicated by the data. The interactive parameterization increases temperatures and reduces evapotranspiration and precipitation compared to the control over the extratropical Northern Hemisphere summer. This interactive leaf model may serve not only to provide feedbacks between vegetation and the climate model, but also to diagnose shortcomings of a climate model simulation from the viewpoint of its impact on the biosphere.

Drewry D. T., P. Kumar, S. Long, C. Bernacchi, X. Z. Liang, and M. Sivapalan, 2010: Ecohydrological responses of dense canopies to environmental variability: 1. Interplay between vertical structure and photosynthetic pathway. J. Geophys. Res., 115( G4), 1- 25.01aaab80-a915-4e8c-84ec-e78ebdd44e17

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El Maayar, M., O. Sonnentag, 2009: Crop model validation and sensitivity to climate change scenarios. Climate Research, 39( 2), 47- 59.10.3354/cr00791

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http://www.cabdirect.org/abstracts/20093196281.htmlField measurements of land surface-atmosphere heat and water exchanges, leaf area index, crop height, dry matter accumulation, and crop yield at Bondville, an agricultural site of the AmeriFlux network located in the USA Midwest, were used to evaluate the performance of the process-oriented crop model Agro-IBIS under a corn (Zea mays L.)-soybean (Glycine max (L.) Merr.) crop rotation. Simulatio...

El Masri, B., S. J. Shu, A. K. Jain, 2015: Implementation of a dynamic rooting depth and phenology into a land surface model: Evaluation of carbon,water, and energy fluxes in the high latitude ecosystems. Agricultural and Forest Meteorology, 211-212, 85- 99.10.1016/j.agrformet.2015.06.002

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refpaperuri:(1d11312434f382c0d086872df82b5978)

http://www.sciencedirect.com/science/article/pii/S0168192315001811Recent studies and observations have shown that northern high latitude ecosystems (NHLE) are strongly responsive to environmental changes, particularly warming temperature. Ecosystem models are important tools that help us to understand and assess the impact of environmental changes in the NHLE. However, models lack processes that are essential for modeling ecosystem dynamics for the NHLEs. In this study, NHLE-specific dynamic phenology and dynamic rooting distribution and depth parameterizations was implemented in a land surface model, the Integrated Science Assessment Model (ISAM), to improve the estimated carbon, water, and energy fluxes in the NHLs. These parameterizations account for light, water, and nutrient stresses while allocating the assimilated carbon to leaf, stem, and root pools. The model parameters related to these processes were calibrated and evaluated using measured data from 16 sites (12 fluxnet sites and 4 non-flux net sites) representative of the dominant NHLEs. By including these dynamic processes, ISAM was able to capture the measured seasonal variability in leaf area index (LAI) and root distribution in the soil layers. The evaluation of the model results suggested that without including the dynamic processes, the modeled growing season length (GSL) in the NHLE was almost two times higher, as compared to measurements. To quantify the implication of these processes on the C, water, and energy fluxes, we compared the results of two different versions of ISAM, a dynamic version that includes dynamic processes (ISAM DYN ) and a static version that does not include dynamic processes (ISAM BC ), with measurements from 12 eddy covariance flux sites. The results showed that ISAM DYN , unlike ISAM BC , was more capable to capture the flux site-based seasonal variability in GPP, water, and energy fluxes. Regional analysis revealed that the growing season length increased on average by about 5 days in the NHLs in the 2000s compared to 1990s.

Fan F. C., L. F. Zhang, Z. H. Li, S. Y. Liu, Y. F. Shi, and J. M. Jia, 2012: Response of root distribution of tomato to different irrigation methods in Greenhouse. Journal of Hebei Agricultural Sciences, 16( 9), 36- 40, 44. (in Chinese)3ed8c85432ed7f89984086b2f81cb3d4

http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-HBKO201208009.htm

http://en.cnki.com.cn/Article_en/CJFDTotal-HBKO201208009.htmIn order to provide technical support for the implementation of tomato root layer irrigation and fertilizer management,the distribution characteristics of tomato root and the response to the irrigation methods in greenhouse under different growing period on different irrigation methods(no mulching furrow irrigation,furrow irrigation under membrane,membrane under infiltration irrigation)were studied.The results showed that the largest vertical depth of greenhouse tomato in flowering-fruiting period and harvesting period respectively was 50 cm and 60 cm.It was not affected indistinctively by the irrigation methods,but plastic film mulching could make the root distributions show shallowing trend,and the trend showed root distribution in 0-10 cm soil layer.The distribution of main root layer of vegetables was relatively stable,it mainly distributed in 0-30 cm shallow soil layer of three irrigation methods,and the root mass weight of the layer was 92.26%-99.15% of total.The root distribution of underground water(infiltration irrigation)showed a more uniform characteristics,and had a larger space for the concentrated distribution area than ground water(furrow irrigation),the root of furrow irrigation was mainly distributed in 5-20 cm soil layer space,and the root of infiltration irrigation was more uniformly distributed in 0-25 cm soil layer space."Managing according to shallow root"of facing the main root layer was particularly important for vegetable crops,vegetable managing should pay more attention to the water and fertilizer supply in shallow root micro domain space.

Feddes, R. A., Coauthors, 2001: Modeling root water uptake in hydrological and climate models. Bull. Amer. Meteor. Soc., 82, 2797- 2810.10.1175/1520-0477(2001)082<2797:MRWUIH>2.3.CO;2

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2001bams...82.2797f

http://adsabs.harvard.edu/abs/2001bams...82.2797fFrom 30 September to 2 October 1999 a workshop was held in Gif-sur-Yvette, France, with the central objective to develop a research strategy for the next 3-5 years, aiming at a systematic description of root functioning, rooting depth, and root distribution for modeling root water uptake from local and regional to global scales. The goal was to link more closely the weather prediction and climate and hydrological models with ecological and plant physiological information in order to improve the understanding of the impact that root functioning has on the hydrological cycle at various scales. The major outcome of the workshop was a number of recommendations, detailed at the end of this paper, on root water uptake parameterization and modeling and on collection of root and soil hydraulic data.

Hatzis J. J., 2010: The development of a dynamic root distribution for the Community Land Model with carbon-nitrogen interactions. M.S. thesis, Northern Illinois University, Di Kalb, 184 pp.

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http://search.proquest.com/docview/520388024Land surface models have employed a variety of fine root distributions, but it is unclear which is the most accurate. To test if the choice of root distribution mattered, a sensitivity test was conducted on the Community Land Model with Carbon-Nitrogen Interactions (CLM-CN) for three different root distributions. The sensitivity test showed that the CLM-CN was sensitive to root distribution, and thus the choice of root distribution did matter. An existing dynamic root distribution was adapted to use observed soil nutrient profiles instead of the original prescribed nutrient profiles and was run in the CLM-CN. The new dynamic root distribution was evaluated against existing root distributions and was shown to have: (1) vegetation with reduced water stress and (2) modeled fine root carbon profiles which most closely matched the observed soil organic carbon profiles. The new dynamic root distribution appears to be an improvement over existing root distributions.

Hodge A., 2004: The plastic plant: Root responses to heterogeneous supplies of nutrients. New Phytologist, 162, 9- 24.10.1111/j.1469-8137.2004.01015.x

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http://onlinelibrary.wiley.com/doi/10.1111/j.1469-8137.2004.01015.x/fullWhen roots encounter a nutrient-rich zone or patch they often proliferate within it. Roots experiencing nutrient-rich patches can also enhance their physiological ion-capacities compared with roots of the same plant outside the patch zone. These plastic responses by the root system have been proposed as the major mechanism by which cope with the naturally occurring heterogeneous supplies of nutrients in soil. Various attempts to predict how contrasting species will respond to patches have been made based on specific root length (), root demography and biomass allocation within the patch zone. No one criterion has proved definitive. Actually demonstrating that root proliferation is beneficial to the plant, especially in terms of capture from patches, has also proved troublesome. Yet by growing under more realistic conditions, such as in interspecific plant competition, and with a complex organic patch, a direct benefit can be demonstrated. Thus, as highlighted in this review, the environmental context in which the root response is expressed is as important as the magnitude of the response itself.

Hudiburg T. W., B. E. Law, and P. E. Thornton, 2013: Evaluation and improvement of the Community Land Model (CLM4) in Oregon forests. Biogeosciences, 10, 453- 470.10.5194/bgd-9-12757-2012

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http://www.oalib.com/paper/2114209Ecosystem process models are important tools for determining the interactive effects of global change and disturbance on forest carbon dynamics. Here we evaluated and improved terrestrial carbon cycling simulated by the Community Land Model (CLM4), the land model portion of the Community Earth System Model (CESM1.0.4). Our analysis was conducted primarily in Oregon forests using FLUXNET and forest inventory data for the period 2001-2006. We go beyond prior modeling studies in the region by incorporating regional variation in physiological parameters from > 100 independent field sites in the region. We also compare spatial patterns of simulated forest carbon stocks and net primary production (NPP) at 15 km resolution using data collected from federal forest inventory plots (FIA) from > 3000 plots in the study region. Finally, we evaluate simulated gross primary production (GPP) with FLUXNET eddy covariance tower data at wet and dry sites in the region. We improved model estimates by making modifications to CLM4 to allow physiological parameters (e. g., foliage carbon to nitrogen ratios and specific leaf area), mortality rate, biological nitrogen fixation, and wood allocation to vary spatially by plant functional type (PFT) within an ecoregion based on field plot data in the region. Prior to modifications, default parameters resulted in underestimation of stem biomass in all forested ecoregions except the Blue Mountains and annual NPP was both over-and underestimated. After modifications, model estimates of mean NPP fell within the observed range of uncertainty in all ecoregions (two-sided P value = 0.8), and the underestimation of stem biomass was reduced. This was an improvement from the default configuration by 50% for stem biomass and 30% for NPP. At the tower sites, modeled monthly GPP fell within the observed range of uncertainty at both sites for the majority of the year, however summer GPP was underestimated at the Metolius semi-arid pine site and spring GPP was overestimated at the Campbell River mesic Douglas-fir site, indicating GPP may be an area for further improvement. The low bias in summer maximum GPP at the semi-arid site could be due to seasonal response of V-cmax to temperature and precipitation while overestimated spring values at the mesic site could be due to response of V-cmax to temperature and day length.

Hutchings M. J., H. de Kroon, 1994: Foraging in plants: The role of morphological plasticity in resource acquisition. Advances in Ecological Research, 25, 159- 238.5d05eb9e186a08138b047fc4650849c6

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Ichii K., H. H. Hashimoto, M. A. White, C. Potter, L. R. Hutyra, A. R. Huete, R. B. Myneni, and R. R. Nemani, 2007: Constraining rooting depths in tropical rainforests using satellite data and ecosystem modeling for accurate simulation of gross primary production seasonality. Global Change Biology,13, 67-77, doi: 10.1111/j.1365-2486.2006.01277.x.10.1111/j.1365-2486.2006.01277.x

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1111%2Fj.1365-2486.2006.01277.x%2Fpdf

http://new.med.wanfangdata.com.cn/Paper/Detail?id=PeriodicalPaper_JJ029557930Accurate parameterization of rooting depth is difficult but important for capturing the spatio-temporal dynamics of , and energy cycles in tropical forests. In this study, we adopted a new approach to constrain rooting depth in terrestrial ecosystem models over the Amazon using satellite data [moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index ()] and Biome-BGC terrestrial ecosystem model. We simulated seasonal variations in gross primary production () using different rooting depths (1, 3, 5, and 10 m) at point and spatial scales to investigate how rooting depth affects modeled seasonal variations and to determine which rooting depth simulates consistent with satellite-based observations. First, we confirmed that rooting depth strongly controls modeled seasonal variations and that only deep rooting systems can successfully track flux-based seasonality at the Tapajos km67 flux site. Second, spatial analysis showed that the model can reproduce the seasonal variations in satellite-based seasonality, however, with required rooting depths strongly dependent on precipitation and the dry season length. For example, a shallow rooting depth (1-3 m) is sufficient in regions with a short dry season (e.g. 0-2 months), and deeper roots are required in regions with a longer dry season (e.g. 3-5 and 5-10 m for the regions with 3-4 and 5-6 months dry season, respectively). Our analysis suggests that setting of proper rooting depths is important to simulating seasonality in tropical forests, and the use of satellite data can help to constrain the spatial variability of rooting depth.

Ivanov V. Y., R. L. Bras, and E. R. Vivoni, 2008: Vegetation-hydrology dynamics in complex terrain of semiarid areas: 1. A mechanistic approach to modeling dynamic feedbacks. Water Resour. Res., 44,W03429, doi: 10.1029/2006WR005588.10.1029/2006WR005588

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2006WR005588%2Fpdf

http://onlinelibrary.wiley.com/doi/10.1029/2006WR005588/pdfVegetation, particularly its dynamics, is the often-ignored linchpin of the land-surface hydrology. This work emphasizes the coupled nature of vegetation-water-energy dynamics by considering linkages at timescales that vary from hourly to interannual. A series of two papers is presented. A dynamic ecohydrological model [tRIBS + VEGGIE] is described in this paper. It reproduces essential water and energy processes over the complex topography of a river basin and links them to the basic plant life regulatory processes. The framework focuses on ecohydrology of semiarid environments exhibiting abundant input of solar energy but limiting soil water that correspondingly affects vegetation structure and organization. The mechanisms through which water limitation influences plant dynamics are related to carbon assimilation via the control of photosynthesis and stomatal behavior, carbon allocation, stress-induced foliage loss, as well as recruitment and phenology patterns. This first introductory paper demonstrates model performance using observations for a site located in a semiarid environment of central New Mexico.

Jackson R. B., H. A. Mooney, and E. D. Schulze, 1997: A global budget for fine root biomass, surface area, and nutrient contents. Proceedings of the National Academy of Sciences of the United States of America, 94, 7362- 7366.32819022237398478730290229222322221103855785203997756193690900

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http://xueshu.baidu.com/s?wd=paperuri%3A%281902d22d37f398f47b87badbf30a2902%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fwww.bioone.org%2Fservlet%2Flinkout%3Fsuffix%3Dbibr27%26dbid%3D8%26doi%3D10.2980%252F16-3-3267%26key%3D11038557&ie=utf-8&sc_us=5203997756193690900

Jackson R. B., J. Canadell, J. R. Ehleringer, H. A. Mooney, O. E. Sala, and E. D. Schulze, 1996: A global analysis of root distributions for terrestrial biomes. Oecologia, 108, 389- 411.10.1007/BF00333714

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http://onlinelibrary.wiley.com/resolve/reference/XREF?id=10.1007/BF00333714Understanding and predicting ecosystem functioning (e.g., carbon and water fluxes) and the role of soils in carbon storage requires an accurate assessment of plant rooting distributions. Here, in a comprehensive literature synthesis, we analyze rooting patterns for terrestrial biomes and compare distributions for various plant functional groups. We compiled a database of 250 root studies, subdividing suitable results into 11 biomes, and fitted the depth coefficient β to the data for each biome (Gale and Grigal 1987). β is a simple numerical index of rooting distribution based on the asymptotic equation Y =1-β d , where d = depth and Y = the proportion of roots from the surface to depth d . High values of β correspond to a greater proportion of roots with depth. Tundra, boreal forest, and temperate grasslands showed the shallowest rooting profiles (β=0.913, 0.943, and 0.943, respectively), with 80–90% of roots in the top 30 cm of soil; deserts and temperate coniferous forests showed the deepest profiles (β=0.975 and 0.976, respectively) and had only 50% of their roots in the upper 30 cm. Standing root biomass varied by over an order of magnitude across biomes, from approximately 0.2 to 5 kg m -2 . Tropical evergreen forests had the highest root biomass (5 kg m -2 ), but other forest biomes and sclerophyllous shrublands were of similar magnitude. Root biomass for croplands, deserts

Jing C. Q., L. Li, X. Chen, and G. P. Luo, 2014: Comparison of root water uptake functions to simulate surface energy fluxes within a deep-rooted desert shrub ecosystem. Hydrological Processes, 28, 5436- 5449.10.1002/hyp.10047

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http://onlinelibrary.wiley.com/doi/10.1002/hyp.10047/pdfRoot water uptake (RWU) is a unique process whereby plants obtain water from soil, and it is essential for plant survival. The mechanisms of RWU are well understood, but their parameterization and simulation in current Land Surface Models (LSMs) fall short of the requirements of modern hydrological and climatic modelling research. Though various RWU functions have been proposed for potential use in LSMs, none was proven to be applicable for dryland ecosystems where drought was generally the limiting factor for ecosystem functioning. This study investigates the effect of root distribution on the simulated surface energy fluxes by incorporating the observed vertical root distribution. In addition, three different RWU functions were integrated into the Common Land Model (CLM) in place of the default RWU function. A comparison of the modified model's results with the measured surface energy fluxes measured by eddy covariance techniques in a Central Asian desert shrub ecosystem showed that both RWU function and vertical root distribution were able to significantly impact turbulent fluxes. Parameterizing the root distribution based on in恠itu measurement and replacing the default RWU function with a revised version significantly improved the CLM's performance in simulating the latent and sensible heat fluxes. Sensitivity analysis showed that varying the parameter values of the revised RWU function did not significantly impact the CLM's performance, and therefore, this function is recommended for use in the CLM in Central Asian desert ecosystems and, possibly, other similar dryland ecosystems. Copyright 2013 John Wiley & Sons, Ltd.

Jung M., M. Reichstein, and A. Bondeau, 2009: Towards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6, 2001- 2013.10.5194/bgd-6-5271-2009

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http://onlinelibrary.wiley.com/resolve/reference/XREF?id=10.5194/bg-6-2001-2009Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998-2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.

Jung, M., Coauthors, 2011: Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. J. Geophys. Res., 116,G00J07, doi: 10.1029/2010JG001566.

Lai C. T., G. Katul, 2000: The dynamic role of root-water uptake in coupling potential to actual transpiration. Advances in Water Resources, 23, 427- 439.10.1016/S0309-1708(99)00023-8

d7dcc207b12cc48403b1101bf61cb7bc

http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0309170899000238

http://www.sciencedirect.com/science/article/pii/S0309170899000238The relationship between actual ( E) and potential ( E) transpiration above a grass-covered forest clearing was investigated numerically and experimentally from simultaneous measurements of soil moisture content profiles, mean meteorological conditions, turbulent heat and water vapor fluxes in the atmospheric surface layer, and soil hydraulic properties for two drying periods. The relationship between E/ Ewas found to be approximately constant and insensitive to variability in near-surface soil moisture content. To explore this near-constant E/ E, a model that relates potential and actual transpiration and accounts for root-uptake efficiency, potential transpiration rate, and root-density distribution was proposed and field-tested. The total amount of water consumed by the root system was integrated and compared with eddy-correlation latent heat flux measurements (field scale) and total water storage changes (local scale). Model calculations suggested that the deeper and more efficient roots are primarily responsible for the total water loss within the root zone when the near-surface soil layer approaches their wilting point.

Lawrence, D. M., Coauthors, 2011: Parameterization Improvements and Functional and Structural Advances in Version 4 of the Community Land Model. Journal of Advances in Modeling Earth Systems, 3, M03001.10.1029/2011MS000045

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http://onlinelibrary.wiley.com/doi/10.1029/2011MS00045/citedbyThe Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM development community to create CLM4. The model is extended with a carbon-nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC) capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within-canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR) - which includes aerosol deposition, grain-size dependent snow aging, and vertically-resolved snowpack heating - as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to 50-m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, surface layer thickness, roughness length and displacement height, and the disposition of snow-capped runoff are also incorporated. The new model exhibits higher snow cover, cooler soil temperatures in organic-rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is degraded because the vegetation structure is prognostic rather than prescribed, though running in this mode also allows more complex terrestrial interactions with climate and climate change.

Lawrence P. J., T. N. Chase, 2007: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0). J. Geophys. Res., 112,G01023, doi: 10.1029/2006JG000168.10.1029/2006JG000168

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http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2006JG000168%2Fpdf

http://onlinelibrary.wiley.com/doi/10.1029/2006JG000168/pdfRecently a number of studies have found significant differences between Moderate Resolution Imaging Spectroradiometer (MODIS) land surface mapping and the land surface parameters of the Community Land Model (CLM) of the Community Climate System Model (CCSM). To address these differences in land surface description, we have developed new CLM 3.0 land surface parameters that reproduce the physical properties described in the MODIS land surface data while maintaining the multiple Plant Functional Type (PFT) canopy and herbaceous layer representation used in CLM. These new parameters prescribe crop distributions directly from historical crop mapping allowing cropping to be described in CLM for any year from 1700 to current day. The new model parameters are calculated at 0.05 degrees resolution so they can be aggregated and used over a wider range of model grid resolutions globally. Compared to the current CLM 3.0 parameters, the new parameters have an increase in bare soil fraction of 10% which is realized through reduced tree, shrub, and crop cover. The new parameters also have area average increases of 10% for leaf area index (LAI) and stem area index (SAI) values, with the largest increases in tropical forests. The new land surface parameters have strong repeatable impacts on the climate simulated in CCSM 3.0 with large improvements in surface albedo compared to MODIS values. In many cases the improvements in surface albedo directly resulted in improved simulation of precipitation and near-surface air temperature; however, for the most part the existing biases of CCSM 3.0 remained with the new parameters. Further analysis of changes in surface hydrology revealed that the increased LAI of the new parameters resulted in lower overall evapotranspiration with reduced precipitation in CCSM 3.0. This was an unexpected result given that other research into the impacts of vegetation change suggests that the new parameters should have the opposite impact. This suggests that while the new parameters significantly improve the climate simulated in CLM 3.0 and CCSM 3.0, the new surface parameters have limited success in rectifying surface hydrology biases that result from the parameterizations within the CLM 3.0.

Le P. V. V., P. Kumar, D. T. Drewry, and J. C. Quijano, 2012: A graphical user interface for numerical modeling of acclimation responses of vegetation to climate change. Computers & Geosciences,49, 91-101, doi: 10.1016/j.cageo.2012.07.007.10.1016/j.cageo.2012.07.007

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http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0098300412002324

http://www.sciencedirect.com/science/article/pii/S0098300412002324Ecophysiological models that vertically resolve vegetation canopy states are becoming a powerful tool for studying the exchange of mass, energy, and momentum between the land surface and the atmosphere. A mechanistic multilayer canopy-soil-root system model (MLCan) developed by Drewry et al. (2010a) has been used to capture the emergent vegetation responses to elevated atmospheric COfor both Cand Cplants under various climate conditions. However, processing input data and setting up such a model can be time-consuming and error-prone. In this paper, a graphical user interface that has been developed for MLCan is presented. The design of this interface aims to provide visualization capabilities and interactive support for processing input meteorological forcing data and vegetation parameter values to facilitate the use of this model. In addition, the interface also provides graphical tools for analyzing the forcing data and simulated numerical results. The model and its interface are both written in the MATLAB programming language. Finally, an application of this model package for capturing the ecohydrological responses of three bioenergy crops (maize, miscanthus, and switchgrass) to local environmental drivers at two different sites in the Midwestern United States is presented.

Li F., S. Levis, and D. S. Ward, 2013: Quantifying the role of fire in the Earth system-Part 1: Improved global fire modeling in the Community Earth System Model (CESM1). Biogeosciences,10, 2293-2314, doi: 10.5194/bg-10-2293-2013.10.5194/bg-10-2293-2013

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http%3A%2F%2Fwww.oalib.com%2Fpaper%2F1374980

http://www.oalib.com/paper/1374980Modeling fire as an integral part of an Earth system model (ESM) is vital for quantifying and understanding fire-climate-vegetation interactions on a global scale and from an Earth system perspective. In this study, we introduce to the Community Earth System Model (CESM) the new global fire parameterization proposed by Li et al. (2012a, b), now with a more realistic representation of the anthropogenic impacts on fires, with a parameterization of peat fires, and with other minor modifications. The improved representation of the anthropogenic dimension includes the first attempt to parameterize agricultural fires, the economic influence on fire occurrence, and the socioeconomic influence on fire spread in a global fire model - also an alternative scheme for deforestation fires. The global fire parameterization has been tested in CESM1's land component model CLM4 in a 1850-2004 transient simulation, and evaluated against the satellite-based Global Fire Emission Database version 3 (GFED3) for 1997-2004. The simulated 1997-2004 average global totals for the burned area and fire carbon emissions in the new fire scheme are 338 Mha yrand 2.1 Pg C yr. Its simulations on multi-year average burned area, fire seasonality, fire interannual variability, and fire carbon emissions are reasonable, and show better agreement with GFED3 than the current fire scheme in CESM1 and modified CTEM-FIRE. Moreover, the new fire scheme also estimates the contributions of global fire carbon emissions from different sources. During 1997-2004, the contributions are 8% from agricultural biomass burning, 24% from tropical deforestation and degradation fires, 6% from global peat fires (3.8% from tropical peat fires), and 62% from other fires, which are close to previous assessments based on satellite data, government statistics, or other information sources. In addition, we investigate the importance of direct anthropogenic influence (anthropogenic ignitions and fire suppression) on global fire regimes during 1850-2004, using CESM1 with the new fire scheme. Results show that the direct anthropogenic impact is the main driver for the long-term trend of global burned area, but hardly contributes to the long-term trend of the global total of fire carbon emissions.

Li L. H., Y. P. Wang, Q. Yu, B. Pak, D. Eamus, J. Yan, E. van Gorsel, and I. T. Baker, 2012: Improving the responses of the Australian community land surface model (CABLE) to seasonal drought. J. Geophys. Res., 117,G04002, doi: 10.1029/2012JG002038.a4afc46d0094526d0bf4978ddaf7e050

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Li X. M., C. X. Xu, and S. M. Su, 1998: Affection of deep ditch manuring method to apple root system pattern in arid farming orchard. Acta Botanica Boreali-Occidentalia Sinica, 18( 5), 590- 594. (in Chinese)0ecd04f26309d83a796f86a9e4f31796

http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-DNYX804.023.htm

http://en.cnki.com.cn/Article_en/CJFDTotal-DNYX804.023.htmWith the method of dry ditching,the paper studied the affection of deep ditch manuring measure to the weight,composition and distribution scope of apple root system.It is proved that the total root weight,volume and length of the deep ditch manured tree were decrease sharply compared with those of check tree.The decreased data were 50%,60% and 1.8 m respectively.But the length of small root (function roots) and its partition were increased.The apple root system of the deep ditch manured tree showed an economic growth pattern in which there was less big roots but more small one.The function roots concentrated in ditch area where has the optimum miniecological conditions, which was a best system pattern.

Marthews T. R., C. A. Quesada, D. R. Galbraith, Y. Malhi, C. E. Mullins, M. G. Hodnett, and I. Dharssi, 2014: High-resolution hydraulic parameter maps for surface soils in tropical South America. Geoscientific Model Development, 7, 711- 723.10.5194/gmdd-6-6741-2013

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http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2014GMD.....7..711M

http://adsabs.harvard.edu/abs/2014GMD.....7..711MModern land surface model simulations capture soil profile water movement through the use of soil hydraulics sub-models, but good hydraulic parameterisations are often lacking, especially in the tropics. We present much-improved gridded data sets of hydraulic parameters for surface soil for the critical area of tropical South America, describing soil profile water movement across the region to 30 cm depth. Optimal hydraulic parameter values are given for the Brooks and Corey, Campbell, van Genuchten-Mualem and van Genuchten-Burdine soil hydraulic models, which are widely used hydraulic sub-models in land surface models. This has been possible through interpolating soil measurements from several sources through the SOTERLAC soil and terrain data base and using the most recent pedotransfer functions (PTFs) derived for South American soils. All soil parameter data layers are provided at 15 arcsec resolution and available for download, this being 20x higher resolution than the best comparable parameter maps available to date. Specific examples are given of the use of PTFs and the importance highlighted of using PTFs that have been locally parameterised and that are not just based on soil texture. We discuss current developments in soil hydraulic modelling and how high-resolution parameter maps such as these can improve the simulation of vegetation development and productivity in land surface models.

McMurtrie R. E., C. M. Iversen, R. C. Dewar, B. E. Medlyn, T. Näsholm, D. A. Pepper, and R. J. Norby, 2012: Plant root distributions and nitrogen uptake predicted by a hypothesis of optimal root foraging. Ecology and Evolution, 2( 7), 1235- 1250.10.1002/ece3.266

3402197

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http://onlinelibrary.wiley.com/doi/10.1002/ece3.266/fullCO(2)-enrichment experiments consistently show that rooting depth increases when trees are grown at elevated CO(2) (eCO(2)), leading in some experiments to increased capture of available soil nitrogen (N) from deeper soil. However, the link between N uptake and root distributions remains poorly represented in forest ecosystem and global land-surface models. Here, this link is modeled and analyzed using a new optimization hypothesis (MaxNup) for root foraging in relation to the spatial variability of soil N, according to which a given total root mass is distributed vertically in order to maximize annual N uptake. MaxNup leads to analytical predictions for the optimal vertical profile of root biomass, maximum rooting depth, and N-uptake fraction (i.e., the proportion of plant-available soil N taken up annually by roots). We use these predictions to gain new insight into the behavior of the N-uptake fraction in trees growing at the Oak Ridge National Laboratory free-air CO(2)-enrichment experiment. We also compare MaxNup with empirical equations previously fitted to root-distribution data from all the world's plant biomes, and find that the empirical equations underestimate the capacity of root systems to take up N.

Miguez-Macho G., Y. Fan, 2012: The role of groundwater in the Amazon water cycle: 2. Influence on seasonal soil moisture and evapotranspiration. J. Geophys. Res., 117,D15114, doi: 10.1029/2012JD017540.10.1029/2012JD017540

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http://onlinelibrary.wiley.com/doi/10.1029/2012JD017540/citedby[1] We investigate the potential influence of groundwater on seasonal evapotranspiration (ET) in the Amazon using a coupled groundwater-surface water model (LEAF-Hydro-Flood) forced with ERA-Interim reanalysis, at 2km grid and 4min steps over 11yrs (2000–2010), and validated with available soil moisture and ET observations. We find that first, the simulated water table is<2m deep over a significant portion of the Amazon (20–40%). Second, shallow groundwater can reduce wet season soil drainage, leading to larger soil water stores before the dry season arrives. Third, capillary rises from the water table can reach the root zone and maintain high dry season ET near the valleys. Fourth, groundwater's delayed response to rainfall can buffer surface stress in the dry season, when groundwater is the shallowest. Fifth, this temporal delay can be seen as spatial patterns; continued drainage and convergence maintain moist valleys forming a structured mosaic of wet-dry patches in the dry season. Results from two parallel runs, with and without groundwater, suggest that overall groundwater made a large difference in modeled soil moisture where the water table is shallow, but it only made a difference in modeled ET where the seasonality is strong; over southeastern Amazonia, July–August ET differs by 1mm/day. We note that our results are based on model simulations, which only suggest the potential importance of the groundwater system to the Amazon water cycle. The ultimate knowledge must come from carefully designed field observations linking vegetation, soil and groundwater with water balance studies and tracer tests, across a range of physical-biological settings.

Nepstad, D. C., Coauthors, 1994: The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures. Nature, 372, 666- 669.10.1038/372666a0

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http%3A%2F%2Fwww.nature.com%2Fnature%2Fjournal%2Fv372%2Fn6507%2Fabs%2F372666a0.html

http://www.nature.com/nature/journal/v372/n6507/abs/372666a0.htmlPresents a study on the role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures. Effect of deforestation and logging in eastern and souther Amazonia; Analysis of effects on water and carbon cycles; Precipitation in the Amazon region; Vertical profile of the region.

Oleson, K. W., Coauthors, 2010: Technical description of version 4.0 of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-478+STR, National Center for Atmospheric Research, 257 pp.10.1117/12.739234

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http://dx.doi.org/10.5065/D6FB50WZVirtual Reality; Virtual Huanghe River System; dynamic real-time; navigation; 3D model with real texture; mutual response between 3D scene; and 2D electronic map

Oleson, K. W., Coauthors, 2013: Technical description of version 4.5 of the Community Land Model (CLM). NCAR Tech. Note NCAR/TN-503+STR, National Center for Atmospheric Research, 420 pp.10.1117/12.739234

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http%3A%2F%2Fdx.doi.org%2F10.5065%2FD6FB50WZ

http://dx.doi.org/10.5065/D6FB50WZVirtual Reality; Virtual Huanghe River System; dynamic real-time; navigation; 3D model with real texture; mutual response between 3D scene; and 2D electronic map

Ryel R., M. Caldwell, C. Yoder, D. Or, and A. Leffler, 2002: Hydraulic redistribution in a stand of Artemisia tridentata: Evaluation of benefits to transpiration assessed with a simulation model. Oecologia,130(3), 173-184, doi: 10.1007/ s004420100794.10.1007/s004420100794

1cb00ba2a22ce1d1a47df75c073381d1

http%3A%2F%2Flink.springer.com%2F10.1007%2Fs004420100794

http://new.med.wanfangdata.com.cn/Paper/Detail?id=PeriodicalPaper_JJ028884272The significance of soil water redistribution facilitated by roots (an extension of "hydraulic lift", here termed hydraulic redistribution) was assessed for a stand of Artemisia tridentata using measurements and a simulation model. The model incorporated water movement within the soil via unsaturated flow and hydraulic redistribution and soil water loss from transpiration. The model used Buckingham-Darcy's law for unsaturated flow while hydraulic redistribution was developed as a function of the distribution of active roots, root conductance for water, and relative soil oot (rhizosphere) conductance for water. Simulations were conducted to compare model predictions with time courses of soil water potential at several depths, and to evaluate the importance of root distribution, soil hydraulic conductance and root xylem conductance on transpiration rates and the dynamics of soil water. The model was able to effectively predict soil water potential during a summer drying cycle, and the rapid redistribution of water down to 1.5m into the soil column after rainfall events. Results of simulations indicated that hydraulic redistribution could increase whole canopy transpiration over a 100-day drying cycle. While the increase was only 3.5% over the entire 100-day period, hydraulic redistribution increased transpiration up to 20.5% for some days. The presence of high soil water content within the lower rooting zone appears to be necessary for sizeable increases in transpiration due to hydraulic redistribution. Simulation results also indicated that root distributions with roots concentrated in shallow soil layers experienced the greatest increase in transpiration due to hydraulic redistribution. This redistribution had much less effect on transpiration with more uniform root distributions, higher soil hydraulic conductivity and lower root conductivity. Simulation results indicated that redistribution of water by roots can be an important component in soil water dynamics, and the model presented here provides a useful approach to incorporating hydraulic redistribution into larger models of soil processes.

Saleska S. R., K. Didan, A. R. Huete, and H. R. da Rocha, 2007: Amazon forests green-up during 2005 drought. Science, 318, 612.10.1126/science.1146663

17885095

bc63773fba03bd910a9a4db7296cc0a9

http%3A%2F%2Feuropepmc.org%2Fabstract%2FMED%2F17885095

http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM17885095Coupled climate-carbon cycle models suggest that Amazon forests are vulnerable to both long- and short-term droughts, but satellite observations showed a large-scale photosynthetic green-up in intact evergreen forests of the Amazon in response to a short, intense drought in 2005. These findings suggest that Amazon forests, although threatened by human-caused deforestation and fire and possibly by more severe long-term droughts, may be more resilient to climate changes than ecosystem models assume.

Schenk H. J., 2008: The shallowest possible water extraction profile: A null model for global root distributions. Vadose Zone Journal, 7, 1119- 1124.10.2136/vzj2007.0119

354a69f8f55d9aa60466bed9ff50671e

http%3A%2F%2Fdl.sciencesocieties.org%2Fpublications%2Fvzj%2Fabstracts%2F7%2F3%2F1119

http://dl.sciencesocieties.org/publications/vzj/abstracts/7/3/1119ABSTRACT The factors that shape vertical root distributions in diff erent soils and under diff erent climates and vegetation are poorly understood. This makes it difficult to parameterize root profiles in vegetation-, hydrology, biogeochemistry-, or global circulation models. Recently, it has been proposed that vertical root distributions in the vadose zone could be predicted from soil water infiltration and extraction patterns as a function of climatic variability, soil, and vegetation characteristics. A number of ecological factors favor shallow over deep roots, suggesting that root profiles of plant communities may tend to be as shallow as possible and as deep as needed to fulfill evapotranspirational demands. To test this hypothesis, a stochastic, one-dimensional soil water infiltration and extraction model (SWIEM) was developed that simulates soil water infiltration through 600 discrete soil layers to a depth of 6m. Water input is simulated in Monte Carlo fashion based on site-specific long-term precipitation data. Water extraction proceeds from the top down, with extraction depths determined by potential evapotranspiration (PET) and the vertical distribution of soil water. The resulting shallowest possible water extraction profile was tested against nine measured root profiles from long-term ecological research sites in different biomes. Two other approaches, based on mean root distributions for biomes and an empirical regression model, were also compared to the observed root distributions. Soil water extraction patterns predicted by the SWIEM model matched observed vertical root distributions better than the other two approaches. These findings show that vertical root distributions in different biomes tend to approach the shallowest possible shape, thereby creating a useful null model for future research on root distributions and a promising tool for parameterization of global models.

Schenk, H. J. and R. B. Jackson, 2002: The global biogeography of roots. Ecological Monographs, 72( 4), 311- 328.10.2307/3100092

497632032b14a3563aa2d8d402f766e7

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1890%2F0012-9615%282002%29072%5B0311%3ATGBOR%5D2.0.CO%3B2%2Fabstract

http://onlinelibrary.wiley.com/doi/10.1890/0012-9615(2002)072[0311:TGBOR]2.0.CO;2/abstractStudies in global plant biogeography have almost exclusively analyzed relationships of abiotic and biotic factors with the distribution and structure of vegetation aboveground. The goal of this study was to extend such analyses to the belowground structure of vegetation by determining the biotic and abiotic factors that influence vertical root distributions in the soil, including soil, climate, and plant properties. The analysis used a database of vertical root profiles from the literature with 475 profiles from 209 geographic locations. Since most profiles were not sampled to the maximum rooting depth, several techniques were used to estimate the amount of roots at greater depths, to a maximum of 3 m in some systems. The accuracy of extrapolations was tested using a subset of deeply (>2 m) sampled or completely sampled profiles. Vertical root distributions for each profile were characterized by the interpolated 50% and 95% rooting depths (the depths above which 50% or 95% of all roots were located). Gene...

Shangguan W., Y. J. Dai, Q. Y. Duan, B. Y. Liu, and H. Yuan, 2014: A global soil data set for earth system modeling. Journal of Advances in Modeling Earth Systems, 6, 249- 263.10.1002/2013MS000293

b831ded2501d7d433cda85ae1c4b4b21

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2013MS000293%2Ffull

http://onlinelibrary.wiley.com/doi/10.1002/2013MS000293/fulldeveloped a comprehensive, gridded Global Soil Dataset for use in Earth System Models (GSDE) and other applications. The GSDE provides soil information, such as soil particle-size distribution, organic carbon, and nutrients, and quality control information in terms of confidence level at 30~ 30 horizontal resolution and for eight vertical layers to a depth of 2.3 m. The GSDE is based on the Soil Map of the World and various regional and national soil databases, including soil attribute data and soil maps. We used a standardized data structure and data processing procedures to harmonize the data collected from various sources. We then used a soil type linkage method (i.e., taxotransfer rules) and a polygon linkage method to derive the spatial distribution of the soil properties. To aggregate the attributes of different compositions of a mapping unit, we used three mapping approaches: the area-weighting method, the dominant soil type method, and the dominant binned soil attribute method. The data set can also be aggregated to a lower resolution. In this paper, we only show the vertical and horizontal variations of sand, silt and clay contents, bulk density, and soil organic carbon as examples of the GSDE. The GSDE estimates of global soil organic carbon stock to the depths of 2.3, 1, and 0.3 m are 1922.7, 1455.4, and 720.1 Gt, respectively. This newly developed data set provides more accurate soil information and represents a step forward to advance earth system modeling.

Sivand ran, G., R. L. Bras, 2013: Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed. Water Resour. Res.,49, 3292-3305, doi: 10.1002/wrcr.20245.

Smithwick E. A. H., M. S. Lucash, M. L. McCormack, and G. Sivandran, 2014: Improving the representation of roots in terrestrial models. Ecological Modelling, 291, 193- 204.10.1016/j.ecolmodel.2014.07.023

020bbccda1bfd418da40aa78d0ef05e7

http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0304380014003603

http://www.sciencedirect.com/science/article/pii/S0304380014003603Root biomass, root production and lifespan, and root-mycorrhizal interactions govern soil carbon fluxes and resource uptake and are critical components of terrestrial models. However, limitations in data and confusions over terminology, together with a strong dependence on a small set of conceptual frameworks, have limited the exploration of root function in terrestrial models. We review the key root processes of interest to both field ecologists and modelers including root classification, production, turnover, biomass, resource uptake, and depth distribution to ask (1) what are contemporary approaches for modeling roots in terrestrial models? and (2) can these approaches be improved via recent advancements in field research methods? We isolate several emerging themes that are ready for collaboration among field scientists and modelers: (1) alternatives to size-class based root classifications based on function and the inclusion of fungal symbioses, (2) dynamic root allocation and phenology as a function of root environment, rather than leaf demand alone, (3) improved understanding of the treatment of root turnover in models, including the role of root tissue chemistry on root lifespan, (4) better estimates of root stocks across sites and species to parameterize or validate models, and (5) dynamic interplay among rooting depth, resource availability and resource uptake. Greater attention to model parameterization and structural representation of roots will lead to greater appreciation for belowground processes in terrestrial models and improve estimates of ecosystem resilience to global change drivers.

Tomasella J., M. G. Hodnett, L. A. Cuartas, A. D. Nobre, M. J. Waterloo, and S. M. Oliveira, 2008: The water balance of an Amazonian micro-catchment: The effect of interannual variability of rainfall on hydrological behaviour. Hydrological Processes,22, 2133-2147, doi: 10.1002/hyp.6813.10.1002/hyp.6813

c1d0b7badc03a733abf3f1def01c5a60

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fhyp.6813%2Fpdf

http://onlinelibrary.wiley.com/doi/10.1002/hyp.6813/pdfNot Available

Verhoef A., G. Egea, 2014: Modeling plant transpiration under limited soil water: Comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models. Agricultural and Forest Meteorology, 191, 22- 32.

Viovy N., 2011: CRUNCEP data set [Description available at . Data available at .http://dods.extra.cea.fr/data/p529viov/cruncep/readme.htm

Warren J. M., P. J. Hanson, C. M. Iversen, J. Kumar, A. P. Walker, and S. D. Wullschleger, 2015: Root structural and functional dynamics in terrestrial biosphere models-evaluation and recommendations. New Phytologist, 205, 59- 78.10.1111/nph.13034

25263989

33c21967f013bad49fab06c95b11ab28

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1111%2Fnph.13034%2Fpdf

http://med.wanfangdata.com.cn/Paper/Detail/PeriodicalPaper_PM25263989There 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.

Weaver J. E., 1926: Root Development of Field Crops. McGraw-Hill Book Co., New York & London, 291 pp.10.2134/agronj1926.00021962001800060007x

7abb886cada657264a825d7dd2692331

http%3A%2F%2Fwww.soils.org%2Fpublications%2Faj%2Fabstracts%2F18%2F6%2FAJ0180060518

http://www.soils.org/publications/aj/abstracts/18/6/AJ0180060518

White M. A., P. E. Thornton, S. W. Running, and R. R. Nemani, 2000: Parameterization and sensitivity analysis of the Biome-BGC terrestrial ecosystem model: Net primary production controls. Earth Interactions, 4, 1- 85.f45291d22c56566ec83a725436312e9e

http%3A%2F%2Fwww.nrcresearchpress.com%2Fservlet%2Flinkout%3Fsuffix%3Drefg392%2Fref392%26dbid%3D16%26doi%3D10.1139%252Fer-2013-0041%26key%3D10.1175%252F1087-3562%282000%290042.0.CO%253B2

http://xueshu.baidu.com/s?wd=paperuri%3A%28fd1f238ffeb1760ba11615d62f876123%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fwww.nrcresearchpress.com%2Fservlet%2Flinkout%3Fsuffix%3Drefg392%2Fref392%26dbid%3D16%26doi%3D10.1139%252Fer-2013-0041%26key%3D10.1175%252F1087-3562%282000%290042.0.CO%253B2&ie=utf-8&sc_us=17415088842567736917

Yan B. Y., R. E. Dickinson, 2014: Modeling hydraulic redistribution and ecosystem response to droughts over the Amazon basin using Community Land Model 4.0 (CLM4). J. Geophys. Res.,119, 2130-2143, doi: 10.1002/2014JG002694.8c00a1e30b9997664781b486cdd4dbc6

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2014JG002694%2Fpdf

http://xueshu.baidu.com/s?wd=paperuri%3A%28ed762debb34986eb5b65198c50950246%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2F2014JG002694%2Fpdf&ie=utf-8&sc_us=15841759427449595228

Yuan X., X. Z. Liang, 2011: Evaluation of a Conjunctive Surface-Subsurface Process model (CSSP) over the contiguous United States at regional-local scales. Journal of Hydrometeorology,12, 579-599, doi: 10.1175/2010JHM1302.1.10.1175/2010JHM1302.1

f490848bec98ceafb9153bf7e6b81889

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2011JHyMe..12..579Y

http://adsabs.harvard.edu/abs/2011JHyMe..12..579YAbstract This study presents a comprehensive evaluation on a Conjunctive Surface–Subsurface Process Model (CSSP) in predicting soil temperature–moisture distributions, terrestrial hydrology variations, and land–atmosphere exchanges against various in situ measurements and synthetic observations at regional–local scales over the contiguous United States. The CSSP, rooted in the Common Land Model (CoLM) with a few updates from the Community Land Model version 3.5 (CLM3.5), incorporates significant advances in representing hydrology processes with realistic surface (soil and vegetation) characteristics. These include dynamic surface albedo based on satellite retrievals, subgrid soil moisture variability of topographic controls, surface–subsurface flow interactions, and bedrock constraint on water table depths. As compared with the AmeriFlux tower measurements, the CSSP and CLM3.5 reduce surface sensible and latent heat flux errors from CoLM by 10 W m 612 on average, and have much higher correlations with observations for daily latent heat variations. The CSSP outperforms the CLM3.5 over the crop, grass, and shrub sites in depicting the latent heat annual cycles. While retaining the improvement for soil moisture in deep layers, the CSSP shows further advantage over the CLM3.5 in representing seasonal and interannual variations in root zones. The CSSP reduces soil temperature errors from the CLM3.5 (CoLM) by 0.2 (0.7) K at 0.1 m and 0.3 (0.6) K at 1 m; more realistically captures seasonal–interannual extreme runoff and streamflow over most regions and snow depth anomalies in high latitude (45°–52°N); and alleviates climatological water table depth systematic bias (absolute error) by about 1.2 (0.4) m. Clearly, the CSSP performance is overall superior to both the CoLM and CLM3.5. The remaining CSSP deficiencies and future refinements are also discussed.

Zeng N., J. H. Yoon, J. A. Marengo, A. Subramaniam, C. A. Nobre, A. Mariotti, and J. D. Neelin, 2008: Causes and impacts of the 2005 Amazon drought. Environmental Research Letters, 3,014002, doi: 10.1088/1748-9326/3/1/014002.10.1088/1748-9326/3/1/014002

d576780dc99f8a4ea282b0aa47286f85

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2008ERL.....3a4002Z

http://adsabs.harvard.edu/abs/2008ERL.....3a4002ZA rare drought in the Amazon culminated in 2005, leading to near record-low streamflows, small Amazon river plume, and greatly enhanced fire frequency. This episode was caused by the combination of 2002 03 El Niño and a dry spell in 2005 attributable to a warm subtropical North Atlantic Ocean. Analysis for 1979 2005 reveals that the Atlantic influence is comparable to the better-known Pacific linkage. While the Pacific influence is typically locked to the wet season, the 2005 Atlantic impact concentrated in the Amazon dry season when its hydroecosystem is most vulnerable. Such mechanisms may have wide-ranging implications for the future of the Amazon rainforest.

Zeng X. B., 2001: Global vegetation root distribution for land modeling. Journal of Hydrometeorology, 2( 6), 525- 530.10.1175/1525-7541(2001)002<0525:GVRDFL>2.0.CO;2

e5f597ea427220824ae8690fe3f0f93d

http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2001JHyMe...2..525Z

http://adsabs.harvard.edu/abs/2001JHyMe...2..525ZVegetation root distribution is one of the factors that determine the overall water holding capacity of the land surface and the relative rates of water extraction from different soil layers for vegetation transpiration. Despite its importance, significantly different root distributions are used by different land surface models. Using a comprehensive global field survey dataset, vegetation root distribution (including rooting depth) has been developed here for three of the most widely used land cover classifications [i.e., the Biosphere070705Atmosphere Transfer Scheme (BATS), International Geosphere070705Biosphere Program (IGBP), and version 2 of the Simple Biosphere Model (SiB2)] for direct use by any land model with any number of soil layers.

Zeng X. B., M. Shaikh, Y. J. Dai, R. E. Dickinson, and R. Myneni, 2002: Coupling of the common land model to the NCAR community climate model. J.Climate, 15, 1832- 1854.61038036010bae7a416e5cb167fc22c9

http%3A%2F%2Fwww.nrcresearchpress.com%2Fservlet%2Flinkout%3Fsuffix%3Drg207%2Fref207%26dbid%3D16%26doi%3D10.1139%252FA10-016%26key%3D10.1175%252F1520-0442%282002%290152.0.CO%253B2

http://xueshu.baidu.com/s?wd=paperuri%3A%285dfb92de1cb45bc210c7fd77afd663c6%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fwww.nrcresearchpress.com%2Fservlet%2Flinkout%3Fsuffix%3Drg207%2Fref207%26dbid%3D16%26doi%3D10.1139%252FA10-016%26key%3D10.1175%252F1520-0442%282002%290152.0.CO%253B2&ie=utf-8&sc_us=2708824223190987322

Zeng X. B., Y. J. Dai, R. E. Dickinson, and M. Shaikh, 1998: The role of root distribution for climate simulation over land. Geophys. Res. Lett., 25, 4533- 4536.10.1029/1998GL900216

961e82b278e62af68e7c619014ac1aac

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F1998GL900216%2Ffull

http://onlinelibrary.wiley.com/doi/10.1029/1998GL900216/fullA comprehensive global root database is used to derive vertical root distribution and rooting depth for various vegetation categories in one of the most widely-used land models; i.e., the Biosphere—Atmosphere Transfer Scheme (BATS). Using a variety of observational datasets, observed root distribution is found to significantly improves the offline simulation of surface water and energy balance. Global climate modeling further demonstrates that observed root distribution primarily affects latent heat flux and soil wetness over tropical and midlatitude land, respectively.

Zheng Z., G. L. Wang, 2007: Modeling the dynamic root water uptake and its hydrological impact at the Reserva Jaru site in Amazonia. J. Geophys. Res., 112,G04012, doi: 10.1029/ 2007JG000413.e5229a5deedafb50f6617957342b1b05

http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2007JG000413%2Fpdf

http://xueshu.baidu.com/s?wd=paperuri%3A%287f5a6e4e74f0a3188f91cff491354b98%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2007JG000413%2Fpdf&ie=utf-8&sc_us=14570521813608709541