scholarly journals Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED)

2015 ◽  
Vol 8 (11) ◽  
pp. 3593-3619 ◽  
Author(s):  
R. A. Fisher ◽  
S. Muszala ◽  
M. Verteinstein ◽  
P. Lawrence ◽  
C. Xu ◽  
...  
Keyword(s):  
Land Surface ◽  
Plant Traits ◽  
Carbon Assimilation ◽  
Life History Strategies ◽  
Costs And Benefits ◽  
Leaf Trait ◽  
Community Land Model ◽  
Plant Trait ◽  
Vegetation Models ◽  
The Impact

Abstract. We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties using the parameter space defined by the GLOPNET global leaf trait database. Furthermore, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked to each other, but we also find support for direct linkages to environmental conditions. We advocate intensified study of the costs and benefits of plant life history strategies in different environments and the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.

scholarly journals Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

2015 ◽  
Vol 8 (4) ◽  
pp. 3293-3357 ◽  
Author(s):  
R. A. Fisher ◽  
S. Muszala ◽  
M. Verteinstein ◽  
P. Lawrence ◽  
C. Xu ◽  
...  
Keyword(s):  
Land Surface ◽  
Plant Traits ◽  
Carbon Assimilation ◽  
Life History Strategies ◽  
Costs And Benefits ◽  
Leaf Trait ◽  
Community Land Model ◽  
Plant Trait ◽  
Vegetation Models ◽  
The Impact

Abstract. We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.

scholarly journals Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]

2019 ◽  
Author(s):  
Elias C. Massoud ◽  
Chonggang Xu ◽  
Rosie Fisher ◽  
Ryan Knox ◽  
Anthony Walker ◽  
...  
Keyword(s):  
Land Surface ◽  
Canopy Structure ◽  
Land Surface Model ◽  
Carbon Stocks ◽  
Surface Model ◽  
Model Parameters ◽  
Growth Strategies ◽  
Community Land Model ◽  
Vegetation Models ◽  
The Impact

Abstract. Vegetation plays a key role in regulating global carbon cycles and is a key component of the Earth System Models (ESMs) aimed to project Earth's future climates. In the last decade, the vegetation component within ESMs has witnessed great progresses from simple 'big-leaf' approaches to demographically-structured approaches, which has a better representation of plant size, canopy structure, and disturbances. The demographically-structured vegetation models are typically controlled by a large number of parameters, and sensitivity analysis is generally needed to quantify the impact of each parameter on the model outputs for a better understanding of model behaviors. In this study, we use the Fourier Amplitude Sensitivity Test (FAST) to diagnose the Community Land Model coupled to the Ecosystem Demography Model, or CLM4.5(ED). We investigate the first and second order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks. While the photosynthetic capacity parameter Vc,max25 is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which are shown here to determine vegetation demography and carbon stocks through their impacts on survival and growth strategies. The results of this study highlights the importance of understanding the dynamics of the next generation of demographically-enabled vegetation models within ESMs toward improved model parameterization and model structure for better model fidelity.

scholarly journals Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

2019 ◽  
Vol 12 (9) ◽  
pp. 4133-4164 ◽  
Author(s):  
Elias C. Massoud ◽  
Chonggang Xu ◽  
Rosie A. Fisher ◽  
Ryan G. Knox ◽  
Anthony P. Walker ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Land Surface ◽  
Canopy Structure ◽  
Surface Model ◽  
Model Parameters ◽  
Growth Strategies ◽  
Climate Conditions ◽  
Community Land Model ◽  
Vegetation Models ◽  
The Impact

Abstract. Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple “big-leaf” approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1∘. While the photosynthetic capacity parameter (Vc,max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity.

scholarly journals Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

2016 ◽  
Vol 20 (5) ◽  
pp. 2001-2018 ◽  
Author(s):  
Congsheng Fu ◽  
Guiling Wang ◽  
Michael L. Goulden ◽  
Russell L. Scott ◽  
Kenneth Bible ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Bowen Ratio ◽  
Hydraulic Redistribution ◽  
Energy Budgets ◽  
Vegetation Types ◽  
Ecological Processes ◽  
Community Land Model ◽  
Hydrological Impact ◽  
The Impact

Abstract. Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.

scholarly journals Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models

2021 ◽  
Vol 18 (1) ◽  
pp. 95-112
Author(s):  
Peter Horvath ◽  
Hui Tang ◽  
Rune Halvorsen ◽  
Frode Stordal ◽  
Lena Merete Tallaksen ◽  
...  
Keyword(s):  
High Latitude ◽  
Vegetation Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Radiative Properties ◽  
Community Land Model ◽  
Precipitation Seasonality ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterized strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVMs) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products and less often by other vegetation products or by in situ field observations. In this study, we evaluate the performance of three methods for spatial representation of present-day vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DMs), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV; Community Land Model 4.5 Bio-Geo-Chemical cycles and Dynamical Vegetation). While DGVMs predict PFT profiles based on physiological and ecological processes, a DM relies on statistical correlations between a set of predictors and the modelled target, and the RS dataset is based on classification of spectral reflectance patterns of satellite images. PFT profiles obtained from an independently collected field-based vegetation dataset from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVMs often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, three new environmental variables (e.g. minimum temperature in May, snow water equivalent in October and precipitation seasonality) were selected as the threshold for the establishment of these high-latitude PFTs. We performed a series of sensitivity experiments to investigate if these thresholds improve the performance of the DGVM method. Based on our results, we suggest implementation of one of these novel PFT-specific thresholds (i.e. precipitation seasonality) in the DGVM method. The results highlight the potential of using PFT-specific thresholds obtained by DM in development of DGVMs in broader regions. Also, we emphasize the potential of establishing DMs as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

scholarly journals Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

2016 ◽  
Author(s):  
C. Fu ◽  
G. Wang ◽  
M. L. Goulden ◽  
R. L. Scott ◽  
K. Bible ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Hydraulic Redistribution ◽  
Energy Budgets ◽  
Soil Moisture Dynamics ◽  
Community Land Model ◽  
The Us ◽  
Hydrological Impact ◽  
The Impact ◽  
Moisture Dynamics

Abstract. Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) has tackled the magnitude of the HR flux itself or the soil moisture dynamics from which HR magnitude can be directly inferred. Here we incorporated Ryel et al.'s (2002) empirical equation describing HR into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on surface water and energy budgets, and to explore how it may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites characterized by contrasting climate regimes and multiple vegetation types were studied, including the US-Wrc Wind River Crane site in Washington State, the US-SRM Santa Rita Mesquite Savanna site in southern Arizona, and six sites along the Southern California Climate Gradient (US-SCs, g, f, w, c, and d). HR flux, evapotranspiration, and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement match particularly during dry seasons. Our results also reveal that HR has important hydrological impact (on evapotranspiration, Bowen ratio, and soil moisture) in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.

scholarly journals Domestication has altered within-plant trait variability in a crop plant

2020 ◽  
Author(s):  
M. Robinson ◽  
A.L. Schilmiller ◽  
W.C. Wetzel
Keyword(s):  
Plant Traits ◽  
Biotic Interactions ◽  
Ecological Interactions ◽  
Multiple Traits ◽  
Leaf Trait ◽  
Crop Fields ◽  
Plant Trait ◽  
Trait Diversity ◽  
Wild Progenitors ◽  
Trait Variability

AbstractFor over 10,000 years humans have shaped plant traits through domestication. Studies of domestication have focused on changes to trait averages; however, plants also have characteristic levels of trait variability among their repeated parts, which can be heritable and mediate critical ecological interactions. Here, we ask how domestication selection has altered among-leaf trait variability using alfalfa (Medicago sativa), the oldest forage crop in the world. We found that domestication changed variability more than averages for multiple traits. Relative to wild progenitors, domesticates had elevated variability in specific leaf area, trichomes, C:N, and phytochemical concentrations and reduced variability in phytochemical composition among their leaves. Our work shows that within-plant trait variability is a novel facet of the domesticated plant phenotype, constituting a novel frontier of trait diversity within crop fields. As many critical biotic interactions occur at the scale of individual plants, our findings suggest that trait variability and diversity among leaves could act to magnify or counter the depauperate trait diversity often found at higher scales in agroecosystems.

Fire impact on water and carbon fluxes in a wild olive-based ecosystem

2021 ◽  
Author(s):  
Matteo Curreli ◽  
Nicola Montaldo ◽  
Roberto Corona ◽  
Gabriel G. Katul
Keyword(s):  
Land Surface ◽  
Soil Layer ◽  
Carbon Assimilation ◽  
Carbon Fluxes ◽  
Surface Fluxes ◽  
State Variables ◽  
Rainy Period ◽  
Wild Olive ◽  
Autumn And Winter ◽  
The Impact

<p>Fire, harvesting and beetles attacks are important disturbances for the forested ecosystems. The aim of this study is to examine the impact of the disturbances on water and carbon fluxes using a eddy‐covariance (EC) – based tower in a wild-olive forest.</p><p>The study has been performed at the Orroli site, Sardinia (Italy), which is an experimental site for the FLUXMED project of the Water Joint Programming Initiative. From 2003, a 10 m micrometeorological tower equipped with eddy-covariance system has been used to measuring water, carbon and energy surface fluxes, as well as key state variables (e.g. leaf and soil skin temperature, radiations, air humidity and wind velocity).</p><p>The landscape is covered by patchy vegetation: wild olives trees in clumps and herbaceous species, drying to bare soil in late spring. The climate is Mediterranean maritime with long droughts from May to October, and rainy period is concentrated in the autumn and winter months. In this ecosystem water uptake by olive’s roots, from underlying substrate to the shallow soil layer, allow woody vegetation and grass to remain physiologically active during dry conditions.</p><p>In summer 2017, which was a very dry season, an extended fire affected the forested area, impacting the north – west footprint of the tower, with consequences also to the close trees due to beetle attack, probably related to the sensitive conditions of the trees after the drought.</p><p>We compared pre-disturbance with post-disturbance land surface fluxes. Both fire and beetle attack, altered the partitioning of available energy to lE and H, evapotranspiration (ET) and carbon assimilation. Results show a reduction of evapotranspiration and carbon assimilation during the growing season. Differently, in autumn and winter the difference between pre-disturbance and post-disturbance was negligible due to low physiological activities of vegetation.</p>

scholarly journals Crop physiology calibration in the CLM

2015 ◽  
Vol 8 (4) ◽  
pp. 1071-1083 ◽  
Author(s):  
I. Bilionis ◽  
B. A. Drewniak ◽  
E. M. Constantinescu
Keyword(s):  
Land Surface ◽  
Sequential Monte Carlo ◽  
Net Ecosystem Exchange ◽  
Crop Productivity ◽  
Biofuel Production ◽  
Community Land Model ◽  
Crop Development ◽  
Choose Parameter ◽  
Parameter Values ◽  
The Impact

Abstract. Farming is using more of the land surface, as population increases and agriculture is increasingly applied for non-nutritional purposes such as biofuel production. This agricultural expansion exerts an increasing impact on the terrestrial carbon cycle. In order to understand the impact of such processes, the Community Land Model (CLM) has been augmented with a CLM-Crop extension that simulates the development of three crop types: maize, soybean, and spring wheat. The CLM-Crop model is a complex system that relies on a suite of parametric inputs that govern plant growth under a given atmospheric forcing and available resources. CLM-Crop development used measurements of gross primary productivity (GPP) and net ecosystem exchange (NEE) from AmeriFlux sites to choose parameter values that optimize crop productivity in the model. In this paper, we calibrate these parameters for one crop type, soybean, in order to provide a faithful projection in terms of both plant development and net carbon exchange. Calibration is performed in a Bayesian framework by developing a scalable and adaptive scheme based on sequential Monte Carlo (SMC). The model showed significant improvement of crop productivity with the new calibrated parameters. We demonstrate that the calibrated parameters are applicable across alternative years and different sites.

scholarly journals An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations

2006 ◽  
Vol 19 (12) ◽  
pp. 2867-2881 ◽  
Author(s):  
Menglin Jin ◽  
Shunlin Liang
Keyword(s):  
Land Surface ◽  
Regression Equations ◽  
Surface Emissivity ◽  
Land Surface Models ◽  
Community Land Model ◽  
Land Surface Emissivity ◽  
Variable Surface ◽  
Surface Models ◽  
Sensitivity Studies ◽  
The Impact

Abstract Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply constant, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, and 0.96 for bare soil as in the National Center for Atmospheric Research (NCAR) Community Land Model version 2 (CLM2). This is the so-called constant-emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the constant emissivity induces errors in modeling the surface energy budget, especially over large arid and semiarid areas where ɛ is far smaller than unity. One feasible solution to this problem is to apply the satellite-based broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities (ɛλ) in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity (ɛ) required by land surface models. The observed emissivity data show strong seasonality and land-cover dependence. Specifically, emissivity depends on surface-cover type, soil moisture content, soil organic composition, vegetation density, and structure. For example, broadband ɛ is usually around 0.96–0.98 for densely vegetated areas [(leaf area index) LAI > 2], but it can be lower than 0.90 for bare soils (e.g., desert). To examine the impact of variable surface broadband emissivity, sensitivity studies were conducted using offline CLM2 and coupled NCAR Community Atmosphere Models, CAM2–CLM2. These sensitivity studies illustrate that large impacts of surface ɛ occur over deserts, with changes up to 1°–2°C in ground temperature, surface skin temperature, and 2-m surface air temperature, as well as evident changes in sensible and latent heat fluxes.

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