scholarly journals CO<sub>2</sub> fluxes and ecosystem dynamics at five European treeless peatlands – merging data and process oriented modelling

2014 ◽  
Vol 11 (6) ◽  
pp. 9249-9297
Author(s):  
C. Metzger ◽  
P.-E. Jansson ◽  
A. Lohila ◽  
M. Aurela ◽  
T. Eickenscheidt ◽  
...  
Keyword(s):  
Water Table ◽  
Photosynthetic Efficiency ◽  
Heterotrophic Respiration ◽  
Soil Conditions ◽  
Model Parameters ◽  
Co2 Fluxes ◽  
Area Index ◽  
Wide Range ◽  
Process Oriented ◽  
Organic Decomposition

Abstract. The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in landuse intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out to what extent CO2 fluxes measured at different sites, can be explained by common processes and parameters implemented in the model. The CoupModel was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analysed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. The model, utilizing a site independent configuration for most of the parameters, captured seasonal variability in the major fluxes well. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, heterotrophic respiration rates were consistently lowest on formerly drained sites and highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Applying common parameter values for the timing of plant shooting and senescence, and a minimum temperature for photosynthesis, had only a minor effect on model performance, even though the gradient in site latitude ranged from 48° N (South-Germany) to 68° N (northern Finland). This was also true for common parameters defining the moisture and temperature response for decomposition. CoupModel is able to describe measured fluxes at different sites or under different conditions, providing that the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon (C) pool are estimated from available information on specific soil conditions, vegetation and management of the ecosystems.

scholarly journals CO<sub>2</sub> fluxes and ecosystem dynamics at five European treeless peatlands – merging data and process oriented modeling

2015 ◽  
Vol 12 (1) ◽  
pp. 125-146 ◽  
Author(s):  
C. Metzger ◽  
P.-E. Jansson ◽  
A. Lohila ◽  
M. Aurela ◽  
T. Eickenscheidt ◽  
...  
Keyword(s):  
Water Table ◽  
Photosynthetic Efficiency ◽  
Heterotrophic Respiration ◽  
Soil Conditions ◽  
Model Parameters ◽  
Co2 Fluxes ◽  
Site Specific ◽  
Process Oriented ◽  
A Site ◽  
Organic Decomposition

Abstract. The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in land use intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out whether CO2 fluxes, measured at different sites, can be explained by common processes and parameters or to what extend a site specific configuration is needed. The model was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analyzed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. Seasonal variability in the major fluxes was well captured, when a site independent configuration was utilized for most of the parameters. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, rate coefficients for heterotrophic respiration were consistently the lowest on formerly drained sites and the highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Specific parameter values for the timing of plant shooting and senescence, the photosynthesis response to temperature, litter fall and plant respiration rates, leaf morphology and allocation fractions of new assimilates, were not needed, even though the gradient in site latitude ranged from 48° N (southern Germany) to 68° N (northern Finland) differed largely in their vegetation. This was also true for common parameters defining the moisture and temperature response for decomposition, leading to the conclusion that a site specific interpretation of these processes is not necessary. In contrast, the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon pool need to be estimated from available information on specific soil conditions, vegetation and management of the ecosystems, to be able to describe CO2 fluxes under different conditions.

scholarly journals Modeling carbon dynamics in two adjacent spruce forests with different soil conditions in Russia

2008 ◽  
Vol 5 (1) ◽  
pp. 271-296
Author(s):  
J. Kurbatova ◽  
C. Li ◽  
A. Varlagin ◽  
X. Xiao ◽  
N. Vygodskaya
Keyword(s):  
Water Table ◽  
Soil Conditions ◽  
Organic Layer ◽  
Spruce Forest ◽  
Eddy Covariance Method ◽  
Southern Boundary ◽  
Organic C ◽  
Spruce Forests ◽  
Net Ecosystem Carbon Exchange ◽  
Wide Range

Abstract. Net ecosystem carbon exchange (NEE) were measured with eddy covariance method for two adjacent forests located at the southern boundary of European taiga in Russia in 1999–2004. The two spruce forests shared similar vegetation composition but differed in soil conditions. The wet spruce forest (WSF) possessed a thick peat layer (60 cm) with a high water table seasonally close to or above the soil surface. The dry spruce forest (DSF) had a relatively thin organic layer (5 cm) with a deep water table (>60 cm). The measured NEE fluxes (2000 and −1440 kg C ha−1 yr−1 for WSF and DSF, respectively) indicated that WSF was a source while DSF a sink of atmospheric carbon dioxide during the experimental years. A process-based model, Forest-DNDC, was employed in the study to interpret the observations. The modeled NEE fluxes were 1800 and −2200 kg C ha−1 yr−1 for WSF and DSF, respectively, which were comparable with the observations. The modeled data indicated that WSF and DSF had similar rates of photosynthesis and plant autotrophic respiration but differed in soil heterotrophic respiration. The simulations resulted in a hypothesis that the water table fluctuation at WSF could play a key role in determining the negative C balance in the ecosystem. A sensitivity test was conducted by running Forest-DNDC with varied water table scenarios for WSF. The results proved that the NEE fluxes from WSF were highly sensitive to the water table depth. When the water table dropped, the length of flooding season became shorter and more organic matter in the soil profile suffered from rapid decomposition that converted the ecosystem into a source atmospheric C. The conclusion from this modeling study could be applicable for a wide range of wetland and forest ecosystems that have accumulated soil organic C while face hydrological changes under certain climatic or land-use change scenarios.

Effects of date of planting on plant emergence, leaf growth, and yield in contrasting potato varieties

1983 ◽  
Vol 101 (1) ◽  
pp. 81-95 ◽  
Author(s):  
J. L. Jones ◽  
E. J. Allen
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Leaf Growth ◽  
Growth And Yield ◽  
Soil Conditions ◽  
Area Index ◽  
Potato Varieties ◽  
Wide Range ◽  
Emerging Treatments ◽  
Soil Temperatures

SUMMARYFive experiments which studied the effects of a wide range of dates of planting on contrasting potato varieties in Pembrokeshire are reported. In three experiments (1976–7) four early varieties (Home Guard, Arran Comet, Irish Peace and Ulster Sceptre) were sprouted from the end of dormancy and compared at four dates of planting, which began as soon as soil conditions allowed (February in 1975 and 1976 and March in 1977). In these experiments all early-emerging treatments were damaged by frost and in 1975 and 1976 date of planting had little effect on leaf area index or yield. In 1977 planting in late April delayed and increased peak leaf area index but reduced yields throughout harvesting. In all experiments the emergence of varieties was affected by date of planting. The varieties with the longest sprouts emerged first only from the earliest plantings; at late plantings all varieties emerged together, which suggests that rate of post-planting sprout elongation decreased in this old seed as planting was delayed despite increasing soil temperatures. The implications for testing of early varieties are discussed.In two further experiments two early varieties (Home Guard in both years and Red Craigs Royal and Arran Comet in 1 year) were compared with three maincrop varieties (Désirée, Maris Piper, Stormont Enterprise) using seed which did not begin to sprout until January at dates of planting beginning in March. Sprout length was again poorly related to earliness of emergence. Delaying planting delayed and increased peak leaf area index in all varieties but only increased yields in the early varieties which had the smallest leaf areas. In maincrop varieties date of planting had little effect on final yields. In these years there were long periods without rain and in 1976 yields were limited by the amount of water available from the soil, for as each treatment exhausted this supply bulking ceased.

scholarly journals Modeling carbon dynamics in two adjacent spruce forests with different soil conditions in Russia

2008 ◽  
Vol 5 (4) ◽  
pp. 969-980 ◽  
Author(s):  
J. Kurbatova ◽  
C. Li ◽  
A. Varlagin ◽  
X. Xiao ◽  
N. Vygodskaya
Keyword(s):  
Water Table ◽  
Carbon Balance ◽  
Atmospheric Co2 ◽  
Soil Conditions ◽  
Organic Layer ◽  
General Effect ◽  
Spruce Forest ◽  
Spruce Forests ◽  
Net Ecosystem Carbon Exchange ◽  
Wide Range

Abstract. Net ecosystem carbon exchange (NEE) was measured with eddy covariance method for two adjacent forests located at the southern boundary of European taiga in Russia in 1999–2004. The two spruce forests shared similar vegetation composition but differed in soil conditions. The wet spruce forest (WSF) possessed a thick peat layer (60 cm) with a high water table seasonally close to or above the soil surface. The dry spruce forest (DSF) had a relatively thin organic layer (5 cm) with a deep water table (>60 cm). The measured multi-year average NEE fluxes (2000 and –1440 kg C ha−1yr−1 for WSF and DSF, respectively) indicated that WSF was a source while DSF a sink of atmospheric carbon dioxide (CO2) during the experimental years. A process-based model, Forest-DNDC, was employed in the study to interpret the observations. The modeled multi-year average NEE fluxes were 1800 and –2200 kg C ha−1yr−1 for WSF and DSF, respectively, which were comparable with observations. The modeled data also showed high soil heterotrophic respiration rates at WSF that suggested that the water table fluctuation at WSF could have played a key role in determining the negative carbon balance in the wetland ecosystem. A sensitivity test was conducted by running Forest-DNDC with varied water table scenarios for WSF. The results indicated that the NEE fluxes from WSF were highly sensitive to the water table depth. When the water table was high, the WSF ecosystem maintained as a sink of atmospheric CO2; while along with the drop of the water table the length of the flooded period reduced and more organic matter in the soil profile suffered from rapid decomposition that gradually converted the ecosystem into a source of atmospheric CO2. The general effect of water table variation on wetland carbon balance observed from this modeling study could be applicable for a wide range of wetland ecosystems that have accumulated soil organic carbon while face hydrological changes under certain climatic or land-use change scenarios.

scholarly journals Pan-Arctic modelling of net ecosystem exchange of CO 2

2013 ◽  
Vol 368 (1624) ◽  
pp. 20120485 ◽  
Author(s):  
G. R. Shaver ◽  
E. B. Rastetter ◽  
V. Salmon ◽  
L. E. Street ◽  
M. J. van de Weg ◽  
...  
Keyword(s):  
Leaf Area ◽  
Air Temperature ◽  
Net Ecosystem Exchange ◽  
Light Response ◽  
The Arctic ◽  
Model Parameters ◽  
Arctic Ecosystems ◽  
Area Index ◽  
Wide Range ◽  
Single Regression

Net ecosystem exchange (NEE) of C varies greatly among Arctic ecosystems. Here, we show that approximately 75 per cent of this variation can be accounted for in a single regression model that predicts NEE as a function of leaf area index (LAI), air temperature and photosynthetically active radiation (PAR). The model was developed in concert with a survey of the light response of NEE in Arctic and subarctic tundras in Alaska, Greenland, Svalbard and Sweden. Model parametrizations based on data collected in one part of the Arctic can be used to predict NEE in other parts of the Arctic with accuracy similar to that of predictions based on data collected in the same site where NEE is predicted. The principal requirement for the dataset is that it should contain a sufficiently wide range of measurements of NEE at both high and low values of LAI, air temperature and PAR, to properly constrain the estimates of model parameters. Canopy N content can also be substituted for leaf area in predicting NEE, with equal or greater accuracy, but substitution of soil temperature for air temperature does not improve predictions. Overall, the results suggest a remarkable convergence in regulation of NEE in diverse ecosystem types throughout the Arctic.

scholarly journals Modelling transpiration of soilless greenhouse cucumber and its relationship with leaf temperature in a Mediterranean climate

2018 ◽  
pp. 911 ◽  
Author(s):  
Georgios Nikolaou ◽  
Damianos Neocleous ◽  
Nikolaos Katsoulas, Constantinos Kittas
Keyword(s):  
Water Resource Management ◽  
Correlation Coefficients ◽  
Prediction Equation ◽  
Climatic Conditions ◽  
Leaf Temperature ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Winter Crop ◽  
Greenhouse Cucumber

Three experiments (spring and autumn-winter seasons) with soilless cucumber crop (cv. Phenomeno) were conducted in order: (i) to calibrate the simplified Penman -Monteith model equation as affected by greenhouse microclimate (ii) to validate the prediction efficiency of the model at different climatic conditions and (iii) to establish a relationship between transpiration and leaf temperature. To determine Penman-Monteith model parameter variables related to the plants such as transpiration and leaf area index (LAI), so as environmental variables (i.e., radiation, temperature, humidity) were recorded. The results revealed that the determined model parameters were suitable for the whole cucumber cultivation cycle and a wide range of climatic conditions. However, parameterization of the model using autumn-winter crop data revealed superiority compared to spring data, as indicated by the correlation coefficients. Model validation showed a good fit between simulates and measures allowing implementation in commercial soilless practices. With respect to greenhouse microclimate, cooling affected daily mean air temperature and vapor pressure deficit, so as model coefficients. Leaf temperature indicated a good correlation with transpiration and the prediction equation was validated under different greenhouse climatic conditions. These results may be of value in Mediterranean greenhouses, enabling a more efficient water resource management without significant losses in agricultural productivity.   

scholarly journals How can the First ISLSCP Field Experiment contribute to present-day efforts to evaluate water stress in JULESv5.0?

2019 ◽  
Vol 12 (7) ◽  
pp. 3207-3240 ◽  
Author(s):  
Karina E. Williams ◽  
Anna B. Harper ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Camilla T. Mathison ◽  
...  
Keyword(s):  
Water Stress ◽  
Field Experiment ◽  
Tallgrass Prairie ◽  
Land Surface ◽  
Carbon Assimilation ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Dry Spell ◽  
Depth Analysis

Abstract. The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Now, 30 years on, we demonstrate how the wealth of data collected during FIFE and its subsequent in-depth analysis in the literature continue to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating “unstressed” vegetation parameters and thresholds for water stress. In particular, the responses to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES.

scholarly journals Revisiting the First ISLSCP Field Experiment to evaluate water stress in JULESv5.0

2018 ◽  
Author(s):  
Karina E. Williams ◽  
Anna B. Harper ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Camilla T. Mathison ◽  
...  
Keyword(s):  
Water Stress ◽  
Field Experiment ◽  
Tallgrass Prairie ◽  
Land Surface ◽  
Carbon Assimilation ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Dry Spell ◽  
Depth Analysis

Abstract. The First ISLSCP Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land-surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Thirty years on, we demonstrate how the wealth of data collected at FIFE and its subsequent in-depth analysis in the literature continues to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating "unstressed" vegetation parameters and thresholds for water stress. In particular, the response to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

scholarly journals Inferring Linkage Disequilibrium Between a Polymorphic Marker Locus and a Trait Locus in Natural Populations

Genetics ◽  
2000 ◽  
Vol 156 (1) ◽  
pp. 457-467 ◽  
Author(s):  
Z W Luo ◽  
S H Tao ◽  
Z-B Zeng
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Random Mating ◽  
Natural Populations ◽  
Polymorphic Marker ◽  
Marker Locus ◽  
Model Parameters ◽  
Phenotypic Variance ◽  
Wide Range ◽  
Trait Locus

Abstract Three approaches are proposed in this study for detecting or estimating linkage disequilibrium between a polymorphic marker locus and a locus affecting quantitative genetic variation using the sample from random mating populations. It is shown that the disequilibrium over a wide range of circumstances may be detected with a power of 80% by using phenotypic records and marker genotypes of a few hundred individuals. Comparison of ANOVA and regression methods in this article to the transmission disequilibrium test (TDT) shows that, given the genetic variance explained by the trait locus, the power of TDT depends on the trait allele frequency, whereas the power of ANOVA and regression analyses is relatively independent from the allelic frequency. The TDT method is more powerful when the trait allele frequency is low, but much less powerful when it is high. The likelihood analysis provides reliable estimation of the model parameters when the QTL variance is at least 10% of the phenotypic variance and the sample size of a few hundred is used. Potential use of these estimates in mapping the trait locus is also discussed.

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