An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance

This paper presents the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), which is a vertical (1-D) integrated radiative transfer and energy balance model. The model links visible to thermal infrared radiance spectra (0.4 to 50 μm) as observed above the canopy to the fluxes of water, heat and carbon dioxide, as a function of vegetation structure, and the vertical profiles of temperature. Output of the model is the spectrum of outgoing radiation in the viewing direction and the turbulent heat fluxes, photosynthesis and chlorophyll fluorescence. A special routine is dedicated to the calculation of photosynthesis rate and chlorophyll fluorescence at the leaf level as a function of net radiation and leaf temperature. The fluorescence contributions from individual leaves are integrated over the canopy layer to calculate top-of-canopy fluorescence. The calculation of radiative transfer and the energy balance is fully integrated, allowing for feedback between leaf temperatures, leaf chlorophyll fluorescence and radiative fluxes. Leaf temperatures are calculated on the basis of energy balance closure. Model simulations were evaluated against observations reported in the literature and against data collected during field campaigns. These evaluations showed that SCOPE is able to reproduce realistic radiance spectra, directional radiance and energy balance fluxes. The model may be applied for the design of algorithms for the retrieval of evapotranspiration from optical and thermal earth observation data, for validation of existing methods to monitor vegetation functioning, to help interpret canopy fluorescence measurements, and to study the relationships between synoptic observations with diurnally integrated quantities. The model has been implemented in Matlab and has a modular design, thus allowing for great flexibility and scalability.

Towards an improved and more flexible representation of water stress in coupled photosynthesis–stomatal conductance models

Coupled photosynthesis–stomatal conductance (A–gs) models are commonly used in ecosystem models to represent the exchange rate of CO2 and H2O between vegetation and the atmosphere. The ways these models account for water stress differ greatly among modelling schemes. This study provides insight into the impact of contrasting model configurations of water stress on the simulated leaf-level values of net photosynthesis (A), stomatal conductance (gs), the functional relationship among them and their ratio, the intrinsic water use efficiency (A/gs), as soil dries. A simple, yet versatile, normalized soil moisture dependent function was used to account for the effects of water stress on gs, on mesophyll conductance (gm) and on the biochemical capacity. Model output was compared to leaf-level values obtained from the literature. The sensitivity analyses emphasized the necessity to combine both stomatal and non-stomatal limitations of A in coupled A–gs models to accurately capture the observed functional relationships A vs. gs and A/gsvs. gs in response to drought. Accounting for water stress in coupled A–gs models by imposing either stomatal or biochemical limitations of A, as commonly practiced in most ecosystem models, failed to reproduce the observed functional relationship between key leaf gas exchange attributes. A quantitative limitation analysis revealed that the general pattern of C3 photosynthetic response to water stress may be well represented in coupled A–gs models by imposing the highest limitation strength to gm, then to gs and finally to the biochemical capacity.

Relating traits to diversification: A simple test

We describe a simple comparative method for determining whether rates of diversification are correlated with continuous traits in species-level phylogenies. This involves comparing traits of species with net speciation rate (number of nodes linking extant species with the root divided by the root to tip evolutionary distance), using a phylogenetically corrected correlation. We use simulations to examine the power of this test. We find that the approach has acceptable power to uncover relationships between speciation and a continuous trait and is robust to background random extinction; however, the power of the approach is reduced when the rate of trait evolution is decreased. The test has low power to relate diversification to traits when extinction rate is correlated with the trait. Clearly, there are inherent limitations in using only data on extant species to infer correlates of extinction; however, this approach is potentially a powerful tool in analyzing correlates of speciation.

Quantifying the effects of perturbing the physics of an interactive sulfur scheme using an ensemble of GCMs on the climateprediction.net platform

Aerosols from anthropogenic and natural sources have been recognized as having an important impact on the climate system. However, the small size of aerosol particles (ranging from 0.01 to more than 10 μm in diameter) and their influence on solar and terrestrial radiation makes them difficult to represent within the coarse resolution of general circulation models (GCMs) such that small-scale processes, for example, sulfate formation and conversion, need parameterizing. It is the parameterization of emissions, conversion, and deposition and the radiative effects of aerosol particles that causes uncertainty in their representation within GCMs. The aim of this study was to perturb aspects of a sulfur cycle scheme used within a GCM to represent the climatological impacts of sulfate aerosol derived from natural and anthropogenic sulfur sources. It was found that perturbing volcanic SO2 emissions and the scavenging rate of SO2 by precipitation had the largest influence on the sulfate burden. When these parameters were perturbed the sulfate burden ranged from 0.73 to 1.17 TgS for 2050 sulfur emissions (A2 Special Report on Emissions Scenarios (SRES)), comparable with the range in sulfate burden across all the Intergovernmental Panel on Climate Change SRESs. Thus, the results here suggest that the range in sulfate burden due to model uncertainty is comparable with scenario uncertainty. Despite the large range in sulfate burden there was little influence on the climate sensitivity, which had a range of less than 0.5 K across the ensemble. We hypothesize that this small effect was partly associated with high sulfate loadings in the control phase of the experiment.

The influence of hilly terrain on canopy-atmosphere carbon dioxide exchange

Topography influences many aspects of forest-atmosphere carbon exchange; yet only a small number of studies have considered the role of topography on the structure of turbulence within and above vegetation and its effect on canopy photosynthesis and the measurement of net ecosystem exchange of CO2 (N-ee) using flux towers. Here, we focus on the interplay between radiative transfer, flow dynamics for neutral stratification, and ecophysiological controls on CO2 sources and sinks within a canopy on a gentle cosine hill. We examine how topography alters the forest-atmosphere CO2 exchange rate when compared to uniform flat terrain using a newly developed first-order closure model that explicitly accounts for the flow dynamics, radiative transfer, and nonlinear eco physiological processes within a plant canopy. We show that variation in radiation and airflow due to topography causes only a minor departure in horizontally averaged and vertically integrated photosynthesis from their flat terrain values. However, topography perturbs the airflow and concentration fields in and above plant canopies, leading to significant horizontal and vertical advection of CO2. Advection terms in the conservation equation may be neglected in flow over homogeneous, flat terrain, and then N-ee = F-c, the vertical turbulent flux of CO2. Model results suggest that vertical and horizontal advection terms are generally of opposite sign and of the same order as the biological sources and sinks. We show that, close to the hilltop, F-c departs by a factor of three compared to its flat terrain counterpart and that the horizontally averaged F-c-at canopy top differs by more than 20% compared to the flat-terrain case.

Acclimation of photosynthesis to elevated CO2 in onion (Allium cepa) grown at a range of temperatures

Onion (Allium cepa) was grown in the field within temperature gradient tunnels (providing about -2.5degreesC to +2.5degreesC from outside temperatures) maintained at either 374 or 532 mumol mol(-1) CO2. Plant leaf area was determined non-destructively at 7 day intervals until the time of bulbing in 12 combinations of temperature and CO2 concentration. Gas exchange was measured in each plot at the time of bulbing, and the carbohydrate content of the leaf (source) and bulb (sink) was determined. Maximum rate of leaf area expansion increased with mean temperature. Leaf area duration and maximum rate of leaf area expansion were not significantly affected by CO2. The light-saturated rates of leaf photosynthesis (A(sat)) were greater in plants grown at normal than at elevated CO2 concentrations at the same measurement CO2 concentration. Acclimation of photosynthesis decreased with an increase in growth temperature, and with an increase in leaf nitrogen content at elevated CO2. The ratio of intercellular to atmospheric CO2 (C-i/C-a ratio) was 7.4% less for plants grown at elevated compared with normal CO2. A(sat) in plants grown at elevated CO2 was less than in plants grown at normal CO2 when compared at the same C-i Hence, acclimation of photosynthesis was due both to stomatal acclimation and to limitations to biochemical CO2 fixation. Carbohydrate content of the onion bulbs was greater at elevated than at normal CO2. In contrast, carbohydrate content was less at elevated compared with normal CO2 in the leaf sections in which CO2 exchange was measured at the same developmental stage. Therefore, acclimation of photosynthesis in fully expanded onion leaves was detected despite the absence of localised carbohydrate accumulation in these field-grown crops.

Effects of cultural system (organic and conventional) on growth, photosynthesis and yield components of sweet corn (zea mays L.) under semi-arid environment

Organic sweet maize consists of a new industrial crop product. Field experiment was conducted to determine the effects of cultural systems on growth, photosynthesis and yield components of sweet maize crop (Zea mays L. F-1 hybrid 'Midas'). A randomized complete block design was employed with four replicates per treatment (organic fertilization: cow manure (5, 10 and 20 t ha(-1)), poultry manure (5, 10 and 20 t ha(-1)) and barley mulch (5, 10 and 20 t ha(-1)), synthetic fertilizer (240 kg N ha(-1)): 21-0-0 and control). The lowest dry weight, height and leaf area index and sod organic matter were measured in the control treatment. Organic matter content was proportionate to the amount of manure applied. The control plots had the lowest yield (1593 kg ha(-1)) and the double rate cow manure plots the had,greatest one. (6104 kg ha(-1)). High correlation between sweet corn yield and organic matter was registered. Moreover, the lowest values of 1000-grain weight were obtained with control plot. The fertilizer plot gave values which were similar to the full rate cow manure treatment. The photosynthetic race of the untreated control was significantly lower than that of the other treatments. The phorosynthetic rate increased as poultry manure and barley mulch ram decreased and as cow manure increased. Furthermore the untreated control had the lowest stomatal conductance and chlorophyll content. Our results indicated that sweet corn growth and yield in the organic plots was significantly higher than those in the conventional plots.

Acclimation of photosynthesis to elevated CO2 in onion (allium cepa) grown at a range of temperatures

Onion (Allium cepa) was grown in the field within temperature gradient tunnels (providing about -2.5 degrees C to +2.5 degrees C from outside temperatures) maintained at either 374 or 532 mumol mol (-1) CO2. Plant leaf area was determined non-destructively at 7 day intervals until the time of bulbing in 12 combinations of temperature and CO2 concentration. Gas exchange was measured in each plot at the time of bulbing, and the carbohydrate content of the leaf (source) and bulb (sink) was determined. Maximum rate of leaf area expansion increased with mean temperature. Leaf area duration and maximum rate of leaf area expansion were not significantly affected by CO2. The light-saturated rates of leaf photosynthesis (A(sat)) were greater in plants grown at normal than at elevated CO2 concentrations at the same measurement CO2 concentration. Acclimation of photosynthesis decreased with an increase in growth temperature, and with an increase in leaf nitrogen content at elevated CO2. The ratio of intercellular to atmospheric CO2 (C-i/C-a ratio) was 7.4% less for plants grown at elevated compared with normal CO2. A(sat) in plants grown at elevated CO2 was less than in plants grown at normal CO2 when compared at the same C-i Hence, acclimation of photosynthesis was due both to stomatal acclimation and to limitations to biochemical CO2 fixation. Carbohydrate content of the onion bulbs was greater at elevated than at normal CO2. In contrast, carbohydrate content was less at elevated compared with normal CO2 in the leaf sections in which CO2 exchange was measured at the same developmental stage. Therefore, acclimation of photosynthesis in fully expanded onion leaves was detected despite the absence of localised carbohydrate accumulation in these field-grown crops.

Increased temperature sensitivity of net DOC production from ombrotrophic peat due to water table draw-down.

The production and release of dissolved organic carbon (DOC) from peat soils is thought to be sensitive to changes in climate, specifically changes in temperature and rainfall. However, little is known about the actual rates of net DOC production in response to temperature and water table draw-down, particularly in comparison to carbon dioxide (CO2) fluxes. To explore these relationships, we carried out a laboratory experiment on intact peat soil cores under controlled temperature and water table conditions to determine the impact and interaction of each of these climatic factors on net DOC production. We found a significant interaction (P < 0.001) between temperature, water table draw-down and net DOC production across the whole soil core (0 to −55 cm depth). This corresponded to an increase in the Q10 (i.e. rise in the rate of net DOC production over a 10 °C range) from 1.84 under high water tables and anaerobic conditions to 3.53 under water table draw-down and aerobic conditions between −10 and − 40 cm depth. However, increases in net DOC production were only seen after water tables recovered to the surface as secondary changes in soil water chemistry driven by sulphur redox reactions decreased DOC solubility, and therefore DOC concentrations, during periods of water table draw-down. Furthermore, net microbial consumption of DOC was also apparent at − 1 cm depth and was an additional cause of declining DOC concentrations during dry periods. Therefore, although increased temperature and decreased rainfall could have a significant effect on net DOC release from peatlands, these climatic effects could be masked by other factors controlling the biological consumption of DOC in addition to soil water chemistry and DOC solubility. These findings highlight both the sensitivity of DOC release from ombrotrophic peat to episodic changes in water table draw-down, and the need to disentangle complex and interacting controls on DOC dynamics to fully understand the impact of environmental change on this system.

Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence?

Attempts to estimate photosynthetic rate or gross primary productivity from remotely sensed absorbed solar radiation depend on knowledge of the light use efficiency (LUE). Early models assumed LUE to be constant, but now most researchers try to adjust it for variations in temperature and moisture stress. However, more exact methods are now required. Hyperspectral remote sensing offers the possibility of sensing the changes in the xanthophyll cycle, which is closely coupled to photosynthesis. Several studies have shown that an index (the photochemical reflectance index) based on the reflectance at 531 nm is strongly correlated with the LUE over hours, days and months. A second hyperspectral approach relies on the remote detection of fluorescence, which is a directly related to the efficiency of photosynthesis. We discuss the state of the art of the two approaches. Both have been demonstrated to be effective, but we specify seven conditions required before the methods can become operational.

Elastic-net prefiltering for two-class classification

A two-stage linear-in-the-parameter model construction algorithm is proposed aimed at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage which constructs a sparse linear-in-the-parameter classifier. The prefiltering stage is a two-level process aimed at maximizing a model's generalization capability, in which a new elastic-net model identification algorithm using singular value decomposition is employed at the lower level, and then, two regularization parameters are optimized using a particle-swarm-optimization algorithm at the upper level by minimizing the leave-one-out (LOO) misclassification rate. It is shown that the LOO misclassification rate based on the resultant prefiltered signal can be analytically computed without splitting the data set, and the associated computational cost is minimal due to orthogonality. The second stage of sparse classifier construction is based on orthogonal forward regression with the D-optimality algorithm. Extensive simulations of this approach for noisy data sets illustrate the competitiveness of this approach to classification of noisy data problems.

Sensitivity analysis of an ocean carbon cycle model in the North Atlantic: an investigation of parameters affecting the air-sea CO2 flux, primary production and export of detritus

The sensitivity of the biological parameters in a nutrient-phytoplankton-zooplankton-detritus (NPZD) model in the calculation of the air-sea CO2 flux, primary production and detrital export is analysed. We explore the effect on these outputs of variation in the values of the twenty parameters that control ocean ecosystem growth in a 1-D formulation of the UK Met Office HadOCC NPZD model used in GCMs. We use and compare the results from one-at-a-time and all-at-a-time perturbations performed at three sites in the EuroSITES European Ocean Observatory Network: the Central Irminger Sea (60° N 40° W), the Porcupine Abyssal Plain (49° N 16° W) and the European Station for Time series in the Ocean Canary Islands (29° N 15° W). Reasonable changes to the values of key parameters are shown to have a large effect on the calculation of the air-sea CO2 flux, primary production, and export of biological detritus to the deep ocean. Changes in the values of key parameters have a greater effect in more productive regions than in less productive areas. The most sensitive parameters are generally found to be those controlling well-established ocean ecosystem parameterisations widely used in many NPZD-type models. The air-sea CO2 flux is most influenced by variation in the parameters that control phytoplankton growth, detrital sinking and carbonate production by phytoplankton (the rain ratio). Primary production is most sensitive to the parameters that define the shape of the photosynthesis-irradiance curve. Export production is most sensitive to the parameters that control the rate of detrital sinking and the remineralisation of detritus.

Changes in global net radiative imbalance 1985-2012

Combining satellite data, atmospheric reanalyses and climate model simulations, variability in the net downward radiative flux imbalance at the top of Earth's atmosphere (N) is reconstructed and linked to recent climate change. Over the 1985-1999 period mean N (0.34 ± 0.67 Wm–2) is lower than for the 2000-2012 period (0.62 ± 0.43 Wm–2, uncertainties at 90% confidence level) despite the slower rate of surface temperature rise since 2000. While the precise magnitude of N remains uncertain, the reconstruction captures interannual variability which is dominated by the eruption of Mt. Pinatubo in 1991 and the El Niño Southern Oscillation. Monthly deseasonalized interannual variability in N generated by an ensemble of 9 climate model simulations using prescribed sea surface temperature and radiative forcings and from the satellite-based reconstruction is significantly correlated (r ∼ 0.6) over the 1985-2012 period.

Joint data assimilation of satellite reflectance and net ecosystem exchange data constrains ecosystem carbon fluxes at a high-elevation subalpine forest

We utilized an ecosystem process model (SIPNET, simplified photosynthesis and evapotranspiration model) to estimate carbon fluxes of gross primary productivity and total ecosystem respiration of a high-elevation coniferous forest. The data assimilation routine incorporated aggregated twice-daily measurements of the net ecosystem exchange of CO2 (NEE) and satellite-based reflectance measurements of the fraction of absorbed photosynthetically active radiation (fAPAR) on an eight-day timescale. From these data we conducted a data assimilation experiment with fifteen different combinations of available data using twice-daily NEE, aggregated annual NEE, eight-day f AP AR, and average annual fAPAR. Model parameters were conditioned on three years of NEE and fAPAR data and results were evaluated to determine the information content from the different combinations of data streams. Across the data assimilation experiments conducted, model selection metrics such as the Bayesian Information Criterion and Deviance Information Criterion obtained minimum values when assimilating average annual fAPAR and twice-daily NEE data. Application of wavelet coherence analyses showed higher correlations between measured and modeled fAPAR on longer timescales ranging from 9 to 12 months. There were strong correlations between measured and modeled NEE (R2, coefficient of determination, 0.86), but correlations between measured and modeled eight-day fAPAR were quite poor (R2 = −0.94). We conclude that this inability to determine fAPAR on eight-day timescale would improve with the considerations of the radiative transfer through the plant canopy. Modeled fluxes when assimilating average annual fAPAR and annual NEE were comparable to corresponding results when assimilating twice-daily NEE, albeit at a greater uncertainty. Our results support the conclusion that for this coniferous forest twice-daily NEE data are a critical measurement stream for the data assimilation. The results from this modeling exercise indicate that for this coniferous forest, average annuals for satellite-based fAPAR measurements paired with annual NEE estimates may provide spatial detail to components of ecosystem carbon fluxes in proximity of eddy covariance towers. Inclusion of other independent data streams in the assimilation will also reduce uncertainty on modeled values.