Modeling coupled interactions of carbon, water, and ozone exchange between terrestrial ecosystems and the atmosphere. I: model description

A new seasonal frozen soil water-thermal coupled migration model and its numerical simulation

In this paper, a mathematical model based on spherical differential unit cell is proposed as a model for studying seasonal freeze-thaw soil space infinitesimal differential unit cell. From this model, the basic equations of permafrost moisture and heat flow motion are directly derived, then the linked equations form the permafrost water-heat coupled transport model. On this basis, the one-dimensional seasonal permafrost water-heat transport equation is derived. The model reduces the original spatial three-variable coordinate system (parallel hexahedron) into a coupled equation with a single spherical radius (R) as the independent variable, so the iterations of the numerical simulation algorithm is greatly reduced and the complexity is decreased. Finally, the model is used to simulate the seasonal freeze-thaw soil in the ShiHeZi region of Xinjiang, China. The principle of the simulation is to collect the soil temperature and humidity values of the region in layers and fixed-points using a homemade freeze-thaw soil sensor, after that we solve it by numerical calculation using MATLAB. The analysis results show that the maximum relative error of the model we proposed is 4.36, the minimum error is 0.98, and the average error is 2.515. The numerical simulation results are basically consistent with the measured data, then the proposed model is consistent with the matching states of permafrost moisture content and soil temperature in the region at different times. In addition, the experiments also demonstrate the reliability and accuracy of the model.

Automatic tree parameter extraction by a Mobile LiDAR System in an urban context

In an urban context, tree data are used in city planning, in locating hazardous trees and in environmental monitoring. This study focuses on developing an innovative methodology to automatically estimate the most relevant individual structural parameters of urban trees sampled by a Mobile LiDAR System at city level. These parameters include the Diameter at Breast Height (DBH), which was estimated by circle fitting of the points belonging to different height bins using RANSAC. In the case of non-circular trees, DBH is calculated by the maximum distance between extreme points. Tree sizes were extracted through a connectivity analysis. Crown Base Height, defined as the length until the bottom of the live crown, was calculated by voxelization techniques. For estimating Canopy Volume, procedures of mesh generation and α-shape methods were implemented. Also, tree location coordinates were obtained by means of Principal Component Analysis. The workflow has been validated on 29 trees of different species sampling a stretch of road 750 m long in Delft (The Netherlands) and tested on a larger dataset containing 58 individual trees. The validation was done against field measurements. DBH parameter had a correlation R2 value of 0.92 for the height bin of 20 cm which provided the best results. Moreover, the influence of the number of points used for DBH estimation, considering different height bins, was investigated. The assessment of the other inventory parameters yield correlation coefficients higher than 0.91. The quality of the results confirms the feasibility of the proposed methodology, providing scalability to a comprehensive analysis of urban trees.

Simultaneous improvement in productivity, water use, and albedo through crop structural modification

Spanning 15% of the global ice-free terrestrial surface, agricultural lands provide an immense and near-term opportunity to address climate change, food, and water security challenges. Through the computationally informed breeding of canopy structural traits away from those of modern cultivars, we show that solutions exist that increase productivity and water use efficiency, while increasing land-surface reflectivity to offset greenhouse gas warming. Plants have evolved to maximize capture of radiation in the upper leaves, thus shading competitors. While important for survival in the wild, this is suboptimal in monoculture crop fields for maximizing productivity and other biogeophysical services. Crop progenitors evolved over the last 25 million years in an atmosphere with less than half the [CO2] projected for 2050. By altering leaf photosynthetic rates, rising [CO2] and temperature may also alter the optimal canopy form. Here using soybean, the world's most important protein crop, as an example we show by applying optimization routines to a micrometeorological leaf canopy model linked to a steady-state model of photosynthesis, that significant gains in production, water use, and reflectivity are possible with no additional demand on resources. By modifying total canopy leaf area, its vertical profile and angular distribution, and shortwave radiation reflectivity, all traits available in most major crop germplasm collections, increases in productivity (7%) are possible with no change in water use or albedo. Alternatively, improvements in water use (13%) or albedo (34%) can likewise be made with no loss of productivity, under Corn Belt climate conditions.

Combining sap flow and eddy covariance approaches to derive stomatal and non-stomatal O3 fluxes in a forest stand

Stomatal O3 fluxes to a mixed beech/spruce stand (Fagus sylvatica/Picea abies) in Central Europe were determined using two different approaches. The sap flow technique yielded the tree-level transpiration, whereas the eddy covariance method provided the stand-level evapotranspiration. Both data were then converted into stomatal ozone fluxes, exemplifying this novel concept for July 2007. Sap flow-based stomatal O3 flux was 33% of the total O3 flux, whereas derivation from evapotranspiration rates in combination with the Penman-Monteith algorithm amounted to 47%. In addition to this proportional difference, the sap flow-based assessment yielded lower levels of stomatal O3 flux and reflected stomatal regulation rather than O3 exposure, paralleling the daily courses of canopy conductance for water vapor and eddy covariance-based total stand-level O3 flux. The demonstrated combination of sap flow and eddy covariance approaches supports the development of O3 risk assessment in forests from O3 exposure towards flux-based concepts.

The challenge of making ozone risk assessment for forest trees more mechanistic

Upcoming decades will experience increasing atmospheric CO2 and likely enhanced O3 exposure which represents a risk for the carbon sink strength of forests, so that the need for cause-effect related O3 risk assessment increases. Although assessment will gain in reliability on an O3 uptake basis, risk is co-determined by the effective dose, i.e. the plant's sensitivity per O3 uptake. Recent progress in research on the molecular and metabolic control of the effective O3 dose is reported along with advances in empirically assessing O3 uptake at the whole-tree and stand level. Knowledge on both O3 uptake and effective dose (measures of stress avoidance and tolerance, respectively) needs to be understood mechanistically and linked as a pre-requisite before practical use of process-based O3 risk assessment can be implemented. To this end, perspectives are derived for validating and promoting new O3 flux-based modelling tools.

Toward a biologically significant and usable standard for ozone that will also protect plants

Ozone remains an important phytotoxic air pollutant and is also recognized as a significant greenhouse gas. In North America, Europe, and Asia, incidence of high concentrations is decreasing, but background levels are steadily rising. There is a need to develop a biologically significant and usable standard for ozone. We compare the strengths and weaknesses of concentration-based, exposure-based and threshold-based indices, such as SUM60 and AOT40, and examine the O(3) flux concept. We also present major challenges to the development of an air quality standard for ozone that has both biological significance and practicality in usage.

Comparison of different stomatal conductance algorithms for ozone flux modelling

A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221-224.] algorithm for calculating stomatal conductance (g(s)) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of g(s), whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (A(n)).

Modelling ozone effects on adult beech trees through simulation of defence, damage, and repair costs: Implementation of the CASIROZ ozone model in the ANAFORE forest model

Ozone affects adult trees significantly, but effects on stem growth are hard to prove and difficult to correlate with the primary sites of ozone damage at the leaf level. To simulate ozone effects in a mechanistic way, at a level relevant to forest stand growth, we developed a simple ozone damage and repair model (CASIROZ model) that can be implemented into mechanistic photosynthesis and growth models. The model needs to be parameterized with cuvette measurements on net photosynthesis and dark respiration. As the CASIROZ ozone sub-model calculates effects of the ozone flux, a reliable representation of stomatal conductance and therefore ozone uptake is necessary to allow implementation of the ozone sub-model. In this case study the ozone sub-model was used in the ANAFORE forest model to simulate gas exchange, growth, and allocation. A preliminary run for adult beech (FAGUS SYLVATICA) under different ozone regimes at the Kranzberg forest site (Germany) was performed. The results indicate that the model is able to represent the measured effects of ozone adequately, and to distinguish between immediate and cumulative ozone effects. The results further help to understand ozone effects by distinguishing defence from damage and repair. Finally, the model can be used to extrapolate from the short-term results of the field study to long-term effects on tree growth. The preliminary simulations for the Kranzberg beech site show that, although ozone effects on yearly growth are variable and therefore insignificant when measured in the field, they could become significant at longer timescales (above 5 years, 5 % reduction in growth). The model offers a possible explanation for the discrepancy between the significant effects on photosynthesis (10 to 30 % reductions simulated), and the minor effects on growth. This appears to be the result of the strong competition and slow growth of the Kranzberg forest, and the importance of stored carbon for the adult beech (by buffering effects on carbon gain). We finally conclude that inclusion of ozone effects into current forest growth and yield models can be an important improvement into their overall performance, especially when simulating younger and less dense forests.

Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange.