Simulation of thermodynamic transmission in green roof ecosystem

Green roofs entail the creation of vegetated space on the top of artificial structures. They can modify the thermal properties of buildings to bring cooling energy conservation and improve human comfort. This study evaluates the thermodynamic transmission in the green roof ecosystem under different vegetation treatments. Our model simulation is based on the traditional Bowen ratio energy balance model (BREBM) and a proposed solar radiation shield effectiveness model (SEM). The BREBM investigates energy absorption of different components of radiation, and the SEM evaluates the radiation shield effects. The proposed model is tested and validated to be efficient to simulate solar energy transmission in green roofs, with some major findings. Firstly, the solar radiation transmission processes might be considered as free vibration motion. Daytime positive heat storage of the green roof is 350-520 W·m⁻² on an hourly basis. Nighttime or afternoon negative value registers a rather constant magnitude of −60 W·m⁻². Daily net average is positive around 155-210 W·m⁻². Secondly, solar radiation vibration is highly correlated with plant structure. The canopy reflectance and transmittance are strongly correlated (R² = 0.87). The multi-layer shrub treatment has the highest shield effectiveness (0.34), followed by two-layer groundcover (0.27), and single-layer grass (0.16). Green roof vegetation absorbs and stores large amounts of heat to form an effective thermal buffer against daily temperature fluctuation. Vegetated roofs drastically depress air temperature in comparison with bare ground (control treatment). Finally, the thermodynamic model is relatively simple and efficient for investigating thermodynamic transmission in green roof ecosystem, and it could be developed into a broad solar radiant land cover model.     

Estimation of annual potential evapotranspiration at regional scale based on the effect of moisture on soil respiration

Potential evapotranspiration (PET) is an important component of water cycle. For traditional models derived from the principle of aerodynamics and the surface energy balance, its calculation always includes many parameters, such as net radiation, water vapor pressure, air temperature and wind speed. We found that it can be acquired in an easier way in specific regions. In this study, a new PET model (PETP model) derived from two empirical models of soil respiration was evaluated using the Penman-Monteith equation as a standard method. The results indicate that the PETP model estimation concur with the Penman-Monteith equation in sites where annual precipitation ranges from 717.71 mm to 1727.37 mm (R² = 0.68, p = 0.0002), but show large discrepancies in all sites (R² = 0.07, p = 0.1280). Then we applied our PETP model at the global scale to the regions with precipitation higher than 700 mm using 2.5° CMAP data to obtain the annual PET for 2006. As expected, the spatial pattern is satisfactory overall, with the highest PET values distributed in the lower latitudes or coastal regions, and with an average of 1292.60 ± 540.15 mm year⁻¹. This PETP model provides a convenient approach to estimate PET at regional scales.     

Abundance and variability of microorganisms and transparent exopolymer particles across the ice–water interface of melting first-year sea ice in the Laptev Sea (Arctic)

The distribution and abundance of transparent exopolymer particles (TEP) was determined in and below pack ice of the Laptev Sea from July to September 1995. Samples were collected from the lowermost 10 cm of ice floes and at 10 cm below the ice–water interface. Abundance of bacteria, protists and TEP was determined, and the sea ice–water boundary layer was characterized using temperature, salinity and molecular viscous shear stress. TEP, with a distinct size distribution signal, were found in highest concentrations inside the sea ice, ranging from not detectable to 16 cm² l⁻¹ (median: 2.9 cm² l⁻¹). In the water, concentrations were one order of magnitude lower, ranged from below detection to 2.7 cm² l⁻¹ (median: 0.2 cm² l⁻¹) and decreased after the middle of August, whereas abundances of autotrophic flagellates (AF), diatoms, heterotrophic flagellates (HF) and ciliates increased. The abundance of TEP decreased with its size in all samples following a power law relationship. The relation of TEP to the microbial community differed between the sea ice and water, being positively correlated with bacteria and diatoms in the ice and negatively correlated with HF in the sea water. The presence of a pycnocline significantly influenced the abundance of organisms, diatom composition and TEP concentrations. Pennate diatoms dominated by Nitzschia frigida were most abundant inside the ice. Though bacteria have the potential to produce exopolymeric substances (EPS), the results of this study indicate that the majority of TEP at the ice–water interface in first-year Arctic summer pack ice are produced by diatoms. Received: 19 August 1999 / Accepted: 4 July 2000     

Structural changes in lake functioning induced from nutrient loading and climate variability

Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964–1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)–phytoplankton–zooplankton–detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r = 0.41), herbivorous grazing (r = 0.38), and detritus mineralization (r = 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042–2051.] to emphasize the “bottom-up” control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 μg L⁻¹) and chlorophyll a (4 μg L⁻¹) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment.     

Identification of important factors for water vapor flux and CO2 exchange in a cropland

Water vapor flux and carbon dioxide (CO₂) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation neural network technique associated with the Bayesian technique of automatic relevance determination (ARD) was employed to investigate water vapor and CO₂ exchange between the canopy of summer maize and atmosphere in responses to variations of environmental and physiological factors. These factors, namely the photosynthetically active radiation (PAR), air temperature (T), vapor pressure deficient (VPD), leaf-area index (LAI), soil water content in root zone (W), and friction velocity (U*), were used as inputs in neural network analysis. Results showed that PAR, VPD, T and LAI were the primary factors regulating both water vapor and CO₂ fluxes with VPD and W more critical to water vapor flux and PAR and T more crucial to CO₂ exchange. Furthermore, two time variables “day of the year (DOY)” and “time of the day (TOD)” could also improve the simulation results of neural network analysis. The important factors identified by the neural network technique used in this study were in the order of PAR > T > VPD > LAI > U* > TOD for water vapor flux and in the order of VPD > W > LAI > T > PAR > DOY for CO₂ exchange. This study suggests that neural network technique associated with ARD could be a useful tool for identifying important factors regulating water vapor and CO₂ fluxes in terrestrial ecosystem.     

Mechanisms of moisture stress in a mid-latitude temperate forest: Implications for feedforward and feedback controls from an irrigation experiment

While it is well established that stomata close during moisture stress, strong correlations among environmental (e.g., vapor pressure deficit, soil moisture, air temperature, radiation) and internal (e.g., leaf water potential, sap flow, root-shoot signaling) variables obscure the identification of causal mechanisms from field experiments. Models of stomatal control fitted to field data therefore suffer from ambiguous parameter identification, with multiple acceptable (i.e., nearly optimal) model structures emphasizing different moisture status indicators and different processes. In an effort to minimize these correlations and improve parameter and process identification, we conducted an irrigation experiment on red maples (Acer rubrum L.) at Harvard Forest (summers of 2005 and 2006). Control and irrigated trees experienced similar radiative and boundary layer forcings, but different soil moisture status, and thus presumably different diurnal cycles of internal leaf water potential. Measured soil moisture and atmospheric forcing were used to drive a transient tree hydraulic model that incorporated a Jarvis-type leaf conductance in a Penman–Monteith framework with a Cowan-type (resistance and capacitance) tree hydraulic representation. The leaf conductance model included dependence on both leaf matric potential, Ψ_L (so-called feedback control) and on vapor pressure deficit, D (so-called feedforward control). Model parameters were estimated by minimizing the error between predicted and measured sap flow. The whole-tree irrigation treatment had the effect of elevating measured transpiration during summer dry-downs, demonstrating the limiting effect that subsurface resistance may have on transpiration during these times of moisture stress. From the best fitted model, we infer that during dry downs, moisture stress manifests itself in an increase of soil resistance with a resulting decrease in Ψ_L, leading to both feedforward and feedback controls in the control trees, but only feedforward control for the irrigated set. Increases in the sum-of-squares error when individual model components were disabled allow us to reject the following three null hypotheses: (1) the f(D) stress is statistically insignificant (p = 0.01); (2) the f(Ψ_L) stress is statistically insignificant (p = 0.07); and (3) plant storage capacitance is independent of moisture status (p = 0.07).     

Modeling ecosystem responses to prescribed fires in a phosphorus-enriched Everglades wetland: I. Phosphorus dynamics and cattail recovery

We have developed and applied a process-based model, the Wetland Ecosystem Model (WEM), to evaluate the effects of a prescribed fire on the phosphorus (P) dynamics and cattail (Typha domingensis) growth in a P-enriched area in the Florida Everglades. The WEM couples major ecosystem processes including carbon (C), nitrogen (N) and P biogeochemical cycles, plant growth, hydrology, and fire disturbance. The model is used to assess the effects of a prescribed fire on P dynamics and cattail growth through dynamic interaction among four modules: fire, water chemistry, soil, and vegetation. The simulation results are in agreement with observed data including cattail above- and belowground biomass and dead mass, P concentration in surface-water, pore-water, and soil, and soil and water temperature. Cattail aboveground biomass reached the unburned level one year after burn; belowground biomass recovered to unburned level one and half years after the fire, however, dead mass did not completely reach unburned level two years after fires. The fire increased water and soil temperatures in the short term, while indirectly increasing the sensitivity of water and soil temperature post-fire response to air temperature by altering the energy exchange between air and water through a canopy gap created by fire. The fire also altered the P dynamics in surface-water and pore-water. A post-fire P pulse that lasted for less than one month was observed in surface-water. A similar P pulse, but in a small magnitude and a longer duration, was also observed in the pore-water total phosphorus (TP), and then came back to normal level after approximately three months. No significant changes in soil TP was observed during the study period. Meanwhile, no significant changes in water nutrients were observed downstream of the study plot. This finding indicated that the P-enriched wetlands in Everglades act as a buffer in regulating the P concentration in surface-water. Our study showed that the distance of fire effects on a 300 m × 300 m plot was less than 300 m downstream. Sensitivity analysis identified that the air temperature and hydrological conditions are two important driving factors which may alter the cattail community dynamics in response to prescribed fires. Similar to the filed studies, this study provided evidences that fire played an important role in managing plant growth and P dynamics in the Florida Everglades.     

Modelling radiative balance in a row-crop canopy: Row-soil surface net radiation partition

Row crops like vineyards undergo various and significant manipulations of training system and cultural practices, which strongly influence the quality of products. Variations of water vapour fluxes from the soil surface and the leaves in the row volume are closely linked to the ratio of energy available to each compartment. A physically realistic model of available energy partition between the rows and the soil surface is therefore a key factor towards optimization of such systems, and must be included in canopy models. A number of available models were not directly validated. The purpose of the study was therefore to design a model of net radiation partition and check it directly.The model of net radiation partition between rows (Rnv), considered as a whole, and intervening soil surface (Rns) of a row-crop canopy was developed from physically realistic yet simple assumptions:

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global solar (short wave) radiation partition was calculated by a previously validated geometric model;

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long-wave radiative fluxes between the soil surface, the rows and the atmosphere were calculated from the corresponding view factors, which only depended on canopy geometry;

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atmospheric radiation was estimated by a simple empirical relation based on air temperature as the only input variable;

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air temperature in the vicinity of leaves replaced leaf surface temperatures as a more convenient input variable, with little loss of information.

The input variables were incoming direct and diffuse solar radiation, soil surface mean temperature and air temperature near the leaves. The main parameters were soil and leaf albedos, row porosity and dimensions.A direct validation of the model was attempted by measuring net radiation above the canopy and at five positions above the soil surface in a vineyard of the Bordeaux area. The reliability of soil surface net radiation measurements was estimated by thorough error propagation analysis. When found significant, errors were corrected and finally soil surface net radiation data were corrected only for delay in direct downward solar radiation striking net radiometers, because canopy was discontinuous and height of net radiometers was not negligible compared to canopy height.In these conditions, model calculations were in agreement with measurements, although the model slightly underestimated Rns and therefore overestimated Rnv. As the mean error was about 20 W m⁻², and therefore compatible with instrument accuracy, the results were considered satisfactory.This available energy partition model is able to estimate radiative balance in various canopy systems and in various thermal environment conditions, leading to easier simulations of energy balance and water fluxes. It could therefore be a useful tool for optimizing row-crop canopies, taking fully into account any kind of present or future thermal environment.     

Dissolved organic carbon concentrations and fluxes in forest catchments and streams: DOC-3 model

Dissolved organic carbon (DOC) concentrations in south-western Nova Scotia streams, sampled at weekly to biweekly intervals, varied across streams from about 3 to 40 mg L⁻¹, being highest mid-summer to fall, and lowest during winter to spring. A 3-parameter model (DOC-3) was proposed to project daily stream DOC concentrations and fluxes from modelled estimates for daily soil temperature and moisture, year-round, and in relation to basin size and wetness. The parameters of this model refer to (i) a basin-specific DOC release parameter “k_DOC^”, related to the wet- and open-water area percentages per basin, (ii) the lag time “τ” between DOC production and subsequent stream DOC emergence, related to the catchment area above the stream sampling location; and (iii) the activation energy “Ea”, to deal with the temperature effect on DOC production. This model was calibrated with the 1988-2006 DOC concentration data from three streams (Pine Marten, Moosepit Brook, and the Mersey River sampled at or near Kejimkujik National Park, or KNP), and was used to interpret the biweekly 1999-2003 DOC concentrations data (stream, ground and lake water, soil lysimeters) of the Pockwock-Bowater Watershed Project near Halifax, Nova Scotia. The data and the model revealed that the DOC concentrations within the streams were not correlated to the DOC concentrations within the soil- and groundwater, but were predictable based on (i) the hydrologically inferred weather-induced changes in soil moisture and temperature next to each stream, and (ii) the topographically inferred basin area and wet- and open-water area percentages associated with each stream (R² = 0.53; RMSE = 3.5 mg L⁻¹). Model-predicted fluxes accounted 74% of the hydrometrically determined DOC exports at KNP.     

Local calibration of coliforms parameters of water quality problem at Igapó I Lake, Londrina, Paraná, Brazil

This article presents results concerning the local calibration of the transport parameters (longitudinal and transversal diffusions and decay coefficient) for a two-dimensional problem of water quality at Igapó I Lake, located in Londrina, Paraná, Brazil, using fecal coliforms as an indicator of water quality. The simulation of fecal coliforms concentrations all over the water body is conducted by means of a structured discretization of the geometry of Igapó I Lake, together with the finite difference and finite element methods. By using the velocity field, modeled by the Navier-Stokes and Poisson equations, the flow of fecal coliforms is described by means of a transport model, which considers advective and diffusive processes, as well as a process of fecal coliforms decay. In the checkpoint, the longitudinal and transversal diffusion coefficients and the coliforms decay coefficient that best fitted the value of the fecal coliforms concentration were D_x = D_y = 0.001 m²/h and k = 0.5 d⁻¹ = 0.02083 h⁻¹. A qualitative and quantitative analysis of the numerical simulations conducted in function of the diffusion coefficients and of the coliforms decay parameter provided a better understanding of the local water quality at Igapó I Lake.     

An integrated modeling framework for performing environmental assessments: Application to ecosystem services in the Albemarle-Pamlico basins (NC and VA, USA)

The U.S. Environmental Protection Agency uses environmental models to inform rulemaking and policy decisions at multiple spatial and temporal scales. As decision-making has moved towards integrated thinking and assessment (e.g. media, site, region, services), the increasing complexity and interdisciplinary nature of modern environmental problems has necessitated a new generation of integrated modeling technologies. Environmental modelers are now faced with the challenge of determining how data from manifold sources, types of process-based and empirical models, and hardware/software computing infrastructure can be reliably integrated and applied to protect human health and the environment.In this study, we demonstrate an Integrated Modeling Framework that allows us to predict the state of freshwater ecosystem services within and across the Albemarle-Pamlico Watershed, North Carolina and Virginia (USA). The Framework consists of three facilitating technologies: Data for Environmental Modeling automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation is a hardware and software parallel-computing interface with pre/post-processing analysis tools, including parameter estimation, uncertainty and sensitivity analysis. In this application, five environmental models are linked within the Framework to provide multimedia simulation capabilities: the Soil Water Assessment Tool predicts watershed runoff; the Watershed Mercury Model simulates mercury runoff and loading to streams; the Water quality Analysis and Simulation Program predicts water quality within the stream channel; the Habitat Suitability Index model predicts physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator predicts fish growth and production, as well as exposure and bioaccumulation of toxic substances (e.g., mercury).Using this Framework, we present a baseline assessment of two freshwater ecosystem services-water quality and fisheries resources-in headwater streams throughout the Albemarle-Pamlico. A stratified random sample of 50 headwater streams is used to draw inferences about the target population of headwater streams across the region. Input data is developed for a twenty-year baseline simulation in each sampled stream using current land use and climate conditions. Monte Carlo sampling (n = 100 iterations per stream) is also used to demonstrate some of the Framework's experimental design and data analysis features. To evaluate model performance and accuracy, we compare initial (i.e., uncalibrated) model predictions (water temperature, dissolved oxygen, fish density, and methylmercury concentration within fish tissue) against empirical field data. Finally, we ‘roll-up’ the results from individual streams, to assess freshwater ecosystem services at the regional scale.     

Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

Spatio-temporal modelling of ground vegetation development in mountain spruce forests

More complex models of forest ecosystems are required to understand how land-cover changes can impact vegetation dynamics and spatial pattern. In order to document spatio-temporal modelling abilities, the observations conducted in the declined climax mountain Norway spruce forest during the recovery period (1995-2006) are used for simulation and spatial analysis in the GIS environment. The developed spatio-temporal model is used for simulation of forest vegetation dynamics in a mountain spruce forest in the framework of regeneration processes after stress from air pollution. In order to explore the spatial and temporal phenomena of regeneration processes, the spatio-temporal model is based on a large set of ordinary differential equations that solve dynamic processes in sets of microsites arranged in grids for each ground vegetation species and each age group of Norway spruce seedlings. The spatial extent of the explored site is composed of a set of 50 × 50 microsites. Each microsite is represented by a square with dimensions of 1 m × 1 m. The presented simulation studies are mainly focused on seedlings from the seed year 1992, in order to explore the longest monitored time series of survival. It is based on exponential growth models that are related to the environmental conditions for each microsite. The canopy gaps based on estimates of the local crown projected area, the soil type layer, and the dominant grass density are used to provide case simulation studies. The first case study simulates the influence of microsite positions in relation to the local tree crown projections on the survival of spruce seedlings. It is assumed that the density of the trees is the main factor that determines the light and heat supply to the ground level of the Norway spruce seedlings. The second case study extends the previous study to include terms that determine the growth ratio in dependence on the crown projection area. The third case study provides further extensions in order to simulate growth ratio relations to the local soil type. The fourth case study demonstrates the local influence of the dominant grasses, such as Avenella flexuosa and Calamagrostis villosa, on the natural regeneration of Norway spruce. Starting from the conditions at the sites before the recovery period, the case simulation studies are able to project the short-term succession for a regeneration decade and the approximate long-term development. In addition to the standard simulation procedures based on solution of ordinary differential equations, spatio-temporal modelling in the GIS environment is able to provide spatial data management, analysis and visualization of the data.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

Using classification trees to analyze the impact of exotic species on the ecological assessment of polder lakes in Flanders, Belgium

Polder lakes in Flanders are stagnant waters that were flooded by the sea in the past. Several of these systems are colonized by exotic species, but have hardly been studied until present. The aim of the present study was: (1) to assess the influence of exotic macrobenthic species on the outcome of the Multimetric Macroinvertebrate Index Flanders (MMIF) and (2) to use classification trees for evaluating to what extent physical-chemical characteristics affect the presence of exotic species.In total, 27 mollusc and 10 macro-crustacean species were present in the monitored lakes of which respectively five and four were exotic. The exclusion of the exotic species from the MMIF resulted in a significant decline of this ecological index (−0.03 ± 0.04; p = 0.00). This elimination often resulted into a lower ecological water quality class and more samples were classified into the bad and poor ecological water quality classes.Single-target classification trees for Gammarus tigrinus and Potamopyrgus antipodarum were constructed, relating environmental parameters and ecological status (MMIF) to the occurrence of both exotic invasive species. The major advantages of using single-target classification trees are the transparency of the rule sets and the possibility to use relatively small datasets. However, this classification technique only predicts a single-target attribute and the trees of the different species are often hard to integrate and use for water managers. As a solution, a multi-target approach was used in the present study. Exotic molluscs and crustaceans communities were modelled based on environmental parameters and the ecological status (MMIF) using multi-target classification trees. Multi-target classification trees can be used in management planning and investment decisions as they can lead to integrated decisions for the whole set of exotic species and avoid the construction of many models for each individual species. These trees provide general insights concerning the occurrence patterns of individual crustaceans and molluscs in an integrated way.     

Interpreting spatial heterogeneity of crop yield with a process model and remote sensing

A process-based crop growth model (Vegetation Interface Processes (VIP) model) is used to estimate crop yield with remote sensing over the North China Plain. Spatial pattern of the key parameter—maximum catalytic capacity of Rubisco (V_cmax) for assimilation is retrieved from Normalized Difference of Vegetation Index (NDVI) from Terra-MODIS and statistical yield records. The regional simulation shows that the agreements between the simulated winter wheat yields and census data at county-level are quite well with R² being 0.41-0.50 during 2001-2005. Spatial variability of photosynthetic capacity and yield in irrigated regions depend greatly on nitrogen input. Due to the heavy soil salinity, the photosynthetic capacity and yield in coastal region is less than 50 μmol C m⁻² s⁻¹ and 3000 kg ha⁻¹, respectively, which are much lower than that in non-salinized region, 84.5 μmol C m⁻² s⁻¹ and 5700 kg ha⁻¹. The predicted yield for irrigated wheat ranges from 4000 to 7800 kg ha⁻¹, which is significantly larger than that of rainfed, 1500-3000 kg ha⁻¹. According to the path coefficient analysis, nitrogen significantly affects yield, by which water exerts noticeably indirect influences on yield. The effect of water on yield is regulated, to a certain extent, by crop photosynthetic capacity and nitrogen application. It is believed that photosynthetic parameters retrieved from remote sensing are reliable for regional production prediction with a process-based model.     

Light regime in an Arctic fjord: a study related to stratospheric ozone depletion as a basis for determination of UV effects on algal growth

Solar radiation as a primary abiotic factor affecting productivity of seaweeds was monitored in the Arctic Kongsfjord on Spitsbergen from 1996 to 1998. The radiation was measured in air and underwater, with special emphasis on the UV-B (ultraviolet B, 280–320 nm) radiation, which may increase under conditions of stratospheric ozone depletion. The recorded irradiances were related to ozone concentrations measured concurrently in the atmosphere above the Kongsfjord with a balloon-carried ozone probe and by TOMS satellite. For comparison, an ozone index (a spectroradiometrically determined irradiance of a wavelength dependent on ozone concentration, standardized to a non-affected wavelength) was used to indicate the total ozone concentration present in the atmosphere. Weather conditions and, hence, solar irradiance measured at ground level were seldom stable throughout the study. UV-B irradiation was clearly dependent on the actual ozone concentration in the atmosphere with a maximal fluence rate of downward irradiance of 0.27 W m⁻² on the ground and a maximal daily fluence (radiation exposure) of 23.3 kJ m⁻². To characterize the water body, the light transmittance, temperature and salinity were monitored at two different locations: (1) at a sheltered shallow-water bay and (2) at a wave-exposed, deep-water location within the Kongsfjord. During the clearest water conditions in spring, the vertical attenuation coefficient (K _d) for photosynthetically active radiation (PAR) was 0.12 m⁻¹ and for UV-B 0.34 m⁻¹. In spring, coinciding with low temperatures and clear water conditions, the harmful UV radiation penetrated deeply into the water column and the threshold irradiance negatively affecting primary plant productivity was still found at about 5–6 m depth. The water body in spring was characterized as a Jerlov coastal water type 1. With increasing temperature in summer, snow layers and glacier ice melted, resulting in a high discharge of turbid fresh water into the fjord. This caused a stratification in the optical features, the salinity and temperature of the water body. During melt-water input, a turbid freshwater layer was formed above the more dense sea water. Under these conditions, light attenuation was stronger than defined for a Jerlov coastal water type 9. Solar radiation was strongly attenuated in the first few metres of the water column. Consequently, organisms in deeper water are protected against harmful UV-B radiation. In the surface water, turbidity decreased when rising tide caused an advection of clearer oceanic water. In the course of the summer season, salinity continuously decreased and water temperature increased particularly in shallow water regions. The impact of global climate change on the radiation conditions under water and its effects on primary production of seaweeds are discussed, since organisms in the eulittoral and upper sublittoral zones are affected by UV radiation throughout the polar day. In clearer water conditions during spring, this may also apply to organisms inhabiting greater depths. Received: 20 June 2000 / Accepted: 17 October 2000     

Modeling and coupling of soil respiration and soil water content in fenced Leymus chinensis steppe,Inner Mongolia

Soil respiration was measured with the enclosed chamber method during 2 years in fenced Leymus chinensis steppe, Inner Mongolia, China. Soil water content at 0–10 cm depth was a major limited factor of soil respiration in semi-arid grassland, accounting for 76.4% of the variation. The temperature-dependent exponential function could only explain 38.7% of the variation in soil respiration. With 246 data over the entire experimental period, multiple linear stepwise regressions of soil respiration rate were analyzed with the influencing factors, including soil water content at 0–10 cm depth, air temperature, air pressure, air humidity, total radiation and their interactions. With soil water content at 0–10 cm depth (W) and air temperature (T_h) as combined factors, the twice linear regression (F = 1.68WT_h − 109.09) was simple and its coefficients were significant, accounting for 83.1% of the variation in soil respiration. Due to the lack of long-term and continuous soil water content, a water sub-model based on precipitation and evapotranspiration was introduced, which could provide better fits with the measured values (R² = 0.813). The magnitudes of soil respiration calculated from the twice linear regression equation and water sub-model were 439.58 and 463.06 g CO₂ m⁻² in 2001 (19 June–23 September) and in 2002 (1 June–24 September), respectively. The mean hourly soil respiration rates were in the range of the previous studies in the adjacent region and the world's major temperate grasslands.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Carbon, nitrogen, oxygen and sulfide budgets in the Black Sea: A biogeochemical model of the whole water column coupling the oxic and anoxic parts

Carbon, nitrogen, oxygen and sulfide budgets are derived for the Black Sea water column from a coupled physical-biogeochemical model. The model is applied in the deep part of the sea and simulates processes over the whole water column including the anoxic layer that extends from ?115 m to the bottom (?2000 m). The biogeochemical model involves a refined representation of the Black Sea foodweb from bacteria to gelatinous carnivores. It includes notably a series of biogeochemical processes typical for oxygen deficient conditions with, for instance, bacterial respiration using different types of oxidants (i.e denitrification, sulfate reduction), the lower efficiency of detritus degradation, the ANAMMOX (ANaerobic AMMonium OXidation) process and the occurrence of particular redox reactions. The model has been calibrated and validated against all available data gathered in the Black Sea TU Ocean Base and this exercise is described in Gregoire et al. (2008). In the present paper, we focus on the biogeochemical flows produced by the model and we compare model estimations with the measurements performed during the R.V. KNORR expedition conducted in the Black Sea from April to July 1988 (Murray and the Black Sea Knorr Expedition, 1991). Model estimations of hydrogen sulfide oxidation, metal sulfide precipitation, hydrogen sulfide formation in the sediments and water column, export flux to the anoxic layer and to the sediments, denitrification, primary and bacterial production are in the range of field observations.With a simulated Gross Primary Production (GPP) of 7.9 mol C m⁻² year⁻¹ and a Community Respiration (CR) of 6.3 mol C m⁻² year⁻¹, the system is net autotrophic with a Net Community Production (NCP) of 1.6 mol C m⁻² year⁻¹. This NCP corresponds to 20% of the GPP and is exported to the anoxic layer. In order to model Particulate Organic Matter (POM) fluxes to the bottom and hydrogen sulfide profiles in agreement with in situ observations, we have to consider that the degradation of POM in anoxic conditions is less efficient that in oxygenated waters as it has often been observed (see discussion in Hedges et al., 1999). The vertical POM profile produced by the model can be fitted to the classic power function describing the oceanic carbon rate (C_R=Z^−α) using an attenuation coefficient α of 0.36 which is the value proposed for another anoxic environment (i.e. the Mexico Margin) by Devol and Hartnett (2001). Due to the lower efficiency of detritus degradation in anoxic conditions and to the aggregation of particles that enhanced the sinking, an important part of the export to the anoxic layer (i.e. 33%, 0.52 mol C m⁻² year⁻¹) escapes remineralization in the water column and reaches the sediments. Therefore, sediments are active sites of sulfide production contributing to 26% of the total sulfide production.In the upper layer, the oxygen dynamics is mainly governed by photosynthesis and respiration processes as well as by air-sea exchanges. ?71% of the oxygen produced by phytoplankton (photosynthesis+nitrate reduction) is lost through respiration, ?21% by outgasing to the atmosphere, ?5% through nitrification and only ?2% in the oxidation of reduced components (e.g. Mn²⁺, Fe²⁺, H₂S).The model estimates the amount of nitrogen lost through denitrification at 307 mmol N m⁻² year⁻¹ that can be partitioned into a loss of ?55% through the use of nitrate for the oxidation of detritus in low oxygen conditions, ?40% in the ANAMMOX process and the remaining ?5% in the oxidation of reduced substances by nitrate.In agreement with data analysis performed on long time series collected since the 1960s (Konovalov and Murray, 2001), the sulfide and nitrogen budgets established for the anoxic layer are not balanced in response to the enhanced particle fluxes induced by eutrophication: the NH₄ and H₂S concentrations increase.