On the association between the column ozone and the spectral solar ultraviolet radiation

An estimation of the increase in the daily spectral solar ultraviolet radiation reaching the ground is attempted, by using the daily total ozone observations made by the Total Ozone Mapping Spectrometer (TOMS) flown on the satellite Nimbus‐7 during 1978–1992. This investigation has been performed for the high latitudes by employing a recently proposed parametric model for the estimation of the spectral solar ultraviolet radiation at the earth's surface considering the total ozone content and various meteorological parameters.     

1961-2007年期间南宁紫外线辐射的变化趋势及其与皮肤癌发病相关分析

采用2002年9月至2005年10月逐日太阳总辐射、云量、太阳天顶角、臭氧、水汽压、空气污染物和紫外线辐射资料,建立了基于气象要素推算紫外线曝辐量的模型;采用该模型重建1961-2007逐日紫外线曝辐量资料,从年、春、夏、秋、冬不同尺度分析重建序列的特征;采用1991-2003年皮肤癌发病人数资料,分析紫外线曝辐量与各类皮肤癌发病人数相关性;对未来紫外线变化进行展望。主要结论有:1961-2007年,南宁紫外线曝辐量年平均日值为95.83 W.h/m2;绝对变率以夏季最大,相对变率以冬季最大,秋季绝对变率和相对变率均最小;年平均和春、夏、秋季紫外线曝辐量有微弱的下降趋势,冬季下降趋势明显;突变主要发生在1970 s中后期至1980 s初期和1990 s初期;年和各季最显著的周期是准7年,夏季还有明显的11年周期;1991-2003年鳞状细胞癌发病人数与紫外线曝辐量相关显著;基底细胞癌、鳞状细胞癌、恶性黑色瘤3种皮肤癌均好发于高紫外线辐射时间;展望2050年以前紫外线变化情况,认为:偏高年份可能在2017、2031、2045年附近,偏低年份可能在2010、2024、2038年附近。     

Impact of generated solar radiation on simulated crop growth and yield

The availability of observed daily solar radiation (OSR) is restricted to recent years. Its estimation through different methods is necessary to develop long-term data sets for agricultural and environmental applications. The objective of this study was to analyze the impact of using generated daily solar radiation (GSR) on simulated growth and yield of cotton, maize, and peanut. Nine locations representing Georgia's major crop belt were selected. Daily weather data from the Georgia Automated Environmental Monitoring Network (AEMN), including solar radiation, maximum and minimum temperature, and precipitation, were duplicated. The OSR was removed from one set and then generated using a stochastic procedure. The Cropping System Models (CSM)-CROPGRO-Cotton, CERES-Maize, and CROPGRO-Peanut of the Decision Support System for Agrotechnology Transfer (DSSAT) v4 were used to simulate crop growth and yield at each location with both OSR and GSR and for rainfed and irrigated conditions. The statistical analysis included summary statistics, Pearson's coefficient of correlation, mean squared deviation (MSD) and its components, namely: squared bias (SB), squared difference between standard deviations (SDSD), lack of correlation weighted by the standard deviations (LCS), and regressions. Within locations, for the three crops under rainfed and irrigated conditions, GSR did not significantly affect simulated total evapotranspiration and aboveground biomass and yields. For the three crops, deviations of simulated water use and yields from GSR with respect to simulated water use and yields from OSR were lower for the rainfed than for the irrigated conditions. Yields from the CSM-CROPGRO-Cotton and -Peanut models had lower deviations than yields from the CSM-CERES-Maize model. LCS was the major component of the MSD suggesting that the extent of the difference between standard deviations of GSR and OSRG could affect the outputs of the crop models. Nevertheless, for most locations none of the MSD components of the GSR showed significant correlation with simulated yields and the overall performance of the models was not affected. It can be concluded based on the results of this study that GSR can be used as an input for crop model simulation models when OSR is not available.     

Significance tables for the exact variance test for the Poisson distribution with alternative underdispersion

Fisher (1950) introduced the variance or dispersion index test statistic to test deviations of the Poisson distribution. For this test approximate critical values exist for large sample sizes. If the number of observations is small this approximation can lead to a wrong conclusion. For small samples, the exact critical values can only be derived by enumeration of all possibilities. Tables of critical values for overdispersion already exist (e.g., Rao and Chakravarti, 1956) However, in many biological situations underdispersion, a more-regular-than-Poisson distribution, is a common phenomenon. Therefore, we have tabulated in this paper the one-tailed critical values for a small number of observations under the null hypothesis (H₀) that the random variable is Poisson distributed against the alternative hypothesis of underdispersion. With the help of this table, the hypothesis that the observations in a data set are Poisson distributed, can be tested easily with the variance test. The tables are illustrated with examples from the literature and some observations from our own research. In general, the ² approximation gives a smaller significance level than the exact variance test.     

Modification of a stream temperature model with Beer's law and application to GaoShan Creek in Taiwan

A physics-based stream temperature model [Tung, C.P., Lee, T.Y., Yang, Y.C., 2006. Modelling climate-change impacts on stream temperature of Formosan Landlocked Salmon habitat. Hydrol. Process. 20, 1629–1649] was improved by incorporating shading effects caused by both cliff terrain and riverbank dense vegetation to simulate hourly stream temperature variations in 1 day. Daily maximal stream temperature is a critical factor to the habit distribution of the Formosan Landlocked Salmon, an important and endangered species. Currently, it only can be found in ChiChiaWan Creek and GaoShan Creek in Taiwan. The former stream temperature model only considers the shading effects of cliff terrain and works well for ChiChiaWan Creek, but overestimates stream temperatures of GaoShan Creek having dense riverbank vegetative covers. The model was modified with the Beer's law and a parameterization scheme to describe the diminishing of the incident solar radiation to take vegetative shading effects into account. Simulation results of GaoShan Creek show the success of this improvement. The shading effects induced by both terrain and vegetation can significantly affect stream temperature distributions. Simulation experiments were conducted to indicate shading effects are varied in different watersheds and seasons.     

Damage to grass shrimp (Palaemonetes pugio) embryo DNA by summer sunlight followed by DNA repair in the dark

 DNA strand damage, using the single-cell gel electrophoresis (comet) method, was determined in different-stage embryos of grass shrimp (Palaemonetes pugio) collected from surface waters of a local estuary near Savannah, Georgia, USA. Late-stage embryos collected from the estuarine river at midday in the summer or placed in a solar simulator showed extensive DNA strand damage. The solar simulator, which produced the total irradiance found at midday in the summer at 34°N caused DNA strand damage in embryos similar to that found in sunlight-exposed embryos. A large increase in cyclobutane pyrimidine dimers (18 cyclobutane pyrimidine dimers per 1000 kilobases) were detected in DNA from the late-stage embryos exposed to the solar simulator for 1 h (solar irradiance of 126 μW cm⁻²). DNA repair took place within a few hours when late-stage embryos collected at midday from the river were transferred to the dark. Early grass-shrimp embryo stages showed no DNA strand damage either after placement in the solar simulator or when collected at midday in the summer. This lack of solar-damaged DNA in early-stage embryos was probably due to the presence of high concentrations of carotenoids, which can act as anti-oxidants to prevent damage from activated oxygen species produced by cells exposed to ultraviolet light. These carotenoids are utilized by the developing embryos, and only low concentrations of carotenoids were present in late embryo stages. Received: 24 May 1999 / Accepted: 11 May 2000     

Relation between primary production and irradiance

The irradiant energy values in the Saronicos Gulf (Aegean Sea) for the period December 1963 to March 1964 were computed from the solar irradiance values measured at the Observatory of Athens. The computation was based on the energy curves presented by Jerlov and the type of water as determined from measurements of transmission. The results of the computations were related to the values of primary production in the Gulf on the same dates and strong correlation was observed. The relation found was compared with the theoretical relation of Steele and satisfactory agreement was found.     

Dynamics of surface albedo of a boreal forest and its simulation

Surface albedo determines the distribution of solar radiation between the earth's surface and the atmosphere. It affects the global climate directly by altering surface energy balance, and indirectly by controlling ecosystem processes and greenhouse gas exchange. In this study, a land surface albedo model was constructed based on the gap probability approach for ray tracing and the basic optical parameters of ecosystem elements. The model was applied to a boreal deciduous forest and results were compared with field measurements. Results show that seasonal and diurnal albedo dynamics were well simulated by the model. The standard deviation between the simulated and measured reflected radiation was 2.5–5.0 W m⁻² in different seasons. The model also provided an insight into the relationships between surface albedo and radiation components (direct versus diffuse), solar zenith angle, and different wave bands. Model sensitivity analyses show that the surface albedo in winter is very sensitive to the forest wood area index for this boreal aspen forest, suggesting that accurate estimates of wood area index are necessary to improve the accuracy of surface albedo simulation in leafless seasons.     

Modeling the annual thermal regime of lake Ohrid,Yugoslavia, using daily weather data

The time-dependent characteristics of the five weather variables which control the annual thermal response of Lake Ohrid are analyzed in detail. These are daily values for solar radiation, air temperature, humidity, wind speed and cloud cover. A simple numerical model of the lake's thermal response, forced by thermally driven density mixing, is developed and tested using observed thermal profiles for verification. The numerical model successfully reproduces the major features of the lake's thermal regime over a 6 y period from 1972 to 1977, the average root mean square value for the simulated profiles being 1.2°C with extremes of 2.2 and 0.3°C and a standard deviation of 0.4°C.     

Identification and ecotoxicity assessment of intermediates generated during the degradation of clofibric acid by advanced oxidation processes

The aim of this study was to identify the intermediates in clofibric acid degradation under various advanced oxidation processes, namely ultraviolet (UV), UV/H₂O₂, vacuum ultraviolet (VUV), VUV/H₂O₂, and solar/TiO₂ processes, as well as to assess the toxicity of these intermediates. Eleven intermediates have been detected by gas chromatography-mass spectrometer, most of which were reported for the first time to our best knowledge. Combining the evolution of the dissolved organic carbon, Cl^- and specific ultraviolet absorption at 254 nm, it could be deduced that cleavage of aromatic ring followed by dechlorination was the mechanism in solar/TiO₂ process, while dechlorination happened first and accumulation of aromatic intermediates occurred in the other processes. Different transformation pathways were proposed for UV-, VUV-assisted and solar/TiO₂ processes, respectively. The acute toxicity was evaluated by means of Photobacterium phosphoreum T₃ spp. bioassay. It was believed that aromatic intermediates increased the toxicity and the ring-opening pathway in solar/TiO₂ process could relieve the toxicity.     

Best linear unbiased estimators for the simple linear regression model using ranked set sampling

When sample observations are expensive or difficult to obtain, ranked set sampling is known to be an efficient method for estimating the population mean, and in particular to improve on the sample mean estimator. Using best linear unbiased estimators, this paper considers the simple linear regression model with replicated observations. Use of a form of ranked set sampling is shown to be markedly more efficient for normal data when compared with the traditional simple linear regression estimators.     

Applying artificial neural network methodology to ocean color remote sensing

Artificial neural networks (ANN) are widely used as continuous models to fit non-linear transfer functions. In this study we used ANN to retrieve chlorophyll pigments in the near-surface of oceans from Ocean Color measurements. This bio-optical inversion is established by analyzing concomitant sun-light spectral reflectances over the ocean surface and pigment concentration. The relationships are complex, non-linear, and their biological nature implies a significant variability. Moreover, the sun-light reflectances are usually measured by satellite radiometers flying at 800 km over the ocean surface, which affect the data by adding radiometric noise and atmospheric correction errors. By comparison with the polynomial fit usually employed to treat this problem, we show the advantages of neural function approximation like the association of non-linear complexity and noise filtering.     

A non-negative and high-resolution finite volume method for the depth-integrated solute transport equation using an unstructured triangular mesh

This paper proposes a new high-resolution finite volume method for solving the two-dimensional (2D) solute transport equation using an unstructured mesh. A new simple r-factor algorithm is introduced into the Total Variation Diminishing flux limiter to achieve a more efficient yet accurate high-resolution scheme for solving the advection term. To avoid the physically-meaningless negative solutions resulted from using the Green–Gauss theorem, a nonlinear two-point flux approximation scheme is adopted to deal with the anisotropic diffusion term. The developed method can be readily coupled with a two-dimensional finite-volume-based flow models under unstructured triangular mesh. By integrating with the ELCIRC flow model, the proposed method was verified using three idealized benchmark cases (i.e., advection of a circle-shaped solute field, advection in a cyclogenesis flow field and transport of a initially square-shaped solute plume), and further applied to simulate the non-reactive solute transport process driven by irregular tides in the Deep Bay, eastern Pearl River Estuary of China. These cases are also simulated by models using other existing methods, including different r-factor for advection term and the Green–Gauss theorem for diffusion term. The comparison between the results from the new method and those from other existing methods demonstrated the new method could describe advection induced concentration shock and discontinuities, and anisotropic diffusion at high resolution without providing spurious oscillations and negative values.     

Analysis of a two-layer cloud system with RAMS model and comparison to airborne observations

A three-dimensional numerical model (Regional Atmospheric Modeling System—-RAMS) was used to study the formation and evolution of water forms in a two-layer cloud structure observed during a field campaign over Brest (France). The model performance in regular operations, using conventional meteorological data as initial and lateral boundary conditions, was also examined. Remote sensing observations of the cloud system and in-situ aircraft data, selected during the campaign, were used to validate the model outputs. The model simulations showed that the lower cloud formation was characterized by high number concentration of pristine ice and snow, while the concentration of aggregates, graupel and hail were considerably lower. Hydrometeors in liquid phase appeared demonstrating high number concentration and water content on the top of this layer. The upper cloud layer consisted only of frozen water substances in lower amounts. The qualitative and quantitative comparison of the model-calculated meteorological and microphysical fields to the available observational data revealed that the model reflected fairly well the cloud structure (e.g., the spatio-temporal variability of the cloud parameters, the geometry of the cloud system). However, there were deviations as far as the model underestimating the ice water content (IWC) and number concentration (N_t) fields is concerned, especially at the atmospheric layer between 2.5 and 4 km of altitude. These deviations of the model simulated quantities from the measured ones may be attributed either to the performance of the model’s microphysics scheme, to instrument inaccuracies and to the local disturbance caused by the aircraft.     

A neural network experiment on the simulation of daily nitrate-nitrogen and suspended sediment fluxes from a small agricultural catchment

In this paper, we report an application of neural networks to simulate daily nitrate-nitrogen and suspended sediment fluxes from a small 7.1 km² agricultural catchment (Melarchez), 70 km east of Paris, France. Nitrate-nitrogen and sediment losses are only a few possible consequences of soil erosion and biochemical applications associated to human activities such as intensive agriculture. Stacked multilayer perceptrons models (MLPs) like the ones explored here are based on commonly available inputs and yet are reasonably accurate considering their simplicity and ease of implementation. Note that the simulation does not resort on water quality flux observations at previous time steps as model inputs, which would be appropriate, for example, to predict the water chemistry of a drinking water plant a few time steps ahead. The water quality fluxes are strictly mapped to historical mean flux values and to hydro-climatic variables such as stream flow, rainfall, and soil moisture index (12 model input candidates in total), allowing its usage even when no flux observations are available. Self-organizing feature maps based on the network structure established by Kohonen were employed first to produce the training and the testing data sets, with the intent to produce statistically close subsets so that any difference in model performance between validation and testing has to be associated to the model and not to the data subsets. The stacked MLPs reached different levels of performance simulating the nitrate-nitrogen flux and the suspended sediment flux. In the first instance, 2-input stacked MLP nitrate-nitrogen simulations, based on the same-day stream flow and on the 80-cm soil moisture index, have a performance of almost 90% according to the efficiency index. On the other hand, the performance of 3-input stacked MLPs (same-day stream flow, same-day historical flux, and same-day stream flow increment) reached a little more than 75% according to the same criterion. The results presented here are deemed already promising enough, and should encourage water resources managers to implement simple models whenever appropriate.     

Obtaining species: sample size considerations

Suppose fish are to be sampled from a stream. A fisheries biologist might ask one of the following three questions: ‘How many fish do I need to catch in order to see all of the species?’, ‘How many fish do I need to catch in order to see all species whose relative frequency is more than 5%?’, or ‘How many fish do I need to catch in order to see a member from each of the species A, B, and C?’. This paper offers a practical solution to such questions by setting a target sample size designed to achieve desired results with known probability. We present three sample size methods, one we call ‘exact’ and the others approximate. Each method is derived under assumed multinomial sampling, and requires (at least approximate) independence of draws and (usually) a large population. The minimum information needed to compute one of the approximate methods is the estimated relative frequency of the rarest species of interest. Total number of species is not needed. Choice of a sample size method depends largely on available computer resources. One approximation (called the ‘Monte Carlo approximation’) gets within ±6 units of exact sample size, but usually requires 20–30 minutes of computer time to compute. The second approximation (called the ‘ratio approximation’) can be computed manually and has relative error under 5% when all species are desired, but can be as much as 50% or more too high when exact sample size is small. Statistically, this problem is an application of the ‘sequential occupancy problem’. Three examples are given which illustrate the calculations so that a reader not interested in technical details can apply our results.     

Spatial patterns of forest characteristics in the western United States derived from inventories.

In the western United States, forest ecosystems are subject to a variety of forcing mechanisms that drive dynamics, including climate change, land-use/land-cover change, atmospheric pollution, and disturbance. To understand the impacts of these stressors, it is crucial to develop assessments of forest properties to establish baselines, determine the extent of changes, and provide information to ecosystem modeling activities. Here we report on spatial patterns of characteristics of forest ecosystems in the western United States, including area, stand age, forest type, and carbon stocks, and comparisons of these patterns with those from satellite imagery and simulation models. The USDA Forest Service collected ground-based measurements of tree and plot information in recent decades as part of nationwide forest inventories. Using these measurements together with a methodology for estimating carbon stocks for each tree measured, we mapped county-level patterns across the western United States. Because forest ecosystem properties are often significantly different between hardwood and softwood species, we describe patterns of each. The stand age distribution peaked at 60-100 years across the region, with hardwoods typically younger than softwoods. Forest carbon density was highest along the coast region of northern California, Oregon, and Washington and lowest in the arid regions of the Southwest and along the edge of the Great Plains. These results quantify the spatial variability of forest characteristics important for understanding large-scale ecosystem processes and their controlling mechanisms. To illustrate other uses of the inventory-derived forest characteristics, we compared them against examples of independently derived estimates. Forest cover compared well with satellite-derived values when only productive stands were included in the inventory estimates. Forest types derived from satellite observations were similar to our inventory results, though the inventory database suggested more heterogeneity. Carbon stocks from the Century model were in good agreement with inventory results except in the Pacific Northwest and part of the Sierra Nevada, where it appears that harvesting and fire in the 20th century (processes not included in the model runs) reduced measured stand ages and carbon stocks compared to simulations.     

Graviperception and motility of three Prorocentrum strains impaired by solar and artificial ultraviolet radiation

The effects of solar and artificial ultraviolet radiation on the motility and graviorientation of three strains of the dinoflagellate Prorocentrum were studied. P. micans isolated from the Baltic Sea shows a pronounced negative gravitaxis which switches to a positive one even after short exposure times to either solar or artificial UV irradiation. In constrast P. minimum strains isolated from the Kattegat and the Atlantic coast off Portugal showed only a weak upward orientation. In all three strains the linear swimming velocity decreases after short exposure times and, in addition, the percentage of motile cells in the populations drastically decreases. Removing the ultraviolet component of solar radiation with a cut-off filter prolongs the tolerated exposure times.     

Invisible Losses and the Logics of Resettlement Compensation

The necessity of compensating people negatively affected by conservation and other development projects has been widely acknowledged. It is less widely acknowledged that because conventional compensation assessments focus on material resources and their economic equivalents, many important losses incurred by resettlers are invisible to project authorities. Through ethnographic observations and interviews, we documented losses identified by people facing resettlement from Mozambique's Limpopo National Park. We also examined resettlement planning documents to determine why decision makers’ assessments of natural resource use and value neglect losses residents identified as critical. Identifying, preventing, and mitigating invisible losses in resettlement planning necessitates a better understanding of intangible benefits residents derive from resources, which are often as or more important than their readily apparent material properties. These benefits include but are not limited to decision‐making authority linked to owning land versus having the use of fields; ancestral identity and social belonging linked to gravesites; the importance of tree roots that provide a powerful sense of security because they suppress hunger in periods of scarcity; and the importance of people's location within social networks and hierarchies as they determine the benefits versus risks that will be incurred through resettlement. Pérdidas Invisibles y la Lógica de la Compensación de Repoblación