Spatial distribution of main forest soil groups in Croatia as a function of basic pedogenetic factors

The model of spatial distribution of main forest soil groups in Croatia was developed as a function of basic pedogenetic factors: lithological substratum, macroclimate and relief. Used data about soil group, lithological substratum, terrain slope and aspect were collected on 1881 soil profiles. Macroclimatic data were estimated for each soil profile by spatial interpolation between meteorological stations. Feedforward neural networks were used as modelling tool. The final model has total classification correctness of 63.5% for training data set and 62.3% for independent test data set. The best result (86.4%) was achieved for fluvisols which are strongly spatially correlated with alluvial sediment in a flood plains. The worst result was achieved for luvisol (14.2%) which mainly comprised very old soils, probably developed under pedogenetic factors different from actual. The model was applied on entire Croatian territory aiming at construction of potential spatial distribution of main forest soils (without human impact), which was compared by the potential spatial distribution of major forest types modelled independently.     

Integrated biogeochemical modelling of nitrogen load from anthropogenic and natural sources in Japan

This study proposed an integrated biogeochemical modelling of nitrogen loads from anthropogenic and natural sources in Japan. Firstly, the nitrogen load (NL) from different sources such as crop, livestock, industrial plant, urban and rural resident was calculated by using datasets of fertilizer utilization, population distribution, land use map, and social census. Then, the nitrate leaching from soil layers in farmland, grassland and natural conditions was calculated by using a terrestrial nitrogen cycle model (TNCM). The Total Runoff Integrating Pathways (TRIP) was used to transport nitrogen from natural and anthropogenic sources through river channels, as well as collect and route nitrogen to the river mouths. The forcing meteorological and hydrological data is a 30-year (1976–2005) dataset for Japan which were obtained by the land surface model, Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO). For the model validation, we collected total nitrogen (TN) concentration data from 59 rivers in Japan. As a comparison result, calculated TN concentration values were in good agreement with the observed ones, which shows the reliability of the proposed model. Finally, the TN loads from point and nonpoint sources were summarized and evaluated for 59 river basins in Japan. The proposed modelling framework can be used as a tool for quantitative evaluation of nitrogen load in terrestrial ecosystems at a national scale. The connection to land use and climate data provides a possibility to use this model for analysis of climate change and land use change impacts on hydrology and water quality.     

Gridded meteorological data as a resource for mechanistic macroecology in coastal environments

Gridded weather data were evaluated as sources of forcing variables for biophysical models of intertidal animal body temperature with model results obtained using local weather station data serving as the baseline of comparison. The objective of the study was to determine which gridded data are sufficient to capture observed patterns of thermal stress. Three coastal sites in western North America were included in this analysis: Boiler Bay, Oregon; Bodega Bay, California; and Pacific Grove, California. The gridded data with the highest spatial resolution, the 32-km North American Regional Reanalysis (NARR) and the 38-km Climate Forecasting System Reanalysis (CFSR), predicted daily maximum intertidal animal temperature most similarly to the local weather Station data. Time step size was important for variables that change rapidly throughout the day, such as solar radiation. There were site-based differences in the ability of the model to predict daily maximum intertidal animal temperature, with the gridded data predictions being the closest to local weather station predictions in Boiler Bay, Oregon. In a review of gridded data used as part of ecological studies, there was broad use of the data across subject areas and ecosystems so the recent improvements in the spatial (from 2 degrees to 32 km) and temporal scales (from 6 hours to 1 hour) of gridded data will further add to the applicability within the ecological community particularly for mechanistic studies.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.     

Metabolic rates of epipelagic marine copepods as a function of body mass and temperature

Metabolic rates (oxygen consumption, ammonia excretion, phosphate excretion) have been calculated as a function of body mass (dry, carbon, nitrogen and phosphorus weights) and habitat temperature, using multiple regression. The metabolic data used for this analysis were species structured, collected from Arctic to Antarctic seas (temperature range: -1.7°C to 29.0°C). The data were further divided into geographical and/or seasonal groups (35 species and 43 data sets for oxygen consumption; 38 species and 58 data sets for ammonia excretion; 22 species and 31 data sets for phosphate excretion). The results revealed that the variance attributed to body mass and temperature was highest (93-96%) for oxygen consumption rates, followed by ammonia excretion rates (74-80%) and phosphate excretion rates (46-56%). Among the various body mass units, the best correlation was provided by the nitrogen unit, followed by the dry weight unit. The calculated Q₁₀ values varied slightly according to the choice of body mass units; overall ranges were 1.8-2.1 for oxygen consumption rates, 1.8-2.0 for ammonia excretion rates and 1.6-1.9 for phosphate excretion rates. The effects of body mass and temperature on the metabolic quotients (O:N, N:P, O:P) were insignificant in most cases. Although the copepod metabolic data used in the present analysis were for adult and pre-adult stages, possible applications of the resultant regression equations to predict the metabolic rates of naupliar and early copepodite stages are discussed. Finally, global patterns of net growth efficiency [growth (growth+metabolism)^-1] of copepods were deduced by combining the present metabolic equation with Hirst and Lampitt's global growth equation for epipelagic marine copepods.     

Settlement of the wreckfish (<Emphasis Type="Italic">Polyprion</Emphasis><Emphasis Type="Italic">americanus</Emphasis>)

The wreckfish (Polyprion americanus) is a panoceanic, long-lived, deep-water demersal species, characterized by an extended pelagic juvenile phase associated with floating objects. In the present study morphometric data from 435 specimens collected from Greece (Crete), Italy (Ionian Sea) and the Atlantic coast of France from September 1999 to March 2001 were analyzed to estimate the settlement size of the species and associated changes in morphology. The fishery sample included specimens from both the pelagic and the demersal stage. Length-at-settlement (TL₅₀) and 95% confidence intervals were estimated by fitting a logistic function. Eleven morphometric characters were analyzed, and the existing inflection points, reflecting alterations in body shape, were defined: (1) iteratively, as the transition point, splitting the data set into two groups, for which the reduced major axis functions, between a character and total length, of the successive groups best fit (minimum sum of squares of residuals) the combined data set and (2) where the second derivative of the fitted third-order polynomial functions to morphometric ratios equaled zero. The main size range within which wreckfish settled was 56-65 cm, and the means of the inflection points defined by the two methods were 61 and 64 cm. These results indicate changes in functional morphology associated with settlement. The monitoring of wreckfish juveniles caught in the wild and kept individually in captivity showed changes in growth and food intake at approximately the estimated settlement length and suggested that temperature was the most likely factor triggering settlement.     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

基于本土物种的3种典型化合物急性生态效应阈值研究

预测无效应浓度(PNEC)是进行风险污染物水生态安全管理的重要依据。本研究进行了3种典型化合物五氯酚、硝基苯和氯化镉对10种我国不同营养级水生生物的24 h、48 h和96 h的急性毒性测试,根据实验结果计算了相应的急性PNEC,同时与根据美国环境保护局毒性数据库里的毒性数据计算获得的急性PNEC值,以及综合本实验结果与毒性数据库里的数据计算得到的急性PNEC值进行对比,发现通过3种数据来源获得的急性PNEC值中,硝基苯的PNEC值差异较大,由本次实验结果获得的急性PNEC值最小;其他2种化合物差异较小。这可能是由于本次实验所选的本土生物中华田螺和麦穗鱼对硝基苯比较敏感,并且数据库中硝基苯的急性致死数据较少、毒性值较大且变化范围较窄,而其他2种化合物数据量较为丰富,变化范围较宽,包括了较敏感物种的毒性数据。这表明为给我国水生生物提供一个安全可靠的保护,对于数据量较为丰富并且毒性值变化较宽的化合物(如五氯酚和氯化镉)可以直接根据数据库里的毒性数据进行PNEC值的计算;而对于毒性数据量较少、毒性值偏大且变化较窄的化合物(如硝基苯)需要进行本土敏感物种的毒性测试。     

Physical factors controlling abundance of meiofauna on tidal and atidal beaches

Quantitative samples of interstitial sand beach meiofauna were collected from Morocco along the North African coast (Algeria and Tunisia) and northwards to Lebanon, Turkey and Cyprus. Data on the sediment median diameter, sorting coefficient and beach temperature were used to construct multiple-regression equations relating these factors to the total meiofaunal numbers. Curvilinear regression was found to give a significantly better fit than linear regression in all cases but one. Treating the whole Mediterranean data, the equation explained 9.3% of the variance in meiofaunal abundance. Within narrower geographical areas, however, the equations explained significantly more of the variance: 56.70% of Moroccan tidal beach data, 75.60% of South Tunisian tidal beach data, and 62.3% of South Tunisian atidal beach data. For the tidal beach equations sorting was the most important factor, followed by temperature and median diameter. It is suggested that the factors controlling meiofaunal abundance on these beaches are likely to be wave, tide and current action which also control sorting. The lack of fit of most atidal beach data suggests that here biological interactions such as competition and predation may control meiofaunal abundance. The detection of beaches affected by pollutants may also be possible using regression techniques. Beaches having a significantly enriched population (sewage-induced) or depleted population (pollutant-induced) can be readily detected.     

Evidence for restricted gene flow over small spatial scales in a marine snapping shrimp <Emphasis Type="Italic">Alpheus angulosus</Emphasis>

Despite the apparent absence of geographic barriers, connectivity among marine populations may be restricted by, for example, ecological or behavioral mechanisms. In such cases, populations may show genetic differentiation even over relatively small spatial scales. Here, mitochondrial sequence data from the cytochrome oxidase I (COI) gene and seven polymorphic microsatellite markers were used to investigate fine geographic scale population genetic structure in the snapping shrimp Alpheus angulosus, a member of the A. armillatus species complex, from collections in Florida, Jamaica, and Puerto Rico carried out from 1999 to 2005. The COI data showed a deep divergence that separated these samples into two mitochondrial clades, but this divergence was not supported by the microsatellite data. The COI data reflect past population divergence not reflected in extant population structure on the whole genome level. The microsatellite data also revealed evidence for moderate population structure between populations as close as ∼10 km, and no evidence for isolation by distance, as divergences between near populations were at least as strong as those between more broadly separated populations. Overall, these data suggest a role for restricted gene flow between populations, though the mechanisms that reduce gene flow in this taxon remain unknown.     

Seasonal changes in biochemical composition of the bivalve Abra alba from the Clyde Sea Area

Seasonal changes in the body weight and composition of Abra alba (W. Wood) from south of the Little Cumbrae in the Clyde Sea Area (UK) were studied during 1969–1971. The composition of a specimen of standard size was calculated for each sampling data to provide information on seasonal changes independent of shell growth. Increase in body weight took place rapidly in early summer as the gonad developed and reserves were built up. Spawning in July resulted in a fall in body weight, and this was followed by a slower fall during the autumn and winter as reserves were utilized. The changes are related to seasonal fluctuations in food availability and temperature, which are reflected in the amount of pigment (phaeophytin) retained in the tissues.     

Data quality assessment for studies investigating microplastics and nanoplastics in food products: Are current data reliable?

● Data quality assessment criteria for MP/NPs in food products were developed. ● Data quality of 71 data records (69 of them only focused on MPs) was assessed. ● About 96% of the data records were considered unreliable in at least one criterion. ● Improvements need to be made regarding positive controls and polymer identification. ● A mismatch between MP/NPs used in toxicity studies and those in foods was recorded. Data on the occurrence of microplastics and nanoplastics (MP/NPs) in foods have been used to assess the human health risk caused by the consumption of MP/NPs. The reliability of the data, however, remains unclear because of the lack of international standards for the analysis of MP/NPs in foods. Therefore, the data quality needs to be assessed for accurate health risk assessment. This study developed 10 criteria applicable to the quality assessment of data on MP/NPs in foods. Accordingly, the reliability of 71 data records (69 of them only focused on MPs) was assessed by assigning a score of 2 (reliable without restrictions), 1 (reliable but with restrictions), or 0 (unreliable) on each criterion. The results showed that only three data records scored 2 or 1 on all criteria, and six data records scored 0 on as many as six criteria. A total of 58 data records did not include information on positive controls, and 12 data records did not conduct the polymer identification, which could result in the overestimation or underestimation of MP/NPs. Our results also indicated that the data quality of unprocessed foods was more reliable than that of processed foods. Furthermore, we proposed a quality assurance and quality control protocol to investigate MP/NPs in foods. Notably, the characteristics of MP/NPs used in toxicological studies and those existing in foods showed a remarkable discrepancy, causing the uncertainty of health risk assessment. Therefore, both the estimated exposure of MP/NPs and the claimed potential health risks should be treated with caution.     

Tiger shark (Galeocerdo cuvier) abundance and growth in a subtropical embayment: evidence from 7 years of standardized fishing effort

The tiger shark (Galeocerdo cuvier Peron and Lesueur 1822) is a widely distributed predator with a broad diet and the potential to affect marine community structure, yet information on local patterns of abundance for this species is lacking. Tiger shark catch data were gathered over 7 years of tag and release research fishing (1991–2000, 2002–2004) in Shark Bay, Western Australia (25°45′S, 113°44′E). Sharks were caught using drumlines deployed in six permanent zones (~3 km² in area). Fishing effort was standardized across days and months, and catch rates on hooks were expressed as the number of sharks caught h⁻¹. A total of 449 individual tiger sharks was captured; 29 were recaptured. Tiger shark catch rate showed seasonal periodicity, being higher during the warm season (Sep–May) than during the cold season (Jun–Aug), and was marked by inter-annual variability. The most striking feature of the catch data was a consistent pattern of slow, continuous variation within each year from a peak during the height of the warm season (February) to a trough in the cold season (July). Annual growth rates of recaptured individuals were generally consistent with estimates from other regions, but exceeded those for populations elsewhere for sharks >275 cm fork length (FL), perhaps because mature sharks in the study area rely heavily on large prey. The data suggest that (1) the threat of predation faced by animals consumed by tiger sharks fluctuates dramatically within and between years, and (2) efforts to monitor large shark abundance should be extensive enough to detect inter-annual variation and sufficiently intensive to account for intra-annual trends.     

Auswahl repräsentativer Standorte zur Modellierung der Ausbreitung von gentechnisch veränderten Pflanzen in Nord-Deutschland

Goal and Scope

The use of genetically modified plants (GMP) in agriculture is increasing rapidly. While GMP in North and South America are already established an extensive cultivation in Germany is yet to come. Risk assessment on possible effects of released GMP are mainly based on empirical studies with a small spatial extent (laboratories, small-scale field trials). The joint research project ‘Generic detection and extrapolation of genetically modified rape (GenEERA)’ aimed at estimating the dispersal and persistence of genetically modified oilseed rape (Brassica napus) by the use of individual based models. The objective of the article at hand is to give a detailed account of the spatial variability of climate in Northern Germany (German Federal States of Brandenburg, Lower Saxony and Bremen Mecklenburg Western Pomerania, Schleswig-Holstein and Hamburg). Based on this, a method was developed that includes both, the determination of representative oilseed rapefields for modelling the dispersal of GM oilseed rape at field scale, and the subsequent generalisation of the results to landscapes.

Data and Methods

The statistically founded selection of modelling sites was performed by a compilation of available indicators within a GIS environment which are supposed to be important for the dispersal and the persistence of oilseed rape. Meteorological data on precipitation (P), air temperature (T), and sunshine duration (S) collected at up to 1,200 monitoring sites from 1961–1990 were as well as data on wind conditions (W) aggregated multivariate-statistically by Ward cluster analysis. An ecoregionalisation was used for characterising Northern Germany ecologically. Phenological data on the start of the oil seed rape bloom differentiated in the monitoring periods 1961–1990 and 1991–1999, respectively, were regionalised by performing variogram analysis and kriging interpolation. These maps were used to select appropriate Landsat images to identify rape fields by remote sensing algorithms as well as to define the respective flowering periods for individual based modelling.

Results

The separately generated P-T-S-W-Cluster were aggregated to four homogenic climatic regions. In combination with agricultural clusters defining typical landuse patterns (crop rotation, cultivation management) eight model regions were derived which describe the climatic and agronomic variations in Northern Germany. For each of these regions a representative monitoring site was selected serving for individual based modelling. At last, the modelling results were extrapolated back to the model regions applying corresponding GIS queries.

Discussion

The generated climatic regions reflect the transition of marine climate at the North Sea to continental climate in Northeast Germany. The shift in flowering of oil seed rape coincides with other studies on phenological changes of agricultural crops and wild plants.

Conclusions

Due to the huge calculation efforts and the lack of adequate land registers it was not possible to simulate the potential dispersal of GM oil seed rape at farm scale. Thus, generalisations were used to describe the variations of relevant ecological drivers affecting the dispersal of GMP. It could be shown that the aggregation of those factors to homogenic climatic regions was a successful approximation.

Recommendations and Perspectives

Due to the limited empirical data base it is necessary to validate and substantiate the modelling results by a GMP monitoring. The EU Directive 2001/18/EC on the deliberate release of genetically modified organisms into the environment stipulates assessment of direct and indirect effects of GMP on humans and the environment by case-specific monitoring and general surveillance. It should be realised as soon as possible, since the release and the cultivation of GMP in Germany have been started, already. The monitoring should be complemented by the implementation of a web-based geoinformation system (WebGIS) which enables access to relevant geodata and monitoring data and assists in analysing possible GMP impacts.     

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.     

Using Presence-Absence Data to Build and Test Spatial Habitat Models for the Fisher in the Klamath Region, U.S.A.

Abstract: Forest carnivores such as the fisher ( Martes pennanti ) have frequently been the target of conservation concern because of their association in some regions with older forests and sensitivity to landscape-level habitat alteration. Although the fisher has been extirpated from most of its former range in the western United States, it is still found in northwestern California. Fisher distribution, however, is still poorly known in most of this region where surveys have not been conducted. To predict fisher distribution across the region, we created a multiple logistic regression model using data from 682 previously surveyed locations and a vegetation layer created from satellite imagery. A moving-window function in a geographic information system was used to derive landscape-level indices of canopy closure, tree size class, and percent conifer. The model was validated with new data from 468 survey locations. The correct classification rate of 78.6% with the new data was similar to that achieved with the original data set (80.4%). Whereas several fine-scale habitat attributes were significantly correlated with fisher presence, the multivariate model containing only landscape- and regional-scale variables performed as well as one incorporating fine-scale data, suggesting that habitat selection by fishers may be dominated by factors operating at the home-range scale and above. Fisher distribution was strongly associated with landscapes with high levels of tree canopy closure. Regional gradients such as annual precipitation were also significant. At the plot level, the diameter of hardwoods was greater at sites with fisher detections. A comparison of regional fisher distribution with land-management categories suggests that increased emphasis on the protection of biologically productive, low- to mid-elevation forests is important to ensuring the long-term viability of fisher populations.     

污水再生处理工艺中卡马西平的去除过程模拟及其生态风险评价

卡马西平在污水和水环境中广泛存在,且对水生生态系统安全构成风险,因此成为目前研究较多的药品之一。以北京清河再生水厂为例,研究"超滤—臭氧氧化—氯消毒"处理工艺中卡马西平的去除特性,并针对臭氧氧化和氯消毒工艺建立模拟卡马西平去除过程的机理模型。同时,利用美国环境保护署ECOTOX数据库,获取卡马西平对北京市水生生物物种的毒性数据,并基于毒性数据建立物种敏感度分布(species sensitivity distribution,SSD)模型,评价再生水厂出水补给地表水体时卡马西平产生的生态风险。臭氧氧化和氯消毒模型对卡马西平、总有机碳、氨氮等指标的模拟误差总体低于20%,模型的灵敏参数均可以被较好地识别,且其不确定性显著下降。对比7种SSD模型发现,对数正态分布和对数Logistic分布模型较好地拟合了北京市6个物种的卡马西平毒性数据,二者预测得到的总体生态风险期望值分别为7.4%和8.5%。