Agreste provides dry matter yield annual values for both per- manent and temporary grasslands. In this study, low alti- tude permanent grasslands were studied for 48 d´epartements (Fig. 2). In Agreste, permanent grasslands are defined as natural grasslands or as planted grasslands older than 6 yr. Also, since 2000, M´et´eo-France has issued the ISOP index (Ruget et al., 2006). This index is derived from an inte- grated system providing a real-time assessment ofthe for- age production variabilityoverFrance. The system is based on simulations ofthe STICS model of Institut National de la Recherche Agronomique (INRA), driven by daily atmo- spheric variables derived from interpolated ground observa- tions of meteorological variables. Inthe ISOP-STICS sim- ulations, the grass is regularly cut, from January to October, and the cut biomass is cumulated throughout the year in or- der to calculate the annual dry matter yield. The harvest dates depend on climatic conditions and are derived from temper- ature sums. Management practices, such as the frequency of mowing, the thermal time between mowings or the amount of nitrogen supply, were estimated through a national sur- vey carried out in 1998 by the French Ministry of Agricul- ture. The fodder production was assessed for more than 6000 combinations of soils, climates, and management practices and then aggregated on about 200 forage regions previously defined by the French Ministry of Agriculture. The ISOP in- dex was calibrated for delivering a good representation ofthe inter-annual variability. In this study, both Agreste and ISOP were used to assess theISBA-A-gs simulations for grass- lands. The advantage ofthe Agreste data is that they are pro- duced by local experts, and Ruget et al. (2006) used this in- dependent bottom-up information to validate the ISOP prod- uct for the 1982–1998 period (for more recent years, the two products are not independent as the local experts contribut- ing to Agreste could use ISOP). Ruget et al. (2006) found that the consistency between the two fodder production es- timates varies a lot from one region to another (R 2 varies from 0 to 0.6). The two products present shortcomings: (1) although the STICS model used to produce ISOP was cali- brated and validated by Ruget et al. (2006) using five INRA grassland test sites, mapping the numerous STICS parame- ters is not easy, (2) at a regional scale, the Agreste fodder pro-
data from instrumented sites. For example, the DIF version ofISBA was tested on a local scale by Decharme et al. (2011) over a grassland site in south-western France. However, the soil and vegetation characteristics at a given site may dif- fer sharply from those at neighbouring sites. It is important to explore new ways of assessing and benchmarking model simulations on a regional scale. Remote-sensing products can be used to monitor terrestrial variables over large areas and to benchmark landsurfacemodels (Szczypta et al., 2014). At the same time, using in situ observations as much as possible is key, as remote-sensing products are affected by uncertain- ties. So far, the French annual agricultural yield data have been publicly available on a département scale only. In order to take advantage ofthe existing information on soil proper- ties, an option could be touse satellite-derived LAI products at a spatial resolution of 1 km × 1 km in conjunction with soil maps at the same spatial resolution (e.g. derived from the Harmonized World Soil Database, Nachtergaele et al., 2012). Since these products are now available on a global scale, the methodology explored in this studyover metropolitan France could be extended to other regions.
provides a consistent assessment of drought conditions both spatially and throughout thelandsurface hydrological cycle. This 50-yr drought reanalysis allowed the identification of dry periods experienced inFrance and the description – through the examination of two specific events – ofthe way a drought propagates through the hydrological cycle. Mod- elling the complete surface water and energy budgets allowed for example to describe agricultural drought events like 2003 which were driven not only by precipitation deficits by also by positive temperature anomalies. A local-scale analysis of drought events identified regional specificities of drought characteristics: frequency, duration, timing and magnitude. Frequency and duration results for example show that wa- ter managers should prepare to face diverse physical drought patterns across the country, and that these patterns are closely linked withthe climate, soil and vegetation ofthe catchment considered. They are moreover highly dependent on both the time scale and the variable considered. Characteristics of individual spatio-temporal drought events were then com- pared at the national scale in order to identify benchmark events among those that occurred during the last 50 yrs. The analysis of benchmark events has been here performed at the national scale, but it would be relevant to run it at the scale of each catchment/water resource zone. This would provide water managers withthe actual worst-case events ofthe last 50-year over their specific zone of interest. The ranking of drought events, either from summary statistics or Severity- Area-Time scale curves, is also highly dependent on both the time scale and the level ofthe hydrological cycle considered. The drought characteristics identified during the 1958– 2008 period will serve as a reference for the assessment ofthe impact of climate change on droughts inFrance. Further work on the C LIM S EC project will make useofIsba-Modcou hydrological simulations forced by downscaled climate pro- jections for the 21st century in order to evaluate the poten- tial changes in drought characteristics through techniques recently applied to UK meteorological droughts (Vidal and Wade, 2009). Theland-surface modelling approach adopted here will allow the description of changes in drought charac- teristics driven by changes not only in precipitation but also in temperature.
There were no differences among landuse strategies during winter or among soil layers on microporosity and bulk density of soil, but macroporosity was lower inthesurface layer inthe pasture without N (Table 2). The reduction in macroporosity is related tothe stress applied by animal trampling on thesurface, which was greater than soil strength, resulting in plastic soil deformation (Horn & Rostek, 2000). This is probably a consequence ofthe lower forage availability inthe pasture without N treatment (Table 1), in which the animals trampled more to achieve the same amount of forage in comparison tothe pasture with N treatment (Baggio et al., 2009). The increase in animal trampling inthe same area results in additional soil compaction; the magnitude of this process depends not only on the soil strength and on the stress applied on thesurface, but also on the frequency this stress is applied inthe same area (Horn & Rostek, 2000). The intensity of soil compaction may also be related to pasture availability
Paper by Venevsky and Venevskaia (2005) suggests quantitative measures which enable two criteria ofthe global biodiversity hotspots to be applied on a national level for 74 large countries, and show how these measures can be applied to map national biodiversity hotspots. The basic concept in identifying biodiversity hotspot is to elaborate and further develop the national protected area system, to satisfy both national and international conservation goals. They showed how national biodiversity hotspots can be mapped from the species–energy relationship for vascular plants using climate, topographical and landuse data when spatial pattern of species richness is not known. This methodology to map national biodiversity hotspots from abiotic factors is applied to Russia as a casestudy. Three Russian biodiversity hotspots, North Caucasus, South Siberia and Far East were identified. The resulting hotspot maps cover national-scale environmental gradients across Russia and although they are also identified by Russian experts their actual geographical locations were hitherto unspecified. The large-scale national hotspots, identified for Russia, can be used for further fine scale and more detailed conservation planning.
An estimate by Food and Agricultural Organisation (FAO) in 1984 indicated that 5 to 7 million hectares ofland a year are lost globally toagricultural production as a result of erosion and related forms ofland degradation, including siltation of water ways and dams. Tropical soils, which are generally less stable than those ofthe temperate climates, are particularly severely threatened, due to their fragile properties and the very aggres- sive climatic conditions. However, since the primary step to- wards ef ective land conservation is appropriate allocation oflandto uses for which they are most suitable, landuse should be in accordance toland potential capacity, so as to optimize and sustain agricultural productivity. However, in practice, par- ticularly is south western Nigeria, theuseto which land is put is not ot en related totheland potential capacity for theuse type (Senjobi, 2001). h is is largely because the decision on landuse rests virtually withland owners/users, who are mostly peasant farmers and not on the outcome of professional land evaluation (Ogunkunle and Eghaghara, 1992). h is had rendered some ofthe previously agriculturally rich lands, progressively uni t for agricultural production especially where two or more landuse types, contrasting in specii c details and potentials occur on similar soils or the same landuse types on dissimilar soils.
Inthe sub-region of TLPD B, which is the maize type, physical conditions for agriculture are similarly favourable as in TLPD A, but land-use patterns and dynamics are different. Here, a distinct land-use change occurred especially on arable land. Both variables, the proportion of maize area (18.7% in 2010) and its average annual expansion rate (12.1% from 2005-2010), are the highest ones of all five TLPDs. It can be assumed that the conversion of arable land is in favour of maize. In consequence, in this sub-region the proportion of maize area is clearly higher than the average for Hesse. Similar developments concerning maize area were also reported for other parts of Germany (Kandziora et al. 2014; Lupp et al. 2014). In TLPD B, grassland is also a part of this conversion. Livestock density is comparatively high due to high cattle numbers. Thus, it can be assumed, that the reason for this relatively high proportion of maize area is both cattle farming and its need for fodder, and biogas production. Maize fields are known to feature relatively few species compared to other crops. Thus, in sub-regions of TLPD B measures should be taken to preserve and promote species richness. In this context, one recommendation is reported by Waldhardt et al. (2011). They suggest that within the maize fields small areas and stripes should be cultivated without crop protection measures since these measures advance the number and variety of species.
In July 2015, the patient was referred tothe department of internal medicine by her family doctor with weight loss of 8 kg, persistent fatigue, and pain inthe right hypochondriac region. There were no urinary symptoms. Clinical examination revealed tenderness inthe right hypochondriac region, and ultrasonography showed a mass on the upper pole ofthe right kidney. A computed tomography (CT) scan ofthe abdomen revealed a voluminous tumour of 8.2 cm inthe upper pole ofthe right kidney. The tumour showed irregular contrast captation and was assessed as a malignant solid renal tumour, presumably renal cell carcinoma. No pathologically enlarged retroperitoneal nodes were seen (Figure 1A and 1B). A CT image ofthe thorax showed no abnormalities. A radical right nephrectomy was performed with an uncomplicated postoperative course.
The cell volume was calculated from geometric models according tothe shape ofthe cells (Sun and Liu, 2003). Taxa contributing more than 5% tothe total phytoplankton biovolume per year were grouped in FGs according to Reynolds et al. (2002) and Padisák et al. (2009). All phytoplankton taxa were grouped in MBFGs according to Kruk et al. (2010). A Principal Component Analysis (PCA) was performed to summarize the environmental variabilityofthe limnophase and potamophase periods. The Indicator Value Analysis (INDVAL) (Dufrêne and Legendre, 1997) was applied toverifytheuseof phytoplankton FGs and MBFGs as indicators ofthe trophic status ofthe Corutuba channel. The relationships between the abiotic data and the biovolume ofthe phytoplankton FGs and MBFGs were analyzed through Canonical Correspondence Analysis (CCA). For the analysis was performed the software PC-Ord 6.0 (McCune and Mefford, 1999).
be viewed as a special knowledge network that captures one’s beliefs in a risky decision. Each node (circle) represents an uncertain event; each arrow (or edge) represents dependence between two events, and the lack of arrow indicates conditional independence. The structure of a BN relects how we think diferent events relate to each other. The numerical part of a BN inthe form of conditional probabilities relects the strength of such dependence. Inthecaseof NG tube positioning, the tube site is the shared parent node of diferent bedside tests. Arrows pointing out from tube site and into the bedside tests indicate our belief that the outcome of these tests depend, among other things, on the location ofthe feeding tube which could be lung, intestine, stomach, or oesophagus. No arrows, however, link diferent tests together because we believe that the outcome of one test (its indings) does not depend on those of another test (conditional independence). For aspirate pH, feeding and medication history of a patient were modelled as additional parents ofthe pH test; pH paper was modelled as a child of pH meter (which is a child of tube site). This allows us to examine test results from various combinations of feeding and medication conditions, as well as to test using a less reliable measurement of pH.
In order to evaluate the susceptibility to hot cracking inthe high-temperature brittleness range, we have determined the changes of temperature of individual points when the alloy was cooled down from the solidus temperature. The tests were performed on the cylindrical Ø 10 x 120 mm specimens, using the Gleeble 3800 simulator, at Iron Metallurgy Institute in Gliwice. Four S-type thermocouples were pressure welded tothe specimens: inthe specimen axis and 2, 5 and 8 mm away from the axis. The specimens were fixed in copper holders, keeping a constant distance of 33 mm, and then were heated inthe argon atmosphere at the 20 0 C/s rate tothe temperature of liquid phase appearance, and were afterwards freely cooled. Changes in
The Saurashtra region comprises the south western part of Gujarat state in western India. Many south-west flowing rivers exist in southern Saurashtra. Minsar river is an ephemeral river that originates in a village of Jamnagar district inthe inland hilly region. It drains into the low lying Kerly Ghed area near the Arabian Sea coast in Porbandar district (Fig.1). In 1970s, different measures were initiated by the State Government at various sites to conserve freshwater runoff so as to meet water supply demands ofthe region as well as reduce groundwater salinity problems. Figure 1 shows the location of Barda Sagar, one of such sites, in Porbandar district. Barda Sagar, located north-west of Porbandar city, is a low lying flat region (previously termed Barda ‘Ghed’). It receives water from seasonal streams that originate in Barda Hills. Maximum water spread area of Barda Sagar is about 21 km 2 . Changes occurring over a period of three decades are studied in and around a buffer zone of 2 km from the boundary of this site.
A first step to testing if MDF approaches are effective is touse synthetic data, where the underlying “true” state ofthe system and model parameters are known. A synthetic truth is generated by running the model with given parameters, noise is added, and data are thinned. These data are provided tothe MDF scheme to test estimation of parameters and retrieval of C fluxes, all of which are known (Fig. 9). A second step is to examine posterior parameter distributions relative to pri- ors. Have parameters been constrained? Is there evidence that parameter priors were correct? For example, inthe syn- thetic case shown in Fig. 9 it is clear that turnover rates of foliage and soil organic matter were better constrained by NEE data, with PDFs concentrated around the true param- eter values used to generate the synthetic data. Posterior turnover rates for fine roots and wood are barely different from the priors, with broad distributions spanning the prior range. A third step is to check model residuals on NEE (or any other observations), to see if they are Gaussian and not autocorrelated, a typical hypothesis of Bayesian approaches (see above). If multiple data time series are used, are they all consistent withthe model, or do they reveal potential bi- ases in data or model (Williams et al., 2005)? It is useful to iterate the optimization process from a different starting point (initial conditions) to see if the posteriors are similar. Testing different assumptions inthe MDF is also useful, for instance, uniform versus Gaussian priors, altered model error estimates in KF schemes etc.
oocyte growth) or by increasing enzyme activity necessary for vitellogenesis (Medford and Mac kay, 1978). However, the males H.S.I. in this study, were stable during all the sampling period, this probably indicates that males of C. conger do not used the liver reserves for maturation before migration because of abundance prey in these periods (Abi-Ayad et al., 2011). Inthe Mediterranean Sea, males conger eel are reported to be smaller than females, and rarely exceeding 100 cm in length and females reaching over 200 cm (Cau and Manconi, 1983). In fact, 50 % of males become sexually mature earlier than 50 % of females in all samples analyzed in this study. However, the present study is the first attempt to determine the size at first maturity for this species. There were no references dealing withthe size at maturity for C.conger, reported from other regions. The sex ratio ofthe European conger eel population inthe western coast of Algeria was strongly skewed towards females in summer and spring seasons, which represent 86 % ofthe population. In winter and autumn the percentage between males and female in quite equal. Different findings have been reported by Sbaihi et al., 2001, Sullivan et al., 2003, and Correia et al., 2009. This may be caused by different gear used in summer and spring and in winter and autumn. In fact, the European conger eel present a spatial displacement of sexes, females were found inthe inshore waters but males were only found at much greater depths (Cau and Manconi, 1983). The conclusion of that contribution, the inshore fishery ofthe European conger eel (Conger conger) target mainly young individuals with sizes between 50 cm and 60 cm. Thestudyofthe biology of C.
To characterize thelanduse and cover in Rio das Lontras's watershed, mosaics were prepared using satellite images from Google Earth, which were georeferenced according the base map from Salto do Lontra and Nova Esperança do Sudoeste, two cities located inthe state of Paraná. For this analysis, considering a visual classification, was generated a thematic map withthelanduse and cover inthe watershed. In this type of classification, the vector structure is composed by points, lines and polygons, using a coordinate system for its representation. The points are represented by one coordinate pair, the lines and polygons are represented by a set of coordinate pairs.
cycle, increases stem production by 43.5% and 67.2%, respectively. This means that ofthe overall 1,942 mm and 2,224 mm approximately one fourth and one third ofthe water requirements are covered by irrigation. Although irrigation increases the yield under humid conditions as inthe state of São Paulo, it is seldom used because ofthe remaining paradigm that irrigation is economically not reasonable (SILVA et al., 2014). By applying irrigation even inthe semiarid northeast- ern parts of Brazil sugar cane can be grown. Silva et al. (2012) estimate a water demand of 1,710 mm for the entire growing cycle of sugar cane; however, the an- nual precipitation at the location of their experiment inthe semiarid Sub-middle São Francisco river basin (Juazeiro) sums up to 523 mm. Assuming that the wa- ter requirements must not be fulfilled by 100%, that is, applying deficit irrigation, the irrigation water demand still is inthe magnitude of 800 to 1,000 mm for the en- tire growing cycle of sugar cane. This means approxi- mately two thirds ofthe water requirements must be covered by irrigation. However, Maneta et al. (2009) found that increasing irrigation water demand inthe São Francisco river basin would not affect other uses such as hydropower generation, negatively.
differences are mostly seen around the outer edges ofthe domain, but after three days we see clear changes inthesurface concentrations throughout the domain aproaching about ±15 ppbV over California with a large spatial and temporal variability. Figure 11 shows the root mean square (RMS) difference for the entire simulation period together with a map ofthe domain topography. High altitude locations commonly are expected
The aim of this study is to develop and validate two heat input source models by ANSYS Multiphysics software , which is FEM based model, to simulate the magnetic arc deflection in weld bead in autogean GTAW process. Both models are based on a Gaussian surface flux distribution, which has the advantage of having only two degrees of freedom (arc efficiency and radial distance from the center) and being suitable for a range of welding powers and plate thicknesses and diferent types of welding processes (Teixeira et al., 2014; Farias et al., 2017; Venkatkumar and Ravindran, 2016; Khurram et al., 2013; Hussain and Sherif El-Gizawy, 2016). Firstly, numerical simulations are compared with experimental ones for non-deflected arc to calibrate numerical models. Afterwards, straight magnetic deflected arcs along the torch movement are used for validating both models. In these experiments, fixed deflection ofthe arc along the welding is imposed to avoid a more complicated analysis if the torch weaves and, therefore, to enable the proposed modelsto be easily validated. Temperatures at three different points on the backside ofthe plates (two away from the welding center line and one in its center) and weld pools of SAE 1020 3.2 mm and 6 mm thick steel plates are analyzed. Finally, welding with weaving (frequency of 1Hz) on 3 mm thick steel plates is analyzed. Comparisons of width and visual presentation ofthe bead and experimental results (Larquer and Reis, 2016; Larquer et al., 2016) are carried out.
through stomatal uptake and large-scale meteorological con- ditions including stratosphere–troposphere exchange and the position ofthe jet stream (Barnes and Fiore, 2013) also play important roles. These surface observations show the same well-known cycle that has been seen inthe northern hemispheric midlatitude troposphere from ozone sondes and clean-air remote sites (Logan, 1989; Fiore et al., 2009): low- est values in late fall (ND), increasing through winter (JFM) followed by a broad flat peak over spring–summer (AMJJA). The lower reactivity region NEU peaks in April and declines until January, indicating meteorologically driven increases through the winter (e.g., stratospheric influx). The observa- tions show a phase m = 5.6, 5.3, 5.5, and 4.3 month of year for WNA, ENA, SEU, and NEU, respectively; and corre- sponding amplitudes M = 22, 21, 26, and 17 ppb. By fitting a cosine curve to each grid cell’s time series, we find that in terms of specific locations, the earliest m occur in Canada, Florida, and NEU while the latest m occur in California, south-central NA, and SEU (not shown). Most ACCMIP models have m within ± 1 month ofthe observations, gener- ally earlier in NEU, later in ENA and SEU, and split in WNA. Models C and G have difficulty producing the observed sea- sonal cycles, and their derived phases are not meaningful.
but it may be because ofthe dilution effect from rainfall. Carvalho et al. (2000) also observed lower concentration of these nutrients inthe winter season. As previously described, total P concentrations are much smaller compared with total N (Kjeldahl) and, therefore, dilution may be affecting the results of total P and not the results of total N. Palacio et al. (2009) observed a strong influence of seasonality on surface water quality in a catchment monitored at seven points from January to August. However, it is important to consider that, inthe Campestre catchment, most ofthe sampling days were not after intense rainfall. The results from this study show mainly the effect of subsurface drainage. So, the seasonality effect would not have a significant influence. Thestudy area is head drainage (Figure 2); therefore, the contribution ofsurface runoff on water quality occurs fundamentally during rainfall events. In a head drainage system, to check the effect of runoff on water quality parameters, water samples should be taken during the rainfall event. The EC is expected to increase in summer (Table 9), due tothe increase in fertilizer applications and higher rainfall, which in fact occurred inthe Campestre catchment.