Study of density, distribution and yield on benthic fauna and brown trout (Salmo trutta fario) feeding in Laar reservoirs

Lar lake, with the international UTM specification of 39S 579680 3976567 & 39S 589930 3976184 is Situated in Lar national Park with an aerial distance of 55 Km of Tehran along Haraz road. The present research is carried out as part of a comprehensives Plan for assessment of bioresearches of Lar lake & the rivers flowing into it. This research includes examination of there benthic Samplings performed in Lar lake and each of the related rivers including Delichaee, Ab-e-sefid , Alarm & Lar (Kamardasht).Tubifex and Chironomus genus were found to have the highest frequencies of occurrence in the lake with %77.117 & %21.823 respectively followed by Chironomidae and Simulidae from the Diptera order which accounted for %72.328 and %13.812 occurrences in four rivers examined in the Study. The benthic biomass at various examined Sites and the average wet weight of the benthic biomass in station No one in the lake Was 17.397g and the figure for the examined site in Alarm was 20.242 g which were the highest level among Other examination stations the index for the abundance of species in Alarm river was greater than the rest of the examined rivers with 12.57. A sum of 354 Pieces of brown trouts was caught in the course of sampling which were closely investigated in terms of their digestive tract Content. It was identified that Daphniidae and Chironomus constituted the bulk of eaten items from the lake with %17.985 and %63.973 respectively. Meanwhile, Chironomidae and Simuladae were the most frequently eanten benthos by the fish with %81.47 and %7.93 respectively.The index for the relative length of gut was recorded at 0.49± 0.08 which is well indicative of the carnivorous diet of the fish.The index for the feeding intensity amounted to 138  83 showing that the one year old fish were of more feeding intensity.The coefficient of condition (K) was estimated at 1.02  0.142 for all the caught fish. The average wet weight of the benthos was 10.348 g per square meter which if extended to 700ha surface area of the lake, the total macrobenthic production in the lake would amount to 72730Kg of wet weight or 6510 Kg of dry weight. Since the Secondary Production of macrobenthos have always been double that of their biomass, it is reasonable to assume that the Secondary Production of macrobenthos amount to 145640 Kg by their wet weight and Since the energy transfer in the food chain of the lake from benthos to fish is 10 percent, the fish production Capacity Coming from benthic resources of the lake (Lar) would be 14.5 MT, half of which (7000-8000MT) could annually be harvested. Further more, the actual fish Production Capacity might exceed the projected level Since Daphnia, Rotifers and Ostracoda which belong to Zooplanktons, play a part in the natural diet of trout. Meanwhile, rivers Play a major role in fish nutrition and the annual fish production in Delichaee river is about 4481.8Kg while the figures for Ab-e-sefid, Alerm and Lar rivers are 2370.7 4848.7 and 2586.2 Kg respectively, that further increase fish Production in the area and every year half of these resources can be exploitable from the river & the lake.Nevertheless, due to ecological & biological importance of rivers and the probability of environmental Pollution, devastation of natural fish habitats & their nursery grounds, Sport fishing is not recommended at all.

Isobaric yield ratios and the symmetry energy in heavy-ion reactions near the Fermi energy

The relative isobaric yields of fragments produced in a series of heavy-ion-induced multifragmentation reactions have been analyzed in the framework of a modified Fisher model, primarily to determine the ratio of the symmetry energy coefficient to the temperature, a(sym)/T, as a function of fragment mass A. The extracted values increase from 5 to similar to 16 as A increases from 9 to 37. These values have been compared to the results of calculations using the antisymmetrized molecular dynamics (AMD) model together with the statistical decay code GEMINI. The calculated ratios are in good agreement with those extracted from the experiment. In contrast, the values extracted from the ratios of the primary isobars from the AMD model calculation are similar to 4 to 5 and show little variation with A. This observation indicates that the value of the symmetry energy coefficient derived from final fragment observables may be significantly different than the actual value at the time of fragment formation. The experimentally observed pairing effect is also studied within the same simulations. The Coulomb coefficient is also discussed.

Spatial Variability of Durum Wheat Yield as Related to Soil Parameters in an Organic Field

The yield in organic farming is generally much lower than its potential, which is due to its specificity. The objective of the present study was to quantify the yield spatial variation of wheat and relate it to soil parameters in an organic farm located in the north of the Negev Desert. Soil samples were gathered in a triangular grid at three time intervals. Yields were measured at 73 georeferenced points before the actual harvest. Several thematic maps of soil and yield parameters were produced using geographic information system and geostatistical methods. The strongest spatial correlation was found in the weight of 1000 grains and the weakest was in carbon flow. Temporal relationships were found between soil nitrate concentration, soil water content, and leaf area index. Wheat yield varied from 1.11 to 2.84 Mg ha(-1) and this remarkable variation indicates that the spatial analysis of soil and yield parameters is significant in organic agriculture.

Attribution of climate change: a methodology to estimate the potential contribution to increases in potato yield in Scotland since 1960

Maincrop potato yields in Scotland have increased by 3035 similar to t similar to ha-1 since 1960 as a result of many changes, but has changing climate contributed anything to this? The purpose of this work was to answer this question. Daily weather data for the period 19602006 were analysed for five locations covering the zones of potato growing on the east coast of Scotland (between 55.213 and 57.646 similar to N) to determine trends in temperature, rainfall and solar radiation. A physiologically based potato yield model was validated using data obtained from a long-term field trial in eastern Scotland and then employed to simulate crop development and potential yield at each of the five sites. Over the 47 similar to years, there were significant increases in annual air and 30 similar to cm soil temperatures (0.27 and 0.30 similar to K similar to decade-1, respectively), but no significant changes in annual precipitation or in the timing of the last frost in spring and the first frost of autumn. There was no evidence of any north to south gradient of warming. Simulated emergence and canopy closure became earlier at all five sites over the period with the advance being greater in the north (3.7 and 3.6 similar to days similar to decade-1, respectively) than the south (0.5 and 0.8 similar to days similar to decade-1, respectively). Potential yield increased with time, generally reflecting the increased duration of the green canopy, at average rates of 2.8 similar to t similar to ha-1 decade-1 for chitted seed (sprouted prior to planting) and 2.5 similar to t similar to ha-1 decade-1 for unchitted seed. The measured warming could contribute potential yield increases of up to 13.2 similar to t similar to ha-1 for chitted potato (range 7.119.3 similar to t similar to ha-1) and 11.5 similar to t similar to ha-1 for unchitted potato (range 7.115.5 similar to t similar to ha-1) equivalent to 3439% of the increased potential yield over the period or 2326% of the increase in actual measured yields.

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Called versus Calculated Yield Grades

An evaluation of carcass data collected over a two year period from southwest Iowa steer tests and 4-H carcass shows was conducted to compare USDA yield grades called by the Federal grader to yield grades calculated by actual carcass measurements. A regression equation was developed to predict called yield grade from carcass measurements. A comparison of the generated equation with the USDA equation used in calculating yield grades suggest that USDA graders accurately predict preliminary yield grades based on fat thickness, but may not have adequate time at line speeds to fully account for adjustments in ribeye size relative to carcass weight.

A simple regional-scale model for forecasting sorghum yield across North-Eastern Australia

Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.

Modifying the yield factor based on more efficient use of fertilizer — The environmental impacts of intensive and extensive agricultural practices

The aim of this article is to draw attention to calculations on the environmental effects of agriculture and to the definition of marginal agricultural yield. When calculating the environmental impacts of agricultural activities, the real environmental load generated by agriculture is not revealed properly through ecological footprint indicators, as the type of agricultural farming (thus the nature of the pollution it creates) is not incorporated in the calculation. It is commonly known that extensive farming uses relatively small amounts of labor and capital. It produces a lower yield per unit of land and thus requires more land than intensive farming practices to produce similar yields, so it has a larger crop and grazing footprint. However, intensive farms, to achieve higher yields, apply fertilizers, insecticides, herbicides, etc., and cultivation and harvesting are often mechanized. In this study, the focus is on highlighting the differences in the environmental impacts of extensive and intensive farming practices through a statistical analysis of the factors determining agricultural yield. A marginal function is constructed for the relation between chemical fertilizer use and yield per unit fertilizer input. Furthermore, a proposal is presented for how calculation of the yield factor could possibly be improved. The yield factor used in the calculation of biocapacity is not the marginal yield for a given area, but is calculated from the real and actual yields, and this way biocapacity and the ecological footprint for cropland are equivalent. Calculations for cropland biocapacity do not show the area needed for sustainable production, but rather the actual land area used for agricultural production. The proposal the authors present is a modification of the yield factor and also the changed biocapacity is calculated. The results of statistical analyses reveal the need for a clarification of the methodology for calculating marginal yield, which could clearly contribute to assessing the real environmental impacts of agriculture.

Modifying the yield factor based on more efficient use of fertilizer — The environmental impacts of intensive and extensive agricultural practices

The aim of this article is to draw attention to calculations on the environmental effects of agriculture and to the definition of marginal agricultural yield. When calculating the environmental impacts of agricultural activities, the real environmental load generated by agriculture is not revealed properly through ecological footprint indicators, as the type of agricultural farming (thus the nature of the pollution it creates) is not incorporated in the calculation. It is commonly known that extensive farming uses relatively small amounts of labor and capital. It produces a lower yield per unit of land and thus requires more land than intensive farming practices to produce similar yields, so it has a larger crop and grazing footprint. However, intensive farms, to achieve higher yields, apply fertilizers, insecticides, herbicides, etc., and cultivation and harvesting are often mechanized. In this study, the focus is on highlighting the differences in the environmental impacts of extensive and intensive farming practices through a statistical analysis of the factors determining agricultural yield. A marginal function is constructed for the relation between chemical fertilizer use and yield per unit fertilizer input. Furthermore, a proposal is presented for how calculation of the yield factor could possibly be improved. The yield factor used in the calculation of biocapacity is not the marginal yield for a given area, but is calculated from the real and actual yields, and this way biocapacity and the ecological footprint for cropland are equivalent. Calculations for cropland biocapacity do not show the area needed for sustainable production, but rather the actual land area used for agricultural production. The proposal the authors present is a modification of the yield factor and also the changed biocapacity is calculated. The results of statistical analyses reveal the need for a clarification of the methodology for calculating marginal yield, which could clearly contribute to assessing the real environmental impacts of agriculture.