Monitoring parasitic abundance in cage-based aquaculture : the effects of clustering

Most discussions of sampling protocols within the literature on monitoring aquatic parasites are based on the assumptions of simple random sampling. There has been a growing recognition within the fields of human and terrestrial veterinary epidemiology that data are often collected from individuals within clusters where such assumptions are not valid. These circumstances arise when monitoring ectoparasitic sea lice on Scottish salmon farms. In previous work the authors have demonstrated that significant intraclass correlation coefficients (ICC) values are associated with cage-level abundance of sea lice, particularly when the parasite reaches its adult stage of development. In this paper two sets of data from Scottish farms with ICC values for adult L. salmonis of 0.35 [0.08-0.72, 95%CI] and for adult C. elongatus of 0.42 [0.14-0.66, 95%CI] are used to investigate the implications of clustering. A Monte Carlo simulation approach is used to illustrate the effect of various sampling approaches. The protocols simulated reflect those typically used across a range of countries and production environments in which salmon are currently reared. By illustrating clearly from empirical data sets what is known by theoretical argument it is hoped that guidelines for sampling parasites, and disease monitoring more generally, within aquaculture will in future incorporate appropriate consideration of issues related to the clustering that is typically present in cage-based production systems

ESTIMATING CORN YIELD RESPONSE MODELS TO PREDICT IMPACTS OF CLIMATE CHANGE

Projections of the impacts of climate change on agriculture require flexible and accurate yield response models. Typically, estimated yield response models have used fixed calendar intervals to measure weather variables and omitted observations on solar radiation, an essential determinant of crop yield. A corn yield response model for Illinois crop reporting districts is estimated using field data. Weather variables are time to crop growth stages to allow use of the model if climate change shifts dates of the crop growing season. Solar radiation is included. Results show this model is superior to conventionally specified models in explaining yield variation in Illinois corn.Crop Production/Industries,

Standard Meteorological Measurements

Instruments that measure weather variables have been invented and tested since the time of Leonardo de Vinci. The earliest instruments were crude by today’s standards and required manual observation and notation of the weather variable of interest. In recent years, the miniaturization of circuits–sensors and the use of electronic processors have made it possible to collect ever-increasing numbers of observations on scales not previously considered. In many agricultural applications, the primary portion of the atmosphere that is of interest is the lower planetary boundary layer, or that layer affected by the earth’s surface. Accurate measurement of weather variables in the lower planetary boundary layer requires an understanding of the interactions among the atmosphere, plant communities, and soils. Temperature and pressure are often measured because of their role in air movement and energy exchange between the earth’s surface and the atmosphere. Temperature is perhaps of greater interest in agricultural applications because it is a driving variable that determines the rate of growth and development of an organism, and thus determines what species can grow in a region. Wind speed and direction are measured because of their role in convective energy exchange and the movement of spores, pollen, odors, and chemicals as they drift in the atmosphere. Precipitation amount, intensity, frequency, and form are important in determining the availability of water for crops and play an important role in soil erosion by water and in water quality issues. Solar radiation and relative humidity are additional weather variables, important to agriculture, that are often measured by appropriate sensors at automated weather stations. These variables will be discussed by Klassen and Bugbee (2005, this volume) and Campbell and Diak (2005, this volume)

Standard Meteorological Measurements

Instruments that measure weather variables have been invented and tested since the time of Leonardo de Vinci. The earliest instruments were crude by today’s standards and required manual observation and notation of the weather variable of interest. In recent years, the miniaturization of circuits–sensors and the use of electronic processors have made it possible to collect ever-increasing numbers of observations on scales not previously considered. In many agricultural applications, the primary portion of the atmosphere that is of interest is the lower planetary boundary layer, or that layer affected by the earth’s surface. Accurate measurement of weather variables in the lower planetary boundary layer requires an understanding of the interactions among the atmosphere, plant communities, and soils. Temperature and pressure are often measured because of their role in air movement and energy exchange between the earth’s surface and the atmosphere. Temperature is perhaps of greater interest in agricultural applications because it is a driving variable that determines the rate of growth and development of an organism, and thus determines what species can grow in a region. Wind speed and direction are measured because of their role in convective energy exchange and the movement of spores, pollen, odors, and chemicals as they drift in the atmosphere. Precipitation amount, intensity, frequency, and form are important in determining the availability of water for crops and play an important role in soil erosion by water and in water quality issues. Solar radiation and relative humidity are additional weather variables, important to agriculture, that are often measured by appropriate sensors at automated weather stations. These variables will be discussed by Klassen and Bugbee (2005, this volume) and Campbell and Diak (2005, this volume)

Southern great plains 1997 hydrological experiment: vegetation sampling and data documentation

"Prepared for the United States Department of Agriculture, Agricultural Research Service"--Cover

Characteristics of Magnetoplasmas Semiannual Status Report No. 12, May 1 - Oct. 31, 1965

Magnetoplasma characteristics - anomalous diffusion across magnetic field, heat conduction in plasma, cesium plasma generator, and electron velocity distribution function in magnetoplasma

Evaluating the climate effects of mid-1800s deforestation in New England, USA, using a Weather, Research, and Forecasting (WRF) Model Multi-Physics Ensemble

The New England region of the northeastern United States has a land use history characterized by forest clearing for agriculture and other uses during European colonization and subsequent reforestation following widespread farm abandonment. Despite these broad changes, the potential influence on local and regional climate has received relatively little attention. This study investigated wintertime (December through March) climate impacts of reforestation in New England using a high-resolution (4 km) multiphysics ensemble of the Weather Research and Forecasting Model. In general, the conversion from mid-1800s cropland/grassland to forest led to warming, but results were sensitive to physics parameterizations. The 2-m maximum temperature (T2max) was most sensitive to choice of land surface model, 2-m minimum temperature (T2min) was sensitive to radiation scheme, and all ensemble members simulated precipitation poorly. Reforestation experiments suggest that conversion of mid-1800s cropland/grassland to present-day forest warmed T2max +0.5 to +3 K, with weaker warming during a warm, dry winter compared to a cold, snowy winter. Warmer T2max over forests was primarily the result of increased absorbed shortwave radiation and increased sensible heat flux compared to cropland/grassland. At night, T2min warmed +0.2 to +1.5 K where deciduous broadleaf forest replaced cropland/grassland, a result of decreased ground heat flux. By contrast, T2min of evergreen needleleaf forest cooled –0.5 to –2.1 K, primarily owing to increased ground heat flux and decreased sensible heat flux

Influence of the Soret effect on convection of binary fluids

Convection in horizontal layers of binary fluids heated from below and in particular the influence of the Soret effect on the bifurcation properties of extended stationary and traveling patterns that occur for negative Soret coupling is investigated theoretically. The fixed points corresponding to these two convection structures are determined for realistic boundary conditions with a many mode Galerkin scheme for temperature and concentration and an accurate one mode truncation of the velocity field. This solution procedure yields the stable and unstable solutions for all stationary and traveling patterns so that complete phase diagrams for the different convection types in typical binary liquid mixtures can easily be computed. Also the transition from weakly to strongly nonlinear states can be analyzed in detail. An investigation of the concentration current and of the relevance of its constituents shows the way for a simplification of the mode representation of temperature and concentration field as well as for an analytically manageable few mode description.Comment: 30 pages, 12 figure

Remote sensing of corn and soybean canopy productivity: data collection and documentation

"Prepared for the U.S. Department of Agriculture"--Cover."August 2001.