Explore the vast range of titles available.

It has been hypothesized that submesoscale flows play an important role in the vertical transport of climatically important tracers, due to their strong associated vertical velocities. However, the multi-scale, non-linear, and Lagrangian nature of transport makes it challenging to attribute proportions of the tracer fluxes to certain processes, scales, regions, or features. Here we show that criteria based on the surface vorticity and strain joint probability distribution function (JPDF) effectively decomposes the surface velocity field into distinguishable flow regions, and different flow features, like fronts or eddies, are contained in different flow regions. The JPDF has a distinct shape and approximately parses the flow into different scales, as stronger velocity gradients are usually associated with smaller scales. Conditioning the vertical tracer transport on the vorticity-strain JPDF can therefore help to attribute the transport to different types of flows and scales. Applied to a set of idealized Antarctic Circumpolar Current simulations that vary only in horizontal resolution, this diagnostic approach demonstrates that small-scale strain dominated regions that are generally associated with submesoscale fronts, despite their minuscule spatial footprint, play an outsized role in exchanging tracers across the mixed layer base and are an important contributor to the large-scale tracer budgets. Resolving these flows not only adds extra flux at the small scales, but also enhances the flux due to the larger-scale flows.

Missing values in water level data is a persistent problem in data modelling and especially common in developing countries. Data imputation has received considerable research attention, to raise the quality of data in the study of extreme events such as flooding and droughts. This article evaluates single and multiple imputation methods used on monthly univariate and multivariate water level data from four water stations on the rivers Benue and Niger in Nigeria. The missing completely at random, missing at random and missing not at random data mechanisms were each considered. The best imputation method is identified using two error metrics: root mean square error and mean absolute percentage error. For the univariate case, the seasonal decomposition method is best for imputing missing values at various missingness levels for all three missing mechanisms, followed by Kalman smoothing, while random imputation is much poorer. For instance, for 5% missing data for the Kainji water station, missing completely at random, the Kalman smoothing, random and seasonal decomposition methods had average root mean square errors of 13.61, 102.60 and 10.46, respectively. For the multivariate case, missForest is best, closely followed by k nearest neighbour for the missing completely at random and missing at random mechanisms, and k nearest neighbour is best, followed by missForest, for the missing not at random mechanism. The random forest and predictive mean matching methods perform poorly in terms of the two metrics considered. For example, for 10% missing data missing completely at random for the Ibi water station, the average root mean square errors for random forest, k nearest neighbour, missForest and predictive mean matching were 22.51, 17.17, 14.60 and 25.98, respectively. The results indicate that the seasonal decomposition method, and missForest or k nearest neighbour methods, can impute univariate and multivariate water level missing data, respectively, with higher accuracy than the other methods considered.

Using observations from the Argo array of profiling floats, the large-scale circulation of the upper 2000 decibars (db) of the global ocean is computed for the period from December 2004 to November 2010. The geostrophic velocity relative to a reference level of 900 db is estimated from temperature and salinity profiles, and the absolute geostrophic velocity at the reference level is estimated from the trajectory data provided by the floats. Combining the two gives the absolute geostrophic velocity on 29 pressure surfaces spanning the upper 2000 db of the global ocean. These velocities, together with satellite observations of wind stress, are then used to evaluate Sverdrup balance, the simple canonical theory relating meridional geostrophic transport to wind forcing. Observed transports agree well with predictions based on the wind field over large areas, primarily in the tropics and subtropics. Elsewhere, especially at higher latitudes and in boundary regions, Sverdrup balance does not accurately describe meridional geostrophic transports, possibly due to the increased importance of the barotropic flow, nonlinear dynamics, and topographic influence. Thus, while it provides an effective framework for understanding the zero-order wind-driven circulation in much of the global ocean, Sverdrup balance should not be regarded as axiomatic.

Upwelling of global deep waters to the sea surface in the Southern Ocean closes the global overturning circulation and is fundamentally important for oceanic uptake of carbon and heat, nutrient resupply for sustaining oceanic biological production, and the melt rate of ice shelves. However, the exact pathways and role of topography in Southern Ocean upwelling remain largely unknown. Here we show detailed upwelling pathways in three dimensions, using hydrographic observations and particle tracking in high-resolution models. The analysis reveals that the northern-sourced deep waters enter the Antarctic Circumpolar Current via southward flow along the boundaries of the three ocean basins, before spiraling southeastward and upward through the Antarctic Circumpolar Current. Upwelling is greatly enhanced at five major topographic features, associated with vigorous mesoscale eddy activity. Deep water reaches the upper ocean predominantly south of the Antarctic Circumpolar Current, with a spatially nonuniform distribution. The timescale for half of the deep water to upwell from 30° S to the mixed layer is ~60–90 years. Deep waters of the Atlantic, Pacific and Indian Oceans upwell in the Southern Oceanbut the exact pathways are not fully characterized. Here the authors present a three dimensional view showing a spiralling southward path, with enhanced upwelling by eddy-transport at topographic hotspots.

There is high demand for honey in Saudi Arabia, honey bees make a valuable contribution to agriculture and the economy, and therefore it is important to know levels of colony loss and potential reasons for losses. While there is much research into honey bee colony losses worldwide, little is known about colony losses in Saudi Arabia, management practices or beekeeping experience there. The aims of this work were to address this knowledge gap. Results of a survey of beekeepers in southwest Saudi Arabia conducted in summer 2018 are presented, including colony losses in five different seasons. Data collection involved face-to-face interviews, supplemented by an online survey, using a purpose-designed questionnaire. Responses were obtained from 109 beekeepers, all male, managing 135 to 1700 colonies, with 2 to 45 years of beekeeping experience. Most (73.1%) respondents mainly kept local hybrid bees, while 25.9% mainly kept Apis mellifera jemenitica. Honey yields per colony varied much more between beekeepers than between bee races. A high proportion (83.5%) of beekeepers reported losing colonies over the period studied. The reported colony loss rate was significantly higher in summer than in other seasons, but still low. The overall proportion of colonies lost was 11.4% in summer 2017 and was lowest in spring 2018 (6.6%). The main reported causes of loss were Varroa destructor and disease. Most beekeepers (88.0%) treated against the Varroa mite, although only one method was reported, tau-fluvalinate as Apistan strips, and only 41.7% used a screened bottom board. The results establish a benchmark for future beekeeper surveys in Saudi Arabia and other environmentally similar countries where colony losses are of interest in all seasons of the year. Informing and supporting Saudi beekeepers concerning Varroa monitoring and treatment and optimal hive management could result in fewer losses, higher honey yields, potential to market organic honey and a greater share of the domestic honey market.

This article presents results of an analysis of honey bee losses over the winter of 2011-2012 in the Netherlands, from a sample of 86 colonies, located at 43 apiaries. The apiaries were selected using spatially stratified random sampling. Colony winter loss data were collected and related to various measures of colony strength recorded in summer, as well as data from laboratory analysis of sample material taken from two selected colonies in each of the 43 apiaries. The logistic regression model which best explained the risk of winter loss included, in order of statistical importance, the variables (1) Varroa destructor mite infestation rate in October 2011, (2) presence of the cyano-substituted neonicotinoids acetamiprid or thiacloprid in the first 2 weeks of August 2011 in at least one of the honey bee matrices honey, bees or bee bread (pollen), (3) presence of Brassica napus (oilseed rape) or Sinapis arvensis (wild mustard) pollen in bee bread in early August 2011, and (4) a measure of the unexplained winter losses for the postal code area where the colonies were located, obtained from a different dataset. We consider in the discussion that reduced opportunities for foraging in July and August because of bad weather may have added substantially to the adverse effects of acetamiprid and thiacloprid. A novel feature of this work is its use of postal code random effects from two other independent datasets collected in the annual national monitoring by questionnaires of winter losses of honey bees in the Netherlands. These were used to plan the sample selection and also in the model fitting of the data in this study. It should however be noted that the results of the present pilot study are based on limited data, which may consequently reveal strong factors but fail to demonstrate possible interaction effects.