A highly sensitive,non‐invasive qPCR‐based strategy for direct quantification of Yersinia ruckeri in fish faeces

Finfish with asymptomatic Yersinia ruckeri infections pose a major risk as they can transmit the pathogen and cause clinical outbreaks in stock populations. Current tools have insufficient quantitative ability for accurately detecting the trace levels of Y. ruckeri typically associated with asymptomatic infection, necessitate invasive or lethal sampling, or require long processing times. This study presents a highly sensitive qPCR‐based method, targeting part of the Y. ruckeri 16S rRNA sequence, that is capable of detecting extremely low levels of Y. ruckeri in noninvasively collected faecal samples. Quantitative precision and accuracy of faecal sample analysis was consistent, despite the complexity of the faecal matrix. The assay demonstrated linearity over a six log‐wide dynamic range. Its limit of detection (LOD) and limit of quantification (LOQ) were 4 and 10 copies of the target sequence, respectively. Sensitivity of the assay was comparable to other qPCR‐based methods without requiring invasive or lethal sampling. Applicability as a screening strategy was tested using passively collected faecal samples. Asymptomatic Y. ruckeri infection was detected in all samples, although none of the fish exhibited overt infection. This method will be beneficial for finfish disease management if developed further as a noninvasive, screening tool against asymptomatic Y. ruckeri infection.     

Biological,environmental and socioeconomic threats to citrus lime production

Journal of Plant Diseases and Protection - Limes as a fruit crop are of great economic importance, key to Asian and South American cuisines and cultivated in nearly all tropical and subtropical...     

Modelling individual variability in growth of bull trout in the Walla Walla River Basin using a hierarchical von Bertalanffy growth model

We examined growth in length of fluvial bull trout (Salvelinus confluentus) in the Walla Walla River Basin, Washington and Oregon. Our objectives were to quantify individual variability in growth; examine growth within and among years, life history forms, life stages and sexes; and estimate von Bertalanffy growth parameters. Individual variability was evaluated by modelling asymptotic length (L_∞) and the growth coefficient (k) as random variables. All models were fit with Bayesian methods and were evaluated for fit by the deviance information criterion. By incorporating individual variability, population‐level estimates of L_∞ and k appeared appropriate and estimated growth trajectories for specific bull trout fit individual observed patterns in growth. Growth trajectories and positive correlation between individual estimates of L_∞ and k suggest that some individuals grow at a faster rate and reach a larger maximum size than other individuals and those differences are maintained throughout life. Selected models suggest that fluvial migrants have higher estimates of L_∞ and k than residents, but there were only slight differences in parameter estimates among migrants from two adjacent spawning populations in the Walla Walla River Basin, as well as between males and females. Growth rates increased for fluvial migrants after subadult emigration. Individual variability in growth is consistent with the life history diversity assumed essential for bull trout population persistence. Quantifying this variability is important for modelling population dynamics and viability to conserve this threatened species.     

Estimating fishery effects in a marine protected area: Lamlash Bay

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Changing rainfall patterns and farmers’ adaptation through soil water management practices in semi-arid eastern Kenya

There is limited documentation of soil and water management technologies that enhance adaptation to climate change in drylands of Kenya. Rainfall patterns were analyzed in the semi-arid Machakos and Makueni counties of eastern Kenya using historical data. A total of forty-three smallholder farmers implementing soil water management practices were sampled, and an estimate of the seasonal water budget for current crop and livestock production systems computed. Analysis of rainfall amounts and distribution shows increasing variability, with the average annual total amounts decreasing over the past 50 years. Furthermore, the number of rainy days within the March-April-May season that can support crop growth is gradually decreasing. These decreases are however not significant at P < 0.05. There were more seasons with low rainfall amounts compared to those with high rainfall amounts. All these subject the smallholder crop and livestock production system to limited soil moisture. Farmers address the risk by harnessing and utilizing green (rainfall stored in soil) and blue (rainfall collected into storage tanks) water technologies. The study found that farmers in these semi-arid counties practice fifteen diverse soil and water management interventions on their farms. The most popular practices are cut-off drains, retention ditches, terracing, run-off harvesting, and agroforestry. The estimated seasonal water budget indicates the need for integrated soil and water management interventions to address the crop and livestock production constraints.     

Effects of Land Use on Selected Properties and Heavy Metal Concentration for Soil in the US Great Plains

There is increasing interest in the current conditions of dynamic soil properties and element concentration in the US Great Plains as well as the nature and magnitude of change due to land use and management practices. The study was conducted on Pawnee soil, a major U.S. benchmark soil in the Great Plains. The objectives were to investigate the effects of four common land uses [NoTill (NT), Conventional Till (CT), Grass (G), and Conservation Reserve Program (CRP)] on: i) selected soil properties [total organic carbon (TOC), bulk density (BD), pH, cation exchange capacity (CEC), and electric conductivity (EC)] and ii) water-soluble concentration of 14 heavy metals and micronutrients. The analysis of variance (ANOVA test) indicated that the land use had significant effects on the TOC, CEC, and EC, whereas no relation was detected for BD and pH. Irrespective of land use, the mean element concentration in soil could be arranged in the order: Si (Silicon) > Al (Aluminum) > Fe (Iron) > Mn (Manganese) > B (Boron) > Zn (Zinc) > Cr (Chromium) > Ni (Nickel) > Cu (Copper) > As (Arsenic) > Pb (Lead) > Co (Cobalt) > Mo (Molybdenum) > Cd (Cadmium). Silicon, Al, and Fe which are usually form the major components of soil minerals were present in much higher levels (91 to 308 mg/kg) than other elements in soil. Essential plant micronutrients such as B, Cu, Mn, Mo, and Zn, generally presented moderate levels in soil (7 to 698 µg/kg), whereas toxic heavy metals such as As, Cd, Co, Ni, and Pb were present in the lowest values (0.7–96.2 µg/kg). The ANOVA test indicated land use had significant effects on As, B, Cd, Co, Cu, Ni, and Si concentration in soil while effects were insignificant for other elements. The data proved the important effects of land use on dynamic soil properties as well as nutrient and heavy metal for a major benchmark soil. Thus, more studies on other major soils are warranted. The information is needed to modify and adapt management practices to improve and sustain soil health and water quality in the US Great Plains.     

Dryland agriculture and rangeland restoration priorities in Afghanistan

Afghanistan is threatened by rangeland degradation.A quantitative visual analysis of Google Earth Imagery was used to systematically locate,characterize and quantify the current extent of rangelands in Afghanistan degraded as a consequence of dryland agriculture.Climate data were used in conjunction with dryland agriculture locations to establish a climate envelope comprised by temperature and mean annual precipitation to create a geographical mask known to contain dryland agriculture.Within this mask we created a grid of 100 km2 cells that we analyzed individually to access dryland agriculture extent.Climatic limits to sustainable dryland agriculture and areas of high restoration priority were also assessed as was the distribution of rain-fed agriculture with respect to the location of traditional migration routes for extensive livestock producers.The extents of agriculture in Afghanistan,at both upper and lower elevations,correlated most closely with mean annual temperature(MAT) at the upper elevation limits,and with mean annual precipitation(MAP) at the lower elevation limits.In total,dryland agriculture comprised 38,980 km2 of former native rangeland.Conversion was highest in the northwestern,northern and northeastern provinces of Herat,Badghis,Faryab,Jawzjan,Sar-e-Pul,Samangan,Balkh,Baghlan,Kunduz,Takhar and Badakhshan,with the highest percentage of conversion occurring in Takhar.An MAP value of <400 mm is perceived by farmers as the current climatic limit to sustainable dryland agriculture across the northern regions of the country.Uder this MAP value,approximately 27,677 km2 of converted rangeland met the need for restoration priority.Climate projections indicate that Afghanistan will become warmer and drier in the coming decades.One consequence of this trend is that the MAP threshold of <400 mm to sustainable dryland agriculture will become obsolete in the coming decades.Restoration of currently converted rangelands is needed to restore critical grazing areas as is the adoption of prudent range management policies to prevent further land degradation and support a vital livestock industry.Food security is at stake as the conversion of rangelands to unsustainable rain-fed agriculture may leave large tracks of land unusable for either agriculture or livestock production.