Satellite evidence of harmful algal blooms and related oceanographic features in the Bohai Sea during autumn 1998

Harmful algal blooms (HABs) are truly global marine phenomena of increasing significance. Some HAB occurrences are different to observe because of their high spatial and temporal variability and their advection, once formed, by surface currents. A serious HAB occurred in the Bohai Sea during autumn 1998, causing the largest fisheries economic loss. The present study analyzes the formation, distribution, and advection of HAB using satellite SeaWiFS ocean color data and other oceanographic data. The results show that the bloom originated in the western coastal waters of the Bohai Sea in early September, and developed southeastward when sea surface temperature (SST) increased to 25-26 °C. The bloom with a high Chl-a concentration (6.5 mg m-3) in center portion covered an area of 60 × 65 km2. At the end of September, the bloom decayed when SST decreased to 22-23 °C. The HAB may have been initiated by a combination of the river discharge nutrients in the west coastal waters and the increase of SST; afterwards it may have been transported eastward by the local circulation that was enhanced by northwesterly winds in late September and early October.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

High resolution satellite imagery and GPS collars can help assist in the assessment of patch selection by grazing cattle in semi-arid savannas.

The selection of different patch types for grazing by cattle in tropical savannas is well documented. Advances in high resolution satellite imagery and computing power now allow us to identify patch types over an entire paddock, combined with GPS collars as a non instrusive method of capturing positional data, an accurate and comprehensive picture of landscape use by cattle can be quantified.

Patch selection by cattle can be quantified using satellite imagery and GPS in extensive, semi-arid savannas.

Patch selection by grazing animals is difficult to quantify, particularly in large, extensive paddocks like those in northern Australia. However, advances in high resolution satellite imagery now allow identification of patch types over an entire paddock which combined with GPS collars to capture positional data, can give an accurate and comprehensive picture of landscape use by cattle.

Satellite Telemetry and Long-Range Bat Movements.

Background: Understanding the long-distance movement of bats has direct relevance to studies of population dynamics, ecology, disease emergence, and conservation. Methodology/Principal Findings: We developed and trialed several collar and platform terminal transmitter (PTT) combinations on both free-living and captive fruit bats (Family Pteropodidae: Genus Pteropus). We examined transmitter weight, size, profile and comfort as key determinants of maximized transmitter activity. We then tested the importance of bat-related variables (species size/weight, roosting habitat and behavior) and environmental variables (day-length, rainfall pattern) in determining optimal collar/PTT configuration. We compared battery- and solar-powered PTT performance in various field situations, and found the latter more successful in maintaining voltage on species that roosted higher in the tree canopy, and at lower density, than those that roost more densely and lower in trees. Finally, we trialed transmitter accuracy, and found that actual distance errors and Argos location class error estimates were in broad agreement. Conclusions/Significance: We conclude that no single collar or transmitter design is optimal for all bat species, and that species size/weight, species ecology and study objectives are key design considerations. Our study provides a strategy for collar and platform choice that will be applicable to a larger number of bat species as transmitter size and weight continue to decrease in the future.

A core metabolic enzyme mediates resistance to phosphine gas

Phosphine is a small redox-active gas that is used to protect global grain reserves, which are threatened by the emergence of phosphine resistance in pest insects. We find that polymorphisms responsible for genetic resistance cluster around the redox-active catalytic disulfide or the dimerization interface of dihydrolipoamide dehydrogenase (DLD) in insects (Rhyzopertha dominica and Tribolium castaneum) and nematodes (Caenorhabditis elegans). DLD is a core metabolic enzyme representing a new class of resistance factor for a redox-active metabolic toxin. It participates in four key steps of core metabolism, and metabolite profiles indicate that phosphine exposure in mutant and wild-type animals affects these steps differently. Mutation of DLD in C. elegans increases arsenite sensitivity. This specific vulnerability may be exploited to control phosphine-resistant insects and safeguard food security.

Development of a Rapid Multiplex PCR Assay To Genotype Pasteurella multocida Strains by Use of the Lipopolysaccharide Outer Core Biosynthesis Locus

Pasteurella multocida is a Gram-negative bacterial pathogen that is the causative agent of a wide range of diseases in many animal species, including humans. A widely used method for differentiation of P. multocida strains involves the Heddleston serotyping scheme. This scheme was developed in the early 1970s and classifies P. multocida strains into 16 somatic or lipopolysaccharide (LPS) serovars using an agar gel diffusion precipitin test. However, this gel diffusion assay is problematic, with difficulties reported in accuracy, reproducibility, and the sourcing of quality serovar-specific antisera. Using our knowledge of the genetics of LPS biosynthesis in P. multocida, we have developed a multiplex PCR (mPCR) that is able to differentiate strains based on the genetic organization of the LPS outer core biosynthesis loci. The accuracy of the LPS-mPCR was compared with classical Heddleston serotyping using LPS compositional data as the "gold standard." The LPS-mPCR correctly typed 57 of 58 isolates; Heddleston serotyping was able to correctly and unambiguously type only 20 of the 58 isolates. We conclude that our LPS-mPCR is a highly accurate LPS genotyping method that should replace the Heddleston serotyping scheme for the classification of P. multocida strains.

Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range

Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific. © 2015 Macmillan Publishers Limited.