Slope correction for LAI estimation from gap fraction measurements

Digital hemispherical photography poses specific problems when deriving leaf area index (LAI) over sloping terrain. This study proposes a method to correct from the slope effect. It is based on simple geometrical considerations to account for the path length variation within the canopy for cameras pointing vertically. Simulations over sloping terrain show that gap fraction increases up-slope while decreasing down-slope. As a consequence of this balance between up- and down-slope effects, effective LAI estimates derived from inversion of the Poisson model are marginally affected for low to medium slopes (<25°) and LAI (LAI < 2). However, for larger slopes and LAI values, estimated LAI values may be strongly underestimated. The proposed correction was evaluated over four forested sites located over sloping terrain. Results indicate that in these conditions (LAI between 0.6 up to 3.0, clumped canopies with relatively erectophile leaf distribution), the effect of the slope (between 25° and 36°) was moderate as compared to other potential sources of problems when deriving LAI from gap fraction measurements, including clumping, leaf angle inclination and spatial sampling.     

A bayesian approach to crop Model calibration under unknown error covariance

Bayesian methods seem well adapted to dynamic system models in general and to crop models in particular, because there is in general prior information about parameter values. The usefulness of a Bayesian approach has often been pointed out, but actual applications are rather rare. A major difficulty is including the elements of the covariance matrix of model errors in the treatment. We treat the specific case of balanced data and an unstructured covariance matrix. In our particular case this is a 3 × 3 matrix. We illustrate two methods for deriving a sample from the joint posterior density for the crop model parameters and the error covariance matrix parameters. The first method is based on importance sampling, the second on Metropolis within Gibbs sampling. We derive an instrumental density for the former and a proposal density for the latter which are adapted to this type of model and data. Both algorithms work well and they give very similar results. The example concerns a model for sunflowers during rapid leaf growth. The ultimate goal is to use the model as a decision aid in predicting disease risk.     

Detection of full and limited amphidromous migratory dynamics of fish in Caribbean rivers

All native fishes living in the Caribbean island rivers are considered diadromous but few species have been validated as diadromous. In Guadeloupe (Lesser Antilles) as well as in the other tropical islands, the riverine habitats are subject to strong anthropogenic pressure due to resource modifications or dams. The management of fish biodiversity requires knowledge concerning their life history traits and behaviour that are still unknown for most species at a local scale and at the whole distribution area of the species. In a Guadeloupe river, we inferred the migratory patterns of four freshwater fishes common to Caribbean rivers by the analysis of otolith microchemistry. We found two species Eleotris perniger (Eleotridae) and Sicydium plumieri (Gobiidae) to be completely amphidromous with a marine larval phase and a freshwater adult phase. Agonostomus monticola (Mugilidae) was also found to be amphidromous in this system. The fourth species Gobiesox cephalus (Gobiesocidae) showed elemental ratios suggesting an estuarine larval phase and was defined as “limited amphidromous”. The identification of such life history traits, with limited dispersion abilities, argues for specific management measures in tropical island rivers at a basin scale for the conservation of biodiversity.     

Improved visualization of the lumbar spine nerve roots in dogs using water excitation (ProSet) as opposed to short tau inversion recovery: A retrospective study of two fat suppression MRI sequences

Magnetic resonance imaging fat suppression techniques are commonly used for diagnosis of canine spinal disease, however, studies comparing different techniques are currently lacking. This retrospective, methods comparison study aimed to evaluate water excitation and STIR MRI pulse sequences for visualization of canine lumbar spinal nerve roots. For inclusion, all dogs had to have dorsal planar MRI studies of the lumbar spine using both sequences. Visual grading analysis was used for scoring the following five criteria: degree of fat suppression; nerve root visualization; subjective tissue contrast; presence of noise; and overall better image quality. Scores were independently recorded by three board‐certified veterinary radiologists on two separate occasions, 3‐6 weeks apart. A total of 90 dogs were sampled. A two‐tailed t‐test showed that there were significant differences in all scored parameters (P < 0.00001), with the exception of noise (P = 0.47343), and that the water excitation sequence scored higher in all cases excluding noise. A Gwets AC kappa for intraobserver and interobserver reliability showed “almost perfect” agreement for the nerve roots in both tests (intra: k = 0.88; inter: k = 0.90). Intraobserver agreement was “substantial” for the degree of fat suppression (k = 0.68), subjective tissue contrast (k = 0.75), and overall better image quality (k = 0.76) and it was “fair” for the noise (k = 0.46). Interobserver agreement was “moderate” for the degree of fat suppression (k = 0.53), subjective tissue contrast (k = 0.63), and overall better image quality (k = 0.66) and “slight” for noise (k = 0.25). These findings supported using the water excitation pulse sequence for fat‐suppressed MRI of canine lumbar spinal nerve roots.     

Low prevalence of zoonotic multidrug‐resistant bacteria in veterinarians in a country with prudent use of antimicrobials in animals

The occurrence of multidrug‐resistant zoonotic bacteria in animals has been increasing worldwide. Working in close contact with livestock increases the risk of carriage of these bacteria. We investigated the occurrence of extended‐spectrum beta‐lactamase (ESBL) and plasmidic AmpC beta‐lactamase producing Enterobacteriaceae (ESBL/pAmpC‐PE) and livestock‐associated methicillin‐resistant Staphylococcus aureus (LA‐MRSA) in Finnish veterinarians (n = 320). In addition to microbiological samples, background information was collected. Bacterial whole genome sequencing was performed to deduce sequence types (STs), spa types and resistance genes of the isolates. In total, 3.0% (9/297) of the veterinarians carried ESBL producing Escherichia coli, with one ESBL producing E. coli isolate producing also AmpC. Seven different STs, sequences of several different plasmid groups as well as several different bla_ESBL/pAmpC genes existed in different combinations. No carbapenemase or colistin resistance genes were detected. MRSA was detected in 0.3% (1/320) of the samples. The strain belonged to LA‐MRSA clonal complex (CC) 398 (ST398, spa type 011, lacking Panton‐Valentine leukocidin genes). In conclusion, this study shows low carriage of multidrug‐resistant zoonotic bacteria in Finnish veterinarians. However, finding LA‐MRSA for the first time in a sample from a veterinarian in a country with prudent use of animal antimicrobials and regarding the recent rise of LA‐MRSA on Finnish pig farms, a strong recommendation to protect people working in close contact with animals carrying LA‐MRSA CC398 is given. Further studies are needed to explain why the prevalence of LA‐MRSA in veterinarians is lower in Finland than in other European countries.     

Phytomass estimation using eMODIS NDVI and ground data in arid rangelands of Morocco

The assessment of rangeland productivity in semi-extensively grazed arid rangelands is a prerequisite for livestock management in relation to sustainable use of pastoral resources. The objective of this study was to assess rangeland productivity based on normalised difference vegetation index (NDVI) images. Data on phytomass were measured on 61 field samples in arid rangelands of Morocco, covering various rangeland categories during autumn (November) and spring (April), i.e. when phytomass is at low and high levels, respectively, for two consecutive years (2008 and 2009). Dekadal EROS Moderate Resolution Imaging Spectroradiometer (eMODIS) NDVI data were linearly regressed to field measurements for these four periods. Results show that phytomass values were correlated with NDVI during spring, with R² and RMSE values of 0.82 and 0.3 t ha^?1, respectively. This study indicates there is a high potential for operational use of remotely sensed data to estimate rangeland phytomass of semi-extensively grazed rangelands.