Comparative enzyme activities and cytochrome P-450 levels of some rat tissues with respect to their metabolism of several pesticides

Cytochrome P-450, A- and B-esterase, amidase, and glutathione S-aryl transferase were assayed in the postmitochondrial centrifugal fraction, microsomes, and supernatant of rat liver, lungs, kidneys, and testes. Liver microsomes contained the highest P-450 levels and A-esterase activity. B-esterase activity was more generally distributed and higher in the microsomal tissue fractions. Microsomal amidase activity was highest in rat lung and lowest in the liver (per mg protein). Glutathione S-aryl transferase activity was highest in the liver. The in vitro metabolism of carbaryl, phosphamidon, and chlorotoluron by the various centrifugal fractions revealed many differences. Carbaryl metabolism was greater in the liver microsomal fractions than in any other preparation. 1-Naphthol was the major metabolite in all tissue fractions. Although very little metabolism of phosphamidon occurred in the rat, metabolism in the rat liver postmitochondrial fraction was slightly higher with respect to the production of metabolites than in the supernatant and microsomes combined. Chlorotoluron was not metabolized by any of the tissue fractions of the rat. At least a low level of activity toward some compounds was observed in all tissues, but this study confirmed that the liver was the most active metabolizing tissue as well as having the highest levels of enzymatic activity usually associated with pesticide metabolism.     

Geriatric heart diseases in dogs.

A discussion of the diagnosis and therapy of heart disease in an aged pet does not differ significantly from that in a pet of any age. Mitral regurgitation constitutes by far the most important geriatric heart disease, and the selection of drugs to treat heart disease of aging pets is based on identification of specific pathologic features (eg, atrial fibrillation, left atrial enlargement) for which each aspect of treatment (eg, diuretics, angiotensin-converting enzyme inhibitors, spironolactone) is specific.     

The influence of sampling scheme and interpolation method on the power to detect spatial effects of forest birds in Ontario (Canada)

Spatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches >10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences. This revised version was published online in July 2006 with corrections to the Cover Date.     

A leakiness index for assessing landscape function using remote sensing

The cover, number, size, shape, spatial arrangement and orientation of vegetation patches are attributes that have been used to indicate how well landscapes function to retain, not ‘leak’, vital system resources such as rainwater and soil. We derived and tested a directional leakiness index (DLI) for this resource retention function. We used simulated landscape maps where resource flows over map surfaces were directional and where landscape patch attributes were known. Although DLI was most strongly related to patch cover, it also logically related to patch number, size, shape, arrangement and orientation. If the direction of resource flow is multi-directional, a variant of DLI, the multi-directional leakiness index (MDLI) can be used. The utility of DLI and MDLI was demonstrated by applying these indices to three Australian savanna landscapes differing in their remotely sensed vegetation patch attributes. These leakiness indices clearly positioned these three landscapes along a function-dysfunction continuum, where dysfunctional landscapes are leaky (poorly retain resources). This revised version was published online in July 2006 with corrections to the Cover Date.     

Occurrence of Mirafiori Lettuce Virus and Lettuce Big-vein Virus in Relation to Development of Big-vein Symptoms in Lettuce Crops

Big-vein disease (BV) of lettuce has been attributed to infection by Lettuce big-vein virus (LBVV), vectored by the soil fungus Olpidium brassicae. The finding of a second soil-borne virus in lettuce, Mirafiori lettuce virus (MiLV), led to a re-investigation of the role of LBVV in big-vein disease, with evidence emerging that both MiLV and LBVV are vectored by O. brassicae, and that MiLV, not LBVV, is the cause of BV (Lot et al. (2002), Phytopathology 92: 288–293). The two viruses have coat proteins of similar size but have different morphologies and are serologically unrelated. We tested individual lettuce plants in BV-prone fields and protected crops in France and Italy for the presence of the two viruses, using DAS-ELISA and antisera specific for each virus. Both MiLV and LBVV were found at high incidence, often together but sometimes separately. Symptoms were frequently found to be associated with MiLV alone or both viruses, but rarely LBVV alone. However, no absolute correlation emerged, because sometimes MiLV was present in the absence of symptoms, and vice versa. To clarify the situation, individual lettuce plants were examined over a period of time in two further surveys. In surveys of protected crops in France, plants with big-vein were always ELISA-positive for MiLV, or else symptomless plants positive for MiLV were later seen to develop big-vein symptoms. Presence or absence of LBVV appeared to have no effect on symptom development. In surveys of open fields in Italy, all combinations were found: presence of both viruses, apparent absence of both viruses, or presence of each one alone, in plants that developed BV. At the end of the observation period, nearly all plants had BV and contained both viruses.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.