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.     

Oral eosinophilic granulomas in tigers (Panthera tigris)--a collection of 16 cases.

Oral eosinophilic granulomas were diagnosed in 16 tigers (Panthera tigris). All lesions were located on the hard or soft palate and typically consisted of flat or slightly raised circular ulcers. Histologic features of these lesions were essentially identical to those seen in oral eosinophilic granulomas of domestic cats and dogs. No clinical signs were noted in eight cases, though various degrees of inappetence, excessive salivation, and dysphagia were noted in the other eight tigers. Six cases were not treated. Treatment for the remaining 10 cases centered on corticosteroids and additional treatments included surgical removal, cryotherapy, antibiotics, and chlorpheniramine. Treatment with corticosteroids did appear to be effective in some cases, though lesions would worsen after cessation of therapy and no cases were cured. In addition, three cases developed complications possibly related to this corticosteroid therapy. The etiology of these lesions remains unknown, though an underlying allergic condition is likely.     

A streak disease of pearl millet caused by a leafhopper-transmitted geminivirus

The cause of a streak disease of pearl millet (Pennisetum glaucum), originating from Nigeria, has been attributed to a geminivirus belonging to the African streak virus cluster. A full-length, infectious clone of the virus was obtained which was transmissible by the vectorCicadulina mbila (Naudé). Analysis of the complete nucleotide sequence of the coat protein gene of this virus shows it to be most closely related to sugarcane streak virus. The possible evolutionary implications of this finding are discussed.     

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.