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.     

Flow Cytometry Identification of X- and Y-Chromosome-Bearing Goat Spermatozoa

Flow cytometric sorting technology was used to measure the difference in DNA content between X- and Y-chromosome-bearing spermatozoa in bucks. Spermatozoa were analysed by flow cytometry to characterize X- and Y-chromosome-bearing sperm populations and to quantify the DNA difference between them. Two symmetrical, overlapping and clearly separated peaks, corresponding to X- and Y-bearing spermatozoa, were detected. The difference in fluorescence intensity between the peaks was 4.4 +/- 0.03% without any significant inter- or intra-animal variations. Therefore, the identification and selection of high-purity samples of sperm populations for sex sorting is easier in bucks compared with other domestic species.     

Review: The strobilurin fungicides

The original article to which this Correction refers was published in Pest Management Science 58 (7): 649–662 (2002).Copyright © 2004 Society of Chemical Industry     

Equine pituitary pars intermedia dysfunction: current understanding and recommendations from the Australian and New Zealand Equine Endocrine Group

The purpose of this article is to provide a review of the current knowledge and opinions about the epidemiology, clinical findings (including sequelae), diagnosis, treatment and monitoring of equine pituitary pars intermedia dysfunction, particularly in the Australian context. This information and the recommendations provided will assist practitioners in making informed decisions regarding the diagnosis and management of this disorder.     

Effect of bovine seminal plasma on bovine endometrial epithelial cells in culture

The purpose of this study was to investigate the effect of seminal plasma (SP) from bulls of known fertility on bovine endometrial epithelial cells (bEEC) in culture. The bEEC from passage 5, approximately 5.0–13 × 10⁵ cells per flask, were challenged with SP from bulls of high or low fertility (n = 3 and 2, respectively) or PBS (control), at 1% (75 μl) or 4% (300 μl) and were incubated for 72 hr (n = 13 per challenge). Total cell number and viability of bEEC after challenge with 1% SP from either high‐ or low‐fertility bulls (75H or 75L, respectively) did not differ from controls. In contrast, challenge with 4% of SP from high‐ or low‐fertility bulls (300H or 300L) negatively affected bEEC cell number and viability. Challenge with 300 L had a greater adverse effect than 300H. These results suggest that the negative effect of bovine SP on bEEC is both dose‐dependent and fertility‐dependent.     

A framework for evaluation of on-farm mastitis diagnostics in Australia

Numerous culture-based diagnostics are available on the Australian and international markets for on-farm detection of bacterial pathogens in milk. Use of such diagnostics may provide an opportunity to improve the prudent use of antimicrobials in udder health management. Farms are low-resource settings in terms of diagnostic microbiology capacity. The World Health Organisation has identified criteria for the evaluation of diagnostic tests in low resource settings based on Accuracy, Sensitivity, Specificity, User-friendliness, being Rapid or Robust, Equipment-free and being Deliverable (ASSURED). Here, we review how those criteria can be interpreted in the context of microbiological diagnosis of mastitis pathogens, and how on-farm diagnostics that are currently available in Australia perform relative to ASSURED criteria. This evaluation identifies multiple trade-offs, both with regard to scientific criteria and with regards to convenience criteria. More importantly, the purpose of testing may differ between farms, and test performance should be evaluated relative to its intended use. The ability of on-farm mastitis diagnostics to inform mastitis treatment decision-making in a timely and cost-effective manner depends not just on test characteristics but also on farm-specific pathogen prevalence, and on the farm enterprise's priorities and the farm manager's potential courses of action. With most assay evaluations to date conducted in professional laboratories, there is a surprising dearth of information on how well any of the diagnostic tests perform on-farm and, indeed, of the on-farm decision-making processes that they aim to inform.     

Recombinant gene expression in vivo within endothelial cells of the arterial wall

A technique for the transfer of endothelial cells and expression of recombinant genes in vivo could allow the introduction of proteins of therapeutic value in the management of cardiovascular diseases. Porcine endothelial cells expressing recombinant beta-galactosidase from a murine amphotropic retroviral vector were introduced with a catheter into denuded iliofemoral arteries of syngeneic animals. Arterial segments explanted 2 to 4 weeks later contained endothelial cells expressing beta-galactosidase, an indication that they were successfully implanted on the vessel wall.     

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.