Investigation of brix refractometry for estimating bovine colostrum immunoglobulin G concentration

Many dairy operations uses a Brix refractometer to assess the quality of first-milking colostrum. This study investigated whether a digital Brix refractometer could be used in a model to predict colostrum IgG concentration and whether more than one %Brix threshold could be used for different colostrum IgG concentrations. Colostrum from 182 animals was tested using a digital Brix refractometer and by single radial immunodiffusion. Statistical analysis, using simple linear regression to relate %Brix results with corresponding colostral IgG concentration, and receiver operating characteristic (ROC) analysis were used to identify %Brix cutoffs that had no false positive results. Colostral IgG concentrations from digital Brix refractometry had a R2 value of 0.818 and a S-value of 21.7 g/L. The large S-value shows that a digital Brix refractometer should not be used in a model to predict colostrum IgG concentration. However, %Brix scores of 19.0, 22.0, 25.0 and 30.0 percent can be used to estimate minimum colostral IgG concentrations of 25, 50, 75 and 100 g/L. These four cutoffs can be used to strategically feed smaller volumes of colostrum to newborn calves. Smaller volumes may reduce unwanted side effects and shorten the time interval in which calves refuse to nurse, while still delivering an adequate mass of IgG to have successful transfer of passive immunity

Human and biophysical influences on fire occurrence in the United States

National-scale analyses of fire occurrence are needed to prioritize fire policy and management activities across the United States. However, the drivers of national-scale patterns of fire occurrence are not well understood, and how the relative importance of human or biophysical factors varies across the country is unclear. Our research goal was to model the drivers of fire occurrence within ecoregions across the conterminous United States. We used generalized linear models to compare the relative influence of human, vegetation, climate, and topographic variables on fire occurrence in the United States, as measured by MODIS active fire detections collected between 2000 and 2006. We constructed models for all fires and for large fires only and generated predictive maps to quantify fire occurrence probabilities. Areas with high fire occurrence probabilities were widespread in the Southeast, and localized in the Mountain West, particularly in southern California, Arizona, and New Mexico. Probabilities for large-fire occurrence were generally lower, but hot spots existed in the western and southcentral United States The probability of fire occurrence is a critical component of fire risk assessments, in addition to vegetation type, fire behavior, and the values at risk. Many of the hot spots we identified have extensive development in the wildland–urban interface and are near large metropolitan areas. Our results demonstrated that human variables were important predictors of both all fires and large fires and frequently exhibited nonlinear relationships. However, vegetation, climate, and topography were also significant variables in most ecoregions. If recent housing growth trends and fire occurrence patterns continue, these areas will continue to challenge policies and management efforts seeking to balance the risks generated by wildfires with the ecological benefits of fire.Keywords: MODIS active fires, Wildfire risk, Wildland–urban interface, Fire occurrenc

Systematic Temporal Patterns in the Relationship Between Housing Development and Forest Bird Biodiversity

As people encroach increasingly on natural areas, one question is how this affects avian biodiversity. The answer to this is partly scale-dependent. At broad scales, human populations and biodiversity concentrate in the same areas and are positively associated, but at local scales people and biodiversity are negatively associated with biodiversity. We investigated whether there is also a systematic temporal trend in the relationship between bird biodiversity and housing development. We used linear regression to examine associations between forest bird species richness and housing growth in the conterminous United States over 30 years. Our data sources were the North American Breeding Bird Survey and the 2000 decennial U.S. Census. In the 9 largest forested ecoregions, housing density increased continually over time. Across the conterminous United States, the association between bird species richness and housing density was positive for virtually all guilds except ground nesting birds. We found a systematic trajectory of declining bird species richness as housing increased through time. In more recently developed ecoregions, where housing density was still low, the association with bird species richness was neutral or positive. In ecoregions that were developed earlier and where housing density was highest, the association of housing density with bird species richness for most guilds was negative and grew stronger with advancing decades. We propose that in general the relationship between human settlement and biodiversity over time unfolds as a 2-phase process. The first phase is apparently innocuous; associations are positive due to coincidence of low-density housing with high biodiversity. The second phase is highly detrimental to biodiversity, and increases in housing density are associated with biodiversity losses. The long-term effect on biodiversity depends on the final housing density. This general pattern can help unify our understanding of the relationship of human encroachment and biodiversity response.Keywords: Animals, Forest, Housing, Woodland, Functional groups, Temporal pattern, North America, Bird

ETHNOVETERINARY APPLICATION OF MORINDA CITRIFOLIA FRUIT PUREE ON A COMMERCIAL HEIFER REARING FACILITY WITH ENDEMIC SALMONELLOSIS

Abstract We have previously reported that Morinda citrifolia (noni) puree modulates neonatal calves developmental maturation of the innate and adaptive immune system. In this study, the effect of noni puree on respiratory and gastrointestinal (GI), health in preweaned dairy calves on a farm with endemic salmonellosis was examined. Two clinical trials were conducted whereby each trial evaluated one processing technique of noni puree. Trials 1 and 2 tested noni versions A and B, respectively. Puree analysis and trial methods were identical to each other, with the calf as the experimental unit. Calves were designated to 1 of 3 treatment groups in each trial and received either: 0, 15 or 30 mL every 12 hr of noni supplement for the first 3 weeks of life. Health scores, weaning age, weight gain from admission to weaning, and weaned by 6 weeks, were used as clinical endpoints for statistical analysis. In trial 1, calves supplemented with 15 mL noni puree of version A every 12 hr had a higher probability of being weaned by 6 weeks of age than control calves (P = 0.04). In trial 2, calves receiving 30 mL of version B every 12 hr had a 54.5% reduction in total medical treatments by 42 days of age when compared to controls (P = 0.02). There was a trend in reduced respiratory (61%), and GI (52%) medical treatments per calf when compared to controls (P = 0.06 and 0.08, respectively). There were no differences in weight gain or mortality for any treatment group in either trial

Pulmonary angiography with 64-multidetector-row computed tomography in normal dogs

Pulmonary angiography using 64-multidetector-row computed tomography (MDCT) was used to evaluate pulmonary artery anatomy, and determine the sensitivity of pulmonary artery segment visualization in four Beagle dogs using images reconstructed to 0.625 mm and retro-reconstructed to 1.25 and 2.5 mm slice thickness. Morphologically, characteristic features included a focal narrowing in the right cranial pulmonary artery in all dogs, which should not be mistaken as stenosis. While the right cranial pulmonary artery divided into two equally sized branches that were tracked into the periphery of the lung lobe in all dogs, only a single left cranial (cranial portion) lobar artery was present. Compared with 1.25 and 2.5 mm retro-reconstructions, 0.625 mm reconstructions allowed for detection of significantly (P ≤ 0.05) more pulmonary artery segments and sharper depiction of vessel margins. Clinical applications such as prevalence and significance of diameter changes, and detection of pulmonary arterial thrombembolism on lobar and sublobar level, using pulmonary angiography with 64-MDCT applying 0.625 mm reconstruction slice thickness remain to be established

Housing development erodes avian community structure in U.S. protected areas

Protected areas are a cornerstone for biodiversity conservation, but they also provide amenities that attract housing development on inholdings and adjacent private lands. We explored how this development affects biodiversity within and near protected areas among six ecological regions throughout the United States. We quantified the effect of housing density within, at the boundary, and outside protected areas, and natural land cover within protected areas, on the proportional abundance and proportional richness of three avian guilds within protected areas. We developed three guilds from the North American Breeding Bird Survey, which included Species of Greatest Conservation Need, land cover affiliates (e.g., forest breeders), and synanthropic species associated with urban environments. We gathered housing density data for the year 2000 from the U.S. Census Bureau, and centered the bird data on this year. We obtained land cover data from the 2001 National Land Cover Database, and we used single- and multiple-variable analyses to address our research question. In all regions, housing density within protected areas was positively associated with the proportional abundance or proportional richness of synanthropes, and negatively associated with the proportional abundance or proportional richness of Species of Greatest Conservation Need. These relationships were strongest in the eastern forested regions and the central grasslands, where more than 70% and 45%, respectively, of the variation in the proportional abundance of synanthropes and Species of Greatest Conservation Need were explained by housing within protected areas. Furthermore, in most regions, housing density outside protected areas was positively associated with the proportional abundance or proportional richness of synanthropes and negatively associated with the proportional abundance of land cover affiliates and Species of Greatest Conservation Need within protected areas. However, these effects were weaker than housing within protected areas. Natural land cover was high with little variability within protected areas, and consequently, was less influential than housing density within or outside protected areas explaining the proportional abundance or proportional richness of the avian guilds. Our results indicate that housing development within, at the boundary, and outside protected areas impacts avian community structure within protected areas throughout the United States

Monitoring the invasion of an exotic tree (\u3ci\u3eLigustrum lucidum\u3c/i\u3e) from 1983 to 2006 with Landsat TM/ETM + satellite data and Support Vector Machines in Córdoba, Argentina

In central Argentina, the Chinese tree glossy privet (Ligustrum lucidum) is an aggressive invasive species replacing native forests, forming dense stands, and is thus a major conservation concern. Mapping the spread of biological invasions is a necessary first step toward understanding the factors determining invasion patterns. Urban areas may function as propagule sources for glossy privet because it has been used as a landscaping tree for over a century. The objectives of this paperwere to 1)map the patterns of glossy privet expansion from1983 to 2006 using a time series of Landsat TM/ETM+images, and 2) analyze the spatial pattern of glossy privet standswith regard to urban extent. Using six summer Landsat TM images (1983, 1987, 1992, 1997, 2001, and 2006) the expansion of glossy privet was analyzed using Support Vector Machines (SVM), a non-parametric classifier which we applied to a stack of all images simultaneously, a novel approach in its application to monitor non-native tree invasions. Wethenmeasured the area of glossy privet in a series of 200-mbuffers at increasing distances around urban areas in 1983 and 2006, and compared itwith the amount of privet expected in proportion to buffer area. Glossy privet in the study area has spread very rapidly during the 23 years that we studied and the SVM resulted in highly accurate classifications (Kappa Index 0.88, commission error 0.07, omission error 0.16). Between 1983 and 2006 glossy privet area increased 50 times (from50 to 2500 ha), and 20% of all forest in the study area is nowdominated by glossy privet. Most of the glossy privet dominated stands were located within 600m of urban areas. However, the rate of glossy privet expansion accelerated substantially after 1992 and new glossy privet dominated stands tend to be located away from urban areas. This suggests that glossy privet is now self-sustaining, but expected urban growth in the area could further foster glossy privet invasion. Management and development plans should include mitigation efforts to contain this species and prevent invasion into native forests, and citizens should be informed about the risk of invasion associated with the use of glossy privet for landscaping

Image Texture Predicts Avian Density and Species Richness

<div><p>For decades, ecologists have measured habitat attributes in the field to understand and predict patterns of animal distribution and abundance. However, the scale of inference possible from field measured data is typically limited because large-scale data collection is rarely feasible. This is problematic given that conservation and management typical require data that are fine grained yet broad in extent. Recent advances in remote sensing methodology offer alternative tools for efficiently characterizing wildlife habitat across broad areas. We explored the use of remotely sensed image texture, which is a surrogate for vegetation structure, calculated from both an air photo and from a Landsat TM satellite image, compared with field-measured vegetation structure, characterized by foliage-height diversity and horizontal vegetation structure, to predict avian density and species richness within grassland, savanna, and woodland habitats at Fort McCoy Military Installation, Wisconsin, USA. Image texture calculated from the air photo best predicted density of a grassland associated species, grasshopper sparrow (<i>Ammodramus savannarum</i>), within grassland habitat (<i>R²</i> = 0.52, <i>p-value</i> <0.001), and avian species richness among habitats (<i>R²</i> = 0.54, <i>p-value</i> <0.001). Density of field sparrow (<i>Spizella pusilla</i>), a savanna associated species, was not particularly well captured by either field-measured or remotely sensed vegetation structure variables, but was best predicted by air photo image texture (<i>R²</i> = 0.13, <i>p-value</i> = 0.002). Density of ovenbird (<i>Seiurus aurocapillus</i>), a woodland associated species, was best predicted by pixel-level satellite data (mean NDVI, <i>R²</i> = 0.54, <i>p-value</i> <0.001). Surprisingly and interestingly, remotely sensed vegetation structure measures (i.e., image texture) were often better predictors of avian density and species richness than field-measured vegetation structure, and thus show promise as a valuable tool for mapping habitat quality and characterizing biodiversity across broad areas.</p></div

Appendix B. Logistic regressions for major species.

Logistic regressions for major species