A Lack of "Environmental Earth Data" at the Microhabitat Scale Impacts Efforts to Control Invasive Arthropods That Vector Pathogens

We currently live in an era of major global change that has led to the introduction and range expansion of numerous invasive species worldwide. In addition to the ecological and economic consequences associated with most invasive species, invasive arthropods that vector pathogens (IAVPs) to humans and animals pose substantial health risks. Species distribution models that are informed using environmental Earth data are frequently employed to predict the distribution of invasive species, and to advise targeted mitigation strategies. However, there are currently substantial mismatches in the temporal and spatial resolution of these data and the environmental contexts which affect IAVPs. Consequently, targeted actions to control invasive species or to prepare the population for possible disease outbreaks may lack efficacy. Here, we identify and discuss how the currently available environmental Earth data are lacking with respect to their applications in species distribution modeling, particularly when predicting the potential distribution of IAVPs at meaningful space-time scales. For example, we examine the issues related to interpolation of weather station data and the lack of microclimatic data relevant to the environment experienced by IAVPs. In addition, we suggest how these data gaps can be filled, including through the possible development of a dedicated open access database, where data from both remotely- and proximally-sensed sources can be stored, shared, and accessed

Positional errors in species distribution modelling are not overcome by the coarser grains of analysis

The performance of species distribution models (SDMs) is known to be affected by analysis grain and positional error of species occurrences. Coarsening of the analysis grain has been suggested to compensate for positional errors. Nevertheless, this way of dealing with positional errors has never been thoroughly tested. With increasing use of fine-scale environmental data in SDMs, it is important to test this assumption. Models using fine-scale environmental data are more likely to be negatively affected by positional error as the inaccurate occurrences might easier end up in unsuitable environment. This can result in inappropriate conservation actions. Here, we examined the trade-offs between positional error and analysis grain and provide recommendations for best practice. We generated narrow niche virtual species using environmental variables derived from LiDAR point clouds at 5 x 5 m fine-scale. We simulated the positional error in the range of 5 m to 99 m and evaluated the effects of several spatial grains in the range of 5 m to 500 m. In total, we assessed 49 combinations of positional accuracy and analysis grain. We used three modelling techniques (MaxEnt, BRT and GLM) and evaluated their discrimination ability, niche overlap with virtual species and change in realized niche. We found that model performance decreased with increasing positional error in species occurrences and coarsening of the analysis grain. Most importantly, we showed that coarsening the analysis grain to compensate for positional error did not improve model performance. Our results reject coarsening of the analysis grain as a solution to address the negative effects of positional error on model performance. We recommend fitting models with the finest possible analysis grain and as close to the response grain as possible even when available species occurrences suffer from positional errors. If there are significant positional errors in species occurrences, users are unlikely to benefit from making additional efforts to obtain higher resolution environmental data unless they also minimize the positional errors of species occurrences. Our findings are also applicable to coarse analysis grain, especially for fragmented habitats, and for species with narrow niche breadth

Fat patterning of adolescents: Allometry of fatfolds

The relationship between fatfold thickness and fat mass of 101 male and 66 female adolescents (10–16 yr) was examined with the allometric equation y = bx a . Body composition was assessed by underwater weighing and 5 fatfolds were measured: triceps, subscapular, suprailiac, abdominal, and thigh. Percent body fat ranged from 4.9% to 56.1%. The log of each fatfold thickness was plotted versus the log of fat mass. All the relationships were linear and exhibited monophasic allometry. All the alpha coefficients (slope of the log-log plots) exhibited positive allometry. The prepubescent male and female alphas were similar and had the same pattern. The pattern contrasted the trunk with the extremity fatfolds. No differences ( P > .05) were found between the alphas for the pubescent males. The triceps alpha of the pubescent females was less ( P .05) different. In conclusion, the trunk was the predominant site of subcutaneous fat deposition for prepubescents, while pubescents exhibit a more general pattern of fat distribution. © 1992 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38553/1/1310040411_ftp.pd

Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward

Ecosystem structure, especially vertical vegetation structure, is one of the six essential biodiversity variable classes and is an important aspect of habitat heterogeneity, affecting species distributions and diversity by providing shelter, foraging, and nesting sites. Point clouds from airborne laser scanning (ALS) can be used to derive such detailed information on vegetation structure. However, public agencies usually only provide digital elevation models, which do not provide information on vertical vegetation structure. Calculating vertical structure variables from ALS point clouds requires extensive data processing and remote sensing skills that most ecologists do not have. However, such information on vegetation structure is extremely valuable for many analyses of habitat use and species distribution. We here propose 10 variables that should be easily accessible to researchers and stakeholders through national data portals. In addition, we argue for a consistent selection of variables and their systematic testing, which would allow for continuous improvement of such a list to keep it up-to-date with the latest evidence. This initiative is particularly needed not only to advance ecological and biodiversity research by providing valuable open datasets but also to guide potential users in the face of increasing availability of global vegetation structure products

MRI of surgically created pulmonary artery narrowing in the dog

Narrowing of the pulmonary arteries was created surgically in twelve dogs. In six of the dogs the narrowing was central (main pulmonary artery), and in the remaining six the narrowing was located peripherally at the hilar level of the right pulmonary artery beyond the pericardial reflection. MRI and angiography were performed in all dogs. MRI clearly delineated the site of the pulmonary band and the caliber of the pulmonary artery at the site of the band in all dogs ( N =6). MRI was not able to visualize any of the stenosis of the right pulmonary arteries at the hila, beyond the pericardial reflection. In addition, optimal imaging planes to depict each segment of the central pulmonary arteries were determined. The capability to image in oblique planes is essential in evaluating the morphology of the central pulmonary arteries.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46691/1/247_2005_Article_BF02010634.pd

Role for aldosterone in blood pressure regulation of obese adolescents

To determine the role of aldosterone in the regulation of blood pressure (BP) in obese adolescents, supine and 2-hour upright plasma renin activity (PRA), and aldosterone and cortisol were measured in 10 nonobese and 30 obese adolescents before and after a 20-week weight loss program. The obese adolescents had significantly higher supine and 2-hour upright plasma aldosterone concentrations (17 +/- 8 vs 6 +/- 2 ng/dl [p < 0.01 supine obese vs nonobese] and 30 +/- 11 vs 14 +/- 8 ng/dl [p < 0.01 2-hour upright]). Although PRA was not significantly different between the 2 groups of children, a given increment in PRA produced a greater increment in aldosterone in the obese adolescents. In addition, obese subjects had a significantly increased mean BP (93 +/- 12 vs 74 +/- 8, p < 0.005) and a weak correlation between BP and plasma aldosterone concentration. Compared with an obese control group, weight loss resulted in a significant decrease in plasma aldosterone (p < 0.01) without an associated decrease in PRA. After weight loss there was also a significant decrease in the slope of the posture-induced relation between PRA and aldosterone. In addition to weight loss being associated with a significant decrease in BP (p < 0.01), there was a significant correlation between the change in plasma aldosterone and the change in mean BP (r = 0.538; p < 0.002 change in upright aldosterone vs change in mean BP). Obese adolescents have an increased plasma aldosterone concentration that may be important in the regulation of their BP.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26170/1/0000247.pd

Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns

Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive to colour palette selection. The aim of this paper is to present the cblindplot R package and its founding function - cblind.plot() - which enables colour blind people to just enter an image in a coding workflow, simply set their colour blind deficiency type, and immediately get as output a colour blind friendly plot. We will first describe in detail colour blind problems, and then show a step by step example of the function being proposed. While examples exist to provide colour blind people with proper colour palettes, in such cases (i) the workflow include a separate import of the image and the application of a set of colour ramp palettes and (ii) albeit being well documented, there are many steps to be done before plotting an image with a colour blind friendly ramp palette. The function described in this paper, on the contrary, allows to (i) automatically call the image inside the function without any initial import step and (ii) explicitly refer to the colour blind deficiency type being experienced, to further automatically apply the proper colour ramp palette

Basal metabolism of obese adolescents: Evidence for energy conservation compared to normal and lean adolescents

To test if obese adolescents systematically conserve energy, comparisons of basal metabolic rate (BMR) of obese, normal, and lean male and female adolescents were made. Obese had eleevated values by as much as 23% ( P ≤ 0.05) expressed as kJ · 24 hr −1 compared to the normal and lean. When indexed to body mass (kJ · kg-BM −1 · hr −1 ), the BMR for the obese was depressed by as much as −53% ( P ≤ 0.01), and when indexed to fat free mass (kJ · kg-FFM −1 · hr −1 ) it was depressed by −33% compared to normal and lean adolescents. A “theoretical metabolic rate” (TMR), based on the observed fat free mass, fat mass, and their thermal equivalents, was proposed as a theoretical way to properly index basal metabolism, referenced to body composition. Comparisons of the TMR between the obese, normal, and lean revealed that the obese values were depressed by an average −22% ( P ≤ 0.05). In comparison, differences in TMR between the normal and lean males and females were no larger than 8% (ns). It was concluded that since both the observed BMR (expressed relative to body composition), and the derived TMR values were depressed for the obese compared to the normal and lean adolescent, the data suggest an energy saving hypothesis for obese adolescents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/38546/1/1310020510_ftp.pd

Preconditioning 2D integer data for fast convex hull computations

In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ? n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ? n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ? n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved