A preliminary list of butterflies and skippers from the UWM Field Station

This preliminary list is a result of opportunistic collecting by staff members of the Milwaukee Public Museum\u27s Invertebrate Zoology Section at the UWM Cedar-Sauk Field Station during the past nine years. A total of 55 butterfly (Papilionoidea) and skipper (Hesperioidea) species have been collected in various habitats at the Field Station with one additional species, Lycaena epixanthe found in the Sapa-Black Spruce Bog. More intensive collecting should turn up additional species since the Field Station lies within the geographic ranges of over 90 butterflies and skippers according to recent distribution maps (Opler and Krizek, 1984; and Scott, 1986). Of course, specific habitat requirements and other factors will exclude some of these species from occurring at the site

Antithetic Conjuncts in Written English

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68390/2/10.1177_003368827901000204.pd

Interspecific variation and elevated CO2 influence the relationship between plant chemical resistance and regrowth tolerance

To understand how comprehensive plant defense phenotypes will respond to global change, we investigated the legacy effects of elevated CO2 on the relationships between chemical resistance (constitutive and induced via mechanical damage) and regrowth tolerance in four milkweed species (Asclepias). We quantified potential resistance and tolerance trade‐offs at the physiological level following simulated mowing, which are relevant to milkweed ecology and conservation. We examined the legacy effects of elevated CO2 on four hypothesized trade‐offs between the following: (a) plant growth rate and constitutive chemical resistance (foliar cardenolide concentrations), (b) plant growth rate and mechanically induced chemical resistance, (c) constitutive resistance and regrowth tolerance, and (d) regrowth tolerance and mechanically induced resistance. We observed support for one trade‐off between plant regrowth tolerance and mechanically induced resistance traits that was, surprisingly, independent of CO2 exposure. Across milkweed species, mechanically induced resistance increased by 28% in those plants previously exposed to elevated CO2. In contrast, constitutive resistance and the diversity of mechanically induced chemical resistance traits declined in response to elevated CO2 in two out of four milkweed species. Finally, previous exposure to elevated CO2 uncoupled the positive relationship between plant growth rate and regrowth tolerance following damage. Our data highlight the complex and dynamic nature of plant defense phenotypes under environmental change and question the generality of physiologically based defense trade‐offs.To understand how comprehensive plant defense phenotypes will respond to global change, we investigated the legacy effects of elevated CO2 on the relationships between chemical resistance and regrowth tolerance in four milkweed species (Asclepias). We found interspecific variation among milkweed species influenced the relationship between mechanically induced chemical resistance and regrowth tolerance. Previous exposure to elevated CO2 increased mechanically induced resistance by 28% and uncoupled the positive relationship between plant growth rate and regrowth tolerance following damage.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155974/1/ece36284_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155974/2/ece36284.pd

Mixture models for distance sampling detection functions

Funding: EPSRC DTGWe present a new class of models for the detection function in distance sampling surveys of wildlife populations, based on finite mixtures of simple parametric key functions such as the half-normal. The models share many of the features of the widely-used “key function plus series adjustment” (K+A) formulation: they are flexible, produce plausible shapes with a small number of parameters, allow incorporation of covariates in addition to distance and can be fitted using maximum likelihood. One important advantage over the K+A approach is that the mixtures are automatically monotonic non-increasing and non-negative, so constrained optimization is not required to ensure distance sampling assumptions are honoured. We compare the mixture formulation to the K+A approach using simulations to evaluate its applicability in a wide set of challenging situations. We also re-analyze four previously problematic real-world case studies. We find mixtures outperform K+A methods in many cases, particularly spiked line transect data (i.e., where detectability drops rapidly at small distances) and larger sample sizes. We recommend that current standard model selection methods for distance sampling detection functions are extended to include mixture models in the candidate set.Publisher PDFPeer reviewe

Evaluation of Filesystem Provenance Visualization Tools

Having effective visualizations of filesystem provenance data is valuable for understanding its complex hierarchical structure. The most common visual representation of provenance data is the node-link diagram. While effective for understanding local activity, the node-link diagram fails to offer a high-level summary of activity and inter-relationships within the data. We present a new tool, InProv, which displays filesystem provenance with an interactive radial-based tree layout. The tool also utilizes a new time-based hierarchical node grouping method for filesystem provenance data we developed to match the user’s mental model and make data exploration more intuitive. We compared InProv to a conventional node-link based tool, Orbiter, in a quantitative evaluation with real users of filesystem provenance data including provenance data experts, IT professionals, and computational scientists. We also compared in the evaluation our new node grouping method to a conventional method. The results demonstrate that InProv results in higher accuracy in identifying system activity than Orbiter with large complex data sets. The results also show that our new time- based hierarchical node grouping method improves performance in both tools, and participants found both tools significantly easier to use with the new time-based node grouping method. Subjective measures show that participants found InProv to require less mental activity, less physical activity, less work, and is less stressful to use. Our study also reveals one of the first cases of gender differences in visualization; both genders had comparable performance with InProv, but women had a significantly lower average accuracy (56%) compared to men (70%) with Orbiter.Engineering and Applied Science

MASS HINDLIMB DEFORMITIES OF GREEN FROGS (PELOPHYLAX ESCULENTUS COMPLEX) IN PRIDNESTROVIE: CAUSES AND BIOINDICATION

Mass hindlimb abnormalities (above 60 %) were found in twolocalities with syntopic Pelophylax ridibundus and hybridogenous P. esculentus in Pridnestrovie. Individually, frogs can have 1–7 anomalies in P. ridibundus and 2–4 in P. esculentus. Some diffe-rences in variety of deformities and their frequencies were observed between both species and both localities. Importantly, water bodies inhabited by green frogs with mass abnormalities were characterizedby absence of chemical pollution and any significant human impact.Массовые аномалии задних конечностей (свыше 60 %)были отмечены у синтопических Pelophylax ridibundus и гибридных P. esculentus в двух локалитетах в Приднестровье. Особь P. ridibundus может нести 1-7 аномалий, а P. esculentus – 2-4. Для обоих видов и локалитетов отмечены различия в вариантах аномалий и их частотах. Важно отметить, что водоемы, населенные лягушками с массовыми аномалиями, характеризовались отсутствием химического загрязнения и какого-либо существенного антропогенного воздействия

NetMets: software for quantifying and visualizing errors in biological network segmentation

One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization