Land cover types of the Las Vegas Wash, Nevada

Vegetation type, extent, continuity, and structure are some of the most important factors that determine wildlife diversity and distribution. Other contributing factors that shape wildlife communities include disturbance, competition, climate, and water availability. Because vegetation communities in the southwestern U.S. gradate sharply along zones of soil moisture, wildlife are often restricted to specific vegetation types. Along the Las Vegas Wash (Wash), Nevada, more than 250 wildlife species have been documented to occur in distinct wetland, riparian, and upland vegetation types. Recent studies have investigated the diversity and distribution of amphibians, birds, fishes, mammals, and reptiles (Shanahan 2005, 2005a, Van Dooremolen 2005, O\u27Farrell and Shanahan 2006, Larkin 2006). Moreover, focused surveys for the endangered southwestern willow flycatcher (Empidonax traillii extimus) and Yuma clapper rail (Rallus longirostris yumanensis) have been conducted since as early as 1998 (SWCA 1998, 1999, 2000, 2001, 2002, 2003, 2005, 2006; McKernan and Braden 2001, 2002). Field surveys have concluded that wildlife habitats are improving. Habitat analyses are integral components of the biological surveys that are conducted in the Wash. Because survey locations are finite, however, vegetation descriptions are often spatially limited. Vegetative communities described from a landscape perspective are helpful to understand the landscape structure and its effects on the distribution and abundance of organisms. The Las Vegas Wash Coordination Committee, a multi-stakeholder collaborative planning group, has been facilitating biological resource inventories and ecological improvements along the Wash for the past several years. Besides the wildlife studies previously described, on the ground activities have included constructing multiple erosion control structures and stream bank protection facilities. Moreover, extensive revegetation projects have been completed to further protect the channel bed and banks from eroding as well as to improve wildlife habitat values. These activities are directed by a planning document that was completed in 2000, the Las Vegas Wash Comprehensive Adaptive Management Plan (CAMP). Among the action items that were listed in the CAMP was a recommendation to prepare a long-term wildlife management plan for the Wash, which is currently underway (Shanahan et al. 2007). In order for wildlife management planning to be successful, however, the availability and extent of wildlife habitats must be considered. Often, wildlife management is effectively accomplished by focusing management recommendations towards habitats. The goal for this study is to identify and delineate land cover types along the Wash with specific attention given to vegetated cover types (i.e., vegetation communities). Vegetation communities are described by using standardized vegetation classifications (Association for Biodiversity Information 2001), Geographic Information System (GIS) technologies, and appropriate ecological methodologies (e.g., Barbour et al. 1999, Mueller-Dombois and Ellenberg 1974). This study provides a critical catalog of vegetative communities along the Wash using a repeatable standardized nomenclature. This study was conducted to facilitate wildlife management planning along the Wash (Shanahan et al. 2007), however, ecosystem restoration initiatives (Kloeppel et al. 2006, Bickmore 2003) were intended to benefit from these data as well. Specifically important land cover classifications, such as wetlands, are also presented to help plan for and meet long-term management goals along the Wash

A survey of statistical network models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference

Financial Technology For SMEs Capital Problems With Crowdfunding Method

This study motivated by Micro, Small, and Medium Enterprises (SMEs) problem. SMEs still have difficulty accessing financial institutions. This problem should overcome when SMEs utilize information technology in business management such as crowdfunding features through Financial technology, where crowdfunding has known as a funding offering facility for social interests. The study is a qualitative descriptive analysis. This study intended to decide how to use crowdfunding-based financial technology by SME's at Tarakan City. The experiment subject is a randomized participant of 15 participants based on a predetermined category faced with stakeholders SME’s at Tarakan City. The data consisted of primary data non-metric or qualitative data. Participants were interviewed and examined to learn about the use of crowdfunding-based financial technology by small and medium-sized companies in Tarakan City, followed by triangulation with three models, i.e. data triangulation, investigator triangulation, and methods triangulation. Then analyzed with an interactive model through data reduction, data display, and conclusion drawing procedures. The result of the research shows that from the 15 informants in this study, there were only two informants who knew about Financial technology, and only a small proportion of SMEs at Tarakan City able to utilize Financial technology based on crowdfunding for their funding needs and use crowdfunding for working capital

Proceedings of the 8th Cologne-Twente Workshop on Graphs and Combinatorial Optimization

International audienceThe Cologne-Twente Workshop (CTW) on Graphs and Combinatorial Optimization started off as a series of workshops organized bi-annually by either Köln University or Twente University. As its importance grew over time, it re-centered its geographical focus by including northern Italy (CTW04 in Menaggio, on the lake Como and CTW08 in Gargnano, on the Garda lake). This year, CTW (in its eighth edition) will be staged in France for the first time: more precisely in the heart of Paris, at the Conservatoire National d’Arts et Métiers (CNAM), between 2nd and 4th June 2009, by a mixed organizing committee with members from LIX, Ecole Polytechnique and CEDRIC, CNAM

Protein quality as a complementary functional unit in life cycle assessment (LCA)

Goal and theoretical commentary A number of recent life cycle assessment (LCA) studies have concluded that animal-sourced foods should be restricted—or even avoided—within the human diet due to their relatively high environmental impacts (particularly those from ruminants) compared with other protein-rich foods (mainly protein-rich plant foods). From a nutritional point of view, however, issues such as broad nutrient bioavailability, amino acid balances, digestibility and even non-protein nutrient density (e.g., micronutrients) need to be accounted for before making such recommendations to the global population. This is especially important given the contribution of animal sourced foods to nutrient adequacy in the global South and vulnerable populations of high-income countries (e.g., children, women of reproductive age and elderly). Often, however, LCAs simplify this reality by using ‘protein’ as a functional unit in their models and basing their analyses on generic nutritional requirements. Even if a ‘nutritional functional unit’ (nFU) is utilised, it is unlikely to consider the complexities of amino acid composition and subsequent protein accretion. The discussion herein focuses on nutritional LCA (nLCA), particularly on the usefulness of nFUs such as ‘protein,’ and whether protein quality should be considered when adopting the nutrient as an (n)FU. Further, a novel and informative case study is provided to demonstrate the strengths and weaknesses of protein-quality adjustment. Case study methods To complement current discussions, we present an exploratory virtual experiment to determine how Digestible Indispensable Amino Acid Scores (DIAAS) might play a role in nLCA development by correcting for amino acid quality and digestibility. DIAAS is a scoring mechanism which considers the limiting indispensable amino acids (IAAs) within an IAA balance of a given food (or meal) and provides a percentage contribution relative to recommended daily intakes for IAA and subsequent protein anabolism; for clarity, we focus only on single food items (4 × animal-based products and 4 × plant-based products) in the current case exemplar. Further, we take beef as a sensitivity analysis example (which we particularly recommend when considering IAA complementarity at the meal-level) to elucidate how various cuts of the same intermediary product could affect the interpretation of nLCA results of the end-product(s). Recommendations First, we provide a list of suggestions which are intended to (a) assist with deciding whether protein-quality correction is necessary for a specific research question and (b) acknowledge additional uncertainties by providing mitigating opportunities to avoid misinterpretation (or worse, dis-interpretation) of protein-focused nLCA studies. We conclude that as relevant (primary) data availability from supply chain ‘gatekeepers’ (e.g., international agri-food distributors and processors) becomes more prevalent, detailed consideration of IAA provision of contrasting protein sources needs to be acknowledged—ideally quantitatively with DIAAS being one example—in nLCA studies utilising protein as a nFU. We also contend that future nLCA studies should discuss the complementarity of amino acid balances at the meal-level, as a minimum, rather than the product level when assessing protein metabolic responses of consumers. Additionally, a broader set of nutrients should ideally be included when evaluating “protein-rich foods” which provide nutrients that extend beyond amino acids, which is of particular importance when exploring dietary-level nLCA

A Survey of Statistical Network Models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active “network community” and a substantial liter- ature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning net- work literature in statistical physics and computer science. The growthof the World Wide Web and the emergence of online “networking com- munities” such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize for- mal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Statistic

Assessing the natural range of variability in minimally disturbed wetlands across the Rocky Mountains: the Rocky Mountain ReMAP Project

Prepared for: the U.S. Environmental Protection Agency.Includes bibliographical references (pages 35-40).In Montana, Wyoming, Colorado and Utah, extremes of mountain climate, high elevations and characteristic geology produce a large range of natural variability within ecological systems. Even under minimal human disturbance regimes, environmental gradients can result in wetlands with very low vegetation cover, low species diversity and unpredictable hydrologic shifts. Documenting the range of variability found under minimally disturbed conditions can help distinguish signal from noise when assessing more altered occurrences, and aid in the calibration of assessment metrics. The project was a collaboration between the Montana Natural Heritage Program (MTNHP), the Colorado Natural Heritage Program (CNHP) and the Wyoming Natural Diversity Database (WYNDD). It had three objectives:1) identify reference standards for four wetland ecological systems across four Rocky Mountain ecoregions; 2) assess the range of natural variability of these ecological systems; and3) produce a regionally standardized Level 1,2 and 3 method for assessing and monitoring wetland condition, including quality assurance project plans, sampling strategies, and metrics calibrated to the four different wetland ecological systems. This report summarizes our approach, activities, and conclusions