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A bootstrap estimation scheme for chemical compositional data with nondetects

The bootstrap method is commonly used to estimate the distribution of estimators and their associated uncertainty when explicit analytic expressions are not available or are difficult to obtain. It has been widely applied in environmental and geochemical studies, where the data generated often represent parts of whole, typically chemical concentrations. This kind of constrained data is generically called compositional data, and they require specialised statistical methods to properly account for their particular covariance structure. On the other hand, it is not unusual in practice that those data contain labels denoting nondetects, that is, concentrations falling below detection limits. Nondetects impede the implementation of the bootstrap and represent an additional source of uncertainty that must be taken into account. In this work, a bootstrap scheme is devised that handles nondetects by adding an imputation step within the resampling process and conveniently propagates their associated uncertainly. In doing so, it considers the constrained relationships between chemical concentrations originated from their compositional nature. Bootstrap estimates using a range of imputation methods, including new stochastic proposals, are compared across scenarios of increasing difficulty. They are formulated to meet compositional principles following the log-ratio approach, and an adjustment is introduced in the multivariate case to deal with nonclosed samples. Results suggest that nondetect bootstrap based on model-based imputation is generally preferable. A robust approach based on isometric log-ratio transformations appears to be particularly suited in this context. Computer routines in the R statistical programming language are provided.

Journal of Chemometrics

Titanium 2013

Titanium is the ninth most abundant element in the earth's crust and can be found in nearly all rocks and sediments. It is a lithophile element with a strong affinity for oxygen and is not found as a pure metal in nature. Titanium was first isolated as a pure metal in 1910, but it was not until 1948 that the metal was produced commercially using the Kroll process (named after its developer, William Kroll) to reduce titanium tetrachloride with magnesium to produce titanium metal.

Mining Engineering

On estimating the economic value of insectivorous bats: Prospects and priorities for biologists

Bats are among the most economically important nondomesticated mammals in the world. They are well-known pollinators and seed dispersers, but crop pest suppression is probably the most valuable ecosystem service provided by bats. Scientific literature and popular media often include reports of crop pests in the diet of bats and anecdotal or extrapolated estimates of how many insects are eaten by bats. However, quantitative estimates of the ecosystem services provided by bats in agricultural systems are rare, and the few estimates that are available are limited to a single cotton-dominated system in Texas. Despite the tremendous value for conservation and economic security of such information, surprisingly few scientific efforts have been dedicated to quantifying the economic value of bats. Here, we outline the types of information needed to better quantify the value of bats in agricultural ecosystems. Because of the complexity of the ecosystems involved, creative experimental design and innovative new methods will help advance our knowledge in this area. Experiments involving bats in agricultural systems may be needed sooner than later, before population declines associated with white-nose syndrome and wind turbines potentially render them impossible.

Book chapter

Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems

Hydrogeomorphic, vegetative, and biogeochemical processes interact in floodplains resulting in great complexity that provides opportunities to better understand linkages among physical and biological processes in ecosystems. Floodplains and their associated river systems are structured by four dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depends on improved understanding and predictive models of interactive system controls and behavior.

Book chapter

Assessment of the NASA-USGS Global Land Survey (GLS) Datasets

The Global Land Survey (GLS) datasets are a collection of orthorectified, cloud-minimized Landsat-type satellite images, providing near complete coverage of the global land area decadally since the early 1970s. The global mosaics are centered on 1975, 1990, 2000, 2005, and 2010, and consist of data acquired from four sensors: Enhanced Thematic Mapper Plus, Thematic Mapper, Multispectral Scanner, and Advanced Land Imager. The GLS datasets have been widely used in land-cover and land-use change studies at local, regional, and global scales. This study evaluates the GLS datasets with respect to their spatial coverage, temporal consistency, geodetic accuracy, radiometric calibration consistency, image completeness, extent of cloud contamination, and residual gaps. In general, the three latest GLS datasets are of a better quality than the GLS-1990 and GLS-1975 datasets, with most of the imagery (85%) having cloud cover of less than 10%, the acquisition years clustered much more tightly around their target years, better co-registration relative to GLS-2000, and better radiometric absolute calibration. Probably, the most significant impediment to scientific use of the datasets is the variability of image phenology (i.e., acquisition day of year). This paper provides end-users with an assessment of the quality of the GLS datasets for specific applications, and where possible, suggestions for mitigating their deficiencies.

Remote Sensing of Environment

Molecular techniques to distinguish morphologically similar Hydrilla verticillata , Egeria densa , Elodea nuttallii , and Elodea canadensis

The four submerged aquatic species, hydrilla (Hydrilla verticillata [monoecious and dioecious]), Brazilian waterweed (Egeria densa), Canadian waterweed (Elodea canadensis), and western waterweed (Elodea nuttallii), are difficult to positively identify because of their morphological similarity to each other, resulting in possible misidentification. This limits our ability to understand their past and present distribution, which is important in aquatic plant management. We investigated a molecular technique to identify these species, which are problematic because of their invasive nature on multiple continents. Approximately 100 samples of these species, ranging in age from 40-yr-old herbarium samples to recently collected plants, were collected from regions across the United States. The distribution and range of the samples collected in this research were compared to those reported in the literature. We confirmed information on the current wide distribution of both hydrilla biotypes in the United States and discovered that hydrilla had actually invaded the waterways near Washington, DC 6 yr earlier than originally reported. In addition, we found evidence of the confusion, dating back to the 1980s, between Canadian waterweed and western waterweed in the mid-Atlantic region of the United States. Canadian waterweed was previously reported as common and western waterweed as rare; however, our samples indicate the opposite is true. This information indicates there is a need for investigators to anticipate the spread of hydrilla populations to northern U.S. waterways, where it will compete with existing plant species, including Canadian and western waterweeds. Our ability to confirm distribution and pace of spread of invasive and noninvasive species will improve with increased application of molecular techniques.

Journal of Aquatic Plant Management

Priority data on marine and estuarine resources within northeastern National Parks: Inventory and acquisition needs

The purpose of this project was to guide development of a strategy for the inventory and mapping of submerged natural resources associated within 10 coastal parks of the National Park Service (NPS) Northeast Region (NER; see Table 1). Priority data needs were identified by the NER Ocean Stewardship Task Force. The majority of the NER priority data needs involve the biotic, chemical, and geological characterization of the seabed. Taken collectively, this demands a consistent and unified approach to habitat classification. The Coastal and Marine Ecological Classification Standard (CMECS) is endorsed by the Federal Geographic Data Committee (FGDC-STD-018) for classifying ecological units in coastal and marine environments, and is recommended as a framework for acquiring and organizing NER data. We prepared an inventory of existing data on priority marine and estuarine natural resources within the ten NER coastal parks. This report describes the data and information sources relevant to each park and identifies gaps in available data. Overwhelmingly and uniformly across all parks, the most pressing needs are consistent, high-resolution bathymetry and seafloor characterization data. Approaches for acquiring these data using an integrated, multi-resolution sampling framework are recommended.

Natural Resource Report

International summit on integrated environmental modeling

This report describes the International Summit on Integrated Environmental Modeling (IEM), held in Reston, VA, on 7th-9th December 2010. The meeting brought together 57 scientists and managers from leading US and European government and non-governmental organizations, universities and companies together with international organizations convened over a number of years, including: the US Environmental Protection Agency (USEPA) workshop on Collaborative Approaches to Integrated Modeling: Better Integration for Better Decisionmaking (December, 2008); the AGU Fall Meeting, San Francisco (December 2009); and the International Congress on Environmental Modeling and Software (July 2010). From these meetings there is now recognition that many separate communities are involved in developing IEM. The aim of the Summit was to bring together two key groupings, the US and Europe, with the intention of creating a community open to all.

Conference Paper

Conservation in an age of climate change

Are you a gardener? Then you know that certain species and varieties of species grow best in certain growing zones related to climate. This growing zone concept also applies to species in natural ecosystems. One threat of climate change to wetland biodiversity is that some species may be losing the ability to track an appropriate season for flowering, seed production and growth, impairing their ability to regenerate. Based on genetic constraints, such species may have a limited ability to adjust to changing climates. For biodiversity conservation to be successful in the future, the first order of business is to formulate the goals of such projects regardless of philosophical differences in approaches. If the real goal is to conserve species, then conservation planners may need to put all management options on the table. Despite the uncertainties, with the risk of species losses so imminent, the best strategy may be to throw any dogmatism out the window and use multiple approaches.

National Wetlands Newsletter

Sensitivity of spring phenology to warming across temporal and spatial climate gradients in two independent databases

Disparate ecological datasets are often organized into databases post hoc and then analyzed and interpreted in ways that may diverge from the purposes of the original data collections. Few studies, however, have attempted to quantify how biases inherent in these data (for example, species richness, replication, climate) affect their suitability for addressing broad scientific questions, especially in under-represented systems (for example, deserts, tropical forests) and wild communities. Here, we quantitatively compare the sensitivity of species first flowering and leafing dates to spring warmth in two phenological databases from the Northern Hemisphere. One—PEP725—has high replication within and across sites, but has low species diversity and spans a limited climate gradient. The other—NECTAR—includes many more species and a wider range of climates, but has fewer sites and low replication of species across sites. PEP725, despite low species diversity and relatively low seasonality, accurately captures the magnitude and seasonality of warming responses at climatically similar NECTAR sites, with most species showing earlier phenological events in response to warming. In NECTAR, the prevalence of temperature responders significantly declines with increasing mean annual temperature, a pattern that cannot be detected across the limited climate gradient spanned by the PEP725 flowering and leafing data. Our results showcase broad areas of agreement between the two databases, despite significant differences in species richness and geographic coverage, while also noting areas where including data across broader climate gradients may provide added value. Such comparisons help to identify gaps in our observations and knowledge base that can be addressed by ongoing monitoring and research efforts. Resolving these issues will be critical for improving predictions in understudied and under-sampled systems outside of the temperature seasonal mid-latitudes.

Northern Hemisphere

Book review: The requisite reference for the study of Sirenia

Sirenians often are given little or no notice in texts on marine mammals; whales, dolphins, and seals are what come to mind for most when a marine mammal is imagined. An order of only four extant species, the Sirenia is indeed the “other” frequently overlooked group of marine mammals. Dugongs and manatees remain unknown by much of the world, but to those that study these species, the members are extraordinarily unique and fascinating. The three highly respected authors of this newly published volume are all distinguished researchers, with more than a century of combined expertise in the study of this mammalian order. Their collective experience and insight make this book a captivating and valuable read for students, professionals, and anyone interested in having an all-inclusive reference for learning about the Order Sirenia. Review info: Ecology and conservation of the Sirenia-dugongs and manatees . By H. Marsh, T. J. O'Shea, and J. E. Reynolds, III, 2012. ISBN: 978-0521888288, 521 pp.

Journal of Mammalian Evolution

Crop classification modelling using remote sensing and environmental data in the Greater Platte River Basin, USA

With an ever expanding population, potential climate variability and an increasing demand for agriculture-based alternative fuels, accurate agricultural land-cover classification for specific crops and their spatial distributions are becoming critical to researchers, policymakers, land managers and farmers. It is important to ensure the sustainability of these and other land uses and to quantify the net impacts that certain management practices have on the environment. Although other quality crop classification products are often available, temporal and spatial coverage gaps can create complications for certain regional or time-specific applications. Our goal was to develop a model capable of classifying major crops in the Greater Platte River Basin (GPRB) for the post-2000 era to supplement existing crop classification products. This study identifies annual spatial distributions and area totals of corn, soybeans, wheat and other crops across the GPRB from 2000 to 2009. We developed a regression tree classification model based on 2.5 million training data points derived from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) in relation to a variety of other relevant input environmental variables. The primary input variables included the weekly 250 m US Geological Survey Earth Observing System Moderate Resolution Imaging Spectroradiometer normalized differential vegetation index, average long-term growing season temperature, average long-term growing season precipitation and yearly start of growing season. An overall model accuracy rating of 78% was achieved for a test sample of roughly 215 000 independent points that were withheld from model training. Ten 250 m resolution annual crop classification maps were produced and evaluated for the GPRB region, one for each year from 2000 to 2009. In addition to the model accuracy assessment, our validation focused on spatial distribution and county-level crop area totals in comparison with the NASS CDL and county statistics from the US Department of Agriculture (USDA) Census of Agriculture. The results showed that our model produced crop classification maps that closely resembled the spatial distribution trends observed in the NASS CDL and exhibited a close linear agreement with county-by-county crop area totals from USDA census data ( R 2 = 0.90).

Greater Platte River Basin

Landsat Data Continuity Mission (LDCM) space to ground mission data architecture

The Landsat Data Continuity Mission (LDCM) is a scientific endeavor to extend the longest continuous multi-spectral imaging record of Earth's land surface. The observatory consists of a spacecraft bus integrated with two imaging instruments; the Operational Land Imager (OLI), built by Ball Aerospace & Technologies Corporation in Boulder, Colorado, and the Thermal Infrared Sensor (TIRS), an in-house instrument built at the Goddard Space Flight Center (GSFC). Both instruments are integrated aboard a fine-pointing, fully redundant, spacecraft bus built by Orbital Sciences Corporation, Gilbert, Arizona. The mission is scheduled for launch in January 2013. This paper will describe the innovative end-to-end approach for efficiently managing high volumes of simultaneous realtime and playback of image and ancillary data from the instruments to the reception at the United States Geological Survey's (USGS) Landsat Ground Network (LGN) and International Cooperator (IC) ground stations. The core enabling capability lies within the spacecraft Command and Data Handling (C&DH) system and Radio Frequency (RF) communications system implementation. Each of these systems uniquely contribute to the efficient processing of high speed image data (up to 265Mbps) from each instrument, and provide virtually error free data delivery to the ground. Onboard methods include a combination of lossless data compression, Consultative Committee for Space Data Systems (CCSDS) data formatting, a file-based/managed Solid State Recorder (SSR), and Low Density Parity Check (LDPC) forward error correction. The 440 Mbps wideband X-Band downlink uses Class 1 CCSDS File Delivery Protocol (CFDP), and an earth coverage antenna to deliver an average of 400 scenes per day to a combination of LGN and IC ground stations. This paper will also describe the integrated capabilities and processes at the LGN ground stations for data reception using adaptive filtering, and the mission operations approach fro- the LDCM Mission Operations Center (MOC) to perform the CFDP accounting, file retransmissions, and management of the autonomous features of the SSR.

Conference Paper

Land-cover change detection

Land cover is the biophysical material on the surface of the earth. Land-cover types include grass, shrubs, trees, barren, water, and man-made features. Land cover changes continuously. The rate of change can be either dramatic and abrupt, such as the changes caused by logging, hurricanes and fire, or subtle and gradual, such as regeneration of forests and damage caused by insects (Verbesselt et al., 2001). Previous studies have shown that land cover has changed dramatically during the past sevearal centuries and that these changes have severely affected our ecosystems (Foody, 2010; Lambin et al., 2001). Lambin and Strahlers (1994b) summarized five types of cause for land-cover changes: (1) long-term natural changes in climate conditions, (2) geomorphological and ecological processes, (3) human-induced alterations of vegetation cover and landscapes, (4) interannual climate variability, and (5) human-induced greenhouse effect. Tools and techniques are needed to detect, describe, and predict these changes to facilitate sustainable management of natural resources.

Book chapter

Knowledge gained from video-monitoring grassland passerine nests

In the mid-1990s, researchers began using miniature cameras to videotape activities at cryptic passerine nests in grasslands.In subsequent years, use of these video surveillance systems spread dramatically, leading to major strides in our knowledge of nest predation and nesting ecology of many species.Studies using video nest surveillance have helped overturn or substantiate many long-standing assumptions and have provided insights on a wide range of topics.Using examples from grasslands, we highlight the accumulated knowledge about activities at nests documented with video; we also discuss implications of this knowledge for our understanding of avian ecology.Like all tools, video nest surveillance has potential limitations, and users must take precautions to minimize possible sources of bias in data collection and interpretation.

Minnesota, North Dakota

VS30 – A site-characterization parameter for use in building Codes, simplified earthquake resistant design, GMPEs, and ShakeMaps

VS30, defined as the average seismic shear-wave velocity from the surface to a depth of 30 meters, has found wide-spread use as a parameter to characterize site response for simplified earthquake resistant design as implemented in building codes worldwide. VS30 , as initially introduced by the author for the US 1994 NEHRP Building Code, provides unambiguous definitions of site classes and site coefficients for site-dependent response spectra based on correlations derived from extensive borehole logging and comparative ground-motion measurement programs in California. Subsequent use of VS30 for development of strong ground motion prediction equations (GMPEs) and measurement of extensive sets of VS borehole data have confirmed the previous empirical correlations and established correlations of SVS30 with VSZ at other depths. These correlations provide closed form expressions to predict S30 V at a large number of additional sites and further justify S30 V as a parameter to characterize site response for simplified building codes, GMPEs, ShakeMap, and seismic hazard mapping.

Conference Paper