University of Maryland, Baltimore County

About: University of Maryland, Baltimore County is a education organization based out in Baltimore, Maryland, United States. It is known for research contribution in the topics: Population & Aerosol. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.

Species-Level Paraphyly and Polyphyly: Frequency, Causes, and Consequences, with Insights from Animal Mitochondrial DNA

Abstract: ▪ Abstract Many uses of gene trees implicitly assume that nominal species are monophyletic in their alleles at the study locus. However, in well-sampled gene trees, certain alleles in one species may appear more closely related to alleles from different species than to other conspecific alleles. Such deviations from species-level monophyly have a variety of causes and may lead to erroneous evolutionary interpretations if undetected. The present paper describes the causes and consequences of these paraphyletic and polyphyletic patterns. It also provides a detailed literature survey of mitochondrial DNA studies on low-level animal phylogeny and phylogeography, results from which reveal the frequency of nonmonophyly and patterns of interpretation and sampling. This survey detected species-level paraphyly or polyphyly in 23% of 2319 assayed species, demonstrating this phenomenon to be statistically supported, taxonomically widespread, and far more common than generally recognized. Our findings call for increa...

Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards

Abstract: Myeloid-derived suppressor cells (MDSCs) have emerged as major regulators of immune responses in cancer and other pathological conditions. In recent years, ample evidence supports key contributions of MDSC to tumour progression through both immune-mediated mechanisms and those not directly associated with immune suppression. MDSC are the subject of intensive research with >500 papers published in 2015 alone. However, the phenotypic, morphological and functional heterogeneity of these cells generates confusion in investigation and analysis of their roles in inflammatory responses. The purpose of this communication is to suggest characterization standards in the burgeoning field of MDSC research.

Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations

Abstract: The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1 deg x 1 deg lat/long grid from currently available observational data. Where possible (40 deg N-40 deg S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR T(sub b)) are thresholded and all "cold" pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), but for the TMPI the IR Tb threshold and conditional rain rate are set locally by month from Special Sensor Microwave/Imager (SSM/I)-based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite-gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) precipitation. The frequency of rain days in the TOVS is scaled down to match that in the TMPI at the data boundaries, and the resulting non-zero TOVS values are scaled locally to sum to the SG (which is a globally complete monthly product). The time series of the daily 1DD global images shows good continuity in time and across the data boundaries. Various examples are shown to illustrate uses. Validation for individual grid -box values shows a very high root-mean-square error but, it improves quickly when users perform time/space averaging according to their own requirements.

Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery

Abstract: Linear spectral mixture analysis (LSMA) is a widely used technique in remote sensing to estimate abundance fractions of materials present in an image pixel. In order for an LSMA-based estimator to produce accurate amounts of material abundance, it generally requires two constraints imposed on the linear mixture model used in LSMA, which are the abundance sum-to-one constraint and the abundance nonnegativity constraint. The first constraint requires the sum of the abundance fractions of materials present in an image pixel to be one and the second imposes a constraint that these abundance fractions be nonnegative. While the first constraint is easy to deal with, the second constraint is difficult to implement since it results in a set of inequalities and can only be solved by numerical methods. Consequently, most LSMA-based methods are unconstrained and produce solutions that do not necessarily reflect the true abundance fractions of materials. In this case, they can only be used for the purposes of material detection, discrimination, and classification, but not for material quantification. The authors present a fully constrained least squares (FCLS) linear spectral mixture analysis method for material quantification. Since no closed form can be derived for this method, an efficient algorithm is developed to yield optimal solutions. In order to further apply the designed algorithm to unknown image scenes, an unsupervised least squares error (LSE)-based method is also proposed to extend the FCLS method in an unsupervised manner.

Loss of foundation species: consequences for the structure and dynamics of forested ecosystems

Abstract: In many forested ecosystems, the architecture and functional ecology of certain tree species define forest structure and their species-specific traits control ecosystem dynamics. Such foundation tree species are declining throughout the world due to introductions and outbreaks of pests and pathogens, selective removal of individual taxa, and over-harvesting. Through a series of case studies, we show that the loss of foundation tree species changes the local environment on which a variety of other species depend; how this disrupts fundamental ecosystem processes, including rates of decomposition, nutrient fluxes, carbon sequestration, and energy flow; and dramatically alters the dynamics of associated aquatic ecosystems. Forests in which dynamics are controlled by one or a few foundation species appear to be dominated by a small number of strong interactions and may be highly susceptible to alternating between stable states following even small perturbations. The ongoing decline of many foundation species provides a set of important, albeit unfortunate, opportunities to develop the research tools, models, and metrics needed to identify foundation species, anticipate the cascade of immediate, short- and long-term changes in ecosystem structure and function that will follow from their loss, and provide options for remedial conservation and management.