948 research outputs found

    Updated statewide abundance estimates for the Florida manatee

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    Knowing how many manatees live in Florida is critical for conservation and management of this threatened species. Martin and others flew aerial surveys in 2011–2012 and estimated abundance in those years using advanced techniques that incorporated multiple data sources. We flew additional aerial surveys in 2015–2016 to count manatees and again applied advanced statistical techniques to estimate their abundance. We also made several methodological advances over the earlier work, including accounting for how sea state (water surface conditions) and synchronous surfacing behavior affect the availability of manatees to be detected and incorporating all parts of Florida in the area of inference. We estimate that the number of manatees in Florida in 2015–2016 was 8,810 (95% Bayesian credible interval 7,520–10,280), of which 4,810 (3,820–6,010) were on the west coast of Florida and 4,000 (3,240–4,910) were on the east coast. These estimates and associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses

    Pennsylvania Folklife Vol. 19, No. 1

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    • The Moravian Settlements of Pennsylvania in 1757: The Nicholas Garrison Views • The San Rocco Festival at Aliquippa, Pennsylvania: A Transplanted Tradition • Amish Genealogy: A Progress Report • Pulpit Humor in Central Pennsylvania • The Pre-Metric Foot and its Use in Pennsylvania German Architecture • Mennonite Contacts Across the Atlantic: The Van der Smissen Letter of 1838 • Bread, Baking, and the Bakeoven: Folk-Cultural Questionnaire No. 13https://digitalcommons.ursinus.edu/pafolklifemag/1037/thumbnail.jp

    Stochastic Population Dynamics of a Montane Ground-Dwelling Squirrel

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    Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990–2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λ<1) for 9 out of 18 years. The stochastic population growth rate λs was 0.92, suggesting a declining population; however, the 95% CI on λs included 1.0 (0.52–1.60). Stochastic elasticity analysis showed that survival of adult females, followed by survival of juvenile females and litter size, were potentially the most influential vital rates; analysis of life table response experiments revealed that the same three life history variables made the largest contributions to year-to year changes in λ. Population viability analysis revealed that, when the influences of density dependence and immigration were not considered, the population had a high (close to 1.0 in 50 years) probability of extinction. However, probability of extinction declined to as low as zero when density dependence and immigration were considered. Destabilizing effects of stochastic forces were counteracted by regulating effects of density dependence and rescue effects of immigration, which allowed our study population to bounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration

    Calibration Technique for Polarization-Sensitive Lidars

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    Polarization-sensitive lidars have proven to be highly effective in discriminating between spherical and non-spherical particles in the atmosphere. These lidars use a linearly polarized laser and are equipped with a receiver that can separately measure the components of the return signal polarized parallel and perpendicular to the outgoing beam. In this work we describe a technique for calibrating polarization-sensitive lidars that was originally developed at NASA s Langley Research Center (LaRC) and has been used continually over the past fifteen years. The procedure uses a rotatable half-wave plate inserted into the optical path of the lidar receiver to introduce controlled amounts of polarization cross-talk into a sequence of atmospheric backscatter measurements. Solving the resulting system of nonlinear equations generates the system calibration constants (gain ratio, G, and offset angle, theta) required for deriving calibrated measurements of depolarization ratio from the lidar signals. In addition, this procedure also determines the mean depolarization ratio within the region of the atmosphere that is analyzed. Simulations and error propagation studies show the method to be both reliable and well behaved. Operational details of the technique are illustrated using measurements obtained as part of Langley Research Center s participation in the First ISCCP Regional Experiment (FIRE)

    An evaluation of CALIOP/CALIPSO’s aerosol-above-cloud detection and retrieval capability over North America

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    Assessing the accuracy of the aerosol-above-cloud (AAC) properties derived by CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarization) is challenged by the shortage of accurate global validation measurements. We have used measurements of aerosol vertical profiles from the NASA Langley airborne High Spectral Resolution Lidar (HSRL-1) in 86 CALIOP-coincident flights to evaluate CALIOP AAC detection, classification, and retrieval. Our study shows that CALIOP detects ~23% of the HSRL-detected AAC. According to our CALIOP-HSRL data set, the majority of AAC aerosol optical depth (AOD) values are \u3c 0.1 at 532 nm over North America. Our analyses show that the standard CALIOP retrieval algorithm substantially underestimates the occurrence frequency of AAC when optical depths are less than ~0.02. Those aerosols with low AOD values can still have a consequent radiative forcing effect depending on the underlying cloud cover and overlying aerosol absorption properties. We find essentially no correlation between CALIOP and HSRL AAC AOD (R2 = 0.27 and N = 151). We show that the CALIOP underestimation of AAC is mostly due to tenuous aerosol layers with backscatter less than the CALIOP detection threshold. The application of an alternate CALIOP AAC retrieval method (depolarization ratio) to our data set yields very few coincident cases. We stress the need for more extensive suborbital CALIOP validation campaigns to acquire a process-level understanding of AAC implications and further evaluate CALIOPs AAC detection and retrieval capability, especially over the ocean and in different parts of the world where AAC are more frequently observed and show higher values of AOD

    Modeling regional aerosol variability over California and its sensitivity to emissions and long-range transport during the 2010 CalNex and CARES campaigns

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    Abstract. The performance of the Weather Research and Forecasting regional model with chemistry (WRF-Chem) in simulating the spatial and temporal variations in aerosol mass, composition, and size over California is quantified using measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010. The extensive meteorological, trace gas, and aerosol measurements collected at surface sites and along aircraft and ship transects during CalNex and CARES were combined with operational monitoring network measurements to create a single dataset that was used to evaluate the one configuration of the model. Simulations were performed that examined the sensitivity of regional variations in aerosol concentrations to anthropogenic emissions and to long-range transport of aerosols into the domain obtained from a global model. The configuration of WRF-Chem used in this study is shown to reproduce the overall synoptic conditions, thermally-driven circulations, and boundary layer structure observed in region that controls the transport and mixing of trace gases and aerosols. However, sub-grid scale variability in the meteorology and emissions as well as uncertainties in the treatment of secondary organic aerosol chemistry likely contribute to errors at a primary surface sampling site located at the edge of the Los Angeles basin. Differences among the sensitivity simulations demonstrate that the aerosol layers over the central valley detected by lidar measurements likely resulted from lofting and recirculation of local anthropogenic emissions along the Sierra Nevada. Reducing the default emissions inventory by 50% led to an overall improvement in many simulated trace gases and black carbon aerosol at most sites and along most aircraft flight paths; however, simulated organic aerosol was closer to observed when there were no adjustments to the primary organic aerosol emissions. The model performance for some aerosol species was not uniform over the region, and we found that sulfate was better simulated over northern California whereas nitrate was better simulated over southern California. While the overall spatial and temporal variability of aerosols and their precursors were simulated reasonably well, we show cases where the local transport of some aerosol plumes were either too slow or too fast, which adversely affects the statistics regarding the differences between observed and simulated quantities. Comparisons with lidar and in-situ measurements indicate that long-range transport of aerosols from the global model was likely too high in the free troposphere even though their concentrations were relatively low. This bias led to an over-prediction in aerosol optical depth by as much as a factor of two that offset the under-predictions of boundary-layer extinction resulting primarily from local emissions. Lowering the boundary conditions of aerosol concentrations by 50% greatly reduced the bias in simulated aerosol optical depth for all regions of California. This study shows that quantifying regional-scale variations in aerosol radiative forcing and determining the relative role of emissions from local and distant sources is challenging during "clean" conditions and that a wide array of measurements are needed to ensure model predictions are correct for the right reasons. In this regard, the combined CalNex and CARES datasets are an ideal testbed that can be used to evaluate aerosol models in great detail and develop improved treatments for aerosol processes

    An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

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    Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality

    Comparison of Aerosol Classification From Airborne High Spectral Resolution Lidar and the CALIPSO Vertical Feature Mask

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    Knowledge of aerosol composition and vertical distribution is crucial for assessing the impact of aerosols on climate. In addition, aerosol classification is a key input to CALIOP aerosol retrievals, since CALIOP requires an inference of the lidar ratio in order to estimate the effects of aerosol extinction and backscattering. In contrast, the NASA airborne HSRL-1 directly measures both aerosol extinction and backscatter, and therefore the lidar ratio (extinction-to-backscatter ratio). Four aerosol intensive properties from HSRL-1 are combined to infer aerosol type. Aerosol classification results from HSRL-1 are used here to validate the CALIOP aerosol type inferences
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