Quantifying uncertainty in citizen weather data

The sheer volume of citizen weather data collected and uploaded to online data hubs is immense. However as with any citizen data it is difficult to assess the accuracy of the measurements. Within this project we quantify just how much data is available, where it comes from, the frequency at which it is collected, and the types of automatic weather stations being used. We also list the numerous possible sources of error and uncertainty within citizen weather observations before showing evidence of such effects in real data. A thorough intercomparison field study was conducted, testing popular models of citizen weather stations. From this study we were able to parameterise key sources of bias. Most significantly the project develops a complete quality control system through which citizen air temperature observations can be passed. The structure of this system was heavily informed by the results of the field study. Using a Bayesian framework the system learns and updates its estimates of the calibration and radiation-induced biases inherent to each station. We then show the benefit of correcting for these learnt biases over using the original uncorrected data. The system also attaches an uncertainty estimate to each observation, which would provide real world applications that choose to incorporate such observations with a measure on which they may base their confidence in the data. The system relies on interpolated temperature and radiation observations from neighbouring professional weather stations for which a Bayesian regression model is used. We recognise some of the assumptions and flaws of the developed system and suggest further work that needs to be done to bring it to an operational setting. Such a system will hopefully allow applications to leverage the additional value citizen weather data brings to longstanding professional observing networks.

Quantifying nitrogen cycling rates in freshwater marshes of the southern Everglades using nitrogen-15 tracer techniques

This dissertation research project addressed the question of how hydrologic restoration of the Everglades is impacting the nutrient dynamics of marsh ecosystems in the southern Everglades. These effects were analyzed by quantifying nitrogen (N) cycle dynamics in the region. I utilized stable isotope tracer techniques to investigate nitrogen uptake and cycling between the major ecosystem components of the freshwater marsh system. I recorded the natural isotopic signatures (δ15N and δ 13C) for major ecosystem components from the three major watersheds of the Everglades: Shark River Slough, Taylor Slough, and C-111 basin. Analysis of δ15 N and δ13C natural abundance data were used to demonstrate the spatial extent to which nitrogen from anthropogenic or naturally enriched sources is entering the marshes of the Everglades. In addition, I measured the fluxes on N between various ecosystem components at both near-canal and estuarine ecotone locations. Lastly, I investigated the effect of three phosphorus load treatments (0.00 mg P m-2, 6.66 mg P m-2, and 66.6 mg P m-2) on the rate and magnitude of ecosystem N-uptake and N-cycling. The δ15N and δ13C natural abundance data supported the hypothesis that ecosystem components from near-canal sites have heavier, more enriched δ 15N isotopic signatures than downstream sites. The natural abundance data also showed that the marshes of the southern Everglades are acting as a sink for isotopically heavier, canal-borne dissolved inorganic nitrogen (DIN) and a source for "new" marsh derived dissolved organic nitrogen (DON). In addition, the 15N mesocosm data showed the rapid assimilation of the 15N tracer by the periphyton component and the delayed N uptake by soil and macrophyte components in the southern Everglades.

Quantifying protein folding pathways

A deep understanding of the proteins folding dynamics can be get quantifying folding landscape by calculating how the number of microscopic configurations (entropy) varies with the energy of the chain, Ω=Ω(E). Because of the incredibly large number of microstates available to a protein, direct enumeration of Ω(E) is not possible on realistic computer simulations. An estimate of Ω(E) can be obtained by use of a combination of statistical mechanics and thermodynamics. By combining different definitions of entropy that are valid for a system whose probability for occupying a state is given by the canonical Boltzmann probability, computers allow the determination of Ω(E). ^ The energy landscapes of two similar, but not identical model proteins were studied. One protein contains no kinetic tracks. Results show a smooth funnel for the folding landscape. That allows the contour determination of the folding funnel. Also it was presented results for the folding landscape for a modified protein with kinetic traps. Final results show that the computational approach is able to distinguish and explore regions of the folding landscape that are due to kinetic traps from the native state folding funnel.^

Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems: Implications for predictive uncertainty and data collection

Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. ^ The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. ^ The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. ^

Quantifying the responses of calcareous periphyton crusts to rehydration: A microcosm study (Florida Everglades)

We examined the high-resolution temporal dynamics of recovery of dried periphyton crusts following rapid rehydration in a phosphorus (P)-limited short hydroperiod Everglades wetland. Crusts were incubated in a greenhouse in tubs containing water with no P or exogenous algae to mimic the onset of the wet season in the natural marsh when heavy downpours containing very low P flood the dry wetland. Algal and bacterial productivity were tracked for 20 days and related to compositional changes and P dynamics in the water. A portion of original crusts was also used to determine how much TP could be released if no biotic recovery occurred. Composition was volumetrically dominated by cyanobacteria (90%) containing morphotypes typical of xeric environments. Algal and bacterial production recovered immediately upon rehydration but there was a net TP loss from the crusts to the water in the first 2 days. By day 5, however, cyanobacteria and other bacteria had re-absorbed 90% of the released P. Then, water TP concentration reached a steady-state level of 6.6 μg TP/L despite water TP concentration through evaporation. Phosphomonoesterase (PMEase) activity was very high during the first day after rehydration due to the release of a large pre-existing pool of extracellular PMEase. Thereafter, the activity dropped by 90% and increased gradually from this low level. The fast recovery of desiccated crusts upon rehydration required no exogenous P or allogenous algae/bacteria additions and periphyton largely controlled P concentration in the water.

Quantifying the Impacts of the Recent Economic Crisis on Regional Tourism Industry and Economy

The purpose of this study is to explore the accuracy issue of the Input-Output model in quantifying the impacts of the 2007 economic crisis on a local tourism industry and economy. Though the model has been used in the tourism impact analysis, its estimation accuracy is rarely verified empirically. The Metro Orlando area in Florida is investigated as an empirical study, and the negative change in visitor expenditure between 2007 and 2008 is taken as the direct shock. The total impacts are assessed in terms of output and employment, and are compared with the actual data. This study finds that there are surprisingly large discrepancies among the estimated and actual results, and the Input-Output model appears to overestimate the negative impacts. By investigating the local economic activities during the study period, this study made some exploratory efforts in explaining such discrepancies. Theoretical and practical implications are then suggested.

Quantifying the Impacts of the Recent Economic Crisis on a Regional Tourism Industry and Economy

The purpose of this study is to explore the accuracy issue of the Input-Output model in quantifying the impacts of the 2007 economic crisis on a local tourism industry and economy. Though the model has been used in the tourism impact analysis, its estimation accuracy is rarely verified empirically. The Metro Orlando area in Florida is investigated as an empirical study, and the negative change in visitor expenditure between 2007 and 2008 is taken as the direct shock. The total impacts are assessed in terms of output and employment, and are compared with the actual data. This study finds that there are surprisingly large discrepancies among the estimated and actual results, and the Input-Output model appears to overestimate the negative impacts. By investigating the local economic activities during the study period, this study made some exploratory efforts in explaining such discrepancies. Theoretical and practical implications are then suggested.

Quantifying confinement effects in ice impact loads

Ships and offshore structures, that encounter ice floes, tend to experience loads with varying pressure distributions within the contact patch. The effect of the surrounding ice adjacent to that which is involved in the contact zone has an influence on the effective strength. This effect has come to be called confinement. A methodology for quantifying ice sample confinement is developed, and the confinement is defined using two non-dimensional terms; a ratio of geometries and an angle. Together these terms are used to modify force predictions that account for increased fracturing and spalling at lower confinement levels. Data developed through laboratory experimentation is studied using dimensional analysis. The characteristics of dimensional analysis allow for easy comparison between many different load cases; provided the impact scenario is consistent. In all, a methodology is developed for analyzing ice impact testing considering confinement effects on force levels, with the potential for extrapolating these tests to full size collision events.

Basin stability approach for quantifying responses of multistable systems with parameters mismatch

Acknowledgement This work is funded by the National Science Center Poland based on the decision number DEC-2015/16/T/ST8/00516. PB is supported by the Foundation for Polish Science (FNP).

Quantifying topological invariants of neuronal morphologies

10 pages, 5 figures, conference or other essential info Acknowledgments LK and JCS were supported by Blue Brain Project. P.D. and R.L. were supported in part by the Blue Brain Project and by the start-up grant of KH. Partial support for P.D. has been provided by the Advanced Grant of the European Research Council GUDHI (Geometric Understanding in Higher Dimensions). MS was supported by the SNF NCCR ”Synapsy”.

Quantifying wind and pressure effects on trace gas fluxes across the soil–atmosphere interface

Acknowledgements. We would like to acknowledge the manufacturers of the inner toroid: Mark Bentley and Steve Howarth from the University of York, Dept. of Biology, mechanical and electronics workshops respectively. Furthermore, we would like to acknowledge the Forestry Commission for access and aid at Wheldrake Forest, Mike Bailey and Natural Resources Wales for access and assistance at Cors Fochno, and Norrie Russell and the Royal Society for the Protection of Birds for access and aid at Forsinard. We would also like to thank Graham Hambley, James Robinson, and Elizabeth Donkin for equipment preparation and sampling. Phil Ineson is thanked for the loan of essential equipment, site suggestions, and accessible power supply. Funding was provided by the University of York, Dept. of Biology, and by a grant to YAT by the UK Natural Environment Research Council (NE/H01182X/1).

Quantifying avian relative abundance and ecosystem service value to identify conservation opportunities in the Midwestern U.S.

Grassland birds are highly imperiled because of historical habitat loss and ongoing conversion of grasslands to agricultural and urban land uses. Therefore, prioritizing and further justifying conservation action in remaining grasslands is critical to protecting what remains. Grassland bird conservation has focused on identifying and protecting large grassland complexes referred to as Grassland Bird Conservation Areas (GBCAs). We identified and classified GBCAs in a region highly impacted by both agricultural and urban land conversion using previously developed methods. Then, we extended the analysis to include estimated relative abundance of five grassland focal species in each GBCA. Models of relative abundance were built using eight years of monitoring data collected by citizen scientists. Finally, we quantified the value of ecosystem services provided by each GBCA. There were nearly 55,000 ha of grassland habitats in the Chicago Metropolitan Region that met GBCA criteria, 33% (18,415 ha) of which were protected. Proportion of abundance in protected versus unprotected areas was similar for Bobolink (Dolichonyx oryzivorus; 46%), Grasshopper Sparrow (Ammodramus savannarum; 52%), and Sedge Wren (Cistothorus platensis; 48%), whereas, Henslow’s Sparrow (Ammodramus henslowii; 75%) had a higher proportion of relative abundance in protected GBCAs and Eastern Meadowlark (Sturnella magna) had lower proportions (37%). GBCAs provisioned just under $900 million annually in ecosystem services, 73% of which is because of flood control. Outputs of this comprehensive approach will inform grassland bird conservation by providing detailed information about the value for birds and people of grassland habitats.

Quantifying Eukaryotic Gene Regulation in Hormone Response and Disease.

Quantifying the function of mammalian enhancers at the genome or population scale has been longstanding challenge in the field of gene regulation. Studies of individual enhancers have provided anecdotal evidence on which many foundational assumptions in the field are based. Genome-scale studies have revealed that the number of sites bound by a given transcription factor far outnumber the genes that the factor regulates. In this dissertation we describe a new method, chromatin immune-enriched reporter assays (ChIP-reporters), and use that approach to comprehensively test the enhancer activity of genomic loci bound by the glucocorticoid receptor (GR). Integrative genomics analyses of our ChIP-reporter data revealed an unexpected mechanism of glucocorticoid (GC)-induced gene regulation. In that mechanism, only the minority of GR bound sites acts as GC-inducible enhancers. Many non-GC-inducible GR binding sites interact with GC-induced sites via chromatin looping. These interactions can increase the activity of GC-induced enhancers. Finally, we describe a method that enables the detection and characterization of the functional effects of non-coding genetic variation on enhancer activity at the population scale. Taken together, these studies yield both mechanistic and genetic evidence that provides context that informs the understanding of the effects of multiple enhancer variants on gene expression.

Quantifying Aflatoxin B1 in peanut oil using fabricating fluorescence probes based on upconversion nanoparticles

Rare earth doped upconversion nanoparticles convert near-infrared excitation light into visible emission light. Compared to organic fluorophores and semiconducting nanoparticles, upconversion nanoparticles (UCNPs) offer high photochemical stability, sharp emission bandwidths, and large anti-Stokes shifts. Along with the significant light penetration depth and the absence of autofluorescence in biological samples under infrared excitation, these UCNPs have attracted more and more attention on toxin detection and biological labelling. Herein, the fluorescence probe based on UCNPs was developed for quantifying Aflatoxin B₁ (AFB₁) in peanut oil. Based on a specific immunity format, the detection limit for AFB₁ under optimal conditions was obtained as low as 0.2 ng·ml^{- 1}, and in the effective detection range 0.2 to 100 ng·ml^{- 1}, good relationship between fluorescence intensity and AFB₁ concentration was achieved under the linear ratios up to 0.90. Moreover, to check the feasibility of these probes on AFB₁ measurements in peanut oil, recovery tests have been carried out. A good accuracy rating (93.8%) was obtained in this study. Results showed that the nanoparticles can be successfully applied for sensing AFB₁ in peanut oil.

Expanding Agri-Food Production and Employment in the Presence of Climate Policy Constraints: Quantifying the Trade-Off in Ireland

This chapter explores the trade-off between competing objectives of employment creation and climate policy commitments in Irish agriculture. A social accounting matrix (SAM) multiplier model is linked with a partial equilibrium agricultural sector model to simulate the impact of a number of GHG emission reduction scenarios, assuming these are achieved through a constraint on beef production. Limiting the size of the beef sector helps to reduce GHG emissions with a very limited impact on the value of agricultural income at the farm level. However, the SAM multiplier analysis shows that there would be significant employment losses in the wider economy. From a policy perspective, a pragmatic approach to GHG emissions reductions in the agriculture sector, which balances opportunities for economic growth in the sector with opportunities to reduce associated GHG emissions, may be required.