Extinction debt of high-mountain plants under 21st-century climate change

Quantitative estimates of the range loss of mountain plants under climate change have so far mostly relied on static geographical projections of species' habitat shifts(1-3). Here, we use a hybrid model(4) that combines such projections with simulations of demography and seed dispersal to forecast the climate-driven spatio-temporal dynamics of 150 high-mountain plant species across the European Alps. This model predicts average range size reductions of 44-50% by the end of the twenty-first century, which is similar to projections from the most 'optimistic' static model (49%). However, the hybrid model also indicates that population dynamics will lag behind climatic trends and that an average of 40% of the range still occupied at the end of the twenty-first century will have become climatically unsuitable for the respective species, creating an extinction debt(5,6). Alarmingly, species endemic to the Alps seem to face the highest range losses. These results caution against optimistic conclusions from moderate range size reductions observed during the twenty-first century as they are likely to belie more severe longer-term effects of climate warming on mountain plants.

Climate Change Impacts on Iowa, 2010, January 1, 2011

Today, perhaps without their realization, Iowans are factoring climate change into their lives and activities. Current farming practices and flood mitigation efforts, for example, are reflecting warmer winters, longer growing seasons, warmer nights, higher dew-point temperatures, increased humidity, greater annual stream flows, and more frequent severe precipitation events (Fig. 1) than were prevalent during the past 50 years. Some of the effects of these changes (such as longer growing season) may be positive, while others (particularly the tendency for greater precipitation events that lead to flooding) are negative. Climate change embodies all of these results and many more in a complex manner. The Iowa legislature has been proactive in seeking advice about climate change and its impacts on our state. In 2007, Governor Culver and the Iowa General Assembly enacted Senate File 485 and House File 2571 to create the Iowa Climate Change Advisory Council (ICCAC). ICCAC members reported an emissions inventory and a forecast for Iowa’s greenhouse gases (GHGs), policy options for reducing Iowa’s GHG, and two scenarios charting GHG reductions of 50% and 90% by 2050 from a baseline of 2005. Following issuance of the final report in December 2008, the General Assembly enacted a new bill in 2009 (Sec. 27, Section 473.7, Code 2009 amended) that set in motion a review of climate change impacts and policies in Iowa. This report is the result of that 2009 bill. It continues the dialogue between Iowa’s stakeholders, scientific community, and the state legislature that was begun with these earlier reports.

Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

Missouri Work Zone Capacity: Results of Field Data Analysis, TPF-5(081), 2011

This report presents the results of work zone field data analyzed on interstate highways in Missouri to determine the mean breakdown and queue-discharge flow rates as measures of capacity. Several days of traffic data collected at a work zone near Pacific, Missouri with a speed limit of 50 mph were analyzed in both the eastbound and westbound directions. As a result, a total of eleven breakdown events were identified using average speed profiles. The traffic flows prior to and after the onset of congestion were studied. Breakdown flow rates ranged between 1194 to 1404 vphpl, with an average of 1295 vphpl, and a mean queue discharge rate of 1072 vphpl was determined. Mean queue discharge, as used by the Highway Capacity Manual 2000 (HCM), in terms of pcphpl was found to be 1199, well below the HCM’s average capacity of 1600 pcphpl. This reduced capacity found at the site is attributable mainly to narrower lane width and higher percentage of heavy vehicles, around 25%, in the traffic stream. The difference found between mean breakdown flow (1295 vphpl) and queue-discharge flow (1072 vphpl) has been observed widely, and is due to reduced traffic flow once traffic breaks down and queues start to form. The Missouri DOT currently uses a spreadsheet for work zone planning applications that assumes the same values of breakdown and mean queue discharge flow rates. This study proposes that breakdown flow rates should be used to forecast the onset of congestion, whereas mean queue discharge flow rates should be used to estimate delays under congested conditions. Hence, it is recommended that the spreadsheet be refined accordingly.

Investigation of Warm-Mix Asphalt for Iowa Roadways, TR-635, 2013

Phase II of this study further evaluated the performance of plant-produced warm-mix asphalt (WMA) mixes by conducting additional mixture performance tests at a broader range of temperatures, adding additional pavements to the study, comparing virgin and recovered binder properties, performing pavement condition surveys, and comparing survey data with the Mechanistic Empirical Pavement Design Guide (MEPDG) forecast for pavement damage over 20 years of service life. Further objectives detailing curing behavior, quality assurance testing, and hybrid technologies were as follows: * Compare the predicted and observed field performance of existing WMA trials produced in the previous Phase I study to that of hot-mix asphalt (HMA) control sections to determine if Phase I conclusions are translating to the field; * Identify any curing effect (and timing of the effect) of WMA mixtures and binders in the field; * Determine how the field-compacted mixture properties and recovered binder properties of WMA compare to those of HMA over time for technologies common to Iowa; * Identify the protocols for WMA sample preparation for volumetric and performance testing that best simulate field conditions. The findings of this study indicate that WMA additives do show statistical differences in mixture properties in some of the mixes tested. These differences will not always be statistically different from mixture to mixture. Multiple factors, such as WMA additive type, amount of recycled asphalt material, construction conditions, and mixture variability all play a role in determining the extent of which WMA and HMA mixes differ. Other significant findings of this study include effects of curing, aging in recovered binders from HMA and WMA cores, and the influence of recycled asphalt shingles (RAS) used with WMA. These findings will be of interest to owner agencies and contractors utilizing WMA technologies.

Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Development of an Expert System for Forecasting Frost on Bridges and Roadways in Iowa, HR-305, 1991

An expert system has been developed that provides 24 hour forecasts of roadway and bridge frost for locations in Iowa. The system is based on analysis of frost observations taken by highway maintenance personnel, analysis of conditions leading to frost as obtained from meteorologists with experience in forecasting bridge and roadway frost, and from fundamental physical principles of frost processes. The expert system requires the forecaster to enter information on recent maximum and minimum temperatures and forecasts of maximum and minimum air temperatures, dew point temperatures, precipitation, cloudiness, and wind speed. The system has been used operationally for the last two frost seasons by Freese-Notis Associates, who have been under contract with the Iowa DOT to supply frost forecasts. The operational meteorologists give the system their strong endorsement. They always consult the system before making a frost forecast unless conditions clearly indicate frost is not likely. In operational use, the system is run several times with different input values to test the sensitivity of frost formation on a particular day to various meteorological parameters. The users comment. that the system helps them to consider all the factors relevant to frost formation and is regarded as an office companion for making frost forecasts.

Agreement in interpersonal perception as a predictor of group performance

The present work deals with quantifying group characteristics. Specifically, dyadic measures of interpersonal perceptions were used to forecast group performance. 46 groups of students, 24 of four and 22 of five people, were studied in a real educational assignment context and marks were gathered as an indicator of group performance. Our results show that dyadic measures of interpersonal perceptions account for final marks. By means of linear regression analysis 85% and 85.6% of group performance was respectively explained for group sizes equal to four and five. Results found in the scientific literature based on the individualistic approach are no larger than 18%. The results of the present study support the utility of dyadic approaches for predicting group performance in social contexts.

Maximizing the Use of Roadway Weather Information Systems: Final Report, TR-404, 1998

This project was proposed as Phase I of a 2-phase program to evaluate the present use of weather information by Iowa Department of Transportation (IaDOT) personnel, recommend revised procedures, and then implement the resulting recommendations. Midway through Phase I (evaluation phase) the FORETELL project was funded. This project is a multi-state venture that engages the National Weather Service (NWS) and the Forecast Systems Laboratory of the National Oceanic and Atmospheric Administration and proposes to supplant the current weather information-generation and distribution system with an advanced system based on state-of-the-art technologies. The focus of the present project was therefore refined to consider use of weather data by IaDOT personnel, and the training programs needed to more effectively use these data. Results of the survey revealed that two major areas - training of personnel on use of data from whatever source and more precise information of frost formation - are not addressed in the FORETELL project. These aspects have been the focus of the present project.

Conditional predictive density evaluation in the presence of instabilities

We propose new methods for evaluating predictive densities. The methods includeKolmogorov-Smirnov and Cram?r-von Mises-type tests for the correct specification ofpredictive densities robust to dynamic mis-specification. The novelty is that the testscan detect mis-specification in the predictive densities even if it appears only overa fraction of the sample, due to the presence of instabilities. Our results indicatethat our tests are well sized and have good power in detecting mis-specification inpredictive densities, even when it is time-varying. An application to density forecastsof the Survey of Professional Forecasters demonstrates the usefulness of the proposedmethodologies.

Pilot Project for a Hybrid Road-Flooding Forecasting System on Squaw Creek, TR-642

A network of 25 sonic stage sensors were deployed in the Squaw Creek basin upstream from Ames Iowa to determine if the state-of-the-art distributed hydrological model CUENCAS can produce reliable information for all road crossings including those that cross small creeks draining basins as small as 1 sq. mile. A hydraulic model was implemented for the major tributaries of the Squaw Creek where IFC sonic instruments were deployed and it was coupled to CUENCAS to validate the predictions made at small tributaries in the basin. This study demonstrates that the predictions made by the hydrological model at internal locations in the basins are as accurate as the predictions made at the outlet of the basin. Final rating curves based on surveyed cross sections were developed for the 22 IFC-bridge sites that are currently operating, and routine forecast is provided at those locations (see IFIS). Rating curves were developed for 60 additional bridge locations in the basin, however, we do not use those rating curves for routine forecast because the lack of accuracy of LiDAR derived cross sections is not optimal. The results of our work form the basis for two papers that have been submitted for publication to the Journal of Hydrological Engineering. Peer review of our work will gives a strong footing to our ability to expand our results from the pilot Squaw Creek basin to all basins in Iowa.

Predicting current and future spatial community patterns of plant functional traits

Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.

Exchange rate predictability

The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known thatexchange rate fluctuations are very difficult to predict using economic models, andthat a random walk forecasts exchange rates better than any economic model (theMeese and Rogoff puzzle). However, the recent literature has identified a series of fundamentals/methodologies that claim to have resolved the puzzle. This article providesa critical review of the recent literature on exchange rate forecasting and illustratesthe new methodologies and fundamentals that have been recently proposed in an up-to-date, thorough empirical analysis. Overall, our analysis of the literature and thedata suggests that the answer to the question: "Are exchange rates predictable?" is,"It depends" -on the choice of predictor, forecast horizon, sample period, model, andforecast evaluation method. Predictability is most apparent when one or more of thefollowing hold: the predictors are Taylor rule or net foreign assets, the model is linear, and a small number of parameters are estimated. The toughest benchmark is therandom walk without drift.

Libertad condicional : propuestas para aumentar su concesión

La libertad condicional es una institución cuya aplicación no se da con la frecuencia que debería para lograr una resocialización y reinserción adecuada. Para reducir las tasas de encarcelamiento y los costes que se derivan, así como para igualar las tasas de liberados condicionales en Cataluña con las del resto del Estado, se proponen posibles mejoras para la concesión del último grado penitenciario. Las propuestas se desarrollan a partir de una investigación empírica basada en una revisión exhaustiva de los informes de pronóstico de reinserción de la Junta de Tratamiento y las resoluciones del Fiscal de Vigilancia Penitenciaria.Se formularán propuestas generales y específicas. Las primeras estarán encabezadas a modificar el punitivismo de la sociedad y la implementación de la libertad condicional. Las segundas estarán orientadas a focalizar el último grado penitenciario también a internos con alto riesgo de reincidencia, siempre y cuando se les proporcione una intervención intensiva; a mejorar y tratar tanto los factores estáticos como los dinámicos –hábitos laborales, toxicomanías, apoyo familiar– para facilitar el acceso a la libertad condicional según los actuales requisitos; a concienciar sobre la importancia de satisfacer la responsabilidad civil y a seguir la línea del modelo de riesgo, necesidad y responsividad.ABSTRACTParole is an institution whose application does not occur as often as it should to achieve resocialization and reintegration adequately. To reduce incarceration rates and its costs, as well as to equalize Catalonia’s parole rates with the rest of the state, it is suggested possible improvements for the last grade prison’s granting. The proposals were developed from an empirical research based on the analysis of the Treatment Assembly’s forecast reports reintegration and the Fiscal’s resolutions.It will be formulated general and specific proposals. The first one will be led to modify society’s punitivity and parole’s implementation. The second one will be directed on focusing parole in high risk prison inmates, as long as they have an intensive intervention; on improving and treat both static and dynamic factors –work habits, addictions, family support– to facilitate the access on parole under the current requirements; on raising the importance of paying the civil liability and follow the principles of the model of risk, needs and responsivity.