Use of hydroclimatic forecasts for improved water management in central Texas

Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

Microfluidic fabrication of advanced microcapsules for use in self-healing materials

The proposed work aims to facilitate the development of a microfluidic platform for the production of advanced microcapsules containing active agents which can be the functional constituents of self-healing composites. The creation of such microcapsules is enabled by the unique flow characteristics within microchannels including precise control over shear and interfacial forces for droplet creation and manipulation as well as the ability to form a solid shell either chemically or via the addition of thermal or irradiative energy. Microchannel design and a study of the fluid dynamics and mechanisms for shell creation are undertaken in order to establish a fabrication approach capable of producing healing-agent-containing microcapsules. An in-depth study of the process parameters has been undertaken in order to elucidate the advantages of this production technique including precise control of size (i.e., monodispersity) and surface morphology of the microcapsules. This project also aims to aid the optimization of the mechanical properties as well as healing performance of self-healing composites by studying the effects of the advantageous properties of the as-produced microcapsules. Scale-up of the microfluidic fabrication using parallel devices on a single chip as well as on-chip microcapsule production and shape control will also be investigated. It will be demonstrated that microfluidic fabrication is a versatile approach for the efficient creation of functional microcapsules allowing for superior design of self-healing composites.

DYNAMICS AND CONTROL OF REACTIVE DISTILLATION PROCESS FOR MONOMER SYNTHESIS OF POLYCARBONATE PLANTS

Polycarbonate (PC) is an important engineering thermoplastic that is currently produced in large industrial scale using bisphenol A and monomers such as phosgene. Since phosgene is highly toxic, a non-phosgene approach using diphenyl carbonate (DPC) as an alternative monomer, as developed by Asahi Corporation of Japan, is a significantly more environmentally friendly alternative. Other advantages include the use of CO2 instead of CO as raw material and the elimination of major waste water production. However, for the production of DPC to be economically viable, reactive-distillation units are needed to obtain the necessary yields by shifting the reaction-equilibrium to the desired products and separating the products at the point where the equilibrium reaction occurs. In the field of chemical reaction engineering, there are many reactions that are suffering from the low equilibrium constant. The main goal of this research is to determine the optimal process needed to shift the reactions by using appropriate control strategies of the reactive distillation system. An extensive dynamic mathematical model has been developed to help us investigate different control and processing strategies of the reactive distillation units to increase the production of DPC. The high-fidelity dynamic models include extensive thermodynamic and reaction-kinetics models while incorporating the necessary mass and energy balance of the various stages of the reactive distillation units. The study presented in this document shows the possibility of producing DPC via one reactive distillation instead of the conventional two-column, with a production rate of 16.75 tons/h corresponding to start reactants materials of 74.69 tons/h of Phenol and 35.75 tons/h of Dimethyl Carbonate. This represents a threefold increase over the projected production rate given in the literature based on a two-column configuration. In addition, the purity of the DPC produced could reach levels as high as 99.5% with the effective use of controls. These studies are based on simulation done using high-fidelity dynamic models.

Tenofovir use is associated with an increase in serum alkaline phosphatase in the Swiss HIV Cohort Study

BACKGROUND: Tenofovir (TDF) use has been associated with proximal renal tubulopathy, reduced calculated glomerular filtration rates (cGFR) and losses in bone mineral density. Bone resorption could result in a compensatory osteoblast activation indicated by an increase in serum alkaline phosphatase (sAP). A few small studies have reported a positive correlation between renal phosphate losses, increased bone turnover and sAP. METHODS: We analysed sAP dynamics in patients initiating (n = 657), reinitiating (n = 361) and discontinuing (n = 73) combined antiretroviral therapy with and without TDF and assessed correlations with clinical and epidemiological parameters. RESULTS: TDF use was associated with a significant increase of sAP from a median of 74 U/I (interquartile range 60-98) to a plateau of 99 U/I (82-123) after 6 months (P < 0.0001), with a prompt return to baseline upon TDF discontinuation. No change occurred in TDF-sparing regimes. Univariable and multivariable linear regression analyses revealed a positive correlation between sAP and TDF use (P < or = 0.003), but no correlation with baseline cGFR, TDF-related cGFR reduction, changes in serum alanine aminotransferase (sALT) or active hepatitis C. CONCLUSIONS: We document a highly significant association between TDF use and increased sAP in a large observational cohort. The lack of correlation between TDF use and sALT suggests that the increase in sAP is because of the bone isoenzyme and indicates stimulated bone turnover. This finding, together with published data on TDF-related renal phosphate losses, this finding raises concerns that TDF use could result in osteomalacia with a loss in bone mineral density at least in a subset of patients. This potentially severe long-term toxicity should be addressed in future studies.

Gaze behavior nonlinear dynamics assessed in virtual immersion as a diagnostic index of sexual deviancy: preliminary results

This paper presents preliminary results about the use of virtual characters, penile plethysmography and gaze behaviour dynamics to assess deviant sexual preferences. Pedophile patients’ responses are compared to those of non-deviant subjects while they were immersed with virtual characters depicting relevant sexual features.

Community mean traits as additional indicators to monitor effects of land-use intensity on grassland plant diversity

Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far. Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German ‘Biodiversity Exploratory’ research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.

Comparison of inorganic nitrogen uptake dynamics following snowmelt and at peak biomass in subalpine grasslands

Subalpine grasslands are highly seasonal environments and likely subject to strong variability in nitrogen (N) dynamics. Plants and microbes typically compete for N acquisition during the growing season and particularly at plant peak biomass. During snowmelt, plants could potentially benefit from a decrease in competition by microbes, leading to greater plant N uptake associated with active growth and freeze-thaw cycles restricting microbial growth. In managed subalpine grasslands, we expect these interactions to be influenced by recent changes in agricultural land use, and associated modifications in plant and microbial communities. At several subalpine grasslands in the French Alps, we added pulses of 15N to the soil at the end of snowmelt, allowing us to compare the dynamics of inorganic N uptake in plants and microbes during this period with that previously reported at the peak biomass in July. In all grasslands, while specific shoot N translocation (per g of biomass) of dissolved inorganic nitrogen (DIN) was two to five times greater at snowmelt than at peak biomass, specific microbial DIN uptakes were similar between the two sampling dates. On an area basis, plant communities took more DIN than microbial communities at the end of snowmelt when aboveground plant biomasses were at least two times lower than at peak biomass. Consequently, inorganic N partitioning after snowmelt switches in favor of plant communities, allowing them to support their growing capacities at this period of the year. Seasonal differences in microbial and plant inorganic N-related dynamics were also affected by past (terraced vs. unterraced) rather than current (mown vs. unmown) land use. In terraced grasslands, microbial biomass N remained similar across seasons, whereas in unterraced grasslands, microbial biomass N was higher and microbial C : N lower at the end of snowmelt as compared to peak biomass. Further investigations on microbial community composition and their organic N uptake dynamics are required to better understand the decrease in microbial DIN uptake.

A biophysical model of synaptic plasticity and metaplasticity can account for the dynamics of the backward shift of hippocampal place fields.

Hippocampal place cells in the rat undergo experience-dependent changes when the rat runs stereotyped routes. One such change, the backward shift of the place field center of mass, has been linked by previous modeling efforts to spike-timing-dependent plasticity (STDP). However, these models did not account for the termination of the place field shift and they were based on an abstract implementation of STDP that ignores many of the features found in cortical plasticity. Here, instead of the abstract STDP model, we use a calcium-dependent plasticity (CaDP) learning rule that can account for many of the observed properties of cortical plasticity. We use the CaDP learning rule in combination with a model of metaplasticity to simulate place field dynamics. Without any major changes to the parameters of the original model, the present simulations account both for the initial rapid place field shift and for the subsequent slowing down of this shift. These results suggest that the CaDP model captures the essence of a general cortical mechanism of synaptic plasticity, which may underlie numerous forms of synaptic plasticity observed both in vivo and in vitro.

Assessing traditional knowledge on forest uses to understand forest ecosystem dynamics

Forest ecosystems worldwide are heavily influenced by human activities. Information on these human activities are key for understanding ecosystem dynamics, especially as some of these human activities have long-term consequences, i.e. legacy effects. We assessed the diversity of forest uses across the Swiss Alps and the respective traditional forest-related knowledge (TFRK) by conducting 56 oral history interviews in five regions. As TFRK tends to be underrepresented in written records, oral history proves to be a very valuable approach. We classified the information gathered in 61 specific forest use practices, characterized by activity, product and use, in order to gain a comprehensive picture of the regional variability but also cross-regional ubiquity of certain forest uses. Based on these results we are able to name the ecologically most relevant forest uses which were most likely, or potentially occurring in Central European forests. We suggest a simple, systematic historical assessment of these relevant forest uses to be applied in all studies on forest ecosystems. This procedure will enable scientists to better evaluate to what degree human activities had an impact on forest ecosystem dynamics in their study area.

Assessing dynamics of forced livestock movements, livelihoods and future development options for pastoralists/agro-pastoralists in Ruvuma and Lindi Regions, in the Southern Tanzania

The study that aimed at understanding the dynamics of forced livestock movements and pastoral livelihood and development options was conducted in Lindi and Ruvuma regions, using both formal and informal approaches. Data were collected from 60 randomly selected Agro-pastoralists/Pastoralists and native farmers using a structured questionnaire. Four villages were involved; two in Lindi region (Matandu and Mkwajuni) and the other two in Ruvuma region (Gumbiro and Muhuwesi). Data were analyzed using descriptive statistics of SPSS to generate means and frequencies. The results indicate that a large number of animals moved into the study area following the eviction order of the government in Ihefu wetlands in 2006/2007. Lindi region was earmarked by the government to receive all the evicted pastoralists. However, by 2008 only 30% of the total cattle that were expected to move into the region had been received. Deaths of many animals on transit, selling of the animals to pay for transportation and other costs while on transit and many pastoralists settling in Coastal and Ruvuma regions before reaching their destinations were reported to be the reasons for the discrepancy observed. To mitigate anticipated conflicts between farmers and pastoralists, Participatory Land Use Management (PLUM) plans were developed in all the study villages in order to demarcate village land area into different uses, including grazing, cropping, settlement and forests. Land units for grazing were supposed to be provided with all necessary livestock infrastructures (dips, charcoal dams, livestock markets and stock routes). However, the land use plans were not able to prevent the anticipated conflicts because most of the livestock infrastructures were lacking, the land use boundaries were not clearly demarcated and there was limited enforcement of village by-laws, since most had not been enacted by the respective district councils. Similarly, the areas allocated for grazing were inadequate for the number of livestock available and thus the carrying capacity exceeded. Thus, land resource-based conflicts between farmers and pastoralists were emerging in the study areas for the reason that most of the important components in the PLUM plans were not in place. Nevertheless, the arrival of pastoralists in the study areas had positive effects on food security and growth of social interactions between pastoralists and farmers including marriages between them. Environmental degradations due to the arrival of livestock were also not evident. Thus, there is a need for the government to purposely set aside enough grazing land with all necessary infrastructures in place for the agro-pastoral/pastoral communities in the country.

Model-Based Estimates of Right Whale Habitat Use in the Gulf of Maine

Balancing human uses of the marine environment with the recovery of protected species requires accurate information on when and where species of interest are likely to be present. Here, we describe a system that can produce useful estimates of right whale Eubalaena glacialis presence and abundance on their feeding grounds in the Gulf of Maine. The foundation of our system is a coupled physical-biological model of the copepod Calan us finmarchicus, the preferred prey of right whales. From the modeled prey densities, we can estimate when whales will appear in the Great South Channel feeding ground. Based on our experience with the system, we consider how the relationship between right whales and copepods changes across spatial scales. The scale-dependent relationship between whales and copepods provides insight into how to improve future estimates of the distribution of right whales and other pelagic predators.

A model-data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics

Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11700years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid-inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim, a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid-inferred July-temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model-data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500m and treeline positions of ca. 2500m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low-impact pastoralism to preserve species-rich alpine meadows.

Impact of geomagnetic excursions on atmospheric chemistry and dynamics

Geomagnetic excursions, i.e. short periods in time with much weaker geomagnetic fields and substantial changes in the position of the geomagnetic pole, occurred repeatedly in the Earth's history, e.g. the Laschamp event about 41 kyr ago. Although the next such excursion is certain to come, little is known about the timing and possible consequences for the state of the atmosphere and the ecosystems. Here we use the global chemistry climate model SOCOL-MPIOM to simulate the effects of geomagnetic excursions on atmospheric ionization, chemistry and dynamics. Our simulations show significantly increased concentrations of nitrogen oxides (NOx) in the entire stratosphere, especially over Antarctica (+15%), due to enhanced ionization by galactic cosmic rays. Hydrogen oxides (HOx) are also produced in greater amounts (up to +40%) in the tropical and subtropical lower stratosphere, while their destruction by reactions with enhanced NOx prevails over the poles and in high altitudes (by −5%). Stratospheric ozone concentrations decrease globally above 20 km by 1–2% and at the northern hemispheric tropopause by up to 5% owing to the accelerated NOx-induced destruction. A 5% increase is found in the southern lower stratosphere and troposphere. In response to these changes in ozone and the concomitant changes in atmospheric heating rates, the Arctic vortex intensifies in boreal winter, while the Antarctic vortex weakens in austral winter and spring. Surface wind anomalies show significant intensification of the southern westerlies at their poleward edge during austral winter and a pronounced northward shift in spring. Major impacts on the global climate seem unlikely.

Evidence from the real world: N-15 natural abundances reveal enhanced nitrogen use at high plant diversity in Central European grasslands

Complementarity that leads to more efficient resource use is presumed to be a key mechanism explaining positive biodiversity–productivity relationships but has been described solely for experimental set-ups with controlled environmental settings or for very short gradients of abiotic conditions, land-use intensity and biodiversity. Therefore, we analysed plant diversity effects on nitrogen dynamics across a broad range of Central European grasslands. The 15N natural abundance in soil and plant biomass reflects the net effect of processes affecting ecosystem N dynamics. This includes the mechanism of complementary resource utilization that causes a decrease in the 15N isotopic signal. We measured plant species richness, natural abundance of 15N in soil and plants, above-ground biomass of the community and three single species (an herb, grass and legume) and a variety of additional environmental variables in 150 grassland plots in three regions of Germany. To explore the drivers of the nitrogen dynamics, we performed several analyses of covariance treating the 15N isotopic signals as a function of plant diversity and a large set of covariates. Increasing plant diversity was consistently linked to decreased δ15N isotopic signals in soil, above-ground community biomass and the three single species. Even after accounting for multiple covariates, plant diversity remained the strongest predictor of δ15N isotopic signals suggesting that higher plant diversity leads to a more closed nitrogen cycle due to more efficient nitrogen use. Factors linked to increased δ15N values included the amount of nitrogen taken up, soil moisture and land-use intensity (particularly fertilization), all indicators of the openness of the nitrogen cycle due to enhanced N-turnover and subsequent losses. Study region was significantly related to the δ15N isotopic signals indicating that regional peculiarities such as former intensive land use could strongly affect nitrogen dynamics. Synthesis. Our results provide strong evidence that the mechanism of complementary resource utilization operates in real-world grasslands where multiple external factors affect nitrogen dynamics. Although single species may differ in effect size, actively increasing total plant diversity in grasslands could be an option to more effectively use nitrogen resources and to reduce the negative environmental impacts of nitrogen losses.

An indicator framework for assessing livelihood resilience in the context of social–ecological dynamics

Livelihood resilience draws attention to the factors and processes that keep livelihoods functioning despite change and thus enriches the livelihood approach which puts people, their differential capabilities to cope with shocks and how to reduce poverty and improve adaptive capacity at the centre of analysis. However, the few studies addressing resilience from a livelihood perspective take different approaches and focus only on some dimensions of livelihoods. This paper presents a framework that can be used for a comprehensive empirical analysis of livelihood resilience. We use a concept of resilience that considers agency as well as structure. A review of both theoretical and empirical literature related to livelihoods and resilience served as the basis to integrate the perspectives. The paper identifies the attributes and indicators of the three dimensions of resilience, namely, buffer capacity, self-organisation and capacity for learning. The framework has not yet been systematically tested; however, potentials and limitations of the components of the framework are explored and discussed by drawing on empirical examples from literature on farming systems. Besides providing a basis for applying the resilience concept in livelihood-oriented research, the framework offers a way to communicate with practitioners on identifying and improving the factors that build resilience. It can thus serve as a tool for monitoring the effectiveness of policies and practices aimed at building livelihood resilience.