Natural streamflow regime alterations: Damming of the Piave river basin (Italy)

A novel approach is proposed to estimate the natural streamflow regime of a river and to assess the extent of the alterations induced by dam operation related to anthropogenic (e.g., agricultural, hydropower) water uses in engineered river basins. The method consists in the comparison between the seasonal probability density function (pdf) of observed streamflows and the purportedly natural streamflow pdf obtained by a recently proposed and validated probabilistic model. The model employs a minimum of landscape and climate parameters and unequivocally separates the effects of anthropogenic regulations from those produced by hydroclimatic fluctuations. The approach is applied to evaluate the extent of the alterations of intra-annual streamflow variability in a highly engineered alpine catchment of north-eastern Italy, the Piave river. Streamflows observed downstream of the regulation devices in the Piave catchment are found to exhibit smaller means/modes, larger coefficients of variation, and more pronounced peaks than the flows that would be observed in the absence of anthropogenic regulation, suggesting that the anthropogenic disturbance leads to remarkable reductions of river flows, with an increase of the streamflow variability and of the frequency of preferential states far from the mean. Some structural limitations of management approaches based on minimum streamflow requirements (widely used to guide water policies) as opposed to criteria based on whole distributions are also discussed. Copyright © 2010 by the American Geophysical Union.

A range-wide experiment to investigate nutrient and soil moisture interactions in loblolly pine plantations

© 2015 by the authors.The future climate of the southeastern USA is predicted to be warmer, drier and more variable in rainfall, which may increase drought frequency and intensity. Loblolly pine (Pinus taeda) is the most important commercial tree species in the world and is planted on ~11 million ha within its native range in the southeastern USA. A regional study was installed to evaluate effects of decreased rainfall and nutrient additions on loblolly pine plantation productivity and physiology. Four locations were established to capture the range-wide variability of soil and climate. Treatments were initiated in 2012 and consisted of a factorial combination of throughfall reduction (approximate 30% reduction) and fertilization (complete suite of nutrients). Tree and stand growth were measured at each site. Results after two growing seasons indicate a positive but variable response of fertilization on stand volume increment at all four sites and a negative effect of throughfall reduction at two sites. Data will be used to produce robust process model parameterizations useful for simulating loblolly pine growth and function under future, novel climate and management scenarios. The resulting improved models will provide support for developing management strategies to increase pine plantation productivity and carbon sequestration under a changing climate.

Computational Journalism: from Answering Question to Questioning Answers and Raising Good Questions

Our media is saturated with claims of ``facts'' made from data. Database research has in the past focused on how to answer queries, but has not devoted much attention to discerning more subtle qualities of the resulting claims, e.g., is a claim ``cherry-picking''? This paper proposes a Query Response Surface (QRS) based framework that models claims based on structured data as parameterized queries. A key insight is that we can learn a lot about a claim by perturbing its parameters and seeing how its conclusion changes. This framework lets us formulate and tackle practical fact-checking tasks --- reverse-engineering vague claims, and countering questionable claims --- as computational problems. Within the QRS based framework, we take one step further, and propose a problem along with efficient algorithms for finding high-quality claims of a given form from data, i.e. raising good questions, in the first place. This is achieved to using a limited number of high-valued claims to represent high-valued regions of the QRS. Besides the general purpose high-quality claim finding problem, lead-finding can be tailored towards specific claim quality measures, also defined within the QRS framework. An example of uniqueness-based lead-finding is presented for ``one-of-the-few'' claims, landing in interpretable high-quality claims, and an adjustable mechanism for ranking objects, e.g. NBA players, based on what claims can be made for them. Finally, we study the use of visualization as a powerful way of conveying results of a large number of claims. An efficient two stage sampling algorithm is proposed for generating input of 2d scatter plot with heatmap, evalutaing a limited amount of data, while preserving the two essential visual features, namely outliers and clusters. For all the problems, we present real-world examples and experiments that demonstrate the power of our model, efficiency of our algorithms, and usefulness of their results.

A soft robust model for optimization under ambiguity

In this paper, we propose a framework for robust optimization that relaxes the standard notion of robustness by allowing the decision maker to vary the protection level in a smooth way across the uncertainty set. We apply our approach to the problem of maximizing the expected value of a payoff function when the underlying distribution is ambiguous and therefore robustness is relevant. Our primary objective is to develop this framework and relate it to the standard notion of robustness, which deals with only a single guarantee across one uncertainty set. First, we show that our approach connects closely to the theory of convex risk measures. We show that the complexity of this approach is equivalent to that of solving a small number of standard robust problems. We then investigate the conservatism benefits and downside probability guarantees implied by this approach and compare to the standard robust approach. Finally, we illustrate theme thodology on an asset allocation example consisting of historical market data over a 25-year investment horizon and find in every case we explore that relaxing standard robustness with soft robustness yields a seemingly favorable risk-return trade-off: each case results in a higher out-of-sample expected return for a relatively minor degradation of out-of-sample downside performance. © 2010 INFORMS.

Are immigrant remittance flows a source of capital for development?

There is a general presumption in the literature and among policymakers that immigrant remittances play the same role in economic development as foreign direct investment and other capital flows, but this is an open question. We develop a model of remittances based on the economics of the family that implies that remittances are not profit-driven, but are compensatory transfers, and should have a negative correlation with GDP growth. This is in contrast to the positive correlation of profit-driven capital flows with GDP growth. We test this implication of our model using a new panel data set on remittances and find a robust negative correlation between remittances and GDP growth. This indicates that remittances may not be intended to serve as a source of capital for economic development. © 2005 International Monetary Fund.

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

Scaling limits of a model for selection at two scales

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

WormSizer: high-throughput analysis of nematode size and shape.

The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy) mutant is short and fat and that a Long (Lon) mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma) mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc) and Roller (Rol) mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.