Temporal and spatial variation of limnological variables and biomass of different macrophyte species in a Neotropical reservoir (São Paulo - Brazil)

Aim: This study reports an investigation of limnological characteristics and aquatic macrophyte occurrence in a neotropical reservoir in order to assess the spatio-temporal variation of water and sediment variables and their influence on plant distribution. Methods: Macrophytes, water and sediment samples were collected from a Brazilian reservoir in different seasons from four main arms of the reservoir. In total sixteen water-sediment variables were analyzed including N:P ratio and Trophic State Index. The plants were collected using a quadrat sampling procedure and the dry weight per sample was measured. MANOVA was performed to evaluate spatial and temporal variation of environmental variables as well as seasonal biomass differences. To assess the relationship among environmental variables and macrophytes an ordination analysis (using Canonical Correspondence Analysis: CCA) was carried out. Results: The spatial and temporal variation of limnological variables generated a heterogeneous system which supports the presence of different species of macrophyte. pH, dissolved oxygen and sediment composition were important predictors of Polygonum lapathifolium occurrence while nutrients were associated with Eichhornia crassipes and Pistia stratiotes. Inorganic substances were related to biomass variation of Eichhornia azurea and Myriophyllum aquaticum. Conclusions: The spatial variation of the environmental variables has caused heterogeneity in the reservoir and it may support the occurrence of different species of macrophyte. Limnological variables highlighted in CCA are important to predict the species occurrence and their control in the study area

Self-adjoint Lyapunov variables, temporal ordering and irreversible representations of Schroedinger evolution

In non relativistic quantum mechanics time enters as a parameter in the Schroedinger equation. However, there are various situations where the need arises to view time as a dynamical variable. In this paper we consider the dynamical role of time through the construction of a Lyapunov variable - i.e., a self-adjoint quantum observable whose expectation value varies monotonically as time increases. It is shown, in a constructive way, that a certain class of models admit a Lyapunov variable and that the existence of a Lyapunov variable implies the existence of a transformation mapping the original quantum mechanical problem to an equivalent irreversible representation. In addition, it is proved that in the irreversible representation there exists a natural time ordering observable splitting the Hilbert space at each t>0 into past and future subspaces.Comment: Accepted for publication in JMP. Supercedes arXiv:0710.3604. Discussion expanded to include the case of Hamiltonians with an infinitely degenerate spectru

A Temporal Logic for Hyperproperties

Hyperproperties, as introduced by Clarkson and Schneider, characterize the correctness of a computer program as a condition on its set of computation paths. Standard temporal logics can only refer to a single path at a time, and therefore cannot express many hyperproperties of interest, including noninterference and other important properties in security and coding theory. In this paper, we investigate an extension of temporal logic with explicit path variables. We show that the quantification over paths naturally subsumes other extensions of temporal logic with operators for information flow and knowledge. The model checking problem for temporal logic with path quantification is decidable. For alternation depth 1, the complexity is PSPACE in the length of the formula and NLOGSPACE in the size of the system, as for linear-time temporal logic

Spatio-Temporal Wildland Arson Crime Functions

Wildland arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p) model, is estimated for six high arson Census tracts in the state for the period 1994-2001. Spatio-temporal lags of wildland arson ignitions are introduced as dummy variables indicating the presence of an ignition in previous days in surrounding Census tracts and counties. Temporal lags of ignition activity within the Census tract are shown to be statistically significant and larger than previously reported for non-spatial variants of the PAR(p) model. Spatio-temporal lagged relationships with current arson that were statistically significant show that arson activity up to a county away explains arson patterns, and spatio-temporal lags longer than two days were not significant. Other variables showing significance include weather and wildfire activity in the previous six years, but prescribed fire and several variables that provide evidence that such activity is consistent with an economic model of crime were less commonly significant.Resource /Energy Economics and Policy,

Measuring the dependence structure between yield and weather variables

The design and pricing of weather-based crop insurance and weather derivatives is strongly based on an implicit assumption that the dependence structure between yields and weather variables remains unchanged over time. In this paper, we prove this assumption based on empirical time series of weather variables and farm wheat yields from Kazakhstan over the period from 1961 to 2003. By employing two different methods to measure dependence in multivariate distributions – the regression analysis and copula approach – we reveal statistically significant temporal changes in the joint distribution of relevant variables. These empirical results indicate that greater effort is required to capture potential temporal changes in the dependence between yield and weather variables, and subsequently to consider them in the design and rating of weather-based insurance instruments.weather-based index insurance, dependence structure, copula estimation, Bayesian hierarchical model, Kazakhstan.