Land use and climate influences on waterbirds in the Prairie Potholes

Aim We examined the influences of regional climate and land‐use variables on mallard (Anas platyrhynchos), blue‐winged teal (Anas discors), ruddy duck (Oxyura jamaicensis) and pied‐billed grebe (Podilymbus podiceps) abundances to inform conservation planning in the Prairie Pothole Region of the United States. Location The US portion of Bird Conservation Region 11 (US‐BCR11, the Prairie Potholes), which encompasses six states within the United States: Montana, North Dakota, South Dakota, Nebraska, Minnesota and Iowa. Methods We used data from the North American Breeding Bird Survey (NABBS), the National Land Cover Data Set, and the National Climatic Data Center to model the effects of environmental variables on waterbird abundance. We evaluated land‐use covariates at three logarithmically related spatial scales (1000, 10,000 and 100,000 ha), and constructed hierarchical spatial count models a priori using information from published habitat associations. Model fitting was performed using a hierarchical modelling approach within a Bayesian framework. Results Models with the same variables expressed at different scales were often in the best model subset, indicating that the influence of spatial scale was small. Both land‐use and climate variables contributed strongly to predicting waterbird abundance in US‐BCR11. The strongest positive influences on waterbird abundance were the percentage of wetland area across all three spatial scales, herbaceous vegetation and precipitation variables. Other variables that we included in our models did not appear to influence waterbirds in this study. Main conclusions Understanding the relationships of waterbird abundance to climate and land use may allow us to make predictions of future distribution and abundance as environmental factors change. Additionally, results from this study can suggest locations where conservation and management efforts should be focused.     

Natural selection. V. How to read the fundamental equations of evolutionary change in terms of information theory

The equations of evolutionary change by natural selection are commonly expressed in statistical terms. Fisher's fundamental theorem emphasizes the variance in fitness. Quantitative genetics expresses selection with covariances and regressions. Population genetic equations depend on genetic variances. How can we read those statistical expressions with respect to the meaning of natural selection? One possibility is to relate the statistical expressions to the amount of information that populations accumulate by selection. However, the connection between selection and information theory has never been compelling. Here, I show the correct relations between statistical expressions for selection and information theory expressions for selection. Those relations link selection to the fundamental concepts of entropy and information in the theories of physics, statistics and communication. We can now read the equations of selection in terms of their natural meaning. Selection causes populations to accumulate information about the environment.     

Assessing population parameters and trends of Guiana dolphins (Sotalia guianensis): An eight‐year mark‐recapture study

This study represents the first attempt to study the population dynamics of Guiana dolphins (Sotalia guianensis), by evaluating a set of demographic parameters. The population of the Caravelas River estuary, eastern Brazil, was systematically monitored through a long‐term mark‐recapture experiment (2002–2009). Abundance estimates revealed a small population (57–124 dolphins), comprised of resident dolphins and individuals that temporarily leave or pass through the study area. Temporary emigration from the estuary to adjacencies (γ″= 0.33 ± 0.07 SE) and return rate (1 ?γ′= 0 .67) were moderate and constant, indicating that some dolphins use larger areas. Survival rate (?= 0.88 ± 0.07 SE) and abundance were constant throughout the study period. Power analysis showed that the current monitoring effort has high probability of detecting abrupt population declines (1 ?β= 0.9). Although the monitoring is not yet sensitive to subtle population trends, sufficient time to identify them is feasible (additional 3 yr). Despite such apparent stability, this population, as many others, inhabits waters exposed to multiple human‐related threats. Open and closed population modeling applied to photo‐identification data provide a robust baseline for estimating several demographic parameters and can be applied to other populations to allow further comparisons. Such synergistic efforts will allow a reliable definition of conservation status of this species.     

Vague-to-crisp dynamics of percept formation modeled as operant (selectionist) process

We model the vague-to-crisp dynamics of forming percepts in the brain by combining two methodologies: dynamic logic (DL) and operant learning process. Forming percepts upon the presentation of visual inputs is likened to model selection based on sampled evidence. Our framework utilizes the DL in selecting the correct “percept” among competing ones, but uses an intrinsic reward mechanism to allow stochastic online update in lieu of performing the optimization step of the DL framework. We discuss the connection of our framework with cognitive processing and the intentional neurodynamic cycle.     

Mesoscale Modeling of Amphiphilic Fluid Dynamics

Abstract

So-called “vector models”, in which surfactant molecules retain only translational and orientational degrees of freedom, have been used to study the equilibrium properties of amphiphilic fluids for nearly a decade now. We demonstrate that hydrodynamic lattice-gas automata provide an effective means of coupling the Hamiltonian of such vector models to hydrodynamic flow with conserved momentum, thereby providing a self-consistent treatment of the hydrodynamics of amphiphilic fluids. In this “talk”, we describe these hydrodynamic lattice-gas models in two and three dimensions, and present their application to problems of amphiphilic-fluid hydrodynamics, including the dynamics of phase separation and the shear-induced sponge-to-lamellar phase transition.     

Assessing changes over time in healthcare provider performance: Addressing regression to the mean over multiple time points

In recent years, the evaluation of healthcare provider performance has become standard for governments, insurance companies, and other stakeholders. Often, performance is compared across providers using indicators in one time period, for example a year. However it is often important to assess changes in the performance of individual providers over time. Such analyses can be used to determine if any providers have significant improvements, deteriorations, unusual patterns or systematic changes in performance. Studies which monitor healthcare provider performance in this way have to date typically been limited to comparing performance in the most recent period with performance in a previous period. It is also important to consider a longer‐term view of performance and assess changes over more than two periods. In this paper, we develop test statistics that account for variable numbers of prior performance indicators, and show that these are particularly useful for assessing consecutive improvements or deteriorations in performance. We apply the tests to coronary artery bypass graft mortality rates in New York State hospitals, and mortality data from Australian and New Zealand intensive care units. Although our applications are to medical data, the new tests have broad application in other areas.     

Seemingly Unrelated Generalized Linear Models

By using deviance standardized residuals, the seemingly unrelated regression estimation procedure is extended to generalized linear models, and fitted by an iterative procedure. The matrix of cross products of standardized residuals is asymptotically multivariate normal, and can be used for further multivariate analyses and for hypothesis testing.     

Analysing gametic variation with an animal model

Summary A method is presented to treat gametes as homozygous diploid individuals allowing their inclusion into the relationship matrix between animals. In this way standard techniques developed for the analysis of individual genetic variation may be used to analyze gametic variation. An example is given for maternal gametic imprinting and equivalence is shown to a gametic model. The method may also be adopted for the analysis of species (like the honey bee) with one haploid sex.AGBU is a joint initiative of UNE and the NSW Department of Agriculture