Dry season habitat use by critically endangered white-shouldered ibis in northern Cambodia

We present the first scientific study of white-shouldered ibis Pseudibis davisoni habitat preferences in dry dipterocarp forest. Foraging sites included seasonal pools, forest understorey grasslands and fallow rice fields, with terrestrial sites used more following rainfall. Habitat and anthropogenic effects in logistic models of foraging site selection were examined by multimodel inference and model averaging. White-shouldered ibis preferred pools with greater cover of short vegetation (<25 cm) and less of the boundary enclosed, and forest sites with greater cover of bare substrate and lower people encounter rate. At forest sites, livestock density was positively related to bare substrate extent and thus may improve suitability for foraging ibis. At pools, livestock removed tall vegetation between the early and late dry season indicating their importance in opening up foraging habitats after wet season growth. However, by the late dry season, pools with greater livestock density had less short vegetation, the habitat favoured by ibis. Conservation strategies for white-shouldered ibis must consider a range of habitats, not just seasonal wetlands, and should incorporate extensive grazing and associated burning practises of local communities. Further understanding of the effects of these practices on vegetation, prey abundance and prey availability are therefore needed for effective conservation of this species. This will also develop our understanding of potentially beneficial anthropogenic influences in tropical environments.     

A note on Gauss--Hermite quadrature

For Gauss—Hermite quadrature, we consider a systematicmethod for transforming the variable of integration so thatthe integrand is sampled in an appropriate region. The effectivenessof the quadrature then depends on the ratio of the integrandto some Gaussian density being a smooth function, well approximatedby a low-order polynomial. It is pointed out that, in this approach,order one Gauss-Hermite quadrature becomes the Laplace approximationmxHermitequadrature becomes the Laplace approximationmxHermite quadraturebecomes the Laplace approximationmxHermite quadrature becomesthe Laplace approximation. Thus the quadrature as implementedhere can be thought of as a higher-order Laplace approximation.     

Tinbergen on mirror neurons

Fifty years ago, Niko Tinbergen defined the scope of behavioural biology with his four problems: causation, ontogeny, survival value and evolution. About 20 years ago, there was another highly significant development in behavioural biology—the discovery of mirror neurons (MNs). Here, I use Tinbergen''s original four problems (rather than the list that appears in textbooks) to highlight the differences between two prominent accounts of MNs, the genetic and associative accounts; to suggest that the latter provides the defeasible ‘best explanation’ for current data on the causation and ontogeny of MNs; and to argue that functional analysis, of the kind that Tinbergen identified somewhat misleadingly with studies of ‘survival value’, should be a high priority for future research. In this kind of functional analysis, system-level theories would assign MNs a small, but potentially important, role in the achievement of action understanding—or another social cognitive function—by a production line of interacting component processes. These theories would be tested by experimental intervention in human and non-human animal samples with carefully documented and controlled developmental histories.     

Improving neural network prediction of effluent from biological wastewater treatment plant of industrial park using fuzzy learning approach

Three types of adaptive network-based fuzzy inference system (ANFIS) in which the online monitoring parameters served as the input variable were employed to predict suspended solids (SS_eff), chemical oxygen demand (COD_eff), and pH_eff in the effluent from a biological wastewater treatment plant in industrial park. Artificial neural network (ANN) was also used for comparison. The results indicated that ANFIS statistically outperforms ANN in terms of effluent prediction. When predicting, the minimum mean absolute percentage errors of 2.90, 2.54 and 0.36% for SS_eff, COD_eff and pH_eff could be achieved using ANFIS. The maximum values of correlation coefficient for SS_eff, COD_eff, and pH_eff were 0.97, 0.95, and 0.98, respectively. The minimum mean square errors of 0.21, 1.41 and 0.00, and the minimum root mean square errors of 0.46, 1.19 and 0.04 for SS_eff, COD_eff, and pH_eff could also be achieved.     

Computing likelihoods for coalescents with multiple collisions in the infinitely many sites model

One of the central problems in mathematical genetics is the inference of evolutionary parameters of a population (such as the mutation rate) based on the observed genetic types in a finite DNA sample. If the population model under consideration is in the domain of attraction of the classical Fleming-Viot process, such as the Wright-Fisher- or the Moran model, then the standard means to describe its genealogy is Kingman's coalescent. For this coalescent process, powerful inference methods are well-established. An important feature of the above class of models is, roughly speaking, that the number of offspring of each individual is small when compared to the total population size, and hence all ancestral collisions are binary only. Recently, more general population models have been studied, in particular in the domain of attraction of so-called generalised Lambda-Fleming-Viot processes, as well as their (dual) genealogies, given by the so-called Lambda-coalescents, which allow multiple collisions. Moreover, Eldon and Wakeley (Genetics 172:2621-2633, 2006) provide evidence that such more general coalescents might actually be more adequate to describe real populations with extreme reproductive behaviour, in particular many marine species. In this paper, we extend methods of Ethier and Griffiths (Ann Probab 15(2):515-545, 1987) and Griffiths and Tavaré (Theor Pop Biol 46:131-159, 1994a, Stat Sci 9:307-319, 1994b, Philos Trans Roy Soc Lond Ser B 344:403-410, 1994c, Math Biosci 12:77-98, 1995) to obtain a likelihood based inference method for general Lambda-coalescents. In particular, we obtain a method to compute (approximate) likelihood surfaces for the observed type probabilities of a given sample. We argue that within the (vast) family of Lambda-coalescents, the parametrisable sub-family of Beta(2 - alpha, alpha)-coalescents, where alpha in (1, 2], are of particular relevance. We illustrate our method using simulated datasets, thus obtaining maximum-likelihood estimators of mutation and demographic parameters.