Zoogeography of Bats

The Order Chiroptera is the second largest order of mammals, with, according to my most recent revised figure, 846 species. Inasmuch as the group is world-wide, reaching many distant islands, and inasmuch as many species and higher groups are quite localized and some very distinctive, one might expect that a good deal of work on bat zoogeography would have been undertaken. However, such is not the case. Darlington (1957, pp. 320-410) does discuss the general geographical patterns of bats, and Tate (1946) gives a useful analysis of the bats of the Malay archipelago. However, many writers on zoogeography have given them at best a very perfunctory treatment. This contrasts markedly with the attention given to bird zoogeography. From talking with various zoogeographers, I suspect the reason is that whereas birds are treated as a separate group in their own right, bats are treated as part of the Class Mammalia. Since all bats can fly, there seems to be a general assumption that they regularly cross various kinds of geographical barriers at will, with the result that they have been rather consistently downgraded with respect to flightless mammals in zoogeographical studies (see, e.g., Bigalke, 1968). Actually, except for their ability at crossing narrow water gaps without too much difficulty, bats have several advantages in zoogeographical studies over various other groups of land vertebrates. With a very few exceptions, they are not likely to fly over the open ocean as part of their normal activities. They are almost entirely free of the problems of human introduction. I know of only one case where (unintentional) human introduction has played a role, and this has not resulted in an introduced population. This was a specimen of the North American Myotis lucifugus, collected in Iceland, that is believed to have been inadvertently transported by ship (see Koopman & Gudmundsson, 1966). Aside from the advantages mentioned above, the large number of species, at least in the tropics, means that there are enough individual cases to enable zoogeographical patterns to be worked out

Statistical Software for State Space Methods

In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods for the analysis of time series. This is followed by a concise overview of linear Gaussian state space analysis including the modelling framework and appropriate estimation methods. We discuss the important class of unobserved component models which incorporate a trend, a seasonal, a cycle, and fixed explanatory and intervention variables for the univariate and multivariate analysis of time series. We continue the discussion by presenting methods for the computation of different estimates for the unobserved state vector: filtering, prediction, and smoothing. Estimation approaches for the other parameters in the model are also considered. Next, we discuss how the estimation procedures can be used for constructing confidence intervals, detecting outlier observations and structural breaks, and testing model assumptions of residual independence, homoscedasticity, and normality. We then show how ARIMA and ARIMA components models fit in the state space framework to time series analysis. We also provide a basic introduction for non-Gaussian state space models. Finally, we present an overview of the software tools currently available for the analysis of time series with state space methods as they are discussed in the other contributions to this special volume.

From Classical to Quantum Mechanics: "How to translate physical ideas into mathematical language"

In this paper, we investigate the connection between Classical and Quantum Mechanics by dividing Quantum Theory in two parts: - General Quantum Axiomatics (a system is described by a state in a Hilbert space, observables are self-adjoint operators and so on) - Quantum Mechanics properly that specifies the Hilbert space, the Heisenberg rule, the free Hamiltonian... We show that General Quantum Axiomatics (up to a supplementary "axiom of classicity") can be used as a non-standard mathematical ground to formulate all the ideas and equations of ordinary Classical Statistical Mechanics. So the question of a "true quantization" with "h" must be seen as an independent problem not directly related with quantum formalism. Moreover, this non-standard formulation of Classical Mechanics exhibits a new kind of operation with no classical counterpart: this operation is related to the "quantization process", and we show why quantization physically depends on group theory (Galileo group). This analytical procedure of quantization replaces the "correspondence principle" (or canonical quantization) and allows to map Classical Mechanics into Quantum Mechanics, giving all operators of Quantum Mechanics and Schrodinger equation. Moreover spins for particles are naturally generated, including an approximation of their interaction with magnetic fields. We find also that this approach gives a natural semi-classical formalism: some exact quantum results are obtained only using classical-like formula. So this procedure has the nice property of enlightening in a more comprehensible way both logical and analytical connection between classical and quantum pictures.Comment: 47 page

Classification of Bats

In the 10th edition of Systema Naturae, published in 1758 and the starting point of the binomial system of nomenclature currently employed in zoology, Linnaeus recognized seven species of bats, which he placed in a single genus (Vespertilio) and grouped with the primates and dermopterans. All of Linnaeus\u27s seven species are recognized today, but as they now are classified each represents a distinctive genus, and the genera are arranged taxonomically in five different families of two suborders. In contrast to Linnaeus\u27s scheme, the present classification of bats (long ago placed in a distinct order, Chiroptera) lists 847 Recent species, belonging to 169 Recent genera, 15 families (at least three other families are known only as fossils), and two suborders (see Table 1). Much work remains in elucidating the relationships of bats, even at the higher taxonomic levels. In the plethora of publications that have appeared in recent years on the distribution and systematics of bat genera and species, the trend has been to reduce the number of recognized taxa at these levels, even though some new species, and occasionally a new genus, are named annually. Several of the subsequent papers in this symposium touch on problems relating to classification

Missing observations in observation-driven time series models

We argue that existing methods for the treatment of missing observations in time-varying parameter observation-driven models lead to inconsistent inference. We provide a formal proof of this inconsistency for a Gaussian model with time-varying mean. A Monte Carlo simulation study supports this theoretical result and illustrates how the inconsistency problem extends to score-driven and, more generally, to observation-driven models, which include well-known models for conditional volatility. To overcome the problem of inconsistent inference, we propose a novel estimation procedure based on indirect inference. This easy-to-implement method delivers consistent inference. The asymptotic properties of the new method are formally derived. Our proposed estimation procedure shows a promising performance in a Monte Carlo simulation exercise as well as in an empirical study concerning the measurement of conditional volatility from financial returns data

Chalinolobus and Glauconycteris

10 p. : ill. ; 24 cm.Includes bibliographical references (p. 9-10)."The African genus Glauconycteris is shown to be a subgenus of the Australasian genus Chalinolobus. The two Pacific island taxa of Chalinolobus are here called Chalinolobus tuberculatus and Chalinolobus gouldi neocaledonicus. Three problematical species of the subgenus Glauconycteris are discussed and their suggested taxonomic status are represented by the names Chalinolobus (Glauconycteris) variegatus machadoi, Chalinolobus (Glauconycteris) beatrix humeralis, and Chalinolobus (Glauconycteris) alboguttatus"--P. 9

Papuan bats

34 p. : map ; 26 cm.Includes bibliographical references (p. 31-34)."The bat fauna of eastern Papua, including Central, Northern, and Milne Bay provinces on the mainland and the Louisiade, D'Entrecasteaux, and Trobriand archipelagos, is reviewed. Five families, 23 genera, and 45 species are known from the area. Forty species are known from the mainland or continental islands and 23 from from one or another island (or islands) of the three archipelagos. Only six species occur on the islands but not on the mainland and only two of these (Dobsonia pannietensis, Kerivoula agnella) are endemic. Most of the insular species for which precise affinities can be determined show closest relationship to mainland populations, but a few have their affinities with those of the Bismarcks or Solomons. Most of the East Papuan mainland species are apparently confined to the lowlands. The East Papuan highland bat fauna is seemingly depauperate compared with that of more extensive highland areas to the northwest. There is only one documented case of altitudinal variation within a species (Pipistrellus) and only one of altitudinal replacement among close relatives (Tadarida). A new subspecies, Rhinolophus megaphyllus vandeuseni, is described"--P. [1]