Tree species-area and species-diameter relationships at three lowland rain forest sites in Sumatra

Data from three forest sites in Sumatra (Batang Ule, Pasirmayang and Tebopandak) have been analysed and compared for the effects of sample area cut-off, and tree diameter cut-off. An 'extended inverted exponential model' is shown to be well suited to fitting tree-species-area curves. The model yields species carrying capacities of 680 for Batang Ule, 380 species for Pasirmayang, and 35 for Tebopandak (tree diameter >10cm). It would seem that in terms of species carrying capacity, Tebopandak and Pasirmayang are rather similar, and both less diverse than the hilly Batang Ule site. In terms of conservation policy, this would mean that rather more emphasis should be put on conserving hilly sites on a granite substratum. For Pasirmayang with tree diameter >3cm, the asymptotic species number estimate is 567, considerably higher than the estimate of 387 species for trees with diameter >10cm. It is clear that the diameter cut-off has a major impact on the estimate of the species carrying capacity. A conservative estimate of the total number of tree species in the Pasirmayang region is 632 species! In sampling exercises, the diameter cut-off should not be chosen lightly, and it may be worth adopting field sampling procedures which involve some subsampling of the primary sample area, where the diameter cut-off is set much lower than in the primary plots.

A new parameterization of Johnson's SB distribution with application to fitting forest tree diameter data

The SB distributional model of Johnson's 1949 paper was introduced by a transformation to normality, that is, z ~ N(0, 1), consisting of a linear scaling to the range (0, 1), a logit transformation, and an affine transformation, z = γ + δu. The model, in its original parameterization, has often been used in forest diameter distribution modelling. In this paper, we define the SB distribution in terms of the inverse transformation from normality, including an initial linear scaling transformation, u = γ′ + δ′z (δ′ = 1/δ and γ′ = �γ/δ). The SB model in terms of the new parameterization is derived, and maximum likelihood estimation schema are presented for both model parameterizations. The statistical properties of the two alternative parameterizations are compared empirically on 20 data sets of diameter distributions of Changbai larch (Larix olgensis Henry). The new parameterization is shown to be statistically better than Johnson's original parameterization for the data sets considered here.

Tree diameter distribution modelling: introducing the logitlogistic distribution

Johnson's SB distribution is a four-parameter distribution that is transformed into a normal distribution by a logit transformation. By replacing the normal distribution of Johnson's SB with the logistic distribution, we obtain a new distributional model that approximates SB. It is analytically tractable, and we name it the "logitlogistic" (LL) distribution. A generalized four-parameter Weibull model and the Burr XII model are also introduced for comparison purposes. Using the distribution "shape plane" (with axes skew and kurtosis) we compare the "coverage" properties of the LL, the generalized Weibull, and the Burr XII with Johnson's SB, the beta, and the three-parameter Weibull, the main distributions used in forest modelling. The LL is found to have the largest range of shapes. An empirical case study of the distributional models is conducted on 107 sample plots of Chinese fir. The LL performs best among the four-parameter models.

Bivariate distribution modeling with tree diameter and height data

The Logit-Logistic (LL), Johnson's SB, and the Beta (GBD) are flexible four-parameter probability distribution models in terms of the (skewness-kurtosis) region covered, and each has been used for modeling tree diameter distributions in forest stands. This article compares bivariate forms of these models in terms of their adequacy in representing empirical diameter-height distributions from 102 sample plots. Four bivariate models are compared: SBB, the natural, well-known, and much-used bivariate generalization of SB; the bivariate distributions with LL, SB, and Beta as marginals, constructed using Plackett's method (LL-2P, etc.). All models are fitted using maximum likelihood, and their goodness-of-fits are compared using minus log-likelihood (equivalent to Akaike's Information Criterion, the AIC). The performance ranking in this case study was SBB, LL-2P, GBD-2P, and SB-2P

A new procedure to optimize the selection of groups in a classification tree

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.

Beyond the Orange and the Green. The Diversification of the Qualitative Social Research Landscape in Northern Ireland.

The Northern Ireland conflict has been described as one of the most over-researched conflicts in the world. However, this is a relatively recent development. For many years, when the conflict was most intense, social scientists in Northern Ireland were silent and not vocal. The sectarian violence that dominated the life in Northern Ireland as well as the fact that the country was a fundamentally unjust society contributed to this silence. However, since the peace process began in the mid 1990s, a growing number of qualitative studies have been published, utilising one-to-one interviews and focus group discussions, in order to "make people's voices heard" and deal with the consequences of the so-called "Troubles". This paper looks into the emergence of a qualitative social research landscape in Northern Ireland beyond the conflict and explores issues so far neglected. It is argued that a number of factors have contributed to this, among them the availability of research funding to voluntary and community sector organisations that use their data to influence policy-making and equality legislation in a country which is still deeply divided along socio-religious lines.

High-precision radiocarbon measurements of contemporaneous tree-ring wood from the British Isles and New Zealand: AD 1850-950.

The University of Waikato, Hamilton, New Zealand and The Queen's University of Belfast, Northern Ireland radiocarbon dating laboratories have undertaken a series of high-precision measurements on decadal samples of dendrochronologically dated oak (Quercus petraea) from Great Britain and cedar (Libocedrus bidwillii) and silver pine (Lagarostrobos colensoi) from New Zealand. The results show an average hemispheric offset over the 900 yr of measurement of 40±13 yr. This value is not constant but varies with a periodicity of about 130 yr. The Northern Hemisphere measurements confirm the validity of the Pearson et al. (1986) calibration dataset.

Novel frenatins from the skin of the Australasian Giant White-lipped tree frog, Litoria infrafrenata: cloning of precursor cDNAs and identification in defensive skin secretion.

The Australasian anuran amphibian genus Litoria, contains many phenotypically-diverse species as a result of radial evolution of an ancestral species into different biotopes much in the manner of the indigenous marsupial mammals. In common with members of the Central/South American genus Phyllomedusa, their specialized skin granular glands are factories for the production of a plethora of biologically-active peptides. Here we report a more detailed study of those present in the defensive skin secretion of the Australasian giant white-lipped tree frog, Litoria infrafrenata, and, for the first time, we have identified three novel frenatins by deduction of primary structures from cDNAs that were cloned from a library constructed from lyophilized skin secretion using a recently-developed technique. All open-reading frames consisted of a putative signal peptide and an acidic pro-region followed by a single copy of a frenatin peptide. Processed peptides corresponding in molecular mass to the deduced molecular masses of frenatins (named 1.1, 3, 3.1 and 4.1) were identified in the same secretion sample using HPLC and mass spectroscopy. The application of this technique thus permits parallel peptidomic and transcriptomic analyzes on the same lyophilized skin secretion sample circumventing sacrifice of specimens from endangered herpetofauna.