The scrub pythons (Morelia amethistina complex) are revised based on museum specimens and new material recently collected in eastern Indonesia. Morelia kinghorni (formerly M. amethistina kinghorni) and M. amethistina (formerly M. amethistina amethistina) are recognized as species, and three new species are described. The phylogenetic relationships of scrub pythons are resolved using morphological and molecular characters Scrub pythons are most closely related to Morelia boeleni and have undergone both ancient divergences and a relatively recent radiation. The distribution of scrub pythons corresponds well with areas of endemism recognized in earlier studies of other taxa. Their distribution and evolution appears to have been shaped by combined effects of dispersal and vicariance. Scrub python populations exhibit interesting color and pattern polymorphism and ontogenetic change, and these characteristics vary among populations.

No description available.

The green python Morelia viridis is a most striking animal. Individuals are born either brick red or bright yellow and both colours change to green as adults. These colours and the remarkable colour change have long made them of interest to biologists and in demand for the pet trade. Despite this interest nothing is known of their distribution, biology or ecology in the wild. Here I address this knowledge gap by presenting results from the first detailed study of the species, at Iron Range on eastern Cape York Peninsula, Australia.¶ Individual growth was described by the von Bertalanffy growth curve, with a maximum predicted size of 1.35 metres snout-vent length. Males matured at 2.4 years and females at 3.6 years, and growth was indeterminate after approximately 12 years. The colour change from yellow to green occurs at 55 centimetres, which corresponds to individuals approximately a year old. There was no sexual dimorphism in adults, however juvenile females had larger heads than juvenile males. Adult sized individuals comprised ~50% of the population.¶ Females had a home range of 6.2 ± 1.9 ha (mean ± SE), which was positively correlated with their snout-vent length. Males adopted a roaming strategy through suitable habitat while juveniles were restricted to areas where more light reached the ground. There was overlap between multiple female home ranges, and between female home ranges and the movement paths of males. There were no differences in the distances moved by males and females of any size, although the variation in movement distances was greater in the dry season than the wet season.¶ Green pythons are obligate ambush predators which eat a variety of prey. They show an ontogenetic shift from invertebrates and terrestrial, diurnal reptiles to birds and terrestrial, nocturnal mammals. This diet change is concurrent with a shift in the time of hunting, and the location and characteristics of ambush sites. Yellow individuals were usually found within ten metres of the ground, while green individuals used the full vegetation strata and were often found in the canopy.¶ The three colour morphs of the green python appear to be adaptive for camouflage rather than intraspecific communication, as conspicuousness of each morph was always greater to a predator than to that of a conspecific. Using advanced light analysis techniques I show that each colour morph is adaptive for camouflage from visually orientated avian predators under different environmental conditions. Yellow and red morphs are half as conspicuous as green individuals would be in locations near the ground where juveniles hunt during the day. Green was the least conspicuous morph in only the canopy, where it was half as conspicuous as either the red or yellow morph. In both leafy and non-leafy sub-canopy environments green individuals were more conspicuous than both yellow and red morphs. Red morphs were least conspicuous in only the non-leafy sub-canopy environment. The conspicuousness of green males decreased with age, but this was not the case with green females. Predation of plasticine models of the three colour morphs showed that red models were ten times more likely to be predated than either green or yellow morphs, however the model colours did not always match the real morph colours.¶ There is a large predicted global distribution in Papua New Guinea, including some offshore islands, however the Australian range is restricted to small areas of eastern Cape York Peninsula. In Australia green pythons occurred in nine regional ecosystems, with most records for the closed semi-deciduous mesophyll vine forest ecosystem. A mark-recapture study at Iron Range captured 101 individuals 147 times over two wet seasons, which equates to a population size of 227 ± 81 individuals in the study area of 51 hectares. Based on the known population structure at this site only 114 (or 50%) of these individuals are adult. Although green pythons have a high density at the one intensely studied site and are predicted to occur over a large geographic area, my data are insufficient to conclude that the species is not vulnerable.

Thesis (Ph. D.)--University of California, San Diego, 2001. / Vita. Includes bibliographical references (leaves 574-587).

[EN] To obtain the market value for urban properties, the following is necessary for the decision making in different scenarios: in case of dealing with financial institutions, the focus will be in acquiring knowledge of the value of the property to finance a mortgage. One of the different government orders are to collect property taxes, so this profit will serve as the foundation for proceedings before public and private organizations. For an accurate estimate of the price or value that will describe the market conditions, it is necessary to build models that will be capable of calculating such value. The synthetic methods that currently use a minor amount of information are the ones that are mostly used by appraisers, as well as the econometric models. Also, they are considered as the concept of multiple linear regression that utilize abundant observations. In reality the econometric models are a generalization of synthetic methods. On the other hand, artificial neural networks and in particular the multi-layer network, can be an alternative for a price estimate. Currently a comparison is being performed between the selected econometric model and the neural network, revealing that the networks give a better outcome for price estimates. This study has been achieved in Morelia, Michoacán, Mexico for several housing segments. / [ES] Obtener el valor de mercado para inmuebles urbanos es necesario para la toma de decisiones en diferentes escenarios: tratándose de instituciones financieras, su interés radica en conocer este valor para el financiamiento de préstamo con garantía hipotecaria, a los diferentes órdenes de gobierno para cobrar los impuestos catastrales, así este valor servirá de base para la realización de diferentes trámites ante entidades públicas o particulares. Para una buena estimación del precio o valor que explique las condiciones del mercado, es necesario construir modelos capaces de estimar dicho valor. Actualmente los métodos sintéticos que usan información escasa son los más utilizados por los tasadores, así como los modelos econométricos -también denominados con el concepto de regresión lineal múltiple- que usan muchas observaciones, en realidad los modelos econométricos son una generalización de los métodos sintéticos. Por otro lado, las redes neuronales artificiales, y en concreto la red multicapa, pueden ser una alternativa para la estimación del precio. En el presente se realiza una comparativa entre el modelo econométrico seleccionado y la red neuronal, demostrando que las redes obtienen mejores resultados en la estimación de precio. El estudio se ha realizado en la ciudad de Morelia, Michoacán, México, para varios segmentos de vivienda. / [CA] Obtindre el valor de mercat per a immobles urbans és necessari per a la presa de decisions en diferents escenaris: tractant-se d'institucions financeres, el seu interès està en conèixer aquest valor per al finançament de préstec amb garantia hipotecària, als diferents ordres de govern per cobrar els impostos cadastrals. Així aquest valor servirà de base per a la realització de diferents tràmits davant entitats públiques o particulars. Per a una bona estimació del preu o valor que expliqui les condicions del mercat, cal construir models capaços d'estimar aquest valor. Actualment els mètodes sintètics que fan servir informació escassa són els més utilitzats pels valuadors, així com els models economètrics -també denominats de regressió lineal múltiple, que fan servir moltes observacions. En realitat els models economètrics són una generalització dels mètodes sintètics. D'altra banda, les xarxes neuronals artificials, i en concret la xarxa multicapa, poden ser una alternativa per a l'estimació del preu. En el present treball es realitza una comparativa entre el model economètric seleccionat i la xarxa neuronal, demostrant que les xarxes obtenen millors resultats en l'estimació de preu. L'estudi s'ha realitzat a la ciutat de Morelia, Michoacán, Mèxic, per a diversos segments d'habitatge. / Preciado Carrillo, JC. (2016). Valoración de inmuebles urbanos comparativa modelo regresión multivariable versus redes neuronales artificiales para la ciudad de Morelia Michoacán, México [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/62202