O comprimento descritivo mínimo na amostragem por transectos lineares

Apresenta·se um breve resumo histórico da evolução da amostragem por transectos lineares e desenvolve·se a sua teoria. Descrevemos a teoria de amostragem por transectos lineares, proposta por Buckland (1992), sendo apresentados os pontos mais relevantes, no que diz respeito à modelação da função de detecção. Apresentamos uma descrição do princípio CDM (Rissanen, 1978) e a sua aplicação à estimação de uma função densidade por um histograma (Kontkanen e Myllymãki, 2006), procedendo à aplicação de um exemplo prático, recorrendo a uma mistura de densidades. Procedemos à sua aplicação ao cálculo do estimador da probabilidade de detecção, no caso dos transectos lineares e desta forma estimar a densidade populacional de animais. Analisamos dois casos práticos, clássicos na amostragem por distâncias, comparando os resultados obtidos. De forma a avaliar a metodologia, simulámos vários conjuntos de observações, tendo como base o exemplo das estacas, recorrendo às funções de detecção semi-normal, taxa de risco, exponencial e uniforme com um cosseno. Os resultados foram obtidos com o programa DISTANCE (Thomas et al., in press) e um algoritmo escrito em linguagem C, cedido pelo Professor Doutor Petri Kontkanen (Departamento de Ciências da Computação, Universidade de Helsínquia). Foram desenvolvidos programas de forma a calcular intervalos de confiança recorrendo à técnica bootstrap (Efron, 1978). São discutidos os resultados finais e apresentadas sugestões de desenvolvimentos futuros. ABSTRACT; We present a brief historical note on the evolution of line transect sampling and its theoretical developments. We describe line transect sampling theory as proposed by Buckland (1992), and present the most relevant issues about modeling the detection function. We present a description of the CDM principle (Rissanen, 1978) and its application to histogram density estimation (Kontkanen and Myllymãki, 2006), with a practical example, using a mixture of densities. We proceed with the application and estimate probability of detection and animal population density in the context of line transect sampling. Two classical examples from the literature are analyzed and compared. ln order to evaluate the proposed methodology, we carry out a simulation study based on a wooden stakes example, and using as detection functions half normal, hazard rate, exponential and uniform with a cosine term. The results were obtained using program DISTANCE (Thomas et al., in press), and an algorithm written in C language, kindly offered by Professor Petri Kontkanen (Department of Computer Science, University of Helsinki). We develop some programs in order to estimate confidence intervals using the bootstrap technique (Efron, 1978). Finally, the results are presented and discussed with suggestions for future developments.

Application of Mixture Models to Survival Data

Survival models are being widely applied to the engineering field to model time-to-event data once censored data is here a common issue. Using parametric models or not, for the case of heterogeneous data, they may not always represent a good fit. The present study relays on critical pumps survival data where traditional parametric regression might be improved in order to obtain better approaches. Considering censored data and using an empiric method to split the data into two subgroups to give the possibility to fit separated models to our censored data, we’ve mixture two distinct distributions according a mixture-models approach. We have concluded that it is a good method to fit data that does not fit to a usual parametric distribution and achieve reliable parameters. A constant cumulative hazard rate policy was used as well to check optimum inspection times using the obtained model from the mixture-model, which could be a plus when comparing with the actual maintenance policies to check whether changes should be introduced or not.

Discrimination capacity in species distribution models depends on the representativeness of the environmental domain

Aim When faced with dichotomous events, such as the presence or absence of a species, discrimination capacity (the ability to separate the instances of presence from the instances of absence) is usually the only characteristic that is assessed in the evaluation of the performance of predictive models. Although neglected, calibration or reliability (how well the estimated probability of presence represents the observed proportion of presences) is another aspect of the performance of predictive models that provides important information. In this study, we explore how changes in the distribution of the probability of presence make discrimination capacity a context-dependent characteristic of models. For the first time,we explain the implications that ignoring the context dependence of discrimination can have in the interpretation of species distribution models.

Applying fuzzy logic to comparative distribution modelling: a case study with two sympatric amphibians.

We modelled the distributions of two toads (Bufo bufo and Epidalea calamita) in the Iberian Peninsula using the favourability function, which makes predictions directly comparable for different species and allows fuzzy logic operations to relate different models. The fuzzy intersection between individual models, representing favourability for the presence of both species simultaneously, was compared with another favourability model built on the presences shared by both species. The fuzzy union between individual models, representing favourability for the presence of any of the two species, was compared with another favourabilitymodel based on the presences of either or both of them. The fuzzy intersections between favourability for each species and the complementary of favourability for the other (corresponding to the logical operation “A and not B”) were compared with models of exclusive presence of one species versus the exclusive presence of the other. The results of modelling combined species data were highly similar to those of fuzzy logic operations between individual models, proving fuzzy logic and the favourability function valuable for comparative distribution modelling. We highlight several advantages of fuzzy logic over other forms of combining distribution models, including the possibility to combine multiple species models for management and conservation planning.

Distribution modelling of wild rabbit hunting yields in its original area (S Iberian Peninsula)

In this work we used the information of the Annual Hunting Reports (AHRs) to obtain a high-resolution model of the potential favourableness for wild rabbit harvesting in Andalusia (southern Spain), using environmental and land-use variables as predictors. We analysed 32,134 AHRs from the period 1993/2001 reported by 6049 game estates to estimate the average hunting yields of wild rabbit in each Andalusian municipality (n5771). We modelled the favourableness for obtaining good hunting yields using stepwise logistic regression on a set of climatic, orographical, land use, and vegetation variables. The favourability equation was used to create a downscaled image representing the favourableness of obtaining good hunting yields for the wild rabbit in 161 km squares in Andalusia, using the Idrisi Image Calculator. The variables that affected hunting yields of wild rabbit were altitude, dry wood crops (mainly olive groves, almond groves, and vineyards), temperature, pasture, slope, and annual number of frost days. The 161 km squares with high favourableness values are scattered throughout the territory, which seems to be caused mainly by the effect of vegetation. Finally, we obtained quality categories for the territory by combining the probability values given by logistic regression with those of the environmental favourability function.

Distribution patterns of endemic flora to define hotspots on Hispaniola

Nineteen areas on the island of Hispaniola (Haiti and the Dominican Republic) were studied with the aim of determining the distribution pattern of the endemic flora in these areas, and their variability with altitude. The main concentration of endemic species occurs in mountains with a medium altitude and in certain mountain sites (palaeo-islands), which coincide with hotspots; a lower number of endemics are found in low-lying areas (coldspots), due to the degradation of their habitats. A total of 1,582 endemic species were studied and were distributed in 19 areas. The whole island is of outstanding interest for its richness in endemics; it has 2,050 endemic species, representing 34.16% of its total flora. The territory in the study is home to 1,284 genera of which 31 are endemic to the island, including monotypical genera such as Tortuella abietifolia Urb. & Ekman, and endemic genera such as Hottea, containing seven endemic species. The sites with the highest rate of endemics are area A16 in the central range with a total of 440 endemic species, of which 278 are exclusive to the territory; and the Sierra de Bahoruco, la Selle, La Hotte and Tibur on in area A12, where we found 699 plants of which 482 are endemic and exclusive to the area; and A13 with 173 and 129 respectively. This work highlights the exceptional floristic diversity in endemic species and genera and analyses their distribution patterns as a tool for conservation in this area of the world, whose high endemicity rate makes it one of the most significant hotspots in the Caribbean.