Spectral and statistical characteristics of shoaling waves of Alleppey West coast of India

Some investigations on the spectral and statistical characteristics of deep water waves are available for Indian waters. But practically no systematic investigation on the shallow water wave spectral and probabilistic characteristics is made for any part of the Indian coast except for a few restricted studies. Hence a comprehensive study of the shallow water wave climate and their spectral and statistical characteristics for a location (Alleppey) along the southwest coast of India is undertaken based on recorded data. The results of the investigation are presented in this thesis.The thesis comprises of seven chapters

Combining multispecies home range and distribution models aids assessment of MPA effectiveness

Marine protected areas (MPAs) are today's most important tools for the spatial management and conservation of marine species. Yet, the true protection that they provide to individual fish is unknown, leading to uncertainty associated with MPA effectiveness. In this study, conducted in a recently established coastal MPA in Portugal, we combined the results of individual home range estimation and population distribution models for 3 species of commercial importance and contrasting life histories to infer (1) the size of suitable areas where they would be fully protected and (2) the vulnerability to fishing mortality of each species. Results show that the relationship between MPA size and effective protection is strongly modulated by both the species' home range and the distribution of suitable habitat inside and outside the MPA. This approach provides a better insight into the true potential of MPAs in effectively protecting marine species, since it can reveal the size and location of the areas where protection is most effective and a clear, quantitative estimation of the vulnerability to fishing throughout an entire MPA.

Distribution of the nonlinear random ocean wave period

Because of the intrinsic difficulty in determining distributions for wave periods, previous studies on wave period distribution models have not taken nonlinearity into account and have not performed well in terms of describing and statistically analyzing the probability density distribution of ocean waves. In this study, a statistical model of random waves is developed using Stokes wave theory of water wave dynamics. In addition, a new nonlinear probability distribution function for the wave period is presented with the parameters of spectral density width and nonlinear wave steepness, which is more reasonable as a physical mechanism. The magnitude of wave steepness determines the intensity of the nonlinear effect, while the spectral width only changes the energy distribution. The wave steepness is found to be an important parameter in terms of not only dynamics but also statistics. The value of wave steepness reflects the degree that the wave period distribution skews from the Cauchy distribution, and it also describes the variation in the distribution function, which resembles that of the wave surface elevation distribution and wave height distribution. We found that the distribution curves skew leftward and upward as the wave steepness increases. The wave period observations for the SZFII-1 buoy, made off the coast of Weihai (37A degrees 27.6' N, 122A degrees 15.1' E), China, are used to verify the new distribution. The coefficient of the correlation between the new distribution and the buoy data at different spectral widths (nu=0.3-0.5) is within the range of 0.968 6 to 0.991 7. In addition, the Longuet-Higgins (1975) and Sun (1988) distributions and the new distribution presented in this work are compared. The validations and comparisons indicate that the new nonlinear probability density distribution fits the buoy measurements better than the Longuet-Higgins and Sun distributions do. We believe that adoption of the new wave period distribution would improve traditional statistical wave theory.

Estimation of Submerged Aquatic Vegetation Height and Distribution in Nova Avanhandava Reservoir (São Paulo State, Brazil) Using Bio-Optical Modeling

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of the parafunctional occlusal loading and crown height on stress distribution

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Eliciting and encoding expert knowledge on variable selection into classical or Bayesian species distribution models

The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.

Behavioural context of multi-scale species distribution models assessed by radio-tracking

Incorporating ecological processes and animal behaviour into Species Distribution Models (SDMs) is difficult. In species with a central resting or breeding place, there can be conflict between the environmental requirements of the 'central place' and foraging habitat. We apply a multi-scale SDM to examine habitat trade-offs between the central place, roost sites, and foraging habitat in . Myotis nattereri. We validate these derived associations using habitat selection from behavioural observations of radio-tracked bats. A Generalised Linear Model (GLM) of roost occurrence using land cover variables with mixed spatial scales indicated roost occurrence was positively associated with woodland on a fine scale and pasture on a broad scale. Habitat selection of radio-tracked bats mirrored the SDM with bats selecting for woodland in the immediate vicinity of individual roosts but avoiding this habitat in foraging areas, whilst pasture was significantly positively selected for in foraging areas. Using habitat selection derived from radio-tracking enables a multi-scale SDM to be interpreted in a behavioural context. We suggest that the multi-scale SDM of . M. nattereri describes a trade-off between the central place and foraging habitat. Multi-scale methods provide a greater understanding of the ecological processes which determine where species occur and allow integration of behavioural processes into SDMs. The findings have implications when assessing the resource use of a species at a single point in time. Doing so could lead to misinterpretation of habitat requirements as these can change within a short time period depending on specific behaviour, particularly if detectability changes depending on behaviour. © 2011 Gesellschaft für ökologie.

Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants

Abiotic factors are considered strong drivers of species distribution and assemblages. Yet these spatial patterns are also influenced by biotic interactions. Accounting for competitors or facilitators may improve both the fit and the predictive power of species distribution models (SDMs). We investigated the influence of a dominant species, Empetrum nigrum ssp. hermaphroditum, on the distribution of 34 subordinate species in the tundra of northern Norway. We related SDM parameters of those subordinate species to their functional traits and their co-occurrence patterns with E. hermaphroditum across three spatial scales. By combining both approaches, we sought to understand whether these species may be limited by competitive interactions and/or benefit from habitat conditions created by the dominant species. The model fit and predictive power increased for most species when the frequency of occurrence of E. hermaphroditum was included in the SDMs as a predictor. The largest increase was found for species that 1) co-occur most of the time with E. hermaphroditum, both at large (i.e. 750 m) and small spatial scale (i.e. 2 m) or co-occur with E. hermaphroditum at large scale but not at small scale and 2) have particularly low or high leaf dry matter content (LDMC). Species that do not co-occur with E. hermaphroditum at the smallest scale are generally palatable herbaceous species with low LDMC, thus showing a weak ability to tolerate resource depletion that is directly or indirectly induced by E. hermaphroditum. Species with high LDMC, showing a better aptitude to face resource depletion and grazing, are often found in the proximity of E. hermaphroditum. Our results are consistent with previous findings that both competition and facilitation structure plant distribution and assemblages in the Arctic tundra. The functional and co-occurrence approaches used were complementary and provided a deeper understanding of the observed patterns by refinement of the pool of potential direct and indirect ecological effects of E. hermaphroditum on the distribution of subordinate species. Our correlative study would benefit being complemented by experimental approaches.

Effect of abutment's height and framework alloy on the load distribution of mandibular cantilevered implant-supported prosthesis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatial and temporal distribution of the zoobenthos community during the filling up period of Porto Primavera Reservoir (Paraná River, Brazil)

Este estudo é parte do monitoramento limnológico empreendido pela Companhia Energética do Estado de São Paulo (CESP) durante o processo de enchimento do reservatório de Porto Primavera (Usina Hidrelétrica Engenheiro Sérgio Motta). Este reservatório, localizado no alto rio Paraná, entre os Estados de São Paulo e Mato Grosso, é o quarto maior do país. A primeira etapa de enchimento do lago começou em dezembro de 1998 e a segunda em março de 2001. Amostras para a análise da comunidade bentônica e das características sedimentológicas foram coletadas trimestralmente entre agosto de 1999 e novembro de 2001 e também em agosto de 2002 (11 campanhas). As coletas foram feitas em 13 estações de amostragem distribuídas no reservatório e em uma localizada a jusante da barragem. 128 táxons de invertebrados foram encontrados, sendo Mollusca, Annelida, Insecta e Nematoda os grupos dominantes durante praticamente todos os meses analisados. A classe Insecta foi a melhor representada, com 9 diferentes ordens, dentro das quais os Diptera contribuíram com a ocorrência de 63 táxons. A espécie exótica de bivalve Corbicula fluminea foi registrada em todas as estações de amostragem mostrando sua grande capacidade para colonizar novos habitats em regiões neotropicais. Variações consideráveis na densidade da fauna foram observadas para os diferentes períodos e locais analisados. A densidade máxima (média de 7812 ind.m-2) foi registrada no centro do reservatório enquanto que as densidades mínimas foram registradas na zona lacustre próxima à barragem (média de 9 ind.m-2). A maior riqueza de espécies por local/período (24 táxons) foi encontrada no trecho superior do reservatório (trecho fluvial). A diversidade máxima foi observada nas zonas superior e central do reservatório, com valores de 3.82 e 3.86 (bits.ind-1) no início (agosto/1999) e final (agosto/2002) do processo de enchimento, respectivamente. Não foi encontrado um padrão de distribuição dos grupos faunísticos que pudesse estar associado com a textura granulométrica dos diferentes locais amostrados. Por outro lado, constatou-se a diminuição, ou mesmo a não ocorrência de organismos, nas estações com elevada concentração de matéria orgânica (>40%) em baixo estado de degradação (grandes detritos vegetais). Tal fato pode estar relacionado com a falta de depósitos de sedimentos, dificultando a fixação de organismos da fauna bentônica, bem como com condições químicas mais redutoras em função da intensidade dos processos de decomposição da fitomassa inundada.

Climate refugia: joint inference from fossil records, species distribution models and phylogeography

Climate refugia, locations where taxa survive periods of regionally adverse climate, are thought to be critical for maintaining biodiversity through the glacial–interglacial climate changes of the Quaternary. A critical research need is to better integrate and reconcile the three major lines of evidence used to infer the existence of past refugia – fossil records, species distribution models and phylogeographic surveys – in order to characterize the complex spatiotemporal trajectories of species and populations in and out of refugia. Here we review the complementary strengths, limitations and new advances for these three approaches. We provide case studies to illustrate their combined application, and point the way towards new opportunities for synthesizing these disparate lines of evidence. Case studies with European beech, Qinghai spruce and Douglas-fir illustrate how the combination of these three approaches successfully resolves complex species histories not attainable from any one approach. Promising new statistical techniques can capitalize on the strengths of each method and provide a robust quantitative reconstruction of species history. Studying past refugia can help identify contemporary refugia and clarify their conservation significance, in particular by elucidating the fine-scale processes and the particular geographic locations that buffer species against rapidly changing climate.

Conservation of threatened habitat types under future climate change – Lessons from plant-distribution models and current extinction trends in southern Germany

A higher risk of future range losses as a result of climate change is expected to be one of the main drivers of extinction trends in vascular plants occurring in habitat types of high conservation value. Nevertheless, the impact of the climate changes of the last 60 years on the current distribution and extinction patterns of plants is still largely unclear. We applied species distribution models to study the impact of environmental variables (climate, soil conditions, land cover, topography), on the current distribution of 18 vascular plant species characteristic of three threatened habitat types in southern Germany: (i) xero-thermophilous vegetation, (ii) mesophilous mountain grasslands (mountain hay meadows and matgrass communities), and (iii) wetland habitats (bogs, fens, and wet meadows). Climate and soil variables were the most important variables affecting plant distributions at a spatial level of 10 × 10 km. Extinction trends in our study area revealed that plant species which occur in wetland habitats faced higher extinction risks than those in xero-thermophilous vegetation, with the risk for species in mesophilous mountain grasslands being intermediary. For three plant species characteristic either of mesophilous mountain grasslands or wetland habitats we showed exemplarily that extinctions from 1950 to the present day have occurred at the edge of the species’ current climatic niche, indicating that climate change has likely been the main driver of extinction. This is largely consistent with current extinction trends reported in other studies. Our study indicates that the analysis of past extinctions is an appropriate means to assess the impact of climate change on species and that vulnerability to climate change is both species- and habitat-specific.