title: Genetic Diversity and Structure in the Philippine Rafflesia lagascae Complex (Rafflesiaceae) inform its Taxonomic Delimitation and Conservation

authors: Pelser, Pieter B.

subjects: Microsatellites

abstract: Rafflesia lagascae (Rafflesiaceae) is a rare endo-holoparasitic plant species with a disjunct distribution on Luzon Island in the Philippines. It is morphologically very similar to R. manillana, which is only known from a single population on nearby Samar Island. This study aims to contribute to the taxonomy and conservation of R. lagascae and R. manillana (i.e., the R. lagascae complex) by resolving their patterns of genetic diversity and genetic structure. The results of population genetic analyses of a microsatellite data set indicate that despite their frequently extremely small sizes and geographic isolation, Rafflesia populations display moderate genetic diversity and do not show evidence of pronounced inbreeding. Most populations appear to be strongly genetically differentiated from each other, suggesting limited gene flow between them. Patterns of genetic diversity of staminate and pistillate Rafflesia flowers growing on the same Tetrastigma host plants indicate that the R. lagascae complex is monoecious and that host plants are regularly infected by more than one Rafflesia plant. Both might enable Rafflesia to maintain viable populations in areas with low host densities. PCoA and Bayesian cluster analyses show that the R. lagascae complex is composed of three genetically isolated taxa. One of these constitutes R. manillana, supporting the morphology-based hypothesis that it is taxonomically distinct from R. lagascae. The second taxon in this complex is composed of the single population of R. lagascae from Mt. Labo. This morphologically cryptic population is genetically distinct from the 11 remaining R. lagascae populations that were included in this study and that form the third taxon. We recommend that R. lagascae s. s., the Mt. Labo R. lagascae, and R. manillana should be managed as different conservation entities.

text: Genetic Diversity and Structure in the Philippine Rafflesia lagascae Complex (Rafflesiaceae) inform its Taxonomic Delimitation and Conservation Rafflesia lagascae (Rafflesiaceae) is a rare endo-holoparasitic plant species with a disjunct distribution on Luzon Island in the Philippines. It is morphologically very similar to R. manillana, which is only known from a single population on nearby Samar Island. This study aims to contribute to the taxonomy and conservation of R. lagascae and R. manillana (i.e., the R. lagascae complex) by resolving their patterns of genetic diversity and genetic structure. The results of population genetic analyses of a microsatellite data set indicate that despite their frequently extremely small sizes and geographic isolation, Rafflesia populations display moderate genetic diversity and do not show evidence of pronounced inbreeding. Most populations appear to be strongly genetically differentiated from each other, suggesting limited gene flow between them. Patterns of genetic diversity of staminate and pistillate Rafflesia flowers growing on the same Tetrastigma host plants indicate that the R. lagascae complex is monoecious and that host plants are regularly infected by more than one Rafflesia plant. Both might enable Rafflesia to maintain viable populations in areas with low host densities. PCoA and Bayesian cluster analyses show that the R. lagascae complex is composed of three genetically isolated taxa. One of these constitutes R. manillana, supporting the morphology-based hypothesis that it is taxonomically distinct from R. lagascae. The second taxon in this complex is composed of the single population of R. lagascae from Mt. Labo. This morphologically cryptic population is genetically distinct from the 11 remaining R. lagascae populations that were included in this study and that form the third taxon. We recommend that R. lagascae s. s., the Mt. Labo R. lagascae, and R. manillana should be managed as different conservation entities.

year: 2017

title: Computational Bayesian inference using low discrepancy sequences

authors: Brown, Paul Tamataatoi

subjects: Bayesian Inference

abstract: The Integrated Nested Laplace Approximation (INLA) provides fast and accurate Bayesian inference for complex hierarchical models. For INLA, and other deterministic methods, the hyperparameter space is explored and points are laid out in a grid structure. These points are used in some numerical integration scheme for which marginal posterior distributions are computed. The main drawback is that the number of points increase exponentially with the number of hyperparameters. The grid is a type of quasi-Monte Carlo (QMC) point set. Low discrepancy sequences (LDS) are QMC point sets that are well known to have significant advantages over grids in terms of convergence and accuracy, and suffer less from the so-called curse of dimensionality.

This work makes several important contributions. We introduce a new method using LDS to compute marginal posterior distributions for hyperparameters, discuss the convergence properties of the approximations and show that they converge to the true posterior. We also show how these methods can be incorporated into the INLA inference framework, and we outline important extensions that improve the accuracy of our approximations with little extra computational effort needed. Lastly, we build a unique spatio-temporal model of residential crime in Hamilton, using INLA’s stochastic partial differential equation approach to a Log-Gaussian Cox Process, and use an LDS to approximate the latent parameters of the model.

Our results show that for a fixed number of points or computational time, LDS methods can outperform general grid-based methods, leading to better marginal posterior approximations. Modifying the method for the purposes of incorporation to INLA, we show that we can outperform INLA’s grid with respect to computational speed, and obtain accurate and flexible approximations to the model hyperparameters.

text: Computational Bayesian inference using low discrepancy sequences The Integrated Nested Laplace Approximation (INLA) provides fast and accurate Bayesian inference for complex hierarchical models. For INLA, and other deterministic methods, the hyperparameter space is explored and points are laid out in a grid structure. These points are used in some numerical integration scheme for which marginal posterior distributions are computed. The main drawback is that the number of points increase exponentially with the number of hyperparameters. The grid is a type of quasi-Monte Carlo (QMC) point set. Low discrepancy sequences (LDS) are QMC point sets that are well known to have significant advantages over grids in terms of convergence and accuracy, and suffer less from the so-called curse of dimensionality.

This work makes several important contributions. We introduce a new method using LDS to compute marginal posterior distributions for hyperparameters, discuss the convergence properties of the approximations and show that they converge to the true posterior. We also show how these methods can be incorporated into the INLA inference framework, and we outline important extensions that improve the accuracy of our approximations with little extra computational effort needed. Lastly, we build a unique spatio-temporal model of residential crime in Hamilton, using INLA’s stochastic partial differential equation approach to a Log-Gaussian Cox Process, and use an LDS to approximate the latent parameters of the model.

Our results show that for a fixed number of points or computational time, LDS methods can outperform general grid-based methods, leading to better marginal posterior approximations. Modifying the method for the purposes of incorporation to INLA, we show that we can outperform INLA’s grid with respect to computational speed, and obtain accurate and flexible approximations to the model hyperparameters.

year: 2019

title: Exploring the constitution of environment education as situated, critical processes of learning and change: A collaborative synthesis across diverse regional contexts

authors: Eames, Chris W.

subjects: Critical approaches

abstract: This article offers a set of unique vignettes or stories that attempt to illustrate examples of critical approaches to environmental education (EE) in diverse contexts. It draws from the experiences of five environmental educators in four different regions of the world. We detail the history of the emergence of critical consciousness in education in Brazil, and its application in a Brazilian region, then move to examples of critical educational responses to oppression in New Zealand and Zimbabwe, before closing with a critical examination of innovative teaching and research in Europe. Through this breadth of endeavour, we identify commonalities across these contexts such as the importance of participatory action and research to examine peopleenvironment relations, particularly as constituted by indigenous peoples, and to interpret realities in ways that empower through learning-led social-ecological change. We argue that this critical approach can foster emancipation through individual and collective learning in EE processes within very different contexts.

text: Exploring the constitution of environment education as situated, critical processes of learning and change: A collaborative synthesis across diverse regional contexts This article offers a set of unique vignettes or stories that attempt to illustrate examples of critical approaches to environmental education (EE) in diverse contexts. It draws from the experiences of five environmental educators in four different regions of the world. We detail the history of the emergence of critical consciousness in education in Brazil, and its application in a Brazilian region, then move to examples of critical educational responses to oppression in New Zealand and Zimbabwe, before closing with a critical examination of innovative teaching and research in Europe. Through this breadth of endeavour, we identify commonalities across these contexts such as the importance of participatory action and research to examine peopleenvironment relations, particularly as constituted by indigenous peoples, and to interpret realities in ways that empower through learning-led social-ecological change. We argue that this critical approach can foster emancipation through individual and collective learning in EE processes within very different contexts.

year: 2018