Which environmental variables should I use in my biodiversity model?

Appropriate selection of environmental variables is critical to the performance of biodiversity models, but has received less attention than the choice of modelling method. Online aggregators of biological and environmental data, such as the Global Biodiversity Information Facility and the Atlas of Living Australia, necessitate a rational approach to variable selection. We outline a set of general principles for systematically identifying, compiling, evaluating and selecting environmental variables for a biodiversity model. Our approach aims to maximise the information obtained from the analysis of biological records linked to a potentially large suite of spatial environmental variables. We demonstrate the utility of this structured framework through case studies with Australian vascular plants: regional modelling of a species distribution, continent-wide modelling of species compositional turnover and environmental classification. The approach is informed by three components of a biodiversity model: (1) an ecological framework or conceptual model, (2) a data model concerning availability, resolution and variable selection and (3) a method for analysing data. We expand the data model in structuring the problem of choosing environmental variables. The case studies demonstrate a structured approach for the: (1) cost-effective compilation of variables in the context of an explicit ecological framework for the study, attribute accuracy and resolution; (2) evaluation of non-linear relationships between variables using knowledge of their derivation, scatter plots and dissimilarity matrices; (3) selection and grouping of variables based on hypotheses of relative ecological importance and perceived predictor effectiveness; (4) systematic testing of variables as predictors through the process of model building and refinement and (5) model critique, inference and synthesis using direct gradient analysis to evaluate the shape of response curves in the context of ecological theory by presenting predictions in both geographic and environmental space

Examining Connections between Gendered Dimensions of Inequality and Deforestation in Nepal

The United Nations recognizes empowering women as a key component of achieving numerous development-related goals. Qualitative studies suggest that communities where men and women have equal levels of agency over resource allocation and land tenure sometimes experience decreases in forest degradation and deforestation, all else being equal. However, these patterns are spatially heterogeneous, as are patterns of gender inequality in terms of land tenure and agency. This paper uses data from the Demographic and Health Surveys (DHS) to quantify the relationship between gender inequality and ecosystem degradation using three linear regression models, Empirical Bayesian Kriging, and mapping the intersections between gender inequality and deforestation. Results from LASSO, Ordinary Least Squares, and Stepwise regression models show that there is no linear relationship between gender inequality and deforestation. Additionally, the distributions of gender inequality as it pertains to land tenure and deforestation are highly heterogeneous over space, indicating potential sociocultural and sociodemographic factors not captured in my data. Further work should focus on identifying ways to incorporate complex gender dynamics into environmental planning at multiple levels of forest governance

Environmental screening tools for assessment of infrastructure plans based on biodiversity preservation and global warming (PEIT, Spain).

Most Strategic Environmental Assessment (SEA) research has been concerned with SEA as a procedure, and there have been relatively few developments and tests of analytical methodologies. The first stage of the SEA is the ‘screening’, which is the process whereby a decision is taken on whether or not SEA is required for a particular programme or plan. The effectiveness of screening and SEA procedures will depend on how well the assessment fits into the planning from the early stages of the decision-making process. However, it is difficult to prepare the environmental screening for an infrastructure plan involving a whole country. To be useful, such methodologies must be fast and simple. We have developed two screening tools which would make it possible to estimate promptly the overall impact an infrastructure plan might have on biodiversity and global warming for a whole country, in order to generate planning alternatives, and to determine whether or not SEA is required for a particular infrastructure plan

Participatory land management planning in biodiversity conservation areas of Lao PDR

The importance of integrating forest conservation and rural development objectives is much better understood today than in the past. Despite an increased understanding such integration in many countries remains poorly supported in terms of co-ordination between government agencies and stakeholders. Environmental degradation and loss of biodiversity conservation areas to competing alternative uses is widespread throughout the world and Lao PDR is no exception. The forest policy in Lao PDR has developed under the framework of international conventions. The protected area system has been established with the aim of conserving healthy and diverse forests. Rehabilitation and reforestation policies are important complements. The former “rules by decree” approach has been replaced by a set of laws and regulations. This thesis presents and discusses a management approach for biodiversity conservation areas in Lao PDR. As part of that, it highlights the significance of appropriate policies and legislation as a base for sustainable management, discusses various interdisciplinary and interactive planning methods tested in case studies, and analyses the utilisation of non-timber forest products as part of a strategy for sustainable management of biodiversity conservation areas. The integration of techniques from social sciences and natural sciences is emphasised to encourage local participation in managing the conservation areas. Participatory Rural Appraisal, simple sampling methods, and remote sensing were used in the studies. A simple simulation model (the Area Production Model) strengthened the inter-action process. The integrated and cross-sectoral approach turned out to be simple, flexible and dynamic. The recognition of non-timber forest products (NTFPs) plays an important role in the conservation and development of protected area management. A literature review was made to gain insight into the research trend in Southeast Asia in terms of tenure rights of NTFPs and the way people utilise them. Quantitative resource assessment is an important part in sustainable management. In a case study, a participatory two-phase sampling approach for cardamom assessment was developed and tested with a promising result

Modelling tools to predict potential distribution of forest species : using Pico Island and the Azores as study case

Tese de Doutoramento, Biologia, 16 de novembro de 2018, Universidade dos Açores.Os modelos de distribuição de espécies (SDMs) têm sido aplicados em diferentes áreas da ecologia, nomeadamente para modelar a distribuição potencial de espécies invasoras, para avaliar espécies prioritárias no âmbito da conservação e para apoiar o planeamento florestal. Um SDM é uma descrição matemática da distribuição de uma espécie no espaço ambiental, a qual pode ser utilizada para prever a distribuição da espécie no espaço geográfico. O avanço ao nível da capacidade computacional disponibilizou uma diversidade de métodos estatísticos, que anteriormente não era possível utilizar. Esta diversidade de métodos reflete-se num número crescente de publicações direcionadas ao estudo e aplicação dos SDMs e também numa variedade crescente de métodos de modelação. Nos Açores, a abundância crescente de dados corológicos, a diversidade geomorfológica do arquipélago e os diferentes padrões espaciais que é possível encontrar em diferentes ilhas e em diferentes espécies, contribuem para que o arquipélago seja um bom modelo para a comparação de diferentes abordagens de modelação, bem como para testar possíveis constrangimentos inerentes ao processo de modelação. As perguntas de investigação a que pretendemos responder nesta tese foram as seguintes: (i) As abordagens de modelação, baseadas em diferentes fundamentos teóricos, originam resultados semelhantes, ao nível da distribuição potencial das espécies florestais estudadas? (ii) Existe alguma diferença relevante, entre o cálculo de Modelos Lineares Generalizados (GLMs) usando métodos de máxima verossimilhança ou métodos bayesianos? (iii) Existe alguma vantagem, no uso de um campo aleatório relativo à estrutura espacial dos dados, em comparação com os modelos que incluem apenas os efeitos fixos das variáveis ambientais? (iv) As diferentes abordagens de modelação originam resultados consistentes, em particular quando o número de variáveis ambientais utilizadas na modelação é reduzido? (v) As diferentes técnicas de modelação são afetadas de um modo relevante pela dimensão da amostra, pelo tipo de distribuição da espécie e pelas alterações no uso do solo? Para responder a estas questões, foram desenvolvidos três exercícios de modelação: (i) Uma comparação da Análise Fatorial do Nicho Ecológico (ENFA) e da modelação baseada na Máxima Entropia (MaxEnt), utilizando dados relativos à presença de três espécies (Pittosporum undulatum, Acacia melanoxylon e Morella faya) em três ilhas (Pico, Terceira e São Miguel), e incluindo o efeito da redução da dimensão da amostra; (ii) A comparação de modelos com efeitos fixos ou mistos, utilizando a plataforma R para o cálculo de GLMs e da aproximação de Laplace (INLA), permitindo o cálculo da estrutura espacial dos dados (função de covariância de Matérn), baseada em dados de duas ilhas (Pico e São Miguel) para duas espécies (P. undulatum e M. faya), e incluindo o efeito da redução da dimensão da amostra; e (iii) A comparação de GLMs e de uma seleção de algoritmos de autoaprendizagem (Machine Learning), usados para modelar as possíveis alterações nas áreas de distribuição de P. undulatum, A. melanoxylon e M. faya nas três ilhas, resultantes das alterações climáticas previstas para 2100. Em relação ao primeiro exercício, ambas as abordagens originaram cenários semelhantes, particularmente quando a quantidade de informação explicada pela ENFA era elevada; os resultados da modelação foram afetados pela redução do tamanho da amostra; os modelos com melhor capacidade de previsão incluíam um conjunto variado de variáveis ambientais (topográficas, climáticas e de uso do solo); e os modelos eram afetados pela transferência para um novo habitat (i.e. ilha). Os resultados do segundo exercício de modelação indicaram que os GLMs, calculados através de métodos de máxima verossimilhança ou métodos bayesianos originaram resultados similares, mesmo nos casos em que a dimensão da amostra era reduzida; e que a adição de um campo aleatório aumentou o ajustamento dos modelos, particularmente para a árvore menos abundante, M. faya, embora a estrutura do campo aleatório fosse claramente afetada pela dimensão da amostra. O terceiro exercício de modelação revelou que existem várias limitações quando se modela o efeito das alterações climáticas na distribuição das espécies, uma vez que os melhores modelos incluíram variáveis topográficas, demonstrando que a modelação baseada somente no clima poderá não ser fiável; verificou-se igualmente que o ajuste dos modelos variava de forma relevante entre as diferentes abordagens de modelação, e que o algoritmo Random Forest apresentou, em geral, os melhores resultados. De uma forma geral, os resultados desta investigação poderão ser aplicados como forma de apoio à gestão da floresta açoriana. Poderão ser replicados em outros sistemas insulares e noutras regiões florestais, não somente em projetos direcionados para a ecologia das espécies florestais, mas também em questões de investigação relacionadas com a previsão do sucesso e expansão das plantas invasoras, a deteção de áreas adequadas para projetos de restauro, a modelação baseada em dados de deteção remota e a modelação do efeito potencial das alterações climáticas.ABSTRACT: Species distribution models (SDMs) have been used in different areas within ecology, namely to model the potential spread of invasive species, to evaluate and manage priority species for conservation and to support forest management. An SDM is a mathematical description of the species distribution in the environmental space that can be used to predict the distribution of the species in the geographic space. The advances in computational capabilities have provided increasingly greater and more intensive statistical algorithms than was previously possible, as reflected by the increasing number of publications addressing SDMs and also the growing variety of modelling approaches. In the Azores, the growing abundance of the species distribution data, the diversity on island size and morphology, and the different spatial patterns that are possible among islands and species, make the archipelago a good model for the comparison of different modelling approaches and to test possible modelling constraints. Overall, the results of this research can be expanded to support Azorean forestry management, and could be replicated in other island systems and forest regions, not only in projects addressing the ecology of particular forest species, but also when handling research questions related with the prediction of plant invader success and expansion, the detection of areas potentially suited for restoration projects, modelling based on remote sense data, and modelling of the potential effect of climate change

Understanding evolutionary processes during past Quaternary climatic cycles: Can it be applied to the future?

Climate change affected ecological community make-up during the Quaternary which was probably both the cause of, and was caused by, evolutionary processes such as species evolution, adaptation and extinction of species and populations

Understanding drivers of species distribution change: a trait-based approach

The impacts of anthropogenic environmental change on biodiversity are well documented, with threats such as habitat loss and climate change identified as causes of change in species distributions. The high degree of variation in responses of species to environmental change can be partly explained through comparative analyses of species traits. I carried out a phylogenetically informed trait-based analysis of plant range change in Britain, discovering that traits associated with competitive ability and habitat specialism both explained variation in range changes. Competitive, habitat generalists out-perform ed species specialised to nutrient-poor conditions; a result which can be attributed to the impact of agricultural intensification in Britain. A limitation of the comparative approach is that the models do not directly test the impact of environmental change on species distribution patterns, but instead infer potential impacts. I tested the potential of comparative analyses from a spatial context by conducting a spatial analysis of plant distribution change in Britain, examining the direct impact of environmental change on the spatial distribution of the trait characteristics of species that have gone locally extinct. I discovered a loss of species associated with nitrogen poor soils in regions that had an increase in arable land cover, a result that supports the results from the trait-based analysis of plant range change and demonstrates that comparative studies can accurately infer drivers of distribution change. I found that the cross-region transferability of trait-based models of range change to be related to land cover similarity, highlighting that the trait-based approach is dependent on a regional context. Additionally, I discovered that traits derived from distribution data were significant predictors of range shift across many taxonomic groups, out-performing traditional life history traits. This thesis highlights the potential of the data accumulated through the increased public participation in biological recording to address previously unanswerable ecological research questions.Open Acces

Developing measures for valuing changes in biodiversity : final report

This document reports the findings from the DEFRA funded research project 'Developing measures for valuing changes in biodiversity'. The aim of the research was to develop an appropriate framework that will enable cost-effective and robust valuations of the total economic value of changes to biodiversity in the UK countryside. The research involved a review of ecological and economic literature on the valuation of biodiversity changes. The information gathered from this review, along with the findings from a series of public focus groups and an expert review of valuation methodologies, were used to develop a suite of valuation instruments that were used to measure the economic value of different aspects of biodiversity. Contingent valuation and choice experiment studies were administered to households in Cambridgeshire and Northumberland, while valuation workshops were conducted in Northumberland only. The data from these studies were also used to test for benefits transfer