Os Sistemas de Informação Geográfica como ferramenta de apoio à decisão em Protecção Civil

Dissertação apresentada à Escola Superior Agrária do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Sistemas de Informação Geográfica - Recursos Agro-Florestais e Ambientais.

Biosystematics of the Genus Andryala L. (Asteraceae)

Andryala (Asteraceae: Cichorieae) is a little-known Mediterranean-Macaronesian genus whose taxonomy is much in need of revision. The aim of the present biosystematic study was to elucidate species relationships within this genus based on morphological and molecular data. In this study several taxa are recognised: 17 species, 14 subspecies, and 3 hybrids. Among these, 5 species are Macaronesian endemics (A. glandulosa, A. sparsiflora, A. crithmifolia Aiton, A. pinnatifida, and A. perezii), 4 species are Northwest African endemics (A. mogadorensis, A. maroccana, A. chevallieri, and A. nigricans) and one species is endemic to Romania (A. laevitomentosa). Historical background regarding taxonomic delimitation in the genus is addressed from Linnaean to present day concepts, as well as the origin of the name Andryala. The origin of Asteraceae and the systematic position of Andryala is shortly summarised. The morphological study was based on a bibliographic review and the revision of 1066 specimens of 13 herbaria as well as additional material collected during fieldwork. The variability of the morphological characters of the genus, including both vegetative taxonomic characters (root, stem, leaf and indumentum characters) and reproductive ones (inflorescence, floret, fruit and pappus characters), is assessed. Numerical analysis of the morphological data was performed using different similarity or dissimilarity measures and coefficients, as well as ordination and clustering methods. Results support the segregation of the recognised taxa and the congruence of the several analyses in the separation of the recognised taxa (using quantitative, binary or multi-state characters). The proposed taxonomy for Andryala includes a new infra-generic classification, new taxa and new combinations and ranks, typifications and diagnostic keys (one for the species and several for subspecies). For each taxon a list of synonyms, typification comments and a detailed description are provided, just as comments on taxonomy and nomenclature, and a brief discussion on karyology. Additionally, information on ecology and conservation status as well as on distribution and a list of studied material are also presented. Phylogenetic analyses based on different nuclear and chloroplast DNA markers, using Bayesian and maximum parsimony methods of inference, were performed. Results support three main lineages: separate ones for the relict species A. agardhii and A. laevitomentosa and a third including the majority of the Andryala species that underwent a relatively rapid and recent speciation. They also suggest a single colonization event of Madeira and the Canary Islands from the Mediterranean region, followed by insular speciation. Biogeography and speciation within the genus are briefly discussed, including a proposal for the centre of origin of the genus and possible dispersal routes.

Cadastro do Património Arbóreo da Cidade de Portalegre – Conceção de um Sistema de Informação Geográfico

Os meios urbanos são espaços cada vez mais edificados, compactos e com solos impermeabilizados, onde a ausência ou reduzida presença de espaços verdes é uma realidade. Os elementos arbóreos, qualquer que seja a sua disposição, ganham cada vez mais significado enquanto representantes do meio natural na conservação da qualidade e conforto de vida nas cidades. Este trabalho desenvolveu-se a partir do tema das árvores em meio urbano, tendo por base os benefícios das árvores nas cidades, a sua distribuição espacial e o estado de conservação deste tipo de património. O principal fio condutor passou pela concepção do inventário do Património Arbóreo da cidade de Portalegre, com recurso às novas tecnologias da informação, nomeadamente os Sistemas de Informação Geográfica, capaz de se integrar nos sistemas homólogos do Município de Portalegre. O inventário à escala do perímetro urbano da cidade de Portalegre contabilizou 2087 elementos arbóreos localizados em áreas públicas, dos quais 1500 são árvores de folha caduca e 587 são perenifólias. Registou-se um elevado índice de diversidade para aquela área, cerca de 705 árvores/km2, embora as árvores estejam distribuídas de forma heterogénea pelo território considerado, percebendo-se com isso as zonas de carência de arborização. Com este inventário foi ainda possível conceber uma avaliação económica segundo a Norma de Granada, de 13 árvores isoladas e uma alameda com 38 indivíduos, assim como propor a classificação destes elementos a Árvores de Interesse Público. Anseia-se que este trabalho seja um documento informativo e sensibilizador de todo o público em geral, mas principalmente que se assuma como uma ferramenta útil aos responsáveis pelos espaços verdes da cidade de Portalegre.

Protocols for listing threatened species can forecast extinction

Risk-ranking protocols are used widely to classify the conservation status of the world's species. Here we report on the first empirical assessment of their reliability by using a retrospective study of 18 pairs of bird and mammal species (one species extinct and the other extant) with eight different assessors. The performance of individual assessors varied substantially, but performance was improved by incorporating uncertainty in parameter estimates and consensus among the assessors. When this was done, the ranks from the protocols were consistent with the extinction outcome in 70-80% of pairs and there were mismatches in only 10-20% of cases. This performance was similar to the subjective judgements of the assessors after they had estimated the range and population parameters required by the protocols, and better than any single parameter. When used to inform subjective judgement, the protocols therefore offer a means of reducing unpredictable biases that may be associated with expert input and have the advantage of making the logic behind assessments explicit. We conclude that the protocols are useful for forecasting extinctions, although they are prone to some errors that have implications for conservation. Some level of error is to be expected, however, given the influence of chance on extinction. The performance of risk assessment protocols may be improved by providing training in the application of the protocols, incorporating uncertainty in parameter estimates and using consensus among multiple assessors, including some who are experts in the application of the protocols. Continued testing and refinement of the protocols may help to provide better absolute estimates of risk, particularly by re-evaluating how the protocols accommodate missing data.

A Site Description of the CARICOMP Mangrove, Seagrass and Coral Reef Sites in Bocas del Toro, Panama

Bocas del Toro is located in the western region of the Republic of Panama. It is part of a province of approximately 8917 km(2) with an estimated 68% of its area covered by tropical rainforest. The area receives 2870 mm/year of rainfall. The dry and rainy seasons are not clearly defined. There are two periods each of low and high rainfall, March and September-October, and July and December, respectively. Mangrove forests, seagrass meadows and coral reefs are vast, covering large areas in the shallow waters surrounding the islands of the archipelago and along the mainland coast. The CARICOMP sites were established in 1998-99 and are periodically monitored following Level I protocol. Herein we describe the sites in a regional context and present the baseline data for each site. This paper fulfills the requirements of the formal site description for CARICOMP monitoring sites.

The consistency of extinction risk classification protocols

Systematic protocols that use decision rules or scores arc, seen to improve consistency and transparency in classifying the conservation status of species. When applying these protocols, assessors are typically required to decide on estimates for attributes That are inherently uncertain, Input data and resulting classifications are usually treated as though they arc, exact and hence without operator error We investigated the impact of data interpretation on the consistency of protocols of extinction risk classifications and diagnosed causes of discrepancies when they occurred. We tested three widely used systematic classification protocols employed by the World Conservation Union, NatureServe, and the Florida Fish and Wildlife Conservation Commission. We provided 18 assessors with identical information for 13 different species to infer estimates for each of the required parameters for the three protocols. The threat classification of several of the species varied from low risk to high risk, depending on who did the assessment. This occurred across the three Protocols investigated. Assessors tended to agree on their placement of species in the highest (50-70%) and lowest risk categories (20-40%), but There was poor agreement on which species should be placed in the intermediate categories, Furthermore, the correspondence between The three classification methods was unpredictable, with large variation among assessors. These results highlight the importance of peer review and consensus among multiple assessors in species classifications and the need to be cautious with assessments carried out 4), a single assessor Greater consistency among assessors requires wide use of training manuals and formal methods for estimating parameters that allow uncertainties to be represented, carried through chains of calculations, and reported transparently.

Qualidade da água de um reservatório e do solo da zona ripária sob diferentes usos na região semiárida do Rio Grande do Norte

Reservoirs are artificial ecosystems intermediate between rivers and lakes widely used in the Brazilian semiarid region as a way to provide water supply due to the said region’s water scarcity. The use of water from these supply sources for multiple uses, along with occupation and utilization of its riparian zone without proper management, directly influences the increased nutrient flow into aquatic environments, there with contributing to the acceleration of eutrophication. The semi-arid region is characterized by peculiar weather conditions, such as severe evaporation, high temperatures with little variation throughout the year and long water residence time, making it susceptible to prolonged drought occurrence, which tends to concentrate the nutrients in reservoirs, which favors the development of eutrophic conditions. Moreover, it is common soil use and occupation by carrying out activities with potential environmental impact on natural resources such as agriculture, livestock farming and lack of sanitation. The aim of this study is both to evaluate the water quality of the Cruzeta Reservoir, located in the semiarid region of Rio Grande do Norte, during a prolonged drought period, and assess the quality of its riparian zone soil under different uses, by monitoring physical-chemical variables. Along the prolonged drought, high levels of turbidity, suspended solids, nutrients and chlorophyll a were verified as present, therefore featuring low water quality. In the riparian zone of Cruzeta Reservoir, the areas under use of agriculture and livestock farming appeared as one of the main diffuse sources of nutrients to the said reservoir, featuring the highest levels of phosphorus and nitrogen in the soil, originated from decomposition of animal excreta and from the use of fertilizers, creating a tendency to increased eutrophication of such water supply source. The indicators of water and soil quality are useful for monitoring and evaluating the conservation status of natural resources, allowing the control and mitigation of the reservoir eutrophication process. This study confirmed the hypothesis that the reduction of water level, resulting from prolonged drought event, aggravates the symptoms of eutrophication; and also that using the soil under severalways modifies the physic chemical properties of the soil, having livestock farming and agriculture as the usages with greatest potential towards yielding P and N to the aquatic environment.

A paisagem da Mata Atlântica do estado do Rio Grande do Norte: remanescentes, configuração espacial e disponibilidade de habitat

The Atlantic Forest in Rio Grande do Norte (RN) is included in Pernambuco biogeographic sub-region and it is composed by Semi-deciduous Forest, deciduous Forest, Mangrove and Restinga. We assessed the conservation status of Atlantic Forest in the RN through remnants mapping using high resolution satellite images and landscape ecology approaches. We evaluated if there is difference between the north and south coastal regions considering their natural a historical land use differences. We also assessed the influence of the small remnants on landscape cover and configuration. The proportion of the original biome area with remnants larger than 3 hectares is 15.60% for the official governmental limit and is 16.60% for the alternative limit (SNE, 2002). This remnants proportion varies between 0.56 and 46.52% in the hydrographic basins. 89.70% of the remnants are smaller than 50 hectares. Only 6.00% of the remnants are greater than 100 hectares, and these remnants are responsible by 65% of remaining area. The patches with smaller area influence all calculated metrics. The south coastal hydrographic basins have higher percentage of coverage of remnants, larger patch densities and fragments with larger areas than north coastal hydrographic basins. The diffuse drainage basins of the southern coastal have the highest percentage of coverage with remnants. 18.28% and 10% of the biome area are protected by reserves, according to the official governmental and alternative limits respectively. The reserves are mainly of sustainable use (IUCN V-VI). Therefore, the Atlantic Forest in Rio Grande do Norte is in critical situation, with low proportion of remaining area and high fragmentation level. It’s indispensable to biome conservation keep all the remaining area, especially the large remnants, and restore areas to increase remnants proportion and to increase landscape connectivity

Mapped distribution of intertidal habitats in Australia between 1999 and 2014, link to data in ArcGIS format (29 MB)

Shorebirds have declined severely across the East Asian-Australasian Flyway. Many species rely on intertidal habitats for foraging, yet the distribution and conservation status of these habitats across Australia remain poorly understood. Here, we utilised freely available satellite imagery to produce the first map of intertidal habitats across Australia. We estimated a minimum intertidal area of 9856 km**2, with Queensland and Western Australia supporting the largest areas. Thirty-nine percent of intertidal habitats were protected in Australia, with some primarily within marine protected areas (e.g. Queensland) and others within terrestrial protected areas (e.g. Victoria). In fact, three percent of all intertidal habitats were protected both by both marine and terrestrial protected areas. To achieve conservation targets, protected area boundaries must align more accurately with intertidal habitats. Shorebirds use intertidal areas to forage and supratidal areas to roost, so a coordinated management approach is required to account for movement of birds between terrestrial and marine habitats. Ultimately, shorebird declines are occurring despite high levels of habitat protection in Australia. There is a need for a concerted effort both nationally and internationally to map and understand how intertidal habitats are changing, and how habitat conservation can be implemented more effectively.

Data to Decision in a Dynamic Ocean: Robust Species Distribution Models and Spatial Decision Frameworks

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

Anatomy and variability of "Cuvierichelys parisiensis", a geoemydid turtle that crosses the Eocene-Oligocene boundary in Belgium

Abundant material of turtles from the early Oligocene site of Boutersem-TGV (Boutersem, Belgium), is presented here. No information on the turtles found there was so far available. All the turtle specimens presented here are attributable to a single freshwater taxon that is identified as a member of Geoemydidae, Cuvierichelys. It is the first representative of the ‘Palaeochelys s. l.–Mauremys’ group recognized in the Belgian Paleogene record. This material, which allows to know all the elements of both the carapace and the plastron of the taxon, cannot be attributed to the only species of the genus Cuvierichelys so far identified in the Oligocene, the Spanish form Cuvierichelys iberica. The taxon from Boutersem is recognized as Cuvierichelys parisiensis. Thus, both the paleobiogeographic and the biostratigraphic distributions of Cuvierichelys parisiensis are extended, its presence being confirmed for the first time outside the French Eocene record. The validity of some European forms is refuted, and several characters previously proposed as different between Cuvierichelys iberica and Cuvierichelys parisiensis are recognized as subjected to intraspecific variability.

Juniperus navicularis - a study of Portuguese population structure and fitness

Juniperus navicularis Gand. is a dioecious endemic conifer that constitutes the understory of seaside pine forests in Portugal, areas currently threatened by increasing urban expansion. The aim of this study is to assess the conservation status of previously known populations of this species located on its core area of distribution. The study was performed in south-west coast of Portugal. Three populations varying in size and pine density were analyzed. Number of individuals, population density, spatial distribution and individual characteristics of junipers were estimated. Female cone, seed characteristics and seed viability were also evaluated. Results suggest that J. navicularis populations are vulnerable because seminal recruitment is scarce, what may lead to a reduction of genetic variability due solely to vegetative propagation. This vulnerability seems to be strongly determined by climatic constraints toward increasing aridity. Ratio between male and female shrubs did not differ from 1:1 in any population. Deviations from 1:1 between mature and non-mature plants were found in all populations, denoting population ageing. Very low seed viability was observed. A major part of described Juniperus navicularis populations have disappeared through direct habitat loss to urban development, loss of fitness in drier and warmer locations and low seed viability. This study is the first to address J. navicularis conservation, and represents a valuable first step toward this species preservation. 

The international importance of the archipelago of Cape Verde for marine turtles, in particular the loggerhead turtle Caretta caretta

[ES] The shores of Cape Verde hosts one of the most important nesting populations of the loggerhead turtle Caretta caretta in the world, as well as important feeding grounds for hawksbill Eretmochelys imbricata and green turtles Chelonia mydas. In the past few years, a number of scientific studies have demonstrated the relevance of the waters and beaches of this archipelago for the conservation of these endangered marine megavertebrates. This article aims to bring together the most relevant scientific information published on the subject so far. In addition, we will provide an overview of the current situation of sea turtles in Cape Verde, their conservation status and their importance in an international context.

O pedestrianismo como instrumento de valorização ecoturística dos sítios da Rede Natura 2000, nas ilhas de São Miguel e Flores

Tese de Doutoramento, Ciências do Ambiente (Ecologia), 30 de Julho de 2013, Universidade dos Açores.