Marinez Ferreira de Siqueira

Bio: Marinez Ferreira de Siqueira is an academic researcher from University of York. The author has contributed to research in topics: Environmental niche modelling & Biodiversity. The author has an hindex of 17, co-authored 48 publications receiving 8068 citations.

Challenges and perspectives for species distribution modelling in the neotropics

Abstract: The workshop ‘ Species distribution models: applications, challenges and perspectives ’ held at Belo Horizonte (Brazil), 29–30 August 2011, aimed to review the state-of-the-art in species distribution modelling (SDM) in the neotropical realm It brought together researchers in ecology, evolution, biogeography and conservation, with different backgrounds and research interests The application of SDM in the megadiverse neotropics—where data on species occurrences are scarce—presents several challenges, involving acknowledging the limitations imposed by data quality, including surveys as an integral part of SDM studies, and designing the analyses in accordance with the question investigated Specific solutions were discussed, and a code of good practice in SDM studies and related field surveys was drafted

Biodiversity Conservation: Uncertainty in predictions of extinction risk/Effects of changes in climate and land use/Climate change and extinction risk (reply).

Abstract: Thomas et al. reply — We reconsider our estimates of climate-related extinction1 in the light of three questions raised by Thuiller .2, Buckley and Roughgarden 3 and Harte .4. We are able to confirm our original conclusion that climate change represents a major threat to terrestrial species1.

Modelagem da distribuição geográfica de espécies lenhosas de cerrado no Estado de São Paulo

Abstract: Many different techniques are used today with different objectives to model species geographic distribution. Some of these techniques are based on environmental analysis where algorithms search for environmental conditions similar to those where the species are known to occur, resulting in potential areas where the environmental conditions would be favorable for the growth of these species. The present study is based on predictive modeling of species geographic distribution using genetic algorithm as a tool for plant conservation in modeling the "cerrado" biome of the State of Sao Paulo. The methodology used and the results obtained were considered satisfactory for the generation of geographic distribution models for plant species, based on abiotic data for the regions studied. The accuracy of the model in predicting the occurrence of species in the "cerrado" is greater if only points that occur within the "cerrado" and not in transition areas are used. In order to minimize problems due to the lack of convergence of the genetic algorithm GARP ("Genetic Algorithm for Rule Set Production"), 100 models were generated for each specie. The use of modeling tools can help understand the distribution patterns of a biome or ecosystem in a regional analysis.

A survey of biodiversity informatics: Concepts, practices, and challenges

Abstract: The unprecedented size of the human population, along with its associated economic activities, has an ever‐increasing impact on global environments. Across the world, countries are concerned about the growing resource consumption and the capacity of ecosystems to provide resources. To effectively conserve biodiversity, it is essential to make indicators and knowledge openly available to decision‐makers in ways that they can effectively use them. The development and deployment of tools and techniques to generate these indicators require having access to trustworthy data from biological collections, field surveys and automated sensors, molecular data, and historic academic literature. The transformation of these raw data into synthesized information that is fit for use requires going through many refinement steps. The methodologies and techniques applied to manage and analyze these data constitute an area usually called biodiversity informatics. Biodiversity data follow a life cycle consisting of planning, collection, certification, description, preservation, discovery, integration, and analysis. Researchers, whether producers or consumers of biodiversity data, will likely perform activities related to at least one of these steps. This article explores each stage of the life cycle of biodiversity data, discussing its methodologies, tools, and challenges.

Edaphic Endemism in the Amazon: Vascular Plants of the canga of Carajás, Brazil

Abstract: Amazonia is one of the most diverse biomes worldwide, and, as well as luxuriant forest, it includes mountain areas which, despite their small surface area, display fascinating endemism. In these regions, the specificity of edaphic factors is mirrored by a highly specialised, isolated flora adapted to survive adverse conditions. The Serra dos Carajas in the Brazilian state of Para is one of world’s largest iron ore reserves. Known locally as canga, this ironstone formation occupies an area of 115.9 km2, and supports campo rupestre of canga vegetation on outcrops that are mostly in the Floresta Nacional de Carajas (FLONA of Carajas) and Parque Nacional dos Campos Ferruginosos (PNCF). The recent publication of the Flora of the cangas of Carajas lists 856 species of seed plants and 186 species of ferns and lycophytes. This project assessed the canga endemic species growing in the region, and further expeditions guided by SDM were carried out in order to ascertain their distribution outisde the area. Departing from an initial list of 58 putative endemics, the final list comprises 38 species of vascular plants (c. 4% of the local flora). These are distributed in 31 genera and 22 families, including three monotypic genera: Carajasia (Rubiaceae), Monogereion and Parapiqueria (Asteraceae). From these, 24 are classified as Rare Species for Brazil and seven as Highly Restricted Endemic (EEO < 100 km2). An illustrated account is provided, as well as further SDM to detect other possible areas of distribution based on the studied species. The knowledge generated is aimed at directing appropriate conservation plans for the area.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Novel methods improve prediction of species' distributions from occurrence data

Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

Predicting species distribution: offering more than simple habitat models.

Abstract: In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.