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Author

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.


Papers
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Journal ArticleDOI
08 Jan 2004-Nature
TL;DR: Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
Abstract: Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.

7,089 citations

Journal ArticleDOI
TL;DR: A generic approach for building a single computing framework capable of handling different data formats and multiple algorithms that can be used in potential distribution modelling is described and an example use case illustrates potential distribution maps generated by the framework.
Abstract: Species' potential distribution modelling is the process of building a representation of the fundamental ecological requirements for a species and extrapolating these requirements into a geographical region. The importance of being able to predict the distribution of species is currently highlighted by issues like global climate change, public health problems caused by disease vectors, anthropogenic impacts that can lead to massive species extinction, among other challenges. There are several computational approaches that can be used to generate potential distribution models, each achieving optimal results under different conditions. However, the existing software packages available for this purpose typically implement a single algorithm, and each software package presents a new learning curve to the user. Whenever new software is developed for species' potential distribution modelling, significant duplication of effort results because many feature requirements are shared between the different packages. Additionally, data preparation and comparison between algorithms becomes difficult when using separate software applications, since each application has different data input and output capabilities. This paper describes a generic approach for building a single computing framework capable of handling different data formats and multiple algorithms that can be used in potential distribution modelling. The ideas described in this paper have been implemented in a free and open source software package called openModeller. The main concepts of species' potential distribution modelling are also explained and an example use case illustrates potential distribution maps generated by the framework.

294 citations

Journal ArticleDOI
TL;DR: In this article, the most frequent threats and land use types in the vicinity of 81 Cerrado (tropical savanna type) fragments in the State of Sao Paulo, Brazil, were analyzed in order to verify if the frequency of every type of disturbance to the natural ecosystem depends on the neighboring land use.
Abstract: Patches of natural vegetation remaining in landscapes occupied by man are continuously under threat due to the edge effects and also to land use types around these remnants. The most frequent threats and land use types in the vicinity of 81 Cerrado (tropical savanna type) fragments in the State of Sao Paulo, Brazil, were analyzed in order to verify if the frequency of every type of disturbance to the natural ecosystem depends on the neighboring land use. The hypothesis of the study assumes that environmental threats are correlated with land use around protected areas. From the 81 areas, the most frequent human-induced land cover types around the Cerrado remnants were: pasture (recorded in 78% of the areas), sugarcane plantations (26%), roads (19%), annual crops and reforestation (14% each). The most frequent sources of threats were invasive grasses (35% of the areas partially or totally invaded) and cattle (observed in 32% of the areas), followed by deforestation (21%), and fire (21%). The chi-square analysis revealed that, with the exception of deforestation, which does not depend on land use, all other threats are influenced by the neighboring land use. The occurrence of invasive grasses and fires are strongly favored by the presence of roads and urban areas. Sugarcane, reforestation, and permanent crops were the less impacting land use types found in the study area, when only considering impact frequency. These land use types have fire and weed control, and also exclude cattle, indirectly protecting natural ecosystems.

192 citations

Journal ArticleDOI
TL;DR: Using an actual large-scale restoration target of the Atlantic Forest hotspot, it is shown that this approach can deliver an eightfold increase in cost-effectiveness for biodiversity conservation compared with a baseline of non-systematic restoration.
Abstract: International commitments for ecosystem restoration add up to one-quarter of the world’s arable land. Fulfilling them would ease global challenges such as climate change and biodiversity decline but could displace food production and impose financial costs on farmers. Here, we present a restoration prioritization approach capable of revealing these synergies and trade-offs, incorporating ecological and economic efficiencies of scale and modelling specific policy options. Using an actual large-scale restoration target of the Atlantic Forest hotspot, we show that our approach can deliver an eightfold increase in cost-effectiveness for biodiversity conservation compared with a baseline of non-systematic restoration. A compromise solution avoids 26% of the biome’s current extinction debt of 2,864 plant and animal species (an increase of 257% compared with the baseline). Moreover, this solution sequesters 1 billion tonnes of CO2-equivalent (a 105% increase) while reducing costs by US$28 billion (a 57% decrease). Seizing similar opportunities elsewhere would offer substantial contributions to some of the greatest challenges for humankind. A restoration prioritization approach applied to the Brazilian Atlantic Forest biodiversity hotspot considers 362 scenarios for synergies and trade-offs between ecological and economic costs, benefits and scales.

181 citations

Journal ArticleDOI
TL;DR: In this article, the authors examined species distribution models for a Neotropical anuran restricted to ombrophilous areas in the Brazilian Atlantic Forest hotspot, using GPS field surveys and selected bioclimatic and topographic variables to model the species distribution.

147 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.

13,120 citations

01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
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.

10,124 citations

01 Jan 2002

9,314 citations

Journal ArticleDOI
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
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.

7,589 citations

Journal ArticleDOI
TL;DR: An overview of recent advances in species distribution models, and new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales are suggested.
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.

5,620 citations