https://www.cs.princeton.edu/~schapire/papers/ecolmod.pdf

Maximum entropy modeling of species geographic distributions

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.

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

Data Mining - Concepts and Techniques.

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.

/pdf/novel-methods-improve-prediction-of-species-distributions-3cmioqeu6v.pdf

Novel methods improve prediction of species' distributions from occurrence data

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.

Predicting species distribution: offering more than simple habitat models.

Occurrence data on geographic distribution for most endemic Neotropical plants are scarce and spatially biased, which interferes with decisions on their conservation status. In this study we present a three-step approach applying: 1) Euclidean Environmental Distance models to search for unknown populations; 2) MaxEnt incorporating additional presence data to produce forecasts of the potential distribution and 3) coupling of convex hull methods with SDM. We studied Petunia mantiqueirensis, an Atlantic Forest endemic species. This approach enabled us to obtain new presence points, and to improve species distribution models. Finally, we identified and excluded environmental unsuitable areas inside the extent of occurrence, allowing us to reassess the conservation status of the species. These recommendations are important to crucial to establish, in a more assertive way, the extent of occurrence and area of occupancy of the species to determine proper strategies for conservation.

/pdf/reassessment-of-the-extinction-risk-of-endemic-species-in-1ajmg3oghg.pdf

Reassessment of the extinction risk of endemic species in the Neotropics: How can modelling tools help us?

modelling has been used to analyze species geographic distribution through extrapolation of environmental characteristics of known occurrence areas. Interest in this kind of modelling is derived from the need for rapid and well-grounded answers to the threats faced by species due to habitat loss, exotic species invasion, climate changes, and others. This article provides an overall view of recent advances in modelling and aims to encourage the discussion and application of this method that can help with basic biological knowledge acquisition as well as with public policies aimed at their conservation.

Artigo de Revisão / Review Paper Desafios atuais da modelagem preditiva de distribuição de espécies

Introduction 

In 1957 Hutchinson (4) formalised the fundamental
niche principle In essence, he proposed that if all
the environmental conditions that allow a species to
exist indefinately could be tabulated as a multidimensional
hypercube, then the resulting hypercube
could be considered to be the organismâ??s fundamental
ecological niche Naturally, fully understanding
all the ecological conditions for any given species is
a monumental task, limited primarily by the lack of
rich data that could drive such an analysis By extrapolation
of the association between species occurrence
localities and a set of GIS raster layers representing
environmental conditions such as rainfall,
temperature, solar radiation etc, a correlative approach
can be taken towards describing an organismâ??s
ecological niche (10) Using this technique, a
raster layer can be produced with areas that most
resemble the environmental conditions at the original
known sites of occurrence for the organism Arguably,
this approach first garnered widespread interest
with the publication of â??A biogeographic analysis
of Australian Elapid snakesâ?? (5), where the
authors produced predicted distribution maps for
Elapid snakes based on simple models of climatic
preference As the world starts to engage more fully
in the discussion of the potential impacts of global
climate change, the abillity to predict the impact of
these changes on the distribution of organisms has
become more topical Fundamental niche modelling
has been used to predict species loss in the face of future
climate changes (12; 2) It has also been used to
model invasive species, spread of disease vectors (6)
and in phylogenetic modelling to produce distribution
maps for hypothetical ancestors (13; 14)

https://journal.osgeo.org/index.php/journal/article/download/62/48

Introducing Open Modeller - A fundamental niche modelling framework

Risk analysis using species distribution modeling to support public policies for the alien alga Kappaphycus alvarezii aquaculture in Brazil

Metzgeriaceae are a cosmopolitan family that is particularly diverse in the Neotropics. In Brazil, the species of Metzgeria Raddi preferentially inhabit the coastal ecosystem Atlantic Rain Forest (from northeastern to southern Brazil). For bryophytes, the IUCN distribution criteria are of critical importance to evaluate threat status. In this study, we propose the use of ecological niche modeling methods to estimate the extent of potential occurrence of five Metzgeria species. Herbarium collection data were used to estimate the potential distribution of the species based on the method MAXENT. Understanding the spatial distribution of species is essential for the conservation of biodiversity, and the use of potential distribution models in biogeographic analysis is an important tool for the conservation of rare or endangered species. Modeling the distribution of five Metzgeria species endemic and/or threatened reveals that the species are currently not known from several areas that are, however, p...

https://bioone.org/journals/The-Bryologist/volume-115/issue-2/0007-2745-115.2.341/Modeling-the-potential-geographic-distribution-of-five-species-of-span/10.1639/0007-2745-115.2.341.pdf

Marinez Ferreira de Siqueira

Papers

Reassessment of the extinction risk of endemic species in the Neotropics: How can modelling tools help us?

Artigo de Revisão / Review Paper Desafios atuais da modelagem preditiva de distribuição de espécies

Introducing Open Modeller - A fundamental niche modelling framework

Risk analysis using species distribution modeling to support public policies for the alien alga Kappaphycus alvarezii aquaculture in Brazil

Modeling the potential geographic distribution of five species of Metzgeria Raddi in Brazil, aiming at their conservation