plantR: An R package and workflow for managing species records from biological collections

Species records from biological collections are becoming increasingly available online. This unprecedented availability of records has largely supported recent studies in taxonomy, biogeography, macroecology and biodiversity conservation. Biological collections vary in their documentation and notation standards, which have changed through time. For different reasons, neither collections nor data repositories perform the editing, formatting and standardisation of the data, leaving these tasks to the final users of the species records (e.g. taxonomists, ecologists and conservationists). These tasks are challenging, particularly when working with millions of records from hundreds of biological collections. To help collection curators and final users perform those tasks, we introduce plantR, an open-source package that provides a comprehensive toolbox to manage species records from biological collections. The package is accompanied by the proposal of a reproducible workflow to manage this type of data in taxonomy, ecology and biodiversity conservation. It is implemented in R and designed to handle relatively large datasets as fast as possible. Initially designed to handle plant species records, many of the plantR features also apply to other groups of organisms, given that the data structure is similar. The plantR workflow includes tools to (a) download records from different data repositories, (b) standardise typical fields associated with species records, (c) validate the locality, geographical coordinates, taxonomic nomenclature and species identifications, including the retrieval of duplicates across collections, and (d) summarise and export records, including the construction of species lists with vouchers. Other R packages provide tools to tackle some of the workflow steps described above. But in addition to the new tools and resources related to data standardisation and validation, the greatest strength of plantR is to provide a comprehensive and user-friendly workflow in one single environment, performing all tasks from data retrieval to export. Thus, plantR can help researchers better assess data quality and avoid data leakage in a wide variety of studies using species records

Current challenges of species distribution predictive modelling

A modelagem preditiva tem sido aplicada para analisar a distribuição geográfica de espécies, a partir de extrapolações das características ambientais dos locais conhecidos de ocorrência. O interesse por esse tipo de modelagem deve-se à necessidade de respostas rápidas e fundamentadas para as ameaças que as espécies têm enfrentado, devido à perda de habitat, invasão de espécies exóticas, mudanças climáticas, entre outros. Este artigo oferece uma visão geral dos avanços recentes no campo da modelagem e visa incentivar a discussão e aplicação desse método, que pode auxiliar tanto na aquisição de conhecimento básico sobre a biologia das espécies, quanto na análise e formulação de políticas para sua conservação

Desafios atuais da modelagem preditiva de distribuição de espécies

A modelagem preditiva tem sido aplicada para analisar a distribuição geográfica de espécies, a partir de extrapolações das características ambientais dos locais conhecidos de ocorrência. O interesse por esse tipo de modelagem deve-se à necessidade de respostas rápidas e fundamentadas para as ameaças que as espécies têm enfrentado, devido à perda de habitat, invasão de espécies exóticas, mudanças climáticas, entre outros. Este artigo oferece uma visão geral dos avanços recentes no campo da modelagem e visa incentivar a discussão e aplicação desse método, que pode auxiliar tanto na aquisição de conhecimento básico sobre a biologia das espécies, quanto na análise e formulação de políticas para sua conservação

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo)CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

Comprehensive conservation assessments reveal high extinction risks across Atlantic Forest trees

International audienceBiodiversity is declining globally, yet many biodiversity hotspots still lack comprehensive species conservation assessments. Using multiple International Union for Conservation of Nature (IUCN) Red List criteria to evaluate extinction risks and millions of herbarium and forest inventory records, we present automated conservation assessments for all tree species of the Atlantic Forest biodiversity hotspot, including ~1100 heretofore unassessed species. About 65% of all species and 82% of endemic species are classified as threatened. We rediscovered five species classified as Extinct on the IUCN Red List and identified 13 endemics as possibly extinct. Uncertainties in species information had little influence on the assessments, but using fewer Red List criteria severely underestimated threat levels. We suggest that the conservation status of tropical forests worldwide is worse than previously reported

Challenges and perspectives for species distribution modelling in the neotropics

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

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

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 Carajás in the Brazilian state of Pará is one of world’s largest iron ore reserves. Known locally as , this ironstone formation occupies an area of 115.9 km , and supports of vegetation on outcrops that are mostly in the Floresta Nacional de Carajás (FLONA of Carajás) and Parque Nacional dos Campos Ferruginosos (PNCF). The recent publication of the Flora of the s of Carajás lists 856 species of seed plants and 186 species of ferns and lycophytes. This project assessed the 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: (Rubiaceae), and (Asteraceae). From these, 24 are classified as Rare Species for Brazil and seven as Highly Restricted Endemic (EEO A Amazôna é um dos mais diversos biomas do mundo e inclui, bem como florestas luxuriantes, regiões montanhosas que, apesar de ocuparem uma área superficial relativamente pequena, apresentam endemismo fascinante. Ali, a especificidade de fatores edáficos é espelhada por uma flora isolada e altamente especializada para sobreviver em condições adversas. A Serra dos Carajás, no estado do Pará, é uma das maiores reservas de minério de ferro do mundo. Conhecidas localmente como cangas, as áreas de minério exposto ocupam uma área de 115,9 km , sobre as quais a vegetação de campo rupestre ocorre. A maioria destes afloramentos está incluída na Floresta Nacional de Carajás (FLONA of Carajás) e no Parque Nacional dos Campos Ferruginosos (PNCF). A publicação recente da Flora das cangas de Carajás listou 856 espécies de fanerógamas e 186 de samambaias e licófitas. Este projeto categorizou as espécies endêmicas da canga na região e valeu-se de expedições a áreas circunvizinhas delineadas por SDM, buscando estabelecer o endemismo dessas espécies fora da área contemplada na Flora. Partindo de uma lista inicial com 58 possíveis endêmicas, a lista final inclui 38 espécies de plantas vasculares (c. 4% da flora local). Estas são distribuídas em 31 gêneros e 22 famílias, incluindo três gêneros monotípicos: (Rubiaceae), e (Asteraceae). Destas, 24 foram classificadas como plantas de distribuição restritas no Brasil e sete como endêmicas altamente restritas (EE