Dora Ann Lange Canhos

Bio: Dora Ann Lange Canhos is an academic researcher from Centra. The author has contributed to research in topics: Biodiversity & Biodiversity informatics. The author has an hindex of 9, co-authored 22 publications receiving 744 citations.

openModeller: a generic approach to species' potential distribution modelling

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.

New Brazilian Floristic List Highlights Conservation Challenges

Abstract: A comprehensive new inventory of Brazilian plants and fungi was published just in time to meet a 2010 Convention on Biological Diversity target and offers important insights into this biodiversity's global significance. Brazil is the home to the world's richest flora (40,989 species; 18,932 endemic) and includes two of the hottest hotspots: Mata Atlântica (19,355 species) and Cerrado (12,669 species). Although the total number of known species is one-third lower than previous estimates, the absolute number of endemic vascular plant species is higher than was previously estimated, and the proportion of endemism (56%) is the highest in the Neotropics. This compilation serves not merely to quantify the scale of the challenge faced in conserving Brazil's unique flora but also serves as a key resource to direct action and monitor progress. Similar efforts by other megadiverse countries are urgently required if the 2020 targets of the Convention on Biological Diversity and the Global Strategy for Plant Conserva...

The Importance of Biodiversity E-infrastructures for Megadiverse Countries

Abstract: Addressing the challenges of biodiversity conservation and sustainable development requires global cooperation, support structures, and new governance models to integrate diverse initiatives and achieve massive, open exchange of data, tools, and technology. The traditional paradigm of sharing scientific knowledge through publications is not sufficient to meet contemporary demands that require not only the results but also data, knowledge, and skills to analyze the data. E-infrastructures are key in facilitating access to data and providing the framework for collaboration. Here we discuss the importance of e-infrastructures of public interest and the lack of long-term funding policies. We present the example of Brazil’s speciesLink network, an e-infrastructure that provides free and open access to biodiversity primary data and associated tools. SpeciesLink currently integrates 382 datasets from 135 national institutions and 13 institutions from abroad, openly sharing ~7.4 million records, 94% of which are associated to voucher specimens. Just as important as the data is the network of data providers and users. In 2014, more than 95% of its users were from Brazil, demonstrating the importance of local e-infrastructures in enabling and promoting local use of biodiversity data and knowledge. From the outset, speciesLink has been sustained through project-based funding, normally public grants for 2–4-year periods. In between projects, there are short-term crises in trying to keep the system operational, a fact that has also been observed in global biodiversity portals, as well as in social and physical sciences platforms and even in computing services portals. In the last decade, the open access movement propelled the development of many web platforms for sharing data. Adequate policies unfortunately did not follow the same tempo, and now many initiatives may perish.

Predicting species distributions for conservation decisions

Abstract: Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

Growing knowledge: an overview of Seed Plant diversity in Brazil

Abstract: An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora.

sdm: a reproducible and extensible R platform for species distribution modelling

Abstract: sdm is an object-oriented, reproducible and extensible, platform for species distribution modelling. It uses individual species and community-based approaches, enabling ensembles of models to be fitted and evaluated, to project species potential distributions in space and time. It provides a standardized and unified structure for handling species distributions data and modelling techniques, and supports markedly different modelling approaches, including correlative, process-based (mechanistic), agent-based, and cellular automata. The object-oriented design of software is such that scientists can modify existing methods, extend the framework by developing new methods or modelling procedures, and share them to be reproduced by other scientists. sdm can handle spatial and temporal data for single or multiple species and uses high performance computing solutions to speed up modelling and simulations. The framework is implemented in R, providing a flexible and easy-to-use GUI interface.

Brazilian Flora 2020: Innovation and collaboration to meet Target 1 of the Global Strategy for Plant Conservation (GSPC)

Abstract: The Global Strategy for Plant Conservation (GSPC) was established by the Conference of Parties in 2002 to decrease the loss of plant diversity, reduce poverty and contribute to sustainable development. To achieve this overarching goal, the GSPC has established a series of targets, one of which is to ensure that plant diversity is well understood, so that it can be effectively conserved and used in a sustainable manner. Brazil hosts more than 46,000 species of plants, algae and fungi, representing one of the most biodiverse countries on Earth, and playing a key role in the GSPC. To meet the GSPC goals of Target 1 and facilitate access to plant diversity, Brazil committed to preparing the List of Species of the Brazilian Flora (2008–2015) and the Brazilian Flora 2020 (2016–present). Managing all the information associated with such great biodiversity has proven to be an extremely challenging task. Here, we synthesize the history of these projects, focusing on the multidisciplinary and collaborative approach adopted to develop and manage the inclusion of all the knowledge generated though digital information systems. We further describe the methods used, challenges faced, and strategies adopted, as well as summarize advances to date and prospects for completing the Brazilian flora in 2020.