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.

/pdf/strategic-approaches-to-restoring-ecosystems-can-triple-otgxrg6zbz.pdf

Strategic approaches to restoring ecosystems can triple conservation gains and halve costs

The intrinsic value of biodiversity extends beyond species diversity, genetic heritage, ecosystem variability and ecological services, such as climate regulation, water quality, nutrient cycling and the provision of reproductive habitats it is also an inexhaustible source of molecules and products beneficial to human well-being. To uncover the chemistry of Brazilian natural products, the Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products Database (NuBBEDB) was created as the first natural product library from Brazilian biodiversity. Since its launch in 2013, the NuBBEDB has proven to be an important resource for new drug design and dereplication studies. Consequently, continuous efforts have been made to expand its contents and include a greater diversity of natural sources to establish it as a comprehensive compendium of available biogeochemical information about Brazilian biodiversity. The content in the NuBBEDB is freely accessible online (https://nubbe.iq.unesp.br/portal/nubbedb.html) and provides validated multidisciplinary information, chemical descriptors, species sources, geographic locations, spectroscopic data (NMR) and pharmacological properties. Herein, we report the latest advancements concerning the interface, content and functionality of the NuBBEDB. We also present a preliminary study on the current profile of the compounds present in Brazilian territory.

/pdf/nubbe-db-an-updated-database-to-uncover-chemical-and-3acskrmhuu.pdf

NuBBE(DB): an updated database to uncover chemical and biological information from Brazilian biodiversity

Ecological niche models (ENMs) is a popular method in ecology, mostly due to its broad applicability and the fact that required data is simple and easily accessible from digital databases. Nevertheless, there is an underlying methodological complexity, often overlooked by many scientists that rely on ENMs to achieve other objectives. We present here the package ENMTML, an Open Source R package. The main purpose of this package is to assemble all this methodological complexity spread over several papers and bring it into the spotlight in a simple way for people not used to the details of ENMs. The package contains several alternatives to different methodological steps, e.g., pseudo-absence allocation and accessible area delimitation, formulated within a single function, to make it accessible for people not used to the programming environment.

/pdf/enmtml-an-r-package-for-a-straightforward-construction-of-562n0wawi4.pdf

ENMTML: An R package for a straightforward construction of complex Ecological Niche Models

Taxonomic Information from Around the Web

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.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1394

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

Spatial analysis tools and synthesis of results are key to identifying the best solutions in biodiversity conservation. The importance of process automation is associated with increased efficiency and performance both in the data pre-processing phase and in the post-analysis of the results generated by the packages and modeling programs. The Model-R framework was developed with the main objective of unifying pre-existing ecological niche modeling tools into a common framework and building a web interface that automates steps of the modeling process and occurrence data retrieval. The web interface includes RJabot, a functionality that allows for searching and retrieving occurrence data from Jabot, the main reference on botanical collections management system in Brazil. It returns data in a suitable format to be consumed by other components of the framework. Currently, the tools are multi-projection, they can thus be applied to different sets of temporal and spatial data. Model-R is also multi-algorithm, with seven algorithms available for modeling: BIOCLIM, Mahalanobis distance, Maxent, GLM, RandomForest, SVM, and DOMAIN. The algorithms as well as the entire modeling process may be parametrized using command-line tools or through the web interface. We hope that the use of this application, not only by modeling specialists but also as a tool for policy makers, will be a significant contribution to the continuous development of biodiversity conservation analysis. The Model-R web interface can be installed locally or on a server. A software container is provided to automate the installation.

Model-R: A Framework for Scalable and Reproducible Ecological Niche Modeling

In this article we describe the Brazilian Biodiversity Information System, which aims to provide an infrastructure for gathering, integrating, and analyzing data produced by various institutions in this area. Both its architecture and the process for harvesting and indexing data on species occurrences and checklists, one of the already implemented components, are described. An implementation of a scalable scientific workflow for species distribution modeling, one of the most used applications for analyzing biodiversity, is presented. Finally, we describe current work on integrating socioeconomic data and on managing ecological data. Resumo. Neste artigo descrevemos o Sistema de Informação sobre a Biodiversidade Brasileira, que tem como objetivo fornecer uma infraestrutura para coleta, integração e análise de dados produzidos e disponibilizados por diversas instituições da área. A arquitetura de software do sistema é descrita, bem como o fluxo de coleta e indexação de dados de ocorrências e listas de espécies, um dos componentes já implementados. É apresentada a implementação de um workflow científico escalável para a modelagem da distribuição de espécies, uma das aplicações mais utilizadas na análise da biodiversidade. Finalmente, são descritos trabalhos em andamento como a integração de dados socioeconômicos e o gerenciamento de dados ecológicos.

SiBBr: Uma Infraestrutura para Coleta, Integração e Análise de Dados sobre a Biodiversidade Brasileira

Ecological niche models (ENM) use the environmental variables associated with the currently known distribution of a species to model its ecological niche and project it into the geographic space. Widely used and misused, ENM has become a common tool for ecologists and decision-makers. Many ENM platforms have been developed over the years, first as standalone programs, later as packages within script-based programming languages and environments. The democratization of these programming tools and the advent of Open Science brought a growing concern regarding the reproducibility, transparency, robustness, portability, and interoperability in ENM workflows.ENM workflows have some core components that are replicated between projects. However, they have a large internal variation due to the variety of research questions and applications. Any ecological niche modeling platform should take into account this trade-off between stability and reproducibility on one hand, and flexibility and decision-making on the other. Here, we present modleR, a four-step workflow that wraps some of the common phases executed during an ecological niche model procedure. We have divided the process into (1) data setup, (2) model fitting and projection, (3) partition joining and(4) ensemble modeling (consensus between algorithms). modleR is highly adaptable and replicable depending on the user9s needs and is open to deeper internal parametrization. It can be used as a testing platform due to its consistent folder structure and its capacity to control some sources of variation while changing others. It can be run in interactive local sessions and in high-performance or high-throughput computational (HPC/HTC) platforms and parallelized by species or algorithms. It can also communicate with other tools in the field, allowing the user to enter and exit the workflow at any phase, and execute complementary routines outside the package. Finally, it records metadata and session information at each step, ensuring reproducibility beyond the use of script-based applications.

https://biorxiv.org/content/10.1101/2020.04.01.021105v1.full.pdf

Guilherme Gall

Papers

Model-R: A Framework for Scalable and Reproducible Ecological Niche Modeling

SiBBr: Uma Infraestrutura para Coleta, Integração e Análise de Dados sobre a Biodiversidade Brasileira

modleR: a modular workflow to perform ecological niche modeling in R