Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

A influência da estrutura de propriedade e controle sobre a estrutura de capital : um estudo empírico no mercado acionário brasileiro de 2010 a 2016

Uma das principais políticas financeiras está relacionada à estrutura de capital, definida pelas empresas. Por este motivo, existe uma alta prioridade na agenda das pesquisas na área de finanças os estudos relacionados a fatores que determinam a estrutura de capital. Portanto, o objetivo geral desta pesquisa é identificar se a estrutura de capital das empresas abertas brasileiras é influenciada pela estrutura de propriedade e pela concentração de capital: é utilizado, o Maior Acionista Último (MAU1) e os três maiores acionistas últimos e suas características, seja familiar, capital estrangeiro, governo, BNDES e fundo de pensão, sendo que é utilizado cut-offs, de acordo com a teoria estudada, de 10% e 50%. A amostra analisada abrange 128 empresas brasileiras listadas na B3, entre 2010 e 2016, excluindo da amostra empresas do setor financeiro. Para verificar a influência da estrutura de capital, são utilizados modelos de regressão com dados em painel (efeito fixo e robustez). Os resultados são condizentes com os esperados, portanto, o excesso de concentração de capital prejudica o endividamento. Outra característica importante do mercado acionário brasileiro é o controle familiar, que em função da aversão à perda do controle, reduz o financiamento por dívidas. Já a presença de capital estrangeiro, governo, BNDES e fundo de pensão têm relações positivas com o endividamento. Aponta-se como possíveis contribuições originais e relevantes deste projeto: o efeito da estrutura de propriedade sobre a estrutura de capital das empresas; a metodologia empregada utilizando os formulários de referência, que nos proporciona detectar o Maior Acionista Último em detalhes; e as estruturas mais complexas (piramidais) da empresa. Também são analisados a abrangência e a atualização da amostra: são usados dados desde a concepção dos formulários de referência de janeiro de 2010 até o fim de 2016 – divulgados até dezembro de 2017 – e, por fim, as novas variáveis explicativas sobre estrutura de capital, o grau de concentração de capital e a natureza do controle acionário.One of the main financial policies is related to the capital structure that companies define for themselves. Due to this reason, determinants of factors of capital structure is a high priority topic on the agenda of financial researchers. However, the main objective of this research is to determine if the capital structure of Brazilian public companies is influenced by their own ownership structure and by it‟s capital concentration. We utilize the major last shareholder (MAU1) and the three major last shareholders (MAU3) and their characteristics, be them a family company, foreign capital, government, BNDES or pension fund. Cut-offs between 10% to 50% are utilized based on the corporate finance theory. The sample studied comprises 128 Brazilian companies listed on the B3 stock exchange. The data comprises the period between 2010 and 2016, excluding financial companies from the sample. To verify the influence of capital structure fixed effects panel data with robust regressions are used. The results corroborate that which is expected by the theory. However, excess capital concentration hurts debt financing. Another important characteristic of the Brazilian stock market is the prevalence of companies with founding families as controlling members, this leads to a reduced use of debt financing due to worries related to loss of control. In the other hand the existence of foreign capital, government, BNDES and pension funds has a positive relationship with debt financing. We point to the effect of ownership structure on the capital structure of companies, the utilized methodology regarding reference forms which allows us to detect the last major shareholder in detail, and the more complex ownership structure (pyramidal) for companies as possible original and relevant contributions to the literature that result from this research. We also analyze the comprehensiveness and contemporaneous quality of the sample: The data used starts at the creation of the reference forms in January of 2010 until the end of2016 – published in December 2017 – and finally, the new explanatory variables in capital structure literature (capital concentration and nature of the ownership structure)

O nível de concentração de capital influencia a estrutura de capital das empresas brasileiras?

O objetivo da presente pesquisa é identificar se a estrutura de capital das empresas abertas brasileiras é influenciada pelo nível de concentração de capital. Adotou-se como amostra as  104 empresas brasileiras de capital aberto listadas na BM&FBOVESPA, totalizando 1.258 observações para dados anuais do período de 1º de janeiro de 2008 a 31 de dezembro de 2014. Ao utilizar a análise com dados em painel e levar em consideração as variáveis de controle apontadas como relevantes pela literatura, os principais resultados mostraram que (i) a concentração de capital possui uma relação positiva com o endividamento de mercado e com a dívida líquida de longo prazo sobre Patrimônio Líquido de mercado; (ii) as variáveis tamanho, volatilidade, rentabilidade e tangibilidade, destacadas no arquétipo teórico, evidenciaram uma significativa influência na dívida de longo prazo sobre PL a mercado e contábil, e (iii) não houve qualquer tipo de constatação e/ou inferência que a dívida líquida sobre o EBITDA pode trazer implicações para a concentração de capital dos acionistas. Para estudos futuros, sugere-se i) incrementar observações de empresas de capital fechado brasileiras; ii) comparar os resultados obtidos com a estrutura de capital de outros países, e iii) evidenciar e relacionar outras variáveis da literatura não abordadas pela presente pesquisa

Empresas Brasileiras Estatais e não Estatais: uma Análise das Relações de Endividamento

Objetivo: O objetivo desta pesquisa é analisar as relações do endividamento das empresas brasileiras estatais e não estatais. Para o desenvolvimento da pesquisa, adotou-se como amostra as empresas brasileiras de capital aberto listadas na BM&FBOVESPA no período de 2008 à 2014.Fundamento: A partir das abordagens das Teoria de Trade Off, Teoria de Pecking Order e Teoria de Agência, muito tem se discutido com relação a compreensão de como as empresas privadas e estatais tomam decisões relacionadas a encontrar as fontes de financiamento dos seus respectivos negócios.Método: A composição da amostra foi constituída por 104 companhias abertas no Brasil, totalizando 4.936 observações para dados anuais no período de 1º de janeiro de 2008 a 31 de dezembro de 2014. Os seguintes testes estatísticos foram aplicados: (i) teste de Shapiro-Wilk, para avaliar se as observações das companhias abertas possuíam distribuição de retornos próxima da distribuição normal, (ii) Winsorize, para verificação de possíveis outiliers na base de dados e inferir valor de limite; (iii) Teste VIF, medidor de colinearidade e (iv) Dados em Painel, com os respectivos testes de validação para cada modelo (Chow, Breusch Pagan e Hausman).Resultados: Os principais resultados mostraram que: (i) quanto maior o tamanho da empresa, menor o nível de endividamento; (ii) o endividamento das empresas privadas é menor do que as empresas estatais e (iii) não houve qualquer tipo de constatação e/ou inferência que a variável concentração de capital pode trazer implicações para a possível relação significativa do endividamento contábil e de mercado nas empresas brasileiras estatais e não estatais.Contribuições: Como contribuição teórica, evidencia-se que a estrutura de capital ainda carece de pesquisas, seja na parte teórica quanto nas inter-relações com outros aspectos de finanças corporativas. Já como contribuição prática, esta pesquisa objetiva apresentar a determinação adequada da estrutura de capital para os gestores financeiros, seja ela privada e/ou estatal, oportunizando um menor nível de custo de capital possível

O nível de concentração de capital influencia a estrutura de capital das empresas brasileiras?

The purpose of the present research is to identify whether the capital structure of the Brazilian listed companies is influenced by the capital concentration level. The sample comprises 104 Brazilian publicly traded companies listed on the BM&FBOVESPA, totaling 1,258 observations for annual data in the period from January 1st, 2008 to December 31st, 2014. By using panel data analysis and taking into account the control variables identified as relevant in the literature, the main results show that (i) capital concentration has a positive relation with market indebtedness and with long-term net debt to market equity; (ii) the variables size, volatility, profitability and tangibility, highlighted in the theoretical archetype, evidence a significant influence on long-term debt to market equity and book equity, and (iii) there are no findings and/or inferences that net debt to EBITDA may bring implications for shareholders´ capital concentration. For future studies, suggestions are: i) to increase observations of Brazilian privately held companies; ii) to compare the results obtained with the capital structure of other countries, and iii) to highlight and relate other variables in the literature which are not addressed by the present research.O objetivo da presente pesquisa é identificar se a estrutura de capital das empresas abertas brasileiras é influenciada pelo nível de concentração de capital. A amostra aborda 104 empresas brasileiras de capital aberto, listadas na BM&FBOVESPA, totalizando 1.258 observações para dados anuais, do período de 1º de janeiro de 2008 a 31 de dezembro de 2014. Ao utilizar a análise com dados em painel e levar em consideração as variáveis de controle, apontadas como relevantes pela literatura, os principais resultados mostram que (i) a concentração de capital possui uma relação positiva com o endividamento de mercado e com a dívida líquida de longo prazo sobre o Patrimônio Líquido de mercado; (ii) as variáveis tamanho, volatilidade, rentabilidade e tangibilidade, destacadas no arquétipo teórico, evidenciam uma significativa influência na dívida de longo prazo sobre PL a mercado e contábil, e (iii) não houve qualquer tipo de constatação e/ou inferência que a dívida líquida sobre o EBITDA pode trazer implicações para a concentração de capital dos acionistas. Para estudos futuros, sugere-se i) incrementar observações de empresas de capital fechado brasileiras; ii) comparar os resultados obtidos com a estrutura de capital de outros países, e iii) evidenciar e relacionar outras variáveis da literatura, não abordadas pela presente pesquisa

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data