MODELOS ORGANIZACIONAIS PARA TREINAMENTO VERSUS ESTILOS DE APRENDIZAGEM DE COLABORADORES: UM ESTUDO DE CASO EM UMA EMPRESA DE SERVIÇOS DE INFRAESTRUTURA

The study aimed to identify the training mechanisms used by a company that operates in the area of infrastructure services, and belong to the Productive Chain PVC, Oil, Gas and Energy in Maceió city, State of Alagoas, Brazil, to promote and encourage the productive skills in their employees and learning style of these employees, to assess convergences or asymmetries between these factors. The methodology, conducted in case study format, had a multi-level character, through documentary, interviews and survey research of learning styles. Based on the Kolb’s theory (1984), the survey of learning styles was made through the Inventory of Learning Styles. Results indicated that there there was a balance between the styles Divergent (40%) and Assimilator (35%) for employees participating in the survey. These learning styles have compatibility with the formats of training and capacity developed by the company investigated. The discussion brings a deepening of the theme of learning in organizational terms, which emerge implications of these results for improving the productive contexts by organizations in networks. Furthermore, increases the prospect of training and of experiential learning to the levels of teaching and learning, which provides support to other studies in this direction.El estudio objetivó identificar los mecanismos de entrenamiento utilizados por una empresa que opera en la área del servicios de infraestructura, y que pertenece a la Cadena Productiva de PVC, Petróleo, Gas y Energía en Maceió/AL, para promover y fomentar la capacidad productiva de sus empleados y comprobar el estilo de aprendizaje de estos empleados, para evaluar convergencias o asimetrías entre estos factores. La metodología, realizada en formato de estudio de caso, tuvo carácter multinivel, a través de investigaciones documentáis, entrevistas y encuesta de los estilos de aprendizaje. Con base en la teoría de Kolb (1984), la encuesta de los estilos de aprendizaje se hizo a través del Inventario de Estilos de Aprendizaje. Había un equilibrio entre estilos divergentes (40%) y asimilador (35%) de los empleados que participan de la encuesta. Estos estilos asumen compatibilidad con los formatos de los entrenamientos e de las formaciones desarrolladas por la empresa investigada. La discusión puede profundizar el tema del aprendizaje en organizaciones, a medida que surgen implicaciones de estos resultados para la mejora de la producción de las organizaciones en redes. Por otra parte, aumenta la perspectiva del entrenamiento y aprendizaje experiencial para niveles de enseñanza y aprendizaje, que presta apoyo a otros estudios en esta dirección.O artigo tem como objetivo identificar os mecanismos de treinamento utilizados por uma empresa que atua na área de serviços de infraestrutura e estilos de aprendizagem de seus colaboradores, para aferir convergências ou assimetrias entre esses fatores. A empresa objeto do estudo faz parte da Cadeia Produtiva de PVC, Petróleo, Gás e Energia em Maceió – AL. A metodologia, conduzida em formato de estudo de caso, teve caráter multinível e utilizou pesquisas documentais, entrevistas e um levantamento dos estilos de aprendizagem. Com base na teoria de Kolb (1984), o levantamento dos estilos de aprendizagem deu-se através do Inventário de Estilos de Aprendizagem. Verificou-se um equilíbrio entre estilos Divergente (40%) e Assimilador (35%) para os colaboradores participantes da pesquisa. Estes estilos assumem compatibilidade com os formatos de treinamento e capacitação desenvolvidos pela empresa investigada. A discussão traz um aprofundamento do tema da aprendizagem em termos organizacionais, emergindo as implicações desses resultados para contextos de melhoria produtiva por parte de organizações em rede. Além disso, amplia a perspectiva do treinamento e da aprendizagem experiencial em níveis de ensino-aprendizagem, o que fornece suporte para outros estudos nessa direção

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

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 ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

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