Pontes entre famílias e acolhidos: reintegração familiar e adoção de crianças e adolescentes com deficiência

The study aimed to describe the perception of caregivers and the role of professionals in the process of family reintegration and adoption of children and adolescents with disabilities in a host institution in Belém/PA. Ten family members of five children and three professionals from the technical team participated. The data were collected during the execution of the Pontes Project, by means of recording in a field diary, and the analysis was carried out with the content analysis technique using the software Iramuteq (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires). The main findings showed the importance of the families being monitored by the technical team for the process of family reintegration and adoption.El presente estudio tuvo como objetivo describir la percepción de los cuidadores y el rol de los profesionales en el proceso de reinserción familiar y adopción de niños, niñas y adolescentes con discapacidad en una institución de acogida. La investigación se llevó a cabo en una institución que acoge a niños y adolescentes con discapacidad en la ciudad de Belém/PA. Participaron diez familiares de cinco acogidos y tres profesionales del equipo técnico. Los datos fueron recogidos durante la ejecución del Proyecto Pontes, mediante el registro en un diario de campo, y el análisis se realizó mediante la técnica de análisis de contenido y utilizando el software Iramuteq (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires). Los principales hallazgos mostraron la importancia del seguimiento de las familias por parte del equipo, como fundamental para el proceso de reintegración y adopción familiar.O estudo teve como objetivo descrever a percepção de cuidadores e o papel de profissionais no processo de reintegração familiar e adoção de crianças e adolescentes com deficiência em uma instituição de acolhimento de Belém/PA. Participaram dez familiares de cinco acolhidos e três profissionais da equipe técnica. Os dados foram coletados durante a execução do Projeto Pontes, por meio de registro em diário de campo, e a análise foi realizada por meio da técnica de análise de conteúdo mediante a aplicação do software IRaMuTeQ (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires). Os principais achados demonstraram a importância do acompanhamento das famílias por parte da equipe técnica para o processo de reintegração familiar e adoção

INTELLIGENCE PROFILE OF CHILDREN WITH A HISTORY OF INSTITUTIONAL CARE: A LONGITUDINAL STUDY

Intelligence is the general mental capacity that involves using the ability to reason, plan, solve problems, think abstractly and learn from experience, in addition to allowing the acquisition of new learning over time that require logical and abstract relationships, as well as the ability to solve increasingly complex problems. Despite the prominent role played by genetic inheritance, when analyzing the different trajectories of human development, empirical evidence reveals the influence of the context on the development of intelligence and the structuring of distinct intellectual profiles over time. One of these development contexts may be the Institutional Home, a protective measure aimed at guaranteeing the rights and protection of children and adolescents. Thus, this study aimed to describe the intelligence profile of children with a history of institutionalization in the Metropolitan Region of Belém. This is a longitudinal study, of a quantitative and qualitative nature, in which 15 children, located in two municipalities in the metropolitan region of Belém, who were in the childcare services participated. Data collection took place between December 2017 and December 2018, in three stages, with an interval of six months between each stage, forming two different groups: Group 1, formed by four children institutionalized throughout the research and Group 2, consisting of eleven children who were with their family at the last moment of the collection. The results show statistically significant differences regarding the average IQ in the three assessment moments, emphasizing that children in G1 have a low intellectual profile when compared to the participants in G2. Cognitive development was associated with the interaction of the individual attributes of each participant with the characteristics of their developmental context. In this sense, the existence of an unfavorable particularity, such as having psychopathological complications and being in an institutional environment, generated a low intellectual profile. On the other hand, having experienced situations of vulnerability and institutionalization, without the emergence of severe mental disorders and being reinserted in the family, made it possible to overcome intellectual damage generated by adverse experiences, provided that in the family context there were adults available for establishing a bond, carrying out joint activities and providing personalized care

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

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 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

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