Family education and support programme: implementation and cultural adaptation in Cape Verde

This article describes some preliminary data on the implementation of the Family Education and Support Programme (FAF) on psychosocially at-risk families of Boavista Island, Cape Verde, specifically in relation to its effectiveness in parenting competences. The FAF is a family intervention programme designed to be integrated into preventive and formative actions and it has the purpose of promoting positive parenting and preventing child abuse. This study aims to (a) describe the participants’ psychosocial profile regarding sociodemographic characteristics and negative or risky life events, (b) analyse the effectiveness of the FAF on improving parenting competences, and (c) address the main procedural topics related to the implementation of the FAF in Cape Verde. An experiential and participatory methodology was used with 66 parents, who participated in 12 group sessions, with a weekly periodicity, for four months. The evaluation was performed, in the pre-test and post-test, with the control group and the intervention group. Results show the effectiveness of the FAF in an African context, including its impact. The intervention group improved their post-intervention scores on perceived efficacy and satisfaction with a moderate and high effect size, respectively. We present some recommendations to be considered in future programs to promote positive parenting, since improvements in parents’ competences, are key to reducing neglectful or abusive situations.info:eu-repo/semantics/publishedVersio

SOME ASPECTS OF THE POPULATION ECOLOGY OF THE EXOTIC AMPHIPOD, TALITROIDES TOPITOTUM, IN AN ATLANTIC FOREST RESERVE IN BRAZIL

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First report on dung beetles in intra-Amazonian savannahs in Roraima, Brazil

This is the first study to address the dung beetle (Coleoptera: Scarabaeidae: Scarabaeinae) diversity in intra-Amazonian savannahs in the state of Roraima, Brazil. Our aim was to survey the dung beetle fauna associated with these savannahs (regionally called 'lavrado'), since little is known about the dung beetles from this environment. We conducted three field samples using pitfall traps baited with human dung in savannah areas near the city of Boa Vista during the rainy seasons of 1996, 1997, and 2008. We collected 383 individuals from ten species, wherein six have no previous record in intra-Amazonian savannahs. The most abundant species were Ontherus appendiculatus (Mannerheim, 1829), Canthidium aff. humerale (Germar, 1813), Dichotomius nisus (Olivier, 1789), and Pseudocanthon aff. xanthurus (Blanchard, 1846). We believe that knowing the dung beetles diversity associated with the intra-Amazonian savannahs is ideal for understanding the occurrence and distribution of these organisms in a highly threatened environment, it thus being the first step towards conservation strategy development

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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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