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

Primary health care as assessed by health professionals: comparison of the traditional model versus the Family Health Strategy

ABSTRACT: Introduction: The Family Health Strategy (FHS) should be first-contact care in the Brazilian Health System. However, Primary Health Care (PHC) still encompasses two models: the FHS and the traditional health care facilities. The expansion of the FHS has been slow and heterogeneous in many cities, rendering a comparative evaluation of key quality-related elements of PHC models crucial. Objective: To compare the performance of PHC models as perceived by health professionals. Methods: A cross-sectional study involving managers and health professionals from PHC of a medium-size city in South-eastern Brazil. Data were collected by applying the Primary Care Assessment Tool. The performance was estimated through primary health care indexes (general and partial PHCI by attributes). Univariate polytomous logistic regression was performed to compare care model performances according to their attributes. Strength of association was estimated by odds ratio with 95% confidence interval. Results: Three managers and 81 health professionals participated in the study. The FHS had a better index rating than the traditional care model for general PHCI and for the attributes longitudinality, comprehensiveness, family focus and professional level. Conclusion: Although the FHS attained higher scores compared to the traditional model, it has not yet achieved the performance expected. This scenario points to the need for increased FHS cover and quality improvements at the existing units

Primary health care as assessed by health professionals: comparison of the traditional model versus the Family Health Strategy

<div><p>ABSTRACT: Introduction: The Family Health Strategy (FHS) should be first-contact care in the Brazilian Health System. However, Primary Health Care (PHC) still encompasses two models: the FHS and the traditional health care facilities. The expansion of the FHS has been slow and heterogeneous in many cities, rendering a comparative evaluation of key quality-related elements of PHC models crucial. Objective: To compare the performance of PHC models as perceived by health professionals. Methods: A cross-sectional study involving managers and health professionals from PHC of a medium-size city in South-eastern Brazil. Data were collected by applying the Primary Care Assessment Tool. The performance was estimated through primary health care indexes (general and partial PHCI by attributes). Univariate polytomous logistic regression was performed to compare care model performances according to their attributes. Strength of association was estimated by odds ratio with 95% confidence interval. Results: Three managers and 81 health professionals participated in the study. The FHS had a better index rating than the traditional care model for general PHCI and for the attributes longitudinality, comprehensiveness, family focus and professional level. Conclusion: Although the FHS attained higher scores compared to the traditional model, it has not yet achieved the performance expected. This scenario points to the need for increased FHS cover and quality improvements at the existing units.</p></div