Desvendando padrões estruturais de fragmentos florestais na Amazônia Oriental

Natural fragments are an important source of richness for the management and conservation of a local flora. The objective of this study was to evaluate the effect of fragmentation on the structure and composition of the plant communities of forest fragments (FF) in Alter do Chão, eastern Brazilian Amazonia. The study sample consisted of 25 FF and nine continuous forest (CF) sites. We compared plant density and species richness between site categories by t-tests, analyzed the differences in composition by cluster analysis, and assessed the effect of fragment size and distance to CF on the basal area and diameter of FF assemblages by linear regression. Individual trees and shrubs with DBH ≥1.27 cm were measured in 2x250 m plots. 17,078 individuals were recorded - 75.32% in FF and 24.68% in CF, comprising 475 species, 216 genera and 64 families. Myrtaceae and Fabaceae were the most abundant families in both FF and CF. Average species richness in FF and CF was statistically different. The 20 species with the highest importance values were similar in FF and CF. The average plant diameter was similar in FF and CF, suggesting that both are "mature" forests composed of thin individuals. Average diameter and total basal area showed a negative relationship with distance to CF and fragment area, respectively. Similarity analysis revealed two groups, one composed exclusively of portions of fragmented forest. Fragments and continuous forest differed in species composition, but were similar in structure. Diameter distribution in fragments was similar to that of primary forests.Fragmentos naturais constituem importante fonte de recursos para o manejo e conservação da flora local. Este trabalho avaliou o efeito da fragmentação sobre a estrutura e a composição das comunidades de plantas de fragmentos florestais (FF), em Alter do Chão, na Amazônia oriental brasileira. Foram amostrados 25 sítios em FF e nove em floresta contínua (CF). Analisamos a diferença na densidade de plantas e na riqueza de espécies entre FF e CF por teste-t, e na composição por análise de agrupamento. Utilizou-se regressão linear para avaliar o efeito do tamanho dos fragmentos e distância à CF sobre a área basal e diâmetro. Os indivíduos com DAP ≥1,27 cm foram medidos em parcelas de 2x250 m. Foram registrados 17.078 indivíduos, 75,32% nos FF e 24,68% na CF, distribuídos em 475 espécies, 216 gêneros e 64 famílias. As famílias Myrtaceae e Fabaceae foram as mais abundantes em ambos FF e CF. A riqueza média diferiu significativamente entre FF e CF. As 20 espécies com maior valor de importância foram semelhantes nos FF e CF. O diâmetro médio nos FF e CF foi semelhante, sugerindo tratar-se em ambos casos de florestas "maduras" compostas por indivíduos finos. O diâmetro médio e a área basal total mostraram relação negativa com a distância à CF e área dos fragmentos, respectivamente. A análise de similaridade revelou dois grupos, um deles composto exclusivamente por fragmentos. Composicionalmente, os fragmentos diferiram da floresta contínua, sendo estruturalmente semelhantes entre si, evidenciando distribuição diamétrica semelhante à das florestas primárias

Wild dogs at stake: deforestation threatens the only Amazon endemic canid, the short-eared dog (Atelocynus microtis)

The persistent high deforestation rate and fragmentation of the Amazon forests are the main threats to their biodiversity. To anticipate and mitigate these threats, it is important to understand and predict how species respond to the rapidly changing landscape. The short-eared dog Atelocynus microtis is the only Amazon-endemic canid and one of the most understudied wild dogs worldwide. We investigated short-eared dog habitat associations on two spatial scales. First, we used the largest record database ever compiled for short-eared dogs in combination with species distribution models to map species habitat suitability, estimate its distribution range and predict shifts in species distribution in response to predicted deforestation across the entire Amazon (regional scale). Second, we used systematic camera trap surveys and occupancy models to investigate how forest cover and forest fragmentation affect the space use of this species in the Southern Brazilian Amazon (local scale). Species distribution models suggested that the short-eared dog potentially occurs over an extensive and continuous area, through most of the Amazon region south of the Amazon River. However, approximately 30% of the short-eared dog's current distribution is expected to be lost or suffer sharp declines in habitat suitability by 2027 (within three generations) due to forest loss. This proportion might reach 40% of the species distribution in unprotected areas and exceed 60% in some interfluves (i.e. portions of land separated by large rivers) of the Amazon basin. Our local-scale analysis indicated that the presence of forest positively affected short-eared dog space use, while the density of forest edges had a negative effect. Beyond shedding light on the ecology of the short-eared dog and refining its distribution range, our results stress that forest loss poses a serious threat to the conservation of the species in a short time frame. Hence, we propose a re-assessment of the short-eared dog's current IUCN Red List status (Near Threatened) based on findings presented here. Our study exemplifies how data can be integrated across sources and modelling procedures to improve our knowledge of relatively understudied species

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

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

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions

Possible impacts of climate change on wetlands and its biota in the Brazilian Amazon

Wetlands cover approximately 6% of the Earth's surface. They are frequently found at the interface between terrestrial and aquatic ecosystems and are strongly dependent on the water cycle. For this reason, wetlands are extremely vulnerable to the effects of climate change. Mangroves and floodplain ecosystems are some of the most important environments for the Amazonian population, as a source of proteins and income, and are thus the types of wetlands chosen for this review. Some of the main consequences that can be predicted from climate change for wetlands are modifications in hydrological regimes, which can cause intense droughts or inundations. A possible reduction in rainfall can cause a decrease of the areas of mangroves and floodplains, with a consequent decline in their species numbers. Conversely, an increase in rainfall would probably cause the substitution of plant species, which would not be able to survive under new conditions for a long period. An elevation in water temperature on the floodplains would cause an increase in frequency and duration of hypoxic or anoxic episodes, which might further lead to a reduction in growth rates or the reproductive success of many species. In mangroves, an increase in water temperature would influence the sea level, causing losses of these environments through coastal erosion processes. Therefore, climate change will likely cause the loss of, or reduction in, Amazonian wetlands and will challenge the adaptability of species, composition and distribution, which will probably have consequences for the human population that depend on them

Steps of the methodological approach used in this study (GDM–geographical distribution model).

<p>Methods.</p