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

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications

Coccidioidomicose pulmonar em caçador de tatus Pulmonary coccidioidomycosis in a armadillo hunter

A coccidioidomicose, uma doença fúngica adquirida através da inalação do agente Coccidioides immitis sob forma de artroconídio, vem sendo descrita desde 1892. Restringe-se principalmente a áreas de clima árido, solo alcalino e regiões de baixo índice pluviométrico. Não por acaso, a maioria dos casos descritos no Brasil ocorreu na região Nordeste. Relata-se o caso de um homem de 19 anos, imunocompetente, com queixa de dor pleural bilateral, febre, adinamia e tosse seca havia dois meses. A radiografia de tórax evidenciou múltiplos nódulos bilaterais. O paciente participava de caçadas a tatus (Dasypus novemcinctus) e a pesquisa direta para fungos no escarro evidenciou Coccidioides sp. Tratado com anfotericina B, apresentou pneumotórax e insuficiência respiratória, indo a óbito. A biópsia pulmonar post mortem evidenciou Coccidioides immitis sob a forma de endósporos.<br>Coccidioidomycosis is a disease caused by inhalation of arthrospores of the fungus Coccidioides immitis. It has been recognized as a clinical entity since 1892. It is related to activities that involves dust exposure. It is found in many regions of the western hemisphere with dry and alkaline soil. In Brazil it has been described almost exclusively in the Northeast region where drought periods may favor its growth in its soil. We report a case of fatal coccidioidomycosis, in an immunocompetent host, associated to the activity of armadillo hunting (Dasypus novemcynctus) in a rural area of Ceará state

Aplicação foliar de fungicidas e incidência de grãos ardidos e fumonisinas totais em milho

O objetivo deste trabalho foi avaliar a eficiência da aplicação foliar de fungicidas na redução da incidência de patógenos fúngicos, de grãos ardidos e de fumonisinas totais em grãos de milho (Zea mays). Foram conduzidos três ensaios: um no município de Luís Eduardo Magalhães, na Bahia, e dois em Sete Lagoas, em Minas Gerais, nas safras 2010/2011 e 2011/2012, com cultivo de diferentes híbridos comerciais. Os seguintes fungicidas foram aplicados zero, uma e duas vezes: picoxistrobina + ciproconazol, piraclostrobina + epoxiconazole, trifloxistrobina + tebuconazole, azoxistrobina + ciproconazol e tiofanato metílico. Em todos os ensaios, foram realizados a quantificação da incidência de grãos ardidos, o teste de patologia de sementes e a quantificação dos teores de fumonisinas totais. Não foi observada diferença significativa para os fatores fungicida e número de aplicações, exceto para rendimento de grãos, em todos os ensaios. Esses resultados são indicativos da ineficiência da aplicação de fungicidas na redução da incidência de patógenos fúngicos, de grãos ardidos e dos teores de fumonisinas totais em grãos de milho.The objective of this work was to evaluate fungicide leaf application on the reduction of fungal pathogen incidence, kernel rot, and total fumonisins in corn (Zea mays) kernels. Three experiments were performed: one in the municipality of Luís Eduardo Magalhães, in the state of Bahia, and two in the municipality of Sete Lagoas, in the state of Minas Gerais, Brazil, during the 2010/2011 and 2011/2012 crop seasons, with planting of different commercial hybrids. The following fungicides were applied zero, one, and two times: picoxystrobin + cyproconazole, pyraclostrobin + epoxiconazole, trifloxystrobin + tebuconazole, azoxystrobin + cyproconazole, and thiophanate-methyl. For all trials, the quantification of kernel rot incidence, the grain pathology test, and the quantification of total fumonisins were performed. No significant difference was observed for the factors fungicide and number of applications, except for grain yield, in all trials. These results show the ineffectiveness of fungicide applications in reducing fungi incidence, kernel rot, and levels of total fumonisins in corn kernels

Chicken eggs as a surveillance tool for malaria and leishmaniasis vector presence

Abstract INTRODUCTION: Malaria and leishmaniases are transmitted by vectors during blood-feeding. Vector-infected animals develop antibodies against the vector’s saliva. This study evaluated IgY antibody detection in the chicken eggs exposed to bites from Migonemyia migonei, Lutzomyia longipalpis and Anopheles aquasalis. METHODS: We used ELISA to quantify the antibody levels in the sera and exposed chicken eggs. RESULTS: High IgY levels were observed following immunization; furthermore, higher reactivity was observed in the eggs and species-specific immune response was observed post final immunization. CONCLUSIONS: Chicken eggs can be used as sentinels to surveil vector saliva antibodies

AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest

The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these data