Semiaquatic bugs (Insecta, Hemiptera, Heteroptera, Gerromorpha) from Parque Natural Municipal das Andorinhas, Ouro Preto, Minas Gerais state, Brazil

We present a survey of the semiaquatic bugs (Insecta, Hemiptera, Heteroptera, Gerromorpha) from Parque Natural Municipal das Andorinhas, Ouro Preto, Minas Gerais State, southeastern Brazil. Thirteen species are recorded from the area based on regular collection events, namely Brachymetra albinervus (Amyot & Serville, 1843); Cylindrostethus palmaris Drake & Harris, 1934; Halobatopsis delectus Drake & Harris, 1941; Ha. platensis (Berg, 1879); Metrobates plaumanni genikos Nieser, 1993; Neogerris kontos Nieser, 1994 (Gerridae); Hydrometra fruhstorferi Hungerford & Evans, 1934 (Hydrometridae); Platyvelia brachialis (Stål, 1860); Rhagovelia macta Drake & Carvalho, 1955; R. robusta Gould, 1931; R. sbolos Nieser & Melo, 1997; R. triangula Drake, 1953; and R. trianguloides Nieser & Melo, 1997 (Veliidae)

The grasshoppers (Orthoptera: Caelifera) of the grasslands in the southern portion of the Espinha?o Range, Minas Gerais, Brazil.

Neotropical mountains host much of the Earth?s biodiversity. The Espinha?o Range of Brazil consists of a fragmented series of low-altitude mountains with extensive areas of grasslands. As is often the case with grasslands, grasshoppers are abundant and diverse in this ecosystem, although they are poorly known. The study was carried in three regions of the Espinha?o Range, located at southeastern Minas Gerais state: Serra do Ouro Branco, Serra do Ribeiro, and Serra do Cip?. The sampling of grasshoppers was performed using sweep and insect nets. Forty-six species (Serra do Cip? with 39 species, Serra do Ouro Branco with 25 species, and Serra do Ribeiro with 21 species) were collected. The richest family and subfamily was Acrididae and Gomphocerinae, respectively. This study recorded 17 new species occurrences to Minas Gerais

Environmental factors can influence dengue reported cases

Introduction: Global climate changes directly affect the natural environment and contribute to an increase in the transmission of diseases by vectors. Among these diseases, dengue is at the top of the list. The aim of our study was to understand the consequences of temporal variability of air temperature in the occurrence of dengue in an area comprising seven municipalities of the Greater Sao Paulo. Method: Characterization of a temporal trend of the disease in the region between 2010 and 2013 was performed through analysis of the notified number of dengue cases over this period. Our analysis was complemented with meteorological (temperature) and pollutant concentration data (PM10). Results: We observed that the months of January, February, March, April and May (from 2010 to 2013) were the ones with the highest number of notified cases. We also found that there is a statistical association of moisture and PM10 with the reported cases of dengue. Conclusion: Although the temperature does not statistically display an association with recorded cases of dengue, we were able to verify that temperature peaks coincide with dengue outbreak peaks. Future studies on environmental pollution and its influence on the development of Aedes aegypti mosquito during all stages of its life cycle, and the definition of strategies for better monitoring, including campaigns and surveillance, would be compelling.ABC, FM, Santo Andre, SP, BrazilCoimbra Hlth Sch, Environm Hlth IPC, EsTesC, Coimbra, PortugalEsTesC, Coimbra Hlth Sch, Dept Ciencias Complementares IPC, Coimbra, PortugalFMABC, Gestao Saude Ambiental, Santo Andre, SP, BrazilUniv Fed Sao Paulo Unifesp, Biol Sci Dept, Diadema, SP, BrazilUniv Fed Sao Paulo Unifesp, Biol Sci Dept, Diadema, SP, BrazilWeb of Scienc

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