Notes on mating behaviour and a possible new host plant for Megacyllene angulata (Fabricius, 1775) (Cerambycidae, Coleoptera)

The mating behavior of M. angulata (Fabricius, 1775) is described, illustrated and discussed. Additionally, we also comment on the possible new host plant of this species based on two plants (Luehea cymulosa Spruce ex Benth. (Malvaceae) and Doliocarpus dentatus (Aubl.) Standl (Dilleniaceae) on which copulation occurs

Alien spiders: First record of Loxosceles gaucho Gertsch, 1967 (Araneae: Sicariidae) in the Amazon region, Brazil

We present the first record for Loxosceles gaucho Gertsch, 1967 in the Amazonian region of Brazil. Four males, fifteen females and forty-nine immatures were collected in different places in Manaus, Amazonas, Brazil. This is the third species of Loxosceles reported in the Amazon region along with L. amazonica Gertsch, 1967, and L. similis Moenkhaus, 1898. This is the first record of an invasive species of a venomous animal in the state of Amazonas, Brazil, which is noteworthy due to its synanthropic habit, which increases the risk to the local population

Hexapoda Yearbook (Arthropoda: Mandibulata: Pancrustacea) Brazil 2020: the first annual production survey of new Brazilian species

This paper provided a list of all new Brazilian Hexapoda species described in 2020. Furthermore, based on the information extracted by this list, we tackled additional questions regarding the taxa, the specialists involved in the species descriptions as well as the journals in which those papers have been published. We recorded a total of 680 new Brazilian species of Hexapoda described in 2020, classified in 245 genera, 112 families and 18 orders. These 680 species were published in a total of 219 articles comprising 423 different authors residing in 27 countries. Only 30% of these authors are women, which demonstrates an inequality regarding sexes. In relation to the number of authors by species, the majority of the new species had two authors and the maximum of authors by species was five. We also found inequalities in the production of described species regarding the regions of Brazil, with Southeast and South leading. The top 10 institutions regarding productions of new species have four in the Southeast, two at South and with one ate North Region being the outlier of this pattern. Out of the total 219 published articles, Zootaxa dominated with 322 described species in 95 articles. The average impact factor was of 1.4 with only seven articles being published in Impact Factors above 3, indicating a hardship on publishing taxonomic articles in high-impact journals.The highlight of this paper is that it is unprecedent, as no annual record of Hexapoda species described was ever made in previous years to Brazil.Fil: Silva Neto, Alberto Moreira. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Lopes Falaschi, Rafaela. Universidade Estadual do Ponta Grossa; BrasilFil: Zacca, Thamara. Universidade Federal Do Rio de Janeiro. Museu Nacional; BrasilFil: Hipólito, Juliana. Universidade Federal da Bahia; BrasilFil: Costa Lima Pequeno, Pedro Aurélio. Universidade Federal de Roraima; BrasilFil: Alves Oliveira, João Rafael. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Oliveira Dos Santos, Roberto. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Heleodoro, Raphael Aquino. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Jacobina, Adaiane Catarina Marcondes. Universidade Federal do Paraná; BrasilFil: Somavilla, Alexandre. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Camargo, Alexssandro. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: de Oliveira Lira, Aline. Universidad Federal Rural Pernambuco; BrasilFil: Sampaio, Aline Amanda. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: da Silva Ferreira, André. Universidad Federal Rural Pernambuco; BrasilFil: Martins, André Luis. Universidade Federal do Paraná; BrasilFil: Figueiredo de Oliveira, Andressa. Universidade Federal do Mato Grosso do Sul; BrasilFil: Gonçalves da Silva Wengrat , Ana Paula. Universidade do Sao Paulo. Escola Superior de Agricultura Luiz de Queiroz; BrasilFil: Batista Rosa, Augusto Henrique. Universidade Estadual de Campinas; BrasilFil: Dias Corrêa, Caio Cezar. Universidade Federal Do Rio de Janeiro. Museu Nacional; BrasilFil: Costa De-Souza, Caroline. Museu Paraense Emilio Goeldi; BrasilFil: Anjos Dos Santos, Danielle. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Centro de Investigación Esquel de Montaña y Estepa Patagónica. Universidad Nacional de la Patagonia "San Juan Bosco". Centro de Investigación Esquel de Montaña y Estepa Patagónica; ArgentinaFil: Pacheco Cordeiro, Danilo. Instituto Nacional Da Mata Atlantica; BrasilFil: Silva Nogueira, David. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Almeida Marques, Dayse Willkenia. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Nunes Barbosa, Diego. Universidade Federal do Paraná; BrasilFil: Mello Mendes, Diego Matheus. Instituto de Desenvolvimento Sustentável Mamirauá; BrasilFil: Galvão de Pádua, Diego. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Silva Vilela, Diogo. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Gomes Viegas, Eduarda Fernanda. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Carneiro dos Santos, Eduardo. Universidade Federal do Paraná; BrasilFil: Rodrigues Fernandes, Daniell Rodrigo. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; Brasi

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

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

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