Phylogeny and revision of the Neotropical genus Grumichella Müller (Trichoptera: Leptoceridae), including nine new species and a key

The systematics of the Neotropical caddisfly genus Grumichella Müller (Leptoceridae: Grumichellinae) are reviewed. Diagnoses, descriptions and illustrations are provided for four previously described species, G. aequiunguis Flint, 1983, G. flaveola (Ulmer, 1911), G. pulchella (Banks, 1910) and G. rostrata Thienemann, 1905, and nine new species: G. blahniki sp. nov. (Peru), G. boraceia sp. nov. (Brazil), G. cressae sp. nov. (Venezuela), G. jureia sp. nov. (Brazil), G. leccii sp. nov. (Brazil), G. muelleri sp. nov. (Brazil), G. paprockii sp. nov. (Brazil), G. parati sp. nov. (Brazil) and G. trujilloi sp. nov. (Venezuela). The monophyly of the genus is corroborated (16 synapomorphies) and the phylogenetic relationships of its included species, based on analysis of 66 adult, larval, and pupal characters, are inferred as (G. aequiunguis ((G. boraceiae (G. leccii, G. parati)) (G. rostrata ((G. flaveola, G. pulchella) (G. muelleri, G. paprockii)) (G. jureia (G. trujilloi (G. cressae, G. blahniki)))))). A taxonomic key to the males of the species is presented

A new classification of the long-horned caddisflies (Trichoptera: Leptoceridae) based on molecular data

Background: Leptoceridae are among the three largest families of Trichoptera (caddisflies). The current classification is founded on a phylogenetic work from the 1980's, based on morphological characters from adult males, i.e. wing venation, tibial spur formula and genital morphology. In order to get a new opinion about the relationships within the family, we undertook a molecular study of the family based on sequences from five genes, mitochondrial COI and the four nuclear genes CAD, EF-1 alpha, IDH and POL. Results: The resulting phylogenetic hypotheses are more or less congruent with the morphologically based classification, with most genera and tribes recovered as monophyletic, but with some major differences. For monophyly of the two subfamilies Triplectidinae and Leptocerinae, one tribe of each was removed and elevated to subfamily status; however monophyly of some genera and tribes is in question. All clades except Leptocerinae, were stable across different analysis methods. Conclusions: We elevate the tribes Grumichellini and Leptorussini to subfamily status, Grumichellinae and Leptorussinae, respectively. We also propose the synonymies of Ptochoecetis with Oecetis and Condocerus with Hudsonema.authorCount :

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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

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