27 research outputs found
Carnívoros (Mammalia, Carnivora) do Quaternário da Serra da Bodoquena, Mato Grosso do Sul, Brasil
A report on fossil remains of carnivores from the Quaternary of Serra da Bodoquena (Mato Grosso do Sul, Brazil), recovered from two limestone flooded caves, is presented. A total of six species could be identified belonging to three carnivore families, namely Felidae (Smilodon populator, Panthera onca, Leopardus braccatus), Canidae (Protocyon troglodytes, Chrysocyon brachyurus) and Mustelidae (Pteronura brasiliensis), a mosaic of extinct and extant species presumably related to the Holo-Pleistocene fauna of the region. These findings support in part previous suggestions of a paleoecological scenario of open savannas rich in wetlands for the Quaternary environment of Serra da Bodoquena.Uma primeira apreciação relativa aos fragmentos fósseis de carnívoros do Quaternário da Serra da Bodoquena (Mato Grosso do Sul, Brasil) é apresentada. A amostra analisada foi recuperada em duas cavernas submersas e, presumivelmente, representam depósitos de origem associada ao intervalo entre Pleistoceno inferior e o Holoceno. Esta hipótese é corroborada pela megafauna de mamíferos associada. Seis espécies puderam ser identificadas, compreendendo três famílias de Carnívora: Felidae (Smilodon populator, Panthera onca, Leopardus braccatus), Canidae (Protocyon troglodytes, Chrysocyon brachyurus) e Mustelidae (Pteronura brasiliensis), retratando, assim, um mosaico de espécies recentes e extintas da fauna de carnívoros que compõem a região. Estes achados suportam parcialmente sugestões anteriores de um cenário paleoecológico de savanas ricas em áreas úmidas para o Quaternário da Serra da Bodoquena
Evolutionary scenarios associated with the Pteronotus parnellii cryptic species-complex (Chiroptera: Mormoopidae).
One of the major challenges to understanding the evolution of Neotropical bats concerns our capacity to successfully scrutinize phylogenetic patterns associated with cases of cryptic species complexes. In this study Pteronotus parnellii is examined as a selected example of a known lineage of mormoopid bat that potentially contains several cryptic species. A samples of 452 individuals from 83 different localities, essentially covering its entire mainland distribution, was evaluated using two genetic markers: COI (mitochondrial) and DBY (nuclear) genes. The findings of this study strongly support the hypothesis of high genetic variability and identify at least six lineages within P. parnellii, some of which appear to be cryptic species.Peer reviewe
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
Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences
The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported
by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on
18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based
researchers who signed it in the short time span from 20 September to 6 October 2016
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
Felid phylogenetics : extant taxa and skull morphology (Felidae, Aeluroidea). American Museum novitates ; no. 3047
67 p. : ill. ; 26 cm.Includes bibliographical references (p. 61-63