ESTUDO DA POTENCIALIDADE TURÍTICA DO PARQUE NACIONAL DE SETE CIDADES – PIAUÍ

O Ecoturismo é uma alternativa para apreciar a natureza, sendo um refúgio das atividades rotineiras dos grandes centros. Unidades de Conservação, como os Parques Nacionais, são áreas de proteção ambiental salvaguardadas de atividades impactantes à fauna e flora por atividades antrópicas, contribuindo para a preservação e conservação da biodiversidade dos biomas para as gerações futuras. Desta forma, como esses espaços são receptores de turistas, faz-se necessário uma estrutura para recebê-los, assim o principal objetivo do artigo é analisar a estrutura do Parque Nacional de Sete Cidades localizado no Piauí, a partir da análise SWOT. A metodologia empregada foi de cunho qualitativo, bibliográfico e pesquisa de campo. Assim sendo, pode-se concluir que o PARNA apresenta relevantes pontos fortes e oportunidades para se trabalhar o turismo, entretanto observam-se necessárias melhorias a serem aplicadas para que se tenha um melhor atendimento ao turista, além de investimentos em marketing atraindo, assim, mais visitantes ao PARNA

Plant stand failures effect in genetic parameters estimation procedure in Eucalyptus sp.

The objective of this work was to verify the influence of the percentage of failures in a forest genetics experiment in the estimation of genetic parameters. The study consisted in the evaluation of two experiments of full‑sib families under randomized complete block design with three replicates conducted in the state of Minas Gerais, Brazil. The experiment I was evaluated in January 2002, with approximately 60 months of age. The experiment II was evaluated in January 2003, with 45 months of age. In both experiments, the evaluations consisted of the measurement of the diameter at breast height and plant height. For all the investigated genetic parameters, an increase in the amplitude of the estimates was verified due to the increase in the number of experimental failures. Variances and negative heritabilities were detected, from 35% of failure, indicating that in such cases, this proportion of failure may be problematic to estimate genetic values, to estimate the gain with the selective process and for make decision

Exercise during pregnancy protects adult mouse offspring from diet-induced obesity

Physical exercise induces positive alterations in gene expression involved in the metabolism of obesity. Maternal exercise provokes adaptations soon after birth in the offspring. Here, we investigated whether adult mouse offspring of swim-trained mothers is protected against the development of the deleterious effects of high fat diet (HFD). Our study comprises two parts. First, female C57BL/6 mice were divided into one sedentary and one swim-trained group (before and during pregnancy, n = 18). In the second part, adult offspring (n = 12) of trained and sedentary mothers was challenged to HFD for 16 weeks. Notably, most of the analysis was done in male offspring. Our results demonstrate that maternal exercise has several beneficial effects on the mouse offspring and protects them from the deleterious effects of HFD in the adult. Specifically, swimming during pregnancy leads to lower birth weight in offspring through 2 months of age. When subjected to HFD for 4 month in the adulthood, our study presents novel data on the male offspring’s metabolism of trained mothers. The offspring gained less weight, which was accompanied by less body fat, and they used more calories during daytime compared with offspring of sedentary mothers. Furthermore, we observed increased adiponectin expression in skeletal muscle, which was accompanied by decreased leptin levels and increased insulin sensitivity. Decreased interleukin-6 expression and increased peptide PYY levels were observed in sera of adult offspring of mothers that swam during pregnancy. Our results point to the conclusion that maternal exercise is beneficial to protect the offspring from developing obesity, which could be important for succeeding generations as well12FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP2013/04757-

An extensive reef system at the Amazon River mouth

Large rivers create major gaps in reef distribution along tropical shelves. The Amazon River represents 20% of the global riverine discharge to the ocean, generating up to a 1.3 x 10(6)-km(2) plume, and extensive muddy bottoms in the equatorial margin of South America. As a result, a wide area of the tropical North Atlantic is heavily affected in terms of salinity, pH, light penetration, and sedimentation. Such unfavorable conditions were thought to imprint a major gap in Western Atlantic reefs. We present an extensive carbonate system off the Amazon mouth, underneath the river plume. Significant carbonate sedimentation occurred during lowstand sea level, and still occurs in the outer shelf, resulting in complex hard-bottom topography. A permanent near-bottom wedge of ocean water, together with the seasonal nature of the plume's eastward retroflection, conditions the existence of this extensive (similar to 9500 km(2)) hard-bottom mosaic. The Amazon reefs transition from accretive to erosional structures and encompass extensive rhodolith beds. Carbonate structures function as a connectivity corridor for wide depth-ranging reef-associated species, being heavily colonized by large sponges and other structure-forming filter feeders that dwell under low light and high levels of particulates. The oxycline between the plume and subplume is associated with chemoautotrophic and anaerobic microbial metabolisms. The system described here provides several insights about the responses of tropical reefs to suboptimal and marginal reef-building conditions, which are accelerating worldwide due to global changes.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Coordenadoria de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro (FAPERS)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)BrasoilMCTIBrazilian NavyU.S. NSFGordon and Betty Moore Foundation (GBMF)Univ Fed Rio de Janeiro UFRJ, Inst Biol, BR-21941599 Rio De Janeiro, RJ, BrazilUniv Fed Rio de Janeiro, COPPE, Inst Alberto Luiz Coimbra Posgrad & Pesquisa Engn, Lab Sistemas Avancados Gestao Prod, BR-21941972 Rio de Janeiro, RJ, BrazilInst Pesquisas Jardim Bot Rio de Janeiro, BR-22460030 Rio De Janeiro, RJ, BrazilUniv Sao Paulo, Inst Oceanog, BR-05508120 Sao Paulo, SP, BrazilUniv Fed Espirito Santo, Dept Oceanog, BR-29199970 Vitoria, ES, BrazilUniv Estadual Norte Fluminense, Lab Ciencias Ambientais, Ctr Biociencias & Biotecnol, BR-28013602 Campos Dos Goytacazes, RJ, BrazilUniv Fed Fluminense, Inst Geociencias, BR-24210346 Niteroi, RJ, BrazilUniv Fed Fluminense, Inst Biol, BR-24210130 Niteroi, RJ, BrazilUniv Fed Rio de Janeiro, Museo Nacl, BR-20940040 Rio De Janeiro, RJ, BrazilFed Univ Para, Inst Estudos Costeiros, BR-68600000 Braganca, PA, BrazilUniv Fed Sao Paulo, Dept Ciencias Mar, BR-11070100 Santos, SP, BrazilUniv Fed Pernambuco, Dept Oceanog, BR-50670901 Recife, PE, BrazilUniv Georgia, Dept Marine Sci, Athens, GA 30602 USAUniv Fed Paraiba, BR-58297000 Rio Tinto, PB, BrazilUniv Estadual Santa Cruz, Dept Ciencias Biol, BR-45650000 Ilheus, BA, BrazilUniv Fed Sao Paulo, Dept Ciencias Mar, BR-11070100 Santos, SP, BrazilU.S. NSF: OCE-0934095GBMF: 2293GBMF: 2928Web 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

Educomunicação, Transformação Social e Desenvolvimento Sustentável

Esta publicação apresenta os principais trabalhos dos GTs do II Congresso Internacional de Comunicação e Educação nos temas Transformação social, com os artigos que abordam principalmente Educomunicação e/ou Mídia-Educação, no contexto de políticas de diversidade, inclusão e equidade; e, em Desenvolvimento Sustentável os artigos que abordam os avanços da relação comunicação/educação no contexto da educação ambiental e desenvolvimento sustentável

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