ASPECTOS DO MANEJO DA VERMINOSE OVINA NA REGIÃO OESTE DE SANTA CATARINA

Os ovinos foram uma das primeiras espécies de animais a serem domesticados pelo homem, estando hoje presentes em praticamente todos os continentes. A ampla distribuição dos ovinos em diversos ambientes deve-se em grande parte à sua alta capacidade de adaptação aos diferentes climas e pastagens. Essa característica pode ser observada dentro do próprio território brasileiro, onde a ovinocultura é explorada em diversos estados, tanto com fins lucrativos, quanto para subsistência de famílias em áreas rurais (VIANA, 2008).A ovinocultura brasileira vem apresentando um crescimento constante. Isto se deve ao aumento no consumo da carne ovina e à viabilização desse sistema de produção em áreas impróprias para outras explorações pecuárias ou mesmo para a implantação de lavouras (NICIURA; VERÍSSIMO; MOLENTO, 2009)

Múltipla resistência anti-helmíntica em rebanhos ovinos no sul do Brasil

Gastrointestinal parasites represent an important cause of reduced productivity of sheep worldwide. As anthelmintic are still the main control tool for these parasites, this work evaluated the efficacy of commercially available active principles in 22 sheep flocks in the southern region of Rio Grande do Sul, Brazil. In each farm 10 sheep were randomly distributed in seven groups with the following treatments: abamectin; albendazole; closantel; levamisole; monepantel; trichlorphon and no anthelmintic (control). All flocks showed resistance to at least three anthelmintics and in 20 farms only two products demonstrated efficacy for parasitic control. In two farms, there was no susceptibility to the six active principles tested. The results of this study provide evidence that the common commercially available anthelmintic are not assuring effective chemical control of gastrointestinal parasitic infections in ovine flocks in the southern region of Rio Grande do Sul. Monepantel, the newest introduced drug in the Brazilian market was not effective in 18% of the flocks tested, confirming that the parasitic resistance can be established quickly after the introduction of new molecules mainly when alternative program of parasite control is not performed.As parasitoses gastrintestinais representam importante causa de queda na produtividade na ovinocultura mundial. Como a utilização de anti-helmínticos é, ainda, a principal forma de controle parasitário, o presente estudo avaliou a eficácia de princípios ativos comercialmente disponíveis, em 22 rebanhos ovinos da região Sul do Rio Grande do Sul, Brasil. Em cada propriedade foram utilizados 10 ovinos divididos em sete grupos que receberam os seguintes tratamentos: abamectina; albendazole; closantel; levamisole; monepantel; e triclorfon. Um grupo permaneceu como controle, sem tratamento anti-helmíntico. Nas 22 propriedades do estudo houve resistência, no mínimo, a três anti-helmínticos. Em 20 propriedades apenas dois produtos demonstraram eficácia para o controle parasitário. Em duas propriedades não houve sensibilidade aos seis princípios ativos testados. Os resultados do presente estudo demonstraram que os anti-helmínticos disponíveis no marcado Brasileiro não asseguram um controle parasitário efetivo nos rebanhos ovinos da região Sul do Rio Grande do Sul, incluindo o monepantel que foi ineficaz em 18% dos rebanhos testados, confirmando que a resistência dos parasitos aos princípios ativos pode se estabelecer rapidamente após a introdução de novas moléculas, principalmente quando programas alternativos de controle não são realizados

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