Ocorrência de linfadenite em suínos criados em sistema convencional e cama sobreposta nas fases de crescimento e terminação

The occurrence of granulomatous lymphadenitis caused by the agents of the Mycobacterium avium Complex (MAC), and other pathologies, was studied comparing pigs created in deep-litter with two substrates. The study used 72 pigs/treatment/group in four consecutive groups distributed in three treatments: T1 deep-litter of wood shaving, T2 deeplitter of rice husk and T3 partially slatted floor. In all three treatments 2 pigs/pen at the first group were challenged with 2mg of MAC inoculum, in the first day. The occurrence of lymphadenitis was greater in pigs created in wood shaving, followed by those in rice husk and those in conventional system. The percentage of rough fiber in the feces was higher on animals grown in wood shaving, followed by those in rice husk, showing differences between treatments. This indicates that pigs ingested the materials used as bedding. The daily gain and conversion feed were better in pigs created in conventional system.Estudou-se a ocorrência de linfadenite granulomatosa causada por agentes do Complexo Mycobacterium avium (MAC), e outras patologias, de suínos criados em cama sobreposta com dois substratos. Utilizaramse 72 leitões/tratamento/lote em quatro lotes consecutivos distribuídos em três tratamentos: T1 maravalha, T2 casca de arroz e T3 piso de alvenaria semi-ripado. No primeiro lote 2 leitões/baia nos três tratamentos foram desafiados com suspensão de 2mg de MAC no primeiro dia. A ocorrência de linfadenite foi maior nos suínos em maravalha, seguidos daqueles em casca de arroz e em sistema convencional. A porcentagem média de fibra bruta nas fezes foi maior nos animais criados em maravalha, seguido de casca de arroz, mostrando diferença entre os tratamentos. Isto indica que os animais ingeriram o substrato usado como cama. O ganho de peso médio diário e conversão alimentar foi melhor nos suínos criados em sistema convencional

Fator de emissão de metano em depósitos abertos utilizados para armazenar dejetos suínos no Sul do Brasil

The objective of this work was to contribute to the establishment of a baseline for the methane emission factor for the management of swine manure, considering the current practice of raw manure storage in two open deposits in parallel, in Southern Brazil. Methane (CH4) emissions were continuously measured in three PVC tanks of 3 m3, during 180 days, in the summer. As the content of volatile solids of pig slurry ran out in approximately 130 days, the CH4 emission factor was calculated as B0= 0.48 m3 kg-1 VS. Although this value is higher than the B0 estimated by Intergovernmental Panel on Climate Change for Latin America (0.29 m3 kg-1 VS), it is in agreement with the B0 estimated for developed countries (0.45 and 0.48 m3 kg-1 VS, for the US and EU, respectively). The graphic of accumulated CH4-C emission x time fitted a sigmoidal, kinetic model (r2= 0.998) that showed a good correlation when tested with the emission data collected from a slurry deposit, under field conditions, in winter. This suggests that the model reproduces the CH4 emission kinetics in the region. By applying the reviewed state law rules (retention time of 50 instead of 120 days), estimates by the sigmoidal equation show that it is possible to reduce in more than 80% methane gas emission.O objetivo deste trabalho foi estabelecer uma linha de base do fator de emissão de metano para o manejo de dejetos suínos, ao se considerar a prática atual de armazenamento de dejetos sólidos em dois depósitos abertos paralelos, no Sul do Brasil. As emissões de metano (CH4) foram medidas continuamente em três tanques de PVC de 3 m3, durante 180 dias, no verão. Como o conteúdo de sólidos voláteis dos dejetos esgotou-se em aproximadamente 130 dias, calculou-se o fator de emissão de CH4 dos dejetos como B0 = 0,48 m3 kg-1 VS. Embora este valor seja superior ao B0 estimado pelo Painel Intergovernamental sobre Mudanças Climáticas para a América Latina (0,29 m3 kg-1 VS), ele está de acordo com o B0 estimado para países desenvolvidos (0,45 e 0,48 m3 kg-1 VS, para EUA e UE, respectivamente). O gráfico de emissão acumulada de C-CH4 x tempo ajustou-se a um modelo cinético sigmoidal (r2= 0,998), que apresentou boa correlação quando testado com dados coletados de um depósito de dejetos em condições de campo, no inverno. Isto sugere que o modelo reproduz a cinética de emissão do CH4 na região. Pela aplicação das regras revisadas da lei estadual (tempo de retenção de 50 dias, em substituição a 120 dias), as estimativas pela equação sigmoidal mostram que é possível reduzir em mais de 80% a emissão de gás metano

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

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer 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 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

Aeration frequency on accelerated composting of animal carcasses

ABSTRACT Rotary drum reactors (RDRs) for accelerated carcass composting are being installed in animal production units as an alternative for the disposal of pig and poultry carcasses in Brazil. The aim of the present study was to investigate the influence of aeration frequency on gas emissions (CO2-C, CH4-C, NH3-N and N2O-N) during composting of pig and poultry carcasses in RDRs. RDRs with a volume of 3.6 m3 (50% useful volume) were used. Aeration time was 24 minutes. Four intervals between aeration periods were tested (treatments) as follows: 1 hour (T1), 2 hours (T2), 3 hours (T3) and 4 hours (T4). Gas emissions were continuously monitored using a photoacoustic gas monitor (INNOVA 1412). Temperature was monitored using iButtons mixed with the biomass. Mathematical models of CO2-C and NH3-N emissions relative to the observed biomass temperature were proposed. Biomass temperature was affected by the treatments. The highest aeration frequency had the shortest thermophilic phase (>50 °C). No significant differences in total gas emissions were observed between treatments (p>0.05). CO2-C and NH3-N emissions were better fitted by non-linear models (R2=0.75 and R2=0.78, respectively). A minimum 2-hour interval should be adopted between aeration periods of 24 minutes to guarantee a longer thermophilic phase and elimination of possible pathogenic contaminants