Efeito da temperatura de carbonização sobre características físico- químicas dos carvões de duas espécies de bambu: Effect of pyrolisis temperature on physicochemical properties of biochars made from two different bamboo species

Por sua alta eficiência fotossintética e conversão em biomassa, o bambu tem gran- de potencial para a produção de carvão de uso agrícola (biocarvão). Este trabalho comparou os carvões produzidos a diferentes temperaturas de pirólise a partir do colmo de duas espécies de larga ocorrência no sul do país: Phyllostachys aurea (uma espécie exótica) e Guadua sp. (na- tiva do sul do Brasil). Os resultados mostraram diferenças entre as duas espécies, a começar pelo teor de lignina e de voláteis dos colmos in natura, sendo que a espécie exótica mostrou maiores teores de lignina e menores de extrati- vos. Estas diferenças se refletem no processo de pirólise e nas características químicas dos carvões, sendo que a espécie exótica produz carvões com maiores teores de carbono

Fluxos de nitrogênio em feijoeiro irrigado influenciados pela cobertura morta e a fertilização mineral

The objective of this work was to measure the fluxes of N2O‑N and NH3‑N throughout the growing season of irrigated common‑bean (Phaseolus vulgaris), as affected by mulching and mineral fertilization. Fluxes of N2O‑N and NH3‑N were evaluated in areas with or without Congo signal grass mulching (Urochloa ruziziensis) or mineral fertilization. Fluxes of N were also measured in a native Cerrado area, which served as reference. Total N2O‑N and NH3‑N emissions were positively related to the increasing concentrations of moisture, ammonium, and nitrate in the crop system, within 0.5 m soil depth. Carbon content in the substrate and microbial biomass within 0.1 m soil depth were favoured by Congo signal grass and related to higher emissions of N2O‑N, regardless of N fertilization. Emission factors (N losses from the applied mineral nitrogen) for N2O‑N (0.01–0.02%) and NH3‑N (0.3–0.6%) were lower than the default value recognized by the Intergovernmental Panel on Climate Change. Mulch of Congo signal grass benefits N2O‑N emission regardless of N fertilization.O objetivo deste trabalho foi medir os fluxos de N2O‑N e NH3‑N, ao longo de uma safra de feijoeiro irrigado (Phaseolus vulgaris), influenciados pelo uso ou não de cobertura morta e fertilização mineral. Os fluxos de N2O‑N e NH3‑N foram avaliados em áreas com ou sem cobertura de braquiária (Urochloa ruziziensis) ou fertilização mineral. Os fluxos de N também foram medidos em uma área nativa de Cerrado, a qual serviu como referência. As emissões de N2O‑N and NH3‑N foram positivamente relacionadas ao aumento da umidade e das concentrações de amônio e nitrato na área cultivada, na camada até 0,5 m de profundidade do solo. O conteúdo de C no substrato e a atividade microbiana na camada até 0,1 m de profundidade do solo foram favorecidos pela presença da palhada de braquiária e estiveram relacionadas com maiores emissões de N2O‑N, independentemente da fertilização nitrogenada. Os fatores de emissão (perdas de N a partir do nitrogênio mineral adicionado) para N2O‑N (0,01–0,02%) e NH3‑N (0,3–0,6%) foram menores do que o valor estabelecido pelo Painel Intergovernamental de Mudanças Climáticas. A cobertura com braquiária aumenta a emissão de N2O‑N, independentemente da fertilização com nitrogênio

Disponibilidade de nitrogênio, espaço poroso preenchido por água e fluxos de N 2 O-N após aplicação de biochar e fertilização nitrogenada

The objective of this work was to investigate the impact of the application of wood biochar, combined with N fertilizations, on N2O-N fluxes, nitrogen availability, and water-filled pore space (WFPS) of a clayey Oxisol under rice (wet season) and common bean (dry season) succession. Manual static chambers were usedto quantify N2O-N fluxes from soil immediately after a single application of wood biochar (32 Mg ha-1) andafter four crop seasons with N applications (90 kg ha-1 N). Soil ammonium (N-NH4 +) and nitrate (N-NO3-) availability, as well as WFPS, was measured together with N2O-N fluxes. There was no interaction between biochar and N fertilization regarding N2O-N fluxes in any of the four seasons monitored, although these fluxes were clearly enhanced by N applications. At 1.5 and 2.5 years after biochar application, the WFPS decreased. In addition, in the seasons characterized by low WFPS, N2O-N fluxes and soil N-NO3- and N-NH4+ availability were enhanced after N applications. Long-term experiments in the field are important to quantify the impacts of biochar on N2O-N fluxes and to determine the dynamics of these fluxes on soil-related variables.O objetivo deste trabalho foi investigar o impacto da aplicação de biochar de madeira, combinada com fertilizações itrogenadas, nos fluxos de N2O-N, na disponibilidade de nitrogênio e no espaço poroso preenchido por água (EPPA), em um Latossolo argiloso sob sucessão com arroz (época chuvosa) e feijão (época seca). Câmaras estáticas manuais foram utilizadas para quantificar os fluxos de N2O-N no solo logo após uma única aplicação de biochar (32 Mg ha-1) e após quatro épocas de cultivo com aplicações de N (90 kg ha-1 de N). A disponibilidade de amônio (N-NH4+) e de nitrato (N-NO3-) no solo, bem como o EPPA, foi medida juntamente com os fluxos de N2O-N. Não houve interação entre biochar e fertilização nitrogenada quanto aos fluxos de N2O-N, em nenhuma das quatro épocas monitoradas, apesar de esses fluxos terem aumentado com as aplicações de N. Aos 1,5 e 2,5 anos após a aplicação do biochar, o EPPA diminuiu. Além disso, nas épocas caracterizadas por reduzido EPPA, os fluxos de N2O-N e a disponibilidade de N-NO3- e N-NH4 + no solo aumentaram após as aplicações de N.Experimentos em campo de longa duração são importantes para quantificar o impacto do uso de biochar sobre os fluxos de N2O-N e para determinar a dinâmica desses fluxos sobre as variáveis relacionadas ao solo

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

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

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

More than 10,000 pre-Columbian earthworks are still hidden throughout Amazonia

Indigenous societies are known to have occupied the Amazon basin for more than 12,000 years, but the scale of their influence on Amazonian forests remains uncertain. We report the discovery, using LIDAR (light detection and ranging) information from across the basin, of 24 previously undetected pre-Columbian earthworks beneath the forest canopy. Modeled distribution and abundance of large-scale archaeological sites across Amazonia suggest that between 10,272 and 23,648 sites remain to be discovered and that most will be found in the southwest. We also identified 53 domesticated tree species significantly associated with earthwork occurrence probability, likely suggesting past management practices. Closed-canopy forests across Amazonia are likely to contain thousands of undiscovered archaeological sites around which pre-Columbian societies actively modified forests, a discovery that opens opportunities for better understanding the magnitude of ancient human influence on Amazonia and its current state