Tree composition of a seasonal semideciduous forest in Pirenópolis, Goiás state

A Floresta Estacional Semidecidual é um ecossistema bastante ameaçado no Brasil, cuja condução de levantamentos florísticos em florestas remanescentes é fundamental para fornecer dados que contribuam para a proposição de estratégias de manejo e a recuperação desses ecossistemas. Neste sentido,o objetivo do trabalho foi realizar o levantamento florístico de um trecho de Floresta Estacional Semidecidual de aproximadamente 10 ha., localizado na Fazenda Raio de Sol (15º 45’ 54’’ S e 49º 04’03’’ W) próxima à cidade de Pirenópolis, Goiás, inserida na biorregião do Ecomuseu do Cerrado.Para o levantamento do componente arbóreo foram alocadas dez parcelas de 20 x 20 m. Todos osindivíduos com DAP igual ou superior a 5 cm foram incluídos na amostragem, excluindo-se as lianase os indivíduos mortos. Amostraram-se 742 indivíduos pertencentes a 83 espécies distribuídas em 67 gêneros e 36 famílias. As famílias de maior riqueza foram Fabaceae, Myrtaceae, Rubiaceae, Chrysobalanaceae e Apocynaceae, que contribuíram com 48% do total das espécies encontradas. ___________________________________________________________________________________ ABSTRACTThe Seasonal Semideciduous Forest is one of the most threatened Brazilian ecosystems. Therefore, toconduct forest mensuration studies in these areas is of vital importance to provide data for development of management strategies and they are also important for recovery of degraded areas. In viewof this, the objective was to study the flora of a fragment of 10 ha of semideciduous forest at Raio deSol farm (15º 45’ 54’’ S and 49º 04’ 03’’ W) in Pirenópolis municipality, in the State of Goiás. It isinserted into the bioregion called Cerrado EcoMuseum. Ten sample plots (20 X 20 m) were sur-veyed. In these plots all living trees with 5 cm diameter at 1.30 m above ground (DBH) were mea-sured. 742 individuals belonging to 83 species, 67 genera, and 36 families were registered. The ri-chest families in number of species were Fabaceae, Myrtaceae, Rubiaceae, Chrysobalanaceae andApocynaceae, which contributed 48% of total species found

Thermo-acoustic catalytic effect on oxidizing woody torrefaction

The torrefaction (mild pyrolysis) process modifies biomass chemical and physical properties and is applied as a thermochemical route to upgrade solid fuel. In this work, the catalytic effect of thermo-acoustic on oxidizing woody torrefaction is assessed. The combined effect of two acoustic frequencies (1411, 2696 Hz) and three temperatures (230, 250, and 290 °C) was evaluated through weight loss and its deviation curves, calculated torrefaction severity index (TSI), as well as proximate, calorific, and compression strength analysis of Eucalyptus grandis. A new index to account for the catalytic effects on torrefaction (TCEI) was introduced, providing the quantitative analysis of acoustic frequencies influence. A two-step consecutive reaction numerical model allowed the thermo-acoustic experiment evaluation. For instance, the thermogravimetric profiles revealed that the acoustic field has a catalytic effect on wood torrefaction and enhances the biomass oxidation process for severe treatments. The kinetic simulation of the acoustic coupling resulted in faster conversion rates for the solid pseudo-components showing the boosting effect of acoustic frequencies in anticipating hemicellulose decomposition and enhancing second step oxidizing reaction

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

Influence of potassium carbonate addition on the condensable species released during wood torrefaction

In order to investigate the effect of potassium addition on the composition of torrefaction condensates, two demineralized wood species were impregnated with different concentrations of K2CO3 and then torrefied at 275 degrees C up to an anhydrous weight loss (AWL) of 25%. Torrefaction was carried out in both a thermogravimetric analysis (TGA) instrument and a laboratory fixed-bed reactor. Condensates from the fixed bed reactor were collected and analyzed by Gas Chromatography-Mass Spectroscopy (GC-MS). TGA of raw and K2CO3-impregnated biopolymers (cellulose, xylan and lignin) were performed to facilitate interpretation of the results. TGA showed that when potassium content increased in the biomass, shorter torrefaction times were sufficient to obtain the targeted AWL. GC-MS showed, for both wood species, that potassium promotes the formation of acetol and slightly enhances acetic acid yield. The amount of some lignin derivatives (guaiacol, syringol, 4-vinylguaiacol) also rose with potassium addition. Yields of levoglucosan, LAC (1-hydroxy-(1R)-3,6-dioxabicyclo [3.2.1]octan-2-one) and DGP (1,4:3,6-dianhydro-alpha-D-glucopyranose), as well as furfural and 5-hydroxymethylfurfural, decreased drastically in the presence of potassium. In conclusion, small additions of potassium carbonate deeply affected thermal degradation of wood species and the speciation of torrefaction condensates

A potassium responsive numerical path to model catalytic torrefaction kinetics

To assess the potassium catalytic influence on the kinetic behavior of non-oxidative biomass torrefaction, two woody biomass samples (Amapaí and Eucalyptus), as well as Miscanthus samples impregnated with three different K2CO3 concentrations (0.003 M, 0.006 M, and 0.009 M) were comprehensively studied. The solid thermal degradation kinetics were analyzed through thermogravimetric analysis in usual torrefaction conditions (275 °C during 68min and 10 °C.min−1 heating rate) and an original Potassium Responsive Numerical Path (PRNP). Therefore, a two-step reaction model with unified activation energies was integrated within a numerical method that considers the torrefaction severity influence for each potassium-loading content in all three biomasses. The proposed PRNP enables an accurate solid yield prediction (R2 > 0.9995). A strong (R2 between 0.91 and 0.99) and a significant (0.0463) linear correlation was highlighted between the potassium content in biomass, the increasing reaction rates, and pre-exponential factors. The solid and volatile product distribution depicted faster and marked degradation for solid pseudo-components and anticipated a higher volatile release. The catalytic torrefaction severity factor determination enabled correlating treatment severity and kinetic rates showing better correlations than K% for wood biomass. The accurate results are conducive to developing numerical models that are essential for assessing solid fuel upgrading under catalytic effect in torrefaction plants