Integrando dados de fluxos de metano no solo e da diversidade da comunidade microbiana em resposta à mudança no uso do solo em florestas tropicais e temperadas.
Bibliographic record
Abstract
Methane (CH4) constitutes the second most important greenhouse gas after CO2, and accounts for up to 2030% of global warming. Significant accumulation of CH4 in the atmosphere (~44%) is associated with land-use change. In soil, CH4 production and oxidation rates are intrinsically linked, and driven by methanogens (archaea) and methanotrophs (bacteria) which are, at the same time, shaped by edaphic and environmental conditions. This arises as a relevant issue due to the increasing intensification of agriculture, particularly in the context of climate change. This thesis focused on the characterization of methanogenic and methanotrophic communities and their response to land-use change in tropical and temperate forests. The thesis consists of three chapters presented in scientific manuscript format. The study in Chapter 1 was addressing the impact of forest-to-pasture conversion on CH4-cycling communities in Rondonia, Brazil, through metagenomic sequencing and high-resolution taxonomic and functional analysis, exploring biotic and abiotic factors influencing these microbial groups. Chapter 2 delves deeper into the study of forest-to-pasture conversion in another region of the Amazon Basin (Pará, Brazil) to identify the abiotic drivers of methanogenic and methanotrophic communities in forest and pasture soils. In this chapter, CH4 fluxes and edaphic parameters were measured in two seasons (wet and dry), two soil types (sandy and clayey) and four soil depths. The analyses included ~280 samples of 16S rRNA sequencing, the isotopic composition of CH4 samples, and soil physical and chemical properties. The study in Chapter 3, performed in Ontario, Canada, aims to compare the structure and activity of methanogens and methanotrophs in five riparian buffer systems with contrasting plant coverage in an agricultural landscape. Soils samples were collected during CH4 emissions hotspots, and DNA and cDNA samples were sequenced using nPCR-amplicons from pmoA gene (methanotrophs) and archaeal 16S rRNA (methanogens). Overall, our results provide strong evidence of the transformation of CH4-cycling communities due to land-use change, and identifies key abiotic drivers behind these microbial changes
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".