Biology subjects

de Oliveira, C. P.

Publications and source records attributed to de Oliveira, C. P..

4 recordsLinked to original sources

bioRxiv2025

Thresholds of drought and terrain complexity shape biomasspatterns in South America's Caatinga

Seasonally Tropical Dry Forests (STDFs) are widespread throughout the world and store significant amounts of carbon; however, they are often overlooked in spatial assessments compared to humid tropical forests. The Caatinga, which is the largest seasonally dry tropical forest in South America, covers approximately 862,000 km{superscript 2} in northeastern Brazil and supports millions of people. Unfortunately, its carbon dynamics has not been thoroughly quantified, especially after centuries of land-use transformation and wood extraction that have significantly diminished its biomass stocks. In this study, we model the potential aboveground biomass (AGB) that Caatinga could sustain under current climatic, atmospheric, and topographic conditions. We integrated data from 301 geo-referenced plots along with high-resolution environmental predictors. The principal Component Analysis revealed two main gradients: a hydro-thermal axis dominated by precipitation, temperature, and severity of drought, and a topographic axis reflecting slope, ruggedness, and terrain position. Random Forest models, validated through both random and spatial cross-validation, explained a significant amount of variation in AGB (R{superscript 2} = 0.81, RMSE = 21 Mg ha). Our findings indicated that AGB is highly sensitive to water availability. In particular, biomass increased sharply when the maximum cumulative water deficit (MCWD) was less than -500 mm and annual rainfall exceeded approximately 1,100 mm. In contrast, elevated vapour pressure deficit (VPD) and potential evapotranspiration (PET) were associated with reduced carbon storage. Topographic heterogeneity further influenced AGB, with rugged and concave terrains supporting potential biomass levels more than twice as high as those found in flat, convex areas. Our predictive map reveals a mosaic of low-biomass cores and localized high-biomass refugia, highlighting the dual influence of hydroclimatic and topographic factors. These findings reposition Caatinga as a heterogeneous and dynamic potential carbon reservoir - historically degraded by changes in land-use but still capable of storing substantial carbon. This research offers critical insights for the restoration, conservation and mitigation efforts for climate change in tropical drylands worldwide.

ecology↗

bioRxiv2025

Mapping giant-tree density in the Amazon

Tall trees are pivotal in maintaining tropical forests biodiversity and regulating biogeochemical cycles, mainly through their influence on carbon storage, nutrient cycling, and habitat structuring. Despite their ecological importance, the drivers behind their spatial distribution and the environmental factors driving the density of these emergent trees remain unexplained. Here we analyzed tall-tree density data derived from airborne LiDAR across 900 randomly distributed transects throughout the Brazilian Amazon. We paired each transect location with climatic, topographic, atmospheric, and soil metrics to investigate regional-level environmental drivers of large tree density using spatial modeling. Water availability and stable climatic conditions (low incidence of storms and of lightning) were the main drivers of tall-tree density at the regional level. The occurrence of tall trees is aggregated along the Amazon, with 14% occurring within 1.3% of the Amazon and 50% concentrated in 11.2% of the area. These patterns suggest that tall trees dominate localized regions of the biome and that high densities of tall trees are primarily dependent on mechanical rather than physiological drivers. Understanding the dynamics of 55.5 million emergent trees is imperative for advancing research in biogeochemistry, ecology, and climate resilience. Our results are especially relevant in the context of conserving nature and carbon stocks under increasing anthropogenic and environmental pressures.

ecology↗

bioRxiv2025

Warmer climate threatens the occurrence of giant trees in the Amazon basin

Giant trees in the Amazon play crucial ecological roles by acting as substantial carbon sinks and supporting diverse forest ecosystems. However, these emergent trees are increasingly vulnerable to climatic changes, and recent research suggests that the distribution and niche of many emergent species are severely threatened. This study employs ecological niche modeling using data LiDAR and forest inventory, global repository data, and bioclimatic variables to project the potential larger tree distributions under past, current, and future climate scenarios (SSP1-2.6 and SSP5-8.5) in different biogeographic provinces in the Amazon basin. We used algorithms MARS, RandomForest, MaxEnt, and GAM to assess the impact of critical climatic factors, including isothermality, maximum temperatures, and precipitation patterns, on the habitat suitability of these larger trees and species Dinizia excelsa and Goupia glabra. Our results show that the tall trees dataset, Dinizia excelsa and Goupia glabra exhibit congruent distinct responses to climate variables, with Dinizia excelsa being more sensitive to increased temperature extremes, particularly in the Guiana Shield and Roraima Provinces. In contrast, Goupia glabra displays a broader tolerance to precipitation variability. Under the high-emission scenario (SSP5-8.5), both species are projected to lose up to 45% of their suitable habitats by 2080, primarily in southern Amazon provinces like Xingu-Tapajos, where increased drought frequency and temperature extremes are expected. Conversely, the low-emission scenario (SSP1-2.6) suggests potential habitat stability or even slight expansions in the northern Amazon regions due to moderate temperature and rainfall conditions. These findings highlight the urgent need for conservation strategies to protect critical refugia and enhance ecosystem resilience. By integrating niche modeling with climate projections, our study provides vital insights into managing Amazonian giant trees, emphasizing their potential role in mitigating global climate change impacts.

ecology↗

bioRxiv2021

Height-diameter allometry for tropical forest in northern Amazonia

Height measurements are essential to manage and monitor forest biomass and carbon stocks. However, accurate estimation of this variable in tropical ecosystems is still difficult due to species heterogeneity and environmental variability. In this article, we compare and discuss six nonlinear allometric models parameterized at different scales (local, regional and pantropical). We also evaluate the height measurements obtained in the field by the hypsometer when compared with the true tree height. We used a dataset composed of 180 harvested trees in two distinct areas located in the Amapa State. The functional form of the Weibull model was the best local model, showing similar performance to the pantropical model. The inaccuracy detected in the hypsometer estimates reinforces the importance of incorporating new technologies in measuring individual tree heights. Establishing accurate allometric models requires knowledge of ecophysiological and environmental processes that govern vegetation dynamics and tree height growth. It is essential to investigate the influence of different species and ecological gradients on the diameter/height ratio.

ecology↗