Biology subjects

Ometto, J. P.

Publications and source records attributed to Ometto, J. P..

5 recordsLinked to original sources

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↗

bioRxiv2022

Tracking canopy gap dynamics across four sites in the Brazilian Amazon

Background information to give context to the studyCanopy gaps are the most evident manifestation of how disturbances disrupt forest landscapes. The size distribution and return frequency of gaps, and subsequent recovery processes, determine whether the old-growth state can be reached. The aim or research questionWe used remote sensing metrics to compare the disturbance regime of four Amazon regions based on the size distribution of gaps, their dynamics and geometric characteristics. A brief summary of the methodology usedWe assessed gap dynamics at four sites in the central, central eastern, southeastern, and northeastern regions of the Brazilian Amazon using repeated airborne laser scanning surveys. We developed a novel analysis to quantify four possible stages of gap dynamics: formation, expansion, persisting and recovering. For that, we overlapped layers of gap locations from two consecutive airborne laser scanning surveys. Key results with some significance measuresThe gap fraction in our study sites varied between 1.26% to 7.84%. All the sites have similar proportion of gaps among size classes. What notably changed between sites was not the gap size-distribution, but the relative importance of stages of gap dynamics. Growing and persisting rates were greatest in the site with the stronger seasonal variation in climate, lower annual precipitation, higher mean wind speed and higher solar radiation. The conclusions, which address the main aimsThe concept of stability reflects the tendency of a system to quickly return to a position of equilibrium when disturbed. We showed that gap dynamics varied among sites, with one example of low recovery rate contrasted to three other sites with faster recovery. Our results support that such as assessing the size distribution of gaps, investigating their return frequency and severity is crucial for understanding forest dynamics at the landscape and regional scales.

ecology↗

bioRxiv2021

Forest structure and degradation drive canopy gap sizes across the Brazilian Amazon

Canopy gaps are openings in the forest canopy resulting from branch fall and tree mortality events. Light reaches the lower layers of the canopy through these gaps, enabling understory trees to grow and maintaining the high heterogeneity and biodiversity of tropical forests. The size-frequency distribution of canopy gaps follows a power-law distribution, and the slope of this power-law () is a key indicator of forest structure and dynamics. We detected canopy gaps using a unique LiDAR data set consisting of 650 transects randomly distributed across the Brazilian Amazon Forest providing an unprecedented perspective on forest structural variation over 2500 km2 of forest. We then investigated how varied with forest structure, elevation, soil fertility, water deficit, wind gust speed and lightning intensity. We found that human modified forests had more large gaps than intact forests. Within the intact forests we observed a large-scale Northwest to Southeast pattern in (more large gaps in the Southeast), which aligns with recent work on tree mortality rates. The two most important variables in predicting were median canopy height and maximum modeled height, which had opposite effects on the number of large gaps. Forests with higher median canopy height contain fewer large gaps but the presence of very tall trees was associated with more large gaps. Environmental variables were of secondary importance in our model, with larger gaps occurring in drier forests with high soil fertility, wind speed, and lightning intensity. The distribution of large gaps in the forest canopy varies substantially over the Brazilian Amazon as a result of canopy structure and mortality rates. We mapped this variation and found more large gaps in human modified forests, forests on fertile soils and those exposed to higher wind, lightning and drought stress. Increasing extreme weather events due to climate change may therefore increase the number of large gaps in currently intact forests, causing them to resemble human modified forests.

ecology↗

bioRxiv2020

Resource availability and availability and disturbance shape maximum tree height across the Amazon

The factors shaping the distribution of giant tropical trees are poorly understood, despite its importance as a link between evolutionary biology and ecosystem biogeochemistry. The recent discovery of clusters of trees over 80 metres tall in the Guiana Shield region of the Amazon rainforest challenges the current understanding of the factors controlling the growth and survival of giant trees. The new discovery led us to revisit the question: what determines the distribution of the tallest trees of the Amazon? Here, we used high-resolution airborne LiDAR (Light Detection and Ranging) surveys to measure canopy height across 282,750 ha of primary old-growth and secondary forests throughout the entire Brazilian Amazon to investigate the relationship between the occurrence of giant trees and the environmental factors that influence their growth and survival. Our results suggest that the factors controlling where trees grow extremely tall are distinct from those controlling their longevity. Trees grow taller in areas with high soil clay content (> 42%), lower radiation (< 130 clear days per year) and wind speeds, avoiding alluvial areas (elevations higher than 40 m a.s.l), and with an optimal precipitation range of 1,500 to 2,500 mm yr-1. We then used an envelope model to determine the environmental conditions that support the very tallest trees (i.e. over 70 m height). We found that, as opposed to the myriad of interacting factors that control the maximum height at a large scale, wind speed had by far the largest influence on the distribution of these sentinel trees, and explained 67% of the probability of finding trees over 70 m in the Brazilian Amazon forest. The high-resolution pan-Amazon LiDAR data showed that environmental variables that drive growth in height are fundamentally different from environmental variables that support their survival. While precipitation and temperature seem to have lower importance for their survival than expected from previous studies, changes in wind and radiation regimes could reshape our forested biomes. This should be carefully considered by policy-makers when identifying important hotspots for the conservation of biodiversity in the Amazon.

ecology↗