Tracking tree demography and forest dynamics at scale using remote sensing DOI Creative Commons
Robin Battison, Suzanne M. Prober, Katherine Zdunic

et al.

New Phytologist, Journal Year: 2024, Volume and Issue: 244(6), P. 2251 - 2266

Published: Oct. 18, 2024

Summary Capturing how tree growth and survival vary through space time is critical to understanding the structure dynamics of tree‐dominated ecosystems. However, characterising demographic processes at scale inherently challenging, as trees are slow‐growing, long‐lived cover vast expanses land. We used repeat airborne laser scanning data acquired across 25 km 2 semi‐arid, old‐growth temperate woodland in Western Australia track height growth, crown expansion mortality 42 213 individual over 9 yr. found that rates constrained by a combination size, competition topography. After initially investing progressively shifted they grew larger, while risk decreased considerably with size. Across landscape, both increased topographic wetness, resulting vegetation patterns strongly spatially structured. Moreover, biomass gains from woody generally outpaced losses mortality, suggesting these woodlands remain net carbon sink absence wildfires. Our study sheds new light on shape spatial semi‐arid ecosystems provides roadmap for using emerging remote sensing technologies demography scale.

Language: Английский

Evaluating terrestrial laser scanning for structural characterization of mangrove forests in Southeastern Brazil DOI

Tatiane C. Matta,

Lucas Silva Pereira,

Yasmin C.B. Belmonte

et al.

Forest Ecology and Management, Journal Year: 2025, Volume and Issue: 583, P. 122567 - 122567

Published: Feb. 22, 2025

Language: Английский

Citations

0
State of the art and for remote sensing monitoring of carbon dynamics in African tropical forests DOI Creative Commons
Thomas Bossy, Philippe Ciais,

Solène Renaudineau

et al.

Frontiers in Remote Sensing, Journal Year: 2025, Volume and Issue: 6

Published: March 17, 2025

African tropical forests play a crucial role in global carbon dynamics, biodiversity conservation, and climate regulation, yet monitoring their structure, diversity, stocks changes remains challenging. Remote sensing techniques, including multi-spectral data, lidar-based canopy height vertical structure detection, radar interferometry, have significantly improved our ability to map forest composition, estimate biomass, detect degradation deforestation features at finer scale. Machine learning approaches further enhance these capabilities by integrating multiple data sources produce maps of attributes track over time. Despite advancements, uncertainties remain due limited ground-truth validation, the structural complexity large spatial heterogeneity forests. Future developments remote should examine how multi-sensor integration high-resolution from instruments such as Planet, Tandem-X, SPOT AI methods can refine storage function maps, large-scale tree biomass improve detection down level. These advancements will be essential for supporting science-based decision-making conservation mitigation.

Language: Английский

Citations

0
Photosynthetic traits scale linearly with relative height within the canopy in an African tropical forest DOI
Thomas Sibret, Marc Peaucelle, Kristine Y. Crous

et al.

New Phytologist, Journal Year: 2025, Volume and Issue: unknown

Published: April 7, 2025

Summary Understanding leaf photosynthetic traits and their variation in tropical forests is crucial for improving model predictions of forest productivity, accurately representing the high functional diversity these remains a challenge. Moreover, photosynthesis data are lacking Congo basin. We observed photosynthetic, chemical structural 24 woody species Congolese studied variance across guilds, within‐tree crown positions overall canopy defined by relative height within canopy. Guild position jointly influenced traits, with significant effect (marginal R 2 > 0.43). The traditional guild classification explained portion interspecies variation, revealing clear gradient from shade‐tolerant to light‐demanding species. Crown significantly affected intraindividual trait variability, bottom leaves exhibiting values at least 19.3% lower than top leaves. Importantly, linear relationship between emerged as robust continuous metric, effectively integrating both inter‐ intraspecific variability. conclude that while guild‐based classifications provide useful framework identifying plant groups, offers quantitative approach capturing valuable modeling processes.

Language: Английский

Citations

0
Tracking tree demography and forest dynamics at scale using remote sensing DOI Creative Commons
Robin Battison, Suzanne M. Prober, Katherine Zdunic

et al.

New Phytologist, Journal Year: 2024, Volume and Issue: 244(6), P. 2251 - 2266

Published: Oct. 18, 2024

Summary Capturing how tree growth and survival vary through space time is critical to understanding the structure dynamics of tree‐dominated ecosystems. However, characterising demographic processes at scale inherently challenging, as trees are slow‐growing, long‐lived cover vast expanses land. We used repeat airborne laser scanning data acquired across 25 km 2 semi‐arid, old‐growth temperate woodland in Western Australia track height growth, crown expansion mortality 42 213 individual over 9 yr. found that rates constrained by a combination size, competition topography. After initially investing progressively shifted they grew larger, while risk decreased considerably with size. Across landscape, both increased topographic wetness, resulting vegetation patterns strongly spatially structured. Moreover, biomass gains from woody generally outpaced losses mortality, suggesting these woodlands remain net carbon sink absence wildfires. Our study sheds new light on shape spatial semi‐arid ecosystems provides roadmap for using emerging remote sensing technologies demography scale.

Language: Английский

Citations

0