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

Global carbon balance of the forest: satellite-based L-VOD results over the last decade DOI Creative Commons
Jean‐Pierre Wigneron, Philippe Ciais, Xiaojun Li

et al.

Frontiers in Remote Sensing, Journal Year: 2024, Volume and Issue: 5

Published: May 10, 2024

Monitoring forest carbon (C) stocks is essential to better assess their role in the global balance, and model predict long-term trends inter-annual variability atmospheric CO2 concentrations. On a national scale, inventories (NFIs) can provide estimates of stocks, but these are only available certain countries, limited by time lags due periodic revisits, cannot spatially continuous mapping forests. In this context, remote sensing offers many advantages for monitoring above-ground biomass (AGB) on scale with good spatial (50–100 m) temporal (annual) resolutions. Remote has been used several decades monitor vegetation. However, traditional methods AGB using optical or microwave sensors affected saturation effects moderately densely vegetated canopies, limiting performance. Low-frequency passive less effects: occurs at levels around 400 t/ha L-band (frequency 1.4 GHz). Despite its coarse resolution order 25 km × km, method based L-VOD (vegetation depth L-band) index recently established itself as an approach annual variations continental scale. Thus, applied continents biomes: tropics (especially Amazon Congo basins), boreal regions (Siberia, Canada), Europe, China, Australia, etc. no reference study yet published analyze detail terms capabilities, validation results. This paper fills gap presenting physical principles calculation, analyzing performance reviewing main applications tracking balance vegetation over last decade (2010–2019).

Language: Английский

Citations

13
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
Global covariation of forest age transitions with the net carbon balance DOI Creative Commons
Simon Besnard, Viola Heinrich, Nuno Carvalhais

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 12, 2024

Abstract Understanding the impact of forest age transitions on global net carbon balance is critical for advancing management and climate change mitigation strategies. We analysed changes in (2010-2020) using Global Age Mapping Integration (GAMI) v2.0 dataset alongside satellite-derived aboveground (AGC) atmospheric inversion-derived CO2 flux data. observe decreasing Amazon, Congo Basin, Southeast Asia, primarily old-growth forests due to stand-replacing disturbances like clear-cutting followed by regrowth. Large patches older Siberian forests, ranging from 80 200 years, transitioned younger ages increased fire5 harvest6. Despite stand-replacements, China, Europe, North America experienced a ageing nearly ten years average. A substantial portion gradually located South Tropical (0.19 total fraction, 0.64 billion hectares), Eurasia boreal (a fraction 0.17, 0.56 Europe 0.10, 0.35 temperate 0.094, 0.31 hectares). find significant correlation between stand-replaced inversely derived 2010-2020 trend sink strength at scales (R2 = 0.33, slope +109.19 gC m-2 year-2, p-val < 0.001, N=60). This partly transition carbon-rich (approximately 98.0 MgC ha⁻¹) young 43.5 ha⁻¹), resulting AGC loss +0.15 (+ denotes AGC) PgC year⁻¹. When accounting all this increases +0.43 year⁻¹, representing approximately 1.6% biomass (around 270 2020) over years. Our findings highlight that shifts are crucial understanding losses gains. these dynamics essential developing strategies optimise harvesting methods sequester more anthropogenic CO2.

Language: Английский

Citations

1
Tracking tree demography and forest dynamics at scale using remote sensing DOI Creative Commons
Robin Battison, Suzanne M. Prober, Katherine Zdunic

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 12, 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 over 25 km 2 semi-arid, old-growth temperate woodland in Western Australia track height growth, crown expansion mortality 42,810 individual nine years. 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
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