Biology subjects

Buras, A.

Publications and source records attributed to Buras, A..

3 recordsLinked to original sources

bioRxiv2025

Soil and atmospheric drought trigger early leaf senescence and increase subsequent canopy mortality risk in temperate forests

Early leaf senescence - an advanced decline in leaf functionality before the typical autumn period - has emerged as recurring drought response in temperate forests. Yet its large-scale patterns, drivers, and impacts on tree vitality remain poorly understood. Using six years (2018-2023) of Sentinel-2 time series across Germany, we estimated the onset of leaf senescence in European beech (Fagus sylvatica) and oak (Quercus robur, Q. petraea) forests. Early leaf senescence was most widespread during exceptional drought years (2018, 2019, and 2022) and showed pronounced spatial variability. Sustained high atmospheric demand (VPD) and critically low soil water potential ({psi}soil) in summer were key drivers identified by logistic regression analysis (F1-score = 0.57), with beech responding more strongly to soil drought and oak to atmospheric drought. Thresholds triggering early leaf senescence (probability >50%) were six weeks of daily maximum VPD [≥]1.9 kPa in beech and [≥]2.1 kPa in oak, or two weeks of root zone {psi}soil [≤]-0.8 MPa and [≤]-0.9 MPa, respectively. Elevated spring VPD further amplified early senescence risk in both species, indicating seasonal legacy effects that may reduce hydraulic function or leaf longevity. Forests with very early and repeated early leaf senescence exhibited elevated canopy mortality in subsequent years, highlighting them as potential warning signals of drought-induced forest decline. K-means clustering of forest stands based on senescence patterns, mortality, and drought sensitivity classified three drought response types - resistant, sensitive, and vulnerable - shaped mainly by local soil water availability and stand structure. Our findings demonstrate that early leaf senescence reflects cumulative drought stress and indicates increased mortality risk, rather than a stress-avoidance strategy. We propose it as a mechanistic indicator that can be incorporated into ecosystem models to improve predictions of forest vulnerability and carbon dynamics under climate extremes, and guide forest management to anticipate climate-induced forest decline.

physiology↗

bioRxiv2024

deadtrees.earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, not standardized and not spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map tree mortality over time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Drones provide a cost-effective source of training data by capturing high-resolution orthophotos of tree mortality events at sub-centimeter resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than a thousand centimeter-resolution orthophotos, covering already more than 300,000 ha, of which more than 58,000 ha are fully annotated. This community-sourced and rigorously curated dataset shall serve as a foundation for a global initiative to gather comprehensive reference data. In concert with Earth observation data and machine learning it will serve to uncover tree mortality patterns from local to global scales. This will provide the foundation to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. Thus, the open and interactive nature of deadtrees.earth together with the collective effort of the community is meant to continuously increase our capacity to uncover and understand tree mortality patterns.

ecology↗

bioRxiv2019

Pitfalls in estimating the global carbon removal via forest expansion - a comment on Bastin et al. (2019)

We believe the carbon removal potential of 205 Gt C reported by Bastin et al. (2019) to be overestimated. The authors did not consider the carbon already stored on the land with identified tree restoration potential. For instance, grasslands and degraded forests have similar soil carbon stocks as old-growth forests. Accounting for these inconsistencies in the calculation, we estimate a carbon removal potential of 81 Gt C, i.e. only 39% of the Bastin et al. estimate. In addition, some of the assumptions about potential restoration area seem questionable and an essential question remains unanswered: why do areas identified as suitable for tree growth currently lack tree cover?

ecology↗