Biology subjects

Garbarino, M.

Publications and source records attributed to Garbarino, M..

3 recordsLinked to original sources

bioRxiv2026

Treeline ecotone habitat loss and upward shift is driven by land abandonment rather than climate change in the Italian Alps

1. Plant populations at high elevation persist near their physiological limits, and treeline position is one of the clearest expressions of this constraint. In many mountain regions, however, this limit reflects historical land use as much as climate. Treeline shift is most often tracked as the displacement of a boundary line (1D) overlooking structural changes only visible when the ecotone is analysed as a surface (2D). 2. We reconstructed treeline ecotone dynamics at nine sites in the Italian Alps using aerial imagery from 1954 and 2017. At each site we detected the timberline and tree species line, quantified elevational displacement, and measured ecotonal surface change, relating them to climatic, land-use, and topographic predictors. 3. Both boundaries advanced upslope at all nine sites, with timberlines shifting faster (1.6 m/yr) than tree species lines (1.1 m/yr). This decoupled velocity caused the ecotonal surface to contract by ~17%. Land-use variables consistently explained more variance than climatic ones. 4. Land-use legacy and abandonment have a major role in shaping treeline dynamics. Boundary displacement reveals vegetation advance at both margins, while the surface view reveals concurrent narrowing of the habitat available for tree establishment. Both perspectives are needed to fully characterize how plant populations respond to shifting limiting factors at the treeline ecotone.

ecology↗

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↗

bioRxiv2020

European Primary Forest Database (EPFD) v2.0

Primary forests are scarce in Europe and continue to disappear at an alarming rate. Despite these losses, we know little about where such forests still occur. Here, we present an updated geodatabase and map of Europes known primary forests. Our geodatabase harmonizes 48 different datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). To assess the robustness of our geodatabase, we checked each patch for forest disturbance events using Landsat satellite-image time series (1985-2018). We estimate that 94% of the patches in our database did not experience significant disturbances that would alter their primary forest status in the last 30 year. Our database is the most comprehensive dataset on primary forests in Europe, and will be useful for biogeographic and ecological studies, and conservation planning to safeguard these unique forests.

ecology↗