Biology subjects

Dalling, J. W.

Publications and source records attributed to Dalling, J. W..

3 recordsLinked to original sources

bioRxiv2025

The Global Canopy Atlas: analysis-ready maps of 3D structure for the world's woody ecosystems

Woody canopies regulate exchanges of energy, water and carbon, and their three-dimensional (3D) structure supports much of terrestrial biodiversity. Remote sensing technologies such as airborne laser scanning (ALS) now enable the 3D mapping of entire landscapes. However, we lack the large, harmonized and geographically representative ALS collections needed to build a global picture of woody ecosystem structure. To address this challenge, we developed the Global Canopy Atlas (GCA): 3,458 ALS acquisitions transformed into standardized and analysis-ready maps of canopy height and elevation at 1 m2 resolution. The GCA covers 56,554 km2 across all major biomes. 19% of this area has been scanned multiple times, and 87% of all GCA products are openly available, covering 95% of the total area. To showcase its wide range of applications, we applied the GCA in three case studies. First, we validated three global satellite-derived canopy height maps, finding poor performance at native resolution (1-30 m, R2 < 0.38) and moderate performance at 250 m resolution (R2 < 0.65). Second, analyzing global patterns in canopy gap size frequency we discovered an unexpectedly large variation of power law exponents from branch to stand level ( = 1.52 to 2.38), pointing to a fundamental scale-dependence of forest structure. Third, we developed a framework to standardize forest turnover quantification from multi-source, multi-temporal ALS. In a temperate forest in North America it revealed that 21% of canopy gaps closed within 12 years of opening and would thus be missed by infrequent monitoring. As demonstrated by these case studies, the GCA provides a novel data source for ecologists, foresters, remote sensing scientists and the ecosystem modelling community that substantially advances our ability to understand the structure and dynamics of woody ecosystems at global scales.

ecology↗

bioRxiv2024

Functional traits of ectomycorrhizal trees influence their effects on surrounding soil organic matter properties

Ectomycorrhizal (EM) effects on forest ecosystem carbon (C) and nitrogen (N) cycling are highly variable, which may be due to underappreciated functional differences among EM-associating trees. We hypothesize that differences in functional traits among EM tree genera will correspond to differences in soil organic matter (SOM) dynamics. We explored how differences among three genera of angiosperm EM trees (Quercus, Carya, and Tilia) in functional traits associated with leaf litter quality, resource use and allocation patterns, and microbiome assembly related to overall soil biogeochemical properties. In support of our hypothesis, we found consistent differences among EM tree genera in function traits. Quercus trees had lower litter quality, lower {delta}13C in SOM, higher {delta}15N in leaf tissues, greater oxidative extracellular enzyme activities, and higher EM fungal diversity than Tilia trees, while Carya trees were often intermediary. These functional traits corresponded to overall SOM C and N dynamics and soil fungal and bacterial community composition. Our findings suggest that trait variation among EM-associating tree species should be an important consideration in assessing plant-soil relationships such that EM trees cannot be categorized as a unified functional guild.

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↗