Biology subjects

Fischer, F. J.

Publications and source records attributed to Fischer, F. J..

11 recordsLinked to original sources

bioRxiv2026

Laser scanning identifies large trees as a major source of uncertainty in mangrove carbon accounting

BackgroundMangrove forests are crucial ecosystems which support biodiversity, protect coastlines and store vast amounts of carbon. Mangrove conservation and protection rely on accurate carbon accounting to unlock investment. However, the allometric equations underpinning these carbon estimates remain poorly constrained, particularly for the large trees. MethodsWe used terrestrial laser scanning (TLS) to estimate the biomass of 187 mangrove stems across Suriname, Panama, Colombia and Jamaica, including 84 stems >20 cm DBH. TLS-derived biomass estimates were used to evaluate local, regional and pantropical allometric equations. ResultsMost diameter-based allometric equations underestimated biomass by 8-65%. Equations additionally incorporating tree height performed better, but still underestimated biomass by 12-16% on average. Applying alternative allometries to a representative mangrove inventory from Panama produced biomass estimates ranging from 80 to 200 Mg ha-{superscript 1}, demonstrating that allometric uncertainty alone can generate more than a two-fold difference in estimated carbon stocks. ConclusionsCurrent allometric equations systematically underestimate the biomass of large mangrove trees and are therefore likely to underestimate mangrove carbon stocks. TLS provides a practical, non-destructive approach for expanding biomass datasets and improving allometric equations. Reducing allometric uncertainty should be a priority for strengthening blue carbon accounting and mangrove conservation.

ecology↗

bioRxiv2026

Liana cutting accelerates tropical forest recovery at a fraction of the cost of tree planting

We urgently need to restore degraded tropical forests to mitigate the climate and biodiversity crises, but how to do so rapidly and cost-effectively remains an open question. Here we provide a long-term, landscape-scale assessment of the effectiveness of enrichment tree planting and liana cutting, the two most common restoration interventions used across many tropical regions. Leveraging one of the worlds largest and longest running forest restoration experiments, we used repeat airborne laser scanning to track the 3D structural recovery of 500 ha of selectively logged rainforest in Borneo. Over an 18-year period, enrichment planting increased mean canopy height by 1.6 m relative to unplanted controls. Remarkably, liana cutting increased canopy height more than four times faster (3.7 m over just 9 years). This recovery was jointly driven by accelerated canopy gap closure, enhanced tree growth, and a 50% reduction in tree mortality. Given that liana cutting is around 10 times cheaper to implement than enrichment planting, our results suggest it provides a cost-effective, scalable solution to accelerate the structural recovery of logged tropical forests.

ecology↗

bioRxiv2026

Limited predictability of tree-level responses to drought across European forests

Climate change is increasing the frequency, duration and severity of extreme events such as heatwaves and droughts, pushing trees near or beyond their ecophysiological limits. Understanding what governs variability in how trees respond to drought - such as intrinsic factors related to their size, age, and species, or extrinsic factors shaped by their local competitive environment - is critical for predicting long-term forest resilience to climate change and developing climate-smart forest management strategies. Here, we use tree ring data from 2909 trees belonging to sixteen species distributed across Europes major forest types to comprehensively assess what factors contribute most to a trees ability to withstand and recover from extreme drought events. We found that trees with larger living crowns generally exhibited higher post-drought growth recovery and resilience, while trees exposed to lower drought intensities showed greater resistance. Conversely, neither the density nor the diversity of a trees local competitive neighbourhood had any clear influence on its response to drought. More generally, we found that our ability to predict whether a tree would exhibit resilience to drought was low (R2 = 13-21) and was largely driven by species-specific responses and topographic variation across forest types, rather than by tree- and stand-level attributes. These findings highlight that drought responses are inherently complex and strongly influenced by forest type and by heterogeneous responses among species. Integrating tree-ring, physiological, and remote-sensing data with mechanistic models represents a promising avenue for improving forecasts of future forest resilience to climate change.

ecology↗

bioRxiv2026

No detrimental long-term impacts of coring on tree growth ormortality across European forests

O_LITree cores are widely used across a broad range of disciplines in the environmental sciences, most notably as a tool to measure tree growth, estimate tree age, characterise wood anatomy and reconstruct past climate. However, because extracting tree cores is an invasive procedure, concerns about their use are often raised due to perceived risks to trees. C_LIO_LIHere we comprehensively test the long-term impacts of tree coring on 16 European tree species using a dataset spanning a broad range of forest types across the continent. Over the course of a decade, we tracked the growth and survival of 3201 trees cored in 2012 (including those cored once and twice) and used hierarchical Bayesian models to compare them with those of a cohort of 7262 neighbouring trees that were never cored. C_LIO_LIWe found no evidence that coring had a detrimental impact on tree growth, irrespective of size, species, forest type or the number of times a tree was cored. However, we did observe a small positive stem increment response, which we hypothesise is most likely the result of localised vertical scarring from the coring wound. C_LIO_LIImpacts of tree coring on mortality were instead more uncertain, with mortality rates of cored trees slightly elevated relative to ones that were not cored, but overlapping widely in their credible intervals. This underscores the challenge of attributing drivers of rare and stochastic processes such as tree mortality, even with relatively large datasets. C_LIO_LIOur study generally supports the use of tree coring as a low-impact method for characterising the growth, age and function of a wide range of tree species, but highlights that there are circumstances in which it may cause harm. Future work should explore these further by considering the broader impacts of coring on tree health. Additionally, tree cores should always be collected well above or below the point of measurement of tree stem diameters to avoid biasing long-term forest census datasets. C_LI

ecology↗

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↗

bioRxiv2025

Beyond species means - the intraspecific contribution to global wood density variation

Wood density is central for estimating vegetation carbon storage and a plant functional trait of great ecological and evolutionary importance. However, the global extent of wood density variation is unclear, especially at the intraspecific level. We assembled the most comprehensive wood density collection to date (GWDD v.2), including 109,626 records from 16,829 plant species across woody life forms and biomes. Using the GWDD v.2, we explored the sources of variation in wood density within individuals, within species, and across environmental gradients. Intraspecific variation accounted for up to 15% of overall wood density variation (sd = 0.068 g cm-3). Sapwood densities varied 50% less than heartwood densities, and branchwood densities varied 30% less than trunkwood densities. Individuals in extreme environments (dry, hot, acidic soils) had higher wood density than conspecifics elsewhere (+0.02 g cm-3, [~]4% of the mean). Intraspecific environmental effects strongly tracked interspecific patterns (r = 0.83) but were only 20-30% as large and varied considerably among taxa. Individual plant wood density was difficult to predict (RMSE > 0.08 g cm-3; single-measurement R2 = 0.59). We recommend (i) systematic within-species sampling for local applications, and (ii) expanded taxonomic coverage combined with integrative models for robust estimates across ecological scales.

plant biology↗

bioRxiv2025

A global map of wood density

Wood density influences how quickly woody plants grow, how long they live and how much carbon they store, yet its global variation remains poorly mapped. Here we combined 109,626 wood density measurements from 16,829 species with 300,949 vegetation plots to produce a km-scale map of community-weighted wood density for every woody biome. Our model led to a prediction accuracy 32-51 % higher than previous global products, and a 1.8-3.7-fold wider wood density range (0.28-1.00 g cm-3; global mean: 0.57 g cm-3) than previously assumed. Spatial cross-validation showed low bias ({+/-}2.5 % of the mean), and uncertainties decreased from 20% in poorly sampled drylands and boreal regions to 5% in data-rich temperate forests. Mean annual temperature was the best predictor of community-weighted mean wood density, increasing by 0.01 g cm-3 for every 1{degrees}C change. We deliver a low-bias, high-resolution wood density layer for Earth system models, together with spatially explicit error maps. This study represents a major step forward for carbon accounting and trait-based forecasts of vegetation change.

plant biology↗

bioRxiv2024

Competition, precipitation and temperature shape deviations from scaling laws in the crown allometries of miombo woodlands

Scaling relationships between different axes of tree size, such as height, crown radius, crown depth and stem diameter, play a direct role in shaping forest structure and function. Theoretical models such as metabolic scaling theory postulate that they are optimized for biomechanical stability and hydraulic sap distribution. However, empirical data often show that such models are only good enough as first order approximations because they do not account for differences in species traits and environmental conditions where trees grow. Nevertheless, the vast majority of research has focused on temperate systems or tropical rainforests, so we continue to lack a full understanding of what factors shape allometries of trees in tropical dry forests. Here, we compile data on tree height, diameter, crown radius and depth from miombo woodlands across Zambia and use Bayesian hierarchical modelling framework to explore how allometric scaling relationships are shaped by climate and competition. Similar to previous studies, our results revealed that allometric scaling relationships deviate substantially from theoretical expectations. We found that competition, precipitation and temperature all affect crown allometric scaling relationships, with trees becoming more slender where neighbourhood competition was greater, while crowns were wider and deeper in warmer and wetter climates. Our study highlights how the structure and function of miombo woodlands is shaped by more than just water availability. Moreover, by developing improved crown allometric models for miombo woodlands, we provide new tools to aid the estimation of aboveground biomass and calibration of remote sensing products in these critically important dry forest ecosystems.

ecology↗

bioRxiv2024

Tracking tree demography and forest dynamics at scale using remote sensing

O_LICapturing how tree growth and survival vary through space and time is critical to understanding the structure and dynamics of tree-dominated ecosystems. However, characterising demographic processes at scale is inherently challenging, as trees are slow-growing, long-lived, and cover vast expanses of land. C_LIO_LIWe used repeat airborne laser scanning data acquired over 25 km2 of semi-arid, old-growth temperate woodland in Western Australia to track the height growth, crown expansion and mortality of 42,810 individual trees over nine years. C_LIO_LIWe found that demographic rates are constrained by a combination of tree size, competition and topography. After initially investing in height growth, trees progressively shifted to crown expansion as they grew larger, while mortality risk decreased considerably with size. Across the landscape, both tree growth and survival increased with topographic wetness, resulting in vegetation patterns that are strongly spatially structured. Moreover, biomass gains from woody growth generally outpaced losses from mortality, suggesting these old-growth woodlands remain a net carbon sink in the absence of wildfires. C_LIO_LIOur study sheds new light on the processes that shape the dynamics and spatial structure of semi-arid woody ecosystems and provides a roadmap for using emerging remote sensing technologies to track tree demography at scale. C_LI

ecology↗

bioRxiv2024

Robust characterization of forest structure from airborne laser scanning - a systematic assessment and sample workflow for ecologists

O_LIForests display tremendous structural diversity, shaping carbon cycling, microclimates, and terrestrial habitats. One of the most common tools for forest structure assessments are canopy height models (CHMs): maps of canopy height obtained at high resolution and large scale from airborne laser scanning (ALS). CHMs can be computed in many ways, but little is known about the robustness of different CHM algorithms and how they affect ecological analyses. C_LIO_LIHere, we used high-quality ALS data from nine sites in Australia, ranging from semi-arid shrublands to 90-m tall Mountain Ash canopies, to comprehensively assess CHM algorithms. This included testing their sensitivity to point cloud degradation and quantifying the propagation of errors to derived metrics of canopy structure. C_LIO_LIWe found that CHM algorithms varied widely both in their height predictions (differences up to 10 m, or 60% of canopy height) and in their sensitivity to point cloud characteristics (biases of up to [~]5 m or 40% of canopy height). Impacts of point cloud properties on CHM-derived metrics varied, from robust inference for height percentiles, to considerable errors in aboveground biomass estimates ([~]50 Mg ha-1, or 10% of total), and high volatility in metrics that quantify spatial associations in canopies (e.g., gaps or spatial autocorrelation). In some cases, biases exceeded ecological variation across sites by a factor of 2. However, we also found that two CHM algorithms - a variation on a "spikefree" algorithm that adapts to local pulse densities and a simple Delaunay triangulation of first returns - allowed for robust canopy characterization and should thus create a secure foundation for ecological comparisons in space and time. C_LIO_LICanopy height models are a widely used tool in ecology, but their derivation is not trivial. Our study provides a best-practice guideline and a sample workflow to create robust CHMs and minimize biases and uncertainty in downstream analyses. In doing so we pave the way for global-scale comparisons of forest structural complexity from airborne laser scanning. C_LI

ecology↗

bioRxiv2018

New formula and conversion factor to compute tree species basic wood density from a global wood technology database.

Premise of the studyBasic wood density is an important ecological trait for woody plants. It is used to characterize species performance and fitness in community ecology, and to compute tree and forest biomass in carbon cycle studies. While wood density has been historically measured at 12% moisture, it is convenient for ecological purposes to convert this measure to basic wood density, i.e. the ratio of dry mass over green volume. Basic wood density can then be used to compute tree dry biomass from living tree volume.\n\nMethodsHere, we derive a new, exact formula to compute the basic wood density Db from the density at moisture content w denoted Dw, the fibre saturation point S, and the volumetric shrinkage coefficient R. We estimated a new conversion factor using a global wood technology database where values to use this formula are available for 4022 trees collected in 64 countries (mostly tropical) and representing 872 species.\n\nKey resultsWe show that previous conversion factors used to convert densities at 12% moisture into basic wood densities are inconsistent. Based on theory and data, we found that basic wood density could be inferred from the density at 12% moisture using the following formula: Db = 0.828D122. This value of 0.828 provides basic wood density estimates 4-5% smaller than values inferred from previous conversion factors.\n\nConclusionsThis new conversion factor should be used to derive basic wood densities in global wood density databases. This would prevent overestimating global forest carbon stocks and allow predicting better tree species community dynamics from wood density.

plant biology↗