Biology subjects

Jackson, T. D.

Publications and source records attributed to Jackson, T. D..

17 recordsLinked to original sources

bioRxiv2026

MillionTrees: A global benchmark for tree detection across geography, sensor, and annotation geometry

Airborne tree monitoring using remotely sensed data, combined with the growth of computer vision models for object detection and segmentation, can facilitate broad scale assessment of tree health, ecology and ecosystem function. However, datasets for airborne tree detection have been largely limited to a single geography, resolution, or annotation approach, making it difficult to develop general models and benchmark their utility for broad applications. We compile existing and newly published annotation datasets to create a comprehensive dataset for training and evaluating airborne tree detection in RGB imagery. The MillionTrees dataset has over a million individual trees from a broad range of forest types, tree species, and geographic locations. In addition, it has six million weakly supervised annotations from a range of sources including airborne LiDAR and photogrammetry, arborist surveys, and simulated landscapes. An evaluation standard is provided to facilitate rapid model development. We benchmark several existing tree detection algorithms and demonstrate that while current open-source models do not generalize across the diverse datasets in the benchmark, training on MillionTrees improves both within-domain and out-of-domain performance. Held-out validation datasets using ground truth derived from terrestrial LiDAR paired with overhead RGB show that overfitting to test data is common and hyperparameter tuning is an underappreciated challenge towards a global zero shot tree detection method. We discuss the limitations of the currently available data for airborne RGB tree detection, how to create more robust evaluation data and the need for better understanding of the uncertainty and utility of tree detection from airborne remote sensing.

ecology↗

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

SMAD4 loss drives chromosomal instability during tumourigenesis via translational reprogramming

Chromosomal instability (CIN), arising from errors in chromosome segregation during cell division, is a hallmark of cancer. Whilst CIN can result from several mitotic defects, the mechanisms that initiate CIN to drive tumourigenesis remain incompletely understood. Here, we show that loss of SMAD4 reprograms translation to induce CIN, resulting in tumour formation. Multi-omics analysis of tumourigenesis models driven by loss of SMAD4 complemented by functional studies demonstrate that loss of SMAD4 in pre-neoplastic cells leads to dysfunctional mitosis and an altered global translation landscape. We show that CDK11B is translationally downregulated in SMAD4-\- cells, and re-expression of the mitosis-specific isoform of this protein (CDK11B-p58) rescues the mitotic defects. Analysis of patient tumours reveals a strong correlation between markers of CIN and SMAD4 status, indicating the clinical relevance of this phenotype. Collectively, we reveal a previously unrecognised role for SMAD4 as a gatekeeper for CIN-mediated tumourigenesis via regulation of translation.

cancer biology↗

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↗

bioRxiv2025

Riboflavin drives nucleotide biosynthesis and iron-sulfur metabolism to promote acute myeloid leukemia

Riboflavin is a diet-derived vitamin in higher organisms that serves as a precursor for flavin mononucleotide and flavin adenine dinucleotide, key cofactors that participate in oxidoreductase reactions. Here, using proteomic, metabolomic and functional genomics approaches, we describe a specific riboflavin dependency in acute myeloid leukemia and demonstrate that, in addition to energy production via oxidative phosphorylation, a key biological role of riboflavin is to enable nucleotide biosynthesis and iron-sulfur cluster metabolism. Genetic perturbation of riboflavin metabolism pathways or exogenous depletion in physiological culture medium induce nucleotide imbalance and DNA damage responses, as well as impair the stability and activity of proteins which utilize [4Fe-4S] iron-sulfur clusters as cofactors. We identify a window of therapeutic opportunity upon riboflavin starvation or chemical riboflavin metabolism perturbation and demonstrate that this strongly synergizes with BCL-2 inhibition. Our work identifies riboflavin as a critical metabolic dependency in leukemia, with functions beyond energy production.

cancer biology↗

bioRxiv2025

Mapping giant-tree density in the Amazon

Tall trees are pivotal in maintaining tropical forests biodiversity and regulating biogeochemical cycles, mainly through their influence on carbon storage, nutrient cycling, and habitat structuring. Despite their ecological importance, the drivers behind their spatial distribution and the environmental factors driving the density of these emergent trees remain unexplained. Here we analyzed tall-tree density data derived from airborne LiDAR across 900 randomly distributed transects throughout the Brazilian Amazon. We paired each transect location with climatic, topographic, atmospheric, and soil metrics to investigate regional-level environmental drivers of large tree density using spatial modeling. Water availability and stable climatic conditions (low incidence of storms and of lightning) were the main drivers of tall-tree density at the regional level. The occurrence of tall trees is aggregated along the Amazon, with 14% occurring within 1.3% of the Amazon and 50% concentrated in 11.2% of the area. These patterns suggest that tall trees dominate localized regions of the biome and that high densities of tall trees are primarily dependent on mechanical rather than physiological drivers. Understanding the dynamics of 55.5 million emergent trees is imperative for advancing research in biogeochemistry, ecology, and climate resilience. Our results are especially relevant in the context of conserving nature and carbon stocks under increasing anthropogenic and environmental pressures.

ecology↗

bioRxiv2024

Harnessing temporal and spectral dimensionality to map and identify species of individual trees in diverse tropical forests

Species-level canopy maps underpin tropical forest biodiversity monitoring, conservation planning, and carbon accounting, yet high species richness and structural complexity make remote classification challenging. Here we evaluate how far a two-step mapping approach can be taken, and where it breaks down, in hyperdiverse moist forest at the Paracou Field Station, French Guiana. First, we delineate individual tree crowns from ten repeat uncrewed aerial vehicle (UAV) RGB surveys with Mask R-CNN, fusing predictions across dates by temporal consensus: mean segmentation F1 rose from 0.68 (single date) to 0.78 (ten dates), covering approximately 86% of test-region canopy area. Second, we classify each crown from a single airborne hyperspectral acquisition (416-2500 nm, 1 m) using machine learning classifiers trained and tested on 3,186 field-verified crowns spanning 169 species. Linear Discriminant Analysis performed best (weighted F1 = 0.75), outperforming more flexible models, but unevenly: across repeated cross-validation (20 x 5-fold), on average 50 species (95% CI: 41-63) attained F1 [≥] 0.7 in a given fold and only 15 did so reliably, with many rare species unclassifiable (macro-average F1 = 0.48). Combining both steps, we estimate approximately 70% of the landscapes canopy area was correctly mapped to species. Band-importance and ablation analyses identified the far-red edge (748-775 nm) as the most informative spectral region. These results advance on studies limited to 20 or fewer species and set out spectral-resolution and training-data requirements for airborne and forthcoming spaceborne imaging spectrometers, while showing that accuracy remains strongly conditioned by training-data availability and the single-site, single-acquisition design.

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↗

bioRxiv2023

Selective Mitochondrial Respiratory Complex I Subunit Deficiency Causes Tumor Immunogenicity

Targeting of specific metabolic pathways in tumor cells has the potential to sensitize them to immune-mediated attack. Here we provide evidence for a specific means of mitochondrial respiratory Complex I (CI) inhibition that improves tumor immunogenicity and sensitivity to immune checkpoint blockade (ICB). Targeted genetic deletion of the CI subunits Ndufs4 and Ndufs6, but not other subunits, induces an immune-dependent tumor growth attenuation in mouse melanoma models. We show that deletion of Ndufs4 induces expression of the transcription factor Nlrc5 and genes in the MHC class I antigen presentation and processing pathway. This induction of MHC-related genes is driven by an accumulation of pyruvate dehydrogenase-dependent mitochondrial acetyl-CoA downstream of CI subunit deletion. This work provides a novel functional modality by which selective CI inhibition restricts tumor growth, suggesting that specific targeting of Ndufs4, or related CI subunits, increases T-cell mediated immunity and sensitivity to ICB.

cancer biology↗

bioRxiv2023

Caspase-2 protects against ferroptotic cell death

Caspase-2, one of the most evolutionarily conserved member of the caspase family, is an important regulator of the cellular response to oxidative stress. Given that ferroptosis is suppressed by antioxidant defense pathways, such as that involving selenoenzyme glutathione peroxidase 4 (GPX4), we hypothesised that caspase-2 may play a role in regulating ferroptosis. This study provides the first demonstration of an important and unprecedented function of caspase-2 in protecting cancer cells from undergoing ferroptotic cell death. Specifically, we show that depletion of caspase-2 leads to downregulation of stress response genes including SESN2, HMOX1, SLC7A11 and sensitises mutant-p53 cancer cells to cell death induced by various ferroptosis inducing compounds. Importantly, the canonical catalytic activity of caspase-2 is not required for its role and suggests that caspase-2 regulates ferroptosis via non-proteolytic interaction with other proteins. Using an unbiased BioID proteomics screen, we identified novel caspase-2 interacting proteins (including heat shock proteins and co-chaperones) that regulate cellular responses to stress. Finally, we demonstrate that caspase-2 limits chaperone mediated autophagic degradation of GPX4 to promote survival of mutant-p53 cancer cells. In conclusion, we document a novel role for caspase-2 as a negative regulator of ferroptosis in cells with mutant-p53. Our results provide evidence for a novel function of caspase-2 functions in cell death regulation and open potential new avenues to exploit ferroptosis in cancer therapy.

cancer biology↗

bioRxiv2022

Tree segmentation in airborne laser scanning data is only accurate for canopy trees

Individual tree segmentation from airborne laser scanning data is a longstanding and important challenge in forest remote sensing. There are a number of segmentation algorithms but robust intercomparison studies are rare due to the difficulty of obtaining reliable reference data. Here we provide a benchmark data set for temperate and tropical broadleaf forests generated from labelled terrestrial laser scanning data. We compare the performance of four widely used tree segmentation algorithms against this benchmark data set. All algorithms achieved reasonable accuracy for the canopy trees, but very low accuracy for the understory trees. The point cloud based algorithm AMS3D (Adaptive Mean Shift 3D) had the highest overall accuracy, closely followed by the 2D raster based region growing algorithm Dalponte2016+. This result was consistent across both forest types. This study emphasises the need to assess tree segmentation algorithms directly using benchmark data. We provide the first openly available benchmark data set for tropical forests and we hope future studies will extend this work to other regions.

ecology↗

bioRxiv2022

Accurate tropical forest individual tree crown delineation from RGB imagery using Mask R-CNN

Tropical forests are a major component of the global carbon cycle and home to two-thirds of terrestrial species. Upper-canopy trees store the majority of forest carbon and can be vulnerable to drought events and storms. Monitoring their growth and mortality is essential to understanding forest resilience to climate change, but in the context of forest carbon storage, large trees are underrepresented in traditional field surveys, so estimates are poorly constrained. Aerial photographs provide spectral and textural information to discriminate between tree crowns in diverse, complex tropical canopies, potentially opening the door to landscape monitoring of large trees. Here we describe a new deep convolutional neural network method, Detectree2, which builds on the Mask R-CNN computer vision framework to recognise the irregular edges of individual tree crowns from airborne RGB imagery. We trained and evaluated this model with 3,797 manually delineated tree crowns at three sites in Malaysian Borneo and one site in French Guiana. As an example application, we combined the delineations with repeat lidar surveys (taken between 3 and 6 years apart) of the four sites to estimate the growth and mortality of upper-canopy trees. Detectree2 delineated 65,000 upper-canopy trees across 14 km2 of aerial images. The skill of the automatic method in delineating unseen test trees was good (F1 score = 0.64) and for the tallest category of trees was excellent (F1 score = 0.74). As predicted from previous field studies, we found that growth rate declined with tree height and tall trees had higher mortality rates than intermediate-size trees. Our approach demonstrates that deep learning methods can automatically segment trees in widely accessible RGB imagery. This tool (provided as an open-source Python package) has many potential applications in forest ecology and conservation, from estimating carbon stocks to monitoring forest phenology and restoration. Python package available to install at https://github.com/PatBall1/Detectree2

ecology↗

bioRxiv2021

Forest structure and degradation drive canopy gap sizes across the Brazilian Amazon

Canopy gaps are openings in the forest canopy resulting from branch fall and tree mortality events. Light reaches the lower layers of the canopy through these gaps, enabling understory trees to grow and maintaining the high heterogeneity and biodiversity of tropical forests. The size-frequency distribution of canopy gaps follows a power-law distribution, and the slope of this power-law () is a key indicator of forest structure and dynamics. We detected canopy gaps using a unique LiDAR data set consisting of 650 transects randomly distributed across the Brazilian Amazon Forest providing an unprecedented perspective on forest structural variation over 2500 km2 of forest. We then investigated how varied with forest structure, elevation, soil fertility, water deficit, wind gust speed and lightning intensity. We found that human modified forests had more large gaps than intact forests. Within the intact forests we observed a large-scale Northwest to Southeast pattern in (more large gaps in the Southeast), which aligns with recent work on tree mortality rates. The two most important variables in predicting were median canopy height and maximum modeled height, which had opposite effects on the number of large gaps. Forests with higher median canopy height contain fewer large gaps but the presence of very tall trees was associated with more large gaps. Environmental variables were of secondary importance in our model, with larger gaps occurring in drier forests with high soil fertility, wind speed, and lightning intensity. The distribution of large gaps in the forest canopy varies substantially over the Brazilian Amazon as a result of canopy structure and mortality rates. We mapped this variation and found more large gaps in human modified forests, forests on fertile soils and those exposed to higher wind, lightning and drought stress. Increasing extreme weather events due to climate change may therefore increase the number of large gaps in currently intact forests, causing them to resemble human modified forests.

ecology↗

bioRxiv2020

Genome-wide CRISPR screens reveal APR-246 (Eprenetapopt) triggers ferroptosis and inhibits iron-sulfur cluster biogenesis

The mechanisms by which cells respond and adapt to oxidative stress are largely unknown but are key to developing a rationale for cancer therapies that target antioxidant pathways. APR-246 is a mutant-p53 targeted therapeutic currently under clinical investigation in myeloid dysplastic syndrome (MDS) and acute myeloid leukemia1. Whilst the mechanism of action of APR-246 is thought to be reactivation of wild-type p53 activity through covalent modification of cysteine residues in the core domain of mutant-p53 protein2,3, here we report that the anti-neoplastic capacity of APR-246 lies predominantly in the conjugation of free cysteine. Genome-wide CRISPR perturbation screening, metabolite profiling and proteomics in response to APR-246 treatment in mutant-p53 cancer cells highlighted the role of GSH and mitochondrial metabolism in determining APR-246 efficacy. APR-246 sensitivity was increased through loss of key enzymes in mitochondrial one-carbon metabolism, SHMT2 and MTHFD1L, due to diminished glycine supply for de novo GSH synthesis. Critically, we show that APR-246 induces iron-dependent, apoptotic machinery-independent cell death, ferroptosis. Whole-cell proteomics analyses indicated an upregulation of proteins involved in iron-sulfur cluster biogenesis (eg. FDX1). GSH, acetyl-CoA and NADH levels were also depleted in APR-246 treated cells. Importantly, we found that APR-246 inhibits iron-sulfur cluster biogenesis in the mitochondria of cancer cells through cysteine conjugation. This work not only details novel determinants of APR-246 activity in cancer cells, but also provides a clinical roadmap for targeting antioxidant pathways in tumours - beyond targeting mutant-p53 tumours. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/398867v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@11155f8org.highwire.dtl.DTLVardef@1231cb7org.highwire.dtl.DTLVardef@324881org.highwire.dtl.DTLVardef@136146f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

The TIM22 complex regulates mitochondrial one-carbon metabolism by mediating the import of Sideroflexins

The Acylglycerol Kinase (AGK) is a mitochondrial lipid kinase that contributes to protein biogenesis as a subunit of the TIM22 complex at the inner mitochondrial membrane. Mutations in AGK cause Sengers syndrome, an autosomal recessive condition characterized by congenital cataracts, hypertrophic cardiomyopathy, skeletal myopathy and lactic acidosis. We undertook proteomic profiling of Sengers patient fibroblasts and an AGKKO cell line to map the proteomic changes that ensue upon AGK dysfunction. This uncovered extensive remodelling of mitochondrial one-carbon metabolism enzymes and showed that inner membrane serine transporters, Sideroflexins (SFXNs), are novel substrates of the TIM22 complex. Deletion of SFXN1 recapitulates the remodelling of one-carbon metabolism observed in Sengers patient cells. Proliferation of cells lacking AGK is perturbed in the absence of exogenous serine and rescuable through addition of formate, highlighting the dysregulation of one carbon metabolism as a key molecular feature in the biology of Sengers syndrome.

cell biology↗

bioRxiv2019

The mechanical stability of the worlds tallest broadleaf trees

The factors that limit the maximum height of trees, whether ecophysiological or mechanical, are the subject of longstanding debate. Here we examine the role of mechanical stability in limiting tree height and focus on trees from the tallest tropical forests on Earth, in Sabah, Malaysian Borneo, including the recently discovered tallest tropical tree, a 100.8 m Shorea faguetiana. We use terrestrial laser scans, in situ strain gauge data and finite-element simulations to map the architecture of tall broadleaf trees and monitor their response to wind loading. We demonstrate that a trees risk of breaking due to gravity or self-weight decreases with tree height and is much more strongly affected by tree architecture than by material properties. In contrast, wind damage risk increases with tree height despite the larger diameters of tall trees, resulting in a U-shaped curve of mechanical risk with tree height. The relative rarity of extreme wind speeds in north Borneo may be the reason it is home to the tallest trees in the tropics.

ecology↗