Biology subjects

Frey, J.

Publications and source records attributed to Frey, J..

9 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

Cryo-EM Structure of a Triazole alpha-Conotoxin GI Mimetic Bound to the Muscle-Type Nicotinic Acetylcholine Receptor

Disulfide-rich peptides possess exceptional potency and selectivity but are often limited by the instability and synthetic challenges associated with native disulfide bonds. Here, we report the design, synthesis, pharmacological evaluation, and structural characterisation of triazole-based peptidomimetics of the -GI conotoxin, a selective antagonist of the muscle-type nicotinic acetylcholine receptor (nAChR). A series of 1,4- and 1,5-disubstituted triazole analogues were prepared entirely on resin using CuAAC and RuAAC chemistry to replace the native Cys3/13 disulfide bridge. Functional evaluation against human muscle nAChRs revealed that 1,5-triazole analogues retained low-nanomolar potency, with the lead mimetic exhibiting activity comparable to native -GI. Cryo-electron microscopy of the lead compound bound to the muscle-type nAChR provided the first structure of a disulfide-isostere peptidomimetic in complex with a membrane receptor. The structure demonstrates that the 1,5-triazole reproduces the native peptide fold with high fidelity while contributing receptor-facing interactions not available to the native disulfide bridge. Molecular dynamics simulations further revealed conserved hydration networks and similar conformational sampling between the native peptide and lead mimetic. Together, these findings establish triazoles as effective disulfide surrogates and provide a structural framework for the rational design of stabilised conotoxin therapeutics.

biochemistry↗

bioRxiv2026

Controls of spatio-temporal patterns of soil respiration in a mixed forest

IntroductionPatterns of soil respiration (Rs) are heterogeneous on spatio-temporal scales. The best studied controlling factors of Rs are microclimatic conditions such as soil temperature and moisture. However, a strong pronounced seasonality shifts Rs patterns from temperature to moisture-controlled regimes. Hereby, lag effects and influences of trees in mixed forests on large spatio-temporal scales are rarely investigated. Material and MethodsWe investigated Rs over two years on a weekly to fortnightly measurement frequency at a 1 ha area in a mixed forest on 35 predefined locations using open bottom chambers. Analysis was derived using downscaled meteorological data and a tree species map. ResultsOur data confirmed soil temperature and moisture as important variables which explained up to 72% in variability. Yet, our results revealed an additional predictor: the atmospheric vapour pressure. Together with seasonality and the vapour pressure deficit, 84% in variability could be explained. Additionally, the predictors traced a decrease in Rs due to drought and an increase due to rewetting. By tendency, Rs correlated negatively with distance to the tree and Rs was significantly higher in broadleaf patches compared to coniferous and mixed patches during the summer seasons. ConclusionWe conclude that meteorological conditions might serve as valuable predictors for CO2 emissions from forest soil. This enables upscaling of Rs given the dense availability of meteorological data. Tree species distribution partly explained the spatial patterns of Rs. However, a detailed analysis of local soil properties would enhance our understanding of the interactions between soils, plants and the atmosphere.

ecology↗

bioRxiv2026

Structures of muscle-type nicotinic acetylcholine receptor with α-conotoxins reveal determinants of receptor-subtype specificity

-Conotoxins (-CTX) are disulfide-rich peptide antagonists with exceptional potency and subtype selectivity across nicotinic acetylcholine receptors (nAChRs), making them promising leads for therapeutic development. The molecular basis of their specificity has remained unresolved for decades, limiting rational drug design. Here, we present the first high-resolution cryo-EM structures of full-length muscle-type nAChR bound to three distinct -CTXs, revealing their precise binding modes at both acetylcholine binding sites. Our integrated approach, combining structural biology, pharmacological profiling, and computational hydration mapping, uncovers conserved pharmacophore features, water-mediated interactions, and subunit-specific determinants that govern potency and selectivity. These findings provide a long-sought molecular framework for -conotoxin recognition and inhibition, addressing a critical gap required to realise the full potential of conotoxins as lead compounds in drug discovery.

molecular biology↗

bioRxiv2025

Sea urchin consumption of kelp controlled by the density of drift algae

Rocky reef kelp forests can exhibit abrupt shifts between forested and barren states where unchecked sea urchin grazing inhibits kelp recovery. Forefront to urchin barren formation is a behavioral switch where sedentary urchins become active and graze upon attached kelp. This is hypothesized to occur when the availability of drift (i.e., detached kelp on the surface of the reef), which urchins are believed to prefer over intact and attached kelp, declines. Although observed repeatedly, the density-dependent nature of this apparent resource preference has not been characterized quantitatively. We used a series of subtidal functional response experiments in central California, USA, to quantify how consumption rates by Strongylocentrotus purpuratus (purple urchins) on Macrocystis pyrifera (giant kelp) and drift varied with their relative availability and over time as urchins became satiated. Our experiments indicate that the preference for drift over kelp is strong when drift and kelp are at equal abundance, that the abundance of drift has a strong effect on kelp consumption but not vice versa, and that the preferences for drift is indeed density dependent with the qualitative switch to a greater preference for kelp occurring when the availability of drift declines below approximately 1 g of drift for every 60 g of kelp. Our analyses suggest further that maintaining at least equal amounts of drift and kelp is sufficient to all but preclude urchins from grazing on live kelp. We recommend drift be used as an indicator of reef health, and that our thresholds be considered to guide drift subsidies to preserve and restore kelp forests.

ecology↗

bioRxiv2025

AngleCam V2: Predicting leaf inclination angles across taxa from daytime and nighttime photos

O_LIUnderstanding how plants capture light and maintain their energy balance is crucial for predicting how ecosystems respond to environmental changes. By monitoring leaf inclination angle distributions (LIADs), we can gain insights into plant behaviour that directly influences ecosystem functioning. LIADs affect radiative transfer processes and reflectance signals, which are essential components of satellite-based vegetation monitoring. Despite their importance, scalable methods for continuously observing these dynamics across different plant species throughout day-night cycles are limited. C_LIO_LIWe present AngleCam V2, a deep learning model that estimates LIADs from both RGB and near-infrared (NIR) night-vision imagery. We compiled a dataset of over 4,500 images across 200 globally distributed species to facilitate generalization across taxa. Moreover, we developed a method to simulate pseudo-NIR imagery from RGB imagery to enable an efficient training of a deep learning model for tracking LIADs across day and night. The model is based on a vision transformer architecture with mixed-modality training using the RGB and the synthetic NIR images. C_LIO_LIAngleCam V2 achieved substantial improvements in generalization compared to AngleCam V1 (R2 = 0.62 vs 0.12 on the same holdout dataset). Phylogenetic analysis across 100 genera revealed no systematic taxonomic bias in prediction errors. Testing against leaf angle dynamics obtained from multitemporal terrestrial laser scanning demonstrated the reliable tracking of diurnal leaf movements (R2 = 0.61-0.75) and the successful detection of water limitation-induced changes over a 14-day monitoring period. C_LIO_LIThis method enables continuous monitoring of leaf angle dynamics using conventional cameras, enabling applications in ecosystem monitoring networks, plant stress detection, interpreting satellite vegetation signals, and citizen science platforms for global-scale understanding of plant structural responses. C_LI

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↗

bioRxiv2024

Perceived biodiversity: is what we measure also what we see and hear?

1. Biodiversity is crucial for human health and well-being. Perceived biodiversity - peoples subjective experience of biodiversity - seems to be particularly relevant for mental well-being. 2. Using photographs and audio recordings of forests that varied in levels of species richness, we conducted two sorting studies to assess how people perceive visual and acoustic diversity and whether their perceptions align with measured tree and bird species richness ( actual diversity). Per study, 48 participants were asked to sort the stimuli according to any similarity-based sorting criteria they liked ( open sorts) and perceived diversity ( closed sorts). 3. The main perceived visual forest characteristics identified by participants in the open visual sorts were vegetation density, light conditions, forest structural attributes and colours. The main perceived acoustic forest characteristics identified in the open acoustic sorts comprised bird song characteristics, physical properties such as volume, references to the time of day or seasonality and evoked emotions. 4. Perceived visual and acoustic diversity were significantly correlated with actual tree and bird species richness, respectively. Notably, the relationship was twice as strong for the acoustic sense. The acoustic sense may thus be crucial to obtain a more thorough understanding of perceived biodiversity. 5. We further computed several visual and acoustic diversity indices from the photos and audio recordings, e.g. colourfulness or acoustic complexity, and assessed their relevance for perceived and actual diversity. While all acoustic diversity indices were significantly associated with perceived acoustic diversity and bird richness, we could not identify a visual diversity index that captured perceived visual diversity and tree richness. 6. Our results suggest that people can perceive species richness. Our identified visual and acoustic forest characteristics may help to better understand perceived diversity and how it differs from actual diversity. We present acoustic diversity indices that quantify aspects of perceived and actual acoustic diversity. These indices may serve as cost-efficient tools to manage and plan greenspaces to promote biodiversity and mental well-being.

ecology↗

bioRxiv2020

Emergence and global spread of Listeria monocytogenes main clinical clonal complex

Retracing microbial emergence and spread is essential to understanding the evolution and dynamics of pathogens. The bacterial foodborne pathogen Listeria monocytogenes clonal complex 1 (Lm-CC1) is the most prevalent clonal group associated with listeriosis, and is strongly associated with cattle and dairy products. Here we analysed 2,021 Lm-CC1 isolates collected from 40 countries, since the first Lm isolation to the present day, to define its evolutionary history and population dynamics. Our results suggest that Lm-CC1 spread worldwide from North America following the Industrial Revolution through two waves of expansion, coinciding with the transatlantic livestock trade in the second half of the 19th century and the rapid growth of cattle farming in the 20th century. Lm-CC1 then firmly established at a local level, with limited inter-country spread. This study provides an unprecedented insight into Lm-CC1 phylogeography and dynamics and can contribute to effective disease surveillance to reduce the burden of listeriosis.

genomics↗