Biology subjects

Heurich, M.

Publications and source records attributed to Heurich, M..

11 recordsLinked to original sources

bioRxiv2026

Continent-wide calibration of camera-trap metrics reveals low population densities in the European wildcat

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.

ecology↗

bioRxiv2025

How big is enough? Movement-informed zoning for African swine fever mitigation

O_LIAfrican swine fever (ASF) poses a serious threat to domestic pigs and wild boar populations. Wild boar can disperse the virus, making effective containment crucial. One of the main control strategies involves establishing restricted zones around detected cases, i.e., areas with temporary restrictions on access and hunting; however, determining the appropriate size of these zones remains a major challenge. C_LIO_LITo inform the size of restricted zones, we analyzed GPS data from 527 wild boar across 46 European study sites using a two-step approach combining first-passage time analysis and survival modelling to quantify the risk of wild boar leaving areas of different radii (i.e., spatial scales). We investigated how the risk of leaving varied over time and across environmental gradients. To go further, we used our model findings to develop an online application that generates predictive maps of optimal buffer sizes for ASF management at the European scale, based on a given risk threshold (the maximum acceptable probability that a wild boar leaves the area). C_LIO_LIWe found that the relationship between radius and the risk of leaving is negative exponential, and the risk of leaving increased over time, with a more rapid increase for smaller radii. Landscape homogeneity, terrain ruggedness and human impact increased the risk of leaving, with stronger effects at small scales. Contrary to other predictors, agricultural cover exerted a strong effect on risk of leaving over large spatial scales, especially when it was abundant. C_LIO_LIAcross Europe, a buffer radius of [~]8 km is likely sufficient around high-risk infection zones in most areas (considering an infectious period of 14 days and a risk threshold of 5%); however, in certain areas, a radius of up to 20 km may be needed to effectively limit wild boar movement. C_LIO_LISynthesis and applications: Our results highlight the need for adaptive, context-specific restricted zones. Buffers of 8 km around ASF-affected areas can limit the risk of infected wild boar dispersal, but they may be reduced to 5 km in highly heterogeneous landscapes or high-human impacted areas. Larger buffers may be required in agricultural landscapes. We provide spatially explicit outputs (optimal buffer sizes) that can directly inform policy and wildlife disease response strategies. The approach can be adapted to any other infectious disease. 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↗

bioRxiv2024

Prey attracting but not repelled by predators suggests an asymmetric investment in the encounter-avoid-escape sequence.

Understanding predator-prey interactions, particularly how species use space and time to influence encounter rates, is fundamental in community and behavioural ecology. However, for large, free-ranging animals, encounter rates are rarely quantified directly, because of logistical and methodological challenges associated with tracking both predators and prey simultaneously. Instead, studies commonly rely on proxies such as spatial or temporal overlap. While informative, these proxies provide only incomplete estimates of encounter rates because they typically consider only one dimension of the interaction process (spatial or temporal). Although camera traps cannot directly measure encounters among large free-roaming species, they offer the opportunity to quantify the proximal co-occurrence, i.e., the extent to which species tolerate or avoid one anothers proximity in space and time. We analysed data from a one-year study conducted across four German protected areas using 283 camera traps and applying recurrent event analysis to investigate interactions among three prey species, red deer (Cervus elaphus), roe deer (Capreolus capreolus), wild boar (Sus scrofa) and two large predators grey wolf (Canis lupus), and Eurasian lynx (Lynx lynx). Prey visitation rates were unaffected by predator presence, whereas wolves exhibited a strong attraction to prey, with visitation rates four to six times higher immediately after prey detections. The limited sample size prevented robust conclusions regarding Eurasian lynx responses. These findings point towards an asymmetry in the predation sequence (i.e., spatio-temporal proximity, encounter, ignorance or avoidance post-encounter, capture or escape from attack): Predators must succeed at every stage of the sequence to capture prey, while prey can avoid predation by disrupting the process at any single stage. Our results suggest that prey species do not necessarily reduce large-scale spatio-temporal proximity to predators and may instead rely on anti-predator responses occurring later in the predation sequence.

ecology↗

bioRxiv2024

Density-dependent network structuring within and across wild animal systems

High population density should drive individuals to more frequently share space and interact, producing better-connected spatial and social networks [1-4]. Although this theory is fundamental to our understanding of disease dynamics [2,5-8], it remains unconfirmed how local density generally drives individuals positions within their networks, which reduces our ability to understand and predict density-dependent processes [4,9,10]. Here we provide the first general evidence that density drives greater network connectedness at fine spatiotemporal scales, at the scale of individuals within wild animal populations. We analysed 36 datasets of simultaneous spatial and social behaviour in >58,000 individual animals, spanning 30 species of fish, reptiles, birds, mammals, and insects. 80% of systems exhibited strong positive relationships between local density and network centrality. However, >80% of relationships were nonlinear and 75% became shallower at higher values, signifying that demographic and behavioural processes counteract densitys effects, thereby producing saturating trends [11-15]. Densitys effect was much stronger and less saturating for spatial than social networks, such that individuals become disproportionately spatially connected rather than socially at higher densities. Consequently, ecological processes that depend on spatial connections (e.g. indirect pathogen transmission, resource competition, and territory formation) are likely more density-dependent than those involving social interactions (e.g. direct pathogen transmission, aggression, and social learning). These findings reveal fundamental ecological rules governing societal structuring, with widespread implications. Identifying scaling rules based on processes that generalise across systems, such as these patterns of density dependence, might provide the ability to predict network structures in novel systems.

ecology↗

bioRxiv2024

Individual variation in red deer responsiveness towards human disturbance: A prospect for wildlife viewing in Europes national parks.

Animals adjust behavior to changes in perceived predation risk, even when risk is non-consumptive, as is the case for human recreation. However, individuals within populations can differ greatly in their plasticity towards perceived risk, especially when antipredator responses incur fitness costs via lost foraging opportunities. Therefore, risk-benefit trade-offs are usually made at the individual level. We test whether red deer (Cervus elaphus) inhabiting the Bavarian Forest National Park show individual variation in behavioral plasticity towards human disturbance. We measured human disturbance as the number of recreationists on the closest trail on a given day and used random regression to dissolve movement responses, measured as hourly step-length, of 63 GPS-collared red deer females to fine scale spatio-temporal variation in disturbance. We quantified behavioral state specific between-individual variation along the disturbance gradient. At the population level, red deer responded to recreational disturbance during the middle of the day only, and reduced movement in response to recreation. However, population patterns masked strong between-individual variation in plasticity to recreation activity during the morning, midday, and evening, such that some deer reacted with flight while others responded little. Behavioral responses were mediated by vegetation cover with stronger responses in more open areas. Flight responses are costly due to lost foraging opportunities. A shift in risk-benefit trade-offs when risk is non-lethal, as is the case for recreation in many national parks, may favor more human-tolerant individuals over time. Lay summaryWe assessed the individual response of red deer towards recreational activities in the Bavarian Forest National Park, using GPS-telemetry data and modelled daily numbers of tourists on trails. Red deer varied in their fear of humans, most red deer adjusted movement on days with many park visitors, but some individuals did not respond to human disturbance. Individual variation in movement increased with human disturbance. Foraging-risk trade-offs may promote behavioral variation of red deer and their tolerance of humans.

animal behavior and cognition↗

bioRxiv2022

Spatial variation in red deer density in relation to forest disturbance and ungulate management in a transboundary forest ecosystem

1. ContextForests in Europe are exposed to increasingly frequent and severe disturbances. The resulting changes in the structure and composition of forests can have profound consequences for the wildlife inhabiting them. Moreover, wildlife populations in Europe are often subjected to differential management regimes as they regularly extend across multiple national and administrative borders. The red deer (Cervus elaphus) population in the Bohemian Forest Ecosystem, straddling the Czech-German border, has experienced forest disturbances, primarily caused by windfalls and bark beetle (Ips typographus) outbreaks during the past decades. To adapt local management strategies to the changing environmental conditions and to coordinate them across the international border, reliable estimates of red deer density and abundance are highly sought-after by policymakers, wildlife managers, and stakeholders. 2. Approach and MethodsCovering a 1081-km2 study area, we conducted a transnational non-invasive DNA sampling study in 2018 that yielded 1578 genotyped DNA samples from 1120 individual red deer. Using spatial capture-recapture models, we estimated total and jurisdiction-specific abundance of red deer throughout the ecosystem and quantified the role of forest disturbance and differential management strategies in shaping spatial heterogeneity in red deer density. We hypothesized that (a) forest disturbances provide favourable habitat conditions (e.g., forage and cover), and (b) contrasting red deer management regimes in different jurisdictions create a differential risk landscape, ultimately shaping density distributions. 3. ResultsOverall, we estimated that 2851 red deer (95% Credible Intervals = 2609 - 3119) resided in the study area, with a relatively even overall sex ratio (1406 females, 1229 - 1612 and 1445 males, 1288 - 1626). The average red deer density was higher in Czechia (3.5 km-2, 1.2 - 12.3) compared to Germany (2 km-2, 0.2 - 11). The effect of forest disturbances on red deer density was context dependent. Forest disturbances had a positive effect on red deer density at higher elevations and a negative effect at lower elevations, which could be explained by partial migration and its drivers in this population. Density of red deer was generally higher in management units where hunting is prohibited. In addition, we found that sex ratios differed between administrative units and were more balanced in the non-intervention zones. 4. Synthesis and applicationsOur results show that the effect of forest disturbances on wild ungulates is modulated by additional factors, such as elevation and ungulate management practices. Overall density patterns and sex ratios suggested strong gradients in density between administrative units. With climate change increasing the severity and frequency of forest disturbances, population-level monitoring and management are becoming increasingly important especially for wide-ranging species as both wildlife and global change transcend administrative boundaries.

ecology↗

bioRxiv2021

imageseg: an R package for deep learning-based image segmentation

O_LIConvolutional neural networks (CNNs) and deep learning are powerful and robust tools for ecological applications. CNNs can perform very well in various tasks, especially for visual tasks and image data. Image segmentation (the classification of all pixels in images) is one such task and can for example be used to assess forest vertical and horizontal structure. While such methods have been suggested, widespread adoption in ecological research has been slow, likely due to technical difficulties in implementation of CNNs and lack of toolboxes for ecologists. C_LIO_LIHere, we present R package imageseg which implements a workflow for general-purpose image segmentation using CNNs and the U-Net architecture in R. The workflow covers data (pre)processing, model training, and predictions. We illustrate the utility of the package with two models for forest structural metrics: tree canopy density and understory vegetation density. We trained the models using large and diverse training data sets from a variety of forest types and biomes, consisting of 3288 canopy images (both canopy cover and hemispherical canopy closure photographs) and 1468 understory vegetation images. C_LIO_LIOverall classification accuracy of the models was high with a Dice score of 0.91 for the canopy model and 0.89 for the understory vegetation model (assessed with 821 and 367 images, respectively), indicating robustness to variation in input images and good generalization strength across forest types and biomes. C_LIO_LIThe package and its workflow allow simple yet powerful assessments of forest structural metrics using pre-trained models. Furthermore, the package facilitates custom image segmentation with multiple classes and based on color or grayscale images, e.g. in cell biology or for medical images. Our package is free, open source, and available from CRAN. It will enable easier and faster implementation of deep learning-based image segmentation within R for ecological applications and beyond. C_LI

ecology↗

bioRxiv2021

Eurasian lynx populations in Western Europe: What prospects for the next 50 years?

Persistence of populations may be uncertain for large carnivore species, especially for those established in human-dominated landscapes. Here, we studied the Eurasian lynx in Western Europe established in the Upper Rhine meta-population (i.e., Jura, Vosges-Palatinian and Black Forest populations) and the Alpine population. These populations are currently considered endangered or critically endangered due to high anthropogenic mortality, small population size and low genetic diversity, and isolation. We assessed lynx persistence over a 50-year time horizon by implementing a spatially-explicit individual-based model, while accounting for road mortality and habitat selection. Forecasts showed a steady growth rapidly reaching a more stable phase for the Alpine and Jura populations, and a more heterogeneous positive growth with less precision for the Vosges-Palatinian and Black Forest populations. Exchanges of individuals between populations were limited, the Jura population playing the role of a crossroad. Finally, the persistence of lynx in Western Europe seems likely on a large scale over the next 50 years. Indeed, simulations showed high female occupancy as well as average lynx density over the core areas of the four studied populations. Nevertheless, these results should be interpreted with the model limitations in mind, concerning the absence of movement barriers and inbreeding depression.

ecology↗

bioRxiv2021

Complement Regulator Factor H is a Cofactor for Thrombin in both Pro- and Anticoagulant Roles

BackgroundComplement FH (FH) is a key regulator of complement activity whereas thrombin (FIIa) is central to hemostasis with both pro- and anticoagulant functions. Both have separately been shown to have auxiliary activities across the two systems. The purpose of this study was to determine the effect of FH on pro- and anti-coagulant functions and investigate the interaction between FH and thrombin. MethodsTail bleeding time and hemolysis were measured in FH-deficient mice (CFH-/-). Activated partial thromboplastin time (aPTT) was determined in FH-depleted human plasma. FH effect on fibrin clot generation was investigated in turbidity assays and on activated protein C (APC) generation. Binding affinity of thrombin with FH was determined using surface plasmon resonance (SPR). ResultsTail bleeding time in CFH-/- mice was significantly prolonged compared to wild type mice. The aPTT in FH-depleted human plasma was elevated compared to normal plasma and restored by adding back FH to depleted plasma. Accordingly, FH enhanced thrombin-mediated fibrin clot generation by shortening lag time, increasing rate of clot formation and maximum turbidity, and affected clot structure. Despite this, FH also increased the rate of thrombin-mediated protein C (PC) activation, both in the presence and absence of soluble recombinant thrombomodulin (TM). Nanomolar affinity binding of FH with thrombin, but not prothrombin, was confirmed. ConclusionComplement FH binds thrombin with strong affinity and acts as a novel cofactor that enhances both pro- and anticoagulant actions of thrombin. These data highlight an important role for FH in hemostasis. Key pointsO_LIAbsence of FH prolongs tail bleeding time in CFH-/- mice and activated partial thromboplastin time (aPTT) is elevated in human FH-depleted plasma. C_LIO_LIFH acts a cofactor for thrombin by enhancing fibrin generation, altering fibrin clot structure and enhancing TM-thrombin mediated protein C activation C_LI

immunology↗

bioRxiv2021

The Structure of ChAdOx1/AZD-1222 Reveals Interactions with CAR and PF4 with Implications for Vaccine-induced Immune Thrombotic Thrombocytopenia

Adenovirus derived vectors, based on chimpanzee adenovirus Y25 (ChAdOx1) and human adenovirus type 26 are proving critical in combatting the 2019 SARS-CoV-2 pandemic. Following emergency use authorisation, scale up in vaccine administration has inevitably revealed vaccine related adverse effects; too rare to observe even in large Phase-III clinical trials. These include vaccine-induced thrombotic thrombocytopenia (VITT), an ultra-rare adverse event in which patients develop life-threatening blood clots 5-24 days following vaccination. To investigate vector-host interactions of ChAdOx1 underpinning VITT we solved the structure of the ChAdOx1 capsid by CryoEM, and the structure of the primary receptor tropism determining fiber-knob protein by crystallography. These structural insights have enabled us to unravel key protein interactions involved in ChAdOx1 cell entry and a possible means by which it may generate misplaced immunity to platelet factor 4 (PF4), a protein involved in coagulation. We use in vitro cell binding assays to show that the fiber-knob protein uses coxsackie and adenovirus receptor (CAR) as a high affinity binding partner, while it does not form a stable interface with CD46. Computational simulations identified a putative mechanism by which the ChAdOx1 capsid interacts with PF4 by binding in the spaces between hexon proteins, with downstream implications for the causes of VITT. SummaryWe present the structure of the ChAdOx1 viral vector, derived from chimpanzee adenovirus Y25 at 4.2[A] resolution1. ChAdOx1 is in global use in the AstraZeneca vaccine, ChAdOx1 nCoV-19/AZD-1222, to combat the SARS-CoV-2 coronavirus pandemic. Recently observed, rare, adverse events make detailed mechanistic understanding of this vector key to informing proper treatment of affected patients and the development of safer viral vectors. Here, we determine a primary mechanism ChAdOx1 uses to attach to cells is coxsackie and adenovirus receptor (CAR), a protein which is identical in humans and chimpanzees. We demonstrate the vector does not form a stable CD46 interaction, a common species B adenovirus receptor, via its primary attachment protein. Further, we reveal the surface of the ChAdOx1 viral capsid has a strong electronegative potential. Molecular simulations suggest this charge, together with shape complementarity, are a mechanism by which an oppositely charged protein, platelet factor 4 (PF4) may bind the vector surface. PF4 is a key protein involved in the formation of blood clots2, and the target of auto-antibodies in heparin-induced immune thrombotic thrombocytopenia (HITT)3, an adverse reaction to heparin therapy which presents similarly to vaccine-induced immune thrombotic thrombocytopenia (VITT), a rare complication of ChAdOx1 nCoV-19 vaccination4-6. We propose a mechanism in which the ChAdOx1-PF4 complex may stimulate the production of antibodies against PF4, leading to delayed blood clot formation, as observed in VITT.

molecular biology↗