Belgium

Arbuscular mycorrhizal fungi (AM fungi) may facilitate plants during increasingly prevalent extreme stress events such as heatwaves and drought. Heatwaves are commonly characterised by the presence of extreme temperatures and frequently co-occur with droughts or water deficits. The combination of these stressors is deleterious for plants and the role of AM fungi in ameliorating this compound stress event is not fully understood, particularly within threatened communities such as grasslands. This study has investigated the role of field-collected AM fungi in facilitating plant responses to heat and water stress using a simulated heatwave event in a factorial greenhouse experiment to test how native grassland species respond. We found that the impact of heat stress combined with water stress on plant performance was shown to be greater than the additive effects of heat and water stress in isolation. AM fungi was shown to have variable influences on plant growth, fitness, and physiological responses but these influences were commonly at odds with previous publications on AM fungi with agricultural species. Most notably, AM fungi increased the germination success of seeds of one species grown following exposure to climate stress. The results of this study highlight the dynamic role of AM fungi and help us understand grassland responses to heatwave events in the face of increasing extreme climate events. Furthermore, this study emphasises the importance of building ecologically relevant ex-situ experiments to study and understand current global pressures facing natural ecological communities.

SEB Conference 2025

Interactions of Arbuscular Mycorrhizal Fungi with Native Grassland Species Under Combined Heat and Water Stress

grass

abiotic stress

heatwaves

drought

facilitation

climate

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SEB’s Annual Conference is celebrated for creating the perfect composition of research, new discoveries and collaborative connections. Be creative and innovative by exchanging ideas and knowledge with masters of biology from all over the world. 

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Latitudinal patterns in fitness-related traits within species are getting increased attention as these inform how high-latitude populations may evolve in response to global warming. The underlying mechanisms for these latitudinal trait patterns remain poorly understood, and recently the gut microbiome has been suggested to be a potentially important proximate driver of these patterns. We investigated the novel idea whether the gut microbiome drives differences in immune function and pathogen load between slow-paced, Southern Swedish, high-latitude and fast-paced, Southern French, low-latitude populations of Ischnura elegans damselflies. A reciprocal gut microbiome transplant was performed between high- and low-latitude larvae, at both a colder and warmer thermal regime, whereafter larvae were exposed to Escherichia coli , a pathogen naturally found in aquatic ecosystems. During the experiment, larval mortality, growth rate, phenoloxidase level (a measure of immune function), E. coli burden (a measure of pathogen load), and the gut microbiome diversity (α-diversity) and community compositions (β-diversity) were analysed. Exposure to the pathogen increased mortality, especially under warming. Our results confirmed latitude-associated thermal adaptation and a faster pace-of-life of the low-latitude larvae, and revealed this to be associated with a lower immune function and higher pathogen load. Moreover, our results provided the first experimental evidence that the gut microbiome causally contributed to latitudinal differences in the host’s immune function and pathogen load. Taking into account how the gut microbiome shapes latitudinal patterns in fitness-related traits will deepen our understanding of the evolution of host populations under warming.

The gut microbiome shapes latitudinal differences in host immunity and pathogen load, and buffers against immunosuppression under future warming

The pace-of-life hypothesis predicts that intrinsic traits such as rates of metabolism and growth influence behaviour, with high-metabolism individuals expected to be bolder, more aggressive, and more exploratory. These behavioural tendencies may increase predation risk by driving individuals to forage in riskier habitats. We tested this hypothesis in a freshwater fish community by integrating metabolic assays, growth analysis, stable isotope analysis, and acoustic telemetry. Using lakeside intermittent flow respirometry, we measured routine metabolic rate (RMR) as a proxy for baseline energy expenditure. Using biopsy, we back-calculated individual rates of growth and quantified stable isotope ratios (δ13 C and δ15 N) to infer diet composition and trophic position. Fish were then implanted with predation-sensing acoustic transmitters to track movement, habitat use, and predation events in a whole-lake acoustic positioning system (Ontario, Canada). The lake was divided into habitat zones (e.g., open water, vegetated shallows, nearshore areas) to assess how individuals used risky versus safe habitats. We studied prey species (bluegill Lepomis macrochirus, pumpkinseed Lepomis gibbosus) and a predator (largemouth bass Micropterus salmoides) to characterize metabolic-behavioural syndromes and their links to diet, growth, movement, and survival. This research rigorously tests the pace-of-life hypothesis and may inform conservation efforts by identifying traits that increase vulnerability to predation and environmental change.

Predicting the behaviour of wild fish using metabolism, growth, and diet

Certain animal groups are able to capture prey in the deep ocean, where sunlight is severely limited, and each has its own strategy along with their sensory and locomotive capacities. King penguins (Aptenodytes patagonicus) have the remarkable ability to dive to depths exceeding 100 meters and capture fish in near-total darkness. However, no study has successfully recorded visual evidence of how this penguin captures its prey in deep sea, and its foraging strategies and the predator-prey interactions are largely unknown. Here, we present a successful record of king penguin’s foraging behavior and prey response in the dark ocean depths using a video logger with an LED light source (N = 1). The king penguin targeted its prey fish 0.5 to 1.5 seconds before predation by directing its head, and exhibited a high feeding success rate of 86.8% (118/136). The penguin repeatedly ascend and descend below 100 m during dives, while most feeding events (81.6%) occurred during ascent, suggesting advantages for king penguins in capturing prey from below. The prey fish remained stationary or did not attempt evasive maneuvers until 0.0 to 0.1 seconds before capture, which highlights king penguins' ability to stealthily approach their prey. In the same oceanic region, king penguins share their habitat with elephant seals and fur seals, competing for the same fish species. Understanding how penguins develop foraging strategies and how fish respond is crucial for contributing to comparative studies of foraging strategies among marine predators.

Prey-predator interactions in the deep sea between king penguin and its prey fish observed by animal-borne video camera

A prominent feature of biodiverse habitats is the acoustic landscape. Yet very little is known about the acoustic landscapes of extinct environments, for example of a Jurassic Forest. One problem is that recovering the real acoustic features of extinct tetrapods is challenging, as their vocal organs do not readily fossilize. Conversely, the stridulating organs present in the sclerotised cuticle of some arthropods do fossilise well. For example, the stridulatory structures (a file, plectrum, and sound radiating membranes) in the forewings of male crickets and katydids are preserved in fossils, offering a unique opportunity to investigate species diversification and the acoustic landscapes of the past. Integrating experimental and numerical procedures, several katydid fossils (of nine species) were studied to recreate the acoustic landscape of the mid Jurassic (Inner Mongolia, China). Wing vibration and calling songs of these fossils were recovered and validated. Jurassic katydids used sharp pure-tones (musical) calls, which made localization by eavesdropping predators difficult. While 60% of these species communicate in the low audio range 5-7 kHz, one species exploited ultrasounds (>20kHz). Results imply that ultrasonic communication in insects was established long before the emergence of bats. The results extend current understanding of the Jurassic soundscape, revealing insect song and hearing diversity, but also highlighting the co-evolutionary pressures and constraints exerted by ultrasound sensitive eavesdropping insectivorous predators other than bats. Such arm race is proposed as one of the main pressures that boosted the evolution of the mammalian cochlea and the sophisticated ‘insect cochlea’ shown by living katydids.

The reconstruction of an extinct Jurassic soundscape

Penetrative tracks preserve significant information regarding foot motion due to the increased interaction between the foot and the sediment. Using surface and subsurface track morphology of a fossil track, the motion used by extinct animals can be experimentally replicated via testable hypotheses of motion. However, track morphology varies with sediment consistency, potentially affecting the reliability of these reconstructed motions. While track morphology at the surface is well known to vary with substrate consistency, the effect on the more constrained subsurface morphology is poorly understood. Using Discrete Element Method simulations, we examined the variability of subsurface track morphology with changes to sediment consistency. Two model systems were utilized; a simple cylinder vertically indenting, and a dynamic, simplified foot for which motions were reconstructed using an early Jurassic penetrative dinosaur track. Increasing sediment friction (reducing ‘flowability’) resulted in higher and more extensive displacement rims throughout the track volume. Increased cohesion led to tracks remaining open at and below the original surface, rather than subsurface tracks infilling with sediment from above as was seen in lower cohesion traces. However, tracks exposed along subsurface layers had morphologies which were considerably more robust to changes in sediment properties than the true surface tracks. This provides confidence that foot motions recovered from penetrative tracks can be accurate regardless of sediment consistency at the time of track formation and may therefore offer more reliable information about foot motion than surface tracks.

Track morphology and sediment parameters: motion recovered from subsurface layers are robust to changes in substrate properties

The clade of boxfish (Ostraciidae and Aracanidae) are reef-dwelling fish that share a unique feature, the carapace. The body of Ostraciidae is completely covered by a bony shell of fused hexagonal plates. In Aracanidae, the carapace also covers the body, but is not completely closed at the caudal peduncle for some of the species. The carapace provides protection against predators, but its shape also defines their hydrodynamic characteristics. Among the many extant species, shapes vary between boxes with major lateral keels, over wedges with dorsal and ventrolateral keels, to more disc-like shapes with major dorsoventral keels. Here, we studied how hydrodynamic performance differs among twenty-nine species of boxfish. Drag forces and pitch and yaw moments were calculated using computational fluid dynamics simulations based on 3D laser-scans of museum specimens, which were all digitally rescaled to the same carapace volume. Up to 40% difference was observed between boxfish species with the lowest drag force and those with the highest drag force. We determined that Aracanidae have a significantly higher drag force than Ostraciidae. Additionally, we found a strong positive correlation between drag force and frontal-projected area and a negative correlation between drag force and carapace length. The strong variability in drag force related to the degree of axial compression of boxfish shapes, together with the relatively high coefficients of drag in boxfish in general, suggests that weak selection pressures on drag-reduction are common in this group.

Variation in hydrodynamic performance among boxfish carapace shapes

In aquatic ecosystems, the growth and physiology of species are profoundly influenced by trophic interactions and environmental conditions, especially light and food sources. Daphnids, commonly known as water fleas, have a central role in freshwater ecosystems due to their wide distribution, crucial position in food webs, and sensitivity to environmental changes. In this study, we focused on the impact of food quality and light conditions on lifespan, growth, reproduction, and metabolic responses of daphnids. Frozen algae food is a less nutritious source that led to slower growth, reduced reproduction, and induced metabolic restrictions, while deprivation of light induced distinct metabolic changes, suggesting disruptions in circadian rhythms. These changes point to potential impacts on broader ecological interactions and metabolic efficiency.
Our research highlights the importance of food quality and light in shaping aquatic organisms’ physiology, providing insights into the ecological and metabolic processes that govern freshwater species. The study’s results could inform broader ecological models and risk assessments, emphasising the interconnectedness of environmental factors on aquatic species' health and ecosystem dynamics.

Molecular approaches unravel the impact of food quality and light on the physiology of daphnids 

Per- and polyfluoroalkyl substances (PFAS), widely used in industries and consumer products, often contaminate marine environments, posing potential risks to wildlife and humans. Their bioaccumulation and toxicity have led to global concern, particularly with the emergence of short-chain PFAS as alternatives to restricted legacy compounds. However, limited information exists on their environmental fate and toxicity, necessitating further research on their effects on marine organisms, particularly bivalves.
This study investigates the toxicity of six PFAS (short-chain: PFHxA, 6:2 FTA; long-chain: PFUnDA, PFDoA, PFTriDA, PFTeDA) in the digestive gland (DG) and gills (G) of Mytilus galloprovincialis, a key bioindicator, through in vitro exposure. To understand early toxicity mechanisms, biochemical responses related to oxidative stress and neurotransmission were assessed.
The results indicated organ-specific effects, with the DG demonstrating heightened sensitivity to PFHxA, evidenced by a reduction in total antioxidant capacity. Conversely, PFTriDA exhibited a propensity to induce cellular damage at elevated concentrations. Gills exhibited a heightened response to PFDoA and PFTeDA, manifesting as the inhibition of antioxidant enzymes resulting in oxidative stress. Additionally, PFHxA and PFTriDA were observed to exert neurotoxic effects through the inhibition of acetylcholinesterase. Among all compounds, 6:2 FTA was the least toxic, while PFHxA was the most toxic.
These findings highlight the complexity of PFAS toxicity and the need to assess short- and long-chain compounds to establish safe environmental thresholds. M. galloprovincialis proves to be a valuable bioindicator, reinforcing the need for regulatory measures to mitigate PFAS pollution while providing insights into organ-specific toxicity and environmental exposure pathways.

Revealing Hidden Risks: In Vitro Analysis of PFAS Hazards in Mytilus galloprovincialisGills and Digestive Gland

Optimizing radiation use efficiency (RUE) is essential for increasing wheat crop yields. Conventional RUE measurements rely on the dynamics of above-ground biomass (AGB) and intercepted photosynthetic active radiation (IPAR). It therefore suffers from low throughput, hindering large-scale phenotyping of RUE for crop improvement. In this study, we propose a high-throughput phenotyping method utilizing multi-view RGB cameras to estimate RUE in wheat crops in the field. Initially, a deep semantic segmentation model assesses the green fraction (GF) from zenith angle 0° and 45° RGB images, denoted as GF(0°) and GF(45°). Subsequently, employing the digital plant phenotyping platform from our prior work, we generate a synthetic dataset with 10,000 simulations, including GF(0°) and GF(45°), along with the corresponding green area index (GAI) and fraction of intercepted PAR (FIPAR). This synthetic dataset facilitates training a Gaussian Process Regression model to estimate GAI and FIPAR based on GF(0°) and GF(45°). Consequently, the accumulation of intercepted PAR is computed from FIPAR dynamics, and AGB is estimated from GAI using the allometric growth law developed in our previous work. Finally, RUE is estimated by fitting a linear regression between biomass dynamics and accumulated IPAR. Our high-throughput phenotyping method for RUE was implemented on a wheat population exceeding 500 genotypes across three sites. This approach successfully identified key genes strongly associated with the photosynthetic process, validating the reliability of our algorithm. In summary, our algorithm, requiring observations from only two RGB cameras, significantly enhances feasibility and throughput for application in wheat breeding programs.

High-Throughput Phenotyping the Radiation Use Efficiency of Wheat Crops in the Field

Tomato (Solanum lycopersicum) is among the world’s most important crops, yet its cultivation is increasingly threatened by climate change. Traditional destructive analyses can accurately classify stress symptoms, but novel Artificial Intelligence driven approaches offer promising solutions for early abiotic stress detection through computer vision. This study integrates image-derived traits with laboratory-based physiological parameters within a machine learning framework to classify, identify, and quantify the responses of two dwarf tomato cultivars (Microtom and Tiny Tim) under long-term drought and salinity conditions, at increasing intensities. RGB and PAM chlorophyll fluorescence imaging were combined with biochemical assays, including pigment content (chlorophylls and carotenoids), malondialdehyde (MDA) content, relative water content (RWC), and electrolyte leakage (EL). Notably, color indices exhibited significant shifts in pixel distribution peaks across treatments, highlighting their sensitivity to stress-induced physiological changes. Moreover, cultivar-specific differences at 7 and 14 Days After Stress (DAS) suggested genetic variability in stress responses. Based on these multi-source features, various decision tree-based models were trained, tested, and evaluated. The binary presence/absence classifier achieved the highest accuracy (precision=0.87, recall=0.97, F-measure=0.92), outperforming more complex models designed to differentiate and quantify stressors. As classification complexity increased, image-derived features—particularly geometrical (e.g., area, perimeter), colorimetric (e.g., chroma indices), and fluorescence-based traits (e.g., NPQ)—became more influential, while laboratory-derived attributes (e.g., RWC) had reduced importance. These findings underscore the potential of digital traits as reliable, non-destructive indicators for early stress monitoring in tomato plants. Future research will refine and generalize this AI-based framework to enhance its robustness, scalability, and applicability in field studies.

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