Biology subjects

Kasper, J.

Publications and source records attributed to Kasper, J..

7 recordsLinked to original sources

bioRxiv2026

New Zealand spider orchid (Corybas trilobus) exploits the reproductive behaviour of fungus gnats (Diptera: Mycetophila) for pollination.

Due to a reduce pollinator diversity, plant-pollinator interactions in remote habitats are commonly unspecialised. In New Zealand (NZ), many plants exhibit a generalist pollination syndrome where flowers are open-access and pollinated by a range of insects. Orchids in the genus Corybas seem to be the exception. It is believed they mimic mushrooms and their pollination occur by brood-site deception. This study aims to uncover whether this pollination strategy operates in a form of Corybas trilobus known by the tag-name Corybas Remutaka. We used hand-pollination experiments to determine the breeding system of this orchid. SEM observations and neutral red staining were used to study the floral micro-morphology and location of scent glands, respectively. Pollinators behaviour was observed, and filmed, in the field and ex situ. Olfactory signals were assessed using solid-phase micro-extraction and solvent extractions, and visual cues by photography with a UV sensor. Only hand self- and cross-pollinated flowers formed capsules, while natural fruit-set was low. Male and female individuals of the endemic fungus gnat Mycetophila phyllura (Diptera) were the only pollinators observed. Both sexes can remove and deposit pollinia. None of the typical fungal compounds, or other compounds linked to brood-site deception, were detected in the orchid but a prevalence of alkane, sesquiterpene and fatty aldehydes. Some of these compounds were also detected in a mushroom used by fungus gnats for mating and ovipositioning. Features in the labellum surface and base (e.g. exit holes) and UV reflectance may help directing movement of the gnats within the flower. Corybas Remutaka is a self-compatible, nectarless, pollinator-dependent orchid that relies on a mix of volatiles and micro-morphological features to attract a specific pollinator. The orchid exploits the reproductive instinct of male and female fungus gnats to secure its pollination. This deceptive pollination strategy combines features of rendezvous site pollination and brood-site deception.

plant biology↗

bioRxiv2026

Passive Acoustic Monitoring within the Northwest Forest Plan Area: 2025 Annual Report

The Northwest Forest Plan (NWFP) Passive Acoustic Monitoring (PAM) program is a large-scale interagency biodiversity monitoring framework designed to assess the status and trends of northern spotted owls (Strix occidentalis caurina), barred owls (Strix varia), marbled murrelets (Brachyramphus marmoratus), and broader forest biodiversity across federally administered lands in the Pacific Northwest. In 2025, we deployed autonomous recording units at 2,095 sampling stations within 532 5-km2 hexagons randomly selected across approximately 24 million acres of federal forest lands in Washington, Oregon, and California. These deployments generated 1.37 million hours of acoustic recordings that we processed using the convolutional neural network PNW-Cnet v5 for automated species identification and subsequent human validation of focal species detections. Northern spotted owls were detected in 28% of sampled hexagons range-wide, including 16% in Washington, 25% in Oregon, and 60% in California. Occupancy patterns remained consistent compared to previous years, with higher occupancy concentrated in southern portions of the geographic range and continued low occupancy across much of the Washington Cascades and Oregon Coast Range. Barred owls were detected in 86% of sampled hexagons and remained broadly distributed throughout most of the NWFP area. Marbled murrelets were detected in 50% of reviewed hexagons within NWFP marbled murrelet management zones, with highest occupancy occurring in coastal forests of Oregon and Washington. The 2025 field season occurred under substantial operational constraints that reduced sampling effort by approximately half relative to 2023 and 2024 because of staffing limitations affecting participating federal agencies. Despite these reductions, the NWFP-PAM framework continued to provide broad-scale, spatially representative ecological information across the NWFP area. Results highlight the growing importance of passive acoustic monitoring and machine learning approaches for long-term biodiversity monitoring under changing environmental and operational conditions.

ecology↗

bioRxiv2025

Passive Acoustic Monitoring within the Northwest Forest Plan Area: 2024 Annual Report

Passive acoustic monitoring (PAM) has become the primary framework for assessing the status, distribution, and habitat associations of forest-dependent wildlife under the Northwest Forest Plan (NWFP). In 2024, the NWFP PAM program continued to operate as a fully integrated, range-wide monitoring network, building on deployments initiated in 2018 and now conducting surveys across approximately 24 million acres of federal land. Using a randomized 2+20% sampling design, more than 4,000 autonomous recording units generated over 2 million hours of acoustic data analyzed with convolutional neural networks, enabling statistically rigorous inference at regional and range-wide scales. This report summarizes 2024 field efforts and analytical advancements in the context of recent peer-reviewed and in-progress studies. Updated analyses confirm persistent, low occupancy of northern spotted owls (Strix occidentalis caurina), with detections concentrated in the Klamath Mountains and southern Cascades, consistent with long-term demographic declines. Range-wide models of barred owl (Strix varia) landscape use continue to show high occupancy across much of the NWFP area, reinforcing competitive displacement as the dominant driver of spotted owl range contraction. The PAM network also advanced monitoring of marbled murrelets (Brachyramphus marmoratus), with 2024 results supporting PAM as a cost-efficient alternative to traditional audio-visual surveys for assessing inland nesting habitat use in coastal forests. Beyond focal species, the program increasingly supports multi-taxa biodiversity monitoring through bioacoustic bycatch and soundscape analyses, linking species occurrence, habitat condition, and disturbance dynamics. Collectively, 2024 results demonstrate that PAM has reached operational maturity as the cornerstone of Phase II NWFP effectiveness monitoring. Sustaining adequate sampling effort and field capacity remains a challenge but essential, as reduced deployment intensity would increase uncertainty and weaken inference. Continued investment in PAM infrastructure and expertise is critical for informing adaptive management, supporting sustainable timber harvest, and evaluating ecosystem resilience under changing disturbance regimes.

ecology↗

bioRxiv2025

Passive Acoustic Monitoring within the Northwest Forest Plan Area: 2023 Annual Report

Here we document progress in implementing large-scale passive acoustic monitoring across the Northwest Forest Plan area to track population trends of northern spotted owls (Strix occidentalis caurina), barred owls (S. varia), marbled murrelets (Brachyramphus marmoratus), and a broad array of forest-adapted wildlife. In 2023, we deployed 4,012 autonomous recording units across 1,009 randomly selected 5-km{superscript 2} hexagons, generating nearly 2.2 million hours of recordings, representing approximately 1 petabyte of acoustic data. These data were processed with PNW-Cnet v5, the latest version of our convolutional neural network model, trained on 135 sound classes representing over 80 species and environmental sounds. Model performance demonstrated high precision for focal species and many additional taxa, substantially reducing manual review effort while enabling broad-scale biodiversity assessments. Results confirmed northern spotted owl detections in all 20% sample areas, with occupancy varying geographically and declining notably in the Tyee study area. Barred owls were widely detected, with the highest prevalence in Oregon and Washington and comparatively lower occupancy in California. Marbled murrelets were consistently detected in coastal areas, particularly the Olympic Peninsula and Oregon Coast Range. Beyond these focal species, PAM and PNW-Cnet generated robust datasets for a wide range of birds, mammals, and disturbance indicators, underscoring the value of random-site, multi-species monitoring. The 2023 field season marked the first full implementation of the 2% + 20% NWFP sampling design, expanding monitoring coverage while strengthening collaborations with federal and state partners. These efforts provide the foundation for long-term, cost-effective wildlife monitoring and inform conservation strategies in dynamic forest ecosystems.

ecology↗

bioRxiv2024

Can we predict sleep health based on brain features? A large-scale machine learning study

BackgroundsSeveral correlational or group comparison evidence highlighted robust associations between sleep health and macro-scale brain organization. However, inter-individual variability is critical in such interplay. Therefore, in this study, we aimed to investigate the role of brain imaging features in predicting diverse sleep health-related characteristics at the individual subject level using the Machine Learning (ML) approach. MethodsA sample of 28,088 participants from the UK Biobank was employed to calculate 4677 structural and functional neuroimaging markers. Then, we employed them to predict self-reported insomnia symptoms, sleep duration, easiness of getting up in the morning, chronotype, daily nap, daytime sleepiness, and snoring. To assess the predictability of brain features, we built seven different linear and nonlinear ML models for each sleep health-related characteristic. ResultsWe performed extensive ML analyses that involved more than 19 years of compute time. We observed relatively low performance in predicting all sleep health-related characteristics from brain images (e.g., balanced accuracy ranging between 0.50-0.59). Across all models, the best performance achieved was 0.59, using a linear ML model to predict the ease of getting up in the morning. In fact, a similar performance was achieved with models trained solely on age and sex, indicating that these demographic factors might be the ones driving the predictions. ConclusionsThe low capability of multimodal neuroimaging markers in predicting sleep health-related characteristics, even under extensive ML optimization in a large population sample, suggests a complex relationship between sleep health and brain organization.

neuroscience↗

bioRxiv2023

Resting state changes in aging and Parkinson's disease are shaped by underlying neurotransmission - a normative modeling study

Human healthy and pathological aging is linked to a steady decline in brain resting state activity and connectivity measures. The neurophysiological mechanisms underlying these changes remain poorly understood. Making use of recent developments in normative modeling and availability of in vivo maps for various neurochemical systems, we test in the UK Biobank cohort (N=25,917) if and how age- and Parkinsons disease related resting state changes in commonly applied local and global activity and connectivity measures co-localize with underlying neurotransmitter systems. We find the distributions of several major neurotransmitter systems including serotonergic, dopaminergic, noradrenergic and glutamatergic neurotransmission to explain age-related changes as observed across functional activity and connectivity measures. Co-localization patterns in Parkinsons disease deviate from normative aging trajectories for these, as well as for cholinergic and GABAergic neurotransmission. The deviation from normal co-localization of brain function and GABAa correlates with disease duration. These findings provide new insights into molecular mechanisms underlying age- and Parkinsons related brain functional changes. Combining normative modeling and neurotransmitter mapping may aid future research and drug development through deeper understanding of neurophysiological mechanisms underlying specific clinical conditions.

neuroscience↗

bioRxiv2023

Is resting state fMRI better than individual characteristics at predicting cognition?

Changes in spontaneous brain activity at rest provide rich information about behavior and cognition. The mathematical properties of resting-state functional magnetic resonance imaging (rsfMRI) are a depiction of brain function and are frequently used to predict cognitive phenotypes. Individual characteristics such as age, gender, and total intracranial volume (TIV) play an important role in predictive modeling of rsfMRI (for example, as "confounders" in many cases). It is unclear, however, to what extent rsfMRI carries independent information from the individual characteristics that is able to predict cognitive phenotypes. Here, we used predictive modeling to thoroughly examine the predictability of four cognitive phenotypes in 20,000 healthy UK Biobank subjects. We extracted common rsfMRI features of functional brain connectivity (FC) and temporal complexity (TC). We assessed the ability of these features to predict outcomes in the presence and absence of age, gender, and TIV. Additionally, we assessed the predictiveness of age, gender, and TIV only. We find TC and FC features to perform comparably with regard to predicting cognitive phenotypes. As compared to rsfMRI features, individual characteristics provide systematically better predictions with smaller sample sizes and, to some extent, in larger cohorts. It is also consistent across different levels of inherent temporal noise in rsfMRI. Our results suggest that when the objective is to perform cognitive predictions as opposed to understanding the relationship between brain and behavior, individual characteristics are more applicable than rsfMRI features.

neuroscience↗