Biology subjects

Gibb, R.

Publications and source records attributed to Gibb, R..

14 recordsLinked to original sources

bioRxiv2026

Contributions of human-caused climate change and individual emitters to global coral bleaching

Coral bleaching is among the most infamous climate impacts. Yet the extent of bleaching due to human-caused climate change, as opposed to natural El Nino variability, and the contributions of individual countries and carbon majors (fossil fuel and cement producers) remains unquantified. Here, we leverage coral monitoring globally across 4,479 sites from 1985-2024 to link specific emitters to marine heat stress and bleaching. For events with >10% of corals bleached at a site, we find that 99% (95% CI: 88-100%) were attributable to human-caused climate change. Even during major El Ninos, 97-100% of bleaching events were attributable to human-caused climate change and the extent of damage increases over time from 23% of sites bleached (95% CI: 3-35%) during 1998 to 71% of sites (95% CI: 37-85%) during 2023-2024. Emissions of the United States, the largest historical emitter, contributed to 51% (95% CI: 39-65%) of bleaching events. Emissions linked to Chevron, Saudi Aramco, Gazprom, and ExxonMobil each contributed to 14% (95% CI: 11-19%) of bleaching events -- roughly double the contribution of the 39 countries of the Alliance for Small Island States. It is virtually certain emissions of China, the United States, and Indonesia caused bleaching in their coastal waters. Strong inequalities exist where countries with high socioeconomic dependence on coral reefs experienced 54% of bleaching yet contributed only 5% to bleaching. As global warming rapidly nears levels catastrophic for warm-water corals, our results show the massive contribution from anthropogenic emissions to historical coral beaching and help fill an important evidentiary gap on accountability for non-economic loss and damage from climate change.

ecology↗

bioRxiv2025

Evidence of ecosystem process recovery across a large-scale coral reef restoration programme using AI accelerated soundscape analysis

1.Coral reef restoration efforts are on the increase globally. However, reporting on the ecological outcomes of these efforts is rare and typically focuses on coral related metrics. As a result, understanding of whether restoration can recover broader aspects of reef functioning remains limited. In this study we use passive acoustic monitoring coupled with human-in-the-loop artificial intelligence to analyse >12 months of soundscape recordings from 45 sites across five biogeographically independent regions to investigate the impact of active restoration on reef functioning. We trained and rigorously evaluated machine learning models to identify 34 biological sound types within this data, generating >912,000 high-confidence detections. These detections were used to infer four key functions across healthy, degraded, early-stage (<3 months) and mid-stage (32-53 months) restored reefs. Restoration significantly enhanced: (i) biological sounds at night, key to recruiting juvenile fish; (ii) diversity of biological sounds, an indicator of fish community diversity; and (iii) snapping shrimp activity, an indicator of bioturbation. However, effects varied by region, and audible parrotfish grazing, key to algal control and bioerosion, did not differ among habitat types in four of the five regions. Our findings provide evidence that restoration can support recovery of broader ecosystem functioning when carefully implemented in the right contexts. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/678197v4_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@7d5462org.highwire.dtl.DTLVardef@2efa7dorg.highwire.dtl.DTLVardef@3f4b9eorg.highwire.dtl.DTLVardef@17d829c_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2025

Contact networks of small mammals highlight potential transmission foci of Lassa mammarenavirus.

Lassa fever (Mammarenavirus lassaense; LASV), is an endemic zoonosis in West Africa. Human infections arise from rodent-to-human transmission, mainly from the synanthropic reservoir Mastomys natalensis. In Sierra Leone, small-mammal communities vary across land use gradients, shaping LASV transmission risk. How anthropogenic environments facilitate the rodent-rodent interactions remains poorly understood. We sampled small mammals over 43,266 trap nights in Sierra Leones LASV-endemic Eastern Province, detecting 684 rodents and shrews. To assess potential transmission, we constructed space-sharing networks from co-trapping events within species-specific home range radii. These networks approximated shared space use, allowing comparison of encounter patterns across habitats. Network topology varied significantly by land use. Village networks were the most connected (highest average degree), whereas agricultural communities supported the most species (higher rarefied richness) and were the most fragmented (higher modularity). Notably, the probability of intraspecific space sharing among M. natalensis was highest in agriculture, suggesting land use modulates key intra-specific transmission pathways. LASV seroprevalence was 5.7% community-wide, with antibodies in nine species. We found no statistically significant association between overall seroprevalence and land use or aggregate network structure (mean degree). However, predictive modeling for M. natalensis indicated that higher individual degree is associated with seropositivity, suggesting complex, scale-dependent relationships. These findings show that simple ecological drivers do not fully explain LASV exposure, highlighting the importance of species-specific behaviors (i.e., M. natalensis clustering in agriculture) and the multi-host serological landscape in assessing transmission risk.

ecology↗

bioRxiv2024

Bilingualism Modulates Executive Function Development in Pre-School Aged Children: A Preliminary Study

This preliminary study was conducted to explore the effects of bilingualism on executive function development in children ages 3-5-years old. Two groups (bilinguals and monolinguals) were recruited across various sites in Southern Alberta. Children were assessed through parent rated executive function using the Behaviour Rating Inventory of Executive Function - Preschool version, a standardized assessment of executive function in children aged 2 years, 0 months through 5 years, 11 months. The questionnaire contains 63 items measuring 5 aspects of executive functioning, inhibit, shift, emotional control, working memory, and plan/organize. Children were also assessed using a battery of executive function tasks, which include the reverse categorization, pictorial Stroop, Dimensional Change Card Sort, backward digit span, and dyadic social play. Results show that bilingual children outperform monolinguals on the emotional control scale, dimensional change card sort and dyadic social play. Despite the controversial literature surrounding bilingualisms impact on executive function, the study reveals support for second language use to improve areas of executive function among young children.

neuroscience↗

bioRxiv2024

Behavioral and anatomical effects of complex rearing after day 7 neonatal frontal lesions vary with sex

Rats received medial frontal lesions, or sham surgery, on postnatal day 7 (P7), and were placed in complex environments or standard lab housing at weaning. Three months later the animals were tested in a spatial learning task and in a skilled reaching task. Rats with P7 lesions had smaller deficits in spatial learning than similar adult operates, and males performed better than females. Complex housing further improved the performance of male, but not female, lesion rats. The opposite was seen in motor performance as female lesion rats performed better than males and benefited from experience whereas males did not. There was a correlation between behavior and dendritic change as complex housing reversed lesion-induced dendritic atrophy, an effect that was greater in males. P7 frontal males, but not females, showed an increase in spine density that was reversed by complex housing. Experience thus can affect functional and anatomical outcome after early brain injury, but the effects vary with sex.

neuroscience↗

bioRxiv2023

Viral genomic features predict orthopoxvirus reservoir hosts

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs. We demonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range.

microbiology↗

bioRxiv2022

Functional recovery from tactile stimulation after perinatal cortical injury is mediated by FGF-2

The consequences of perinatal brain injury can be devastating but currently there are few effective treatments. We sought to determine if tactile stimulation (TS) or exogenous application of fibroblast growth factor-2 (FGF-2) following injury could reverse the behavioral loss. Infant rats received frontal cortex removals on postnatal day 4 (P4) or a sham surgery. The TS animals received thrice-daily 15-minute bouts of stimulation (Experiment 1) on the day following surgery until weaning. In Experiment 2, treated animals received subcutaneous injections of FGF-2 once daily for one week, postsurgery. Behavioral testing began on postnatal day 60. Brains were later processed for Golgi analysis. We show in Experiment 1, that tactilely stimulating infant rats with perinatal cortical injury stimulates functional recovery and reverses injury-related changes in neuronal morphology in the cerebral cortex. The TS induction of recovery is associated with changes in expression of FGF-2 in both the skin and brain. Direct administration of FGF-2 (Experiment 2) is also effective in facilitating recovery, although not as completely as TS. These results suggest that early behavioral intervention after perinatal cortical injury can stimulate plastic neuronal changes that can underlie functional recovery and that these changes are mediated, in part, through an upregulation of FGF-2.

neuroscience↗

bioRxiv2021

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data form the backbone of research into eco-evolutionary drivers of viral diversity and host-level zoonotic risk. However, knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6,571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are still either constant or accelerating, with little evidence of declines towards viral richness asymptotes in even highly-sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species ranked viral richness. Our results show that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since our findings suggest that an analysis conducted today could feasibly draw quite different conclusions than one conducted only a decade ago.

ecology↗

bioRxiv2021

Data proliferation, reconciliation, and synthesis in viral ecology

The fields of viral ecology and evolution have rapidly expanded in the last two decades, driven by technological improvements, and motivated by efforts to discover potentially zoonotic wildlife viruses under the rubric of pandemic prevention. One consequence has been a massive proliferation of host-virus association data, which comprise the backbone of research in viral macroecology and zoonotic risk prediction. These data remain fragmented across numerous data portals and projects, each with their own scope, structure, and reporting standards. Here, we propose that synthesis of host-virus association data is a central challenge to improve our understanding of the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open reconciled mammal-virus database from four key published datasets, applying a standardized taxonomy and metadata. We show that reconciling these datasets provides a substantially richer view of the mammal virome than that offered by any one individual database. We argue for a shift in best practice towards the incremental development and use of synthetic datasets in viral ecology research, both to improve comparability and replicability across studies, and to facilitate future efforts to use machine learning to predict the structure and dynamics of the global virome.

ecology↗

bioRxiv2021

Urban-adapted mammal species have more known pathogens

The world is rapidly urbanising, inviting mounting concern that urban environments will experience increased zoonotic disease risk. Urban animals could have more frequent contact with humans, and therefore may transmit more zoonotic parasites; however, these animals have a specific set of underlying traits that may determine their parasite burdens while predisposing them to urban living, and they may be subject to more intense research effort, both of which could complicate our ability to reliably identify the role of urbanisation in driving zoonotic risk. Here, we test whether urban mammal species host more known zoonotic parasites, investigating the potential underlying drivers while accounting for a correlated suite of phenotypic, taxonomic, and geographic predictors. We found that urban-adapted mammals have more documented parasites, and more zoonotic parasites specifically: despite comprising only 157 of the 2792 investigated species (6%), urban mammals provided 39% of known host-parasite combinations and showed consistently higher viral discovery rates throughout the last century. However, contrary to predictions, much of the observed effect was attributable to research effort rather than to urban adaptation status itself, and urban-adapted species in fact hosted fewer zoonoses than expected given their total observed parasite richness. We conclude that extended historical contact with humans has had a limited impact on the number of observed zoonotic parasites in urban-adapted mammals; instead, their greater observed zoonotic richness likely reflects sampling bias arising from proximity to humans, which supports a near-universal underlying pattern of conflation between zoonotic risk, research effort, and synanthropy. These findings underscore the need to resolve the ecological mechanisms underlying links between anthropogenic change, sampling bias, and observed wildlife disease dynamics.

ecology↗

bioRxiv2020

Data-driven analysis of rat pup behavior reveals novel effects of maternal pre-conception exposure to nicotine

We present a deep neural network for data-driven analyses of infant rat behavior in an open field task. The network was applied to study the effect of maternal nicotine exposure prior to conception on offspring motor development. The neural network outperformed human expert designed animal locomotion measures in distinguishing rat pups born to nicotine exposed dams versus control dams. Notably, the network discovered novel movement alterations in posture, movement initiation and a stereotypy in "warm-up" behavior (the initiation of movement along specific dimensions) that were predictive of nicotine exposure. The results suggest that maternal preconception nicotine exposure delays and alters offspring motor development. In summary, we demonstrated that a deep neural network can automatically assess animal behavior with high accuracy, and that it offers a data-driven approach to investigating pharmacological effects on brain development. SignificanceRelating neuronal activity to behavior is crucial to understand brain function. Despite the staggering progress in monitoring brain activity, behavioral analyses still do not differ much from methods developed 30-50 years ago. The reason for that is the difficulty for automated video analyses to detect small differences in complex movements. Here we show that applying deep neuronal networks for automated video analyses can help to solve this problem. More importantly, knowledge extracted from the network allowed to identify subtle changes in multiple behavioral components, which were caused by maternal preconception nicotine exposure in rat pups. Thus, the examples presented here show how neuronal networks can guide the development of more accurate behavioral tests to assess symptoms of neurological disorders.

neuroscience↗

bioRxiv2019

Differential effects of emerging broad-spectrum streetlight technologies on landscape-scale bat activity

Urbanization has greatly reduced the extent of high quality habitat available to wildlife with detrimental consequences documented across a range of taxa. Roads and artificial lighting regimes are dominant features of the modern environment, and there is currently a rapid worldwide transition towards energy-efficient, broad-spectrum white-light streetlight technologies such as metal halide (MH) and more recently, light-emitting diode (LED), despite little being known about their broad ecological impacts. Here, in a five-year citizen science study across the island of Jersey, we combine detailed lighting and habitat data with ultrasonic bat survey data collected from 2011 to 2015 (before and after a LED lighting technology transition), to analyse the landscape-scale effects of different broad-spectrum streetlight technologies on activity of a widespread, generalist bat species. In contrast to many experimental studies, we show that the local density of both traditional yellow high-pressure sodium (HPS) and more modern LED streetlights have significant negative effects on activity of the common pipistrelle (Pipistrelluspipistrellus) compared to unlit areas, while accounting for spatial bias, bat population trends over time, surrounding habitat type and road-type. In contrast, we find no discernable impact of the density of ultra-violet emitting MH lighting on bat activity. This is the first large-scale evidence that emerging artificial lighting technologies have differential impacts on activity, even for a bat species generally characterised as light-tolerant and commonly found in urban areas. Importantly, our landscape-level approach also demonstrates that the degree of urbanization and road type have even larger negative impacts on bat activity, independent of artificial lighting regime. Our findings emphasise the need for improving landscape-scale understanding of the ecological impacts of new lighting technologies prior to widespread uptake, and have important implications for future streetlight installation programmes and urban planning more generally.

ecology↗

bioRxiv2018

Visual field advantage: Redefined by training?

In 1990, Fred Previc postulated that most peri-personal space interactions occurred in the lower visual field (LVF), leading to an advantage when compared to the upper visual field (UVF). It is not clear if extensive practice can affect the difference between interactions in the LVF/UVF. We tested male and female basketball varsity athletes and non-athletes on a DynaVision D2 visuomotor reaction task. We recruited basketball players because in their training they spend significant amount of time processing upper visual field information. We found a lower visual field advantage in all participants, but this advantage was significantly reduced in the athletes. The results suggest that training can be a powerful modulator of visuomotor function.

neuroscience↗

bioRxiv2017

Bat Detective - Deep Learning Tools for Bat Acoustic Signal Detection

O_LIPassive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings.\nC_LIO_LIWe developed a convolutional neural network (CNN) based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats (BatDetect). Our deep learning algorithms (CNN FULL and CNN FAST) were trained on full-spectrum ultrasonic audio collected along road-transects across Romania and Bulgaria by citizen scientists as part of the iBats programme and labelled by users of www.batdetective.org. We compared the performance of our system to other algorithms and commercial systems on expert verified test datasets recorded from different sensors and countries. As an example application, we ran our detection pipeline on iBats monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system.\nC_LIO_LIHere, we show that both CNNFULL and CNNFAST deep learning algorithms have a higher detection performance (average precision, and recall) of search-phase echolocation calls with our test sets, when compared to other existing algorithms and commercial systems tested. Precision scores for commercial systems were reasonably good across all test datasets (>0.7), but this was at the expense of recall rates. In particular, our deep learning approaches were better at detecting calls in road-transect data, which contained more noisy recordings. Our comparison of CNNFULL and CNNFAST algorithms was favourable, although CNNFAST had a slightly poorer performance, displaying a trade-off between speed and accuracy. Our example monitoring application demonstrated that our open-source, fully automatic, BatDetect CNNFAST pipeline does as well or better compared to a commercial system with manual verification previously used to analyse monitoring data.\nC_LIO_LIWe show that it is possible to both accurately and automatically detect bat search-phase echolocation calls, particularly from noisy audio recordings. Our detection pipeline enables the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale, particularly when combined with automatic species identification. We release our system and datasets to encourage future progress and transparency.\nC_LI

ecology↗