Biology subjects

Mostert, P.

Publications and source records attributed to Mostert, P..

6 recordsLinked to original sources

bioRxiv2026

Addressing Data Fragmentation in Biodiversity: A Workflow for integrated Species Distribution Models

AimA comprehensive understanding of the spatial distribution of biodiversity is hindered by fragmented datasets, sampling biases, and inconsistent observation protocols. Here, we present a workflow that integrates disparate datasets to produce large scale maps of biodiversity metrics as a basis for management-relevant information tools. We use integrated species distribution modeling (iSDM) to account for sampling biases and disparate data collection techniques, taking advantage of the vast numbers of open datasets available in data aggregators like GBIF. LocationNorway (excluding Svalbard and Jan Mayen) TaxonVascular plants MethodsThe workflow consists of four main steps: data acquisition, data integration, integrated species distribution modelling (iSDM), and the production of derived outputs. Input data include structured surveys, opportunistic observations, and environmental covariates. These are standardised and integrated into a point-processed based iSDM framework to produce species richness maps, associated uncertainties, and sampling effort maps. The outputs are further processed to identify biodiversity hotspots or to summarise species-environment relationships. The workflow used vascular plant data from Norway, combining occurrence-only and presence-absence datasets with environmental covariates. Outputs were generated at a spatial resolution of 500 x 500 meters, balancing accuracy, computational feasibility and relevance for management decisions. High-performance computing resources were utilized for model fitting and predictions. A subset of available data was used to validate the species richness maps. ResultsWe produced detailed maps of species richness, uncertainties and sampling intensity across Norways heterogeneous landscape, incorporating 1218 species in our final results. The species richness patterns highlight patterns consistent with previous mapping efforts. Validation showed an increase in model accuracy when compared to models which did not use an iSDM framework. The workflow highlights limitations in the infrastructure of the currently openly accessible data, particularly the need for more structured presence-absence datasets and standardized metadata. Main conclusionsThis study underscores the potential of workflows that integrate disparate datasets for biodiversity modeling. To maximize accuracy and utility, future efforts should focus on improving data standardization, the publication and collection of more structured data, and fostering data-sharing collaborations. Advances in the workflow itself, including optimising modelling covariates and integrating more comprehensive spatio-temporal aspects, will also increase the relevance of the outputs. These advances will increase our ability to estimate species richness with a precision and accuracy that can reliably inform conservation and management decisions.

ecology↗

bioRxiv2022

PointedSDMs -- an R package to help facilitate the construction of integrated species distribution models

1O_LIIntegration of disparate datasets is a rapidly growing area in quantitative ecology, and is subsequently becoming a major asset in understanding the shifts and trends in species distributions. C_LIO_LIHowever, the tools and software available to construct statistical models to integrate these disparate datasets into a unified framework is lacking, stagnating the growth of data integration in applications. C_LIO_LIThis paper presents PointedSDMs: an easy to use R package used to construct integrated species distribution models using the integrated nested Laplace Approximation methodology. C_LIO_LIThe package is presented in this paper through an illustrative example for a selection of species found across Pennsylvania state. C_LI

ecology↗

bioRxiv2017

Differential temporal dynamics during visual imagery and perception

Visual perception and imagery rely on similar representations in the visual cortex. During perception, visual activity is characterized by distinct processing stages, but the temporal dynamics underlying imagery remain unclear. Here, we investigated the dynamics of visual imagery in human participants using magnetoencephalography. We show that, contrary to perception, the onset of imagery is characterized by broad temporal generalization. Furthermore, there is consistent overlap between imagery and perceptual processing around 150 ms and from 300 ms after stimulus onset, presumably reflecting completion of the feedforward sweep and perceptual stabilization respectively. These results indicate that during imagery either the complete representation is activated at once and does not include low-level visual areas, or the order in which visual features are activated is less fixed and more flexible than during perception. These findings have important implications for our understanding of the neural mechanisms of visual imagery.

neuroscience↗

bioRxiv2017

Eye movement-related confounds in neural decoding of visual working memory representations

The study of visual working memory (VWM) has recently seen revitalization with the emergence of new insights and theories regarding its neural underpinnings. One crucial ingredient responsible for this progress is the rise of neural decoding techniques. These techniques promise to uncover the representational contents of neural signals, as well as the underlying code and the dynamic profile thereof. Here, we aimed to contribute to the field by subjecting human volunteers to a combined VWM/imagery task, while recording and decoding their neural signals as measured by MEG. At first sight, the results seem to provide evidence for a persistent, stable representation of the memorandum throughout the delay period. However, control analyses revealed that these findings can be explained by subtle, VWM-specific eye movements. As a potential remedy, we demonstrate the use of a functional localizer, which was specifically designed to target bottom-up sensory signals and as such avoids eye movements, to train the neural decoders. This analysis revealed a sustained representation for approximately 1 second, but no longer throughout the entire delay period. We conclude by arguing for more awareness of the potentially pervasive and ubiquitous effects of eye movement-related confounds.\n\nSignificance statementVisual working memory is an important aspect of higher cognition and has been subject of much investigation within the field of cognitive neuroscience. Over recent years, these studies have increasingly relied on the use of neural decoding techniques. Here, we show that neural decoding may be susceptible to confounds induced by stimulus-specific eye movements. Such eye movements during working memory have been reported before, and may in fact be a common phenomenon. Given the widespread use of neural decoding and the potentially contaminating effects of eye movements, we therefore believe that our results are of significant relevance for the field.

neuroscience↗

bioRxiv2017

Stimulus familiarity and expectation jointly modulate neural activity in the visual ventral stream

Prior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex (IT). It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. In order to address this issue and to examine whether previous findings generalize to non-invasively measured neural activity in humans of both sexes, we separately manipulated stimulus familiarity and expectation, while non-invasively recording human brain activity using magnetoencephalography (MEG). We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex (LOC), the putative human homologue of monkey IT. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.

neuroscience↗

bioRxiv2017

Prior expectations induce pre-stimulus sensory templates

Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to pre-stimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn affects the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from post-stimulus processes. Here, we combined human MEG with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal well before they were presented, demonstrating that expectations indeed induce a pre-activation of stimulus templates. These results suggest a mechanism for how predictive perception can be neurally implemented.

neuroscience↗