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47 results for “spatial bias”
Data to "Object visibility, not energy expenditure, accounts for spatial biases in human grasp selection"
<p>This record contains experimental and analysis scripts (written in Matlab) as well as raw and processed data to reproduce the results shown in:</p> <p><strong>Maiello, G</strong>.<sup> †</sup>, Paulun, V. C.<sup> †</sup>, Klein, L. K. , & Fleming, R. W. (2018) Object visibility, not energy expenditure, accounts for spatial biases in human grasp selection. <em>i-Perception,10</em>(1), 1–5. doi:10.1177/2041669519827608.</p> <p><sup>†</sup>co-first authors</p>
State of biodiversity documentation in the Philippines: Metadata gaps, taxonomic biases, and spatial biases in the DNA barcode data of animal and plant taxa in the context of species occurrence data
<p>These files can be categorized into three groups: (1) raw datasets obtained from public databases (i.e., GBIF, BOLD, and GenBank), (2) manually edited files needed for parsing and analysis, and (3) supplementary files for spatial analysis. All are used in the examination of gaps and biases present in Philippine biodiversity data, which can direct research on the taxa and spatial regions that need more sampling.</p>
Temporal trends in the spatial bias of species occurrence records
<p>Large-scale biodiversity databases have great potential for quantifying long-term trends of species, but they also bring many methodological challenges. Spatial bias of species occurrence records is well recognized. Yet, the dynamic nature of this spatial bias - how spatial bias has changed over time - has been largely overlooked. We examined the spatial sampling bias of species occurrence records within multiple biodiversity databases in Germany and tested whether spatial bias in relation to land cover or land use (urban and protected areas) has changed over time. We focused our analyses on urban and protected areas as these represent two well-known correlates of sampling bias in biodiversity datasets. We found that the proportion of annual records from urban areas has increased over time while the proportion of annual records within protected areas has not consistently changed. Using simulations, we examined the implications of this changing sampling bias for estimation of long-term trends of species' distributions. When assessing biodiversity change, our findings suggest that the effects of spatial bias depend on how it affects sampling of the underlying land-use change drivers affecting species. Oversampling of regions undergoing the greatest degree of change, for instance near human settlements, might lead to overestimation of the trends of specialist species. For robust estimation of the long-term trends in species' distributions, analyses using species occurrence records may need to consider not only spatial bias, but also changes in the strength of spatial bias through time.</p>
Lying in a 3T MRI scanner induces neglect-like spatial attention bias
<p>Exposing subjects to the magnetic field of a 3T MRI scanner stimulates the vestibular organ and thereby induces - besides a VOR - horizontal biases in visual search and in subjective straight ahead, which are similar to those seen in stroke patients with spatial neglect.</p>
Temporal trends in the spatial bias of species occurrence records
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Lying in a 3T MRI scanner induces neglect-like spatial attention bias
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Spatial survival analysis accounts for female-biased breeding dispersal and provides realistic estimates of true annual survival in migratory warblers
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Short-Tandem-Repeat (STR) marker set for Eurasian lynx for article: Genetic analysis indicates spatial-dependent patterns of sex-biased dispersal in Eurasian lynx in Finland
<p>Conservation and management of large carnivores requires knowledge of female and male dispersal. Such information is crucial to evaluate the population's status and thus management actions. This knowledge is challenging to obtain, often incomplete and contradictory at times. The size of the target population and the methods applied can bias the results. Also, population history and biological or environmental influences can affect dispersal on different scales within a study area. We have genotyped Eurasian lynx (180 males and 102 females, collected 2003-2017) continuously distributed in southern Finland (~23,000 km<sup>2</sup>) using 21 short tandem repeats (STR) loci and compared statistical genetic tests to infer local and sex-specific dispersal patterns within and across genetic clusters as well as geographic regions. We tested for sex-specific substructure with individual-based Bayesian assignment tests and spatial autocorrelation analyses. Differences between the sexes in genetic differentiation, relatedness, inbreeding, and diversity were analysed using population-based AMOVA, F-statistics, and assignment indices. Our results showed two different genetic clusters that were spatially structured for females but admixed for males. Similarly, spatial autocorrelation and relatedness was significantly higher in females than males. However, we found weaker sex-specific patterns for the Eurasian lynx when the data were separated in three geographical regions than when divided in the two genetic clusters. Overall, our results suggest male-biased dispersal and female philopatry for the Eurasian lynx in Southern Finland. The female genetic structuring increased from west to east within our study area. In addition, detection of male-biased dispersal was dependent on analytical methods utilized, on whether subtle underlying genetic structuring was considered or not, and the choice of population delineation. Conclusively, we suggest using multiple genetic approaches to study sex-biased dispersal in a continuously distributed species in which population delineation is difficult.</p>
The apparent exponential radiation of Phanerozoic land vertebrates is an artefact of spatial sampling biases
There is no consensus about how terrestrial biodiversity was assembled through deep time, and in particular whether it has risen exponentially over the Phanerozoic. Using a database of 38,711 fossil occurrences, we show that the spatial extent of the 'global' terrestrial tetrapod fossil record itself expands exponentially through the Phanerozoic, and that this spatial variation explains around 75% of the variation in known fossil species counts. Controlling for this bias, we find that regional-scale terrestrial tetrapod diversity was constrained over timespans of tens to hundreds of millions of years, and similar patterns are recovered for major subgroups, such as dinosaurs, mammals and squamates. The Cretaceous/Paleogene mass extinction, 66 million years ago, fundamentally disrupted terrestrial ecosystems, catalysing an abrupt increase in its aftermath. Nevertheless, this was followed by general stasis and recent diversity levels do not exceed those of the Paleogene. These findings parallel those recovered in analyses of local community-level richness, suggesting that tetrapod beta diversity has also not shown a general increase through time. Taken together, our findings strongly contradict past studies that suggested unbounded diversity increases over the last 100 million years.
Data for: The meta-analysis of the effects of spatial sampling bias correction on presence only species distribution models
<p>This dataset contains information extracted from 70 studies identified through a systematic review of the peer-reviewed literature (Web of Science and SCOPUS databases both searched on the 13/02/2023) to evaluate the effect of spatial sampling bias correction methods in presence-only species distribution models.</p>
Biogeography of the world's worst invasive species has spatially-biased knowledge gaps but is predictable
<p>The world's "100 worst invasive species" were listed in 2000. The list is taxonomically diverse and often cited (typically for single-species studies), and its species are frequently reported in global biodiversity databases. We acted on the principle that these notorious species should be well-reported to help answer two questions about global biogeography of invasive species (i.e., not just their invaded ranges): (1) "how are data distributed globally?" and (2) "what predicts diversity?" We collected location data for each of the 100 species from multiple databases; 95 had sufficient data for analyses. For question (1), we mapped global species richness and cumulative occurrences since 2000 in (0.5 degree)<sup>2</sup> grids. For question (2) we compared alternative regression models representing non-exclusive hypotheses for geography (i.e., spatial autocorrelation), sampling effort, climate, and anthropocentric effects.</p> <p>Reported locations of the invasive species were spatially-biased, leaving large gaps on multiple continents. Accordingly, species richness was best explained by both anthropocentric effects not often used in biogeographic models (Government Effectiveness, Voice & Accountability, human population size) and typical natural factors (climate, geography; R<sup>2</sup> = 0.87). Cumulative occurrence was strongly related to anthropocentric effects (R<sup>2</sup> = 0.62). We extract five lessons for invasive species biogeography; foremost is the importance of anthropocentric measures for understanding invasive species diversity patterns and large lacunae in their known global distributions. Despite those knowledge gaps, advanced models here predict well the biogeography of the world's worst invasive species for much of the world.</p>
Inductive biases of neural network modularity in spatial navigation
<p>The brain may have evolved a modular architecture for reward-based learning in daily tasks, with circuits featuring functionally specialized modules that match the task structure. We propose that this architecture enables better learning and generalization than architectures with less specialized modules. To test this hypothesis, we trained reinforcement learning agents with various neural architectures on a naturalistic navigation task. We found that the architecture that largely segregates computations of state representation, value, and action into specialized modules enables more efficient learning and better generalization. The behavior of agents with this modular architecture also resembles macaque behaviors more closely. Investigating the latent state computations in these agents, we discovered that the learned state representation combines prediction and observation, weighted by their relative uncertainty, akin to a Kalman filter. These results shed light on the possible rationale for the brain's modular specializations and suggest that artificial systems can use this insight from neuroscience to improve learning and generalization in natural tasks.</p>
Review data for: SnowQM 1.0: A fast R Package for bias-correcting spatial fields of snow water equivalent using quantile mapping
<p>Climatology of snow water equivalent of Switzerland between winters 1962 and 2021. Obtained using quartile mapping between a model using data assimilation since 1998 and a model without data assimilation. This version of the dataset corresponds to the publication revision time. The publication has been submitted to GMD Copernicus journal as: <em>SnowQM 1.0: A fast R Package for bias-correcting spatial fields of snow water equivalent using quantile mapping</em></p>
The apparent exponential radiation of Phanerozoic land vertebrates is an artefact of spatial sampling biases
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Data for: The meta-analysis of the effects of spatial sampling bias correction on presence only species distribution models
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Lactose operon sequences from: Spatial-scale evolutionary bias sheds light on the latitudinal diversity gradient
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Inductive biases of neural network modularity in spatial navigation
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Short-Tandem-Repeat (STR) marker set for Eurasian lynx for article: Genetic analysis indicates spatial-dependent patterns of sex-biased dispersal in Eurasian lynx in Finland
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Biogeography of the world’s worst invasive species has spatially-biased knowledge gaps but is predictable
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Data from: Aragonite bias exhibits systematic spatial variation in the late Cretaceous Western Interior Seaway, North America
Preferential dissolution of the biogenic carbonate polymorph aragonite promotes preservational bias in shelly marine faunas. Whilst field studies have documented the impact of preferential aragonite dissolution on fossil molluscan diversity, its impact on regional and global biodiversity metrics is debated. Epicontinental seas are especially prone to conditions which both promote and inhibit preferential dissolution, which may result in spatially extensive zones with variable preservation. Here we present a multi-faceted evaluation of aragonite dissolution within the late Cretaceous Western Interior Seaway of North America. Occurrence data of molluscs from two time intervals (Cenomanian-Turonian boundary, early Campanian) are plotted on new high-resolution paleogeographies to assess aragonite preservation within the seaway. Fossil occurrences, diversity estimates and sampling probabilities for calcitic and aragonitic fauna were compared in zones defined by depth and distance from the seaway margins. Apparent range sizes, which could be influenced by differential preservation potential of aragonite between separate localities, were also compared. Our results are consistent with exacerbated aragonite dissolution within specific depth zones for both time slices, with aragonitic bivalves additionally showing a statistically significant decrease in range size compared to calcitic fauna within carbonate-dominated Cenomanian-Turonian strata. However, we are unable to conclusively show that aragonite dissolution impacted diversity estimates. Therefore, whilst aragonite dissolution is likely to have affected the preservation of fauna in specific localities, time averaging and instantaneous preservation events preserve regional biodiversity. Our results suggest that the spatial expression of taphonomic biases should be an important consideration for paleontologists working on paleobiogeographic problems.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.