Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
262,645
result(s) for
"Spatial"
Sort by:
Community ecology in the age of multivariate multiscale spatial analysis
Species spatial distributions are the result of population demography, behavioral traits, and species interactions in spatially heterogeneous environmental conditions. Hence the composition of species assemblages is an integrative response variable, and its variability can be explained by the complex interplay among several structuring factors. The thorough analysis of spatial variation in species assemblages may help infer processes shaping ecological communities. We suggest that ecological studies would benefit from the combined use of the classical statistical models of community composition data, such as constrained or unconstrained multivariate analyses of site-by-species abundance tables, with rapidly emerging and diversifying methods of spatial pattern analysis. Doing so allows one to deal with spatially explicit ecological models of beta diversity in a biogeographic context through the multiscale analysis of spatial patterns in original species data tables, including spatial characterization of fitted or residual variation from environmental models. We summarize here the recent progress for specifying spatial features through spatial weighting matrices and spatial eigenfunctions in order to define spatially constrained or scale-explicit multivariate analyses. Through a worked example on tropical tree communities, we also show the potential of the overall approach to identify significant residual spatial patterns that could arise from the omission of important unmeasured explanatory variables or processes.
Journal Article
The 3-D global spatial data model : principles and applications
Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems. -- Provided by publisher.
Book
A sense of space in postrhinal cortex
Successful movement depends on an accurate sense of one's location within a particular environment. Neuroscientists distinguish self-centered and world-centered navigation and have been searching for a brain region where all ingredients of navigation come together. As rats foraged in an open field, LaChance et al. recorded activity from single neurons in an area called the postrhinal cortex. The authors found a population of cells that transform an animal's immediate sensory perception of its environment into a spatial map. This map is markedly different from the high-level representations observed in hippocampal place cells or entorhinal grid cells, but it is very flexible and is likely to provide the necessary building blocks for creating higher-level representations. Science , this issue p. eaax4192 Neurons in the rat postrhinal cortex provide a template for the formation of high-level topographic spatial maps. A topographic representation of local space is critical for navigation and spatial memory. In humans, topographic spatial learning relies upon the parahippocampal cortex, damage to which renders patients unable to navigate their surroundings or develop new spatial representations. Stable spatial signals have not yet been observed in its rat homolog, the postrhinal cortex. We recorded from single neurons in the rat postrhinal cortex whose firing reflects an animal’s egocentric relationship to the geometric center of the local environment, as well as the animal’s head direction in an allocentric reference frame. Combining these firing correlates revealed a population code for a stable topographic map of local space. This may form the basis for higher-order spatial maps such as those seen in the hippocampus and entorhinal cortex.
Journal Article
Coordinated prefrontal–hippocampal activity and navigation strategy-related prefrontal firing during spatial memory formation
Learning the location of relevant places in the environment is crucial for survival. Such capacity is supported by a distributed network comprising the prefrontal cortex and hippocampus, yet it is not fully understood how these structures cooperate during spatial reference memory formation. Hence, we examined neural activity in the prefrontal–hippocampal circuit in mice during acquisition of spatial reference memory. We found that interregional oscillatory coupling increased with learning, specifically in the slow-gamma frequency (20 to 40 Hz) band during spatial navigation. In addition, mice used both spatial and nonspatial strategies to navigate and solve the task, yet prefrontal neuronal spiking and oscillatory phase coupling were selectively enhanced in the spatial navigation strategy. Lastly, a representation of the behavioral goal emerged in prefrontal spiking patterns exclusively in the spatial navigation strategy. These results suggest that reference memory formation is supported by enhanced cortical connectivity and evolving prefrontal spiking representations of behavioral goals.
Journal Article
Foundations of geometric cognition
\"Foundations of Geometric Cognition presents an empirically inspired theory of geometric cognition. The book explains how language and diagrams provide cognitive scaffolding for abstract geometric thinking within a context of Euclidean systems of thought. Hohol argues that geometric cognition is founded on our basic spatial abilities and requires interactions between concrete spatial representations and abstract linguistic ones. Drawing on research from diverse fields including psychology, cognitive science, and mathematics, this book is a must-read for anyone interested in the burgeoning field of geometric cognition\"-- Provided by publisher.
Book
Mice learn multi-step routes by memorizing subgoal locations
The behavioral strategies that mammals use to learn multi-step routes are unknown. In this study, we investigated how mice navigate to shelter in response to threats when the direct path is blocked. Initially, they fled toward the shelter and negotiated obstacles using sensory cues. Within 20 min, they spontaneously adopted a subgoal strategy, initiating escapes by running directly to the obstacle’s edge. Mice continued to escape in this manner even after the obstacle had been removed, indicating use of spatial memory. However, standard models of spatial learning—habitual movement repetition and internal map building—did not explain how subgoal memories formed. Instead, mice used a hybrid approach: memorizing salient locations encountered during spontaneous ‘practice runs’ to the shelter. This strategy was also used during a geometrically identical food-seeking task. These results suggest that subgoal memorization is a fundamental strategy by which rodents learn efficient multi-step routes in new environments.
Shamash et al. examine how mice learn to get past an obstacle blocking their path to a goal. They found that mice instinctively adopt a subgoal memory strategy, which combines elements from both habitual learning and the cognitive map theory.
Journal Article
Estimation of Above-Ground Carbon Storage and Light Saturation Value in Northeastern China’s Natural Forests Using Different Spatial Regression Models
In recent years, accurate estimation and spatial mapping of above-ground carbon (AGC) storage in forests have been crucial for formulating carbon trading policies and promoting sustainable development strategies. Forest structure complexities mean that during their growth, trees may be affected by the surrounding environment, giving rise to spatial autocorrelation and heterogeneity in nearby forest segments. When estimating forest AGC through remote sensing, data saturation can arise in dense forest stands, adding to the uncertainties in AGC estimation. Our study used field-measured stand factors data from 138 forest fire risk plots located in Fenglin County in the Northeastern region, set within a series of temperate forest environments in 2021 and Sentinel-2 remote sensing image data with a spatial resolution of 10 m. Using ordinary least squares (OLS) as a baseline, we constructed and compared it against four spatial regression models, spatial lag model (SLM), spatial error model (SEM), spatial Durbin model (SDM), and geographically weighted regression (GWR), to better understand forest AGC spatial distribution. The results of local spatial analysis reveal significant spatial effects among plot data. The GWR model outperformed others with an R2 value of 0.695 and the lowest rRMSE at 0.273, considering spatial heterogeneity and extending the threshold range for AGC estimation. To address the challenge of light saturation during AGC estimation, we deployed traditional linear functions, the generalized additive model (GAM), and the quantile generalized additive model (QGAM). AGC light saturation values derived from QGAM most accurately reflect the actual conditions, with the forests in Fenglin County exhibiting a light saturation range of 108.832 to 129.894 Mg/ha. The GWR effectively alleviated the impact of data saturation, thereby reducing the uncertainty of AGC spatial distribution in Fenglin County. Overall, accurate predictions of large-scale forest carbon storage provide valuable guidance for forest management, forest conservation, and the promotion of sustainable development strategies.
Journal Article