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Spatial Correspondence (spatial + correspondence)

Distribution by Scientific Domains
Life Sciences60%

Selected Abstracts

Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictors

ECOGRAPHY, Issue 6 2009
Alexandra D. Syphard
Prediction maps produced by species distribution models (SDMs) influence decision-making in resource management or designation of land in conservation planning. Many studies have compared the prediction accuracy of different SDM modeling methods, but few have quantified the similarity among prediction maps. There has also been little systematic exploration of how the relative importance of different predictor variables varies among model types and affects map similarity. Our objective was to expand the evaluation of SDM performance for 45 plant species in southern California to better understand how map predictions vary among model types, and to explain what factors may affect spatial correspondence, including the selection and relative importance of different environmental variables. Four types of models were tested. Correlation among maps was highest between generalized linear models (GLMs) and generalized additive models (GAMs) and lowest between classification trees and GAMs or GLMs. Correlation between Random Forests (RFs) and GAMs was the same as between RFs and classification trees. Spatial correspondence among maps was influenced the most by model prediction accuracy (AUC) and species prevalence; map correspondence was highest when accuracy was high and prevalence was intermediate (average prevalence for all species was 0.124). Species functional type and the selection of climate variables also influenced map correspondence. For most (but not all) species, climate variables were more important than terrain or soil in predicting their distributions. Environmental variable selection varied according to modeling method, but the largest differences were between RFs and GLMs or GAMs. Although prediction accuracy was equal for GLMs, GAMs, and RFs, the differences in spatial predictions suggest that it may be important to evaluate the results of more than one model to estimate the range of spatial uncertainty before making planning decisions based on map outputs. This may be particularly important if models have low accuracy or if species prevalence is not intermediate. [source]

Spatial correspondence between areas of concentration of Patagonian scallop (Zygochlamys patagonica) and frontal systems in the southwestern Atlantic

FISHERIES OCEANOGRAPHY, Issue 5 2005
EUGENIA BOGAZZI
Abstract It has been hypothesized that the geographical location of scallop beds in extensive shelf regions mirrors hydrographic structures (e.g. frontal systems) that favor the retention/concentration of pelagic larvae. Large, discontinuous concentrations of the Patagonian scallop (Zygochlamys patagonica) are known to have occurred recurrently (for more than 30 yr) at certain geographical locations over the extensive Patagonian shelf. These stocks, exploited since 1996, currently support one of the most important scallop fisheries in the world. Here, we investigate whether those aggregations are spatially coincidental with major frontal systems. Several pieces of information were used: historical survey data documenting the geographic distribution of the Patagonian scallop beds, catch and effort data from the commercial fleet, oceanographic data on frontal systems, and remote sensing imagery. We found that large-scale aggregations do match the location of three major and very different frontal systems in the southwestern Atlantic: the Shelf-Break Frontal System, the Northern Patagonia Frontal System, and the Southern Patagonia Frontal System. We describe the three frontal systems and their associated scallops fishing grounds and discuss which processes can contribute to sustaining the productivity of the scallop grounds in each case. [source]

Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictors

ECOGRAPHY, Issue 6 2009
Alexandra D. Syphard
Prediction maps produced by species distribution models (SDMs) influence decision-making in resource management or designation of land in conservation planning. Many studies have compared the prediction accuracy of different SDM modeling methods, but few have quantified the similarity among prediction maps. There has also been little systematic exploration of how the relative importance of different predictor variables varies among model types and affects map similarity. Our objective was to expand the evaluation of SDM performance for 45 plant species in southern California to better understand how map predictions vary among model types, and to explain what factors may affect spatial correspondence, including the selection and relative importance of different environmental variables. Four types of models were tested. Correlation among maps was highest between generalized linear models (GLMs) and generalized additive models (GAMs) and lowest between classification trees and GAMs or GLMs. Correlation between Random Forests (RFs) and GAMs was the same as between RFs and classification trees. Spatial correspondence among maps was influenced the most by model prediction accuracy (AUC) and species prevalence; map correspondence was highest when accuracy was high and prevalence was intermediate (average prevalence for all species was 0.124). Species functional type and the selection of climate variables also influenced map correspondence. For most (but not all) species, climate variables were more important than terrain or soil in predicting their distributions. Environmental variable selection varied according to modeling method, but the largest differences were between RFs and GLMs or GAMs. Although prediction accuracy was equal for GLMs, GAMs, and RFs, the differences in spatial predictions suggest that it may be important to evaluate the results of more than one model to estimate the range of spatial uncertainty before making planning decisions based on map outputs. This may be particularly important if models have low accuracy or if species prevalence is not intermediate. [source]

Topographical organization of pathways from somatosensory cortex through the pontine nuclei to tactile regions of the rat cerebellar hemispheres

EUROPEAN JOURNAL OF NEUROSCIENCE, Issue 10 2006
Trygve B. Leergaard
Abstract The granule cell layer of the cerebellar hemispheres contains a patchy and noncontinuous map of the body surface, consisting of a complex mosaic of multiple perioral tactile representations. Previous physiological studies have shown that cerebrocerebellar mossy fibre projections, conveyed through the pontine nuclei, are mapped in registration with peripheral tactile projections to the cerebellum. In contrast to the fractured cerebellar map, the primary somatosensory cortex (SI) is somatotopically organized. To understand better the map transformation occurring in cerebrocerebellar pathways, we injected axonal tracers in electrophysiologically defined locations in Sprague,Dawley rat folium crus IIa, and mapped the distribution of retrogradely labelled neurons within the pontine nuclei using three-dimensional (3-D) reconstructions. Tracer injections within the large central upper lip patch in crus IIa-labelled neurons located centrally in the pontine nuclei, primarily contralateral to the injected side. Larger injections (covering multiple crus IIa perioral representations) resulted in labelling extending only slightly beyond this region, with a higher density and more ipsilaterally labelled neurons. Combined axonal tracer injections in upper lip representations in SI and crus IIa, revealed a close spatial correspondence between the cerebropontine terminal fields and the crus IIa projecting neurons. Finally, comparisons with previously published three-dimensional distributions of pontine neurons labelled following tracer injections in face receiving regions in the paramedian lobule (downloaded from http://www.rbwb.org) revealed similar correspondence. The present data support the coherent topographical organization of cerebro-ponto-cerebellar networks previously suggested from physiological studies. We discuss the present findings in the context of transformations from cerebral somatotopic to cerebellar fractured tactile representations. [source]

Global Daily Reference Evapotranspiration Modeling and Evaluation,

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2008
G.B. Senay
Abstract:, Accurate and reliable evapotranspiration (ET) datasets are crucial in regional water and energy balance studies. Due to the complex instrumentation requirements, actual ET values are generally estimated from reference ET values by adjustment factors using coefficients for water stress and vegetation conditions, commonly referred to as crop coefficients. Until recently, the modeling of reference ET has been solely based on important weather variables collected from weather stations that are generally located in selected agro-climatic locations. Since 2001, the National Oceanic and Atmospheric Administration's Global Data Assimilation System (GDAS) has been producing six-hourly climate parameter datasets that are used to calculate daily reference ET for the whole globe at 1-degree spatial resolution. The U.S. Geological Survey Center for Earth Resources Observation and Science has been producing daily reference ET (ETo) since 2001, and it has been used on a variety of operational hydrological models for drought and streamflow monitoring all over the world. With the increasing availability of local station-based reference ET estimates, we evaluated the GDAS-based reference ET estimates using data from the California Irrigation Management Information System (CIMIS). Daily CIMIS reference ET estimates from 85 stations were compared with GDAS-based reference ET at different spatial and temporal scales using five-year daily data from 2002 through 2006. Despite the large difference in spatial scale (point vs. ,100 km grid cell) between the two datasets, the correlations between station-based ET and GDAS-ET were very high, exceeding 0.97 on a daily basis to more than 0.99 on time scales of more than 10 days. Both the temporal and spatial correspondences in trend/pattern and magnitudes between the two datasets were satisfactory, suggesting the reliability of using GDAS parameter-based reference ET for regional water and energy balance studies in many parts of the world. While the study revealed the potential of GDAS ETo for large-scale hydrological applications, site-specific use of GDAS ETo in complex hydro-climatic regions such as coastal areas and rugged terrain may require the application of bias correction and/or disaggregation of the GDAS ETo using downscaling techniques. [source]