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Spatial Dependency (spatial + dependency)
Selected AbstractsSpatial correlations of Diceroprocta apache and its host plants: evidence for a negative impact from Tamarix invasionECOLOGICAL ENTOMOLOGY, Issue 1 2002Aaron R. Ellingson Abstract 1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m. 2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected. 3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture. 4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies. [source] Thresholds in landscape connectivity and mortality risks in response to growing road networksJOURNAL OF APPLIED ECOLOGY, Issue 5 2008Jacqueline L. Frair Summary 1The ecological footprint of a road may extend for several kilometres with overlapping effects from neighbouring roads causing a nonlinear accumulation of road effects in the landscape. Availability of preferred habitat, spatial dependencies between roads and habitat types, and fidelity to traditionally used areas further confound our ability to predict population-level responses of animals to growing road networks. 2To isolate these effects, we developed an individually based movement model using elk Cervus elaphus L. as a model system. Empirically derived movement rules redistributed elk under different amounts of preferred habitat (clearcuts), road densities, and road development schemes. We tracked potential mortality risk (given time spent near roads) and emigration rates (given declining accessibility of foraging habitat). 3Design of the road network accounted for up to 30,55% difference in mortality risk and emigration rates, with the largest differences occurring at intermediate road densities (1,1·5 km km,2) when road effects began to saturate the landscape. Maintaining roads in association with clearcuts caused a decline in habitat accessibility equivalent to replacing 50,75% of these foraging patches with conifer forest. A nine-fold difference in potential emigration was observed after varying elk tolerance for declining habitat accessibility despite holding local movement biases constant. 4Elk responses to growing road networks were non-linear, exposing thresholds for road density that were reflected in the home range occupancy patterns of a large sample of elk in the region. 5Synthesis and applications. Our approach provides a means of scaling-up complex movement decisions to population-level redistribution, separating the confounding effects of landscape context from road effects, and exposing thresholds in connectivity and mortality risks for wildlife caused by infrastructure growth. Our model indicated that road densities , 0·5 km km,2 yielded the highest probability of elk occurrence where elk were hunted (and sensitive to roads), but disassociating roads from foraging habitats or managing human access to roads may maintain effective elk habitat at substantially higher road densities. [source] Motor units in cranial and caudal regions of the upper trapezius muscle have different discharge rates during brief static contractionsACTA PHYSIOLOGICA, Issue 4 2008D. Falla Abstract Aim:, To compare the discharge patterns of motor unit populations from different locations within the upper trapezius muscle during brief submaximal constant-force contractions. Methods:, Intramuscular and surface electromyographic (EMG) signals were collected from three sites of the right upper trapezius muscle distributed along the cranial-caudal direction in 11 volunteers during 10 s shoulder abduction at 25% of the maximum voluntary force. Results:, A total of 38 motor units were identified at the cranial location, 36 from the middle location and 17 from the caudal location. Initial discharge rate was greatest at the caudal location (P < 0.05; mean ± SD, cranial: 16.7 ± 3.6 pps, middle: 16.9 ± 4.0 pps, caudal: 19.2 ± 3.3 pps). Discharge rate decreased during the contraction for the most caudal location only (P < 0.05). Initial estimates of surface EMG root mean square values were highest at the most caudal location (P < 0.05; cranial: 32.3 ± 20.9 ,V, middle: 41.3 ± 21.0 ,V, caudal: 51.6 ± 23.6 ,V). Conclusion:, This study demonstrates non-uniformity of motor unit discharge within the upper trapezius muscle during a brief submaximal constant-force contraction. Location-dependent modulation of discharge rate may reflect spatial dependency in the control of motor units necessary for the development and maintenance of force output. [source] Representing genetic variation as continuous surfaces: an approach for identifying spatial dependency in landscape genetic studiesECOGRAPHY, Issue 6 2008Melanie A. Murphy Landscape genetics, an emerging field integrating landscape ecology and population genetics, has great potential to influence our understanding of habitat connectivity and distribution of organisms. Whereas typical population genetics studies summarize gene flow as pairwise measures between sampling localities, landscape characteristics that influence population genetic connectivity are often continuously distributed in space. Thus, there are currently gaps in both the ability to analyze genotypic data in a continuous spatial context and our knowledge of expected of landscape genetic structure under varying conditions. We present a framework for generating continuous "genetic surfaces", evaluate their statistical properties, and quantify statistical behavior of landscape genetic structure in a simple landscape. We simulated microsatellite genotypes under varying parameters (time since vicariance, migration, effective population size) and used ancestry (q) values from STRUCTURE to interpolate a genetic surface. Using a spatially adjusted Pearson's correlation coefficient to test the significance of landscape variable(s) on genetic structure we were able to detect landscape genetic structure on a contemporary time scale (,5 generations post vicariance, migration probability ,0.10) even when population differentiation was minimal (FST,0.00015). We show that genetic variation can be significantly correlated with geographic distance even when genetic structure is due to landscape variable(s), demonstrating the importance of testing landscape influence on genetic structure. Finally, we apply genetic surfacing to analyze an empirical dataset of black bears from northern Idaho USA. We find black bear genetic variation is a function of distance (autocorrelation) and habitat patch (spatial dependency), consistent with previous results indicating genetic variation was influenced by landscape by resistance. These results suggest genetic surfaces can be used to test competing hypotheses of the influence of landscape characteristics on genetic structure without delineation of categorical groups. [source] Space varying coefficient models for small area dataENVIRONMETRICS, Issue 5 2003Renato M. Assunção Abstract Many spatial regression problems using area data require more flexible forms than the usual linear predictor for modelling the dependence of responses on covariates. One direction for doing this is to allow the coefficients to vary as smooth functions of the area's geographical location. After presenting examples from the scientific literature where these spatially varying coefficients are justified, we briefly review some of the available alternatives for this kind of modelling. We concentrate on a Bayesian approach for generalized linear models proposed by the author which uses a Markov random field to model the coefficients' spatial dependency. We show that, for normally distributed data, Gibbs sampling can be used to sample from the posterior and we prove a result showing the equivalence between our model and other usual spatial regression models. We illustrate our approach with a number of rather complex applied problems, showing that the method is computationally feasible and provides useful insights in substantive problems. Copyright © 2003 John Wiley & Sons, Ltd. [source] Streamflow estimation using optimal regional dependency functionHYDROLOGICAL PROCESSES, Issue 25 2009Abdüsselam Altunkaynak Abstract The determination of spatial dependency of regionalized variable (ReV) is important in engineering studies. Regional dependency function that leads to calculation of weighting coefficients is required in order to make regional or point-wise estimations. After obtaining this dependency function, it is possible to complete missing records in the time series and locate new measurement station. Also determination of regional dependency function is also useful to understand the regional variation of ReV. Point Cumulative Semi-Variogram (PCSV) is another methodology to understand the regional dependency of ReV related to the magnitude and the location. However, this methodology is not useful to determine the weighting coefficient, which is required to make regional and point-wise estimations. However, in Point Semi-Variogram (PSV) proposed here, weighting coefficient depends on both magnitude and location. Although the regional dependency function has a fluctuating structure in PSV approach, this function gradually increases with distance in PCSV. The study area is selected in Mississippi river basin with 38 streamflow stations used for PCSV application before. It is aimed to compare two different geostatistical models for the same data set. PSV method has an ability to determine the value of variable along with optimum number of neighbour stations and influence radius. PSV and slope PSV approaches are compared with the PCSV. It was shown that slope slope point semi-variogram (SPSV) approaches had relative error below 5%, and PSV and PCSV methods revealed relative errors below 10%. Copyright © 2009 John Wiley & Sons, Ltd. [source] | ||||||||||