caa a22 4500 467904189 CHVBK 20180406152828.0 cr unu---uuuuu 170328e20061001xx s 000 0 eng 10.1007/s10661-005-9156-7 doi (NATIONALLICENCE)springer-10.1007/s10661-005-9156-7 Patterns of Spatial Autocorrelation in Stream Water Chemistry [Elektronische Daten] [Erin Peterson, Andrew Merton, David Theobald, N. Urquhart] Geostatistical models are typically based on symmetric straight-line distance, which fails to represent the spatial configuration, connectivity, directionality, and relative position of sites in a stream network. Freshwater ecologists have explored spatial patterns in stream networks using hydrologic distance measures and new geostatistical methodologies have recently been developed that enable directional hydrologic distance measures to be considered. The purpose of this study was to quantify patterns of spatial correlation in stream water chemistry using three distance measures: straight-line distance, symmetric hydrologic distance, and weighted asymmetric hydrologic distance. We used a dataset collected in Maryland, USA to develop both general linear models and geostatistical models (based on the three distance measures) for acid neutralizing capacity, conductivity, pH, nitrate, sulfate, temperature, dissolved oxygen, and dissolved organic carbon. The spatial AICC methodology allowed us to fit the autocorrelation and covariate parameters simultaneously and to select the model with the most support in the data. We used the universal kriging algorithm to generate geostatistical model predictions. We found that spatial correlation exists in stream chemistry data at a relatively coarse scale and that geostatistical models consistently improved the accuracy of model predictions. More than one distance measure performed well for most chemical response variables, but straight-line distance appears to be the most suitable distance measure for regional geostatistical modeling. It may be necessary to develop new survey designs that more fully capture spatial correlation at a variety of scales to improve the use of weighted asymmetric hydrologic distance measures in regional geostatistical models. Springer Science+Business Media, Inc., 2006 geostatistics nationallicence hydrologic distance nationallicence scale nationallicence spatial autocorrelation nationallicence stream networks nationallicence water chemistry nationallicence weighted asymmetric hydrologic distance nationallicence Peterson Erin CSIRO Mathematical & Information Sciences, Queensland Bioscience Precinct, 306 Carmody Road, 4067, St. Lucia, QLD, Australia aut Merton Andrew Department of Statistics, Colorado State University, Fort Collins, CO, USA aut Theobald David Natural Resource Ecology Lab and Natural Resources Recreation and Tourism Department, Colorado State University, Fort Collins, CO, U.S.A. aut Urquhart N. Department of Statistics, Colorado State University, Fort Collins, CO, USA aut Environmental Monitoring and Assessment Springer Netherlands 121/1-3(2006-10-01), 571-596 0167-6369 121:1-3<571 2006 121 10661 https://doi.org/10.1007/s10661-005-9156-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10661-005-9156-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Peterson Erin CSIRO Mathematical & Information Sciences, Queensland Bioscience Precinct, 306 Carmody Road, 4067, St. Lucia, QLD, Australia aut NATIONALLICENCE 700 1- Merton Andrew Department of Statistics, Colorado State University, Fort Collins, CO, USA aut NATIONALLICENCE 700 1- Theobald David Natural Resource Ecology Lab and Natural Resources Recreation and Tourism Department, Colorado State University, Fort Collins, CO, U.S.A aut NATIONALLICENCE 700 1- Urquhart N. Department of Statistics, Colorado State University, Fort Collins, CO, USA aut NATIONALLICENCE 773 0- Environmental Monitoring and Assessment Springer Netherlands 121/1-3(2006-10-01), 571-596 0167-6369 121:1-3<571 2006 121 10661 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer