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Article: Characterizing spatial-temporal tree mortality patterns associated with a new forest disease

TitleCharacterizing spatial-temporal tree mortality patterns associated with a new forest disease
Authors
KeywordsSpatial-temporal patterns
Sudden Oak Death
Spatial point pattern analysis
Inhomogeneous K function
Neyman-Scott point process
Issue Date2007
Citation
Forest Ecology and Management, 2007, v. 253, n. 1-3, p. 220-231 How to Cite?
AbstractA new forest disease called Sudden Oak Death, caused by the pathogen Phytophthora ramorum, occurs in coastal hardwood forests in California and Oregon. In this paper, we analyzed the spatial-temporal patterns of overstory oak tree mortality in China Camp State Park, CA over 4 years using the point patterns mapped from high spatial resolution remotely sensed imagery. Both univariate and multivariate spatial point pattern analyses were performed with special considerations paid to the spatial trends illustrated in the mapped point patterns. In univariate spatial point pattern analyses, we investigated inhomogeneous K-functions and Neyman-Scott point processes to characterize and model the spatial dependence among dead oak trees in each year. The results showed that the point patterns of dead oak trees are significantly clustered at different scales and spatial extents through time; and that both the extent and the scale of the clustering patterns decrease with time. In multivariate spatial point pattern analyses, we developed two simulation methods to test the spatial-temporal dependence among dead oak trees over time and the spatial dependence between dead oak trees and California bay trees, an important host for the pathogen. The results showed that new dead oak trees tend to be located within up to 300 m of past dead oak trees; and that a strong spatial association between oak tree mortality and California bay trees exists 150 m away.
Persistent Identifierhttp://hdl.handle.net/10722/296474
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 1.197
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiu, Desheng-
dc.contributor.authorKelly, Maggi-
dc.contributor.authorGong, Peng-
dc.contributor.authorGuo, Qinghua-
dc.date.accessioned2021-02-25T15:15:59Z-
dc.date.available2021-02-25T15:15:59Z-
dc.date.issued2007-
dc.identifier.citationForest Ecology and Management, 2007, v. 253, n. 1-3, p. 220-231-
dc.identifier.issn0378-1127-
dc.identifier.urihttp://hdl.handle.net/10722/296474-
dc.description.abstractA new forest disease called Sudden Oak Death, caused by the pathogen Phytophthora ramorum, occurs in coastal hardwood forests in California and Oregon. In this paper, we analyzed the spatial-temporal patterns of overstory oak tree mortality in China Camp State Park, CA over 4 years using the point patterns mapped from high spatial resolution remotely sensed imagery. Both univariate and multivariate spatial point pattern analyses were performed with special considerations paid to the spatial trends illustrated in the mapped point patterns. In univariate spatial point pattern analyses, we investigated inhomogeneous K-functions and Neyman-Scott point processes to characterize and model the spatial dependence among dead oak trees in each year. The results showed that the point patterns of dead oak trees are significantly clustered at different scales and spatial extents through time; and that both the extent and the scale of the clustering patterns decrease with time. In multivariate spatial point pattern analyses, we developed two simulation methods to test the spatial-temporal dependence among dead oak trees over time and the spatial dependence between dead oak trees and California bay trees, an important host for the pathogen. The results showed that new dead oak trees tend to be located within up to 300 m of past dead oak trees; and that a strong spatial association between oak tree mortality and California bay trees exists 150 m away.-
dc.languageeng-
dc.relation.ispartofForest Ecology and Management-
dc.subjectSpatial-temporal patterns-
dc.subjectSudden Oak Death-
dc.subjectSpatial point pattern analysis-
dc.subjectInhomogeneous K function-
dc.subjectNeyman-Scott point process-
dc.titleCharacterizing spatial-temporal tree mortality patterns associated with a new forest disease-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.foreco.2007.07.020-
dc.identifier.scopuseid_2-s2.0-36048968560-
dc.identifier.volume253-
dc.identifier.issue1-3-
dc.identifier.spage220-
dc.identifier.epage231-
dc.identifier.isiWOS:000251760300024-
dc.identifier.issnl0378-1127-

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