FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1983992248> ?p ?o ?g. }

• W1983992248 endingPage "131" @default.
• W1983992248 startingPage "120" @default.
• W1983992248 abstract "Tree species display different abundance patterns over the landscape due to a number of hierarchical factors, all of which have implications when modeling their distribution. While climate is often the primary driver for global to regional scale tree species distributions, modeling of presence and abundance patterns at finer scales, and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Proxies for biotic and disturbance processes may be captured by a combination of multispectral remote sensing and light detection and ranging (LiDAR) data. LiDAR data have shown great potential for capturing three-dimensional (3D) characteristics of the forest canopy and a number of these characteristics may have strong relationships with drivers of local tree species distributions. The objective of this study was to investigate the importance of remote sensing derived variables related to biotic and disturbance processes in predicting fine–scale abundance patterns of several dominant tree species in a mixed mature forest in the Great Lakes–St. Lawrence Forest Region, Ontario, Canada. Boosted regression trees, an ensemble classification and regression algorithm, was used to compare tree species abundance models that included LiDAR derived topographic variables with models that included spectral and LiDAR derived topographic and vegetation variables. Average model fit (rescaled Nagelkerke R2) and predictive accuracy (correlation) improved from 0.12 to 0.63 and 0.25 to 0.71, respectively, when spectral and LiDAR derived vegetation variables were included in the tree species abundance models. This indicates that these variables capture some of the variance in local tree species' abundance distributions generated by biotic and disturbance processes in a landscape with limited topographic and climatic variation. Decreased model performance at higher tree species' abundances additionally suggests that our models do not capture all of the local drivers of tree species' abundance. Variables related to historical and current silvicultural practices may be missing." @default.
• W1983992248 created "2016-06-24" @default.
• W1983992248 creator A5043352426 @default.
• W1983992248 creator A5043761294 @default.
• W1983992248 creator A5045994689 @default.
• W1983992248 creator A5076590102 @default.
• W1983992248 date "2014-07-01" @default.
• W1983992248 modified "2023-10-18" @default.
• W1983992248 title "Predicting fine-scale tree species abundance patterns using biotic variables derived from LiDAR and high spatial resolution imagery" @default.
• W1983992248 cites W1496467185 @default.
• W1983992248 cites W1510083326 @default.
• W1983992248 cites W1678356000 @default.
• W1983992248 cites W1918984626 @default.
• W1983992248 cites W1972495330 @default.
• W1983992248 cites W1974789528 @default.
• W1983992248 cites W1981646498 @default.
• W1983992248 cites W1982722692 @default.
• W1983992248 cites W1989404805 @default.
• W1983992248 cites W1996263757 @default.
• W1983992248 cites W2002022751 @default.
• W1983992248 cites W2002041313 @default.
• W1983992248 cites W2015134267 @default.
• W1983992248 cites W2023188233 @default.
• W1983992248 cites W2024046085 @default.
• W1983992248 cites W2025992337 @default.
• W1983992248 cites W2031493166 @default.
• W1983992248 cites W2046229920 @default.
• W1983992248 cites W2061015378 @default.
• W1983992248 cites W2066451700 @default.
• W1983992248 cites W2070493638 @default.
• W1983992248 cites W2072708786 @default.
• W1983992248 cites W2073597781 @default.
• W1983992248 cites W2074854752 @default.
• W1983992248 cites W2098919237 @default.
• W1983992248 cites W2100165672 @default.
• W1983992248 cites W2101203599 @default.
• W1983992248 cites W2112095519 @default.
• W1983992248 cites W2112315008 @default.
• W1983992248 cites W2113488626 @default.
• W1983992248 cites W2116754686 @default.
• W1983992248 cites W2120160157 @default.
• W1983992248 cites W2121795775 @default.
• W1983992248 cites W2123162799 @default.
• W1983992248 cites W2123337039 @default.
• W1983992248 cites W2124155637 @default.
• W1983992248 cites W2125574854 @default.
• W1983992248 cites W2126703278 @default.
• W1983992248 cites W2129464821 @default.
• W1983992248 cites W2133425694 @default.
• W1983992248 cites W2133851850 @default.
• W1983992248 cites W2135695572 @default.
• W1983992248 cites W2136636747 @default.
• W1983992248 cites W2139525108 @default.
• W1983992248 cites W2139565535 @default.
• W1983992248 cites W2140217857 @default.
• W1983992248 cites W2141145624 @default.
• W1983992248 cites W2142763255 @default.
• W1983992248 cites W2148119123 @default.
• W1983992248 cites W2148233263 @default.
• W1983992248 cites W2150523054 @default.
• W1983992248 cites W2150986124 @default.
• W1983992248 cites W2158669261 @default.
• W1983992248 cites W2161105229 @default.
• W1983992248 cites W2164198104 @default.
• W1983992248 cites W2167695859 @default.
• W1983992248 cites W2169059815 @default.
• W1983992248 cites W2177299793 @default.
• W1983992248 cites W228375214 @default.
• W1983992248 cites W2318655468 @default.
• W1983992248 cites W2322480672 @default.
• W1983992248 cites W2333389735 @default.
• W1983992248 cites W4234750113 @default.
• W1983992248 cites W4240911509 @default.
• W1983992248 cites W4243825911 @default.
• W1983992248 doi "https://doi.org/10.1016/j.rse.2014.04.026" @default.
• W1983992248 hasPublicationYear "2014" @default.
• W1983992248 type Work @default.
• W1983992248 sameAs 1983992248 @default.
• W1983992248 citedByCount "47" @default.
• W1983992248 countsByYear W19839922482015 @default.
• W1983992248 countsByYear W19839922482016 @default.
• W1983992248 countsByYear W19839922482017 @default.
• W1983992248 countsByYear W19839922482018 @default.
• W1983992248 countsByYear W19839922482019 @default.
• W1983992248 countsByYear W19839922482020 @default.
• W1983992248 countsByYear W19839922482021 @default.
• W1983992248 countsByYear W19839922482022 @default.
• W1983992248 countsByYear W19839922482023 @default.
• W1983992248 crossrefType "journal-article" @default.
• W1983992248 hasAuthorship W1983992248A5043352426 @default.
• W1983992248 hasAuthorship W1983992248A5043761294 @default.
• W1983992248 hasAuthorship W1983992248A5045994689 @default.
• W1983992248 hasAuthorship W1983992248A5076590102 @default.
• W1983992248 hasConcept C100970517 @default.
• W1983992248 hasConcept C101000010 @default.
• W1983992248 hasConcept C132124917 @default.
• W1983992248 hasConcept C132215390 @default.
• W1983992248 hasConcept C142724271 @default.

• next