%0 Journal Article %1 soto_tree_2017 %A Soto, Gerardo E. %A Pérez-Hernández, Christian G. %A Hahn, Ingo J. %A Rodewald, Amanda D. %A Vergara, Pablo M. %D 2017 %J Remote Sensing of Environment %K Habitat Plant Reflectance Senescence %P 1--10 %R 10.1016/j.rse.2017.02.018 %T Tree senescence as a direct measure of habitat quality: Linking red-edge Vegetation Indices to space use by Magellanic woodpeckers %U https://www.sciencedirect.com/science/article/pii/S0034425717300755 %V 193 %X Accurate estimates of the quality and quantity of remnant habitats is critical for planning management activities for the conservation of threatened species. Although habitat quality usually is understood from a multidimensional niche space approach, the availability of foraging substrates can be a suitable and more proximate index of habitat quality for species with specialized habitat requirements, like woodpeckers that feed almost exclusively on larvae of wood-boring beetles in the trunks and branches of infested trees. Recent approaches use simple mathematical algorithms on spectral bands called Vegetation Indices (VI) to identify infestations, providing a new opportunity to assess habitat quality for woodpeckers. In this paper, we tested the ability of 102 VI to estimate tree attributes explaining habitat quality for Magellanic woodpeckers for its usage as a reliable foraging habitat quality estimator. We hypothesized that space use of Magellanic woodpeckers is positively associated with the spatial distribution of decayed trees in the landscape. We developed a methodological framework based on high-resolution, multispectral imagery with three basic steps. First, we mapped individual Nothofagus trees based on estimates of species composition from a supervised classification procedure, VI estimates and image segmentation. Second, we selected the best VI predicting the tree quality for Magellanic woodpeckers. Third, we tested these habitat quality predictors, the species composition and tree age, by using two Synoptic Models of Space Use (SMSU) of Magellanic woodpeckers based on very high-frequency (VHF) radio-telemetry and global positioning system (GPS) telemetry data. Generalized Linear Mixed Models (GLMM) showed that the VI that best predicted habitat quality at the tree-scale was the Plant Senescence Reflectance Index (PSRI, computed as Red-Blue/Red-edge), included in almost all the most parsimonious models. The most parsimonious SMSU included only PSRI as an independent covariate, with a strong positive relation. Although coefficient differences were found between telemetry data (VHF vs. GPS data) both showed a positive overall response. Consequently, Red-edge based PSRI can be considered a reliable estimator of tree-scale foraging habitat quality at landscape extents for future research and management activities including Magellanic woodpeckers living on heterogeneous Nothofagus forests.

@article{soto_tree_2017, abstract = {Accurate estimates of the quality and quantity of remnant habitats is critical for planning management activities for the conservation of threatened species. Although habitat quality usually is understood from a multidimensional niche space approach, the availability of foraging substrates can be a suitable and more proximate index of habitat quality for species with specialized habitat requirements, like woodpeckers that feed almost exclusively on larvae of wood-boring beetles in the trunks and branches of infested trees. Recent approaches use simple mathematical algorithms on spectral bands called Vegetation Indices (VI) to identify infestations, providing a new opportunity to assess habitat quality for woodpeckers. In this paper, we tested the ability of 102 VI to estimate tree attributes explaining habitat quality for Magellanic woodpeckers for its usage as a reliable foraging habitat quality estimator. We hypothesized that space use of Magellanic woodpeckers is positively associated with the spatial distribution of decayed trees in the landscape. We developed a methodological framework based on high-resolution, multispectral imagery with three basic steps. First, we mapped individual Nothofagus trees based on estimates of species composition from a supervised classification procedure, VI estimates and image segmentation. Second, we selected the best VI predicting the tree quality for Magellanic woodpeckers. Third, we tested these habitat quality predictors, the species composition and tree age, by using two Synoptic Models of Space Use (SMSU) of Magellanic woodpeckers based on very high-frequency (VHF) radio-telemetry and global positioning system (GPS) telemetry data. Generalized Linear Mixed Models (GLMM) showed that the VI that best predicted habitat quality at the tree-scale was the Plant Senescence Reflectance Index (PSRI, computed as [Red-Blue]/Red-edge), included in almost all the most parsimonious models. The most parsimonious SMSU included only PSRI as an independent covariate, with a strong positive relation. Although coefficient differences were found between telemetry data (VHF vs. GPS data) both showed a positive overall response. Consequently, Red-edge based PSRI can be considered a reliable estimator of tree-scale foraging habitat quality at landscape extents for future research and management activities including Magellanic woodpeckers living on heterogeneous Nothofagus forests.}, added-at = {2021-08-27T23:27:28.000+0200}, author = {Soto, Gerardo E. and Pérez-Hernández, Christian G. and Hahn, Ingo J. and Rodewald, Amanda D. and Vergara, Pablo M.}, biburl = {https://www.bibsonomy.org/bibtex/2de7afc8c9ca6de5d9d87b82ed9e1dfb8/gerardo.soto}, doi = {10.1016/j.rse.2017.02.018}, interhash = {6ccdd086b62751e69ee85e9e463c39af}, intrahash = {de7afc8c9ca6de5d9d87b82ed9e1dfb8}, issn = {0034-4257}, journal = {Remote Sensing of Environment}, keywords = {Habitat Plant Reflectance Senescence}, month = may, pages = {1--10}, timestamp = {2021-08-27T23:27:28.000+0200}, title = {Tree senescence as a direct measure of habitat quality: {Linking} red-edge {Vegetation} {Indices} to space use by {Magellanic} woodpeckers}, url = {https://www.sciencedirect.com/science/article/pii/S0034425717300755}, volume = 193, year = 2017 }