Sehee Kim - Academia.edu (original) (raw)

Papers by Sehee Kim

Endocrine Journal, 2009

Ghrelin is known to promote neuronal defense and survival against ischemic injury by inhibiting a... more Ghrelin is known to promote neuronal defense and survival against ischemic injury by inhibiting apoptotic processes. In the present study, we investigated the role of prostate apoptosis response-4 (Par-4), a proapoptotic gene the expression of which is increased after ischemic injury, in ghrelin-mediated neuroprotection during middle cerebral artery occlusion (MCAO). Both ghrelin and des-acyl ghrelin protected cortical neurons from ischemic injury. Ghrelin receptor specific antagonist abolished the protective effects of ghrelin, whereas those of des-acyl ghrelin were preserved, suggesting the involvement of a receptor that is distinct from GHS-R1a. The expression of Par-4 was increased by MCAO, which was attenuated by ghrelin and des-acyl ghrelin treatments. Both ghrelin and des-acyl ghrelin increased the Bcl-2/Bax ratio, prevented cytochrome c release, and inhibited caspase-3 activation. Our data indicate that des-acyl ghrelin, as well as ghrelin, protect cortical neurons against ischemic injury through the inhibition of Par-4 expression and apoptotic molecules in mitochondrial pathway.

Neurotoxicity Research, 2009

Ghrelin is an endogenous ligand for growth hormone (GH) secretagogue receptor 1a (GHS-R1a) and is... more Ghrelin is an endogenous ligand for growth hormone (GH) secretagogue receptor 1a (GHS-R1a) and is produced and released mainly from the stomach. It was recently demonstrated that ghrelin can function as a neuroprotective factor by inhibiting apoptotic pathways. 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) causes nigrostriatal dopaminergic neurotoxicity in rodents; previous studies suggest that activated microglia actively participate in the pathogenesis of Parkinson’s disease (PD) neurodegeneration. However, the role of microglia in the neuroprotective properties of ghrelin is still unknown. Here we show that, in the mouse MPTP PD model generated by an acute regimen of MPTP administration, systemic administration of ghrelin significantly attenuates the loss of substantia nigra pars compacta (SNpc) neurons and the striatal dopaminergic fibers through the activation of GHS-R1a. We also found that ghrelin reduced nitrotyrosine levels and improved the impairment of rota-rod performance. Ghrelin prevents MPTP-induced microglial activation in the SNpc and striatum, the expression of pro-inflammatory molecules tumor necrosis factor α (TNF-α) and interleukin-1β (IL-1β), and the activation of inducible nitric oxide synthase. The inhibitory effect of ghrelin on the activation of microglia appears to be indirect by suppressing matrix metalloproteinase-3 (MMP-3) expression in stressed dopaminergic neurons because GHS-R1a is not expressed in SNpc microglial cells. Finally, in vitro administration of ghrelin prevented 1-methyl-4-phenylpyridinium-induced dopaminergic cell loss, MMP-3 expression, microglial activation, and the subsequent release of TNF-α, IL-1β, and nitrite in mesencephalic cultures. Our data indicate that ghrelin may act as a survival factor for dopaminergic neurons by functioning as a microglia-deactivating factor and suggest that ghrelin may be a valuable therapeutic agent for neurodegenerative diseases such as PD.

Endocrine Journal, 2009

The aim of our study was to investigate the effect of the peripheral administration of ghrelin, a... more The aim of our study was to investigate the effect of the peripheral administration of ghrelin, a peptide hormone secreted from the stomach, on cellular proliferation and differentiation of progenitor cells in the adult hippocampus. Double immunohistochemical staining revealed that Ki-67-positive hippocampal progenitor cells expressed ghrelin receptors. In mice treated with ghrelin (80 microg/kg, i.p.) for 8 days, bromodeoxyuridine incorporation and doublecortin-positive neuroblasts were significantly increased in the dentate subgranular zone. We also found that the numbers of bromodeoxyuridine- and doublecortin-immunoreactive cells were significantly reduced after anti-ghrelin antibody (10 microg/kg, i.p.) treatment for 8 days. Therefore, our results indicate that ghrelin induces proliferation and differentiation of adult hippocampal progenitors, suggesting an involvement of ghrelin in hippocampal neurogenesis.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Endocrine Journal, 2009

Ghrelin is known to promote neuronal defense and survival against ischemic injury by inhibiting a... more Ghrelin is known to promote neuronal defense and survival against ischemic injury by inhibiting apoptotic processes. In the present study, we investigated the role of prostate apoptosis response-4 (Par-4), a proapoptotic gene the expression of which is increased after ischemic injury, in ghrelin-mediated neuroprotection during middle cerebral artery occlusion (MCAO). Both ghrelin and des-acyl ghrelin protected cortical neurons from ischemic injury. Ghrelin receptor specific antagonist abolished the protective effects of ghrelin, whereas those of des-acyl ghrelin were preserved, suggesting the involvement of a receptor that is distinct from GHS-R1a. The expression of Par-4 was increased by MCAO, which was attenuated by ghrelin and des-acyl ghrelin treatments. Both ghrelin and des-acyl ghrelin increased the Bcl-2/Bax ratio, prevented cytochrome c release, and inhibited caspase-3 activation. Our data indicate that des-acyl ghrelin, as well as ghrelin, protect cortical neurons against ischemic injury through the inhibition of Par-4 expression and apoptotic molecules in mitochondrial pathway.

Neurotoxicity Research, 2009

Ghrelin is an endogenous ligand for growth hormone (GH) secretagogue receptor 1a (GHS-R1a) and is... more Ghrelin is an endogenous ligand for growth hormone (GH) secretagogue receptor 1a (GHS-R1a) and is produced and released mainly from the stomach. It was recently demonstrated that ghrelin can function as a neuroprotective factor by inhibiting apoptotic pathways. 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) causes nigrostriatal dopaminergic neurotoxicity in rodents; previous studies suggest that activated microglia actively participate in the pathogenesis of Parkinson’s disease (PD) neurodegeneration. However, the role of microglia in the neuroprotective properties of ghrelin is still unknown. Here we show that, in the mouse MPTP PD model generated by an acute regimen of MPTP administration, systemic administration of ghrelin significantly attenuates the loss of substantia nigra pars compacta (SNpc) neurons and the striatal dopaminergic fibers through the activation of GHS-R1a. We also found that ghrelin reduced nitrotyrosine levels and improved the impairment of rota-rod performance. Ghrelin prevents MPTP-induced microglial activation in the SNpc and striatum, the expression of pro-inflammatory molecules tumor necrosis factor α (TNF-α) and interleukin-1β (IL-1β), and the activation of inducible nitric oxide synthase. The inhibitory effect of ghrelin on the activation of microglia appears to be indirect by suppressing matrix metalloproteinase-3 (MMP-3) expression in stressed dopaminergic neurons because GHS-R1a is not expressed in SNpc microglial cells. Finally, in vitro administration of ghrelin prevented 1-methyl-4-phenylpyridinium-induced dopaminergic cell loss, MMP-3 expression, microglial activation, and the subsequent release of TNF-α, IL-1β, and nitrite in mesencephalic cultures. Our data indicate that ghrelin may act as a survival factor for dopaminergic neurons by functioning as a microglia-deactivating factor and suggest that ghrelin may be a valuable therapeutic agent for neurodegenerative diseases such as PD.

Endocrine Journal, 2009

The aim of our study was to investigate the effect of the peripheral administration of ghrelin, a... more The aim of our study was to investigate the effect of the peripheral administration of ghrelin, a peptide hormone secreted from the stomach, on cellular proliferation and differentiation of progenitor cells in the adult hippocampus. Double immunohistochemical staining revealed that Ki-67-positive hippocampal progenitor cells expressed ghrelin receptors. In mice treated with ghrelin (80 microg/kg, i.p.) for 8 days, bromodeoxyuridine incorporation and doublecortin-positive neuroblasts were significantly increased in the dentate subgranular zone. We also found that the numbers of bromodeoxyuridine- and doublecortin-immunoreactive cells were significantly reduced after anti-ghrelin antibody (10 microg/kg, i.p.) treatment for 8 days. Therefore, our results indicate that ghrelin induces proliferation and differentiation of adult hippocampal progenitors, suggesting an involvement of ghrelin in hippocampal neurogenesis.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.

Forest Ecology and Management, 2000

Soil temperature is a variable that links surface structure to soil processes and yet its spatial... more Soil temperature is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. In this study, a hybrid soil temperature model was developed to predict daily spatial patterns of soil temperature in a forested landscape by incorporating the effects of topography, canopy and ground litter. The model is based on both heat transfer physics and empirical relationship between air and soil temperature, and uses input variables that are extracted from a digital elevation model (DEM), satellite imagery, and standard weather records. Model-predicted soil temperatures ®tted well with data measured at 10 cm soil depth at three sites: two hardwood forests and a bare soil area. A sensitivity analysis showed that the model was highly sensitive to leaf area index (LAI) and air temperature. When the spatial pattern of soil temperature in a forested watershed was simulated by the model, different responses of bare and canopy-closed ground to air temperature were identi®ed. Spatial distribution of daily air temperature was geostatistically interpolated from the data of weather stations adjacent to the simulated area. Spatial distribution of LAI was obtained from Landsat Thematic Mapper images. The hybrid model describes spatial variability of soil temperature across landscapes and different sensitivity to rising air temperature depending on site-speci®c surface structures, such as LAI and ground litter stores.