Vegetation productivity responses to drought on tribal lands in the four corners region of the Southwest USA. El-Vilaly, M. A. S., Didan, K., Marsh, S. E., van Leeuwen, W. J. D., Crimmins, M. A., & Munoz, A. B. Frontiers of Earth Science, 12(1):37–51, March, 2018. ![Vegetation productivity responses to drought on tribal lands in the four corners region of the Southwest USA [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex The droughts striking the Colorado Plateau, where the Hopi Tribe and Navajo Nation Native American reservation lands are located, and their impacts have appeared slowly and relatively unnoticed in conventional national drought monitoring efforts like the National Drought Monitor. To understand the effect of drought-based drivers on vegetation productivity in the Hopi Tribe and Navajo Nation reservation lands, an assessment approach was developed integrating climate, land cover types, and topographical data with annual geospatially explicit normalized difference vegetation index (NDVI)-related productivity from 1989 to 2014 derived from 15-day composite multi-sensor NDVI time series data. We studied vegetation-environment relationships by conducting multiple linear regression analysis to explain the driver of vegetation productivity changes. Our results suggest that the interannual change of vegetation productivity showed high variability in middle elevations where needleleaf forest is the dominant vegetation cover type. Our analysis also shows that the spatial variation in interannual variability of vegetation productivity was more driven by climate drivers than by topography ones. Specifically, the interannual variability in spring precipitation and fall temperature seems to be the most significant factor that correlated with the interannual variability in vegetation productivity during the last two and a half decades.
@article{el-vilaly_vegetation_2018,
title = {Vegetation productivity responses to drought on tribal lands in the four corners region of the {Southwest} {USA}},
volume = {12},
issn = {2095-0195},
url = {http://link.springer.com/10.1007/s11707-017-0646-z},
doi = {10.1007/s11707-017-0646-z},
abstract = {The droughts striking the Colorado Plateau, where the Hopi Tribe and Navajo Nation Native American reservation lands are located, and their impacts have appeared slowly and relatively unnoticed in conventional national drought monitoring efforts like the National Drought Monitor. To understand the effect of drought-based drivers on vegetation productivity in the Hopi Tribe and Navajo Nation reservation lands, an assessment approach was developed integrating climate, land cover types, and topographical data with annual geospatially explicit normalized difference vegetation index (NDVI)-related productivity from 1989 to 2014 derived from 15-day composite multi-sensor NDVI time series data. We studied vegetation-environment relationships by conducting multiple linear regression analysis to explain the driver of vegetation productivity changes. Our results suggest that the interannual change of vegetation productivity showed high variability in middle elevations where needleleaf forest is the dominant vegetation cover type. Our analysis also shows that the spatial variation in interannual variability of vegetation productivity was more driven by climate drivers than by topography ones. Specifically, the interannual variability in spring precipitation and fall temperature seems to be the most significant factor that correlated with the interannual variability in vegetation productivity during the last two and a half decades.},
number = {1},
journal = {Frontiers of Earth Science},
author = {El-Vilaly, Mohamed Abd Salam and Didan, Kamel and Marsh, Stuart E. and van Leeuwen, Willem J. D. and Crimmins, Michael A. and Munoz, Armando Barreto},
month = mar,
year = {2018},
keywords = {NALCMS},
pages = {37--51},
}
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To understand the effect of drought-based drivers on vegetation productivity in the Hopi Tribe and Navajo Nation reservation lands, an assessment approach was developed integrating climate, land cover types, and topographical data with annual geospatially explicit normalized difference vegetation index (NDVI)-related productivity from 1989 to 2014 derived from 15-day composite multi-sensor NDVI time series data. We studied vegetation-environment relationships by conducting multiple linear regression analysis to explain the driver of vegetation productivity changes. Our results suggest that the interannual change of vegetation productivity showed high variability in middle elevations where needleleaf forest is the dominant vegetation cover type. Our analysis also shows that the spatial variation in interannual variability of vegetation productivity was more driven by climate drivers than by topography ones. 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