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Christina Tague  - - - 
Top co-authors See all
K. Farley

232 shared publications

Division of Geological and Planetary Sciences; California Institute of Technology; Pasadena CA

Dar A. Roberts

231 shared publications

Department of Geography, University of California, Santa Barbara, CA 93106, USA

Jon Chorover

194 shared publications

Department of Soil, Water and Environmental Science; University of Arizona; Tucson AZ USA

Michael Farrell

169 shared publications

National Drug and Alcohol Research Centre; University of New South Wales, Australia; Sydney NSW Australia

Glen E. Liston

144 shared publications

Colorado State University

Publication Record
Distribution of Articles published per year 
(1970 - 2018)
Publications See all
Article 0 Reads 0 Citations Using Imaging Spectrometry to Study Changes in Crop Area in California’s Central Valley during Drought Sarah W. Shivers, Dar A. Roberts, Joseph P. McFadden, Christ... Published: 27 September 2018
Remote Sensing, doi: 10.3390/rs10101556
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In California, predicted climate warming increases the likelihood of extreme droughts. As irrigated agriculture accounts for 80% of the state’s managed water supply, the response of the agricultural sector will play a large role in future drought impacts. This study examined one drought adaptation strategy, changes in planting decisions, using Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery from June 2013, 2014, and 2015 from the Central Valley of California. We used the random forest classifier to classify crops into categories of similar water use. Classification accuracy was assessed using the random forest out-of-bag accuracy, and an independently validated accuracy at both the pixel and field levels. These results were then compared to simulated Landsat Operational Land Imager (OLI) and simulated Sentinel-2B results. The classification was further analyzed for method portability and band importance. The resultant crop maps were used to analyze changes in crop area as one measure of agricultural adaptation in times of drought. The results showed overall field-level accuracies of 94.4% with AVIRIS, as opposed to 90.4% with Landsat OLI and 91.7% with Sentinel, indicating that hyperspectral imagery has the potential to identify crops by water-use group at a single time step at higher accuracies than multispectral sensors. Crop maps produced using the random forest classifier indicated that the total crop area decreased as the drought persisted from 2013 to 2015. Changes in area by crop type revealed that decisions regarding which crop to grow and which to fallow in times of drought were not driven by the average water requirements of crop groups, but rather showed possible linkages to crop value and/or crop permanence.
Article 4 Reads 0 Citations Accounting for disturbance history in models: using remote sensing to constrain carbon and nitrogen pool spin-up Christina Tague, Janet Choate, Mingliang Liu, Crystal Kolden... Published: 26 April 2018
Ecological Applications, doi: 10.1002/eap.1718
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Article 3 Reads 1 Citation Balancing uncertainty and complexity to incorporate fire spread in an eco-hydrological model Maureen C. Kennedy, Donald McKenzie, Christina Tague, Aubrey... Published: 01 January 2017
International Journal of Wildland Fire, doi: 10.1071/WF16169
DOI See at publisher website
Article 2 Reads 0 Citations Populations of aspen (Populus tremuloidesMichx.) with different evolutionary histories differ in their climate occupancy Burke T. Greer, Christopher Still, Glenn T. Howe, Christina ... Published: 30 March 2016
Ecology and Evolution, doi: 10.1002/ece3.2102
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Quaking aspens (Populus tremuloides Michx.) are found in diverse habitats throughout North America. While the biogeography of aspens' distribution has been documented, the drivers of the phenotypic diversity of aspen are still being explored. In our study, we examined differences in climate between northern and southwestern populations of aspen, finding large-scale differences between the populations. Our results suggest that northern and southwestern populations live in distinct climates and support the inclusion of genetic and phenotypic data with species distribution modeling for predicting aspens' distribution.
Article 2 Reads 1 Citation Social Science/Natural Science Perspectives on Wildfire and Climate Change Andrew Ayres, Alexander DeGolia, Matthew Fienup, Yunyeol Kim... Published: 01 February 2016
Geography Compass, doi: 10.1111/gec3.12259
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Article 2 Reads 6 Citations An Eco-Hydrological Model-Based Assessment of the Impacts of Soil and Water Conservation Management in the Jinghe River ... Hui Peng, Yangwen Jia, Christina (Naomi) Tague, Peter Slaugh... Published: 11 November 2015
Water, doi: 10.3390/w7116301
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Many soil and water conservation (SWC) measures have been applied in the Jinghe River Basin to decrease soil erosion and restore degraded vegetation cover. Analysis of historical streamflow records suggests that SWC measures may have led to declines in streamflow, although climate and human water use may have contributed to observed changes. This paper presents an application of a watershed-scale, physically-based eco-hydrological model—the Regional Hydro-Ecological Simulation System (RHESSys)—in the Jinghe River Basin to study the impacts of SWC measures on streamflow. Several extensions to the watershed-scale RHESSys model were made in this paper to support the model application at larger scales (>10,000 km2) of the Loess Plateau. The extensions include the implementation of in-stream routing, reservoir sub-models and representation of soil and water construction engineering (SWCE). Field observation data, literature values and remote sensing data were used to calibrate and verify the model parameters. Three scenarios were simulated and the results were compared to quantify both vegetation recovery and SWCE impacts on streamflow. Three scenarios respectively represent no SWC, vegetation recovery only and both vegetation recovery and SWCE. The model results demonstrate that the SWC decreased annual streamflow by 8% (0.1 billion m3), with the largest decrease occurring in the 2000s. Model estimates also suggest that SWCE has greater impacts than vegetation recovery. Our study provides a useful tool for SWC planning and management in this region.