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C. Tague  - - - 
Top co-authors See all
Jon Chorover

149 shared publications

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

Glen E. Liston

145 shared publications

Mingliang Liu

116 shared publications

Dar A. Roberts

108 shared publications

Sarah Lewis

73 shared publications

Publication Record
Distribution of Articles published per year 
(1970 - 2018)
Total number of journals
published in
Publications See all
Article 1 Read 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: 24 March 2018
Ecological Applications, doi: 10.1002/eap.1718
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Disturbances such as wildfire, insect outbreaks, and forest clearing, play an important role in regulating carbon, nitrogen, and hydrologic fluxes in terrestrial watersheds. Evaluating how watersheds respond to disturbance requires understanding mechanisms that interact over multiple spatial and temporal scales. Simulation modeling is a powerful tool for bridging these scales; however, model projections are limited by uncertainties in the initial state of plant carbon and nitrogen stores. Watershed models typically use one of two methods to initialize these stores: spin-up to steady state, or remote sensing with allometric relationships. Spin-up involves running a model until vegetation reaches equilibrium based on climate; this approach assumes that vegetation across the watershed has reached maturity and is of uniform age, which fails to account for landscape heterogeneity and non-steady state conditions. By contrast, remote sensing, can provide data for initializing such conditions. However, methods for assimilating remote sensing into model simulations can also be problematic. They often rely on empirical allometric relationships between a single vegetation variable and modeled carbon and nitrogen stores. Because allometric relationships are species- and region-specific, they do not account for the effects of local resource limitation, which can influence carbon allocation (to leaves, stems, roots, etc.). To address this problem, we developed a new initialization approach using the catchment-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spin-up with the spatial fidelity of remote sensing. It uses remote sensing to define spatially explicit targets for one, or several vegetation state variables, such as leaf area index, across a watershed. The model then simulates the growth of carbon and nitrogen stores until the defined targets are met for all locations. We evaluated this approach in a mixed pine-dominated watershed in central Idaho, and a chaparral-dominated watershed in southern California. In the pine-dominated watershed, model estimates of carbon, nitrogen, and water fluxes varied among methods, while the target-driven method increased correspondence between observed and modeled streamflow. In the chaparral watershed, where vegetation was more homogeneously aged, there were no major differences among methods. Thus, in heterogeneous, disturbance-prone watersheds, the target-driven approach shows potential for improving biogeochemical projections. This article is protected by copyright. All rights reserved.
Article 1 Read 0 Citations 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
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Wildfire affects the ecosystem services of watersheds, and climate change will modify fire regimes and watershed dynamics. In many eco-hydrological simulations, fire is included as an exogenous force. Rarely are the bidirectional feedbacks between watersheds and fire regimes integrated in a simulation system because the eco-hydrological model predicts variables that are incompatible with the requirements of fire models. WMFire is a fire-spread model of intermediate complexity designed to be integrated with the Regional Hydro-ecological Simulation System (RHESSys). Spread in WMFire is based on four variables that (i) represent known influences on fire spread: litter load, relative moisture deficit, wind direction and topographic slope, and (ii) are derived directly from RHESSys outputs. The probability that a fire spreads from pixel to pixel depends on these variables as predicted by RHESSys. We tested a partial integration between WMFire and RHESSys on the Santa Fe (New Mexico) and the HJ Andrews (Oregon State) watersheds. Model assessment showed correspondence between expected spatial patterns of spread and seasonality in both watersheds. These results demonstrate the efficacy of an approach to link eco-hydrologic model outputs with a fire spread model. Future work will develop a fire effects module in RHESSys for a fully coupled, bidirectional model.
Article 1 Read 0 Citations Populations of aspen ( Populus tremuloides Michx.) with different evolutionary histories differ in their climate occupan... Burke Greer, Christopher Still, Glenn T. Howe, Christina Tag... 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 1 Read 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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In western North America, wildfire is a critical component of many ecosystems and a natural hazard that can result in catastrophic losses of human lives and property. Billions of dollars are spent suppressing wildfires each year. In the past decades, academic research has made substantial contributions to the understanding of fire and its interaction with climate and land management. Most reviews of the academic literature, however, are centered in either natural or social science. We offer an integrated cross-disciplinary guide to state-of-the art fire science and use this review to identify research gaps. We focus on the modern era and understanding fire in the context of a changing climate in western North America. We find that studies combining social and natural science perspectives remain limited and that interactions among coupled system components are poorly understood. For example, while natural science studies have identified how fuel treatments alter fire regimes, few social science studies examine how decisions are made about fuel treatments and how these decisions respond to changes in fire regimes. A key challenge is to better quantify the effects of actual fire management policies in a way that accounts for the complexity of coupled natural and natural–human system interactions.
Article 1 Read 4 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 Tague, Peter Slaughter 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.
Article 1 Read 25 Citations Hydrological partitioning in the critical zone: Recent advances and opportunities for developing transferable understand... Paul D. Brooks, Jon Chorover, Ying Fan, Sarah E. Godsey, Ree... Published: 01 September 2015
Water Resources Research, doi: 10.1002/2015wr017039
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