Integrating modelling and remote sensing to identify ecosystem performance anomalies in the boreal forest, Yukon River Basin, Alaska

2008 ◽  
Vol 1 (2) ◽  
pp. 196-220 ◽  
Author(s):  
B.K. Wylie ◽  
L. Zhang ◽  
N. Bliss ◽  
L. Ji ◽  
L.L. Tieszen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boreal Forest ◽  
River Basin ◽  
Yukon River ◽  
Yukon River Basin

Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

2015 ◽  
Vol 36 (4) ◽  
pp. 939-953 ◽  
Author(s):  
Lei Ji ◽  
Bruce K. Wylie ◽  
Dana R. N. Brown ◽  
Birgit Peterson ◽  
Heather D. Alexander ◽  
...  
Keyword(s):  
Boreal Forest ◽  
River Basin ◽  
Forest Biomass ◽  
Spatially Explicit ◽  
Yukon River ◽  
Yukon River Basin

Importance of large woody debris for juvenile chinook salmon habitat in small boreal forest streams in the upper Yukon River basin, Canada

2004 ◽  
Vol 34 (9) ◽  
pp. 1955-1966 ◽  
Author(s):  
Brent Mossop ◽  
Michael J Bradford
Keyword(s):  
Boreal Forest ◽  
River Basin ◽  
Chinook Salmon ◽  
Woody Debris ◽  
Large Woody Debris ◽  
Juvenile Chinook Salmon ◽  
Yukon River ◽  
Yukon River Basin ◽  
Juvenile Chinook ◽  
Forest Streams

The importance of large woody debris (LWD) in forested stream ecosystems is well documented. However, little is known about LWD in northern boreal forest streams. We investigated the abundance, characteristics, and function of LWD in 13 small tributary streams of the upper Yukon River basin, Yukon Territory, Canada. LWD abundance was similar to values reported from temperate regions, whereas LWD size and total volume were well below values for the Pacific Northwest. LWD formed 28% of the pools, which provide important habitat for juvenile chinook salmon (Oncorhynchus tshawytscha Walbaum). The median diameter of pool-forming pieces was 17 cm, and ring counts on fallen riparian trees indicated that pool-forming pieces were likely 70–200 years old when downed. Juvenile chinook salmon density was correlated with LWD abundance in our study reaches. We conclude that despite differences in climate and forest type, LWD in Yukon streams and LWD in temperate regions appear to perform a similar function in creating fish habitat. Resource managers should consider the relatively slow tree growth and thus potentially long recovery times following human disturbances in these watersheds.

Remote Sensing, the Archival Record, and Modeling Ecosystem Processes in the Yukon River Basin

2011 ◽  
Author(s):  
Larry Tieszen ◽  
Bruce Wylie ◽  
Jennifer Rover ◽  
Lei Ji ◽  
Laura Bourgeau‐Chavez ◽  
...  
Keyword(s):  
Remote Sensing ◽  
River Basin ◽  
Ecosystem Processes ◽  
Yukon River ◽  
Yukon River Basin ◽  
Archival Record

Assessment of boreal forest historical C dynamics in the Yukon River Basin: relative roles of warming and fire regime change

2012 ◽  
Vol 22 (8) ◽  
pp. 2091-2109 ◽  
Author(s):  
F.-M. Yuan ◽  
S.-H. Yi ◽  
A. D. McGuire ◽  
K. D. Johnson ◽  
J. Liang ◽  
...  
Keyword(s):  
Boreal Forest ◽  
River Basin ◽  
Regime Change ◽  
Fire Regime ◽  
Yukon River ◽  
C Dynamics ◽  
Yukon River Basin

scholarly journals Effects of Disturbance and Climate Change on Ecosystem Performance in the Yukon River Basin Boreal Forest

2014 ◽  
Vol 6 (10) ◽  
pp. 9145-9169 ◽  
Author(s):  
Bruce Wylie ◽  
Matthew Rigge ◽  
Brian Brisco ◽  
Kevin Murnaghan ◽  
Jennifer Rover ◽  
...  
Keyword(s):  
Climate Change ◽  
Boreal Forest ◽  
River Basin ◽  
Yukon River ◽  
Yukon River Basin

Mercury Export from the Yukon River Basin and Potential Response to a Changing Climate

2011 ◽  
Vol 45 (21) ◽  
pp. 9262-9267 ◽  
Author(s):  
Paul F. Schuster ◽  
Robert G. Striegl ◽  
George R. Aiken ◽  
David P. Krabbenhoft ◽  
John F. Dewild ◽  
...  
Keyword(s):  
River Basin ◽  
Potential Response ◽  
Changing Climate ◽  
Yukon River ◽  
Yukon River Basin

A novel application of an adaptive surrogate-based modeling optimization (ASMO) for the Community Territory System Model (CTSM) in Alaska

2021 ◽  
Author(s):  
Yifan Cheng ◽  
Andrew Newman ◽  
Sean Swenson ◽  
David Lawrence ◽  
Anthony Craig ◽  
...  
Keyword(s):  
High Resolution ◽  
River Basin ◽  
Land Surface ◽  
Computational Cost ◽  
Reanalysis Data ◽  
Freshwater Ecosystems ◽  
System Model ◽  
Surface Model ◽  
Yukon River ◽  
Yukon River Basin

<p>Climate-induced changes in snow cover, river flow, and freshwater ecosystems will greatly affect the indigenous groups in the Alaska and Yukon River Basin. To support policy-making on climate adaptation and mitigation for these underrepresented groups, an ongoing interdisciplinary effort is being made to combine Indigenous Knowledge with western science (https://www.colorado.edu/research/arctic-rivers/).</p><p>A foundational component of this project is a high fidelity representation of the aforementioned land surface processes. To this end, we aim to obtain a set of reliable high-resolution parameters for the Community Territory System Model (CTSM) for the continental scale domain of Alaska and the entire Yukon River Basin, which will be used in climate change simulations. CTSM is a complex, physically based state-of-the-science land surface model that includes complex vegetation and canopy representation, a multi-layer snow model, as well as hydrology and frozen soil physics necessary for the representation of streamflow and permafrost. Two modifications to the default CTSM configuration were made. First, we used CTSM that is implemented with hillslope hydrology to better capture the fine-scale hydrologic spatial heterogeneity in complex terrain. Second, we updated the input soil textures and organic carbon in CTSM using the high-resolution SoilGrid dataset.</p><p>In this study, we performed a multi-objective optimization on snow and streamflow metrics using an adaptive surrogate-based modeling optimization (ASMO). ASMO permits optimization of complex land-surface models over large domains through the use of surrogate models to minimize the computational cost of running the full model for every parameter combination. We ran CTSM at a spatial resolution of 1/24<sup>th</sup> degree and a temporal resolution of one hour using the ERA5 reanalysis data as the meteorological forcings. The ERA5 reanalysis data were bias-corrected to account for the orographic effects. We will discuss the ASMO-CTSM coupling workflow, performance characteristics of the optimization (e.g., computational cost, iterations), and comparisons of the default configuration and optimized model performance.</p>

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