Riparian Vegetation Monitoring 

and Research

GCMRC Annual Reporting Meeting 2019

Brad Butterfield1, Joel Sankey2, Emily 

Palmquist2, Laura Durning3

1 Center for Ecosystem Science and Society (ECOSS), Northern Arizona University

2 U.S. Geological Survey Grand Canyon Monitoring and Research Center

3 School of Earth and Sustainability, Northern Arizona University
Project C: Riparian Vegetation 

Monitoring and Research

• C.1 Ground-based vegetation monitoring

• Objective: Monitor annual changes to riparian species composition 

and cover

• C.2 Imagery-based vegetation monitoring at the landscape scale

• Objective: Monitor broad-scale change in riparian vegetation cover

• C.3 Vegetation responses to LTEMP flow scenarios

• Objective: Develop predictive models of vegetation composition as it 

relates to hydrological regime

• C.4 Vegetation management decision support

• Objective: Provide monitoring protocols and decision support tools for 

active vegetation management

• Funding for FY19 – $485,251 from AMP

• Cooperators

– Brad Butterfield & Laura Durning, NAU

– Northern Colorado Plateau Inventory and Monitoring Network, NPS
Project C: Products

• Butterfield, B.J., Palmquist, E.C., and Ralston, B.E., 2018, Hydrological regime and climate interactively shape riparian 

vegetation composition along the Colorado River, Grand Canyon: Applied Vegetation Science, 21, 572-583, 

https://doi.org/10.1111/avsc.12390.

• Bedford, A., Sankey, T.T., Sankey, J.B., Durning, L.E. and Ralston, B.E., 2018, Remote sensing derived maps of tamarisk (2009) 

and beetle impacts (2013) along 412 km of the Colorado River in the Grand Canyon, Arizona: U.S. Geological Survey data 

release, https://doi.org/10.5066/F72B8X71.

• Bedford, A., Sankey, T.T., Sankey, J.B., Durning, L., Ralston B.E., 2018, Remote sensing of tamarisk beetle (Diorhabda

carinulata) impacts along 412 km of the Colorado River in the Grand Canyon, Arizona, USA: Ecological Indicators, 89, 365-

375, https://doi.org/10.1016/j.ecolind.2018.02.026.

• Durning, L.E., Sankey, J.B., Bedford, A., and Sankey, T.T., 2018, Riparian species vegetation classification data for the Colorado 

River within Grand Canyon derived from 2013 airborne imagery: U.S. Geological Survey data release, 

https://doi.org/10.5066/P9OUB1RS.

• Sankey, J.B., Chain, G.R., Solazzo, D., Durning, L.E., Bedford, A., Grams, P.E., and Ross, R.P., 2018, Sand classifications along the 

Colorado River in Grand Canyon derived from 2002, 2009, and 2013 high-resolution multispectral airborne imagery: U.S. 

Geological Survey data release, https://doi.org/10.5066/P99TN424.

• Kasprak, A., Sankey, J.B., Buscombe, D., Caster, J., East, A.E. and Grams, P.E., 2018. Quantifying and forecasting changes in the 

areal extent of river valley sediment in response to altered hydrology and land cover. Progress in Physical Geography: Earth 

and Environment, 42, 739-764.

• Palmquist, E.C., Ralston, B.E., Merritt, D.M., and Shafroth, P.B., 2018, Landscape-scale processes influence riparian plant 

composition along a regulated river: Journal of Arid Environments, v. 148, p. 54-64, 

https://doi.org/10.1016/j.jaridenv.2017.10.001.

• Palmquist, E.C., Ralston, B.E., Sarr, D.A., and Johnson, T.C., 2018b, Monitoring riparian-vegetation composition and cover 

along the Colorado River downstream of Glen Canyon Dam, Arizona: U.S. Geological Survey Techniques and Methods, book 2, 

chap. A14, 65 p., https://doi.org/10.3133/tm2A14

• Palmquist, E.C., 2018, Climate, hydrology and riparian vegetation composition data, Grand Canyon, Arizona: U.S. Geological 

Survey data release, https://doi.org/10.5066/F7DN4493
C.1 Ground-based vegetation 

monitoring

• NAU sandbars

• Coupled with DEMs 

for high-resolution 

analysis

• Relevant to camp 

sites

• Random sites

• Multiple geomorphic 

features

• Broader picture of 

entire CRe
C.1 Ground-based vegetation 

monitoring (cont.)

• Protocol published 

under USGS 

Techniques and 

Methods 

(Palmquist and 

others, 2018)

• Has been 

implemented since 

2013
Site Selection
Delineating 

Hydrological 

Zones
Positioning 

Transects and Plots
C.2 Imagery-based vegetation 

monitoring (cont., 1)

Durning and others, 2018, USGS data release
C.2 Imagery-based vegetation 

monitoring (cont., 2)

Durning and others, 2018, USGS data release
C.2 Imagery-based vegetation 

monitoring (cont., 3)

Beetle-impacted tamarisk (in percent) by 1.61 km river reaches and overall 

accuracies throughout the study region (Bedford and others 2018)
C.3 Vegetation responses to LTEMP 

flow scenarios

• Sandbar habitat suitability models for

• 16 woody species (shrubs/trees)

• 58 herbaceous species (grass/forb)

• Hydrological variables

• Elevation above channel

• Inundation duration

• Climate variables

• Minimum temperature

• Maximum temperature

• Annual precipitation

Preliminary data, do not cite
C.3 Vegetation responses to LTEMP 

flow scenarios (cont., 1)

• Predict spatial variation in 

habitat suitability across 

sandbars

1991 at 51 Mile

Preliminary data, do not cite
C.3 Vegetation responses to LTEMP 

flow scenarios (cont., 2)

• Predict spatial variation in 

habitat suitability across 

sandbars

1991 at 51 Mile

Preliminary data, do not cite
C.3 Vegetation responses to LTEMP 

flow scenarios (cont., 3)

• Predict spatial variation in 

habitat suitability across 

sandbars

• Can simulate responses 

based on different flow 

scenarios

1991 at 51 Mile

Preliminary data, do not cite
C.3 Vegetation responses to LTEMP 

flow scenarios (cont., 4)

• Active Channel

• Inundated by 

hydropeaking or base 

flows

• Active Floodplain

• Inundated by HFEs

• Inactive Floodplain

• Historical floodplain, no 

longer inundated

Butterfield and others, 2018, AppVegSci

Vegetation Optima
C.3 Vegetation responses to LTEMP 

flow scenarios (cont., 5)

• Woody vegetation 

has expanded into 

very wet conditions, 

herbaceous plants 

would like it even 

wetter

• Vegetation responds 

strongly to 

hydrological 

zonation, but is 

highly variable within 

zones

Butterfield and others, 2018 AppVegSci

Vegetation Optima
C.3 Vegetation responses to LTEMP 

flow scenarios (cont., 6)

• Hydrology and climate 

interact to shape 

vegetation

• Precipitation interacts with 

elevation above channel

• Temperature interacts with 

inundation duration

• Climate variability can 

impact response to flow 

regime, and/or vice versa

• Long-term predictions for 

management success

Tradeoff between inundation and 

heat tolerance

Butterfield and others, 2018 AppVegSci

CWM

Spp
C.4 Vegetation management decision 

support

• 3 meetings with Tribal Stakeholders and NPS in 2018

• reviewed project goals and proposed methods

• outlined likely sites to be treated

• Projected launch on April 16th for first non-flow 

vegetation mitigation work in GRCA

• NPS vegetation removal planned at 4-5 sites with sandbardune field-arch site complexes

• Follow-up monitoring by Joel Sankey (GCMRC)

• Continued NPS work at -7 Mile in GLCA

• Dead tamarisk has been removed, being chipped

• Native plants being propagated for planting this fall