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RESEARCH ARTICLE
Development of Vegetation and Aquatic Habitat in
Restored Riparian Sites of California’s North Coast
Rangelands
Michael S. Lennox,1,2David J. Lewis,1Randall D. Jackson,3John Harper,4Stephanie Larson,1
and Kenneth W. Tate5
Abstract
The preponderance of short-term objectives and lack of
systematic monitoring of restoration projects limits oppor-
tunities to learn from past experience and improve future
restoration efforts. We conducted a retrospective, cross-
sectional survey of 89 riparian revegetation sites and 13
nonrestored sites. We evaluated 36 restoration metrics at
each site and used project age (0–39 years) to quantify
plant community and aquatic habitat trajectories with a
maximum likelihood model selection approach to com-
pare linear and polynomial relationships. We found sig-
nificant correlations with project age for 16 of 21 ripar-
ian vegetation, and 11 of 15 aquatic habitat attributes.
Our results indicated improvements in multiple ecosystem
services and watershed functions such as diversity, sed-
imentation, carbon sequestration, and available habitat.
Ten riparian vegetation metrics, including native tree and
exotic shrub density, increased nonlinearly with project
age, while litter and native shrub density increased lin-
early. Species richness and cover of annual plants declined
over time. Improvements in aquatic habitat metrics, such
as increasing pool depth and decreasing bankfull width-
to-depth ratio, indicated potentially improved anadromous
fish habitats at restored sites. We hypothesize that certain
instream metrics did not improve because of spatial and/or
temporal limitations of riparian vegetation to affect aquatic
habitat. Restoration managers should be prepared to main-
tain or enhance understory diversity by controlling exotic
shrubs or planting shade-tolerant native species as much
as 10 years after revegetation.
Key words: site-specific riparian revegetation, trajectory
analysis, restoration monitoring, regional assessment, post-
project appraisal.
Introduction
Revegetation is a common tool to restore riparian areas for
many reasons, often by excluding livestock and/or planting
native trees. The number of river and stream restoration
projects in the United States has steadily increased since the
1980s from 100 to over 4,000 projects per year (Bernhardt
et al. 2005; Palmer et al. 2007). In California, over $2 billion
was spent on river restoration since 1980 with riparian
management the most common project type (Kondolf et al.
2007), but there has been limited systematic documentation of
project effectiveness to provide quality habitat and watershed
1University of California Cooperative Extension, Sonoma County, 133 Aviation
Boulevard, 109, Santa Rosa, CA 95403, U.S.A.
2Address correspondence to M. Lennox, email mslennox@comcast.net
3Department of Agronomy, University of Wisconsin-Madison, 1575 Linden Drive,
Madison, WI 53706-1597, U.S.A.
4University of California Cooperative Extension, Mendocino County, 890 N. Bush
Street, Ukiah, CA 95482, U.S.A.
5Department of Plant Sciences, University of California, Davis, Mail Stop 1, One
Shields Avenue, Davis, CA 95616-8780, U.S.A.
©2009 Society for Ecological Restoration International
doi: 10.1111/j.1526-100X.2009.00558.x
functions (Kondolf et al. 2007; Miller & Hobbs 2007; Palmer
et al. 2007).
Evaluation of previously restored sites has provided valu-
able feedback for understanding riparian habitat response
to various stream rehabilitation practices (Frissell & Nawa
1992; Opperman & Merenlender 2004; Tompkins & Kon-
dolf 2007). Numerous studies quantified riparian vegetation
recovery (Platts 1981; Kauffman et al. 1997; Opperman &
Merenlender 2000) and indirect recovery of aquatic habitat
has followed woody riparian vegetation establishment (Hupp
& Osterkamp 1996; Opperman & Merenlender 2004; Corenblit
et al. 2007). Restored project sites offer opportunities to learn
about resulting community structure and ecosystem processes
beyond static endpoints provided by reference sites (Parker
1997); however, long-term research over multiple decades
has been limited to case studies unable to quantify regional
variability or unintended consequences in a holistic evalua-
tion.
Some have used the amount of time since project imple-
mentation in various forms of trajectory analysis to provide
timelines for achieving specific objectives (Zedler & Callaway
1999; Golet et al. 2008). Watershed management carries the
Restoration Ecology 1
Developing California’s Vegetation and Aquatic Habitats
expectation that certain important societal objectives will be
achieved over time as a result of vegetation interacting with
physical processes (e.g., stochastic flood events transporting
sediment and pollutants). Examples of these objectives include
diversity (Hobbs 1993; Hupp & Osterkamp 1996), pollina-
tion (Kremen et al. 2004), sedimentation (Hupp & Osterkamp
1996; Corenblit et al. 2007), trophic dynamics (Baxter et al.
2005; Muotka & Syrjanen 2007), carbon storage (USDA 2000;
Bush 2008), nutrient cycling (Kauffman et al. 2004; Sheibley
et al. 2006; Bush 2008), water quality (Phillips 1989; Peterson
et al. 2001; Houlahan & Findlay 2004), infiltration (Kauff-
man et al. 2004), flood retention (Hupp & Osterkamp 1996;
Corenblit et al. 2007), available habitat (Dobkin et al. 1998;
Opperman & Merenlender 2004), and habitat use (Dobkin
et al. 1998; Golet et al. 2008). However, the trajectory analysis
has not been applied to watershed management in a holistic
approach using numerous attributes to assess the recovery of
multiple ecosystem services (Kremen 2005).
We conducted a retrospective, cross-sectional survey (i.e.,
chronosequence) of site-specific riparian revegetation projects
in three northern California coastal counties. Riparian veg-
etation and aquatic habitat response to stream rehabilitation
was quantified in a trajectory analysis using regression rela-
tionships with project age for 36 restoration metrics at 102
sites to provide a holistic regional evaluation of long-term
success over multiple decades. We used these trajectories to
infer changes in ecosystem services and watershed functions
(Black 1997) provided by riparian restoration.
Methods
Project Identification
Riparian revegetation sites were located in the mixed oak
woodland and annual grassland of California’s north coast. The
region has a Mediterranean climate with cool wet winters and
hot dry summers. However, this coastal region of California
is cooler with more moderate rainfall than most hardwood
rangelands. During the study period, mean annual precipitation
in the study area was 1,019 mm (range =679 −1,629 mm)
and mean annual temperatures were 13.7◦C (range =12.0−
15.1◦C). Streams and rivers in the region are dominated by
varying degrees of channel incision (Darby & Simon 1999)
and are located in watersheds with an average area of 23.5 km2
(range =0.2−133.1km
2), elevation of 145.3 m asl (range =
3.7−656.4 m asl), and 21.9% forested (range =0−100%).
We surveyed 102 sites in Marin, Mendocino, and Sonoma
Counties (Fig. 1). Sites were selected in collaboration with
consultants, agencies, and landowners, whose permission was
solicited for access to conduct surveys. Project cooperators
identified both “successful” and “unsuccessful” projects to be
included in the study. Site selection focused on projects with
documented implementation dates in alluvial stream reaches
of willow and mixed oak woodland vegetation with few trees
present prior to project installation (e.g., Fig. 2a). Surveyed
project sites were primarily on second- and third-order streams
with a range in project age from 4 to 39 years since restoration.
Revegetation design at surveyed projects (n=89) was
site-specific and focused on establishing Salix species to
“jump start” recovery of riparian forests to control erosion
and sustain multiple watershed functions (Kauffman et al.
Figure 1. The three county study areas north of San Francisco Bay including locations of restored and nonrestored survey sites (image courtesy of
Sonoma County GIS Central) a). Aerial view of an idealized survey site depicting belt transects, plots delineated by landform, and herbaceous quadrats
b). Stream channel cross-section showing landforms along a transect c).
2Restoration Ecology
Developing California’s Vegetation and Aquatic Habitats
Figure 2. Photographic time-series of an example project site on a tributary to Walker Creek in Marin County, documenting vegetation response at 0 a),
2 b), 8 c), and 12 years d) since restoration occurred (images courtesy of Marin Resource Conservation District).
1997). The methods utilized were often implemented as
combinations of practices including tree or shrub planting
with dormant willow posts or container plants (Johnson
2003), biotechnical bank stabilization (Johnson 2003; Flosi
et al. 2004), and passive restoration (Kauffman et al. 1997)
using large herbivore management (e.g., removal, reduced
stocking rate, or exclusionary fencing for livestock and/or
deer). Nonrestored sites were surveyed (n=13) where local
experts indicated that a particular stream reach had vegetation
similar in structure to the project site before revegetation
occurred.
Site Characterization
We characterized riparian forest and aquatic habitats at riparian
restoration project sites using 36 ecological attributes collected
at 5 nested spatial scales: (1) site (n=102, Fig. 1a), (2)
belt transect (n=3 per site, Fig. 1b), (3) landform class
(n=4 per transect, Fig. 1c), (4) plot (n=2+per landform),
and (5) quadrat (n=3 per plot, Fig. 1b). Landform classes
were delineated by channel morphology and depositional
or erosional features adapted from Harris (1987, 1999).
Specifically, we used the lowest observed bankfull location
and flood-prone elevation (2 ×bankfull depth) described by
Rosgen (1996) to delineate plots in the active floodplain. The
final plot sampled on each bank extended from the top of
the bank to the fence or field edge, and included alluvial
valley, terrace, or upland hillside geomorphic features. This
landform-based approach to collecting vegetation data allowed
for comparable results to be analyzed from various types of
stream channels.
At the site scale, data collected included small woody debris
(diameter <12 in), large woody debris (diameter >12 in),
and aggregate woody debris (debris jam clumps of 4 or more
pieces) counted within the bankfull channel (Flosi et al. 2004).
Pool characteristics assessed were mean pool depth,maximum
pool depth,pool frequency and percent pool habitat type (Flosi
et al. 2004). We collected stream substrate data at each site
and calculated percent fine sediment and embeddedness (Flosi
et al. 2004). The linear distance of riparian shade over the
thalweg was recorded at intervals with a hip chain as linear
channel canopy.
We placed three cross-sections and transects perpendicu-
lar to the channel stratified within each site at fast-water
riffle locations. Stream width and depth were measured and
documented as bankfull width-to-depth ratio (Rosgen 1996).
Streambank stability was assessed for both banks at each cross-
section according to Platts et al. (1987) and bank angle was
measured using a clinometer. Canopy density was measured
with a spherical densiometer following California Department
of Fish and Game protocols (Flosi et al. 2004) and solar radia-
tion was measured with a solar pathfinder by using the month
of August to standardize values before calculating intercepted
Restoration Ecology 3
Developing California’s Vegetation and Aquatic Habitats
solar radiation (Platts et al. 1987). Both measurements were
taken from the thalweg at each cross-section.
Data gathered within each plot included woody vegetation
density (trees >1m)andcanopy cover. Species identification
followed Hickman (1993). Herbaceous vegetation cover was
estimated using a modified Daubenmire Frame (20 ×50 cm)
to stratify quadrats equidistant in each plot perpendicular to
the stream channel (BLM 1996). The metric ground cover
included the sum of litter, vegetation, and stone cover (BLM
1996). Relative cover was calculated for six herbaceous
functional groups. Documenting survival was not possible
because of the lack of consistent record keeping on specific
numbers of plant species installed during the restoration
project and difficulty finding individual plantings in the field
at the oldest restored sites.
Data Analysis
We focused our analysis on detecting relationships between
project age and riparian forest and aquatic habitat metrics.
Plot and stream cross-section data were summarized into one
mean value of each metric by site for analysis to avoid
pseudoreplication (Hurlbert 1984). We then tested each metric
for curvilinear or linear fits. Models were constructed with
the generalized least squares function in S-Plus version 8
(Insightful Corp., Seattle, WA). Polynomial, linear, and null
(intercept only) models were compared with likelihood ratio
tests. If the models were significantly different (P <0.05),
we chose the model with the lowest Akaike Information
Criteria (AIC; Akaike 1974), otherwise the model with fewer
parameters was selected. If a linear model was better than the
polynomial model, we compared the linear model to a model
with no slope parameter using the same approach. Once best
fits were determined, the same parameters were estimated with
least squares regression to extract multiple R2values as an
assessment of goodness-of-fit.
Results
Riparian Vegetation
Sixteen of 21 riparian vegetation metrics were significantly
related to project age, including 12 positive and 4 negative tra-
jectories (Table 1). The considerable increase over time in total
woody vegetation (Fig. 3), native tree, and exotic shrub/vine
densities were best characterized by polynomial relationships
with project age, but only total woody vegetation had a rel-
atively good fit. Exotic tree density did not demonstrate a
significant trajectory while the best fit for native shrub/vine
density was linear, but the fit was poor (Table 1).
Total canopy cover, native tree canopy cover, ground
cover, and exposed root cover increased curvilinearly as a
Table 1. Riparian vegetation parameter estimates for best fits determined by likelihood ratio tests (P <0.05) comparing polynomial, linear, and null
models using generalized least squares.
Parameter Estimates
Restoration Metric Best Fit y-intercept xx
2R2
Density (individuals ha−1)
Total woody vegetation polynomial 459.8 329.9–7.60.39
Native tree polynomial 145.560.6–1.50.16
Native shrub/vine linear 204.825.1 — 0.08
Exotic tree n.s. 4.6— ——
Exotic shrub/vine polynomial 32.392.2–1.90.13
Absolute cover (%) — — — —
Total canopy polynomial 11.64.9–0.09 0.56
Native tree canopy polynomial 10.74.7–0.09 0.54
Ground cover polynomial 81.90.4–0.01 0.04
Exposed root polynomial –0.30.5–0.01 0.26
Total vegetation linear 43.2–0.3 — 0.05
Litter linear 19.90.4 — 0.21
Relative cover (%) — — — —
Native perennial grass n.s. 4.5— ——
Native perennial forb n.s. 2.5— ——
Exotic perennial grass n.s. 2.9— ——
Exotic perennial forb n.s. 1.8— ——
Annual grass polynomial 15.3–0.80.01 0.28
Annual forb polynomial 10.3–0.60.008 0.30
Species richness (spp. plot−1)————
Tree polynomial 0.60.16 –0.004 0.27
Shrub/vine polynomial 0.40.1–0.002 0.24
Perennial herbaceous polynomial 1.90.1–0.004 0.14
Annual herbaceous linear 4.4–0.1 — 0.21
Correlation coefficient (R2) determined with ordinary least squares regression.
4Restoration Ecology
Developing California’s Vegetation and Aquatic Habitats
Figure 3. Vegetation attributes as a function of project age (n=102) for
total woody density a), total canopy cover b), native tree cover c), and
annual forbs relative cover d).
function of project age, while litter cover increased in a linear
positive manner and total vegetation cover decreased linearly.
Native and exotic perennial grass and forb results were highly
variable and no significant relationships with project age were
found. Relative cover of annual forbs (Fig. 3) and grasses
had negative curvilinear trajectories. Species richness metrics
had positive curvilinear relationships to project age for the
tree, shrub/vine, and perennial herbaceous functional groups.
Annual species richness decreased linearly as project age
increased. Of all these significant relationships, the best fits
were total canopy cover and native tree canopy cover (Fig. 3).
Aquatic Habitat
Significant relationships with project age were observed for 11
of 15 aquatic habitat metrics, including eight positive and three
negative trajectories (Table 2). Stream channel morphology
results had significant trajectories for five of the six attributes.
The width-to-depth ratio of the bankfull channel had a negative
linear relationship with project age. Streambank stability had
a positive curvilinear relationship with project age and no
relationship was found for bank slope angle. The three woody
debris frequency metrics increased over time (Fig. 4). Small
and large wood frequencies were best described by curvilinear
relationships with project age, while aggregate debris jams of
wood were best described by a linear relationship.
Water column attributes had significant trajectories for six
of the nine investigated. Stream shade metrics, including
intercepted solar radiation, canopy density, and linear channel
canopy all increased curvilinearly over time (Fig. 4). Fine
sediment and embeddedness showed no significant trajectory.
Pool habitat metrics that had curvilinear relationships with
project age were maximum and mean pool depth as well as
pool habitat type. Pool frequency was not significantly related
to project age (Table 2).
Discussion
Riparian Vegetation
While many significant polynomial and linear relationships
with project age were detected, most were relatively weak
as indicated by the R2values. However, we expected high
variability given the complex biophysical settings inherent
to riparian ecosystems specifically and Mediterranean climate
in general. The fact that we detected trajectories at all
indicates their broad application and importance to understand
fundamental changes following restoration.
Site-specific revegetation strategies accomplished the main
objectives of increasing woody species abundance and diver-
sity. Native tree establishment was the focus of revegeta-
tion efforts, so the large increases in tree density and cover
were expected (Fig. 2). Overall, an indirect plant community
response was predicted to follow a successional shift over
time from exotic annual herbaceous species to woody veg-
etation composed of overstory trees with a mosaic of native
shrubs and herbaceous perennials (Parker 1997; Dobkin et al.
1998). We detected this basic sequence, although native peren-
nial grasses and forbs did not show any long-term directional
trend, and shrubs colonized faster than has been observed at
more xeric inland riparian areas (Dobkin et al. 1998). Tree
density peaked 15–25 years after restoration. Canopy cover
increase was relatively rapid indicating improved terrestrial
habitat for birds (Dobkin et al. 1998; White et al. 2005; Golet
et al. 2008), amphibians (USFWS 2002; Bulger et al. 2003),
and various wildlife species (Golet et al. 2008). In addition,
Restoration Ecology 5
Developing California’s Vegetation and Aquatic Habitats
Table 2. Aquatic habitat parameter estimates for best fits as determined by likelihood ratio tests (P <0.05) comparing polynomial, linear, and null models
using generalized least squares.
Parameter Estimates
Restoration Metric Best Fit y-intercept xx
2R2
Stream channel morphology
Bankfull width:depth ratio linear 35.5–0.6 — 0.10
Bank stability (%) polynomial 67.62.5–0.06 0.26
Bank slope (degrees) n.s. 15.2— ——
Small woody debris (count 100m–1)polynomial –0.40.5–0.007 0.48
Large woody debris (count 100m–1)polynomial –0.20.1–0.002 0.32
Aggregate woody debris (count 100m–1)linear 0.003 0.07 — 0.34
Water column
Intercepted solar radiation (%) polynomial 19.14.8–0.08 0.52
Canopy density (%) polynomial 12.35.0–0.08 0.49
Linear channel canopy (%) polynomial – 0.55.8–0.10.49
Fine sediment (%) n.s. 15.3— ——
Embeddedness (%) n.s. 41.2— ——
Pool habitat (%) polynomial 28.71.8–0.04 0.10
Pool frequency (count 100m–1)n.s. 3.3— ——
Maximum pool depth (m) polynomial 0.60.04 – 0.0009 0.19
Mean pool depth (m) polynomial 0.40.03 – 0.0007 0.18
Correlation coefficient (R2)determined with ordinary least squares regression.
Figure 4. Aquatic habitat attributes as a function of project age (n=102) for small woody debris a), large woody debris b), aggregate woody debris
jams c), intercepted solar radiation d), canopy density e), and linear channel canopy f).
6Restoration Ecology
Developing California’s Vegetation and Aquatic Habitats
riparian vegetation changes at restored sites indicated improve-
ments in ecosystem services such as carbon storage via greater
tree abundance (USDA 2000). Other ecosystem services that
may be improved under these trajectories include diversity
(Hupp & Osterkamp 1996; Hobbs 1993), pollination (Kremen
et al. 2004), sedimentation (Hupp & Osterkamp 1996; Coren-
blit et al. 2007), nutrient cycling (Peterson et al. 2001; Kauff-
man et al. 2004; Sheibley et al. 2006), and trophic dynamics
(Baxter et al. 2005; Muotka & Syrjanen 2007).
The increase in exotic shrub density over time was unin-
tended and undesirable. This phenomenon has been noted
in past work (Borgmann & Rodewald 2005; Badano et al.
2007). Exotic tree abundance did not correlate with project
age, but these taxa were occasionally present at restored
sites from previous plantings. In contrast, the most common
exotic shrub, Himalayan blackberry (Rubus discolor ), domi-
nated many older restored sites (greater than 20 years old) by
establishing homogeneous patches, which is similar to obser-
vations by Lambrecht-McDowell and Radosevich (2005). The
rapid trajectory of exotic shrub abundance reduces options
for management in the riparian corridor. Consideration of
exotic vegetation should focus on the trade-offs that exotic
species present for achieving management goals over multi-
ple decades (Parker 1997). For example, White et al. (2005)
found juvenile Swainson’s Thrush (Catharus ustulatus)used
Himalayan blackberry for cover and food, so removing this
vegetation from recently restored sites may affect wildlife pop-
ulations negatively. However, delaying active control of exotic
shrubs past the initial 20 years of restoration may eliminate
chances for adaptive management and cost effective solutions,
as explained by Zavaleta (2000).
It was not surprising that perennial herbaceous species did
not respond to restoration since the focus of revegetation
was woody species. Holl and Crone (2004) made similar
observations. Annual vegetation was clearly reduced over
time, but resurgence of native perennial grasses and forbs is not
likely without significant propagule supply (Bartolome et al.
2004) from flood inundation (Hupp & Osterkamp 1996) and
less competition from exotic (Holl & Crone 2004) or shrub
species (Brown & Archer 1999).
Aquatic Habitat
A primary purpose for establishing native trees, in particular
Salix species, was to stabilize streambanks (Johnson 2003)
because forested vegetation contains the greatest fine root
density for erosion resistance (Wynn et al. 2004) and tree den-
sity increases channel roughness increasing sedimentation and
retention of flood water (Hupp & Osterkamp 1996; Coren-
blit et al. 2007). Therefore, the changes we found in stream
channel morphology and streambank stability were expected
and should result in improved water quality with less chronic
sediment delivery to streams from restored sites (NCRWQCB
1998; Corenblit et al. 2007). Decreasing the bankfull chan-
nel width-to-depth ratio was also an expected response from
revegetation because stream channels tend to deepen and nar-
row as sedimentation on floodplains increases following tree
establishment (Hupp & Osterkamp 1996; Opperman & Meren-
lender 2004; Corenblit et al. 2007). This process was enhanced
by live wood interacting with woody debris forming persistent
instream structure, as explained by Opperman and Merenlen-
der (2007). The accumulation of large wood and debris jams
provides greater complexity of instream habitat such as deeper
pools (Beechie & Sibley 1997) and cover (Cederholm et al.
1997)
Improved pool habitat and depth indicate greater abundance
and diversity of aquatic fauna may be able to use habitat
at restored sites as complexity within the water column
increased over time. Pools provide cover that protect prey from
predators, create slower flow niches during winter storms, and
contribute to temperature stratification for thermal refugia in
summer (Ebersole et al. 2001). The large increase of stream
shade attributes over time was an expected outcome and
indicates water temperature may be reduced following riparian
revegetation (Brown 1969; Opperman & Merenlender 2004).
Aquatic habitat metrics that did not improve over time offer
further insight into biogeomorphic processes in the riparian
zone (Corenblit et al. 2007). Fine sediment and embeddedness
of stream channel substrate did not change indicating that
these metrics may be linked to watershed processes operating
at spatial scales larger than those of the typical revegetation
project site (Houlahan & Findlay 2004; Opperman et al. 2005).
Moreover, the temporal range of our survey may not have been
sufficient to encompass change in these parameters.
While long-term monitoring of individual sites would have
produced a clearer understanding of riparian vegetation and
aquatic habitat trajectories following restoration, the sub-
stitution of space-for-time in our chronosequence compar-
isons provided useful insights that inform regional restoration
efforts. This cross-sectional survey approach also offers an
effective option for systematic, objective assessment of com-
pleted projects and postproject appraisals (Kondolf et al. 2007;
Tompkins & Kondolf 2007). We suggest that stream restoration
research further investigate the impact of establishing woody
species on stream channel morphology, nutrient cycling, and
overall plant diversity. This will prepare the restoration part-
nership to manage numerous objectives and ecosystem ser-
vices over multiple decades.
Implications for Practice
•Site-specific riparian revegetation strategies were suc-
cessful in maintaining native tree and shrub density,
cover, and richness over multiple decades.
•Shrub control may be important for maintaining under-
story diversity at restored riparian sites, since the trajec-
tory for exotic shrub abundance and variability in native
herbaceous species indicated a need for vegetation man-
agement 10–20 years postrestoration.
•Although aquatic habitat improved following revegeta-
tion (e.g., more shade, more woody debris, and deeper
pools), other important instream attributes such as fines
Restoration Ecology 7
Developing California’s Vegetation and Aquatic Habitats
and embeddedness did not recover over multiple decades
and may be controlled by watershed factors.
•Monitoring of riparian revegetation projects should
include bank stability, woody debris, channel width-to-
depth ratio, and pool depth where appropriate, in addition
to plant diversity and cover over time.
Acknowledgments
We are grateful to the cooperative group of natural resource
managers whose contributions are the reason the project was
possible. We want to recognize the assistance provided by
Thomas Schott, Paul Sheffer, Gale Ranch, Paul Martin, Jeff
Opperman, and Lisa Bush as well as the Marin County
Resource Conservation District (RCD), Mendocino County
RCD, Southern Sonoma RCD, Natural Resources Conserva-
tion Service, Prunuske Chatham, Inc., Bay Institute’s Students
& Teachers Restoring A Watershed (STRAW), Bioengineering
Associates, and many more. Funding was provided by Califor-
nia Coastal Conservancy, National Oceanographic and Atmo-
spheric Administration’s Restoration Center, and University of
California Division of Agriculture and Natural Resources.
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