Download Same Time, Different Place: Deriving Riparian Vegetation

Reference Condition in Riparian Forests:
What does it look like and how can we achieve it?
A method of identifying reference condition from undisturbed
streams and deriving indices for restoration
Kristen Van Dam, M.F., Senior Ecologist
Urban Creeks Council
Shortcomings in success criteria
• Permit requirements focus on simplistic performance criteria:
percent survival or percent cover
• Standards for success do not address ecosystem function –
does your project actually work?
– limited correlation between ecosystem function and percent
survival/percent cover criteria
• Lack of guidelines for selection of “reference sites” can result in the
bar being set too low
• If reference condition is not incorporated into project monitoring,
we’ll never know if project approximates reference
• This limits recovery of damaged systems – we may not be
maximizing results for our investment
Goals & performance criteria for
restored riparian woodlands
• There is no consistent definition of
restoration success for riparian
woodlands
• We propose that long-term success should be measured by
degree to which a site approximates reference condition
• Thus, reference condition must be defined and assigned
measurable metrics
• Tools are needed that incorporate both robust science and
usable assessment protocols
Characteristics of a good toolkit
• Minimizes subjectivity
• Data collection is simple
and inexpensive
• Indicators measure relative
ecosystem function
• Indicators are detailed enough
to be used to model restoration
projects, yet
• Universal enough to allow a
bar to be set
Challenge 1/2 : Measuring function
• Ecosystem function is
extraordinarily complex
and difficult to measure
directly
Solution:
• Ecosystem structure
can be used as a proxy
for function (Stein et al 2009)
• CRAM protocol incorporates
this concept
Challenge 2/2 : Locating reference sites
• No statewide vegetation reference program
Solution:
• Select other riparian program sites representing “best
achievable condition” as proxies for vegetative quality
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–
–
–
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CRAM
SWAMP
Lunde (2011) (SWAMP)
Riparian Bird Index (PRBO)
Conserved remnant riparian
• These protocols are useful for approximating high ecosystem
function but they do not result in usable vegetation reference
information.
Solution:
• Develop new protocol
Study Area and
Reference Site
Locations
• EPA level III “Coastal
Sage Scrub, Chaparral,
and Oak Woodlands”
ecoregion
• 15 SWAMP sites
(including Lunde, 2011)
• Three CRAM sites
• Two RBI sites (PRBO)
• One remnant site
selected by author
Result: Toolkit for identification of reference
condition
• Riparian Vegetation Reference (RiVR) Index
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•
•
•
Species Richness
Relative Abundance
Diameter class distribution
Forest or woodland alliances
• Manual of California Vegetation (2009)
• Structural composition (layers
and their dominant constituents)
• Stems per acre
• Modeled species-area curves from site data
• Regional species-area curve (preliminary)
RiVR Overview
• RiVR uses census sampling along a transect about the size of a
CRAM site, identifies species and size class of woody plants
• Reference condition metrics can be derived from a group of
reference sites
• RiVR metrics are independent of species composition
• Species richness can be modeled from known sample curves
to derive richness target for restoration
• Target trees per acre can be derived from reference group
(Group average = 153 TPA)
• Some RiVR metrics are most useful for tree species
– Difficult to obtain accurate stem count for many shrubs
Similarity in metrics and site characteristics
• Watersheds and boundary conditions were minimally
disturbed (few roads, zero urbanization)
• Sites exhibit mature vegetation structure with both large trees
and recruitment of new age classes
• Reference sites clearly fall into definable MCV vegetation
alliances
• Low (<5) woody species diversity atypical
• Shrub layers usually intermittent, rarely continuous
• Sites demonstrate common pattern of relative abundance:
less than 4 dominant species and at least 5 minor species,
usually more
• Species richness increases with site size
MCV Classification
• Relative abundance analysis
provides exact dominance and
good proxy for relative cover
• Each site defined by dominant
species per MCV treatment
• It appears that some
ecological driver acts to sort
relative abundance into
predictable patterns
• Given that reference sites fall into MCV alliances, it follows
that restoration sites should do the same.
Species richness: By site, reference type, and MCV alliance
Reference Type
Number of
Average number
sites
of species
CRAM
3
14
Remnant Site
1
13
BMI
15
12.3
Avian
2
8.5
Majority of new species encountered in first 100 feet;
5-10 tree species per site
Richness varies by site and by assemblage
Patterns of species richness
• Richness varies throughout reference group; some alliances
appear to be intrinsically depauperate in woody species
(Sequoia sempervirens, Salix laevigata)
• Species richness on reference sites increases with site size
• Average richness = 15 woody species at 400 feet
• Different richness categories : lower-richness sites are not
necessarily correlated with poor quality
– But low-richness sites were atypical in the reference group
Relative Abundance
• Relative abundance patterns are virtually identical across all
reference sites:
– Dominants defined as any species constituting greater than 10% RA on
a site; minors defined as any species at less than 10% RA
– Very few dominants (average <3 per site)
– 82% of all species in sample are minor species
Definitions:
• Relative abundance: Describes the proportions of species on a
given site
• Mean relative abundance: Describes average relative
abundance for a group of sites, i.e. all sites in an alliance or
the reference group as a whole
Relative abundance on all reference sites
Mean relative abundance: the majority of species are minor species
Results indicate that relative abundance is an important
component of site composition
• Dominants may provide critical functions (e.g. primary
productivity, system stability), but
• Prevalence of minor species throughout the reference group
suggests their importance to these systems.
• Relative abundance should be incorporated into planting and
adaptive management goals
Diameter distribution for reference group approximates typical
forest model: many small trees, few large trees
Modeling species-area relationships for riparian
woody plants
Species Extrapolations
20
15
10
Species
25
30
Prediction Line
95% Prediction Interval
Species
Composite SA curve for
site group:
• Model averages ~18
WP species at 1000 ft
to ~24 species at 6000
ft
• Richness increases
with area, but not by a
large amount
• Individual site curves
have smaller
confidence intervals, as
they are assemblagespecific
1000
2000
3000
4000
Area
Distance
5000
y =2 −3.881 + 3.231(ln(Area))
R 0.368
6000
Assessing sites using RiVR: A preliminary model
• RiVR can be used to compare
proximity to reference
condition for:
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–
–
–
Species richness
Relative abundance
Size class distribution
Trees per acre
• Scoring model uses variance
from reference condition to
assess site condition
• Restoration sites will need to
be fairly mature before they
compare favorably on many
metrics
Example of theoretical RiVR scoring module
• Models progressive deviation from reference condition via
cumulative variance
• Scores A-D by 3 top dominants and all minor species
• Many different scenarios possible at each score level.
Conclusion
Limitations and considerations
• Species-area models are critical to proper estimation of
richness for restoration sites
• RiVR currently incorporates only woody species and is
designed for forests and woodlands only
• Only half of riparian-associated MCV alliances were detected;
data needed for all alliances
• We don’t yet understand exactly how site dynamics influence
species composition- but we know assemblages do shift over
space and time
Implications for restoration and management
• If restoration sites are intended to approximate reference sites—
• Relative abundance patterns should be used in conjunction with
species palettes
• Restoration palettes should be modeled after existing vegetation
alliances
• Richness accumulation model indicates that richness should
increase with site size, and
• Suggests that restoration sites should be more species-rich than
they typically are.
• Discernible size classes should be present; RiVR can detect level of
recruitment by size class
• Any forest or woodland site, including restoration sites, can be
assessed for similarity to reference condition based on RiVR metrics
Implications for monitoring & assessment
• Current assessment methods (e.g. CRAM, SWAMP) do not
give any information about vegetative composition, and make
assumptions about desired condition that may not reflect
reference condition
– most reference sites do not have a lush and continuous shrub layer
• Focus on dominant species may present an incomplete view
to system function
• RiVR can supplement other assessment methods for more
detailed vegetative information
Next Steps
• Preliminary RiVR scoring module in process
• RiVR data needed for all riparian alliances in ecoregion
(eventual total of 20 sites per alliance, 19 alliances = 360
reference sites)
• Sampling method needed for shrub and herbaceous layers
• Make RiVR toolset accessible for data input and
experimentation