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Reference Condition in Riparian Forests: What does it look like and how can we achieve it? A method of identifying reference condition from undisturbed.

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Presentation on theme: "Reference Condition in Riparian Forests: What does it look like and how can we achieve it? A method of identifying reference condition from undisturbed."— Presentation transcript:

1 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

2 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

3 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

4 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

5 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

6 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 – 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

7 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

8 Result: Toolkit for identification of reference condition Riparian Vegetation Reference (RiVR) Index 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)

9 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

10 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

11 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.

12 Species richness: By site, reference type, and MCV alliance Reference Type Number of sites Average number of species CRAM314 Remnant Site113 BMI Avian28.5

13 Majority of new species encountered in first 100 feet; 5-10 tree species per site

14 Richness varies by site and by assemblage

15 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

16 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

17 Relative abundance on all reference sites

18 Mean relative abundance: the majority of species are minor species

19 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

20 Diameter distribution for reference group approximates typical forest model: many small trees, few large trees

21 Modeling species-area relationships for riparian woody plants 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 assemblage- specific Distance Species

22 Assessing sites using RiVR: A preliminary model RiVR can be used to compare proximity to reference condition for: – 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

23 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.

24 Conclusion

25 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

26 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

27 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

28 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


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