Targets for ecological restoration Robert K. Peet University of North Carolina
1. Introduction • Why me? I’m not a restoration ecologist. • Icon = “an object of uncritical devotion: especially a traditional belief or ideal” • My icon = a simple model for how to conduct ecological restoration. • My approach = A Carolina case study • Goal: ecological function & biodiversity
2. A methodological icon • Document reference conditions • Derive restoration targets • Design site-specific restoration plan • Implement the plan • Monitor change and assess success • Employ adaptive management
3. Carolina Vegetation Survey • Multi-institutional collaborative study to document and understand the natural vegetation of the Carolinas. • High-quality, quantitative records of reference vegetation
Over 5000 plots, containing over 2600 species, representing over 200 vegetation types. Reference data collection is an on-going activity
4. North Carolina Ecosystem Enhancement Program “The EEP mission is to restore, enhance, preserve and protect the functions associated with wetlands, streams, and riparian areas, including … restoration, maintenance and protection of water quality and riparian habitats …”
Ecosystem Enhancement Program Biennial Budget FY 2005/06 and 2006 -07 Cost by Category: Summary Administration $ 9, 477, 939 Restoration* $ 102, 910, 770 HQ Preservation $ 57, 984, 804 Project Development $ 4, 704, 366 Biennial Total $ 175, 077, 880 Total $175, 077, 880 *Includes Implementation and Future Mitigation Projects
Stream Restoration Durham, NC
5. Traditional EEP method • Consult brief habitat-based plant lists • Design a site-specific restoration plan • Implement the plan • Monitor survival of planted stems 5 yrs • Replant if needed
6. EEP-CVS Collaboration • EEP wants to do a better job creating natural ecosystems. • CVS provides improved reference data, target design, monitoring, and data management and analysis
7. Reference site initiative • Goal: move from modest species lists to a quantitative plot database and highresolution community classification with quantitative descriptions and defined environmental settings.
8. Target generation • Simple goal – Deliver composition goal based on the vegetation type most appropriate for the site and region. • Sophisticated goal. – Automated system that uses site data to generate likely NVC types, from which compositional goals are extracted.
Longleaf pine – feasibility study • Few longleaf pine sites remain in “original” condition. • Restoration targets must be extrapolated from a limited number of reference stands.
Dataset: -188 plots across fall-line sandhills of NC, SC, & GA - All sites contained near-natural, firemaintained groundlayer vegetation - Soil attributes included for both the A and B horizon: sand, silt, clay, Ca, Mg, K, P, S, Mn, Na, Cu, Zn, Fe, BD, p. H, organic content, CEC, BS.
Step 1. Classification. Developed a classification of the major vegetation types of the ecoregion. Used cluster analysis with a matrix of 188 plots x 619 species. Vegetation types were seen to be differentiated with respect to soil texture, moisture, nutrient status, & geography.
Step 2. Build model. - Forward selection with linear discriminant analysis identified predictor variables. - Critical variables were Latitude, Manganese, Phosphorus, Clay, Longitude. - 75% of plots correctly identified to series. Typically 75% of communities within a series that were correctly classified.
Step 3. Select species. 1. Generate a list of all species in type (species pool) with frequency, mean cover values, and mean richness. 2. Randomly order the list 3. Compare species frequency to random number between 0 & 1, and if the random number is less than the proportion of plots the species is selected. Continue until the number in list of selected species equals the number predicted.
Overall strategy: • Identify biogeographic region and obtain predictive models. • Select pool of candidate species for a specific site based on range information. • Divide restoration site into environmentally homogenous areas, stratifying by topography and soil. • Use models to select species number and composition.
9. Monitoring – CVS methods
• Trade off between detail and time. • EEP protocol seamlessly integrates with CVS methods by allowing a series of sampling levels. • MS-Access data-entry tool to assure standardize data, easy assimilation, and automated quality control. • Standard backend database for reports and analysis
10. Reports & Analysis • Datasheets for monitoring • Survival & growth of planted stems • Direction of compositional change • Rate of change • Problems needing attention, such as exotic species
CVS-EEP Training is essential
11. Reference stand issues Reference stand conditions may be difficult to achieve because of altered • Soil nutrients • Herbivory • Hydology • Exotic species, and diseases • Disturbance regimes • Sea level • Climate
12. Concluding remarks • The iconic model, although analytically simple, provides a firm foundation. • My case study lacks the sophisticated but impractical approaches generally advocated at an ESA symposium, yet it improves on a highly respected program. • Don’t forget Robert May’s observation that ‘ecology is a science of contingent generalization. ’ The CVS method focuses on contingencies of site and history.
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