Targets for ecological restoration

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Targets for ecological restoration

• Robert K. Peet
• University of North Carolina

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1. Introduction

• Why me? Im not a restoration ecologist.
• Icon an object of uncritical
  devotionespecially 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

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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

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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

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Over 5000 plots, containing over 2600 species,
representing over 200 vegetation types.
Reference data collection is an on-going activity
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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
  

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Ecosystem Enhancement Program
Biennial Budget FY 2005/06 and 2006-07 Cost by
Category Total 175,077,880
Summary Administration
9,477,939 Restoration
102,910,770 HQ Preservation
57,984,804 Project Development
4,704,366 Includes Implementation and Biennial
Total 175,077,880 Future
Mitigation Projects
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Stream Restoration Durham, NC
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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

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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

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7. Reference site initiative

• Goal move from modest species lists to a
  quantitative plot database and high-resolution
  community classification with quantitative
  descriptions and defined environmental settings.

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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.

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• Longleaf pine feasibility study
• Few longleaf pine sites remain in original
  condition.
• Restoration targets must be extrapolated from a
  limited number of reference stands.

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• Dataset
• 188 plots across fall-line sandhills of NC, SC,
  GA
• - All sites contained near-natural,
  fire-maintained 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, pH, organic content, CEC, BS.

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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.
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• 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.

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• Step 3. Select species.
• Generate a list of all species in type (species
  pool) with frequency, mean cover values, and mean
  richness.
• Randomly order the list
• 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.

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• 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.

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9. Monitoring CVS methods
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• 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

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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

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CVS-EEP Training is essential
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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

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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.
• Dont forget Robert Mays observation that
  ecology is a science of contingent
  generalization. The CVS method focuses on
  contingencies of site and history.