Planning tools

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Planning tools

• Working together to restore North Carolina's
  natural communities

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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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Where we are going

• CVS is developing tools and data sources to
  facilitate planning of restoration activities and
  to evaluate their success.
• New data sources and tools are being designed
• Suggestions for new tools and increased
  functionality are.

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Restoration protocol

• 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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Target generation

• Simple goal Deliver composition target based on
  the vegetation type most appropriate for the site
  and region.
• Sophisticated goal Automated system that uses
  site information and reference plot data to
  predict vegetation composition.

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Improving restoration targets

• Crude species lists
• Plot database linked to the National Vegetation
  Classification and the Natural Heritage Program
  documentation
• High-resolution community classification with
  quantitative descriptions.
• Dynamically generated targets

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Ecological Groups

• Mountain Vegetation
• Montane upland forests
• Montane open upland vegetation
• Montane alluvial wetland vegetation
• Montane nonalluvial wetland vegetation
• Piedmont Vegetation
• Piedmont upland forests
• Piedmont open upland vegetation
• Piedmont alluvial wetland vegetation
• Piedmont nonalluvial wetland vegetation
• Coastal Plain Vegetation
• Coastal Plain upland forests
• Coastal Plain upland open woodland vegetation
• Coastal Plain alluvial wetland vegetation
• Coastal Plain nonalluvial wetland vegetation
• Coastal Fringe Vegetation
• Maritime upland forests shrublands
• Maritime open upland vegetation
• Maritime nontidal wetland vegetation

http//cvs.bio.unc.edu
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Community types linked to NVC
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Description in the NVC
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Primary sources of data

• Targeted communities
• Mountain bogs
• Piedmont alluvial forests
• Pulse events with regional focus

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Plot map in pulse report
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Classification table from Pulse
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Community summary from Pulse
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Compositon table from Pulse
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Goal for the next yearDescriptive summaries,
keys, maps, species tables, site data, photos
where available
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Example compositional summary
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Example site summary
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Example photo of type
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Longleaf Pine vegetation
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Xeric barrens Subxeric uplands Longleaf
turkey oak woodlands on entisols
9 Types13 Types
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• Flatwoods
• Longleaf woodlands of spodosols

5 types
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Silty uplands Longleaf woodlands on
well-drained ultisols
12 types
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Savannas and seeps Longleaf woodlands on moist
alfisols
13 types
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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 vegetation
  series. Typically 75 of plots within a series
  were correctly classified to community type.

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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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• Summary of 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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Looking forward to continued collaboration