SCOPE OF WORK
Assessment of South Atlantic Landscape Conservation Cooperative Terrestrial Indicators
Principal Investigators
Jaime A. Collazo, U.S. Geological Survey, North Carolina Cooperative Research Unit,
Department of Applied Ecology, Raleigh, NC 27695; Jaime_Collazo@ncsu.edu
C. Ashton Drew, North Carolina Cooperative Research Unit, Department of Applied Ecology,
Raleigh, NC 27695; cadrew@ncsu.edu
Background/Justification: SALCC has developed a list of terrestrial data products expected to
serve as indicators to both guide landscape-scale, long-term natural resource conservation
planning and to monitor the success of the plan as it is implemented. Selected through regional
workshops and expert elicitation, these indicators are believed to broadly represent the critical
ecosystem processes and components necessary to ensure the integrity of the targeted natural
resources. However, often experts’ knowledge of correlations is based on field observations.
Given differences in scale and data processing, experts’ field observed correlations do not always
directly translate to similar correlations in mapped data. Furthermore, landscapes in SALCC are
dynamic and it is not guaranteed that correlative relationships observed today will continue to
hold under threat of climate change, land us change, and sea level rise.
SALCC is proceeding with initial design of a regional Conservation Blueprint (Version 1.0)
based on these indicators, but desires a full assessment of indicator performance to incorporate
improvements into future versions. High performing indicators would correlate strongly with
ecosystem components and processes not only under present day conditions, but also under
future conditions (as modeled in the State of the South Atlantic report, expected January 2014).
Once identified, high performing indicators could be targeted by SALCC partners for increased
monitoring effort in support of learning through adaptive management or for directed research to
better understand mechanisms behind correlative relationships. Low performing or redundant
indicators could be recommended for removal from the Blueprint design.
At present, the terrestrial natural resources and their associated indicators are:
Beaches and Dunes
Productivity of loggerhead sea turtles
Index of beach birds
Miles of altered beach
Forested wetlands
Acres of forested wetlands
Index of forested wetland birds
Acres of natural habitat near isolated wetlands
Landscapes
Index of functional connectivity
Acres of interior natural communities
Index of structural connectivity
Acres of “biodiversity hotspots” in natural condition
Maritime forest
Abundance of painted bunting
Acres in protected status
Pine woodlands, savannas, and prairies
Index of pine woodland, savanna, and prairie birds
Acres of open canopy habitat that is regularly burned
Occurrence of flatwoods salamanders
Tidal and Nontidal Freshwater Marshes
Index of tidal and nontidal freshwater marsh birds
Acres of tidal freshwater marsh
Acres of invasive species
Upland hardwood forests
Acres of “biodiversity hotspots” in natural condition
Abundance of big trees
Index of upland hardwood birds
Project Objectives: Project staff will work closely with the staff of the South Atlantic Landscape
Conservation Cooperative (SALCC) and NatureServe to:
1. assess the correlation of the SALCC terrestrial indicators with other spatial ecosystem
components (species and habitats), processes (fire, freshwater flow), and threats (land use
change, climate change, and sea level rise);
2. propose alternatives to improve the terrestrial indicators, based on the assessment results.
Methods: SALCC and NatureServe are presently compiling data to generate a spatial layer for
each indicator, as well as a variety of the species, habitats, and processes that the indicators are
expected to represent. These data will be delivered to NCSU once they have been produced,
reviewed, and accepted by SALCC for use in the Blueprint design. This will ensure that the
analysis conducted by NCSU directly informs SALCC of strengths and weaknesses of the data
underlying Version 1.0.
We anticipate using contingency tables and regression analyses to test for correlation between
pairs and sets of spatial data layers. Specific methods will depend upon whether the spatial data
are raster or vector data, and whether the data attributes are categorical or continuous. The
project is envisioned to proceed in two stages:
1. Whole Region Analysis: This will be a rapid “first-cut” look at correlation among the
proposed indicators and between indicators and the variables for which they are
hypothesized to indicate. When testing for indicators’ ability to predict for species, we
anticipate summarizing results at the taxa level (e.g., percent of birds, mammals with
distributions correlated to the indicator), as well as for selected species groups (e.g.
specialists only, at-risk species only). After first calculating correlations between each
data layer using the current data, we will then examine whether these correlations remain
constant through time. The temporal analysis will be conducted for the subset of
indicators and other variables for which SALCC can provide multiple temporal datasets.
2. Sub-Regional Analysis: NatureServe’s Element Occurrence records represent the best
source of data for region-wide spatial and temporal analysis. However, challenges
associated with presence-only data and the absence of a consistent sampling design can
raise concerns. Therefore, SALCC will provide two high-quality datasets at a subregional scale with which we can test whether the correlations observed in the rapid
assessment hold true for data collected under more rigorous sampling design. Depending
on the data provided, this analysis will test correlations among a subset of the possible
indicator and variable combinations.
Project Timeline
Sept 2013 Project Commences
Feb 2014 Interim Report to SALCC
July 2014 Draft Final Report to SALCC & USGS
Sept 2014 Final Technical Report and Non-Technical Project Summary to SALCC
Deliverables: The final technical report will include a full assessment of the terrestrial indicator
performance with recommendations regarding indicator selection and monitoring of indicator
performance within an evolving conservation landscape.