EMAP Monitoring Design & Design Team
Ecological Research
LTG 1 Poster # 1
Anthony (Tony) R. Olsen (USEPA), N. Scott Urquhart (Colorado State U), & Don L. Stevens (Oregon State U)
1.0
Continuous domain with no voids
0.8
0.6
Exponentially increasing polygon size, total perimeter = 43.1
50
100
150
200
250
Predict likelihood of water-quality impaired stream
reaches from probability survey and auxiliary data,
e.g., landscape characteristics: relevant to 303(d)
point density
Maryland Bioglogical Stream Survey (MBSS) Sample Site Locations
Improved variance estimation:
Better precision for fixed cost.
1.00
• 4 Fellows American Statistical
Association
sh
sv
ac
cac
Kilometers
30
0
Legend
nbh
MBSS sample sites
1:100,000 National Hydrography Dataset
0.85
Maryland
0
0.0
0.5
1.0
CV Parameter
Relative Risk Estimation:
The risk of Poor BMI is 1.6 times greater in streams with
Poor SED than in streams with OK SED.
1.5
2.0
5,000
Meters
¯
1. A geostatistical model
•
•
•
•
•
Predict a specific reach scale condition at points that were not sampled
Provide a better understanding of the relationship between the landscape and reach scale conditions
Give insight into potential sources of water quality degradation
Develop landscape indicators
Crucial for the rapid and cost efficient monitoring of large areas
2. Better understanding of spatial autocorrelation in stream networks
• What is the distance within which it occurs?
• How does that differ between chemical variables?
3. Produce map of study area
• Shows the likelihood of water quality impairment for each stream segment
• Based on water quality standards or relative condition (low, medium, high)
• Future sampling efforts can be concentrated in areas with higher probability of impairment
4. Transfer technology to States and Tribes
EMAP Design Team
• Members from 4 NHEERL Eco-divisions, 2 NERL divisions,
Office of Water and EPA Regions
• Mechanism to transfer statistical research to EPA and state
monitoring designs while team works with states
Develop
methodology using
Maryland
Biological Stream
Survey data
srs
0.95
Coverage
•Graybill Conference on Spatial Statistics
Linearly increasing polygon size, total perimeter = 84.9
0
•Computational Environmetrics 2004
•Monitoring Science & Technology
Symposium: Statistical track, 2004
Constant polygon size, total perimeter = 88.4
0.90
• Conferences organized:
Improvement over simple random or systematic sampling
0.4
• Invited monitoring program
reviews (e.g., NOAA Mussel Watch,
Pacific Rim Salmon monitoring,
Everglades restoration, Grand
Canyon, Alberta biodiversity, NPS
inventory & monitoring)
GRTS: Spatially-balanced sampling:
0.2
• Over 250 peer-reviewed
publications
Use EMAP probability survey data
from 557 lakes to estimate average
lake ANC for 113 Hydrologic
units. Requires auxiliary data and
new semi-parametric statistical
methods
0.0
• Collaboration among ORD
researchers and STAR Grant
statistical researchers
Small area estimation: Making available data do more
•More efficient survey designs
•Better statistical analyses
polygon area variance ratio
Statistical Research
305(b): Status & Trends
Technical Transfer
• Aquatic Resource Monitoring website:
\\www.epa.gov\nheerl\arm
• Software for site selection and statistical analysis:
psurvey.design & psurvey.analysis
• Monitoring workshops for states and EPA Regions (over 10)
• Internet meeting training sessions with individual
states on monitoring design & analysis
• 30-40 monitoring designs per year for states, EPA, and other
federal agencies (USGS, NPS, NMFS, USFS)
"Developing statistically-valid and -defensible frameworks to assess status and trends of
ecosystem condition at national scales"