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ANATOMY OF SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME {on the web at http://www.oregonstate.edu/instruct/st571/urquhart/anatomy/index.htm}. by N. Scott Urquhart Oregon State University, USA and Anthony R. Olsen US EPA. This research is funded by U.S.EPA – Science To Achieve
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ANATOMY OF SAMPLING STUDIES OFECOLOGICAL RESPONSES THROUGH TIME{on the web at http://www.oregonstate.edu/instruct/st571/urquhart/anatomy/index.htm} by N. Scott Urquhart Oregon State University, USA and Anthony R. Olsen US EPA
This research is funded by U.S.EPA – Science To Achieve Results (STAR) Program Cooperative Agreement # CR - 829095 STARMAP FUNDINGSpace-Time Aquatic Resources Modeling and Analysis Program The work reported here today was developed under the STAR Research Assistance Agreement CR-829095 awarded by the U.S. Environmental Protection Agency (EPA) to Colorado State University. This presentation has not been formally reviewed by EPA. The views expressed here are solely those of presenters and STARMAP, the Program they represent. EPA does not endorse any products or commercial services mentioned in these presentation.
THE AUTHORS • N. SCOTT URQUHART • Trained in Statistics • About 40 Years of Experience in Applications • Worked With Ecologists in Desert, Arctic, Pacific Northwest • Many Surveys with Rural Sociologists and Ag Economists • Including 10 years with EPA’s Environmental Monitoring and Assessment Program (EMAP) • ACADEMIC And AGENCY; PLANT And ANIMAL • ANTHONY (Tony) R. OLSEN • Trained in Statistics • 30+ Years of Experience in Private and Government Applications • Worked With Atmospheric Modelers And Air Pollution Field Scientists • Survey Experience With Health Professionals And Large-scale National Resource Monitoring • Now Statistical Lead with EPA’s EMAP
EVOLUTION OF THE “ANATOMY” • The first step in the development of the ANATOMY focused on experimental design situations. • Served as the structure for several part-semester courses in advanced statistical methods at New Mexico State University • Eventually published as • Urquhart, N. S. (1981). Anatomy of a study. HortScience16:621-627. • Experience with EMAP led to its expansion to surveys
TODAY’S CONTEXT for SURVEYS • “EMAP-type Situations” EMAP = US EPA’S Environmental Monitoring and Assessment Program • Estimate Status, Changes ... In Indicators • Estimate Status, Changes, ... In Extent • Describe Associations ...
Hypereutrophic Hypereutrophic Eutrophic Eutrophic Mesotrophic Mesotrophic Oligotrophic Oligotrophic Objective #1: Estimate the status, changes and trends in selected indicators of the condition of our Nation's ecological resources on a regional scale on a regional scale with known confidence with known confidence 17.6% ± 10% 6.8% 31.8% ± 6% ± 8% 43.8% ± 12% (N=258) Source: EMAP Northeast Lakes Study
12000 Est. Est. SE SE 10000 Lake # Area North 8000 4,030 814 11,455 1,251 east 6000 285 Adir 1,506 1,082 395 4000 NEU 5,689 758 1,206 2,099 2000 850 C/L/P 4,280 1,048 254 0 Northeast Adir NEU C/L/P Objective #2: Estimate the status, changes and trends in the extent and geographic coverage of our Nation's ecological resources on a regional scale with known confidence Adir = Adirondacks; NEU = New England Uplands; C/L/P = Coast & Lake Plains Source: EMAP Northeast Lakes Study
Objective #3: Describe associations between indicators of anthropogenic stress and indicators of condition Good Relative Ranking of Stressors Fish Index of Biotic Integrity (Insufficient Data) Fair Poor Proportion of Stream Length Source: EMAP Mid-Atlantic Highlands Assessment
WHO MUST COMMUNICATE • Ecologists & Other Biologists • Statisticians • Geographers • Geographic Information Specialists (GIS) • Information Managers • Quality Assurance Personnel • Managers, At Various Levels
“SAMPLING” • A WORD OF MANY MEANINGS • Statisticians Often Associate It With Survey Sampling • An Ecologist May Associate It with the Selection of Local Sites or Material • A Laboratory Scientist May Associate It With the Selection Of Material to be Analyzed from Material Supplied • Common General Meaning, Varied Specific Meanings
THE SPECIAL NEED • Communication Demands a Distinction Between • The Local Process of Evaluating a Response,and • The Statistical Selection of a Sampling Unit, • For example, • A LAKE • A POINT ON A STEAM
THE SPECIAL NEED - continued • The Terms • Response Design • Sampling Design or Survey Design • Can Be Used to Make this Distinction • But a Complex Ecological Survey Clearly Has More Parts Than These!
BASIC ROLES • Survey Design Tells Us Where to Go to Collect Sample Information or Material • Response Design Tells Us What to Do Once We Get There • But These Two Components Exist in a Broader Context
AN IMPORTANT DISTINCTION • Monitoring Strategy • Conceptual • Impacted by Objectives • Addressable Without Regard to the Inference Strategy • Inference Strategy
AN IMPORTANT DISTINCTION- continued • Monitoring Strategy • .......... • Inference Strategy • Places to Evaluate the Response – “the WHERE” • Relation Between Points Evaluated and the Population • IE, the Basis for Inference
These components exist regardless of the inference strategy These components exist for any monitoring strategy SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • Monitoring Strategy • Universe Model • Statistical Population • Domain Design • Response Design • Inference Strategy • Survey Design • Temporal Design • Quality Assurance Design
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The MONITORING STRATEGY • The MONITORING STRATEGY MUST RESPOND TO • Monitoring Objectives • State of Knowledge in Ecological Sciences • Characteristics of Ecological Resource(s) of Interest • EXPECTED FUNDING Compared To COSTS • Operational Constraints
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The UNIVERSE MODEL • Reality (Universe): Ecological Entity Within a Defined Geographic Area to Be Monitored • Model of the Universe: • Development of a Monitoring Approach Requires Construction of a Model for the Universe • Elements Of The Universe Model: Set of Entities Composing The Entire Universe
The UNIVERSE MODEL • Population Description and Its Sampling Require Definition of the “Units” in the Population • Discrete Units: • Lakes May Be Viewed This Way • Continuous Structure in Space of Some Dimension: • 2-space: forests or agroecosystems • 1-space: Streams • 3-space: Ground Water
Second Order First Orders Second Order First Orders Second Order First Orders First Order THE MODEL FOR STREAMSStrahler Orders Third Order
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The STATISTICAL POPULATION • The Collection of Units (as modeled) Over Some Region of Definition • Spatial • Temporal • SPATIAL And TEMPORAL • Population Definition Could Include Features Which Depend on Response Values • EX: acid sensitive streams at upper elevations
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The DOMAIN Design • Specifies Subpopulations or “Domains” of Special Interest • May Specify Meaningful Comparisons Between Domains • Similar to Planned Comparisons in Experimental Design Situations • Domain Design May Depend on Response Values • Ex: Warm Versus Cold Water Lakes
The DOMAIN DESIGN - continued • Specifies Subpopulations or “Domains” of Special Interest • Determined From Defining Factors For The Monitoring Activity • Must Have Critical Connection To Clients • Other Domains May Be Used For Analysis, Without Having Been Used In Defining The Monitoring Strategy • EX: EMAP domains include ECOAREAS and STANDARD FEDERAL REGIONS
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The RESPONSE Design • The Response Design Specifies • The Process of Obtaining A Response • At An Individual Element (Site) • Of The Resource • During A Single Monitoring Period • Response: What Will Be Determined On An Element – • Needs To Be Responsive to the Objectives of the Monitoring Activity
The RESPONSE Design - continued • EMAP Responses Focus On Indicators of • STRESS and • Condition • The Response Design Also Defines • Plot Design • Measurement Protocols • Support Region – area around the site where material is collected, or measurements are taken • Data Reduction Protocols • Calculation Of The Final Indicator Value for the Element
The RESPONSE Design- Continued • For example, consider a response related to macroinvertebrates in streams • RESPONSE = proportion EPT (This is the proportion of collected macrobenthos organisms, mainly insects, which fall in the taxonomic classes of Ephemeroptera , Plecoptera , or Trichoptera. Low values indicate polluted streams; high values indicate rather pristine streams)
The RESPONSE Design - continued - 2 • ... response related to macrobenthos ... • The COLLECTION UNITS could be 10 30cm x 30cm areas, systematically organized, at the stream site, sampled with a “Surber sampler” • The EVALUATION UNIT could be a jar containing the composite of all macroinvertebrate organisms collected at the 10 collection sites, or • The EVALUATION UNIT also could be a jar containing a 1/6 subsample of the composite of macroinvertebrate organisms collected in the 10 collection units.
The RESPONSE Design - continued - 3 • ... response related to macrobenthos ... • The LABORATORY EVALUATION of the material would consist of determining and recording the taxa (like family, genus, or species) of each organism in the evaluation material • The RESPONSE would be determined by computing the number of organisms in the evaluation material belonging to the E, P, T taxonomic classes, and dividing this by the number of organisms classified.
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The INFERENCE STRATEGY • Is The Basis For Scientific Inference • Provides The Connection Between Objectives and the Monitoring Strategy • Monitoring Strategy Usually Must Rely on Obtaining Information on a Subset Of All Possible Elements in the Universe • Specifies Which Elements of the Universe Will Have Responses Determined on Them • Can Be Based On Either ... (continued )
The INFERENCE STRATEGY(continued) • ... Connection ... • ... Subset ... • ... Have Responses • Can Be Based On Either • Judgment Selection Of Units • Inferential Validity Rests on Knowledge Of Relation Between the Universe And the Units Evaluated • Probability Selection Of Units • (The Focus Here)
SAMPLING STUDIES OF ECOLOGICAL RESPONSES THROUGH TIME HAVE • MONITORING STRATEGY • Universe Model • Statistical Population • Domain Design • Response Design • INFERENCE STRATEGY • Survey Design • Temporal Design • Quality Assurance Design
The SURVEY Design • Probability Based Survey Designs Are Considered Here • May Be Somewhat Limited To Sedentary Resources • Positive Features(As An Observational Study) • Permit Clear Statistical Inference to Well-Defined Populations • Measurements Often can be Made in Natural Settings, Giving Rise to Greater Realism Eventual Results
The SURVEY DESIGN - CONTINUED • Disadvantages • Limited Control Over Values of Predictor Variables • Restricts Causative Inference • Usually Will Produce Inaccessible Sampling Points • Good - For Inference • Bad - For Logistics
The SURVEY DESIGN - CONTINUED • Execution of a Sampling Plan Requires • A Sampling Frame • A way to identify elements in the population • Usually somewhat inaccurate for ecological resources • Example selecting vegetation sites along the Colorado River in the Grand Canyon
The SURVEY DESIGN - CONTINUED • Execution of a Sampling Plan Requires • A Sampling Frame • A way to identify elements in the population • Usually somewhat inaccurate for ecological resources • Example selecting vegetation sites along the Colorado River in the Grand Canyon • Example: Frame for selecting field sites on streams in the Western US
FRAME ERRORSTO BE DOCUMENTED SHORTLY • Water Body Size • Flow Status -- re Perennial • Identified As Perennial, but not correct • Wastes Effort Of Field Crews • Identified as Non-perennial, but Really is Perennial • Missed Resource • Inaccurate Assessment
EMAP-West Stream/river Length(km ± 95% CI)from Peck, et al (2002) - EMAP symposium
EMAP-West Stream/river Length(km ± 95% CI)from Peck, et al (2002) - EMAP symposium
EMAP-West Stream/river Length(km ± 95% CI)from Peck, et al (2002) - EMAP symposium
The SURVEY DESIGN - CONTINUED • Execution of a Sampling Plan Requires • A Sampling Frame • A way to identify elements in the population • Usually somewhat inaccurate for ecological resources • Example selecting vegetation sites along the Colorado River in the Grand Canyon • Example: Frame for selecting field sites on streams in the Western US • May change over time • As, for example, land use changes
SITE SELECTION • Needs to Accommodate Realities Such As • Frame Imperfection • Frame Which Changes Over Time • Sites nearly Uniform Over the Resource • But with substantial randomization • Supports Variable Probability of Selection • Generalized Random Tessellation Stratified Sampling = GRTS • The topic of the next session
The EMAP SURVEY Design • Assures Representation and Inference to Populations • Adapted to Resource Characteristics • Emphasizes Spatial Allocation of Samples • Uses Two-phase Sampling; Phase I • Based on a Randomized Point Grid and Associated Areas