Anthony R. Olsen

Spatially Balanced Sampling of Natural Resources

The spatial distribution of a natural resource is an important consideration in designing an efficient survey or monitoring program for the resource. Generally, sample sites that are spatially balanced, that is, more or less evenly dispersed over the extent of the resource, are more efficient than simple random sampling. We review a unified strategy for selecting spatially balanced probability samples of natural resources. The technique is based on creating a function that maps two-dimensional space into one-dimensional space, thereby defining an ordered spatial address. We use a restricted randomization to randomly order the addresses, so that systematic sampling along the randomly ordered linear structure results in a spatially well-balanced random sample. Variable inclusion probability, proportional to an arbitrary positive ancillary variable, is easily accommodated. The basic technique selects points in a two-dimensional continuum, but is also applicable to sampling finite populations or one-dimensional continua embedded in two-dimensional space. An extension of the basic technique gives a way to order the sample points so that any set of consecutively numbered points is in itself a spatially well-balanced sample. This latter property is extremely useful in adjusting the sample for the frame imperfections common in environmental sampling.

Spatially Restricted Surveys Over Time for Aquatic Resources

Consideration of the natural characteristics of aquatic resources and available frame material has led to the development of new designs for surveying large-scale regions. This paper illustrates survey designs developed to meet the requirements for surveying various aquatic resources, including a finite, discrete population, such as lakes within one or more states; a continuous linear population within a bounded area, such as wadeable streams within one or more states; and a continuous two-dimensional population within a bounded area, such as coastal waters associated with one or more states. We present a unified approach that addresses the differences of the aquatic resources assuming the availability of frame material, such as Geographic Information System (GIS) coverages of the boundary for coastal waters, stream network, and lake locations from U.S. Environmental Protection Agencys River Reach File 3, derived from U.S. Geological Survey digital line graph data from 1:100,000 scale maps. The basic design methodology distributes the sample over the spatial extent of the resource domain, and a panel structure can be used to extend the sample through time. Key features for the approach are (1) utilizing survey theory for continuous populations within a bounded area, (2) explicit control of the spatial dispersion of the sample, (3) variable spatial density, (4) nested subsampling, and (5) incorporating panel structures for sampling over time.

Condition of stream ecosystems in the US: an overview of the first national assessment

Abstract The Wadeable Streams Assessment (WSA) provided the first statistically sound summary of the ecological condition of streams and small rivers in the US. Information provided in the assessment filled an important gap in meeting the requirements of the US Clean Water Act. The purpose of the WSA was to: 1) report on the ecological condition of all wadeable, perennial streams and rivers within the conterminous US, 2) describe the biological condition of these systems with direct measures of aquatic life, and 3) identify and rank the relative importance of chemical and physical stressors affecting stream and river condition. The assessment included perennial wadeable streams and rivers that accounted for 95% of the length of flowing waters in the US. The US Environmental Protection Agency, states, and tribes collected chemical, physical, and biological data at 1392 randomly selected sites. Nationally, 42% of the length of US streams was in poor condition compared to best available reference sites in their ecoregions, 25% was in fair condition, and 28% was in good condition. Results were reported for 3 major regions: Eastern Highlands, Plains and Lowlands, and West. In the West, 45% of the length of wadeable flowing waters was in good condition. In the Eastern Highlands, only 18% of the length of wadeable streams and rivers was in good condition and 52% was in poor condition. In the Plains and Lowlands, almost 30% of the length of wadeable streams and rivers was in good condition and 40% was in poor condition. The most widespread stressors observed nationally and in each of the 3 major regions were N, P, riparian disturbance, and streambed sediments. Excess nutrients and excess streambed sediments had the highest impact on biological condition; streams scoring poor for these stressors were at 2 to 3× higher risk of having poor biological condition than were streams that scored in the good range for the same stressors.

Survey design and extent estimates for the Wadeable Streams Assessment

Abstract The US Environmental Protection Agency (EPA) conducted a Wadeable Stream Assessment (WSA) of all wadeable streams and rivers in the conterminous US between 1999 and 2005. The assessment was led by the EPA Office of Water, in cooperation with EPA regions, states, tribal nations, and the EPA Office of Research and Development (ORD). The WSA was implemented as 2 large-scale regional surveys of streams and rivers. Both studies used EPAs River Reach File (RF3) as the basis for the sample frame. The Environmental Monitoring and Assessment Program (EMAP) Western Pilot Study, conducted by ORD in cooperation with EPA Regions 8, 9, and 10 and 12 western states, assessed all streams and rivers in the 12 western states (EMAP-West). A stratified, unequal probability survey design (50 sites/state and additional sites in 5 intensive study areas) was used to select sites from all streams and river segments coded as perennial in RF3. The unequal selection depended on Strahler order, aggregated Omernik level III ecoregion, and special study region. The WSA study used the EMAP-West wadeable streams (WSA-West) and implemented a new design for the remaining 36 eastern conterminous states (WSA-East). The WSA-East design was an unequal probability survey design with unequal selection depending on Strahler order, Omernik Level II ecoregion, and EPA region. RF3 includes 5.29 million km of rivers and streams, of which 39% (2.07 million km) are coded as perennial. The WSA sample frame included 2.84 million km of streams (54% of the total length in RF3), of which 2.24 million km were in WSA-East and 0.60 million km were in WSA-West. Each selected site was classified on the basis of wadeability and the presence of flowing water. The estimated length of wadeable streams and rivers in the 48 conterminous states was 1.30 ± 0.025 (SE) million km (45.7 ± 1.1% of the stream length in the sample frame). Of this wadeable stream length, 78.6 ± 1.0% (1.02 million km) was estimated to be appropriate for sampling. Nationally, 11.5 ± 0.8% and 5.2 ± 0.6% of this length could not be sampled because of access denial or physical inaccessibility, respectively. The proportion of length affected by access denial was higher in Southern Plains, Northern Plains, and Xeric West aggregated ecoregions, whereas stream length affected by physical inaccessibility was greatest in the Western Mountains aggregated ecoregion. Improvements in the sample frame (RF3 and its successors National Hydrography Database [NHD] and NHD-Plus) would reduce field costs for national surveys.

The Stream‐Catchment (StreamCat) Dataset: A Database of Watershed Metrics for the Conterminous United States

We developed an extensive database of landscape metrics for ~2.65 million stream segments, and their associated catchments, within the conterminous United States (U.S.): The Stream-Catchment (StreamCat) Dataset. These data are publically available (http://www2.epa.gov/national-aquatic-resource-surveys/streamcat) and greatly reduce the specialized geospatial expertise needed by researchers and managers to acquire landscape information for both catchments (i.e., the nearby landscape flowing directly into streams) and full upstream watersheds of specific stream reaches. When combined with an existing geospatial framework of the Nations rivers and streams (National Hydrography Dataset Plus Version 2), the distribution of catchment and watershed characteristics can be visualized for the conterminous U.S. In this article, we document the development and main features of this dataset, including the suite of landscape features that were used to develop the data, scripts and algorithms used to accumulate and produce watershed summaries of landscape features, and the quality assurance procedures used to ensure data consistency. The StreamCat Dataset provides an important tool for stream researchers and managers to understand and characterize the Nations rivers and streams.

Perfluorinated compounds in fish from U.S. urban rivers and the Great Lakes.

Perfluorinated compounds (PFCs) have recently received scientific and regulatory attention due to their broad environmental distribution, persistence, bioaccumulative potential, and toxicity. Studies suggest that fish consumption may be a source of human exposure to perfluorooctane sulfonate (PFOS) or long-chain perfluorocarboxylic acids. Most PFC fish tissue literature focuses on marine fish and waters outside of the United States (U.S.). To broaden assessments in U.S. fish, a characterization of PFCs in freshwater fish was initiated on a national scale using an unequal probability design during the U.S. Environmental Protection Agencys (EPAs) 2008-2009 National Rivers and Streams Assessment (NRSA) and the Great Lakes Human Health Fish Tissue Study component of the 2010 EPA National Coastal Condition Assessment (NCCA/GL). Fish were collected from randomly selected locations--164 urban river sites and 157 nearshore Great Lake sites. The probability design allowed extrapolation to the sampled population of 17,059 km in urban rivers and a nearshore area of 11,091 km(2) in the Great Lakes. Fillets were analyzed for 13 PFCs using high-performance liquid chromatography tandem mass spectrometry. Results showed that PFOS dominated in frequency of occurrence, followed by three other longer-chain PFCs (perfluorodecanoic acid, perfluoroundecanoic acid, and perfluorododecanoic acid). Maximum PFOS concentrations were 127 and 80 ng/g in urban river samples and Great Lakes samples, respectively. The range of NRSA PFOS detections was similar to literature accounts from targeted riverine fish sampling. NCCA/GL PFOS levels were lower than those reported by other Great Lakes researchers, but generally higher than values in targeted inland lake studies. The probability design allowed development of cumulative distribution functions (CDFs) to quantify PFOS concentrations versus the sampled population, and the application of fish consumption advisory guidance to the CDFs resulted in an estimation of the proportion of urban rivers and the Great Lakes that exceed human health protection thresholds.

Perspectives on large-scale natural resource surveys when cause-effect is a potential issue

Our objective is to present a perspective on large-scale natural resource monitoring when cause-effect is a potential issue. We believe that the approach of designing a survey to meet traditional commodityproduction and resource state descriptive objectives is too restrictive and unnecessarily limits theability to investigate cause-effect issues. We only consider terrestrial natural resources, focusing on forests and rangeland. A large institutionalized programme is required to establish cause-effect relationships when monitoring terrestrial resources. This is justified based on the growing concerns about our natural resources. A long-term vision of a desirable future terrestrial monitoring system, realizing that it is not clear yet what key variables should be measured, will increase the chances that decisions on current designs will ultimately lead to better systems in the future. We propose a pronounced shift in the designs applied to forest and range, specifically, the NationalResources Inventory (NRI), the Forest Inventory and Analysis (FIA), and the Forest Health Monitoring (FHM) programmes. The designs must not only address simple status and trends estimation but also give emphasis to identifying interesting changes occurring in the sampled populations thus facilitating identification and establishment of possible cause-effect relationships. We propose an integrated design consisting of a large-scale, long-term ongoing survey as the core design accompanied by supplemental experimental design studies or analytic survey. Continuous inventory involving annual measurement of a subset of the sample from selected populations should be implemented: inventorying a population every five years (as with NRI) or every ten years (as with FIA) is insufficient. FHM, FIA, and NRI should collect a subset of variables in common. Complementarity of data collected would make it more likely to identify promising cause-effect relationships for a wider range of resource variables. At this stage we recommend focusing on the mortality of trees, shrubs, forbs, and grasses as the key indicator of forest and range health. Mortality is objectively measurable and can often be detected by remote sensing. When possible, follow-up observational studies to document cause-effect relationships should be limited to public lands because of concern of infringing on the personal rights of landowners. This may not be possible if unrepresentative populations result because of this. If studies are designed properly, we could achieve our objectives yet tie such studies to current natural resource inventory systems.

Using a Master Sample to Integrate Stream Monitoring Programs

The need for aquatic resource condition surveys at scales that are too extensive to census has increased in recent years. Statistically designed sample surveys are intended to meet this need. Simple or stratified random sampling or systematic survey designs are often used to obtain a representative set of sites for data collection. However, such designs have limitations when applied to spatially distributed natural resources, like stream networks. Stevens and Olsen proposed a design that overcomes the key limitations of simple, stratified random or systematic designs by selecting a spatially balanced sample. The outcome of a spatially balanced sample is an ordered list of sampling locations with spatial distribution that balances the advantages of simple or stratified random samples or systematic samples. This approach can be used to select a sample of sites for particular studies to meet specific objectives. This approach can also be used to select a “master sample” from which subsamples can be drawn for particular needs. At the same time, these individual samples can be incorporated into a broader design that facilitates integrated monitoring and data sharing.

Survey design and extent estimates for the National Lakes Assessment

Abstract.  The US Environmental Protection Agency (USEPA) conducted a National Lakes Assessment (NLA) in the conterminous USA in 2007 as part of a national assessment of aquatic resources. The EPA used the National Hydrography Dataset (NHD) as the basis for the sample frame for the NLA. The target population was all lakes >4 ha, excluding the Laurentian Great Lakes and the Great Salt Lake. An unequal probability survey design was used to select 4472 candidate lakes for potential sampling. The unequal selection depended on 5 lake area classes and 9 aggregated Omernik level III ecoregions. In all, 2034 candidate lakes were evaluated for inclusion in the target population, and 1309 lakes (representing ∼68,000 lakes in the sample frame) met the criteria. A total of 1028 lakes (of 1309) were sampled and represented ∼50,000 lakes. The remaining lakes (231, representing ∼18,000 lakes) could not be sampled because of access denial or physical inaccessibility. The target population included natural (41 ± 2% [SE]) and man-made lakes (59 ± 2%). All target lakes in the Southern Appalachian region and >90% of the target population in the Southern Plains and Xeric regions were man-made. In the Upper Midwest region, 97 ± 1% of the target population were natural lakes. Small lakes (4–10 ha) made up 47 ± 2% of the target population, and lakes >50 ha made up ∼15% of the target population. The results raise 2 issues that have implications for current and future NLA projects: 1) the cost and effort required to identify lake features in the sample frame that do not meet the criteria for inclusion in the target population (∼50% in NLA 2007), and 2) the potential for biased estimates of the size and condition of the target population caused by lakes that cannot be sampled. Future NLA efforts involve refining the survey design to include smaller lakes and resampling lakes from previous NLAs. We offer approaches for addressing both issues, including use of a high-resolution version of NHD as the basis for developing the NLA sample frame. Developing a master sample frame of lakes would provide a consistent basis of lake numbers (or surface area) from which to estimate extent or assess ecological condition.

Using Linked Micromap Plots to Characterize Omernik Ecoregions

The paper introduces linked micromap (LM) plots for presenting environmental summaries. The LM template includes parallel sequences of micromap, label, and statistical summary graphics panels with attention paid to perceptual grouping, sorting and linking of the summary components. The applications show LM plots for Omernik Level II Ecoregions. The summarized United States continental data includes USGS digital elevation, 30-year normal precipitation and temperature, and 8 million AVHRR pixels classified into 159 types of land cover. One LM plot uses a line-height glyph to represent all 159 land cover percentages per ecoregion. LM plots represent new visualization methodology that is useful in the data and knowledge based pattern representation and knowledge discovery process. The LM plots focus on providing an orienting overview. The overview provides a starting place for subsequent drilling down to what could otherwise be viewed as an overwhelming mass of data. The overview also provides a starting place to learn about the intellectual structure that lies behind the notion of ecoregions and begins to connect this abstract structure to quantitative methods.