Selecting the optimum plot size for a California design-based stream and wetland mapping program

Accurate estimates of the extent and distribution of wetlands and streams are the foundation of wetland monitoring, management, restoration, and regulatory programs. Traditionally, these estimates have relied on comprehensive mapping. However, this approach is prohibitively resource-intensive over large areas, making it both impractical and statistically unreliable. Probabilistic (design-based) approaches to evaluating status and trends provide a more cost-effective alternative because, compared with comprehensive mapping, overall extent is inferred from mapping a statistically representative, randomly selected subset of the target area. In this type of design, the size of sample plots has a significant impact on program costs and on statistical precision and accuracy; however, no consensus exists on the appropriate plot size for remote monitoring of stream and wetland extent. This study utilized simulated sampling to assess the performance of four plot sizes (1, 4, 9, and 16 km²) for three geographic regions of California. Simulation results showed smaller plot sizes (1 and 4 km²) were most efficient for achieving desired levels of statistical accuracy and precision. However, larger plot sizes were more likely to contain rare and spatially limited wetland subtypes. Balancing these considerations led to selection of 4 km² for the California status and trends program.     

Optimising the sampling effort in riparian surveys

Riparian condition is commonly measured as part of stream health monitoring programs as riparian vegetation provides an intricate linkage between the terrestrial and aquatic ecosystems. Field surveys of a riparian zone provide comprehensive riparian attribute data but can be considerably intensive and onerous on resources and workers. Our objective was to assess the impact of reducing the sampling effort on the variation in key riparian health indicators. Subsequently, we developed a non-parametric approach to calculate an information retained (IR) statistic for comparing several constrained systematic sampling schemes to the original survey. The IR statistic is used to select a scheme that reduces the time taken to undertake riparian surveys (and thus potentially the costs) whilst maximising the IR from the original survey. Approximate bootstrap confidence intervals were calculated to improve the inferential capability of the IR statistic. The approach is demonstrated using riparian vegetation indicators collected as part of an aquatic ecosystem health monitoring program in Queensland, Australia. Of the nine alternative sampling designs considered, the sampling design that reduced the sampling intensity per site by sixfold without significantly comprising the quality of the IR, results in halving the time taken to complete a riparian survey at a site. This approach could also be applied to reducing sampling effort involved in monitoring other ecosystem health indicators, where an intensive systematic sampling scheme was initially employed.     

Physical integrity: the missing link in biological monitoring and TMDLs

The Clean Water Act mandates that the chemical, physical, and biological integrity of our nation’s waters be maintained and restored. Physical integrity has often been defined as physical habitat integrity, and as such, data collected during biological monitoring programs focus primarily on habitat quality. However, we argue that channel stability is a more appropriate measure of physical integrity and that channel stability is a foundational element of physical habitat integrity in low-gradient alluvial streams. We highlight assessment tools that could supplement stream assessments and the Total Maximum Daily Load stressor identification process: field surveys of bankfull cross-sections; longitudinal thalweg profiles; particle size distribution; and regionally calibrated, visual, stream stability assessments. Benefits of measuring channel stability include a more informed selection of reference or best attainable stream condition for an Index of Biotic Integrity, establishment of a baseline for monitoring changes in present and future condition, and indication of channel stability for investigations of chemical and biological impairments associated with sediment discontinuity and loss of habitat quality.     

Using statistical power analysis as a tool when designing a monitoring program: experience from a large-scale Swedish landscape monitoring program

The National Inventory of Landscapes in Sweden (NILS) is a large-scale, sample-based monitoring program that combines aerial photointerpretation with field inventory to follow landscape-scale biophysical conditions and changes. A statistical power analysis was conducted before the NILS program began in 2003 with the aim to determine an appropriate sampling effort and compare some design alternatives. The chosen sampling effort was then evaluated in a second power analysis conducted just before the first 5-year re-inventory rotation started. The latter power analysis revealed which magnitude of actual change might be detected within the future for different central monitoring variables. This article reports results from these power analyses and discusses our experiences in using power analysis as a tool for designing large-scale monitoring programs. The results showed that even quite small changes in the more common variables, such as land cover types and more common plant species, can be detected on the national scale. However, on the regional scale, or for less common variables, changes will be more difficult to detect. The power analyses have revealed the size level of changes that will be possible to detect. The results have also generated incentives for further improvements of NILS, e.g., input to the modification and revision of the variable content, flow and hierarchy, and incentives for launching other complementary monitoring programs connected to NILS. They have also created a basis for a better and more user-oriented communication of results from NILS to different stakeholders.     

Assessment of wadeable stream resources in the driftless area ecoregion in Western Wisconsin using a probabilistic sampling design

The Wisconsin Department of Natural Resources (WDNR), with support from the U.S. EPA, conducted an assessment of wadeable streams in the Driftless Area ecoregion in western Wisconsin using a probabilistic sampling design. This ecoregion encompasses 20% of Wisconsin’s land area and contains 8,800 miles of perennial streams. Randomly-selected stream sites (n = 60) equally distributed among stream orders 1–4 were sampled. Watershed land use, riparian and in-stream habitat, water chemistry, macroinvertebrate, and fish assemblage data were collected at each true random site and an associated “modified-random” site on each stream that was accessed via a road crossing nearest to the true random site. Targeted least-disturbed reference sites (n = 22) were also sampled to develop reference conditions for various physical, chemical, and biological measures. Cumulative distribution function plots of various measures collected at the true random sites evaluated with reference condition thresholds, indicate that high proportions of the random sites (and by inference the entire Driftless Area wadeable stream population) show some level of degradation. Study results show no statistically significant differences between the true random and modified-random sample sites for any of the nine physical habitat, 11 water chemistry, seven macroinvertebrate, or eight fish metrics analyzed. In Wisconsin’s Driftless Area, 79% of wadeable stream lengths were accessible via road crossings. While further evaluation of the statistical rigor of using a modified-random sampling design is warranted, sampling randomly-selected stream sites accessed via the nearest road crossing may provide a more economical way to apply probabilistic sampling in stream monitoring programs.     

Assessing the ecological condition of streams in a southeastern Brazilian basin using a probabilistic monitoring design

Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region.     

Principles for the monitoring and evaluation of wetland extent,condition and function in Australia

The monitoring of resource condition is receiving renewed attention across several levels of government in Australia. This interest is linked to substantial investment in environmental remediation and aquatic ecosystem restoration in particular. In this context, it is timely to consider principles which ought to guide the development and implementation of monitoring programmes for wetland ecosystems. A framework is established which places monitoring in the context of the strategic adaptive management of wetlands. This framework requires there has to be clear goals for the extent and condition of the resource, with these goals being defined within thresholds of acceptable variability. Qualitative and, where possible, quantitative conceptual models linking management interventions to management goals should be the basis of indicator selection and assessment. The intensity of sampling ought to be informed by pilot surveys of statistical power in relation to the thresholds of acceptable variability identified within the management plan.     

Contemplating the Assessment of Great River Ecosystems

The science and practice of assessing the status and trends of ecological conditions in great rivers have not kept pace with perturbation wrought on these systems. Participants at a symposium sponsored by the U.S. Environmental Protection Agency (USEPA) and the Council of State Governments concluded that useful and efficient assessments of great river ecosystems require thoughtful alignment of sampling designs, spatial and temporal scales, indicators, management needs, and ecosystem characteristics. Site-specific physical, chemical, and biological data long accumulated by monitoring programs have value but fail to provide the integrated system-wide perspective required for adaptive management and the Clean Water Act. Use of existing data may be limited by methodological incompatibilities, access difficulties, and the exclusive applicability of data to specific habitats or sites. The transition from site-specific to system-wide assessments benefits from research being done by USEPA's Environmental Monitoring and Assessment Program (EMAP) and other programs that use probability surveys and biological indicators. Indicators of various taxa (in particular fish, algae, and benthic invertebrates) have been successfully developed for great rivers. However, optimizing the information these ecological indicators convey to managers and the public is the subject of ongoing research.     

Framework for designing sampling programs

A general framework for designing sampling programs is described. As part of the sampling program the problem of concern, or reason for sampling, needs to be clearly stated and objectives specified. The development of a conceptual model will assist the clarification of objectives and the choice of indicators to be sampled.Objectives can then be stated as testable hypotheses and decisions made about the samallest difference/changes that are to be detected/observed by the sampling.To allow the collection of representative samples, and the statistical analysis of data to be collected, the potential sources of variability in the data must be considered. Site, selection, frequency and replication must account for the expected variability.Before field collection of samples occurs, the sample collection device needs to be tested as to its efficiency to collect a representative sample. It also will usually be necessary to consider how samples are to be preserved to inhibit biological and chemical change. All sample programs require a quality assurance program to identify, measure and control errors.As well as the above the cost-effectiveness of the program should be evaluated in terms of maximizing the information obtained/cost.     

Statistical Issues for Monitoring Ecological and Natural Resources in the United States

The United States funds a number of national monitoring programs to measure the status and trends of ecological and natural resources. Each of these programs has a unique focus; the scientific objectives are different as are the sample designs. However, individuals and committees, all well aware of the cost of ecological monitoring, have called for more effective monitoring programs. The objective of this paper is to summarize existing programs' statistical designs and discuss potential alternatives for improvement in national monitoring. Can we improve the current situation by providing an overall framework for the design or analysis of data from these disparate surveys? First, the paper summarizes the objectives of these surveys, compares and contrasts their survey designs as currently implemented, and determines what variables they collect. Through this process we identify commonalities and issues that impact our ability to combine information across one or more of the surveys. Three potential alternatives are presented, leading to comprehensive monitoring in the United States.     

Attributes of reliable long-term landscape-scale studies: Malpractice insurance for landscape ecologists

Monitoring long-term change in forested landscapes is an intimidating challenge with considerable practical, methodological, and theoretical limitations. Current field approaches used to assess vegetation change at the plot-to-stand scales and nationwide forest monitoring programs may not be appropriate at landscape scales. We emphasize that few vegetation monitoring programs (and, thus, study design models) are designed to detect spatial and temporal trends at landscape scales. Based primarily on advice from many sources, and trial and error, we identify 14 attributes of a reliable long-term landscape monitoring program: malpractice insurance for landscape ecologists. The attributes are to: secure long-term funding and commitment; develop flexible goals; refine objectives; pay adequate attention to information management; take an experimental approach to sampling design; obtain peer-review and statistical review of research proposals and publications; avoid bias in selection of long-term plot locations; insure adequate spatial replication; insure adequate temporal replication; synthesize retrospective, experimental, and related studies; blend theoretical and empirical models with the means to validate both; obtain periodic research program evaluation; integrate and synthesize with larger and smaller scale research, inventory, and monitoring programs; and develop an extensive outreach program. Using these 14 attributes as a guide, we describe one approach to assess the potential effect of global change on the vegetation of the Front Range of the Colorado Rockies. This self-evaluation helps identify strengthes and weaknesses in our program, and may serve the same role for other landscape ecologists in other programs.     

Theoretical and practical criteria for the selection of ecosystem monitoring plots in Swiss forests

A great deal of attention has been paid to the selection of nature reserves. These are important from a conservation viewpoint but, for long-term evaluations, it is important to monitor ecosystems. The need for long-term monitoring plots has been recognized for some time in forest ecology. Of the natural ecosystems, forests are some of the most difficult to monitor because of the time-scales involved in the life-spans of the dominant organisms (100 1000 years). The selection of long-term forest ecosystem monitoring plots is a critical process involving decisions that need to remain valid for many years. Traditional sampling theory suggests that some form of systematic or random sampling may be appropriate, but this is usually inappropriate for the selection of ecosystem monitoring plots. Instead, the selection of plots more closely resembles some of the procedures that are used in the selection of nature reserves. In Switzerland, a monitoring programme has been established which uses a number of criteria for the selection of sites. These include site homogeneity, the abundance and sensitivity of the plant communities to change and the presence of pre-existing data series or monitoring equipment. In addition, the human factor is incorporated by selecting sites from throughout the country, with the willingness of the local forest managers to help with the project being an important factor influencing the final choice of plots. In contrast to most inventories, statistical representativeness is not a requirement for the programme, as the plots are treated as a series of case studies.     

State of the Estuaries in the Mid-Atlantic Region of the United States

The U.S. EPA has prepared a State of the Region Report for Mid-Atlantic Estuaries to increase knowledge of environmental condition for improved environmental management. Sources of information included the National Estuary Programs, the Chesapeake Bay Program, the state monitoring programs in Delaware, Maryland, and Virginia, Federal programs such as National Status & Trends, National Shellfish Register, National Wetlands Inventory, the Environmental Monitoring and Assessment Program, and other primary literature sources. The state of the estuarine environment was summarized using indicators for water and sediment quality, habitat change, condition of living resources, and aesthetic quality. Each indicator was briefly discussed relative to its importance in understanding estuarine condition. Wherever possible, data from multiple programs were used to depict condition. Finally, an overall evaluation of estuarine condition in the region was determined. The usefulness of monitoring programs that collect consistent information with a well-defined sampling design cannot be overemphasized.     

Assessment of the statistical significance of seasonal groundwater quality change in a karstic aquifer system near Izmir-Turkey

The main objective of this study was to statistically evaluate the significance of seasonal groundwater quality change and to provide an assessment on the spatial distribution of specific groundwater quality parameters. The studied area was the Mount Nif karstic aquifer system located in the southeast of the city of Izmir. Groundwater samples were collected at 57 sampling points in the rainy winter and dry summer seasons. Groundwater quality indicators of interest were electrical conductivity (EC), nitrate, chloride, sulfate, sodium, some heavy metals, and arsenic. Maps showing the spatial distributions and temporal changes of these parameters were created to further interpret spatial patterns and seasonal changes in groundwater quality. Furthermore, statistical tests were conducted to confirm whether the seasonal changes for each quality parameter were statistically significant. It was evident from the statistical tests that the seasonal changes in most groundwater quality parameters were statistically not significant. However, the increase in EC values and aluminum concentrations from winter to summer was found to be significant. Furthermore, a negative correlation between sampling elevation and groundwater quality was found. It was shown that with simple statistical testing, important conclusions can be drawn from limited monitoring data. It was concluded that less groundwater recharge in the dry period of the year does not always imply higher concentrations for all groundwater quality parameters because water circulation times, lithology, quality and extent of recharge, and land use patterns also play an important role on the alteration of groundwater quality.     

Aerial Monitoring of Marine Waterfowl in the Alaskan Beaufort Sea

The purpose of this study was to design and test a monitoring protocol for marine waterfowl in the central Alaskan Beaufort Sea. The study provides an important case-study of how a long-term monitoring program may be affected by unanticipated human disturbances.Because of its overwhelming and widespread abundance, relatively sedentary behavior, ease in counting, and the extensive historical database, the long-tailed duck (Clangula hyemalis) was selected as the focal species. Two null hypotheses were formulated concerning potential changes in the numbers and distribution of long-tailed ducks in relation to disturbance in an industrial study area, compared to a reference study area located about 50 km to the east.A 9-year historical database (1977–1984, 1989) of long-tailed duck densities and other important data recorded during systematic aerial surveys was analyzed retrospectively using multiple regression techniques. The retrospective analyses determined which of several predictor variables recorded were significantly related to long-tailed duck density. Separate analyses were conducted for two periods: (1) the overall period when long-tailed ducks were present in the lagoon study areas, and (2) the shorter adult male molt period. The results of the two analyses indicated that 57% and 68%, respectively, of the total variation in long-tailed duck density during the two periods could be explained by variables recorded during the surveys. Predictor variables representing habitat, day of the year, time of day, amount of ice, and wave height recorded on-transect during surveys were most closely associated with long-tailed duck density. Measurement error during the surveys, and influences outside the study area such as nesting success in tundra habitats and mortality during migration and in over-wintering areas likely also had strong influences on the results, but these factors were not measurable in our study.Based on results of the retrospective analyses, a long-term monitoring protocol consisting of a program of systematic aerial surveys and an analyses of variance and covariance (ANOVA and ANCOVA) statistical procedure was designed and initially tested in 1990 and 1991. This 2-year testing phase resulted in several revisions to the monitoring protocol. Refinements were made to the original sampling procedures, to the survey schedule, and to the recommended statistical analysis procedures. Results of the ANOVA and ANCOVA indicated that there was no evidence of a change in long-tailed duck densities that could be attributable to disturbance (from any source) in the industrial study area relative to a reference area with no industrial development. Other analyses indicated that the sampling and analysis procedures would be adequate to detect long-term trends in long-tailed duck density and localized disturbance effects, but that the monitoring program should be continued well beyond two years to detect statistically significant changes. As a result, additional aerial surveys of both study areas were conducted again during 1999–2001.Results of the revised ANOVA and ANCOVA of the 1990–1991 and 1999–2001 survey data indicated that the density of long-tailed ducks had significantly declined in coastal lagoons along the central Alaskan Beaufort Sea coast during the study period. In addition, disturbances throughout the barrier island-lagoon systems used by these ducks, including both the industrial and the reference study areas, had significantly increased over the same period. However, because unanticipated disturbances from a variety of anthropogenic sources, and not just industry sources, increased in both study areas, the reference study area was not an effective statistical control. As a result, the decline in long-tailed duck density in both study areas was not attributable to industry-related activities. Although the monitoring protocol described here is an effective method to detect statistically significant changes in long-tailed duck distribution and abundance in the nearshore Alaskan Beaufort Sea, many more years of sampling would be necessary to attribute observed changes to industry-related disturbances.     

A proposed coast-wide reference monitoring system for evaluating wetland restoration trajectories in Louisiana

Wetland restoration efforts conducted in Louisiana under the Coastal Wetlands Planning, Protection and Restoration Act require monitoring the effectiveness of individual projects as well as monitoring the cumulative effects of all projects in restoring, creating, enhancing, and protecting the coastal landscape. The effectiveness of the traditional paired-reference monitoring approach in Louisiana has been limited because of difficulty in finding comparable reference sites. A multiple reference approach is proposed that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling. This approach includes a suite of sites that encompass the range of ecological condition for each stratum, with projects placed on a continuum of conditions found for that stratum. Trajectories in reference sites through time are then compared with project trajectories through time. Plant community zonation complicated selection of indicators, strata, and sample size. The approach proposed could serve as a model for evaluating wetland ecosystems.     

Optimising vegetation monitoring. A case study in A French lowland forest

Biodiversity monitoring surveys are rarely optimised statistically before being initiated. Here, we optimised the monitoring of plants in a temperate forest. The total inventory cost, the number and size of quadrats were optimised to detect a 10% change in species richness over 5 years with α = β = 0.05, using data from ongoing long-term floristic monitoring programs. The procedure showed that the inventory cost would be ca 15% lower using 100-, 200-m² quadrats instead of 300- or 400-m² quadrats. Despite the cost associated with the optimisation (e.g. gathering preliminary data) and the imprecise estimates (due to the typically small sample size of the pilot studies), optimisation would often be a better option than expert opinion when designing a monitoring survey.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

A comparison of techniques to sample salamander assemblages along highland streams of Maryland

Amphibians may be useful indicators of biological condition in small streams so determining which sampling technique maximizes encounters at the least cost and at the optimal time of year is important. Area constrained surveys (ACS), used by the Maryland Biological Stream Survey, were tested against cover board surveys, drift fences with pitfall and funnel traps, quadrat leaf litter searches, and leaf litter bags. Sixteen, 100 m-long sites were established in headwater streams in the Savage River State Forest in Garrett County, Maryland. Each technique was randomly assigned to a 25 m stream section within each overall sampling site, and sites were sampled once each month from May to October (2005) with additional sampling in March and April (2006). Area constrained surveys yielded means of 2.7 taxa and 14.9 total individuals per sampling visit, which was significantly higher than the yield of all other methods in all months except October and March, when yields were low for all techniques. Area constrained surveys were also significantly more cost-effective per taxon and per individual compared to all other methods. September produced the most taxa and individuals, October and March produced the least, and yields for April through August were similar to September. We employed removal sampling at four sites in April 2006, but abundance could not be estimated because a significant linear decrease in the accumulated catch versus catch per unit effort did not occur for three of the sites.     

Mathematical balance models for monitoring the state of Lake Baikal

The global cycles of man-produced pollutants entering the natural environment are reflected in changes of pollutant cycles, even in background regions.The system of mathematical balance simulation models of inorganic pollutant distribution and circulation (some heavy metals and pesticides included in the priority list for integrated background monitoring) has been developed for the Lake Baikal drainage basin. The system consists of the following units: (1) inventory and classification of regional sources of pollutants entering the atmosphere, natural waters and soils; (2) computation of the global atmospheric transfer and depositions; (3) regional spreading with atmospheric fluxes and deposition onto the underlying surfaces; (4) transport with waterflows feeding Lake Baikal; (5) transport with the lake currents and balance in the lake.The models developed have enabled improvement of existing programmes and systems of observations, in particular to substantiate the large-scale snow sampling and analysis network, and to develop the programme of integrated surveys of the state of Lake Baikal. Since 1981 these actions have been included in the operational network observations within the Lake Baikal Monitoring System.