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Guidance for Designing an Integrated Monitoring Program

Introduction

Natural resource monitoring is a major component of park stewardship, and a cornerstone of the NPS Natural Resource Challenge - a program to revitalize and expand the natural resource program within the park service and improve park management through greater reliance on scientific knowledge. The overall purpose for natural resource monitoring is to determine the status and trend in the condition of selected park resources. Monitoring results will be used to assess the efficacy of management and restoration efforts, provide early warning of impending threats, and provide a basis for understanding and identifying meaningful change in natural systems characterized by complexity, variability, and surprises. Monitoring data may help to determine what constitutes impairment and to identify the need to initiate or change management practices.

The intent of park vital signs monitoring is to track a subset of physical, chemical, and biological elements and processes of park ecosystems that are selected to represent the overall health or condition of park resources, known or hypothesized effects of stressors, or elements that have important human values. The elements and processes that are monitored are a subset of the total suite of natural resources that park managers are directed to preserve "unimpaired for future generations," including water, air, geological resources, plants and animals, and the various ecological, biological, and physical processes that act on those resources. In situations where natural areas have been so highly altered that physical and biological processes no longer operate (e.g., control of fires and floods in developed areas), information obtained through monitoring can help managers understand how to develop the most effective approach to restoration or, in cases where restoration is impossible, ecologically sound management. The broad-based, scientifically sound information obtained through natural resource monitoring will have multiple applications for management decision-making, research, education, and promoting public understanding of park resources.

Integration: Ecological, Spatial, Temporal and Programmatic

One of the most difficult aspects of designing a comprehensive monitoring program is integration of monitoring projects so that the interpretation of the whole monitoring program yields information more useful than that of individual parts. Integration involves ecological, spatial, temporal and programmatic aspects:

Establishing Monitoring Goals and Objectives

The overall purpose of natural resource monitoring in parks is to develop scientifically sound information on the current status and long term trends in the composition, structure, and function of park ecosystems, and to determine how well current management practices are sustaining those ecosystems. Use of monitoring information will increase confidence in manager's decisions and improve their ability to manage park resources, and will allow managers to confront and mitigate threats to the park and operate more effectively in legal and political arenas. To be effective, the monitoring program must be relevant to current management issues as well as anticipate future issues based on current and potential threats to park resources. The program must be scientifically credible, produce data of known quality that are accessible to managers and researchers in a timely manner, and be linked explicitly to management decision-making processes.

To guide the monitoring program, all 32 park networks address the following five Goals of Vital Signs Monitoring as they plan, design, and implement integrated natural resource monitoring:

An effective long-term ecosystem monitoring program will: One of the first steps in developing a long-term monitoring program is to articulate clearly the goals and objectives of the parks and the network of parks in concert with these Servicewide goals. Park-specific goals and objectives will be based on factors such as the park's enabling legislation, legal mandates for monitoring endangered species and other resources, planning documents such as the General Management Plan or Resource Management Plan, and input from park managers and scientists regarding important park resources and the stressors affecting those resources. The information needed to formulate these goals and objectives will be obtained through the steps outlined in the Recommended Approach for Developing a Network Monitoring Program.

Monitoring objectives, to be effective, should be realistic, specific, unambiguous, and measurable. This goes back to the statement that monitoring should not be an "I'll know it when I see it" process. Monitoring objectives should include six components to be complete (Elzinga et al. 1998:41): the indicator or "vital sign" to be monitored, the location or geographical area, the attribute of the indicator to be measured (e.g., population size, density, percent cover), the intended management action (increase, decrease, maintain), the measurable state or degree of change for the attribute, and the time frame. Specific monitoring objectives have not been documented by most parks, but objectives must be explicitly stated in order to design an effective monitoring program and to determine if management objectives are being met. Specific, measurable objectives for vital signs will usually not be developed until Phase 3 of the planning and design process.

As described by Elzinga et al. (1998:46), management objectives can usually be classified as one of two types: (1) target/threshold objectives (e.g., increase the population size of Species A to 5000 individuals; maintain a population of a rare plant Species B at 2500 individuals or greater; keep Site C free of invasive weeds X and Y); or (2) change/trend objectives (e.g., increase mean density of Species A by 20%; decrease frequency of invasive weed X by 30% at Site C).

Examples of management objectives:

Technical Guidance on Specific Topics

Staff from the Natural Resource Program Center are developing technical guidance on specific topics to assist park networks in developing their monitoring program. The following materials are available, and will be updated and improved as new information becomes available:

Remote Sensing (including land use/land cover change)

Landscape-scale and Remote Sensing Resources for Monitoring Programs

Air Quality

Download Guidance on Air Quality and Air Quality Related Values Vital Signs Monitoring

Air Atlas - The Air Atlas is a GIS system that identifies air quality monitoring stations and air pollutant data for individual parks. It has been available for inventory purposes for some time, and continues to be improved on a regular basis. Because air quality monitoring is not done at all parks, the data is spatially interpolated. A lookup table that summarizes the estimated pollutant levels at all I&M parks is also available.

Geologic Resource Monitoring

Download Guidance on Geologic Monitoring for Vital Signs

Water Quality, Contaminants, and Aquatic Biology Vital Signs Monitoring

Download Part A: Identification of priority impaired and pristine waters for the water quality vital signs monitoring component.

Download Part B: Planning Process Steps. Issues to consider and then to document in a detailed study plan that includes a Quality Assurance Project Plan (QAPP) and monitoring protocols (Standard Operating Procedures)

Download Part C: Draft guidance on WRD required and other field parameter measurements,general monitoring methods, and some design considerations in preparation of a detailed study plan.

Download Part D: Draft guidance on laboratory analytes/ measurements and their consideration in preparation of a detailed study plan.

Download Part E: Draft guidance on data reporting and archiving in STORET.

Download Recommendations for Core Water Quality Monitoring Parameters  Final report from the freshwater workgroup subcommittee.

Download Recommendations for Core Water Quality (Vital Signs) Monitoring Parameters for Marine and Coastal National Parks.

Biological Resources - Threatened and Endangered Species

Biological Resources - Invasive Species

See guidance on invasive plant monitoring at Invasive Plants I&M Workshop and Guidance

Developing Conceptual Models of Relevant Ecosystem Components

A conceptual model is a visual or narrative summary that describes the important components of the ecosystem and the interactions among them. Development of a conceptual model helps in understanding how the diverse components of a monitoring program interact, and promotes integration and communication among scientists and managers from different disciplines. Conceptual model diagrams often take the form of a "boxes and arrows" diagram, whereby mutually exclusive components are shown in boxes and interactions among the components are shown with arrows, but many conceptual models include tables, matrices, sentences or paragraphs to summarize and communicate our understanding of the system.

The next section is condensed from a more detailed paper (with appendices) on guidelines for developing and preparing conceptual models.

Conceptual models are important throughout all phases of development of a monitoring program. Early in the process, simple conceptual models provide a framework that relates information in discussions and literature reviews to a broader context - it’s a structure to organize information. Learning that accompanies the design, construction, and revision of the models contributes to a shared understanding of system dynamics and appreciation of the diversity of information needed to identify an appropriate suite of ecosystem indicators.

Well designed conceptual models will
  • Formalize current understanding of system processes and dynamics
  • Identify linkages of processes across disciplinary boundaries
  • Identify the bounds and scope of the system of interest

    • and contribute to communication

  • Among scientists and program staff
  • Between scientists and managers
  • With the general public.

    • These roles are important throughout the life of a monitoring program. Once the program is underway, proper interpretation of indicators is greatly facilitated by sound and defensible linkages between the indicator and the ecological function or critical resource it is intended to represent (Kurtz et al. 2001). These key linkages should be explicit in conceptual models and their articulation is essential to justifying and interpreting ecological measurements.

    Conceptual models can take the form of any combination of narratives, tables, matrices of factors, or box-and-arrow diagrams. Jorgensen (1988) discusses 10 kinds of models and evaluates their advantages and disadvantages. Most monitoring programs will use a combination of these forms, and it may occasionally be useful to combine several forms in the same figure.

    Tables and matrices provide a convenient means to summarize large quantities of information, including interactions between components. However, many people find it difficult to comprehend how a system works from tabulated data, especially where the spatial context is significant.

    Diagrams are usually necessary to clearly communicate linkages between systems or system components. Most monitoring programs develop a set of conceptual models that consist of diagrams and accompanying narratives. Narratives describe the diagrams, justify functional relationships in figures, and cite sources of information and data on which the models are based.

    The process of constructing system diagrams almost always identifies inadequately understood or controversial model components. There isn’t a single correct conceptual model, and it can be insightful to explore alternative ways to represent the system. These different representations of the system can help articulate important, and often exclusive, hypotheses about drivers, stressors, or interactions that are central to understanding how the system operates. These alternative hypotheses can form the basis of an effective adaptive management program, and it will likely be worthwhile to make the extra effort to clearly document and archive alternatives that arise during the process of model construction. Workshops to construct conceptual models are brainstorming sessions, and they provide an important opportunity to explore alternative ways to compress a complex system into a small set of variables and functions.

    Most ecological systems are complex and management decisions are based on ecological, social, political, and economic considerations. To accommodate the full range of considerations, a set of models with different spatial domains and relevant subsystems will be necessary. Thus you can anticipate the need to construct different models that vary in scope, detail, spatial extent, relevant time frame, and focus. For realistic systems, it probably will not be particularly insightful or rewarding to attempt to construct a single model with all important components and interactions. An all-encompassing model will be too complex for most people to understand.

    While the monitoring program does not intend to develop quantitative ecosystem models or dictate management policy, constructing a set of realistic, focused conceptual models is an important starting point for designing effective monitoring programs and for evaluating effective management policies. Monitoring programs founded on a solid conceptual model are more likely to identify key processes and indicators, and thereby contribute significantly to Parks management. The central role of models (both conceptual and quantitative) is well illustrated in the Applied Science Strategy adopted by the South Florida Ecosystem Restoration Working Group.

    DEVELOPING CONCEPTUAL MODELS

    In many cases it will be difficult to create even a single conceptual model, and the more complex the system is, the more difficult it will be to reach consensus on the elements to be included, the key interactions between elements, and the response of the system to drivers and stressors. It may require a multiple meetings to obtain general agreement on model structure and content. Keep the end in mind - you want to develop a suite of models that address the time and spatial scales of interest, at an appropriate level of detail.

    Control and stressor models

    Depending on the intended use of the conceptual model, two fundamentally different model structures have been used by I & M Networks and other agencies. A control model is a conceptualism of the actual controls, feedback, and interactions responsible for system dynamics. A control model therefore needs to represent, in a mechanistic way, the key processes, interactions, and feedbacks. Quantitative ecosystem simulation models are control models, and they vary in complexity from relatively simple to highly complex. Most groups begin by constructing a set of control models since this is the way we typically think about how systems operate. For a particular system (e.g., Park or other land) control models are typically hierarchical, with a top level, highly aggregated model and more detailed models of subsystems. In quantitative simulation models, the subsystems are usually functional units (e.g., soils, plant, fire, etc.) that overlap in space, whereas conceptual models often first decompose a larger system into more-or-less spatially distinct vegetation or habitat types. Jackson et al. (2000) describe the process of creating simple simulation models.

    Stressor models are designed to articulate the relationships between stressors, ecosystem components, effects, and (sometimes) indicators. Stressor models normally do not represent feedbacks and they include only those system components that are most pertinent to the monitoring program. The intent of a stressor model is to illustrate sources of stress, ecological responses, and system attributes of most interest. These models are founded on known or hypothesized ecological relationships, frequently derived from control models, but they do not attempt a mechanistic representation of the system . The Everglades restoration program produced a comprehensive set of stressor models, and they have excellent documentation on how the models contribute to their overall management strategy (e.g., Gentile et al. 2001). The Greater Yellowstone and Northeast Coastal and Barrier Networks have developed sets of stressor models to guide their monitoring programs.

    It may be necessary to develop both kinds of model, at least for some subsystems or habitats. Control models present a more complete and accurate picture of system components and their interactions. Stressor models are likely to more clearly communicate the direct linkages between stressors, ecological responses, and indicators. The appendices to Everglades Restoration Plan include a set of well constructed and documented stressor models; some of these are reproduced in Appendix IV of the full document.

    STEPS IN CONSTRUCTING CONCEPTUAL MODELS

    A systematic program that leads to a set of conceptual models will include the following tasks. These tasks are described in more detail in the full document.
  • Clearly state the goals of the conceptual models.
  • Identify bounds of the system of interest.
  • Identify key model components, subsystems, and interactions.
  • Develop control models of key systems and subsystems.
  • Identify natural and anthropogenic stressors
  • Describe relationships of stressors, ecological factors, and responses.
  • Articulate key questions or alternative approaches.
  • Identify inclusive list of indicators.
  • (Prioritize indicators - a separate process)
  • Review, revise, refine models.

    • These steps appear in a sequential list, but it will be necessary to at least partially address the goals of some tasks simultaneously. For example, the construction of control models (steps 3 & 4) must include substantial discussion and consideration of stressors and relationships between stressors and ecological functions (steps 5 & 6).

    EXECUTION AND NETWORK EXPERIENCES

    Networks and prototypes have employed a wide variety of processes to develop conceptual models and the resulting models reflect this diversity. Here are some general observations from Network's experiences:

  • It is very useful to have a general (high level) conceptual model to focus groups on linkages between submodels and to encourage model builders to conform to a common model structure.
  • Hierarchical sets of models work well. At intermediate levels, submodels most commonly focus on vegetation types. The lowest-level models may focus on species, soils, or nutrients.
  • It can be difficult to include animal species or animal communities in ecosystem models. Separate models may be required for a particular species or community.
  • Models that address different scales are insightful, even when they focus on the same process or variables, but at different scales.
  • It is very time-consuming to build useful conceptual models. Engage collaborators with appropriate disciplinary expertise as early as possible and allow time for repeated revision.
  • There is a large return on investment in documenting the ecological theory that underpins a modeling approach. The underlying theory supports use of a common approach and shared vision of system processes and linkages. The NCPN report (currently being revised) is an excellent example.
  • At the lowest levels, models must include sufficient detail to link indicators to ecological processes and, where possible, to management actions. Insufficiently detailed models have limited utility. It is a substantial challenge to construct a model with just the right amount of detail, and to decide when to split a model into separate submodels to avoid an overly-complicated model.
  • Provide definitions of key terms and phrases. Syntax is important.

    Greater Yellowstone Network - is using the I&M program as an opportunity to review and integrate a variety of NR programs. Up to July 2003, they have developed a comprehensive set of control and stressor models, and a few hybrids. The models operate on a variety of scales (e.g., they include a dry timberland model as well as a Lake Bob model).

    Northern Colorado Plateau Network - report has an excellent discussion of underlying ecosystem theory. They have adopted state and transition models as a structural framework for representing dynamics of many systems. In conversation, they noted that insufficient detail in early models limited their usefulness.

    Mediterranean Coast Network - Developed an initial set of Everglades-type stressor models, but had difficulties adequately incorporating animal communities. The Network is currently developing energy flow models to better represent trophic relationships.

    Cape Cod - Implementation of stressor models and tables. Excellent early work on conceptual foundation of these models (Roman and Barrett 1997).

    Prioritizing and Selecting Indicators - What Should be Monitored?

    The task of selecting a few ecological indicators for a national park that "represent the overall health or condition of park resources, known or hypothesized effects of stressors, or elements that have important human values" is extremely difficult. It is relatively easy to generate a list of potential monitoring projects or indicators to address a park's most critical data needs, but the process of paring the list down to a few "vital signs" that best represent the composition, structure, and function of the larger ecosystem is very challenging.

    There is no tried and true method for developing and prioritizing a list of potential indicators. Many different approaches for developing and evaluating potential indicators have been used by various monitoring programs, and there are numerous sets of criteria for the 'ideal indicator'. A number of these approaches have been summarized in the following document:

    Example Criteria and Methodologies for Prioritizing Indicators

    Most networks of parks are following the basic approach depicted below to identify and prioritize potential vital signs. The scoping process usually involves a series of meetings, workshops, brainstorming sessions, questionnaires, literature reviews, and other information-gathering exercises to identify monitoring questions and data needs that include (1) focal resources (including ecological processes) important to each park, (2) agents of change or stressors that are known or suspected to cause changes in the focal resources over time; and (3) some basic key properties and processes of ecosystem health (e.g., weather, soil nutrients). Conceptual models are then developed to help organize and communicate the information compiled during scoping, and to identify where cause-effect is known between some of the stressors and response variables. The scoping and conceptual modeling efforts will result in a list of potential vital signs, which must then be prioritized to determine the network's "short list" of vital signs that will be included in the initial monitoring program.
    Basic approach to identifying and selecting vital signs
    Basic approach to identifying and selecting vital signs for integrated monitoring of park resources (source: Kurt Jenkins, USGS Olympic Field Station).

    The process of prioritizing the list of potential vital signs for a park network will involve a group decision that involves many different parks, individuals, and disciplines. A structured group decision-making process should be used to take all of the information and ideas available, and then produce judgments, manage conflict, and enable consensus. Several approaches to group decision-making are summarized below, and explained in more detail in the following document:

    Group Decision-Making Processes used to Prioritize Vital Signs

    Sampling Design Considerations; Where and When to Sample

    The NPS recognizes the importance of collecting data in a scientifically credible manner so that they can be used to address current and future management issues. All parks and their contractors and cooperators should use certain "good sampling practices" so that data meet the purpose for which they were collected and withstand scrutiny by critics. Sample sizes will almost always be limited by shortages of funding and personnel, and it is critical to be able to make inferences to larger areas from data collected at relatively few sampling locations.

    In February 2000, a panel of statisticians developed guidance for designing a sampling framework for monitoring natural resources in parks. Recommendations of this panel are presented in the following two documents:

    Download Guidance for the Design of Sampling Schemes for Inventory and Monitoring in National Parks (S. Fancy, March 2000)
    Download Examples of Park Sampling Designs (S. Fancy, March 2000)
    Download "Examples Illustrating the Design and Analysis of Monitoring Surveys in National Parks" (P. Geissler, May 2001)

    Download Sample Designs for National Park Monitoring (P. Geissler and T. McDonald, April 2003)

    See also the Summary of a Statistical Workshop at Olympic NP (A. Woodward and K. Jenkins, April 2001)

    A good manual on statistical methods, Statistical Methods for Adaptive Management Studies is available from the British Columbia Ministry of Forests Research Program.

    A summary of key elements of the recommendations for designing a sampling scheme are as follows:
    1. Some sort of probability sample should always be taken to avoid bias. Conceptually, the target population (usually the entire park) is divided into sampling units such that every point in the park is included in a sampling unit, but not in more than one. The sampling design is used to select a probabilistic sample of the sampling units. As a result, statistical estimates of population attributes can be produced with an estimate of their reliability. Probability samples occur when each unit in the target population has a known, non-zero probability of being included in the sample, and always include a random component (such as a systematic sample with a random start). The credibility of data that are not collected using these principles is easily undermined.
    2. Statistical, design based inferences can only be made to areas that have a chance of being included in the sample. If study plots are chosen to be close to roads, design-based inferences can only be made to areas near roads. Since the NPS's mission is to protect resources in the entire park, sampling should be designed so that robust inferences can be made to the entire park and not some easily accessible portion of it. Model based inferences and professional judgement can be used to infer values in portions of a park that had no probability of being included in the sample. However, accuracy of model based inferences and professional judgement is only as good as the model and the decision making process of the individual providing the professional judgement, and models and judgement-based information can often be easily discredited by critics. Areas of the park that are too inaccessible or unsafe to sample can be simply excluded from the program, but then no inference can be made about resources in these areas.
    3. Judgement sampling, using "representative" sites selected by experts, should be avoided. If there is no controversy, judgement sampling sounds good at the beginning, but "representative" sites may come back to haunt you in the future because they are easily discredited by critics and may produce biased, unreliable information.
    4. Panel members supported a general framework of first spreading samples out over the entire park or target population, and then increasing the sampling intensity in areas of special interest. Simple random sampling is not recommended because you may select a sample that is not spatially balanced, and because we are often interested in species or other park resources that occur in limited areas and we want to make sure we include adequate samples in those areas. Samples can be spread out over the area of interest by using some sort of grid or cell design or a tesselation procedure. Within this overall design, areas of special interest such as rare habitats can be sampled with higher frequencies using either stratification or the more general approach of defining the cells corresponding to the areas of interest and varying their selection probabilities (the unequal selection probability approach). In either case, the areas are then sampled disproportionate to their availability so that adequate samples are taken from each. This unequal sampling probability approach accomplishes most of the advantages of stratification, but avoids some of the problems of stratification that are mentioned below. An overall framework based on this design that allows for including site-specific studies and legacy data is presented below.
    5. A design based on stratification of the park by "habitats" derived from vegetation maps is not recommended because stratum boundaries will change over time, and unless you fix the stratum boundaries forever there will be problems in the future with data analysis and incorporating new information into the design. A vegetation map is a model based on remote sensing data and data collected on the ground at a series of plots; the map boundaries will change as the classification models change or as additional ground-truthing data becomes available. Using these units to define strata will limit (and greatly complicate) long-term uses of the data by restricting future park managers' abilities to include new information into the sampling framework.
    6. It is legitimate, and better, to delineate areas of special interest such as riparian or alpine areas based on physical characteristics such as terrain, and use these to judiciously define either strata or areas to sample with higher probability.
    7. Permanent plots that are revisited over time are recommended for monitoring, because the objective is to detect changes over time. Revisiting the same plots removes plot to plot differences from the change estimates, increasing the precision.
    8. An important step in developing a sampling design for a park is determining the sample size needed to significantly reduce the uncertainty of guessing about the status or trend of a resource and consequently reduce the costs of stewardship. Taking too few samples may increase the costs of stewardship and put resources at risk because important changes are missed or detected too late for management to be effective, whereas taking too many samples will waste time and resources. The sample size that is needed to meet a sampling objective is largely a function of the effect size, which is the amount of change in the resource from one point in time to the next that the manager seeks to detect, and the variability of the resource across space and time. For a statistician to be able to estimate the sample size needed for a particular program, the park manager needs to be able to specify how much change they need to be able to detect, and with what certainty, to affect their management strategies and practices or to confront and mitigate threats to the park in legal and political arenas. For planning purposes, sample size calculations in most statistical texts can be used to obtain a rough idea of the magnitude of the sample needed to produce a confidence interval of a specified width for a particular variable. If a statistical comparison is to be made between two samples, a "rule of thumb" minimum sample size is 6 measurements in each sample. It is useful to think about sampling over space when allocating samples.
    9. Be sensitive to spatial integrity of the sample! These data will be used for many purposes, and an initial view of the sample on a map will help to clarify the use and limitations of the sample. When a sample is allocated, it is probably a good idea to display the sample on a GIS to ensure that adequate coverage occurs for areas of interest.
    10. When repeated measurements of the same site are made to determine trend, remember that the precision will increase as the number of years of sampling increases. [The sample size of comparisons is usually the number of plots, which will not increase. However, the precision will increase because the means for each plot become less variable (var=s2/n.)]. There may be considerable intra-year variability in a measure because of small sample sizes, sampling errors and spatial variation, all of which increase needed sample sizes, and yet you may still be able to identify a trend as you increase the number of years of data.
    11. When designing a monitoring program, remember that it is not necessary to visit all of the selected sites every year. Sampling designs exist that allow for increased spatial coverage though "rotating panel" designs, where each site is sampled every five years, for example, but five times as many sites can be sampled because only 1/5 of them are visited each year. Data from a complex rotating panel design with multiple strata can be difficult, so data analysis needs to be considered when the design is put together.
    12. Collocation of samples is recommended to allow comparisons among components. For example, in the same stream segments you might sample water quality, aquatic macroinvertebrates, amphibians, and fish. Another example would be to monitor changes in vegetation, birds, mammals, and certain invertebrates at sites that are close to each other.

    Protocol Development

    REQUIRED CONTENT AND FORMAT OF MONITORING PROTOCOLS

    Any successful long-term monitoring program must survive turnovers in personnel (as people change jobs or retire) and technology. In almost all cases measurements over time will be taken by different people. Several important conclusions follow from these facts: (1) sampling protocols must be fully documented, with great enough detail that different people can take measurements in exactly the same way; (2) protocols must include quality control/quality assurance measures, so that it can be demonstrated that any changes in measurements are actually occurring in nature, and not simply a result of measurements being taken by different people or in slightly different ways; and (3) protocols should not rely on the latest instrumentation or technology that may change in a few years, such that measurements cannot be repeated.

    The NPS I&M Program and the USGS Status and Trends Program have developed guidelines for the content and format of monitoring protocols. These guidelines were formerly posted on this website as a document entitled "Characteristics of a good monitoring protocol". The guidelines are being published in the Wildlife Society Bulletin, and have now been adopted as a program requirement by the NPS monitoring program and by the USGS Status and Trends Program. All monitoring in national parks that uses funding from the NPS vital signs monitoring program MUST develop protocol documents that follow these guidelines.

    Download the Guidelines for long-term monitoring protocols.

    NPS PROTOCOL DATABASE

    The NPS I&M Progam is developing a Protocol Database to catalog and make available sampling protocols that are used or developed in the prototype monitoring parks or that are widely used by other agencies. In addition to being able to get a brief summary and to download an electronic version of the protocol, the vision for the protocol database is that users can also download components of a relational database in MS Access that pertains to a particular protocol. Developers of a protocol can post the protocol document itself, database components following the database template scheme (e.g., table structure, queries, data entry forms, code for error checking, etc.), and also a document that summarizes how they do certain routine statistical analyses and graphing.

    Download the Protocol Database.

    EXAMPLES OF PROTOCOLS USED BY OTHER PROGRAMS AND AGENCIES

    Protocol development requires a research effort. Sampling protocols must be field tested, and experiments must be conducted to determine when and how often a site should be sampled. It has been estimated that the federal government spends $640 million per year to monitor the environment. The EPA, USDA Forest Service, and Natural Resource Conservation Service alone have spent tens of millions of dollars developing and testing sampling protocols. The National Park Service, whenever possible, should take advantage of these efforts by other agencies by using well-tested, standardized sampling protocols developed by other agencies if they meet park objectives. If other agencies are using well-established protocols to sample certain components outside of the park boundaries, it not only makes fiscal and political sense to use them (or at least adapt them to specific park needs), but also allows the park to put it's monitoring data in context by making comparisons with areas outside the park. Many biological data sets require 10 years or more of data before trends can be clearly established. Use of standardized protocols that are in use by others outside the park adds a spatial dimension to the monitoring program that may allow the park to see problems much earlier, and therefore to act much sooner than if only the temporal component is available.

    Information on various sampling protocols being used or developed by the prototype monitoring parks is provided below. I also include information on indicators and protocols included in the USDA Forest Inventory and Analysis (FIA) Program, and particularly methods used in the Phase 3 subset of plots that were formerly known as the Forest Health Monitoring Program. The FIA and FHM programs have developed protocols to sample understory diversity, exotic plant species, down woody debris, and fuel loading that may be particularly interesting to parks. See the following Overview of Forest Monitoring Protocols, with information on how to get further information.

    For Water Quality sampling, the Water Resources Division of NPS is developing guidance for designing and conducting water quality monitoring that is compatible with efforts outside of national parks. The latest water quality sampling guidance can be found above in the Technical Guidance section. See the Recommendations for Core Water Quality Monitoring Parameters - Final report from the freshwater workgroup subcommittee, and the Core Water Quality (Vital Signs) Monitoring Parameters for Marine and Coastal National Parks - .

    The Resources Inventory Branch of the British Columbia Ministry of Environment, Lands and Parks has developed inventory and monitoring methods for birds, mammals, and herptiles, as well as general guidance for sampling vertebrate populations. Most of their Species Inventory Manuals can be viewed or downloaded from their website. Each manual presents standard methods for inventory at three levels of inventory intensity: presence/not detected, relative abundance, and absolute abundance for groups of species with similar inventory requirements. The manual "Species Inventory Fundamentals" includes a discussion of sampling design, sampling techniques, and statistical analyses. A good sampling protocol for terrestrial vegetation was developed in Canada as one of a number of good sampling protocols recommended by the Ecological Monitoring and Assessment Network.

    EPA's EMAP - Surface Waters group has funded development of a set of standardized protocols for sampling various components of lakes, including water quality parameters, fish, benthic invertebrates, and birds. Protocols are described in the 1997 report "Environmental Monitoring and Assessment Program Surface Waters: Field Operations Manual for Lakes", EPA/620/R-97/001. Protocols can be downloaded in .pdf format from their EPA Website. Links to other sites concerning aquatic macroinvertebrates and other aquatic monitoring are found at EPA's Biological Monitoring Resources site.

    Widely-used protocols for monitoring stream fish, benthic invertebrates, and stream habitat as part of the USGS NAWQA program (National Water-Quality Assessment) are found at NAWQA Website.

    Coral Reef Monitoring protocols and assessment methods can be viewed at NOAA's Coral Health and Monitoring Program website.

    DATA MANAGEMENT AND ANALYSIS

    Sound data management practices are the key to having a credible monitoring program that provides useful data to managers. The experience of the prototype monitoring parks is that at least 30% of total funding for a monitoring program should be used for data management and reporting. Only by maintaining consistency in the collection, analysis, and management of long-term datasets can we accurately detect trends in ecosystem conditions. The major objectives of data management are to ensure that data are stored and transferred accurately, secured from loss or damage, and made available to decisionmakers in a timely and understandable manner. Data Management Guidelines are currently being developed for the NPS, but while they are being developed, the draft Data Management Guidelines may be helpful to NPS units as they develop comprehensive data management programs. An example of a data management plan for the Prairie Cluster prototype LTEM Program can be downloaded here. Parks that are developing a relational database in MS Access for their natural resource information may find this document on Converting legacy data to a relational database helpful.

    Information Management Tools

    A priority of the inventory and monitoring effort is to make information more useable for management, research, and education and integrating natural resource information with park operations such as interpretation and maintenance. The following information management tools are being developed to assist parks and networks in making information more readily available to managers, scientists and the public:

    Synthesis is an information management system for efficiently locating, organizing, integrating, and disseminating data and information. Synthesis presents the user with a simple, graphical user interface that functions as a gateway to information that may be stored on local computers, networks, intranets, or the Internet. From this single gateway, a user may view and integrate many types of information including text-based documents, photographic libraries, databases, spreadsheets, presentation graphics, geographic information system (GIS) data, bibliographies, Internet-based information, and decision support systems. All of the databases listed below, including the NPBib, NPSpecies, Dataset Catalog, GIS Theme Manager, and the Natural Resource Database Template, will operate as stand-alone applications or can be accessed through Synthesis.

    The GIS Theme Manager is a GIS application in Arcview that makes natural resource information more available and useful to managers, interpreters, resource specialists, maintenance personnel, and others. The Theme Manager can be used as a standalone application, or can be launched from within Synthesis. It can also be used in conjunction with the NR database template as a means of organizing and displaying integrated natural resource information. The Theme Manager has the full functionality and spatial data analysis capabilities of ArcView for those who routinely use GIS, but can also be used by someone with only a few hours of training to display integrated natural resource information for planning, park operations, and decision-making. The Arcview extension and documentation for this tool can be downloaded from the GIS Theme Manager Website.

    The Natural Resource Database Template is a flexible, relational database in MS Access for storing inventory and vital signs monitoring data (including raw data collected during field studies). This relational Access database can be used as a standalone database or in conjunction with the GIS Theme Manager to enter, store, retrieve, and otherwise manage natural resource information. The template has a core database structure that can be modified and built upon by different parks and networks depending on the components of their inventory and monitoring program and the specific sampling protocols they use. Additional information can be obtained from the Database Template Website.

    NPSpecies is the NPS Biodiversity Database to store, manage and disseminate information on species and subspecific organisms documented in NPS units. It contains current species lists for each park that have been verified by standard quality assurance procedures and a history of evidence that documents each organism in each park. The evidence includes voucher (specimen) records with collection dates and locations from park collections, and museums and heraria around the world; field observation records with dates and locations; species links to reference citations (traditional library material such as survey reports and publications) that are cataloged in NatureBib; species links to data set citations (such as spreadsheets and databases from field surveys) that are cataloged in NatureBib; and access to digital copies of references and data sets stored in the Biodiversity Data Store. The master version of NPSpecies is available online in both a secure, password protected application for NPS use and a publicly accessible application to share non-sensitive information.

    The Dataset Catalog is a tool for keeping an inventory and providing abbreviated metadata or "Metadata light" about a variety of natural resource data sets, from physical files and photographs to digital scientific and spatial data. The one-page input and report forms provide a straightforward way to document all types of resource data that may or may not have met formal metadata standards. As with other NRPC applications, the master version of the Dataset Catalog will be available through a website and will be linked to NPSpecies (the NPSpecies database) and the NatureBib bibliography, and it will also be possible to download a version in MS Access from the website.

    NatureBib is the master database for natural resource bibliographic references that merges a number of previously separate databases such as NRBib, GeoBib, and others. As with NPSpecies, it will be possible to download data from the master web-based version into an MS Access version that can be used locally on computers without an internet connection. The data structure of NatureBib makes it possible to import/export records with ProCite software. The web-based version of NatureBib is linked to other databases such as NPSpecies and the NPS Online Permitting system.

    REPORTING THE RESULTS OF MONITORING

    The broad-based, scientifically sound information obtained through natural resource monitoring has multiple applications for management decision-making, research, education, and promoting public understanding of park resources. The primary audience for the results of vital signs monitoring is park management: provide superintendents, park resource chiefs, and other managers with the data they need to make and defend management decisions and to work with others for the benefit of park resources. However, other key audiences for monitoring results include park planners, interpreters, researchers and other scientific collaborators, the general public, and Congress and OMB. To be most effective, monitoring data must be analyzed, interpreted, and provided at regular intervals to each of these key audiences in a format they can use, which means that the same information needs to be packaged and distributed in several different formats.

    The scientific data we need to better understand how park systems work and to better manage the parks will come from many sources. In addition to new field data collected through the I&M Program, other data to help us assess and keep track of the condition of park resources will come from other park projects and programs, other agencies, and from the general scientific community. To the extent that staffing and funding is available, the vital signs program will collaborate and coordinate with these other data collection and analysis efforts, and will promote the integration and synthesis of data across projects, programs, and disciplines. A summary of the Types of Reports, Purpose, and Intended Audience expected to be generated by the monitoring program are listed here.

    Download an Overview of Reporting the Results of Vital Signs Monitoring

    DOWNLOAD DOCUMENTS RELEVANT TO DESIGNING A PARK MONITORING PROGRAM

    pdf file Download NPS-75  NPS-75 Natural Resource Inventory and Monitoring Guidelines (outdated; currently under revision)

    pdf fileDownload Davis 1997  Davis, G. E. 1997. General ecological monitoring program design, implementation, and applications: a case study from Channel Islands National Park, California In: J. K. Reaser and F. Dallmeier (eds.) Measuring and monitoring biodiversity for conservation science and adaptive management. Smithsonian Institution, Washington, D.C.

    pdf fileDownload Silsbee and Peterson 1991  Silsbee, D. G. and D. L. Peterson. 1991. Designing and implementing comprehensive long-term inventory and monitoring programs for National Park System lands. National Park Service, Natural Resources Report NPS/NRUW/NRR-91/04.

    pdf fileDownload Peterson et al. 1995  Peterson, D. L., D. G. Silsbee, and D. L. Schmoldt. 1995. A planning approach for developing inventory and monitoring programs in national parks. National Park Service, Natural Resources Report NPS/NRUW/NRR-95/16.

    pdf fileDownload Roman and Barrett 1999  Roman, C. T. and N. E. Barrett. 1999. Conceptual framework for the development of long-term monitoring protocols at Cape Cod National Seashore. USGS Patuxent Wildlife Research Center, Coop. National Park Studies Unit, University of Rhode Island.

    pdf fileDownload Noon et al. 1999  Noon et al. 1999. Conceptual basis for designing an effectiveness monitoring program. Chpt. 2 in The strategy and design of the effectiveness monitoring program for the Northwest Forest Plan. USDA Forest Service Gen. Tech. Rept. PNW-GTR-437.

    pdf fileDownload National Research Council 1990  National Research Council 1990. Managing troubled waters: the fole of marine environmental monitoring. National Academy Press, Washington D.C.

    pdf fileDownload McDonald et al. 1998  McDonald, L., T. McDonald, and D. Robertson. 1998. Review of the Denali National Park and Preserve (DENA) long-term ecological monitoring program (LTEM). WEST Tech. Rept. 98-7.

    pdf file Dale, V. H. and S. C. Beyeler. 2001.   Challenges in the development and use of ecological indicators. Ecological Indicators 1:3-10.

    pdf file Gibbs, J. P., H. L. Snell and C. E. Causton. 1999.   Effective monitoring for adaptive wildlife management: lessons from the Galapagos Islands. J Wildl Mgmt 63:1055-1065.

    pdf file Johnson, D. H. 1999.  The insignificance of statistical significance testing. J Wildl Mgmt 63:763-772.

    pdf file Kurtz, J. C., L. E. Jackson and W. S. Fisher. 2001.  Strategies for evaluating indicators based on guidelines from the EPA's Office of Research and Development. Ecol Indicators 1:49-60.
    pdf file Noon, B. R., T. A. Spies, and M. G. Raphael. 1999.   Conceptual basis for designing an effectiveness monitoring program. Chpt. 2 in USDA FS Rpt PNW-GTR-437.

    pdf file Joyce, L. and R. Heitschmidt. 2003.   Indicators for ecological health and diversity on rangelands. Progress report from Sustainable Rangelands Roundtable symposium. See http://sustainablerangelands.cnr.colostate.edu/

    Recommendations for Inventorying and Monitoring Birds in National Parks

    Guidelines for Biological Inventories

    Overview of Biological Inventories effort

    How to Plan for and Hold a Vital Signs Scoping Workshop - The Lake Mead NRA example

    Send Comments to Steven Fancy, National Monitoring Program Leader

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