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At least 55 records · Page 3Linked to original sources
USGS2012

Gap Analysis of Benthic Mapping at Three National Parks: Assateague Island National Seashore, Channel Islands National Park, and Sleeping Bear Dunes National Lakeshore

The National Park Service (NPS) Inventory and Monitoring (I&M) Program initiated a benthic habitat mapping program in ocean and coastal parks in 2008-2009 in alignment with the NPS Ocean Park Stewardship 2007-2008 Action Plan. With more than 80 ocean and Great Lakes parks encompassing approximately 2.5 million acres of submerged territory and approximately 12,000 miles of coastline (Curdts, 2011), this Servicewide Benthic Mapping Program (SBMP) is essential. This report presents an initial gap analysis of three pilot parks under the SBMP: Assateague Island National Seashore (ASIS), Channel Islands National Park (CHIS), and Sleeping Bear Dunes National Lakeshore (SLBE) (fig. 1). The recommended SBMP protocols include servicewide standards (for example, gap analysis, minimum accuracy, final products) as well as standards that can be adapted to fit network and park unit needs (for example, minimum mapping unit, mapping priorities). The SBMP requires the inventory and mapping of critical components of coastal and marine ecosystems: bathymetry, geoforms, surface geology, and biotic cover. In order for a park unit benthic inventory to be considered complete, maps of bathymetry and other key components must be combined into a final report (Moses and others, 2010). By this standard, none of the three pilot parks are mapped (inventoried) to completion with respect to submerged resources. After compiling the existing benthic datasets for these parks, this report has concluded that CHIS, with 49 percent of its submerged area mapped, has the most complete benthic inventory of the three. The ASIS submerged inventory is 41 percent complete, and SLBE is 17.5 percent complete.

Assateague Island National Seashore;Channel Island↗
USGS2013

Phenology monitoring protocol: Northeast Temperate Network

Phenology is critical to many aspects of human life and nearly all ecological relationships and processes. Recent climate change has already led to widespread changes in phenological patterns across the globe, and more change is inevitable. This protocol has been developed to provide standardized methods for monitoring phenology within the National Park Service (NPS) Northeast Temperate Network (NETN), as part of the NPS Inventory and Monitoring Program (I&M). NETN encompasses the Appalachian National Scenic Trail (APPA), Acadia National Park (ACAD), the Boston Harbor Islands National Recreation Area (BOHA), and 10 national historical parks and national historic sites in the northeastern US. This protocol was developed in collaboration with and relies upon the procedures and infrastructure of the USA National Phenology Network (USA-NPN), including Nature’s Notebook , USA-NPN’s online plant and animal phenology observation program (www.nn.usanpn.org). Organized in 2007, USA-NPN is a nation-wide partnership among federal agencies, schools and universities, citizen volunteers, and others to monitor and understand the influence of seasonal cycles on the nation’s biological resources. The overall goal of NETN’s phenology monitoring program is to determine trends in the phenology of key species in order to assist park managers with the detection and mitigation of the effects of climate change on park resources. An additional programmatic goal is to interest and educate park visitors and staff, as well as a cadre of volunteer monitors.

National Park Service Natural Resource Report↗
USGS2014

Summary of preliminary step-trend analysis from the Interagency Whitebark Pine Long-termMonitoring Program—2004-2013

In mixed and dominant stands, whitebark pine ( Pinus albicaulis ) occurs in over two million acres within the six national forests and two national parks that comprise the Greater Yellowstone Ecosystem (GYE). Currently, whitebark pine, an ecologically important species, is impacted by multiple ecological disturbances; white pine blister rust ( Cronartium ribicola ), mountain pine beetle ( Dendroctonus ponderosae ), wildfire, and climate change all pose significant threats to the persistence of whitebark pine populations. Substantial declines in whitebark pine populations have been documented throughout its range. Under the auspices of the Greater Yellowstone Coordinating Committee (GYCC), several agencies began a collaborative, long-term monitoring program to track and document the status of whitebark pine across the GYE. This alliance resulted in the formation of the Greater Yellowstone Whitebark Pine Monitoring Working Group (GYWPMWG), which consists of representatives from the U.S. Forest Service (USFS), National Park Service (NPS), U.S. Geological Survey (USGS), and Montana State University (MSU). This groundbased monitoring program was initiated in 2004 and follows a peer-reviewed protocol (GYWPMWG 2011). The program is led by the Greater Yellowstone Inventory and Monitoring Network (GRYN) of the National Park Service in coordination with multiple agencies. More information about this monitoring effort is available at: http://science. nature.nps.gov/im/units/gryn/monitor/whitebark_pine.cfm. The purpose of this report is to provide a draft summary of the first step-trend analysis for the interagency, long-term monitoring of whitebark pine health to the Interagency Grizzly Bear Study Team (IGBST) as part of a synthesis of the state of whitebark pine in the GYE. Due to the various stages of the analyses and reporting, this is the most efficient way to provide these results to the IGBST.

Natural Resource Data Series↗
USGS2006

Vascular Plant and Vertebrate Inventory of Casa Grande Ruins National Monument

Executive Summary This report summarizes results of the first comprehensive biological inventory of Casa Grande Ruins National Monument (NM) in southern Arizona. Surveys at the monument were part of a larger effort to inventory vascular plants and vertebrates in eight National Park Service units in Arizona and New Mexico. In 2001 and 2002 we surveyed for vascular plants and vertebrates (amphibians, reptiles, birds, and mammals) at Casa Grande Ruins NM to document the presence, and in some cases relative abundance, of species. By using repeatable study designs and standardized field techniques, which included quantified survey effort, we produced inventories that can serve as the basis for a biological monitoring program. Of the National Park Service units in the region, no other has experienced as much recent ecological change as Casa Grande Ruins NM. Once situated in a large and biologically diverse mesquite bosque near the perennially flowing Gila River, the monument is now a patch of sparse desert vegetation surrounded by urban and commercial development that is rapidly replacing agriculture as the dominant land use in the area. Roads, highways, and canals surround the monument. Development, and its associated impacts, has important implications for the plants and animals that live in the monument. The plant species list is small and the distribution and number of non-native plants appears to be increasing. Terrestrial vertebrates are also being impacted by the changing landscape, which is increasing the isolation of these populations from nearby natural areas and thereby reducing the number of species at the monument. These observations are alarming and are based on our review of previous studies, our research in the monument, and our knowledge of the biogeography and ecology of the Sonoran Desert. Together, these data suggest that the monument has lost a significant portion of its historic complement of species and these changes will likely intensify as urbanization continues. Despite isolation of the monument from nearby natural areas, we recorded noteworthy species or observations for all taxonomic groups: * Plants: night-blooming cereus * Amphibians: high abundance of Couch's spadefoot toads * Reptiles: high abundance of long-nosed snakes * Birds: 10 species of diurnal raptors including 4 species of falcons * Mammals: American badger This study is a first step in the process of compiling information about the biological resources of Casa Grande Ruins NM and surrounding areas. We recommend additional inventory and research studies, and we identify aspects of our effort that could be improved upon through application of new techniques or by extending the temporal (and possibly spatial) scope of our work.

Open-File Report↗
USGS2004

Characterization and comparison of phytoplankton in selected lakes of five Great Lakes area national parks

Phytoplankton species have been widely used as indicators of lake conditions, and they may be useful for detecting changes in overall lake condition. In an attempt to inventory and monitor its natural resources, the National Park Service wants to establish a monitoring program for aquatic resources in the Great Lakes Cluster National Parks. This study sought to establish baseline information on the phytoplankton and water chemistry of selected lakes in five national parks in a preliminary effort toward establishing a long-term monitoring program. Phytoplankton and water chemistry samples were collected from ten lakes in five national parks over a two-year period. A total of 176 taxa were identified during the study. Northern lakes generally had higher Shannon-Wiener diversity and clustered together in similarity. Lakes exhibited a south to north gradient of many water chemistry variables, with northern lakes having lower hardness, sulfate, turbidity, and temperature and higher dissolved oxygen. Chloride and sulfate concentrations were the variables that best explained variation among phytoplankton in the ten lakes. A monitoring plan will have to incorporate the differences among lakes, but by coordinating the effort, comparisons within and among parks and other regions will prove useful for determining environmental change.

Aquatic Ecosystem Health & Management↗
USGS2007

Field Guide to the Plant Community Types of Voyageurs National Park

INTRODUCTION The objective of the U.S. Geological Survey-National Park Service Vegetation Mapping Program is to classify, describe, and map vegetation for most of the park units within the National Park Service (NPS). The program was created in response to the NPS Natural Resources Inventory and Monitoring Guidelines issued in 1992. Products for each park include digital files of the vegetation map and field data, keys and descriptions to the plant communities, reports, metadata, map accuracy verification summaries, and aerial photographs. Interagency teams work in each park and, following standardized mapping and field sampling protocols, develop products and vegetation classification standards that document the various vegetation types found in a given park. The use of a standard national vegetation classification system and mapping protocol facilitate effective resource stewardship by ensuring compatibility and widespread use of the information throughout the NPS as well as by other Federal and state agencies. These vegetation classifications and maps and associated information support a wide variety of resource assessment, park management, and planning needs, and provide a structure for framing and answering critical scientific questions about plant communities and their relation to environmental processes across the landscape. This field guide is intended to make the classification accessible to park visitors and researchers at Voyageurs National Park, allowing them to identify any stand of natural vegetation and showing how the classification can be used in conjunction with the vegetation map (Hop and others, 2001).

Techniques and Methods↗
USGS2024

Delineating draft inventory analysis units for National Scenic and Historic Trails inventory, assessment, and monitoring programs

As of 2024, there are 32 National Scenic and Historic Trails (NSHTs) in the system administered by the Bureau of Land Management (BLM), National Park Service, and U.S. Department of Agriculture Forest Service. The BLM administers, manages, and protects 19 of these trails as part of its system of national conservation lands. Various laws, regulations, and policies require that the BLM conduct and maintain an inventory to protect trail-related resources, qualities, values, associated settings, and primary use or uses. There are set procedures for conducting inventory, assessment, and monitoring (IAM) of NSHTs, as outlined in volumes 1 and 2 of BLM Technical Reference 6280-1. One of the first steps in the IAM process is deciding the area along a trail to inventory. However, volumes 1 and 2 of BLM Technical Reference 6280-1 do not specify how the land area to be inventoried should be delineated. The BLM calls these focus areas for IAM efforts “inventory analysis units” (IAUs), which are defined as the geospatial boundary for the location of an inventory along a trail. This report reviews the approach used to delineate the IAUs for an inventory effort and identifies best practices for creating initial IAUs, termed “draft IAUs.” Draft IAUs would provide standardization across multiple management jurisdictions by applying the same parameters for their delineation. These draft IAUs would provide trail managers with an area surrounding NSHTs that would trigger the need for an inventory if a project were proposed within it and are meant to be refined during localized inventory efforts. The best practices herein are for creating draft IAUs using standard parameters for performing a viewshed analysis to identify a proxy of land to include in an initial inventory effort.

New Mexico↗
USGS2003

A Framework for Long-term Ecological Monitoring in Olympic National Park: Prototype for the Coniferous Forest Biome

This report is the result of a five-year collaboration between scientists of the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, Olympic Field Station, and the natural resources staff of Olympic National Park to develop a comprehensive strategy for monitoring natural resources of Olympic National Park. Olympic National Park is the National Park Serviceʼs prototype monitoring park, representing parks in the coniferous forest biome. Under the umbrella of the National Park Serviceʼs prototype parks program, U.S. Geological Survey and Olympic National Park staffs are obligated to: develop strategies and designs for monitoring the long-term health and integrity of national park ecosystems with a significant coniferous forest component. design exportable monitoring protocols that can be used by other parks within the coniferous forest biome (i.e., parks having similar environments), and create a demonstration area and ʻcenter of excellenceʼ for assisting other parks in developing ecological monitoring programs. Olympic National Park is part of the North Coast and Cascades Network, a network of seven Pacific Northwestern park units created recently by the National Park Serviceʼs Inventory and Monitoring Program to extend the monitoring of ʻvital signsʼ of park health to all National Park Service units. It is our intent and hope that the monitoring strategies and conceptual models described here will meet the overall purpose of the prototype parks monitoring program in proving useful not only to Olympic National Park, but also to parks within the North Coast and Cascades Network and elsewhere. Part I contains the conceptual design and sampling framework for the prototype long-term monitoring program in Olympic National Park. In this section, we explore key elements of monitoring design that help to ensure the spatial, ecological, and temporal integration of monitoring program elements and discuss approaches used to design an ecosystem-based monitoring program. Basic monitoring components include ecosystem drivers, (e.g., climate, atmospheric inputs, human pressures), indicators of ecosystem integrity (e.g., biogeochemical indicators), known threats (e.g., impacts of introduced mountain goats), and focal or ʻkeyʼ species (e.g., rare or listed species, Roosevelt elk). Monitoring system drivers and key indicators of ecosystem integrity provide the long-term baseline needed to judge what constitutes ʻunnaturalʼ variation in park resources and provide the earliest possible warning of unacceptable change. Monitoring effects of known threats and the status of focal species will provide information useful to park managers for dealing with current park issues. In Part I we describe the process of identifying potential indicators of ecological condition and present conceptual models of park ecosystems. In addition we report results from several workshops held in conjunction with Olympic National Park aimed at identifying potential indicators of change in the parkʼs ecosystem. First, we describe the responses of Olympic National Park staff to the generic question, “What is the most important resource to monitor in Olympic National Park and why?” followed by the responses from resource and land managers from areas adjoining the park. We also catalogue the responses of various expert groups that we asked to help identify the most appropriate system drivers and indicators of change in the Olympic National Park ecosystems. Results of the workshops provided the justification for selecting basic indicators of ecosystem integrity, effects of current threats to park resources, and focal resources of parks to detect both the currently evident and unforeseeable changes in park resources. We conclude Part I by exploring several generic statistical issues relevant to monitoring natural resources in Olympic National Park. Specifically we discuss trade-offs associated with sampling extensively versus sampling intensively in smaller geographic regions and describe a conceptual framework to guide development of a generic sampling frame for monitoring. We recommend partitioning Olympic National Park into three zones of decreasing accessibility to maximize monitoring efficiency. We present examples of how the generic sampling frame could be used to help ensure spatial integration of individual monitoring projects. Part II of the report is a record of the potential monitoring questions and indicators identified to date in our workshops. The presentation is organized according to the major system drivers, components, and processes identified in the intermediate-level working model of the Olympic National Park ecosystem. For each component of the park system, we develop the need and justification for monitoring, articulate park management issues, and describe key resources and ecosystem functions. We also present a pictorial conceptual model of each ecological subsystem, identify monitoring questions, and list potential indicators for each monitoring question. We conclude each section by identifying linkages of indicators to other ecological subsystems in our general ecosystem model, spatial and temporal contexts for monitoring (where and how often to monitor), and research and development needs. Part II represents the most current detailed listing of potential indicators—the material for subsequent discussions of monitoring priorities and selection of indicators for protocol development. Collectively, the sections of this report contain a comprehensive list of the important monitoring questions and potential indicators as well as recommendations for designing an integrated monitoring program. In Part I, Chapter 6 we provide recommendations on how to proceed with the important next steps in the design process: establishing priorities among the many possible monitoring questions and indicators, and beginning to research and design effective long-term monitoring protocols.

Information and Technology Report↗
USGS2017

National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project. To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation. A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA. Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.

Appalachian National Scenic Trail↗
USGS2013

National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio

The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA. Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA. A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type. A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha. Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent. A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval. The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at <http://science.nature.nps.gov/im/inventory/veg> and <http://www.usgs.gov/core_science_systems/csas/vip/index.html>.

Natural Resource Technical Report↗
USGS2014

Connecting the dots: a collaborative USGS-NPS effort to expand the utility of monitoring data

The Natural Resource Challenge (National Park Service 1999) was a call to action. It constituted a mandate for monitoring based on the twin premises that (1) natural resources in national parks require active management and stewardship if we are to protect them from gradual degradation, and (2) we cannot protect what we do not understand. The intent of the challenge was embodied in its original description: We must expand existing inventory programs and develop efficient ways to monitor the vital signs of natural systems. We must enlist others in the scientific community to help, and also facilitate their inquiry. Managers must have and apply this information to preserve our natural resources. In this article, we report on ongoing collaborative work between the National Park Service (NPS) and the US Geological Survey (USGS) that seeks to add to our scientific understanding of the ecological processes operating behind vital signs monitoring data. The ultimate goal of this work is to provide insights that can facilitate an understanding of the systems and identify potential opportunities for active stewardship by NPS managers (Bennetts et al. 2007; Mitchell et al. 2014). The bulk of the work thus far has involved Acadia and Rocky Mountain national parks, but there are plans for extending the work to additional parks. Our story stats with work designed to consider ways of assessing the status and condition of natural resources and the potential for historical or ongoing influences of human activities. In the 1990s, the concept of "biotic integrity" began to take hold as an aspiration for developing quantitative indices describing how closely the conditions at a site resemble those found at pristine, unimpacted sites. Quantitative methods for developing indices of biotic integrity (IBIs) and elaborations of that idea (e.g., ecological integrity) have received considerable attention and application of these methods to natural resources has become widespread (Karr 1991; Barbour et al. 1999; Stoddard et al. 2008). Despite widespread use, many questions remain about how metrics are combined to form effective indices and about how to interpret both. Scientists and natural resource specialists within NPS and USGS have joined forces to critique the current analysis methods, with the collaboration involving the Rocky Mountain and Northeast Temperate NPS Inventory and Monitoring (I & M) networks, along with others, and USGS scientists from the National Wetlands Research Center and Patuxent Wildlife Research Center. Funding that initiated the project was from a joint-partnership fund managed by the USGS Ecosystems Program for National Park Monitoring research and the work was focused at Acadia National Park and Rocky Mountain National Park. Here we present synopses of two major issues addressed by the group.

The George Wright Forum↗
USGS2016

National Park Service Vegetation Mapping Inventory Program: Natchez Trace Parkway vegetation mapping project report

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Gulf Coast Network, and NPS Natchez Trace Parkway (NATR; also referred to as Parkway) have completed vegetation classification and mapping of NATR for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of NATR and to determine how best to map them by using aerial imagery. Analyses of data from 589 vegetation plots had been used to describe an initial 99 USNVC associations in the Parkway; this classification work was completed prior to beginning this NATR vegetation mapping project. Data were collected during this project from another eight quick plots to support new vegetation types not previously identified at the Parkway. Data from 120 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Furthermore, data from 900 accuracy assessment (AA) sites were collected (of which 894 were used to test accuracy of the vegetation map layer). The collective of all these datasets resulted in affirming 122 USNVC associations at NATR. To map the vegetation and open water of NATR, 63 map classes were developed. including the following: 54 map classes represent natural (including ruderal) vegetation types in the USNVC, 5 map classes represent cultural (agricultural and developed) vegetation types in the USNVC, 3 map classes represent nonvegetation open-water bodies (non-USNVC), and 1 map class represents landscapes that had received tornado damage a few months prior to the time of aerial imagery collection. Features were interpreted from viewing 4-band digital aerial imagery by means of digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems. (The aerial imagery was collected during mid-October 2011 for the northern reach of the Parkway and mid-November 2011 for the southern reach of the Parkway to capture peak leaf-phenology of trees.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in geographic information systems. Polygon units were mapped to either a 0.5 hectare (ha) or 0.25 ha minimum mapping unit, depending on vegetation type or scenario. A geodatabase containing various feature-class layers and tables present the locations of USNVC vegetation types (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial image centers. The feature-class layer and related tables for the vegetation map provide 13,529 polygons of detailed attribute data covering 21,655.5 ha, with an average polygon size of 1.6 ha; the vegetation map coincides closely with the administrative boundary for NATR. Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 12,648 polygons (93.5% of polygons) and cover 18,542.7 ha (85.6%) of the map extent for NATR. The map layer indicates the Parkway to be 70.5% forest and woodland (15,258.7 ha), 0.3% shrubland (63.0 ha), and 14.9% herbaceous cover (3,221.0 ha). Map classes representing USNVC cultural types apply to 678 polygons (5.0% of polygons) and cover 2,413.9 ha (11.1%) of the map extent.

Natural Resource Report↗
USGS2014

Status of whitebarkpine in the Greater Yellowstone Ecosystem: A step-trend analysis comparing 2004-2007 to 2008-2011

Whitebark pine (Pinus albicaulis) is a foundation and keystone species in upper subalpine environments of the northern Rocky Mountains that strongly influences the biodiversity and productivity of high-elevation ecosystems (Tomback et al. 2001, Ellison et al. 2005). Throughout its historic range, whitebark pine has decreased significantly as a major component of high-elevation forests. As a result, it is critical to understand the challenges to whitebark pine—not only at the tree and stand level, but also as these factors influence the distribution of whitebark pine across the Greater Yellowstone Ecosystem (GYE). In 2003, the National Park Service (NPS) Greater Yellowstone Inventory & Monitoring Network identified whitebark pine as one of twelve significant natural resource indicators or vital signs to monitor (Jean et al. 2005, Fancy et al. 2009) and initiated a long-term, collaborative monitoring program. Partners in this effort include the U.S. Geological Survey, U.S. Forest Service, and Montana State University with representatives from each comprising the Greater Yellowstone Whitebark Pine Monitoring Working Group. The objectives of the monitoring program are to assess trends in (1) the proportion of live, whitebark pine trees (>1.4-m tall) infected with white pine blister rust (blister rust); (2) to document blister rust infection severity by the occurrence and location of persisting and new infections; (3) to determine mortality of whitebark pine trees and describe potential factors contributing to the death of trees; and (4) to assess the multiple components of the recruitment of understory whitebark pine into the reproductive population. In this report we summarize the past eight years (2004-2011) of whitebark pine status and trend monitoring in the GYE. Our study area encompasses six national forests (NF), two national parks (NP), as well as state and private lands in portions of Wyoming, Montana, and Idaho; this area is collectively described as the GYE here and in other studies. The sampling design is a probabilistic, twostage cluster design with stands of whitebark pine as the primary units and 10x50 m belt transects as the secondary units. Primary sampling units (stands) were selected randomly from a sample frame of approximately 10,770 mapped pure and mixed whitebark pine stands ≥2.0 hectares in the GYE (Dixon 1997, Landenburger 2012). From 2004 through 2007 (monitoring transect establishment or initial time-step), we established 176 permanent belt transects (secondary sampling units=176) in 150 whitebark pine stands and permanently marked approximately 4,740 individual trees >1.4 m tall to monitor long-term changes in blister rust infection and survival rates. Between 2008 and 2011 (revisit time-step), these same 176 transects were surveyed and again all previously tagged trees were observed for changes in blister rust infection and survival status. Objective 1. Using a combined ratio estimator, we estimated the proportion of live trees infected in the GYE in the initial time-step (2004-2007) to be 0.22 (0.031 SE). Following the completion of all surveys in the revisit time-step (2008-2011), we estimated the proportion of live trees infected with white pine blister rust as 0.23 (0.028 SE; Table 2). We detected no significant change in the proportion of trees infected in the GYE between the two time-steps. Objective 2. We documented blister rust canker locations as occurring in the canopy or bole. We compared changes in canker position between the initial time-step (2004-2007) and the revisit time-step (2008-2011) in order to assess changes in infection severity. This analysis included the 3,795 trees tagged during the initial time-step that were located and documented as alive at the end of the revisit time-step. At the end of the revisit time-step, we found 1,217 trees infected with blister rust. This includes the 287 newly tagged trees in the revisit time step of which 14 had documented infections. Of these 1,217 trees, 780 trees were infected with blister rust in both time steps. Trees with only canopy cankers made up approximately 43% (519 trees) of the total number of trees infected with blister rust at the end of the revisit time-step, while trees with only bole cankers comprised 20% (252 trees), and those with both canopy and bole cankers included 37% (446 trees) of the infected sample. A bole infection is considered to be more consequential than a canopy canker, as it compromises not only the overall longevity of the tree, but its functional capacity for reproductive output as well (Kendall and Arno 1990, Campbell and Antos 2000, McDonald and Hoff 2001, Schwandt and Kegley 2004). In addition to infection location, we also documented infection transition between the canopy and bole. Of the 780 live trees that were infected with blister rust in both time-steps, approximately 31% (242) maintained canopy cankers and 36% (281) retained bole infections at the end of the revisit time-step. Infection transition from canopy to bole occurred in 30% (234) of the revisit time-step trees while 3% (23) transitioned from bole to canopy infections during this period. Objective 3. To determine whitebark pine mortality, we resurveyed all belt transects to reassess the life status of permanently tagged trees >1.4 m tall. We compared the total number of live tagged trees recorded during monitoring transect establishment to the total number of resurveyed dead tagged trees recorded during the revisit time-step and identified all potential mortality-influencing conditions (blister rust, mountain pine beetle, fire and other). By the end of the revisit time-step, we observed a total of 975 dead tagged whitebark pine trees; using a ratio estimator, this represents a loss of approximately 20% (SE=4.35%) of the original live tagged tree population (GYWPMWG 2012). Objective 4. To investigate the proportion of live, reproducing tagged trees, we divided the total number of positively identified cone-bearing trees by the total number of live trees in the tagged tree sample at the end of the revisit time-step. To approximate the average density of recruitment trees per stand, trees ≤1.4 m tall were summed by stand (within the 500 m² transect area) and divided by the total number of stands. Reproducing trees made up approximately 24% (996 trees) of the total live tagged population at the end of the revisit time-step. Differentiating between whitebark pine and limber pine seedlings or saplings is problematic given the absence of cones or cone scars. Therefore, understory summaries as presented in this report may include individuals of both species when they are sympatric in a stand. The average density of small trees ≤1.4 m tall was 53 understory trees per 500 m². Raw counts of these understory individuals ranged from 0-635 small trees per belt transect. In addition, a total of 287 trees were added to the tagged tree population by the end of 2011. These newly tagged trees were individuals that upon subsequent revisits had reached a height of >1.4 m tall and subsequently added to the sample. Throughout the past decade in the GYE, monitoring has helped document shifts in whitebark pine forests; whitebark pine stands have been impacted by insect, pathogen, wildland fire, and other disturbance events. Blister rust infection is ubiquitous throughout the ecosystem and infection proportions are variable across the region. And while we have documented mortality of whitebark pine, we have also recorded considerable recruitment. We provide this first step-trend report as a quantifiable baseline for understanding the state of whitebark pine in the GYE. Many aspects of whitebark pine health are highly variable across the range of its distribution in the GYE. Through sustained implementation of the monitoring program, we will continue efforts to document and quantify whitebark pine forest dynamics as they arise under periodic upsurges in insect, pathogen, fire episodes, and climatic events in the GYE. Since its inception, this monitoring program perseveres as one of the only sustained longterm efforts conducted in the GYE with a singular purpose to track the health and status of this prominent keystone species.

Natural Resource Technical Report↗
USGS2006

Inventory of Amphibians and Reptiles in Southern Colorado Plateau National Parks

In fiscal year 2000, the National Park Service (NPS) initiated a nationwide program to inventory vertebrates andvascular plants within the National Parks, and an inventory plan was developed for the 19 park units in the Southern Colorado Plateau Inventory & Monitoring Network. We surveyed 12 parks in this network for reptiles and amphibians between 2001 and 2003. The overall goals of our herpetofaunal inventories were to document 90% of the species present, identify park-specific species of special concern, and, based on the inventory results, make recommendations for the development of an effective monitoring program. We used the following standardized herpetological methods to complete the inventories: time-area constrained searches, visual encounter ('general') surveys, and nighttime road cruising. We also recorded incidental species sightings and surveyed existing literature and museum specimen databases. We found 50 amphibian and reptile species during fieldwork. These included 1 salamander, 11 anurans, 21 lizards, and 17 snakes. Literature reviews, museum specimen data records, and personal communications with NPS staff added an additional eight species, including one salamander, one turtle, one lizard, and five snakes. It was necessary to use a variety of methods to detect all species in each park. Randomly-generated 1-ha time-area constrained searches and night drives produced the fewest species and individuals of all the methods, while general surveys and randomly-generated 10-ha time-areas constrained searches produced the most. Inventory completeness was likely compromised by a severe drought across the region during our surveys. In most parks we did not come close to the goal of detecting 90% of the expected species present; however, we did document several species range extensions. Effective monitoring programs for herpetofauna on the Colorado Plateau should use a variety of methods to detect species, and focus on taxa-specific methods. Randomly-generated plots must take into account microhabitat and aquatic features to be effective at sampling for herpetofauna.

Open-File Report↗
USGS2006

Field-based evaluation of two herbaceous plant community composition sampling methods for long-term monitoring in Northern Great Plains National Parks

The Northern Great Plains Inventory & Monitoring (I&M) Network (Network) of the National Park Service (NPS) consists of 13 NPS units in North Dakota, South Dakota, Nebraska, and eastern Wyoming. The Network is in the planning phase of a long-term program to monitor the health of park ecosystems. Plant community composition is one of the 'Vital Signs,' or indicators, that will be monitored as part of this program for three main reasons. First, plant community composition is information-rich; a single sampling protocol can provide information on the diversity of native and non-native species, the abundance of individual dominant species, and the abundance of groups of plants. Second, plant community composition is of specific management concern. The abundance and diversity of exotic plants, both absolute and relative to native species, is one of the greatest management concerns in almost all Network parks (Symstad 2004). Finally, plant community composition reflects the effects of a variety of current or anticipated stressors on ecosystem health in the Network parks including invasive exotic plants, large ungulate grazing, lack of fire in a fire-adapted system, chemical exotic plant control, nitrogen deposition, increased atmospheric carbon dioxide concentrations, and climate change. Before the Network begins its Vital Signs monitoring, a detailed plan describing specific protocols used for each of the Vital Signs must go through rigorous development and review. The pilot study on which we report here is one of the components of this protocol development. The goal of the work we report on here was to determine a specific method to use for monitoring plant community composition of the herb layer (< 2 m tall).

Open-File Report↗
USGS2021

National Park Service Vegetation Mapping Inventory Program: Great Smoky Mountains National Park vegetation mapping project

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation communities in national park units throughout the United States. The NPS VMI Program is managed by the NPS Natural Resource Stewardship and Science Inventory and Monitoring Program and provides baseline vegetation information to natural resource managers, researchers, and ecologists. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, and NPS Great Smoky Mountains National Park (GRSM, also referred to as the “Park”) have completed vegetation classification and mapping of GRSM, including the Foothills Parkway, for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types of GRSM and to determine how best to map the vegetation types by using aerial imagery. A vegetation classification developed in 2003 by NatureServe and the NPS served as a foundation to further classify and map the vegetation types of the Park. Data from an additional 10 vegetation plots supported vegetation types either rare or not documented in the 2003 classification. Data from 203 verification sites were collected to test the field key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 972 accuracy assessment (AA) sites were collected (of which 966 were used to test accuracy of the vegetation map layer). This GRSM vegetation mapping project identified 112 vegetation types consisting of 105 association types in the U.S. National Vegetation Classification (USNVC), 2 “park-special” types, 1 “map-special” type, and 4 cultural types in the USNVC. To map the vegetation and land cover of GRSM, 52 map classes were developed. Of these 52 map classes, 46 represent natural (including ruderal) vegetation types, most of which types are recognized in the USNVC. For the remaining 6 of the 52 map classes, 4 represent USNVC cultural types for agricultural and developed areas, and 2 represent non-USNVC types for nonvegetated open water and nonvegetated rock. Features were interpreted from viewing four-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems; digital aerial imagery was collected during September 23–October 30, 2015. The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in a geographic information system. Polygon units were mapped to either a 0.5- or 0.25- hectare (ha) minimum mapping unit, depending on vegetation type. A geodatabase containing several feature-class layers and tables provides the locations and data of USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, AA sites, project boundary extent, and aerial image centers and flight lines. Covering 210,875 ha, the feature-class layer and related tables for the vegetation map layer provide 34,084 polygons of detailed attribute data when special modifiers are not considered (average polygon size of 6.2 ha) and 36,589 polygons of detailed attribute data when special modifiers are considered (average polygon size of 5.8 ha). Each map polygon is assigned a map-class code and name and, when applicable, are linked to USNVC classification tables within the geodatabase. The vegetation map extent includes the administrative boundary for GRSM and the Foothills Parkway. A summary report, generated from the vegetation map layer, concludes that the 46 map classes representing natural (including ruderal) vegetation types apply to 99.2% of polygons (33,797 polygons; average size of 6.2 ha) and cover 98.6% of the Park (207,971.4 ha). Further broken down, map classes representing natural vegetation types indicate that the Park is 97.7% forest and woodland (205,882.5 ha), 0.6% shrubland (1,174.6 ha), and 0.4% herbaceous (914.3 ha). Map classes representing cultural vegetation types apply to 0.8% of polygons (259 polygons; average size of 4.9 ha) and cover 0.6% of the Park (1,277.4 ha). Map classes representing nonvegetation open and flowing water and unvegetated rock apply to 0.08% of polygons (28 polygons; average size of 58.1 ha) and cover 0.8% of the Park (1,625.9 ha). A thematic AA study was completed of map classes representing the natural (including ruderal) vegetation types of the Park. Initial AA results were discussed with NPS staff from the Park. Following input from NPS staff on how to handle map classes that fell below accuracy standards, adjustments were made to the vegetation map layer. Final results indicate an overall accuracy of 80.64% (kappa index of 79.96% for chance agreements) based on data from 966 of the 972 AA sites. Most individual map-class themes exceed the NPS VMI Program standard of 80% with a 90% confidence interval. The GRSM vegetation mapping project delivers many geospatial and vegetation data products, including an in-depth project report discussing methods and results, which includes map classification and map-class descriptions. This suite of products also includes descriptions and a field key to vegetation types; a database of vegetation plots, verification sites, and AA sites; digital images of field sites; field data sheets; digital aerial imagery; hardcopy and digital maps; a geodatabase of vegetation and land cover (map layer), field sites (vegetation plots, verification sites, and AA sites), aerial imagery index, project boundary, and metadata; and a contingency table listing AA results. Geospatial products are projected in the Universal Transverse Mercator, Zone 17 North, by using the North American Datum of 1983. Information on the NPS VMI Program and completed mapping projects are on the internet at https://www.nps.gov/im/vegetation-inventory.htm.

North Carolina, Tennessee↗
USGS2015

National Park Service vegetation inventory program: Mississippi National River and Recreation Area, Minnesota

The Mississippi National River and Recreation Area (MISS) vegetation mapping project is an initiative of the National Park Service (NPS) Vegetation Inventory Program (VIP) to classify and map vegetation types of MISS. (Note: “MISS” is also referred to as “park” throughout this report.) The goals of the project are to adequately describe and map vegetation types of the park and to provide the NPS Natural Resource Inventory and Monitoring (I&M) Program, resource managers, and biological researchers with useful baseline vegetation information. The MISS vegetation mapping project was officially started in spring 2012, with a scoping meeting wherein partners discussed project objectives, goals, and methods. Major collaborators at this meeting included staff from the NPS MISS, the NPS Great Lakes Network (GLKN), NatureServe, and the USGS Upper Midwest Environmental Sciences Center. The Minnesota Department of Natural Resources (DNR) was also in attendance. Common to all NPS VIP projects, the three main components of the MISS vegetation mapping project are as follows: (1) vegetation classification, (2) vegetation mapping, and (3) map accuracy assessment (AA). In this report, each of these fundamental components is discussed in detail. With the completion of the MISS vegetation mapping project, all nine park units within the NPS GLKN have received vegetation classification and mapping products from the NPS and USGS vegetation programs. Voyageurs National Park and Isle Royale National Park were completed during 1996–2001 (as program pilot projects) and another six park units were completed during 2004–11, including the Apostle Islands National Lakeshore, Grand Portage National Monument, Indiana Dunes National Lakeshore, Pictured Rocks National Lakeshore, Saint Croix National Scenic Riverway, and Sleeping Bear Dunes National Lakeshore.

Natural Resource Report↗
USGS2024

Power analysis of water quality of standing water bodies in the Pacific Island Network, 2009–2017

The National Park Service (NPS) Inventory and Monitoring Division (IMD) aims to provide data on park ecosystems' health to guide management decisions. Since 2007, NPS IMD has monitored water quality in marine areas, streams, anchialine pools, wetlands, and lakes in the Pacific Island Network (PACN) national parks. To maintain long-term monitoring program efficiency, protocols are reviewed and revised every 10 years based on trend analyses, including new power analyses for significant sampling regime changes. This report focuses on standing water bodies, evaluating statistical power across different sampling intensities to detect water quality trends and anomalies. It covers 10 areas with a varying number of sample stations. Data from 2009–2017 for nine water quality parameters were examined, and statistical power was assessed by using linear regression and Wilcoxon two-sample tests with 80% power and a Type I error rate of 0.05. Results show that higher sampling effort and larger effect sizes increase the power to detect changes, although power varies by parameter and site due to differences in mean and variance. The analysis results may be used to devise optimal sampling strategies, including balancing the number of sample sites and sampling frequency. Periodic evaluations and adaptive strategies are essential for maintaining statistical power and for the long-term management of the PACN water quality monitoring program, especially in the context of climate change.

Hawaii↗