Landscape Gap Analysis
Background and Justification:
Few USDI land units have distribution maps for exotic plant species, while all of them lack detailed information on the ecology, biogeography and extent of most of the exotic plant species on their lands. Furthermore, data from individual management units are not comparable, so regional exotic plant distribution assessments are difficult, and predictive capabilities for future exotic plant establishment are limited or nonexistent. Since a species by species approach to conservation is too costly, a multi-scale, ecosystem approach is necessary to understand and evaluate the threat of exotic plant species to native plant diversity, wildlife populations, and ecosystem structure and function. Over the past four years, we have developed multi-scale vegetation sampling methods, remote sensing and spatial analysis techniques, and predictive modeling capabilities to rapidly assess native and exotic plant diversity at local, landscape, and regional scales (Stohlgren et al. 1997a, b, c, and 1998).
This project provides a model opportunity to link multiple studies of the ecology and control of exotic plant species. Data collected using the modified-Whittaker multi-scale vegetation sampling design (Stohlgren et al. 1995) can be used to assess the current status of exotic and native plant diversity as well as changes in plant composition over time (species and abundance). Perhaps more important, because data are collected in a standardized manner, they can be used to examine patterns of exotic and native plant species at multiple scales from local to regional, and they become part of a much larger sampling effort (from the Rocky Mountains east to the Mississippi). This extensive database from multiple, on-going research projects will allow the rapid development of predictive models of weed invasion. This research is based on Landscape-scale Gap Analysis (Stohlgren et al. 1997c), which is described below.
The above objectives will be achieved by maintaining all information in a GIS and other databases that are readily accessible to resource managers and other researchers. Data analysis will be a team effort. Individual and team efforts will result in site-specific and regional-scale publications and products for resource management and outreach.(1) Synthesize existing information on the weeds in the Central Region.
(2) Rapidly assess the diversity of native and exotic vascular plant species in habitats susceptible to invasion on USDI lands in the Central Region.
(3) Begin to evaluate the effects of edaphic characteristics, water level manipulation, grazing, fire, and other management actions on the spread of exotics.
(4) Develop predictive models of invasibility that can be linked to remotely sensed data.
(5) Develop a long-term monitoring plan for selected exotic species and invasible habitats.
(1) Rapid assessment of invaded areas and susceptible habitats (e.g., riparian areas, burned areas, heavily grazed sites, invasible soil/geology types) in many USDI units throughout the Central Region using standardized, multi-scale techniques (Stohlgren et al. 1995, 1997a,b,c, and 1998).(2) Link all sampling efforts to remotely sensed data (e.g. Landsat TM, aerial photos) and a GIS (Stohlgren 1998a, b, and c).Modified-Whittaker plots (cover, frequency, height and species richness of native and exotic plants; Stohlgren et al. 1998)
Soil sampling (texture, total N, total C; Stohlgren et al. 1998)
GIS data (UTM location to derive slope, aspect and elevation)
(3) Develop predictive models of invasion/invasibility (spatial and multiple-regression models; Stohlgren et al. 1998).
(4) Develop a conceptual, cooperative long-term monitoring plan for weeds in the Central Region (Stohlgren 1998b,c).
Landscape-scale Gap Analysis: A Complementary Geographic Approach for Land Managers
Gap Analysis (Scott et al. 1993) is a method to identify gaps in representation of biological diversity in protected (and less protected) areas. Typically applied to large areas (states and regions), the strengths of Gap Analysis are: (1) consolidating diverse data sets using geographic information systems (GIS); (2) standardizing habitat and land use classification systems for the area of study; and (3) developing predictive models based on habitat affinities for each species. Scott et al. (1993) admit that Gap Analysis is a course-filter approach to conservation evaluation. They recognize several limitations including large minimum mapping units (typically 100 ha to 1 km2) where small habitat patches are often missed, failure to distinguish between most seral stages, and failure to detect gradual ecotones and other important landscape features (e.g., small wetlands and riparian zones). In short, since most U.S. Department of Interior (USDI) land management units are small, large-scale Gap Analysis must be complemented with a down-scaled approach and systematic resource inventories at finer spatial resolution to be useful to land managers (our customers).
We developed and tested several field and geographic information
system (GIS) techniques at a scale useful to land managers: Landscape-scale
Gap Analysis. We focused on customer-identified management issues in Rocky
Mountain National Park, Colorado. We are addressing strategic concerns
common to most USDI land managers of semi-protected islands including development,
urbanization, invasive species, and fragmented habitats. Our products include:
(1) new, standardized field techniques for measuring biodiversity (using
plant diversity as an indicator); (2) refined techniques to down-scale
and consolidate diverse data sets from several land management agencies
(local, private, and regional sources) using a GIS; (3) field validation
for habitat and land use classification systems including seral stage,
and small, important habitats (wetlands, riparian zones, migratory corridors);
(4) development and testing of generalized predictive models for conservation
strategies (using native plant diversity and elk- and moose-habitat protection
as examples); and (5) development of a long-term monitoring program to
evaluate the status and trends of selected biological resources. These
methods can be applied widely to most USDI land units and will be an essential
linkage to large-scale inventory and monitoring programs (Gap Analysis,
Environmental Protection Agency's Environmental Monitoring and Assessment
Program (EMAP), etc.).
Dr. Thomas J. Stohlgren (MESC, 970/491-1980) serves as the lead contact and as co-principal investigator on measuring biodiversity, sampling strategies, and statistical design for long-term monitoring. He will also be responsible for collecting, summarizing and distributing quarterly and annual reports. However, the "team approach" is employed throughout this program. All decisions related to budget, work priorities, and routine roles and responsibilities will be team decisions.
Dr. James K. Detling (CSU, 970/491-5393) serves as co-principal investigator with Stohlgren on measuring biodiversity, sampling strategies, and statistical design for long-term monitoring.
Geneva Chong is an Ecologist (MESC, 970/491-5835) with a background in landscape and field ecology and will share responsibility for developing and implementing vegetation biodiversity sampling. She will ensure that communication is maintained with Partner agencies so that common needs are met, existing data are assessed and new data are distributed.
Seasonal Botanists are employed during the spring and summer to conduct
field surveys of vascular plant species richness. They have extensive experience
in field plant identification, herbaria use, and multi-scale sampling methods.
Kalkhan, M.A., R.M. Reich, and T.J. Stohlgren. 1998 Assessing the Accuracy of Landsat Thematic Mapper Classification Using Double Sampling. International Journal of Remote Sensing (In press).
Kalkhan, M.A. and T.J. Stohlgren. 1998. Linking multiphase, multiscale, and spatial cross correlation to investigate biodiversity pattern in Rocky Mountain National Park, Colorado, USA. Paper presented at the Third International Symposium of Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, May 20-22, 1998, Quebec City, Quebec, Canada.
Scott, M.J., F. Davis, B. Cusuti, R. Noss, B. Butterfield, C. Groves, H. Anderson, S. Caicco, F. D?Erchia, T.C. Edwards, J. Ulliman, and R.G. Wright. 1993. GAP Analysis: A Geographic Approach to Protection of Biological Diversity. Wildlife Monographs 123:1-41.
Stohlgren, T.J., M.B. Falkner, and L. D. Schell. 1995. A modified-Whittaker nested vegetation sampling method. Vegetatio 117:113-121.
Stohlgren, T.J., G.W. Chong, M.A. Kalkhan, and L.D. Schell. 1997a. Multi-scale sampling of plant diversity: effects of the minimum mapping unit. Ecological Applications 7:1064-1074.
Stohlgren, T.J., G.W. Chong, M.A. Kalkhan, and L.D. Schell. 1997b. Rapid assessment of plant diversity patterns: a methodology for landscapes. Environmental Monitoring and Assessment 48:24-43.
Stohlgren, T.J., M.B. Coughenour, G.W. Chong, D. Binkley, and M.A. Kalkhan. 1997c. Landscape analysis of plant diversity. Landscape Ecology 12:155-170.
Stohlgren, T.J., D. Binkley, G.W. Chong, M.A. Kalkhan, L.D. Schell, K.A. Bull, Y. Otsuki, G. Newman, M. Bashkin, and Y. Son. 1998. Invasion of hot spots of native plant diversity by exotic plant species. Ecology or Ecological Applications dependent on length (In press).
Stohlgren, T.J. 1998a. Landscape-scale rapid assessments prior to long-term monitoring. Book Chapter for the Smithsonian Institution. (In Review).
Stohlgren, T.J. 1998b. Scale-dependency in studies of plant diversity. Integrative Biology: Issues, News, and Reviews (In Review).
Stohlgren, T.J. 1998c. Data Acquisition for Ecological Assessments. Invited Book Chapter, "Ecological Assessments." Patrick Bougeron, Editor, Springer-Verlag (In Review).
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updated 12 September 2000