Transcript Synthesizing and spatially-linking disparate datasets

Synthesizing and Spatially Linking Disparate Datasets
Catherine
1,2
Crosier ,
1Natural
Gregory J.
1
Newman ,
and Thomas J.
Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado 80523-1499
2Fort
Collins Science Center, US Geological Survey, Fort Collins, Colorado 80525
Objectives
Abstract
Extensive surveys to obtain species distribution data are expensive and
time consuming. In addition, many land managers do not know what
species occur within their management boundaries, let alone adjacent to
them. Yet, there is a wealth of data collected by government agencies and
non-government organizations that, when synthesized, maximize the use
of existing data on species locations without incurring large costs. We
obtained datasets on non-native species including species lists, plot data,
transect data, point data, and individual species polygon data that have
been collected using various methods at different spatial scales to meet
different objectives. We then created a geodatabase with ESRI’s ArcGIS
and Microsoft Access 2000 that relates these different datasets spatially
and hierarchically and allows us to use them in concert. When combined
and spatially linked, the data improve the completeness of each individual
dataset. As an example, species reported in a specific area by one dataset
were not reported by a second dataset for the same location. The creation
of a synthesized, spatially linked database allows development of
predictive models and maps for the distribution and abundance of nonnative species. These products can be used by land managers at all levels
to aid in the early detection, management, and control of non-native
species.
Methods
1. Obtain datasets from partners (Table 1).
2. Synthesize pre-existing datasets, including multiple scale (i.e., 1-m2 to
entire county) information on non-native vascular plant species in
Colorado obtained from individuals, organizations, and agencies at all
levels (i.e., federal to local) in a geodatabase (Figure 1).
1. Create three linked geodatabases to synthesize datasets using nested
locations (i.e., plot located in a park located in a county) and
standardized NRCS plant codes (Figure 1). The three geodatabases
are general enough to accommodate plot data; GIS point, line and
polygon data; and species lists for large geographic units.
3. Use on-line GIS technology to disseminate information on non-native
species locations to land managers and the public in a user-friendly and
easily understood manner (Figure 1).
2. Compare datasets at smaller scales to those at larger scales where they
are nested. Datasets include 63 county lists, two National Park unit lists,
493 plots, and 15,666 GIS points, lines, and polygons.
Table 1: Datasets Used, Pending
DATA SOURCE
2. U.S. Geological Survey
Multi-scale plot data
3. U.S. Forest Service
Multi-scale plot data (2 national programs)
4. Graduate students
Multi-scale plot data
5. San Luis Valley GIS Authority
Point, line, and polygon data
6. Larimer County
Point, line, and polygon data (noxious
weeds)
7. Center for the Environmental
Management of Military Lands (CEMML)
Vegetation monitoring transects
8. The Nature Conservancy
Polygon, point, and transect data
Problem: Lack of knowledge
9. Colorado Natural Heritage Program
Polygon and point data
1. Ecological studies often are conducted over short temporal scales in
specific areas.
10. State of Colorado
Quarter quad data for 20 species; DOT
weed GIS data
2. Species occurrence and abundance data do not exist for many public
land units (e.g. Fish and Wildlife Refuges), making it hard to make sound
management decisions.
11. CSU Research Scientists
Point data and control data
12. National Park Service
Park species lists and GIS data
13. U.S. Fish and Wildlife Service
Refuge manager survey results
14. LTER
Plot data
15. Bureau of Land Management
Point, polygon, and control data
Solution: Synthesize smaller studies
• Dataset synthesis indicates biases in individual datasets. For example,
the county dataset is based on herbarium records that are biased
towards specific areas (Figure 2).
Figure 3: Species Added
• Cardaria draba (Hoary cress) was added to six county lists. In addition,
Cardaria draba was not listed in parks and other areas within some
counties listing it, indicating managers should be vigilant for these
species (Figure 4).
DATA TYPE
County species list
Introduction
Results
• Two hundred seventy four new species records (including 35 Colorado
noxious weeds and 99 unique species) were added to 47 of 48 counties
containing nested locations (Figure 3).
1. Biota of North America Program
Keywords: Data synthesis, Data synergy, Spatial linking, Non-native
species, Ecological databases
1,2
Stohlgren
Conclusions and Future Steps
These results indicate that data synergy can be used to improve the quality
of individual datasets. Bias of county datasets can be diminished by
supporting them with data from other sources. Land managers can use
synthesized non-native datasets to set priorities for early detection and
prevention efforts. In addition, the geodatabase can be used to create
predictive spatial models for hotspots of invasion in the state or in a
specific land management unit and to create distribution surfaces for
individual species. These models can then be served on-line to distribute
non-native species information to land mangers at all levels (Figure 5) .
1. Addresses additional and more complex questions
2. Capitalizes on resources already expended
3. Creates probable species lists and distribution maps
Figure 4: Dataset Synergy
Figure 2: Dataset Bias
Figure 5: On-line Interface
Figure 1: Data Management
Acknowledgements
San Luis Valley GIS/GPS