Bushing, Dr. William W., Janet Takara and Herman Saldaña

Integration of GPS Locational Data in a GIS to Manage Native Plants, and Control Non-Native Invasive Plants, on Santa Catalina Island


The Santa Catalina Island Conservancy is responsible for the ecological management of more than 42,000 acres (17,000+ ha) of high relief landscape. Identifying the ecologically significant factors determining native plant species distributions, and controlling the spread of invasive non-native plants, over such a large area is a difficult task. GIS provides the island-wide perspective necessary to address these important ecological issues.

Recently the Conservancy initiated a long-term program to map native and non-native plant species locations in the field. This data is imported into an established enterprise GIS where the distributions may be visualized and statistically analyzed. Appropriate ecological management strategies for the conservation of native taxa, and the control of invasive non-natives, are determined based in part on this information.

Handheld GPS receivers taken into the field by Conservancy employees and volunteers will be used to record the desired species locations as they are encountered either opportunistically or through systematic surveys. Once integrated with previously collected data, the distribution patterns for individual taxa may be analyzed relative to the topographic and environmental GIS data layers to determine any correlations, and give a better understanding of each taxon's ecological requirements to help the organization formulate its ecological management strategies.


Santa Catalina Island is one of eight Channel Islands located off the southern California coast (see Figure 1). The island is about 34 km long and is oriented in a NW-to-SE direction with a high (450-600 m) central ridge running nearly its entire length. A series of secondary ridges and valleys extend from the main ridge on either side resulting in an extremely rugged topography and a wide range of differing slopes, aspects and topographic shading conditions. Island elevations range from sea level to more than 600 m within a short distance. Combined with differences in underlying geology, soil type, rainfall and other factors, this topographic diversity and the resulting differences in insolation create a wide range of microhabitats for plants.

Location of Santa Catalina Island relative to western North America and southern California

The Santa Catalina Island Conservancy, formed in 1972, owns more than 88% (17,000+ ha) of the island and is responsible for ecologically managing and restoring it. Although the previous owner exhibited a strong commitment to conservation, nearly two centuries of prior human impact have created conditions requiring an active ecological management program as opposed to passive preservation or conservation of the island's resources.

The ecological management and restoration of Catalina is a complex challenge. The most important elements in the Conservancy's current program are the preservation and conservation of its native plants and animals (especially its endemics and rare taxa), the removal of threats to those native species, and the restoration of areas formerly degraded by these threats.

Catalina is home for a number of endemic plants and animals which are found nowhere else in the world. The endemic plants include the Santa Catalina Island ironwood (Lyonothamnus floribundus floribundus), Catalina mahogany (Cerocarpus traskiae), St. Catherine's lace (Eriogonum giganteum var. giganteum), Catalina liveforever (Dudleya hassei), Catalina manzanita (Arctostaphylos catalinae), Catalina bedstraw (Galium catalinense subsp. catalinense), yerba santa (Eriodictyon traskiae) and wild tomato (Solanum wallacei). Other species considered to be endemic, such as Mimulus traskiae have not been seen in many decades and may already be extinct. Programs to preserve and protect the extant species, especially the Catalina mahogany which is one of the rarest trees in the world and a candidate for federal listing as an endangered taxon, are on-going.

Non-native animals such as sheep, goats and pigs were introduced to the island in the 1800's and early 1900's and have had significant impact on Catalina's vegetation and floristics. Programs to control these non-native mammals have been underway for several decades, and have resulted in the reappearance or range expansion of several plants formerly thought to be extirpated or rare on the island. The effects of non-native herbivores on native vegetation, especially on islands which are "closed" systems, are well-documented (see separate list of references).

Over the last decade, a less obvious ecological impact due to non-native species has surfaced as a concern (see separate list of references). This is the ecological effect of invasive non-native plants, or "wildland weeds," on native species and ecosystems. When introduced to an area outside their normal range, whether accidentally as incidentals or intentionally for landscaping or agricultural use, these plants may outcompete native plants or invade disturbed sites. For example, on Catalina the introduced Dyer's greenwold (Genista linifolia) and fennel (Foeniculum vulgare) have proven to be highly invasive (see linked page on wildland weeds), displacing native plants such as the endemic St Catherine's lace (Eriogonum giganteum var. giganteum). The Conservancy has authored a management plan for the control of wildland weeds (Fone 1997) on its property and is actively implementing this plan. The spatial relationships between non-native plant populations, and any correlations with environmental variables, across this large landscape must be evaluated to determine the dynamics of infections, and to identify appropriate control strategies.

Part of the Conservancy's program to preserve its native taxa and manage its wildland weeds problem involves the use of a geographic information system (GIS). Due to the islands large size, its ecological complexity, and the time it takes for its ecological systems to recover, the GIS provides an excellent mechanism to study these issues over long time periods and "large" scales. To properly manage native species, and control non-native ones, requires that the taxa in question be accurately mapped, and the distributions analyzed relative to the environmental complexity, to properly define and prioritize strategies for native plant conservation and weed control. This GIS has already been used successfully to study the distribution and persistence of giant kelp (Macrocystis pyrifera) in the marine environment around the island (Bushing 1994, 1995, 1996a, 1996b, 1997).

This paper will discuss the initial work involved in two GIS mapping and analysis projects underway at the Santa Catalina Island Conservancy. The first is an effort to survey and map all known groves of the endemic Catalina ironwood (Lyonothamnus floribundus floribundus) on the island. Once mapped and entered into the Conservancy GIS, the distributions can be analyzed for observed patterns. This effort is part of a program known as the Ironwood Project initiated by former president A. Douglas Propst in the 1980's. A related subspecies, the Santa Cruz ironwood (Lyonothamnus floribundus asplenifolius) was the subject of an early study using a GIS on Santa Cruz Island (Junak 1987).

The second project is the mapping activity and analysis related to our wildland weeds control effort. Although weed abatement has been underway on the island for several decades, the GIS and Global Positioning System (GPS) have just recently been employed in this project. This paper will discuss the early stages of these programs, and present some of the preliminary analyses from them.


Creation of GIS Data Layers and Analysis

The GIS data layers used in this study included mapped distributions of Catalina ironwoods and various wildland weed species (see discussion below) and environmental variables including terrestrial elevation, aspect, slope, geologic rock types, soils and solar insolation. The creation of the topographic (elevation, aspect and slope) and solar insolation data layers has been described previously (Bushing 1995, 1996a). These data layers were created at 20-m resolution. The geology and soils layers were provided by Southern California Edison in ArcInfo format.

The solar insolation model used the TOPQUAD module developed by Dozier (1980, 1989) for integration into the IPW (Image Processing Workbench) software toolkit (Frew 1990). The TOPQUAD algorithm and its derivatives have been used extensively for modeling light environments in regions of high relief (see Dozier 1980, Dozier et al. 1981, Frew and Dozier 1986, Davis and Dozier 1990, Davis and Goetz 1990, Dozier and Frew 1990, Dubayah et al. 1990, Dubayah and Rich 1996).

Many of the data layers were stored both as polygon and raster data to facilitate the analyses in this study. Visualization of the data was accomplished by displaying the desired GIS layers (e.g., ironwood distribution and soils) simultaneously. For numeric analyses of the ironwood distributions, binary raster masks representing ironwood locations from the mapped data were created by defining buffers around the point data corresponding to the expected accuracy of the location, and rasterizing the buffer polygons. These masks were used to extract data from the other raster GIS layers (elevation, aspect, slope, solar insolation) using standard overlay techniques. This method is described more completely by Bushing (1994, 1995, 1996a, 1996b).

This data was analyzed within the GIS and imported into Foxpro databases with each record representing one point (cell) on the 20-m resolution distribution mask. Each data layer (eg, aspect) was imported as a separate field in the database so each record represented a single geographic location (raster cell) incorporating the associated data in multiple fields. Several programs were written in the xBASE computer language to further analyze the data on a cell-by-cell basis.

Over the lifetime of the Conservancy GIS, data has been migrated from IDRISI into Atlas*GIS and is in the process of being converted to ArcInfo format for final deployment under Esri's ARC/View 3.0. Although the results presented here were achieved through the methods referenced above, ARC/View's Spatial Analyst extension will be used in the future to simplify these analyses.

GPS Error Determination

Handheld GPS receivers are becoming increasingly popular tools in field biology. However, due to orbital errors, atmospheric effects, the geometry of the satellite configuration used to acquire a positional fix, the satellite signal strength, multipath signals, and the imposition of Selective Availability by the Department of Defense (DoD), civilian grade GPS receivers are known to produce significant error in positional readings (see discussions on the Internet in the BYTE Magazine, by Racal Corporation, and by Paul Ross). Although the civilian grade GPS receivers are capable of 10-20 m accuracy when the DoD imposed Selective Availability is not active, errors experienced in the field are reported to range from about 50 to 100 m.

To determine the effectiveness of the Conservancy's handheld GPS receivers, each was taken into the field to a known location and readings were taken on that site for varying periods of time. The initial readings in 1994, using a Magellan NAV 5000D on the Brush Peak USGS benchmark, produced an error circle of about 85 m, which is consistent with tests from other studies, but the data was discarded shortly after the test. When new GPS receivers (Garmin 38 and Garmin 45XL) were recently acquired, they were likewise taken to known locations and tested.

The Garmin 45XL was used to take readings from a post outside a house on Vieudelou Avenue in the City of Avalon, Santa Catalina Island, on January 21, 1997. Readings from this fixed position were taken over a period of nearly 12 hours at intervals varying from every 5 seconds to every minute during daylight and night. This location provided limited visibility of the entire horizon due to potential blockage by nearby hills and the building itself.

When the Garmin 38 was acquired, both Garmin units were taken to the Lower Windsock USGS benchmark. Coincident readings using both units were taken on March 1, 1997, by two individuals every 10 seconds for a period of 10 minutes (61 readings total). This benchmark, located on the island's channel side, experiences partial blockage of the horizon to the west due to the island's main ridge. However, this blockage is at relatively low angles of elevation from the true horizon, and probably did not limit optimal satellite geometry when available.

A second set of simultaneous readings using both the Garmin 38 and 45XL was taken near the peak of Mt. Black Jack, the second highest peak on the island (elevation 612 m), on March 22, 1997. This location has a nearly unobstructed view of the entire horizon. For this test a total of only twenty (20) readings were taken at an interval of 15 seconds with each instrument using two individuals.

The positional fixes from each test were stored as waypoints in the Garmin units, downloaded to a computer, and converted to GIS format using an xBase program written by the principal author. These data were then displayed against GIS background layers to get a visual feel for the error. Approximate error circles were described by defining the radius from the known fixed location to the most distant reading.

Ironwood Mapping Project

In 1975, the Santa Catalina Island Company (SCICo) which formerly owned most of the island, produced a map of the locations of the major vegetation types and plant species on the island including the Catalina ironwood. Then in 1976, as part of a project in anticipation of the transfer of most of the SCICo lands to the Conservancy and a recreational easement agreement with Los Angeles County, the Center for Natural Areas (CNA) was contracted to prepare a comprehensive management study of the island. This study also included a map (Center for Natural Areas 1976a, 1976b) showing the locations of ironwood groves on the island. Then, during the 1980's, Peter Henriksen, an intern with the Wrigley Memorial and Botanical Garden (WMBG) (now a department within the Santa Catalina Island Conservancy), field mapped the location of most (but not all) of our ironwood groves and gathered associated data about these groves.

In 1994 the three hardcopy ironwood distribution maps created by the SCICo (1975), the CNA (1976) and Peter Henriksen were manually digitized and integrated into the Conservancy's GIS. The intent was to assess the relative accuracy of the mapped ironwood grove positions in each of the three surveys, and to generate a comprehensive map of all known groves by reconciling the locations in each survey.

Even when all three maps were combined, it was evident that a number of known ironwood groves were not identified on any of the maps. These unmapped groves would have to be added by additional field mapping. It was decided to use GPS receivers to conduct this field mapping program. Concurrent with the initial field mapping, the GPS receivers were used to take positional readings at known locations such as USGS benchmarks on the island (see above). This was done to test the accuracy of these test readings, and use the accuracy determined to comparing field mapped locations using the GPS with the earlier hardcopy maps.

In 1994, botanists from Rancho Santa Ana Botanic Garden (RSABG) in Claremont, CA, collected ironwood leaf samples on Santa Catalina Island for genetic studies. The Conservancy's native plant horticulturist Janet Takara accompanied them in the field, and collected sample locational data for those groves using the handheld Magellan NAV5000D GPS receiver. This data consisted of single readings on the site of each ironwood grove sampled by RSABG.

The Conservancy's native plant horticulturist
taking a reading with the Garmin 45XL
handheld GPS receiver in the field.

© 1997 Dr. Bill Bushing

The field-mapped GPS locations were imported into the GIS and compared with those from the hardcopy maps in the vicinity of Long Point on the island. Later, additional GPS receivers (Garmin 38's and 45XL's) were acquired for these projects due to their lighter weight in the field, lower cost, the ability to identify positions in UTM coordinates and to download the data directly into a computer for conversion to GIS format.

Wildland Weeds Mapping Project

The Conservancy has had an on-going wildland weeds control program for several decades. Infestations of selected weed species such as Dyer's greenwold (Genista linifolia), fennel (Foeniculum vulgare) and Russian thistle (Salsola pestifera) were mapped by Conservancy weed specialist Herman Saldaña on USGS 1:24,000 quad maps. In addition, field notes were maintained regarding the status of these infestations and any control efforts undertaken. These original wildland weeds maps were manually digitized as vector polygons using a Calcomp Drawing Board II digitizing tablet.

Inexpensive handheld GPS receivers now allow all Conservancy employees in the field (biologists, rangers, facilities management) to acquire locational information on newly identified infestations. This data will be incorporated into the GIS by downloading it from the GPS via cable. Initially it was hoped the weed locations could be identified using named waypoints and the traditional eight character codes determined by the first four letters of the genus and species names (e.g., Russian thistle or Salsola pestifera would be recorded as SALSPEST). Unfortunately, named waypoints in the Garmin handheld GPS receivers are limited to only six characters (see below) requiring a different naming convention. In addition, each waypoint must have a unique name, preventing the use of the same identifiers for different infestations of the same species.

Garmin 38 GPS receiver display illustrating the
six character limit to named waypoints making it
difficult to use them as fields for designating
the name of weed species.

© 1997 Dr. Bill Bushing


GPS Error Results

From earlier data collecting using the Conservancy's Magellan NAV500D GPS receiver at a known location (the Brush Peak USGS benchmark), location readings were known to fall within a circle of about 85 m radius from the actual location. This error is consistent with results from other studies and vendor claims for signals obtained under DoD's Selective Availability. The results of the GPS readings taken in the field at various locations on Santa Catalina Island are presented on this linked page.

Ironwood Mapping Project

The Ironwood Project mapping effort involved two activities. The first was an attempt to reconcile the various ironwood maps prepared by the SCICo, CNA and Peter Henriksen with the field-derived GPS locational data. The results of the mapping reconciliation effort for ironwood groves in the vicinity of Long Point are presented on this linked page.

The second aspect of the ironwood mapping project involved the analysis of the observed distributions using environmental data from other GIS layers. Some of the preliminary results from this analysis are presented on this linked page.

Wildland Weeds Mapping Project

The Conservancy's wildland weeds mapping effort is currently undergoing a transition from its traditional hardcopy map base to a digital data collection effort. The original hardcopy maps have been digitized, and field personnel are being trained to use the GPS receivers to collect new data digitally that can be directly imported into our GIS and added to the manually digitized distribution data. To see some of the preliminary results of our wildland weeds mapping effort, see the page linked here.


Ironwood Mapping Project

The existing error in single positional readings from a civilian-grade handheld GPS receiver are currently sufficient for recording the locations of obvious plant species such as ironwood groves. These trees are of sufficient stature and visibility to be obvious despite the 50-85 m error involved. However, better accuracy is required if these distributions are to be analyzed using the GIS and conventional overlay methods (including Spatial Analyst).

An accurate and comprehensive map of all the ironwood groves will require returning to the field with a more precise GPS receiver (survey or research grade), the use of differential GPS (see paper by Robert Holloway of Racal Survey Australia Ltd. utilizing the U.S. Coast Guard beacon signals, post- processing the field data, or a employing a protocol involving averaging of several positional fixes for each grove (see Paul Ross' paper) to determine exactly which groves are represented and where they are located. It is expected that the Department of Defense's "Selective Availability" will be removed from the GPS system by the year 2000, allowing the Conservancy to acquire reasonably accurate (~10-20 m) positional fixes even with our current equipment.

Because ironwood groves are all of the same species, it is not necessary to use unique character-based identifiers in the collection of locational data. The known groves have been assigned numbers, and their locations can readily be stored as waypoints using these grove identifiers.

The initial analysis of ironwood distributions relative to environmental variables suggests that GIS is a useful tool in determining correlations with such variables, and thereby characterizing the environmental requirements for the species. This analysis will proceed further once we have acquired an accurate reconciled map of all known ironwood grove locations on the island. Such information, linked with genetic studies underway by Rancho Santa Ana Botanic Garden and Duff (1994), seasonal phenologies, observed seedlings and other data should provide valuable information to manage this unique endemic species and ensure its continued survival.

Wildland Weeds Mapping Project

Wildland weeds include a number of different species, and multiple locations for the same species. The limitations imposed with inexpensive handheld GPS units like the Garmin 38 or 45XL make it difficult to store reasonable information on these locations without accompanying field notes. The six character waypoint name restriction, and the inability to use the same identifier for separate locations, makes it hard to store easily identifiable information for a variety of species and locations in the field using such equipment.

An additional limitation of the current equipment is the achieved accuracy of 50 to 85 m under field conditions on Santa Catalina Island. Although such accuracy would be sufficient to relocate large infestations, or plant species that are obvious from a distance, not all mapped locations meet these criteria. In addition, follow-up visits to infestation sites where controls have been initiated may require greater accuracy to ensure proper location and assessment of the success of weed control efforts. This suggests the need for a GPS receiver like the Trimble Pro XR with greater accuracy, and the ability to incorporate a data dictionary allowing recording in the field of species identifiers, infestation size and other attribute information.

The Conservancy's original weed mapping effort was largely conducted from roadside observations, as is apparent in the original weed maps. The road system, with its frequently disturbed roadside areas, offers an excellent mechanism for the dispersal and establishment of non-native weedy species. However, to get an accurate picture of the overall distribution patterns will require distributional data collection from areas off-road. Light-weight handheld GPS receivers offer a good means for hikers to obtain such data and integrate with the current distributions.

Despite these limitations, GPS receivers and GIS offer good potential for the mapping, visualization and analysis of wildland weed infestations across Catalina's expansive landscape. It will be important to incorporate background information on each weed species' life history (e.g., ecological requirements, dispersal mechanisms, pollinators) to evaluate the observed distribution patterns and analyses relative to environmental variables. The preliminary results are encouraging, and once appropriate equipment is acquired, this project should yield valuable information for the management of this ecological problem.


The author would like to thank the following: the Santa Catalina Island Conservancy, the Offield Family Foundation, and the University of California Santa Barbara Map & Imagery Lab for their support in the development of the early data layers in this GIS; Environmental Systems Research Institute for their kind donation of software to the Conservancy; Southern California Edison, especially GIS Specialist Albert Lin, for the underlying geology and soils GIS data layers; donors to the Conservancy's Ironwood Project; Mark Hoefs, Director and Curator of the Wrigley Memorial & Botanical Garden; Conservancy employee Frank Starkey who assisted in data collection, and Director of Ecological Restoration Dr. Allan Fone who did much of the wildland weeds control planning; and all the wonderful Conservancy volunteers, led by Director of Volunteer Services Annette LaFleuer who contribute to our success in so many areas.


  1. Axelrod, D. I., 1973. History of the Mediterranean ecosystem in California. In di Castri, F. and H. A. Mooney (eds.), Mediterranean type ecosystems: origin and structure. pp. 225-277. Springer-Verlag. New York.
  2. Banwar, S. C., 1966. Morphological and anatomical studies on the genus Lyonothamnus. Ph.D. Dissertation. Univ. Calif. Berkeley. 299 pp.
  3. Barrett, S. C. H. and J. R. Kohn, 1991. Genetic and evolutionary consequences of small population size in plants: implications for conservation. In Falk, D. A. and K. E. Holsinger (eds.), Genetics and Conservation of Rare Plants, pp. 3-30. Oxford University Press. New York
  4. Brandegee, T. S., 1888. Flora of the Santa Barbara Islands. Prof. of the Calif. Acad. of Sci., 2nd Ser., Vol. 1:201-233.
  5. Brandegee, T. S., 1890. The plants of Santa Catalina Island. Zoe 1:107-115.
  6. Bushing, W. W., 1994. The influence of topography on the distribution of giant kelp (Macrocystis pyrifera) beds around Santa Catalina Island using a geographic information system. In W. L. Halvorson and G. J. Maender (eds.), The Fourth California Islands Symposium: Update on the Status of Resources. Santa Barbara Museum of Natural History Santa Barbara, CA). pp. 70-82.
  7. Bushing, W. W., 1995. Identifying regions of persistent giant kelp (Macrocystis pyrifera) around Santa Catalina Island for designation as marine reserves. Proc. 15th Esri User Conference, Palm Springs, CA, May 21-26, 1995.
  8. Bushing, W. W., 1996a. The influence of island topography on the nearshore light regime and the distribution of giant kelp around Santa Catalina Island. Proc. 16th Esri User Conference, Palm Springs, CA, May 19-24, 1996.
  9. Bushing, W. W. 1996b. The Use of Satellite Remote Sensing and a Geographic Information System (GIS) to Characterize Regions of Persistent Giant Kelp (Macrocystis pyrifera) Around Santa Catalina Island for Designation as Marine Reserves. Unpublished Ph.D. dissertation. University of California, Santa Barbara. 719 pp.
  10. Bushing, W. W., 1997. GIS-based gap analysis of an existing marine reserve network around Santa Catalina Island. International Journal of Marine Geodesy 20(2-3):205-234.
  11. Center for Natural Areas, 1976a. Santa Catalina Island Conservation and Recreation Plan, Phase I. Third Progress Report. Inventory and Issue Identification of Geology, Physiography and Soils for Santa Catalina Island. Unpublished report.
  12. Center for Natural Areas, 1976b. Appendix E. Excerpts from the Resource Management Plan: E-1, The Resources; E-2, Past Management Practices; E-3, The State of the Catalina Environment: Historical and Future. Santa Catalina Island Conservation and Recreation Plan. Unpublished report.
  13. Davis. F. W. and J. Dozier, 1990. Information analysis of a spatial database for ecological land classification. Photogr. Engr. and Remote Sensing 56(5):605-613.
  14. Davis, F. W. and S. Goetz, 1990. Modeling vegetation pattern using digital terrain data. Landscape ecology 4(1):69-80.
  15. Dozier, J. 1980. A clear-sky spectral solar radiation model for snow-covered mountainous terrain. Water Resources Research 16(4):709-718.
  16. Dozier, J., 1989. On-line computer documentation for the contributed TOPQUAD module in the IPW (Image Processing Workbench) dated July 6, 1989.
  17. Dozier, J., J. Bruno and P. Downey, 1981. A faster solution to the horizon problem. Computers & Geosciences 7:145- 151.
  18. Dozier, J. and J. Frew, 1990. Rapid calculation of terrain parameters for radiation modeling from digital elevation data. IEEE Trans. on Geoscience and Remote Sensing 28(5):963-969.
  19. Dubayah, R. and P. M. Rich, 1996. GIS-based solar radiation modeling. In Goodchild, M. F., L. T. Steyaert, B. O. Parks, C. Johnston, D. Maidment, M. Crane and S. Glendinning (eds.). GIS and Environmental Modeling: Progress and Research Issues. Proc. 2nd Intl. Conference/Workshop on Integrating Geographic Information Systems and Environmental Modeling. Sept. 26-30, 1993. Breckenridge CO. Natl. Center for Geographic Information and Analysis. GIS World Books (Fort Collins, CO), pp. 129-134.
  20. Dubayah, R., J. Dozier and F. W. Davis, 1990. Topographic distribution of clear-sky radiation over the Konza Prairie, Kansas. Water Resources Research 26(4):679-690.
  21. Duff, M., 1994. Population Structure and Isozymic Diversity in Natural Populations of the Paleoendemic Tree Lyonothamnus floribundus (Rosaceae). Unpublished M.S. thesis, University of Colorado. 98 pp.
  22. Fone, A., 1997. Management Plan for the Control and Eradication of Wildland Weeds. Unpublished document, March 17, 1997, draft. Santa Catalina Island Conservancy. 33 pp.
  23. Frew, J. E., 1990. The Image Processing Workbench. Ph.D. Dissertation. Dept. of Geography, University of California at Santa Barbara. 305 pp.
  24. Frew, J. and J. Dozier 1986. The Image Processing Workbench- portable software for remote sensing instruction and research. Proceedings of the 1986 International Geoscience and Remote Sensing Symposium, European Space Agency, Paris, pp. 271-276.
  25. Gray, A., 1985. Contributions to the botany of North America. III. New genera of Arizona, California, and their Mexican borders, and two additional species of Asclepiadaceae. Proc. Amer. Acad. Arts & Sci. 20:290-296.
  26. Hall, H. M., 1910. Studies in ornamental trees and shrubs. Univ. Calif. Publ. Bot. 4:1-74.
  27. Hickman, J. C. (ed.), 1993. The Jepson Manual: Higher Plants of California. University of California Press. Berkeley, CA.
  28. Jepson, W. L., 1936. A Manual of Flowering Plants of California. University of California Press. Berkeley, CA.
  29. Juliano, J. B., 1931. Floral morphology of Lyonothamnus floribundus. Bot Gaz. 91:426-440.
  30. Junak, S. A., 1987. Environmental Factors Correlated with the Distribution of Island Ironwood (Lyonothamnus floribundus subsp. asplenifolius) on Santa Cruz Island, California. Unpublished M.A. Thesis, University of California at Santa Barbara. 132 pp.
  31. Millspaugh, C. F. and L. W. Nuttall, 1923. Flora of Santa Catalina Island. Field Museum of Natural History Publ. 212. 413 pp.
  32. Minnich, R., 1980. Vegetation of Santa Cruz and Santa Catalina Islands. In Power, D. M. (ed.), The California Islands: Proceedings of a Multidisciplinary Symposium, pp. 123-137. Santa Barbara Museum of Natural History, Santa Barbara, CA.
  33. Raven, P. H., 1963. A flora of San Clemente Island, California. Aliso 5:289-347.
  34. Raven, P. H. and D. I. Axelrod, 1978. Origin and relationships of the California flora. Univ. Calif. Publ. Bot. 72:1-134.
  35. Saunders, C. F., 1926. Trees and shrubs of California gardens. R. M. McBride & Co. New York. 323 pp.
  36. Thorne, R. F., 1967. A flora of Santa Catalina Island, California. Aliso 6:1-77.
  37. Wolfe, J., 1964. Miocene floras from Fingerrock Wash, southwestern Nevada. U. S. Geol. Surv. Prof. Paper 454-N. 36 pp.


Dr. William W. Bushing
Vice President- SEER (Science, Education and Ecological Restoration)

Janet Takara
Director of the James H. Ackerman Native Plant Nursery
Ecological Restoration Department

Herman Saldaña
Bison and Weeds Management
Ecological Restoration Department

Santa Catalina Island Conservancy
125 Claressa Avenue
P. O. Box 2739
Avalon, CA 90704
Telephone: (310) 510-2595 ext. 105
FAX: (310) 510-2594
E-mail: seer@catalinas.net