Geographic information systems have become increasingly useful tools in many natural resource disciplines, including plant ecology. The ability to track vegetation change through time and to make predictions about future vegetation change are just two of the many possible uses of GIS. On this page I cite examples of some interesting uses of GIS within plant ecology, including examples of research involving the analysis and prediction of vegetation change. Useful GIS and mapping web links are also included.
Annotated References (Publications)
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Vegetation change along a transition from open water to swamp forest was studied in the Netherlands. The researchers used remote sensing data and a GIS to evaluate the plant communities along this riparian gradient, and found a strong correlation between the distribution of community types and changes in local land management practices.
Canopy gaps in New Forest, Hampshire, UK were analyzed using imagery from a Compact Airborne Spectrographic Imager (CASI) to produce a vegetation cover map for 5 types of deciduous woodlands. The researchers used a GIS to evaluate data from the five woodland types, and to determine the usefulness of GIS in ecological studies of woodlands.
The researchers developed a probabilistic vegetation model to simulate the geographical distribution of 71 forest community types in Switzerland. The model was developed by linking empirical data with a GIS, and creating new maps on the basis of 12 environmental variables. The researchers found that similarity between these maps and maps produced from field methods ranged from 50% to 80%.
The researchers used a GIS to optimize planting site selection for Big Sagebrush (Artemisia tridentata) at the Hanford site in south-central Washington, and to reduce time required in the field to identify suitable planting sites. Several site criteria were assembled in separate layers, which were overlain to determine suitable planting sites.
This study took place in northern England in a variety of plant community types. A hierarchical, predictive matrix model consisting of four ecological levels (landscape, land cover type, community, species) was produced. A GIS was used to make predictions about plant species distribution based upon landscape classifications.
The authors devised a method of detailed vegetation mapping for use on undulating terrain where the combination of vegetation communities, topography, and other factors makes it difficult to locate a position on typical maps. The merged location and vegetation data set for individual points were imported into a GIS to map point vegetation data accurately. Delaunay triangulation was used to produce a final vegetation map.
The advantages and consequences of using GIS-based spatial information in comparison to a 1-D heathland (Calluna vulgaris-Deschampsia flexuosa) competition model are examined. The authors use a heathland case study to validate the GIS model and to show how atmospheric N deposition may cause patterns in heathland vegetation.
Pre-fire and post-fire maps were created for the Huron National Forest in northern Michigan using Landsat TM data. A raster-based GIS was used to compare the maps and produce a map of vegetation change. The GIS was also used to classify the burned area by degrees of burn intensity. Using spatial analysis, the researchers found that severity of burn was correlated with forest community type.
A useful reference text that explains in detail the use of GIS in ecology. Contains chapters on topographic operations, spatial interpolation, remote sensing and other topics. Emphasis is given to problems and techniques unique to ecology, including specific references to plant ecology.
A GIS was used to evaluate whether plant species changes in Alnus glutinosa-dominated peat fens in Germany resulted from decreasing groundwater tables and nitrogen stores. With the aid of GIS and spatial analysis, the author found a significant relationship between the decrease in groundwater level and declining cover of Carex acutiformis as well as peat acidification.
The researchers performed an ecological risk assessment for the adaptation of different forest sites in Switzerland to a changing climate. The study consisted of a spatially explicit forest community model that generated estimates of the potential natural vegetation for the entire forest area of the then-current climate (1996) and altered climate regimes.
The authors used digital processing techniques to scan and analyze aerial photographs showing encroachment of trees into grasslands, and used GIS modeling to relate tree invasion patterns to topographic orientation, changes in settlement patterns, and periods of favorable climatic conditions.
Several examples of applications of GIS technology in a landscape ecology and spatial analysis approach to the problem of deforestation and biodiversity conservation are presented. The authors review their work with GIS in the analysis of land-cover and land-use change, estimation of deforestation rates and rates of forest fragmentation, change in distribution of biodiversity as a result of land use change, and other examples.
The authors tackle three issues in this paper. First, they discuss historical trends in vegetation mapping concepts with an emphasis on improving the use of GIS in studying vegetation dynamics. Second, they compare the usefulness of satellite data in studying riparian vegetation to that of aerial photos. Third, they discuss the use of GIS in riparian ecosystems as a way to moderate the subjectivity of conceptual statements and to validate ecological theories.
An index identifying the most probable locations of three medicinal plants in the Amazonian rain forest was developed. A GIS was used to calculate the index from digital maps, data from aerial photographs, and data from Landsat TM satellite images. The researchers also conducted ground-truthing surveys for index verification.
The impacts of disturbance on the landscape structure of three vegetation zones were evaluated with remote sensing data and a GIS. The researchers derived a community-level vegetation map from Landsat TM data, which was used to measure species richness, biomass, physiography, and certain patch characteristics. The authors examined which parameters were most influential in making ecological distinctions between the three vegetation zones.
To test whether indices of habitat pattern estimate habitat connectivity and correlate with predictions of dispersal success, Schumaker examined correlations between nine common indices of habitat pattern and the results of a simulated dispersal process, using GIS data on the distribution of old-growth forest in the Pacific Northwest, USA.
A GIS was used to aid in management of land protected for wildlife resources. The authors used an ecological land classification system that incorporated information on plant communities, physiography, geology, soils, and topography of the areas protected for wildlife.
A GIS was used to locate potential habitats for Isotria medeoloides (the rarest orchid in North America, north of Florida) in New Hampshire and Maine. The researchers evaluated characteristics at sites where the species occurred, digitized site locations, and produced predictive GIS overlay models.
A spatial analysis of forest cover for an area in Wisconsin was performed for three time periods: pre-European settlement (1860s), post-settlement (1931), and 1989. GIS was used to analyze land area occupied by different forest types at different dates, temporal transitions between dates and their driving processes, and successional changes in vegetation.
Annotated References (Web Links)
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The researchers are integrating GPS-collected data with an enterprise GIS to aid in identification the ecologically significant factors determining native plant species distributions, and controlling the spread of invasive non-native plants on Santa Catalina Island. The GIS aids in management decisions about the conservation of native taxa, and the control of invasive non-natives.
Researchers combined a vegetation cover map divided into broad categories (derived from satellite imagery) and a geology map (also divided into broad categories) in a GIS to determine the extent and distribution of the remaining primary vegetation in Madagascar. The resulting map was classified into vegetation types by the underlying geology. Conservation priorities were identified by using the final map.
The researchers collected several data layers in a GIS, including habitat attributes of individual endangered Andean species, to track land use change. This was a pilot study to assess the effectiveness of GIS and remote sensing techniques for monitoring the degradation of forests in mountainous regions of the Neotropics.
The researchers are producing regional, fine-scale vegetation maps for USFS land in S. California. The digital maps are being produced by combining satellite imagery and ecological gradient models in a GIS. The maps will be used for land management decision-making.
The ecological portion of this study involves predicting changes in carbon stores within these forest regions. The researchers are combining remotely sensed data (including potential vegetation and maximum potential leaf area) with biogeoclimatic data in a GIS to create predictive models.
Myers conducted a multi-scale analysis of vegetation data. Vegetation data from remote sensing and other sources was analyzed in a GIS with information on land use and vegetation change to determine the spread of alien species across East Maui in the past 40 years.
The researchers used a DEM, scanned IR aerial photos, and field sampling data in a GIS to distinguish plant communities and their distribution in relation to micro-environmental conditions near a glacier front in Svalbard. Probability models for occurrence of community types were produced.
van Horssen is combining non-spatial statistics (logistic regression) with a GIS for use in landscape ecological modeling of a wetland area in The Netherlands. His model can calculate responses for 102 plant species in marsh ecosystems to spatially variable environmental conditions.
Useful GIS & Mapping Links
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Mapping and Other Links