Center For Advanced Spatial Technologies (CAST)

THE ARKANSAS GAP ANALYSIS PROJECT

FINAL REPORT

INTRODUCTION

TABLE OF CONTENTS

1. INTRODUCTION

1.1. The Gap Analysis Concept

1.2. Objectives of the Study

1.3. The Study Area

1.4. General Limitations

1.5. How This Report is Organized

2. LANDCOVER CLASSIFICATION AND MAPPING

3. PREDICTED ANIMAL DISTRIBUTIONS AND SPECIES RICHNESS

4. LAND STEWARDSHIP

5. ANALYSIS BASED ON STEWARDSHIP AND MANAGEMENT STATUS

6. CONCLUSIONS AND MANAGEMENT IMPLICATIONS

7. DATA USE AND AVAILABILITY

8. LITERATURE CITED

9. GLOSSARY

10. GLOSSARY OF ACRONYMS

11. APPENDICES AND MAPS

1.1. The Gap Analysis Concept

The National Gap Analysis Program (GAP) brings together the problem-solving capabilities of federal, state, and private scientists to tackle the difficult issues of landcover mapping, vertebrate habitat characterization, assessment, and biodiversity conservation at the state, regional, and national levels. The program seeks to facilitate cooperative development and use of information.

Much of the following discussion was taken verbatim from Edwards et al. 1995, Scott et al. 1993, and Davis et al. 1995. Gap analysis provides an overview of the distribution and conservation status of several components of biodiversity. It uses the distribution of actual vegetation and terrestrial vertebrates and, when available, invertebrate taxa. Digital map overlays in a geographic information systems (GIS) are used to identify individual species, species-rich areas, and vegetation cover types that are unrepresented or underrepresented in existing management areas. It functions as a preliminary step to the more detailed studies needed to establish actual boundaries for potential biodiversity management areas. These data and results are then made available to institutions, as well as individual land owners and managers, so that they may become more effective stewards through more complete knowledge of the management status of these elements of biodiversity. Gap analysis, by focusing on higher levels of biological organization, is likely to be both cheaper and more likely to succeed than conservation programs focused on single species or populations (Scott et al. 1993).

Biodiversity inventories can be visualized as "filters" designed to capture elements of biodiversity at various levels of organization. The filter concept has been applied by The Nature Conservancy,

which has established Natural Heritage Programs in all 50 states, most of which are now operated by state government agencies. The Nature Conservancy employs a fine filter of rare species inventory and protection and a coarse filter of community inventory and protection (Jenkins 1985, Noss 1987). It is postulated that 85-90% of species can be protected by the coarse filter, without having to inventory or plan reserves for those species individually. A fine filter is then applied to the remaining 15-10% of species to ensure their protection. GAP is a coarse filter method because it can be used to quickly and cheaply assess the other 85-90% of species.

The intuitively appealing idea of conserving most biodiversity by maintaining examples of all natural community types has never been applied, although numerous approaches to the spatial identification of biodiversity have been described (Kirkpatrick 1983, Margules et al. 1988, Pressey and Nicholls 1989, Nicholls and Margules 1993). Furthermore, the spatial scale at which organisms use the environment differs tremendously among species and depends on body size, food habits, mobility, and other factors. Hence, no coarse filter will be a complete assessment of biodiversity protection status and needs. However, species that fall through the pores of the coarse filter, such as narrow endemics and wide-ranging mammals, can be captured by the safety net of the fine filter. Community-level (coarse-filter) protection is a complement to, not a substitute for, protection of individual rare species.

Gap analysis is essentially an expanded coarse-filter approach (Noss 1987) to biodiversity protection. The cover types mapped in gap analysis serve directly as a coarse filter, the goal being to assure adequate representation of all types in biodiversity management areas. Landscapes with great vegetation diversity often are those with high edaphic variety or topographic relief. When elevational diversity is very great, a nearly complete spectrum of vegetation types known from a biological region may occur within a relatively small area. Such areas provide habitat for many species, including those that depend on multiple habitat types to meet life history needs (Diamond 1986, Noss 1987). By using landscape-sized samples (Forman and Godron 1986) as an expanded coarse filter, gap analysis searches for and identifies biological regions where unprotected or underrepresented cover types and vertebrate species occur.

A second filter uses combined species distribution information to identify a set of areas in which all, or nearly all, mapped species are represented. There is a major difference between identifying the richest areas in a region (many of which are likely to be neighbors and share essentially the same list of species ) and identifying areas in which all species are represented. The latter task is most efficiently accomplished by selecting areas whose species lists are most different or complementary. Areas with different environments tend to also have the most different species lists for a variety of taxa. As a result, complementary sets of species for one higher taxon (e.g. mammals) often will also do a good job representing most species of other higher taxa (e.g. trees, butterflies). Species with large home ranges, such as large carnivores, or species with very local distributions may require individual attention. Additional data layers can be used for a more holistic conservation evaluation. These include indicators of stress or risk (e.g. human population growth, road density, rate of habitat fragmentation, distribution of pollutants) and the locations of habitat corridors between wildlands that allow for natural movements of wide-ranging animals and the migration of species in response to climate change. These more detailed analyses were not part of this project, but are areas of research that GAP is pursuing as a national program.

1.2. Objectives of the Study

There are five major objectives of gap analysis: 1) map actual vegetation as closely as possible to the alliance level (Jennings 1993), 2) map the predicted distribution of those animals for which adequate distributional habitats, associations, and mapped habitat variables are available, 3) document the occurrence of vegetation types that are inadequately represented (gaps) in special management areas, 4) document the occurrence of animal species that are inadequately represented (gaps) in special management areas, and 5) make all GAP information available to users in a readily accessible format.

To meet these objectives, it is necessary that GAP be operated at the state level but maintain consistency with national standards. Within the state, participation by a wide variety of cooperators is necessary and desirable to ensure understanding and acceptance of the data and forge relationships that will lead to cooperative conservation planning (Dzur et al. 1996 b.).

1.3. The Study Area

The project study are includes the entire state of Arkansas, which generally can be divided into five physiographic regions: Ozarks, Arkansas River Valley, Ouachita Mountains, Gulf Coastal Plain, and Mississippi Delta (Figure 1.). Smith (1989) discusses the natural setting, climate and weather, and socioeconomic aspects of Arkansas in detail. The smallest state west of the Mississippi River, Arkansas is at the western edge of the Eastern Deciduous Forest biome and the ecotone with the prairie grasslands. The northern part of the state represents the southern third of the Interior Highlands (Braun 1950) and the Ouachita Mountains are one of the two major ranges in the United States to run east to west. The anomalous Crowley's Ridge juts up in the Mississippi

Figure 1. Physiographic regions of Arkansas.

Delta, a primarily loess deposit that the Mississippi River has failed to erode away despite having been on both sides of the ridge. The highest point in the state is the summit of Mount Magazine (2,753 ft.), the highest point between the Appalachians and the Rockies. The lowest points are 54 feet above sea level where the Ouachita River flows into Louisiana and 79 ft. where the Mississippi River leaves the state.

Historically, Arkansas was about 98% forested at the time of settlement and remains about 54% forested today. The Ozarks represent the largest contiguous oak-hickory forest association in the world (Shelford 1963). In Arkansas, the Ozarks are interspersed with small prairies and mixtures of pine and hardwoods. The Ouachitas contain large stands of pines and pines mixed with hardwoods. Bottomland hardwoods have been greatly decreased, but still persist along the Ouachita and Saline Rivers in the Gulf Coastal Plain and along the Arkansas, White, and Mississippi Rivers in the Delta. One of the largest grasslands in Eastern United States was found in the Delta. Known as the Grand Prairie, it and most of the Delta have been converted into agricultural lands.

1.4. General Limitations

Limitations must be recognized so that additional studies can be implemented to supplement gap analysis. The following are general project limitations; specific limitations for the data are described in the sections that describe them:

1. Gap analysis data are derived from remote sensing and modeling to make general assessments about conservation status. Any decision based on the data must be supported by ground-truthing and more detailed analyses, such as field studies.

2. Gap analysis is not a substitute for threatened and endangered species listing and recovery efforts. A primary argument in favor of gap analysis is that it is proactive: it seeks to recognize and manage sites of high biodiversity value for the long-term maintenance of populations of native species and natural ecosystems before individual species and plant communities become critically rare. Thus, it should help to reduce the rate at which species require listing as threatened or endangered. Those species that are already greatly imperiled, however, still require individual efforts to assure their recovery.

3. The static nature of the gap analysis data also limits their utility in conservation risk assessment. Our database provides a snapshot of Arkansas in the early 1990s, in which landcover and land ownership are both very dynamic and where trend data would be especially useful.

4. Gap analysis is not a substitute for a thorough national biological inventory. As a response to rapid habitat loss, gap analysis provides a quick assessment of the distribution of vegetation and associated species before they are lost and provides focus and direction for local, regional, and national efforts to maintain biodiversity. The process of improving knowledge in systematics, taxonomy, and species distributions is lengthy and expensive. That process must be continued and expedited, however, in order to provide the detailed information needed for a comprehensive assessment of our nation's biodiversity. Vegetation and species distribution maps developed for Gap Analysis can be used to make such surveys more cost-effective by stratifying sampling areas according to expected variation in biological attributes.

1.5. How This Report is Organized

The organization of this report follows the general chronology of the project development, beginning with the production of the individual data layers and concluding with analysis of the data. It diverges from standard scientific reporting by embedding results and discussion sections within individual chapters. This was done to allow the individual data products to stand on their own as testable hypotheses and provide data users with a concise and complete report for each data and analysis product.

We begin with an overview, that describes how the current biodiversity condition came to be, followed by landcover mapping, animal distribution prediction, species richness, and land stewardship mapping and categorization. Data development leads to the Analysis section which reports on the status of the elements of biodiversity (natural community alliances and terrestrial vertebrate species) for Arkansas. Finally, we describe the management implications of the analysis results and provide information on how to acquire and use the data.