Wildland Fire in Ecosystems Effects of Fire on Fauna

General Technical Report RMRS-GTR-42-volume 1
January 2000


Smith, Jane Kapler, ed. 2000. Wildland fire in ecosystems: effects of fire on fauna. Gen. Tech. Rep. RMRS-GTR-42-vol. 1. Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 83 p.

Fires affect animals mainly through effects on their habitat. Fires often cause short-term increases in wildlife foods that contribute to increases in populations of some animals. These increases are moderated by the animals’ ability to thrive in the altered, often simplified, structure of the postfire environment. The extent of fire effects on animal communities generally depends on the extent of change in habitat structure and species composition caused by fire. Stand-replacement fires usually cause greater changes in the faunal communities of forests than in those of grasslands. Within forests, stand-replacement fires usually alter the animal community more dramatically than understory fires. Animal species are adapted to survive the pattern of fire frequency, season, size, severity, and uniformity that characterized their habitat in presettlement times. When fire frequency increases or decreases substantially or fire severity changes from presettlement patterns, habitat for many animal species declines.

Keywords: fire effects, fire management, fire regime, habitat, succession, wildlife


Jane Kapler Smith, Rocky Mountain Research Station, U.S. Department of Agriculture, Forest Service, Missoula, MT 59807.


L. Jack Lyon, Research Biologist (Emeritus) and Project Leader for the Northern Rockies Forest Wildlife Habitat Research Work Unit, Intermountain (now Rocky Mountain) Research Station, U.S. Department of Agriculture, Forest Service, Missoula, MT 59807.

Mark H. Huff, Ecologist, Pacific Northwest Research Station, U.S. Department of Agriculture, Forest Service, Portland, OR 97208.

Robert G. Hooper, Research Wildlife Biologist, Southern Research Station, U.S. Department of Agriculture, Forest Service, Charleston, SC 29414.

Edmund S. Telfer, Scientist (Emeritus), Canadian Wildlife Service, Edmonton, Alberta, Canada T6B 2X3.

David Scott Schreiner, Silvicultural Forester (retired), Los Padres National Forest, U.S. Department of Agriculture, Forest Service, Goleta, CA 93117.

Jane Kapler Smith, Ecologist, Fire Effects Research Work Unit, Rocky Mountain Research Station, U.S. Department of Agriculture, Forest Service, Missoula, MT 59807.


Cover photo—Male black-backed woodpecker on fire-killed lodgepole pine. Photo by Milo Burcham.


In 1978, a national workshop on fire effects in Denver, Colorado, provided the impetus for the “Effects of Wildland Fire on Ecosystems” series. Recognizing that knowledge of fire was needed for land management planning, state-of-the-knowledge reviews were produced that became known as the “Rainbow Series.” The series consisted of six publications, each with a different colored cover, describing the effects of fire on soil, water, air, flora, fauna, and fuels.

The Rainbow Series proved popular in providing fire effects information for professionals, students, and others. Printed supplies eventually ran out, but knowledge of fire effects continued to grow. To meet the continuing demand for summaries of fire effects knowledge, the interagency National Wildfire Coordinating Group asked Forest Service research leaders to update and revise the series. To fulfill this request, a meeting for organizing the revision was held January 4-6, 1993, in Scottsdale, Arizona. The series name was then changed to “The Rainbow Series.” The five-volume series covers air, soil and water, fauna, flora and fuels, and cultural resources.

The Rainbow Series emphasizes principles and processes rather than serving as a summary of all that is known. The five volumes, taken together, provide a wealth of information and examples to advance understanding of basic concepts regarding fire effects in the United States and Canada. As conceptual background, they provide technical support to fire and resource managers for carrying out interdisciplinary planning, which is essential to managing wildlands in an ecosystem context. Planners and managers will find the series helpful in many aspects of ecosystem-based management, but they will also need to seek out and synthesize more detailed information to resolve specific management questions.

– The Authors
January 2000


The Rainbow Series was completed under the sponsorship of the Joint Fire Sciences Program, a cooperative fire science effort of the U.S. Department of Agriculture, Forest Service and the U.S. Department of the Interior, Bureau of Indian Affairs, Bureau of Land Management, Fish and Wildlife Service, and National Park Service. We thank Marcia Patton-Mallory and Louise Kingsbury for persistence and support.

The authors are grateful for reviews of the manuscript from James K. Brown, Luc C. Duchesne, R. Todd Engstrom, Bill Leenhouts, Kevin C. Ryan, and Neil Sugihara; the reviews were insightful and helpful. Reviews of special topics were provided by David R. Breininger, John A. Crawford, Steve Corn, and Kevin R. Russell; their help strengthened many sections of the manuscript. We are thankful to Nancy McMurray for editing; Dennis Simmerman for assistance with graphics; Bob Altman for literature reviews of special topics; Loren Anderson, Steve Arno, Milo Burcham, Robert Carr, Chris Clampitt, Betty Cotrille, Kerry Foresman, Jeff Henry, Catherine Papp Herms, Robert Hooper, Dick Hutto, Bob Keane, Larry Landers, Melanie Miller, Jim Peaco, Dean Pearson, Rick McIntyre, Dale Wade, and Vita Wright for providing photographs or helping us locate them.





The cover landscape photo and the picture of the two people  sampling were taken by Daniel Salzer. Both photos were  taken at The Nature Conservancy’s Katharine Ordway Sycan  Marsh Preserve. The individuals shown sampling in the small  photo are Rob Lindsay and Linda Poole Rexroat, both are  TNC employees. The inset flower photo was taken by Linda M. Hardie, and shows grass-widows (Sisyrinchium douglasii),  at the Nature Conservany’s Tom McCall Preserve at Rowena Crest.



Caryl L. Elzinga Ph.D.
Alderspring Ecological Consulting P.O. Box 64
Tendoy, ID 83468

Daniel W. Salzer
Coordinator of Research and Monitoring
The Nature Conservancy of Oregon
821 S.E. 14th Avenue
Portland, OR 97214

John W. Willoughby
State Botanist
Bureau of Land Management
California State Office
2135 Butano Drive
Sacramento, CA 95825

This technical reference represents a team effort by the three authors. The order of authors is alphabetical and does not represent the level of contribution.

Though this document was produced through an interagency effort, the following BLM numbers have been assigned for tracking and administrative purposes:

BLM Technical Reference 1730-1



The production of this document would not have been possible without the help of many individuals. Phil Dittberner of the Bureau of Land Management’s National Applied Resource Sciences Center (NARSC) coordinated the effort for BLM. Ken Berg, former BLM National Botanist, provided support and funding for the project.

The content of many chapters in this Technical Reference has benefited from the review of lecture outlines included in “Vegetation Monitoring in a Management Context,” a week-long  monitoring workshop offered jointly by The Nature Conservancy and the U.S. Forest Service.

The authors would also like to acknowledge those persons who reviewed the document and provided valuable comments, including Jim Alegria of the BLM Oregon State Office; Paul  Sawyer of the BLM Arizona State Office; Rita Beard, Andrew Kratz, Will Moir, and David  Wheeler of the Forest Service; Peggy Olwell of the National Park Service; and Gary White of Colorado State University.

We’d like to thank Sherry Smith of Indexing Services for the many hours she donated to this project in developing the index to this TR.

We extend a special thank you to Janine Koselak (Visual Information Specialist) of NARSC for doing a masterful job in layout, design, and production of the final document.


This technical reference applies to monitoring situations involving a single plant species, such as  an indicator species, key species, or weed. It was originally developed for monitoring special status plants, which have some recognized status at the Federal, State, or agency level because of  their rarity or vulnerability. Most examples and discussions in this technical reference focus on  these special status species, but the methods described are also applicable to any single-species  monitoring and even some community monitoring situations. We thus hope wildlife biologists,  range conservationists, botanists, and ecologists will all find this technical reference helpful.

Monitoring is not a new activity for land management agencies, but there is a renewed interest  and a new national emphasis on improving the quality of monitoring. Monitoring designed and  executed effectively is a powerful tool for better management of resources. Good monitoring,  while initially expensive to implement, is eventually costffective because management problems can be detected at an early stage, when solutions may yet be relatively inexpensive. Good monitoring can demonstrate that management is effective and successful, can silence critics, and can encourage the widespread adoption of an effective management technique.

Often, however, the results from monitoring are inconclusive and fail to provide the information needed to evaluate the success of management. Inconclusive or ambiguous monitoring results are  expensive, both in terms of the resources wasted on the monitoring project and the potential  costs of incorrect action. These costs are often difficult to measure because they are exacted  from the environment in the form of environmental damage, or from industry in the form of  unnecessary controls. Reduced public confidence and litigation expenses are additional hidden costs of poor monitoring.

Many monitoring projects suffer one of five unfortunate fates: (1) they are never completely implemented; (2) the data are collected but not analyzed; (3) the data are analyzed but results are inconclusive; (4) the data are analyzed and are interesting, but are not presented to decision makers; (5) the data are analyzed and presented, but are not used for decision-making because of internal or external factors (see Appendix 1 for some typical scenarios). The problem is rarely the collection of data. Agency personnel are often avid collectors of field data because it is one of the most enjoyable parts of their jobs. Data collection, however, is a small part of successful monitoring.

Because of the difficulty and importance of effective monitoring, agencies developed standard monitoring approaches in the 1960s through 1980s. While these techniques effectively met the challenges of that time, they are inadequate now for several reasons:

  • The resources and management effects of interest today are more variable and complex. It is difficult for standard designs to keep pace with the rapid changes in issues. Monitoring data from standard techniques are sometimes inconclusive because the studies are not specifically designed for the issue in question.
  • Many standard techniques do not address issues of statistical precision and power during design; thus, standard monitoring techniques that involve sampling may provide estimates that are too imprecise for confident management decisions.
  • Commodity and environmental groups have become more sophisticated in resource measurement and are increasingly skeptical of data from standard agency techniques.
  • Funding reductions are restricting resources available for monitoring projects. Concurrently, agencies are being required to more clearly demonstrate through monitoring that funds are being used to effectively manage public lands. This situation requires the design of efficient monitoring projects that provide data specific to the current issues.

The challenges of successful monitoring involve efficient and specific design, and a commitment to implementation of the monitoring project, from data collection to reporting and using results.  We have designed this technical reference with these challenges in mind. Our approach differs radically from the development of standard techniques for field offices to apply. We instead provide technical guidance that assists field personnel in thinking through the many decisions that they must make to specifically design monitoring projects for the site, resources, and issues. We base this approach on the belief that local resource managers and specialists understand their issues and their resources best and, therefore, are best able to design monitoring to meet their specific needs. With this technical reference, local personnel can design much of the monitoring done at the local level, and recognize when they need additional specialized skills for a successful project.

We encourage you to treat this technical reference not as a step-by-step guide on how to implement a monitoring study, but as a collection of pieces that you need to choose among and put together for your particular situation and species. We have organized this technical reference to follow a logical progression of planning and objective setting, designing the methodology, taking the measurements in the field, analyzing and presenting the data, and making the necessary management responses. Many of these steps, however, occur simultaneously, or provide feedback to others. Decisions made at each step of the monitoring process can affect the whole project, and those made at later stages sometimes require the reassessment of previous decisions. A listing and short content description of each chapter should make it clear that those chapters we have placed in the latter part of the reference are also important in the conceptual stage if the monitoring is to be efficient and effective:

Chapter 1.     Introduction—Describes the role of monitoring in adaptive management. Contrasts monitoring with other data-collection activities, such as inventory and long-term ecological studies.

Chapter 2.     Monitoring Overview—Provides a step-by-step overview of the entire monitoring process, and references chapters where information on each step can be found in more detail. Flow charts are included to illustrate feedback loops and interrelationships among the steps.

Chapter 3.     Setting Priorities and Selecting Scale—Presents criteria and techniques for setting priorities among species or populations and choosing the most appropriate scale and intensity for monitoring.

Chapter 4.     Management Objectives—Illustrates the foundational nature of management objectives and describes their components, types, and development.

Chapter 5.     Basic Principles of Sampling—Describes basic terms and concepts relevant to sampling using simple examples. This chapter provides background information critical to understanding material presented in Chapters 6, 7, and 11.

Chapter 6.     Sampling Objectives—Describes objectives that complement management objectives whenever the monitoring includes sampling procedures. A sampling objective sets a specific goal for the level of precision or acceptable error rates associated with the sampling process.

Chapter 7.     Sampling Design—Describes how to make the six basic decisions that must be made in designing a sample-based monitoring study: (1) What is the population of  interest? (2) What is an appropriate sampling unit? (3) What is an appropriate sampling unit size and shape? (4) How should sampling units be positioned? (5) Should sampling units be permanent or temporary? (6) How many sampling units should be sampled?

Chapter 8.     Field Techniques for Measuring Vegetation—Discusses selecting an appropriate vegetation attribute to measure when monitoring (e.g., cover, density, frequency, biomass, etc.) in terms of the biology and morphology of the species, and the practical limitations involved in each type of measurement. Field techniques for measuring each vegetation attribute and advice on field techniques and tools are provided.

Chapter 9.     Data Management—Covers different ways of recording monitoring data in the field and describes means for entering and managing field monitoring data sets with computers.

Chapter 10. Communication and Monitoring Plans—Encourages the use of monitoring plans to solicit involvement in the development of a monitoring project, and to document the accepted monitoring protocol. Describes parties whose support may be critical for a successful monitoring project.

Chapter 11. Statistical Analysis—Describes the methods used to analyze monitoring data collected using sampling procedures, the use of graphs to examine data prior to analysis and to display the results of analysis, and the interpretation of monitoring data following analysis.

Chapter 12. Demography—Describes techniques for demographic analysis of populations and provides cautions and suggestions for their use.

Chapter 13. Completing Monitoring and Reporting Results—Summarizes the final stages of a monitoring project and describes methods for reporting results.

Effective monitoring is not easy; it requires a commitment of time and a willingness to think through alternatives during planning and design. We believe you will find that increasing time spent in design reduces total monitoring costs by making monitoring more efficient and effective. Above all, we hope to help you avoid wasting time on a monitoring project that fails to yield results useful for management decisions.

Because this is a somewhat novel approach, and because we intend to eventually update this handbook, we are especially interested in receiving your comments and opinions. You can send comments to:

Dr. Phil Dittberner

National Applied Resource Sciences Center, RS-140
Denver Federal Center, Building 50
P.O. Box 25047
Denver, CO 80225-0047



Sparks, Jeffrey C.1, Masters, Ronald E.1*, Engle, David M.2,
Palmer, Michael W.3 & Bukenhofer, George A.4

1Department of Forestry, 2Department of Agronomy, 3Department of Botany, Oklahoma State University, Stillwater,
OK 74078, USA; 4U.S. Forest Service, Ouachita National Forest, Heavener, OK 74937, USA;
*Corresponding author; Tel.+1 405 744 6432; Fax +1 405 744 9693; E-mail: rmaster@okway.okstate.edu

Abstract. We compared the effects of late dormant-season and late growing-season prescribed fires on herbaceous species in restored shortleaf pine- (Pinus echinata) grassland communities in the Ouachita Highlands of western Arkansas.Herbaceous species richness, diversity, and total forb and legume abundance increased following fire. Late growing season burns reduced distribution and abundance of panicums (primarily Panicum boscii, P. dichotomum, and P. lineari folium) while late dormant-season burns increased Panicum distribution and abundance. Density of legumes (such as Stylosanthes biflora) increased following frequent or annual dormant-season fires. However, season of fire influenced the distribution and abundance of fewer than 10 % of the species. Fire plays an essential role in pine-grassland communities by creating and maintaining open canopy conditions that perpetuate understory herbaceous plant communities.

Keywords: Arkansas; Fire ecology; Fire frequency; Fire season; Ouachita Mountains; Restoration ecology.

NomenclatFure: Smith (1988).



Fire played an important role in shaping formerly abundant pine- (Pinus spp.) grassland communities in the southeastern United States (Buckner 1989; Platt et al. 1988; Waldrop et al. 1992; Masters et al. 1995). Historical accounts before settlement describe these pine-grassland communities as open ‘park-like’ pine stands with a distinct grass-dominated herbaceous layer and recurrent woody layer, depending on fire frequency (James 1823; Featherstonhaugh 1844; Komarek 1965; Nuttall 1980; Waldrop et al. 1992; Masters et al. 1995). The accumulation of herbaceous material provided adequate fuels for frequent fires of aboriginal and lightning origin which maintained the open structure of these pine-grassland communities (Komarek 1965; Buckner 1989; Foti & Glenn 1991; Waldrop et al. 1992; Masterset al. 1995).

Similar to other forest communities of the World, settlement in the southeastern United States (18th to mid-19th century) altered these landscapes by removing or changing much of the natural vegetation, resulting in fragmented and dissected landscapes (Cottam 1949; Stearns 1949; Curtis 1956; Forman & Godron 1986; Kreiter 1995). The frequency and scale of fires in the region declined after settlement because of aboriginal displacement, fragmentation of habitats causing artificial fire breaks, and fire suppression by settlers (Pyne 1982). This decline in fire frequency caused once open pine-grassland communities to become much more densely forested. Dense forests minimize light reaching the forest floor, thus reducing the herbaceous plant community, understory forage, and habitat quality for many species of wildlife (Lewis & Harshbarger 1976; Masters 1991a; Wilson et al. 1995). The endangered redockaded woodpecker (Picoides borealis), an endemic of southeastern pine forests, is one example of a species that has declined, in part, as a result of increased forest density in the southeastern United States.

The U.S. Forest Service has begun to reconstruct or restore shortleaf pine- (Pinus echinata) grassland communities to benefit both plant and wildlife species dependent on these systems. In the Ouachita National Forest of western Arkansas, the Forest Service uses a program known as Wildlife Stand Improvement (WSI) that consists of thinning midstory and codominant pine and hardwood trees to near pre-settlement basal areas. Currently, WSI treated stands are burned during the dormant season on 3-yr intervals to maintain open structure. However, recent studies in the Ouachitas suggest that the historical fire regime was one of predominantly late growing-season fires and to a lesser extent dormant season burns (Foti & Glenn 1991; Masters et al. 1995). To effectively restore this system, knowledge of the effects of both growing-season and dormant-season prescribed burns is necessary (Masters et al. 1995, 1996).


Fig. 1. Restored pine-grassland in the Ouachita Mountains with Pinus echinata

Numerous studies have compared the effects of growing-season and dormant-season fires on vegetation in Coastal Plain regions of Florida, Louisiana, and South Carolina (Grelen 1975; Hughes 1975; Lewis & Harsh-barger 1976; Platt et al. 1988; Waldrop et al. 1992; Glitzenstein et al. 1995). Masters (1991a, b) and Masters et al. (1993) described the effects of dormant season burns of varying frequency on vegetation under a variety of overstory conditions in interior highlands. Masters et al. (1996) described the effects of WSI and dormant-season burns on restored pine-bluestem communities. However, no information is available on the effects of growing-season burns in the Ouachita Mountains. Our main objective was to compare the effects of growing-season and dormant-season burns on herbaceous vegetation richness, diversity, and abundance in WSI-treated stands.

Study area

Our study focused on stands under active management for the endangered red-cockaded woodpecker within the 40 000-ha Pine-bluestem Ecosystem Renewal Area, on the Poteau Ranger District of the Ouachita National Forest (ONF) in Scott County Arkansas. The ONF lies in the 2 280 000 ha Ouachita Mixed Forest  Meadow Province and comprises 648 000 ha throughout the Ouachita Mountains in Arkansas and Oklahoma (Neal & Montague 1991; Bailey 1995). The Ouachita mountains are east-west trending, strongly dissected and range in elevation from 150 – 790 m (Fenneman 1938: 669). South-facing slopes tend to be dominated by shortleaf pine and more mesic north-facing slopes tend to be dominated by oaks (Quercus spp.), hickories (Carya spp.) and other hardwoods (Johnson 1986; Foti & Glenn 1991). Ouachita Mountain soils developed from sandstone and shales and are thin and drought prone. A semi-humid to humid climate prevails with hot summers and mild winters (Smith 1989).

Pinus echinata was the dominant overstory species in all stands (Fig. 1). Codominant and intermediate over story species included Quercus stellata, Q. marilandica, alba, Q. rubra, Q. velutina, Carya texana and C. tomentosa. Tree heights in our study stands ranged from 15 – 23 m ( x = 18.3 m; S.D. = 3.1). Canopy cover ranged  from 68 – 93 % (x = 84.1% ; S.D. = 7.5). Woody sprouts  (≤ 3 m tall) dominated the understory of these stands. The dominant understory woody species and vines included Toxicodendron radicans, Vaccinium pallidum, Quercus stellata, Carya tomentosa, Rubus spp., Parthenocissus quinquefolia, Ceanothus americanus, Vitis rotundifolia, Quercus alba and Pinus echinata (Sparks 1996).


Experimental design

Our experimental design encompassed two studies (Study 1 and Study 2) and was completely randomized. In these studies we used 12 stands (13.8 to 26.7 ha) that had been previously subjected to WSI and prescribed fire at 3-yr intervals (≥ 3 prescribed fire cycles). Overstory pine density and basal area was similar across all stands (Sparks 1996). Study 1 consisted of three treatments with four replications of each treatment (n = 12). Study 2 used the control and dormant-season fire stands from Study 1 (n = 8). Treatments are as follows:

Study 1

(1) No-burn control (CON1; n = 4);

(2) Late growing-season burn, September 1994 (GS1; n = 4);

(3) Late dormant-season burn March-April 1995 (DS1; n = 4);

Study 2

(4) Late growing-season burn, October 1995 (GS2; n = 2);

(5) Late dormant-season burn, March 1996 (DS2; n = 2);

(6) Frequent dormant-season fire, March-April 1995 and March 1996

(FDS; n = 2);

(7) Infrequent dormant-season fire, burned March-April 1995, no-
burn 1996 (IFDS; n = 2).

Study 1 and Study 2 dormant-season and growing season fire treatments differed in that prescribed burns were applied after three vs. four growing seasons, respectively, following previous dormant-season fire. Study 2 used the dormant-season fire treatments from Study 1 to determine the effects of fire frequency on the herbaceous community. In both studies, late growing-season fires were performed because of poor burning conditions (primarily fuel moisture, presence of live vegetation and high relative humidities) earlier in the season.

Vegetation sampling

We sampled herbaceous vegetation during a two week period in late July 1994 (Study 1 pre-treatment), July 1995 (Study 1 post-treatment; Study 2 pre-treatment), and July 1996 (Study 2 post-treatment). In each stand, we established 30, 1 m × 1 m permanent plots (after Oosting 1956) at 30-m intervals on two to four randomly spaced lines perpendicular to the contour (after Masters 1991a, b). To avoid bias from surrounding stands, we did not sample within 50 m of any edge (Mueller-Dombois & Ellenberg 1974: 123). For each herbaceous species, we recorded percent frequency of occurrence and stem density within plots. Percent cover for vascular plant groups and objects such as rocks, tree boles, and logs was also estimated. Voucher specimens were collected, verified and deposited in the Oklahoma State University Herbarium.

Data analysis

We calculated species richness and diversity (Shannon-Weaver H’) after Ludwig & Reynolds (1988) at the sample (m2) and stand scales. In both studies, we summarized herbaceous species by mean density and percent frequency of occurrence for each year and treatment. All plant species were classified according to plant growth form (e.g., forb, legume, grass, etc.) and season of growth (cool vs. warm). Season of growth was determined by flowering dates described by the Great Plains Flora Association (1986) with cool-season species flowering from November to mid May, and warm season species flowering from mid May through October. To account for pre-treatment differences, we determined the percent change [(post-treatment – pre-treatment / pre-treatment) × 100] in density and frequency of occurrence caused by treatments. All variables were tested for homogeneity of variance using Levene’s test (Snedecor & Cochran 1980). These tests indicated homogeneity of variances, so we tested for treatment differences in percent change using a one-way GLM in which treatment was the factor of interest (Anon. 1985).

In Study 1, we used orthogonal contrasts (burn vs noburn and growing-season fire vs. dormant-season fire) and separated treatment means (P ≤ 0.05) with the protected least significant difference test (Steel & Torrie 1980; Conover & Iman 1981).

We performed Detrended Correspondence Analysis (DCA) using CANOCO (ter Braak 1988), to analyze the species composition data. We checked the results for instability caused by a bug in the program (Oksanen & Minchin 1997). DCA is a multivariate indirect gradient analysis that uses variation in species abundance data to display species and stand locations in a two-dimensional ordination space (ter Braak 1986). DCA axes are in units of constant beta-diversity, where one unit is equal to one standard deviation of species turnover (Hill & Gauch 1980). In DCA, changes in location of a stand over time indicate corresponding changes in real or relative species composition of the stand (Wyant et al. 1991). DCA was used to analyze importance values relative density + relative frequency) to determine changes in stand composition from pre-treatment to post-treatment (after Mueller-Dombois & Ellenberg 1974; Smith 1990). We square-root transformed species abundances before analysis.


Response to fire and fire season

We observed more than 150 herbaceous species during these two studies. Fewer than 10% of these species were influenced (P ≤ 0.05) by season of fire. Late dormant-season fires produced a greater frequency of occurrence of Panicum dichotomum (Study 1: F = 26.9; P = 0.0006, Study 2: F = 29.7, P = 0.0320) and Scleria triglomerata (Study 1: F = 15.3; P = 0.0035, Study 2: F = 19.9, P = 0.0467) than late growing-season fires. Density of Panicum dichotomum (F = 54.5; P = 0.0001) and Scleria triglomerata (F = 5.6; P = 0.0416) was less after late growing-season fires than after late dormant season fires in Study 1.

Although few species were influenced by season of fire, differences (P ≤ 0.05) in density and frequency of major plant categories were apparent (Tables 1 and 2). Late dormant-season fires increased panicum density (primarily Panicum boscii, P. dichotomum, and P. linearifolium) while late growing-season fires greatly reduced total panicum density (Tables 1 and 2). Panicum frequency also declined after late growing-season fires in Study 1 (Table 1). Grasses showed a tendency to decrease in percent cover following fire (Table 3), and a tendency for further decline in density following late growing-season fires (Table 2).

Table 1. Study 1, herbaceous stem density (stems/m2) and percent frequency of occurrence response to season of fire in restored pine-grassland communities on the Ouachita National Forest, Arkansas, summer 1994 and 1995.1

1Row means followed by different letters are different (P < 0.05, Least Significant Difference); 2 Percent change = [(post treatment (1995) – pretreatment (1994) / pre-treatment (1994)) × 100] , presented P > F values are for this category; 3 Contrasts: C = Control; B = Burned stands regardless of season; D = Dormant-season fires; G = Growing-season fires.

Table 2. Study 2, herbaceous stem density (stems/m2) and percent frequency of occurrence response to season of fire in restored pine-grassland communities on the Ouachita National Forest, summer 1995 and 1996.1

1 Row means followed by different letters are different (P < 0.05, Least Significant Difference); 2Percent change = [(post treatment (1996) – pretreatment (1995) / pre-treatment (1995)) × 100] presented P > F values are for this category.

Table 3. Post-treatment percent cover in restored red-cockaded woodpecker clusters on the Ouachita National Forest in 1995.1

1Row means followed by different letters are different (P < 0.05, Least Significant Difference); 2Contrasts: C = Control; B = Burned stands regardless of season; D = Dormant-season fires; G = Growing-season fires.

Regardless of season, fire increased density of legumes, however legume frequency did not increase with burning (Tables 1 and 2). Legume species such as Stylosanthes biflora increased in density (F = 16.9; P = 0.0026) after fire, while other legumes such as Desmodium ciliare (F = 6.58; P = 0.0334) and Lespedeza procumbens (F = 8.37; P = 0.0179) increased in frequency of occurrence after fire. Fire also increased density and frequency of occurrence of numerous forbs such as Coreopsis tinctoria, Polygala alba, and Erechtites hieraciifolia, resulting in an increase in total forb density in Study 1 (Table 1). We found that forbs after late dormant-season fires occurred more frequently than after late growing-season fires and generally increased with fire, although it was not biologically significant (Table 1). Cover of herbaceous vegetation was similar for all treatments, but stands burned during the late dormant season had more bare ground and exposed rock (Table 3). Warm season species had lower densities in response to late growing-season burns than late dormant-season burns (Tables 1 and 2).

Response to frequent fire

Panicum frequency increased with frequent late dormant-season burns (Table 4). However, density of Chasmanthium sessiliflorum declined (F = 35.6; P = 0.0270) after frequent late dormant-season fire. Legume density was greater after frequent late dormant-season fires (Table 4). Density of Lespedeza procumbens (F = 124.0, P = 0.0080) and Stylosanthes biflora (F = 124.9; P = 0.0079) was greater after frequent late dormant-season fires. Helianthus hirsutus (F = 33.7; P = 0.0284) frequency of occurrence was also greater after frequent fire. Stand species richness in frequently burned stands remained stable, but declined in control stands (Fig. 2).

Fig. 2. a. Stand species richness by study and treatment; b. Net-change and standard errors in stand species richness by study and treatment. Means followed by different letters are different (P ≤ 0.05, Least Significant Difference). CON1 = Study 1, no-burn control; GS1 = Study 1, growing-season burn; DS1 = Study 1, dormant-season burn; GS2 = Study 2, growing-season burn; DS2 = Study 2, dormant-season burn; FDS = Study 2, frequent dormant-season burn; and IFDS = Study 2, infrequent dormant-season burn.



Fig. 3. a. Sample (m2) species richness by study and treatment; b. Net-change and standard errors in sample species richness by study and treatment. Means followed by different letters are different (P ≤ 0.05, Least Significant Difference). CON1 = Study 1, no-burn control; GS1 = Study 1, growing-season burn; DS1 = Study 1, dormant-season burn; GS2 = Study 2, growing-season burn; DS2 = Study 2, dormant-season burn; FDS = Study 2, frequent dormant-season burn; and IFDS = Study 2, infrequent dormant-season burn.

Table 4. Study 2, herbaceous stem density (stems/m2) and percent frequency of occurrence response to frequent fire in restored pine-grassland communities on the Ouachita National Forest, summer 1995 and 1996.1

1 Row means followed by different letters are different (P < 0.05, Least Significant Difference); 2 Percent change = [(post treatment (1995) -pre-treatment (1994) / pre-treatment (1994)) × 100] , presented P > F values are for this category.

Community response to fire

Fire dramatically influenced community composition in restored pine-grassland stands. Species diversity when compared to unburned stands was greater (P ≤ 0.05) after both late growing-season and late dormant season prescribed fires. Stand species richness increased after both late growing-season and late dormant-season fires, while declining in unburned stands (Fig. 2b). Furthermore, post-treatment stand species richness after late dormant-season and late growing-season fires was greater than the unburned controls in Study 1 (Fig. 2a). Sample (m2) species richness increased dramatically after late dormant-season fires with net change in stand species richness being greatest after late dormant-season fires (Fig. 3b).

Detrended Correspondence Analysis illustrated the nature of change in these stands over time and in response to fire (Fig. 4). Axis 1 indicated that year-to-year variation may be the most important factor in determining species composition of these stands (Fig. 4). Axis 2 indicated that geographical location of stands also determines species composition. Axis 3 was tentatively interpreted as an indicator of stand openness with species assemblages more characteristic of prairies being grouped together versus those more characteristic of closed forest being grouped together. Axis 4 may be interpreted as a treatment axis (Fig. 4). We included Axis 4 because treatment effect was our primary interest.

Control stands shifted to the right on Axis 1 and upward on Axis 4 indicating a year and treatment effect, while late dormant-season fire stands shifted right on Axis 1 and down on Axis 4 also indicating a year and treatment effect (Fig. 4). Late growing-season fire stands shifted directly to the right on Axis 1 indicating that year effects had an overriding influence on treatment (Fig. 4). The shift in stands after treatment indicates a similar change in species composition among the treatments. Axes 1 through 4 had eigenvalues of 0.161, 0.081, 0.060, and 0.040 respectively. Together all axes account for 26.7% of the total variation in species data. With an eigenvalue of only 0.042, and the fact that the apparent ‘treatment axis’ is the 4th axis, it is obvious that the effects of treatment, while highly significant, is minor compared with year-to-year effects and site location effects.

Fig. 4. Detrended Correspondence Analysis of stand importance values by treatment, Ouachita National Forest. Stands are connected by vectors to indicate change from pre-treatment sampling to post-treatment sampling. CON1 = Study 1, no-burn control; GS1 = Study 1, growing-season burn; DS1 = Study 1, dormant-season burn; GS2 = Study 2, growing-season burn; DS2 = Study 2, dormant-season burn; FDS = Study 2, frequent dormant-season burn;and IFDS = Study 2, infrequent dormant season burn.



Treatment response

Burned stands had higher stand species richness and diversity than no-burn controls (Fig. 2). These results are similar to many studies that indicate an initial in crease in species diversity and richness following fire (Trabaud & Lepart 1980; Armour et al. 1984; Thanos et al. 1996). In Study 2, stands in the 2nd growing season since late dormant-season fire (DSC), declined in species richness, indicating that the initial increase in stand richness after fire is short lived (Figs. 2 and 3) and probably influenced by environmental conditions during a given year (Fig. 4). The majority of individual species in both studies did not respond favorably to any one treatment, but were common in all treatments. We believe this is because species present (e.g. Andropogon spp. and various legume species) in restored pine-grassland communities are well adapted to fire, and community changes are small and of short duration. Waldrop et al. (1992) noted that the pine-grassland ecosystem once common throughout the southeastern U.S. was fire derived and fire maintained. Herbaceous species in these restored pine-grassland communities were likely present in pre-settlement communities that developed under a periodically frequent fire regime during both the dormant and growing seasons (Masters et al. 1995).

Fire does not drastically alter species composition in stands with a recent history of fire. Pre-fire composition is a major factor in determining post-fire composition (Armour et al. 1984; Stickney 1986; Rego et al. 1991). Adjacent forests without WSI treatment have dense midstories minimizing light from reaching the forest floor, so species richness and abundance of herbaceous species is much less than in WSI-treated areas (Masters et al. 1996). We also suggest that post-fire species richness and composition is influenced by fire intensity, which is related to litter consumption and reduction in the stature of woody species (Masters et al. 1993; Sparks 1996).

Stand structure

Prescribed fire plays a major role in determining the vegetation structure and composition in restored pinegrassland communities (Wilson et al. 1995). Understories of stands treated with WSI are characteristically dominated by woody sprouts (> 50 000 stems/ha) that restrict light from reaching the forest floor. Late dormant-season fires in these stands on average produce greater fireline intensity than growing-season fires (1300 Kw/m versus < 300 Kw/m), and are more effective at maintaining an open forest structure by reducing the stature of woody sprouts (Sparks 1996).

The effect of a disturbance such as fire on any community or ecosystem depends on the intensity, scale, and frequency (Sousa 1984; Perry 1994; Sparks 1996). Late dormant-season fires in these stands act as more intense disturbances than late growing-season fires, by more effectively reducing stature of the woody community and reducing the litter layer. Increased light penetration due to the reduced stature of the woody understory and reduction of litter after fire provides an opportunity for new herbaceous species to become established, thereby significantly increasing species richness and diversity (Sousa 1984; Masters 1991a, b; Masters et al. 1993). But, fire in either season increases light and allows species already present to prosper, thus the increase in density and percent frequency of occurrence of forbs after fire.

Species composition

Herbaceous species actively growing at the time of a fire in grassland systems are more susceptible to injury than species that are dormant or in early stages of development (Towne & Owensby 1984). Fires during the dormant season reduce cool-season species while favoring many warm-season species (Owensby & Anderson 1967; Hover & Bragg 1981; Towne & Owensby 1984; Hulbert 1988; Howe 1994a). In contrast, growing-season fires reduce warm season species while favoring cool-season species (Hover & Bragg 1981; Ewing & Engle 1988; Biondini et al. 1989; Howe 1994a). Our results in Study 2 showed an increase in density of warm-season species after burning, Study 1 also showed an increase, but not significantly. Neither study showed an increase for cool-season species when late dormant- and late growing-season burns were compared. Growing-season burns may have increased coolseason species had our growing-season fires been conducted earlier in the growing season and before coolseason species initiated new growth. It is important to note that in both studies we attempted to burn earlier in the growing season, but burning conditions (primarily fuel moisture, presence of live vegetation and high relative humidities) were not conducive to fire until later in the growing season.

Several studies have noted that growing-season fires when compared to dormant-season fires and unburned areas increase diversity and richness by increasing the number of annuals and promoting cool-season grasses and forbs (Biondini et al. 1989; Howe 1994b). Platt et al. (1988) noted that growing-season fires produced more flowering stems than fires in other seasons. Many warm season grasses such as wiregrass (Aristida stricta) and little bluestem (Schizachrium scoparium) flower profusely after growing-season fires (Lewis 1964; Robbins & Myers 1992). Hodgkins (1958) noted that composites and legumes increase in response to growing-season fires. Our results indicate an aggressive response from legumes and forbs (Tables 1 and 2), and a larger increase in species richness after dormant-season fires (Fig. 2 and 3). Other studies have found similar results (Grelen & Lewis 1981; Landers 1981; White et al. 1991). Legumes in particular are adapted to fire and benefited because of a hard seed coat and subsequent persistence in the soil seed bank (White et al. 1991; Arianoutsou & Thanos 1996; Thanos et al. 1996).

In Study 2, legume density (primarily Amphicarpa bracteata, Clitoria mariana, Lespedeza repens, and Stylosanthes biflora) was 2 × greater after two frequent late dormant-season fires, similar to Masters et al. (1993), who found legume biomass > 4 × greater after 5 years of annual burning compared to unburned controls. White et al. (1991) found that 43 years of annual winter fires increased legumes by > 25 × over periodic summer and winter burns or annual summer burns. The lack of an increase in legume frequency in our study may be due to relatively high frequency for legumes (80 – 88 %), especially since we observed that most of these species had a tendency towards aggregation. Stem densities within aggregations or sample plots can increase without increasing frequency (Mueller-Dombois & Ellenberg 1974). Further, initial high legume frequency may have been related to the previous fire history within these stands.


Because pine-grassland communities developed under a fire regime that included both dormant and growing season fire, both seasons of fire should be used as management tools in a restoration context. Fire in either season increased species richness, diversity, and total abundance of forbs and legumes, while herbaceous species abundance and richness declined in no-burn controls. Fire reduces woody structure, which influences herbaceous plant composition in restored pine-grassland ecosystems. Increased light and presence of bare ground after fire provide the opportunity for many herbaceous species to become established. Change in species composition and abundance is linked to change in stand structure. Late dormant-season fires are more effective than late growing-season fires at reducing woody sprouts in the understory and at providing bare ground for colonization. As a result, herbaceous species abundance and richness was greater after late dormant season fires.

Acknowledgements. We thank M. E. Payton for assistance with experimental design and statistical analysis, J. Kulbeth, S. Farley, S. Crockett, and D. Gay, for assistance in collecting data and W. Montague for assistance with experimental burns. This project was funded by the U.S. Department of Agriculture, Forest Service, Department of Forestry at Oklahoma State University and was a cooperative effort with Oklahoma Agricultural Experiment Station. This article was published with authorization by the director of the Oklahoma Agricultural Experiment Station.


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Received 11 March 1997;
Revision received 4 August 1997;
Accepted 13 August 1997;
Final revision received 9 January 1998.