Scale, ecosystem resilience, and fire in shortgrass steppe
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SCALE, ECOSYSTEM RESILIENCE, AND FIRE
IN SHORTGRASS STEPPE
by
Pauiette Louise Ford
Copyright ® Pauiette Louise Ford 2000
A Dissertation submitted to the Faculty of the
SCHOOL OF RENEWABLE NATURAL RESOURCES
In Partial Fulfillment of the Requirements For the Degree of
DOCTOR OF PHILOSOPHY WITH A MAJOR IN RENEWABLE NATURAL RESOURCE STUDIES
In the Graduate College
THE UNIVERSITY OF ARIZONA
2000 UMI Number 9983915
Copyright 2000 by Ford, Paulette Louise
All rights reserved.
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THE UNIVERSITY OF ARIZONA ® GRADUATE COLLEGE
As members of the Final Examination Committee, we certify that we have PAULETTE LOUISE FORD read the dissertation prepared by______SCALE, ECOSYSTEM RESILIENCE, AND FIRE IN SHORTGRASS STEPPE entitled ------
and recommend that it be accepted as fulfilling the dissertation DOCTOR OF PHILOSOPHY requirement for the Degree of
Mitchel P. McClaran
I ~DeborahvDf47:e< M. < k1Finch
Robert H. Robichaux
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ACKNOWLEDGMENTS
I would like to acknowledge the many students, professors, colleagues,
technicians, interns, and support staff of the Rocky Mountain Research Station, Kiowa
National Grassland, Cibola National Forest, University of New Mexico, and University of
Arizona, who provided me with encouragement and support. I would like to acknowledge in particular my supervisor and mentor, Deborah M. Finch, for her constant support, both financially and emotionally, and for being a wonderful role model; Mitchel
P. McClaran for caring enough to be my major advisor; James H. Brown for the example you set for excellence in ecology, and for your support over the many years; Robert H.
Robichaux and Malcolm J. Zwolinski for serving on my committee; and Mary Soltero for your counsel and friendship. I also thank Dale Brockway; Rudy King, Ed Bedrick, Bob
Dana, Joyce Van deWater, Sandra Brantley, Richard Fagerlund ,David Lightfoot; Gordon
Johnson; Jeff Kelly, Nora Altamirano, Carmen Gallegos, Roberta Montoya, and my many friends. I thank my dog Angel for always being there for me. I thank my family for loving me and being proud of me. Especially my parents James and Shirley, and my grandmother Jessie, for always expecting the best from me, and my siblings, Suzette,
Amber, Sam, and Morgan, for keeping me grounded. Primarily, I thank my Savior, the
Lord Jesus Christ, for being my Rock and my Refuge, and for directing my path. Amen! 5
TABLE OF CONTENTS LIST OF ILLUSTRATIONS 7 LIST OF TABLES 8 ABSTRACT 10 INTRODUCTION 12 Fire as a Management Tool 13 Grassland History, Fire Frequency and Season 15 Scale and Ecosystem Resilience 18 Shortgrass Steppe and Fire 20 Fire Effects on Ecosystem Components of Shortgrass Steppe 21 Microbiotic Crusts 21 Buffalograss and Blue grama 23 Arthropods and Small Mammals 26 Research Objectives, Questions, and Theoretical Hypotheses 31 STUDY AREA 33 Site Description 33 Soil and Vegetation 34 METHODS 39 Experimental Design and Fire Treatments 39 Ground Cover 42 Microbiotic Crusts 42 Arthropods 45 Small Mammals 46 Statistics 47
RESULTS 49 Fire Treatments 49 Ground Cover 49 Microbiotic Crust 49 Grass 54 Herbaceous Dicot (Live/Dead), Shrub, Cactus 55 Bare Ground 55 Litter 61 Arthropods 61 Small Mammals 64
DISCUSSION 86 6
Appendix A. PRIMARY LITERATURE: BUFFALCXjRASS (BUCHLOE DACTYLOIDES) AND BLUE GRAMA {BOUTELOUA GRACIUS) RESPONSE TO FIRE 101
Appendix B. INFITAL PLANT SURVEY: EXPERIMENTAL FIRE RESEARCH SITE, KIOWA NATIONAL GRASSLAND, UNION COUNTY, NEW MEXICO 1995 113
Appendix C. SURFACE-ACTIVE ARTHROPOD SPECIES COLLECTED FROM EXPERIMENTAL FIRE RESEARCH SITE, KIOWA NATIONAL GRASSLAND, UNION COUNTY, NEW MEXICO 1996-1998 121
LITERATURE CITED 143 7
LIST OF ILLUSTRATIONS
Figure Page
1. New Mexico Grasslands 36
2. Buffalograss, fiwc/i/oe i/acty/oif/ej NutL 37
3. Blue grama, Bouteloua gracilis (H.B.K.) Lag 38
4. Experimental Fire Treatment 41
5. Study Site: Post-treatment, August 1997 50
6. Absolute ground cover (%): total number of hits per ground cover category /500 hits. Categories include grass, bare ground, litter, microbioitc crust, and other (herbaceous dicot live/dead, shrub, cactus) 51
7. Study Site: Conyza canadensis Cronquist, October 1999 59
8. Overall relative abundance (%): total number of individuals per sfjecies compared to the total number of individuals of all species combined. Species include Onychomys leucogaster (Wied-Neuwied) (ONLE), Reithrodontomys montanus (Baird) (REMO), Spermophilus tridecemlineatus J.A. Allen (SPTR), and other (Peromyscus maniculatus (Wagner), Sigmodon hispidus Say and Ord, Dipodomys ordii Woodhouse, Perognathus flavus Baird,Chaetodipus hispidus Baird, Mus musculus Linnaeus) 85 8
LIST OF TABLES
Table Page
1. MULTTEST comparison of microbiotic crust cover between fire treatments and within time periods 52
2. Mean microbiotic crust acetylene reduction (reported as nanomoles ethylene/cm^/h) by treatment and period, and estimated nitrogen fixation rate. Calculation of grams nitrogen/ha/h assumes complete coverage by the microbiotic crust 57
3. MULTTEST comparison of grass cover between fire treatments and within time periods 58
4. MULTTEST comparison of bare ground between fire treatments and within time periods 60
5. MULTTEST comparison of litter cover between fire treatments and within time periods 62
6. Beetle (Coleoptera) families and associated trophic groups from Kiowa National Grassland Experimental Fire Research Study Site Period I (March 1997) and Period 4 (July-October 1998) 65
7. Beetle absolute and relative abundance (%); total number of individuals per species compared to the total number of individuals of all species combined 68
8. Trophic group absolute and relative abundance (%): total number of individuals per trophic group compared to the total number of individuals of all trophic groups combined 69
9. MULTTEST comparison of beetle (Coleoptera) abundance (# individuals) between fire treatments, and within time periods 70
10. MULTTEST comparison of beetle (Coleoptera) richness (# species) between fire treatments, and within time periods 71 9
11. MULTTEST comparison of Carpophilus lugubris (dusky sap beetle) abundance between fire treatments, and within time periods 72
12. MULTTEST comparison of Agrypnus rectangularis (click beetle) abundance between fire treatments and within time periods 73
13. MULTTEST comparison of Carabidae, Scarabaeidae, and Tenebrionidae abundance between fire treatments and within time periods 74
14. Small mammals from Kiowa National Grassland Experimental Fire Research Study Site 1995-1998 78
15. MULTTEST comparison of small mammal abundance between fire treatments and within time periods 79
16. MULTTEST comparison of small mammal richness between fire treatments and within time periods 80
17. MULTTEST comparison of Onychomys leucogaster abundance between fire treatments and within time periods 81
18. MULTTEST comparison of Reithrodontomys montanus abundance between fire treatments and within time periods 82
19. MULTTEST comparison of Sperrnophilus tridecemlineatus abundance between fire treatments and within time periods 83
20. MULTTEST comparison of overall relative abundance of Onychomys leucogaster, Reithrodontomys montanus.and Spermophilus tridecemlineatus between fire treatments and within time periods 84 10
ABSTRACT
Consideration of scale and ecosystem resilience is integral to any conceptual
model of the effects of disturbance on ecosystems. Organisms, populations,
communities, and ecosystems are differentially affected by disturbance based on the scale
at which they occupy the landscape. Scale of observation influences perceptions about
ecosystem resilience. There is no single correct scale at which ecological phenomena
should be studied, and management decisions require the interfacing of phenomena that
occur on very different scales of space and time.
Fire disturbance affects a variety of ecosystem factors including nutrient cycling,
species diversity, and population and community dynamics. My experimental research on
fire in shortgrass steppe examined the effects of fire and season of fire on various
components of shortgrass steppe at multiple spatial and temporal scales and
organizational units. My experimental design was completely randomized, with 3
treatments, and 4 replicates per treatment. Treatments were dormant-season fire,
growing-season fire, and unbumed. Response variables were 1) ground cover; 2)
microbiotic crust nitrogen fixation, and chlorophyll a content; and 3) species richness, abundance, and relative abundance of small mammals and arthropods. Microbiotic crust II
cover never differed significantly among treatments for all periods, however, acetylene
reduction and chlorophyll a content of crusts differed significantly among treatments.
Dormant-season fire-treated crusts had significantly lower rates of acetylene reduction
than unbumed crusts, while growing-season fire-treated crusts did not differ significantly
from unbumed or dormant-season fire-treated crusts. Dormant-season fire-treated crusts
had significantly lower chlorophyll content than unbumed crusts, while growing-season
fire-treated crusts did not significantly differ from unbumed or dormant-season fire
treaied-c rusts.
Initially, growing-season fire significantly reduced grass cover compared to
unbumed and dormant-season fire. Approximately 30 months later there were no significant differences in grass cover among treatments. Bare ground response was basically the inverse of grass cover response. The only significant differences in litter cover between treatments occurred immediately after the growing-season fire.
Arthropod species richness differed significantly among treatments; growing- season fire plots had a significantly higher number of beetle species. However, overall beetle abundance did not significantly differ among treatments. Significant differences were never detected in overall rodent species richness or abundance among treatments. 12
INTRODUCTION
One of the major goals of National Forest System land management is ecological
sustainability. Ecological sustainability is defined as the maintenance or restoration of
ecological system composition, structure, and function that are characteristic of a
managed area over time and space. This concept includes, but is not limited to,
ecological processes, biological diversity, and the productive capacity of ecological
systems (Dombeck 1998). To achieve ecological sustainability, it is necessary to
maintain and restore ecosystem integrity. Ecosystem integrity is defined as the
completeness of an ecosystem that, at multiple geographic and temporal scales, preserves
its characteristic diversity of biological and physical components, spatial patterns,
structure, and functional processes within its approximate range of historic variability
(Dombeck 1998). Sustaining the integrity of ecological systems increases their resilience
to natural disturbance events, allows renewal following use or degradation, and helps to
preserve options for future generations (Dombeck 1998).
My research on the Kiowa National Grassland is part of a continuing effort to
achieve ecological sustainability of National Forest System land by developing a
scientific basis for ecosystem and land management. Funded by the Ecology, Recovery, and Sustainability of Southwestern Grasslands unit of the USDA Forest Service Rocky 13
Mountain Research Station, my research over the last four years has (1) examined the
role of fire as an agent of natural disturbance that regulates ecological processes in grasslands, and (2) assessed its value as a tool for maintaining and restoring grassland ecosystems.
Fire as a Management Tool
The history of the relationship between man and fire has been filled with ambivalence and mistrust, along with an appreciation of both the power of fire as an agent of destruction and as a tool for management. Native Americans frequently started grassland fires to modify habitat and to aid in hunting activities by both driving and attracting wild game (Bahre 1985; Pyne 1982). However, early non-native attitudes regarding fire were colored by the European philosophy of fire suppression as being tantamount to fire management (Ford and McPherson 1996).
In the past 50 years attitudes have changed significantly regarding the use of fire.
Fire as a management tool was reintroduced into North America first in the southeastern
U.S. in the 1930s, following research by scientists, including Chapman (1926, 1932,
1936), the first scientist to provide a scientific basis for prescribed burning. Further support for burning in the 1930s was provided by the works of Green (1931), Heyward
(1936, 1937, 1939) and Stoddard (1931), who published on the effects of fire on forest structure, soil, and wildlife, respectively (Wright and Bailey 1982; Ford and McPherson
1996). Yet, from 1940 to the early 1960s there were still many followers of the European
philosophy who feared fire would be misused (Wright and Bailey 1982; Ford and
McPherson 1996).
Biologists began taking a more benign view of fire in North America starting in
the early 1960s with the release of the Leopold Report (Wright and Bailey 1982). The
report enlightened the general public about the negative effects of total fire suppression in plant communities, including excessive fuel loading, declining wildlife species diversity, and encroachment of shrubs and trees into grasslands (Leopold et al. 1963; Wright and
Bailey 1982).
Fire Is now used as a management tool on at least a limited scale in all areas of
North America (Leopold et al. 1963; Wright and Bailey 1982; Ford and McPherson
1996), but the question of how fire affects rangelands has not been fully addressed
(McPherson 1995; Steuter and McPherson 1995). As a result, the extent and duration of fire's impact on grassland communities in the southern Great Plains is largely unknown
(Ford and McPherson 1999). 15
Grassland History, Fire Frequency and Season
The origin of the North American grasslands can be traced to the Miocene-
Pliocene transition, close to 7-5 million years before present, associated with the beginning of a drying trend. The increased aridity resulted from the chilling of the ocean as the Antarctic ice sheet spread and from the Miocene uplift of the Rocky Mountains, which served as a partial barrier to moist Pacific air masses. Grasses are generally better adapted to drought than most tree species, and the spread of the grasslands occurred at the expense of forest vegetation (Axelrod 1985; Anderson 1990; Ford and McPherson 1996).
Fire interacts with other factors including topography, soil, insects, herbivores, and herbaceous plants to restrict woody plant establishment in grasslands (Grover and
Musick 1990; McPherson 1995; Wright and Bailey 1982). Currently there is general agreement that fire is necessary (though perhaps not sufficient) to control the abundance of woody plants and maintain most grasslands. In the absence of periodic fires, grasslands often give way to shrublands dominated by woody plants (McPherson 1995;
Ford and McPherson 1996).
Grassland fire regimes are characterized by declining fire return intervals with increasing aridity (lower fuel load) and an increase in caespitose growth forms (less fuel 16
continuity). In addition, grasslands communities in large, gently rolling landscapes
developed under higher fire frequencies than those with similar fuels in small dissected
landscapes (Wells 1970; Axelrod 1985; Steuterand McPherson 1995). Compared to
humid grasslands, semi-arid grasslands have lower fire frequencies; and arid grassland
communities have developed under the lowest fire frequencies of the grassland types
(Launchbaugh 1972; Wright and Bailey 1980; Steuter and McPherson 1995).
Reliable historical records of fire frequencies in shortgrass steppe in the southern
Great Plains are not available because there are no trees to cany fire scars from which to estimate fire frequency (Wright and Bailey 1982; Ford and McPherson 1996). However, the recent fire history of the northern Great Plains was reconstructed by examining charcoal fragments from lake sediments cores (Umbanhowar 1996). Results of
Umbanhowar's research indicated that post-settlement patterns of charcoal deposition were highly variable but generally much lower than presettlement intervals, suggesting settlement resulted in a decrease in the number and extent of fires.
This conclusion is similar to that of Bahre (1991), who used historical accounts to infer that fire size and frequency have diminished greatly in desert grasslands since the
1880s. Removal of available fuel by heavy domestic livestock grazing most likely also 17 contributed to the post-settlement decline in fire frequency (Ford and McPherson 1996).
Historical accounts of fires by early settlers in the southern Great Plains do exist.
However, such accounts are often anecdotal and biased toward documenting particularly large or destructive fires (McPherson 1995; Wright and Bailey 1982). A more recent quote by Shantz 88 years ago leaves the impression that fire disturbance was a fairly frequent event- "The effect of fire must be regarded as having been always operative in the Great Plains region. Fires are started by lightning during almost every thunderstorm, and the advent of man, has, if anything, tended to check rather than to increase their ravages." (Shantz 1911).
Grassland communities are usually influenced by season and frequency of fire due to evolutionary adaptations of the organisms to particular habitat features and conditions
(Ford and McPherson 1996, 1998). And fire has been a consistent enough event in semi- arid grasslands for plants to develop structural adaptations to its periodic stress (Steuter and McPherson 1995). For example, forbs tend to be more diverse and represented by a higher number of individuals following fire than in long-term unbumed communities
(Bailey and Anderson 1978; Collins and Barber 1985; Ford and McPherson 1998). 18
In addition, the season in which the fire occurs has the potential to generate a dynamic spatial and temporal mosaic within the landscape (Steuter and McPherson
1995). The fuels of semi-arid grasslands may support high rates of fire spread when dry
(Rothermel 1983), or be too discontinuous or actively growing (green) to carry a fire
(Andrews 1986; Steuter and McPherson 1995). As a result, native communities probably developed under a characteristic range of fire size and frequency for the different seasons
(Stealer 1986; Ford and McPherson 1998).
Overall, variability in the population dynamics of some plant species appears to be related largely to variation in fire behavior (intensity, percent area burned, fuel consumption), regardless of the season of burning, while other plant species are least vulnerable to dormant-season burning and most vulnerable to burning early in the growing-season (Glitzenstein et al. 1995). And in general, plant species in semi-arid grasslands are more strongly influenced by fire season and frequency than by other aspects of fire behavior (Steuter and McPherson 1995; Ford and McPherson 1996).
Scale and Ecosystem Resilience
In ecological terms, fire is a disturbance. A disturbance is defined as any relatively discrete event in time that disrupts ecosystem, community, or population structure and changes resources, substrate availability, or the physical environment 19
(White and Pickett 1985). Consideration of scale and ecosystem resilience is integral to
any conceptual model of the effects of disturbance on ecosystems.
Scale refers to the resolution to which patterns are measured, perceived, or
represented (Morrison and Hall in press). Relating phenomena across scales is a central
problem in biology and in all scientific disciplines (Levin 1992). It is a problem that
unifies population biology and ecosystems science, and marries basic and applied ecology
(Levin 1992). There is no single correct scale at which ecological phenomena should be
studied; systems generally show characteristic variability on a range of spatial, temporal,
and organizational scales. Applied challenges require the interfacing of phenomena that
occur on very different scales of space, time, and ecological organization (Levin 1992).
Many of the characteristics commonly used to define ecosystems (e.g., geographic
limits, temporal duration, environmental factors, taxonomic composition) are themselves
dependent on the temporal and spatial scale of observation (Schopf and Ivany 1998).
What we perceive as the behavior of ecosystems is therefore intimately tied to our scale of observation; what appears as a net flux close up may be net steady state from a few steps away (Schopf and Ivany 1998). Hence, the observer imposes a perceptual bias, a filter through which the system is viewed (Levin 1992). 20
Scale of observation influences perceptions about ecosystem resilience.
Resilience is variously defined as the ability of a community to return to a former state after exogenous disturbance; the capacity to continue functioning after perturbation; the ability to absorb change and variation without turning over into a different state where the variables and controlling structure and behavior suddenly change; or the ability to recover quicidy to conditions and relationships existing prior to the disturbance (Holling
1973, 1996; Lincoln et al. 1998). Resilience represents the property that sustains ecosystems in the face of disturbance, or permits recovery following disturbance.
Ecosystems are not equally resilient, and do not respond uniformly to a particular disturbance (Holling 1973, 1996).
Shortgrass Steppe and Fire
A perception exists that shortgrass steppe is not resilient to fire. This is largely the result of the frequent citation of a handful of studies that have been interpreted as indicating negative effects of fire on shortgrass steppe (i.e., Dix 1960, Dwyer and Pieper
1967, Heirman and Wright 1973, Hopkins et al. 1948, Launchbaugh 1964, Trlica and
Schuster 1969, and Wright 1974). Most of this literature focused primarily on the use of fire as a tool to increase grassland productivity to benefit domestic livestock (Ford 1999). 21
Even though fire is a natural component of shortgrass steppe, semi-arid grasslands do not always recover from fire in the time frame required to meet the forage needs of livestock. Therefore, negative perceptions about resilience, or the value of fire in shortgrass steppe, may have been influenced by a desire for rapid recovery or increase in grassland productivity. However, fire disturbance affects a variety of ecosystem components beyond plant productivity (forage), including nutrient cycling, species diversity, and population and community dynamics of the protists, flora and fauna that constitute the shortgrass steppe ecosystem.
Fire EfFects on Ecosystem Components of Shortgrass Steppe
Microbiotic Crusts
Microbiotic crusts, also known as soil algal crusts or cryptogamic crusts, cover extensive portions of the arid and semiarid regions of the world. They consist of water- stable surface soil aggregates held together by algae, fungi, lichens, and mosses (Johansen
1993).
Several researchers have claimed that microbiotic crusts are critically important components of the arid and semi-arid ecosystems in which they occur (Harper and Marble
1988; Metting 1991; Johansen et al. 1993). For example, input, loss, and cycling of 22
nutrients are fundamental processes in any ecosystem (Evans and Johansen 1999).
Microbiotic crusts are important contributors to nutrient cycling because they are capable of nitrogen fixation (Evans and Johansen 1999). Microbiotic crusts also contribute to soil fertility through organic carbon contributions, and accumulation of fine soils (Johansen et al. 1993).
One of the most important effects that microbiotic crusts can have on ecosystem dynamics is stabilization of soil surfaces (St. Clair and Johansen 1993). Crusts have the potential to affect rates of erosion and hydrology through reduction of water runoff, and reduced sediment production by both wind and water moving across the soil surface; in addition to affecting seed germination and seedling establishment by providing microsites for plant establishment (St. Clair etal. 1984; Harper and Marble 1988; Metting 1991;
Belnap and Gardner 1993; Johansen 1993; Evans and Johansen 1999).
Microbiotic crusts are considered fragile and easily damaged by disturbance.
Several studies have suggested disturbance by fire destroys microbiotic crusts (Johansen et al. 1984, Callison et al. 1985; West and Hassan 1985; West 1990; Johansen 1993;
Kasper 1994; Evans and Johansen 1999). While other studies have suggested that season of fire may influence the severity of damage caused to microbiotic crusts. However, 23 empirical evidence for this hypothesis is lacking (Johansen 1993).
Recovery rates of crustal communities depend on several factors. The type and extent of disturbance, in addition to environmental variables, will greatly influence time to recovery (Belnap 1993). Microbiotic crusts are only metabolically active when wet.
Years with higher effective precipitation will show faster recovery than years with lower effective precipitation (Belnap 1993; Johansen et al. 1984, 1993). Estimates of time for natural recovery of microbiotic crusts from disturbance have varied widely, ranging from a few years to 100 years for full recovery of all components (Anderson et al. 1982;
Callison et al. 1985; Cole 1990; Jeffries and Klopatek 1987; Johansen et al. 1982, 1984;
Belnap 1993).
BufTalograss and Blue grama
Buffalograss {Buchloe dactyloides (Nutt.) Engelm.) and blue grama (Bouteloua gracilis (H. B. K.) Lag.) are two major plant species of shortgrass steppe. These short- statured grasses are considered drought resistant and well adapted to the driest sections of the central Great Plains, where they constitute the principal native plant species in terms of basal area coverage (Savage and Jacobson 1935). The two species are co-dominants over much of the shortgrass region in North America. The central and southern Great 24
Plains is often referred to as a Bouteloua gracilis- Buchloe dactyloides association
(Shantz 1923; Kuchler 1964; Coffin et al. 1996).
Buffalograss is a perennial, sod-forming grass of central North America
(Hitchcock 1951). The species is largely dioecious, with plants bearing either male,
pollen-producing flowers or female, seed-producing flowers (Quinn and Engel 1986).
Buffalograss seeds are enclosed in hard burs (usually 1-5 seeds per bur) that serve as the
dispersal unit (Quinn 1987). Burs greatly reduce fire or heat damage to seeds (Ahring
and Todd 1977). Fire was a regular feature of the original buffalograss environment
(Haley 1929; Vogl 1974; Wright and Bailey 1982; Quinn 1987), so such protection from
heat damage may have been important.
Blue grama, a bunchgrass, is also perennial. It is widely recognized as the key species in shortgrass ecosystems (Hyderet al. 1975; Hook et al. 1991; Burke et al. 1995;
Coffin et al. 1996) and is thought to be the most drought- and grazing-tolerant plant species in shortgrass communities (Hyder et al. 1975; Coffin et al. 1996).
Both buffalograss and blue grama are warm-season plants that use the C4 photosynthetic pathway. Plants with C4 photosynthesis use the dicarboxylic acid pathway 25
for carbon dioxide assimilation (Lincoln et al. 1998). They are adapted to warmer
climates and generally are distributed toward lower latitudes, where average
temperatures during the growing season are higher (Raven and Johnson 1996). Cool-
season plants with Cj photosynthesis (e.g. Stipa), tend to have early spring, winter, or fall
growing seasons when temperatures are cooler (Fort Hays State University 1989).
Growing-season fires are thought to be differentially detrimental to plants, based
on their season of active growth. Fire in the growing season reduces regrowth because a
large proportion of living leaf area is removed (Briske 1991; Briske and Richards 1995).
Plant growing season and fire season, along with other biotic and abiotic environmental
variables, including grazing and rainfall, are important factors in determining the
response of plants to disturbance by fire.
Ford (1999) reviewed 15 studies that assessed buffalograss and blue grama
response to fire (Appendix A). Five studies assessed the effects of fire by comparing burned sites with nearby or adjacent unbumed sites (Hopkins et al. 1948; Dix 1960;
Launchbaugh 1964; Dwyer and Pieper 1967; Morrison et al. 1986). Ten studies used experimental fire treatments and controls (Box et al. 1967; Box and White 1969; Trlica and Schuster 1969; Anderson et al. 1970; Heirman and Wright 1973; Wright 1974; While and Currie 1983; Schacht and Stubbendieck 1985; Whisenant and Uresk 1989,
1990). Because of the variety of fire types, seasons, weather conditions, grazing histories,
and fuel conditions in which the bums can occur, one must be careful in interpreting the
effects of fire (Ford 1999).
However, overall results of the studies suggest that fire does not necessarily have
a detrimental effect in shortgrass steppe. Regardless of fire type (i.e., experimental or
wildfire), buffalograss and blue grama response was predominantly neutral or positive,
and depended largely on precipitation, though some studies indicated that season of fire
may also affect recovery (Ford 1999).
Arthropods and Small Mammals
There has been little research that directly addresses the effects of fire on animal communities in shortgrass steppe (Ford and McPherson 1996). Arthropods and mammals play important roles in the functioning of this ecosystem, serving as decomposers, pollinators, herbivores, predators, or prey. They cycle nutrients and form valuable links among trophic levels.
Numerous studies in other ecosystems (reviewed by Ford and McPherson 1996) 27
have indicated animal species, populations, and communities respond differentially to
disturbance by fire, due in part to the fact that fire can have both direct and indirect
effects. Direct effects are acute but ephemeral (e.g., fire-induced mortality). Indirect
effects (i.e., alteration in habitat) are long-lasting and usually more important. Therefore,
grassland fires may directly or indirectly elicit changes in population or community
structure. The magnitude of these changes depends on the vagility, life history and trophic
level of the animal, and the timing, extent, and intensity of the fire (Ford and McPherson
1996).
More than 1,200 insect species representing 11 taxonomic orders feed on grasses
in Arizona, New Mexico, Utah, Nevada and Colorado (Thomas and Werner 1981). Some arthropods are known to cause extensive damage to grasslands, however, most arthropod species are not agricultural pests, but beneficial components of rangeland ecosystems. In addition to serving as pollinators, parasites, and predators, some arthrop)ods are detritivores and have important roles in the decomposition of dead plant material and nutrient cycling. Furthermore, plant-feeding arthropods may even beneficially affect nutrient cycling rates (Lightfoot and Whitford 1990; Parmenter et al. 1994). Arthropods also serve as an important prey base for small mammals and birds. Grassland burning elicits a diverse array of responses by arthropods. The degree
of modification of arthropod populations by fire, the direction of change, and whether the
effects are acute or chronic vary with several factors (Warren et al. 1987). Some of the
main factors are fire characteristics, arthropod species, timing of the bum relative to
phenological stage of arthropod development, influence of the fire on predator/prey and
parasite/host ratios, post-bum weather, and the direction and degree of habitat change
(Warren et al. 1987). Responses of arthropods to season and frequency of fire also
appears to vary among species (Warren et al. 1987; Ford and McPherson 1996).
One example of the complex interactions between insects and fire is the response
of centipedes to fire. Centipedes are generally found in soil, or under bark or stones, or in
crevices of rotting logs. They feed primarily on other arthropods. Although their
immediate response to burning is probably minimal due to their choice of habitat, they
may be adversely affected during the recovery phase because of their dependence on other
arthropods for food (Warren et al. 1987; Ford and McPherson 1996).
The reaction of mammals to fire is a function of size and vagility. Most small mammals escape fires by hiding in burrows or rock crevices (Howard et al. 1959;
Heinselman 1973). The most common cause of death for small mammals during fire is a 29 combination of heat effects and asphyxiation. However, studies by Bendeil (1974) indicate that soil provides insulation from fire for burrowing animals (Kramp et al. 1983).
Other causes of death include physiological stress as mammals over-exert themselves to escape, trampling as large mammals stampede, and predation as small mammals flee from fire (Kaufman et al. 1990; Ford and McPherson 1996).
Grassland fires that temporarily remove food and cover (litter and standing dead vegetation) may be detrimental to small rodents immediately after fire (Daubenmire
1968; Kaufman et al. 1990). However, repopulation of such areas was reported to be nearly complete within six months (Cook 1959). Mice and rodent populations often increase after fire in response to increased availability of forb seeds and insects (Lyon et aJ. 1978).
In addition, burned areas often support more diverse animal populations than comparable unbumed sites, which may be a result of habitat diversity (Beck and Vogl
1972; Wirtz 1977). Omnivores and carnivores are attracted to bums by increased plant diversity and associated small mammal populations (Gruell 1980).
Kaufman et al. (1990) suggest that most effects of fire on small mammals in 30
grasslands are not neutral, with most mammal species being either "fire-positive" or "fire-
negative". "Fire-negative" mammals include species that forage on invertebrates in the
litter layer, species that live in relatively dense vegetation and eat plant foliage, and
species that use, at least partially, aboveground nests of plant debris.
"Fire-positive" mammals include species that use ambulatory locomotion in
microhabitats with a relatively open herbaceous layer and feed on seeds and/or insects
and that use saltatorial locomotion (Kaufman et al. 1990). They exhibit an increase in populations and habitat use after fire because of an increased availability of forb seeds, insects, newly greening vegetation, the creation of open areas in otherwise dense habitat, and an eventual increase in forb cover. Increases may occur immediately or gradually as the areas begin to revegetate and habitat diversity increases.
No studies have focused on the issue of seasonal effects of fire on small mammals. Numerous studies have examined the response of small mammals in spring and autumn or spring and winter bum plots (Bock and Bock 1978, 1983; Bock et al.
1976; Tester and Marshall 1961); however, these analyses focused on only the general effects of fire on small mammals, and no effects of season were evident (Kaufman et al.
1990). 31
Research Objectives, Questions, and Theoretical Hypotheses
Organisms, populations, communities, and ecosystems are differentially affected by disturbance based on the scale (both spatial and temporal) at which they occupy the landscape. Perceptions about their response are based on the scale at which the responses are measured. My experimental research on fire in shortgrass steppe examined the general effects of fire and season of fire on shortgrass steppe at multiple spatial and temporal scales and organizational units. My objectives were to evaluate ecosystem response (i.e., resilience) of shortgrass steppe to disturbance by fire relative to scale, and to explore consequent management implications. I achieved this by addressing the following questions and evaluating the following theoretical hypotheses.
Questions:
1) How quickly do different components of shortgrass steppe recover from
disturbance by fire- are all components equally resilient?
2) Does season of fire affect response?
3) Will results and conclusions vary with scale of reference?
Hypotheses:
1) Ha: If shortgrass steppe evolved with fire, then its various components 32
including microbiotic crusts, plants, arthropods, and mammals, should be
resilient to fire (i.e., recover quickly to conditions and relationships
existing prior to the disturbance).
Ho: Ecosystem components are not resilient to fire disturbance.
2) Ha: If the nature of fire (i.e., intensity, speed, uniformity) varies with season,
and susceptibility of organisms varies with season of fire, then fire season
should differentially affect response of ecosystem components based on
individual life histories and seasonal environmental conditions.
Ho: No difference in resp)onse regardless of season of fire. 33
STUDY AREA
Site Description
My study site is in shortgrass steppe of the southern Great Plains on the Kiowa
National Grassland (36° 30'N, 103° 7*W) of the Cibola National Forest in Union County,
New Mexico. The southern Great Plains includes the eastern third of New Mexico, the northern two-thirds of Texas, and most of Oidahoma (Wright and Bailey 1982). Almost all of the grassland on the plains in this region is composed of mixed or shortgrass communities (Brown 1994). While these communities have been considerably altered by grazing and the results of this practice (fire suppression followed by shrub invasion), much of the grassland remains an uncluttered perennial grass dominated landscape
(Brown 1994).
Shortgrass steppe (plains grassland) is the most extensive grassland in New
Mexico, making up approximately 50% of the state's grassland vegetation (Fig. I), (Dick-
Peddie 1993). It is estimated that less than 23% of true shortgrass steppe in the United
States still exists in native vegetation (National Grasslands Management Review Team
1995). My study site, located in the far northeast comer of New Mexico, is one such area
(Fig. 1). Out of 22 plant families and 99 plant species identified on my site, only three 34
are introduced species (Appendix B; Bleakly 1995).
My site consists of approximately 160 ha (400 acres) of shortgrass steppe that has
never been plowed, though it was grazed by livestock until 1990. The site is relatively
homogenous and nearly flat. Elevation ranges from 1,455 m (4,775 ft) at the southwest
comer to 1,472 m (4,830 ft) at the northwest comer of the site. Mean annual precipitation
is 391 mm (15.41 in), classifying the site as a semi-arid grassland (Lincoln et al. 1998).
The majority of precipitation occurs from May through September, with peak rainfall in
July. Annual precipitation was above average for 1997 and 1999, with 609 mm (24 in), and 660 mm (26 in) respectively; and slightly below average for 1998, with 387 mm
(15.26 in). Weather data was collected by the New Mexico State University at a climate station on the Clayton Livestock Research Center, located approximately 1.2 km from my study site.
Soil and Vegetation
The soil series for the area consists of approximately 5% Dioxice (Acridic
Calciustolls) loam, 25% Gmver (Aridic Paleustolls) loam, 25% Sherm (Torretic
Paleustolls) clay loam, and 35% Spurlock (Ustollic Calciorthids) loam (Maxwell et al.
1981). Most of the soil types contain pockets of other soil types resulting in a mosaic. 35
Overall, the deep, well-drained loam soils support an almost shrubless grassland with a relatively tight sod of buffalograss (Fig. 2) and blue grama (Fig. 3). These two species account for 85% of the plant cover throughout the site. Depending on the location on the site, galleta {Hilaria jamesii (Torr.) Benth.) ranges from 0 to 12% ground cover; bottlebrush squirreltail (Sitanion hystriv Nutt.) 0 to 8%; and sideoats grama
{Bouieloua curtipendula (Michx.) Torr.) 0 to 5% (Maxwell et al. 1981). Appendix B contains a comprehensive list of grasses found at the study site. Grass fine fuel was estimated to be 1,125 kg/ha (Paulette Ford, unpublished data). Estimates were obtained by clipping, drying, and weighing grass from 8, 10 m x 10 m plots adjacent to the study plots. 36
Figure 1. Distribution of grassland types in New Mexico (after Dick-Peddie 1993).
N
GIRASS\LA\NI\D !DESERT MlESA MONTANE IPlA~NS
Experimental Design
My experimental design was completely randomized, with 3 treatments, and 4
replicates per treatment (when resources were available, 5 replicates were used per treatment). Treatments were I) dormant-season fire in April 1997, 2) growing-season fire in July 1997, and 3) unbumed. Response variables were I) percent ground cover of litter, grass, herbaceous dicot (live/dead), shrub, cactus, microbiotic crust, and bare ground; 2) microbiotic crust nitrogen fixation, and chlorophyll a content; and 3) species richness, species abundance, and relative abundance of small mammals and arthropods.
1 randomly assigned treatments to 12 2-ha plots. Plots were 140 m x 140 m with at least 60 m of unbumed area between plots. Treatments were applied with drip torches by burning "black lines" around the inside perimeter of each bum plot. The interior of each plot was then burned using a strip headfire (Fig. 4). All fire treatments were implemented by the Southwest Region of the U.S. Forest Service. Winds were gusting at
5-10 mph when treatments were applied for both fire seasons. Dormant-season fire maximum flame height was 6-8 ft in the center of the plots, and each plot took approximately 15 minutes to bum completely. I estimated growing-season fire maximum flame height at about 2 feet, and plots took an average of 30-40 minutes to bum. 40
Sampling sessions were divided into five time periods. Period 1 = pre-treatment,
March 1997. Period 2 = post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = late June/July-October 1998. Period
5 = October 1999. Figure 4. Experimental fire treatment sequence. Top photos show establishment of "black lines" on perimeter of the plots, bottom left photo shows execution of strip headfire, and bottom right shows plot immediately after fire.
.. r.$.-.;------/ Ground Cover
To measure treatment effects on vegetation cover, I measured ground cover once
per month during all five sampling periods with one, lOO-m, 500-point, basal area line-
point transect per plot (a point was dropped every 20 cm). I randomly located the
transects, within the inner 100 mx 100 m area of the plots, with a pin flag toss. Exact
sample dates were March 24-25, 1997 (Period 1); April 28-30, June 17-21, 1997 (Period
2); August 7-10, September 17-25, and October 9-18, 1997 (Period 3); June 25-27, July
25-28, and October 20-30 1998 (Period 4); and October 3-7, 1999 (Period 5).
Cover categories included bare ground, litter, grass, herbaceous dicot (live/dead), shrub, cactus, and microbiotic crust. Conyza canadensis was included in the herbaceous dicot category. Categories were analyzed as absolute cover to examine how fire
treatments affected the p>ercentage of ground surface covered by vegetation.
Microbiotic Crust
Microbiotic crust was not differentiated from bare ground until sample Period 2.
In July 1997 and 1998, four to five microbiotic crust samples, and one soil sample were collected along the transects on all 12 plots. Soil was collected from bare ground, at a depth not greater than 1 cm, along the transects to measure background levels of nitrogen 43
fixation and chlorophyll a content. Each sample was collected in a 9 cm petri dish. Crust
and soil samples from Period 3 were analyzed for nitrogen fixation activity and
chlorophyll a content. Due to time and funding constraints, only crust samples, but not
soil samples, from Period 4 were analyzed for nitrogen fixation activity. Neither crust,
nor soil samples from Period 4 or Period 5 were analyzed for chlorophyll content.
Nitrogen fixation activity was measured using acetylene as a substitute substrate for nitrogen gas. Nitrogen-fixing organisms enzymatically reduce acetylene gas to ethylene gas which then is measured by gas chromatography. The presence of nitrogen gas in the incubation container does not significantly interfere with the reduction of acetylene. The ethylene can easily be measured by gas chromatography with great sensitivity providing a rapid and inexpensive assay system for nitrogen fixation activity.
Soil crust samples were exposed to acetylene using methods similar to those of Rychert and Skujins (1974).
Data were computed as nanomoles of ethylene formed by the crust samples/cm^/h.
The conversion to amount of nitrogen fixed from acetylene reduction was calculated as 3 moles of acetylene reduced to ethylene for 1 mole N2 -»^2NH3 Reduction of three molecules of acetylene per one molecule of nitrogen fixed is the commonly accepted 44 conversion to assess nitrogen fixation rates (Weaver 1986; Ladyman and Muidavin
1996). Amount of nitrogen fixed per ha/h was calculated', and converted to percent actual crust cover/ha/h. Yearly estimates of nitrogen fixation by soil crusts are difficult to calculate because they would depend on the percent of the area covered by crusts, in addition to the periods of suitable temperature, light, and moisture for activity, and the condition of the crusts.
Assays were conducted in 25 ml serum vials that had been modified by removal of the bottom of the vial. The serum vial was pressed into the crust sample to extract a subsample with an area of 6.16 cm^. The bottom of the vial was sealed with a rubber stopper and the crust saturated with ca. 3 ml of distilled water. Approximately 1.5 h after moistening the crust, the mouth of the vial was sealed with a serum stopper and acetylene gas was injected into the vial to obtain a 10% acetylene atmosphere in air. Crusts were incubated in a plant growth chamber at 25° C with illumination of approximately 280 jimol s ' mAfter an incubation period of 4 to 4.5 h, duplicate 0.25 ml gas samples were removed and ethylene measured by gas chromatography. Ethylene formed by crust samples was corrected for the presence of a small amount of ethylene as an impurity in
' I ha = 10® cm*, X nmoles Nj/cm^/h x 10® cm^ = X 10® nmoles Nj/ha/h. 1 nmole N, = 28 ng. 28 ng/nmoles x X 10® nmoles N/ha/h = 28X x 10® ng N/ha/h. 28X x 10® ng N/ha/h/10' ng/% = 2.8X g N/ha/h. This calculation assumes complete coverage by the microbiotic crust. 45
the added acetylene gas.
After the acetylene reduction assay, crust samples were stored in a refrigerator at
0-4° C, and subsequently a chlorophyll analysis was performed on most samples to
estimate the abundance of photosynthetic cryptogamic organisms present. Chlorophyll
was measured using the monochromatic method of Lorenzen (Wetzel and Likens 1991).
Crust samples were removed from the refrigerator and shaken in the dark in 90% acetone
for two h. Samples were then stored in the dark in a refrigerator, at 0-4° C, for 20-24 h.
The extract was then filtered and absorbance measured with a spectrophotometer.
Absorbance was measured at 650 nm before and after acidification of the sample. The absorbance at 750 nm was used to correct for the presence of turbidity in the sample.
Arthropods
I captured surface-active arthropods with pitfall traps, 1-pint paint cans set into the ground with the opening flush with the ground surface. Pitfalls were placed 30 m apart.
Propylene glycol was used as the preservative. Twenty pitfalls per plot, for a total of 240 pitfalls, were open two weeks, once per month from Periods 1-4 (March 1997, .April-
June 1997, July-October 1997, July-October 1998). Pitfalls are biased toward the capture of solitary wandering species and against those with low mobility (Uetz and Unzicker 46
1976; Baars 1979; Halsall and Wratten 1988) or that live in colonies (Marsh 1984).
Therefore, this collecting method by itself does not account for all of the site's diversity, even of surface-dwelling species.
Arthropods were identified to species, and number of individuals for each species was tallied. I used one order (Colepotera) in the arthropod analyses, out of the nine orders represented from collections on my site (Appendix C), because of the high diversity of both species and trophic groups represented by that order.
Small Mammals
I used Sherman live traps baited with rolled oats to trap small mammals (100 traps per plot, 1200 total) 5-7 nights, once per month from Periods 1-4 (March 1997, April-
June 1997, July-October 1997, July-October 1998). All 12 plots were trapped simultaneously. Plot checking and baiting sequence were rotated daily to allow traps on all plots to be open approximately the same amount of daylight time. I only trapped in the inner 100 m x ICX) m area of the plots. I marked mammals with ear tags and released them after recording species identification and body measurements.
Small mammal response was analyzed as total number of captures of unique individuals because I considered capture rates too low for mark-recapture density estimation, and my data could not satisfy a number of assumptions on which standard
population estimation models are based (i.e., no births or new entries into the population,
equal survivorship, equal catchability, no tag loss) (Amason et al. 1995; Schwarz and
Amason 1996).
Statistics
Monthly data were pooled into the five sample periods. Data were exclusively analyzed across treatments to explicitly test for fire effects within each sample period.
This was necessary because of unbalanced sample sizes and unequal sampling intensity between sample periods caused by extreme weather events (heavy rain, snow storms, hail, funnel clouds, high winds, lightning); in addition to seasonal fluctuations in animal populations, and extreme variation in precipitation between sample periods.
Data were tested for normality and were found to have both normal and non- normal distributions among the different sample periods. However, a normality assumption was difficult to assess empirically with only 4 replicates per treatment, therefore all data were treated as non-normal. Permutation (or re-randomization) methods in SAS PRCXr MULTTEST (SAS Institute Inc. 1988; 1989-1996) were used for 48 sets of three pairwise comparisons among treatments (unbumed, dormant-season bum and growing-season bum), for all response variables except microbiotic cmst nitrogen fixation rates and chlorophyll content, and one category of ground cover (Conyza canadensis). Permutation methods are recommended as the approach to obtain an overall analysis of an experiment. The test maintains a constant Type I error within and among all periods, and is robust to non-normality (Westfall et al. 1993).
Across treatment comparisons of acetylene reduction rates and chlorophyll content were made for Periods 3 and 4 with the Kmskal-Wallis test (SAS Institute Inc.
1988; 1989-1996), and the Dunn Procedure (Rosner 1995) was used for comparisons of specific treatment groups. Dunn's Procedure also maintains Type I error within the group of data to which it is applied. The Dunn Procedure used an adjusted p-value of <*/(k(k-
1), where 0.05, and k = number of groups compared. The Kmskal-Wallis test was also used for across treatment comparisons of Conyza canadensis density during Period 5.
Unless otherwise stated, all comparisons were considered significant at p = 0.05, and all values are reported as x ± SD. 49
RESULTS
Fire Treatments
Observation of experimental fire treatments during their application supported my prediction that there would be differential effects of fire on plots depending on fire season. Although differences were not measured, fires during the dormant season when fuel was dry and moisture was low appeared to bum hotter, faster, and more completely than growing-season fires. The growing-season fire appeared to bum unevenly and slowly, and it was more smoky and cooler because of the green vegetation and high soil moisture content. Treatment differences were visible in August 1997, three months after dormant-season fire, and one month after growing-season fire ( Fig. 5).
Ground Cover
Microbiotic Crust
Cyanobacteria were the main comp)onents of my microbiotic crust samples.
Microbiotic crust cover made up an average of 7% of total ground cover on my site.
Microbiotic crust cover never significantly differed among treatments for all periods
( Fig. 6, Table 1). Figure 5. Study Site: Post-treatment, August 1997. Dormant-season fire treated plots are light green growing-season fire treated plots are dark green and black. Buffer areas between plots are pale yellow. 51
Figure 6. Absolute ground cover(%): total number of hits per ground cover category /500 hits. Categories include grass, bare ground, litter, microbiotic crust, and other (herbaceous dicot live/dead, shrub, cactus).
Period 1 Period 2
lii > ~ 0 0 ,0 ,0 c: c ~ ~ 0 0 ~ ~ rf1. 20 10
unburned dormant growing unburned dormant Fire Treatment Fire Treatment
Period 3 Period 4
lii lii > > 0 0 ,0 ,0 c: c ~ ~ 0 0 ~ 30 ~ rf1. 20 10 0 unburned dormant growing unburned dormant growing Fire Treatment Fire Treatment
Period 5
c::JGrass ~Bare OIIDLitter im!Other -Crust
unburned dormant growing Fire Treatment
Period 1 =pre-treatment, March 1997. Period 2 =post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998. Period 5 = October 1999. 52
Table 1. MULTTEST comparison of microbiotic crust cover between fire treatments, and within time periods.
Period" Treatment COVER (%) 1 CONTRAST' P Value (N) Mean (SD) 1 1 1
Period 2 Unburned (5) 5(4) 1 U vsD 1.00 Dormant-season (5) 5(4) 1 1 1 Period 3 Unbumed (5) 10(2) 1 U vs D 0.69 Dormant-season (5) 8(4) 1 U vs G 0.17 Growing-season (5) 5(3) 1 D vs G 0.91 1 Period 4 Unbumed (4) 7(1) 1 U vsD 1.00 Dormant-season (4) 7(4) 1 U vsG 0.27 Growing-season (4) 3(1) i D vs G 0.27 1 Period 5 Unbumed (4) 6(4) 1 U vsD 0.99 Dormant-season (4) 5(4) 1 U vsG 0.51 Growing-season (4) 2(1) 1 D vs G 0.92
Period 2 = post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998. Period 5 = October 1999.
^ U = unbumed, D = dormant-season fire treatment, G = growing-season fire treatment. 53
Acetylene reduction of crusts from Period 3 significantly differed among
treatments, X-= 7.5, p = 0.02 (Table 2). The Dunn Procedure, with an adjusted alpha
level of 0.(X)8 and critical value z = 2.41, indicated dormant-season fire-treated crusts had
significantly lower rates of acetylene reduction than unbumed crusts (z = 2.65).
Growing-season fire-treated crusts did not significantly differ from unbumed (z = 0.97) or dormant-season fire-treated crusts (z = 1.81). There were no significant differences among treatments during Period 4, X'= 2.63, p = 0.2 (Table 2).
Chlorophyll a content of the crusts significantly differed among treatments of crusts from Period 3 (X*= 6.03, p = 0.04). The number of micrograms of chlorophyll a
/sample by treatment was unbumed x = 19, SD = 4.5; dormant-season fire x = 9, SD= 4; and growing-season fire x = 15, SD = 6.5. The Dunn Procedure, with an adjusted alpha level of 0.008 and critical value z = 2.41, indicated dormant-season fire-treated cmsts had significantly lower chlorophyll content than unbumed crusts (z = 2.45). Growing-season fire-treated crusts did not significantly differ from unbumed (z = 1.07) or dormant-season fire-treated cmsts (z = 1.37).
Crust-free soil samples collected from each plot during Period 3 did not have significant acetylene reduction activity (activity ranged from 0 to 0.007 nanomoles 54
ethylene/cm-/h), and had low or non-detectible chlorophyll content (contents ranged from
0 to 6.6 micrograms of chlorophyll a per sample).
Grass Pre-treatment (Period I/March 1997) grass cover was not statistically significantly
different between experimental plots. Dormant-season fire during Period 2 significantly
reduced grass cover compared to unbumed plots. By Period 3, approximately 2 months
later, however, plots burned in the dormant season did not significantly differ from
unbumed plots. Approximately two and a half years later there still were no significant differences in grass cover between unbumed and plots burned in the dormant season (Fig.
6, Table 3).
Growing-season fire during Period 3 significantly reduced grass cover compared to unbumed and dormant-season fire plots. One year later growing-season fire plots continued to have significantly lower grass cover than unbumed plots, but did not differ significantly from dormant-season fire plots. Approximately two years later (Period 5) there were no statistically significant differences in grass cover among treatments (Fig. 6,
Table 3). 55
Herbaceous dicot (live/dead), shrub, cactus
Herbaceous dicots, shrubs, and cactus made up on average less than 1% of ground cover at any given time on my experimental plots until 1999. During 1999 my study site was invaded by herbaceous dicots. During sampling Period 5, the dominant herbaceous dicot, Conyza canadensis (L.) Cronq. (horseweed) was conspicuously present on unbumed areas (Fig. 7), including the buffer areas between plots, and conspicuously absent on fire treated plots.
Statistical analysis of Conyza density revealed fire treated plots had statistically significantly lower levels of horseweed (X^ = 9.11, p = 0.01) than unbumed plots. The mean number of plants on unbumed plots was 25(35). Dormant-season fire treated plots had just 1 plant among them, and growing-season fire treated plots had no plants.
Bare ground
Bare ground gave basically the inverse of grass cover response. Pre-treatment
(Period 1) percent bare ground was not significantly different between experimental plots.
Dormant-season fire during Period 2 significantly increased bare ground compared to unbumed plots. By Period 3, approximately 2 months later, bare ground continued to be 56 significantly higher on dormant- season bum plots compared to unbumed plots, but did not differ from plots burned in the growing-season. Approximately one and a half years later there were no significant differences in bareground between unbumed and dormant- season fire plots (Fig. 6, Table 4).
Growing-season fire during Period 3 significantly increased bare ground compared to unbumed plots. One year later, plots bumed in the growing season continued to have significantly higher bare ground than unbumed plots, but did not differ significantly from dormant-season fire plots. Approximately two years later (Period 5) there were no significant differences in bare ground among treatments (Fig. 6, Table 4). Table 2. Mean microbiotic crust acetylene reduction (reported as nanomoles ethylene/cm~/h) by treatment and period, and estimated nitrogen fixation rate.
Sample Period Treatment ''nanomoles ^grams grams ethylene/cmV nitrogen nitrogen h (x, SD) /ha/h /actual crust cover/h Period 3, July 1997 Unbumed 2.97(1.79)" 2.77 0.27 Dormant-season 0.004 (.001)" 0.003 0.00024 Growing-season 0.82(1.63)'" 0.764 0.0382 Period 4, July 1998 Unbumed 0.08 i.oey 0.074 0.00518 Dormant-season 0.21 (0.23)" 0.196 0.01372 Growing-season 0.46 (0.38)" 0.429 0.01287
"'Means with the same letter are not significantly different.
^Calculation of grams nitrogen/ha/h assumes complete coverage by the microbiotic crust. 58
Table 3. MULTTEST comparison of grass cover between fire treatments and within time periods.
Period* Treatment Cover (%) 1 Contrast^ P Value (N) x(SD) 1 1 1 1 Unbumed (4) 66(9) 1 U vsD 1.00 Dormant-season (4) 64(4) 1 U vsG 0.95 Growing-season (4) 60(8) 1 D vsG 0.99 1 2 Unbumed (5) 69(5) 1 U vsD 0.0004 Dormant-season (5) 44(4) 1 1 1 3 Unbumed (5) 57(7) 1 U vsD 0.54 Domiant-season (5) 50(4) 1 U vsG 0.0001 Growing-season (5) 32(5) 1 D vsG 0.01 1 4 Unbumed (4) 64(3) 1 U vsD 0.18 Dormant-season (4) 54(3) 1 U vsG 0.003 Growing-season (4) 43(6) 1 D vsG 0.10 j 5 Unbumed (4) 66(6) 1 U vs D 0.92 Dormant-season (4) 74(7) 1 U vsG 1.00 Growing-season (4) 68(11) 1 D vsG 0.99
6 Period 1 = pre-ireatmcnl, March 1997. Period 2 = post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998. Period 5 = October 1999.
= unburned, D = dormant-season fire treatment, G = growing-season fire treatment. Figure 7. Slu !y Sile: Conyza canadensis Cro nqui st. October 1999 60
Table 4. MULTTEST comparison of bare ground between fire treatments, and within time periods.
Period® Treatment COVER (%) 1 CONTRAST' P Value (N) Mean (SD) 1 1 1 Period 1 Unbumed (4) 13(5) 1 UvsD 0.99 Dormant-season (4) 13(3) 1 U vsG 0.46 Growing-season (4) 20(6) 1 D vs G 0.73 1 Period 2 Unbumed (5) 8(3) 1 U vs D 0.02 Dormant-season (5) 18(3) 1 1 1 Period 3 Unbumed (5) 6(3) 1 UvsD 0.02 Domiant-season (5) 16(4) 1 U vsG 0.03 Growing-season (5) 16(4) 1 D vs G 1.00 1 Period 4 Unbumed (4) 5(2) 1 UvsD 0.29 Dormant-season (4) 15(3) 1 U vsG 0.005 Growing-season (4) 25(8) 1 D vs G 0.15 1 Period 5 Unbumed (4) 7(2) 1 UvsD 0.96 Domiant-season (4) 11(8) 1 U vsG 0.24 Growing-season (4) 17(4) 1 D vs G 0.76
s Period 1 = pre-treatment, March 1997. Period 2 = posl dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998. Period 5 = October 1999.
= unbumcd, D - dormant-season fire treatment, G = growing-season fire treatment. 61
Litter
Pre-treatment (Period 1) litter cover was not significantly different between
experimental plots. The only significant differences in litter cover between treatments
occurred during Period 3, when plots burned during the growing-season had significantly
lower litter cover than unbumed plots and plots burned in the dormant-season (Fig. 6,
Table 5).
Arthropods
Coleopteran samples from Periods 1 (March 1997) and 4 (July-October 1998)
were composed of 7 trophic groups, 29 families, 115 species, and 4,608 individuals
(Table 6; Appendix B). Ten species from 6 families, and 4 trophic groups (or some combination of the 4 trophic groups) made up 90% of the individuals. Tne trophic groups included detritivores (feeding on fragmented particulate organic-matter- detritus), omnivores (feeding on a mixed diet of plant and animal material), herbivores (feeding on plants- synonymous with phytophagous) and predators (feeding on animals) (Lincoln et al. 1998). The vast majority (75%) of beetles were solely, or occasionally phytophagous
(Tables 7, 8). 62
Table 5. MULTTEST comparison of litter cover between fire treatments and within time periods.
Period Treatment COVER (%) 1 CONTRAST" P Value (N) Mean (SD) 1 1 1 Period 1 Unbumed (4) 16(7) 1 UvsD 1.00 Dormant-season (4) 17(4) 1 U vsG 1.00 Growing-sezison (4) 18(3) 1 D vs G 1.00 1 Period 2 Unbumed (5) 23(6) 1 U vs D 0.16 Dormant-season (5) 33(4) 1 1 1 Period 3 Unbumed (5) 31(10) 1 UvsD 0.91 Dormant-season (5) 46(2) 1 U vs G 0.02 Growing-season (5) 25(4) 1 D vs G 0.001 1 Period 4 Unbumed (4) 22(1) 1 UvsD 1.00 Dormant-season (4) 22(5) 1 U vsG 0.83 Growing-season (4) 26(3) 1 D vs G 0.91 1 Period 5 Unbumed (4) 16(4) 1 UvsD 0.47 Dormant-season (4) 9(3) 1 U vsG 0.97 Growing-season (4) 12(6) 1 D vs G 0.98
10 Period I = pre-treatmeni, March 1997. Period 2 = post dormant-season fire. April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998. Period 5 = October 1999.
" U = unbumed, D = dormant-season fire treatment, G = growing-season fire treatment. 63
Pre-treatment (Period 1) measures of coleopteran species richness and abundance
revealed no significant differences among the 12 experimental plots (Tables 9, 10).
Approximately 18 months after dormant-season fire, and 15 months after growing-season
fire (Period 4), species richness significantly differed among treatments; plots burned in
the growing-season had a significantly higher number of beetle species compared to
unbumed plots (Table 10). However, abundance did not significantly differ among
treatments (Table 9).
A single species, Carpophilus lugubris (dusky sap beetle) made up 66% of the beetle individuals present (Table 7). The number of Carpophilus lugubris, a herbivore, did not significantly differ between untreated plots during Period 1 (March 1997) or between treatments during Period 4 (July-October 1998) (Table 11).
The next most abundant species, Agrypnus rectangularis (click beetle) made up
9% of the beetle individuals present (Table 7). Agrypnus rectangularis, a detritivore and omnivore, was not present during Period 1. There were no significant differences in abundance among treatments during Period 4 (Table 12).
There were no statistically significant differences in abundance during Periods 1 64
or 4 for the remaining 16% of beetle individuals analyzed (Table 13). These individuals
comprised three families and eight species and represented three trophic groups (Table 7).
The remaining 9% of species collected was not analyzed for abundance because it
generally consisted of 24 families represented by one specimen for each of 110 species.
Small Mammals
Nine species of small rodents have been identified from my site from 1995 through 1998 (Table 14). Trap success over approximately three years was estimated to be 2%. Approximately 1(X),800 trap nights resulted in 2,071 total captures. Onychomys leucogaster (northern grasshopper mouse), made up close to 50% of those captures, followed by Spermophilus tridecemlineatus (thirteen-lined ground squirrel) at 20% and
Reithrodoniomys montanus (plains harvest mouse) at 16%. The remaining six species each comprised less than 10% of captures (Table 14). Total number of individuals captured for all small mammals was 677, including 191 O. leucogaster, 186 S. tridecemlineatus, and 164 R. montanus, with a combined total of 136 individuals for the six other species (Table 14). 65
Table 6. Beetle (Coleoptera) families and associated trophic groups from Kiowa National Grassland Experimental Fire Research Study Site Period 1 (March 1997) and Period 4 (July-October 1998).
Family Common Name Trophic Groups (White 1983)
Anthicidae antlike flower beetles detritivorous Buprestidea metallic wood-boring beetles phytophagous Cantharidae soldier beetles predaceous,
phytophagous
Carabidae ground beetles predaceous,
omnivorous
Cerambycidae long-homed beetles phytophagous Chrysomelidae leaf beetles phytophagous Cleridae checkered beetles predaceous Coccinellidae ladybird beetles predaceous Cryptophagidae silken fungus beetles detritivorous Curculionoidea snout beetles, weevils phytophagous Dermestidae dermestid beetles carrion feeding,
omnivorous
Elateridae click beetles detritivorous,
omnivorous
Geotnipidae dung beetle carrion feeding,
detritivorous 66
Histeridae hister beetles predaceous
Hydrophilidae water scavenger beetles phytophagous,
detritivorous
Latridiidae minute brown scavenger fungivorous,
beetles detritivorous
Leiodidae round fungus beetles detritivorous Lycidae net-winged beetles predaceous,
detritivorous
Meloidae blister beetles phytophagous Melyridae soft-winged flower beetles predaceous Mordellidae tumbling flower beetles phytophagous Nitidulidae sap beetles phytophagous Scarabaeidae scarab beetles phytophagous,
detritivorous
Scraptiidae scraptiid beetles predaceous,
phytophagous
Silphidae carrion beetles carrion feeding,
predaceous
Silvanidae saw-toothed grain beetle granivorous Staphylinidae rove beetles predaceous,
detritivorous Tenebrionidae dariding beetles detritivorous,
phytophagous Trogidae skin/hide beetles carrion feeding,
detritivorous 68
Table 7. Beetle absolute and relative abundance (%): total number of individuals per species compared to the total number of individuals of all species combined.
Family Species Absolute Relative Abundance Abundance (%)
Carabidae'" Cicindela obsoleta 138 3 Pasimachus califomicus 185 4 Pasimachus obsoletus 46 1 Curculionidae'^ undetermined 46 1 Elateridae'"* Agrypnus rectangularis 415 9 Nitidulidae'^ Carpophilus lugubris 3,041 66 Scarabaeidae'^ Euphoria kemi 46 1 Neopsammodius interruptus 138 3 Phyllophaga glabricula 92 2 Tenebrionidae'^ Eusattus convexus 92 2 Other 369 8 Total 4,608 100
'-predaceous, omnivorous,
"phytophagous
'•'detritivorous, omnivorous
'^phytophagous, detritivorous 69
Table 8. Trophic group absolute and relative abundance (%): total number of individuals per trophic group compared to the total number of individuals of all trophic groups combined. Trophic Group Family Absolute Relative Combinations Abundance Abundance (%)
Detritivorous and Elateridae 415 9 Omnivorous
Detritivorous and Tenebrionldae 92 2 Phytophagous
Phytophagous Nitidulidae and 3,087 67 Curculionidae Predaceous and Carabidae 369 8 Ominvorous
Predaceous and Scarabaeidae 276 6 Phytophagous Other 369 8 Total 4,608 100 70
Table 9. MULTTEST comparison of beetle (Coleoptera) abundance (# individuals) between fire treatments, and within time periods.
Abundance
Period'® T reatment Abundance CONTRAST" P Value (N) Mean (SD)
Period 1 Unbumed (4) 42(28) U vsD 0.83 Dormant-season (4) 73(56) U vsG 0.98 Growing-season (3) 60(26) D vs G 0.99
Period 4 Unbumed (4) 297(80) UvsD 1.00 Dormant-season (4) 317(76) U vs G 0.91 Growing-season (4) 376(189) D vs G 0.97
'^Period 1 = pre-treatment, March 1997. Period 4 = July-October 1998.
'^U = unbumed, D = dormant-season fire treatment, G = growing-season treatment. 71
Table 10. MLXTTEST comparison of beetle (Coleoptera) richness (# species) between fire treatments, and within time periods.
Richness
Period** Treatment Abundance I CONTRAST" /* Value (N) Mean (SD) I
Period 1 Unbumed (4) 7(1) i U vs D 0.99 Dormant-season (4) 8(1) I U vs G 0.55 Growing-season (3) 10(4) I D vs G 0.68
Period 4 Unbumed (4) 16(3) I U vs D 0.75 Dormant-season (4) 20(3) I U vs G 0.04 Growing-season (4) 25(5) I D vs G 0.34
'^Period 1 = pre-treaiment, March 1997. Period 4 = July-October 1998.
"U = unbumed, D = dormant-season fire treatment, G = growing-season treatment. 72
Table 11. MULTTEST comparison of Carpophilus lugubris (dusky sap beetle) abundance between fire treatments, and within time periods.
Period^" Treatment Abundance CONTRAST^' P Value (N) Mean (SD)
Period 1 Unbumed (4) 27(27) U vsD 0.91 Dormant-season (4) 50(56) UvsG 0.99 Growing-season (3) 38(22) D vs G 0.99
Period 4 Unbumed (4) 223(76) U vsD 0.99 Dormant-season (4) 196(62) U vs G 0.99 Growing-season (4) 237(127) D vs G 0.97
'"Period I = pre-treatment, March 1997. Period 4 = July-October 1998.
''U = unbumed, D = dormant-season fire treatment, G = growing-season fire treatment. 73
Table 12. MULTTEST comparison of Agrypnus rectangularis (click beetle) abundance between fire treatments, and within time treatments.
Period" Treatment Abundance CONTRAST" P Value (N) Mean (SD)
Period 1 Unbumed (4) 0(0) U vs D 1.00 Dormant-season (4) 0(0) U vsG 1.00 Growing-season (3) 0(0) D vs G 1.00
Period 4 Unbumed (4) 5(3) U vsD 0.99 Dormant-season (4) 47(36) U vsG 0.99 Growing-season (4) 50(40) D vs G 0.97
-'Period 1 = pre-treatment, March 1997. Pericxl 4 = July-October 1998.
-'U = unbumed, D = dormant-season fire treatment, G = growing-season fire treatment. Table 13. MULTTEST comparison of Carabidae, Scarabaeidae, and Tenebrionidae abundance between fire treatments, and within time periods.
Period" Treatment Abundance I CONTRAST^^ /* Value (N) Mean (SD) I
Carabidae Period 1 Unbumed (4) 2(1) 1 U vs D 0.96 Dormant-season (4) 1(1) 1 U vsG 1.00 Growing-season (3) 2(2) 1 D vs G 0.94
Period 4 Unbumed (4) 44(22) 1 U vsD 0.98 Dormant-season (4) 38(17) 1 U vsG 0.51 Growing-season (4) 26(3) 1 D vs G 0.78
Scarabaeidae Period 1 Unbumed (4) 2(3) 1 U vs D 0.99 Dormant-season (4) 2(1) 1 U vsG 0.99 Growing-season (3) 1(2) 1 D vs G 1.00
Period 4 Unbumed (4) 12(3) 1 U vs D 1.00 Dormant-season (4) 20(13) 1 U vs G 0.37 Growing-season (4) 43(43) 1 D vs G 0.76
"•'Period 1 = pre-treatment, March 1997. Period 4 = July-October 1998.
U = unburned, D = dormant-season fire treatment, G = growing-season fire treatment. Table 13. Continued.
Period-^ Treatment Abundance I CONTRAST'^ Value (N) Mean (SD) I
Tenebrionidae
Period 1 Unbumed (4) 6(4) 1 U vs D 1.00 Dormant-season (4) 7(3) 1 U vsG 0.99 Growing-season (3) 7(4) 1 D vs G 0.99
Period 4 Unbumed (4) 5(4) 1 U vs D 0.99 Dormant-season (4) 4(2) 1 U vs G 0.77 Growing-season (4) 7(3) 1 D vs G 0.67 Significant differences were never detected in overall rodent species richness or abundance among treatments (Tables 15, 16). However, O. leucogaster, R. montanus, and S. tridecemlineatus did respond differentially to fire and fire season. O. leucogaster appeared to respond favorably to fire (Table 17). It tended to have higher numbers of individuals on fire-treaied plots; though the only statistically significant difference in abundance was between unbumed and growing-season fire plots one to three months after the growing-season fire treatments (Period 3). R. montanus responded negatively to both dormant-season and growing-season fire (Table 18). During Periods 2 and 3 it had significantly lower numbers of individuals on fire-treated plots than on unbumed plots.
5. tridecemlineatus tended to be neutral to fire (Table 19), there were never any significant differences in abundance among treatments. By Period 4 there were no statistically significant differences in abundance between treatments for any of the three species.
There were significant differences in overall relative abundance of O. leucogaster across treatments (Table 20, Fig. 8). The main differences in relative abundance occurred between growing-season fire and unbumed treatments; and dormant-season fire and unbumed treatments. Relative abundance did not differ significantly between dormant- and growing-season fire-treated plots. There was some evidence of variation across 77 treatments in overall relative abundance of R. montanus, but the differences were not significant (Table 20, Fig. 8). There was no evidence of treatment effects on overall relative abundance of 5. tridecemlineatus (Table 20, Fig 8). 78
Table 14. Small mammals from Kiowa National Grassland Experimental Fire Research Study Site 1995-1998.
Order Rodentia (rodents) # individuals
Family Cricetidae
Onychomys leucogaster. Northern Grasshopper Mouse 191 Peromyscus maniculatus. Deer Mouse 22 Reithrodontomys montanus. Plains Harvest Mouse 164 Sigmodon hispidus, Cotton Rat 10
Family Heteromyidae
Dipodomys ordii, Ord's Kangaroo Rat 4 Perognathus flavus. Silky Pocket Mouse 52 Chaetodipus hispidus. Hispid Pocket Mouse 46
Family Muridae
Mus musculus, House Mouse 2
Family Sciuridae
Spermophilus tridecemlineatus, 186
Thirteen-lined Ground Squirrel
Total 677 79
Table 15. MULTTEST comparison of small mammal abundance between fire treatments, and within time periods.
Period"^ Treatment Abundance CONTRAST" P Value (N) Mean (SD)
Period 1 Unburned (4) 7(2) U vsD 0.98 Dormant-season (4) 7(2) U vs G 0.84 Growing-season (4) 8(6) D vs G 0.86
Period 2 Unburned (4) 32(8) U vs D 0.32 Dormant-season (4) 23(2) U vs G 0.78 Growing-season (4) 28(12) D vs G 0.66
Period 3 Unburned (4) 23(3) U vsD 1.00 Dormant-season (4) 25(8) U vsG 0.13 Growing-season (4) 40(22) D vs G 0.28
Period 4 Unburned (4) 6(2) U vs D 0.93 Dormant-season (4) 7(3) U vs G 0.15 Growing-season (4) 11(6) D vs G 0.26
26 Period 1 = pre-treatmcnl, March 1997. Period 2 = post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998.
"^U = unburned. D = dormant-season fire treatment, G = growing-season fire treatment. 80
Table 16. MULTTEST comparison of small mammal richness between fire treatments, and within time periods.
Period^ Treatment # Species 1 CONTRAST-' P Value (N) Mean (SD) 1 1 1 Period 1 Unbumed (4) 3(1) 1 U vs D 0.79 Dormant-season (4) 3(1) 1 U vs G 0.99 Growing-season (4) 2(1) 1 D vs G 0.59 1 Period 2 Unbumed (4) 5(1) 1 U vs D 0.99 Dormant-season (4) 4(1) 1 U vs G 1.00 Growing-season (4) 5(1) 1 D vs G 1.00 1 1 Period 3 Unbumed (4) 5(1) 1 U vs D 0.99 Dormant-season (4) 5(1) 1 U vs G 0.90 Growing-season (4) 6(1) 1 D vs G 0.99 1 Period 4 Unbumed (4) 2(1) 1 U vs D 0.95 Dormant-season (4) 2(1) 1 U vs G 0.53 Growing-season (4) 3(1) 1 D vs G 0.95
28 Period 1 = pre-treatment, March 1997. Pericxl 2 = post dormant-season fire. April-June 1997. Period 3 = post growing-season fire. July-October 1997. Period 4 = July-October 1998.
= unburned, D = dormant-season fire treatment, G = growing-season fire treatment. 81
Table 17. MULTTEST comparison of Onychomys leucogaster abundance between fire treatments, and within time periods.
Period^ Treatment Abundance 1 CONTRAST^' P Value (N) Mean (SD) 1 1 1 Period 1 Unbumed (4) 1(2) 1 UvsD 0.98 Dormant-season (4) 2(1) 1 U vs G 0.27 Growing-season (4) 4(3) 1 D vs G 0.59 1 Period 2 Unbumed (4) 4(4) 1 U vs D 0.22 Dormant-season (4) 13(3) 1 U vs G 0.41 Growing-season (4) 11(8) 1 D vs G 0.99 1 1 Period 3 Unbumed (4) 4(2) 1 U vs D 0.68 Dormant-season (4) 9(2) 1 U vs G 0.04 Growing-season (4) 17(9) 1 D vs G 0.30 1 Period 4 Unbumed (4) 1(1) 1 UvsD 0.99 Dormant-season (4) 1(1) 1 U vs G 0.09 Growing-season (4) 4(3) 1 D vs G 0.20
30 Period 1 = pre-ireaimenl, March 1997. Pericxl 2 = post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998.
^'U = unbumed. D = dormant-season fire treatment, G = growing-season fire treatment. 82
Table 18. MULTTEST comparison oiReithrodontomys montanus abundance between fire treatments, and within time periods.
Period^" Treatment Abundance 1 CONTRAST" P Value (N) Mean (SD) 1 1 1 Period 1 Unbumed (4) 3(3) 1 U vs D 0.51 Dormant-season (4) 1(1) 1 U vs G 0.62 Growing-season (4) l(I) 1 D vs G 1.00 1 Period 2 Unbumed (4) 18(6) 1 U vsD 0.01 Dormant-season (4) 2(1) 1 U vs G 0.16 Growing-season (4) 9(6) 1 D vs G 0.29 1 1 Period 3 Unbumed (4) 15(1) 1 U vsD 0.009 Dormant-season (4) 6(4) 1 U vs G 0.003 Growing-season (4) 4(1) 1 D vs G 1.00 1 Period 4 Unbumed (4) 0(0) 1 U vs D 1.00 Dormant-season (4) 0(0) 1 U vsG 1.00 Growing-season (4) 0(0) 1 D vs G 1.00
32 Period 1 = pre-irealment, March 1997. Period 2 = post dormanl-season fire. April-June 1997. Period 3 = post growing-season fire, July-October 1997. Period 4 = July-October 1998.
= unbumcd, D = dormant-season fire treatment, G = growing-season fire treatment. 83
Table 19. MULTTEST comparison oi Spermophilus tridecemlineatus abundance between fire treatments, and within time periods.
Period^ Treatment Abundance 1 CONTRAST^' P Value (N) Mean (SD) 1 1 1 Period 1 Unbumed (4) 2(2) 1 UvsD l.CX) Dormant-season (4) 3(2) 1 U vsG l.CX) Growing-season (4) 3(3) 1 D vs G l.CX) 1 Period 2 Unbumed (4) 8(1) 1 UvsD 0.51 Dormant-season (4) 5(1) 1 U vsG 0.51 Growing-season (4) 5(2) 1 D vs G 1.00 1 1 Period 3 Unbumed (4) 1(1) 1 UvsD 0.48 Dormant-season (4) 3(2) 1 U vsG 0.11 Growing-season (4) 4(1) 1 D vs G 0.99 1 Period 4 Unbumed (4) 5(2) 1 UvsD 1.00 Dormant-season (4) 5(1) I U vsG 1.00 Growing-season (4) 5(1) 1 D vs G 1.00
34 Period 1 = pre-treatment, March 1997. Period 2 = post dormant-season fire, April-June 1997. Period 3 = post growing-season fire, JuJy-October 1997. Period 4 = July-October 1998.
= unburned, D = dormant-season fire treatment, G = growing-season fire treatment. 84
Table 20. MULTTEST comparison of overall relative abundance of Onychomys leucogaster (ONLE), Reithrodontomys montanus (REMO), and Spermophilus tridecemlineatus (SPTR) between fire treatments.
Species T reatment % 1 CONTRAST^ P Value (N) Mean (SD) 1 1 1 ONLE Unbumed (4) 13(4) 1 U vs D 0.04 Dormant-season (4) 36(16) 1 U vs G 0.007 Growing-season (4) 44(7) 1 D vs G 0.92 1 REMO Unbumed (4) 43(26) 1 U vs D 1.00 Dormant-season (4) 11(9) 1 U vs G 0.10 Growing-season (4) 14(13) 1 D vs G 0.16 1 1 SPTR Unbumed (4) 35(35) 1 U vsD 1.00 Dormant-season (4) 35(23) 1 U vs G 1.00 Growing-season (4) 25(13) 1 D vs G 1.00 1
= unbumed, D = dormant-season fire treatment, G = growing-season fire treatment. 85 Figure 8. Overall species relative abundance (%) across treatments. Species include Onychomys leucogaster (ONLE), Reithrodontomys montanus (REMO), Spermphilus tridecemlineatus (SPTR), and other (Peromyscus maniculatus, Sigmodon hispidus, Dipodomys ordii, Perognathusflavus, Chaetodipus hispidus, Mus musculus).
- ONLE ~REMO I . '''<'A SPTR c:::::J OTHER
unburned dormant growing
Fire Treatment 86
DISCUSSION
Ecological sustainability is the central goal of ecosystem management
(Christensen 1996). To achieve sustainability, ecosystems must be managed for multiple
organisms, and for processes that operate over a wide range of spatial and temporal
scales. With the objective of providing a scientific basis for management of shortgrass
steppe, and the ultimate goal of grassland ecological sustainability in mind, I examined
the effects of fire as a natural disturbance on multiple ecosystem components at multiple
spatial and temporal scales.
In general, my data indicated that fire did not affect microbiotic crust cover, but
did significantly affect acetylene reduction and chlorophyll a content of crusts depending
on fire season. Dormant-season fire appeared to significantly lower rates of acetylene
reduction and chlorophyll content, while growing-season fire did not. Grass response was
the inverse of crust response, growing-season fire significantly reduced grass cover, while dormant-season fire did not. Thirty months after fire there were no significant differences
in grass cover among treatments. Bare ground response was the inverse of grass cover response. The only significant differences in litter cover between treatments occurred immediately after the growing-season fire treatment. 87
Arthropod data indicated arthropod species richness significantly differed among
treatments; growing-season fire treated plots had a significantly higher number of beetle
species. However, beetle abundance did not significantly differ among treatments.
Significant differences were never detected in overall rodent species richness or
abundance among treatments. However, O. leucogasrer, R. montanus, and S.
tridecemlineatus populations did respond differentially to fire and fire season, but two and a half years later there were no statistically significant differences in abundance between treatments for any of the three species. Analysis of overall relative abundance of the three species showed a pattern of O. leucogaster being relatively more abundant and
R. montanus being relatively less abundant on fire-treated plots, and S. tridecemlineatus apparently unaffected by fire.
My results suggest: 1) shortgrass steppe has the ability to recover from fire relatively quickly, i.e., three to 30 months; 2) even in the short-term, plant and animal communities on burned and unbumed grasslands are relatively similar; 3) all ecosystem components that I measured are generally, but not equally resilient, and 4) season of fire does affect response. In addition, some fire effects can be immediately obvious, while other effects have a lag time between treatments and results, or are overshadowed by environmental variation. 88
While my research has indicated that fire season does differentially affect various
components of the ecosystem and can alter communities, most effects of fire in my study
were relatively short-term changes. Therefore, even though differential responses to fire
occurred on many different levels, the shortgrass steppe ecosystem still approximated conditions existing prior to the disturbance within 30 months after fire.
Because fire is a natural part of the shortgrass ecosystem, it is not surprising that shortgrass steppe's various components in my study were generally resilient to fire.
Because perceptions about resilience are strongly tied to scale of reference and the ecosystem component under study, it is also not surprising that my research showed that the perception about ecosystem resilience to fire is a function of the organizational unit studied and the length of time since disturbance.
Ground cover
According to the many definitions of resilience, shortgrass steppe can be considered resilient to fire; but all components of the ecosystem were not equally resilient at all scales of reference. Scale of observation (length of time after fire), affected perceptions about vegetation response to fire. Depending on the ecosystem component measured, and the length of time between sampling and fire treatment, shortgrass steppe 89
appeared to recover relatively quickly from fire, or not recover at all.
The response of grass cover to fire illustrates the point quite well. Grass cover did
not differ between unbumed plots and plots burned in the dormant season from three
months to two and a half years after fire treatment. In contrast, grass cover on plots
burned in the growing season still had not recovered from fire when sampling ended for
Period 4 in 1998. However, one year later (Period 5, 1999) there were no statistically
significant differences in grass cover among any of the treatments.
Overall, grass cover on my site recovered fairly quickly from fire, and the effect of
fire in the long-term was largely neutral. Dormant-season fire had little effect on grass
cover, but growing-season fire appeared to negatively impact grass cover for up to two
years after fire. The results of my research are consistent with the majority of studies on
fire response of buffalograss and blue grama, indicating a predominantly neutral response
to fire, dependent on rainfall, time since the fire, and season of fire (Ford 1999).
My results are also consistent with the results of studies predicting fire is differentially detrimental to plants based on their season of active growth. Therefore C4 plant species, like buffalograss and blue grama were predicted to be least vulnerable to 90
dormant-season burning and most vulnerable to burning early in the growing-season
because defoliation by fire reduces leaf area required for regrowth (Briske 1991; Briske
and Richards 1995).
Plants and microbiotic crust clearly responded differentially to season of fire.
This response depended on their individual life histories. Therefore it may not be
possible to maximize all ground cover responses to fire at the same time. For example, growing-season fire appeared to negatively impact grass. But at the same time, growing- season fire apf)eared to reduce the impact of fire on microbiotic crusts.
The growing-season fire occurred during July when vegetation was green and moisture was high. The dormant-season fire occurred in April, when moisture was low and fine fuel (vegetation) was dry. Therefore, my results are consistent with speculation by Johansen (1993) that more intense range fires during the dry months may be more damaging to microbiotic crusts than at other times of the year.
One year later, there were no significant differences among treatments in nitrogen fixation rates or percent crust cover. These results suggest that the ability of crusts to fix nitrogen in fire-treated plots was starting to recover, but levels for all treatments were still 91
far below levels of the unbumed plots in July 1997. One possible explanation for this
phenomenon is that 1998 had significantly lower rainfall than 1997. The difference in
precipitation between years may have overshadowed any fire effects.
Mean acetylene reduction for unbumed crusts from my site (2.97 nanomoles
ethylene/cm%), when compared to published values for microbiotic crusts from arid and
semi-arid regions, where measurements were made under similar laboratory or
greenhouse conditions, fell between those reported from Great Basin desert in Utah (0.78-
2.5 nanomoles ethylene/cm'/h ) (Rychert and Skujins 1974), and those reported from
desert grassland in New Mexico ( 5.5-9.4 nanomoles ethylene/cm"/h ) (Earp 1999).^^
Another example of differential response of vegetation to fire is that shown by
horseweed (Conyza canadensis). C. canadensis, a native of North America grasslands, is
a summer or winter annual. The height of Conyza varies with the habitat, but it may
reach a height of 6-10 feet (Montgomery 1973; IPM 1997). Horseweed is common in
pastures, meadows, cultivated fields, along roadsides and in waste areas. Conyza has been
reported to increase following fire (Engle et al. 1991). It is considered a pest in no-tillage
"Other published values include MacGregor and Johnson (1971) Sonoran desert in Arizona (78); Eskew and Ting (1978) Colorado desert in California, (11); and Earp 1999, gypsum hills, in New Mexico (16.8-41.3). 92
fields where it thrives because it needs an undisturbed habitat to complete its life cycle. It can invade very rapidly because it produces many seeds that can be dispersed by the
wind, and it is tolerant to many herbicides. The increase in herbaceous dicots, mainly
horseweed, on my study site was possibly due to increased precipitation during 1999.
Precipitation from January to October was already 218 mm above the annual average.
In October 1999, fire-treated plots had significantly lower levels of horseweed than unburned plots. This result is contrary to reports that horseweed increases following fire (Engle et al. 1991). However, disturbance by fire during a wet year, 1997, may have changed the seed germination environment between the unbumed and burned plots, or alternatively, decreased the seed bank availability for new populations, by interrupting the life cycle before seeds could be produced. Conyza flowers from July through October, and seedlings emerge in both fall and spring (Buhler and Owen 1997). Dormant- and growing-season fires would have killed both seedlings and mature flowering plants. Two and a half years after the 1997 fire treatments, fire's latent effects were manifested given the proper environmental conditions.
Arthropods and mammals
The organizational unit used to measure response to fire and the component 93 measured, also affect perceptions about resilience. Fire affected species abundance, richness, and relative abundance, but not uniformly across arthropod and mammal communities or fire treatments. Small mammal abundance and richness were unaffected by fire regardless of season. However, beetle species richness was significantly higher on growing-season fire-treated plots, but beetle abundance did not differ regardless of treatment. In addition, overall relative abundance of small mammals showed a pattern of certain species being relatively more or less abundant on fire-treated plots than was indicated by total small mammal abundance. Generally, relative abundance of beetles did not change. A single species, the dusky sap beetle ( C. lugubris) continued to made up approximately 66% of the beetle individuals present across treatments.
The higher beetle species richness on growing-season fire-treated plots was most likely due to the patchy nature of the bum, and the slow recovery of grass cover. These factors would increase species richness by increasing spatial heterogeneity within the area, and by creating gaps in communities that allow recolonization of the gaps by individuals of the same or different species.
Even though infrequent to moderately frequent disturbances enhance diversity, extremely frequent disturbances can be so destructive that they operate in the reverse to 94
reduce diversity; therefore, diversity is predicted to peak at intermediate levels of
disturbance (Connell 1978; Pianka 1994). The intermediate disturbance hypothesis
predicts that maximum species richness occurs at intermediate levels of disturbance because 1) high disturbance levels allow persistence of those species that are disturbance- adapted or in this case fire adapted, and 2) low disturbance levels allow competitive dominance by some species, causing local extinctions of others. However, many species can coexist and persist at intermediate levels of disturbance.
My data support that prediction. Fires during the dormant season, when fuel was dry and moisture was low, appeared to bum hotter and faster, and more completely than growing-season fires. Growing-season fires appeared to bum unevenly in a patchy manner, slow, smoky, and cool. Dormant-season fire represented a higher level of disturbance than growing-season fire, which represented an intermediate level of disturbance. Unbumed plots represented a low level of disturbance. Species richness was higher on plots of intermediate fire intensity than the more intensely burned plots, and almost twice as high as unbumed plots.
Small mammal species richness most likely did not respond in the same manner as arthropod richness due to the differences in the scale at which mammals use the 95
landscape. The fire-induced habitat changes may not have been on a large enough scale
(spatially or temporally) for small mammals species to increase in number. Fire may
have opened up more potential niches for beetles ranging in size in general from 2-25 mm
than for small mammals ranging in size in general from 100 to 297 mm. In addition, non-
volant small mammals may require more time to shift home ranges and respond to environmental cues than more mobile flying arthropods.
My arthropod results are somewhat similar to preliminary results of experimental research of fire effects on carabid beetles in plains grassland by Brantley and Parmenter
(unpublished data)^®. Their research was conducted on the Sevilleta Long-term
Ecological Research site in New Mexico, approximately 400 miles south of my site.
Their site is a desert grassland containing many components of shortgrass steppe, including blue grama. Treatment was a light bum in July 1993, with four replicates and unbumed areas. They suggest there was no response to fire treatment because most species were able to move out of the path of the fire and recolonize the area quickly.
They conclude stronger patterns were seen in response to seasonal change than to fire.
However, unlike my study, they did not actually test for seasonal effects of fire.
Data on file with Sevilleta LTER, New Mexico. 96
My study shows that fire has the potential to significantly alter species
composition of the small mammal component of the shortgrass steppe ecosystem.
Density and diversity of rodents are generally lower in shortgrass steppe than in other
North American grasslands (Grant and Bimey 1979; Stapp 1997), and my study site was
no exception, with an estimated 2% trap success. In general, my study indicated the abundance of "fire-negative" rodents (Reiifirodontomys montanus) decreased on fire treated plots, and the abundance of "fire-positive" rodents (Onychomys leucogaster) increased, while Spermophilus iridecemlineatus was neutral to fire.
My results are generally consistent with results from research on fire effects on the same rodent genera in different ecosystems. Studies of the western harvest mouse,
Reithrodontoniys rnegalotis, in annual grassland in California, and tallgrass prairie in eastern Kansas, also indicate that it is a "fire-negative" species (Cook 1959; Kaufman et al. 1990). Western harvest mice live mainly on seeds, inhabit dry weedy or grassy areas, and lend to nest on or above the ground (Whitaker 1994). Clearly fire would negatively impact this species by removing both its food source and nesting habitat.
The southern grasshopper mouse, Onychomys torridus, is considered a "fire- positive" species in sacaton grassland in southeastern Arizona, (Bock and Bock 1978; 97
Kaufman et aJ. 1990). Like O. leucogaster, it inhabits open areas, lives and nests in burrows and feeds primarily on grasshoppers (Whitaker 1994). Onychomys will most likely respond positively to fire because of increased open areas and increases in grasshoppers and other insects attracted to new green growth of vegetation following fire.
In addition, Onychomys are protected from the lethal effects of fire by their burrows.
The thirteen-lined ground squirrel, Spermophilus tridecemlineatus, has been considered a "fire-positive" species (Beck and Vogl 1972; Kaufman et aJ. 1990). S. iridecemlineatus inhabits open areas in shortgrass, and lives and breeds in burrows. It is an omnivore, eating insects, plants, and the flesh of birds and other rodents. It could be considered "fire-positive" for the same reasons as Onychomys. However, my research results strongly suggests it is "fire-neutral" at my site. My results are most likely due to the fact that S. tridecemlineatus had a relatively large home range, often covering 8 ha or more. Animals that mobile probably do not discriminate habitat on the scale of my 2-ha research plots.
Future Research and Management
Grasslands today are managed for a variety of organisms, including livestock, birds, reptiles, and mammals. The use of prescribed fire has increased recently, primarily 98 as a management tool to control invasions of woody plants into grasslands and to increase productivity of rangelands (McPherson 1995). My experimental research on the Kiowa
National Grassland provides a scientific basis for the use of fire as a management tool in shortgrass steppe of the southern Great Plains.
Based on my results, I feel the challenge to land managers who want to restore fire to shortgrass steppe is to acknowledge 1) the different components of ecosystems, 2) the differential effects of fire on these components, 3) that it may not be possible to maximize all ecosystem responses to fire at one time, with the choice depending on the management goal, and 4) that conclusions about resilience will vary with both temporal and spatial scales. My conclusions are consistent with those voiced by Allen et al. (1984), that management decisions must be made at appropriate temp>oral and spatial scales, in addition to being goal- and objective-specific.
My study is part of a long-term, 18-year experimental study to determine the optimal frequency and season of prescribed fire in shortgrass steppe. Treatments are composed of a combination of dormant- or growing-season fires and fire return intervals of 3, 6, or 9, years, and unbumed plots. The study examines the short- and long-term effects of fire frequency and seasonality on various ecosystem processes including plant 99
community composition, structure, diversity, and productivity; nutrient cycling dynamics;
as well as the effects on biotic crusts, arthropods and small mammals.
This long-term study will be a rich source of information for resource managers,
both for long-term fire effects and for the long-term monitoring data provided on the
unbumed plots. The study will allow managers to distinguish whether patterns in
population dynamics and changes in local diversity are responses to natural climatic
variation, as opposed to management practices. Additionally, it will allow evaluation of
the ability of organisms to adapt to a changing environment over the next 15 years.
My research site was selected as a candidate Research Natural Area (RNA) in
1991 because it represents the best known example of a reasonably large tract of blue
grama/buffalograss grassland in relatively "undisturbed" condition anywhere on Federally
owned lands in the southwestern United States (Dunmire 1991). The site, unlike
approximately 80% of shortgrass steppe in the United States, has never been plowed, has
not been grazed for almost ten years, and still contains most of its native vegetation.
Therefore, the state of most shortgrass stepjje is very different from that of my study site.
However, data from my research will provide a reference point along the continuum of
'^he RNA candidate status has been postponed until the completion of the 18-year fire research. 100 ecosystem response to fire in shortgrass steppe of varying levels of disturbance. 101
Appendix A. Primary Literature: Buffalograss {Buchloe dactyloides) and Blue grama {Bouteloua gracilis) Response to Fire (Ford 1999) Study area Method Grazing Fire ^^AP Blue grama Buffalograss and history date response response citation North Wildfires Little or Aug. 41 Field work No data Dakota, no 1954, cm/yr for the study Badlands domestic Sept. was done in livestock 1955, August (Dix 1960) May 1958. Blue 1958 grama frequency was relatively similar in burned and unbumed paired stands from 3 months to 4 years after fire.
South Experi No April 38 No data Buffalograss Dakota, mental domestic 1983, cm/yr standing crops Badlands fire livestock and/or were increased April for 2 to 3 years (Whisenant 1984 after burning. and Uresk 1990)
^°MAP = Mean annual precipitation 102
South Experi No April 34 Burning in No data Dakota, mental domestic and cm/yr April upland fire livestock Oct. reduced blue 1984, grama (Whisenant 1985 standing and Uresk crop after 1989) both the 1984 and 1985 fires. Burning in October reduced blue grama standing crop relative to unbumed plots when the next growing season was dry, but increased it when greater precipitation occurred during the next growing season. Blue grama standing crop was higher on burned plots in 1986 and 1987 compared to unbumed plots. 103
Texas, Experi No data Sept. 76 No data Buffalograss chaparral mental 1965 cm/yr increased fire significantly (Box et al. on burned 1967) plots across all treatments one year later. Texas, Experi No data Fall 76 No data In summer chaparral mental fire, cm/yr 1967, fire (Sept. buffalograss (Box and 1965) was more White Win abundant on 1969) ter fire combination (Dec. fall/winter 1966) bum plots, and un burned plots than on fall burned or winter burned plots, but statistically significant differences could not be shown. 104
Texas, Experi No data Fall 53 Seedstalk No data Hish mental 1965, cm/yr production Plains fire spring of blue and grama in (Trlica and fall 1967 was Schuster 1966, greater in 1969) 1967, plots burned summ two years in -er succession 1966 than on the unbumed control. Blue grama produced more seedstalks in 1966 than in 1965 regardless of burning treatment. Plant height went down in the first year after fire, but recovered by the second season- plant height was greater in plots burned in spring and summer of 1966 than in the unbumed control. 105
Texas, Experi Domestic March 48 No data Spring burning High mental livestock 23, cm/yr had no effect Plains fire 1970 on yields of buffalograss 3 (Heirman to 6 months and Wright later. 1973)
Texas, Experi Protected March 48-71 For all three For all three High mental from 15 to cm/yr years, blue years. Rolling fire domestic April grama yields buffalograss Plains livestock 7, were higher yields were 1968, on all three higher on all (Wright 1970, burned three burned 1974) 1972 versus versus unbumed unbumed sites. sites, but not but not significantly significantly so. so. 106
Kansas, Wildfires Light Nov. 43-58 Blue grama Buffalograss mixed domestic 1944, cm/yr basal cover basal cover prairie livestock March was reduced was reduced 1945 by 66% by 48% (Hopkins immediately immediately et al. 1948) after fire. after fire. By and fall 1946 thereafter buffalograss recovery of had almost blue grama completely was difficult recovered to to determine normal cover based on the and data production; presented. both yield and percent cover increased where buming occurred. while there was a decline in the unbumed area. 107
Montana, Experi No data Fall 34 Buming No data mixed mental 1978, cm/yr stimulated grass fire and blue grama prairie spring yield. In 1979^ mid-August (White and 1979, fall Currie buming had 1983) resulted in 60% more herbage than the control, and spring buming resulted in 40% more herbage than the control treatment. Blue grama cover was approximatel y the same for fall and spring bums and the control. 108
Nebraska, Experi Rested Late- 55 Post- Buffalograss Loess Hills mental from spring cm/yr treatment herbage yield fire domestic April measure did not (Schacht livestock 1980 ments were significantly and the year made in differ between Stubben- prior to 1980 and bumed and dieck the study 1981. Blue unbumed 1985) grama had plots. higher basal cover and herbage yields on bumed as compared to unbumed plots. 109
Nebraska, Wildfire No Fall, 50 Post-fire No data Sandhills domestic Oct. cm/yr measure livestock 1981 ments were (Morrison taken from et al. 1986) June- October 1982. Initially blue grama had greater phytomass in the bumed area than in the unbumed area, but from July- October had relatively less phytomass on the bumed site as compared to the unbumed site. no
New Wildfire Ungrazed April 39 For three No data Mexico, by 10, cm/yr years blue domestic 1964 following the grama- livestock fire, blue pinyon- grama % juniper cover was rangeland higher in burned areas (Dwyer than and Pieper unbumed 1967) areas. Production of grass was reduced by nearly 30% the first year, but had recovered by the second year. Ill
Kansas, Wildfire Lightly March 43-58 Measure Same shortgrass grazed 18, cm/yr ments were native 1959 made in late (Launch- pasture. surmner each baugh Burned year from 1964) and 1959-1961. unbumed A vegeta comparison tion were of mean protected yields from from bumed and domestic unbumed livestock plots shows that 1959 grass yields in buffalograss- blue grama mixture were reduced 65 % by the fire the first season. By the third year, herbage production of the buffalograss- blue grama mixture was not significantly different from that on unbumed sites. 112
Kansas, Experi Season- Early 81 Blue grama Buffalograss Flint Hills mental long spring cm/y mixed with over 10 years fire. March ear B. hirsuta declined in (Anderson annual 20, (hairy unbumed and et al. 1970) bums for mid grama) over late-spring 17 years. spring 10 years bum pastures. (1950- April remained at a but was stable 1966) 10, low steady in early- and late level in mid-spring spring unbumed bum pastures. May 1 pasture. Over 16 years. Early- and early- and late- mid-spring spring buming bum pastures reduced basal had higher cover. basal cover than late- spring bum pastures, and unbumed pastures. From 1956 to 1965 basal cover of blue and hairy grama was steady under all treatments except late- spring burning. where it declined slightly. 113
Appendix B. Initial plant survey: Experimental Fire Research Site, Kiowa National Grassland, Union County, New Mexico 1995. Nomenclature according to Kartesz (1994), * indicates introduced plant species, name in parenthesis indicates that the taxon's identity is in doubt because of lack of flowers and/or fruit for identification (Bleakly 1995).
TAXON and COMMON NAME
AGAVACEAE, Agave Family
Yucca glauca Nutt. ex Frasier, small soapweed yucca
ASCLEPIADACEAE, Milkweed Family
Asclepias engelmannii Woods, Engelmann milkweed
Asclepias latifolia (Torr.) Raf., broadleaf milkweed
Asclepias pumila (Gray) Vail, plains milkweed
ASTERACEAE (COMPOSFTAE) Sunflower Family
Ambrosia psilostachya DC., western ragweed
Artemisia ludoviciana Nutt., Louisiana wormwood
Berlandiera lyrata Benth., chocolate flower
Brickellia eupatorioides (L.) Shinners var. chlorolepis (Wott. & Standi.) B. L. Turner {Kuchnia chlorolepis Woot. & Standi.; Brickellia chlorolepis (Woots. & Standi.) Shinners), false boneset
Chaetopappa ericoides (Torr.) Nesom (Leucelene ericaides (Torr.) Greene, 114
rose heath
Chiysothamnus {parryi or nauseosus), rabbilbrush Cirsium ochrocentrum Gray, yeilowspine thistle
Conyza canadensis (L.) Cronq., Canadian horseweed
Dyssodia papposa (Vent.) A. S. Hitchc., fetid marigold
Engelmannia pinnatifida Gray ex Nutt., Engelmann daisy
Erigeron flagellaris Gray, trailing fleabane
Grindelia nuda Wood var. nuda (G. squarrosa (Pursh) Dunal var. nuda), curlytop gumweed
Gutierrezia sarothrae (Pursh) Britt. & Rusby, broom snakeweed
Helianthus annuus L., common sunflower
Heterotheca viilosa (Pursh) Shinners, hairy goldenaster
Hymenopappus sp., white ragweed iMctuca sp., lettuce
Liatris punctata Hook., dotted gayfeather
Lygodesmia juncea (Pursh) Hook., rush skeletonweed
Machaeranthera pinnatifida (Hook.) Shinners (Haplopappus spinulosus (Pursh) DC.), lacy tansyaster
Machaeranthera tanacetifolia (Kunth) Nees, tansyleaf aster
Ratibida columnifera (Nutt.) Woot. & Standi., upright prairie coneflower
Ratibida tagetes (James) Bamh., shortray prairie coneflower 115
Senecio riddellii Torr. & Gray, Riddell ragwort
Senecio neomexicanus (Gray), New Mexico groundiiel
Siephanomeria pauciflora (Torr.) A Nels., brownplume wirelettuce
Tetraneuris {scaposa (DC.) Greene) {Hymenoxys scaposa (DC.) Parker) stemmy hymenoxys, yellow daisy
Thelespemia megapotaniicum (Spreng.) Kuntze, Indian tea
*Tragopogon sp., salsify
Vemonia marginata (Torr.) Raf., Plains ironweed
Zinnia grandiflora Nutt., Rocky Mountain zinnia
BORAGINACEAE, Borage Family
Cryptantha sp., catseye
BRASSICACEAE (CRUCIFERAE), Mustard Family
Descurainia sp., tansymustard
Erysimum asperum (Nutt.) DC., Plains wallflower
CACTACEAE, Cactus Family
Echinocereus viridiflorus Engelm. Var. viridiflorus, green-flowered hedgehog cactus
Opuntia imbricata (Haw.) DC., walkingstick or tree cholla
Opuntia phaeacantha Engelm., brownspine or tulip prickly pear Opuntia polyacantha Haw., Plains prickly pear
CHENOPODIACEAE, Goosefoot Family
Chenopodium berlandieri Moq., pitseed goosefoot
Chenopodium incanum (S. Wats.) Heller, mealy goosefoot Chenopodium pratericola Rydb., desert goosefoot
Kochia scoparia (L.) Schrad., fireweed
Salsola kali L., Russian thistle, tumbleweed
CONVOLVULACEAE, Morning glory Family
Evolvuliis nuttallianus J. A. Schultes, shaggy dwarf moming-
Ipomoea leptophylla Torr., bush morning-glory
CUCURBITACEAE, Gourd or Cucumber Family
Curcurbita foetidissima Kunth, buffalo or coyote gourd
EUPHORBIACEAE, Spurge Family
Argythamnia mercurialina (Nutt.) Muell.-Arg., silverbush
Chamaesyce fendleri (Torr. & Gray) Small, Fendler sandmat
Chamaesyce lata (Engelm.) Small, hoary sandmat
Euphorbia marginata Pursh, snow on the mountain 117
FABACEAE (LEGUMINOSAE), Pea or Bean Family
Astragalus missouriensis (Nutt.), Missouri milkvetch
Astragalus mollissimus Torr., woolly milkvetch
Caesalpinia jamesii (Torr. & Gray) Fisher
*\felilotus officinalis (L.) Lam., yellow sweetclover
Psoralidium tenuiflorum (Pursh) Rydb. {Psoralea tenuiflora Pursh), wild alfalfa
Sop flora nuttalliana B. L. Turner, silky sophora
LOAS ACEAE, Loasa or Blazing-star Family
Mentzelia nuda (Pursh) Torr. & Gray, bractless blazingstar
Mentzelia reverchonii (Urban & Gilg) Thomps. & Zavortink, Reverchon blazingstar
MALVACEAE, Mallow Family
Spheralcea coccinea (Nutt.), scarlet globemallow
NYCTAGENACEAE, Four-o'clock Family
Mirabilis linearis (Pursh) Heimerl, narrowleaf four o'clock
ONAGRACEAE, Evening Primrose Family
Gaura coccinea Nutt. ex Pursh, scarlet gaura 118
PLANTAGINACEAE, Plantain Family
Plantago patagonica Jacq. (Plantago purshii Roemer «& J. A. Schultes), woolly plantain
POACEAE (GRAMINAE), Grass Family
Andropogon gerardii Vitmann, big bluestem
Aristida adscensionis L., six-weeks three-awn
Aristida purpurea Nutt. var.fendleriana (Steud.) Vasey, Fendler three-awn
Aristida purpurea Nutt. longiseta (Steud.) Vasey, red three-awn Aristida havardii Vasey, Harvard three-awn
Boihriochloa laguroides (DC.) Herter ssp. torreyana (Steud.) Allred & Gould {Andropogon saccharoides Sw. var. torreyanus (Steud.) Hack.), silver beardgrass or bluestem
Bouteloua curtipendula (Michx.) Torr. var. curtipendula, sideoats grama
Bouteloua gracilis (Willd. ex Kunth) Lag. ex Griffiths, blue grama
Bouteloua liirsuta Lag., hairy grama
*Bromus japonicus Thunb. ex. Murray, Japanese brome
Buchloe dactyloides (Nutt.) Engelm., buffalograss
Chloris verticillata Nutt., tumble windmillgrass
Elymus elymoides (Raf.) Swezey (Elymus longifolius (J. G. Sm.) Gould; Sitanion hystrix (Nutt.) J. G. Sm.), longleaf squirreltail
Erioneuron pilosum (Buckl.) Nash, hairy wooly grass, hairy tridens 119
Hilaria jamesii (Toir.) Benth., galleta
Muhlenbergia arenicola Buckl., sand muhly
Miihlenbergia torreyi (Kunth) A. S. Hitchc. ex Bush, ring muhly
Monroa squarrosa (Nutt.) Torr., false buffalograss
Panicum capillare L., wiichgrass
Panicum halli Vasey var. hallii. Hall panicgrass
Panicum obtusum Kunth., vine mesquite
Pasocopyrum smithii (Rydb.) Love (Elymus smithii (Rydb.) Gould; Agropyron smithii Rydb.)
Schedonnardus paniculatus (Nutt.) Trel., tumblegrass Schizachyrium scoparium (Michx.) Nash {Andropogon scoparius Michx.), little
bluestem
Sporobohts cryptandrus (Torr.) Gray, sand dropseed
Stipa sp., needlegrass
POLYGONACEAE, Buckwheat or Knotweed Family
Eriogonum annuum Nutt., annual buckwheat
PORTULACACEAE, Purslane Family
Portulaca sp., purslane
SCROPHULARIACEAE, Figwort Family 120
Penstemon sp., beardtongue
SOLANACEAE, Nightshade or Potato Family
Physalis hederifolia Gray var. comata (Rydb.) Waterfall, ivyleaf groundcherry
Solarium elaeagnifoliunt Cav., silverleaf nightshade
Solanum rostratum Dunal, buffalobur nightshade
VERBENACEAE, Vervain Family
Glandularia {Verbena) bipinnatiflda (Nutt.) Nutt., Dakota mock vervain 121
Appendix C. Surface-active arthropod species collected from Experimental Fire Research Site, Kiowa National Grassland, Union County, New Mexico 1996-1998.
TAXON
CLASS CHILOPODA (centipedes)
Order Lithobiomorpha (stone centipedes)
Family Lithobiidae
Lithobius fiarrietae Chamberlin
CLASS DIPLOPODA (millipedes)
Order Spirostreptida
Family Cambalidae
1 undetermined species
CLASS ARACHNIDA (arachnids)
Order Solifugae (sun spiders, wind scorpions)
Family Eremobatidae
Eremobates sp.
Order Opiliones (harvestmen, daddy-long-legs) 122
Family Sclerosomatidae
Trachyrhiniis marmoratus Banks
Order Araneae (spiders)
Family Theraphosidae (tarantulas)
Aphonopelma sp.
Family Mimetidae (pirate spiders)
Mimetus sp.
Family Theridiidae (comb-footed spiders)
Crustulina sticta O. Pickard-Cambridge
Latrodectus hesperus Chamberlin & Ivie
Steatoda sp. I
Sieatoda sp.2
Family Linyphiidae (line-weaving spiders)
linyphiid spp. 123
Family Tetragnathidae (thick-jawed orb-weaving spiders)
Pachygnatha dorothea McCook
Family Araneidae (orb-weaving spiders)
Araneus sp.
Larinia borealis Banks
Family Lycosidae (wolf spiders)
Allocosa morelosiana (Gertsch & Davis)
Alopeocsa kochi (Keyserling)
Geolycosa sp.
Hogna carolinensis (Walckenaer)
Pardosa xerophila Vogel
Schizocosa mccooki (Montgomery)
Schizocosa mimula (Gertsch)
Schizocosa minnesotensis (Gertsch)
Trochosa terricola Thorell
Varacosa gosiuta (Chamberlin) 124
Family Agelenidae (funnel-web spiders)
Agelenopsis longistyla (Banks)
Agelenopsis spatula_ Chamberlin & Ivie
Hololena hola (Chamberlin & Gertsch)
Family Hahniidae (hahnild spiders)
Neoantistea sp.
Family Dictynidae (dictynid spiders)
Cicurina sp.
Dictyna coloradensis Chamberlin
Dictyna personata Gertsch and Mulaik
Eniblyna comupeta (Bishop & Ruderman)
Family Titanoecidae (titanoecid spiders)
Titanoeca sp.
Family Oxyopidae (lynx spiders)
Oxyopes apollo Brady 125
Family Corinnidae (corinnid spiders)
Castianeira sp.
Family Gnaphosidae (ground spiders)
Drassodes gosiutus Chamberlin
Drassodes saccaius (Emerton)
Drassyllus dromeus Chamberlin
Drassyllus inanus Chamberlin & Gertsch
Drassyllus insularis group
Drassyllus lamprus (Chamberlin)
Drassyllus lepidus (Banks)
Drassyllus nannellus Chamberlin «& Gertsch
Gnaphosa clara (Keyserling)
Gnaphosa sericata (L. Koch)
Haplodrassus chamberlini Platnick &. Shadab
Nodocion rufithoracicus Worley
Talanites nr. capitosus (Gertsch & Davis)
Zelotes anglo Gertsch & Riechert 126
Zelotes gertsc/ii (Platnick & Shadab)
Zeloies tuobus Chamberlin
Family Philodromidae (running spiders)
Thanalus coloradensis Keyserling
Tibellus chamberlini Gertsch
Family Thomisidae (crab spiders)
Xysticus aprilinus Bryant
Xysticus gulosus Keyserling
Xysticus lassanus Chamberlin
Xysticus paiutus Gertsch
Family Salticidae (jumping spiders)
Habronattus geronimoi Griswold
Pellenes limatus Peckham «fe Peckham
Phidippus sp.
CLASS INSECTA (insects) Order Orthoptera
Family Rhaphldophoridae (camel crickets)
Ceuthophilus nodulosus Brunner
Ceuthophilus pallidas Thomas
Udeopsylla robusta (Haldeman)
Family Tettigoniidae (long-homed grasshoppers, katydids)
Conocephaliis strictus (Scudder)
Pediodectes stevensoni (Thomas)
Family Gryllidae (crickets)
Gryllus spp. - (pennsylvanicus or velelis or closely related species)
Oecanthus quadripunctatus BeutenmuIIer
Oecanthus sp.
Family Mogoplistidae (scaly bush crickets)
Cycloptilum comprehendens Hebard
Family Romaleidae (lubber grasshoppers) 128
Brachystola magna (Girard)
Family Acrididae (grasshoppers)
Ageneotettix deorum (Scudder)
Amphitomus coloradus (Thomas)
Arphia conspersa (Scudder)
Arphia pseudonietana (Thomas)
Aulocara femoratum (Scudder)
Cordillacris crenulata (Bruner)
Dactylotum bicolor (Thomas)
Dissosteira longipennis (Thomas)
Encoptolophus sordidus (Burmeister)
Eritettix simplex (Scudder)
Hadrotettix magnificus (Rehn)
Hesperotettix speciosus (Scudder)
Hesperotettix viridis (Scudder)
Hypochlora alba Dodge
Leprus wheeleri (Thomas)
Melanoplus arizonae (Scudder) 129
Melanoplus differentialis (Thomas)
Melanoplus gladstoni Scudder
Melanoplus lakinus (Scudder)
Melanoplus occidentalis (Thomas)
Melanoplus packardi Scudder
Melanoplus regalis (Dodge)
Mermiria bivittata (Serville)
Metator pardalinus (Saussure)
Opeia obscura (Thomas)
Phlibostroma quadrimaculatum (Thomas)
Plioetaliotes nebracensis (Thomas)
Psoloessa delicatula (Scudder)
Spharagemon equate (Say)
Syrbula admirabilis (Uhler)
Trachyrhachys aspera Scudder
Trachyrhachys kiowa (Thomas)
Trachyrhachys coronata Scudder
Trimerotropis pistrinaria Saussure
Tropidolophus formosus (Say) 130
Xanthippus corallipes Haldeman
Order Mantodea (mantids)
Family Mantidae
Litaneutria minor (Scudder)
Order Phasmatodea (walkingsticks)
Family Heteronemiidae
Diapheromera veli Walsh
Parabacillus sp.
Order Heteroptera (true bugs)
Family Tingidae (lace bugs)
Acalypta cooleyi Drake
Corythucha mollicula Osbom & Drake
Gargaphia angulata Heidemann
Family Miridae (plant bugs)
Lygus sp. 131
1 undetermined species
Family Nabidae (damsel bugs)
Nobis altematus Parshley
Family Reduviidae (assassin bugs)
Apiomeris spissipes (Say)
Barce uhleri Banks
Fitchia aptera Stal
Family Lygaeidae (seed bugs)
Atrazonotus umbrosus Distant
Cynius coriacipennis (Van Duzee)
Emblethis vicarius Horvath
Geocoris uliginosus Dowdy
Kleidocerys sp.
Lygaeus kalmi Stal
Neopamera bilobata (Say)
Nysius niger Baker 132
Slaterobius insignis (Uhler)
Family Coreidae (leaf-footed bugs)
Chariesterus antennator (Fabricius)
Family Alydidae (broad-headed bugs)
Alydus eurinus (Say)
Stachyocnemus apicalis Dallas
Family Rhopalidae (scentless plant bugs)
Liorhyssus hyalinus Fabricius
Family Cydnidae (burrowing bugs)
1 undetermined species
Family Thyreocoridae (negro bugs)
Galgupha sp.
Family Pentatomidae (shield bugs) 133
Coenus delius (Say)
Coenus nr. inermis Harris & Johnston
Family Scutelleridae (shield bugs)
Euptychodera corrugata (Van Duzee)
Order Coleoptera (beetles)
Suborder Adephaga
Family Carabidae (ground beetles)
Amara ellipsis (Casey)
Amara nr. idahoana (Casey)
Amblycheila cylindriformis (Say)
Cicindela punctulata Olivier
Cicindela obsoleta Say
Clivina impressifrons LeConte
Colliuris pennsylvanicus (Linnaeus)
Cyclotrachelus substriatus (LeConte)
Dicaelus laevipennis LeConte
Dyschirius globulosus (Say) 134
Geopinus incrassatus (DeJean)
Harpalus amputatus Say
Harpalus caliginosus (Fabricius)
Harpalus pennsylvanicus (De Geer)
Microlestes nr. nigrinus (Mannerheim)
Pasimachus califomicus Chaudoir
Pasimachus obsoletus LeConte
Piosoma setosum LeConte
Suborder Polyphaga
Superfamily Hydrophiloidea
Family Hydrophilidae
Tropistemus lateralis (Fabricius)
Family Histeridae (hister beetles)
Hister abbreviatus Fabricius
Saprinus sp.
Superfamily Staphylinoidea 135
Family Leicxlidae
Ptomaphagus texanus Melander
Family Silphidae (carrion beetles, burying beetles)
Nicrophorus guttula Mostschulsky
Family Staphylinidae
aleocharines undetermined below subfamily
Creophilus maxillosus (Linnaeus)
Tympanophorus sp.
Superfamily Scaraboidea
Family Trogidae (skin/hide beetles)
Trox suberosus (LeConte)
Trox scutellaris Say
Family Geotrupidae
Eucanthus lazarus (Fabricius) 136
Family Ochodaeidae
Ochodaeus sp.
Family Scarabaeidae (scarab beetles)
Canthon pilularius (Linnaeus)
Cremastocheilus knochi LeConte
Diplotaxis thoracicus Fall
Euphoria fulgida (Fabricius)
Euphoria histrionica Thomson
Euphoria inda (Linnaeus)
Euphoria kemi Haldeman
Hoplia laticollis LeConte
Ligyrus gibbosus (De Geer)
Neopsammodius interruptus Say
Onthophagus hecate (Panzer)
Paracotalpa puncticollis (LeConte)
Phyllophaga glabricula (LeConte)
Phyllophaga lanceolata (Say) 137
Superfamily Buprestoidea
Family Buprestidae (metallic wood-boring beetles)
Agrilus sp.
Superfamily Elateroidea
Family Elateridae (click beetles)
Aeolus livens (LeConte)
Agriotes sp.
Agrypnus rectangularis (Fabricius)
Family Lycidae (net-winged beetles)
Calopteron reticulatus (Fabricius)
Family Cantharidae (soldier beetles)
Belotus abdominalis (LeConte)
Chauliognathus pennsylvanicus (De Geer)
Superfamily Bostrichoidea
Family Dermestidae (carpet beetles) 138
Dermestes niamwratus Say
Superfamily Cleroidea
Family Cleridae (checkered beetles)
Enoclerns spinolai (LeConte)
Family Melyridae (soft-winged flower beetles)
Collops bipunctatus (Say)
Collops sp.1
Collops sp.2
Trichochrous sp.
Superfamily Cucujoidea
Family Nitidulidae (sap beetles)
Carpophilus lugubris Murray
Family Silvanidae (silvanid beetles)
Oryzaephilus surinamensis (Linnaeus) Family Cryptophagidae (silken fungus beetles)
Cryptophagus sp.
Family Coccinellidae (ladybird beetles)
Hippodamia convergens Guerin-Meneville
Hyperaspidius vittigerus (LeConte)
Hyperaspis gemma Casey
Hyperaspis inflexa Casey
Hyperaspis punctata LeConte
Hyperaspis quadrivittata LeConte
Family Latridiidae (latridiid beetles)
Corticaria sp.
Superfamily Tenebrionoidea
Family Mordellidae (tumbling flower beetles)
Mordella atrata Melsheimer
Family Tenebrionidae (darkling beetles) Asidopsis polita (Say)
Edrotes rotundas (Say)
Eleodes acutus (Say)
Eleodes extricatus (Say)
Eleodes fusiformis LeConte
Eleodes hispilabris (Say)
Eleodes obscurus (Say)
Eleodes obsoletus (Say)
Eleodes opacus (Say)
Eleodes suturalis (Say)
Enibaphion muricatum (Say)
Eusattus convexus LeConte
Glyptasida sordida (LeConte)
Hymenorus sp.
Lobometapon fusiformis (Casey)
Melanastus fallax (Casey)
Metaponium sp.
Stenomorpha consors (Casey)
Stenomorpha convexicollis (LeConte) 141
Family Meloidae (blister beetles)
Epicauta ingrata Fall
Epicauta partialis LeConte
Epicauta pennsylvanica (De Geer)
Family Anthicidae (antlike flower beetles)
Anthicus formicarius (Goeze)
Anthicus plectrinus Casey
Baulius tenuis LeConte
Family Scraptiidae (scraptiid beetles)
Anaspis rufa Say
Superfamily Chrysomeloidea
Family Cerambycidae (long-homed beetles)
Typocerus octonotatus (Haldeman)
Family Chrysomelidae (leaf beetles)
Acanthoscelides sp.
Altica sp. Dibolia sp.
Disonycha sp.
Galeruca sp.
Leptinotarsa decemlineata (Say)
Pachybrachis sp.
Paranapiacaba tricincta (Say)
Phaedon sp.
Psylliodes sp.
Saxinus sp.
Zabrotes sp.
1 undetermined species
Superfamily Curculionoidea
Family Curculionidae (snout beetles, weevils)
Cleonidius quadrilineatus (Chevrolat)
Gerstaeckeria sp.
Ophryastes sp.
Sphenophorus sp.
4 undetermined species"*'
Names in parenthesis indicate that the generic name changed since description, parenthesis indicate original name as author described. 143
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