FOFEM: The First-Order Fire Effects Model Adapts to the 21st Century
Technology is playing an increasingly pivotal role in the efficiency and effectiveness of fire management. The First Order Fire Effects Model (FOFEM) is a widely used computer application that predicts the immediate or ‘first-order’ effects of fire: fuel consumption, tree mortality, emissions, and soil heating. FOFEM’s simple operation and comprehensive features have made it a workhorse for fire and resource professionals who need to be able to predict, assess and plan for fire’s effects. Over the last decade FOFEM has undergone several upgrades as developers continue to improve function and expand applicability to meet the growing needs of managers, planners and analysts.
Latest First Order Fire Effects Model (FOFEM) upgrades include:
The FOFEM Mapping Tool which allows the import or input of spatial data layers,
Extensive additions to tree mortality models that expand scope and application,
A tree-mortality modification specifically for use in southeastern longleaf pine ecosystems, and
A web-based version with expanded function, storage, connectivity and customization options.
What’s the status?
Patches of flame and smoldering fuel linger as a fire nears its end. Combustion has consumed fuel and generated heat and smoke. But how much fuel and how much smoke? How hot did it get, and where? What does this all mean for trees, soil and air—right here, right now—and why does it matter?
The imprint of fire on an ecosystem doesn’t end when the flames go out. It’s easy to think of fire as an isolated event, but it’s actually a process. Fire’s effects reverberate through an ecosystem over time. The immediate effects, known as first-order fire effects, influence the way a burned area will respond and regenerate over the coming days, months, decades and even centuries. Effects that occur over these longer time spans are called second-order fire effects. First-order fire effects drive and shape second-order fire effects, creating a roadmap to a burned area’s future and helping to define fire’s role in natural ecosystem processes.
First-order fire effects drive and shape second-order fire effects, creating a roadmap to a burned area’s future and helping to define fire’s role in natural ecosystem processes.
Connecting the dots
First-order effects include plant injury and mortality, soil heating, fuel consumption and smoke production. Second-order effects include vegetation succession, erosion and the eventual atmospheric concentration and dispersion of smoke. Each individual first-order fire effect is an intersection of information connected to the others, and the future, by possibilities. What has taken place and which direction will things go from here?
Fuel consumption is an important first-order effect that’s intricately linked to the others, as well as to the future of the ecosystem. Fire consumes fuel, in turn producing smoke and generating heat. The intensity and duration of heat determine the degree of vegetation mortality and soil heating. The amount of plant mortality and soil heating influence vegetation dynamics after fire. The composition and structure of this post-fire vegetation community influence the behavior and extent of the next fire.
The details of this dot-to-dot picture are vitally important to resource managers. It’s their job to know about the past, current and future conditions of the ecosystems under their purview, and to be able to use that information to shape plans and guide decisions.
Over the years, the Forest Service and science communities have developed different methods and procedures for estimating first-order fire effects. Before the computer age, managers had to rely on experience and knowledge to make general estimations of fire’s immediate effects. Today, FOFEM provides managers with consistent and quantitative prediction methods.
FOFEM provides managers with consistent and quantitative prediction methods.
A quick study
In 1989, a new tool emerged from the Forest Service Fire Science Laboratory in Missoula, MT. Bob Keane, Elizabeth Reinhardt and Jim Brown created the first version of a simple computer program that would forever change the process of predicting and planning for the immediate effects of fire—the First Order Fire Effects Model known as FOFEM. It’s an all-purpose, easy to use, free, downloadable software package that allows users to quantify the immediate effects of fire. It differs from other first-order effects models in that it combines and integrates results from multiple empirical fire effects studies into one program. Keane explains that their design criterion, as put forth by Brown, was straightforward. “Learn it in and hour, run it in a minute,” he says. And apparently, they succeeded.
Since its inception FOFEM has been used by thousands of fire and land managers across the country from a broad spectrum of agencies. It’s been endorsed by the National Wildfire Coordinating Group and sponsored by the Washington Office of Fire and Aviation Management. It’s used for environmental assessment, fire severity assessment, development of fire and silvicultural prescriptions, and preparation of timber salvage guidelines.
The most significant version of FOFEM (v.4.0) was developed by Reinhardt and Keane in 1997 with Joint Fire Science support. It included the Albini BURNUP model which simulates heat transfer to fuels, consumption rate and resulting heat. BURNUP can also model heat transfer to other ecosystem components like the living tissue under tree bark, the mineral soil underneath the fire, or the smoke above it. “BURNUP is the heart of the whole model,” says Keane. “We run it for almost everything now.”
What it does
FOFEM has continued to evolve and is now in version 5.2. FOFEM fire effects analyses can guide prescribed fire activities and wildfire response, help design and evaluate treatments for desired and potential fire effects, and compare the potential ecological consequences of varying alternatives. It can simulate effects of different prescribed treatment alternatives and can be used to customize prescribed fire treatments to meet specific objectives.
FOFEM v5.2 can be downloaded to computers running a Microsoft Windows environment. Users can select analysis for tree mortality, fuel consumption, smoke or soil. A different input interface appears with each choice. Realistic default values are provided, or you can enter your own custom information. It generates results in reports or graph that are appropriate for inclusion in planning documents.
How it does it
FOFEM provides default fuel loads by fuel component (such as litter, duff, and woody fuel by size class). Default values depend on cover type and on fuel type (i.e., natural or slash fuels). The defaults are based on an extensive literature search summarized in the Mincemoyer Fuels Database, which is a major component of FOFEM. The defaults can be adjusted or replaced. Because fuels vary so much within cover type, Reinhardt recommends entering fuel loads directly if you can.
To predict tree mortality, users enter a tree list or stand table that lists species, diameter, height, crown ratio and trees per acre. Tree mortality increases with increasing crown scorch, and decreases with increasing bark thickness, so FOFEM uses bark thickness and the percentage of crown volume scorched for prediction. Bark thickness is derived from species and tree diameter. Crown volume scorch is calculated using tree height and crown base height, and scorch height or flame length.
Reinhardt recommends avoiding flame length as an input when possible, however. This is because scorch height will actually decrease for a given flame length at higher wind speeds typical of many wildfires. Entering flame length may cause over-prediction of scorch height—and therefore tree mortality. Using scorch height is especially appropriate when using FOFEM to predict fire effects after the fact, when scorch height can be directly observed.
When predicting stand mortality, FOFEM assumes that the fire is continuous across the entire area of concern. In the case of discontinuous or patchy fire, the user can estimate the proportion of area burned to adjust estimated tree mortality per acre.
Here again the model assumes continuous fire over the entire area of concern. As with tree mortality, if you’re dealing with patchy fire you should estimate the percentage of area burned and adjust per acre estimates. FOFEM predicts the quantity of fuel consumed by prescribed or wildfire for six different fuel components and predicts mineral soil exposed by fire as a result of duff and litter consumption. Consumption of different fuel types is predicted using a mix of empirical equations, rules of thumb and modeling. Although herbaceous fuels are generally a small component of fuel load, they are calculated by FOFEM because of their contribution to emissions. Calculated by rule of thumb, FOFEM assumes that 100 percent of herbaceous fuels are consumed. The exception is when spring is selected as the burning season, and grass selected as the cover type. Consumption then drops to 90 percent.
Shrub fuels are also modeled with rules of thumb. For example, if the cover type is sagebrush and the season is fall, shrub consumption is predicted at 90 percent. For all other seasons it drops to 50 percent.
When predicting canopy fuel consumption, FOFEM requires the user to estimate the proportion of a given stand that will be affected by crown fire. The consumption of crown fuels is represented for the purposes of estimating smoke production or carbon budget. FOFEM does not predict whether a crown fire will occur or if canopy layers will be consumed.
You can select very dry, dry, moderate or wet burn conditions. FOFEM applies default moisture percentages for each. You can enter fuel moistures directly for duff, 0.25 to 1 inch, and greater than 3 inch woody fuels. If you want to set fuel moistures for all woody fuel size classes, or separate moistures for sound and rotten fuel, you can bypass the FOFEM interface and use BURNUP.
BURNUP physically models heat transfer and burning rate of woody fuel particles as they interact over the duration of a burn. It estimates total fuel consumption by size class, as well as consumption rate and fire intensity over time. FOFEM uses BURNUP to predict woody fuel litter consumption (100 percent of litter is generally consumed) and smoke/emissions predictions.
BURNUP estimates flaming and smoldering consumption simultaneously in each time step. A fuelbed may produce flames in local concentrations of woody fuels at the same time that duff and isolated woody fuels burn in smolder combustion. Flaming and smoldering combustion burn with different combustion efficiencies and produce emissions at different rates. By modeling the two processes separately and simultaneously, BURNUP is able to take both into account in estimating emissions.
Fire intensity is derived from combustion of fuels in each time step, in turn determining fuel temperatures and combustion rates for the next time step. Immediately after ignition, intensity increases as the finest fuel burn. This generates more and more heat, progressively igniting larger and wetter fuel. As the smaller fuel burns up, intensity drops. The fire is assumed to go out when fire intensity is too low to sustain further combustion.
BURNUP computes different species of smoke emissions (chemical and particulate) in each time step. The FOFEM/BURNUP includes a graph and Smoke Emissions Report listing total emissions of PM2.5, PM10, CH4, CO, CO2, nitrogen oxide and sulfur dioxide. This information can then be used in other modeling systems to predict smoke dispersion and concentrations.
FOFEM predicts soil temperature over time at the soil surface and several depths below. It predicts expected average soil heating across the area because soil heating varies considerably within a burn unit. The model has been set up so that heat from surface fire (as modeled in prediction of fuel consumption) is used as the source of soil heat. If duff is present then the model assumes the duff is the source of soil heat. Duff fires have low intensity and spread much slower than flaming fire, but heating of deep soil layers is often greater in duff fires because they burn for a longer time in direct contact with the surface of mineral soil.
The graphic format of the soil heating report plots temperature vs. time, and displays temperature at several depths. Temperatures that exceed the 60°C (considered the lethal temperature for living organisms) are highlighted so you can identify which burning scenarios exceed this temperature at various soil depths. This lethal temperature is the default for the highlight, but you can change that by simply typing in a new number. The graph also includes the maximum temperature reached at the soil surface, the amount of duff consumed, the soil type, and starting soil temperature. The soil heating report contains a complete summary of FOFEM pre- and post-burn conditions, in addition to all the information displayed in the graph, which is useful for comparing scenarios.
New features and functions
FOFEM mapping tool
The new FOFEM MT (FOFEM Mapping Tool) will have the capacity to automatically import LANDFIRE spatial data layers. You will also have the option of entering any spatial data layers you want, from any source. This feature can be used to calculate fire effects across the landscape for use in fire and fuel hazard analysis. This is useful for prioritizing fuel treatment or burn recovery activities.
FRAMES online portal
FOFEM will soon be functional as an online tool that allows users to skip downloading and installation. It will be accessible via FRAMES (Fire Research and Management Exchange System) which adapts fire research and management tools for use in a web-based environment. FRAMES project manager Greg Gollberg selected FOFEM as one of the models to be modified for online ease of use. “It’s a solid, simple program. A lot of people are familiar with it and it’s been around for a while,” he says. “It gave us the chance to start out small and see how it goes. We have hopes for adding more function, data storage and exchange, and new customization options.” The FRAMES website will house not only the web version of FOFEM but all of the downloadable versions too.
Expanded scope for tree mortality
The FOFEM tree mortality module was developed with data from western conifer forests. Although it workswell in the western U.S., it’s commonly acknowledged that problems can arise with over-prediction of tree mortality when FOFEM is applied to other regions and forest types.
But plenty of work is underway to change that. Managers in the southeast will benefit from a new tree mortality model developed by Geoff Wang, with support from the Joint Fire Science Program and Clemson University. Wang created a modified version of FOFEM for use in longleaf pine and longleaf/slash cover types in the Southeastern U.S. Keane is hopeful that this will happen for other parts of the country too. “We constantly scour the literature for new tree mortality equations,” he says. “I’ve got file cabinets full of this stuff. When anyone does work on a new species it goes right into in the next revision.”
In addition, a team led by Sharon Hood at the Fire Modeling Institute at the Rocky Mountain Research Station in Missoula, is analyzing fire injury data on more than 16,000 trees from 82 wild and prescribed fires from 5 western states. They’re testing existing tree mortality models and developing new ones where necessary and incorporating it all into FOFEM.
Keeping pace with management needs
“The beauty of FOFEM is that it combines all the first-order effects under one roof,” says Keane. “The more we can add to it, the better off managers will be. It’s still the same nuts and bolts model. It still has the same guts. It’s just that it’s been repackaged again with new capacities. Next, we want to put in more emission elements and even more tree mortality. That will continue to increase applicability.”
So stay tuned for what are sure to be more changes and features that will keep FOFEM in the top tray of the fire planning and prediction toolbox well into the 21st century.
“The more we can add to it, the better off managers will be. It’s still the same nuts and bolts model. It still has the same guts. It’s just that it’s been repackaged again with new capacities.”
Publications and Web Resources
FOFEM download and tutorials:
Fire history and the establishment of oaks and maples in second-growth forests
Todd F. Hutchinson, Robert P. Long, Robert D. Ford, and Elaine Kennedy Sutherland
Abstract: We used dendrochronology to examine the influence of past fires on oak and maple establishment. Six study units were located in southern Ohio, where organized fire control began in 1923. After stand thinning in 2000, we collected basal cross sections from cut stumps of oak (n = 137) and maple (n = 204). The fire history of each unit was developed from the oaks, and both oak and maple establishment were examined in relation to fire history. Twenty-six fires were documented from 1870 to1933; thereafter, only two fires were identified. Weibull median fire return intervals ranged from 9.1 to 11.3 years for the period ending 1935; mean fire occurrence probabilities (years/fires) for the same period ranged from 11.6 to 30.7 years. Among units, stand initiation began ca. 1845 to 1900, and virtually no oak recruitment was recorded after 1925. Most maples established after the cessation of fires. In several units, the last significant fire was followed immediately by a large pulse of maple establishment and the cessation of oak recruitment, indicating a direct relationship between fire cessation and a shift from oak to maple establishment.
Résumé : Nous avons eu recours à la dendrochronologie pour étudier l’influence du feu dans le passé sur l’établissement du chêne et de l’érable. Six unités expérimentales ont été localisées dans le sud de l’Ohio où la lutte organisée contre les feux a débuté en 1923. Après que des peuplements eurent été éclaircis en 2000, nous avons collecté des sections radiales sur des souches de chêne (n = 137) et d’érable (n = 204). Dans chaque unité, l’historique des feux a été établi à partir des chênes et l’établissement du chêne et de l’érable a été étudié en lien avec l’historique des feux. Vingt-six feux ont été documentés de 1870 à 1933; par la suite, seulement deux feux ont été identifiés. L’intervalle médian de Weibull entre les feux variait de 9,1 à 11,3 ans pour la période se terminant en 1935; la probabilité moyenne d’occurrence de feux (années/ feux) pendant la même période variait de 11,6 à 30,7 ans. Parmi les unités, l’origine des peuplements remonte aux environs de 1845 à 1900 et pratiquement aucun chêne n’a été recruté après 1925. La plupart des érables se sont établis après que les feux eurent cessé. Dans plusieurs unités, le dernier feu important a immédiatement été suivi d’une importante vague d’établissement de l’érable et de l’arrêt du recrutement du chêne, indiquant qu’il y a une relation directe entre la cessation des feux et le changement marqué par l’établissement de l’érable au lieu du chêne.
Across much of the eastern United States, red maple (Acer rubrum L.), sugar maple (Acer saccharum Marsh.), and other mesophytic and (or) shade-tolerant species have become abundant in historically oak-dominated landscapes, threatening the continued dominance of oak (Lorimer 1984; Abrams 1992). Fire-control policies instituted ca. 1910 to 1930 often are considered a primary cause of these successional trends (e.g., Lorimer 1993).
Oaks are considered to be better adapted than maples to a regime of periodic fires primarily because of their relatively thick and, thus, fire-resistant bark; their ability to compartmentalize wounds caused by fire; and the capacity of established seedlings to continue to sprout after being top-killed repeatedly (Smith and Sutherland 1999; Johnson et al. 2002; Van Lear and Brose 2002). Periodic anthropogenic fire is widely considered to have promoted and sustained eastern oak ecosystems throughout their postglacial history (Abrams 2002). However, specific knowledge of past fire regimes, which can be obtained by analysis of fire-scarred trees, is limited to relatively few areas. Several studies show that fire was frequent in oak ecosystems prior to (Cutter and Guyette 1994; Guyette et al. 2003; Shumway et al. 2001) and after Euro-American settlement (Sutherland 1997; Schuler and McClain 2003; Guyette and Stambaugh 2004; Soucy et al. 2005) until fire control was instituted.
Received 8 August 2007. Accepted 8 November 2007. Published on the NRC Research Press Web site at cjfr.nrc.ca on 26 April 2008. T.F. Hutchinson,1 R.P. Long, and R.D. Ford. USDA Forest Service, Northern Research Station, 359 Main Road, Delaware, OH 43015, USA. E.K. Sutherland. USDA Forest Service, Rocky Mountain Research Station, 800 Block East Beckwith, P.O. Box 8089, Missoula, MT 59807, USA.
Much more is known about long-term patterns of tree establishment in old-growth oak forests. These studies often suggest a strong influence of fire cessation on tree recruitment (e.g., Abrams and Downs 1990; Abrams and Copenheaver 1999; Aldrich et al. 2005). Oak recruitment is known to have occurred for up to several hundred years but decreased or ceased around the time that fire control began. Several of these studies also document greatly increased recruitment of maples and other nonoak species during the same period (e.g., Abrams and Downs 1990; Abrams and Copenheaver 1999).
Shumway et al. (2001) were the first to document both the fire history and patterns of establishment for oak and other species in an old-growth oak-dominated stand in western Maryland. The authors showed that fire and oak recruitment were frequent from the early 1600s through the early 1900s. Both the cessation of oak recruitment and the increased recruitment of red maple and black birch (Betula lenta L.) coincided with reduced fire frequency ca. 1930. Soucy et al. (2005) showed that oak-hickory stands in the Arkansas Ozarks originated following harvesting or fire ca. 1900 and that fires were frequent through the 1930s. As fires became much less frequent after ca. 1940, oak recruitment ceased, and other shade-tolerant, nonoak species, such as flowering dogwood (Cornus florida L.), red maple, and blackgum (Nyssa sylvatica Marsh.), became established (Soucy et al. 2005).
The unglaciated ‘‘hill country’’ of southeastern Ohio was dominated by oak forests ca. 1800, just prior to Euro-American settlement (Beatley 1959; Gordon 1969; Dyer 2001). After nearly all of the forests in the region were cut over in the 19th century, many stands regenerated to oak dominance (Goebel and Hix 1997; Dyer 2001; Yaussy et al. 2003), and oak remains abundant in the region today (Griffith et al. 1993). However, as with most areas in the eastern United States that historically were oak dominated, the continued abundance of oak is threatened by increasing densities of maples and other species (e.g., blackgum and beech (Fagus grandifolia Ehrh.)) and poor oak regeneration. Dendrochronology fire histories indicate that fires occurred frequently in the region from ca. 1870 to 1935 (Sutherland 1997; McEwan et al. 2007b). It is hypothesized that this fire regime sustained oak dominance as second-growth forests developed (McEwan et al. 2007b) and that fire control directly facilitated the establishment of the now-abundant maples and other competitors (Sutherland et al. 2003).
To better understand how past fires were related to tree establishment, we conducted a dendrochronology study at the Ohio Hills site of the national Fire and Fire Surrogate Study (FFS). Our study was carried out on three replicate sites, each containing two separate units (*20 ha each) that here thinned. The second-growth forests were dominated by oak in the overstory, but maples and other shade-tolerant species were abundant in the midstory and understory. We collected basal cross sections from cut stumps of both oaks and maples to document stand fire histories and tree establishment. We hypothesized that, within a stand, temporal patterns of oak and maple recruitment would be closely related to the occurrence of past fires. Specifically, we hypothesized that (i) fires were frequent prior to the initiation of fire control, (ii) oak establishment occurred primarily before the initiation of fire control, and (iii) maples established primarily during the fire-control era. By studying units within three spatially separated replicate sites that likely had different fire histories, we also hoped to better understand how variability in past fire regimes affected oak and maple establishment. To our knowledge, this is the first study that directly examines the relationship between specific historic fire events and oak and maple recruitment events. A better understanding of how past fire regimes affected the pattern and pace of recruitment during stand development could provide new insights for the use of prescribed fire to manage oak forests.
Study area and site descriptions
The study area is in southern Ohio within the Southern Unglaciated Allegheny Plateau (McNab and Avers 1994). The topography is highly dissected, consisting of sharp ridges, steep slopes, and narrow valleys. The bedrock geology is predominantly sandstones and shales that produce well-drained and acidic soils.
The Ohio Hills FFS study site has three replicates (hereafter sites): one each in the Raccoon Ecological Management Area (REMA), Zaleski State Forest, and Tar HollowState Forest. The REMA site (39812’34@N, 82823’07@W) is in Vinton County and within the Vinton Furnace Experimental Forest; owned by Forestland Group, LLC, and comanaged with the USDA Forest Service Northern ResearchStation. The Zaleski site (39821’22@N, 82821’59@W), also in Vinton County, is 19 km north of the REMA site. The Tar Hollow site (39819’ 47@N, 82846’11@W) is in Ross County, 35 km west of the Zaleski site. Soils at both REMA and Zaleski are predominantly Steinsburg and Gilpin series silt loams (Typic Hapludalfs); Tar Hollow soils are predominantly Shelocta-Brownsville complex sandy loams (Typic Hapludalfs and Typic Dystrochrepts, respectively) (Boerner et al. 2007). Both state forests are managed by the Ohio Department of Natural Resources’ (ODNR) Division of Forestry.
Human land use has had a major effect on these forests. Both the REMA and Zaleski sites are located near charcoal iron furnaces that operated in the 1800s. REMA is <2 km from Vinton Furnace and Zaleski is <4 km from Hope Furnace; these were in operation from 1853 to 1883 and from 1854 to 1874, respectively (Stout 1933). Forests at both sites presumably were harvested at least once to provide charcoal for iron smelting. The Tar Hollow site was not affected by the iron industry since it was more than 25 km from the nearest furnace. Land deeds show direct human occupation in small parcels within the Tar Hollow study site until the mid-1930s (ODNR, Division of Forestry, District Office, Chillicothe, Ohio).
The forests generally were similar in structure and composition across the three sites. Prethinning data collected in 2000 showed that mean stand basal area at REMA was 28 m2/ha; white oak (Quercus alba L.) accounted for 21% of the basal area; black oak (Quercus velutina Lam.), 17%; chestnut oak (Quercus montana Willd.), 15%; and scarlet oak (Quercus coccinea Muenchh.), 12% (D.A. Yaussy, USDA Forest Service, Delaware, Ohio, unpublished data).
Mean basal area at Zaleski was 27 m2/ha and was dominated by chestnut oak (31%), followed by white oak (22%), red maple (13%), and black oak (13%). At Tar Hollow, mean basal area was 32 m2/ha, and the dominant species were chestnut oak (33%), white oak (20%), and black oak (16%). Oak site indices (base age 50 years) are variable across the landscape because of the dissected topography, ranging from about 17 m (55 ft) on upper south-facing slopes to 24 m (80 ft) on lower north-facing slopes (D.A. Yaussy, USDA Forest Service, Delaware, Ohio, personal communication). On all sites, the sapling layer (1.4 m tall to 9.9 cm diameter at breast height (DBH)) and the midstory (trees 10-25 cm DBH) were dominated by shade-tolerant trees, the most abundant of which were red maple, sugar maple, blackgum, and beech (Albrecht and McCarthy 2006). Shade-tolerant trees >25 cm DBH occurred at low densities on all sites.
The mean annual temperature and precipitation are 11.3 8C and 1024 mm, respectively. Precipitation is distributed fairly evenly throughout the year with no months averaging <60 mm. Today, most fires occur during the early spring (March and April) and fall (October and November), when vegetation is predominantly dormant; spring dormant season fires are the most frequent (Haines et al. 1975; Sutherland et al. 2003), and nearly all fires are anthropogenic in origin.
At each FFS site, four treatment units (19-26 ha) were established: an untreated control (control), mechanical thinning (thin), prescribed fire (burn), and a combination of thinning and fire (thin+burn). Our dendrochronology study was conducted on the two thinned units (thin and thin+burn) at each site. Midstory thinning occurred from November 2000 to April 2001 and favored the retention of dominant and codominant oaks. However, to meet commercial thinning objectives, some dominant and codominant oaks were harvested. Across sites, stand density (trees ‡10 cm DBH) was reduced by 32% from a mean of 400 to 269 trees/ha, and tree basal area was reduced by 30% from a mean of 29 to 20 m2/ha.
Sampling design and field methods
At the REMA site, the two thinned units (hereafter, REMA 2 and REMA 3) were separated by a triangular wedge of untreated forest that ranged in width from several meters to 275 m. The Zaleski thinned units (Zaleski 2 and Zaleski 3) were contiguous, and the boundary between units was an intermittent stream drainage. The Tar Hollow thinned units (Tar Hollow 2 and Tar Hollow 3) also were contiguous, but the boundary did not follow a major topographic feature. Despite the contiguous units at Zaleski and Tar Hollow, we treated the units separately for summary and nalyses, because 50% (14 of 28) of the fires that we document were recorded only in a single unit.
Ten 0.1 ha plots were established in each unit to monitor vegetation and soils for the FFS study. Plot corners were georeferenced with global positioning system (GPS) technology. The plots were distributed across the landscape to represent a continuous range of soil moisture conditions from dry (upper south-facing slopes) to mesic (lower north-facing slopes). In 2000, all overstory trees (‡10 cm DBH) were tallied by species and DBH on each plot prior to treatments. We focused our collection of oak and maple basal cross sections on the plots to utilize the tree data and georeferenced locations.
Full basal cross sections were cut from stumps with a chainsaw from December 2000 to May 2001, soon after thinning operations had been completed in each unit. All oak stumps in a plot were examined for the presence of wounds (discoloration, seams, staining, and wound wood ribs) that might indicate a fire event (Smith and Sutherland 1999). We attempted to locate at least two oak stumps within or adjacent to each plot. We collected 137 oak cross sections across all units and recorded the upslope position on each. Samples included 64 white oak, 40 chestnut oak, 22 black oak, 7 scarlet oak, and 4 northern red oak (Quercus rubra L). All samples were cut at a height of about 5-10 cm aboveground. The mean basal diameter of the oak samples was 47.4 cm and ranged from 23.1 to 98.1 cm. We mapped the approximate location of each sample based on its position within or adjacent to a georeferenced vegetation plot.
To determine the temporal pattern of maple establishment, our objective was to collect basal cross sections from three stumps in and (or) adjacent to each plot. Our goal was to collect three maples for every two oaks, because maples were approximately 1.5 times as abundant as oaks in the midstory, where the thinning treatment was focused. Our first priority was to obtain larger maples to document the time when establishment began, but we sampled across a range of maple stump diameters. We collected 30-39 maples per unit for a total of 204 (142 red maple and 62 sugar maple). Nearly all sugar maple samples were collected in three units: Tar Hollow 2 (n = 27), Tar Hollow 3 (n = 20), and REMA 3 (n = 15). The mean basal diameter of maple samples was 27.5 cm and ranged from 10.1 to 58.4 cm.
Cross sections were planed and sanded to enhance ring boundaries and facilitate dating. Each oak sample was crossdated using skeleton plots (Stokes and Smiley 1968) against a previously established master chronology for the region (Sutherland 1997). Maple cross sections ‡70 years old also were skeleton plotted and cross-dated. Younger maple samples were ring-counted along two to four radii and crossdated by identification of key stress years. Several factors contributed to make the exact pith dates for maples somewhat less precise than that for the oaks. Firstly, the crossdating was less clear for maples than for the oaks, i.e., key stress years were not as consistent among the maples. Secondly, a small proportion of the maples had decay or incipient decay in or near the pith, which obscured the ring boundaries. Thirdly, some maples had rings that were locally absent in a portion of their circumference, a common phenomenon documented by Lorimer et al. (1999) for suppressed sugar maple trees. Several samples that we felt could not be reliably dated (primarily small suppressedstems) were omitted from further analyses.
We required at least three scarred samples per unit per year to classify a wound event as a fire scar and, consequently, a year as a fire year. If only two wounds were present in a unit in a given year but the adjacent unit showed evidence of a fire in the same year (three or more samples scarred), we recorded a fire for the unit with only two scars (this occurred once). These criteria were applied to limit the likelihood that wounds caused by other factors (e.g., logging, falling trees and branches, or animals) were recorded as fire scars (see McEwan et al. 2007a). The seasonality of each fire event was determined by examining where the wounds intersected the annual growth ring. For dormant-season scars (located between annual growth rings) it was not possible to determine whether the scar occurred in the fall after the previous growing season or in the late Hutchinson et al. winter – early spring prior to the upcoming growing season (Sutherland 1997). Because fires in our region are most frequent in the early spring dormant season (March-April), we assigned dormant-season wounds to the calendar year of the upcoming growing season. For example, a dormant-season wound located between the 1922 and 1923 annual growth rings was recorded as a 1923 wound.
To better examine how the relative intensity and (or) extent of fires may have affected tree establishment, we defined fires as ‘‘significant’’ if (i) ‡33.3% of the samples exhibited wounds and (ii) at least five samples had wounds. Since little is known about the relationship between fire intensity and scarring in oaks (see Smith and Sutherland 1999; Guyette and Stambaugh 2004; McEwan et al. 2007a), this definition provides a relative measure of the intensity and extent of the fires within this study. We mapped the location of all samples (oaks and maples) in all fire years at REMA to visualize the spatial pattern of fire scars and tree establishment across the landscape. We used the ArcView version 3.2a geographic information system to map samples based on our field maps that showed locations within or adjacent to a georeferenced vegetation plot. We selected eight of the nine fire years at the REMA study site to illustrate spatial patterns of fire scarring and tree establishment.
Ring widths were measured on the oaks so that growth dynamics and potential release events could be determined. Oak cross sections were scanned and measured using WINDENDRO (Regent Instruments Inc., Ste-Foy, Que.). Two radii approximately 1808 apart were measured in each cross section. Radii were located to minimize the influence of wounds and associated wound wood on growth measurements. Ring-width measurements and crossating were verified with the program COFECHA 2.1 (Holmes 1983; Grissino-Mayer 2001b). The program ARSTAN (Cook and Kairiukstis 1990) from the Lamont Doherty Earth Observatory’s Tree-Ring Laboratory, was used to detrend measurements with a negative exponential curve or linear regression line. This standardization procedure removes the growth trend associated with age and produces dimensionless indices that can be averaged to create a master chronology for a site (Fritts 1976). A master chronology was created for each of the six sampled sites.
Potential releases associated with disturbance events were identified in each master chronology with the JOLTS program (Holmes 1999) from the International Tree-Ring Data Bank Dendrochronology Program Library. Major releases were those where there was a >100% increase in growth expressed as the mean chronology ring-width index over a 15 year period compared with the mean chronology ringwidth index in the preceding 15 year period. Minor releases were those where growth increased 50% over a 10 year period compared with a previous 10 year period (Lorimer and Frelich 1989; Soucy et al. 2005). We report release events only when there were at least 10 trees present in the master chronology. Fire-return interval analyses Data on fire history derived from oak cross sections were analyzed using the FHX2 program (Grissino-Mayer 2001a, 2004). Because fires were so infrequent after 1935, it was not possible to statistically compare fire frequency between pre- and post-fire suppression periods. Instead, for each study unit, we calculated fire intervals from the first fire to 1935 (before and during the early fire-control period) and compared these with fire intervals from the first fire to 2000. Both mean fire intervals (MFI) and Weibull median fire intervals (WMFI) were calculated. The latter is considered a better estimator of central tendency for the typically nonnormal fire-interval distributions (Grissino-Mayer and Swetnam 1997; Grissino-Mayer et al. 2004).
For each unit, we also calculated the mean fire occurrence probability (MFOP) for two periods (stand origination to 1935 and to 2000). Defined by Guyette et al. (2006), MFOP is the number of years divided by the number of fires in a chronological period. Guyette et al. (2006) calculated the MFOP to account for the fire-free period prior to the first recorded fire. For each site, we defined the stand origination as the first year in which at least four samples were present that could potentially record a fire.
Twenty-eight fires were recorded, of which 26 occurred from 1870 to 1933 (Table 1). Twelve fires scarred five or more samples and were classified as significant fires (‡33.3% of the samples were scarred); these fires occurred from 1877 to 1923. Most wounds attributed to fire were recorded on small-diameter trees; for all fires, the basal diameter of oaks at the time of wounding was 12.7 ± 0.7 cm (mean ± SE). In most of the fires (n = 24), all wounds were located between annual growth rings, indicating occurrence in the dormant season (September to early April). In fire years, 147 of the 213 total wounds (69%) were on the uphill portion of the stem (3008 clockwise to 608), based on the uphill position recorded on the sample in the field. Of the 204 maple samples, only one exhibited a fire scar (a wound in a fire year); that maple, from Zaleski 2, had a wound in 1965.
Fire histories of the study units
REMA 2 had the greatest number of fires (n = 7) and significant fires (n = 5) (Table 1); fires were documented from 1877 to 1933. The 1917 significant fire had both dormant and earlywood scars, suggesting an early growing season fire. In the 1933 fire, most wounds were present in the late earlywood; in that fire, all seven scarred trees were young and small, having established in 1923 or 1924 and averaged only 5.1 cm in basal diameter (Table 1). We recorded six fires at REMA 3, three of which were significant, from 1878 1923 (Table 1; Fig. 1). As with REMA 2, the wounds in the 1917 fire indicate an early growing season fire; in the 1906 fire, all three wounds intersected the earlywood.
Zaleski 2 had evidence of six fires; five occurred from 1870 to 1928, and a sixth occurred in 1965 (Table 1). Although only the 1923 fire was classified as significant, it wounded 83% (15 of 18) of the samples; none of the other fires wounded more than three samples. No fires were recorded at Zaleski 2 during a 25 year period from stand origination (1844 to 1869). At Zaleski 3, the chronology was shorter, dating from 1880 to 2000. Although only three fires were recorded, both the 1917 and 1923 fires were significant. Again, the 1923 fire wounded a high percentage (61.9%) of the samples. All fire scars in both Zaleski units were in the dormant season.
Table 1. Summary data for the 28 fires documented on the six study units.
Note: All data are from the oak samples. Years in bold type indicate fires that scarred five or more trees and ‡33.3% of samples. aSample size is the total number of oak samples. Chronology period begins with the first year when four or more samples were present to record fires. bD, dormant season; E, earlywood; D and E, both dormant and earlywood wounds were present in the samples.
We recorded three fires at Tar Hollow 2 from 1883 to 1926 (Table 1). No fires were documented in the 39 years from stand origin (1844) to the 1883 fire; that fire was the only significant fire, wounding five of seven trees. Tar Hollow 3 had the shortest chronology (1899-2000) of all units; fires were documented in 1900, 1912, and 1984. Only two trees were scarred in 1900, but this is included as a fire because of its concordance with the four trees scarred in 1900 in Tar Hollow 2. Only three trees were scarred in the 1912 and 1984 fires at Tar Hollow 3. As with Zaleski, all fire scars were located between annual growth rings, indicating dormant-season fires.
In the period before active fire control and ending in 1935, composite mean fire intervals (MFI) only could be calculated at three of the six units (REMA 2, REMA 3, and Zaleski 2). At these units, MFI ranged from 9.0 to 14.5 years (Table 2). Likewise, the composite Weibull median fire interval (WMFI) ranged from 9.1 years at REMA 2 to 11.3 years at Zaleski 2. For the same pre-1936 period, the mean fire occurrence probabilities (MFOP; Guyette et al. 2006), which also take into account the period of time prior to the first fire, ranged from 11.6 and 12.2 years at REMA 2 and REMA 3, respectively, to 30.7 years at Tar Hollow 2. For the five units originating in 1880 or before (all but Tar Hollow 3), there was a period of at least 20 years from stand origination to the first recorded fire. As only two fires were documented from 1936 to 2000, fire-interval calculations that end in 2000 are longer (Table 2). The WMFI ranged from 12.7 and 13.9 years at REMA 2 and REMA 3, respectively, to 35.4 years at Tar Hollow 2.
Fire and the establishment of oaks and maples
At REMA 2, all oak samples established prior to 1924, and nearly every maple recruited after the 1923 fire (Fig. 2a).
Fig. 1. Fire history diagram for REMA 3. The broken horizontal lines represent the growth years for the 22 oak samples. The solid triangles are wounds that were in a recorded fire year; vertical bars are wounds present in years not recorded as fire years. The six fire years are indicated by the vertical lines located above the timeline.
Period ending in1935
Period ending in 2000
Tar Hollow 2
Tar Hollow 3
Note: A dash indicates that there were an insufficient number of fire events to calculate the interval. aFire interval calculations in these columns are based on a final incomplete interval ending in 2000.
After an initial period of oak establishment (1852 to 1865), presumably after harvesting for the charcoal iron industry, there was a 51 year period (1866 to 1916) when no oak recruitment was recorded. Thereafter, two pulses of oak establishment were documented immediately after the significant fires of 1917 and 1923. No maples predated the 1917 fire, and several maples established between the 1917 and 1923 fires. In 1923, immediately after the last significant fire, 15 maples recruited. Thereafter, 17 maples established from 1924 to 1938.
At REMA 3, initial oak establishment occurred from 1849 to 1860. As with REMA 2, no establishment was recorded after 1924 (Fig. 2b). After 1860, there were no large pulses of oak establishment, but there were 7 years from 1885 to 1924 in which pith dates were recorded for one or two oaks. The oldest maple dated to 1921, and a pulse of 11 stems established in 1923, immediately after the last fire. An additional 12 maples established from 1924 to 1949.
The temporal patterns of fire and establishment at the Zaleski units were similar to those of REMA, remarkably so for the initiation of maple establishment and the corresponding cessation of oak recruitment. At Zaleski 2, four oaks established in the 1840s (Fig. 2c). There was a period of oak recruitment from 1872 to 1880, with a pulse of eight stems in 1879 and 1880, following the 1879 fire. After 1880, we record virtually no oak recruitment for 42 years (1881 to 1922). Oaks then established in 1923 and 1924, immediately after the 1923 fire which scarred 15 of 18 oaks. Maple establishment began in 1922 (n = 4), just before the 1923 fire; four others dated to 1923. Thereafter, 22 maples established from 1924 to 1965, with a maximum of three stems in a single year.
Fig. 2. (a–f) Temporal establishment of oaks and maples for the six study units. Fires are indicated by vertical lines above the timeline; significant fires, those with ‡33.3% of samples wounded, are indicated by vertical arrows.
At Zaleski 3, we recorded 5 oaks that established before 1900 (primarily ca. 1880); then, 10 trees established in 1902 (Fig. 2d). The 1902 pulse of oak recruitment was not associated with a fire. As in unit 2, there was another period of oak establishment (n = 5) in 1923 and 1924, immediately following the 1923 significant fire; thereafter, we recorded only a single oak that established in 1954. As in unit 2, maple recruitment initiated in 1922 (n = 4), and eight trees established in 1923, directly after the significant fire. From 1926 to 1928, 11 maples established, and 11 others had pith dates from 1937 to 1959.
Tar Hollow 2 exhibited an early period of oak establishment (n = 8) from 1835 to 1851, six of the eight trees had pith dates of 1842 and 1843 (Fig. 2e). We recorded no oak establishment from 1852 to 1885; 15 trees established from 1886 to 1919. There was a small pulse (n = 3) of oak recruitment in 1900 after the fire of that year. Unlike REMA and Zaleski, maple establishment began nearly 40 years earlier at Tar Hollow 2. Maples (both red and sugar) recruited for 70 years (1881 to 1951) in a fairly continuous manner but did not exhibit the large pulses recorded at REMA and Zaleski.
The oldest oak recorded in Tar Hollow 3 dated to 1851, but no other samples predated 1894 (Fig. 2f). We record fires in 1900 and 1912. The 1900 fire scarred two of the four samples, and there was a pulse of oak recruitment (n = 6) that year. Thereafter, six oaks had pith dates from 1902 to 1924; no more than one tree was recorded in any single year. Maple recruitment at Tar Hollow 3 spanned from 1897 to 1963. As in Tar Hollow 2, there were no large establishment events. At both Tar Hollow units, despite different patterns of fire and an earlier initiation of maple establishment compared with REMA and Zaleski, oak establishment ceased at the same time at all sites (ca. 1920 to 1925).
Spatial distribution of fire scars and tree establishment at REMA
Fires that occurred in 1885, 1895, 1917, and 1923 were recorded in units 2 and 3 (Fig. 3). The 1885 and 1917 fires were classified as significant in both units. By contrast, the presence of fire-scarred trees was limited to one unit in the other five fire years (1877, 1878, 1900, 1906 [not shown], and 1933). Presumably, these fires did not burn across the intermittent stream drainage separating the two units. Similarly, the stream drainage in the center of unit 2, running southwest, appears to have limited fire spread in several years when trees were scarred only northwest (1895 and 1900) or southeast (1933) of the drainage.
For all fire years, scarred oaks were located near oaks that were not scarred. The trees most prone to exhibiting fire scars were in the northern portion of unit 2, near the top of the ridge; two or more of the seven trees that had established there before the first fire in 1877 were scarred in all unit 2 fires prior to 1933.
Maple establishment is first shown in both units on the 1923 fire map (Fig. 3g); these trees established from 1917 to 1922 and survived the 1923 fire. In unit 3, most of the maples that established before 1923 were in areas where fire scars were not recorded on oaks in 1923, suggesting that those small trees were in unburned patches. In unit 2, all three maples predating 1923 are within 5-20 m of an oak with a 1923 fire scar; however, all three oaks with fire scars were small in 1923, each having established immediately after the 1917 fire. By the time of the 1933 fire (Fig. 3h), maples had established across most of the landscape. All of the maples in the 1933 fire map were relatively near scarred oaks and thus escaped that fire; none of these samples had 1933 wounds. However, the low-intensity and perhaps patchy nature of the 1933 spring growing season fire is suggested by the fact that only small oaks (mean basal diameter 5.1 cm) that established after the 1923 fire were scarred.
Radial growth and releases
The master chronologies show growth that is typical of trees from forest interior sites and show only several sustained release events (Fig. 4). Growth releases were identified at only two of the six units; however, none of these releases coincided with a fire. Zaleski 2 had a major release beginning in 1896, perhaps coinciding with a harvest based on its magnitude. No oak recruitment was associated with this release. A moderate release also was identified at this site for 1906. REMA 3 had a major release in 1864 (Fig. 4), although considerable variability in early growth associated with the small sample size may partially account for this release event. No growth releases were identified at Zaleski 3, REMA 2, or at the Tar Hollow units. At REMA 3, some oak recruitment preceded the 1864 release event, but there is no evidence that these were related (Figs. 2 and 4). These analyses, based on the standardized mean ring width chronologies, indicate that fires were of insufficient intensity to cause standwide mortality and the release of surviving oaks.
Historic fire regime
Generally, fires were frequent from ca. 1870 to 1935 as stands developed but were uncommon thereafter, reflecting the regional postsettlement history of anthropogenic fire and its suppression. A 1920-1922 forest survey of 10 southern Ohio counties reported that 25% of all forested land showed visible evidence of having burned at least once within the previous decade (ODNR, Ohio Division of Forestry, Columbus, Ohio). Data from the same survey indicated that 5% to 7% of forested land burned annually (Ohio Experiment Station 1922). Organized fire control was instituted in 1923, and its infrastructure and effectiveness developed rapidly. By 1935, 19 fire lookout towers had been erected in 8 southern Ohio counties, and 447 fire wardens were employed (Leete 1938). From 1926 to 1935, the mean annual forest acreage burned had been reduced to 0.8% (Leete 1938); from 1950 to 2000, it was further reduced to only 0.1% per year (ODNR, Division of Forestry, Columbus, Ohio).
Our study adds to the growing body of dendrochronological evidence that fire was frequent in the central hardwood region prior to organized fire control; examples include oak and oak-pine community types in the Missouri and Arkansas Ozarks (Cutter and Guyette 1994; Guyette et al. 2002; Guyette and Spetich 2003; Soucy et al. 2005); pine-oak communities in the southern Appalachians (Brose and Waldrop 2006); post oak (Quercus stellata Wang.) barrens in Indiana (Guyette et al. 2003) and Tennessee (Guyette and Stambaugh 2004); and oak forests in southern Ohio (Sutherland 1997; McEwan et al. 2007b), Maryland (Shumway et al. 2001), and West Virginia (Schuler and McClain 2003). The fire-return intervals that we calculated for the REMA and Zaleski sites, ranging from 9.1 years prior to 1936 to 18.2 years overall (WMFI), are within the range reported in those studies (2-24 years), despite our more conservative criteria for classifying fire years. However, the 35 year firereturn interval at Tar Hollow 2 exceeds the range in the other studies.
In the central hardwoods region, dissected topography is known to have limited the spread of fires historically (Guyette et al. 2002). In our study, mapped fire-scarred trees suggest that even relatively small intermittent stream drainages limited fire spread in some years, resulting in some fires that were recorded on, and presumably burned, only a portion of the 20 ha units. By contrast, several of the significant fires spanned two units, scarring trees as far as 900 m apart.
Fig. 3. (a–h) Spatial distribution of oaks and maples at REMA in eight fire years. Solid circles indicate oaks scarred by a fire in the year associated with the map, and open circles show oaks that were not scarred in that year. The shaded triangles indicate the location of maples that had established by the time of the 1923 (Fig. 3g) and 1933 (Fig. 3h) fire years. (No maples were documented to have established at the time of the 1917 fire or before.)
Fig. 4. Master tree ring chronologies (ARSTAN) showing fire events (vertical arrows) and the point when a minimum of 10 trees were averaged (vertical line) into the mean chronology. Major (M) and moderate releases (m) were only noted in the Zaleski 2 and REMA 3 chronologies.
As other dendrochronological fire-history studies in the region have shown (e.g., Sutherland 1997; Shumway et al. 2001; McEwan et al. 2007b), the great majority of fires occurred in the dormant season (September to early April). Only fires in 1906, 1917, and 1933 at REMA had wounds located in the earlywood. In southern Ohio, radial growth (earlywood production) in oak begins in middle to late April, during bud-swelling and leaf unfolding (Phipps 1961). Oak cross sections collected in early May clearly show earlywood production, whereas samples from mid June show latewood production (R.W. McEwan, Department of Forestry, University of Kentucky, Lexington, Ky., unpublished data). Thus, we estimate that fires exhibiting both dormant and earlywood scars likely occurred in mid-April at the onset of radial growth (e.g., the 1917 REMA fire). The single fire (REMA 2 in 1933) that exhibited wounds intersecting the late portion of the earlywood probably occurred in May.
Sutherland (1997) and McEwan et al. (2007a) showed that historic fire occurrence in this region was not related strongly to monthly climatic conditions. Similarly, we recorded fires in both wet and dry periods. However, for the years in which fires occurred at more than one study site (1900, 1917, and 1923), all exhibited two or more months of drought conditions (Palmer drought severity index more negative than -1.5) the previous fall (1900, 1917, 1923) or also in the spring of the recorded fire year (1900).
The intensity of fires as these stands developed is difficult to determine with certainty because research is lacking that directly relates fire intensity to scarring in oak. However, several studies that have examined patterns of scarring in oak following prescribed fires provide some insight. Smith and Sutherland (1999) found that 14 of 18 small oak trees (4-23 cm DBH) had at least one fire scar after two low-intensity prescribed fires (flame lengths generally <50 cm with no overstory tree mortality). Guyette and Stambaugh (2004) showed that 35% to 65% of mostly small post oak trees (10-25 cm basal diameter) were scarred during three separate prescribed fires in an oak community in Tennessee. These fires burned 72%-93% of the area and reduced stand density (mostly small-diameter trees) by 35%. However, in both studies, only trees with visible bark char were selected for sampling. In our study, we found that, on average, 40% of the oak samples, most of which were small at the time (5 to 25 cm basal diameter) were scarred in the historic fires. These scarring percentages suggest that the fires would have been similar in intensity to the prescribed fires reported by Smith and Sutherland (1999) and Guyette and Stambaugh (2004). Although pulses of oak establishment immediately after some historic fires in our study suggest abundant resprouting after top kill, there is no evidence of high-severity stand-replacement fires even in these relatively young, regenerating stands.
McEwan et al. (2007a) reported that during 15 separate prescribed fires that were similar in intensity to those in Smith and Sutherland (1999), the scarring rate was much lower (12.6%) in white oak. However, because the sample trees in that study were much larger (most were >20 cm DBH), it is difficult to compare those scarring percentages with the historic scarring of small trees in our study.
Five years after a prescribed fire, Wendel and Smith (1986) found that 66% of overstory trees (all species, >12.7 cm DBH) exhibited fire scars visible on the exterior of the stem as exposed wood with callous tissue. The fire in their study was higher in intensity, reducing stand basal area by nearly 20%. The high scarring percentage of larger trees in their study suggests a higher intensity fire than was typical of the historic fires in our study.
Fire, land use, and tree establishment
At REMA and Zaleski, periods of oak and maple establishment were related to specific fire events as these stands developed. The establishment and subsequent survival of maples generally began immediately after the cessation of significant fires, i.e., fires that wounded at least one-third of the oak samples. The final oak establishment event also occurred directly after the last significant fire at three of the four REMA and Zaleski units. Because maples seldom were recorded as witness trees in upland forests just before Euro American settlement (Beatley 1959; Dyer 2001), these results lend support to the hypothesis that organized fire control facilitated the invasion of maples into the uplands from the more fire-protected lowlands (Abrams 1998).
The temporal patterns of fire history and maple establishment were similar at all four units at REMA and Zaleski. All units had periodic fires from ca. 1870 to 1925, and all units burned in both 1917 and 1923; in each of those years, fires were significant in three units. The initiation of maple establishment was similar in that none was documented in any units before the 1917 fires. Limited establishment was documented between the 1917 and 1923 fires, and large pulses occurred immediately after the 1923 fires followed by continuous establishment into the 1960s. The large pulses of maple establishment after the 1923 fires suggest resprouting from previously established individuals. Red maple, which accounted for 89% of the maple samples at REMA and Zaleski, has thin bark and is highly susceptible to top kill by fire (Harmon 1984; Regelbrugge and Smith 1994; Hutchinson et al. 2005); however, it also sprouts prolifically after topkill (Albrecht and McCarthy 2006; Blankenship and Arthur 2006). Maples probably began recruiting into these stands earlier than we document, perhaps much earlier, but presumably were being killed or top-killed until the cessation of fires.
The limited establishment and survival of maples before the 1923 fires (1917 to 1922) in all units may have resulted from several factors. Firstly, wildfires usually burn in a mosaic pattern, particularly in dissected landscapes, resulting in variable fire intensities and including unburned patches. Established maples may have escaped the 1923 fires in unburned patches. We also speculate that the initiation of maple establishment at REMA and Zaleski may have been facilitated by reduced anthropogenic land use, particularly by livestock in open-range woodland livestock grazing (Green 1907). The human population of Vinton County declined steadily with the demise of the iron furnace industry from a maximum of 17 223 in 1880 to 10 287 by 1930 (Vinton County Ohio Genealogy 2005). During the same period, farmland in the county decreased from 93283 to 61559 ha, and most of these lands reverted to forest (Bromley 1934a). Woodland grazing also likely decreased during this period, which would have favored the recruitment of trees, including maples. Brose and Waldrop (2006) showed that the cessation of livestock grazing in the Great Smoky Mountains National Park contributed to increased tree recruitment there in the 1920s and 1930s.
Oak also exhibited pulses of establishment immediately after some fires, suggesting resprouting from previously established stems. However, some fires were not followed by pulses of oak establishment. The final period of oak establishment occurred immediately after the 1923 fires; thereafter, we recorded virtually no additional oak stems. These data suggest that the large increase in maple establishment after the cessation of fires contributed via competition to the lack of subsequent oak recruitment. The absence of fire after 1923, probably coupled with reduced woodland grazing, also likely facilitated the development of higher stand densities. The resulting closed-canopy conditions that developed would have greatly limited the ability of the relatively shade-intolerant oaks to establish from seed (Beck 1970) but not the shade-tolerant red maple, which can persist for long periods beneath a canopy (Tift and Fajvan 1999). Thus, further oak recruitment from seed, followed by growth and survival, probably was limited by a combination of shading and competition from both overstory trees and understory maples after fires ceased (e.g., Aldrich et al. 2005)
The history of fire and tree establishment at Tar Hollow differed from that of REMA and Zaleski in several aspects. First, at Tar Hollow, there were fewer historical fires (n = 5) and only one was significant. In all, we recorded only 19 historic fire scars at Tar Hollow compared with 48 at Zaleski and 75 at REMA.
The temporal pattern of maple establishment also differed, beginning nearly 40 years earlier (1881) and not exhibiting the distinct pulses after fire cessation that occurred at REMA and Zaleski. Tar Hollow also differed in that there was a long period of fairly continuous oak establishment (ca. 1890 to 1925), that coincided with the continuous recruitment of maples. These differences in fire and regeneration among sites may have resulted from different human land use.
Timber harvesting in the 1800s at Tar Hollow was not associated with charcoal production as at REMA and Zaleski and, thus, may have differed in intensity and extent. Perhaps more important is the evidence of greater and more varied human land use at the Tar Hollow site. In the 1930s, several Land Utilization Project (LUP) areas were established in which the State of Ohio purchased submarginal farmlands and then resettled the occupants (Bromley 1934a, 1934b). The REMA and Zaleski study sites were located near LUP areas while the Tar Hollow site was within the Ross-Hocking LUP. Land titles and appraisals that included detailed ownership and land-use maps from the time of purchase (ca. 1935) indicate that the Tar Hollow site consisted of a number of small parcels of mixed-ownership (ODNR, Division of Forestry, Regional Office, Chillicothe, Ohio). The maps indicate a patchy mixture of cover types: the most abundant was ‘‘forest land (including woodland pasture),’’ but it also included some areas of ‘‘grazing land (grazing or open pasture)’’ and a smaller portion as ‘‘crop land (including orchard and hay meadows).’’ The more varied land uses at Tar Hollow likely would have created a more patchy distribution of disturbances (fire, grazing, and harvesting). In particular, the patchy ownership and land use might have limited fire spread, resulting in the lower observed occurrence of fire. In turn, fewer fires probably facilitated the recruitment and survival of maples beginning much earlier at this site. At Tar Hollow, woodland grazing may have been more prevalent for a longer period with direct human occupation into the mid-1930s, potentially limiting the large pulses of maple establishment that occurred at REMA and Zaleski. Although fires generally were less frequent and wounded fewer trees at Tar Hollow, these units also developed into oak-dominated forests.
Other potential factors affecting tree establishment In addition to fire and human land use (particularly woodland grazing), the regeneration of oak forests was surely influenced by dramatic changes in wildlife populations. The decline and extirpation of the acorn-consuming white-tailed deer (Odocoileus virginianus (Zimmermann)), wild turkeys (Meleagris gallopavo L.), and passenger pigeons (Ectopistes migratorius (L.)) occurred from the mid-1800s to the early 1900s, as these stands were developing (Chapman 1938). Although these declines could have benefited oak regeneration from seed, the consumption of acorns and grazing of seedlings by domestic livestock probably were widespread during this period. No deer were present in Ohio from 1904 to 1922 when a restocking program was initiated (Chapman 1938). By 1938, it was estimated that only 2000 deer were in Ohio (Chapman 1938); the current estimate is 650 000 (ODNR, Division of Wildlife, Columbus, Ohio). Thus, excessive deer browsing clearly would not have contributed to the cessation of oak recruitment ca. 1925. In fact, a lack of deer browsing, the cessation of fire, and a decrease in livestock grazing may have facilitated the dramatic increase in maple establishment during the 1920s and 1930s.
It also is unlikely that American chestnut (Castanea dentata (Marsh.) Borkh.) mortality, caused by the chestnut blight fungus, facilitated the initial recruitment of maple in these stands. Even at REMA and Zaleski where maple recruitment began later (ca. 1920), it predated the arrival of chestnut blight, which caused mortality in Vinton County primarily from 1928 to 1936 (Beatley 1959). Also, chestnut accounted for only 4%-6% of witness trees ca. 1800 (Beatley 1959).
Selective harvesting was common after the mid-1930s on the Zaleski and Tar Hollow State Forests and at the REMA, then owned by D.B. Frampton and Co. (Beatley 1959). Previous work on sites near our REMA sites showed some growth releases suggestive of selective harvesting (Hutchinson et al. 2003). However, our data indicate that, in the absence of periodic fire, canopy disturbances after ca. 1925 did not facilitate oak recruitment. Similarly, during the fire control era, small openings in closed-canopy stands would have favored the growth of maples, which can respond with rapid growth even after long periods of suppression (Tift and Fajvan 1999).
Implications for oak regeneration today
Our results show the past importance of periodic fire in sustaining oak establishment and in limiting maple recruitment as stands developed. However, in many oak forests, there is now an abundance of maples in the midstory that are large enough to be fire resistant. Also, many forests that remain dominated by overstory oaks may be too dense to support oak regeneration even if the maple midstory could be removed with fire. Research has shown that simply returning low-intensity prescribed fires to fully stocked stands does not open the canopy sufficiently to improve the competitive status of oak regeneration (Hutchinson et al. 2005; Blankenship and Arthur 2006). Similar to the past importance of fire in early stand development, oak regeneration has improved when prescribed fire was applied to openstructured stands that developed after partial harvest (Kruger and Reich 1997; Brose and Van Lear 1998; Iverson et al. 2008). However, other studies have shown that the timing and intensity of the mechanical treatments and fire are critical to their success (Franklin et al. 2003; Albrecht and McCarthy 2006). Although fire was important in sustaining oak forests in the past, the legacy of prolonged fire exclusion necessitates research to refine oak regeneration prescriptions that incorporate canopy disturbances, fire, and other tools (Brose et al. 2006).
We thank David Hosack, Kristy Tucker, Brad Tucker, Bill Borovicka, Tim Fox, Joan Jolliff, and Zachary Traylor for field and laboratory assistance. We thank Patrick Brose, James Rentch, Ryan McEwan, Marty Jones, and two anonymous reviewers for providing many valuable suggestions on previous drafts of the manuscript. We thank the Ohio Department of Natural Resources, Division of Forestry, for supporting this research on Tar Hollow and Zaleski State Forests; we thank Bob Boyles and Michael Bowden of the Division of Forestry for assistance with historical documents. We also thank Forestland Group, LLC, for supporting this research on the Vinton Furnace Experimental Forest. This is publication No. 172 of the Fire and Fire Surrogate Network Project funded by the Join Fire Sciences Program.
Abrams, M.D. 1992. Fire and the development of oak forests. Bioscience, 42: 346-353. doi:10.2307/1311781.
Abrams, M.D. 1998. The red maple paradox: what explains the widespread expansion of red maple in eastern forest? Bioscience, 48: 355-364. doi:10.2307/1313374.
Abrams, M.D. 2002. The postglacial history of oak forests in eastern North America. In Oak forest ecosystems. Ecology and management for wildlife. Edited by W.J. McShea and W.M. Healy. Johns Hopkins University Press, Baltimore, Md. pp. 34-45.
Abrams, M.D., and Copenheaver, C.A. 1999. Temporal variation in species recruitment and dendroecology of an old-growth white oak forest in the Virginia Piedmont, USA. For. Ecol. Manage. 124: 275-284. doi:10.1016/S0378-1127(99)00071-7.
Abrams, M.D., and Downs, J.A. 1990. Successional replacement of old-growth white oak by mixed mesophytic hardwoods in southwestern Pennsylvania. Can. J. For. Res. 20: 1864-1870. doi:10. 1139/x90-250.
Albrecht, M.A., and McCarthy, B.C. 2006. Effects of prescribed fire and thinning on tree recruitment patterns in central hardwood forests. For. Ecol. Manage. 226: 88-103. doi:10.1016/j. foreco.2005.12.061.
Aldrich, P.R., Parker, G.R., Romero-Severson, J., and Michler, C.H. 2005. Confirmation of oak recruitment failure in Indiana old-growth forest: 75 years of data. For. Sci. 51: 406-416.
Beatley, J.C. 1959. The primeval forests of a periglacial area in the Allegheny Plateau (Vinton and Jackson Counties, Ohio). Bull. Ohio Biol. Surv. 1: 1-166.
Beck, D.E. 1970. Effect of competition on survival and height growth of northern red oak seedlings. USDA For. Serv. Southeast. For. Exp. Stn. Res. Pap. SE-5.
Blankenship, B.A., and Arthur, M.A. 2006. Stand structure over 9 years in burned and fire-excluded oak stands on the Cumberland Plateau, Kentucky. For. Ecol. Manage. 225: 134-145. doi:10.1016/j.foreco.2005.12.032.
Boerner, R.E.J., Brinkman, J.A., and Yaussy, D.A. 2007. Ecosystem restoration treatments affect soil physical and chemical properties in Appalachian mixed-oak forests. In Proceedings, 15th Can. J. For. Res. Vol. 38, 2008 Central Hardwood Forest Conference, 27 February – 1 March 2006, Knoxville, Tenn. [CD-ROM.] Edited by D.S. Buckley and W.S. Clatterbuck. USDA For. Serv. Gen. Tech. Rep. SRS-101. pp. 107-116.
Bromley, W.C. 1934a. Preliminary report on the Zaleski rehabilitation and forest project of Vinton County Ohio. Ohio Division of Forestry, Columbus, Ohio.
Bromley, W.C. 1934b. Preliminary report on the submarginal land and state forest project of southeastern Vinton County Ohio. Ohio Division of Forestry, Columbus, Ohio.
Brose, P.H., and Van Lear, D.H. 1998. Responses of hardwood advance regeneration to seasonal prescribed fires in oak-dominated shelterwood stands. Can. J. For. Res. 28: 331-339. doi:10.1139/ cjfr-28-3-331.
Brose, P.H., and Waldrop, T.A. 2006. Fire and the origin of table mountain pine – pitch pine communities in the southern Appalachian Mountains, USA. Can. J. For. Res. 36: 710-718. doi:10. 1139/x05-281.
Brose, P.H., Schuler, T.M., and Ward, J.S. 2006. Responses of oak and other hardwood regeneration to prescribed fire: what we know as of 2005. In Fire in Eastern Oak Forests: Delivering Science to Land Managers. Proceedings of a Conference, 15-17 November 2005, Columbus, Ohio. Edited by M.B. Dickinson. USDA For. Serv. Gen. Tech. Rep. NRS-P-1. pp. 123-135.
Chapman, F.B. 1938. The development and utilization of the wildlife resources of unglaciated Ohio. Ph.D. dissertation, Ohio State University, Columbus, Ohio.
Cook, E.R., and Kairiukstis, L.A. 1990. Methods of dendrochronology. Kluwer Academic Publications, Hingham, Mass.
Cutter, B.E., and Guyette, R.P. 1994. Fire frequency on an oakhickory ridgetop in the Missouri Ozarks. Am. Midl. Nat. 132: 393-398. doi:10.2307/2426595.
Dyer, J.M. 2001. Using witness trees to assess forest change in southeastern Ohio. Can. J. For. Res. 31: 1708-1718. doi:10. 1139/cjfr-31-10-1708.
Franklin, S.B., Robertson, P.A., and Fralish, J.S. 2003. Prescribed burning effects on upland Quercus forest structure and function. For. Ecol. Manage. 184: 315-335. doi:10.1016/S0378-1127(03) 00153-1.
Fritts, H.C. 1976. Tree rings and climate. Academic Press, London. Goebel, P.C., and Hix, D.M. 1997. Changes in the composition and structure of mixed-oak, second-growth forest ecosystems during the understory reinitiation stage of stand development. Ecoscience, 4: 327-340.
Gordon, R.B. 1969. The natural vegetation of Ohio in pioneer days. Ohio State University, Columbus, Ohio. Bull. Ohio Biol. Surv. New Ser. 3. pp. 1-109.
Green, W.J. 1907. First report on forest conditions in Ohio. Bull. Ohio Agric. Exp. Stn. 188: 37-51.
Griffith, D.M., DiGiovanni, D.M., Witzel, T.L., and Wharton, E.H. 1993. Forest statistics for Ohio, 1991. USDA For. Serv. Northeast. For. Range Exp. Stn. Res. Bull. NE-128.
Grissino-Mayer, H.D. 2001a. FHX2—software for analyzing temporal and spatial patterns in fire regimes from tree rings. TreeRing Res. 57: 115-124.
Grissino-Mayer, H.D. 2001b. Evaluating crossdating accuracy: a manual and tutorial for the computer program COFECHA. Tree-Ring Res. 57: 205-221.
Grissino-Mayer, H.D. 2004. FHX2 user’s manual: software for analyzing temporal and spatial patterns in fire regimes from tree rings. University of Tennessee, Knoxville, Tenn.
Grissino-Mayer, H.D., and Swetnam, T.W. 1997. Multi-century history of wildfire in the ponderosa pine forests of El Malpais National Monument. Bull. N.M. Bur. Mines Mineral Resour. 156: 163-172.
Grissino-Mayer, H.D., Romme, W.H., Floyd, M.L., and Hanna, D.D. 2004. Climatic and human influences on fire regimes of the southern San Juan Mountains, Colorado, USA. Ecology, 85: 1708-1724. doi:10.1890/02-0425.
Guyette, R.P., and Spetich, M.A. 2003. Fire history of oak-pine forests in the Lower Boston Mountains, Arkansas, USA. For. Ecol. Manage. 180: 463-474. doi:10.1016/S0378-1127(02) 00613-8.
Guyette, R.P., and Stambaugh, M.C. 2004. Post-oak fire scars as a function of diameter, growth, and tree age. For. Ecol. Manage. 198: 183-192. doi:10.1016/j.foreco.2004.04.016.
Guyette, R.P., Muzika, R.M., and Dey, D.C. 2002. Dynamics of an anthropogenic fire regime. Ecosystems (NY., Print), 5: 472-486. doi:10.1007/s10021-002-0115-7.
Guyette, R.P., Dey, D.C., and Stambaugh, M.C. 2003. Fire and human history of a barren-forest mosaic in southern Indiana. Am. Midl. Nat. 149: 21-34. doi:10.1674/0003-0031(2003) 149[0021:FAHHOA]2.0.CO;2.
Guyette, R.P., Spetich, M.A., and Stambaugh, M.C. 2006. Historic fire regime dynamics and forcing factors in the Boston Mountains, Arkansas, USA. For. Ecol. Manage. 234: 293-304. doi:10.1016/j.foreco.2006.07.016.
Haines, D.A., Johnson, V.J., and Main, W.A. 1975. Wildfire atlas of the northeastern and north central states. USDA For. Serv. Gen. Tech. Rep. NC-16.
Harmon, M.E. 1984. Survival of trees after low-intensity surface fires in Great Smoky Mountains National Park. Ecology, 65: 796-802. doi:10.2307/1938052.
Holmes, R.L. 1983. Computer-assisted quality control in tree-ring dating and measurement. Tree-Ring Bull. 43: 69-78.
Holmes, R.L. 1999. Program JOLTS: finding growth surges or suppression in trees. Laboratory of Tree-Ring Research, University of Arizona, Tucson, Ariz.
Hutchinson, T.F., Rubino, D., McCarthy, B.C., and Sutherland, E.K. 2003. History of forests and land use. In Characteristics of mixed-oak forest ecosystems in southern Ohio prior to the reintroduction of fire. Edited by E.K. Sutherland and T.F. Hutchinson. USDA For. Serv. Gen. Tech. Rep. NE-299. pp 17-27.
Hutchinson, T.F., Sutherland, E.K., and Yaussy, D.A. 2005. Effects of repeated fires on the structure, composition, and regeneration of mixed-oak forests in Ohio. For. Ecol. Manage. 218: 210-228. doi:10.1016/j.foreco.2005.07.011.
Iverson, L.R., Hutchinson, T.F., Prasad, A., and Peters, M.P. 2008. Thinning, fire, and oak regeneration across a heterogeneous landscape in the eastern U.S.: seven-year results. For. Ecol. Manage. In press. oi:10.1016/j.foreco.2007.09.088.
Johnson, P.S., Shifley, S.R., and Rogers, R. 2002. The ecology and silviculture of oaks. CAB International, New York.
Kruger, E.L., and Reich, P.B. 1997. Responses of hardwood regeneration to fire in mesic forest openings. I. Post-fire communitydynamics. Can. J. For. Res. 27: 1822-1831. doi:10.1139/cjfr-27- 11-1822.
Leete, B.E. 1938. Forest fires in Ohio 1923 to 1935. Bull. Ohio Agric. Exp. Stn. 598.
Lorimer, C.G. 1993. Causes of the oak regeneration problem. In Oak Regeneration: Serious Problems, Practical Recommendations, Symposium Proceedings, 8-10 September 1992, Knoxville, Tenn. Edited by D. Loftis and C.E. McGee. USDA For. Serv. Gen. Tech. Rep. GTR-SE-84. pp. 14-39.
Lorimer, C.G. 1984. Development of the red maple understory in northeastern oak forests. For. Sci. 30: 3-22.
Lorimer, C.G., and Frelich, L.E. 1989. A methodology for estimating canopy disturbance frequency and intensity in dense temperate forests. Can. J. For. Res. 19: 651-663. doi:10.1139/X89-102.
Lorimer, C.G., Dahir, S.E., and Singer, M.T. 1999. Frequency of partial and missing rings in Acer saccharum in relation to canopy position and growth rate. Plant Ecol. 143: 189-202. doi:10.1023/A:1009847819158.
McEwan, R.W., Hutchinson, T.F., Ford, R.D., and McCarthy, B.C.
2007a. An experimental evaluation of fire history reconstruction using dendrochronology in white oak (Quercus alba). Can. J. For. Res. 37: 806-816. doi:10.1139/X06-294.
McEwan, R.W., Hutchinson, T.F., Long, R.P., Ford, R.D., and McCarthy, B.C. 2007b. Temporal and spatial patterns of fire occurrence during the establishment of mixed-oak forests in eastern North America. J. Veg. Sci. 18: 655-664. doi:10.1658/1100 9233(2007)18[655:TASPIF]2.0.CO;2.
McNab, W.H., and Avers, P.E. 1994. Ecological subregions of the United States: section descriptions. USDA For. Serv. Wash. Off. Admin. Publ. WO-WSA-5. Ohio Experiment Station. 1922. 42nd annual report. Bull. Ohio Ag-
ric. Exp. Stn. 373.
Phipps, R.L. 1961. Analysis of five years of dendrometer data obtained within three deciduous forest communities of Neotoma. Neotoma Ecological and Bioclimatic Laboratory, Ohio Agricultural Experiment Station, Wooster, Ohio. Res. Circ. 105. pp. 3-34.
Regelbrugge, J.C., and Smith, D.W. 1994. Postfire tree mortality in relation to wildfire severity in mixed oak forests in the Blue Ridge of Virginia. North. J. Appl. For. 11: 90-97.
Schuler, T.M., and McClain, W.R. 2003. Fire history of a Ridge and Valley forest. USDA For. Serv. Northeast. Res. Stn. Res. Pap. NE-724.
Shumway, D.L., Abrams, M.D., and Ruffner, C.M. 2001. A 400 year history of fire and oak recruitment in an old-growth oak forest in western Maryland, USA. Can. J. For. Res. 31: 1437 1443. doi:10.1139/cjfr-31-8-1437.
Smith, K.T., and Sutherland, E.K. 1999. Fire-scar formation and compartmentalization in oak. Can. J. For. Res. 29: 166-171. doi:10.1139/cjfr-29-2-166.
Soucy, R.D., Heitzman, E., and Spetich, M.A. 2005. The establishment and development of oak forests in the Ozark Mountains of Arkansas. Can. J. For. Res. 35: 1790-1797. doi:10.1139/x05 104.
Stokes, M.A., and Smiley, T.L. 1968. An introduction to tree-ring dating. University of Chicago Press, Chicago, Ill.
Stout, W. 1933. The charcoal iron industry of the Hanging Rock Iron District—its influence on the development of the Ohio Valley. Ohio Archaeol. Hist. Q. 42: 72-104.
Sutherland, E.K. 1997. The history of fire in a southern Ohio second-growth mixed-oak forest. In Proceedings of the 11th Central Hardwoods Forest Conference, 23-26 March 1997, Columbia, Mo. Edited by S.G. Pallardy, R.A. Cecich, H.E. Garrett, and P.S. Johnson. USDA For. Serv. Gen. Tech. Rep. NC-188. pp. 172-183.
Sutherland, E.K., Hutchinson, T.F., and Yaussy, D.A. 2003. Introduction, study area description, and experimental design. In Characteristics of mixed-oak forest ecosystems in southern Ohio prior to the reintroduction of fire. Edited by E.K. Sutherland and T.F. Hutchinson. USDA For. Serv. Gen. Tech. Rep. NE-299, pp. 1-16.
Tift, B.D., and Fajvan, M.A. 1999. Red maple dynamics in Appalachian hardwood stands in West Virginia. Can. J. For. Res. 29: 157-165. doi:10.1139/cjfr-29-2-157.
Van Lear, D.H., and Brose, P.H. 2002. Fire and oak management. In Oak forest ecosystems. ecology and management for wildlife. Edited by W.J. McShea and W.H. Healy. Johns Hopkins University Press, Baltimore, Md. pp. 269-279.
Vinton County Ohio Genealogy. 2005. Vinton County Ohio population changes 1850-1990 [online]. Available from www.rootsweb.com/~ohvinton/vintpop.gif.
Wendel, G.W., and Smith, H.C. 1986. Effects of prescribed fire in a central Appalachian oak-hickory stand. USDA For. Serv. Northeast. For. Range Exp. Stn. Res. Pap. NE-RP-594.
Yaussy, D.A., Hutchinson, T.F., and Sutherland, E.K. 2003. Structure, composition, and condition of overstory trees. In Characteristics of mixed-oak forest ecosystems in southern Ohio prior to the reintroduction of fire. Edited by E.K. Sutherland and T.F. Hutchinson. USDA For. Serv. Gen. Tech. Rep. NE-299. pp. 99-111.
The Demise of Fire and “Mesophication” of Forests in the Eastern United States
GREGORY J. NOWACKI AND MARC D. ABRAMS
A diverse array of fire-adapted plant communities once covered the eastern United States. European settlement greatly altered fire regimes, often increasing fire occurrence (e.g., in northern hardwoods) or substantially decreasing it (e.g., in tallgrass prairies). Notwithstanding these changes, fire suppression policies, beginning around the 1920s, greatly reduced fire throughout the East, with profound ecological consequences. Fire-maintained open lands converted to closed-canopy forests. As a result of shading, shade-tolerant, fire-sensitive plants began to replace heliophytic (sun-loving), fire-tolerant plants. A positive feedback cycle—which we term “mesophication”—ensued, whereby microenvironmental conditions (cool, damp, and shaded conditions; less flammable fuel beds) continually improve for shade-tolerant mesophytic species and deteriorate for shade-intolerant, fire-adapted species. Plant communities are undergoing rapid compositional and structural changes, some with no ecological antecedent. Stand-level species richness is declining, and will decline further, as numerous fire-adapted plants are replaced by a limited set of shade-tolerant, fire-sensitive species. As this process continues, the effort and cost required to restore fire-adapted ecosystems escalate rapidly.
Fire was widespread and frequent throughout much of the eastern United States before European settlement 1998). Native Americans were the primary ignition source in many locations, given the moist and humid conditions of the(Pyne 1982, Abrams 1992). Widespread burning created a mismatch between the physiological limits set by climate and the actual expression of vegetation—a common phenomenon throughout the world (Bond et al. 2005). In the eastern United States, presettlement vegetation types were principally pyrogenic; that is, they formed systems assembling under and maintained by recurrent fire (Frost 1998, Wade et al. 2000). Prime examples include tallgrass prairies, aspen (Poulus) parklands, oak (Quercus)-dominated central hardwoods, northern and southern “pineries,” and boreal spruce-fir (Picea-Abies) forests (Wright and Bailey 1982). In turn, an extensive array of eastern animal and plant species have adapted to and depend on fire, either directly (e.g., jack pine [Pinus banksiana Lamb.]) or through the use of fire-maintained habitat (e.g., Kirtland’s warbler [Dendroica kirtlandii]).
A diverse mix of vegetation and site conditions of the eastern United States supported a range of presettlement fire regimes, from intense stand-replacing burns on pine barrens to “asbestos-like” communities that rarely burned (e.g., northern hardwoods). However, most presettlement fire regimes produced low- to mixed-severity surface burns, which maintained the vast expanses of oak and pine forests that dominated much of the eastern United States, often in open “park-like” conditions (Wright and Bailey 1982, Frost East (Whitney 1994). Historical documents indicate that Native American ignitions far outnumbered natural causes (principally lightning) in most locations (Gleason 1913, De-Vivo 1991). In this respect, humans were a “keystone species,” actively managing the environment with fire over millennia (Sauer 1975, Guyette et al. 2006). Nonetheless, within the fire maintained landscapes, variations in human population and land use, topography, and riparian areas (firebreaks) created a mosaic of burned and unburned vegetation types (Heinselman 1973, Anderson 1991, Whitney 1994).
Fire regimes changed in various ways with European settlement, often profoundly. In many instances, fire frequency and severity increased as forests were cut and burned, either intentionally (for agricultural land clearing) or unintentionally (e.g., sparked by wood- and coal-burning steam engines). This transition was most stark for mesic hardwood systems that seldom burned in presettlement times (e.g., northern hardwoods, mixed mesophytic forests). Most noteworthy were the postcutting conflagrations of the upper Great Lakes (Haines and Sando 1969), which led to unprecedented changes in vegetation composition and structure (Webb 1973, White and Mladenoff 1994, Cole et al. 1998). For instance, a sizeable proportion of northern hardwoods converted to aspen-birch (Populus-Betula) or oak through repeated cutting and burning (Palik and Pregitzer 1992, Schulte et al. 2007). Fire frequency remained the same or even increased where settlers adopted Native burning practices, such as in the central hardwood region (Cole and Taylor 1995). Here, frequent understory burning helped maintain the dominance of oak and of fire-adapted associates, especially grasses for pasturage.
On the most flammable landscapes (e.g., midwestern grasslands) where the danger to humans and improvements (e.g., buildings, fences) from fire was especially high, fire was effectively extinguished with European settlement (Gleason 1913, Abrams 1992, Wolf 2004). Here, fires declined for several reasons, including the loss of Native American ignitions, the rapid conversion of native vegetation to croplands and pasturage, landscape fragmentation (caused by roads and rail-roads), and active suppression efforts (Nuzzo 1986). In areas not dedicated to agriculture, the release of fire-suppressed sprouts (grubs) from centuries-old oak root systems turned native grasslands and oak savannas into closed-canopy forests at astonishing rates (Loomis and McComb 1944, Cottam 1949, Anderson 1991, 1998).
Regardless of the directional shifts of the early postsettlement era, fire regimes began to converge with the onset of fire suppression policies in the 1920s. As a result of these policies, fire declined through effective wildfire detection and universal containment. This wholesale shift in fire regimes had unforeseen ecological consequences across the United States. A cascade of compositional and structural changes took place whereby open lands (grasslands, savannas, and woodlands) succeeded to closed-canopy forests, followed by the eventual replacement of fire dependent plants by shade-tolerant, fire-sensitive vegetation. This trend continues today with ongoing fire suppression.
Many studies have individually documented fire regime change and subsequent shifts in vegetation over time (Heinselman 1973, Clark 1990, Abrams and Nowacki 1992, Wolf 2004). However, a broadscale synthesis, projection, and discussion of fire-regime change across the eastern United States is currently lacking. Similarly, discussions regarding the ecological consequences of long-term fire suppression have been largely restricted to local levels. Here, using geospatial analyses of past and current fire regimes, we estimate the extent and magnitude of fire regime change throughout the East. We focus on the vast oak-pine and tallgrass prairie-savanna formations in the eastern United States to illustrate and discuss the biotic and abiotic ramifications of fire regime change and, in the process, to document the near-universal “mesophication” of fire-dependent communities.
Estimating fire regime change
We evaluated the best available geospatial data layers covering the entire eastern United States to derive past and current fire regimes (figure 1). Fire regime groups were assigned to data layers according to Fire Regime Condition Class (FRCC) protocols (figure 1c; http://frcc.gov), based on known fire vegetation relations, the autecology of principal plant species or functional groups, and expert opinion. All selected layers were uniformly converted to 1-kilometer pixels for this coarsescale assessment. Schmidt and colleagues’ (2002) potential natural vegetation (PNV) groups and Frost’s (1998) presettlement fire frequency regions were evaluated for portraying presettlement fire regimes. These two sets of geospatial data generated similar outputs of fire regime groups. Because the PNV-based output provided a slightly higher resolution and was supported by previously published documentation (Schmidt et al. 2002), it was ultimately selected to depict past fire regimes. Some of the best tangible data quantifying past fire regimes come from tree fire scars. Therefore, we used a fire-scar compilation, spanning the eastern United States (table 1; Guyette et al. 2006), to verify our map. Locational data obtained from Michael Stambaugh (Missouri Tree-Ring Laboratory, University of Missouri-Columbia, personal communication, 26 January 2007) were geospatially registered and merged with our past fire regime map for direct comparison. Twenty-seven sites were used in the comparative analysis after eliminating those (a) outside our study area (seven Ontario sites), (b) without preuropean fire data (six sites), and (c) misregistered or lacking locational data (two sites). All fire-scar sites were classified as belonging to fire regime group I, since they possessed trees that survived multiple (indicative of low- and mixed-severity burns) and frequent fires (< 35 years; see figure 1c classification). We found a high correspondence, as 74% of the sites were mapped correctly by our past fire regime map (20 sites), whereas the remaining 26% were misclassified as fire regime group II (1 site), III (5 sites), and IV (1 site).
Current fire regimes were based on a “hybrid” vegetation map that combined the classification strengths of two spatial data layers: Advanced Very High-Resolution Radiometer (AVHRR) and the National Land Cover Dataset (NLCD). AVHRR data (with a superior number of forest types and cover classes) were used to classify forestlands, whereas NLCD data were applied to the remaining, primarily nonforested lands. Fire regime group assignments for the selected layers are listed in tables 1-3. We did not attempt to validate our current fire regime map using Guyette and colleagues’ (2006) database, as most sites did not register any fire over the past 50 years or so, making it impossible to calculate a meaningful current fire-return interval (Michael Stambaugh, personal communication, 26 January 2007).
Table 1. Potential natural vegetation codes, classes, and assigned fire regime groups.
Based on FRCC classification axes (figure 1c), a fire regime gradient, from most to least frequent or severe, strikes diagonally from the lower right-hand to the upper lefthand corner. We selected color palettes to reflect this fire regime gradient, from pyrogenic systems, with the most frequent and intense fires (fire regime group II, red), to “asbestos” systems that rarely burn (fire regime group V, blue). Note that the color spectrum (red hot to cool blue) deviates somewhat from fire regime group enumeration (fire regime groups I-V).
To calculate past-to-current fire regime change for geospatial display, we converted the numeration of fire regime groups to arabic numerals to capture the fire gradient from hottest (most frequent and severe) to coolest (less frequent and severe). Thus, the following values were applied: fire regime group I = 2, fire regime group II = 1, fire regime group III = 4, fire regime group IV = 3, and fire regime group V = 5. A fire regime change map was then generated on a pixel-by-pixel basis, using the following equation:
Fire regime change = past fire regime group – current fire regime group.
This formula projects fire regime change over nine ordinal classes, from -4 through 0 to +4. Positive values represent trends toward more fire than in the past, whereas negative values represent fire reductions. The more negative or positive the values are, the more substantial the trend.
The analysis indicates that there has been a general “cooling” of the eastern United States landscape (i.e., less fire) over time (figure 2). This trend is consistent with the historical record, which points toward wholesale fire reduction, both spatially and temporally, across the East (Pyne 1982, Wright and Bailey 1982, Abrams 1992, Anderson 1998, Frost 1998). The suppression of fire was due to a culmination of events, including the elimination of Native burning, the construction of road networks (serving as firebreaks and providing access for firefighting), the conversion of forest and prairie to croplands (resulting in fuel change and reduction), overgrazing, and aggressive 20th-century fire-suppression efforts.
Table 2. Advanced Very High Resolution Radiometer vegetation classes and assigned fire regime group, by tree cover class.
Table 3. National Land Cover Dataset codes, classes, and assigned fire regime groups.
The degree of change between past and current fire regimes varied geographically across the East (figure 2). The largest fire reductions (depicted in blue) were centered in the Midwest, where a topographically controlled mosaic of pyrogenic grasslands, savannas, and woodlands was replaced by an intensively managed agricultural landscape that seldom burns (Iverson and Risser 1987, Anderson 1998). Those areas not cultivated or pastured quickly succeeded to closed-canopy forests, often through the release of oak grubs (Gleason 1913, Loomis and McComb 1944). Fire suppression has continued for such a long time now that certain fire-sensitive tree species, such as red maple (Fei and Steiner 2007), have expanded their range into the Midwest and Central Plains. Land-use conversion and fire suppression have been so complete that midwestern tallgrass prairies and oak savannas are now some of the rarest ecosystems in the world. For instance, 11 to 13 million hectares (ha) of former oak savanna has now been reduced to 2607 ha—a mere 0.02% of its presettlement coverage (Nuzzo 1986). In Missouri, cultivation, overgrazing, and fire suppression have reduced native prairie land from 4.8 million ha to approximately 16,000 ha (Schroeder 1981).
Substantial reductions in fire (represented by shades of green) extended east and southward from the former Midwest grasslands, essentially enveloping the southern two-thirds of the eastern United States. Here too, the conversion of fire dependent systems to an agriculture-dominated landscape is prominent. This conversion, coupled with compositional shifts of the remaining forestland to increasingly fire-sensitive species (e.g., from oaks to mixed mesophytic species in the central hardwoods; from pine to hardwoods in the South), indicates the reduction of broadscale fire. Fire reductions extended into the sub-boreal landscapes of northern Minnesota as well—a phenomenon well documented in the literature (Heinselman 1973, Clark 1990).
Landscapes with nonpyrogenic tendencies, in particular the Mississippi embayment and the northern hardwood region, displayed little change. In essence, landscapes that historically did not burn (because of prevailing moist to wet conditions) still do not burn. However, some exceptions exist within the northern hardwood region (upper Great Lakes states and New England). Most of these cases of increased fire are an artifact of higher present-day levels of aspen-birch, oak, and off-site pine (Pinus) plantations (fire-dependent forest types)—a legacy of past logging, subsequent fires, field abandonment, and Civilian Conservation Corps activities of the 19th and early 20th centuries (Palik and Pregitzer 1992, Cole et al. 1998, Schulte et al. 2007). Whether the signature of these pyrogenic forest types truly translates into more fire today is suspect, especially considering that these forest types are currently perpetuated by means other than fire (e.g., clear-cutting for aspen, artificial regeneration for pine). Consequently, this anomaly is probably more a reflection of these forests responding to a combination of disturbances than an indicator of actual elevated fire conditions. This illustrates the need for caution when interpreting fire regimes solely on the basis of vegetation characteristics.
Further shortcomings occur when using vegetation layers classified solely by overstory dominance. For instance, understory and shrub cover characteristics, which influence fire behavior and flammability, must be assumed on the basis of their ecological association with overstory components. In most instances, this does not necessarily pose a problem, as shrub cover has been substantially reduced because of livestock overgrazing, lack of rejuvenating fires (Anderson 1991), elevated deer density and browse pressure (Côté et al. 2004), and resource monopolization by youthful developing forests (stem exclusion stage; Oliver and Larson 1996), hence rendering them less susceptible to fire today (largely in concert with overstory-based fire regime change).
However, exceptions do occur. For instance, mountain laurel (Kalmia latifolia L.) and rhododendron (Rhododendron maximum L.)—two highly flammable, sclerophyllous evergreen shrubs—have become prominent along the Appalachian chain as a result of past canopy disturbance (logging and chestnut blight [Cryphonectria parasitica]), the cessation of fire and livestock grazing, and the shrubs’ shade tolerance (Monk et al. 1985). Their presence could potentially result in more fire than is reflected in our maps (figures 1, 2; Moser et al. 1996; H. Grissino-Mayer, University of Tennessee– Knoxville, personal communication, 22 December 2006). Other forests along the northeastern coastal plain have experienced large increases in different native and invasive shrub species, particularly the flammable greenbriar (Smilax), following agricultural abandonment. While most oak and pine forests are currently less prone to severe fire as a result of fire suppression, certain forest understories are now more prone to severe fire because of dense shrub cover of unpalatable or invasive species.
Ecological ramifications of fire regime alteration
In the Americas, the antiquity of natural-origin fires (spanning millions of years), supplemented by human ignitions over thousands of years, has served as a strong evolutionary driver (Scott 2000, Bond et al. 2005). Where fire was common in a landscape, an abundant assortment of fire-tolerant species emerged over time. This explains the diverse array of fireadapted species and plant communities existing in the eastern United States upon European contact (Wright and Bailey 1982, Abrams 1992, Whitney 1994, Wade et al. 2000, Lorimer 2001). Concurrently, presettlement burning maintained open, high-light environments, which favored sun-loving (heliophytic) plants (Cottam 1949, Anderson 1998).
In most locations, fire continued to be an important landscape disturbance during early European settlement, thus maintaining fire-adaptive communities. At times, fire-adapted species actually increased because of other disturbance factors acting as fire surrogates, such as increases in oak and aspen caused by the extensive cutting of northern hardwoods (Palik and Pregitzer 1992, Schulte et al. 2007) or the replacement of blight-killed American chestnut (Castanea dentata [Marsh.] Borkh) by oak (Abrams 1992). However, with time, fire suppression eventually prevailed (figure 3), with profound and unforeseen repercussions for fire-dependent environments (figure 4). Without the rejuvenating effects of recurrent fire, environmental conditions shifted incrementally to favor fire ensitive, shade-tolerant competitors. Under this scenario, larger life forms (trees > shrubs > grasses or forbs) gain a distinct advantage by overtopping and shading their competitors. Over time, trees grew to form closed-canopy forests. Under reduced light conditions, fire-adapted species performed poorly in the understory and increasingly gave way to shade-tolerant species.
Thus began the cycle of “mesophication,” a term coined here to describe the escalation of mesic microenvironmental conditions, accompanied by ever-diminishing prospects for fire and fire-dependent heliophytic species. By altering environmental conditions, shade-tolerant species deter fire through (a) dense shading that promotes moist, cool microclimates and (b) the production of fuels that are not conducive to burning (flaccid, moisture-holding leaf drop; moist, rapidly decaying woody debris). This phenomenon is reinforced and amplified by feedback loops, whereby conditions continually improve for shade-tolerant mesophytic species and further deteriorate for shade-intolerant, fire-adapted species. This phenomenon is not confined to this region but is happening worldwide as a result of fire exclusion (Bond et al. 2005).
Fire suppression and mesophication in oak-pine ecosystems
In presettlement times, recurrent surface burns maintained oak-pine ecosystems in a variety of open states, allowing high-light conditions to sustain an abundance of grasses, forbs, and shrubs (Abrams 1992, Whitney 1994, Anderson 1998, Lorimer 2001). Witness-tree studies bear this out, with open-canopy, low-density conditions prevailing (22 to 155 trees per ha; table 4). Presettlement tree density was largely a function of fire frequency and severity. The resulting variation was richly displayed on the presettlement landscape, wherein annually burned prairies were bounded by a continuum of savannas, open woodlands, and closed-canopy forests with increasing distance (Nuzzo 1986, Anderson 1998), although abrupt prairie-forest transitions did exist along natural firebreaks (e.g., rivers). Similar structural and compositional gradients, from fire-dependent oak savanna to fire-intolerant mesophytic forests, often ringed Native villages or travel corridors from which broadcast burning emanated (Dorney and Dorney 1989). Even though presettlement trees tended to be large on average (quadratic mean diameter of 30to 42 centimeters [cm]), stand basal areas were low to moderate, as a result of tree sparseness (9 to 22 square meters [m2] per ha; Fralish et al. 1991).
The cumulative effects of logging, grazing, and the eventual suppression of surface fires have radically changed oak pine systems. Compared with their predecessors, modern communities are substantially denser (133 to 650 trees per ha), representing increases of up to tenfold (table 4). Much of this increase is in small size classes, as illustrated by structural shifts toward inverse J-shaped diameter distributions. Although average tree diameters are smaller (quadratic mean diameter of 17 to 35 cm), tree densities have compensated, permitting higher stand basal areas to prevail (15 to 30 m2 per ha; Fralish et al. 1991). A compositional shift from fire-dependent xerophytic species (oak, pine, chestnut) to fire-sensitive mesophytic species (maple [Acer], cherry [Prunus], hemlock [Tsuga]) is readily apparent (table 5, figure 5a). Accordingly, stand-level tree richness has also increased (table 4) as a new suite of previously fire-restricted species has recruited into tree size classes. However, this is probably only a temporary phenomenon that will reverse itself in time, as oak, pine, and other fire-adaptive species give way to shade-tolerant species through gap-phase replacement. Where limited pools of replacement species exist (e.g., on highly fragmented landscapes or where past fire regimes greatly inhibited late-successional trees; Cottam 1949, Auclair and Cottam 1971), tree richness could fall well below historic levels.
The dramatic decline in oak and pine recruitment over the last 50-plus years on all but the most xeric and nutrient poor sites dates directly to the 1940s and 1950s, when broadcast burning plummeted in the East (figure 3). In the absence of fire, a variety of highly competitive, later-successional, gap-opportunistic, mesophytic hardwoods now regenerate, including red maple (Acer rubrum L.), sugar maple (Acer saccharum Marsh.), beech (Fagus grandifolia Ehrh.), birch, cherry, tulip poplar (Liriodendron tulipifera L.), and blackgum (Nyssa sylvatica Marsh.) (table 5, figure 5a; Abrams 1992). The high leaf area of shade-tolerant species casts heavy shade and limits air movement, effectively altering understory microclimate. Increased relative humidity and decreased radiation and wind speeds result in a cooler and moister understory and forest floor (Nauertz et al. 2004). These microclimatic conditions decrease understory flammability both directly (through dampness) and indirectly (through moisture-accelerated decomposition and fuel load reduction), and produce a seedbed more conducive for mesophytic species, thus promoting the mesophication cycle. Documented current and projected future increases in atmospheric humidity might further augment the mesophication process (Willett et al. 2007).
Further “fireproofing” occurs as fuel-bed inputs (leaf litter, woody debris) shift from oak and pine to mesophytic trees (cf. figure 5b and 5c; Washburn and Arthur 2003). The change in the composition and quality of litter greatly alters decomposition rates and flammability. The heat content of litter is a function of many factors, including specific leaf mass, carbon content (e.g., cellulose and lignin), leaf chemistry (volatiles), and packing ratio (White 1987, Scarff and Westoby 2006). A lower packing ratio creates a more open, better aerated litter layer, which increases flammability (Scarff and Westoby 2006). The lignin content of leaf litter affects its decomposition rate, with high lignin litter decomposing less rapidly (Cromack and Monk 1975). For example, in a study of five eastern US tree species, leaf lignin content decreasedas follows: pine > oak > maple > tulip poplar > basswood (Tilia americana L.; White 1987). The percentage of lignin and the sclerophyll index were typically higher in chestnut oak (Quercus prinus L.), scarlet oak (Quercus coccinea Muenchh.), white oak (Quercus alba L.), hickory (Carya), American sources needed (in terms reestablishing a burning regime in a system not prone to burn) to restore fire-based systems on the landscape after it becomes mesophytic.
On xeric landscapes, fire-based communities are more entrenched and resilient (note deeper basins on the upper plane in figure 6c). As a result, shifts toward mesophytic hardwoods are more gradual when fire is suppressed (note the higher berm before the forward-shift point). This is consistent with ecological theory, according to which oak and other fireadapted, drought-tolerant species compete better against nutrient- and moisture-demanding, late-successional species on infertile, drought-prone landscapes (Abrams 1990). On the most environmentally severe sites (extremely sandy or shallow to-bedrock soils), these communities may continue to exist even in the absence of fire (as represented by shaded balls on the upper plane; figure 6d). State changes on xeric landscapes are not as abrupt, and not necessarily as enduring, as those on mesic landscapes, as illustrated by the reduced bifurcation fold and basin depth of mesophytic hardwoods.
These illustrations of alternative stable states (figure 6) have practical implications for managing fire-adaptive landscapes, especially those with altered fire regimes. The rate at which fire-adaptive communities undergo sophication and convert to mesophytic hardwoods is dictated by landscape conditions. Generally, the more mesic and fertile a system is, the more rapid and steadfast the conversion will be. However, overstory disturbance (cutting, windstorms) can accelerate this transition on any landscape where a mesophytic understory is present (Abrams and Nowacki 1992). Once communities turn mesophytic, the prospects of returning fire and fire adapted communities to the landscape are limited because of mesophication barriers, the loss of fire-adapted species pools, the establishment of nonnative invasives, and prohibitive management costs associated with prescribed burning. Millions of hectares are in this situation (Abrams 2005). If land managers do not act soon, they will face increasingly expensive and difficult restoration efforts in the future. Furthermore, far more energy is required to restore burning regimes and fire apted species on mesic landscapes than on xeric landscapes. Because of this, prevention through prescribed burning is most urgently needed on mesic landscapes. However, once communities have converted to mesophytic hardwoods, efforts are probably best spent on retaining fire-adaptive communities on xeric systems.
The magnitude of change and the need for restoration
Although humans have a long history (about 12,000 years) on the North American continent, the magnitude of change wrought by European settlement has no parallel since the last glaciation (Whitney 1994, Cole et al. 1998). In New England, rates of landscape change have been far greater in the past 300 years than in the previous 1000 years as a result of forest cutting, agricultural conversion, urban development, altered fire regimes and herbivore populations, nonnative species introductions, and atmospheric pollution (Fuller et al. 1998). Concurrently, there has been a homogenization of regional vegetation and a dissociation of past vegetation climate relations (also see Glitzenstein et al. 1990). There has been no return to presettlement conditions because of continuing low-level disturbance and perhaps insufficient recovery time. McIntosh (1972) drew the same conclusion from research in the Catskill Mountains, noting that nothing suggests that the presettlement dominance of beech or extensive hemlock forest will reemerge anytime soon, if ever.
In the upper Great Lakes states, changes during the last 150 years were found to be 2.4 times greater than the changes recorded over the preceding 1000 years (Cole et al. 1998). Here, forestland declined by 40%, and much of the remaining forest was converted to early successional forest types as a result of extensive logging. Pine forests, boreal forests and conifer swamps, and northern mesic forests all decreased (by 78%, 62%, and 61%, respectively), whereas aspen-birch forest increased (by 83%; Cole et al. 1998). Likewise, the presettlement pattern of hemlock forest may have been irretrievably lost because of logging and fire (White and Mladenoff 1994). Climate-driven changes during this period are probably inconsequential compared with the effects wrought by Europeans (Webb 1973). The severity of late 19th- and early 20th-century disturbance, coupled with present-day overbrowsing by white-tailed deer (Odocoileus virginianus), has greatly homogenized regional vegetation, in terms of the composition and structure of both overstory (Schulte et al. 2007) and understory strata (Rooney et al. 2004).
In the central hardwoods, pollen data indicate that rates of vegetation change over the last 150 years are at least an order of magnitude higher than during the previous 4000 years (Cole and Taylor 1995). This extreme shift in rate change is attributed to intensive logging and burning during the late 19th century, exotic species invasion, atmospheric nitrogen deposition (resulting in accelerated succession), and recent fire exclusion.
The demise of fire across the East documented here (figures 2, 3) is consistent with the dramatic and unprecedented rate shifts of vegetation change expressed above. Restoration opportunities are rapidly waning as (a) fire-adaptive floras are progressively lost to shading, competition, and preferential herbivory; (b) older seed-bearing individuals succumb to old age and existing seed banks lose viability over time; and (c) understory and forest floor conditions become increasingly mesophytic (Abrams 2005). In some cases, fire suppression has allowed for successional changes that have no ecological analogue or antecedent (Auclair and Cottam 1971). Unprecedented levels of deer herbivory further complicate things, directing succession toward less palatable species, including exotics (Côté et al. 2004, Rooney et al.2004).
Fire suppression-induced shifts to closed-canopy forests are most serious on formerly open pyrogenic landscapes where fire-based evolutionary filters have constrained the distribution and availability of fire-sensitive, shade tolerant species. Here, tree diversity, which is cresting because of the intermingling of fire-adaptive, shade-intolerant species with fire-sensitive, shade-tolerant species, might eventually sink to historic lows because of the scant number of shade-tolerant replacements coupled with ongoing deer herbivory (Côté etal. 2004). Indeed, diversity reductions and extirpations have already happened among ground flora associates in the
absence of fire (figure 5d; Anderson and Schwegman 1991). This alarming harbinger of things to come can be avoided through the reintroduction of fire onto eastern landscapes (figure 5e). But time is running out, as systems may be approaching critical ecological thresholds and near-irreversible state shifts.
Setting restoration priorities using prescribed burning can be difficult, as all fire-based communities are important. Burning regimes should be established according to the relations between fire and vegetation, with prairies burned most frequently (annually or biennially) and with progressively longer fire return times for savannas, woodlands, and forests (Anderson 1991, 1998). Site conditions (mesic versus xeric) should be considered along this fire community gradient (prairie to forest), as they dictate the rapidity of vegetation change without fire. Priority should be placed on prescribing fire on mesic sites, as once these sites undergo mesophication, it is difficult to reestablish burning regimes. From a landscape perspective, restoration opportunities are probably greatest on oak and pine woodlands and forests, since lands formerly harboring tallgrass prairie-savanna systems have been largely converted to agriculture, with little land-use change in sight (Iverson and Risser 1987). By focusing on large, contiguous ownerships, especially on federal and state lands where restoration is a priority, larger landscapes could be burned, thereby maximizing benefit-to-cost ratios (spreading relatively fixed costs over a larger area) and allowing variation in fire behavior to form a more “natural” mosaic of burn severities, vegetation patches, and niches for a greater array of species. Considering the scale of fire-suppression effects across the eastern United States, burning larger landscapes is the only feasible approach to make any real headway.
Before European settlement, vast areas of the eastern deciduous biome were dominated by fire-adapted ecosystems, most notably tallgrass prairies and oak-pine savannas, woodlands, and forests. Although surface burns were most prevalent, presettlement fire regimes varied according to climate, topography, and Native American populations (primary igniters), creating a mosaic of vegetation types within each of the major formations. European settlement dramatically altered eastern disturbance regimes through land clearing, extensive timber harvesting, severe fires, and the introduction of nonnative pathogens (e.g., chestnut blight) and invasive plants. In most cases, fire dependent species maintained themselves during this period either directly through fire or indirectly through other surrogate disturbance agents (e.g., cutting).
Euro-American ties with the land began to change in the early 1900s as a result of technology (with increased farm productivity leading to field abandonment) and continued to change as a result of conservation measures (with fire suppression policies affecting succession and game laws leading to deer overabundance). This time, however, the changes in disturbance regimes worked against fire-adapted species. Without fire or fire surrogates, the competitive balance quickly shifted from heliophytic, fire-adapted species to shade-tolerant, fire-sensitive species. This change is apparent in oak-pine systems, wherein oak and pine recruitment has waned on all but the most xeric sites. Oak and pine are aggressively replaced by mesophytic and later-successional hardwood species, such as red maple, sugar maple, beech, blackgum, and black cherry (Prunus serotina Ehrh.). Forest microenvironments, in turn, come shadier, cooler, and moister. The leaf litter of these replacement species is less flammable and more rapidly mineralized than that of oaks and pines, reinforcing the lack of fire and the mesophication of eastern forests. Vegetation changes associated with fire suppression and mesophication are swifter and more enduring on mesic than on xeric sites. The trend toward mesophytic hardwoods will continue on landscapes where fire is actively suppressed, rendering them less combustible and creating further difficulties for land managers and conservationists who wish to restore past fires regimes and fire-based communities.
This article was greatly assisted by numerous USDA Forest Service colleagues. Specifically, we thank Sue Steward, Regina Winkler, and Tom DeMeo for their efforts in acquiring and compiling fire data. Roger Fryar, Beth Buchanan, Bruce Davenport, David Cleland, and Melissa Thomas-Van Gundy assisted in fire regime group assignment. Dialogue with Eugene DeGayner and Mike Ablutz greatly fostered the integration of alternative stable state concepts. A special thanks to Bob Carr for geospatial data acquisition, analysis, and map production. We appreciate Don Waller’s (University of Wisconsin-Madison) insights on linguistics and terminology.
Abrams MD. 1990. Adaptations and responses to drought in Quercus species of North America. Tree Physiology 7: 227-238. ———. 1992. Fire and the development of oak forests. BioScience 42: 346-353.
——. 2005. Prescribing fire in eastern oak forests: Is time running out? Northern Journal of Applied Forestry 22: 1-7.
Abrams MD, Nowacki GJ. 1992. Historical variation in fire, oak recruitment, and post-logging accelerated succession in central Pennsylvania. Bulletin of the Torrey Botanical Club 119: 19-28.
Abrams MD, Ruffner CM. 1995. Physiographic analysis of witness-tree distribution (1765-1798) and present forest cover through north central Pennsylvania. Canadian Journal of Forest Research 25: 659-668.
Anderson RC. 1991. Presettlement forests of Illinois. Pages 9-19 in Burger GV, Ebinger JE, Wilhelm GS, eds. Proceedings of the Oak Woods Management Workshop. Charleston: Eastern Illinois University.
———. 1998. Overview of Midwestern oak savanna. Transactions of the
Wisconsin Academy of Sciences, Arts, and Letters 86: 1-18.
Anderson RC, Schwegman JE. 1991. Twenty years of vegetational change on a southern Illinois barren. Natural Areas Journal 11: 100-107.
Auclair AN, Cottam G. 1971. Dynamics of black cherry (Prunus serotina Erhr.) in southern Wisconsin oak forests. Ecological Monographs 41: 153-177.
Beisner BE, Haydon DT, Cuddington K. 2003. Alternative stable states in ecology. Frontiers in Ecology and the Environment 1: 376-382.
Bond WJ, Woodward FI, Midgley GF. 2005. The global distribution of ecosystems in a world without fire. New Phytologist 165: 525-538.
Brown PM, Ryan MG, Andrews TG. 2000. Historical surface fire frequency in ponderosa pine stands in research natural areas, central Rocky Mountains and Black Hills, USA. Natural Areas Journal 20: 133-139.
Carreiro MM, Sinsabaugh RL, Repert DA, Parkhurst DF. 2000. Microbial enzyme shifts explain litter decay responses to simulated nitrogen deposition. Ecology 81: 2359-2365.
Chojnacky DC, Mickler RA, Heath LS, Woodall CW. 2004. Estimates of down woody materials in eastern US forests. Environmental Management 33 (suppl. 1): S44-S55.
Clark JS. 1990. Twentieth-century climate change, fire suppression, andforest production and decomposition in northwestern Minnesota.
Canadian Journal of Forest Research 20: 219-232.
Cole KL, Taylor RS. 1995. Past and current trends of change in a dune prairie/oak savanna reconstructed through a multiple-scale history. Journal of Vegetation Science 6: 399-410.
Cole KL, Davis MB, Stearns R, Guntenspergen G, Walker K. 1998. Historical landcover changes in the Great Lakes Region. Pages 43-50 in Sisk TD,ed. Perspectives on the Land-use History of North America: A Context for Understanding Our Changing Environment. Springfield (VA): US Geological Survey, Biological Resources Division. Biological Science Report USGS/BRD/BSR 1998-0003.
Côté SD, Rooney TP, Tremblay J-P, Dussault C, Waller DM. 2004. Ecological impacts of deer overabundance. Annual Review of Ecology, Evolution, and Systematics 35: 113-147.
Cottam G. 1949. The phytosociology of an oak woods in southwestern Wisconsin. Ecology 30: 271-287.
Cromack K Jr, Monk CD. 1975. Litter production, decomposition, and nutrient cycling in a mixed-hardwood watedshed and a white pine watershed. Pages 609-624 in Howell FG, Smith MH, eds. Mineral Cycling
in Southeastern Ecosystems: Proceedings of a Symposium Held at Augusta, Georgia, May 1-3, 1974. Oak Ridge (TN): Technical Information Center, Office of Public Affairs, US Energy Research and Development Administration. ERDA Symposium Series, CONF-740513.
DeSelm HR. 1994. Vegetation results from an 1807 land survey of southern middle Tennessee. Castanea 59: 51-68.
DeVivo MS. 1991. Indian use of fire and land clearance in the southern Appalachians. Pages 306-310 in Nodvin SC, Waldrop TA, eds. Fire and the Environment: Ecological and Cultural Perspectives: Proceedings of an International Symposium, Knoxville, Tennessee, March 20-24, 1990. Asheville (NC): US Department of Agriculture, Forest Service, Southeastern Forest Experiment Station. General Technical Report SE-69.
Dorney CH, Dorney JR. 1989. An unusual oak savanna in northeastern Wisconsin: The effect of Indian-caused fire. American Midland Naturalist 122: 103-113.
Dyer JM. 2001. Using witness trees to assess forest change in southeastern Ohio. Canadian Journal of Forest Research 31: 1708-1718.
Fei S, Steiner KC. 2007. Evidence for increasing red maple abundance in the eastern United States. Forest Science 53: 473-477.
Foster DR, Motzkin G, Slater B. 1998. Land-use history as long-term broadscale disturbance: Regional forest dynamics in central New England. Ecosystems 1: 96-119.
Fralish JS, Crooks FB, Chambers JL, Harty FM. 1991. Comparison ofpresettlement, second-growth and old-growth forest on six site types in the Illinois Shawnee Hills. American Midland Naturalist 125: 294-309.
Frost CC. 1998. Presettlement fire frequency regimes of the United States: A first approximation. Tall Timbers Fire Ecology Conference Proceedings 20: 70-81.
Fuller JL, Foster DR, McLachlan JS, Drake N. 1998. Impact of human activity on regional forest composition and dynamics in central New England. Ecosystems 1: 76-95.
Gleason HA. 1913. The relation of forest distribution and prairie fires in the Middle West. Torreya 13: 173-181.
Glitzenstein JS, Canham CD, McDonnell MJ, Streng DR. 1990. Effects of environment and land-use history on upland forests of the Cary Arboretum, Hudson Valley, New York. Bulletin of the Torrey Botanical Club 117: 106-122.
Guyette RP, Dey DC, Stambaugh MC, Muzika R-M. 2006. Fire scars reveal variability and dynamics of eastern fire regimes. Pages 20-39 in Dickinson MB, ed. Fire in Eastern Oak Forests: Delivering Science to Land Managers: Proceedings of a Conference, November 15-17, 2005, Fawcett Center, the Ohio State University, Columbus, Ohio. Newtown Square (PA): US Department of Agriculture, Forest Service. General Technical Report NRS-P-1.
Haines DA, Sando RW. 1969. Climatic Conditions Preceding Historically Great Fires in the North Central Region. St. Paul (MN): US Department of Agriculture, Forest Service, North Central Forest Experiment Station. Research Paper NC-34.
Heinselman ML. 1973. Fire in the virgin forests of the Boundary Waters Canoe Area, Minnesota. Quaternary Research 3: 329-382.
Iverson LR, Risser PG. 1987. Analyzing long-term changes in vegetation with geographic information system and remotely sensed data. Advances in Space Research 7: 183-194.
Loomis WE, McComb AL. 1944. Recent advances of the forest in Iowa. Proceedings of the Iowa Academy of Science 51: 217-224.
Lorimer CG. 1985. The role of fire in the perpetuation of oak forests. Pages 8-25 in Johnson JE, ed. Challenges in Oak Management and Utilization.
Madison: Cooperative Extension Service, University of Wisconsin.
———. 2001. Historical and ecological roles of disturbance in eastern North American forests: 9,000 years of change. Wildlife Society Bulletin 29: 425-439.
MacMillan PC. 1988. Decomposition of coarse woody debris in an old growth Indiana forest. Canadian Journal of Forest Research 18: 1353-1362.
McIntosh RP. 1972. Forests of the Catskill Mountains, New York. Ecological Monographs 42: 143-161.
Monk CD, McGinty DT, Day FP Jr. 1985. The ecological importance of Kalmia latifolia and Rhododendron maximum in the deciduous forest of the southern Appalachians. Bulletin of the Torrey Botanical Club 112: 187-193.
Moser W, Ducey MJ, Ashton PMS. 1996. Effects of fire intensity on competitive dynamics between red and black oaks and mountain laurel. Northern Journal of Applied Forestry 13: 119-123.
Nauertz EA, Crow TR, Zasada JC, Teclaw RM. 2004. Microclimatic Variation between Managed and Unmanaged Northern Hardwood Forests in Upper Michigan, USA. St. Paul (MN): US Department of Agriculture, Forest Service, North Central Research Station. General Technical Report NC-236.
Nuzzo VA. 1986. Extent and status of Midwest oak savanna: Presettlement and 1985. Natural Areas Journal 6: 6-36 Oliver CD, Larson BC. 1996. Forest Stand Dynamics: Updated Edition. New York: Wiley.
Palik BJ, Pregitzer KS. 1992. A comparison of presettlement and present-day forests on two bigtooth aspenominated landscapes in northern Lower Michigan. American Midland Naturalist 127: 327-338.
Parsons DJ. 1976. The role of fire in natural communities: An example from the southern Sierra Nevada, California. Environmental Conservation 3: 91-99.
Pyne SJ. 1982. Fire in America: A Cultural History of Wildland and Rural Fire. Princeton (NJ): Princeton University Press.
Rooney TP, Wiegmann SM, Rogers DA, Waller DM. 2004. Biotic impoverishment and homogenization in unfragmented forest understory communities. Conservation Biology 18: 787-798.
Sauer CO. 1975. Man’s dominance by use of fire. Geoscience and Man 10: 1-13.
Scarff FR, Westoby M. 2006. Leaf litter flammability in some semi-arid Australian woodlands. Functional Ecology 20: 745-752.
Scheffer M, Carpenter S, Foley JA, Folke C, Walker B. 2001. Catastrophic shifts in ecosystems. Nature 413: 591-596.
Schmidt KM, Menakis JP, Hardy CC, Hann WJ, Bunnell DL. 2002. Development of Coarse-scale Spatial Data for Wildland Fire and Fuel Management. Fort Collins (CO): US Department of Agriculture, Forest Service, Rocky Mountain Research Station. General Technical Report RMRS-GTR-87.
Schroeder WA. 1981. Presettlement Prairie of Missouri. Jefferson City (MO): Missouri Department of Conservation. Natural History Series No. 2.
Schulte LA, Mladenoff DJ, Crow TR, Merrick LC, Cleland DT. 2007. Homogenization of northern U.S. Great Lakes forests due to land use. Landscape Ecology 22: 1089-1103.
Scott AC. 2000. The pre-Quaternary history of fire. Palaeogeography, Palaeoclimatology, Palaeoecology 164: 281-329.
Tyrrell LE, Crow TR. 1994. Dynamics of dead wood in old-growth hemlock hardwood forests of northern Wisconsin and northern Michigan. Canadian Journal of Forest Research 24: 1672-1683.
Van Lear DH. 2004. Upland oak ecology and management. Pages 123-127 in Spetich MA, ed. Upland Oak Ecology Symposium: History, Current Conditions, and Sustainability. Asheville (NC): US Department of Agriculture, Forest Service, Southern Research Station. General Technical Report SRS-73.
Wade DD, Brock BL, Brose PH, Grace JB, Hoch GA, Patterson WA III. 2000. Fire in eastern ecosystems. Pages 53-96 in Brown JK, Smith JK, eds.
Wildland Fire in Ecosystems: Effects of Fire on Flora. Ogden (UT): US Department of Agriculture, Forest Service, Rocky Mountain Research Station. General Technical Report RMRS-GTR-42, vol. 2.
Washburn CSM, Arthur MA. 2003. Spatial variability in soil nutrient availability in an oak-pine forest: Potential effects of tree species. Canadian Journal of Forest Research 33: 2321-2330.
Webb T III. 1973. Pre- and postsettlement pollen from a short core, Trout Lake, north-central Wisconsin. Transactions of the Wisconsin Academy of Sciences, Arts, and Letters 61: 141-148.
White MA, Mladenoff DJ. 1994. Old-growth landscape transitions from pre-European settlement to present. Landscape Ecology 9: 191-205.
White RH. 1987. Effects of lignin content and extractives on the higher heating value of wood. Wood and Fiber Science 19: 446-452.
Whitney GG. 1994. From coastal wilderness to fruited plain: A history of environmental change in temperate North America from 1500 to the present. New York: Cambridge University Press.
Willett KM, Gillett NP, Jones PD, Thorne PW. 2007. Attribution of observed surface humidity changes to human influence. Nature 449: 710-713.
Wolf J. 2004. A 200-year fire history in a remnant oak savanna in southeaster Wisconsin. American Midland Naturalist 152: 201-213.
Wright HA, Bailey AW. 1982. Fire Ecology: United States and Southern Canada. New York: Wiley.
Include this information when citing this material.
Managing forests with prescribed fire: Implications for a cavity-dwelling bat species
Justin G. Boylesa, Doug P. Aubreyb,*
a Department of Ecology and Organismal Biology, Indiana State University, Terre Haute, 47809, USA b USDA Forest Service, Savannah River, P.O. Box 700, New Ellenton, SC 29809, USA
Received 1 June 2005; received in revised form 27 September 2005; accepted 30 September 2005
Prescribed burning is used as a restoration and management technique in many deciduous forests of eastern North America. The effects of fire have been studied on habitat selection of many vertebrate species, but no studies have reported the effect of fire on bat roosting habitat. Fire initially leads to an influx of dead and dying trees, an increase of light availability, and a decrease of canopy and sub-canopy tree density. These characteristics are beneficial to many forest-dwelling vertebrates including cavity-roosting bats. We evaluated evening bat (Nycticeius humeralis) roost-site selection at the stand-scale in order to determine roosting preferences as they relate to prescribed burning. Standard radiotelemetry techniques were used to locate evening bat roost trees. Canopy light penetration and overstory tree density were measured in both burned and unburned forests. Sixty-three trees used as roosts by both male and female evening bats were located during both the summer and winter and all 63 roosts were located in the burned portion of the study area. Canopy light penetration was higher and canopy tree density was lower in the burned forest than unburned forest. An increase in light availability may release bats from one of the constraints suggested for many forest-dwelling bat species in roost tree selection—sun-exposure. This should increase the abundance of trees with characteristics suitable for roosting and may allow bats to roost throughout the interior of the forest as opposed to only on forest edges, thereby allowing bats to roost closer to foraging grounds and possibly lessening predation rates. Lower tree density may allow for ease of flight within the forest as well as more efficient locating of roost trees. In addition, there were a significantly higher proportion of dead trees, which evening bats commonly use as roost trees, in burned forests compared to unburned forests. Prescribed burning appears to initially lead to creation or restoration of favorable cavity-dwelling bat habitat and its continual implementation perpetuates an open sub-canopy. Therefore, we suggest that prescribed burning may be a suitable tool for management of roosting habitat for cavity-roosting bats.
Fire is critical in regulating and maintaining many forest ecosystems (Huddle and Pallardy, 1996; van Lear, 2002). In particular, much of the western portion of North America’s eastern deciduous forest is thought to have been shaped and maintained through fires set by Native Americans prior to European settlement (Cottam, 1949; Ladd, 1991; Pyne, 1982). Prescribed burning has been shown to alter many characteristics of forest habitat potentially affecting forest-dwelling bats including tree mortality, which increases available trees commonly used by wildlife (Huddle and Pallardy, 1996; Arthur et al., 1998; Hartman and Heumann, 2003; Aubrey, 2004); pathogen susceptibility, which expedites cavity formation (Burns, 1955; Paulsell, 1957; Smith and Sutherland, 2001); and canopy light penetration (Anderson and Brown, 1986; McCarty, 1998; Aubrey, 2004), which is known to affect roost suitability (Kurta et al., 1993; Brigham et al., 1997).
0378-1127/$ – see front matter # 2005 Elsevier B.V. All rights reserved.
Many forests are managed for timber harvest by the use of mechanical thinning or clear-cutting. Prescribed fire differs from these management techniques because fire is generally used to maintain or restore natural forest ecosystems and reduce understory competition, while other silvicultural methods are predominately used to maximize harvest yield and quality. When first implemented, prescribed burning decreases overstory tree density and basal area (Anderson and Brown, 1986; Peterson and Reich, 2001). Following this initial fire with frequent burns generally reduces fuel accumulation and subsequent burns are therefore relatively cool and somewhat nonuniform (Ladd, 1991). However many fire-sensitive seedlings and saplings are generally eliminated or prevented from regenerating (Lorimer, 1985; Ladd, 1991; Moser et al., 1996; Brose and van Lear, 1997; Barnes and van Lear, 1998). Fire-tolerant trees remain as overstory dominants and canopy recruitment coincides with periods of decreased burn frequency or intensity (Crow et al.,1994). For example, oaks possess thick bark which insulates them from heat associated with burning and are capable of rapid compartmentalization when damaged by fire which inhibits fungal infection and makes mature individuals relatively tolerant of fire (Lorimer, 1985; Abrams, 1985; Crow, 1988; Stearns, 1991; Smith and Sutherland, 1999; Peterson and Reich, 2001). Much of the western portion of the eastern deciduous forest is believed to have resembled the structure and composition of a woodland (i.e. moderate to low canopy coverage) more than a forest (i.e. high canopy coverage) prior to European settlement, which is largely attributed to fire (Cottam, 1949; Curtis, 1959; Nuzzo, 1986; Ladd, 1991). Therefore, managing forests with prescribed fire reintroduces a historic disturbance process that other silvicultural techniques lack, and may provide a more heterogeneous habitat for wildlife that is similar to forested areas prior to wide-spread fire suppression by European settlers. Furthermore, prescribed burning has become increasingly common over the past few decades, as land managers have seen the effects of fire suppression. Specifically, fire has been most commonly reintroduced to systems where conservation of biodiversity and restoration of historic ecosystem processes are paramount.
Numerous studies have focused on vertebrates in forests maintained by prescribed burning (e.g. reptiles, McLeod and Gates, 1998; small mammals, Simon et al., 2002; amphibians, Schurbon and Fauth, 2003; birds, Blake, 2005). However, to our knowledge, there are no studies reporting habitat selection of tree-dwelling bats in burned forests, although the need for such studies has been suggested (Menzel et al., 2001b; Carter et al., 2002). Furthermore, the effects of forest management on roosting habitat of bats are not clear and it has been suggested that wildfires and prescribed burning may have detrimental (Chambers et al., 2002) or beneficial (Carter et al., 2002) impacts on bats. For some bat species, such as the eastern red bat (Lasiurus borealis), fire may pose a direct threat to survival as early spring burns remove litter where occasional winter roosting occurs and can potentially scorch hibernating individuals (Moorman et al., 1999; Rodrigue et al., 2001). Bats roosting in snags (standing dead trees) are also susceptible to direct disturbance from fire if roost trees ignite (Rodrigue et al., 2001), but this is probably not a major cause of mortality unless the roost burns quickly and the bat is in deep torpor (Carter et al., 2002). Availability of suitable roosts likely influences habitat selection (Kunz, 1982) and roosting sites are thought to be of critical importance to conservation of many bat species (Fenton, 1997). Fire generally removes understory saplings and may lead to the creation of suitable roost trees for cavity-roosting bats. Fire may also remove standing snags if fuel loading is high. However, fuel should not accumulate directly under a snag when burning is frequent so snags should persist under these circumstances. As fire increases the heterogeneity of forest structure and composition (Fule et al., 2004), there should be an increase in the diversity of available roosting habitat.
Previous studies have focused on activity (Humes et al., 1999; Patriquin and Barclay, 2003; Tibbels and Kurta, 2003; Mazurek and Zielinski, 2004), demographic parameters (Miller, 2003), and roosting preference (Campbell et al., 1996; Menzel et al., 2002; Elmore et al., 2004) of bats in heavily managed forests, but have not examined fire-based management. With the exception of a few anecdotal reports of L. borealis being driven from their leaf litter ibernacula during winter burns (Moorman et al., 1999; Rodrigue et al., 2001), there is little empirical data about how fire affects forest dwelling bats.
The objective of this study was to determine evening bat (Nycticeius humeralis) roost-site selection at the stand-scale in a forest heavily managed by fire and to understand those characteristics of the forest that may influence roost tree selection. The evening bat is a locally abundant cavity-dwelling bat species found throughout much of the southeastern United States, but it may be declining in parts of its range (Whitaker et al., 2002; Whitaker and Gummer, 2003). Evening bats are known to roost in large numbers in man-made structures (Watkins, 1969; Watkins and Shump, 1981; Bain and Humphrey, 1986; Wilkinson, 1992) and tree cavities (Wilk-inson, 1992; Bowles et al., 1996; Menzel et al., 1999, 2001a; Boyles et al., 2003; Boyles and Robbins, in press). Evening bats roost mainly in cavities in trees of various stages of decay (Bowles et al., 1996; Boyles and Robbins, in press), but relatively little is known about the formation or microclimate of the roosts. During the summer, evening bats roost mainly in large dead trees, but during the winter, live trees are commonly used (Boyles and Robbins, in press). They have a short wingspan and high wing loading so it has been predicted that they are not highly maneuverable relative to other bat species (Norberg and Rayner, 1987). Due to relatively inefficient flight, this species may avoid long foraging trips (Norberg and Rayner, 1987) and it has been suggested that evening bats forage close to their roosting areas Duchamp et al., 2004). Evening bats feed heavily on coleopterans, homopterans, and hemipterans (Whitaker, 2004). As with other tree roosting bat species, they spend over half of its time each day in roosts (Brigham et al., 1997), so conserving roosts is important in managing this species. Evening bats are commonly referred to as migratory in middle latitudes (Jones et al., 1967; Humphrey and Cope, 1968; Watkins, 1969; Wilkinson, 1992; Sparks et al., 1999; Geluso et al., 2004), but it appears that the population discussed herein is largely non-migratory (Boyles et al., 2003; Boyles and Robbins, in press) so roost trees refer to trees used throughout the year.
It was predicted that evening bats would prefer roosting in burned forests because of an increase in the density of dead and dying trees, an increase in light penetration and an overall decrease in overstory and understory tree ensity. These characteristics should benefit forest-dwelling bats and promote use of burned forests as roosting habitat. This study compliments previous work (Boyles and Robbins, in press), which reports the characteristics of roost trees and the surrounding habitat used by this population of evening bats during both the summer and winter. The results presented herein focus on roost selection at the forest stand-level.
2.1. Study area
We conducted this research on the Drury Conservation Area (DCA) in Taney County, Missouri (UTM 40.47.000N, 4.93.000E). DCA is a 1200 ha area located in extreme southwestern Missouri in the Ozark Mountains Region and is bordered on two sides by Bull Shoals Lake. It is actively managed by the Missouri Department of Conservation, which has implemented prescribed burning on approximately 55% of the potential area available for roosting habitat in an attempt to restore historic glades and oak-hickory woodlands and reduce red cedar (Juniperus virginiana) concentrations. Burning was initiated in 1999 after nearly 50 years of fire suppression and the area was then burned on a biennial schedule. All burning was conducted in March or April. The initial 1999 burn was probably more intense than subsequent burns because of accumulated fuels; therefore more overstory tree mortality may have occurred during or as a result of the initial burn (Aubrey, 2004).
Approximately 60% of DCA is dominated by oak-hickory forest with the remainder of the area being glades, wildlife food plots, ponds, and riparian areas (Missouri Department of Conservation, 1991). Elevation ranges from 185 to 335 m on DCA. Several gravel roads facilitate access to the interior of much of the forest and one large gravel road serves as the firebreak between burned and unburned portions of the forest. The canopy of the area consists almost entirely of deciduous trees from the white and red oak groups (Quercus spp.), hickories (Carya spp.), elms (Ulmus spp.), and ashes (Fraxinus spp.).
2.2. Location of roosting sites
Bats were captured from March 2003 to March 2004 using mist nets (Avinet, Dryden, NY, USA) of various lengths (6, 9, 12, or 18 m) placed across ponds or forest roads. The majority of netting sites were on the gravel road that acts as a firebreak between the burned and unburned forest, but one pond and two roads in the burned forest and one pond and one creek bed in the unburned forest were also netted. Approximately 55% of the available roosting area for evening bats was located in an area treated with prescribed fire. Thus, if evening bats were roosting at random, we would expect 55% of roost trees to be located in burned forest and 45% of roost trees to be located in unburned forest. Twenty-three evening bats were fitted with radio- transmitters (0.52 g; Model LB-2N, Holohil, Carp, Canada) by clipping fur to the skin in the interscapular region and affixing the transmitter with surgical adhesive (Skin Bond, Smith and Nephew Inc., Largo, FL, USA). The range of weights of bats fitted with transmitters was 7.5-13.5 g; therefore the transmitter represented 3.9-6.9% of the individual’s body mass.
Each bat’s roost tree was located every day following attachment of the transmitter and tracking was discontinued when the transmitter expired, was shed by the bat, or the bat remained outside of the study area for more than 5 days. This study was conducted year-round so roost trees include those used during both summer and winter by males and females in all reproductive classes (pregnant, lactating, post-lactating, and non-reproductive). All animal handling methods follow guidelines of the American Society of Mammalogists (Animal Care and Use Committee, 1998).
2.3. Canopy light penetration sampling
Leaf area index (LAI) was used as a measure of canopy light penetration to determine if three biennial prescribed burns had resulted in a more open canopy. LAI is an estimate of the ratio of overstory leaf area relative to ground area. A LAI of 0 indicates complete canopy light penetration whereas a LAI of 12 indicates no canopy light penetration (Hyer and Goetz, 2004). Here we define canopy light penetration (CLP) as: 12 LAI.
Two blocks each containing three transects in burned and unburned forests were monitored throughout the 2003 growing season. Unburned and burned forests were adjacent to one another with a gravel road acting as a fire buffer between them. LAI was obtained indirectly at each transect using an AccuPAR PAR-80 light interception device (Decagon Devices Inc., Pullman, WA, USA). Individual light measurements were collected 1.2 m above ground-level at five randomly spaced points along each transect. These five measurements were then averaged to calculate one LAI value, and therefore, one CLP value for each transect per sample period. Measurements were collected monthly throughout the 2003 growing season (April through September). The majority of canopy trees were deciduous species; thus, CLP was high in both burned and unburned forests during winter and was not measured from October through March.
2.4. Tree density
Canopy tree density was estimated in 0.05 ha circular plots centered on 25 randomly selected trees in each of the burn treatments. A random number generator was used to select UTM coordinates for the trees. Coordinates were located using a GPS unit (eTrex, Garmin International Inc., Olathe, Kansas) and selected the tree nearest that point to serve as the center of the plot. All trees in the plot greater than 10 cm diameter at breast height (dbh) were considered overstory trees and were counted and classified as either live or dead.
2.5. Statistical analysis
A binomial probability distribution was used to determine if bats roosted at random or at a proportion different from what would be expected given the amount of burned and unburned forest available. The effect of prescribed fire on CLP was assessed using a multi-factorial analysis of variance (ANOVA). The experiment was a nested block design with repeated measures. Month (April-September) and habitat (burned forest and unburned forest) were treated as fixed factors. Block (n = 2) and transect (n = 12) were treated as random factors, with transect nested under treatment. Mean separations were performed using a post hoc Tukey test. Tree density was analyzed using a t-test. In addition to absolute densities, the arcsine of the proportion of dead trees compared to total trees was calculated and analyzed using a t-test (Zar, 1984). All statistical analyses were conducted in Minitab 14. Alpha is 0.05 for all analyses.
3.1. Roost tree location
Fig. 1. Seasonal trends (mean S.E.) in canopy light penetration (CLP) calculated as 12 leaf area index in burned and unburned forest on Drury Sixty-three roost trees were used by 23 (11 females and 12 males) evening bats from 9 March 2003 to 31 March 2004. All 63 roost trees were located in the portion of the area that was subjected to prescribed burning, although many of the bats were captured on the road that serves as the break between burned and unburned forest or within 200 m of that road. Bats roosted in the burned forest exclusively and significantly more often than expected if they selected burned or unburned forest randomly (P < 0.001). In addition, nearly all the trees used as roosts were located more than 50 m from any forest edge (62 of 63). The one exception was a large white oak Quercus alba (L.) used by a male evening bat in October that was located at the forest edge less than 50 m from where that individual was captured. This tree was not used the first day after capture; it was used on the second and fourth days, so it appears that this tree was actively selected and was not used in response to stress caused by handling.
3.2. Canopy light penetration
Both the main effects of treatment (P < 0.001) and month (P < 0.001) as well as their interaction (P < 0.001) signifi-cantly affected CLP. Maximum leaf expansion occurred in May for the burned forest and July in the unburned forest. Averaged over the 6-month sample period, canopy light penetration was significantly greater in burned forest as compared to unburned forest (P < 0.001). CLP was high in both the burned and unburned forests in April (Fig. 1). Pairwise comparisons suggest that there was no difference in canopy light penetration between burned and unburned forests in April or May but differences were significant throughout the rest of the growing season (June-September, P < 0.05 in all comparisons). As expected, measurements collected prior to leaf expansion (April) suggest that there was no difference in CLP between the burned and unburned forests; therefore, there was likely no difference in light availability between the treatments during the winter.
3.3. Tree density
Mean overstory tree density per hectare was significantly higher in unburned forest (612.0 25.0) relative to burned Conservation Area, Taney County, Missouri during the 2003 growing season. CLP, as defined herein, is measured on a scale of 0-12, with 12 indicating complete light penetration and 0 indicating no light penetration. All measurements were collected mid-month. Asterisks indicate significant differences (at alpha = 0.05) between burned and unburned forests in each month.
forest (513.6 24.2; t = 2.83, P = 0.007) and live tree density was significantly higher in unburned forest (576.0 24.6) than burned forest (468.0 24.1; t = 3.13, P = 0.003). The density of dead trees was not significantly different between the burned (45.6 7.3) and unburned forests (36.0 4.3; t = 1.14, P = 0.263). However, the proportion of dead trees compared to total trees was significantly higher in burned forest (0.092 0.014) relative to unburned forest (0.060 0.007; t = 2.08, P = 0.045).
In our study area, evening bats showed a strong preference for forests managed with prescribed fires. Although there are no data on roost tree selection by evening bats before prescribed burning was initiated, it is likely that the forest characteristics were similar between what are now burned and unburned forests (Aubrey, 2004). All roost trees used by both males and females throughout the year were in the burned portion of the study area. For at least a few years after the initial burn, prescribed fire enhances roosting habitat for evening bats in several ways. First, burning increases the abundance of dead trees in some forests (Burns, 1955; Paulsell, 1957; Huddle and Pallardy, 1996; Peterson and Reich, 2001; Fule et al., 2004) and therefore increases the number of tree cavities formed by decay. We did not directly test the effect of fire on overstory tree mortality; however, dead trees were found in higher densities and at significantly higher proportions in the burned forest. Initial burns with high fuel accumulation can result in the formation of dead trees (Paulsell, 1957; Scowcroft, 1966; Anderson and Brown, 1986; White, 1986; Peterson and Reich, 2001) and leads to a forest with a large number of trees in various stages of decay. Ambient temperatures vary widely during the winter in southwestern Missouri so a large number of trees in varying stages of decay may provide sufficient options for evening bats to meet thermoregulatory needs simply by roost-switching. It has also been suggested that fire-scars allow entry for fungal pathogens, which can lead to heartrot and possibly mortality, which should promote cavity formation (Smith and Sutherland, 2001; Parsons et al., 2003). This population of evening bats is known to roost in trees in all decay stages (Boyles and Robbins, in press) and frequent burning should increase options for roost tree selection.
Second, CLP is significantly higher in burned forest than the unburned forest during the growing season. Although evening bats are not known to preferentially roost on forest edges, many tree-dwelling bats are thought to select roost trees that receive high levels of sun-exposure during the summer months (Kurta et al., 1993); therefore, trees selected as roosts are commonly taller than the canopy (Vonhof and Barclay, 1996; Britzke et al., 2003), near forest edges (Grindal, 1999) or areas with an open canopy (Menzel et al., 2001a). High light exposure is known to improve roost suitability (Kurta et al., 1993; Brigham et al., 1997) so high light penetration into the interior forest will allow bats to roost in trees that would not receive adequate sunexposure to facilitate thermoregulation in unburned forests. The ability to roost in interior forest trees that would not receive adequate sun-exposure in unburned forest may yield many benefits for evening bats. For example, the opportunity to use interior forest trees as roosts increases the availability of suitable roost trees in the habitat relative to populations that are forced to roost near forest edges or openings. This increase in suitable roost trees may allow bats to roost closer to their preferred foraging area and therefore reduce commuting distance and energy expenditure. Predation by meso-carnivores (Sparks et al., 2003) should also be lessened because the roosting sites are not concentrated in small forest patches or along forest edges, which may be easily found by and accessible to predators. An abundance of suitable roost trees may also facilitate frequent roost switching, which in turn may lessen ecto-parasite loads (Lewis, 1995).
Finally, prescribed burning may improve foraging habitat, thereby encouraging bats to roost in the vicinity. High fire frequency of low to moderate intensity prevents the regeneration of a sapling layer if preceded by a high intensity fire that removes this layer (Peterson and Reich, 2001). Exclusion of this stratum will reduce obstructions and make navigation easier in burned forest compared to unburned forest (Boyles and Robbins, in press). Evening bats forage in open areas and wooded habitats (Duchamp et al., 2004) and it has been noted that activity is higher for some bat communities in thinned forest compared to unthinned forest (Humes et al., 1999). It has been predicted that evening bats are not highly maneuverable and have relatively inefficient flight (Norberg and Rayner, 1987). This may prohibit evening bats from roosting in unburned areas because of dense understory that would make straight flight difficult. Other studies have also noted a preference for roosting in areas with a more open understory (Castleberry et al., 2005). Previous work has suggested that evening bats forage close to their roosting areas (Duchamp et al., 2004); therefore roost selection in burned forest may simply be an artifact of selection of burned habitat for foraging. In addition, the major food source of evening bats, coleopterans (Whitaker, 2004), have been found at both higher abundances and greater species richness in burned forests than unburned forests (Saint-Germain et al., 2004). Although it is difficult to distinguish if roosting habitat or foraging habitat is more important in observed habitat selection, anecdotally there does appear to be a close association between the two in this population of evening bats.
It is unlikely that any one of these reasons alone can adequately explain the preferential habitat selection seen in evening bats. Combinations of any or all of these broad forest characteristics may contribute to suitable habitat for this species and each may be of fluctuating importance throughout the year. For example, the difference in light penetration between burned and unburned forest is probably only important during the summer months. Because of the deciduous nature of the majority of the trees in southwestern Missouri, the difference in light penetration between burned and unburned forest will be lessened during the winter. Therefore, it is likely that evening bats roosted exclusively on the burned portion of the area during the winter because of prey availability, lessened clutter, or simple roost fidelity. However, it should be noted that many tree-dwelling bat species in the eastern United States only roost in trees during the summer months, so this may be inconsequential in reference to those species.
Prescribed burning has the potential to provide habitat for evening bats and possibly other species and should be taken into consideration when constructing management plans for these species. Fire may initially increase both the quantity and quality of roosting habitat for evening bats by creating an influx of dead and dying trees as well as facilitating disease and decay in live trees. This study deals only with the first 6 years following the initial burn, and long-term effects of burning may not be as beneficial to evening bats. For example, frequent burning may lead to a decline in roost trees by felling suitable snags and creating a canopy of fire-tolerant species that are not generally killed by fire (Curtis, 1959; Pyne, 1982; Crow, 1988; Ladd, 1991). However, anecdotal evidence suggests that snags persist through these low intensity burns, possibly because leaf litter fails to accumulate underneath a snag (personal observation). The same type of anecdotal evidence exists in southeastern long-leaf pine systems where biennial fire leaves snags intact because of reduced fuel accumulation near the base of the tree (S. Castleberry, University of Georgia, personal communication). To our knowledge, no studies have addressed the fate or residence time for snags suitable for roosting in a frequently burned system. Fire frequency should not remain a static part of management strategy. If biennial burns are continued, eventually the only trees left in the canopy will be fire-tolerant. It is necessary to withhold fire from areas to allow a sufficient fuel source to accumulate, which will allow for highintensity fires that can cause canopy tree mortality and create snags. However, benefits of managing with prescribed fire may surpass those of mechanical thinning techniques because of the random and delayed mortality imposed on canopy trees (Loomis, 1974). Furthermore, prescribed burning is a more cost-effective management tool than mechanical methods (Wade and Lunsford, 1988; Dubois et al., 1999).
This study demonstrates the preference of evening bats to periodically burned forest, but fire can also be beneficial to other bat species that utilize trees as roosts. For example, the Indiana bat (Myotis sodalis), listed as federally endangered in the United States, is known to use a large number of dead and dying trees as roosts because these trees often offer the exfoliating bark that this species uses as a roost-site (Kurta et al., 1993). Through mortality and damage to bark, fire will increase the abundance of trees with exfoliating bark (Burns, 1955; Paulsell, 1957; Smith and Sutherland, 1999) and thereby increase available roosting habitat for species such as the Indiana bat. Other bat species could benefit from fire as a management tool and it should be investigated in other regions with other bat species.
Fire does have the potential to negatively affect forest dwelling bat habitat. For species that preferentially roost in trees in late stages of decay, frequent fire may destroy roost trees before they become suitable for roosting. Frequent fire may also cause the loss of winter habitat for litter-roosting species such as L. borealis (Moorman et al., 1999; Boyles et al., 2003) by continually removing accumulated leaf litter from the forest floor. Long-term studies are necessary to understand the patterns and processes of snag residence time in a periodically burned forest. Resource managers should consider the different habitat needs and life history traits of both tree-dwelling and litter roosting bats when creating management plans. Furthermore, forests respond differently according to the season when burning occurs. For example, summer burns have been shown to cause increased overstory tree mortality relative to burns conducted in other seasons (van Lear and Waldrop, 1991; Brose and van Lear, 1997). Fires in this season would therefore benefit tree-dwelling species as well as allow leaf litter to accumulate in fall benefiting litter-roosting species. More research examining the effect of burn frequency and season of burning on a variety of taxa is necessary to properly manage forests for biodiversity.
Funding for this project was provided in part by the Missouri Department of Conservation, the City of Springfield, MO, Dickerson Park Zoo, and Southwest Missouri State University. We would like to thank L. Robbins and D.A. Wait for assisting in obtaining funding and providing equipment for this project. The Missouri Department of Conservation and the Bull Shoals Field Station provided vehicles, equipment, and access to their property. J. Timpone, M. Milam, B. Mormann, P. Brown, and many others assisted in capturing and tracking bats and conducting vegetation analysis. M. Milam, M. McKnight, M. Coleman, J. Orrock, and anonymous reviewers provided many helpful comments on earlier versions of this manuscript.
Abrams, M.D., 1985. Fire history of oak gallery forests in northeast Kansas tallgrass prairie. Am. Midl. Nat. 114, 188-191.
Anderson, R.C., Brown, L.E., 1986. Stability and instability in plant communities following fire. Am. J. Bot. 73, 364-368.
Animal Care and Use Committee, 1998. Guidelines for the capture, handling, and care of mammals as approved by The American Society of Mammalogists. J. Mamm. 79, 1416-1431.
Arthur, M.A., Paratley, R.D., Blakenship, B.A., 1998. Single and repeated fires affect survival and regeneration of woody and herbaceous species in an oakpine forest. J. Torrey Bot. Soc. 125, 225-236.
Aubrey, D.A., 2004. Savanna restoration through prescribed fire: demographic and physiological responses of oak and hickory seedlings and saplings to a changing light environment. Master’s Thesis, Southwest Missouri State University.
Bain, J.R., Humphrey, S.R., 1986. Social organization and biased primary sex ratio of the evening bat Nycticeius humeralis. Fla. Sci. 49, 22-31.
Barnes, T.A., van Lear, D.H., 1998. Prescribed fire effects on advanced regeneration in mixed hardwood stands. South. J. Appl. For. 22, 138-142.
Blake, J.G., 2005. Effects of prescribed burning on distribution and abundance of birds in a closed-canopy oak-dominated forest, Missouri, USA. Biol. Conserv. 121, 519-531.
Bowles, J.B., Howell, D., Van Zee, J.W., Wilson, G.M., 1996. Use of alternate roost trees by the evening bat, Nycticeius humeralis, in Iowa. In: Genoways, H.H., Baker, R.J. (Eds.), Contributions in Mammalogy: A Memorial Volume Honoring Dr. J. Knox Jones, Jr. Museum of Texas Tech University, Lubbock, Texas, pp. 217-224.
Boyles, J.G., Timpone, J.C., Robbins, L.W., 2003. Late-winter observations of red bats, Lasiurus borealis, and evening bats, Nycticeius humeralis, in Missouri. Bat Res. News 44, 59-61.
Boyles, J.G., Robbins, L.W. Characteristics of summer and winter roost trees used by evening bats (Nycticeius humeralis) in southwestern Missouri. Am. Midl. Nat., in press.
Brigham, R.M., Vonhof, M.J., Barclay, R.M.R., Gwilliam, J.C., 1997. Roosting behavior and roost-site preferences of forest-dwelling California bats (Myotis californicus). J. Mamm. 78, 1231-1239.
Britzke, E.R., Harvey, M.J., Loeb, S.C., 2003. Indiana bat, Myotis sodalis, maternity roosts in the southern United States. Southeast. Nat. 2, 235 242.
Brose, P.H., van Lear, D.H., 1997. Effects of seasonal prescribed fires on density of hardwood advanced regeneration in oak-dominated shelterwood stands.
In: Proceedings of the 25th Annual Hardwood Symposium, ‘‘25 Years of Hardwood Silviculture: A Look Back and a Look Ahead’’, 7-10 May, 1997, Cashiers, NC. National Hardwood Lumber Association, Memphis, TN, pp.
Burns, P.Y., 1955. Fire scars and decay in Missouri oaks. University of Missouri College of Agriculture, Agricultural Experiment Station Bulletin 642.
Campbell, L.A., Hallett, J.G., O’Connell, M.A., 1996. Conservation of bats in managed forests: use of roosts by Lasionycteris noctivagans. J. Mamm. 77, 976-984.
Carter, T.C., Ford, W.M., Menzel, M.A., 2002. Fire and bats in the Southeast and Mid-Atlantic: more questions than answers? In: Ford, W.M., Russell, K.R., Moorman, C.E. (Eds.), The Role of Fire for Nongame Wildlife Management and Community Restoration: Traditional Uses and New Directions. United States Department of Agriculture, General Technical Report NE-288. pp. 139-143.
Castleberry, S., Miles, A., Miller, D., Conner, L., 2005. Habitat ecology of bats at multiple scales in natural longleaf and intensively managed loblolly pine forests in Georgia. In: Abstract from 90th Annual Ecological Society of America Meeting, Montreal, Canada.
Chambers, C.L., Alm, V., Sider, M.S., Rabe, M.J., 2002. Use of artificial roosts by forest-dwelling bats in northern Arizona. Wildl. Soc. Bull. 30, 1085-1091.
Cottam, G., 1949. The phytosociology of an oak woods in south-western Wisconsin. Ecology 30, 271-287.
Crow, T.R., 1988. Reproductive mode and mechanisms for self-replacement of northern red oak (Quercus rubra): a review. Forest Sci. 34, 19-40.
Crow, T.R., Johnson, W.C., Adkisson, C.S., 1994. Fire and recruitment of Quercus in a postagricultural field. Am. Midl. Nat. 131, 84-97.
Curtis, J.T., 1959. The vegetation of Wisconsin. University of Wisconsin Press, Madison.
Dubois, M.R., Straka, T.J., Crim, S.D., Robinson, L.J., 1999. Costs and cost trends for forestry practices in the South. Forest Landowner 50, 28 32.
Duchamp, J.E., Sparks, D.W., Whitaker Jr., J.O., 2004. Foraging-habitat selection by bats at an urban-rural interface: comparison between a successful and less successful species. Can. J. Zool. 82, 1157-1164.
Elmore, L.W., Miller, D.A., Vilella, F.J., 2004. Selection of diurnal roosts by red bats (Lasiurus borealis) in an intensively managed pine forest in Mississippi. Forest Ecol. Manage. 199, 11-20.
Fenton, M.B., 1997. Science and the conservation of bats. J. Mamm. 78, 1-14.
Fule, P.Z., Cocke, A.E., Heinlein, T.A., Covington, W.W., 2004. Effects of an intense prescribed forest fire: is it ecological restoration. Restor. Ecol. 12, 220-230.
Geluso, K.N., Benedict, R.A., Kock, F.L., 2004. Seasonal activity and reproduction in bats of east-central Nebraska. Trans. Nebraska Acad. Sci. 29, 33 44.
Grindal, S.D., 1999. Habitat use by bats, Myotis spp., in western Newfoundland. Can. Field-Nat. 113, 258-263.
Hartman, G.W., Heumann, B.H., 2003. Prescribed fire effects in the Ozarks of Missouri: the Chilton Creek project 1996-2001. In: Proceedings of the Second International Wildland Fire Ecology and Fire Management Congress, 16-22 November, 2003, Orlando, FL.
Huddle, J.A., Pallardy, S.G., 1996. Effects of long-term annual and prescribed burning on tree survival and growth in a Missouri Ozark oak-hickory forest. Forest Ecol. Manage. 82, 1-9.
Humes, M.L., Hayes, J.P., Collopy, M.W., 1999. Bat activity in thinned, unthinned, and old-growth forests in western Oregon. J. Wildl. Manage. 63, 553-561.
Humphrey, S.R., Cope, J.B., 1968. Records of migration of the evening bat Nycticeius humeralis. J. Mamm. 49, 329.
Hyer, E.J., Goetz, S.J., 2004. Comparison and sensitivity analysis of instruments and radiometric methods for LAI estimation: assessments from a boreal forest site. Agric. Forest Meteorol. 122, 157-174.
Jones Jr., J.K., Fleharty, E.D., Dunnigan, P.B., 1967. The distributional status of bats in Kansas. Misc. Publ. Mus. Nat. Hist. Univ. Kansas 46, 1-33.
Kunz, T.H., 1982. Roosting ecology of bats. In: Kunz, T.H. (Ed.), Ecology of Bats. Plenum Press, New York, pp. 1-55.
Kurta, A., King, D., Teramino, J.A., Stribley, J.M., Williams, K.J., 1993. Summer roosts of the endangered Indiana bat (Myotis sodalis) on the northern edge of its range. Am. Midl. Nat. 129, 132-138.
Ladd, D., 1991. Reexamination of the role of fire in Missouri oak woodlands. In: Buger, G.V., Ebinger, J.E., Wilhelm, G.S. (Eds.), Proceedings of the Oak Woods Management Workshop, Eastern Illinois University, Charleston, pp.
Lewis, S.E., 1995. Roost fidelity of bats—a review. J. Mamm. 76, 481-496.
Loomis, R.M., 1974. Predicting the losses in sawtimber volume and quality from fires in oak hickory forests. USDA Forest Service Research Paper NC- 104.
Lorimer, C.G., 1985. The role of fire in the perpetuation of oak forests. In: Johnson, J.E. (Ed.), Challenges in Oak Management and Utilization. Cooperative Extension Service, University of Wisconsin, Madison, pp. 8-25.
Mazurek, M.J., Zielinski, W.J., 2004. Individual legacy trees influence vertebrate wildlife diversity in commercial forests. Forest Ecol. Manage. 193, 321-334.
McCarty, K., 1998. Landscape-scale restoration in Missouri savannas and woodlands. Restor. Manage. Notes 16, 22-32.
McLeod, R.F., Gates, J.E., 1998. Response of herpetofaunal communities to forest cutting and burning at Chesapeake farms, Maryland. Am. Midl. Nat. 139, 164-177.
Menzel, M.A., Krishon, D.M., Carter, T.C., Laerm, J., 1999. Notes on tree roost characteristics of the northern yellow bat (Lasiurus intermedius), the Seminole bat (L. seminolus), the evening bat (Nycticeius humeralis), and the eastern pipistrelle (Pipistrellus subflavus) Fla. Sci. 62, 185-193.
Menzel, M.A., Carter, T.C., Ford, W.M., Chapman, B.R., 2001a. Tree roost characteristics of subadult and female adult evening bats (Nycticeius humeralis) in the upper coastal plain of South Carolina. Am. Midl. Nat. 145, 112-119.
Menzel, M.A., Menzel, J.M., Carter, T.C., Ford, W.M., Edwards, J.W., 2001b. Review of the forest habitat relationships of the Indiana bat (Myotis sodalis).United States Department of Agriculture General Technical Report NE 284.
Menzel, M.A., Owen, S.F., Ford, W.M., Edwards, J.W., Wood, P.B., Chapman, B.R., Miller, K.V., 2002. Roost tree selection by northern long-eared bat (Myotis septentrionalis) maternity colonies in an industrial forest of the
central Appalachian mountains. Forest Ecol. Manage. 155, 107 114.
Miller, D.A., 2003. Species diversity, reproduction, and sex ratios of bats in managed pine forest landscapes of Mississippi. Southeast. Nat. 2, 59 72. Missouri Department of Conservation, 1991. Natural features inventory of Drury-Mincy Wildlife Area.
Moorman, C.E., Russell, K.R., Menzel, M.A., Lohr, S.M., Ellenberger, J.E., Van Lear, D.H., 1999. Bats roosting in deciduous leaf litter. Bat Res. News 40, 74-75.
Moser, W.K., Ducey, M.J., Ashton, P.M.S., 1996. Effects of fire intensity on competitive dynamics between red and black oaks and mountain laurel. North. J. Appl. For. 13, 119-123.
Norberg, U.M., Rayner, J.M.V., 1987. Ecological morphology and flight in bats (Mammalia; Chiroptera): wing adaptations, flight performance, foraging strategy and echolocation. Philos. Trans. R. Soc. London B: Biol. Sci. 316, 335-427.
Nuzzo, V., 1986. Extent and status of midwest oak savanna: presettlement and 1985. Nat. Areas J. 6, 6-36.
Parsons, S., Lewis, K.J., Psyllakis, J.M., 2003. Relationships between roosting habitat of bats and decay of aspen in the sub-boreal forests of British Columbia. Forest Ecol. Manage. 177, 559-570.
Patriquin, K.J., Barclay, R.M.R., 2003. Foraging by bats in cleared, thinned and unharvested boreal forest. J. Appl. Ecol. 40, 646-657.
Paulsell, L.K., 1957. Effects of burning on Ozark hardwood timberlands. University of Missouri College of Agriculture, Agricultural Experimental Station Bulletin 640.
Peterson, D.W., Reich, P.B., 2001. Prescribed fire in oak savanna: fire frequency effects on stand structure and dynamics. Ecol. Appl. 11, 914 927.
Pyne, S.J., 1982. Fire in America. Princeton University Press, Princeton, NJ. Rodrigue, J.L., Schuler, T.M., Menzel, M.A., 2001. Observations of bat activity during prescribed burning in West Virginia. Bat Res. News 42, 48-49.
Saint-Germain, M., Drapeau, P., Hebert, C., 2004. Comparison of coleoptera assemblages from a recently burned and unburned black spruce forests of northeastern North America. Biol. Conserv. 118, 583-592.
Schurbon, J.M., Fauth, J.E., 2003. Effects of prescribed burning on amphibian diversity in a southeastern U.S. National Forest. Conserv. Biol. 17, 1338 1349.
Scowcroft, P.G., 1966. The effects of fire on hardwood forests of the Missouri Ozarks. M.S. Thesis, University of Missouri Columbia, MO, pp. 126.
Simon, N.P.P., Stratton, C.B., Forbes, G.J., Schwab, F.E., 2002. Similarity of small mammal abundance in post-fire and clearcut forests. Forest Ecol. Manage. 165, 163-172.
Smith, K.T., Sutherland, E.K., 1999. Fire-scar formation and compartmentalization in oak. Can. J. Forest Res. 29, 166-171.
Smith, K.T., Sutherland, E.K., 2001. Terminology and biology of fire scars in selected central hardwoods. Tree-Ring Res. 57, 141-147.
Sparks, D.W., Choate, J.R., Winn, R.J., 1999. Observations on reproduction in three species of bats. Prairie Nat. 31, 245-248.
Sparks, D.W., Simmons, M.T., Gummer, C.L., Duchamp, J.E., 2003. Disturbance of roosting bats by woodpeckers and raccoons. Northeast. Nat. 10, 105-108.
Stearns, F., 1991. Oak woods: an overview. In: Buger, G.V., Ebinger, J.E., Wilhelm, G.S. (Eds.), Proceedings of the Oak Woods Management Workshop, Eastern Illinois University, Charleston, pp. 1-7.
Tibbels, A.E., Kurta, A., 2003. Bat activity is low in thinned and unthinned stands of red pine. Can. J. Forest Res. 33, 2436-2442.
van Lear, D.H., 2002. Upland oak ecology and management. In: Spetich, M.A. (Ed.), Upland Oak Ecology Symposium: History, Current Conditions, and Sustainability.
van Lear, D.H., Waldrop, T.A., 1991. Prescribed burning for regeneration. In: Duryea, M.L., Dougherty, P.M. (Eds.), Forest Regeneration Manual. Kluwer Academic Publishers, The Netherlands, pp. 235-250.
Vonhof, M.J., Barclay, R.M.R., 1996. Roost-site selection and roosting ecology of forest-dwelling bats in southern British Columbia. Can. J. Zool. 74, 1797-1805.
Wade, D.D., Lunsford, J.D. 1988. A guide for prescribed fire in southern forests. Revised Edition. United States Department of Agriculture, Forest Service, TechnicalPublicationR8-TP 11,Southern Region. Atlanta,Georgia, pp. 56.
Watkins, L.C., 1969. Observations on the distribution and natural history of the evening bat (Nycticeius humeralis) in northwestern Missouri and adjacent Iowa. Trans. Kansas Acad. Sci. 72, 330-336.
Watkins, L.C., Shump Jr., K.A., 1981. Behavior of the evening bat Nycticeius humeralis at a nursery roost. Am. Midl. Nat. 105, 258-268.
Whitaker Jr., J.O., 2004. Prey selection in a temperate zone insectivorous bat community. J. Mamm. 85, 460-469.
Whitaker Jr., J.O., Gummer, S.L., 2003. Current status of the evening, Nycticeius humeralis, in Indiana. Proc. Indiana Acad. Sci. 112, 55- 60.
Whitaker Jr., J.O., Brack Jr., V., Cope, J.B., 2002. Are bats in Indiana declining? Proc. Indiana Acad. Sci. 111, 95-106.
White, A.S., 1986. Prescribed burning for oak savanna restoration in central Minnesota. USDA Forest Service, North Central Forest Experiment Station; Research Paper NC-266.
Wilkinson, G.S., 1992. Information transfer at evening bat colonies. Anim. Behav. 44, 501-518.