R E S E A R C H A R T I C L E ABSTRACT: Managers of natural areas often employ controlled disturbances as a tool to manage and animal populations. This approach assumes that disturbances are responsible for the structure of biological communities and that appropriate application of the will ensure the persistence of native and animals. If in a community do not respond predictably to variation in disturbance regime, then management strategies based on emulating disturbance may fail to ensure the persistence of all species. In this study, we examined the efficacy of using prescribed fire as a tool • for managing populations of breeding and wintering birds in the pine rocklands of southern . We found that variation in fire history had little effect on vegetation structure and no effect on bird abundance. Instead, vegetation structure was more closely associated with water-table elevation and soil type, whereas most of the observed variation in the structure of bird assemblages appeared to be a function of degree of urbanization in the landscape. That the structure and composition of bird as- semblages was independent of variation in fire history suggests that manipulating the fire regime, at least within the range of variability observed in this study, is unlikely to prove effective as a means to manage bird populations. In general, our results argue for caution in assuming that a single process can Fire History and be used to control the structure of biological communities, especially in systems where landscapes have the Structure of been substantially altered by human activity. Index terms: Florida, hydrology, pine rocklands, prescribed fire, slash pine Pine-rockland Bird INTRODUCTION not without its critics, however; concerns Assemblages include whether scientists and managers Many of the concepts central to conser- have sufficient knowledge of how natural vation biology have received relatively disturbances act to adequately replicate little empirical evaluation (e.g., Simber- them (Landres et al. 1999) or whether John D. Lloyd 1,3 loff 2001), yet they form the basis for we can identify which disturbances to managing most populations of plants and manipulate or replicate (Simberloff 2001). 1Ecostudies Institute animals (Schulte et al. 2006). For example, As such, it remains unclear under what set P.O. Box 106 the concept of coarse filters (Noss 1987; of conditions a process-oriented, coarse- South Strafford VT, 05070 Hunter et al. 1988; Hunter 2005) argues filter approach to conservation will reliably that populations of most species in a com- ensure the persistence of the majority of munity can be controlled by manipulating species in a community. Additional case key structuring processes, especially dis- studies that evaluate the efficacy of this 2 Gary L. Slater turbances that shape the abundance and approach are sorely needed (Bestelmeyer 2Ecostudies Institute distribution of important habitat elements. et al. 2003; Hunter 2005). PO Box 703 This approach is commonly applied in a Mount Vernon WA, 98273 variety of to manage plant and In this paper, we present the results of a animal populations (Leopold et al. 1963; case study in which we examined how Hunter 1993; Haufler et al. 1996; Long one taxonomic group responded to the and Smith 2000). Coarse-filter manage- application of a coarse-filter management ment strategies that focus on restoring strategy. In particular, we examined how • normative disturbance regimes assume breeding- and wintering-bird assemblages that the abundance of each species in a responded to variation in prescribed-fire community is a predictable function of the regimes in the pine-rockland intensity and frequency of the disturbance. of south Florida. Pine rocklands are fire- Maintaining a characteristic community dependent, found only on out- structure requires only that disturbance is crops in south Florida, , and 3 Corresponding author: applied at an intensity and frequency that . In the absence of fire, hardwoods [email protected] approximates the historic range of vari- come to dominate the canopy, inhibiting ability. Intuitively appealing, coarse-filter growth and reproduction of pines, and management strategies allow managers to eventually the pine rockland is replaced address the needs of multiple species with by a dry, broad-leafed tropical forest. In a single action and do not require a detailed the presence of natural fire regimes, pine understanding of the habitat requirements rocklands are characterized by relatively of each species in a community. open-canopied stands of south Florida Natural Areas Journal 32:247–259 slash pine (Pinus elliottii var. densa Little The use of disturbances as a coarse filter is and Dorman) rising above understories

Volume 32 (3), 2012 Natural Areas Journal 247 of grasses, hardwood shrubs, and palms tion in the fire regime should produce varia- includes approximately 4600 ha of pine (Serenoa repens Bartram, Sabal palmetto tion in vegetation structure, which should rockland. The within the study (Walter) Lodd. ex Schult. & Schult. f., in turn produce variation in bird species area is subtropical, with a pronounced and (Jacq.) L.H. composition and abundance of birds. If dry season from November to April and a Bailey). Most (> 90%) of the area in south bird assemblages in pine rocklands do not wet season from May to October. About Florida once covered by pine rocklands, predictably vary as a function of variation 75% of rainfall occurs during the wet known as the Rock Ridge, has in the fire regime, then fire, at least within season, with most of the wet-season rains been replaced by agricultural fields and the range of variation observed, does not act falling during convective storms early in residential or commercial developments as a coarse filter for birds in this system and the season or during tropical cyclones in (USFWS 1999). alternative management strategies may be the late wet-season; July and August are needed to maintain or restore bird popula- relatively dry (Snyder et al. 1990). Annual Accepting that fire is necessary in checking tions in the pine rocklands. We tested these temperature variation is relatively modest, successional pathways that lead inevita- predictions by examining the relationship with an average July temperature of 29 bly to the replacement of pine rocklands between fire history (the number of fires °C and an average January temperature by broad-leafed forests, a critical and and length of the fire-free period), vegeta- of 19 °C. outstanding question remains: within the tion structure, and bird abundance at 156 range of fire-return intervals that prevent locations in south Florida, while at the same Historically, fire-return intervals in the pine succession to hardwood hammocks, does time controlling for a suite of potentially rocklands are thought to have averaged variation in fire regime explain extant varia- confounding variables that might mask the between three and seven years (Wade et tion in the composition and structure of effect of fire history. al. 1980; Snyder 1986; Snyder et al. 1990; plant and animal assemblages at different Liu et al. 2005; Sah et al. 2006). Most sites within the pine rocklands? In other We focused on birds because they have been fires probably occurred during the wet words, is any fire regime that prevents the particularly vulnerable to the degradation season, with the greatest acreage burning encroachment of hardwoods adequate in and destruction of the pine rocklands and, in June, when lightning is common but promoting the mix of plants and animals as such, are of concern to land managers. fuel moisture remains low (Taylor 1981). characteristic of pine rocklands, or is some Seven species of breeding birds have been Ignitions by humans have greatly extended level of fine-tuning required? The primary extirpated from the pine rocklands since the fire season; most human-caused fires in management objective in pine rocklands the middle of the last century: wild turkey south Florida occur during the dry season, has been to restore putatively natural fire (Meleagris gallopavo Linneaus), summer although, as with natural fires, the largest regimes (Maguire 1995; USFWS 1999), the tanager (Piranga rubra Linneaus), brown- fires occur at the transition from dry to assumption being that doing so will create headed nuthatch (Sitta pusilla Latham), wet season (Gunderson 1994; Gunderson and maintain the environmental conditions Eastern bluebird (Sialia sialis Linneaus), and Snyder 1994). necessary to support the characteristic as- red-cockaded woodpecker (Picoides bo- semblage of plants and animals. However, realis Vieillot), Southeastern American Establishing survey points this assumption has rarely been tested. kestrel (Falco sparverius paulus Linneaus), As a coarse filter, fire at any reasonable and hairy woodpecker (Picoides villosus We collected data at 104 points in Long interval may be adequate in maintaining Linneaus). Three species, including wild Pine Key and 52 points in pine-rockland forests of slash pine. Within the broad turkey, brown-headed nuthatch, and East- preserves managed by Miami-Dade County range of fire-return intervals that prevent ern bluebird, have been reintroduced to (Figure 1). We established points at Long encroachment of hardwoods, however, sites National Park, although the Pine Key in 2005 and in Miami-Dade burned at different intervals may support long-term viability of these populations County parks in 2006. For Long Pine very different assemblages of plants and is uncertain (Lloyd et al. 2009). Key, we placed survey points at randomly animals. If so, this information is of great chosen locations, with the restriction that importance in fine-tuning fire as a coarse METHODS survey points were > 350 m apart and filter. Alternatively, variation in biological were surrounded by > 100 m of contigu- assemblages among different sites within ous pine forest. We had fewer potential the pine rocklands may be driven by Study area sites to choose from in the Miami-Dade factors other than fires – hydrology, for County park system, so our selection of example. In this case, at shorter temporal We conducted this study at Long Pine Key, survey locations was essentially system- scales, fire does not act as a coarse filter; located within , atic: we established points in any patch and managers looking to effect change in and in a series of small pine-rockland pre- of pine rockland as long as they met the the numbers of a species would need to serves in the greater Miami metropolitan criteria identified for points in Long Pine manipulate variables other than fire. area that were managed by Miami-Dade Key. The 52 points surveyed in Miami- County (Figure 1). Long Pine Key is the Dade County parks were located in 17 In this study, we tested a corollary of the largest remaining patch of pine rockland different sites; however, three sites (Linda coarse-filter approach, namely that varia- in North America (USFWS 1999), and and Penny Thompson, Martinez Site, and

248 Natural Areas Journal Volume 32 (3), 2012 shrub level.

Estimating bird abundance

We conducted avian surveys during the non-breeding (15 Dec – 15 Feb) and breeding (15 Apr – 1 Jun) seasons. Each station was visited once per season. Each survey consisted of a seven-minute count, during which observers recorded the radial distance from the sampling station to all birds detected within 50 m of the point. Surveys were conducted between sunrise and 10:00 AM. We estimated density and abundance (number of birds per 50- m-radius sampling plot) using distance sampling as implemented by Program Distance (Thomas et al. 2009). Distance sampling is one of several methods that adjusts counts of birds to address imperfect detectability.

Quantifying fire regime

We quantified fire history with two vari- ables: the number of days since each survey point had burned and the total number of times each point had burned within the 10 years prior to the survey. We obtained Figure 1. Map of the study area, showing the 104 points in Long Pine Key, Everglades National Park, fire history data from each organizational and 52 points in Miami-Dade County, Florida, at which bird and plant surveys were conducted from unit (Miami-Dade County and Everglades 2005-2008. All points were located within pine rocklands. National Park). For many of the points, data did not extend beyond 10 years prior Miami Metrozoo) were adjacent, forming survey point at bearings of 0, 120, and to the survey, and so the maximum num- a single large patch of pine forest. Thus, 240. We also used dbh to group living trees ber of days since last fire was artificially we sampled 14 unique patches of pine into three categories for the purposes of truncated at 3650. rockland, each containing from 1 – 17 analysis: small (≤ 10.5 cm dbh), medium survey points. We treated each point as (10.6 – 18.5 cm dbh), and large (> 18.5 a replicate in our analyses because fire cm dbh). We used measurements of dbh to Potentially confounding variables histories varied substantially, even among derive estimates of basal area, where basal adjacent points within a site. area was equal to the cross-sectional area In a review of the literature concerning pine of trees and snags (πr2; where r = dbh/2). rocklands, we identified two other factors At the survey point and at each of the that might influence vegetation structure, Quantifying vegetation structure three sampling plots centered 40 m from and therefore bird assemblages, and which the survey point, we visually estimated the might mask the effects of variation in fire: We quantified vegetation structure because percent cover by plants at ground level (< (1) hydrology (Olmsted et al. 1983; also it is assumed to be the causal link through 1.5 m) and at the shrub level (between 1.5 see Duever 2005 for an example from the which fire affects bird populations. We and 8 m) in a 5-m-radius circular plot. We ecologically similar pine flatwoods) and (2) sampled vegetation at each survey point soil type (Robertson 1953; Possley et al. annually between 1 December and 1 estimated percent cover for three major March. We determined the number and understory habitat components at both the 2008). In addition, we suspected that veg- diameter of living and dead pine trees ≥ ground and shrub levels: grasses, palms, etation structure and bird assemblages in 8.0 cm diameter at breast height (dbh) in and hardwood shrubs. Finally, we used a patches of pine rockland might be strongly an 11.3-m-radius circular plot centered on marked pole to estimate average height influenced by conditions outside of the each survey point and at three additional of palms and the maximum heights of patch, especially within the network of sampling plots centered 40 m from the pines, hardwoods, and palms within the small reserves in Miami-Dade County.

Volume 32 (3), 2012 Natural Areas Journal 249 As a measure of hydrological conditions, shallow (10 cm) layer of silty loam above Pineland preserves in Miami-Dade County we focused on water-table elevation be- limestone bedrock (Noble et al. 1996). are much smaller (the largest patch is < cause it likely has direct effects on vegeta- Long Pine Key, furthest south along the 5% of the size of Long Pine Key) and are tion in the pinelands (Olmsted et al. 1983; Miami Rock Ridge, is not included in surrounded by urban or agricultural land; Ish-Shalom et al. 1992; Ewe et al. 1999) existing soil surveys but, in general, soils in most cases, the pineland preserves are and because it is correlated with hydrope- are almost non-existent and bare limestone the only natural plant communities on the riod, which may influence the intensity and is the dominant substrate. We identified landscape. In addition, most of the fires frequency of fire (Lockwood et al. 2003; the soil type at all of the points within the that affected the pine-rockland preserves Slocum et al. 2003). To estimate water-table Miami-Dade County park network using in Miami-Dade County were unplanned elevation, we downloaded daily stage data soil survey maps (Noble et al. 1996). wildfires, whereas nearly all of the fires at from the South Florida Water Management Long Pine Key were prescribed. We also District for all stations within 25 km of a We assumed that the composition of the expected that the structure of plant and bird survey point. We then averaged the daily surrounding landscape might influence assemblages in the two areas would differ data to estimate the average water stage for bird abundance and vegetation structure, for purely historical reasons. Nearly every the spring sampling period (15 Apr – 1 Jun) and so we estimated the percent of ag- pine tree in Miami-Dade County parks in each year of the study. We chose to use ricultural land and the percent of urban died following Hurricane Andrew in 1992, average water-table elevation during April land (the two primary cover types outside either due to direct mortality from wind – June as our sole measure of hydrological of Everglades National Park) within a damage or indirect mortality caused by a conditions because water-table elevations 500-m radius around each point in the combination of drought, hurricane damage, at a point were closely correlated between Miami-Dade county parks. All points in and infestation by Ips beetles; Long Pine the winter and spring sampling periods Long Pine Key were surrounded by a mix Key was affected to a much lesser degree (r2 = 0.85, 95% CI = 0.76 – 0.94) but of pineland and open glades. We used the (USFWS 1999). Thus, we decided that were more variable among points during 2004 Florida Land Cover Database (avail- analyzing the two areas separately would the spring sampling period (winter CV able at http://www.fgdl.org/) to determine better allow us to isolate the effects of = 1.6%, spring CV = 3.6%) and, thus, land cover. variation in fire history. perhaps more useful as a predictor vari- able. We kriged average stage elevations We used a constrained ordination tech- Statistical analyses using Universal Kriging (spherical model nique, canonical analysis of principal with anisotropy), and extracted the value coordinates (CAP; Anderson and Willis Survey points were sampled each year from for each survey point. We calculated the 2003), to examine whether variation in veg- 2005 (Long Pine Key) or 2006 (Miami- elevation above sea level using the United etation structure and bird abundance was Dade County) to 2008, but we decided that States Geological Survey’s High Accuracy associated with variation in fire history. We measures of bird abundance taken at the Elevation Data model and the Southwest controlled for potentially confounding ef- same point in different years were not inde- Florida Feasibility Study elevation model. fects of hydrology by including water-table pendent of one another, even if the values If a point had data from both models (i.e., elevation as a predictor; for the analyses of for the predictor variables changed from models overlapped at that point), we used points in Miami-Dade County parks, we one year to the next. For example, birds the average of the two models. We then also included soil type and surrounding may show no short-term response even to subtracted the elevation above sea level at land cover. We did not include soils or significant habitat changes simply because each survey point from the estimated stage land cover as covariates in our analysis of of fidelity to a particular site (Wiens and height to calculate water-table elevation. Rotenberry 1985). Thus, we chose to points at Long Pine Key because neither analyze only a random subset of the data varied among points within that site. We Previous authors (Robertson 1955; Ol- collected, drawing at random data from one conducted the analysis using the capscale mstead et al. 1983; Snyder et al. 1990; of the three (Miami-Dade County) or four function in the R package vegan (Oksanen Possley et al. 2008) have noted small-scale (Long Pine Key) years of data collected at et al. 2009). The statistical significance of variation in the structure and composition each point. Therefore, the total sample size the canonical axes was calculated using the of pine rocklands and have attributed this in our analyses was N=156. permutation tests implemented in capscale variation to differences in soil types. Ar- (Oksanen et al. 2009). eas furthest north along the Miami Rock We analyzed data from Long Pine Key Ridge (the “northern Biscayne” region of and Miami-Dade County parks separately. We identified the measures of vegetation Snyder et al. (1990)) occur on the Opal- We did so out of concern that differences structure or bird species that were re- ocka-Rock outcrop complex (Noble et al. in fire regime were confounded by gross sponsible for any patterns revealed by the 1996), which consists of up to 15 cm of differences in soil type, hydrology, and CAP by examining correlations between sand above limestone bedrock. Further landscape composition. Long Pine Key canonical axes and measures of vegetation south (the “Redlands” region of Snyder is a single, large patch of pine forest sur- structure and bird abundance (Jongman et et al. (1990)), pine rocklands occur on rounded by a largely natural environment al. 1995; Anderson and Willis 2003). We the Cardsound-Rock outcrop complex, a that has been protected since the 1940s. conducted follow-up, univariate analyses

250 Natural Areas Journal Volume 32 (3), 2012 on vegetation variables or bird species that showed a strong (i.e., |r|> 0.20) correla- tion with at least one canonical axis. To do so, we used generalized linear models (GLM) with the response variable being bird abundance or vegetation structure and the predictors being water-table elevation, number of days since fire, and number of fires in the past 10 years (and, for points in Miami-Dade County parks, soil type, percent agricultural land within 500 m, and percent urban land within 500 m). We did not attempt to simplify these models, instead including all predictor variables. For count data, we assumed a Poisson distribution with a log link function. For other data (e.g., percent cover or height), we assumed a normal distribution of er- rors, but examined quantile-quantile plots and plots of fitted values versus residuals to determine the validity of this assump- tion. In cases where the assumption of normally distributed errors appeared invalid, we found that log-transforming the response variable addressed problems both of normality of errors and constancy of variance. All analyses were conducted using R version 2.9.1 (R Development Core Team 2009).

RESULTS

Descriptive statistics: fire regime, hydrology, and surrounding land use

Points in Long Pine Key had burned more frequently and more recently than points located in pine-rockland preserves man- aged by Miami-Dade County (Figure 2). Variation in fire frequency among points within the two areas was relatively small. At Long Pine Key, 50% of the points had burned between 3 and 5 times in the preced- ing 10 years, 25% had been burned between 6 and 9 times, and 25% had burned once or twice. In the Miami-Dade County parks, 50% of the points had been burned once or twice, 25% had never burned, and 25% had been burned between 3 and 5 times. Figure 2. (A) Average number of fires in the 10 years preceding the date on which a bird or plant survey Average water-table elevation at survey was conducted at locations in Long Pine Key, Everglades National Park (white bar), or Miami-Dade points in Long Pine Key was higher than County, Florida (gray bar); (B) Average number of days between the date a point was surveyed and the last time it was burned; and (C) water-table elevation in Long Pine Key, Everglades National Park that in Miami-Dade County parks during (white bars) or Miami-Dade County, Florida (gray bars), during breeding-season (April – June) and both April – June and December – February winter (December – February) surveys for birds. Error bars are 95% confidence intervals. (Figure 2). The only significant correlations among fire and hydrology variables were

Volume 32 (3), 2012 Natural Areas Journal 251 between the number of fires in the past 10 years and the number of days since last fire (Long Pine Key: r = -0.47 [95% CI = -0.61 – -0.31]; Miami-Dade County: r = -0.74 [95% CI = -0.85 – -0.59], respectively).

Most of the land within 500 m of survey points in Miami-Dade parks was classified as urban (mean = 61.6%, range = 3.7% – 96.5%), with agriculture accounting for the majority of the remainder (mean = 10.8%, range = 0.0% – 58.8%). The ratio of agricultural land to urban land increased from the northeast portion of the study area, closer to the Miami city center, to the southwest, which has relatively little commercial or residential development. As a result, soil type and landscape were confounded: points in landscapes dominated by agriculture occurred on the Cardsound soil type, whereas points in urban landscapes occurred on the Opal- ocka soil type (Figure 3a). Points on the Opalocka soils also tended to have lower water tables, with the surface of the water table found on average 199.0 cm below ground surface (Figure 3b). Fire histories were similar across soil types (days since fire: Opalocka = 2278; Cardsound = 2173; number of fires in past 10 years: Opalocka = 1.4; Cardsound = 1.3).

Breeding birds: Long Pine Key versus Miami-Dade County parks

Breeding-bird assemblages of the two areas were readily distinguishable from one another (Table 1; see table for scien- tific names). Indeed, although Northern Cardinal was the most abundant breeding Figure 3. (A) Percent agriculture and percent urban land within 500 m of survey points (N=52) on the species in both areas, little overlap existed two main soil types underlying pine-rockland preserves in Miami-Dade County and (B) water-table eleva- tion on these same soil types during breeding-season (April – June) and winter (December – February) in species composition (Table 1). Species surveys for birds. Error bars are 95% confidence intervals. characteristic of intact pinelands, such as Pine Warbler or Downy Woodpecker, were absent outside of Long Pine Key, breeding-bird assemblages in both Long Non-breeding birds: Long Pine Key and were replaced in the parks of Miami- Pine Key and Miami-Dade County parks. versus Miami-Dade County parks Dade County by a suite of generalist, At Long Pine Key, fire history and water- human-commensal species such as Com- table elevation explained a small (3.8%) Bird assemblages present during the non- mon Grackles, Blue Jays, and Northern and insignificant (all P > 0.10) amount of breeding season at Long Pine Key and in Mockingbirds (Table 1). variation in bird abundance. In the pineland Miami-Dade County parks were, as during preserves of Miami-Dade County, fire his- the breeding season, readily distinguishable Breeding birds: effects of fire, tory, soil type, hydrology, and landscape (Table 2; see table for scientific names). hydrology, soil, and landscape conditions were not significant predictors The estimated total density of birds both conditions of variation in the structure and compo- at Long Pine Key and in Miami-Dade sition of the breeding-bird assemblages County parks rose appreciably during the Constrained ordination revealed only (percent of variation explained = 11.6%, winter, from a breeding-season average of weak effects of the predictor variables on P = 0.43). 2.7 individuals ha-1 (95% CI = 2.3 – 3.1)

252 Natural Areas Journal Volume 32 (3), 2012 Table 1. Estimated density (95% confidence interval) of breeding birds (number of individuals ha-1) in pine rocklands at Long Pine Key, Everglades National Park, Florida, and in parks managed by Miami-Dade County, Florida.

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and 3.3 individuals ha-1 (95% CI = 2.8 Non-breeding birds: effects of fire, as was the average and maximum height – 3.9), respectively, to an average of 6.0 hydrology, soil, and landscape of understory palms (Table 3). individuals ha-1 (95% CI = 5.5 – 6.5) and conditions 6.4 individuals ha-1 (4.9 – 8.2), respectively. Vegetation structure: effects of At both sites, winter brought the arrival of Structure and composition of non-breeding fire, hydrology, soil, and landscape large numbers of migrant warblers, espe- bird assemblages in Long Pine Key were conditions 2 cially Yellow-rumped Warbler and Palm unrelated to fire history or hydrology (r = Warbler, but also increased numbers of 3.1%, P = 0.32). Likewise, soil type, fire history, hydrology, and landscape condi- Long Pine Key Pine Warblers. In fact, Pine Warblers were tions were not significant predictors of abundant during winter in Miami-Dade bird assemblages in Miami-Dade County In a constrained ordination, the number County parks, despite their near-absence parks during winter (percent of variation of days since fire, average water-table from these same points during the breeding explained = 13.8%, P = 0.6). elevation, and the number of fires in the season. White-eyed Vireos and Boat-tailed past 10 years explained a significant (P Grackles were also more common during < 0.005) albeit small (8.5%) percentage winter than during the breeding season in Vegetation structure: Long Pine Key of the observed variation in vegetation Miami-Dade County parks. Other short- versus Miami-Dade County parks structure. When tested sequentially, only distance migrants that wintered in relatively the first canonical axis accounted for a sig- large numbers in pinelands in both areas Long Pine Key contained more large pine nificant amount of variation in vegetation trees and fewer small pine trees than did the structure (P < 0.005), explaining 4.4% of included Gray Catbird, Common Yel- pineland preserves of Miami-Dade County the total variation in vegetation structure, lowthroat, Blue-gray Gnatcatcher, House (Table 3). Ground cover by hardwoods and and accounting for 83.1% of the explained Wren, and American Robin. American grasses tended to be somewhat greater in variation. This axis was negatively cor- Robins were far more common in winter Long Pine Key; ground cover by palms related with the number of days since fire in Long Pine Key than in Miami-Dade was greater in Miami-Dade County parks (r = -0.36) and water-table elevation (r = County parks (Table 2). (Table 3). Shrub cover by palms was also -0.35) and positively correlated with the greater in the Miami-Dade County parks, number of fires at a point over a trailing

Volume 32 (3), 2012 Natural Areas Journal 253 Table 2. Estimated density (95% confidence interval) of birds (number of individuals ha-1) wintering in pine rocklands at Long Pine Key, Everglades National Park, Florida, and in parks managed by Miami-Dade County, Florida.

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10-year window (r = 0.28). Points with ground cover by palms was negatively area of pine snags varied from 0.3 m2 positive scores along the first axis had been related to the number of days since last fire ha-1 on the wettest sites to 1.3 m2 ha-1 on burned more frequently and more recently (P = 0.04), but was unrelated to water-table the driest sites, or approximately a 330% and tended to be drier (Figure 4). elevation (P = 0.54) or the number of fires difference. Second, the density of large in the past 10 years (P = 0.74). Model-esti- pine trees around a survey point was also mated ground cover by palms ranged from Ordination results suggested that the height negatively related to water-table elevation 3.5% at sites that had gone without fire for of most understory components – young 2030 days, the maximum observed, to 8.1% (P = 0.02) and unrelated to the other predic- pines, palms, and hardwood shrubs – in- at sites burned 146 days prior to sampling. tors (days since fire: P = 0.28; number of creased as water-table elevation rose and Despite the statistical significance of the fires: P = 0.11). The density of large pine as the time since last fire increased (Figure relationship, the absolute effect size – a trees was estimated to range from 43 ha-1 4). In contrast, drier sites, and those burned change of < 5% cover – is of questionable at the wettest sites to 100 ha-1 at the driest more recently and frequently, had a greater biological significance. sites, a difference of approximately 135%. number of large pine trees, more pine snags, Third, height of the tallest palm was posi- and increased cover at the ground level by Four variables showed significant relation- tively related to water-table elevation (P = hardwoods and palms (Figure 4). ships with water-table elevation only. First, 0.004), but the effect size was relatively the basal area of pine snags was negatively small: maximum height at the driest site Of the six variables strongly correlated related to water-table elevation (P = 0.02), was estimated at 1.3 m; at the wettest site, (|r|> 0.20) with the first canonical axis, all but showed no association with either the 2.0 m. Neither the number of days since showed significant relationships with at number of fires in a trailing 10-year window fire (P = 0.92) nor the number of fires in least one of the predictor variables in fol- (P = 0.29) or the number of days since the past 10 years (P = 0.43) was related to low-up, univariate analyses. One variable last fire (P = 0.09). Based on predictions variation in the maximum height of palms. was related to fire history only. Percent from the generalized linear model, basal Finally, the density of pine snags was

254 Natural Areas Journal Volume 32 (3), 2012 Ordination results indicated differences Table 3. Average values (95% confidence interval) for measures of vegetation structure in pine in vegetation structure between pineland rocklands at Long Pine Key, Everglades National Park, Florida, and in parks managed by Miami- Dade County, Florida. preserves located in urban landscapes, which tended to occur on Opalocka soils, and pineland preserves in agricultural  ""  )"  " landscapes, which tended to occur on  "")- .,+,"'-1+."*".0+$( !1+,"'00+!"*"$1+0( Card Sound soils (Figure 5). By every  "")- --/+$"'%#+0"*"-/,+-( -/-+$"'-,,+."*"-!/+/( measure – height, ground cover, and shrub )- cover – hardwoods were a more important "" $,+/"'#,+."*"%,+/( .0+,"'--+$"*"/!+.( component of pineland preserves on Card "")- 0!+/"'/#+-"*"11+/( 1!+1"'00+/"*"!$+#( . )- Sound soils than of pinelands on the Opal- """"' " ( ,+$"',+!"*",+%( ,+%"',+#"*"-+.( ocka soils (Figure 5). In contrast, palms  " "'&( 0#+-"'0/+#"*"1,+1( /0+,"'/,+/"*"/#+$( formed a more important component of " "'&( -!+%"'-1+,"*"-$+$( -.+1"'-,+/"*"-0+#( the understory of pine rocklands on the " " "'&( --+/"'%+$"*"-.+$( #+1"'1+#"*"%+0( Opalocka soils (Figure 5).  " " "'&( !+0"'1+0"*"#+0( --+0"'%+!"*"-/+.(  " "'&( 1+$"'1+,"*"!+!( $+!"'1+%"*"--+0( Univariate analyses on variables strongly correlated with the first CAP axis suggested " " "'&( .+%"'.+."*"/+1( .+%"'-+!"*"0+.( that only two measures of vegetation struc-  " " "'&( ,+1"',+0"*",+!( .+0"'-+0"*"/+1( ture were related to fire history: (1) height  " " "' ( ,+%"',+$"*"-+,( -+."'-+-"*"-+/( of the tallest hardwood and (2) height of the  ""  "  ""' ( 0+#"'0+-"*"1+/( !+!"'!+,"*"#+.( tallest understory palm. Both increased as  ""  ""' ( /+-"'.+%"*"/+/( /+-"'.+!"*"/+1( the number of days since last fire increased  ""  " "' ( -+!"'-+1"*"-+#( .+0"'.+."*".+#( (hardwoods: P < 0.001; palms: P = 0.04). Estimated effect sizes were greater for hardwoods than for palms. At points burned most recently (three days since fire), the negatively related to water-table elevation Miami-Dade County parks tallest hardwood was predicted to be 1.7 m (P = 0.003) and showed a weakly negative (95% CI = 0.9 – 2.6); at points unburned relationship with the number of days since The predictor variables explained 25.1% for at least 10 years, the predicted height fire (P = 0.06; b = -0.001, 95% CI = -0.002 of the variation in vegetation structure as was 3.9 m (95% CI = 3.2 – 4.6). Over – 0). We found no relationship between described by the constrained ordination (P the same range of fire-free periods, the snag density and the number of fires at = 0.005). Most (57.4%) of the variation predicted height of the tallest understory a point (P = 0.15). Estimated number of explained by the ordination was due to palm ranged from 1.9 m (95% CI = 1.4 pine snags ranged from 13 ha-1 – 85 ha-1 the first canonical axis and indeed, when – 2.4) to 2.7 m (95% CI = 2.3 – 3.1). at the wettest and driest sites, respectively, tested sequentially, only the first canonical axis accounted for a significant amount of a 580% difference. These same variables were also affected by variation in vegetation structure (P = 0.005; soil type, with effect sizes approximately all other axes, P > 0.15). Site scores along One vegetation variable was related to both equal to those predicted for the number of the first canonical axis were most closely fire history and hydrology. The maximum correlated with variation in soil type (r = days since fire. The height of the tallest height of understory pines was positively 0.72), percent agriculture (r = -0.60), and understory hardwood was significantly related to the number of days since fire percent urban land (r = 0.50), indicating greater on Card Sound soils (P < 0.001), (P = 0.01) and water-table elevation (P = that points on the Opalocka soil type, which with predicted values on Card Sound soils 0.04). Estimated effect sizes were similar also tended to be in more urban settings, (4.5 m, 95% CI = 3.7 m – 5.3 m) nearly for both water-table elevation (driest to differed in vegetation structure from points twice as great as those on Opalocka soils wettest: 3.4 m – 6.4 m) and days since on the Card Sound soil type, which tended (2.4 m, 95% CI = 1.9 m – 2.9 m). The height fire (fewest to most: 3.7 m – 6.9 m), each to be found in patches in agricultural of the tallest understory palm was signifi- yielding estimated changes in understory landscapes (Figure 5). The number of days cantly greater (P = 0.006) on the Opalocka pine height of approximately 86% and since fire (r = -0.25), water-table elevation soil type, although the effect size was small 88%, respectively, across the range of (r = -0.19), and the number of fires in the (Opalocka soils, tallest understory palm observed values. Understory pine height past 10 years (r = 0.13) were relatively = 2.7 m, 95% CI = 2.4 m – 3.0 m; Card was unrelated to the number of fires at a unimportant in explaining variation in Sound soils, tallest understory palm = 1.8 point in the past 10 years (P = 0.82). vegetation structure. m, 95% CI = 1.4 m – 2.2 m).

Volume 32 (3), 2012 Natural Areas Journal 255 assemblages were closely associated with variation in fire history. Instead, we found that vegetation structure responded more strongly to relative water-table elevation (Long Pine Key) and soil type (Miami- Dade County parks) and that the composi- tion and structure of bird assemblages at our survey points was not associated with any of our predictor variables.

Our results suggest that the vegetation of the pine rocklands is so resilient and re- sistant to fire that variation in fire history, at least within the range we observed, has relatively little effect on vegetation struc- ture. After a quick recovery following fire, most of the spatial variation in vegetation structure appears to be a function of per- sistent differences among sites in relative water-table elevation and soil type (see also Robertson 1955; Taylor and Herndon 1981; Olmsted et al. 1983; Possley et al. 2008; Slapcinsky et al. 2010). Fire history may be the primary source of variation in vegetation structure only when sites representing the tails of the distribution Figure 4. Results of a canonical analysis of principal coordinates of vegetation structure at points in pine of fire histories are well represented in rocklands within Long Pine Key, Everglades National Park. Arrows represent the strength of correla- the sample. In studies such as ours, where tion between predictor variables and ordination scores; variables with longer arrows explained more variation in ordination scores. Orientation of the arrows indicates the direction of maximum change in variation in fire history was relatively the value of the predictor variables. The position of each labeled variable indicates the relative position small, the effects of fire will appear small of survey points where that variable reached its greatest value. Variables close to an arrow were more or non-existent. closely correlated with variation in that predictor. Variables positioned close to the origin were poorly explained by the ordination. The highlighted inset figure shows the actual position of survey points in the ordination. The lack of strong pattern in the position of points reflects the poor explanatory power The rapid recovery of vegetation likely of the ordination. minimized any change in habitat avail- ability for birds, such that bird assemblages Soil type also exerted significant influence DISCUSSION showed little response to variation in fire on three other measures of vegetation history. Other studies in southeastern pine structure. Hardwood shrub cover was sig- Prescribed fire is the primary tool used forests have yielded similar findings (Em- nificantly greater at sites on the Cardsound to manage biological communities in the len 1970; Lloyd and Slater 2011). Indeed, soil type (P = 0.02). Predicted cover by pine-rockland ecosystem. The assumption organisms in ecosystems where fire is fre- hardwood shrubs at sites on Cardsound underlying this approach is that fire is the quent, such as the pine rocklands, are apt soils was 5.5% (95% CI = 3.1% – 7.9%) key structuring process in pine rocklands to be highly tolerant of fire and may show but only 1.6% (95% CI = 0.1% – 3.1%) (Robertson 1953; Alexander 1967), creat- no response to fire history except under ex- on Opalocka soils. Hardwood ground cover ing the physical conditions required by the treme conditions (Parr and Andersen 2006). was also significantly greater (P = 0.01) on characteristic groups of species occupying The only clear pattern of variation for birds Cardsound soils (11.4%, 95% CI = 9.0% pine rocklands. This assumption is based was the distinction between assemblages – 13.8%) than on Opalocka soils (5.6%, largely on the observation that periodic fire found at points in the Miami-Dade County 95% CI = 3.4% – 7.8%). The percent of the resets successional pathways that appear parks, which were small and embedded ground covered by palms was significantly to lead inevitably to replacement of pine within highly modified landscapes, and greater on the Opalocka soils (P <0.001) points in Long Pine Key, which were and the predicted effect size was much rocklands by broad-leafed forest. Given larger (Opalocka soils, percent ground this, we predicted that vegetation structure surrounded by mostly intact pine forest covered by palms = 14.2%, 95% CI = and the composition and structure of bird and glades. Breeding-bird assemblages in 12.0% – 16.4%; Cardsound soils, percent assemblages would vary among areas dif- Miami-Dade County parks were dominated ground covered by palms = 5.8%, 95% CI fering in fire history. Contrary to expecta- by human-commensal species such as = 2.4% – 9.2%). tion, neither vegetation structure nor bird Common Grackle, Northern Mockingbird,

256 Natural Areas Journal Volume 32 (3), 2012 Davis 1943:253), and we cannot rule out the possibility that some birds may show strong positive or negative responses to these unusual occurrences.

Second, the substantial differences in the bird assemblages present at Long Pine Key and the Miami-Dade parks highlighted the limits of the coarse-filter approach to conservation. Restoring a key ecosystem process – fire – to the pineland preserves in Miami-Dade County will not, in all likelihood, produce breeding-bird assemblages that mimic those found in the largely intact pine rocklands at Long Pine Key. Many exotic plants that have invaded remnant pine rocklands in Miami-Dade County are tolerant of fire (e.g., Doren and Whiteaker 1990) and can greatly af- fect the composition of bird assemblages (Curnutt 1989). Furthermore, the suitability of many of these small patches as habitat for breeding birds may be driven largely by factors unaffected by fire. For example, Figure 5. Results of a canonical analysis of principal coordinates of vegetation structure at points in surrounding land uses likely encourage pine-rockland preserves in Miami-Dade County, Florida. Arrows represent the strength of correlation high densities of predators, such as feral between predictor variables and ordination scores; variables with longer arrows explained more varia- or free-ranging cats (Felis catus Linnaeus), tion in ordination scores. Orientation of the arrows indicates the direction of maximum change in the value of the predictor variables. The position of each labeled variable indicates the relative position of and also subsidize exotic bird species that survey points where that variable reached its greatest value. Variables close to an arrow were more compete with native species (e.g., Ingold closely correlated with variation in that predictor. Variables positioned close to the origin were poorly 1989). Some patches may simply be too explained by the ordination. The highlighted inset figure shows the actual position of survey points in small to attract individuals or support the ordination. The lack of strong pattern in the position of points reflects the poor explanatory power of the ordination. breeding territories. Our results suggest that the greatest value of the pineland preserves from the standpoint of bird conservation is and Blue Jay, and lacked characteristic (Snyder et al. 1990; USFWS 1999). As the habitat that they provide for wintering pineland species such as Pine Warbler long as fire is applied frequently enough species, which appear more flexible in their and Downy Woodpecker (See Table 1 for to prevent hardwood encroachment, birds willingness to use small patches of pineland scientific names). The composition of bird appear tolerant of a range of fire-return within the Miami-Dade County network assemblages in the two areas converged in intervals. At the same time, our results sug- of parks. In sum, although other examples the winter with the arrival of migrants such gest that fire, at least as it was prescribed as Yellow-rumped Warbler, Gray Catbird, during this study, is unlikely to prove exist of capturing ecosystem processes for and Palm Warbler (See Table 2 for scien- useful in effecting change in bird popula- use as coarse filters, and although fire is tific names), which were abundant in both tions. However, the range of fire histories clearly an important filter in this system Long Pine Key and the pineland parks of that we observed within our study sites at relatively long temporal scales (e.g., ≥ Miami-Dade County. was relatively small, and thus we had no 10 years), variation in fire-return intervals way to evaluate the importance of extreme at shorter time scales was of little conse- The management implications are twofold. conditions, such as might occur following quence for breeding and wintering birds. First, birds of the pine rocklands appeared a long fire-free interval and an unusually Our study highlights several limits of the relatively insensitive to fine-scale variation severe fire. In some systems, large and coarse-filter approach, in particular the in fire regime, which suggests that they infrequent disturbances play a key role in substantial constraints imposed by realities should tolerate fire-management plans structuring biotic assemblages (e.g., Dale et such as small patch sizes, baseline condi- developed for other pine-rockland organ- al. 1998). Frequent, low-intensity fires may tions that have been substantially altered isms, such as the many endemic plants that be the rule for pine rocklands, but large and by the presence of non-native species, and inhabit this ecosystem and that seem to intense fires may have swept through the the overriding importance of the condition have more narrowly defined requirements entire Everglades region on occasion (e.g., of the surrounding landscape.

Volume 32 (3), 2012 Natural Areas Journal 257 ACKNOWLEDGMENTS Doren, R., and L. Whiteaker. 1990. Effects of Liu, H., E.S. Menges, and P.F. Quintana-As- fire on different size individuals of Schi- cencio. 2005. Population viability analyses We acknowledge funding from the Joint nus terebinthifolius. Natural Areas Journal of Chamaecrista keyensis: effects of fire Fire Science Program under Project JFSP 10:107-113. season and frequency. Ecological Applica- tions 15:210-221. 05-2-1-88. In addition, we thank Rick Duever, M.J. 2005. Big Cypress regional Anderson and Skip Snow (Everglades ecosystem conceptual ecological model. Lloyd, J.D., and G.L. Slater. 2011. Influence Wetlands 25:843-853. of fire and water regimes on pineland National Park) and Joe Maguire and So- bird assemblages. Natural Areas Journal nya Thompson (Miami-Dade County) for Emlen, J.T. 1970. Habitat selection by birds fol- lowing a forest fire. Ecology 51:343-345. 31:270-282. providing valuable logistical support and Lloyd, J.D., G.L. Slater, and S. Snow. 2009. assistance. Ewe, S.M.L., L.S.L. Sternberg, and D.E. Busch. 1999. Water-use patterns of woody species Demography of reintroduced Eastern blue- in pineland and hammock communities of birds and brown-headed nuthatches. Journal south Florida. Forest Ecology and Manage- of Wildlife Management 73:955-964. John Lloyd is Senior Research Ecologist ment 118:139-148. Lockwood, J.L., M.S. Ross, and J.P. Sah. 2003. at Ecostudies Institute. Research interests Gunderson, L.H. 1994. Vegetation of the Smoke on the water: the interplay of fire and water flow on Everglades restoration. include quantitative natural history and Everglades: determinants of community Frontiers in Ecology and the Environment composition. Pp. 323-340 in S.M. Davis the role of biotic and abiotic factors in 1:462-468. determining patterns of distribution and and J.C. Ogden, eds., Everglades: the Eco- Long, J.N., and F.W. Smith. 2000. Restructur- abundance of birds. Current research system and Its Restoration. St Lucie Press, Boca Raton, Fla. ing the forest: goshawks and the restoration examines the distribution, abundance, and of southwestern ponderosa pine. Journal of habitat requirements of mangrove land Gunderson, L.H., and J.R. Snyder. 1994. Fire Forestry 98:25-30. patterns in the southern Everglades. Pp. birds in south Florida and the natural Maguire, J. 1995. Restoration plan for Dade 291-306 in S.M. Davis and J.C. Ogden, eds., history of mangrove cuckoos. County’s pine rockland forests following Everglades: the Ecosystem and Its Restora- Hurricane Andrew. Dade County Depart- tion. St Lucie Press, Boca Raton, Fla. ment of Environmental Resources Manage- Gary Slater is Research Director at Haufler, J.B., C.A. Mehl, and G.J. Roloff. 1996. ment, Miami, Fla. Ecostudies Institute. Research includes Using a coarse-filter approach with species Noble, C.V., R.W. Drew, and J.D. Slabaugh. studies of habitat use by wintering shore- assessment for ecosystem management. 1996. Soil Survey of Dade County Area, birds and the use of alternative farming Wildlife Society Bulletin 24:200-208. Florida. U.S. Department of Agriculture, practices to create wildlife habitat. Current Hunter, M.L. Jr. 1993. Natural fire regimes as Natural Resource Conservation Service, conservation activities include reintroduc- spatial models for managing boreal forests. Gainesville, Fla. tion of Western bluebirds to San Juan Biological Conservation 65:115-120. Noss, R.F. 1987. From plant communities to Island, Washington State. Hunter, M.L. Jr. 2005. A mesofilter conservation landscapes in conservation inventories: a strategy to complement fine and coarse fil- look at The Nature Conservancy (USA). ters. Conservation Biology 19:1025-1029. Biological Conservation 41:11-37. LITERATURE CITED Hunter, M.L. Jr., G.L. Jacobson Jr., and T. Webb. Oksanen, J., R. Kindt, P. Legendre, B. O’Hara, 1988. Paleoecology and the coarse filter ap- G.L. Simpson, P. Solymos, M.H.M. Stevens, Alexander, T.R. 1967. A tropical hammock on proach to maintaining biological diversity. and H. Wagner. 2009. vegan: Community the Miami (Florida) limestone--a twenty- Conservation Biology 2:375-385. Ecology Package. R package version 1.15-4. http://CRAN.R-project. five-year study. Ecology 48:863-867. Ingold, D.J. 1989. Nesting phenology and Available online < org/package=vegan>. Anderson, M.J., and T.J. Willis. 2003. Canonical competition for nest sites among Red-headed analysis of principal coordinates: a useful and Red-bellied Woodpeckers and European Olmsted, I., W.B. Robertson Jr., J. Johnson, method of constrained ordination for ecol- Starlings. The Auk 106:209-217. and O.L. Bass. 1983. The vegetation of ogy. Ecology 84:511-525. Ish-Shalom, N., L.S.L. Sternberg, M.S. Ross, Long Pine Key, Everglades National Park. J. O’Brien, and L. Flynn. 1992. Water Everglades National Park, South Florida Bestelmeyer, B.T., J.R. Brown, K.M. Havstad, Research Center, Homestead. R. Alexander, G. Chavez, and J.E. Herrick. utilzation of tropical hardwood hammocks Parr, C.L., and A.N. Andersen. 2006. Patch mo- 2003. Development and use of state-and- of the lower . Oecologia saic burning for biodiversity conservation: transition models for rangelands. Journal 92:108-112. Jongman, R.H.G., C.J.F. Ter Braak, and O.F.R. a critique of the pyrodiversity paradigm. of Range Management:114-126. Conservation Biology 20:1610-1619. Van Tongeren. 1995. Data analysis in com- Curnutt, J.L. 1989. Breeding bird use of a munity and landscape ecology. Cambridge Possley, J., S.W. Woodmansee, and J. Mas- mature stand of Brazilian pepper. Florida University Press, Cambridge, U.K. chinski. 2008. Patterns of plant composition Field Naturalist 17:53-76. Landres, P.B., P. Morgan, and F.J. Swanson. in fragments of globally imperiled pine rockland forest: effects of soil type, recent Dale, V.H., A.E. Lugo, J.A. MacMahon, and 1999. Overview of the use of natural variabil- fire frequency, and fragment size. Natural S.T.A. Pickett. 1998. Ecosystem manage- ity concepts in managing ecological systems. ment in the context of large, infrequent Ecological Applications 9:1179-1188. Areas Journal 28:379-394. disturbances. Ecosystems 1:546-557. Leopold, A., S. Cain, C. Cottam, N. Gabrielson, R Development Core Team. 2009. R: A language Davis, J.H. Jr. 1943. The natural features of and T.L. Kimball. 1963. Wildlife manage- and environment for statistical computing. southern Florida, especially the vegetation ment in the national parks. Transactions of R Foundation for Statistical Computing. Vi- and the Everglades. Florida Geological the North American Wildlife and Natural enna, Austria. Available online .

258 Natural Areas Journal Volume 32 (3), 2012 Robertson, W.B. Jr. 1953. A survey of the ef- in Florida’s pyrogenic communities. Natural Everglades National Park. South Florida fects of fire in Everglades National Park. Areas Journal 30:4-19. Research Center Report T-640, Everglades U.S. Department of Interior, National Park Slocum, M.G., W.J. Platt, and H.C. Cooley. National Park, Homestead. Service, Homestead, Fla. 2003. Effects of differences in prescribed Thomas, L., J.L. Laake, E. Rexstad, S. Strind- Robertson, W.B. Jr. 1955. An Analysis of fire regimes on patchiness and intensity of berg, F.F.C. Marques, S.T. Buckland, D.L. the Breeding-bird Populations of Tropical fires in subtropical savannas of Everglades Borchers, D.R. Anderson, K.P. Burnham, Florida in Relation to the Vegetation. Uni- National Park, Florida. Restoration Ecology M.L. Burt, S.L. Hedley, H.H. Pollard, J.R.B. versity of Illinois, Urbana. 11:91-102. Bishop, and T.A. Marques. 2009. Distance Sah, J.P., M.S. Ross, J.R. Snyder, S. Koptur, Snyder, J.R. 1986. The impact of wet season 6.0 Release 2. Research Unit for Wildlife and H.C. Cooley. 2006. Fuel loads, fire re- and dry season prescribed fires on Miami Population Assessment, University of St. gimes, and post-fire fuel dynamics in Florida Rock Ridge pineland. Everglades National Andrews. St. Andrews, U.K. Keys pine forests. International Journal of Park, South Florida Research Center Home- [USFWS] U.S. Fish and Wildlife Service. Wildland Fire 15:463-478. stead. 1999. South Florida multi-species recovery Schulte, L.A., R.J. Mitchell, M.L. Hunter Jr., Snyder, J.R., A. Herndon, and W.B. Robertson plan. U.S. Department of Interior, Fish and J.F. Franklin, R.K. McIntyre, and B.J. Palik. Jr. 1990. South Florida rockland. Pp. 230- Wildlife Service, Atlanta, Ga. 2006. Evaluating the conceptual tools for 277 in R. L. Myers and J. J. Ewel, eds., Wade, D., J. Ewel, and R. Hofstetter. 1980. forest biodiversity conservation and their Ecosystems of Florida. University of Central Fire in south Florida ecosystems. U.S. implementation in the U.S. Forest Ecology Florida Press, Orlando. Department of Agriculture, Forest Service, and Management 232:1-11. Taylor, D.L. 1981. Fire history and fire records Southeastern Forest Experiment Station, Simberloff, D. 2001. Management of boreal for Everglades National Park 1948-1979. Asheville, N.C. forest biodiversity – a view from the outside. Everglades National Park, South Florida Wiens, J.A., and J.T. Rotenberry. 1985. Scandinavian Journal of Forest Research Research Center, Homestead. Response of breeding passerine birds to 16:105-118. Taylor, D., and A. Herndon. 1981. Impact of rangeland alteration in a North American Slapcinsky, J.L., D.R. Gordon, and E.S. Menges. 22 years of fire on understory hardwood shrubsteppe locality. Journal of Applied 2010. Responses of rare plant species to fire shrubs in slash pine communities within Ecology 22:655-668.

Volume 32 (3), 2012 Natural Areas Journal 259