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Analysis of fire frequency on the Talladega National Forest, USA, 1998-2018
Abstract
Fire is an essential ecological process and management tool for many forested landscapes, particularly the pine (Pinus spp.) forests of the southern USA. Within the Talladega National Forest in Alabama, where restoration and maintenance of pine ecosystems is a priority, fire frequency (both wild and prescribed) was assessed using a geographical process applied to a fire history database. Two methods for assessing fire frequency were employed: (1) a simple method that utilised the entire range of years acknowledged in the database and (2) a conservative method that was applied only the date of the first and last fires recorded at each location. Analyses were further separated by (a) method of mean fire return interval calculation (weighted by area or Weibull) and (b) fire season interval with analyses conducted on growing season and dormant season fires. Analyses of fire frequency for national forest planning purposes may help determine whether a prescribed fire program mimics ecological and historical fire frequencies and meets intended objectives. The estimated fire return interval was between ~5 and 6.5 years using common, straightforward (simple) methods. About one-third of the forest receives no fire management and about half of the balance has sufficiently managed fuels.
... As a result, the 3 belt transects per site cumulatively extended for 100 m and encompassed 0.2 ha (Anderson and Pospahala, 1970;Arevalo, 2002). We divided the TNF into 4 management categories (20 sites in each category): prescribed fires occurring at 1-3, > 3-8, > 8-12, and > 12-year fire intervals (Stober et al., 2020). The stands experiencing less frequent fire (>3-year fire interval) did not have any mechanical thinning since the establishment of the fire regime. ...
Snags, or standing dead trees, are an important structural component of forest ecosystems. Many animals, including endangered species, depend on snags for foraging, protection, or raising young. Climate change, habitat loss, and modification of natural disturbance regimes contribute to changes in the availability and characteristics of snags in forests. Therefore, understanding what natural and artificial processes promote snags with the characteristics necessary for wildlife is a significant conservation concern. We examined how low-severity prescribed fire affected the density and characteristics of snags at 80 sites in the Talladega National Forest, Alabama. We sampled sites within 4 prescribed fire intervals, including 1-3 (previously thinned 4-23 years ago), > 3-8, > 8-12, and > 12 years. At each site, we measured snags across transects on 3 different slope positions, including the ridge, mid-slope, and valley, to account for slope-influenced fire behavior and stressors. The average diameter of snags increased in stands with the shortest prescribed fire interval, but snag height, decay class, and percentage of bark remaining were similar across all fire intervals. Snag density was lowest in the shortest fire interval due to fewer small-and medium-sized hardwood snags. A higher density of large snags was found in the shortest fire interval compared to the longest fire interval. Ridges had a greater density of snags compared to mid-slope and valley positions due to more small-and medium-sized pine snags. Although thinning followed by frequent, low-severity prescribed fire reduces snag density, the increase in density of large-diameter snags provides high-quality habitat for snag-dependent birds and bats. More intense fire and other stressors on ridges likely promote higher densities of snags. Our research indicates forest managers can use prescribed fire and thinning to accomplish multiple management goals while continuing to produce valuable snags for wildlife.
... Burned area are likely to demonstrate seasonality, with peaks in fire frequency after the dry or rainy season (Caúla et al., 2015;Oliveira-Júnior et al., 2020a) as was found in the Amazon (Abel et al., 2021) and the Atlantic Forest (Rio de Janeiro state - Freitas et al., 2020; Alagoas state - Oliveira-Júnior et al., 2020a). One study was made in the states with high agricultural aptitude (Mota et al., 2019), and probabilistic modeling is a promising tool for analyzing this phenomenon (e.g., Oliveira et al., 2012aOliveira et al., , 2012bKhastagir, 2018;Stober et al., 2020). Khastagir (2018) found a forest fire danger index with a considerable skewness in Victoria, Australia. ...
The trade-off between conservation of natural resources and agribusiness expansion is a constant challenge in Brazil. The fires used to promote agricultural expansion increased in the last decades. While studies linking annual fire occurrence and rainfall seasonality are common, the relationship between fires, land use, and land cover remains understudied. Here, we investigated the frequency of the fires and performed a trend analysis for monthly, seasonal, and annual fires in three different biomes: Cerrado, Pantanal, and Atlantic Forest. We used burned area and integrated models in distinct scales (interannual, intraseasonal, and monthly) using Probability Density Functions (PDFs). The best fitting was found for Generalized Extreme Values (GEV) distribution at all three biomes from the several PDFs tested. We found the most fire in the Pantanal (wetlands), followed by Cerrado (Brazilian Savanna) and Atlantic Forest (Semideciduous Forest). Our findings indicated that land use and land cover trends changed over the years. There was a strong correlation between fire and agricultural areas, with increasing trends pointing to land conversion to agricultural areas in all biomes. The high probability of fire indicates that expanding agricultural areas through the conversion of natural biomes impacts several natural ecosystems, transforming land cover and land use. This land conversion is promoting more fires each year.
This work describes the development and analysis of a spatially explicit environmental model to estimate the current, ecological, condition class of a managed forest landscape in the southern United States. The model could be extendable to other similar temperate forest landscapes, yet is characterized as a problem-specific, hierarchical, binary process model given the explicit relationships it recognizes between the management of southern United States pine-dominated natural forests and historical ecological conditions. The model is theoretical, based on informed proposals of the landscape processes that influence the ecological condition, and their relationship to perceived ecological condition. The modeling effort is based on spatial data that describe the historical forest community classes, forest plan provisions, fire history, silvicultural treatments, and current vegetation conditions, and six potential ecological condition classes (ECC) are assigned to lands. A case study was provided involving a large national forest, and validation of the outcomes of the modelling effort suggested that the overall accuracy when predicting the exact ecological condition class was about 46%, while the overall accuracy ±1 class was about 81%. For large, heterogeneous forest areas, issues remain in estimating the input variables relatively accurately, particularly the pine basal area.
This study focused on the rare and threatened plant species eastern turkeybeard (Xerophyllum asphodeloides (L.) Nutt.) and its presence or absence in the Talladega National Forest in Alabama, USA. An ensemble suitable habitat map was developed using four different modeling methods (MaxEnt, Generalized Linear Model, Generalized Additive Model, and Random Forest). AUC evaluation scores for each model were 0.99, 0.96, 0.98, and 0.99, respectively. Biserial correlation scores for models ranged from 0.71 (GLM) to 0.94 (RF). The four different models agreed suitable habitat was found to cover 159.57 ha of the land. The ground slope variable was the most contributive variable in the MaxEnt and RF models and was also significant in the GLM and GAM models. The knowledge gained from this research can be used to establish and implement habitat suitability strategies across the Talladega National Forest and similar ecosystems in the southern United States.
Prescribed fire is one of the most widely advocated management practices for reducing wildfire hazard and has a long and rich tradition rooted in indigenous and local ecological knowledge. The scientific literature has repeatedly reported that prescribed fire is often the most effective means of achieving such goals by reducing fuels and wildfire hazard and restoring ecological function to fire-adapted ecosystems in the United States (US) following a century of fire exclusion. This has translated into calls from scientists and policy experts for more prescribed fire, particularly in the Western US, where fire activity has escalated in recent decades. The annual extent of prescribed burning in the Western US remained stable or decreased from 1998 to 2018, while 70% of all prescribed fire was completed primarily by non-federal entities in the Southeastern US. The Bureau of Indian Affairs (BIA) was the only federal agency to substantially increase prescribed fire use, potentially associated with increased tribal self-governance. This suggests that the best available science is not being adopted into management practices, thereby further compounding the fire deficit in the Western US and the potential for more wildfire disasters.
Fire is a global driver of ecosystem structure, function, and change. Problems common to fire scientists and managers worldwide include a limited knowledge of how multiple taxonomic groups within a given ecosystem respond to recurrent fires, and how interactions between fire regimes and environmental gradients influence biodiversity. We tested six hypotheses relating to fire regimes and environmental gradients in forest ecosystems using data on birds (493 sites), mammals (175 sites), and vascular plants (615 sites) systematically collected in dry eucalypt forests in southeastern Australia. We addressed each of these hypotheses by fitting species distribution models which differed in the environmental variables used, the spatial extent of the data, or the type of response data. We found (1) as predicted, fire interacted with environmental gradients and shaped species distributions, but there was substantial variation between species; (2) multiple characteristics of fire regimes influenced the distribution of forest species; (3) common to vertebrates and plants was a strong influence of temperature and rainfall gradients, but contrary to predictions, inter-fire interval was the most influential component of the fire regime on both taxonomic groups; (4) mixed support for the hypothesis that fire would be a stronger influence on species occurrence at a smaller spatial extent; only for vertebrates did scale have an effect in the direction expected; (5) as predicted, vertebrates closely associated with direct measures of habitat structure were those most strongly influenced by fire regimes; and (6) the modeled fire responses for birds were sensitive to the use of either presence–absence or abundance data. These results underscore the important insights that can be gained by modeling how fire regimes, not just fire events, influence biota in forests. Our work highlights the need for management of fire regimes to be complemented by an understanding of the underlying environmental gradients and key elements of habitat structure that influence resource availability for plants and animals. We have demonstrated that there are general patterns in biotic responses to fire regimes and environmental gradients, but landscape management must continue to carefully consider species, scale, and the quality of biodiversity data to achieve biodiversity conservation in fire-prone forests.
Fire and resource managers of the southern Appalachian Mountains, USA, have many questions about the use of prescribed fire and mechanical treatments to meet various land management objectives. Three common objectives include restoration to an open woodland, oak regeneration, and fuel reduction. This paper provides information about reaching each of these three management objectives by using prescribed burning (B), mechanical fuel reduction (M), and a combination of both fire and mechanical treatment (MB). The southern Appalachian site of the National Fire and Fire Surrogate study has been burned three times and a mechanical treatment has been conducted twice since 2002. Stand structure was changed by each active treatment but restoration to an open woodland was not achieved by any. The MB treatment units developed the desired overstory structure but heavy sprouting of woody species in the understory prevented the establishment of a diverse herbaceous forest floor. Oak reproduction was increased by all active treatments, largely by sprouting of top-killed stems. The degree of fuel reduction differed by treatment. All treatments reduced the shrub layer, thus reducing the vertical fuel component. The B and MB treatments reduced most fuels and likely reduced the severity of a subsequent wildfire. We conclude that additional burning is required to meet each management objective, and that fires should be conducted more frequently, in different seasons, or in combination with other treatments.
Sierra de Manantlán Biosphere Reserve (RBSM) in Jalisco is the most important reserve in western Mexico, where fires are one of the main forest disturbances. In order to reconstruct historical fire regimes, partial sections of Pinus douglasiana with fire scars were collected. Using dendrochronological techniques, the exact dating of 293 scars from 51 trees allowed the reconstruction of fire frequency for the period 1867-2010. We reconstructed mean fire interval of 5.5 years (MFI: all scars) and 3.6 years for the Weibull mean probability interval (WMPI). The MFI (≥ 25 % scarred) was 8.9 years and WMPI was 6.9 years. The seasonal patterns of fire occurrence showed that most fires (68.3 %) were formed in middle earlywood, 30 % in early earlywood and 1.7 % in late earlywood. Considering the phenology of the species, it was determined that 98.3 % of fires occurred in spring and 1.7 % at the beginning of summer. The fires were recorded in dry years, but the relationship was not statistically significant. A strong relationship between droughts and widespread fires was observed. Likewise, it was determined that climate variability was strongly related to ENSO; fires reconstructed from 1956 to 2010 correspond with both El Niño and La Niña events.
Climate has a primary influence on the occurrence and rate of combustion in ecosystems with carbon-based fuels such as forests and grasslands. Society will be confronted with the effects of climate change on fire in future forests. There are, however, few quantitative appraisals of
how climate will affect wildland fire in the United States. We demonstrated a method for estimating changes in fire probability based on future climate simulations of temperature and precipitation. The probability of a fire occurring in a particular climate was extracted from the Physical
Chemistry Fire Frequency Model (PC2FM) and represented the rate of change in fire due to climate. Climate output data from two global climate models (GCMs) were applied to the PC2FM to estimate changes in fire probability. We calculated change in fire frequency and probabilities from the difference
between current and future climates and mapped climate-forced percentage change in fire probability under each GCM for the nation at a 1.2 km2 scale. Future fire probability estimates increased in cooler northern and high elevation regions but decreased slightly in some hotter and
drier regions of the southwestern United States. Our approach's greatest strength may be reliance on only climate data and the simple principles of physical chemistry; many other nonclimatic factors that affect fire are often difficult to predict in the distant future.
A predictive equation for estimating fire frequency was developed from theories and data in physical chemistry, ecosystem ecology, and climatology. We refer to this equation as the Physical Chemistry Fire Frequency Model (PC2FM). The equation was calibrated and validated with North American fire data (170 sites) prior to widespread industrial influences (before ~1850 CE) related to land use, fire suppression, and recent climate change to minimize non-climatic effects. We derived and validated the empirically based PC2FM for the purpose of estimating mean fire intervals (MFIs) from proxies of mean maximum temperature, precipitation, their interaction, and estimated reactant concentrations. Parameterization of the model uses reaction rate equations based on the concentration and physical chemistry of fuels and climate. The model was then calibrated and validated using centuries of empirical fire history data. An application of the PC2FM regression equation is presented and used to estimate historic MFI as controlled by climate. We discuss the effects of temperature, precipitation, and their interactions on fire frequency using the PC2FM concept and results. The exclusion of topographic, vegetation, and ignition variables from the PC2FM increased error at fine spatial scales, but allowed for the prediction of complex climate effects at broader temporal and spatial scales. The PC2FM equation is used to map coarse-scale historic fire frequency and assess climate impacts on landscape-scale fire regimes.
This paper estimates fire frequency in Catalonia (NE Spain) for the last quarter of the 20th Century (1975–1998) from historical burned area maps. Remote sensing images provided perimeters of fires ≥30 ha, which were used to characterize the temporal patterns of fire occurrence in Catalonia. Several fire frequency models were used to reproduce the observed pattern of wildfires occurrence in the study period. Natural fire rotation period was estimated to be 133 years. Poisson tests were carried out to check random fire occurrence either along the time period or across the analysed region. Observed fires were not randomly generated either in space or in time, despite being sampled using two different plot sizes. This sampling design was also used for Mean Fire Interval (MFI) analysis, which allowed us to significantly fit a Weibull distribution to the observed proportion of fire intervals (for both sample sizes), enabling us to estimate the hazard of burning, mortality, and survivorship functions. Finally, MFI was also applied to forest regions of Catalonia, which are defined according to forest management plans based on their homogeneous climatic conditions. Such an analysis revealed relevant differences in forest management and their consequences on fire occurrence.
Statistical characterization of past fire regimes is important for both the ecology and management of fire-prone ecosystems.
Survival analysis—or fire frequency analysis as it is often called in the fire literature—has increasingly been used over
the last few decades to examine fire interval distributions. These distributions can be generated from a variety of sources
(e.g., tree rings and stand age patterns), and analysis typically involves fitting the Weibull model. Given the widespread
use of fire frequency analysis and the increasing availability of mapped fire history data, our goal has been to review and
to examine some of the issues faced in applying these methods in a spatially explicit context. In particular, through a case
study on the massive Cedar Fire in 2003 in southern California, we examine sensitivities of parameter estimates to the spatial
resolution of sampling, point- and area-based methods for assigning sample values, current age surfaces versus historical
intervals in generating distributions, and the inclusion of censored (i.e., incomplete) observations. Weibull parameter estimates
were found to be roughly consistent with previous fire frequency analyses for shrublands (i.e., median age at burning of ~30–50years
and relatively low age dependency). Results indicate, however, that the inclusion or omission of censored observations can
have a substantial effect on parameter estimates, far more than other decisions about specifics of sampling.
The capacity of many plant species to resprout in fire-prone shrublands is thought to engender persistence, yet management
concerns exist for the long-term persistence of some resprouting species given anthropogenic impacts including shortened fire
intervals, long periods of fire exclusion, and/or fires of increasingly high severity. We explored the potential demographic
effects of different fire interval regimes on lignotuberous resprouter species using the last fire interval for 36 sites (33
experimental fires, 3 wildfires) in biodiverse SW Australian shrublands, spanning an interval range of 3–42years. Mortality
and regrowth 1year following the last fire was assessed for >7,000 tagged individuals from 20 shrub and sub-shrub species.
Using generalized linear mixed effect models, we estimated the influence of fire interval (and selected fire and environmental
covariates) on mortality and regrowth rates across all species, and individually for the four most common species. The overall
model, as well as the models for three of the four most common species (Banksia attenuata, Melaleuca leuropoma, and M. systena, but not Hibbertia hypericoides) supported the hypothesis of increased mortality at short and long fire intervals, most likely due to total non-structural
carbohydrate (TNC) and bud-bank limitation, respectively. However, no relationship between regrowth rate and fire interval
was detected, suggesting that increased mortality at short (3–5year) fire intervals may not be due solely to resource (TNC)
limitation. Results show that lignotuberous resprouters are potentially vulnerable to population decline through attrition
of mature plants under both shortened and lengthened fire interval regimes.
KeywordsBud bank–Lignotuber–Resprouting–Fire regime–Mortality–
Banksia
–
Melaleuca
Progress requires attention to governance at multiple levels
It has been suggested that large, high-severity fires historically structured warm–dry mixed conifer forests in the American Southwest. To test this, we reconstructed fire regime characteristics of an 1135-ha (11.3 km 2) mixed conifer landscape in northern Arizona using complementary approaches. We analysed composite fire intervals, point fire intervals, natural fire rotation, landscape characteristics and forest age structure. Composite analysis of cross-dated fire scars from 133 trees indicated a mean fire interval (MFI) of 2.0–8.5 years between 1670 and 1879. Frequent fires halted abruptly after 1879. Mean point fire interval (MPFI) was 11.8 years and ranged 2–61 years. Mean fire rotation was 14.4 years. Density of most occurring tree species increased dramatically after fire regime disruption, with southwestern white pine (Pinus strobiformis) and white fir (Abies concolor) showing large numerical gains. Tree establishment patterns compared with widespread fire dates did not suggest historical high-severity fires at the site level. Although strong evidence of high-severity fire at finer scales was lacking, spatial locations of 'young' plots suggested the possibility of historical high-severity disturbances #25 ha in size. The historical fire regime on this landscape was one of high-frequency, low-severity fires. Current conditions call for restoration of forest structure and function.
Accuracy of small-area, fire-interval estimation methods has been inadequately assessed, thus we conducted modern calibration and historical testing of the traditional composite-fire-interval and a newer all-tree-fire-interval method for estimating population mean fire intervals. We tested in eight areas, at four scales, using 30 small plots across ponderosa pine forests on the South Rim of Grand Canyon National Park. In modern calibration, individual-plot all-tree-fire-intervals were equal to population mean fire intervals in all plots. Across the eight areas, a mean-plot version of the all-tree-fire-interval method never failed, whereas mean-plot versions of composite-fire-intervals failed in 37.5-100% of areas. Pooled composite-fire-intervals, the traditional method, failed in all subareas. In historical testing, pooled and mean-plot all-tree-fire-interval methods and two variations of a mean-plot composite-fire-interval method had the lowest mean relative errors. Again, pooled composite-fire-intervals performed poorly across the eight areas. Overall, in modern and historical tests, the mean-plot all-tree-fire-interval method outperformed all others, but highly filtered mean-plot composite-fire-intervals were fairly accurate in historical tests. Both could be reliable methods, if replicated in small plots averaged over 600-1000-ha landscapes, but for small areas, the all-tree-fire-interval method outperformed others. However, for general use, there may be more value in spatially explicit, landscape-scale methods, rather than any small-area method.
The pre-European-settlement forests of the Talladega Mountains in eastern Alabama were analyzed using the 1832 U.S. General Land Office Survey records. The surveyors identified and marked the positions of trees at each township section and quarter-section corner. An examination of the relative densities of tree species was used to reconstruct the composition of forest communities on different topographic sites. The results indicate a pattern of gradation from species-rich hardwood forests found in shaded bottomland sites to species-poor pine forests occurring on ridgetops. The ridgetops have shallow, coarse soils with poor moisture-holding capacity. In contrast, the bottomland sites have much deeper soils that generally have a higher moisture-holding capacity. The differences between soil and litter moisture between these sites probably led to differences in the frequency of fire, which was a major factor controlling forest-stand development and community composition.
In this study, the Weibull distribution is tested as a possible model for fire
interval data derived from dendrochronologically-dated fire scars from four
sites in the American Southwest. Two- and three-parameter Weibull
distributions were fit to fire interval data sets, and additional statistical
descriptors based on the Weibull were derived to improve our understanding of
the range of variability in presettlement fire regimes. The three-parameter
models failed to provide improved fits versus the more parsimonious
two-parameter models, indicating the Weibull shift parameter may be
superfluous for Southwestern fire regimes. The Weibull Modal Interval (MOI)
was a superior overall measure of central tendency, and appears to identify a
common underlying structure in Southwestern fire regimes independent of
habitat type and environmental gradients. Unusually short and long fire
intervals were identified by the lower and upper exceedance intervals (LEI and
UEI) and the Maximum Hazard Interval (MHI) based on the Weibull hazard
function. Model statistics were nearly identical between two pairs of sites
that were 260 kilometers distant that differed in topography, vegetation, and
land-use history. However, differences were observed between sites only 10
kilometers apart, suggesting the influence of local factors (e.g., topography
and substrate) over regional influences (e.g., climate). Although the Weibull
models helped quantify the historical range of variability in presettlement
fire regimes, ecological interpretations of the Weibull parameters proved
difficult.
Although development of pinyon–juniper woodlands is understood to require decades after stand-replacing
fire, data describing relationships between many key structural elements and time since fire (TSF) are
lacking. In this study, we sampled live trees, seedlings, shrubs, snags, and downed logs on 13 sites that
together comprised a 370-year fire chronosequence. We analyzed individual relationships between structural
attributes and TSF. We also developed an additive index of structural complexity and analyzed its
relationship with TSF. Live juniper and total tree density were positively and linearly related to TSF
(R2 = 0.76 and 0.49, respectively). Pinyon tree density and TSF were not significantly related. No live trees
(P1.37 m height) were found on sites burned less than 30 years before sampling, although seedlings
were found as early as 6 years TSF. Live pinyon tree biomass, live juniper biomass, and total tree biomass
followed ‘‘s-shaped’’ functions (4-parameter Weibull; R2 = 0.32, 0.62, and 0.96, respectively), with total
biomass maximizing at 65 Mg ha�1 around 250 years since fire. Seedling densities and shrub cover were
not significantly related to TSF. Juniper snag density showed a significant negative relationship with TSF
(R2 = 0.54) and total snag density followed a ‘‘u-shaped’’ function depending on TSF (2nd-order polynomial;
R2 = 0.47). Pinyon snag density and TSF were not significantly related. Density of rotten logs was
positively and linearly related to TSF (R2 = 0.46) whereas sound logs and TSF were not statistically related.
Structural complexity showed a positive linear relationship with TSF (R2 = 0.46). These results indicate
that although individual structural elements show various relationships with TSF, structural complexity
increases as sites approach persistent woodland conditions. Findings from this study provide resource
professionals with information that can help in developing and assessing management approaches
intended to emulate natural structural patterns.
A total of 53 fire-scarred Pinus echinata (shortleaf pine) trees were examined to reconstruct a ridgetop fire chronology of an oak-pine forest in the Ozark Mountains of north-central Arkansas. This process yielded 104 fire scars dating to 61 separate fire years. Fire frequency was greatest during the Euro-American Settlement Period (1820–1900), when the median fire interval (MFI) was 1.9 years. Most of the sample trees established during this period. Fire remained prevalent through the Regional Development (1901–1930) and Modern (1931–2003) Periods, when the MFI was 2.1 and 2.6 years, respectively. Palmer Drought Severity Index mean values from 1823–2003 did not differ (p = 0.76) between fire years and non-fire years, suggesting that fires in the study area were predominantly anthropogenic in origin.
Four combinations of season and frequency of burning were applied in Coastal Plain loblolly pine stands over a 43-year period. Overstory species composition and growth were unaffected by treatment. Above-ground portions of small hardwoods (less than 12.5 cm d.b.h.) were killed and replaced by numerous sprouts under periodic summer, periodic winter, and annual winter burning regimes. With annual summer burning, small hardwoods and shrubs were killed and replaced by vegetation typical of grassland communities. Grasses and forbs also dominated the understory of annual winter burns but numerous hardwood sprouts survived. Study results emphasize that frequent burning over a long period is needed to create and maintain the pine-grassland community observed by the first European settlers of the southeast.
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