Range expansion of invasive shrubs: implication for crown fire risk in forestlands of the southern USA
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Range expansion of invasive shrubs: implication for crown fire risk in forestlands of the southern USA
Hsiao-Hsuan Wang 2
Carissa L. Wonkka 0 1
William E. Grant 2
William E. Rogers 1
Associate Editor: Jean H. Burns
0 Present address: Department of Agronomy and Horticulture, University of Nebraska , Lincoln, NE 68583 , USA
1 Department of Ecosystem Science and Management, Texas A&M University, College Station , TX 77843 , USA
2 Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station , TX 77843 , USA
Non-native plant invasions and changing management activities have dramatically altered the structure and composition of forests worldwide. Invasive shrubs and fire suppression have led to increased densification and biomass accumulation in forest ecosystems of the southeastern USA. Notably, Chinese and European privets are rapid growing, shade-tolerant shrubs which number among the most aggressive invasive species in these forests. Privet encroachment has caused losses of native diversity, alteration of ecosystem processes and changes in community structure. The latter has become manifest through decreases in fine herbaceous fuels concurrent with increases in coarse woody fuels in forest understoreys. These alterations in fuel structure will potentially lead to less frequent, but more severe forest fires, which threaten important forest resources during extreme weather conditions. Drawing on extensive data sets compiled by the US Forest Service, we integrated statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework to predict potential range expansion of Chinese and European privet (Ligustrum sinense and L. vulgare) and the associated increase in crown fire risk over the next two decades in forestlands of Mississippi and Alabama. Our results indicate that probability of invasion is positively associated with elevation, adjacency (within 300 m) to water bodies, mean daily maximum temperature, site productivity and private land ownership, and is negatively associated with slope, stand age, artificial regeneration, distance to the nearest road and fire disturbance. Our projections suggest the total area invaded will increase from 1.36 to ≈31.39% of all forestlands in Mississippi and Alabama (≈7 million hectares) and the annual frequency of crown fires in these forestlands will approximately double within the next two decades. Such time series projections of annual range expansions and crown fire frequency should provide land managers and restoration practitioners with an invasion chronology upon which to base proactive management plans.
Biological invasion; dispersal model; habitat quality; invasive plants; invasive species; logistic regression; zero-inflated negative binomial regression
Each year millions of acres of wildland unintentionally
burn causing extensive property and resource losses.
Annual wildfire suppression costs in the USA exceed
$1 billion placing a considerable burden on state and
federal taxpayers. Despite this substantial expenditure,
55 544 fires burned 9 159 917 acres in 2012
. Wildfires result in millions of dollars in property
damage, substantial loss of natural resources, especially
timber and wildlife, and potential human death and
injury. In addition, wildfires that deviate from the historic
fire regime of the ecosystem with respect to frequency
or intensity can disrupt a variety of critical ecosystem
functions and jeopardize the long-term integrity of an
affected area. Facilitation of undesirable species
invasions, threats to the persistence of endangered species
and increases in soil erosion and attendant water quality
are all potential consequences of fire regime alteration
(D’Antonio et al. 2009; Smith et al. 2011)
. For instance,
stand-replacing crown fires have been occurring more
frequently in forests with historical low-intensity,
frequent fire regimes because of fire suppression and fuel
accumulation, causing disruption of the production of
essential ecosystem services (Dale et al. 2001).
Southeastern forests are one of the areas under the
highest fire danger in the USA. In most years, the south
leads the USDA Forest Service regions in number of
(Gaither et al. 2011)
. Although these fires are usually
smaller in acreage and overall damage than fires in the
Western USA because of forest fragmentation and
accessibility to firefighters, some of the largest fires in the USA
have occurred in this region during periods of extreme
(Marshall et al. 2008)
Understorey shrubs are often the most hazardous fuels
(Stephens and Ruth 2005)
, and they can act as ladder
fuels to carry surface fires into the forest canopy. In
Thompson and Spies (2010)
greatest crown damage in areas with high shrub cover, despite
lower fine fuels. Similarly,
Andreu et al. (2012)
that reducing shrubs in many types of southeastern
forests consistently resulted in reduced fire flamelengths.
Crown fires kill trees, destroying valuable timber and
increase the suppression efforts necessary to contain
(Albini and Stocks 1986; Michaletz and
. Forest understoreys have become
increasingly thicketized in southeastern US forests due to the
introduction and proliferation of non-native shrub
species. Little experimental data exist regarding the effect
of this thicketization on the frequency of crown fires in
Exotic shrub invasions of southeastern US forests have
been shown to significantly alter fire regimes
D’Antonio 1998; Brooks et al. 2004)
. Invasive shrubs
grow rapidly and substantially increase the live, coarse
woody fuel loads in forest understoreys. Live woody
fuels can inhibit or increase fire spread and intensity
depending on moisture content (Varner et al. 2005).
During normal weather conditions for the Southeast, this
increased shrub density reduces fire risk by reducing
fine herbaceous fuels and increasing moisture content
of foliage litter below the shrub layer
(Thaxton and Platt
2006; Nowacki and Abrams 2008)
. However, during
extreme drought conditions, this thicketized understorey
can increase fire intensity as the shrubs experience
lowered moisture content and full or partial crown dieback,
increasing coarse woody fuel loading
(Van Wilgen and
Richardson 1985; Grace 1998)
. These elevated fire
intensities increase the likelihood of a devastating crown fire
occurring. This is especially concerning given predictions
of increases in summer and fall fire danger and longer fire
seasons in the southeastern USA as a result of climate
change in upcoming decades
(Liu et al. 2010; Mitchell
et al. 2014)
. These dense shrub thickets also increase
vertical continuity within the forest, which reduces the
intensity needed for crown fire ignition since crown fire ignition
is a function of height between surface fuels and forest
crown (Van Wagner 1977).
Based on the Forest Inventory and Analysis (FIA)
surveys from early 2000 until December 2012, there
were a total of 42 637 forested plots in the southern
. Sixty-six major invasive exotic plant
species have been detected on forestlands in Alabama,
Arkansas, Florida, Georgia, Kentucky, Louisiana, North
Carolina, South Carolina, Tennessee, east Texas and
. Among these are many shrubs
and vines that cause thicketization of the understorey.
Chinese and European privet (Ligustrum sinense and
L. vulgare) (henceforth exotic privets) are among the
most aggressive invasive shrubs in this region, having
invaded 9.64 % of forestlands, primarily in Alabama and
Mississippi (Fig. 1).
Exotic privets form dense understorey stands spreading
vegetatively to fill forest gaps. These uniform thickets
greatly increase vertical continuity in southern forests,
reaching over 20 m in height at times
. Observational and limited experimental
evidence suggests that the dense woody understorey
created by exotic privet invasion can supress fine herbaceous
fuels and lower fire risk during periods of high foliar
moisture. However, during drought, dense understorey shrub
thickets with higher dead-to-live fuel ratios could greatly
increase available fuels and can lead to more intense and
severe fires than the historically frequent, but less intense
surface fires of uninvaded forests
(Brockway and Lewis
1997; Varner et al. 2005)
. Aditionally, thick midstorey
strata can catch fallen pine needles, potentially
increasing the flamability of these course woody fuels (Brockway
and Lewis 1997). More reliable predictions of the speed
and scope of exotic privet range expansion and
associated crown fire threats are critically needed to improve
the management of these invasions and their potential
effects on crown fire risk. Yet such predictions remain a
challenge due to modelling and data limitations. In this
article, we first describe an approach for predicting
potential range expansion of exotic privets in forestlands of
Alabama and Mississippi. The approach integrates statistical
forecasting and analytical techniques within a spatially
explicit, agent-based, simulation framework. We then
examine the potential effect of exotic privets on crown
fire risk. Finally, we identify where new invasions are
most likely to occur, and forecast the geographical extent
of range expansion and the associated crown fire
frequency over the next two decades.
Target ecosystem and focal species
Chinese and European privets are multi-stemmed,
shadetolerant, semi-evergreen to evergreen perennial shrubs.
European privet was introduced to the USA in the
mid-1800s and Chinese privet was introduced in 1852
and both were planted widely in the south as ornamental
. Both species have
escaped cultivation and are presently naturalized from
Florida to New England and as far west as Kansas and
. They grow to a maximum
height of 7 – 10 m within a few years of germination and
colonize by sprouting from the roots or seed germination
. As many as 1300 fleshy fruits per square
metre of canopy are produced annually
Westoby 1987; Strong et al. 2005)
. The seeds are widely
dispersed by birds and mammals, have high viability
and few germination requirements (Dirr 2011). Both
species are capable of sustained rapid growth in low light and
nutrient poor conditions which, consequently, allows
them to readily displace native shrub and herbaceous
species and form dense understorey stands, especially
along roadsides and riparian corridors
Miller 2005; Webster et al. 2006)
We focussed our investigation on the woodlands of
Alabama and Mississippi because of the extent of privet
invasion into these areas. Alabama and Mississippi have a
humid, subtropical climate with 1400 mm of precipitation
on average and an average temperature of 18 8C. The
growing season can reach as many as 300 days per
year in the southern portions of the states. Alabama
and Mississippi are part of the southern region of the
USA, providing vast timber resources
(McNulty et al.
. Privet invasions occur in all forest types in these
states, including longleaf-slash pine, loblolly shortleaf
pine, oak-hickory hardwoods and oak-pine communities
(USDA 2012, 2013)
To predict the future range expansion of exotic privets
and the associated effects on crown fire risk in forestlands
of Alabama and Mississippi, we developed a spatially
explicit, agent-based, invasion model following the
general procedure described by Wang et al. (2011, 2012).
The model consisted of a grid of 17 360 geo-referenced
cells (agents), each representing a 2428-ha (6000 acres)
plot of land, which is the size of the sampling units in the
national array of permanent sampling areas maintained
by the US Forest Service (FIA)
. The basic
sampling design of FIA consists of a lattice of 2428-ha
hexagons, with one sample plot located randomly within each
. We assigned each cell to one of
seven land types (urban/built-up land, agricultural land,
rangeland, forest land, water, wetland or barren land)
based on land use and land cover data
each of these forest land cells (2742 in Alabama and
3770 in Mississippi), we assigned additional
characteristics based on the FIA data set
landscape features, forest conditions, management
activities and disturbances, and climatic conditions, as
well as the current frequency of crown fires [see
Supporting Information—Appendix S1]. We also assigned to
each cell the percentage of land currently occupied by
exotic privets, which we based on the Southern Nonnative
Invasive Plant data Extraction Tool
merged the various data sets using ArcMapTM 10 (ESRI,
Redlands, CA, USA) and imported the data associated
with each cell into VB.NET& (Microsoft, 2003), where
each cell was described by the indicated characteristics
as well as by rules governing its dynamics. We then ran
240 twenty-year Monte Carlo simulations.
We represented annual changes in terms of the
percentage of land occupied by exotic privets in each cell
(DPi,t/Dt) as resulting from local spread within a cell
(Lsi,t) plus invasion from other cells (Ii,t):
Pi,t+1 = Pi,t + Lsi,t + Ii,t
Lsi,t+1 = Lsi,t + riPi,t(1 − Pi,tKi−1)
Ii,t+1 = Ii,t +
k jiP j,t
where Pi,t is the percentage of land occupied by exotic
privets in cell i at time t. Lsi,t is the local spread in terms of
the percentage of land occupied by exotic privets within
cell i at time t, which has a logistic growth form. Ii,t is
the increase of the percentage of land occupied by exotic
privets due to invasion from adjacent cells to cell i at time
t, which represents the dispersal process. ri is the mean
intrinsic rate of local spread within cell i and Ki is the
carrying capacity within cell i, both represented in terms
of the percentage of land occupied by exotic privets. kji is
the proportion of a lognormal dispersal kernel
representing invasion from cell j to cell i represented in terms of the
percentage of land occupied by exotic privets (Fig. 2). We
set Pi,0 equal to that reported for the year 2003 and
assumed all Ki ¼ 100 based on information in the
Southern Nonnative Invasive Plant data Extraction Tool, which
indicates that exotic privets already occupy over 95 % of
We calculated ri based on available data from the FIA
and Southern Nonnative Invasive
Plant data Extraction Tool
method described in Wang et al. (2011):
ln(Pi,t2 /Pi,t1 )
t2 − t1
where Pi,t1 and Pi,t2 are the percentage of land occupied
by exotic privets in cell i at the year of the first (t1) and
second (t2) survey, respectively. We excluded plots that
had been subjected to any site preparation treatments
or invasion control or if Pi,t1 was greater than Pi,t2 . The
FIA non-native invasive plant survey began in 2001 and
is intended to survey one-fifth of the plots in each of 13
southern states annually
(Rudis et al. 2006)
. At the time
of our analysis, the first cycle of surveys had been
completed for both Alabama and Mississippi, and the second
cycle, which began in 2006, had been completed for
Alabama, but only 3 % of second cycle had been completed
for Mississippi. For those plots for which the second cycle
data were not yet available, we estimated ri as a function
of a habitat quality index, HQi (0 ≤ HQi ≤ 1, calculation
described below), since the leading edges of invasive
species expansion most often are correlated with habitat
(Jarnevich and Stohlgren 2009)
. We explored the
relationship between ri and HQi using several regression
analyses including linear (ri ¼ a + bHQi), logarithmic
(ri ¼ a + b ln HQi), power (ri = a + bHQi−1 and ri = a + bHQi2)
and exponential (ri = a exp(bHQi0.5), ri = a exp(bHQi) and
ri = a exp(bHQi2))
(Ga´ mez-Virue´ s et al. 2010; Wang et al.
. We identified the best-fit equation based on
P-value of estimated coefficients and R2.
We calculated HQi for each of the 6512 forested plots
sampled during the first survey cycle in terms of invasion
probability using logistic regression
HQi = pi(Y = 1) = [1 + exp(aex+pX(a′ib+)]X=′ibf) (a + X′ib) (5)
where Y is a binary variable taking the value of either 1 if
exotic privets are present or 0 otherwise, pi(Y ¼ 1) is the
probability for Y ¼ 1 and means plot i is invaded by exotic
privets, Xi′ is the vector of climatic conditions, forest
conditions and landscape features of plot i, and a and b (a
vector) are coefficients. We identified the conditions and
features to be tested following
Lemke and Brown (2012)
Wang and Grant (2012
, 2014), and selected the best
equation for HQi based on the Akaike information
criterion (AIC) (Akaike 1973). In addition, we used the Hosmer –
Lemeshow test to verify the statistical validity of the
(Hosmer and Lemeshow 2000)
We estimated kji using a lognormal dispersal kernel,
which has been used successfully to approximate
observed dispersal patterns for a number of trees with
(Stoyan and Wagner 2001;
Greene et al. 2004; Russo et al. 2006; Wang et al. 2011)
k ji ≈
where kji represents the probability of dispersal from cell j
to cell i, the integration variable D is the distance between
cells i and j, S is the shape parameter, which we assumed
was equal to 1, as is typically done when modelling
(Greene et al. 2004)
and L is the scale
parameter, which represents the dispersal velocity (in
grid-width units per year)
(Cannas et al. 2003)
parameterized several versions of the dispersal kernel
function based on different hypothesized dispersal velocities
ranging from 4927, 2463, 1642, . . . 704 m year21 (grid
cell width ¼ 4927 m), that is, with L ranging from 1, 1/2,
1/3, . . . 1/7. For each value of L, we generated simulated
invasion patterns by running 240 eight-year Monte
(Ott and Longnecker 2001)
model initialized to represent the distribution pattern of
exotic privets observed in the field in 2003
We identified the best value of L (hence, the best
estimates of kji) based on the likelihood comparison and
spatial correlation as indicated by Mantel’s test
using 999 randomizations and a ¼ 0.05 level of
significance between simulated and observed invasion
patterns in the year of the second survey.
We estimated the expected frequency of crown fires in
each cell (Ei) by correlating observed frequencies of crown
fires during a 5-year period with landscape features,
forest conditions and climatic conditions [see Supporting
Information—Appendix S2] using zero-inflated negative
Ei(yi|xi′, zi′) = [1 − pi(yi = 0|wi′)]Ei(yi|zi′)
where Ei(yi|wi′, zi′) is the estimated mean frequency of
crown fires during a 5-year period ( yi . 0) in cell i;
pi(yi = 0|wi′) = exp(g + dwi′)/[1 + exp(g + dwi′)] is the
probability that the absence of crown fire was due to
temperature and precipitation, and wi′ is the vector of climatic
conditions; Ei(yi|zi′) = exp(1 + zzi′) is a negative binomial
model predicting crown fire frequency and zi′ is the vector
of landscape features and forest conditions, including
percentage of land occupied by exotic privets; g and, d,
1, and z are vectors and estimated coefficients for the
respective zero-inflated and negative binomial portions
of the model. We selected the best-fit model that included
all significant (P-value , 0.05) variables with lowest value
. Crown fire frequency often has been
related to landscape features
(Hunter 1993; Keeling et al.
, forest conditions
(Link et al. 2006; Keeley 2009)
(Litschert et al. 2012; Liu et al. 2012)
Zero-inflated negative binomial regression commonly is
used to adjust for count variables with excessive zeros
(crown fires were absent from cells characterized by low
temperature and high precipitation).
Results of logistic regression indicated that habitat quality
within cells (HQi) was positively associated with adjacency
(within 300 m) to water bodies, mean daily maximum
temperature, site productivity and private land ownership, and
was negatively associated with slope, stand age, artificial
regeneration, distance to the nearest road and fire
disturbance (Table 1). The logistic regression model correctly
classified 66 % of the cells with regard to presence or absence
of exotic privets, and the P-value of the Hosmer –
Lemeshow test (0.5815) indicated no significant difference
(P-value , 0.05) between observed and model-predicted
occupancy values. HQi values ranged from ,0.01 to 0.95
and generally decreased from west to east (Fig. 3); these
findings are similar to those of
Wang and Grant (2012
2014). Based on the best-fit equation (R2 ¼ 0.72) relating
the mean intrinsic spread rate within cells to habitat quality
(ri ¼ 0.3815 exp(0.8611HQi), Table 2), the most favourable
habitat (HQ ¼ 0.95) produced a local spread rate (r) of
0.86. Of the various dispersal velocities we evaluated, only
a velocity 985 m year21 (L ¼ 1/5 the width of a grid cell
per year) produced simulated invasion patterns that were
not statistically significantly different (P-value , 0.05)
from the observed pattern (Table 3).
The best-fit zero-inflated negative binomial regression
indicated that slope, physiographic class and percentage
of land occupied by exotic privets in 2003 were
statistically significant predictors of the frequency of crown fires
(Table 4). The expected frequency decreased by 4 % (1 2
exp(20.0405) ¼ 0.04) for each 18 increase of slope. The
expected frequencies for sites in the xeric and mesic
physiographic classes were 2.14 and 2.04 times higher,
respectively, than those expected for sites in the hydric
physiographic class. The expected frequency was 1.05
times higher for every % increase of forestland occupied
by exotic privets. Mean daily precipitation and mean daily
maximum temperature were statistically significant
predictors of excessive zeros (that is, predictors of conditions
under which crown fires were unlikely to occur). The
log odds of being an excessive zero would decrease by
0.13 for every 8C increase of mean daily maximum
temperature and would increase by 0.27 for every cm
increase of mean daily precipitation.
Projections of future range expansion in forestlands of
Mississippi and Alabama indicated that exotic privets
have the potential to expand from the ≈0.3 million
acres that they occupied in 2003 to ≈7 million acres in
2023 (Fig. 4A), which represents 31 % of all forestlands
(≈22 million acres) within these two states.
Geographically, projections suggested that the invasion has the
potential to spread outward from virtually all of the
relatively low-occupancy (,25 %) foci that were
scattered throughout Alabama and Mississippi in 2003, the
majority of which were located in south-western
Mississippi, with occupancy levels increasing to .75 % in
many areas by 2023 (Fig. 5A, C, E, G and I). The associated
annual expected crown fire frequencies (ei) increased from
only a few cells (312) in the 0.125 , ei ≤ 0.250 category in
2003 to 1391, 856 and 1479 cells in the 0.125 , ei ≤ 0.250,
0.250 , ei ≤ 0.375 and 0.375 , ei ≤ 0.500 categories,
respectively, in 2023 (Figs 4B and 5B, D, F, H and J).
Exotic privets ecology and crown fire risk
Our model results suggest a strong potential for greater
crown fire risk throughout Alabama and Mississippi during
extreme fire weather due to range expansion and
increased density of exotic privets. High spread rates
associated with the many areas of high habitat quality
depicted by our model suggest that if current
management practices persist, exotic privets could significantly
spread into many unoccupied areas of Alabama and
Mississippi and increase their dominance in already occupied
areas. Our model, which is based on past occurrence of
crown fire in the region, showed a positive correlation
between privet occupation and crown fire risk, suggesting
extreme fire weather
(Brockway and Lewis 1997; Varner
et al. 2005; Duguy et al. 2013)
. Crown fires are more likely
to become manifest with greater fire intensity because a
larger break in vertical continuity can be overcome by hot
fires with longer flame lengths than mild surface fires
(Pollet and Omi 2002)
. In addition, understorey shrubs
increase vertical continuity by providing ladder fuels by
which surface fires ignite the crowns of mature forests
(Doren and Whiteaker 1990; Grace 1998; Brooks et al.
2004; Stephens and Ruth 2005)
. Lonsdale (1993) showed
that increased densities of the understorey shrub Mimosa
pigra lead to an increased frequency of crown torching
during wildfire. Similarly,
Dibble and Rees (2005)
that ladder fuels increased in areas invaded by privet and
Schwilk et al. (2009)
found that crown fires, although rare
during low fire-danger weather, were more frequent in
plots that had not been prescribed burned repeatedly in
the past 40 years. The largest structural difference
between the prescribed burn plots and the control plots
was high levels of shrub cover
(Schwilk et al. 2009)
Despite potential for increased thicketization resulting from
invasion to decrease fine herbaceous fuel, both pine
and foliar litter, which have been shown to be the most
important surface fuel in most southeastern forests
(Ottmar and Prichard 2012)
, will still be available to
carry surface fires in many forest types. Consequently,
the moisture content of the shrub layer will determine
whether it inhibits or increases the intensity of
litterdriven surface fires
Despite observational evidence of low flammability in
privet-invaded areas, little experimental evidence exists
regarding privet stand flammability. Our data show that
highly invaded stands in the study region have
experienced crown fires. The FIA database used in our study
included 220 plots that had a crown fire in the 5 years
prior to data collection. Of those that had a crown fire,
45 plots were invaded by privet with an average privet
cover of 49 %. Therefore, while probability of ignition
could be low in privet stands, especially in years of
average or above average precipitation, privet-invaded stands
do burn, and our model results show that high privet
invasion increases the probability of crown fire initiation
during a fire.
The potential for climate change adds to the threat of
crown fires posed by exotic privet invasion. Our model
shows that average daily precipitation and maximum
daily temperatures are significant predictors of
conditions under which crown fires will be likely to occur.
Crown fire risk increases with decreasing precipitation
and crown fires are more likely to occur with higher
daily maximum temperature. The southern USA is
already one of the most fire-prone areas of the USA
(Gaither et al. 2011)
. Drought is predicted to occur more
Mean daily maximum
Percentage of land
occupied by exotic
the potential for a greater number of crown fires in these
states. Thicketization of understorey shrubs typically leads
to forest mesophication in this region, reducing the
frequency of fire because of the negative feedback between
shrub cover and fine fuel loads and moisture content
(Nowacki and Abrams 2008)
. However, under drought
conditions, shrubs can experience dieback providing coarse
woody fuels that carry fire despite discontinuous fine
herbaceous fuel loading
(Klos et al. 2009; Allen et al. 2010)
Increases in understorey shrub density have been
shown to lead to hotter, more intense fires during
frequently in some areas of the southeastern USA due to
increased temperatures and attendant increases in
evaporation as well as water loss from plants
Mitchell et al. 2014)
. General Circulation Models show
increases in average air temperature (Smith et al. 2009).
In addition, average precipitation predictions are
uncertain for this region. However, most models show great
increases in the distribution and variability of
precipitation and more frequent and intense drought events
(Dale et al. 2001; Allen et al. 2010)
. This can greatly
increase forest susceptibility to devastating wildfires.
Indeed, most fires in the USA occur during periods of
drought (Guyette et al. 2002), and fire hazard in the
Southeast is predicted to increase under many climate
(Dale et al. 2001; Liu et al. 2010)
The humid semi-tropic region accumulates large fuel
loads during rainy periods and hence poses an enormous
fire risk during dry seasons
(Dale et al. 2001; Schoennagel
et al. 2005)
. Variability of precipitation has been shown
to increase ubiquitously with most climate change
prediction scenarios (Smith et al. 2009). While exotic
privet invasions can reduce fire risk by eliminating surface
fuels in some areas, and replacing flammable fuels
(ericaceous species) with a less flammable woody understorey,
the reduction in frequency of low-intensity surface fires
only exacerbates the potential for devastating
highintensity fires as woody plants build up in the
understorey, creating high loads of coarse woody fuels when
shrub canopies dry out and die back during droughts
(Stephens and Ruth 2005; Mandle et al. 2011)
elevated atmospheric CO2 levels have been shown to
increase privet biomass and branching (Smith et al.
2008) potentially creating negative feedbacks that
amplify the thicketization of forest understoreys and magnify
catastrophic crown fire risks during extreme fire weather.
Implications for exotic privet management
Using the output from our model, land owners and forest
managers will be able to more accurately predict
the extent and speed of potential exotic privet invasion
over the next several decades. This will allow them to
better focus their efforts aimed at reducing additional
negative consequences associated with further privet
encroachment. Landowners can apply preventative
management in uninvaded areas that are likely to become
invaded in the future while restoration efforts can be
focussed in areas that are at a high risk for crown fire.
Exotic privets have altered ecosystem function and
suppressed native species regeneration and diversity in
, North Carolina
and Feil 2002)
(Wilcox and Beck 2007)
encroachment has the potential to exacerbate economic
risks associated with timber losses caused by crown fires
as climate change increases variability in precipitation
(Murphy et al. 2014; Enright et al. 2015)
of extreme drought. Exotic privets survive fire by sprouting
from the root crown in response to damage of
aboveground tissue and thus can quickly occupy the
understorey of forest stands (Faulkner et al. 1989). Moreover,
the risks wildfires pose to property and other economic
capital, human health and safety, and a variety of
ecological resources make it imperative that management
action plans be implemented to mitigate the potential
consequences of unimpeded invasion of southern forests
by exotic privets.
There are many options available to effectively manage
exotic privets and even eradicate it from an invaded
area. Cutting and herbicide application has been used
to effectively remove exotic privets
(Wang and Grant
, and although an expensive method of eradication,
this effective management tool might be appropriate
in areas of high crown fire risk, with the costs of the
management offset by the numerous potential economic
losses associated with a wildfire. Additionally, while
single applications of prescribed fire did not decrease
privet abundance in one study
(Caspary and Affolter
, repeated burns have been shown to control privet
encroachment (Huebner 2005). Prescribed fires have
been used effectively and relatively inexpensively to
reduce fuel loads, especially loads of ladder and surface
(Agee and Skinner 2005; Stephens and Ruth 2005)
However, under future climate predictions, increases in
drought frequency could lead to more restrictions on
prescribed burning in the southeastern USA (Mitchell et al.
2014). This could limit the temporal window for privet
management via prescribed fire in this region. Open
burning regulations that allow exemption from burn
bans for certified prescribed burn managers should be
considered for states in the southeastern USA in order to
provide more opportunity for managers to meet invasive
species management goals under an increasingly variable
(Wonkka et al. 2015)
. Of course,
managers need to know where these management strategies
will be most needed and most effective because
management of privet throughout the forestlands of Alabama and
Mississippi is not logistically feasible due to high labour
requirements and other associated costs of control. The
output of our model should be tremendously beneficial
in this regard.
To move beyond reactive control efforts towards more
proactive management of invasive species and
associated crown fire requires prediction of potential ranges
of invasive species on spatial scales relevant to land
owners, forest managers and restoration practitioners.
We drew upon extensive geo-reference data sets on
invasive plants and crown fire records to develop a
model predicting possible range expansion of Chinese
and European privets and associated crown fire
frequency. Our results suggest that the total area invaded
will increase in the forestlands of Mississippi and
Alabama, and the annual frequency of crown fires in these
forestlands will approximately double within the next
two decades. Such time series projections of annual
range expansions and crown fire frequency should
provide land owners, forest managers and restoration
practitioners with an invasion chronology upon which to base
proactive management plans.
Contributions by the Authors
All authors shared in collecting data, constructing the
model and writing.
Conflict of Interest Statement
We would like to thank Dr Brian Oswald (Stephen F. Austin
University) who provided comments on our work at the
Sixth Big Thicket and West Gulf Coastal Plain Science
Conference in Nacogdoches, TX, USA. Moreover, we would like
to thank two anonymous reviewers and Associate Editor,
Dr Jean Burns (Case Western Reserve University) for their
valuable suggestions on earlier drafts of the manuscript.
The manuscript is greatly improved as a result of their
The following additional information is available in the
online version of this article —
Appendix S1. Descriptions, values or units of measure,
and means and ranges or frequencies of landscape
features, forest conditions and management activities and
disturbances evaluated as potential determinants of site
invasion by exotic privets in Alabama and Mississippi.
Appendix S2. Descriptions, values or units of measure,
and means and ranges or frequencies of landscape
features, climatic conditions and forest conditions evaluated
as potential determinants of crown fire frequency on
forested plots in Alabama and Mississippi.
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