Shifting tree species composition of upland oak forests alters leaf litter structure, moisture, and flammability - Jennifer K. McDaniel

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Forest Ecology and Management 482 (2021) 118860 Contents lists available at ScienceDirect Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco Shifting tree species composition of upland oak forests alters leaf litter structure, moisture, and flammability Jennifer K. McDaniel a, *, Heather D. Alexander b, Courtney M. Siegert c, Marcus A. Lashley d a Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30605, United States b School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849-5418, United States c Department of Forestry, Forest and Wildlife Research Center, Mississippi State University, MS 39762, United States d Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 23611, United States A R T I C L E I N F O A B S T R A C T Keywords: In historically open-canopied and fire-dependent upland oak (Quercus spp.) forests of the central and eastern Prescribed fire United States, fire exclusion is contributing to an increase in competing non-oak tree species that are often shade- Mesophication tolerant and fire-sensitive. As these non-oak species encroach and oak abundance declines, forests are becoming Leaf traits denser and will likely become cooler, moister, and less flammable through a hypothesized feedback loop termed Fuel moisture Fire behavior mesophication. To better understand how this gradual shift in forest composition could affect flammability of leaf litter, the primary fuel in these systems, we measured leaf litter traits and moisture dynamics of two pyrophytic oaks and three non-oaks, and implemented experimental burns on plots (~3-m2) with fuel beds comprised of single- and mixed-species leaf litter. Non-oaks produced thinner, smaller leaves with a greater specific leaf area compared to oaks, and had a higher initial fuel moisture content, traits associated with low flammability. Our experimental burns confirmed that non-oak leaf litter flammability was lower than that of oaks and that flammability decreased linearly with increasing non-oak leaf litter contribution to the fuel bed. These species-driven changes in fuelbed flammability may provide a mechanism whereby encroaching non-oak tree species create self-promoting conditions that are less favorable for regeneration of fire-dependent upland oaks. Thus, without other management interventions, our ability to reintroduce fire into these systems as a manage­ ment tool to prevent further compositional shifts and improve oak regeneration will likely decline as non-oak species’ contribution to the fine fuel bed increases. 1. Introduction hereafter referred to as non-oaks, including tulip-poplar (Liriodendron tulipifera L.), sweetgum (Liquidambar styraciflua L.), and others (Han­ Historically, fire-maintained upland oak (Quercus spp.) woodlands berry et al., 2020; Abrams, 1992; Hutchinson et al., 2008). This transi­ and forests were prominent across the central and eastern United States tion in species composition from pyrophytic oaks to non-oak species is since a period of warming and drying began at the end of the last likely a component of a process termed mesophication, whereby non- glaciation (Delcourt and Delcourt, 1997). Recurring fires prevented oaks species promote cooler, moister, less flammable conditions that encroachment from competing species and encouraged growth of in­ are conducive to their own growth and persistence at the expense of termediate shade-tolerant oaks by maintaining open canopies (Abrams, more fire-tolerant species (Nowacki and Abrams, 2008). Although 1992; Stambaugh et al., 2015). Due in part to fire exclusion beginning in shifting forest dynamics are likely a result of multiple interacting factors the early 20th century, however, forests across the region began to including fire exclusion, land use changes, altered herbivore pop­ experience shifting species composition and structure (McEwan et al., ulations, and climate change (McEwan et al., 2011), finer-scale, stand- 2011). Open-canopy woodlands transitioned to closed-canopy forests level drivers likely include changes in fuelbed moisture dynamics and with limited recruitment of oaks yet successful recruitment of shade- flammability (i.e., the ability of a fuel to ignite and burn) that result from tolerant and fire-sensitive species including red maple (Acer rubrum L.) differences in leaf litter traits among species with differing fire toler­ and American beech (Fagus grandifolia Ehrh.) and/or generalists, ances (Alexander and Arthur, 2010; Babl et al., 2020; Kreye et al., 2018; * Corresponding author. E-mail address: [email protected] (J.K. McDaniel). https://doi.org/10.1016/j.foreco.2020.118860 Received 5 October 2020; Received in revised form 7 December 2020; Accepted 8 December 2020 Available online 22 December 2020 0378-1127/© 2020 Elsevier B.V. All rights reserved. J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 Kreye et al., 2013; Nowacki and Abrams, 2008, Varner et al., 2016). Farm (SHF; 34◦ 41′ N, 89◦ 42′ W), located ~ 30 km west of Holly Springs, Understanding species-level differences in leaf litter traits associated Mississippi, USA. The average annual temperature is 15.7 ◦ C and ranges with flammability is crucial in upland oak forests because leaf litter is from 4.0 ◦ C in January to 26.3 ◦ C in July, and the average annual pre­ the primary carrier of fire in these systems (Arthur et al., 2017; Brewer cipitation is 1346 mm y-1 (Arguez et al., 2010). Soils are Ultisols of the and Rogers, 2006). Several leaf litter traits impact flammability, Providence-Ruston, Providence silt loam, and Ruston-Providence com­ including the structural and chemical properties of leaves, moisture plexes and are described as moderately well-drained silty loams and content, and packing or physical arrangement of the fuelbed (Varner sandy loams (Soil Survey Staff, 2019). et al., 2015). Morphological traits of individual leaves, which combine Stands consisted of an oak-dominated overstory (≥20 cm diameter at to form fuelbeds, influence flammability both directly and indirectly. breast height (dbh)) with a total basal area of 21.3 m2 ha− 1 and density For example, larger, curlier leaves burn with greater flame heights and of 210 trees ha− 1. Oaks, including southern red oak (Quercus falcata more consumption than smaller, flatter leaves (Engber and Varner, Michx.; 30%) and post oak (Q. stellata Wangenh.; 25%), comprised most 2012), and time to ignition decreases with increasing specific leaf area of the overstory density with minor contributions of sweetgum (9%), (Grootemaat et al., 2015). Indirectly, leaf traits influence fuel moisture winged elm (Ulmus alata Michx.; 9%), and hickory (Carya spp.; 14%). adsorption and drying. Thin, small, flat leaves are generally associated The midstory (10–20 cm dbh) density was 213 trees ha− 1 and was with more tightly packed fuelbeds (Cornwell et al., 2015; Schwilk and predominately sweetgum (23%), winged elm (20%), and hickory (19%), Caprio, 2011) that gain more moisture and lose moisture more slowly with minor contributions of oaks (7%). Among oaks, southern red oak than aerated, loosely packed fuelbeds made up of large, thick, curly and post oak were the most abundant seedling species (1072 seedlings leaves (Kreye et al., 2013). Moisture content of leaf litter has a large ha− 1 and 2057 seedlings ha− 1, respectively). The most abundant of all impact on flammability and fire behavior due to lowered probability of species in the seedling pool, however, were sweetgum (4674 seedlings ignition and rate of fire spread from increased moisture content (Roth­ ha− 1) and winged elm (4005 seedlings ha− 1). Southern red oak and post ermel, 1972). As bulk density increases, fuel moisture also increases, and oak, in addition to black oak (Q. velutina Lam.) and blackjack oak these moist and compacted fuelbeds have a lower probability of ignition (Q. marilandica Munchh.), historically dominated upland oak forests in (Plucinski and Anderson, 2008). Due to influences on fuel structure and the surrounding area, while species including sweetgum, winged elm, porosity, characteristics of individual leaves including thickness, surface red maple, and blackgum (Nyssa sylvatica Marsh.) were historically ab­ area to volume ratio, and density impact fuelbed moisture adsorption sent or restricted to floodplain sites (Brewer, 2001; Surrette et al., 2008). and retention (Kreye et al., 2013). Differences in leaf traits among The historic fire return interval was approximately 4–6 years (Frost, pyrophytic oaks and less fire-tolerant non-oaks may lead to changes in 1998), but there has been no timber harvesting or fire in stands for at both moisture content and flammability and partially explain shifting least 50 years (B. Bowen, Landowner of SHF, personal communication). fire regimes co-occurring with changes in species composition and structure of upland oak forests. Although prescribed fire is a commonly 2.2. Litter collection used tool to manage upland oak forests, studies throughout the literature report a variety of impacts on oak regeneration and recruitment, both Leaf litter used for leaf measurements, moisture dynamics experi­ positive and negative (Brose et al., 2013), perhaps due to the changes in ments, and experimental burns was collected using a combination of fuel moisture and flammability created by increases in non-oak species. suspended collection nets and hand collection during October 2017- Here, we sought to determine the impacts of increasing non-oak February 2018. We selected the two most abundant oaks (southern species’ dominance in an upland oak forest in north Mississippi, USA, red oak and post oak) and three most abundant non-oak species (winged on flammability by measuring leaf litter traits and examining moisture elm, sweetgum, and hickory) and collected litter of those species that dynamics then implementing experimental burns to confirm differences exhibited no signs of decomposition. Litter was air-dried and stored in in flammability among species. Specific objectives were to 1) examine cardboard boxes until processing. Hickory leaflets, hereafter referred to how varying leaf litter traits known to influence flammability differ as leaves, were collected from all species within the genus found at SHF among non-oaks and upland oaks found in north Mississippi, 2) assess (pignut hickory (C. glabra Mill.), mockernut hickory (C. tomentosa (Poir.) how non-oaks interact with upland oaks to influence fuel moisture dy­ Nutt.), bitternut hickory (C. cordiformis (Wangenh.) K. Koch), and namics in species mixtures of increasing non-oak leaf litter contribution shagbark hickory (C. ovata (Mill.) K. Koch) because of difficulty sepa­ as well as single species fuelbeds, and 3) evaluate differences in burning rating fallen litter to species and similarities in leaf characteristics. We characteristics during dormant season plot-level experimental burns of collected hickory leaflets rather than intact leaves with a rachis attached mixed-species and single-species leaf litter from two upland oaks and because the majority of fallen leaf litter we encountered was only three non-oaks. We tested hypotheses that 1) when compared to non- leaflets. oaks, upland oaks will have morphological traits associated with fire adaptations including thicker, larger, and curlier leaves, 2) increasing 2.3. Leaf litter traits non-oak leaf litter contribution to fuelbeds will lead to higher initial moisture content and slower moisture loss rate than upland oaks, 3) We measured individual leaf litter traits that influence flammability among single-species fuelbeds, leaf litter of non-oak species will have and moisture dynamics on a subsample (n = 50) of collected leaves of dampened flammability compared to that of oak species, and 4) among southern red oak, post oak, winged elm, sweetgum, and hickory. Leaf mixed-species fuelbeds, flammability will decrease with increasing curling was measured as the maximum height of the leaf when laid contribution of non-oak leaf litter. Examining morphological traits and horizontally on a flat surface without flattening and under laboratory, moisture dynamics known to be associated with flammability and con­ air-dried conditions. Leaf perimeter and one-sided surface area were firming differences in flammability of upland oak and non-oak leaf litter determined using a flatbed scanner and threshold-based pixel count in field-based trials will clarify the role of these species in flammability measurement in ImageJ software (Abràmoff et al., 2004). Leaves were that could hinder upland oak regeneration and recruitment in the oven dried at 60 ◦ C for 48 h and weighed to determine the oven-dry eastern and central United States. mass. Specific leaf area (SLA) was calculated as the one-sided surface area of the leaf divided by its oven-dry mass. Leaf volume was calculated 2. Methods as the one-sided surface area multiplied by thickness, and surface area to volume ratio (SA:V) was calculated as the two-sided surface area of the 2.1. Study area leaf divided by volume (Engber and Varner, 2012). The leaf dissection index (LDI), which describes the degree of dissection or lobing of a leaf, Leaf litter was collected from upland hardwood forests at Spirit Hill was calculated as the ratio of perimeter to the square root of area 2 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 (McLellan and Endler, 1998). Higher values represent more incised where E is relative moisture content, mt is moisture content at time t, me leaves while leaves with lower LDI values have less serrations or lobes. is equilibrium moisture content, and mi is initial moisture content. Litter After bisecting the leaf halfway between the leaf base and apex and drying typically exhibits multiple distinct time lags with the most perpendicular to the midvein, we used calipers to measure the leaf moisture loss occurring in the first time lag that corresponds to 63% of thickness near the margin and the midvein and averaged the two values. moisture loss of the most easily evaporable moisture (Nelson and Hiers, All statistical analyses were conducted in R v. 3.5.0 (R Core Team, 2008), so we used piecewise polynomial curve fitting using the function 2018). Leaf traits were compared using a Kruskal-Wallis non-parametric segmented in the package segmented to separate the drying curve into test followed by a Dunn test because data were not normally distributed. two time lags and determine response time, which was calculated as the Because we expected leaf litter traits to be highly correlated, we com­ negative inverse of the slope of the first time lag (Kreye et al., 2013; bined traits into uncorrelated principal components using principal Viney and Catchpole, 1991). component analysis (PCA) and also performed a permutational multi­ We compared single-species initial moisture contents and response variate analysis of variance with 999 permutations (PERMANOVA; times among species with an ANOVA followed by a post-hoc Tukey- Anderson, 2001) using the adonis function in the vegan package to Kramer HSD when significant differences were detected (∝ = 0.05). To understand differences in the centroid locations of each species (Oksa­ understand impacts of increasing non-oak litter proportion in leaf litter nen et al., 2019). Additionally, we analyzed the multivariate homoge­ mixtures, we regressed percent non-oak leaf litter with initial moisture neity of dispersion of each species using the betadisp function in the content and with response time. vegan package to determine if there were significant differences (∝ = 0.05) in the multivariate spread of individual leaves around the centroid 2.5. Experimental burns location of each species and a Tukey-Kramer HSD test to test for pairwise differences in dispersion among species. To determine the effects of increasing non-oak leaf litter contribution on flammability, we implemented two series of plot-level experimental burns at SHF. In 2018, we conducted mixed-species burns of four 2.4. Leaf litter moisture dynamics treatments with five replicates of different leaf litter combinations with increasing contributions from non-oak leaf litter (0%, 33%, 66%, and To examine moisture dynamics of leaf litter, we constructed single- 100% non-oak litter; Table 1). Prior to plot establishment, the per- species and mixed-species litterbeds from collected litter, soaked the square meter annual litterfall was estimated using 15 approximately 2 litterbeds, and weighed them throughout drying until a constant mass × 2-m leaf litter nets installed approximately 1.5 m above the forest was reached using methods described in Kreye et al. (2018; 2013). For floor in October 2017. Leaf litter in each net was collected monthly single-species litter, we constructed 15 g litterbeds (n = 4) from leaf during leaf fall, weighed, and returned to the lab. A subsample was litter of southern red oak, post oak, winged elm, sweetgum, and hickory. collected in the field from each net and weighed before and after drying For mixed-species litter, we constructed 15 g litterbeds (n = 5) of four at 60 ◦ C for 48 h to obtain an air-dry to oven-dry conversion factor. We treatments of mixed oak litter with increasing contribution from non- then calculated the estimated litterfall (234 g m− 2 oven-dry mass) as the oak leaf litter (0%, 33%, 66%, and 100% non-oak litter; Table 1). converted oven-dry mass of the litter in each net divided by the area of Within mixed-species treatments, individual species proportions were each net. Plots were installed in a representative upland hardwood stand based on the combined midstory and overstory density of each species, at SHF in mid-February 2018 and located in areas with little to no un­ with the 33% non-oak mixture representing the current stand condition. derstory vegetation to reduce effects of understory fuels on flamma­ Litterbeds were oven dried at 60 ◦ C for 48 h to determine the oven-dry bility; any existing vegetation was clipped and removed. The existing Oi weight and then allowed to equilibrate under laboratory conditions. horizon was removed using leaf blowers, and 937 g of collected litter Next, litterbeds were soaked in water for 24 h, removed, and placed in was added to each 1.75 × 1.75-m plot (Fig. 1A). Leaf litter treatments elevated metal pans with drainage holes. We weighed litter after soaking were randomly assigned to plots to prevent bias due to any slope or to determine initial moisture content, then litter was allowed to dry microsite variation. Plots were stabilized using 35.5 cm tall wire mesh under laboratory conditions (21.1 ± 0.4 ◦ C, 46.2 ± 0.4% relative hu­ around edges to minimize loss of litter due to wind and prevent any midity) for approximately 48 h or until equilibrium moisture content additional litter inputs. Additionally, we installed a 0.5-m firebreak was reached (Kreye et al., 2013). Assuming a negative exponential around each burn plot using a leaf blower. desorption response (Kreye et al., 2013), litterbeds were weighed more Mixed species plots were ignited on 9 March 2018 between 1300 and often during early stages of drying than later stages (i.e., every 30 min 1530 under stable weather conditions (wind speed 1.8 ± 0.1 m s− 1; air for the first 4 h, hourly for 5–12 h, every 4 h during 13–16 h, etc.). temperature 20.0 ± 0.2 ◦ C; relative humidity 23.8 ± 0.6%). Prior to We calculated the fuel moisture content for each fuelbed at each ignition, we removed a grab sample of leaf litter to determine fuel drying time using the following equation: (Equation 1) mt = (masst - moisture content using Equation 1. We measured litter depth in the massod)/(massod), where mt is the moisture content at time t, masst is the center of each quadrant of each plot, and depths were converted to bulk litter mass at time t, and massod is the oven-dry mass of the litter. Fuel density by dividing the total mass of leaf litter added to the plot by the moisture content was then converted to relative moisture content volume the litter occupied (depth multiplied by plot area). Air temper­ (Fosberg, 1970) using the following equation: E = (mt-me) / (mi-me), ature, relative humidity, and wind speed were recorded using a pocket weather meter (Kestrel® 5500 Fire Weather Pro, Kestrel Meters, Boot­ Table 1 hwyn, PA) prior to ignition of each plot. Proportion of leaf litter by species used in mixed-species moisture dynamics and Each plot was ignited individually with a head fire using a drip torch flammability experiments. Leaf litter was collected at Spirit Hill Farm, MS, USA. (3:1 diesel:gasoline) along a single edge. One plot with 33% non-oak leaf 1 Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and litter was ignited first and with a backing fire that did not spread; this shagbark hickory. plot was excluded from further analyses because other plots were suc­ Non-oak Oaks Non-oaks cessfully ignited with a head fire. We measured several flammability litter Southern red Post Winged Sweetgum Hickory1 metrics including percent area burned, temperature, flame height, rate (%) oak oak elm of spread, and flaming duration. We visually estimated percent area 0 0.50 0.50 0.00 0.00 0.00 burned as a proxy for percent consumption, as we anticipated utilizing 33 0.33 0.33 0.11 0.11 0.11 burned plots for future studies and avoided disturbing remaining litter 66 0.17 0.17 0.22 0.22 0.22 post-burn. The pyrometer-indicated fire temperature, hereafter referred 100 0.00 0.00 0.33 0.33 0.33 to as temperature, was measured using pyrometers that were installed 3 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 timing the fire spread from the ignition edge to the center of the plot and opposite edge of the plot and dividing each distance by the measured time. The flaming duration was measured as the total amount of time from the initial ignition to extinction of a visible flame. In 2019, we implemented single-species burns of leaf litter of each of the two oaks and three non-oak species using the same experimental design used for mixed-species but with different sample sizes among species due to varying amounts of litter collected (post oak: 5; southern red oak: 5; hickory: 3; sweetgum: 4; winged elm: 3). Plots were ignited on 22 March 2019 between 1530 and 1630 (wind speed 1.0 ± 0.2 m s− 1; air temperature 22.5 ± 0.4 ◦ C; relative humidity 22.1 ± 1.0%) and on 27 March 2019 between 1100 and 1400 (wind speed 0.7 ± 0.0 m s− 1; air temperature 20.1 ± 0.5 ◦ C; relative humidity 23.5 ± 1.0%). For mixed species-plots, we first used linear regression to analyze the relationship between each flammability metric and percent non-oak leaf litter. For both mixed-species and single-species plots, we expected flammability metrics to be highly correlated (Engber and Varner, 2012; Varner et al., 2015) and confirmed this using correlation analysis. To understand patterns in overall flammability and to avoid issues with multicollinearity, PCA was performed using centered, scaled, and log- transformed values for temperature, flame height, percent area burned, and rate of spread. Data used for PCA were log-transformed to stabilize variance of each variable. After performing PCA, principal components with eigenvalues greater than one were retained, and each burn replicate’s Principal Component 1 score was used as a measure of overall flammability for mixed-species burns. We then used linear regression to evaluate the impact of percent non-oak leaf litter on the flammability-related Principal Component 1 score. For single-species burns, we used a PERMANOVA to understand multivariate differences among species. 3. Results 3.1. Leaf litter traits Leaf litter traits varied among the five species, with oaks generally having thicker, larger leaves than non-oaks. Post oak and southern red oak leaves were the thickest and had the lowest SLA compared to other species (P < 0.0001; Table 2). The leaf surface area of post oak was ~ 5.3 times the surface area of winged elm, which had the smallest leaves (P < 0.0001). There was less distinction among species with regards to curl, but winged elm had significantly flatter leaves than all other species (P < 0.0001). Combining measured leaf morphological characteristics using a PCA (Fig. 2) resulted in three principal components each with eigenvalues > 1 and was confirmed by a Bartlett test of sphericity (3548; P < 0.001) and a Kaiser-Meyer-Olkin (KMO) measure of sampling ade­ quacy (overall MSA = 0.63). The three principal components explained a cumulative variance of 86.8%. Principal Component 1 loaded strongly on mass (0.42), volume (0.41), and perimeter (0.37; Table 3). Principal Component 2 loaded strongly on SA:V (0.52), thickness (-0.44), and LDI Fig. 1. Leaf litter flammability experimental burn plots at Spirit Hill Farm, MS, (0.34), and Principal Component 3 loaded strongly on curl (0.50), area USA (A) prior to burning, (B) during burning, and (C, D, E, and F) post-burn (-0.41), and LDI (0.38; Table 3). The PERMANOVA indicated that the with 0%, 33%, 66%, and 100% non-oak leaf litter, respectively. species significantly differed in measured leaf traits (F = 67.9; P = 0.001), and the multivariate analysis of homogeneity of variance pre-burn and removed immediately following all burns. Four pyrome­ revealed significant differences in the spread around the centroid of each ters were installed in each plot in four quadrants and were attached to species (F = 32.2; P < 0.0001). A post-hoc Tukey-Kramer HSD revealed pin flags directly on top of the litter layer. Pyrometers were constructed that all pairwise comparisons were significantly different in dispersion using aluminum tags painted with six Tempilaq® fire-sensitive paints (P < 0.001) except southern red oak and post oak (P = 0.83), winged elm ranging from 79 ◦ C to 510 ◦ C (Tempil, South Plainfield, NJ) and covered and southern red oak (P = 0.80), and winged elm and post oak (P = with aluminum foil (Loucks et al., 2008). Maximum temperature was 0.99). recorded for each pyrometer as the highest temperature indicated, and ambient temperature (20◦ C) was used if the pyrometer showed no 3.2. Leaf litter moisture dynamics melted paint. The mean maximum temperature for each plot was calculated as the average of the four pyrometer temperatures. Flame Among single species litterbeds, oaks gained less moisture initially height to the nearest 10 cm was visually estimated every 30 sec using a than non-oaks and lost moisture more quickly (Fig. 3A). Winged elm and marked pole adjacent to the plot. Rate of spread was determined by hickory initial moisture contents (449.5% and 428.5%, respectively) 4 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 significantly different by a Kruskal-Wallis test followed by a Dunn test (∝ = 0.05). SLA, specific leaf area; LDI, leaf dissection index; SA:V, surface area to volume ratio, χ 2, Kruskal-Wallis H-value, d.f., degrees of freedom. Morphological trait values and principal component (PC) scores (mean (± standard error)) measured on individual leaves (n = 50) collected from Spirit Hill Farm, MS. Values followed by a common letter are not 1.22 (0.10) 0.20 (0.17) − 0.79 − 0.21 − 0.42 (0.16) (0.16) (0.07) PC3 0.17 (0.10) 1.79 (0.20) − 0.35 − 0.92 − 0.69 (0.13) (0.16) (0.08) PC2 2.51 (0.18) 1.45 (0.15) − 0.97 − 0.53 − 2.46 (0.14) (0.29) (0.08) PC1 Fig. 2. Principal component analysis (PCA) biplot of morphological traits 76.2 (2.24)b 80.4 (2.24)b measured on leaf litter collected at Spirit Hill Farm, MS, USA. Points indicate <0.0001 individual leaves measured, and the length of the vector arrow represent the (9.56)a (3.18)a (4.39)c 130, 4 102.9 163.7 123.5 SA:V strength of each trait’s correlation with principal components. LDI, leaf dissection index; SLA, specific leaf area; SA:V, surface area to volume ratio. Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and 2.2 (0.1)b <0.0001 shagbark hickory. (0.1)bd (0.2)ad (0.2)a (0.1)c 97, 4 (cm) Curl 2.2 3.3 2.9 1.3 Table 3 0.42 (0.01)ac 0.31 (0.01)d 0.37 (0.01)b c Eigenvectors from principal component (PC) analysis of leaf traits measured on 0.48 (0.03) (0.009)ab (g cm− 3) <0.0001 leaves collected from upland hardwood stands at Spirit Hill Farm, MS, USA. LDI, density Tissue 84, 4 leaf dissection index; SLA, specific leaf area; SA:V, surface area to volume ratio. 0.40 Variable PC 1 PC 2 PC 3 Surface area 0.35 0.24 − 0.41 <0.0001 Perimeter 0.37 0.37 − 0.12 (0.23)b (0.19)a (0.15)a (0.08)c (0.07)c 200, 4 8.25 11.5 5.84 9.27 6.62 Thickness 0.33 − 0.44 0.14 LDI Volume 0.41 0.01 − 0.33 Mass 0.42 0.08 − 0.24 144.63 (6.58)b 100.68 (2.13)a 201.13 (7.27)c SLA − 0.35 0.30 − 0.30 91.97 (2.23)a LDI 0.23 0.34 0.38 (cm2 g− 1) (12.23)bc <0.0001 Density 0.11 0.26 0.37 183.98 130, 4 Curl 0.13 0.26 0.50 SLA SA:V − 0.29 0.52 − 0.14 Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and shagbark hickory. % variance explained 48.4 18.9 14.1 0.35 (0.02)b 0.68 (0.03)a 0.20 (0.02)c <0.0001 (0.004)d (0.03)bc were ~ 1.5-fold higher than southern red oak and post oak initial 170, 4 Mass 0.29 0.06 (g) moisture contents (283.3% and 288.8%, respectively; P < 0.0001; Table 4). As expected, litter mixtures that contained more non-oak leaf litter gained more moisture initially relative to mixtures that contained 0.2 (0.01)d 0.6 (0.01)c c 0.6 (0.01) 0.9 (0.1)b 1.7 (0.1)a <0.0001 primarily oak litter (Fig. 3B). Litter mixtures containing 100% non-oak Volume 160, 4 (cm3) litter had an average initial moisture content that was ~ 1.6x that of litter mixtures containing 0% non-oak litter (Table 4). Initial moisture content exhibited a strong positive linear relationship with percent non- oak leaf litter (R2 = 0.92; P < 0.0001; Fig. 4), but response time was not 0.21 (0.01)b 0.27 (0.01)a 0.26 (0.01)a c 0.17 (0.01)c 0.15 (0.01) Thickness influenced by percent non-oak litter (R2 = 0.01; P = 0.29). <0.0001 130, 4 (mm) 3.3. Leaf litter flammability Perimeter For mixed-species burns, all individual flammability metrics except <0.0001 170, 4 total flaming duration exhibited negative linear relationships with (1.6)b (0.7)b (2.0)a (2.3)a (2.8)a (cm) 63.8 66.9 29.3 57.7 22.3 percent non-oak leaf litter, as plots with increasing percent non-oak litter burned with a slower rate of spread, shorter flames, lower tem­ perature, and less area burned (Fig. 1). Rate of spread (R2 = 0.67; P < Surface area 34.3 (1.5)bc 0.001; Fig. 5A) and flame height (R2 = 0.71; P < 0.001; Fig. 5B) were 11.8 (0.7)d 29.0 (3.4)b 62.5 (3.3)a c 40.0 (3.0) <0.0001 most strongly correlated with percent non-oak leaf litter and decreased 140, 4 (cm2) as percent non-oak leaf litter increased. Area burned (R2 = 0.43; P = 0.001; Fig. 5C) and temperature (R2 = 0.56; P < 0.001, Fig. 5D) were less strongly but significantly correlated with percent non-oak leaf litter Southern red and also decreased as percent non-oak leaf litter increased. Bulk density Winged elm Sweetgum Hickory1 and moisture content were not strongly correlated with percent non-oak Post oak P value Species Table 2 χ2, d.f. oak leaf litter (Table 5). Rate of spread, flame height, area burned, and temperature were 1 5 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 Fig. 3. Drying curves of (A) single-species litter and (B) mixtures of increasing proportion of non-oak litter relative to oak litter collected at Spirit Hill Farm, MS, and soaked for 24 h and dried for 48 h under laboratory conditions. Points indicate means and error bars represent standard error. Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and shagbark hickory. Table 4 Initial moisture content and response time (mean (± standard error)) measured during litter soaking and drying experiment of single and mixed species leaf litter collected at Spirit Hill Farm, MS from fall 2017 to winter 2018. Values sharing a common letter are not significantly different. (∝ = 0.05). Litter type Initial moisture content (%) Response time (h)1 Single species Southern red oak 283.3 (0.6)a 4.1 (0.9) Post oak 288.8 (3.7)a 4.6 (1.7) Sweetgum 393.8 (10.9)b 7.6 (0.6) Hickory2 428.5 (5.0)c 5.0 (2.0) Winged elm 449.5 (4.1)c 6.6 (2.9) P value < 0.0001 0.40 Litter mixture (% non-oak litter) 0 266.2 (7.9) 9.3 (0.4) 33 319.8 (6.2) 8.1 (0.6) 66 374.9 (6.1) 6.1 (0.8) 100 421.9 (11.5) 12.0 (1.0) P value < 0.0001 0.21 R2 0.92 0.03 1 Response time measured as the time necessary for litter to lose 63% of moisture and transition from the first drying time lag to the second time lag as determined by piecewise polynomial curve fitting. 2 Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and Fig. 4. Relationship of percent non-oak leaf litter and initial moisture content shagbark hickory. measured during leaf litter soaking and drying experiment of mixed oak and non-oak leaf litter collected at Spirit Hill Farm, MS. strongly correlated, which justified conducting a PCA for mixed-species burns. Flaming time was weakly correlated with other variables (i.e. rate Flammability metrics for single-species burns were also strongly of spread, r = -0.19; temperature, r = 0.04) and was excluded from the correlated, and temperature and percent area burned most strongly PCA because variance explained was maximized without flaming time. correlated (r = 0.85). A PCA of temperature, rate of spread, percent area Temperature and flame height (r = 0.81) and temperature and percent burned, and flame height resulted in two principal components (Bartlett area burned (r = 0.81) were the most strongly correlated. Combining test = 34.05; Overall MSA = 0.70). Principal Component 1 and Principal temperature, rate of spread, percent area burned, and flame height using Component 2 explained 76.8% and 14.3% of the variation in the dataset, a PCA resulted in two principal components and was confirmed by the respectively (Table 6, Fig. 6B). Principal Component 1 loaded strongly Bartlett test (48.05, P < 0.001) and the KMO index (Overall MSA = on percent area burned (r = 0.55) and temperature (r = 0.54), and 0.84). Principal Component 1 and Principal Component 2 of the PCA Principal Component 2 loaded strongly on rate of spread (r = 0.73) and explained 87.9% and 6.0% of the variation in the dataset, respectively flame height (r = -0.68; Table 6). A PERMANOVA revealed significant (Table 6, Fig. 6A). More flammable, oak-dominated mixtures had differences in flammability metrics among species (F = 5.21; P = 0.009), higher, more positive Principal Component 1 scores while less flam­ but it should be noted that we lacked a large sample size for some species mable, non-oak dominated mixtures had lower, more negative Principal (e.g., winged elm, n = 3). Bulk density varied significantly among spe­ Component 1 scores (Fig. 6A). A regression of Principal Component 1 cies;winged elm had a bulk density ~ 1.8x that of southern red oak and percent fire-sensitive non-oak leaf litter revealed a significant (Table 5). Fuel moisture content did not vary significantly among relationship between flammability and non-oak litter contribution to the species. fuelbed (R2 = 0.58, P < 0.001, Fig. 7). 6 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 Fig. 5. Relationship of percent non-oak leaf litter and (A) rate of spread (ROS), (B) flame height, (C) percent area burned, (D) temperature measured during plot-level experimental burns of mixtures of increasing proportion of non-oak litter relative to oak-litter at Spirit Hill Farm. 4. Discussion ignition probability due to higher initial fuel moisture after the addition of water. We expected to find slower moisture loss rate with increasing Our study demonstrates that leaf litter traits, moisture dynamics, and percent non-oak leaf litter, but we instead found no clear trend. This flammability differed between upland oak and non-oak species and that could be due to additive effects that have been documented in litter flammability decreased as non-oak leaf litter contribution to the fuelbed flammability (Varner et al., 2017; Zhao et al., 2019, 2016), with the increased. When compared to the three non-oaks (winged elm, hickory, most flammable species controlling the flammability of mixtures (de and sweetgum), the two upland oaks (southern red oak and post oak) Magalhães and Schwilk, 2012). Drying rates of mixed litter types could had larger, thicker leaves with a lower SA:V and lower SLA, which is potentially behave similarly, where the species with the quickest consistent with other studies’ findings that fire-tolerant species exhibit response time controls the response time for the mixture through traits associated with higher flammability than fire-sensitive species increased fuelbed depth and decreased bulk density created by curlier, (Engber and Varner, 2012; Grootemaat et al., 2017; Kreye et al., 2013). larger leaves. For example, our 33% and 66% non-oak fuelbed response The three non-oaks exhibited greater moisture gain and a slower drying times were most similar to the response time of 0% non-oak litter, which rate than the two oaks, and mixed species litterbeds with increasing non- could indicate the oak litter in the mixed fuelbeds is at least partially oak proportion exhibited increased initial moisture content as expected controlling litter drying. Additive versus non-additive effects of litter given the behavior of single species litterbeds. This indicates that the drying deserve future work to fully understand the controls of individual addition of non-oak litter could dampen flammability and decrease species on drying of litter mixtures. 7 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 Table 5 experiments, which may be due to interactions between litter types. Mean values (± standard error) of fuelbed characteristics of experimental burns For example, the bulk density of 0% non-oak litter was lower than that of of single-species and litter mixtures of non-oak and oak litter conducted at Spirit either of the constituent oak species, and the bulk density of 100% non- Hill Farm, MS. For litter mixtures, P-values and R2 are for regressions of bulk oak litter was lower than that of the constituent non-oak species, density and % non-oak litter and fuel moisture content and % non-oak litter. For although we do not make direct comparisons between single-species and single-species, P-values are for an ANOVA to test for differences in bulk density mixed-species experiments. Fuel moisture content did not exhibit a clear and fuel moisture content among species. Values followed by a common letter trend in mixed-species flammability experiments or in single-species are not significantly different by an ANOVA followed by a post-hoc Tukey- Kramer HSD. flammability experiments, potentially because litter drying had not progressed enough to produce distinct differences. Fuel moisture con­ Litter type Bulk density (kg Fuel moisture content tent was not included as a covariate in the analyses presented here, as it m− 3) (%) did not explain any further variability in the flammability data. Litter mixture (% non-oak Nowacki and Abrams (2008) referred to mesophytes as fire-sensitive, litter) 0 6.08 (0.58) 8.18 (1.66) shade-tolerant species that create cooler, moister, less flammable forest 33 7.36 (1.00) 12.5 (6.22) conditions, with red maple, sugar maple (Acer saccharum Marsh.), and 66 7.12 (0.71) 7.61 (3.76) other later successional species as the main species of concern. Given our 100 8.51 (1.15) 16.6 (5.96) results, however, we propose that other non-oaks including those stud­ P value 0.07 0.31 ied here may also alter stand conditions and serve as fire-modifiers by R2 0.13 0.01 opportunistically invading stands and altering flammability. We use the Single species term “fire-modifier” to suggest that these species are altering fire re­ Southern red oak 7.60 (0.14)a 7.27 (0.87) gimes to a degree more than initially thought and perhaps enabling strict Post oak 9.11 (1.02)ab 5.51 (0.51) mesophytes to invade stands. Although not strictly fire-intolerant, Sweetgum 11.83 (0.69)bc 6.87 (0.66) sweetgum is increasing in many upland oak forests in the eastern U.S., Hickory1 8.74 (0.59)ab 5.64 (1.78) Winged elm 13.65 (0.76)c 8.05 (0.60) particularly in the southeastern U.S. (Surrette et al., 2008), likely due to fire exclusion and land use changes (Brewer, 2001). We expected P value 0.0003 0.28 sweetgum leaf traits to be most similar to hickory and winged elm 1 Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and because of its ability to persist in fire-excluded forests and potentially shagbark hickory. alter stand conditions, but curl, LDI, and perimeter were similar to oaks. Sweetgum did have significantly different spatial dispersion around the centroid as determined by a multivariate analysis of homogeneity of Table 6 variance, which indicates variability in characteristics. This is poten­ Eigenvectors from principal component (PC) analysis of flammability metrics tially due to differences in slope position or habitat that resulted in measured during mixed-species and single-species leaf litter plot-level burns at Spirit Hill Farm, MS. variation in leaf thickness or size. Hickory, although typically considered a pyrophyte that is strongly Variable Mixed-species litter Single-species litter associated with upland oak forests (Fralish, 2004; Kreye et al., 2013), PC1 PC2 PC1 PC2 was included as a non-oak in this study. Hickory is one of the most Rate of spread 0.49 − 0.58 0.45 0.73 common midstory trees at SHF, along with winged elm and sweetgum, Flame height 0.49 0.71 0.46 − 0.68 and is potentially contributing to the “oak bottleneck” (Nowacki and Percent area burned 0.51 − 0.33 0.55 0.06 Abrams 1992). In north Mississippi, mockernut hickory has demon­ Temperature 0.51 0.21 0.54 − 0.10 strated increased survival and decreased mortality compared to preset­ % variance explained 87.9 6.0 76.8 14.3 tlement conditions and may replace oaks following overstory mortality (Brewer, 2015). Leaf trait and moisture dynamics results indicate that In mixed-species flammability experiments, as expected, rate of hickory is intermediate in leaf traits that may alter fire dynamics, as its spread, percent area burned, flame height, and temperature decreased thickness, curl, and mass are between those of oaks and non-oak species, with increasing percent non-oak leaf litter. Total flaming time did not similar to the findings of Babl et al. (2020). Hickories also have canopy have a significant relationship with percent non-oak leaf litter, likely hydrological characteristics more like other non-oaks than oaks and because plots with non-oak-dominated fuels either burned very slowly influence soil moisture similarly to other non-oaks, suggesting hickories or extinguished soon after ignition and had low fuel consumption. Re­ have intermediate mesophytic properties (Siegert et al., 2020). In our lationships between other flammability metrics and non-oak leaf litter study, the initial moisture content and response time of hickory are in­ contribution were as expected. Combining individual flammability termediate to oaks and other fire-sensitive species, however the flam­ metrics resulted in an overall flammability score that decreased with mability of hickory as revealed in our single-species experiments was increasing percent non-oak leaf litter. This is consistent with the findings similar to that of post oak and southern red oak. The leaf litter used in of Kreye et al. (2018), who examined laboratory flammability of mix­ our experiments was collected from several hickory species, including tures of similar species found in northern Mississippi and found that mockernut hickory, pignut hickory, shagbark hickory, and bitternut flammability metrics decreased as the contribution of sweetgum, winged hickory. Our results may have varied if we selected litter from only one elm, and dogwood (Cornus florida L.) litter increased; this trend was species for experiments; for example, mockernut hickory leaves are strongest when litter was moist. For our single-species flammability generally larger than pignut hickory leaves (White, 2008) and may have experiment, there were significant differences in overall flammability as greater inherent flammability. We also collected leaflets of hickory, as indicated by a PERMANOVA. Two potential mechanisms of such most fallen hickory leaf litter was already detached from the rachis. If we dampened flammability include increased moisture content and differ­ had collected only intact hickory leaves, constructed fuelbeds would ences in leaf characteristics, which we demonstrated here, that lead to have likely been more aerated with a lower bulk density and potentially increased bulk density (Kreye et al., 2013; Varner et al., 2015). Bulk be more flammable (Plucinski and Anderson, 2008). Nevertheless, some density trended higher as the percent non-oak litter increased in mixed- uncertainty remains surrounding the role of hickory in compositional species flammability experiments, potentially driven by winged elm’s shifts in upland oak forests, with perhaps important species-specific increased bulk density relative to oak as found in single-species flam­ differences. mability experiments. Interestingly, bulk density was generally lower in Mesophication is likely occurring in upland oak forests across the mixed-species flammability experiments compared to single-species central and eastern U.S., yet relatively little is known about drivers of 8 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 Fig. 6. Principal component analysis (PCA) biplot of flammability metrics measured during plot-level experimental burns of (A) mixtures of increasing proportion of non-oak litter relative to oak litter and (B) single-species litter at Spirit Hill Farm, MS. Points indicate individual plots burned, and vector arrows represent flam­ mability traits used when conducting the PCA. Hickory includes pignut hickory, mockernut hickory, bitternut hickory, and shagbark hickory. these dynamics outside the Central Hardwood Region where extensive 5. Conclusions research has been conducted (Alexander and Arthur, 2014, 2009; Brose and Lear, 1999; Green et al., 2010). The three non-oaks examined here, In this study, we manipulated leaf litter composition based on sweetgum, hickory, and winged elm, are potentially analogous to red overstory and midstory tree species composition at SHF and examined maple, blackgum, and other species in the southern Appalachians that leaf litter characteristics, moisture dynamics with laboratory experi­ are increasing in dominance and competing with oaks (Fei and Steiner, ments, and flammability with small, field-based experiments. Leaf traits, 2007; Knott et al., 2018). initial fuel moisture content, and flammability varied among two com­ mon upland oaks and three non-oaks. In mixed-species experiments, initial moisture content was positively related and overall flammability negatively related to proportion of non-oak leaf litter. Mesophication is 9 J.K. McDaniel et al. Forest Ecology and Management 482 (2021) 118860 analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing - original draft. Heather D. Alex­ ander: Conceptualization, Data curation, Funding acquisition, Investi­ gation, Methodology, Project administration, Resources, Supervision, Validation, Writing - review & editing. Courtney M. Siegert: Concep­ tualization, Data curation, Investigation, Methodology, Writing - review & editing. Marcus A. Lashley: Conceptualization, Data curation, Investigation, Methodology, Writing - review & editing. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements We thank Bob and Sheryl Bowen of Spirit Hill Farm for access to field sites and several individuals who assisted with fieldwork: Natasha Drotar, Will Kruckeberg, Rachel Arney, Moriah Boggess, and others. This research is a contribution of the Forest and Wildlife Research Center, Mississippi State University and was funded by the National Institute of Food and Agriculture, USDA McIntire-Stennis grant #MISZ- Fig. 7. Relationship of percent non-oak leaf litter and Principal Component 069450. (PC) 1 composed of combined flammability metrics (rate of spread, percent area burned, flame height, and temperature) measured during plot-level experi­ References mental burns of mixed oak and non-oak leaf litter at Spirit Hill Farm, MS. Abràmoff, M.D., Magalhães, P.J., Ram, S.J., 2004. Image processing with imageJ. Biophotonics Int. 11, 36–41. hypothesized to create cooler, moister, more humid forests, and results Abrams, M.D., 1992. 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