Individual Pine Research Articles

Pine trees structure plant biodiversity patterns in savannas.

Overstory trees serve multiple functions in grassy savannas. Past research has shown that understory species can vary along gradients of canopy cover and basal area in savannas. This variation is frequently associated with light availability but could also be related to other mechanisms, such as heterogeneity in soil and litter depth and fire intensity. Several savanna studies have found differences in understory plant functional groups within the local environment near trees versus away from them in canopy openings. Although small-scale variation is known to be high in southeastern U.S. pine savannas, patterns in understory species diversity have not been examined at the scale of individual overstory pine trees in this system. We conducted an observational study of the relationship between understory plant communities and proximity to individual pine trees in xeric and mesic pine savannas in frequently burned sites (1-3 year intervals). We recorded the plant community composition in plots adjacent to tree boles (basal) or outside crown driplines (open). Within each environment, raw species richness was significantly greater in open locations, where light transmittance was greater. In contrast, rarified species richness did not differ. Multivariate analyses showed that community composition differed significantly between basal and open plots. One native, woody species in each environment, Serenoa repens (W. Bartram) Small in mesic and Diospyros virginiana L. in xeric, was more abundant in basal plots. In mesic environments, eight species had greater occurrence in open plots. In xeric environments, four understory forbs were more abundant in open plots. Our results support previous research indicating that individual pine trees are associated with significant variation in understory vegetation in pine savannas.

Diverging growth trends and climate sensitivities of individual pine trees after the 1976 extreme drought

Summer droughts are affecting the productivity and functioning of central European forests, with potentially lasting consequences for species composition and carbon sequestration. Long-term recovery rates and individual growth responses that may diverge from species-specific and population-wide behaviour are, however, poorly understood. Here, we present 2052 pine (Pinus sylvestris) ring width series from 19 forest sites in south-west Germany to investigate growth responses of individual trees to the exceptionally hot and dry summer of 1976. This outstanding drought event presents a distinctive test case to examine long-term post-drought recovery dynamics. We have proposed a new classification approach to identify a distinct sub-population of trees, referred to as “temporarily affected trees”, with a prevalence ranging from 9 to 33 % across the forest stands. These trees exhibited an exceptionally prolonged growth suppression, lasting over a decade, indicating significantly lower resilience to the 1976 drought and a 50 % reduced capacity to recover to pre-drought states. Furthermore, shifts in resilience and recovery dynamics are accompanied by changing climate sensitivities, notably an increased response to maximum temperatures and summer droughts in post-1976 affected pines. Our findings underscore the likely interplay between individual factors and micro-site conditions that contribute to divergent tree responses to droughts. Assessing these factors at the individual tree level is recommended to advancing our understanding of forest responses to extreme drought events. By analyzing sub-population growth patterns, our study provides valuable insights into the impacts of summer droughts on central European forests in context of increasing drought events.

Aerial Image Segmentation of Nematode-Affected Pine Trees with U-Net Convolutional Neural Network

Pine wood nematode disease, commonly referred to as pine wilt, poses a grave threat to forest health, leading to profound ecological and economic impacts. Originating from the pine wood nematode, this disease not only causes the demise of pine trees but also casts a long shadow over the entire forest ecosystem. The accurate identification of infected trees stands as a pivotal initial step in developing effective prevention and control measures for pine wilt. Nevertheless, existing identification methods face challenges in precisely determining the disease status of individual pine trees, impeding early detection and efficient intervention. In this study, we leverage the capabilities of unmanned aerial vehicle (UAV) remote sensing technology and integrate the VGG classical small convolutional kernel network with U-Net to detect diseased pine trees. This cutting-edge approach captures the spatial and characteristic intricacies of infected trees, converting them into high-dimensional features through multiple convolutions within the VGG network. This method significantly reduces the parameter count while enhancing the sensing range. The results obtained from our validation set are remarkably promising, achieving a Mean Intersection over Union (MIoU) of 81.62%, a Mean Pixel Accuracy (MPA) of 85.13%, an Accuracy of 99.13%, and an F1 Score of 88.50%. These figures surpass those obtained using other methods such as ResNet50 and DeepLab v3+. The methodology presented in this research facilitates rapid and accurate monitoring of pine trees infected with nematodes, offering invaluable technical assistance in the prevention and management of pine wilt disease.

Virulence of Dothistroma septosporum and D. pini on Pinus nigra and P. mugo under conditions of natural infection

AbstractDothistroma needle blight (DNB) is a severe needle disease of pines worldwide, caused by two closely related species, Dothistroma septosporum and D. pini. The two fungal species are similar not only in their morphological characteristics, but also cause very similar symptoms in their hosts, and have a similar ecology. The aim of this study was to compare the virulence of the two Dothistroma species in natural infection experiments on 2-year-old seedlings of two DNB susceptible pine species, Pinus nigra and P. mugo, in two seedling stands for each pathogen species. The virulence of the pathogens and presence of symptoms (symptomatic needles, red bands and acervuli) were assessed after 2 years of exposure to inoculum. The incidence of seedlings with DNB symptoms was 65% and 76% for P. nigra and P. mugo, respectively. No difference was found between D. septosporum and D. pini in any of the three DNB symptoms evaluated on seedlings of P. mugo. However, symptoms of disease differed between the two Dothistroma species on P. nigra. Variables that reflect the intensity of disease development, the number of red bands and acervuli per needle, showed a difference in virulence between D. septosporum and D. pini, but only in the case of the host species P. nigra. The results suggest that the virulence of the two Dothistroma species could be affected by host pine species and that there are differences in the susceptibility of individual pine species to D. septosporum and D. pini. Further factors could affect the virulence of these pathogens, including isolate origin, climatic or environmental factors.

Measurement of individual pine trees using 3D point cloud around Yasu region

Measurement of individual pine trees using 3D point cloud around Yasu region

Onset of Action of Selected Second-Generation Antipsychotics (Pines)-A Systematic Review and Meta-Analyses.

Recommendations for duration of treatment with antipsychotics before considering a switch vary from 2 to 8 weeks, although several studies suggest a rapid onset of action. The objective of this review was to estimate time to onset of action and time to maximum antipsychotic effect of asenapine, olanzapine, quetiapine, and zotepine (pines). We searched bibliographic databases for randomized, placebo-controlled trials in adults with schizophrenia estimating the antipsychotic effect of pines over time. Thirty-five studies including 6331 patients diagnosed with chronic schizophrenia were included. We estimated the standardized mean differences (SMD) of changes in symptom score from baseline to follow-up between intervention and placebo groups across studies using meta-analysis techniques. The summarized effect across all included pines administered as immediate-release formulations showed a statistically significant effect at week 1 (SMD, -0.20 [CI95% -0.28, -0.13]), which increased until week 3 (SMD, -0.42 [CI95% -0.50, -0.34]), after which the effect leveled off (week 6: SMD, -0.53 [CI95% -0.62, -0.44]). The sensitivity analyses of the individual pines confirm this finding, although data sparsity increases variability and limits conclusiveness of these analyses.

Competition indexes for individual Pinus taeda L. trees in non-thinned commercial stands

Competition indexes for individual Pinus taeda L. trees in non-thinned commercial stands

A GA and SVM Classification Model for Pine Wilt Disease Detection Using UAV-Based Hyperspectral Imagery

Pine wilt disease (PWD), caused by the pine wood nematode (Bursaphelenchus xylophilus), is a global destructive threat to forests and has led to serious economic losses all over the world. Therefore, it is necessary to establish a feasible and effective method to accurately monitor and estimate PWD infection. In this study, we used hyperspectral imagery (HI) collected by an unmanned airship with a hyperspectral imaging spectrometer to detect PWD in healthy, early, middle and serious infection stages. To avoid massive calculations on the full spectral dimensions of the HI, 16 spectral features were extracted from the HI, and a genetic algorithm (GA) was implemented to identify the optimal ones with the least fitness. Simultaneously, a support vector machine (SVM) classifier was established to predict the PWD infection stage for an individual pine tree. The following results were obtained: (1) the spectral characteristics for pine trees in different PWD infection stages were distinctive in the green region (510–580 nm), red edge (680–760 nm) and near-infrared (780–1000 nm) spectra; (2) the six optimal spectral features (Dgreen, SDgreen, Dred, DRE, DNIR, SDNIR) selected with the GA effectively distinguished the PWD infection stages of pine trees with a lower calculation cost; (3) compared with the traditional classifiers, such as k-nearest neighbor (KNN), random forest (RF) and single SVM, the proposed GA and SVM classifier achieved the highest overall accuracy (95.24%) and Kappa coefficient (0.9234). The approach could also be employed for monitoring and detecting other forest pests.

Individual models for diameter and height projection with contribution of competition index in Pinus taeda L. stands

The aim if this work was to assess and propose projection models for diameter at breast height and total height of individual pine trees and the contribution of competition indexes in these models. Data was obtained from 1056 permanent sampling units of non-thinned Pinus taeda L. stands located in the Telêmaco Borba region, Paraná, Brazil, with ages between 3.4 and 19.5 years. In order to project the diameter and total height of the trees, linear models were tested according to the variable in the current age, the projection age in the future, the basal area, and the site index, as well as their transformations. The Spearman correlation was obtained between competition indexes and dendrometric and stand variables, with the GH (Glover and Hool), LO (Lorimer) and ST (Stage) indexes being selected. These indexes were assessed as independent variables in the models, whose contributions were verified through the “F ci ” test on the incremental contribution. The models were assessed through the adjusted coefficient of determination, standard error of the estimate, and boxplots of residuals. The models provided precise and bias-free projections. The competition indexes statistically contributed to diameter and total height projection according to the “F ci ” test, increasing the precision of projected values for the majority of models tested. The indexes with major contributions to individual tree modelling for diameter and total height projection of Pinus taeda were Glover and Hool (GH) and Lorimer (LO), respectively.

Long-Term Projections of the Natural Expansion of the Pine Wood Nematode in the Iberian Peninsula

The invasive pine wood nematode (PWN), Bursaphelenchus xylophilus, causal agent of pine wilt disease, was first reported in Europe, near Lisbon, in 1999, and has since then spread to most of Portugal. We here modelled the spatiotemporal patterns of future PNW natural spread in the Iberian Peninsula, as dispersed by the vector beetle Monochamus galloprovincialis, using a process-based and previously validated network model. We improved the accuracy, informative content, forecasted period and spatial drivers considered in previous modelling efforts for the PWN in Southern Europe. We considered the distribution and different susceptibility to the PWN of individual pine tree species and the effect of climate change projections on environmental suitability for PWN spread, as we modelled the PWN expansion dynamics over the long term (>100 years). We found that, in the absence of effective containment measures, the PWN will spread naturally to the entire Iberian Peninsula, including the Pyrenees, where it would find a gateway for spread into France. The PWN spread will be relatively gradual, with an average rate of 0.83% of the total current Iberian pine forest area infected yearly. Climate was not found to be an important limiting factor for long-term PWN spread, because (i) there is ample availability of alternative pathways for PWN dispersal through areas that are already suitable for the PWN in the current climatic conditions; and (ii) future temperatures will make most of the Iberian Peninsula suitable for the PWN before the end of this century. Unlike climate, the susceptibility of different pine tree species to the PWN was a strong determinant of PWN expansion through Spain. This finding highlights the importance of accounting for individual tree species data and of additional research on species-specific susceptibility for more accurate modelling of PWN spread and guidance of related containment efforts.

Inverse density-dependent diapause and its influence on population dynamics in Monochamus alternatus alternatus (Coleoptera: Cerambycidae)

Monochamus alternatus alternatus Hope (Coleoptera: Cerambycidae) is the primary vector of pine wilt disease in China and Taiwan. It has a partially bivoltine life cycle with facultative diapause at the final larval instar that is mediated by the initial larval density. To evaluate the effect of density-related induction of diapause on population fluctuation, one, two or four newly hatched larvae were inoculated on individual Pinus thunbergii bolts and the life-history traits including diapause were investigated. This experiment indicated that as initial population size/bolt (crowding) increased, the diapause incidence, larval stage survival, adult body size, development time of nondiapause individuals and pupal period of diapause individuals decreased. The analysis indicated that larval interference as well as food shortage suppressed diapause induction. Increasing larval density decreased the probability of diapausing, survival, adult body mass and other traits. Using the data obtained from this study, a simple mathematical model indicated that inverse density-dependent induction of diapause in the first generation had a destabilizing effect on the population size of overwintering generation, which was composed of diapause larvae of the first and second generations; whereas, direct density-dependent induction of diapause exerted a stabilizing effect on it.

A method for experimental warming of developing tree seeds with a common garden demonstration of seedling responses

BackgroundForest dieback driven by rapid climate warming threatens ecosystems worldwide. The health of forested ecosystems depends on how tree species respond to warming during all life history stages. While it is known that seed development is temperature-sensitive, little is known about possible effects of climate warming on seed development and subsequent seedling performance. Exposure of seeds to high air temperatures may influence subsequent seedling performance negatively, though conversely, warming during seed development may aid acclimation of seedlings to subsequent thermal stress. Technical challenges associated with in-situ warming of developing tree seeds limit understanding of how tree species may respond to seed development in a warmer climate.ResultsWe developed and validated a simple method for passively warming seeds as they develop in tree canopies to enable controlled study of climate warming on seedling performance. We quantified thermal effects of the cone-warming method across individual pine trees and stands by measuring the air temperature surrounding seed cones using thermal loggers and the temperature of seed cone tissue using thermocouples. We then investigated seedling phenotypes in relation to the warming method through a common garden study. We assessed seedling morphology, physiology, and mycorrhizal nodulation in response to experimental cone-warming in 20 seed-source-tree canopies on the San Francisco Peaks in northern Arizona, USA. The warming method increased air temperature surrounding developing seed cones by 2.1 °C, a plausible increase in mean air temperature by 2050 under current climate projections. Notable effect sizes of cone-warming were detected for seedling root length, shoot length, and diameter at root collar using Cohen’s Local f2. Root length was affected most by cone-warming, but effect sizes of cone-warming on root length and diameter at root collar became negligible after the first year of growth. Cone-warming had small but significant effects on mycorrhizal fungal richness and seedling multispectral near-infrared indices indicative of plant health.ConclusionsThe method was shown to reliably elevate the temperature surrounding seed cones and thereby facilitate experimental in-situ climate warming research on forest trees. The method was furthermore shown to influence plant traits that may affect seedling performance under climate warming.

Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

BackgroundPine wilt disease (PWD) is a major ecological concern in China that has caused severe damage to millions of Chinese pines (Pinus tabulaeformis). To control the spread of PWD, it is necessary to develop an effective approach to detect its presence in the early stage of infection. One potential solution is the use of Unmanned Airborne Vehicle (UAV) based hyperspectral images (HIs). UAV-based HIs have high spatial and spectral resolution and can gather data rapidly, potentially enabling the effective monitoring of large forests. Despite this, few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine.MethodTo fill this gap, we used a Random Forest (RF) algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data (data directly collected from trees in the field). We compared relative accuracy of each of these data collection methods. We built our RF model using vegetation indices (VIs), red edge parameters (REPs), moisture indices (MIs), and their combination.ResultsWe report several key results. For ground data, the model that combined all parameters (OA: 80.17%, Kappa: 0.73) performed better than VIs (OA: 75.21%, Kappa: 0.66), REPs (OA: 79.34%, Kappa: 0.67), and MIs (OA: 74.38%, Kappa: 0.65) in predicting the PWD stage of individual pine tree infection. REPs had the highest accuracy (OA: 80.33%, Kappa: 0.58) in distinguishing trees at the early stage of PWD from healthy trees. UAV-based HI data yielded similar results: the model combined VIs, REPs and MIs (OA: 74.38%, Kappa: 0.66) exhibited the highest accuracy in estimating the PWD stage of sampled trees, and REPs performed best in distinguishing healthy trees from trees at early stage of PWD (OA: 71.67%, Kappa: 0.40).ConclusionOverall, our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage, although its accuracy must be improved before widespread use is practical. We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data. We believe that these results can be used to improve preventative measures in the control of PWD.

Characterization of pine and Eucalyptus oil and correlative evaluation of their performance as diesel blend in conventional diesel engine

ABSTRACT The present study envisages the use of diesel blended with plant based oils in conventional engine and their evaluation for engine performance and other emission parameters. Here, individual Pine (P20D80) and Eucalyptus oil (E20D80), and their same (1:1) proportion where ratio mixed (P10E10D80) as a 20% blend with the diesel was used. The selection of mentioned oils was made on the basis of their low viscosity and similarities to fossil diesel. The results revealed that when the engine was operated with P10E10D80, the brake thermal efficiency (5.5%) and lower fuel energy consumption was improved as compared to other blended fuels at full load. Also, the physicochemical characteristics such as viscosity, boiling point lower and calorific value of P10E10D80 were found to be comparable with conventional diesel. The cetane index of P10E10D80 was observed to be lower than E20D80 and conventional diesel, but higher than P20D80. The results revealed that P10E10D80 blend provide a maximum heat release rate of 71.94 J/CA at in-cylinder pressure of 79.63 bar and the ignition delay of the P10E10D80 blend was lower. Moreover, the EGT, HC, and CO smoke opacity emission of the P10E10D80 blend was lower as compared to diesel at full load. Interestingly, the atomization and evaporation rates of P10E10D80 were superior to other blends as well as conventional diesel. The results demonstrated reduction of 15.82%, 23%, 48%, and 26.79% in EGT, HC, CO, and smoke opacity, respectively, with the use of plant based oil blend with diesel. However, NOX emission was increased by 8.60% and observed a 13.50% higher heat release rate compare with blend and conventional diesel at full load. Moreover, an attempt to correlate the constituents of the oils with their performance has also been made.

The Wood of Scots Pine (Pinus sylvestris L.) from Post-Agricultural Lands Has Suitable Properties for the Timber Industry

Scots pine (Pinus sylvestris L.) is a widespread species throughout Europe and at the same time is dominant in Polish forests and of key importance in the wood industry. Pine stands are subjected to numerous environmental stresses, and one of them is the different physico-chemical and biological properties of post-agricultural soils compared to forest soils, which may affect the properties of the resulting wood and its industrial suitability. The research material taken at the height of 1.3 m from tree trunks (breast height diameter, dbh) in the form of sections and discs was collected in an 80-year-old pine stand from four plots, representing former agricultural and ancient forest land, and two types of habitats: fresh coniferous forest and fresh mixed coniferous forest. The forest habitat trophy had a decisive impact on the dendrometric characteristics and properties of pine wood (density, modulus of elasticity, bending strength, and compressive strength along the tracheids). The history of soil use (post-agricultural or forestry) did not affect the analyzed pine wood properties. Regardless of the forest habitat type and soil type history, pine wood at the dbh height showed a variability of features typical of century-old cultivated stands. Individual pine trunks were characterized by significant individual variability.

Potential impact of climate change on throughfall in afforestation areas located in arid and semi-arid environments

We assessed how climate change may impact the canopy hydrology of individual Pinus eldarica, Pinus brutia, and Cupressus arizonica trees planted in arid and semi-arid climates in Iran. Precipitation that reaches the forest floor as throughfall (TF) represents a significant portion of individual precipitation events (Pg ). We used a nondimensional relative sensitivity coefficient to examine the sensitivity of TF to changes in Pg . The Coupled Model Intercomparison Project phase 5 (CMIP5) HadGEM2-ES product was used under two emission scenarios (Representative Concentration Pathway (RCP) 2.6 and 8.5) to project yearly precipitation and Pg for the measurement sites from 2020–50. There was a strong linear relationship between TF and Pg at all sites [TF = 0.6 (Pg ) − 0.2; R 2 = 0.9]. The arid P. eldarica trees showed the highest sensitivity coefficient (5.3) compared with semi-arid C. arizonica trees (1.6). The sensitivity coefficient approximately doubled for individual P. eldarica and C. arizonica trees in the arid climate relative to P. brutia and C. arizonica trees in the semi-arid climate. This suggests that TF under trees in the arid climate were more affected by changing Pg than in the semi-arid climate. Pinus eldarica trees planted in the dry climate exhibited the largest sensitivity coefficient differences (3.4) between small and large Pg . Changes in precipitation and increased smaller storm frequency are expected for arid and semi-arid regions. To buffer expected shifts in storm size due to climate change, it may be suitable to incorporate TF sensitivity when selecting trees for landscaping and urban greening.

Tree-ring δ18O-based July–August relative humidity reconstruction on Mt. Shimen, China, for the last 400 years

Understanding long-term drought variations in the past can help us to evaluate ongoing and future hydroclimate changes in the arid western Chinese Loess Plateau. The present study generated a new stable oxygen isotope (δ18O) chronology composed of five individual Pinus tabulaeformis Carr. isotope series from Mt. Shimen, China. Correlation function analysis revealed that the composite tree-ring δ18O series responded significantly to July–August relative humidity (RHJA, r = −0.684, n = 47, p < .0001). A transfer function was thus designed, and the RHJA in the Mt. Shimen region was reconstructed for the past 397 years. Several famous droughts in Chinese history, such as the Chong Zhen severe drought (1637–1643 CE), Ding Wu extraordinary drought (1876–1878 CE) and 1928–1930 CE severe drought, are captured by our reconstruction. Meanwhile, our reconstructed RHJA compares well with other palaeoclimatic results around the study area. Spatial correlation analysis revealed that the RHJA reconstruction displays large-scale representativeness. The reconstruction is significantly positively correlated with several Asian summer monsoon (ASM) indices, indicating that the reconstructed RHJA reflects the variations in ASM intensity to a large extent. In terms of the local climate change mechanisms, we found that the factors affecting the variations in RHJA in the Mt. Shimen region are complex and involve large-scale oceanic–atmospheric couplings, such as sea surface temperature (SST), El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). Solar activity also certainly has great impacts.

Asian Summer Monsoon‐Related Relative Humidity Recorded by Tree Ring δ18O During Last 205 Years

AbstractTo deeply understand the Asian summer monsoon (ASM) strength variation in its fringe region, we established a 205‐year stable oxygen isotope (δ18O) chronology based on four individual Pinus tabulaeformis Carr. from Ordos Plateau, China. First, we found that δ18O in tree rings inherits the signals of summer (June to August) monsoonal precipitation δ18O (δ18OP). Second, relative humidity (RH) was observed to have a large effect on the δ18O of pine trees. The tree ring δ18O series significantly correlates with the observed local RH from June to August (RHJJA) with r = −0.65 (N = 56, p &lt; 0.001). The RH over Ordos Plateau is greatly influenced by ASM‐related precipitation. As such, it could well reflect the variations of ASM intensity. Thus, we reconstructed the RHJJA over Ordos, the center of the ASM fringe region (ASMFR), for the last two centuries. Our reconstructed RHJJA series has a large geographical and spatial representativeness, which is well compared with other precipitation reconstructions in ASMFR and jointly reflects ASM variations in the past. The RHJJA reconstruction showed that the 1870s–1890s were the wettest years in the entire reconstruction, while the middle‐late 1920s were the driest. From 1930 to 2012, the RH of the study area continuously decreased. We found significantly negative correlations between RHJJA and the Central Pacific sea surface temperature. This finding means that if the El Niño–Southern Oscillation of the Central Pacific continues to increase in the future, the aridification in the ASMFR will be intensified.

Associational resistance to a pest insect fades with time

Tree diversity is one of the drivers of forest resistance to herbivores. Most of the current understanding of the diversity resistance relationship comes primarily from short-term studies. Knowing whether tree diversity effects on herbivores are maintained over time is important for perennial ecosystems like forests. We addressed the temporal dynamics of the diversity resistance relationship by conducting a 6-year survey of pine attacks by the pine processionary moth Thaumetopoea pityocampa (PPM) in a tree diversity experiment where we could disentangle tree composition from host density effects. During the first years after planting the trees, PPM attacks on maritime pine Pinus pinaster were reduced in the presence of birch Betula pendula, a fast-growing non-host tree (i.e. associational resistance). This effect was maintained but faded with time as the pines eventually grew taller than neighbouring birches. The number of repeated attacks on individual pine trees also decreased in mixed pine–birch stands. Pine density had a positive effect on stand colonisation by PPM and a negative effect on the proportion of trees that were attacked. Pines were less likely to be repeatedly attacked as pine density increased, with attacks being spread over a larger number of host trees. Collectively, these results unravel the independent contribution of tree species composition and host density to tree resistance to herbivores. Both processes had directional changes over time. These results indicate that the resistance of planted forests to herbivores can be improved by carefully choosing the composition of mixed forests and the timing of species planting.

Longleaf pine proximity effects on air temperatures and hardwood top-kill from prescribed fire

BackgroundRegulation of the dominance of resprouting understory hardwoods is a common objective for prescribed fire in open-canopy longleaf pine (Pinus palustris Mill.) woodland of the southeastern USA. Nevertheless, little is known about the influence of individual pines on fire and hardwood mortality. We studied growing-season fires in stem-mapped stands in southwest Georgia, USA; the stands displayed large variation in structure due to cutting treatments applied seven years earlier. We measured air temperature and heating duration, and measured post-fire sprouting behavior of four guilds of understory hardwoods: mesic oaks (Quercus spp. L.), upland oaks, xeric oaks, and fleshy-fruited hardwoods. Mean air temperature (i.e., of flames, buoyant plume, and smoldering combustion) and heating duration (time over 60 °C) were analyzed with respect to fuel-bed conditions and neighboring tree density. Hardwood top-kill was analyzed with respect to neighboring tree density and hardwood height.ResultsThe basal area of nearby pines strongly affected heating duration (time over 60 °C), which increased linearly from a mean of 87 s to a mean of 234 s across a gradient of pine basal area from 0 to 30 m2 ha−1. Mean air temperature during prescribed fire was unaffected by pine density but increased linearly from a mean of 114 °C to a mean of 148 °C across a gradient of wiregrass (Aristida stricta Michx.) cover from 0 to 100%, respectively. Neighborhood models showed that time over 60 °C during the burns was longest at the base of pines and decreased by two thirds at 3.3 m distance. Pines affected hardwood top-kill probability at a similar scale, the effect at 4.4 m decreasing by two thirds compared to at the base of the pine. The four hardwood guilds were readily top-killed when ≤1 m tall, but at 2 m height, upland and xeric oaks had become more resistant to top-kill than mesic oaks or fleshy-fruited hardwoods.ConclusionsThe influence of individual pine trees on heating duration and top-kill power of prescribed fire drops by two thirds of maximum within 3 to 4 m of a tree, compared to a maximum at the base of the tree. Neighborhood models provide a method to estimate tree effects on prescribed fire heating duration and top-kill probability, and thus a way of predicting stand structures that provide ecological benefits of openings while remaining below thresholds that trigger vigorous hardwood response.