Download or read book Linking Plant Demography Forest Fuels and Fire in Longleaf Pine Pinus Palustris Savannas Using LIDAR Remote Sensing and Simulation Modeling written by Eva Louise Loudermilk and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A longleaf pine - hardwood simulation model was created to link population level tree dynamics with fuel characteristics and stochastic fire regimes. This is the first known modeling work to simulate interactions between longleaf pine and hardwoods. Spatial components included seed dispersal (including pine seed masting), clonal spreading (for hardwoods), fuel dispersal and distribution, and competition from neighboring trees. Evaluations with in situ data were promising for two modeled longleaf pine sites. Tree distributions and community stability were examined with varying fire frequency. The model was especially useful in identifying scientific knowledge gaps associated with plant competition and facilitation, especially in relation to hardwood demography. The model ultimately provided a foundation for studying fuel and fire heterogeneity influences on population dynamics.

Download or read book Advanced Methods for 3 D Forest Characterization and Mapping from Lidar Remote Sensing Data written by Carlos Alberto Silva and published by . This book was released on 2018 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and spatially explicit measurements of forest attributes are critical for sustainable forest management and for ecological and environmental protection. Airborne Light Detection and Ranging (lidar) systems have become the dominant remote sensing technique for forest inventory, mainly because this technology can quickly provide highly accurate and spatially detailed information about forest attributes across entire landscapes. This dissertation is focused on developing and assessing novel and advanced methods for three dimensional (3-D) forest characterization. Specifically, I map canopy structural attributes of individual trees, as well as forests at the plot and landscape levels in both natural and industrial plantation forests using lidar remote sensing data. Chapter 1 develops a novel framework to automatically detect individual trees and evaluates the efficacy of k-nearest neighbor (k-NN) imputation models for estimating tree attributes in longleaf pine (Pinus palustris Mill.) forests. Although basal area estimation accuracy was poor because of the longleaf pine growth habit, individual tree locations, height and volume were estimated with high accuracy, especially in low-canopy-cover conditions. The root mean square distance (RMSD) for tree-level height, basal area, and volume were 2.96%, 58.62%, and 8.19%, respectively. Chapter 2 presents a methodology for predicting stem total and assortment volumes in industrial loblolly pine (Pinus taeda L.) forest plantations using lidar data as inputs to random forest models. When compared to reference forest inventory data, the accuracy of plot-level forest total and assortment volumes was high; the root mean square error (RMSE) of total, commercial and pulp volume estimates were 7.83%, 7.71% and 8.63%, respectively. Chapter 3 evaluates the impacts of airborne lidar pulse density on estimating aboveground biomass (AGB) stocks and changes in a selectively logged tropical forest. Estimates of AGB change at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg ̇ha−1 when pulse density decreased from 12 to 0.2 pulses ̇m−2. The effects of pulse density were more pronounced in areas of steep slope, but when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and subsequent AGB stocks and change estimates did not exceed 20 Mg ̇ha−1. Chapter 4 presents a comparison of airborne small-footprint (SF) and large-footprint (LF) lidar retrievals of ground elevation, vegetation height and biomass across a successional tropical forest gradient in central Gabon. The comparison of the two sensors shows that LF lidar waveforms are equivalent to simulated waveforms from SF lidar for retrieving ground elevation (RMSE=0.5 m, bias=0.29 m) and maximum forest height (RMSE=2.99 m; bias=0.24 m). Comparison of gridded LF lidar height with ground plots showed that an unbiased estimate of aboveground biomass at 1-ha can be achieved with a sufficient number of large footprints (> 3). Lastly, Appendix A presents an open source R package for airborne lidar visualization and processing for forestry applications.

Download or read book Linking Forest Growth Modeling with LiDAR Simulations written by and published by . This book was released on 2014 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fuel Dynamics of a Longleaf Pine pinus Palustris Mill Woodland Under a Prescribed Fire Rotation written by Raien K. Emery and published by . This book was released on 2020 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a result of historical logging and fire exclusion, longleaf pine (Pinus palustris Mill.) ecosystems have experienced extensive decline, now occurring on only 20́35% of its native range. Attempts to re-introduce fire into these forests where fuels have been altered by previous fire-exclusion or disturbance may not achieve desired management goals because fire effects are largely dependent on available fuels. To understand how fire impacts longleaf pine woodlands where fuels have been altered, fuel was collected before (2017) and after (2019) a prescribed fire on undisturbed, wind-disturbed, and wind-disturbed and salvage-harvested treatment types. In conjunction with percent consumption values calculated form laboratory burns, decomposition rates, and accumulation rates, fuel dynamics models were created and validated against post-fire fuel loadings. Total fuel loadings for undisturbed plots decreased 43%, wind-disturbed plots decreased 67%, and wind-disturbed and salvage-harvested plots decreased 53%. Fuel dynamics models successfully predicted post-fire fuel loadings for pine needles (rs = 0.782; p

Download or read book Patterns and processes written by and published by . This book was released on 2013 with total page 2 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longleaf pine (Pinus palustris) ecosystems are remarkably rich in plant species and represent the dominant upland forest type in several southeastern military installations. Management of these forests on installations is critical both to fulfill the military mission and to conserve this unique natural resource. The researchers will couple a series of field experiments with data mining exercises to help managers meet their objectives for monitoring the impact of various activities on the understory plant community. Results from this project will also aid development of modeling tools to help evaluate different management scenarios based on the intimate link between overstory structure, fire, and understory plant diversity. The project goals are to: (1) understand how the accuracy and effectiveness of sampling and monitoring programs are affected by the scale and timing of measurements, (2) increase plant sampling efficiency and efficacy by identifying and developing statistical approaches for dealing with complex spatial patterns of species distributions, and (3) examine the mechanisms driving patterns of plant diversity and then use this information to find linkages between small scale patterns in understory plant diversity and coarser scale stand characteristics that are more easily monitored and manipulated by managers. The overarching goal will be to develop sampling tools and spatially explicit models that predict the outcomes of various fire- and stand-management practices relative to understory diversity.

Download or read book May Burns Stimulate Growth of Longleaf Pine Seedlings written by Harold E. Grelen and published by . This book was released on 1978 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Assessing Surface Fuel Hazard in Coastal Conifer Forests Through the Use of LiDAR Remote Sensing written by Christos Koulas and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The research problem that this thesis seeks to examine is a method of predicting conventional fire hazards using data drawn from specific regions, namely the Sooke and Goldstream watershed regions in coastal British Columbia. This thesis investigates whether LiDAR data can be used to describe conventional forest stand fire hazard classes. Three objectives guided this thesis: to discuss the variables associated with fire hazard, specifically the distribution and makeup of fuel; to examine the relationship between derived LiDAR biometrics and forest attributes related to hazard assessment factors defined by the Capitol Regional District (CRD); and to assess the viability of the LiDAR biometric decision tree in the CRD based on current frameworks for use. The research method uses quantitative datasets to assess the optimal generalization of these types of fire hazard data through discriminant analysis. Findings illustrate significant LiDAR-derived data limitations, and reflect the literature in that flawed field application of data modelling techniques has led to a disconnect between the ways in which fire hazard models have been intended to be used by scholars and the ways in which they are used by those tasked with prevention of forest fires. It can be concluded that a significant tradeoff exists between computational requirements for wildfire simulation models and the algorithms commonly used by field teams to apply these models with remote sensing data, and that CRD forest management practices would need to change to incorporate a decision tree model in order to decrease risk.

Download or read book Using Lidar Remote Sensing to Estimate Forest Fuels written by Carl Andrew Seielstad and published by . This book was released on 2003 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Lidar in Wildfire Ecology of the California Sierra Nevada Forests written by Marek K. Jakubowski and published by . This book was released on 2012 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: California's fire suppression policy has dramatically changed Sierra Nevada forests over the last century. Forests are becoming more dense and homogenous, leading to fire regime changes that increase the potential of stand-replacing wildfires over large, continuous areas. To mitigate this problem on public lands, the US Forest Service has proposed to implement strategically placed forest fuel reduction treatments. These treatments have been proved effective in modeled and simulated environments, but their efficacy and impact in real forests is not known. The research described in this dissertation is part of a large multidisciplinary project, known as the Sierra Nevada Adaptive Management Project (SNAMP), that aims to evaluate strategically placed landscape area treatments (SPLATs) in two forests of the Sierra Nevada mountains. Specifically, in this thesis, I investigate the feasibility of using an airborne light detection and ranging (lidar) system to gain accurate information about forest structure to inform wildfire behavior models, forest management, and habitat mapping. First, I investigate the use of lidar data in predicting metrics at the landscape level, specifically to derive surface fuel models and continuous canopy metrics at the plot scale. My results in Chapter 2 indicate that using lidar to predict specific fuel models for FARSITE wildfire behavior model is challenging. However, the prediction of more general fuel models and continuous canopy metrics is feasible and reliable, especially for metrics near the top of the canopy. It is also possible to derive canopy parameters at the individual tree level. In Chapter 3, I compare the ability of two processing methods--object-based image analysis (OBIA) and 3D segmentation of the lidar point cloud--to detect and delineate individual trees. I find that while both methods delineate dominant trees and accurately predict their heights, the lidar-derived polygons more closely resemble the shape of realistic individual tree crowns. Acquiring remotely sensed data at high resolution and over large areas can be expensive, especially in the case of lidar. In Chapter 4, I investigate the ability of lidar data to reliably predict forest canopy metrics at the plot level as the data resolution declines. I show that canopy metrics can be predicted at a reasonable accuracy with data resolutions as low as one pulse per squared meter. These findings will be useful to land managers making cost benefit decisions when acquiring new lidar data. Collectively, the results of this dissertation suggest that remote sensing, and in particular lidar, can reliably and cost-effectively provide forest information across scales--from the individual tree level to the landscape level. These results will be useful for the fire and forest management community in general, as well as being key to the goals of the SNAMP program.

Download or read book Effects of Fire Season on Vegetation in Longleaf Pine Pinus Palustris Forests written by Bryan Thomas Mudder and published by . This book was released on 2006 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Not Seeing the Forest for the Points written by Heather Anuhea Kramer and published by . This book was released on 2016 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forest and fire ecology have long utilized remote sensing datasets to learn more about landscapes. Advances in gps spatial accuracy, GIS software capabilities, computing power, and remote sensing technology and software, as well as increases in the spatial and temporal resolution of remote sensing products, have made remote sensing a critical component of forest and fire ecology. Aerial light detection and ranging (LiDAR) is a fast-growing active remote-sensing technology that can be mined for detailed structural information about forests. These data are utilized in the fields of hydrology, forest ecology, silviculture, wildland fire ecology, wildlife ecology, and habitat modeling. LiDAR coverage has also become increasingly common, yet still contains much untapped potential. Despite widespread research that derived copious valuable metrics from aerial LiDAR, few of these metrics are available to managers due to a significant knowledge and software barrier for LiDAR processing. Even when LiDAR is utilized to derive more complex metrics by scientists and LiDAR experts, metrics are often predictions of plot-based data across the landscape. While these metrics are useful, LiDAR can offer so much more. Because it holds information about forest structure in 3 dimensions, new metrics can be derived that capture the full complexity of forest structure. I explore ways in which managers can use the plot network and data layers already available to them to derive large tree density, a metric that is critical for habitat modeling for many species, including the California spotted owl. I also explore the utility of LiDAR for estimating ladder fuels that carry fire from the ground into the canopy. Because there was no reliable method for quantifying these fuels, I also developed a plot-based methodology to collect these data. My dissertation work aims to increase LiDAR accessibility to managers and to develop new ways to use LiDAR to solve old problems. While there is much more work to be done, I am excited to share my work with LiDAR experts and forest managers, and hope that my findings improve the way we use LiDAR, the way we manage forests, and the way that we model and manage for wildland fire.

Download or read book Spring burn aids longleaf pine seedling height growth written by William R. Maple and published by . This book was released on 1977 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling Fire induced Tree Mortality in Longleaf Pine Using Spatial Data written by Holland R. Heese and published by . This book was released on 2014 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Restoration of fire-excluded pine ecosystems is a major conservation and management goal. Land managers have used prescribed fires to reduce accumulated forest floor fuels and restore pinelands. While these fires have been successful at reducing fuels, tree mortality in these restoration fires can be as high as 75 to 95 percent. In this study, I model post-fire mortality of longleaf pine (in two stands in the Mountain Longleaf National Wildlife Refuge in northeastern Alabama) using logistic models composed of only predictors that can be measured pre-fire. These methods are extended by the addition of spatial competition functions since such measures are drawn from available data for managers, and have been shown to have effects on growth and mortality. The best models, selected by AIC, predict survival as well or better than earlier models but have high false mortality predictions. The spatial dynamics of the stand are also studied pre-fire and post-fire to determine the effect of prescribed fire and inter-tree competition. Post-fire, spatial distribution of the trees did not significantly change. Earlier studies detected differences in the spatial dynamics between different classes of longleaf pine. These dynamics were confirmed in some results and in others questioned. Small trees (DBH 30 cm) clustered away from large trees (DBH 30 cm). Large trees were more dispersed than a random process (Poisson) would dictate. Juveniles (DBH

Download or read book Longleaf Pine Pinus Palustris Growth and Population Dynamics Under Climate Change written by Nicole Eugenia Zampieri and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The longleaf pine (Pinus palustris) savanna is an endangered ecosystem within a global biodiversity hotspot. However, most studies of longleaf habitats have not considered the distinct structure and function of unique longleaf communities, which is critical for developing appropriate management strategies. Florida has 50% of the remaining habitat, where it occurs in unique community types that differ in their hydrology, species composition, and disturbance regimes. The structure and growth of longleaf pine in the different community types depends on the unique interactions between these abiotic and biotic components. The legacy of anthropogenic disturbance through logging, fragmentation, fire exclusion, and the rapidly changing climate have resulted in potentially novel dynamics for longleaf pine ecosystems. Identifying the drivers of tree growth and population dynamics can facilitate a better understanding of longleaf status and vulnerability to global change. In this dissertation, I explored and assessed how disturbances (fires and hurricanes) interact with species composition and climatic conditions to affect tree density, growth rates, and stand structure across community types in Florida.First, I assessed how differences in climate, fire, and species composition interact and relate to longleaf pine densities and growth rates in distinct communities. I used field surveys and tree cores to estimate stand structure and growth rates across community types. I used linear mixed-effects models to examine the effect of community type on longleaf pine density and growth rates and then used recursive partitioning and regression tree analyses to identify how climate, fire, and species composition affect density and growth rates. I found that stand structure and species composition were different across communities, whereas growth rates were not. Across communities, unique interactions between climate, fire, and species composition, resulted in differences in stand structure. In general, tree and grass stage densities were best predicted by species composition and fire rather than by climate within unique community types, whereas overall growth rates were best predicted by climate. I show that longleaf growth rates increased with higher temperatures, but this effect is reversed in dry conditions. Our research includes the southernmost extent of longleaf, and our results suggest that longleaf growth rates across its range will be more sensitive to current and future climate change than longleaf population density. Second, I used unique dendroecological methods to explore how climate and fire interact to affect annual tree growth. Traditional dendrochronological methods mask out individual variation by using stand level indices, and have a bias towards sampling resource limited trees, which is an effective strategy for climate reconstruction, but lacks an ecological focus. I present eight ecologically representative Florida longleaf pine chronologies and compare the strength of seasonwood and total ring width chronologies, finding that latewood growth had stronger climatic correlations, but not stronger crossdating. Then, I used correlation analyses to identify the primary climatic drivers of tree growth and found summer precipitation had a positive effect and summer temperature had a negative effect at a majority of sites, although there was no climatic variable at any season length with exact effects on tree growth across sites. Finally, I used linear mixed effects models to estimate how the climatic drivers interact with fire to affect individual tree growth. I identified unique effects from fire seasonality, with negative effects due to dormant season burning at 60% of sites. I found positive effects from fire in the previous year in 60% of sites. In many cases, fire reversed or neutralized the effect of climate, suggesting unique implications for management under climate change. By using ecologically representative samples, I show how climate and fire interact differently to affect tree growth and highlight variability in ecosystem function across communities and sites. Finally, I investigate immediate hurricane impacts to stand structure at four sites after experiencing an unprecedented Category 5 storm, which exemplifies the growing threats the longleaf pine ecosystem faces under anthropogenic climate change. I used variable-area transects and generalized linear mixed-effects models to estimate tree densities and logistic regression to estimate mortality by size class. I found at least 28% of the global total remaining extent of the longleaf pine ecosystem was affected in Florida alone. Mortality was highest in medium sized trees (30-45 cm dbh) and ranged from 4.6-15.4% at sites further from the storm center, but increased to 87.8% near the storm center. As the frequency and intensity of extreme events increases, management plans to mitigate the effects of climate change need to account for large-scale stochastic mortality events to preserve critical habitats. Even where protected, critical habitats are vulnerable to the effects of climate change.

Download or read book Smoldering Fire in Long unburned Longleaf Pine Forests written by Julian Morgan Varner and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In landscape-scale experimental fires in long-unburned pine forests, four replicated treatments based on lower forest floor (duff) moisture content were applied: dry burns were ignited at 55% duff moisture content (DMC); moist burns at 85% DMC; wet burns at 115% DMC; and there was a control treatment that was not burned. Pine mortality was delayed up to 18 months following burning, and was highest (P

Download or read book Using NDVI to Assess Departure from Average Greenness and Its Relation to Fire Business written by Robert E. Burgan and published by . This book was released on 1996 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Effects of Pine Litter Raking on Plant Community Composition and Soil Seed Banks in Longleaf Pine Savannas written by Jordan Andrew Winter and published by . This book was released on 2020 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Longleaf pine (Pinus palustris) savannas have been reduced to a small percentage of their original range in the southeastern United States. These savannas are fire-reliant and require frequent, low-intensity fires to maintain understory plant diversity. Currently, many landowners rake pine litter off the forest floor of longleaf pine savannas for subsequent sale in horticulture. Though raking is a common practice, little is known about the effects of raking on the understory plant community, the soil seed bank, or fire intensity. I conducted my research in two longleaf pine savanna sites where raking has occurred"--Title leaf.