Stand Dynamics and Fire History of a Southern Appalachian Pine-Hardwood Forest on Rainy Mountain, Chattahoochee National Forest, Georgia, U.S.A.

In the American Southeast, forest managers and conservationists are interested in evaluating how forest composition is changing in response to both human and natural disturbances. This study explored the stand dynamics of a pine-hardwood forest on Rainy Mountain in the Chattahoochee National Forest of Georgia over the last 115 years and analyzed the role fire has had as a disturbance in the forest. Increment cores were collected from trees in 30 plots, each 0.01 ha in area. The cores were used to determine date of establishment of each tree and create age structure charts for each plot and for the study area as a whole. Based on calculated importance values, blackgum, pitch pine, and red maple are currently the dominant species in the forest. However, seedling and sapling surveys showed an absence of yellow pine regeneration along with a relative abundance of red maple and blackgum, indicating that these trees will dominate the future forest. A concurrent fire history was also constructed using logs, stumps, remnant wood, and living trees with fire scars. Small sections were collected from each and analyzed to determine how frequently fires occurred in the Rainy Mountain area. The resulting fire chronology, the first developed for the state of Georgia using dendrochronology, spans from 1904 to 2012 and includes 36 individual dated fire scars from 20 trees. Fires occurred as recently as 2010, and the mean fire interval of the chronology indicates a fire event approximately once every four years. Several old stumps with fire scars were also collected, but could not be dated in many cases because of the lack of a sufficiently long master tree-ring chronology. Similar to other research conducted in the southern Appalachian Mountains, this study shows a change in forest composition from a pine-oak dominated forest to a red maple-blackgum dominated forest, a change that has previously been linked to fire suppression management policies beginning in the 1930s. However, the fire chronology at Rainy Mountain shows an actual increase in fire frequency after the 1930s accompanied by a concurrent change in forest composition

Annual Aboveground Biomass Growth in Temperate Forests of Eastern North America

The below dissertation is organized into three individual standalone manuscripts supporting the overarching theme of reconstructing annual aboveground biomass growth in temperate forests of eastern North America using dendrochronological applications. Each manuscript is organized with the intent of submission to a peer-reviewed journal. The first manuscript validated the technique I use throughout my dissertation by comparing tree-ring derived estimates of annual aboveground productivity with estimates from co-located or nearby permanent remeasurement plots at Howland, Maine, Harvard Forest, Massachusetts, and Fernow, West Virginia. The second manuscript investigated the size-related distribution of biomass growth at 16 eastern U.S. forest sites and compared results with United States Forest Service inventory plot data. The goal of this manuscript was to determine where, structurally, biomass was allocated in forests and whether these quantities changed over time and between forests. The third manuscript was inspired by the results of my second chapter. Here, I investigated whether the degree of asymmetry, or the slope of the linear regression between tree diameter and growth, is a useful indicator of total forest productivity. Previous studies linking asymmetry and productivity have been inconclusive, and this chapter evaluates consistency or lack of consistency across the same 16-site eastern U.S. forest network

Evaluating The Effect Of Alternative Carbon Allocation Schemes In A Land Surface Model (Clm4.5) On Carbon Fluxes, Pools And Turnover In Temperate Forests

How carbon (C) is allocated to different plant tissues (leaves, stem and roots) determines C residence time and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and Leaf Area Index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a Land Surface Model (LSM), the Community Land Model (CLM4.5). We ran CLM for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i) Dynamic C allocation scheme (named D-CLM ) with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual Net Primary Production (NPP). ii) An alternative dynamic C allocation scheme (named D-Litton ), where, similar to (i) C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem and coarse roots iii–iv) Two fixed C allocation schemes, one representative of observations in evergreen (named F-Evergreen ) and the other of observations in deciduous forests (named F-Deciduous ). D-CLM generally overestimated Gross Primary Production (GPP) and ecosystem respiration, and underestimated Net Ecosystem Exchange (NEE). In D-CLM, initial aboveground biomass in 1980 was largely overestimated (between 10527 and 12897 g Cm-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g Cm-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C-LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem/Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass, and aboveground NPP for deciduous forests by D-CLM. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. That could be done by addressing some of the current model assumptions about C allocation and the associated parameter uncertainty. Our results highlight the importance of using aboveground biomass data to evaluate and constrain the C allocation scheme in the model, and in particular, the sensitivity to the stem turnover rate. Revising these will be critical to improving long-term C processes in LSMs, and improve their projections of biomass accumulation in forests

Comparing Tree‐Ring and Permanent Plot Estimates of Aboveground Net Primary Production in Three Eastern U.S. Forests

Forests account for a large portion of sequestered carbon, much of which is stored as wood in trees. The rate of carbon accumulation in aboveground plant material, or aboveground net primary productivity (aNPP), quantifies annual to decadal variations in forest carbon sequestration. Permanent plots are often used to estimate aNPP but are usually not annually resolved and take many years to develop a long data set. Tree rings are a unique and infrequently used source for measuring aNPP, and benefit from fine spatial (individual trees) and temporal (annual) resolution. Because of this precision, tree rings are complementary to permanent plots and the suite of tools used to study forest productivity. Here we evaluate whether annual estimates of aNPP developed from tree rings approximate estimates derived from colocated permanent plots. We studied a lowland evergreen (Howland, Maine), mixed deciduous (Harvard Forest, Massachusetts), and mixed mesophytic (Fernow, West Virginia) forest in the eastern United States. Permanent plots at the sites cover an area of 2–3 ha, and we use these areas as benchmarks indicative of the forest stand. We simulate random draws of permanent plot subsets to describe the distribution of aNPP estimates given a sampling area size equivalent to the tree-ring plots. Though mean tree-ring aNPP underestimates permanent plot aNPP slightly at Howland and Fernow and overestimates at Harvard Forest when compared with the entire permanent plot, it is within the 95% confidence interval of the random draws of equal-sized sampling area at all sites. To investigate whether tree-ring aNPP can be upscaled to the stand, we conducted a second random draw of permanent plot subsets simulating a twofold increase in sampling area. aNPP estimates from this distribution were not significantly different from results of the initial sampling area, though variance decreased as sampling area approaches stand area. Despite several concerns to consider when using tree rings to reconstruct aNPP (e.g., upscaling, allometric, and sampling uncertainties), the benefits are apparent, and we call for the continued application of tree rings in carbon cycle studies across a broader range of species diversity, productivity, and disturbance histories to fully develop this potential

Comparing Tree-Ring And Permanent Plot Estimates Of Aboveground Net Primary Production In Three Eastern U.S. Forests

Forests account for a large portion of sequestered carbon, much of which is stored as wood in trees. The rate of carbon accumulation in aboveground plant material, or aboveground net primary productivity (aNPP), quantifies annual to decadal variations in forest carbon sequestration. Permanent plots are often used to estimate aNPP but are usually not annually resolved and take many years to develop a long data set. Tree rings are a unique and infrequently used source for measuring aNPP, and benefit from fine spatial (individual trees) and temporal (annual) resolution. Because of this precision, tree rings are complementary to permanent plots and the suite of tools used to study forest productivity. Here we evaluate whether annual estimates of aNPP developed from tree rings approximate estimates derived from colocated permanent plots. We studied a lowland evergreen (Howland, Maine), mixed deciduous (Harvard Forest, Massachusetts), and mixed mesophytic (Fernow, West Virginia) forest in the eastern United States. Permanent plots at the sites cover an area of 2-3 ha, and we use these areas as benchmarks indicative of the forest stand. We simulate random draws of permanent plot subsets to describe the distribution of aNPP estimates given a sampling area size equivalent to the tree-ring plots. Though mean tree-ring aNPP underestimates permanent plot aNPP slightly at Howland and Fernow and overestimates at Harvard Forest when compared with the entire permanent plot, it is within the 95% confidence interval of the random draws of equal-sized sampling area at all sites. To investigate whether tree-ring aNPP can be upscaled to the stand, we conducted a second random draw of permanent plot subsets simulating a twofold increase in sampling area. aNPP estimates from this distribution were not significantly different from results of the initial sampling area, though variance decreased as sampling area approaches stand area. Despite several concerns to consider when using tree rings to reconstruct aNPP (e.g., upscaling, allometric, and sampling uncertainties), the benefits are apparent, and we call for the continued application of tree rings in carbon cycle studies across a broader range of species diversity, productivity, and disturbance histories to fully develop this potential

Evaluating rural Pacific Northwest towns for wildfire evacuation vulnerability

Wildfire is an annual threat for many rural communities in the Pacific Northwest region of the United States. In some severe events, evacuation is one potential course of action to gain safety from an advancing wildfire. Since most evacuations occur in a personal vehicle along the surrounding road network, the quality of this network is a critical component of a community's vulnerability to wildfire. In this paper, we leverage a high-resolution spatial dataset of wildfire burn probability and mean fireline intensity to conduct a regional-scale screening of wildfire evacuation vulnerability for 696 Oregon and Washington rural towns. We characterize each town’s surrounding road network to construct four simple road metrics related to the potential to quickly and safely evacuate: (1) the number of paved lanes leaving town that intersect a fixed-distance circular buffer; (2) the variety of lane directions available for egress; (3) the travel area that can be reached within a minimum distance while constrained only to movement along the paved road network; and (4) the sum of connected lanes at each intersection for the road network within a fixed-distance circular buffer. We then combine the road metrics with two metrics characterizing fire hazard of the surrounding landscape through which evacuation will occur: (1) burn probability and (2) mean fireline intensity. By combining the road and fire metrics, we create a composite score for ranking all towns by their overall evacuation vulnerability. The most vulnerable towns are those where poor road networks overlap with high fire hazard. Often, these towns are located in remote, forested, mountainous terrain, where topographic relief constrains the available road network and high fuel loads increase wildfire hazard. An interactive map of all road quality and fire hazard metrics is available at https://www.fs.fed.us/wwetac/brief/evacuation.php

RIBA Research in Practice Guide

The RIBA Research in Practice Guide was developed as part of a project that looked into the state of housing research undertaken by architecture practices. This project titled ‘Home Improvements’ began with a survey and series of interviews with practitioners who suggested that architects consider research to be integral to their business. However it was clear that there are con icting understandings of research, in particular about what exactly constitutes research and how it aligns with other everyday activities in practice. This guide is meant to be read with the RIBA Plan of Work, giving architects practical guidance on how to understand and further exploit the research they already do. Its purpose is to help broaden architects’ research horizons, building useful and rewarding programmes of work and strengthening relationships with the wider research community

Spatial patterns and trends of summertime low cloudiness for the Pacific Northwest, 1996-2017

Summertime low clouds are common in the Pacific Northwest (PNW), but spatiotemporal patterns have not been characterized. We show the first maps of low cloudiness for the western PNW and North Pacific Ocean using a 22‐year satellite‐derived record of monthly mean low cloudiness frequency for May through September and supplemented by airport cloud base height observations. Domain‐wide cloudiness peaks in midsummer and is strongest over the Pacific. Empirical orthogonal function (EOF) analysis identified four distinct PNW spatiotemporal modes: oceanic, terrestrial highlands, coastal, and northern coastal. There is a statistically significant trend over the 22‐year record toward reduced low cloudiness in the terrestrial highlands mode, with strongest declines in May and June; however, this decline is not matched in the corresponding airport records. The coastal mode is partly constrained from moving inland by topographic relief and migrates southward in late summer, retaining higher late‐season low cloud frequency than the other areas.In the Pacific Northwest (PNW), low clouds, including fog, are a visible feature of the region's climate. PNW summers are dry, and ecosystems, cities, and agriculture rely on cooling effects and additional moisture provided by low clouds. We seek to understand when and where summertime low cloud frequency varies across the PNW by analyzing 22 years of satellite imagery. Using a statistical technique to isolate unique spatial and temporal groups, we identified four areas exhibiting unique patterns, which we call oceanic, terrestrial highlands, coastal, and northern coastal. Each pattern exhibits unique characteristics. Although low clouds over land are the least frequent, they steadily declined in the 1996–2017 satellite record, particularly in May and June, a trend not apparent in the other three regions or in the airport records. Oceanic low clouds occur the most frequently. Coastal low clouds migrate southward throughout summer and have higher frequencies in August and September relative to the rest of the PNW