Over the three chapters of my dissertation, I combined manipulative experiments and long-term monitoring data from grasslands, mixed conifer, and high elevation forests to explain emerging community shifts in California. I also applied these results to management strategies focused on global change. In the first chapter of my dissertation, I focused on the effects of shifting weather patterns on California’s annual grassland communities. The results highlighted the importance of lagged rainfall effects and two important mechanisms (dry litter and propagule production) driving grass and forb responses to lagged rainfall. For the second chapter of my dissertation, I focused on the causes and consequences white pine blister rust and bark beetles in the Sierra Nevada. Resampling long-term monitoring plots, I characterized how the invasion of white pine blister rust (Cronartium ribicola) shifted over twenty years and how recent bark beetle populations were affecting white pine health in the southern Sierra. My third chapter concludes this dissertation by critiquing resilience applications in natural resource management. By combining resilience theory with concepts from the novel ecosystem literature, management of global change can be improved.

In North America, cottonwood (Populus) and other members of the family Salicaceae are considered to exhibit the classic colonization-competition trade-off. Adaptations that make them highly successful colonists in disturbance-prone floodplain environments appear to reduce their ability to compete for resources in more benign environments. Because cottonwood recruitment dynamics are so tightly coupled to the natural disturbance regime, river regulation has led to widespread decline in seedling establishment along the active channel. However, pioneer trees that require disturbance events for regeneration use a variety of strategies for persisting during periods of relative stability. The use of spatial refugia, while critical for population recovery of many mobile organisms, is generally not considered an important strategy for trees. Episodic channel abandonment in meandering river systems, and the subsequent infill and terrestrialization of the abandoned channel, has been recently highlighted as critical for maintaining the population of a key pioneer riparian tree species, Fremont cottonwood (Populus fremontii). While controls on seedling establishment along the active channel are predominantly abiotic, temporal changes in abandoned channels result in a shift toward a more physically stable and more competitive environment. How a species with such strong colonization traits can establish in abandoned channels, and for how long, are the main questions addressed in my dissertation.

In a controlled community mesocosm experiment (Chapter 1), I used field-informed gradients of substrate texture and herbaceous cover to test interacting effects of soil moisture and interspecific competition on first year cottonwood seedling survival. I found that primary controls on cottonwood seedling establishment switched from abiotic to biotic drivers as a result of the biogeomorphic development of abandoned channels. Like on the active channel, seedlings were strongly moisture limited in conditions immediately following channel abandonment, but competition became a more important determinant of survival in conditions representative of an older abandoned channel. However, I also found that cottonwood seedlings were better competitors than anticipated, and were able to survive in the more physically benign and competitive conditions as well as the more physically stressful conditions to which they are classically adapted. This suggests that abandoned channels provide conditions favorable for cottonwood establishment for a broad window of time. While my focus was on understanding mechanisms controlling seedling establishment within abandoned channels, my results clarify interactions between abiotic and biotic controls that are more broadly applicable within a meandering river corridor. My results also add to evidence that species lie along a competition-colonization continuum, and have implications for incorporating secondary recruitment locations into management and restoration of pioneer riparian forests.

The well-known interspecific trade-off of high-light growth in early colonizing species, versus low-light survival in species that are better resource competitors, leads to the logical conclusion that pioneer trees such as cottonwood are shade intolerant. Empirical evidence also finds seedlings rarely establish in vegetated areas. So how are cottonwoods able to establish in the more densely vegetated (i.e., shadier) environment of abandoned channels? I examined this question using a shade-cloth mesocosm experiment (Chapter 2), in which I considered interactive gradients of moisture and light. In dry ecosystems, sunlight can be considered both a resource and a stress, with shading reducing evaporative demand by maintaining a cooler understory microclimate. I found that shading resulted in reduced vapor pressure deficits and higher soil moistures, and a strong positive effect on first year cottonwood seedling survival in the Mediterranean climate of California. However, seedlings that survived to the end of the experiment showed decreased final biomass and root growth in shade. These results suggest that cottonwoods are much more plastic in their shade tolerance than has been previously assumed. The positive effect of shade on survival was observed regardless of soil moisture availability, whereas the positive effect of sun on growth was much stronger in wetter conditions, suggesting that soil moisture is the dominant limiting resource for seedling growth. I conclude that their high moisture requirement, along with their plasticity in shade tolerance, is what allows cottonwoods to successful establish in abandoned channels. I suggest that lack of understory recruitment along the active channel may have more to do with the fact that vegetated areas are typically higher and drier as a result of biogeomorphic feedbacks.

Based on current theory and previous empirical evidence, it was considered likely that cottonwood establishment would be limited to the period immediately following channel abandonment, when the abandoned channel retains elements of physical dynamism to which the species is well adapted. However, my experimental evidence of better competitive ability and more plastic shade-tolerance, particularly under conditions of high soil moisture, suggested that cottonwood establishment in abandoned channels may be supported for a much longer window of time. On the Sacramento River, California, I used a chronosequence (space-for-time) approach to understand patterns of cottonwood establishment as a function of time since abandonment and biogeomorphic stage (Chapter 3). I examined patterns in overstory community composition and cottonwood diameter size distribution as indicators of past establishment dynamics. I used tree ring analysis to sample the age structure and determine establishment timing. I addressed the main sources of error in the use of tree ring analysis for determining establishment age by cross-dating tree cores, and developing and applying correction-factors for cores potentially missing the earliest years of growth. I also quantified the uncertainty around my correction-factors using a Monte Carlo simulation approach, and propagated the uncertainty through my analyses. My results support a recruitment window that begins at channel abandonment, and consistently lasts ~ 20 years, regardless of site age. Thus, while channel abandonment is episodic, a cohort of trees always successfully establishes, and cohorts can continue to successfully establish for a period of approximately two decades. The duration of the recruitment window extends in time the spatial refuge provided by abandoned channels, and thus helps ensure continued persistence of the cottonwood population.

Climate change poses a profound risk to the functioning of forested ecosystems and past forest management approaches may no longer be appropriate for future forests. As trees vary in their vulnerability to climate change, it is essential to identify the most at risk species for conservation and refine management decisions for resistant tree species. In addition to managing for individual tree species, incorporating adaptive forest management approaches is essential for maintaining future forests. Over three chapters of my dissertation, I use long-term forest inventory data from different silvicultural experiments in the Sierra Nevada mixed conifer forest to evaluate potential management strategies for a changing future. My dissertation investigates three main questions: 1) how does planting density shape the trade-off between individual growth (maximize timber production) and stand-level productivity (maximize carbon sequestration) of giant sequoia, a climate vulnerable species? 2) how does herbivore protection and planting density impact the early survival and growth of incense-cedar, a climate resilient species? And 3) how does an operational femelschlag harvest affect the growth dynamics of Sierra Nevada mixed conifer tree species growing along gap edges? In chapter 1, I demonstrate the potential for incorporating giant sequoia into working forests to achieve different objectives, as they are able to produce merchantable timber at a young age and sequester large amounts of carbon in a relatively short period. In Chapter 2, I show that herbivore protection greatly increases the survival of young incense-cedar. Incense-cedar demonstrates the expected tradeoff between individual tree size and stand production, where narrow spacings yield smaller trees and higher stand-level production and wide spacings yield larger trees and lower stand-level production. Results from chapter 3 show that all mixed-conifer species may be successfully grown along the edges of group selections and most species will exhibit increased height and diameter growth after group expansion. Collectively, these three chapters present information necessary for evaluating forest management decisions to create a resilient future forest.

In the course of its long life, a tree confronts environmental conditions that range from natural variation in local weather or regional climate to large scale alteration of the earth’s atmosphere. Forest ecosystems are modified and potentially degraded by an array of anthropogenic enterprises, not the least of which is air pollution. Environmental change can alter ecosystem patterns and processes, particularly when effects accumulate over the long term or multiple factors interact. My dissertation research examines two key aspects of forest ecosystem dynamics in response to altered environmental conditions over the long term. First, I examine mortality, and in particular standing dead trees, one of the predominant physical consequences of forest ecosystem stress. This work quantifies the decay patterns of six common species of California’s mixed conifer forests, revealing the role of standing dead trees in forest carbon budgets. Next, my research examines influences on the growth and vitality of live trees in the southern Sierra Nevada, a forested region impacted by chronic ozone pollution. This work encompasses the regional patterns of ecosystem exposure to ozone pollution, long term monitoring of ozone-induced injury to ponderosa and Jeffrey pine trees (Pinus ponderosa and Pinus Jeffreyi), and a description of tree growth responses to pollution in light of their simultaneous responses to climate.

Forest mortality is always an important part of ecosystem processes, but in recent years, elevated mortality rates have increased the relative abundance of dead trees in forests across the Western United States. Though the importance of woody debris to ecosystem processes is clear, the structural and biogeochemical contributions of standing dead trees remain largely unknown. The first chapter of my dissertation characterizes the decay patterns and carbon density of standing dead trees in Sierra Nevada mixed conifer forests, examining traits in six dominant species. I used a dimensional analysis to describe the patterns of wood density, carbon concentration, and net carbon density. As decay class advanced, trees showed a progressively lower density and a small increase in carbon concentration. Net carbon density of the most decayed standing dead trees was only 60% that of live trees. The key characteristics that determined these patterns were species, surface to volume ratio, and relative position within each tree. Decay while standing and estimation of deadwood biomass in large scale inventories also have repercussions in greenhouse gas accounting. When the measured changes in carbon density were applied to standing dead carbon stock estimates for California mixed conifer forests, the decay-adjusted estimates were 18% (3.66-3.74 teragrams) lower than estimates that did not incorporate change due to decay.

In the second and third chapters, I focus on anthropogenic ozone pollution, a major stressor in southern Sierra Nevada forests. Ozone poses a risk to ecosystems worldwide because of its damaging effects on plant tissues and the carbon fixation they carry out. Ozone is a secondary pollutant formed by the reaction of nitrogen oxides and oxygen in the presence of sunlight and heat. Elevated tropospheric ozone has impacted parts of southern California, the San Joaquin Valley, and the southern Sierra Nevada for more than 40 years. This field-based research relies on data collected in Sequoia and Kings Canyon National Parks and on the Sierra National Forest.

Chapter two investigates the connections between ozone exposure and injury to trees. The tools of this study were a long term air quality monitoring network across a regional gradient of ozone concentration and repeat measures of pollution injury in ponderosa and Jeffrey pines. I used these measures to quantify trends in ozone concentration, assess patterns in ozone-caused foliar injury, and understand tree demographic responses to ozone exposure. Since region-wide observations began in 1991, air quality has improved, but across much of the mixed conifer forest, ozone exposure is still high enough to cause permanent damage to ecosystems. Chlorotic mottle, the key symptom of pollution injury in ponderosa and Jeffrey pines, continues to provide evidence of physiological impacts to trees but has also incrementally declined in recent years. Because growth is a leading indicator of tree vitality and forest ecosystem condition, in this study I also remeasured tree diameters to determine the long term relative growth rates of individuals exposed to ozone pollution. Relative to asymptomatic trees, typical ozone-injured trees from the most polluted sites had growth reduced by up to 24%. Over the 20-year study survival of damaged trees was lowest at high pollution levels, but within the range of rates in similar forests. The pollution-injured pines that make up southern Sierra Nevada forests today clearly have the capacity for recovery, but will continue to bear a legacy of anthropogenic impacts.

In the third chapter, I examine how Sierra Nevada forest ecosystems respond to climatic conditions and chronic ozone pollution, both individually and interactively. The gradient of pollution exposure on the western slope of the southern Sierra Nevada enabled a comparison of annual tree growth under very low to severe summer ozone levels, across sites with shared climatic conditions. I used the Jeffrey pine tree ring record to characterize growth as shaped by these conditions. First, I found that the temperature and precipitation of the preceding winter and summer have an important influence on annual growth. Building on this understanding of climatic dependency, analysis showed that trees exposed to elevated ozone had slower annual growth rates than their counterparts in relatively unpolluted locations. Annual growth rates in severely polluted sites were 8.4-23% lower than predicted growth under conditions that meet current air quality standards. Although the isolated effects of both ozone and water limitation are negative, an antagonistic interaction between these environmental factors was also apparent. As predicted in earlier research, high summer temperatures limited the negative growth impacts of ozone pollution. The likely mechanism for this interaction amongst stressors is stomatal closure, which prevents uptake of ozone into the leaf. These growth losses, attributable to a chronic anthropogenic stressor and modified by prevailing environmental conditions, may facilitate further change in forest processes.

The sustainability of the northern hardwood forest is threatened by disturbances and perturbations including chronic air pollution, invasive pests, and rare catastrophic events. Hubbard Brook Experimental Forest (HBEF) in New Hampshire is a prime example of a forest experiencing multiple environmental stressors with serious but subtle impacts. Long-term studies at HBEF have documented a decline in forest biomass accumulation that seems to be the result of reduced growth of the dominant tree species: sugar maple (Acer saccharum Marsh.) and beech (Fagus grandifolia Ehrh.). Previous studies have linked soil calcium depletion resulting from acidic deposition to reduced health in sugar maple. In addition, the spread of the exotic scale insect, Cryptococcus fagisuga Lind., that produces bark cankering has reduced growth rates in beech trees. Each of these perturbations may influence species competitive hierarchies. My dissertation focuses on teasing apart these complex competitive interactions in relation to tree growth and examines the role of chronic acid deposition and an ice storm on demographic processes that affect forest productivity. In addition, it synthesizes best practices for evaluating changes in forest dynamics through tagged-tree inventories.

In Chapter 1, I conducted a neighborhood analysis to examine the nature of competition in influencing tree growth and evaluate the dominance of species under current perturbations. A dominant competitor can be defined either in terms of its ability to suppress other individuals (competitive effect) or its ability to avoid being suppressed (competitive response). Using neighborhood models, I quantified the species-specific competitive effects and responses to determine the competitive hierarchy of species in their respective communities (northern hardwood, hemlock, and fir-birch). I predicted late-successional tree species to be at the top of the competitive hierarchy. I used spatially-explicit demography plots, growth rings as a measure of tree growth, and likelihood methods to parameterize and compare a variety of growth models with various neighborhood sizes. These models made different assumptions about the effect of competing neighbors: no competitive effects (i.e., the null model), species-equivalent competitive effects, and species-specific competitive effects. The results demonstrate that the radii of tree neighborhoods varied from 4 to 22 m depending on the target species and community type. Competition was important in these forests and that species-composition of target tree's neighborhood clearly influenced growth in addition to simple crowding. Results from the neighborhood analysis suggest there is no evidence of competitive dominance of late-successional species sugar maple and beech but for different reasons. In the northern hardwood community, sugar maple was very sensitive to competition while beech had low predicted growth rates. In the hemlock community, both species had lower growth rates than its competitors. In contrast, mid-successional shade-intolerant yellow birch exhibited strong competitive effects on its neighbors and had only an intermediate level of sensitivity to competition. In the high elevation fir-birch community, red spruce growth experienced the greatest decline in growth from competition from neighbors, but the absolute values were still higher than for competing species. The success of mid-successional shade-intolerant species and the lack of dominance in the late-successional species suggest that the competitive hierarchy expected at HBEF has been reversed, possibly due to the impact of calcium depletion and beech bark disease.

In Chapter 2, I examined forest dynamics of HBEF in the context of the hierarchical response framework (HRF). HRF identifies a hierarchy of mechanisms leading to ecological change as ecosystems are exposed to press disturbance: individual-level responses, species-reordering, and species immigration/loss within the ecosystem. An experimental calcium amendment to watershed 1 (W1), compared to reference watershed 6 (W6), provided the opportunity to study tree response to chronic acid deposition and potential interactions with a pulse disturbance, an ice storm that occurred in 1998. First, I used a comparative demographic analysis on the paired watershed to quantify the initial individual-level response to chronic acid deposition. Next, I tracked the recovery of the forest after the ice storm to assess whether species-reordering has subsequently occurred in response to exposure to chronic acid deposition. Results from the study provided support for the first two stages of the HRF but there was no evidence of species immigration or loss at HBEF. Evidence for individual-level responses included increased sugar maple growth in response to the Ca amendment. In W6, increased beech growth and recruitment resulted in watershed-level biomass gains. The pattern suggests that strong interspecific competition between sugar maple and beech is driving forest response to disturbance, resulting in species reorganization. Moreover, the increase in beech dominance observed under chronic acid deposition was accelerated by the pulse disturbance. The implications of these results in the context of HRF are that increased pulse disturbances acting on the backdrop of a press disturbance will continue leading to species-reordering, resulting in a more heavily beech dominated forest and potential loss of sugar maple from the northern hardwood forest.

Results reported in Chapters 1 and 2 relied on measuring the demographic responses of individual trees. These tagged-tree inventories not only provide a baseline for community composition, but also insight into species-specific changes through time. In Chapter 3, I identified and summarized potential sources of error at each step of a basic tagged-tree inventory. These steps include keeping track of trees, measuring tree diameters, identifying trees to species, and determining tree vigor. Each source of error affects various demographic components and in different directions and magnitudes. I presented best practices from experiences at HBEF that will help minimize the occurrence of these errors. Recommendations for managing successful long-term tagged-tree inventory monitoring include: (1) Develop robust field procedures with solid initial training and season-long check; (2) Use available data to measure extent of error, to inform field procedures, and to make corrections to the database; (3) Consistently review practices to detect challenges and improve efficiency.

Maintaining the resilience of ecological systems in an era of global change is a priority for

management and conservation. In California, forests are currently threatened by a suite of

disturbances that include altered fire regimes, legacy effects from timber harvesting, a warming

and drying climate, chronic air pollution, and uncharacteristically severe attacks by insects and

pathogens. Managing to preserve the characteristic structure and function of California forests

under novel disturbance regimes requires a clear understanding of these forests’ historical

conditions as well as an understanding of the drivers of change in these forests. A major

challenge of managing for resilience is the lack of quantifiable metrics to assess changes in a

system’s resilience over time. This dissertation uses a multi-timescale approach that quantifies

changes in the structure and composition of California mixed-conifer forests since European

settlement and suggests a framework for measuring and monitoring forest resilience. This work

can be used to guide conservation and restoration activities with the goal of maintaining the

characteristic structure and function of forests under changing disturbance regimes.

In Chapter 1, I explore the demographic responses that have led to a reordering of species

dominance in Sierra Nevada mixed-conifer forests. California mixed-conifer forests have been

subjected to a century of fire suppression, resulting in a shift in the structure and composition of

these forests over time. Historically, a high-frequency, low-severity fire regime maintained

structurally heterogeneous forests where dominance was shared among several conifer species.

With the removal of fire from this system, forest density increased, as did the prevalence of

shade-tolerant fir species at the expense of pines. Previous work suggests that species-specific

differences in demography have contributed to a shift away from a heterogeneous, resilient forest

to a monodominant forest that is more susceptible to catastrophic loss from fire, drought, or

invasive pests or pathogens. However, these conclusions are typically derived from

extrapolations from short-term data. I use a 57-year inventory record from an old-growth mixedconifer

stand in the Plumas National Forest, CA, where fires have been excluded since the early

20th century. Using a Bayesian hierarchical modeling approach, I measure species-specific rates

of mortality, recruitment, and growth over this 57-year period. I also correlated climate trends

with demographic data to determine whether climate may be a driver of shifts in species

composition. I found that basal area, density, and aboveground carbon have increased linearly

over the 57-year period in spite of increasing temperatures, which I expected might have

negatively affected growth. The recruitment and growth rates of Pseudotsuga menziesii

(Douglas-fir) and Abies concolor (white fir) were significantly higher than the community-level

means, while the recruitment and growth rates of Pinus lambertiana (sugar pine) and Pinus

ponderosa (ponderosa pine) were significantly lower than the community-level means. Mortality

rates were similar among species. These results indicate that differences in species-specific

growth and recruitment rates are the main drivers of a shift towards a low-diversity forest system

and may potentially lead to the loss of pines from mixed-conifer forests. These results also

quantify the strong effect that fire has on the regulation of forest biomass and density in this

system.

In Chapter 2, I address the need for accurate understandings of historical forest conditions to be

used as guides when implementing management and restoration plans. Because historical Sierra-

Nevada mixed conifer forests were considered to be resilient to disturbance due to their

heterogeneous structure and function, historical conditions are often considered to be the target

state for restoration. However, multiple methods for estimating historical forest conditions are

available and these methods sometimes give conflicting results regarding the density of forests

prior to European settlement. The General Land Office (GLO) surveys of the late 19th and early

20th centuries provide data on forest structure across a broad geographic range of the western US.

Distance-based plotless density estimators (PDE) have been used previously to estimate density

from the GLO data but this approach is limited due to errors that arise when trees are not

randomly distributed. Recently, an area-based method was developed in order overcome this

limitation of distance-based PDEs. The area-based method relies on estimating the speciesspecific

Voronoi area of individual trees based on regression equations derived in contemporary

stands. This method predicts historical densities that are 2-5 times higher than previous

estimates, and the method has not been independently vetted. I applied three distance-based

PDEs (Cottam, Pollard, and Morisita) and two area-based PDEs (Delincé and mean harmonic

Voronoi density (MHVD)) in six mixed-conifer and pine-dominated stands in California, US and

Baja California Norte, Mexico. These stands ranged in density from 784-159 trees ha-1. I found

that the least biased estimate of tree density in every stand was obtained with the Morisita

estimator and the most biased was obtained with the MHVD estimator. Estimates of tree density

derived from the MHVD estimator were 1-4 times larger than the true densities. While the

concept of area-based estimators is theoretically sound, as demonstrated by the accuracy of the

Delincé estimates, the Delincé approach cannot be used with GLO data and the extension of the

approach to the MHVD estimator is flawed. The inaccuracy of the MHVD method was attributed

to two causes: (1) the use of a crown scaling factor that does not correct for the number of trees

sampled and (2) the persistent underestimate of the true VA due to a weak relationship between

tree size and VA. The results of this study suggest that estimates of historical conditions derived

from applying the MHVD method to GLO data are likely to overestimate density and that tree

size is not an accurate predictor of tree area in these open-canopy forests. I suggest caution in

using density estimates derived from the MHVD method to inform restoration and management

in Sierra Nevada mixed-conifer forests, and recommend the Morisita estimator as the least biased

of the distance-based estimators.

In Chapter 3, I address the concept of resilience as it relates to forest ecology and management

and outline a framework that can be used to determine quantifiable metrics of resilience.

Resilience is an aggregate property of ecological systems that maintains the structure, function,

and composition of the system when faced with a disturbance. The main challenge inherent in

using resilience to inform management and conservation is the multitude of definitions and

concepts that have been developed to describe the resilience of ecological systems. The

framework I develop for operationalizing resilience builds on the theoretical concept of

resilience but provides explicit metrics for measurement. In this framework, resilience is

composed of two properties: resistance to disturbance and recovery from disturbance. I outline

four dimensions of resistance and recovery that can be used to measure and monitor resilience,

including heterogeneity, complexity, quality, and reserves. I dispense with the concept of

strictly-defined alternate stable states and instead focus resilience goals on target states, which

are determined by ecological, economic, recreational, or aesthetic considerations. I also conduct

a literature review of papers which measure forest resilience to assess measurements and

analyses that can be used to quantify the four dimensions of resilience in the context of resistance

and recovery. The results of this review indicate that studies of resilience can effectively make

use of simple methods for quantification and analysis and that the most compelling studies

address both components of resilience (resistance to and recovery from disturbance) and multiple

dimensions of resilience. I then apply metrics to quantify the dimensions of resilience in three

case study systems: the Sierra Nevada mixed-conifer forest of California, the eastern hemlock

forest of the northeastern US, and the northern hardwood forest of the northeastern US. I found

that this resilience framework is limited by the fact that no single, absolute measure of resilience

can be derived. However, the framework is useful for defining baseline resilience measures and

establishing protocols for measuring relative changes in forest resilience over time.

Disturbance ecology is central to the understanding and management of Sierra Nevada mixed conifer forests (MCF). Three studies relying on field data and hierarchical statistical regression models illuminate relationships between pattern and process in this important forest type. In the first chapter, a suite of hierarchical spatial statistical models using Gaussian process spatial random effects is proposed to quantify fine-scale spatial patterns in the fuel load (biomass per unit area) of several wildland fuel components (duff, litter, fine woody debris, coarse woody debris, understory vegetation, trees, and saplings). A sampling protocol that generates spatially explicit fuel load information at a fine scale (sub-meter to tens of meters) is described and implemented in a Sierra Nevada mixed conifer forest affected by extensive mortality in the 2012-2016 drought. The statistical models are described, validated, and applied to test whether Sierra Nevada mixed conifer forests experiencing varying levels of drought mortality exhibit different fine-scale spatial patterns of wildland fuels. Model validation reveals varying performance in three tasks: 1) Making pointwise predictions of training or validation data, 2) reproducing the distribution of fine-scale (sub-meter to meter) fuel load observations, and 3) reproducing the distribution of coarse-scale (sub-hectare to hectare) mean fuel loads of the various fuel components. Models for the depth of duff, depth of litter, count of fine woody debris particles, and the size of coarse woody debris particles generally perform well in all three tasks and parameter estimates are well informed by the data. However, models for infrequent events such as the meter-scale presence of coarse woody debris, trees, or saplings do not perform well in terms of making pointwise predictions or learning from the data. There are mixed results from the models for the size of fine woody debris particles and the presence of understory vegetation. In general, forests experiencing different levels of drought mortality do not exhibit different fine-scale spatial patterns, with two exceptions. First, in the litter depths model the Gaussian process magnitude, controlling the relative strength of the spatial pattern, is greater on the low mortality plots than on the high mortality plots. Second, the Gaussian process length scale parameter for understory vegetation presence, controlling the distance at which spatial autocorrelation occurs, is higher in high mortality plots than in medium mortality plots. The sampling protocol and statistical analysis described in this chapter enable quantitative description and reproduction of the fine-scale spatial patterns of fuel loads, a prerequisite to predicting how fires will behave in fuel beds with varying fine-scale spatial properties. These models also facilitate study of the relationships between pattern and process by illuminating how parameters describing fine-scale spatial pattern vary in different contexts. In the second study, I apply similar hierarchical spatial models with Gaussian process spatial random effects to describe the spatial pattern of litter, duff, and fine woody debris both before and after three replicate prescribed fires in a Sierra Nevada mixed conifer forest. The analysis reveals that prescribed fire alters not only mean fuel loads, but also the fine-scale spatial pattern of biomass. Prescribed fire increased the relative strength of the fine-scale spatial pattern for litter and duff, 1-hour fine woody debris, and 10-hour fine woody debris. The burns decreased the length scale of the spatial pattern (the distance over which autocorrelation occurs) for litter and duff, increased it for 1-hour fuels, and did not change it for 10-hour fuels. Finally, the Gaussian process noise parameter describing very fine-scale autocorrelation increased for 1-hour fuels as a result of the prescribed burns. Changes to the fine-scale spatial pattern of litter, duff, and fine woody debris are likely to impact the behavior of future fires and the ecological function of these forests. As such, information about the effects of prescribed fire on the fine-scale spatial pattern of fuel loads is important to have a complete understanding of this crucial management practice. Finally, for my third chapter I assess how numerous stressors shape the vital rates (survival, growth, and fecundity) of sugar pine across the vast majority of its range. Sugar pine (Pinus lambertiana) is the largest Pinus species, an important timber species, and a component of several dry conifer forest types of western North America, in particular the extensive Sierra Nevada mixed conifer forest. The species faces several challenges in the Anthropocene, including a disrupted fire regime, an invasive pathogen, forest structure changes, and drought with ensuing bark beetle epidemics. Managers are concerned about the conservation outlook for sugar pine, but it is unclear where and how to best invest conservation resources. Using data from the US Forest Service’s Forest Inventory and Analysis program, I synthesize the vital rate functions by constructing an integral projection model which predicts the effects of various stressors on the asymptotic population growth rate. The asymptotic population growth rate is near or slightly below one even under undisturbed conditions, and the actual abundance (in terms of both stem density and basal area) slightly declined over the duration of the study (2001-2019). The analysis reveals that wildfire, white pine blister rust, and forest density are key drivers of the demographic rates of sugar pine across its range. Drought and site dryness had lesser, but still meaningful, effects. Fire has strong negative effects on survival, resulting in a strongly negative population trajectory on burned sites. Conversely, lower than average forest density (neighborhood basal area) results in a positive population growth rate via beneficial effects on individual growth. These results highlight the value of fire hazard mitigation, particularly where it also reduces forest density, in the conservation of this important species.

Fire has long shaped forests across the globe. Anthropogenic forces are reshaping fire regimes, leading to unprecedented forest conditions and unknown long-term consequences. Land management can help mitigate undesired effects of altered fire regimes, but effective management requires information about tree species’ responses to disturbances both historical and modern. In my dissertation, I add to a body of literature examining how novel fire patterns affect tree regeneration and whether forest management strategies can mitigate any undesired effects. I focus on mixed-conifer forests of the Sierra Nevada, where logging, fire exclusion, and climate change have shifted the fire regime from frequent, heterogenous fire to infrequent fire with greater high severity. The tree species that have long comprised these forests are not well adapted to regenerate in large, homogenous fire patches. My dissertation investigates three main questions in three chapters: 1) Can forest management prevent large fire patches and promote post-fire recovery? 2) Will the novel fire regime shift overall species composition toward firs and away from pines? 3) What is the role of post-fire shrub dynamics in determining ecological succession in novel-type fire patches? In Chapter 1, I show that strategically placed fuel reduction treatments effectively reduced fire severity and promoted recovery when burned in a wildfire. In Chapter 2, I explore the idea that the shifting fire regime may lead to regional fir enrichment. I focus on plant interactions following severe wildfire and show that shrub competition affects ponderosa pine more strongly than it affects white fir. However, simulation modeling results in Chapter 3 show that, on net, shrub neighborhood dynamics do not produce an ecological filter favoring firs, though patterns are sensitive to shrub species. These three chapters together illustrate the importance of forest patch dynamics for wildfire resistance and recovery.

My dissertation weaves together paleo-ecological data, archival records, historical evidence, and modern inventories to understand the long-term impacts of fire disturbance on forest carbon dynamics in Six Rivers National Forest, California. Over three chapters, I use my results to evaluate the consequences of management activities, namely anthropogenic manipulation of fire, on aboveground live forest biomass. In the first chapter, I present a reconstruction of forest structure and composition during the 1880s and compare it to modern forests conditions. I found that modern forests are considerably denser and increasingly favor shade-tolerant taxa, likely due to twentieth century fire suppression. In the second chapter, I focus on developing an emerging fossil pollen analysis technique as the first step in quantitative reconstruction of past vegetation biomass. By modeling the relationship between modern pollen influx and modern biomass, I demonstrated that calibrated pollen influx-biomass relationships provide a robust means to infer changes in past plant biomass. My third chapter concludes with the application of the models I developed in the previous chapter to 3000 years of pollen influx data. These models allowed me to estimate aboveground biomass in a mixed conifer forest over the late Holocene. Taking a trans-disciplinary approach in this chapter, I integrate empirical datasets about biomass and fire with Native oral history to illustrate the significant and important role that Indigenous peoples played pre-contact in shaping the forest ecosystems of northwestern California. With this dissertation, I document forest dynamics at different spatial scales over three millennia and provide a practical benchmark for land managers by indicating the scale of intervention needed to move California forests closer to their long-term historical conditions.