Forest resilience measured: Using a multi-timescale approach to quantify forest resilience in a changing world.

Maintaining the resilience of ecological systems in an era of global change is a priority for/nmanagement and conservation. In California, forests are currently threatened by a suite of/ndisturbances that include altered fire regimes, legacy effects from timber harvesting, a warming/nand drying climate, chronic air pollution, and uncharacteristically severe attacks by insects and/npathogens. Managing to preserve the characteristic structure and function of California forests/nunder novel disturbance regimes requires a clear understanding of these forests’ historical/nconditions as well as an understanding of the drivers of change in these forests. A major/nchallenge of managing for resilience is the lack of quantifiable metrics to assess changes in a/nsystem’s resilience over time. This dissertation uses a multi-timescale approach that quantifies/nchanges in the structure and composition of California mixed-conifer forests since European/nsettlement and suggests a framework for measuring and monitoring forest resilience. This work/ncan be used to guide conservation and restoration activities with the goal of maintaining the/ncharacteristic structure and function of forests under changing disturbance regimes./nIn Chapter 1, I explore the demographic responses that have led to a reordering of species/ndominance in Sierra Nevada mixed-conifer forests. California mixed-conifer forests have been/nsubjected to a century of fire suppression, resulting in a shift in the structure and composition of/nthese forests over time. Historically, a high-frequency, low-severity fire regime maintained/nstructurally heterogeneous forests where dominance was shared among several conifer species./nWith the removal of fire from this system, forest density increased, as did the prevalence of/nshade-tolerant fir species at the expense of pines. Previous work suggests that species-specific/ndifferences in demography have contributed to a shift away from a heterogeneous, resilient forest/nto a monodominant forest that is more susceptible to catastrophic loss from fire, drought, or/ninvasive pests or pathogens. However, these conclusions are typically derived from/nextrapolations from short-term data. I use a 57-year inventory record from an old-growth mixedconifer/nstand in the Plumas National Forest, CA, where fires have been excluded since the early/n20th century. Using a Bayesian hierarchical modeling approach, I measure species-specific rates/nof mortality, recruitment, and growth over this 57-year period. I also correlated climate trends/nwith demographic data to determine whether climate may be a driver of shifts in species/ncomposition. I found that basal area, density, and aboveground carbon have increased linearly/nover the 57-year period in spite of increasing temperatures, which I expected might have/nnegatively affected growth. The recruitment and growth rates of Pseudotsuga menziesii/n(Douglas-fir) and Abies concolor (white fir) were significantly higher than the community-level/nmeans, while the recruitment and growth rates of Pinus lambertiana (sugar pine) and Pinus/nponderosa (ponderosa pine) were significantly lower than the community-level means. Mortality/nrates were similar among species. These results indicate that differences in species-specific/ngrowth and recruitment rates are the main drivers of a shift towards a low-diversity forest system/nand may potentially lead to the loss of pines from mixed-conifer forests. These results also/nquantify the strong effect that fire has on the regulation of forest biomass and density in this/nsystem./nIn Chapter 2, I address the need for accurate understandings of historical forest conditions to be/nused as guides when implementing management and restoration plans. Because historical Sierra-/nNevada mixed conifer forests were considered to be resilient to disturbance due to their/nheterogeneous structure and function, historical conditions are often considered to be the target/nstate for restoration. However, multiple methods for estimating historical forest conditions are/navailable and these methods sometimes give conflicting results regarding the density of forests/nprior to European settlement. The General Land Office (GLO) surveys of the late 19th and early/n20th centuries provide data on forest structure across a broad geographic range of the western US./nDistance-based plotless density estimators (PDE) have been used previously to estimate density/nfrom the GLO data but this approach is limited due to errors that arise when trees are not/nrandomly distributed. Recently, an area-based method was developed in order overcome this/nlimitation of distance-based PDEs. The area-based method relies on estimating the speciesspecific/nVoronoi area of individual trees based on regression equations derived in contemporary/nstands. This method predicts historical densities that are 2-5 times higher than previous/nestimates, and the method has not been independently vetted. I applied three distance-based/nPDEs (Cottam, Pollard, and Morisita) and two area-based PDEs (Delincé and mean harmonic/nVoronoi density (MHVD)) in six mixed-conifer and pine-dominated stands in California, US and/nBaja California Norte, Mexico. These stands ranged in density from 784-159 trees ha-1. I found/nthat the least biased estimate of tree density in every stand was obtained with the Morisita/nestimator and the most biased was obtained with the MHVD estimator. Estimates of tree density/nderived from the MHVD estimator were 1-4 times larger than the true densities. While the/nconcept of area-based estimators is theoretically sound, as demonstrated by the accuracy of the/nDelincé estimates, the Delincé approach cannot be used with GLO data and the extension of the/napproach to the MHVD estimator is flawed. The inaccuracy of the MHVD method was attributed/nto two causes: (1) the use of a crown scaling factor that does not correct for the number of trees/nsampled and (2) the persistent underestimate of the true VA due to a weak relationship between/ntree size and VA. The results of this study suggest that estimates of historical conditions derived/nfrom applying the MHVD method to GLO data are likely to overestimate density and that tree/nsize is not an accurate predictor of tree area in these open-canopy forests. I suggest caution in/nusing density estimates derived from the MHVD method to inform restoration and management/nin Sierra Nevada mixed-conifer forests, and recommend the Morisita estimator as the least biased/nof the distance-based estimators./nIn Chapter 3, I address the concept of resilience as it relates to forest ecology and management/nand outline a framework that can be used to determine quantifiable metrics of resilience./nResilience is an aggregate property of ecological systems that maintains the structure, function,/nand composition of the system when faced with a disturbance. The main challenge inherent in/nusing resilience to inform management and conservation is the multitude of definitions and/nconcepts that have been developed to describe the resilience of ecological systems. The/nframework I develop for operationalizing resilience builds on the theoretical concept of/nresilience but provides explicit metrics for measurement. In this framework, resilience is/ncomposed of two properties: resistance to disturbance and recovery from disturbance. I outline/nfour dimensions of resistance and recovery that can be used to measure and monitor resilience,/nincluding heterogeneity, complexity, quality, and reserves. I dispense with the concept of/nstrictly-defined alternate stable states and instead focus resilience goals on target states, which/nare determined by ecological, economic, recreational, or aesthetic considerations. I also conduct/na literature review of papers which measure forest resilience to assess measurements and/nanalyses that can be used to quantify the four dimensions of resilience in the context of resistance/nand recovery. The results of this review indicate that studies of resilience can effectively make/nuse of simple methods for quantification and analysis and that the most compelling studies/naddress both components of resilience (resistance to and recovery from disturbance) and multiple/ndimensions of resilience. I then apply metrics to quantify the dimensions of resilience in three/ncase study systems: the Sierra Nevada mixed-conifer forest of California, the eastern hemlock/nforest of the northeastern US, and the northern hardwood forest of the northeastern US. I found/nthat this resilience framework is limited by the fact that no single, absolute measure of resilience/ncan be derived. However, the framework is useful for defining baseline resilience measures and/nestablishing protocols for measuring relative changes in forest resilience over time.

Advisor: Battles, John J