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

Author(s): Levine, Carrie Levine | Advisor(s): Battles, John J | Abstract: Maintaining the resilience of ecological systems in an era of global change is a priority formanagement and conservation. In California, forests are currently threatened by a suite ofdisturbances that include altered fire regimes, legacy effects from timber harvesting, a warmingand drying climate, chronic air pollution, and uncharacteristically severe attacks by insects andpathogens. Managing to preserve the characteristic structure and function of California forestsunder novel disturbance regimes requires a clear understanding of these forests’ historicalconditions as well as an understanding of the drivers of change in these forests. A majorchallenge of managing for resilience is the lack of quantifiable metrics to assess changes in asystem’s resilience over time. This dissertation uses a multi-timescale approach that quantifieschanges in the structure and composition of California mixed-conifer forests since Europeansettlement and suggests a framework for measuring and monitoring forest resilience. This workcan be used to guide conservation and restoration activities with the goal of maintaining thecharacteristic structure and function of forests under changing disturbance regimes.In Chapter 1, I explore the demographic responses that have led to a reordering of speciesdominance in Sierra Nevada mixed-conifer forests. California mixed-conifer forests have beensubjected to a century of fire suppression, resulting in a shift in the structure and composition ofthese forests over time. Historically, a high-frequency, low-severity fire regime maintainedstructurally 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 ofshade-tolerant fir species at the expense of pines. Previous work suggests that species-specificdifferences in demography have contributed to a shift away from a heterogeneous, resilient forestto a monodominant forest that is more susceptible to catastrophic loss from fire, drought, orinvasive pests or pathogens. However, these conclusions are typically derived fromextrapolations from short-term data. I use a 57-year inventory record from an old-growth mixedconiferstand in the Plumas National Forest, CA, where fires have been excluded since the early20th century. Using a Bayesian hierarchical modeling approach, I measure species-specific ratesof mortality, recruitment, and growth over this 57-year period. I also correlated climate trendswith demographic data to determine whether climate may be a driver of shifts in speciescomposition. I found that basal area, density, and aboveground carbon have increased linearlyover 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-levelmeans, while the recruitment and growth rates of Pinus lambertiana (sugar pine) and Pinusponderosa (ponderosa pine) were significantly lower than the community-level means. Mortalityrates were similar among species. These results indicate that differences in species-specificgrowth and recruitment rates are the main drivers of a shift towards a low-diversity forest systemand may potentially lead to the loss of pines from mixed-conifer forests. These results alsoquantify the strong effect that fire has on the regulation of forest biomass and density in thissystem.In Chapter 2, I address the need for accurate understandings of historical forest conditions to beused as guides when implementing management and restoration plans. Because historical Sierra-Nevada mixed conifer forests were considered to be resilient to disturbance due to theirheterogeneous structure and function, historical conditions are often considered to be the targetstate for restoration. However, multiple methods for estimating historical forest conditions areavailable and these methods sometimes give conflicting results regarding the density of forestsprior to European settlement. The General Land Office (GLO) surveys of the late 19th and early20th 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 densityfrom the GLO data but this approach is limited due to errors that arise when trees are notrandomly distributed. Recently, an area-based method was developed in order overcome thislimitation of distance-based PDEs. The area-based method relies on estimating the speciesspecificVoronoi area of individual trees based on regression equations derived in contemporarystands. This method predicts historical densities that are 2-5 times higher than previousestimates, and the method has not been independently vetted. I applied three distance-basedPDEs (Cottam, Pollard, and Morisita) and two area-based PDEs (Delince and mean harmonicVoronoi density (MHVD)) in six mixed-conifer and pine-dominated stands in California, US andBaja California Norte, Mexico. These stands ranged in density from 784-159 trees ha-1. I foundthat the least biased estimate of tree density in every stand was obtained with the Morisitaestimator and the most biased was obtained with the MHVD estimator. Estimates of tree densityderived from the MHVD estimator were 1-4 times larger than the true densities. While theconcept of area-based estimators is theoretically sound, as demonstrated by the accuracy of theDelince estimates, the Delince approach cannot be used with GLO data and the extension of theapproach to the MHVD estimator is flawed. The inaccuracy of the MHVD method was attributedto two causes: (1) the use of a crown scaling factor that does not correct for the number of treessampled and (2) the persistent underestimate of the true VA due to a weak relationship betweentree size and VA. The results of this study suggest that estimates of historical conditions derivedfrom applying the MHVD method to GLO data are likely to overestimate density and that treesize is not an accurate predictor of tree area in these open-canopy forests. I suggest caution inusing density estimates derived from the MHVD method to inform restoration and managementin Sierra Nevada mixed-conifer forests, and recommend the Morisita estimator as the least biasedof the distance-based estimators.In Chapter 3, I address the concept of resilience as it relates to forest ecology and managementand 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 inusing resilience to inform management and conservation is the multitude of definitions andconcepts that have been developed to describe the resilience of ecological systems. Theframework I develop for operationalizing resilience builds on the theoretical concept ofresilience but provides explicit metrics for measurement. In this framework, resilience iscomposed of two properties: resistance to disturbance and recovery from disturbance. I outlinefour 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 ofstrictly-defined alternate stable states and instead focus resilience goals on target states, whichare determined by ecological, economic, recreational, or aesthetic considerations. I also conducta literature review of papers which measure forest resilience to assess measurements andanalyses that can be used to quantify the four dimensions of resilience in the context of resistanceand recovery. The results of this review indicate that studies of resilience can effectively makeuse of simple methods for quantification and analysis and that the most compelling studiesaddress both components of resilience (resistance to and recovery from disturbance) and multipledimensions of resilience. I then apply metrics to quantify the dimensions of resilience in threecase study systems: the Sierra Nevada mixed-conifer forest of California, the eastern hemlockforest of the northeastern US, and the northern hardwood forest of the northeastern US. I foundthat this resilience framework is limited by the fact that no single, absolute measure of resiliencecan be derived. However, the framework is useful for defining baseline resilience measures andestablishing protocols for measuring relative changes in forest resilience over time.