UC Berkeley

Global changes in climate and increased anthropogenic activity are fundamentally reshaping the structure and function of ecosystems across scales. The velocity, scale, and intensity of human impact are irrefutable, yet quantifying the effects of anthropogenic activities in relation to natural ecosystem dynamics can be difficult. Understanding the interaction between human activities and landscape change is of paramount importance, especially as anthropogenic driven land cover conversion and disturbances threaten ecosystem biodiversity and natural resources. Our approaches to natural resource management are challenged when environmental outcomes are embedded in complex socio-ecological systems characterized by profound uncertainties and interactive. Interdisciplinary approaches are thus needed to adequately address contemporary environmental problems and evaluate interactions between biophysical and socio-ecological drivers of change.

The research presented in this dissertation has two broad research foci. First, I explore the linkages between human activity and landscape change in the context of California forests and woodlands. I draw on historical and contemporary forest inventory data and investigate more than a century of landscape transformations in California to understand the drivers of change that influence today’s landscape. By studying the changes in forest and woodland distribution and structure across California, I review the often under-evaluated broad scale influence of socio-ecological factors such as land ownership and land management in contributing to forest densification and landscape change. Second, my work contributes to the discussion of technical issues of data availability and data aggregation when historical data are used in modern ecological analysis and combined with contemporary data. My research links historical and contemporary empirical data through data science approaches in data digitization, data aggregation, data sharing, spatial modeling, and species distribution modeling in order to increase the scope and potential of historical data to answer complex environmental problems. At the core of this work is one valuable and recently digitized historical ecological data collection: the California Vegetation Type Mapping (VTM) Project.

My second chapter is motivated by several recent studies that report climate (i.e. climate water deficit (CWD)) as the primary mechanism of large tree decline and change in forest structure in California in the 20th century. Reflecting on these studies and other conflicting opinions of primary drivers of change, I found very few studies that quantify the impact of land ownership and land management on the quantities of large trees and other characteristics of forest structure. Land ownership has been used to understand the long-term effects of and variation in land management practices; especially when spatially explicit data on management practices are unavailable or incomplete. Thus, in Chapter Two, I explicitly investigate 20th-century changes in forest structure across six ownership classes in California. In comparing historical and contemporary forest structural data I found that declines in large trees and increases in small tree density were consistent across the state, irrespective of ownership boundaries. However, there were important differences in the magnitude of this change. In particular, this pattern is most pronounced on private timberlands which experience up to 400% regional increases in small tree density since 1930. Nearly all land ownership classes experience declines in large trees, however, private timberland and National Park/Wilderness areas experience a significant reduction of 83% and 73% respectively.

In Chapter Three, I investigate the effects of urban development on changes to the distribution of oak species in California. First, by modeling historical patterns of richness for eight oak species using historical map and plot data from the California Vegetation Type Mapping (VTM) collection I examine spatial intersections between hot spots of historical oak richness and modern urban and conservation land. I found that impacts from development and conservation vary by both species and richness. At the state level, the impact of urban development on oaks has been small within the areas of the highest oak richness but areas of high oak richness are also poorly conserved.

In the first two chapters, I discuss the relationship between social and biophysical drivers of landscape change. This kind of understanding of long-term patterns of change requires data availability and the ability to re-use data. Following from these, Chapter 4 discusses preserving history's place in the growing data landscape, I review three approaches to sharing historical data from field stations using principles from data science. To encourage greater use of historical data across scientific disciplines it is vital to make data findable, accessible, interoperable, and reusable (e.g. the FAIR principles). This summary of three important data collections emerging from the University of California showcase the potential for their use in research and encourages similar ventures that use common archival, geospatial, and data science practices to shepherd historical data out of file drawers and into the contemporary digital data landscape.