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Open Access Publications from the University of California

Scholarly Works (100 results)

  • Article
Frontiers of Biogeography, Volume 1, Issue 2 (2009)
    Cover page: update: Of refugia and colonization, an innovative use of biogeography for climate studiesCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    UC Davis Previously Published Works (2017)
    This study uses a scenario-based approach to ask what are the varying impacts to forest extent and biodiversity from sixteen climate change and forest conversion scenario combinations, and what do they suggest about future forest conservation policy directions? We projected these combinations onto existing forests in South Korea and grouped them into four forest categories. We used species distribution models for 1031 climate vulnerable plant species as a biodiversity index, and found that species richness loss due to forest conversion could be reduced significantly by deploying the scenarios which preserve forest areas that are climatically suitable for these species. Climate-suitable forest areas declined sharply and moved northward as future temperatures increase, and climate-suitable areas lost the highest proportion of forest extent under the current trend of forest conversion. We suggest climate refugia, defined as existing forests with suitable future climates, be protected from land use conversion as a way to preserve forest biodiversity. These spatially explicit results can be used for developing forest conservation policies, and the methods may be applicable to other forested regions. However, planners should consider the assumptions and uncertainties of climate projections, species distribution models, and land use trends when addressing forest biodiversity conservation.
      Creative Commons 'BY-NC-SA' version 4.0 license
      • Thesis
      • Peer Reviewed
      UC Davis Electronic Theses and Dissertations (2024)

      This dissertation is a three-part interconnected geographic study of fine scale soil moisture using monitoring, modeling, and remote sensing in coastal northern California. Although the focus is on hydrology and soil moisture, soil moisture naturally lends itself to be a unifying theme in physical geography connecting hydrology, agriculture, ecology, climate, wildfire, remote sensing, and humans through management actions. The objective of the three chapters is to advance the characterization and process understanding of soil-plant-water dynamics spatially and temporally and to provide high resolution soil moisture data that can be used by decision makers to improve situational awareness and planning through streamflow forecasting, landslide detection, drought warning and fire danger.In Chapter 1, monitoring data was collected in the context of a paired watershed study and soil and tree moisture probes were used to examine soil water-tree-ecosystem dynamics in Sonoma County, California. The results of this study showed: 1) there were noticeable effects on soil moisture and evapotranspiration from mechanical tree thinning and prescribed burns compared to an untreated watershed, 2) soil moisture decreased at the surface and increased in the root zone post-treatment, relative to an untreated watershed, 3) evapotranspiration decreased by 90 mm in the post treatment year for the treated watershed, 4) soil and tree moisture in situ sensors can be used as a surrogate for discrete and time consuming Live Fuel Moisture (LFM) measurements, and 5) soil moisture thresholds can be used to help identify wildfire danger and drought conditions. Improving real-time wildfire danger and drought conditions using existing or low-cost in situ sensors can improve situational awareness and planning. In Chapter 2, a novel L-band Unoccupied Aerial System (UAS) was used to map surface (0-10 cm depth) soil moisture at a high resolution in a complex, natural landscape. L-band UAS was used to map soil moisture at 5-50 meters resolution in a 3,200-acre mixed grassland-forested landscape in Sonoma County, California. The L-band dielectric constant model produced soil moisture maps with an unbiased root mean squared error (ubRMSE) of 0.07 m3/m3. A random forest machine learning model was also applied and produced surface soil moisture maps at 10-m and 30-m using optical UAS and thermal infrared (TIR) satellite data with accuracy levels of 0.020 m3/m3 and 0.017 m3/m3 ubRMSE, respectively. Improved fine-scale soil moisture maps developed using UAS-based systems may be used to help reduce fire risk and improve hydrologic models, streamflow forecasting, and early detection of landslides. In Chapter 3, high resolution root zone soil moisture, live fuel moisture, and fire danger maps were developed using machine learning, water balance, and regression models that connected the results from Chapter 1 and Chapter 2. Root zone soil moisture maps were developed using a random forest model that resulted in R2 values from 0.71 to 0.80. LFM maps were made using relationships developed in Chapter 1 and modeled soil moisture anomalies with an R2 of 0.82 compared against LFM data. The soil moisture anomaly and LFM results were applied to produce retrospective maps of fire danger that indicated predominantly medium to high fire danger during two historical fire ignition dates. An accumulated soil moisture anomaly (aSMA) showed interannual and long-term patterns and characterized an above-normal aSMA that switched to a below-normal aSMA right before the large wildfires that occurred between 2015-2020. Chapter 1 showed that root zone soil moisture was a better predictor of LFM than surface soil moisture and in Chapter 3, root zone soil moisture anomalies were shown to be an accurate predictor for LFM maps that can be useful to assess wildfire danger conditions at a high temporal and spatial scale. High resolution fire danger and LFM maps can be used to improve awareness of landscape conditions and early drought warning for decision makers.

        • Article
        • Peer Reviewed
        UC Davis Previously Published Works (2019)
        The impacts of climate change traverse administrative borders, which calls for new strategies for forest ecosystem conservation and adaptive management. Despite relatively high biodiversity, the temperate forests in East Asia have lacked a comprehensive regional evaluation of potential climate change impacts. Here, we assess the level of climate change exposure of the Temperate Broadleaf and Mixed Forests Biome of East Asia by 2070. These temperate forests occupy 18 ecoregions, five countries, and 102 provinces. We categorize climate change exposure by classifying baseline (1960–1990) climate conditions for the current geographic distribution of five temperate forest types within each ecoregion and within the biome. We then measure the level of change under four future climates: a warmer or a hotter future climate and under reduced emissions (RCP4.5) or with emissions continuing unabated (RCP8.5). By 2070, using the RCP8.5 emission scenario, 24.5–65.7% of these forests enter non-analog or the most marginal 1% of baseline climate conditions. These results reveal the need for extensive transboundary governmental coordination, including forest preservation actions among 51 of 54 provinces that will retain some forest locations in climatically stable or low-risk conditions. Furthermore, among 96 provinces with forests that will be highly exposed, 90 will require transboundary climate change adaptation strategies because these forests span their borders, including the border areas of China, the Russian Federation, and North Korea. The analytical approach of this study could serve as a template for supporting transboundary institutional coordination to address climate change.
          Creative Commons 'BY-NC-SA' version 4.0 license
          • Article
          • Peer Reviewed
          UC Davis Previously Published Works (2019)
          Governance of large cities requires local planning and administration, and most cities contain nested levels of government. There are challenges for coordinating urban planning and development among these local governments, which lead to the need to assess regional or city-wide contexts that can be used by smaller administrative units. Urban metabolism treats a city as a system within which the movement of resources can be estimated. In this study, we employed an urban metabolism approach to estimate the permeability of open space within an entire megacity, Seoul, the capital of South Korea. We provide district-level relative permeability scores for the 25 district governments to use in assessments and incentivize cooperation to improve the city’s overall open space connectivity. We analyzed the relative level of open space of 69 classes using Seoul’s land use map, and used Omniscape, a modeling tool that charts the level of suitability and resistance of every grid cell to every other grid cell using a moving window. This is an omnidirectional continuous approach that does not require open space “cores” or least-cost “paths”. We modeled two scenarios, one where open water is a barrier and contributes little to open space, and the other where open water is considered an attractive element to open space. We used the modeled outputs to define five levels of permeability and then compared the relative permeability scores for the 25 districts. Five districts had over 30% of their area in the lowest level, and eight of the 10 largest impermeable areas spanned across districts under water suitable scenario. The comparable metrics permit intra-district assessments to improve open space access, but also expect creative approaches to overcome issues including limited availability for open spaces.
            Creative Commons 'BY-NC-SA' version 4.0 license
            • Article
            • Peer Reviewed
            Information Center for the Environment Publications (2014)
              Cover page: The state of the valley report: an overview of the characteristics and trends of natural resources in the San Joaquin Valley's rural spaces, with an eye on resource sustainability for the future.Creative Commons 'BY' version 4.0 license
              • Article
              • Peer Reviewed
              UC Davis Previously Published Works (2021)
              The spatial patterns of species richness can be used as indicators for conservation and restoration, but data problems, including the lack of species surveys and geographical data gaps, are obstacles to mapping species richness across large areas. Lack of species data can be overcome with remote sensing because it covers extended geographic areas and generates recurring data. We developed a Deep Learning (DL) framework using Moderate Resolution Imaging Spectroradiometer (MODIS) products and modeled potential species richness by stacking species distribution models (S-SDMs) to ask, “What are the spatial patterns of potential plant species richness across the Korean Peninsula, including inaccessible North Korea, where survey data are limited?” First, we estimated plant species richness in South Korea by combining the probability-based SDM results of 1574 species and used independent plant surveys to validate our potential species richness maps. Next, DL-based species richness models were fitted to the species richness results in South Korea, and a time-series of the normalized difference vegetation index (NDVI) and leaf area index (LAI) from MODIS. The individually developed models from South Korea were statistically tested using datasets that were not used in model training and obtained high accuracy outcomes (0.98, Pearson correlation). Finally, the proposed models were combined to estimate the richness patterns across the Korean Peninsula at a higher spatial resolution than the species survey data. From the statistical feature importance tests overall, growing season NDVI-related features were more important than LAI features for quantifying biodiversity from remote sensing time-series data.
                • Article
                • Peer Reviewed
                UC Davis Previously Published Works (2020)
                Context: Climate change adaptive management strategies for isolated habitats such as wetlands are urgently needed. Conservation areas managed for wildlife refuges can be considered a network, permitting the tracking of current climate conditions within the network under projected future climates. Objectives: We ask how many classes of temporal climate dynamics exist within a set of 48 refuges that comprise a network of conservation areas. Methods: We identified the current-climate conditions of 48 US National Wildlife Refuges using their annual average of minimum temperature and annual precipitation. We then mapped the movement of analogous climates for each refuge from current to future-time periods under four climate projections. We identified distinct types of analog climate dynamics among the network of wildlife refuges that can inform climate-adaptive natural resource planning. Results: We identified five analogous climate categories: (1) disappearing climates; (2) single-analogous climates; (3) multiple-analogous climates; (4) enduring climates; and (5) climate hubs, with some refuges occupying up to three classes. Using four climate projections, we found 10–25 refuges are climatically disappeared; 8–16 whose climate conditions appear in only one other unit; three whose current climate appears in many other refuges; three that are climatically stable; and four that are climate hubs. Conclusions: The relative geographic isolation of refuges makes them particularly appropriate for use as nodes in a network-based climate assessment. The climate classification of the nodes can help inform selection from among multiple refuge management strategies based on their relative analogous climate dynamics. For example, new refuges could be identified to account for species inhabiting climatically disappearing refuges.
                  • Article
                  • Peer Reviewed
                  Information Center for the Environment Publications (2012)
                  This paper documents the development of land use models that represent different urban growth policy scenarios for California, a contribution to the Public Interest Energy Research (PIER) Climate Vulnerability and Assessment Project of 2010–2011. The research team produced six UPlan model runs that portray the following policies as footprint scenarios to 2050: Business as Usual, Smart Growth, Fire Adaptation, Infill, Conservation of Projected Connectivity for Plant Movement under Climate Change, and Conservation of Vulnerable Agricultural Lands. This paper compares the outputs from these six scenarios on outputs from three other PIER vulnerability studies: biodiversity, fire return interval, and agricultural sensitivity. While not directly targeting any conservation or agricultural objective, the Infill scenario preserved more open space for other use than any of the other scenarios. The results suggest that combining Infill objectives with other open space goals will produce better conservation goals for those objectives than merely directing growth away from landscape elements of conservation interest.
                    Cover page: Urban Growth in California: Projecting growth in California (2000-2050) under six alternative policy scenarios and assessing impacts to future dispersal corridors, fire threats and climate-sensitive agriculture.Urban Growth in California: Projecting Growth in California (2000-2050) under six alternative policy scenarios and assessing impacts to future dispersal corridors, fire threats and climate-sensitive agriculture.Creative Commons 'BY' version 4.0 license
                    • Article
                    • Peer Reviewed
                    Information Center for the Environment Publications (2010)
                    The Big Sur Land Trust contracted Connectivity for Wildlife LLC (CFW), a wildlife research organization, to conduct a wildlife connectivity study in the Central Coast of California. Using extensive field work combined with Geographic Information System (GIS) modeling CFW documents species presence and ground-truths habitat suitability models to better understand wildlife movement patterns and identify lands and waterways that provide important connectivity between core habitat areas for wildlife between Central Coast mountain ranges including the Sierra de Salinas, Santa Lucia, Santa Cruz and Gabilan mountains. Data was collected by camera trap stations, wildlife track and sign surveys and documented road-kill incidents. Results may be used to inform the Land Trust’s conservation initiatives, stewardship and education programs and to aid policy makers and planners in developing compensatory mitigation and infrastructure design considerations that protect and enhance critical wildlife linkages throughout California’s Central Coast.This study began in October 2008 and is ongoing. This report discusses data collected from a monitoring period of October 2008 through December 2009 and focused on the Highway 68 corridor and the area around Marks Ranch, Toro Park, and Fort Ord Natural Reserve – protected lands that sit at the north end of the Sierra de Salinas Mountains and level off to the north into the grassland, maritime chaparral, oak woodland, coastal scrub and dune habitats of the coastal plain along the southern end of the Monterey Bay. Understanding wildlife movement in this region is a priority for The Big Sur Land Trust because of the organization’s investment in Marks Ranch and conservation initiatives within the Sierra de Salinas Mountain Range. Highway 68 separates Marks Ranch and Toro Park from the Fort Ord Natural Reserve. El Toro Creek passes under a bridge on Highway 68 providing safe passage and habitat for wildlife moving between the uplands of the Sierra de Salinas and the lowland habitats toward Monterey Bay.A total of 404 individual detections were recorded using riparian habitat and safe passage afforded by the creek and bridge. Results of this portion of the study conclude that this region facilitates a high degree of wildlife movement. The data collected to date, combined with aerial imagery, habitat suitability models and other GIS tools graphically demonstrate that the narrow undeveloped gap that exists between the relatively dense housing along San Benancio Road and Toro Park Estates serves as an active linkage for animals moving between the uplands of the Sierra de Salinas mountains and the lowland, dune and other suitable coastal habitats of the Fort Ord Reserve and the shores of the Monterey Bay National Marine Sanctuary. Policy makers and planners seeking to sustain connectivity and minimize negative impacts on wildlife populations in this region should consider development configurations that accommodate existing movement paths for wildlife. Any proposed and future development in these relatively intact natural lands without primary regard for wildlife, their habitat requirements and movement patterns could effectively and completely isolate populations and individuals of such sensitive and large ranging species as the North American badger and mountain lion. The isolation of these populations could lead to their local extinction in otherwise viable lowland and coastal habitats along the southern portion of Monterey Bay.
                      Cover page: The Central Coast Connectivity Project, Northern Monterey County Linkages: Report on the Mount Toro to Fort Ord Reserve Study 2008-2009Creative Commons 'BY' version 4.0 license
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