No abstract

Increasing pressures from land use coupled with future changes in climate will present unique challenges for California's protected areas. We assessed the potential for future land use conversion on land surrounding existing protected areas in California's twelve ecoregions, utilizing annual, spatially explicit (250 m) scenario projections of land use for 2006-2100 based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios to examine future changes in development, agriculture, and logging. We calculated a conversion threat index (CTI) for each unprotected pixel, combining land use conversion potential with proximity to protected area boundaries, in order to identify ecoregions and protected areas at greatest potential risk of proximal land conversion. Our results indicate that California's Coast Range ecoregion had the highest CTI with competition for extractive logging placing the greatest demand on land in close proximity to existing protected areas. For more permanent land use conversions into agriculture and developed uses, our CTI results indicate that protected areas in the Central California Valley and Oak Woodlands are most vulnerable. Overall, the Eastern Cascades, Central California Valley, and Oak Woodlands ecoregions had the lowest areal percent of protected lands and highest conversion threat values. With limited resources and time, rapid, landscape-level analysis of potential land use threats can help quickly identify areas with higher conversion probability of future land use and potential changes to both habitat and potential ecosystem reserves. Given the broad range of future uncertainties, LULC projections are a useful tool allowing land managers to visualize alternative landscape futures, improve planning, and optimize management practices.

This paper describes a new method of population synthesis that includes land use information. The method is based on an initial identification of suitable land use summaries to build a spatial taxonomy at any spatial scale. This same taxonomy is then used to classify household travel survey records (persons and households) and in parallel geographic subdivisions for the state of California. This land use information is the added dimension in the population synthesis methods for travel demand analysis. Synthetic population generation proceeds by expanding (re-creating) the records of the households responding to the survey and the entire array of travel behavior data reproduced for the synthetic population. The basis for selecting the variables to use in the synthetic population is first testing their significance in simplified specification in models of travel behavior that include land use as an explanatory variable and account for the shape of behavioral data (e.g., observations with no travel). The paper shows differences between synthetic populations with and without land use data to demonstrate the behavioral realism added by this approach.

No abstract

A new method of sequence analysis to measure fragmentation in activity participation is presented in this paper. We applied this method to a sample of residents in the Central Coast of California that participated in the California Household Travel Survey in 2012–2013. This method explores sequences of daily activity and travel employing techniques from the sequencing of events in the life course of individuals. Studying sequences of daily episodes (each activity and each trip) is preferable to other techniques of studying activity-travel behavior because sequences include the entire trajectory of a person’s activity during a day while at the same time considering the number of activities, order of activities in a day, and their durations jointly. We found substantial fragmentation in activity participation among persons with children and in specific age groups (25–65) amplified by the presence of children in the household. We also found poverty plays an important inhibiting role. Examinations of the days of the week showed significant and substantial differences among the days with both Sundays and Saturdays being distinct, but also substantial differences among the weekdays. The paper provides details about this new technique and the statistical analysis of fragmentation. It also provides a discussion about future steps.