Imagining Land Use Futures: Applying the California Futures Model

The California Urban Futures Model (or CUF Model) is the first of a new generation of metropolitan planning models designed to help planners, elected officials, and citizen groups create and compare alternative land-use policies. This article explains how the CUF Model works and then demonstrates its use in simulating realistic alternatives for regional and subregional growth policy/planning. Part One explains the design principles and logic of the CUF Model. Part Two presents CUF Model simulation results of three alternatives for growth policy/ land-use planning alternatives for the San Franciso Bay and Sacramento areas. Part Three demonstrates the use of the CUF Model for evaluating alternative agricultural protection and zoning policies at the county, or sub-regional, level

New Economy Housing Markets: Fast and Furious - But Different?

This article explores the effects of metropolitan industrial structure on housing market outcomes. Housing prices in new economy metropolitan areas are found to be higher, peakier, and more volatile than in old economy markets. Homeownership rates are found to be lower in new economy metropolitan areas, while crowding is higher. Although the distribution of housing values, costs, and rents was more equal in new economy markets, the cause would seem to be differences in area income levels, with poorer metropolitan statistical areas having greater inequalities. Regression analysis is used to identify the contribution of traditional supply and demand factors, such as job growth, income, and residential construction, as well as new economy indicators, to housing market outcomes. Rather than being fundamentally different, new economy housing markets are found to be faster and more extreme versions of traditional housing markets

The Future of Infill Housing in California: Opportunities, Potential, and Feasibility

This article presents a methodology for using county tax assessor records and other geographic information system and secondary source data to develop realistic estimates of community, county, and statewide infill housing potential in California. We first identify the number, acreage, average size, and spatial distribution of vacant and potentially redevelopable parcels within three types of infill counting areas. We then develop a schema for determining appropriate infill housing densities based on transit service availability, local land use mix and character, and initial neighborhood densities. We use this schema to generate local, county, and statewide estimates of infill housing potential. These are then carefully evaluated in terms of their parcel size and financial feasibility, the likelihood that construction will displace existing low-income renters, and the contribution to cumulative overdevelopment. We conclude with a brief discussion of state-level policy changes that would reduce barriers to market-led infill housing construction

Current Law Review Digest Series

Series by David S. Landis, John D. O\u27Neill, Arthur A. May, Arthur M. Diamond, Norbert S. Wleklinski, and Francis J. Paulson

Current Law Review Digest Series

Series by David S. Landis, John D. O\u27Neill, Arthur A. May, Arthur M. Diamond, Norbert S. Wleklinski, and Francis J. Paulson

Surficial Redistribution of Fallout 131iodine in a Small Temperate Catchment

Isotopes of iodine play significant environmental roles, including a limiting micronutrient (127I), an acute radiotoxin (131I), and a geochemical tracer (129I). But the cycling of iodine through terrestrial ecosystems is poorly understood, due to its complex environmental chemistry and low natural abundance. To better understand iodine transport and fate in a terrestrial ecosystem, we traced fallout 131iodine throughout a small temperate catchment following contamination by the 11 March 2011 failure of the Fukushima Daiichi nuclear power facility. We find that radioiodine fallout is actively and efficiently scavenged by the soil system, where it is continuously focused to surface soils over a period of weeks following deposition. Mobilization of historic (pre-Fukushima) 137cesium observed concurrently in these soils suggests that the focusing of iodine to surface soils may be biologically mediated. Atmospherically deposited iodine is subsequently redistributed from the soil system via fluvial processes in a manner analogous to that of the particle-reactive tracer 7beryllium, a consequence of the radionuclides’ shared sorption affinity for fine, particulate organic matter. These processes of surficial redistribution create iodine hotspots in the terrestrial environment where fine, particulate organic matter accumulates, and in this manner regulate the delivery of iodine nutrients and toxins alike from small catchments to larger river systems, lakes and estuaries

Assessing the effects of chemical mixtures using a Bayesian network-relative risk model (BN-RRM) integrating adverse outcome pathways (AOPs) in three Puget Sound watersheds

Chemical mixtures are difficult to assess at the individual level, but more challenging at the population level. There is still little insight of the molecular pathway for numerous chemical mixtures. We have conducted a regional-scale ecological risk assessment by evaluating the effects chemical mixtures to populations with a Bayesian Network- Relative Risk Model (BN-RRM) incorporating a molecular pathway. We used this BN-RRM framework in a case study with organophosphate pesticide (OP) mixtures (diazinon, chlorpyrifos, and malathion) in three watersheds (Lower Skagit, Nooksack, Cedar) in the state of Washington (USA). Puget Sound Chinook salmon (Oncorhynchus tshawytscha) Evolutionary Significant Units (ESU) were chosen as population endpoints. These populations are a valuable ecosystem service in the Pacific Northwest because they benefit the region as a species that provide protection of biodiversity and are spiritually and culturally treasured by the local tribes. Laetz et al. (2009, 2013) indicated that organophosphate pesticide mixtures act synergistically to salmon and impair neurological molecular activity which leads to a change in swimming behavior and mortality, which then leads to changes in population productivity. Exposure response curves were generated for OP mixtures to connect the molecular pathway. Ecological stressors from dissolved oxygen and temperature were also included in our risk analysis. Synergism within the mixtures as well as increasing temperature and decreasing dissolve oxygen content lead to increasing risk to Puget Sound Chinook salmon populations. This research demonstrates a probabilistic approach with a multiple stressor framework to estimate the effects of mixtures through a molecular pathway and predict impacts to these valuable ecosystem services

Dataset for the Incorporation of Climate Change into a Multiple Stressor Risk Assessment for the Chinook Salmon (Oncorhynchus tshawytscha) Population in the Yakima River, Washington USA

Data files available below This data set is in support of Landis et al (in press 2024). A key question in understanding the implications of climate change is how to integrate ecological risk assessments that focus on contaminants with the environmental alterations from climate projections. This article summarizes the results of integrating selected direct and indirect effects of climate change into an existing Bayesian network previously used for ecological risk assessment. The existing Bayesian network Relative Risk Model (BN-RRM) integrated the effects of organophosphate pesticides concentrations, water temperature, and dissolved oxygen levels on the Chinook salmon population in the Yakima River Basin, Washington, USA, with the endpoint being no net loss to the population described by a three patch metapopulation age structured model. Climate change-induced changes in water quality parameters (temperature and dissolved oxygen levels) were incorporated into the model based on projected climatic conditions in the 2050s and 2080s. Pesticide concentrations in the original model were modified assuming different bounding scenarios of pest control strategies in the future, as climate change may alter pest numbers and species and thus the required emission of pesticides. Our results suggest that future direct and indirect changes to the Yakima River Basin result in a high probability (62%) that the salmon population will drop below the management goal of no net loss. The key driver in salmon population risk was found to be increases in temperature levels, with pesticide concentrations playing little to no role, as indicated by the sensitivity analysis. However, indirect effects to community structure and dynamics, such as changes in the food web, were not considered. Our study demonstrates the feasibility of incorporating the direct effects of climate change and its indirect effects on chemical emissions into an integrated Bayesian network relative risk framework. It also highlights the value of using Bayesian networks for identifying key drivers of ecological risk and elucidating possible mitigation measures to avoid unacceptable changes in risk. Future research needs are also described for incorporating climate change projections into exposure-driven ecological risk assessments. The Netica file can be opened and read with the free download version of Netica available at https://www.norsys.com/netica.html. The structure of the model and the notes for each node and the conditional probability tables can then be accessed. A licensed version of Netica can run and modify the file