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With the widespread use of collaborative governance mechanisms for mitigating water pollution, an opportunity exists to test alternative institutional designs based on collaborative governance theory using computer simulation models, particularly when there is a clear relationship between governance networks, observable resource allocation decisions, and measurable outcomes. This is especially the case for wicked problems like nonpoint source water pollution where there are compelling questions regarding how best to design policies, allocate funds, and build administrative capacity to meet water quality standards. We present an agent-based model (ABM) of water governance for the Lake Champlain Basin to simulate the impacts of alternative collaborative governance arrangements on the development of suites of water quality projects. The ABM is connected or coupled with land use and phosphorus load accumulation models that are informed by existing hydrologic models, project datasets, and state-set load reduction targets. We find that regionally arranged collaborative governance in water quality project planning and implementation can lead to better water quality outcomes, thereby affirming one of the central premises of collaborative governance regime theory. We also find that externally mandated collaboration, as opposed to voluntary, self-initiated collaboration, can lead to better water quality outcomes, adding to our understanding of which type of collaborative governance arrangement is best suited to the specific contexts of this case. Further, without adequate administrative capacity in the form of human resources located in central network actors to manage project funds, “administrative bottlenecks” may form and money can go unspent. This research demonstrates the efficacy of using simulations of alternative institutional design for theory testing and tuning, and policy prototyping.

BACKGROUND: School vaccination rates in California have fallen as more parents opt for personal belief exemptions (PBEs) for their children. Our goals were to (1) spatially analyze PBE patterns over time, (2) determine correlates of PBEs, and (3) examine their spatial overlap with personal medical exemptions (PMEs).METHODS: PBE and PME data for California kindergarten classes from the 2001/2002 to 2013/2014 school years were matched to the locations of schools. Nonspatial clustering algorithms were implemented to group 5147 schools according to their trends in PBE percentages among kindergartners. Cluster assignments were mapped and hotspot analysis was performed to find areas in California where schools sharing trends in PBEs over time were colocated. Schools were further associated both with school-level data on minority enrollment and free and reduced price lunch participation and with charter/private and rural/urban status. Spatial regression was implemented to determine which school-level variables were correlated with PBE rates in the 2013/2014 school year.RESULTS: Distinct spatial patterns are observed in California when PBE cluster assignments are mapped. Results indicate that schools belonging to the "high PBE" cluster are spatially buffered from those in "low PBE" areas by "medium PBE" schools. Further, PBE rates are positively associated with the percentage of white students, charter status, and private schools.CONCLUSIONS: Hotspots of high PBE schools are in some cases colocated with schools that have elevated PME rates, prompting concern that herd immunity is diminished for school populations where students have no choice but to remain unvaccinated. WHAT'S KNOWN ON THIS SUBJECT:An increasing number of children are unvaccinated at entry into public schools, potentially endangering children who cannot be vaccinated for medical reasons and threatening herd immunity. Voluntary exemptions from immunizations vary geographically and by parental characteristics. WHAT THIS STUDY ADDS:We find that exemption behavior is highest in peripheral areas of cities and that specific types of student populations are associated with high exemption rates. Additionally, there is spatial overlap between clusters of high personal exemption and medical exemption populations. Dr Carrel conceptualized and designed the study, performed statistical and spatial analysis, and drafted the initial manuscript; Mr Bitterman developed the dataset, carried out spatial and statistical analyses, and reviewed and revised the manuscript; and both authors approved the final manuscript as submitted.www.pediatrics.org/cgi

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ABSTRACT. The resilience of a social-ecological system is measured by its ability to retain core functionality when subjected to perturbation. Resilience is contextually dependent on the state of system components, the complex interactions among these components, and the timing, location, and magnitude of perturbations. The stability landscape concept provides a useful framework for considering resilience within the specified context of a particular social-ecological system but has proven difficult to operationalize. This difficulty stems largely from the complex, multidimensional nature of the systems of interest and uncertainty in system response. Agent-based models are an effective methodology for understanding how cross-scale processes within and across social and ecological domains contribute to overall system resilience. We present the results of a stylized model of agricultural land use in a small watershed that is typical of the Midwestern United States. The spatially explicit model couples land use, biophysical models, and economic drivers with an agent-based model to explore the effects of perturbations and policy adaptations on system outcomes. By applying the coupled modeling approach within the resilience and stability landscape frameworks, we (1) estimate the sensitivity of the system to contextspecific perturbations, (2) determine potential outcomes of those perturbations, (3) identify possible alternative states within state space, (4) evaluate the resilience of system states, and (5) characterize changes in system-scale resilience brought on by changes in individual land use decisions.

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With mounting scientific evidence demonstrating adverse global climate change (GCC) impacts to water quality, water quality policies, such as the Total Maximum Daily Loads (TMDLs) under the U.S. Clean Water Act, have begun accounting for GCC effects in setting nutrient load‐reduction policy targets. These targets generally require nutrient reductions for attaining prescribed water quality standards (WQS) by setting safe levels of nutrient concentrations that curtail potentially harmful cyanobacteria blooms (CyanoHABs). While some governments require WQS to consider climate change, few tools are available to model the complex interactions between climate change and benthic legacy nutrients. We present a novel process‐based integrated assessment model (IAM) that examines the extent to which synergistic relationships between GCC and legacy Phosphorus release could compromise the ability of water quality policies to attain established WQS. The IAM is calibrated for simulating the eutrophic Missisquoi Bay and watershed in Lake Champlain (2001–2050). Water quality impacts of seven P‐reduction scenarios, including the 64.3% reduction specified under the current TMDL, were examined under 17 GCC scenarios. The TMDL WQS of 0.025 mg/L total phosphorus is unlikely to be met by 2035 under the mandated 64.3% reduction for all GCC scenarios. IAM simulations show that the frequency and severity of summer CyanoHABs increased or minimally decreased under most climate and nutrient reduction scenarios. By harnessing IAMs that couple complex process‐based simulation models, the management of water quality in freshwater lakes can become more adaptive through explicit accounting of GCC effects on both the external and internal sources of nutrients.

The role of household meat handling and consumption in the transfer of Staphylococcus aureus (S. aureus) from livestock to consumers is not well understood. Examining the similarity of S. aureus colonizing humans and S. aureus in meat from the stores in which those individuals shop can provide insight into the role of meat in human S. aureus colonization. S. aureus isolates were collected from individuals in rural and urban communities in Iowa (n = 3347) and contemporaneously from meat products in stores where participants report purchasing meat (n = 913). The staphylococcal protein A (spa) gene was sequenced for all isolates to determine a spa type. Morisita indices and Permutational Multivariate Analysis of Variance Using Distance Matrices (PERMANOVA) were used to determine the relationship between spa type composition among human samples and meat samples. spa type composition was significantly different between households and meat sampled from their associated grocery stores. spa types found in meat were not significantly different regardless of the store or county in which they were sampled. spa types in people also exhibit high similarity regardless of residential location in urban or rural counties. Such findings suggest meat is not an important source of S. aureus colonization in shoppers.