Browsing by Author "Velez, Anne-Lise K."

Now showing 1 - 6 of 6
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    Co-management during Crisis: Insights from Jurisdictionally Complex Wildfires
    Nowell, Branda; Steelman, Toddi; Velez, Anne-Lise K.; Albrecht, Kate (2022-04)
    There is a general agreement within the wildfire community that exclusively top down approaches to policy making and management are limited and that we need to build governance capacity to cooperatively manage across jurisdictional boundaries. Accordingly, the concept of co-management has grown in popularity as a theoretical lens through which to understand cross-boundary response to wildland fires. However, definitional ambiguity has led to on-going debates about what co-management is. Further, there is limited understanding about the nature of co-management during crisis events. This had led to scholars posing the question: What is co-management in the context of jurisdictionally complex wildfire? In this paper, we seek to address this question based on interviews with leaders engaged in the management of jurisdictionally complex wildfire incidents. We propose a multi-level framework that defines co-management as strategic efforts of individual actors to cooperatively manage perceived interdependencies with others through one or more formal or informal institutional arrangements. Our findings reveal different strategic orientations to co-management that have management implications. We then demonstrate the value of the proposed framework in its ability to organize a series of diagnostic questions for diagnosing co-management situations within the context of jurisdictionally complex wildfires.
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    Designing Transdisciplinarity: Exploring Institutional Barriers and Drivers of Collaborative Transdisciplinary Teaching
    Velez, Anne-Lise K.; Hall, Ralph P.; Lewis, Stephanie N. (Informa, 2021-01-01)
    Employers increasingly desire new graduates to work across boundaries, in teams, and with developed soft skills, especially in public affairs. Likewise, students increasingly seek academic experiences for learning, practicing, and honing transferable, competency-based skills. This suggests instructors should explore alternative pedagogy engaging problem definition and transdisciplinary teamwork. We describe institutional drivers and barriers to collaborative transdisciplinarity in undergraduate teaching and the structure and processes involved in developing a co-taught studio-based capstone involving public affairs students and varied other unrelated majors. We describe the structure through which the “SuperStudio” (1) combines topic concentrations with a shared policy context allowing students to apply disciplinary knowledge to define transdisciplinary problems and (2) fosters collaborative teaching and strategic exploration of overarching issues like problem framing, equity, and effective communication. We then offer lessons learned regarding the drivers and barriers to such efforts, and advice from institutional decision-makers on designing such courses at other institutions.
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    Methodological considerations in pre- and post-emergency network identification and data collection for disaster risk reduction: Lessons from wildfire response networks in the American Northwest
    Faas, A. J.; Velez, Anne-Lise K.; Nowell, Branda L.; Steelman, Toddi A. (Elsevier, 2019-11)
    While social network analysis continues to enjoy considerable attention, literature on social network data collection often lacks explicit attention to methods. This presents special challenges to approaching the problems of undertaking social network analysis and of studying disaster preparedness, planning, and, ultimately, risk reduction. In this paper, we address this issue by presenting our synthesis of several strategies for network analyses from our processes for network identification and data collection in a longitudinal study of multi-jurisdictional, inter-agency wildfire response networks in the American Northwest. In the course of this ongoing project, the process of detecting and collecting data on pre-existing and emergent networks in the real world was not a matter of one theoretical or empirical judgement, but rather several. We alternated between: (1) spatio-ecological detection of jurisdictions adjacent to areas at-risk for large wildfires; (2) a hybrid approach to selecting actors and agencies identified as common participants in wildfire response networks; and (3) event-based detections of parties to specific wildfire response networks. We conclude with steps for thinking through network identification and bounding, integrating networks, conceptualizing rosters and ties in initial and events-based phases, and how to manage longitudinal network data collection.
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    Pathways of Representation in Network Governance: Evidence from Multi-Jurisdictional Disasters
    Steelman, Toddi A.; Nowell, Branda L.; Velez, Anne-Lise K.; Scott, Ryan (Oxford University Press, 2021-03-04)
    Governance systems reconcile diverse interests to enable collective decision-making and action. Questions related to representation in the governance of networks are addressed in the literature; underexplored is the empirical variation in governance arrangements and pathways of representation. Complex, multi-jurisdictional disasters provide a robust theoretical and empirical context in which to investigate network governance pathways due to the tensions between democratic principles of representation and the need for timely, expert-informed response actions. In this article, we address three questions related to network governance, representation, and complex disasters: what governance structures allow for a representation of diverse interests? What governance structures provide a perception of voice to key affected parties? And where do we see variation in the kinds of structures that give voice to these entities? Using an inductive, grounded theory approach along with mixed methods that include case studies, interviews, and archival data in the form ICS 209 incident reports, we provide evidence from 10 of the most jurisdictionally complex wildfires that took place in 2017. In doing so, we introduce the distinction between macro and micro structures of network governance for understanding more precisely the pathways by which representation occurs and how representation functions in disaster networks. There is no singular normative goal when we think about network governance and representation in disasters; rather there are competing contingencies that emerge out of complex contexts. We propose four key propositions to guide further work in this arena.
  • Reducing risk to historic assets: drivers and barriers of NGO disaster planning engagement
    Velez, Anne-Lise K.; Daniel, Joseph (2023-02-15)
    This study examines the prevalence of and shifts in preservation NGO engagement in disaster planning around historic assets across the U.S. We identify drivers and barriers to planning, leader opinions on what may increase planning engagement, and change in these areas from 2014 to 2020. Data comprise 73 NGO leader interviews from 2014 and 75 survey responses from 2020. Analysis shows a slight increase in NGOs engaged in any type of disaster planning from 2014 to 2020, with more staff generally meaning more planning. While increased staff were considered most likely and regulations least likely to increase engagement in 2014 and 2020, public support and technical assistance were seen in 2020as more likely to increase engagement. This study expands scholarship on NGO disaster planning and practical knowledge regarding areas for collaboration between government and NGOs in overcoming barriers and planning for disasters caused by natural hazards.
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    Wildfire as Coupled Human Natural System
    Farkhondehmaal, Farshad (Virginia Tech, 2022-02-01)
    Wildfire activity has increased in recent years in the United States, endangering both environment and society. Appropriate management of this phenomenon is only achievable with a thorough understanding of the critical factors influencing wildfire activity in each region. In three essays, I use statistical and mathematical models to examine wildfires and propose solutions to mitigate their impact on society. In the first essay, I focused on building a systematic framework for modeling wildfire as a coupled human-natural system. I employ system dynamics modeling, which was previously applied in various fields, including healthcare, sustainability, and disaster mitigation. I show how, in the absence of exogenous factors such as temperature or lightning, the human perception of fire danger may establish a feedback loop that can yield significant trends such as fluctuation or even fluctuation with rising amplitude when linked with the natural system. This conclusion is counter-intuitive, given that the human contribution to wildfire is typically described in the literature using constant or semi-constant variables. Additionally, I analyzed the impact of three important fire protection measures on reducing burning rates (prescribed burning, enhancing immediate suppression accomplishment, and regulating the rate of WUI growth). The research concludes that appropriately integrating several policies can result in a synergistic effect that is greater than the sum of the effects of the individual policies. The second essay calibrates the model built in the first essay and examines wildfire trends across the contiguous United States. The simulation results closely match the real data, and the model serves as a foundation for data-driven policy research. To be more precise, I fit the model to each state separately and then compare the model's goodness of fit. Following that, I examine the influence of various policies and scenarios on wildfire behavior. In the scenario, I examine the effect of maintaining constant temperatures and precipitation levels relative to the average values for these variables over the last century. For the policy analysis, I examine the influence of three policies on each state (prescribed burning, increasing immediate suppression achievement, and regulating the rate of WUI development). Here, I provide state-specific suggestions about the primary factors that contribute to wildfires and the most effective policies for each state. In the third essay, I have implemented the Oregon wildfire history dataset and integrated it with two other aerial datasets, including meteorological data gathered by weather stations located around the state and counties. Then, using hierarchical modeling on over 10,000 wildfire ignitions, I developed a classification system for determining if a given fire has the potential to grow major or not. However, utilizing a huge dataset and a variety of resources presents several obstacles, such as the presence of missing data. I imputed the missing numbers using a sophisticated mathematical approach called "Predictive Mean Matching".