Geology topics

Dawn R. Magness

Publications and source records attributed to Dawn R. Magness.

5 recordsLinked to original sources

USGS2026

Holistic understanding of uncertainty for collaborative and proactive global change decision making

Global change is accelerating and pushing the planet's ecosystems beyond the range of historical observations, creating increasing uncertainty in future system conditions. Despite general agreement that proactive environmental action is warranted, environmental decision conversations often end by identifying additional data needed to reduce uncertainty before taking novel action. Given the inherent uncertainty in complex issues such as global change, quantitative data alone are likely insufficient to support proactive environmental action. Holistic understanding of uncertainty includes scientific quantification of uncertainty paired with emotional responses and transcendental grounding to help people work together toward proactive action in uncertain decision contexts. Holistic understanding arises from the four ways in which humans perceive the world, termed the Four Realms: Physical (e.g., how I observe), Mental (e.g., how I think), Emotional (e.g., how I feel), and Transcendental (e.g., how I connect to greater meaning or purpose). Environmental scientists and decision makers are generally trained in Physical and Mental Realm observation and analysis, but not in how to apply Emotional and Transcendental Realm understanding. Emotional and Transcendental processing occurs in scientists and decision makers whether it is acknowledged or not and contributes to different people interpreting the same information in different ways. Thus, when the role of Emotional and Transcendental Realms in an individual's interpretation process is not understood, it can derail conversations and perpetuate the status quo. Explicitly recognizing all Four Realms can bring people together across differences and inspire shared, novel decision making even in increasing uncertainty. To illustrate the benefits of holistic understanding, we share stories from our experiences in environmental decision contexts. Because accessing the Four Realms requires experiential and embodied techniques, while still relying on core scientific tenets of observation and analysis, we also present techniques for readers to learn to feel their own emotional understanding and connect to their own transcendental understanding. Holistic understanding can enhance data-driven decisions by recognizing that human responses to uncertainty inherently include interactions between emotions, thoughts, transcendental connections, and behavior. Ultimately, holistic understanding can help anchor data-driven decisions in intra- and interpersonal connections, inspiring action in the face of uncertainty.

Ecosphere↗

USGS2021

Navigating ecological transformation: Resist-accept-direct as a path to a new resource management paradigm

Natural resource managers worldwide face a growing challenge: Intensifying global change increasingly propels ecosystems toward irreversible ecological transformations. This nonstationarity challenges traditional conservation goals and human well-being. It also confounds a longstanding management paradigm that assumes a future that reflects the past. As once-familiar ecological conditions disappear, managers need a new approach to guide decision-making. The resist–accept–direct (RAD) framework, designed for and by managers, identifies the options managers have for responding and helps them make informed, purposeful, and strategic choices in this context. Moving beyond the diversity and complexity of myriad emerging frameworks, RAD is a simple, flexible, decision-making tool that encompasses the entire decision space for stewarding transforming ecosystems. Through shared application of a common approach, the RAD framework can help the wider natural resource management and research community build the robust, shared habits of mind necessary for a new, twenty-first-century natural resource management paradigm.

BioScience↗

USGS2021

RAD adaptive management for transforming ecosystems

Intensifying global change is propelling many ecosystems toward irreversible transformations. Natural resource managers face the complex task of conserving these important resources under unprecedented conditions and expanding uncertainty. As once familiar ecological conditions disappear, traditional management approaches that assume the future will reflect the past are becoming increasingly untenable. In the present article, we place adaptive management within the resist–accept–direct (RAD) framework to assist informed risk taking for transforming ecosystems. This approach empowers managers to use familiar techniques associated with adaptive management in the unfamiliar territory of ecosystem transformation. By providing a common lexicon, it gives decision makers agency to revisit objectives, consider new system trajectories, and discuss RAD strategies in relation to current system state and direction of change. Operationalizing RAD adaptive management requires periodic review and update of management actions and objectives; monitoring, experimentation, and pilot studies; and bet hedging to better identify and tolerate associated risks.

BioScience↗

USGS2020

Resist-accept-direct (RAD)-A framework for the 21st-century natural resource manager

An assumption of stationarity—i.e. “the idea that natural systems fluctuate within an unchanging envelope of variability” (Milly et al. 2008)—underlies traditional conservation and natural resource management, as evidenced by widespread reliance on ecological baselines to guide protection, restoration, and other management. Although ecological change certainly occurred under the relatively stable conditions of the recent past, the nature of change under intensifying global change is different; it is unidirectional, and rapidly pushing beyond the bounds of historical variability. In the past, a manager could plausibly work to reverse or mitigate many stressors or their impacts to approximate pre-disturbance ecological conditions, but now accelerated warming, changing disturbance regimes, and extreme events associated with climate change reduce that potential. Indeed, even ‘holding the line’ in the face of inexorable human-caused change is ever more difficult and costly. Thus, the convention of using baseline conditions to define goals for today’s resource management is increasingly untenable, presenting practical and philosophical challenges for managers. As formerly familiar ecological conditions continue to change, bringing novelty, surprise, and uncertainty, natural resource managers require a new, shared approach to make conservation decisions. How, for example, should a manager respond to projections of loss of the Joshua tree from much of its current range, or to the emergence of new and different vegetation communities after a large fire event? The RAD (Resist-Accept-Direct) decision framework has emerged over the past decade as a simple tool that captures the entire decision space for responding to ecosystems facing the potential for rapid, irreversible ecological change. It assists managers in making informed, purposeful choices about how to respond to the trajectory of change, and moreover, provides a straightforward approach to support resource managers in collaborating at larger scales across jurisdictions, which today is more urgent than ever.

Natural Resource Report↗

USGS2020

Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data

Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known pulse disturbance events is often straightforward given that reduction in tree cover is a readily detectable and measurable land-cover change. Land-cover change is more difficult to quantify when disturbance events are unknown, remote, or environmental response is slow in relation to human observation. While disturbance events and related land-cover change are relatively instant, assessing patterns of post-disturbance succession requires long term monitoring. Here, we describe a method for classifying land cover and quantifying land-cover change over time, using Landsat legacy imagery for three historical eras on the western Kenai Peninsula: 1973–2002, 2002–2017, and 1973–2017. Scenes from numerous Landsat sensors, including summer and winter seasons, were acquired between 1973 and 2017 and used to classify vegetation cover using a random forest classifier. Land-cover type was summarized by era and combined to produce a dataset capturing spatially explicit land-cover change at a moderate 30-m resolution. Our results document large-scale forest loss across the study area that can be attributed to known disturbance events including beetle kill and wildfire. Despite numerous and extensive disturbances resulting in forest loss, we estimate that the study area has experienced net forest gain over the duration of our study period due to reforestation within large fire events that predate this study. Transition between forest and graminoid non-forest land cover including wetlands and herbaceous uplands is the most common land-cover change—representing recruitment of a graminoid dominated understory following forest loss and the return of forest canopy given sufficient time post-disturbance.

Alaska↗