Geology topics

Brian W. Miller

Publications and source records attributed to Brian W. Miller.

46 records · Page 3Linked to original sources

USGS2019

Implications of climate scenarios for Badlands National Park resource management

Badlands National Park (BADL) hosts a myriad of natural and cultural resources, including bison and black-footed ferrets, the mixed grass prairie they live in, 37-75 million-year-old fossils, and historic buildings, trails, and roads. All are sensitive to climate, but anticipating precisely how each will be affected by climate change is difficult. In the face of this challenge, park resource managers must nevertheless make forward-looking decisions and take action to meet resource management goals. Fortunately, tools exist to identify strategies and actions likely to succeed under a range of potential future climate conditions. Two such tools—qualitative scenario planning and quantitative ecological simulation modeling—were used to anticipate management challenges and identify solutions for BADL and adjacent federal and tribal lands in the coming decades (through 2050). This brief summarizes and synthesizes results of this work. Although the brief focuses on BADL, it also includes several key insights gained from examining management approaches on adjacent lands.

South Dakota↗

USGS2019

Report on the workshop 'Global modelling of biodiversity and ecosystem services'

A three-day workshop on ‘Global Modelling of Biodiversity and Ecosystem Services’, was held in the Hague, Netherlands, from 24th to 26th June 2019. The workshop, attended by 35 modelling and scenario-building experts, was organised on behalf of the former IPBES1 expert group on scenarios and models of the first IPBES work programme by its interim technical support unit, and hosted by the PBL Netherlands Environmental Assessment Agency. The workshop drew on the ‘nature futures’ participatory scenario-building exercise initiated by the IPBES expert group on scenarios and models, and other biodiversity modelling initiatives such as the ISIMIP project2 working on adding biodiversity to the Shared Socioeconomic Pathways (SSPs) scenarios framework, the 'bending the curve' initiative3 led by IIASA4 and WWF5, and GEOBON6 working on modelling Essential Biodiversity Variables. The workshop was a step towards coordinating across biodiversity modelling initiatives, to build on each other’s work, and to seek synergies for the production of innovative scenarios on biodiversity and ecosystem services to inform the post-2020 agenda of the Convention on Biological Diversity, as well as the Sustainable Development Goals. The aims of the workshop were to: 1. Compile material as input for a first draft of the fifth Global Biodiversity Outlook (GBO-5) based on recent scenario work, including the ‘bending the curve’ scenarios and the newly developed PBL scenarios (modified from the Rio+20 scenarios), and existing models (to be completed by August 2019) 2. Develop a protocol for modelling trends and near term projections on indicators relevant to the Nature Futures Framework7 using models that are readily available (to be completed by early 2020) 3. Set the agenda and define the aims for a larger meeting at the end of 2019 to discuss the long term strategy towards the development of appropriate indicators and models to produce Nature Futures scenarios (to continue beyond Jan 2020)

Report↗

USGS2019

A draft decision framework for the National Park Service Interior Region 5 bison stewardship strategy

The Department of the Interior Bison Conservation Initiative calls for its bureaus to plan and implement collaborative American bison conservation and to ensure involvement by tribal, state, and local governments and the public in that conservation. Four independently managed and geographically separated National Park Service (NPS) units in Interior Region 5 (IR5) preserve bison and other components of a formerly contiguous Great Plains landscape. Management of bison in IR5 parks has historically been specific to each park, and livestock and range management science informed much of the decision making. In the past two decades, NPS has shifted away from managing bison from this livestock-based perspective towards a wildlife stewardship approach, including ensuring their long-term adaptive potential and considering them as just one part of a complex ecosystem. This shift requires a more holistic and cooperative approach to stewardship that is challenging not only because of limitations in funding and fluctuations in leadership priorities, but also because of the constraints imposed by the parks’ relatively small, fenced areas. The IR5 NPS Bison Stewardship Strategy (“Strategy”) will help the NPS to meet its responsibilities in cooperative stewardship of bison. The Strategy will serve to organize and consolidate the NPS’s legal and policy responsibilities within a framework of collectively defined values and objectives to support the careful and transparent decision-making processes that both guide and transcend park-specific planning. This report describes a preliminary decision framework for the Strategy, including the context, the fundamental objectives, and a range of alternative strategies developed and considered through two workshops and a series of conference calls with NPS personnel, stakeholders, and outside experts with an interest in IR5 NPS bison stewardship. Although not the Strategy itself, this framework serves as the Strategy’s starting point and identifies 14 fundamental objectives, falling in four major themes: Persistence of Wild and Healthy Bison 1. Maximize the long-term persistence of bison in IR5 parks 2. Maximize the long-term adaptive capacity of bison in North America 3. Maximize the wildness of the bison herds 4. Maximize humane treatment of bison, while allowing natural processes to occur Supporting Tribal Buffalo Culture 5. Improve relationships, trust, and communication with Tribes to enhance shared stewardship of bison within and beyond IR5 6. Maximize the number of live, healthy bison that can be transferred to tribal herds Persistence of Native Ecological Communities and Processes 7. Maximize structural and compositional heterogeneity of native prairie plant communities across space and time within each park 8. Maximize the abundance and diversity of animal species of special concern 9. Minimize the loss of native grassland within each park 10. Minimize the abundance of exotic plants in the park landscape 11. Maximize riparian area and wetland integrity Public Outreach 12. Maximize the number of healthy, wild bison that are visible to the public 13. Maximize the safety of visitors 14. Maximize public understanding of the past, present, and future of bison and Native Americans in the Great Plains The terms “minimize” and “maximize” in these objectives describe the desired direction for each individual objective. Finding the right balance among these objectives and any others identified in further work is one of the central challenges in developing the Strategy. To that end, this report also demonstrates and describes potential methods for evaluating how well alternative strategies would achieve each of the fundamental objectives.

Natural Resource Report↗

USGS2018

Moving from eco-forecasts to eco-projections

Ecological models can provide estimates of future conditions that are useful for decision-making, including long-term planning and resource prioritization. However, these models often rely on assumptions about ecological relationships and trajectories, forcings (e.g., biophysical conditions), and management approaches that may not be explicitly considered. To make assumptions more transparent, disciplines such as economics, demographics, climatology, and national intelligence make a fairly clear and consistent distinction between “forecasts” and “projections”. Forecasts are typically more near-term and rely on extending existing relationships and trends to estimate the most likely future conditions; whereas projections evaluate conditions under multiple scenarios that are based on an array of assumptions, often going further out in time. Consistently referring to ecological models of future conditions as either “eco-forecasts” or “eco-projections” could help make modelling assumptions more transparent and thus more effectively focus their application across landscapes and through time. To the extent that ecological modelling is used to support management, policy, and programmatic decisions, practitioners can ask the following. If the modelling is an eco-forecast, is it worth considering different initial conditions, trajectories, or forcings based on alternative scenarios? If the modelling is an eco-projection, are the underlying assumptions and future scenarios explicit, and are decisions properly tempered with respect to those modelling specifications? We demonstrate these concepts and methods for conducting eco-projections through examples from invasion biology and climate adaptation.

Conference Paper↗

USGS2017

Model-based scenario planning to inform climate change adaptation in the Northern Great Plains—Final report

Public Summary We worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises. In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention. In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.

Montana, Nebraska, North Dakota, South Dakota, Wyo↗

USGS2017

Co-producing simulation models to inform resource management: a case study from southwest South Dakota

Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.

South Dakota↗

USGS2017

Crossing boundaries in a collaborative modeling workspace

There is substantial literature on the importance of bridging across disciplinary and science–management boundaries. One of the ways commonly suggested to cross boundaries is for participants from both sides of the boundary to jointly produce information (i.e., knowledge co-production). But simply providing tools or bringing people together in the same room is not sufficient. Here we present a case study documenting the mechanisms by which managers and scientists collaborated to incorporate climate change projections into Colorado’s State Wildlife Action Plan. A critical component of the project was the use of a collaborative modeling and visualization workspace: the U.S. Geological Survey’s Resource for Advanced Modeling (RAM). Using video analysis and pre/post surveys from this case study, we examine how the RAM facilitated cognitive and social processes that co-produced a more salient and credible end product. This case provides practical suggestions to scientists and practitioners who want to implement actionable science.

Society and Natural Resources↗

USGS2017

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.

Global Change Biology↗

USGS2017

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

Climate Risk Management↗

USGS2015

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science↗