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Amy Symstad

Publications and source records attributed to Amy Symstad.

At least 19 recordsLinked to original sources
USGS2026

Dormant-season prescribed fires can enhance forage quality for two growing seasons in the northwestern Great Plains

Fire is an ecological disturbance that can accelerate nutrient cycling and alter herbivore distribution in grasslands and shrublands. Historically and today, humans have used prescribed fire to enhance forage quality for wild and domestic herbivores, and to achieve other management objectives. Contextual factors such as ecosystem type, seasonality, and fuel characteristics can determine how prescribed fire affects forage quality. For example, forage quality enhancements are relatively short lived in shortgrass steppe and subhumid grasslands but may persist for multiple years in northern mixed-grass prairie and sagebrush steppe. Outcomes near ecosystem boundaries are uncertain. Using 152 independent, small-plot, prescribed burns completed over multiple years at 36 sites in Wyoming and South Dakota, USA, we tested the effects of ecosystem type (northern mixed-grass prairie vs. sagebrush grassland ecotone), burn seasonality (fall vs. spring), and fuel characteristics (ambient vs. added fuel) on forage quality. Across ecosystems, fall fires had strong positive effects on forage quality parameters during the first growing season after fire, and energy benefits that persisted into the second growing season after fire. In northern mixed-grass prairie, spring and fall prescribed fires implemented before the same growing season yielded similar forage quality enhancements for one season. Finally, artificially increased fuel loads had few effects on forage quality. Although forage quality rarely dropped below critical nutrition thresholds for ruminants regardless of burning, our findings suggest relatively consistent, positive forage quality responses to prescribed fire across ecosystem types, seasonality of dormant-season burns, and fuel characteristics. Many improvements lasted through one growing season, and some persisted into a second growing season. Managers could take advantage of short-term nutritional benefits via adaptive management strategies that allow animals access to burned and unburned areas.

South Dakota, Wyoming↗
USGS2025

Ecological scenarios: Embracing ecological uncertainty in an era of global change

Scenarios, or plausible characterizations of the future, can help natural resource stewards plan and act under uncertainty. Current methods for developing scenarios for climate change adaptation planning are often focused on exploring uncertainties in future climate, but new approaches are needed to better represent uncertainties in ecological responses. Scenarios that characterize how ecological changes may unfold in response to climate and describe divergent and surprising ecological outcomes can help natural resource stewards recognize signs of nascent ecological transformation and identify opportunities to intervene. Here, we offer principles and approaches for more fully integrating ecological uncertainties into the development of future scenarios. We provide examples of how specific qualitative and quantitative methods can be used to explore variation in ecological responses to a given climate future. We further highlight opportunities for ecological researchers to generate actionable projections that capture uncertainty in both climatic and ecological change in meaningful and manageable ways to support climate change adaptation decision making.

Nebraska↗
USGS2025

Accurately characterizing climate change scenario planning in the U.S. National Park Service: Comment on Murphy et al. 2023

We more accurately locate the boundary between current practice and research priorities regarding climate change scenario planning in U.S. federal land management agencies by supplementing the characterization in a recent article (“Understanding perceptions of climate change scenario planning in United States public land management agencies”) of its use in the U.S. National Park Service. Accurately reflecting the full depth and breadth of efforts to streamline and mainstream the method for climate change adaptation planning in the U.S. National Park Service provides readers helpful guidance and resources called for by Murphy et al.

Society and Natural Resources↗
USGS2023

Synthesis of climate and ecological science to support grassland management priorities in the North Central Region

Grasslands in the Great Plains are of ecological, economic, and cultural importance in the United States. In response to a need to understand how climate change and variability will impact grassland ecosystems and their management in the 21st century, the U.S. Geological Survey North Central Climate Adaptation Science Center led a synthesis of peer-reviewed climate and ecology literature relevant to grassland management in the North Central Region (including Montana, Wyoming, Colorado, North Dakota, South Dakota, Nebraska, and Kansas). This synthesis was done to begin to address grassland managers’ information needs and identify research gaps. This open-file report summarizes the impacts of climate change and variability on temperature, water availability, wildfire, vegetation, wildlife, large-bodied ruminants, grazing, and land-use change and the implications for grassland management in the North Central region. This open-file report also identifies areas in which further research is needed. U.S. Geological Survey funded this project.

Colorado, Kansas, Montana, Nebraska, North Dakota,↗
USGS2023

Scenario-Based Decision Analysis: Integrated scenario planning and structured decision making for resource management under climate change

Managing resources under climate change is a high-stakes and daunting task, especially because climate change and associated complex biophysical responses engender sustained directional changes as well as abrupt transformations. This environmental non-stationarity challenges assumptions and expectations among scientists, managers, rights holders, and stakeholders. These challenges are anything but straightforward – a high degree of uncertainty impedes our ability to predict the environmental trajectory with confidence, and affected resources often span multiple governance jurisdictions or are subject to competing management objectives. Fortunately, tools exist to help grapple with such challenges. Two commonly used tools are scenario planning (SP) and structured decision making (SDM). SP is a well-established approach for assessing system response and facilitating decision making under a wide range of conditions that are uncertain and uncontrollable, such as those associated with adapting to climate change. However, SP lacks a defined structure for establishing objectives, quantifying tradeoffs, and evaluating the performance of candidate decisions to meet those objectives. SDM, on the other hand, is rooted in decision theory and focuses on explicit (often quantitative) assessment of the expected outcomes of choosing among a set of decision alternatives. SDM has been criticized for an inability to account for surprises and for imposing an overly narrow framing of problems to increase tractability. We discuss the strengths and limitations of SDM and SP as experienced through their application in various resource-management contexts, and then propose a new generalized framework – Scenario-Based Decision Analysis (SBDA) – that integrates these complementary approaches. SBDA structures resource management problems and solutions while considering uncertainties and surprises to inform resource management decision making.

Biological Conservation↗
USGS2022

Conservation under uncertainty: Innovations in participatory climate change scenario planning from U.S. national parks

The impacts of climate change (CC) on natural and cultural resources are far-reaching and complex. A major challenge facing resource managers is not knowing the exact timing and nature of those impacts. To confront this problem, scientists, adaptation specialists, and resource managers have begun to use scenario planning (SP). This structured process identifies a small set of scenarios—descriptions of potential future conditions that encompass the range of critical uncertainties—and uses them to inform planning. We reflect on a series of five recent participatory CC SP projects at four US National Park Service units and derive guidelines for using CC SP to support natural and cultural resource conservation. Specifically, we describe how these engagements affected management, present a generalized CC SP approach grounded in management priorities, and share key insights and innovations that (1) fostered participant confidence and deep engagement in the participatory CC SP process, (2) shared technical information in a way that encouraged informed, effective participation, (3) contextualized CC SP in the broader picture of relevant longstanding or emerging nonclimate stressors, (4) incorporated quantitative approaches to expand analytical capacity and assess qualitative findings, and (5) translated scenarios and all their complexity into strategic action.

Conservation Science and Practice↗
USGS2022

Adaptive management framework and decision support tool for invasive annual bromes in seven Northern Great Plains National Park Service units

National Park Service (NPS) units in the northern Great Plains (NGP) were established to preserve and interpret the history of the United States, protect and showcase unusual geology and paleontology, and provide a home for vanishing large wildlife. A unifying feature among these national parks, monuments, and historic sites is northern mixed-grass prairie, which not only provides background scenery and habitat but is the foundation of many park missions. As recognition of the prairie’s importance to park fundamental resources and values has grown, so too has the realization that invasive plants threaten these values by reducing native species diversity, altering food webs, and marring the visitor experience. Cheatgrass ( Bromus tectorum ) and Japanese brome ( Bromus japonicus )—collectively referred to as “annual bromes”—are of particular concern because of their documented increase through time, and their association with lower native plant diversity, in NGP parks. A variety of grazing, herbicide-application, and prescribed-fire experiments have shown promising short-term results for controlling annual bromes in research-scale plots in the NGP, but it is unclear whether these management actions will be as effective at the larger spatial and longer temporal scales relevant to park management. When uncertainties about the effectiveness of different management actions cannot be answered with traditional research approaches in time to prevent resource degradation, yet recurrent management decisions must be made, an adaptive management approach may be appropriate. Thus, in 2017, we began to develop the ABAM—Annual Brome Adaptive Management—framework. The aim of this framework is to reduce uncertainties about methods for controlling annual bromes in seven NGP parks through a formal process of learning from the application of on-going management. A uniform framework across seven parks provides greater opportunities for reducing these uncertainties compared to a single park acting alone or to multiple parks using different adaptive management frameworks. This technical report details the development and expected implementation of the ABAM framework. After briefly introducing the issue (Section 1) and describing the context in which the framework was developed (Section 2), the report describes how a structured decision-making process was used to frame the problem, determine concrete objectives, and decide the alternative actions for achieving those objectives that the framework would be designed around (Section 3). Then the report describes the process used to develop the ABAM decision support system (Section 4). At the core of this system is the ABAM decision support tool, a Bayesian decision network built on nearly two decades of vegetation monitoring data from NGP parks, as well as current literature and ABAMspecific experiments. This tool, referred to as the ABAM model by its intended users, is built to work with the existing vegetation monitoring, prescribed fire, and invasive plant management programs that support the seven ABAM parks. In Section 5, the report describes how output from the ABAM model is produced and used in annual vegetation management decision making. It describes the ABAM R package (Baldwin et al. 2021) and an example R script that leads a user through an annual workflow using the model and the package. This workflow updates the model with information from new monitoring events following management actions of prescribed fire, herbicide application, or a combination thereof. With the updated model, data describing the current condition of vegetation in park management units, and current data for environmental factors included in the model (soil texture, slope, weather, and grazing), the user then runs the model to predict future vegetation conditions—and managers’ happiness with the outcome—in response to each of 10 management actions for each management unit in each park. These predictions inform managers’ decisions regarding locations and types of management actions to apply in the upcoming year. The ABAM framework is in its infancy, and the report concludes (Section 6) with a discussion of its longer-term viability. Successful adaptive management requires commitment for the long term, likely decades. Currently, the predictions of the decision support tool are not expected to be highly accurate, but they ideally will improve over time as more management actions are applied and their outcomes are captured by monitoring. We designed the ABAM decision support tool to work with the existing management and monitoring resources in ABAM parks to maximize the sustainability of the model’s use, but the ABAM framework requires more than the model. Because this application of an adaptive management framework supported by a quantitative decision support tool to guide vegetation management is unique within the NPS (to our knowledge), institutional knowledge and mechanisms for long-term implementation of the ABAM framework do not exist within the agency. Additionally, the ABAM model and the data that inform it could be improved in a variety of ways. Thus, this report concludes with a discussion of ways to both sustain and improve upon the work completed so far.

Montana, Nebraska, South Dakota, Wyoming↗
USGS2022

Overcoming “analysis paralysis” through better climate change scenario planning

This "In Brief" article describes the use of scenario planning to facilitate climate change adaptation in the National Park Service. It summarizes best practices and innovations for using climate change scenario planning, with an emphasis on management outcomes and manager perspectives. The scenario planning approach and management outcomes highlighted in this article are the culmination of more than a decade of collaboration between the USGS and the National Park Service.

Park Science↗
USGS2022

Supplemental vegetation monitoring plots at Badlands National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model

The annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The ABAM model includes treatments in which the herbicides indaziflam and imazapic are applied alone or in combination with or without a prescribed fire preceding or following their application. However, the ABAM model currently does not have field data for the effects of those treatments on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks. This annual report provides raw results of these treatments applied to plots at Badlands National Park established specifically to accumulate this type of data and therefore accelerate the rate of learning accomplished in the adaptive management cycle.

South Dakota↗
USGS2022

Supplemental vegetation monitoring plots at Wind Cave National Park to accelerate learning of the Annual Brome Adaptive Management (ABAM) model

The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The ABAM model includes treatments in which the herbicides indaziflam and imazapic are applied alone or in combination with or without a prescribed fire preceding or following their application. However, the original ABAM model did not have field data for the effects of those treatments on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to increase the amount of information about these treatments and therefore accelerate the rate of learning accomplished in the adaptive management cycle.

South Dakota↗
USGS2022

Fort Laramie National Historic Site 2022 ABAM Investigator Annual Report

The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model's parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating is called "learning." Currently, the ABAM model has little information about the effects of the herbicide indaziflam, applied alone or together with the herbicide imazapic, at different times during the growing season, on target invasive annual grasses and other components of the vegetation. The purpose of this study is to increase the amount of information about this herbicide and therefore accelerate the rate of learning accomplished in the adaptive management cycle.

Wyoming↗
USGS2022

Effect of repeated fire on annual brome invasion at Badlands National Park

Prescribed fire is used to combat exotic plant species in mixed-grass prairie of Northern Great Plains parks. However, prescribed fires rarely occur at a frequency likely to maintain any gains against exotic species. The unusual circumstance of experimental plots being burned twice in 2 years provides a unique opportunity to investigate the effect of more frequent fire on invasive annual brome grasses. I established 40 plots on Sheep Mountain Table at Badlands National Park in 2015 to examine the relative effectiveness of prescribed fire alone or in combination with imazapic (an herbicide) application or with native seeding. Ten of the 40 plots were controls, with no experimental treatment; the remainder were burned with a prescribed fire in November 2016, and the herbicide and seeding treatments were applied soon thereafter to 10 plots each. In the 2018 growing season, annual brome abundance remained lower in the burned plots than in the controls, but monitoring by the National Park Service’s Northern Great Plains Fire Effects programs suggests that, by 5 years (or perhaps earlier) following a prescribed fire, annual brome abundance will return to its pre-fire level. Repeated fires may prevent this return if they sufficiently reduce the annual brome seedbank or produce conditions less conducive to annual brome growth (reduced litter layer or increased competition, for example). All plots in this experiment burned as part of a larger prescribed fire in fall 2018. This extension of the original study measures plant community composition (to species level) in the experimental plots (original control and burn only) after the 2018 prescribed fire; this report provides the results from the fourth growing season after that fire.

South Dakota↗
USGS2022

Supplemental vegetation monitoring plots at Little Bighorn Battlefield National Monument to accelerate learning of the Annual Brome Adaptive Management (ABAM) model

The Annual Brome Adaptive Management (ABAM) project is a consortium of seven parks in the Northern Great Plains (NGP) working together to better understand how to control invasive annual grasses (including Bromus species) through an adaptive management approach. This approach is supported by a quantitative model that uses current data from standardized vegetation monitoring plots in all seven parks to annually update the model’s parameters and predictions regarding the effects of different management actions on invasive annual grasses and other components of the mixed-grass prairie plant community. This updating of the model is called “learning.” The original ABAM model has little information about the effects of the herbicide indaziflam (Esplanade or Rejuvra, Bayer Environmental Sciences) on target invasive annual grasses and other components of the vegetation in conditions like those that frequently occur in ABAM parks (i.e., ungrazed). The purpose of this study is to provide some of that information in order to accelerate the rate of learning accomplished in the adaptive management cycle. This annual report to the partner provides that information as collected in 2022 in 3 plots at Little Bighorn Battlefield National Monument.

Montana↗
USGS2021

Biodiversity–productivity relationships in a natural grassland community vary under diversity loss scenarios

Understanding the biodiversity–productivity relationship and underlying mechanisms in natural ecosystems under realistic diversity loss scenarios remains a major challenge for ecologists despite its importance for predicting impacts of rapid loss of biodiversity worldwide. Here we report the results of a plant functional group (PFG) removal experiment conducted on the Mongolian Plateau, the largest remaining natural grassland in the world. Our results demonstrated that the biodiversity–productivity relationship varied among positive linear, neutral and unimodal forms under different PFG loss patterns. Moreover, the form of this relationship with the same PFG loss pattern sometimes changed through time. The abundance of the remaining PFG(s) before removal and their compensation following the loss of other PFGs were two major mechanisms affecting the biodiversity–productivity relationship under diversity loss scenarios. The abundance effect promoted positive responses of productivity to biodiversity, but the compensation effect caused several biodiversity–productivity relationships, hinging on its direction (positive or negative) and strength. As indicated by the values of the compensation index, negative, zero and partial compensations contributed to the positive relationships, while full compensation resulted in a neutral relationship. Overcompensation at intermediate PFG richness levels created a unimodal curve in our system, but it could also lead to a negative linear relationship. Synthesis . Our experiment provides a vivid picture of how the form of the biodiversity–productivity relationship varies among different diversity loss patterns in a natural ecosystem. We argue that compensation by the remaining species, which is not revealed by synthesized biodiversity experiments, plays a critical role in shaping the form of this relationship when diversity is lost from existing systems. The direction and strength of compensation are highly dependent on extirpation scenarios. Thus, impacts of biodiversity loss on natural ecosystems are likely more complex than predicted by the canonical positive saturating curve obtained from the synthesized biodiversity experiments. We suggest that models forecasting the consequences of biodiversity declines on natural ecosystems should take into account diversity loss patterns and the ensuing compensation.

Journal of Ecology↗
USGS2021

Climate change scenario planning for resource stewardship at Wind Cave National Park

This report explains scenario planning as a climate change adaptation tool in general, then describes how it was applied to Wind Cave National Park as the second part of a pilot project to dovetail climate change scenario planning with National Park Service (NPS) Resource Stewardship Strategy development. In the orientation phase, Park and regional NPS staff, other subject-matter experts, natural and cultural resource planners, and the climate change core team who led the scenario planning project identified priority resource management topics and associated climate sensitivities. Next, the climate change core team used this information to create a set of four divergent climate futures—summaries of relevant climate data from individual climate projections—to encompass the range of ways climate could change in coming decades in the park. Participants in the scenario planning workshop then developed climate futures into robust climate-resource scenarios that considered expert-elicited resource impacts and identified potential management responses. Finally, the scenario-based resource responses identified by park staff and subject matter experts were used to integrate climate-informed adaptations into resource stewardship goals and activities for the park's Resource Stewardship Strategy. This process of engaging resource managers in climate change scenario planning ensures that their management and planning decisions are informed by assessments of critical future climate uncertainties.

South Dakota↗
USGS2021

Coflowering invasive plants and a congener have neutral effects on fitness components of a rare endemic plant

Network analyses rarely include fitness components, such as germination, to tie invasive plants to population-level effects on the natives. We address this limitation in a previously studied network of flower visitors around a suite of native and invasive plants that includes an endemic plant at Badlands National Park, South Dakota, USA. Eriogonum visheri coflowers with two abundant invasive plants, Salsola tragus and Melilotus officinalis , as well as a common congener, E. pauciflorum . Network analyses had suggested strong linkages between E. visheri and S. tragus and E. pauciflorum , with a weaker link to M. officinalis . We measured visitation, pollen deposited on stigmas, achene weight and germination over three field seasons (two for germination) in four populations (two in the final season) of E. visheri and applied in situ pollen treatments to E. visheri , adding pollen from other flowers on the same plant; flowers on other E. visheri plants; S. tragus, M. officinalis , or E. pauciflorum ; open pollination; or excluding pollinators. Insect visitation to E. visheri was not affected by floral abundance of any of the focal species. Most visitors were halictid bees; one of these ( Lasioglossum packeri ) was the only identified species to visit E. visheri all three years. Ninety-seven percent of pollen on collected E. visheri stigmas was conspecific, but 22% of flowers had >1 grain of E. pauciflorum pollen on stigmas and 7% had >1 grain of S. tragus pollen; <1% of flowers had M. officinalis pollen on stigmas. None of the pollen treatments produced significant differences in weight or germination of E. visheri achenes. We conclude that, in contrast to the results of the network analysis, neither of the invasive species poses a threat, via heterospecific pollen deposition, to pollination of the endemic E. visheri , and that its congener provides alternative pollen resources to its pollinators.

South Dakota↗