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ContextAgent-based models (ABMs) and state-and-transition simulation models (STSMs) have proven useful for understanding processes underlying social-ecological systems and evaluating practical questions about how systems might respond to different scenarios. ABMs can simulate a variety of agents (autonomous units, such as wildlife or people); agent characteristics, decision-making, adaptive behavior, and mobility; and agent-environment interactions. STSMs are flexible and intuitive stochastic landscape models that can track scenarios and integrate diverse data. Both can be run spatially and track metrics of management success.ObjectivesDue to the complementarity of these approaches, we sought to couple them through a dynamic linkage and demonstrate the relevance of this advancement for modeling landscape processes and patterns.MethodsWe developed analytical techniques and software tools to couple these modeling approaches using NetLogo, R, and the ST-Sim package for SyncroSim. We demonstrated the capabilities and value of this coupled approach through a proof-of-concept case study of bison-vegetation interactions in Badlands National Park.ResultsThe coupled ABM-STSM: (1) streamlined handling of model inputs and outputs; (2) allowed representation of processes at multiple temporal scales; (3) minimized assumptions; and (4) generated spatial and temporal patterns that better reflected agent-environment interactions.ConclusionsThese developments constitute a new approach for representing agent-environment feedbacks; modelers can now use output from an ABM to dictate landscape changes within an STSM that in turn influence agents. This facilitates experimentation across domains (agent and environment) and creation of more realistic and management-relevant projections, and opens new opportunities for communicating models and linking to other methods.

BackgroundQuantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a “gain–loss” approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3).ResultsWe estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year−1. Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source.ConclusionsThe new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures.

In the context of widespread ecological changes, land managers and policymakers confront the need to prioritize ecosystem restoration and fuel management activities across large areas to sustain ecosystem services. Reference conditions inform prioritization efforts by providing a baseline from which to measure where and how vegetation and fuels have changed, but until recently the USA lacked a complete set of reference conditions. We describe the ongoing development of a comprehensive set of vegetation reference conditions based on over 900 quantitative vegetation dynamic models and accompanying description documents for terrestrial ecosystems in the USA. These models and description documents, collaboratively developed by more than 800 experts around the country through the interagency LANDFIRE Program, synthesize fundamental ecological information about ecosystem dynamics, structure, composition, and disturbance regimes before European‐American settlement. These products establish the first comprehensive national baseline for measuring vegetation change in the USA, providing land managers and policymakers with a tool to support vegetation restoration and fuel management activities at regional to national scales. Users have applied these products to support a variety of land management needs including exploring ecosystem dynamics, assessing current and desired conditions, and simulating the effects of management actions. In an era of rapid ecological change, these products provide land managers with an adaptable tool for understanding ecosystems and predicting possible future conditions.

Invasive species can alter ecosystem properties and cause state shifts in landscapes. Resource managers charged with maintaining landscapes require tools to understand implications of alternative actions (or inactions) on landscape structure and function. Simulation models can serve as a virtual laboratory to explore these alternatives and their potential impacts on a landscape. To be useful, however, managers need to participate in model development to ensure that model structure can evaluate the response of key resources to plausible actions. Here, we detail development of a state‐and‐transition simulation model (STSM) to evaluate buffelgrass (Cenchrus ciliaris L. syn Pennisetum ciliare (L.) Link) in Saguaro National Park (SNP), Arizona, USA, through collaboration between managers and researchers. We integrate expert knowledge and research to create and parameterize a stochastic, spatially explicit STSM to evaluate specific management objectives. We also develop a dynamic link between the STSM and a fire behavior model to allow exploration of potential novel processes introduced to the ecosystem by buffelgrass invasion. Our projections show that buffelgrass can be expected to increase on the landscape and that the integration of fire into the model accelerates the projected rate of invasion and increases degradation of resources of management concern. We highlight the benefit of engaging end users in the modeling process so that the model is targeted to evaluate management objectives, in this case retention of saguaro cacti (Carnegiea gigantea (Engelm.) Britton & Rose) on the landscape. Being able to integrate an external model that can help address the unique characteristics of a problem such as the introduction of fire into the SNP desert ecosystem increases the ability of simulations to address complex ecological and management questions.

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

Ecological forecasts of the extent and impacts of invasive species can inform conservation management decisions. Such forecasts are hampered by ecological uncertainties associated with non-analog conditions resulting from the introduction of an invader to an ecosystem. We developed a state-and-transition simulation model tied to a fire behavior model to simulate the spread of buffelgrass ( Cenchrus ciliaris ) in Saguaro National Park, AZ, USA over a 30-year period. The simulation models forecast the potential extent and impact of a buffelgrass invasion including size and frequency of fire events and displacement of saguaro cacti and other native species. Using simulation models allowed us to evaluate how model uncertainties affected forecasted landscape outcomes. We compared scenarios covering a range of parameter uncertainties including model initialization (landscape susceptibility to invasion) and expert-identified ecological uncertainties (buffelgrass patch infill rates and precipitation). Our simulations showed substantial differences in the amount of buffelgrass on the landscape and the size and frequency of fires for dry years with slow patch infill scenarios compared to wet years with fast patch infill scenarios. We identified uncertainty in buffelgrass patch infill rates as a key area for research to improve forecasts. Our approach could be used to investigate novel processes in other invaded systems.

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.

Determining the best strategy for allocating weed management resources across and between landscapes is challenging because of the uncertainties and large temporal and spatial scales involved. Ecological models of invasive plant spread and control provide a practical tool with which to evaluate alternative management strategies at landscape scales. We developed a spatially explicit model for the spread and control of spotted knapweed and leafy spurge across three Montana landscapes. The objective of the model was to determine the ecological and economic costs and benefits of alternative strategies across landscapes of varying size and stages of infestation. Our results indicate that (1) in the absence of management the area infested will continue to increase exponentially leading to a substantial cost in foregone grazing revenues; (2) even though the costs of management actions are substantial, there is a net economic benefit associated with a broad range of management strategies; (3) strategies a that prioritize targeting small new infestations consistently outperform strategies that target large established patches; and (4) inconsistent treatment and short-term delays can greatly reduce the economic and ecological benefits of management. Nomenclature: Leafy spurge, Euphorbia esula L. EPHES; spotted knapweed, Centaurea stoebe L. CENMA. Management Implications: Models of invasive plant spread and control provide a useful way to assess the performance of alternative management strategies and budget levels across broad temporal and spatial scales. To meet long-term goals for their landscape, managers should pursue strategies that are both ecologically effective and economically justified. Model results provide several insights for achieving that success. Early detection and small-patch control strategies consistently outperformed large-patch strategies. Despite these results and previous recommendations for early detection and rapid response programs, managers are often mandated to focus on large infestations where weeds are well established and highly visible. Small infestations do not present an immediate loss of productivity and are often more remote and time-consuming to control. Consequently resources are directed toward locations where, based on our model results, treatment is less beneficial and long-term success is less likely. Our model results support the reallocation of resources to an effective early detection and treatment strategy. Our results also indicate that managers should avoid delaying management or applying inconsistent treatment over time. In these cases, weed populations outpace management efforts and can reinvade previously treated areas, ultimately leading to a greater area invaded with greater economic costs. Preventative actions that reduce weed dispersal distances and spread rates will lower ultimate invasion levels and long-term management costs. For landscapes with relatively few existing infestations of noxious weeds, managers should dedicate resources to detecting and controlling new infestations as early as possible to prevent the development of established populations. For invaded landscapes where large noxious weed infestations already exist, early detection and control remains a foundational strategy but managers should also maximize site-specific treatment success. At the broadest scale, resources should be allocated to landscapes with lower infestation levels and thus greater potential for long-term management success and return on investment, rather than highly invaded landscapes.

Pacific giant salamanders (Dicamptodon tenebrosus Good) in the Chilliwack River valley of southwestern British Columbia are at the periphery of their range, and therefore of conservation concern. Although logging is a potential threat to the species, no studies have examined how clear-cutting affects its terrestrial stage. We used radio telemetry to compare the movements of 35 terrestrial Pacific giant salamanders at sites with three different logging histories: forested, clearcut to the stream margin, and clearcut with riparian buffer strips. The results demonstrate that logging affected movements of the salamanders. Salamanders in clearcuts remained significantly closer to the stream, spent more time in subterranean refuges, and had smaller home ranges than those at forested sites. During a dry year, salamanders in clearcuts were significantly more dependent on precipitation for their movement than salamanders in forested habitats. Salamander movement behavior in riparian buffer strips was not significantly different from that at forested sites but was significantly different from that at clearcut sites. Riparian buffer strips appear to mitigate some of the negative effects of clearcuts on salamander movement.

This report describes a land management modeling effort that analyzed potential impacts of proposed actions under an updated Bureau of Land Management Resource Management Plan that will guide management for 20 years on 4.6 million hectares in the Great Basin ecoregion of the United States. State-and-transition models that included vegetation data, fire histories, and many parameters (i.e., rates of succession, fire return intervals, outcomes of management actions, and invasion rates of native and nonnative invasive species) were developed through workshops with scientific experts and range management specialists. Alternative restoration scenarios included continuation of current management, full fire suppression, wildfire use in designated fire use zones, wildfire use in resilient vegetation types only, restoration with a tenfold budget increase, no restoration treatments, and no livestock grazing. Under all the scenarios, cover of vegetation states with native perennial understory declined and was replaced by tree-invaded and weed-dominated states. The greatest differences among alternative management scenarios resulted from the use of fire as a tool to maintain native understory. Among restoration scenarios, only the scenario assuming a tenfold budget increase had a more desirable outcome than the current management scenario. Removal of livestock alone had little effect on vegetation resilience. Rather, active restoration was required. The predictive power of the model was limited by current understanding of Great Basin vegetation dynamics and data needs including statistically valid monitoring of restoration treatments, invasiveness and invasibility, and fire histories. The authors suggest that such computer models can be useful tools for systematic analysis of potential impacts in land use planning. However, for a modeling effort to be productive, the management situation must be conducive to open communication among land management agencies and partner entities, including nonprofit organizations.