The goal of this study was to integrate a crop model, DNDC (DeNitrification-DeComposition), with life cycle assessment (LCA) and economic analysis models using a GIS-based integrated platform, ...ENVISION. The integrated model enables LCA practitioners to conduct integrated economic analysis and LCA on a regional scale while capturing the variability of soil emissions due to variation in regional factors during production of crops and biofuel feedstocks. In order to evaluate the integrated model, the corn-soybean cropping system in Eagle Creek Watershed, Indiana was studied and the integrated model was used to first model the soil emissions and then conduct the LCA as well as economic analysis. The results showed that the variation in soil emissions due to variation in weather is high causing some locations to be carbon sink in some years and source of CO2 in other years. In order to test the model under different scenarios, two tillage scenarios were defined: 1) conventional tillage (CT) and 2) no tillage (NT) and analyzed with the model. The overall GHG emissions for the corn-soybean cropping system was simulated and results showed that the NT scenario resulted in lower soil GHG emissions compared to CT scenario. Moreover, global warming potential (GWP) of corn ethanol from well to pump varied between 57 and 92gCO2-eq./MJ while GWP under the NT system was lower than that of the CT system. The cost break-even point was calculated as $3612.5/ha in a two year corn-soybean cropping system and the results showed that under low and medium prices for corn and soybean most of the farms did not meet the break-even point.
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•Integrates DNDC model with LCA and economic analysis in ENVISION.•Integrated analysis of cropping systems over long periods at regional scale.•The variation in soil emissions due to variation in weather is high.•Study area GHG emissions ranged −1389 to 6000kgCO-eq/ha/2-year cropping system.•Most farms did not break-even under low/medium prices for corn and soybean.
Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an ...agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern Cascades of Oregon. Our model incorporated existing models of vegetation succession and fire spread and information from original empirical studies of landowner decision making. Our findings indicate that alternative management strategies can have variable effects on landscape outcomes over 50 years for fire, socioeconomic, and ecosystem services metrics. For example, scenarios with federal restoration treatments had slightly less high-severity fire than a scenario without treatment; exposure of homes in the wildland-urban interface to fire was also slightly less with restoration treatments compared to no management. Treatments appeared to be more effective at reducing high-severity fire in years with more fire than in years with less fire. Under the current management scenario, timber production could be maintained for at least 50 years on federal lands. Under an accelerated restoration scenario, timber production fell because of a shortage of areas meeting current stand structure treatment targets. Trade-offs between restoration outcomes (e.g., open forests with large fire-resistant trees) and habitat for species that require dense older forests were evident. For example, the proportional area of nesting habitat for northern spotted owl (Strix occidentalis) was somewhat less after 50 years under the restoration scenarios than under no management. However, the amount of resilient older forest structure and habitat for white-headed woodpecker (Leuconotopicus albolarvatus) was higher after 50 years under active management. More carbon was stored on this landscape without management than with management, despite the occurrence of high-severity wildfire. Our results and further applications of the model could be used in collaborative settings to facilitate discussion and development of policies and practices for fire-prone landscapes.
This editorial introduces the special feature on the social-ecological system of a fire-prone forest landscape in Oregon, USA. Research into social-ecological systems of fire-frequent landscapes is ...in its infancy and this special feature highlights one of the first attempts to understand a fire-dependent forest landscape from this perspective. An agent-based landscape modeling framework, Envision, was the primary tool for the research. The papers in this special feature examine three major questions: (1) What is the landscape structure of forest conditions, fire regimes, ownerships, and attitudes toward fire and forest management?; (2) How are social networks of the study region structured and how might they influence attitudes and actions of landowners?; (3) How do land management policies, institutions, and decisions interact to influence future fire occurrence, biodiversity, and ecosystem services? The findings of the empirical research and simulation modeling reveal how the high ecological and social (e.g., landownership and management goals) diversity of the region contributes to very different fire potentials, attitudes, and management approaches across space. The social network analysis reveals that the social network is divided into fire protection and fire restoration subnetworks that only a few organizations were able to bridge. The simulation modeling shows how difficult it can be to affect fire behavior across large areas, and what the trade-offs of different management actions might be in terms of ecosystem services and fire risk. The special feature also includes papers that examine how social science research is influenced by the use of an agent-based model, and what has been learned about the process of conducting social-ecological research and engaging with stakeholders with the goal of improving understanding of and adaptation to fire-frequent landscapes.
•We simulate four development scenarios with an agent-based landscape change model.•We evaluate scenario impacts with 10 ecologically significant flow metrics.•A flow metric sensitivity typology ...links flow alterations to plans of actions.•Integrated stormwater management (ISM) is crucial for reducing flow alterations.•Compact regional growth may be most important in the absence of ISM.
The ability to anticipate urbanization impacts on streamflow regimes is critical to developing proactive strategies that protect aquatic ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness of integrated stormwater management (i.e., integration of strategic land-use organization with site-scale stormwater BMPs) or its absence, and two regional growth patterns for maintaining streamflow regimes. We applied a three-step sequence to three urbanizing catchment basins in Oregon, to: (1) simulate landscape change under four future development scenarios with the agent-based model Envision; (2) model resultant hydrological change using the Soil and Water Assessment Tool (SWAT); and (3) assess scenario impacts on streamflow regimes using 10 flow metrics that encompass all major flow components. Our results projected significant flow regime changes in all three basins. Urbanization impacts aligned closely with increases in flow regime flashiness and severity of extreme flow events. Most changes were associated with negative impacts on native aquatic organisms in the Pacific Northwest. Scenario comparisons highlighted the importance of integrated stormwater management for reducing flow alterations, and secondarily, compact growth. Based on a flow metric sensitivity typology, six flow metrics were insensitive to development in multiple basins, and four were sensitive to development and manageable with mitigation in multiple basins. Only three metrics were ever sensitive to development and resistant to mitigation, and only in one basin each. Our findings call for regional flow-ecology research that identifies the ecological significance of each flow metric, explores potential remedies for resistant ones and develops specific targets for manageable ones.
Upland forests in the Pacific Northwest currently provide a host of ecosystem services. However, the regional climate is expected to warm significantly over the course of the 21st century and this ...factor must be accounted for in planning efforts to maintain those services. Here we couple a dynamic global vegetation model (MC2) with a landscape simulation model (Envision) to evaluate potential impacts of climate change on the vegetation cover and the disturbance regime in the Willamette River Basin, Oregon. Three CMIP5 climate model scenarios, downscaled to a 4 km spatial resolution, were employed. In our simulations, the dominant potential vegetation cover type remained forest throughout the basin, but forest type transitioned from primarily evergreen needleleaf to a mixture of broadleaf and needleleaf growth forms adapted to a warmer climate. By 2100, there was a difference (i.e., climate/vegetation disequilibrium) between potential and actual forest type for 20–50 % of the forested area. In the moderate to high climate change scenarios, the average area burned per year increased three to nine fold from the present day. Forest harvest on private land is projected to be affected late in the century because of fire altering the availability of rotation-age stands. A generally more disturbed and open forest landscape is expected, which may significantly alter the hydrologic cycle.
We use the simulation model Envision to analyze long-term wildfire dynamics and the effects of different fuel management scenarios in central Oregon, USA. We simulated a 50-year future where fuel ...management activities were increased by doubling and tripling the current area treated while retaining existing treatment strategies in terms of spatial distribution and treatment type. We modeled forest succession using a state-and-transition approach and simulated wildfires based on the contemporary fire regime of the region. We tested for the presence of temporal trends and overall differences in burned area among four fuel management scenarios. Results showed that when the forest was managed to reduce fuels it burned less: over the course of 50 years there was up to a 40% reduction in area burned. However, simulation outputs did not reveal the expected temporal trend, i.e., area burned did not decrease progressively with time, nor did the absence of management lead to its increase. These results can be explained as the consequence of an existing wildfire deficit and vegetation succession paths that led to closed canopy, and heavy fuels forest types that are unlikely to burn under average fire weather. Fire (and management) remained relatively rare disturbances and, given our assumptions, were unable to alter long-term vegetation patterns and consequently unable to alter long-term wildfire dynamics. Doubling and tripling current management targets were effective in the near term but not sustainable through time because of a scarcity of stands eligible to treat according to the modeled management constraints. These results provide new insights into the long-term dynamics between fuel management programs and wildfire and demonstrate that treatment prioritization strategies have limited effect on fire activity if they are too narrowly focused on particular forest conditions.
Wildland fire suppression practices in the western United States are being widely scrutinized by policymakers and scientists as costs escalate and large fires increasingly affect social and ...ecological values. One potential solution is to change current fire suppression tactics to intentionally increase the area burned under conditions when risks are acceptable to managers and fires can be used to achieve long-term restoration goals in fire adapted forests. We conducted experiments with the Envision landscape model to simulate increased levels of wildfire over a 50-year period on a 1.2 million ha landscape in the eastern Cascades of Oregon, USA. We hypothesized that at some level of burned area fuels would limit the growth of new fires, and fire effects on the composition and structure of forests would eventually reduce future fire intensity and severity. We found that doubling current rates of wildfire resulted in detectable feedbacks in area burned and fire intensity. Area burned in a given simulation year was reduced about 18% per unit area burned in the prior five years averaged across all scenarios. The reduction in area burned was accompanied by substantially lower fire severity, and vegetation shifted to open forest and grass-shrub conditions at the expense of old growth habitat. Negative fire feedbacks were slightly moderated by longer-term positive feedbacks, in which the effect of prior area burned diminished during the simulation. We discuss trade-offs between managing fuels with wildfire versus prescribed fire and mechanical fuel treatments from a social and policy standpoint. The study provides a useful modeling framework to consider the potential value of fire feedbacks as part of overall land management strategies to build fire resilient landscapes and reduce wildfire risk to communities in the western U.S. The results are also relevant to prior climate-wildfire studies that did not consider fire feedbacks in projections of future wildfire activity.
Coastal communities face heightened risk to coastal flooding and erosion hazards due to sea-level rise, changing storminess patterns, and evolving human development pressures. Incorporating ...uncertainty associated with both climate change and the range of possible adaptation measures is essential for projecting the evolving exposure to coastal flooding and erosion, as well as associated community vulnerability through time. A spatially explicit agent-based modeling platform, that provides a scenario-based framework for examining interactions between human and natural systems across a landscape, was used in Tillamook County, OR (USA) to explore strategies that may reduce exposure to coastal hazards within the context of climate change. Probabilistic simulations of extreme water levels were used to assess the impacts of variable projections of sea-level rise and storminess both as individual climate drivers and under a range of integrated climate change scenarios through the end of the century. Additionally, policy drivers, modeled both as individual management decisions and as policies integrated within adaptation scenarios, captured variability in possible human response to increased hazards risk. The relative contribution of variability and uncertainty from both climate change and policy decisions was quantified using three stakeholder relevant landscape performance metrics related to flooding, erosion, and recreational beach accessibility. In general, policy decisions introduced greater variability and uncertainty to the impacts of coastal hazards than climate change uncertainty. Quantifying uncertainty across a suite of coproduced performance metrics can help determine the relative impact of management decisions on the adaptive capacity of communities under future climate scenarios.
Coupled models of coastal hazards, ecosystems, socioeconomics, and landscape management in conjunction with alternative scenario analysis provide tools that can allow decision-makers to explore ...effects of policy decisions under uncertain futures. Here, we describe the development and assessment of a set of model-based alternative future scenarios examining climate and population driven landscape dynamics for a coastal region in the U.S. Pacific Northwest. These scenarios incorporated coupled spatiotemporal models of climate and coastal hazards, population and development, and policy and assessed a variety of landscape metrics for each scenario. Coastal flooding and erosion were probabilistically simulated using 99 future 95-year climate scenarios. Five policy scenarios were iteratively co-developed by researchers and stakeholders in Tillamook County, Oregon. Results suggest that both climate change and management decisions have a significant impact across the landscape, and can potentially impact geographic regions at different magnitudes and timescales.
•A framework for comparing adaptation policies under a range of climate impact scenarios is presented.•Probabilistic simulation of total water levels capture coastal flooding and erosion hazards.•Policy scenarios were co-developed with local stakeholders to represent a range of management strategies.•Simulated future landscapes were compared using metrics related to development, property risk, and public good.•Both climate change and management decisions have a significant impact across the coastal landscape.
We developed a new climate-sensitive vegetation state-and-transition simulation model (CV-STSM) to simulate future vegetation at a fine spatial grain commensurate with the scales of human land-use ...decisions, and under the joint influences of changing climate, site productivity, and disturbance. CV-STSM integrates outputs from four different modeling systems. Successional changes in tree species composition and stand structure were represented as transition probabilities and organized into a state-and-transition simulation model. States were characterized based on assessments of both current vegetation and of projected future vegetation from a dynamic global vegetation model (DGVM). State definitions included sufficient detail to support the integration of CV-STSM with an agent-based model of land-use decisions and a mechanistic model of fire behavior and spread. Transition probabilities were parameterized using output from a stand biometric model run across a wide range of site productivities. Biogeographic and biogeochemical projections from the DGVM were used to adjust the transition probabilities to account for the impacts of climate change on site productivity and potential vegetation type. We conducted experimental simulations in the Willamette Valley, Oregon, USA. Our simulation landscape incorporated detailed new assessments of critically imperiled Oregon white oak (
Quercus garryana
) savanna and prairie habitats among the suite of existing and future vegetation types. The experimental design fully crossed four future climate scenarios with three disturbance scenarios. CV-STSM showed strong interactions between climate and disturbance scenarios. All disturbance scenarios increased the abundance of oak savanna habitat, but an interaction between the most intense disturbance and climate-change scenarios also increased the abundance of subtropical tree species. Even so, subtropical tree species were far less abundant at the end of simulations in CV-STSM than in the dynamic global vegetation model simulations. Our results indicate that dynamic global vegetation models may overestimate future rates of vegetation change, especially in the absence of stand-replacing disturbances. Modeling tools such as CV-STSM that simulate rates and direction of vegetation change affected by interactions and feedbacks between climate and land-use change can help policy makers, land managers, and society as a whole develop effective plans to adapt to rapidly changing climate.
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