Integrating continuous stocks and flows into state‐and‐transition simulation models of landscape change

Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie‐Josée

doi:10.1111/2041-210x.12952

Cited by 23 publications

(22 citation statements)

References 36 publications

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“…We used the land use and carbon scenario simulator (LUCAS), an empirical model of LUC coupled with a gain–loss model of ecosystem carbon dynamics (Selmants, Giardina, Jacobi, & Zhu, ; Sleeter et al, ; Sleeter, Sleeter, et al, ) to project changes in ecosystem carbon balance for the state of California under a range of climate and land‐use scenarios. The LUCAS model utilizes a fully coupled state‐and‐transition simulation model with stocks and flows (STSM‐SF; Daniel et al, ) to estimate changes in ecosystem carbon pools resulting from changes in land use, land cover, and disturbances (Sleeter et al, ). The model estimates annual changes in carbon pools resulting from vegetation productivity, litterfall, mortality, decay/decomposition, emission, leaching, and harvest.…”

Section: Methodsmentioning

confidence: 99%

“…Pools representing carbon stored in the atmosphere and aquatic pools were tracked to ensure the mass balance of carbon was maintained. For live, DOM, and soil pools, initial carbon stocks were estimated for each land cover class (forest, grasslands, shrublands, and annual and perennial agriculture) and ecoregion based on a regionally calibrated dynamic global vegetation model (DGVM; Daniel et al, ; Selmants et al, ; Sleeter, Liu, Daniel, Frid, & Zhu, ; Sleeter et al, ) and a remote sensing‐derived map of forest age (see Data S1: Methods).…”

Section: Methodsmentioning

confidence: 99%

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Effects of 21st‐century climate, land use, and disturbances on ecosystem carbon balance in California

Sleeter

Marvin

Cameron

et al. 2019

Global Change Biology

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Terrestrial ecosystems are an important sink for atmospheric carbon dioxide (CO2), sequestering ~30% of annual anthropogenic emissions and slowing the rise of atmospheric CO2. However, the future direction and magnitude of the land sink is highly uncertain. We examined how historical and projected changes in climate, land use, and ecosystem disturbances affect the carbon balance of terrestrial ecosystems in California over the period 2001–2100. We modeled 32 unique scenarios, spanning 4 land use and 2 radiative forcing scenarios as simulated by four global climate models. Between 2001 and 2015, carbon storage in California's terrestrial ecosystems declined by −188.4 Tg C, with a mean annual flux ranging from a source of −89.8 Tg C/year to a sink of 60.1 Tg C/year. The large variability in the magnitude of the state's carbon source/sink was primarily attributable to interannual variability in weather and climate, which affected the rate of carbon uptake in vegetation and the rate of ecosystem respiration. Under nearly all future scenarios, carbon storage in terrestrial ecosystems was projected to decline, with an average loss of −9.4% (−432.3 Tg C) by the year 2100 from current stocks. However, uncertainty in the magnitude of carbon loss was high, with individual scenario projections ranging from −916.2 to 121.2 Tg C and was largely driven by differences in future climate conditions projected by climate models. Moving from a high to a low radiative forcing scenario reduced net ecosystem carbon loss by 21% and when combined with reductions in land‐use change (i.e., moving from a high to a low land‐use scenario), net carbon losses were reduced by 55% on average. However, reconciling large uncertainties associated with the effect of increasing atmospheric CO2 is needed to better constrain models used to establish baseline conditions from which ecosystem‐based climate mitigation strategies can be evaluated.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Effects of 21st‐century climate, land use, and disturbances on ecosystem carbon balance in California

Sleeter

Marvin

Cameron

et al. 2019

Global Change Biology

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“…Biomass stocks and flows. -Aboveground biomass for each simulation cell was modeled using the stock and flow module in ST-Sim (Sleeter et al 2015, Daniel et al 2017. We distinguished live biomass and litter using two separate stocks or pools.…”

Section: Simulation Model Parameterizationmentioning

confidence: 99%

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

et al. 2017

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Abstract. Simulation models can represent complexities of the real world and serve as virtual laboratoriesfor 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.

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“…Unlike most landscape simulation models developed for specific regions and questions, the State and Transition Simulation Model (STSM) is a general, randomized, and spatially explicit approach for projecting landscape dynamics [20]. STSM projects changes in LULC to divide the landscape into a set of raster simulation cells and randomly forwards the state and age of each cell based on chronology, in response to probability transfers.…”

Section: Introductionmentioning

confidence: 99%

Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data

et al. 2020

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Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km2, respectively, but developed lands gained 293 km2 (29 km2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr−1) and agricultural expansion (0.046 Tg C·yr−1); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.

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Integrating continuous stocks and flows into state‐and‐transition simulation models of landscape change

Cited by 23 publications

References 36 publications

Effects of 21st‐century climate, land use, and disturbances on ecosystem carbon balance in California

Effects of 21st‐century climate, land use, and disturbances on ecosystem carbon balance in California

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

Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data

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