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Authors: James L. Smith1
Affiliations: (1) The Nature Conservancy
With a wink and a nod, let’s briefly look back and review how we got to where we are today. What does that tell us about the future? Herein lies what I think I learned….the lesson. What lessons have you learned that are relevant to the future?
Authors: David Anderson1
Affiliations: (1) USDA Forest Service
State and Transition Simulation Models perform well for doing descriptive and predictive analytics, but developing prescriptive analytics falls in the realm of optimization models. This study investigates whether optimization techniques, specifically the heuristic method of genetic algorithms, can be applied to a state and transition model. The optimization objective focused on was minimizing seral state departure from desired conditions by varying the vegetation treatment type, amount and timing. To do so, a Python script was developed to implement a genetic algorithm. The script uses the SyncroSim command line interface to build and run ST-Sim scenarios for each set of treatment type, amount and timing that is needed for each genetic algorithm evaluation. The script processes the ST-Sim outputs to produce the objective values which are used by the genetic algorithm to determine the next set of treatment type, amount and timing to evaluate. This continues until an optimal value is reached. The process was run for an approximately 100,000-acre project area using a vegetation type model. ST-Sim was run non-spatially. The genetic algorithm did find high quality solutions that were better than the proposed actions. The initial test indicates that heuristic search methods can be used in conjunction with State and Transition Simulation Models. More investigation into several genetic algorithm components such as the initial population, crossover and objective function need to be done.
Authors: Kevin Badik1, Louis Provencher1, Sarah Byer1, Leonardo Frid2, Shreeham Senthivasan & Kristin Szabo3
Affiliations: (1) The Nature Conservancy, (2) Apex RMS, (3) Nevada Division of Natural Heritage
Rangelands are often ignored in the discussion of carbon sequestration; however, degraded rangelands may provide win-win opportunities for increased carbon storage and landscape restoration. This is especially important as the potential for setting up carbon markets to offset carbon emission has gained traction. Therefore, we wanted to quantify the restoration and carbon sequestration opportunity in sagebrush shrublands dominated by non-native annual grass and forb species (NNAGF). We used a two-scale approach to look at where NNACF may be restored and how that restoration may impact carbon dynamics. First, NNAGF cover was mapped across the region, which included north and central Nevada, southern Idaho, and southwestern Utah. Then, restoration opportunity was assessed with spatial state-and-transition simulation models coupled with carbon stock-and-flow sub-models for three representative landscapes. The net biome productivity (NBP) and cost per unit area of sagebrush shrublands was quantified by simulating restoration over a 25-year period. While seeding showed increased carbon storage, sequestration opportunity was context dependent relative to disturbance history and other environmental factors. We will discuss the strengths and drawbacks of our approach and how STSMs can further be used to provide practical answers to management questions in carbon markets.
Authors: Kori Blankenship1, Randy Swaty1, Leonardo Frid2 & Jim Smith1
Affiliations: (1) The Nature Conservancy, (2) ApexRMS
A key challenge in modeling efforts is locating and manipulating data to parameterize the model. In state-and-transition simulation models (STSMs) developers must define states and the transitions between them. Model developers often use transitions to represent disturbances that change simulation cells from one state to another. Fire is the dominant disturbance driving change in many ecosystems. Published estimates of fire return intervals from proxy records, such as tree-ring fire-scars and soil charcoal provide a high-quality data source for attributing fire transition in STSMs. The raw data used to develop published fire frequency estimates have not, to our knowledge, been used to attribute these models, although they are often publicly available and potentially valuable. Individual tree-ring fire-scar records are widely available through efforts such as the International Multiproxy Paleofire Database and The North American Tree-ring Fire-scar Network at sites around the world. These raw data provide a rich source of information that can be used to enhance our understanding of fire beyond published frequency estimates and to parameterize STSMs. We used tree-ring fire-scar data to attribute fire transitions in an STSM and improve estimates of the resulting state class distributions. These methods are built on free, publicly available data, developed in the coding language R, and readily transferable to any STSM built in SyncroSim’s ST-Sim package. In this presentation we will demonstrate new methods for leveraging individual tree data in STSMs and explore the potential utility of these data beyond fire transitions.
Authors: Ryan Busby1, Johanna Arredondo2, Adam Bauer3, Jacob Berkowitz4, John Brockhaus2, Colin Daniel5, Sean Griffin2, Pat Guertin3, Jinxun Liu6, Jessica Mingione3, Steve Newman7, Yadav Saptoka4, Paul Selmants6 & Benjamin Sleeter6, Camille Stagg6 & Scott Tweddale3
Affiliations: (1) US Army ERDC-CERL, (2) United States Army Geospatial Research Laboratory, (3) United States Army Construction Engineering Research Laboratory, (4) United States Army Environmental Laboratory, (5) ApexRMS, (6) United States Geological Survey, (7) Cold Regions Research and Engineering Laboratory
The Department of Defense is creating a LUCAS-based carbon assessment for installations in the continental United States. This assessment will have an annual time step and utilizes National Land Cover Database and USFS BigMap for inputs at 30 m resolution. Three carbon flux base models are anticipated, with the CBM-CFS3 forest model, IBIS rangeland model, and a wetland model currently in development. Land changes, including timber harvest, fires, and development and their effects on soil carbon fluxes will be included. An overview of the model and status update will be provided.
Authors: Andia Chaves-Fonnegra1 & Christopher T. Spagnolia1
Affiliations: (1) Florida Atlantic University
The drastic mortality of scleractinian corals, and the low probability of recovery to previous coral states, call for a need to understand reef succession in the absence of scleractinian corals structure. However, quantifying the ecological succession of a diverse benthic community after coral bleaching events is challenging. We have applied ST-Sim models to forecast coral reef systems at different scales: microhabitats and coral colonies. However, we face some challenges; 1) the use of a lower spatial scale and resolution based on underwater images and transects, and 2) the implementation of several species-level states and transitions. We want to propose the integration of coral reef systems features in ST-Sim that will allow combinations of species interactions.
Combining a state-and-transition simulation model with a Bayesian decision network
Authors: Anthony Ciocco1
Affiliations: (1) US Geological Survey
State-and-transition simulation models (STSMs) are valuable tools for understanding and forecasting ecological change. However, translating information from STSMs into effective land management decisions can be challenging because STSM outputs are confounded by numerous practical considerations difficult to account for within STSM models. This study presents a novel approach that combines STSM outputs with a Bayesian decision network (BDN) to better support the decision-making process. A LANDFIRE state-and-transition model was parametrized with hypothetical data to address a pressing management concern: feral horses on a 1-million-acre jurisdictional area within the Navajo Nation. The STSM was used to forecast changes in area of state-classes over time, while other decision-relevant variables were incorporated into the BDN. The results identified a hypothetical management portfolio that best achieved three management objectives of wildlife diversity, drought resilience, and livestock carrying capacity while accounting for the social and financial costs of each portfolio option. This approach combined the strengths of STSMs with BDNs by parsing quantifiable variables suitable for STSM modeling from more heuristic concerns that were vital for decision making. Feeding the STSM output into the BDN leveraged the benefits of STSM precision with wholistic managerial thinking about real-world conditions to optimize the decision product.
Authors: Leonardo Frid1, Catherine Jarnevich2, Chris Stockdale3, Colin Daniel1, Gabrielle Ednie1 & Katie Birchard1
Affiliations: (1) ApexRMS, (2) US Geological Survey, (3) Natural Resources Canada
Wildfire is a key driver of landscape level vegetation change across numerous ecosystems and should be included in models used to forecast landscape change for these systems. Approaches for simulating fire growth can range from relatively simple empirically informed statistical distributions of fire size, severity, and frequency through to complex process-based models with detailed parameters describing factors such as fuels, topography, and fire weather. While simple, empirically informed models are often the most parsimonious, a key limitation with this approach is the inability to look at novel ecosystem processes caused by factors such as species invasions and climate change. Process based models of fire behaviour are especially useful when considering such novel ecosystem processes. In this presentation, we review lessons learned from dynamically linking existing fire behavior models with the ST-Sim SyncroSim package for state-and-transition simulation models of landscape change. We identify the benefits of the approach as well as limitations and priorities for future improvements.
Authors: James Furlaud1, Louis Provencher2, Colin Daniel3, Glenn Newnham4, Katrina Szetey5 & Anna Richards1
Affiliations: (1) Commonwealth Scientific and Industrial Research Organisation, Environment Business Unit, Darwin, NT, Australia, (2) The Nature Conservancy, (3) ApexRMS, (4) Commonwealth Scientific and Industrial Research Organisation, Environment Business Unit, Melbourne, VIC, Australia, (5) Commonwealth Scientific and Industrial Research Organisation, Environment Business Unit, Canberra, ACT, Australia
While Syncrosim and ST-Sim are widely used in North America, their use in the rest of the world to simulate state-and-transition models (STSMs) is not as well documented. Australia provides an interesting international case study for implementing ST-Sim/Syncrosim at a landscape scale. Australian ecosystems are generally dominated by eucalypts, among the most fire-adapted woody plants on Earth, and ecological transitions are often triggered by changes in fire regime, rather than individual fires. Australia’s vast, nutrient-poor landscape and small population result in complex management problems related to altered fire regimes, feral animals, and resource extraction. We attempt to develop the first landscape scale STSMs with ST-Sim in Australia using two test cases from opposite ends of the continent: Tasmanian temperate tall wet forest and Arnhem Land tropical savanna. Tasmania’s tall wet eucalypt forests contain the tallest flowering plants on Earth intergrading with temperate rainforest and support most of Australia’s remaining native timber industry. Tropical eucalypt savannas occupy a monsoonal climate in northern Australia, covering almost a third of the continent, and in Arnhem Land have been managed by First Nations people for up to 60,000 years. We detail our approach to building models with ST-Sim using expert elicitation, including the incorporation of indigenous knowledge using co-design and ‘yarning’ principles, and mapping with satellite imagery. We present preliminary results and discuss how our STSMs could interact with climate change projections, and fire spread and tree growth models, to make informative predictions about future ecosystem states and their fire risk under climate change.
Authors: Darcy Hammond1 & Wendel Hann1
Affiliations: (1) University of Idaho
LANDFIRE (LF) is a national project jointly managed by the USDA Forest Service and Department of the Interior to produce geospatial vegetation and fuels layers to aid in cross-boundary management, research, and policy planning and operations. As the LF project approaches its 20-year anniversary, ST-Sim/SyncroSim models are being developed to project fuel and vegetation outcomes for updates and evaluation of future management scenarios. As part of this effort, a Pre-post Disturbance Vegetation-fuel Type (PDVT) and level 1 grouping layers have been created to serve as ST-Sim primary site potential layers. This stratification of site potential improves the predictions of fuel and vegetation outcomes by reducing variation in successional changes following disturbance. Rules were imposed so as not to split Existing Vegetation Types (EVT), to integrate the Fuel Vegetation Type (FVT), and to cluster lifeform variation. The initial process of creating the layer focused on a simplistic process of grouping the EVT/FVTs with similar lifeforms to achieve a target of 400-600 types across the Continental United States. Subsequent analyses (clustering, non-metric multidimensional scaling, multiple response permutation procedure) were used to validate and assess the 101 version. The ST-Sim/SyncroSim models integrate fuel and lifeform states with lifeform response curves generated from field, modeled, or space-for-time data. Many of the PDVT version 101 types lack sufficient data to develop robust curves, so a level 1 hierarchal grouping of PDVT types was developed to increase response data for curve development.
Authors: Ayn Shlisky Hunt1
Affiliations: (1) Agriculture Conservation Experienced Services Program (ACES)
National forest decision-makers seek input on timber harvest volume levels that can be sustained from national forests for long-term planning. The focal area of this study has experienced wide variation in timber volume production over the past 100 years in response to changing ecological, social and economic objectives for and effects of forest management. We used a state-and-transition simulation model (STSM) to compare two timber volume levels across five forest management strategies for one national forest. We started with a set of STSMs for eight potential vegetation types (PVTs) previously developed using the SyncroSim software platform to characterize the natural range of variability of forest ecosystems encompassing the study area. We edited these to create 50 PVT-management area models characterizing differing management emphases and attributed them with 16 forest harvest types and their respective harvest volume estimates. For summary purposes, we also added four administrative and eighteen watershed strata. We ran five management scenarios with two volume targets over 100 timesteps. Overall, high volume targets comparable to those of the recent past were sustainable for about 30-40 years before available volume dropped precipitously for a decade before climbing again. Halving the historical target resulted in sustainability for about 70-80 years, although a similar pattern in volume exhaustion and recovery was observed. All scenarios resulted in movement toward the natural range of variability over the long term. Fire dynamics had a positive effect on volume production. The STSMs, informed by ecological and forest management processes, provide important information about the sustainability of various timber volume targets.
Authors: Catherine Jarnevich1, Skye Pearman-Gillman2, Brian W. Miller3, Anthony Ciocco3, Peder Engelstad4, Jeff Morisette5, Meagan Oldfather3 & Leonardo Frid2
Affiliations: (1) US Geological Survey, Fort Collins Science Center, (2) ApexRMS, (3) US Geological Survey, North Central Climate Adaptation Science Center, (4) Colorado State University, (5) US Forest Service Rocky Mountain Research Station
Many state-and-transition simulation models (STSMs) rely on habitat suitability layers derived from species distribution models (SDMs). But as climates shift and change and management actions and ecological processes play out on the landscape, habitat suitability layers may need to be updated. Applying SDMs fit with current or historic conditions to future scenarios is possible but a dynamic linkage with STSM does not exist. We are developing a new SyncroSim package called WISDM (the Workbench for Integrated Species Distribution Modeling) to update and replace the VisTrails Software for Assisted Habitat Modeling. The WISDM package streamlines SDM workflows, documents inputs and model decisions, and allows users to customize and run existing SDM algorithms. We used WISDM to develop an SDM for the invasive species Canada thistle (Cirsium arvense) where future habitat suitability predictions are influenced by future climate scenarios. To illustrate the linkage between WISDM and ST-Sim, we then incorporated these WISDM outputs into an existing spatially-explicit STSM of rangeland vegetation dynamics in southwest South Dakota considering grazing, invasive plants, fire, and the effects of climate and management on rangeland productivity and composition. The WISDM outputs provided a dynamic layer with Canada thistle habitat suitability shifting with shifting climate. This example highlights the utility of the interaction between WISDM and ST-Sim within the SyncroSim framework. Future work will build on this case study in creating a dynamic linkage where natural disturbances and land management actions modelled in ST-Sim each timestep can be integrated into projections of future habitat conditions using WISDM.
Authors: Ellynne Kutschera1, Miles Hemstrom2, Jack Triepke3, David Anderson4, Charles Maxwell2 & John Kim5
Affiliations: (1) USDA Forest Service Pacific Northwest Research Station, (2) Institute for Natural Resources, Oregon State University, (3) USDA Forest Service Southwestern Region, (4) USDA Forest Service Mountain Planning Service Group, Regions 1-4, (5) USDA Forest Service Pacific Northwest Research Station, Western Wildland Environmental Threat Assessment Center
State-and-transition simulation models (STSMs) have been used in many regions, including the western United States, to model the conditions of natural landscapes and monitor temporal changes from potential management approaches. Ecosystem STSMs typically define vegetation conditions in terms of successional stage and disturbance variables, but many have not accounted for contemporary climate trends. As climate change has the potential for widespread and pronounced effects on ecosystems across the West, projecting climate-related effects has come to the forefront of ecosystem assessment and land management planning. Dynamic global vegetation models (DGVMs) project changes in vegetation composition due to climate and have been widely applied. However, DGVMs typically have coarse spatial scale output and highly generalized representation of vegetation. To create a region-specific model for how climate change can mediate vegetation, we integrated a DGVM with STSMs for Arizona and New Mexico. Vegetation type outputs from DGVM simulations driven with ten global climate models (GCMs) were cross-walked to STSM ecological response units (ERUs) by way of spatial overlay, which forms the basis of transition probabilities. We divided one study area in New Mexico into two climate zones to particularize the representation of vegetation types for specific climate-zone results. Transition rates were specific to climate zones. Future conditions were generated by running STSMs with transition probabilities specific to DGVM output for each GCM. Initial results suggest a redistribution of forest, woodland, and grassland throughout the century. Planning efforts for large areas may be best served by considering climate zones separately within an overall region.
Forecasting the cumulative effects of multiple stressors on breeding habitat for the Species at Risk, Olive-sided Flycatcher (Contopus cooperi) and implications for restoring ecological balance with Indigenous-led forest stewardship Recording
Authors: Andrea Norris1 & Leonardo Frid2
Affiliations: (1) Wildlife Research Division, Science and Technology Branch, Environment Climate Change Canada, (2) Apex RMS
Olive-sided Flycatchers (Contopus cooperi, OSFL) are a steeply declining aerial insectivore and long-distance songbird, breeding in northern open coniferous forests and wintering in South America. The causes for the population decline of this widely distributed bird are likely due to a multitude of stressors. We examined the cumulative effects of multiple anthropogenic and natural disruptions on the future habitat supply for OSFL in one of their core breeding areas in northeastern British Columbia. First, we modeled OSFL habitat suitability by comparing additive and interactive Bayesian generalized linear mixed-effects models (binomial family) that predicted OSFL occurrence in point count surveys (1997-2011) from spatially- and temporally-matched forest inventory data. Flycatcher occurrence was positively associated with small (∼10 ha) 10- to 20-year-old clearcuts, and with 10-100% tree mortality due to mountain pine beetle (Dendroctonus ponderosae) outbreaks. Then, we used the parameter estimates from the best-fit habitat suitability models to inform spatially explicit state-and-transition simulation models to project change in habitat availability from 2020 to 2050 under six alternative scenarios (three management × two fire alternatives). The simulation models projected significant cumulative effects of land use conversion, forest harvesting, and fire, greatly reducing the area of olive-sided flycatcher habitat. The projected losses of habitat in western boreal forest imply that reversing the ongoing population declines of olive-sided flycatcher and other migratory birds will require attention to forest stewardship beyond protected areas. Small-scale and site-specific forest stewardship that enhances biodiversity and Indigenous Peoples’ cultural values, as demonstrated by some Indigenous-led stewardship practitioners, offers one such model that could benefit olive-sided flycatchers and other migratory birds. Future work will explore how biodiversity targets can be better aligned with Indigenous stewardship goals to promote biodiversity recovery and ecosystem resiliency.
Authors: Elizabeth Orning1, Julie Heinrichs2, David Pyke1, Peter Coates1 & Cameron Aldridge1
Affiliations: (1) US Geological Survey, Fort Collins Science Center, (2) Colorado State University
Wildfires are increasingly destroying wildlife habitat in the western United States, and managers need approaches to scope the pace and degree to which post-fire restoration actions can re-create habitat in dynamic landscapes. We developed a spatially explicit state-transition simulation model (STSM) that simulates annual fires, and projects natural vegetation regeneration rates, annual grass invasion, conifer encroachment, and sagebrush revegetation. We cross-referenced the resulting vegetation outcomes with sage-grouse habitat needs to evaluate habitat restoration for three Greater Sage-grouse Priority Areas for Conservation. We compared habitat restoration outcomes among different (a) types of sagebrush revegetation actions (natural regrowth, seeding, planting), (b) durations of actions (single, multi-year), and (c) sizes of area revegetated. In all restoration scenarios, sagebrush cover was generally insufficient to meet habitat requirements for at least a decade post-fire, and the best habitat conditions declined or remained at low proportions of landscapes for over 50 years post-fire. Under current fire patterns, the pace of habitat restoration is likely to lag behind losses from wildfire. Our results underscore the need for broad-scale habitat restoration strategies that expand the ability to reestablish sagebrush in large, burned areas, as well as strategies for defining which areas should be prioritized for revegetation within landscapes. By gauging potential benefits of restoration decisions, our approach can provide information to aid choices on where to invest time, money, and effort, how best to mitigate losses, and a means to plan long-term restoration and recovery of landscapes across the sagebrush biome.
Authors: Louis Provencher1, Sarah Byer1, Kevin Badik1 & Michael Clifford1
Affiliations: (1) The Nature Conservancy
Ecological departure is a non-spatial metric applied to single ecological systems measuring dissimilarity between the distributions of observed and expected non-stochastic reference proportions of vegetation classes within an area. Project goals were to create spatially explicit measures of ecological departure incorporating stochasticity for each ecological system and all ecological systems from a central Nevada USA landscape. Spatially explicit ecological departure was estimated from a radius from each pixel governed by a distance-decay function within a moving window. Variability was introduced by spatially simulating with state-and-transition simulation models replicated climate time series for each spatial reference condition and calculating departure per spatial replicate. Single-system spatial ecological departure was highly and extensively departed, except for one area of low-elevation groundwater-dependent systems. Variance of spatial ecological departure was extensively low, except in areas of lower ecological departure, despite vegetation differences among replicates. The multisystem ecological departure exhibited lower ecological departure. A spatial overall of traditional ecological departure is warranted for efficient land management as results are concordant between non-spatial and spatial metrics; however, rapid coding languages will be required. Spatially explicit ecological departure of both single and multiple systems facilitate localized vegetation and wildlife habitat management and land protection decisions.
Authors: Bronwyn Rayfield1, Carina Rauen Firkowski1, Frédéric Charron2, Marianne Cheveau3 & Pauline Suffice4
Affiliations: (1) ApexRMS, (2) Conseil régional de l’environnement de l’Abitibi-Témiscamingue, (3) Ministère des Forêts, de la Faune et des Parcs, (4) Université du Québec en Abitibi-Témiscamingue
Habitat connectivity and ecological corridors are often critical elements of successful wildlife management plans. Connectivity assessments have traditionally assumed static landscape conditions, primarily due to data and computational limitations. These limitations have been overcome through increased availability of high-resolution spatio-temporal datasets, easier access to cloud and high-performance computing, and improved computational efficiency and parallelism of connectivity software. Despite these advancements, static-landscape connectivity assessments are still the norm due to workflow management challenges associated with linking models of landscape change and habitat connectivity. Here, we present a pipelining approach to generate forecasts of habitat connectivity that are responsive to projected changes in vegetation and climate. We implemented the approach by chaining together two open-source models: ST-Sim for modeling landscape change and Omniscape for modeling habitat connectivity. Both models are accessible as SyncroSim packages, simplifying the process of constructing reusable forecasting workflows by seamlessly connecting multiple predictive models and datasets. We demonstrated the approach using a case study of future habitat connectivity of American marten in a forest management unit in western Quebec, Canada. We parameterized the model of forest dynamics using the historical pattern of wildfire along with the assumptions of the most recent forest management plan for the region. We projected the effects of different timber harvesting scenarios on marten habitat, and its consequence for marten connectivity at the scale of individual home ranges and natal dispersal. With this case study, we demonstrated how SyncroSim’s infrastructure can be leveraged to connect landscape change and habitat connectivity models, thereby addressing the outstanding challenge in generating assessments of dynamic-landscape connectivity.
Authors: Anna Richards1, Fiona Dickson2, Suzanne Prober1, Kristen Williams1, Becky Schmidt1 & Stephen Roxburgh1, Helen Murphy1, Garry Cook1, Amy Warnick1, Daniel Metcalfe1, James Furlaud1, Katrina Szetey1, Rebecca Jordan1, Glenn Newnham1, Sana Khan1 & Ning Liu1
Affiliations: (1) CSIRO, (2) Department of Climate change, Energy, the Environment and Water, Australian Government
For the past seven years, a framework of conceptual dynamic ecosystem models for Australia has been under development, called the Australian Ecosystem Models (AusEcoModels) framework. The framework has synthesised and summarised scientific knowledge of ecosystem dynamics, including via expert elicitation of land managers, and described this knowledge in a set of 48 conceptual archetype models. This set of models provides a disturbance-based classification of Australia’s terrestrial ecosystems in their reference condition (one with highest ecological integrity). The AusEcoModels framework describes a methodology for using high-level archetype models to define locally-relevant ecosystem reference states and transitions to alternative states resulting from recent and transformative exogenous disturbances. Thus, archetype models provide a basis for a nationally consistent compilation of dynamic state and transition models for Australia. In this presentation, we outline recent applications of the framework to regional ecosystem extent and condition accounts in the Western Australian wheatbelt and the Flinders, Norman and Gilbert River catchments in Queensland. We also outline plans for using the framework within ST-Sim to explore trajectories of ecosystem change under future climate and land management, such as understanding landscape bushfire risk and exploring futures in mixed-use agricultural landscapes.
A new water stock-flow model examining land-use and climate change impacts on groundwater balance along the Central Coast of California
Authors: Paul Selmants1, Tamara Wilson1, James Thorne2, Ryan Boynton2, Ruth Langridge3 & Tim Thomas4
Affiliations: (1) US Geological Survey, (2) University of California, Davis, (3) University of California, Santa Cruz, (4) University of California, Berkeley
Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California’s Central Coast, new land-use related water demand and decreasing groundwater recharge may stress already depleted groundwater basins. We developed a coupled land-use change and water stock-flow simulation model to examine how future climate and land use change will impact groundwater balance in five counties along the Central Coast of California from 2010 to 2060. This spatially-explicit (270 m) model incorporated groundwater recharge estimates based on a “cool wet” and a “warm dry” climate future from a spatially explicit hydrological process-based model. We also incorporated two urbanization projections representing either recent historical trends or state-mandated housing growth requirements. Urbanization projections were based on spatial output from a parcel-based regional urban growth model. Agricultural land change projections were based on historical trends from remote sensing data. We estimated land-use related human water demand based on historical trends and tracked water use over the simulation period along with annual agriculture return flows and drought-induced fallowing. We estimated annual projected changes in groundwater balance, calculated as the difference between land-use related water demand and recharge from the combination of excess precipitation and agricultural irrigation return flows. Our results reveal climate and land use impacts on future groundwater demand and groundwater balance, highlighting where and when continued overdraft may occur. Such information can be used to inform strategies for sustainable groundwater supply management.
Authors: James L. Smith1
Affiliations: (1) The Nature Conservancy, LANDFIRE
The LANDFIRE Program is charged with providing current fuel and vegetation spatial data for all lands in the Continental US, Alaska, Hawai’i and primary island territories, now delivered each year incorporating as many landscape changes from the previous year as possible. To fulfill this important and challenging goal, the LANDFIRE Program uses ST-Sim as the update engine because of its flexible architecture and scalability. The mechanics of the update process will first be described followed by a discussion of the pros and cons of the approach.
Authors: Terry Sohl1
Affiliations: (1) US Geological Survey
Understanding the dynamic nature of US lands and ecosystems is critical for supporting US Administration priorities such as a National Nature Assessment, Natural Capital Accounting, and Nature-based Solutions. This includes developing multidisciplinary approaches for mapping past, present, and future landscape change, and the economic, ecological, and societal impacts that result from that change. The US Geological Survey’s (USGS) Forecasting Scenarios of Land Use (FORE-SCE) model was developed to “temporally extend” USGS land cover forecasts backwards and forwards in time, for dates when supporting remote sensing data are not available. The model accounts for exogenous drivers of land-use change such as climate and socioeconomic scenarios and has been widely used for assessing land use feedbacks with biodiversity, carbon and greenhouse gases, and hydrology. However, FORE-SCE has always been an internal model for USGS use, without a publicly available version. USGS has also had difficulties in developing a strategy for model coupling as the model becomes increasingly interdisciplinary. USGS has recently proposed a new strategy for supporting US Administration priorities that requires a more robust and open-source approach to interdisciplinary modeling. We are investing in the ingest of FORE-SCE capabilities into SyncroSim to facilitate needed interdisciplinary modeling for USGS needs, including a linkage of FORE-SCE with the Land Use and Carbon Scenario Simulation (LUCAS) model. An integrated FORE-SCE capability within SyncroSim will allow for multi-scale assessments of land-use change and impacts on ecosystem services upon which society depends.
Authors: Christopher Spagnolia1, Andia Chaves-Fonnegra1,2 & David S. Gilliam3
Affiliations: (1) Florida Atlantic University Harbor Branch Oceanographic Institute, (2) Florida Atlantic University Harriet Wilkes Honors College, (3) Nova Southeastern University, Halmos College of Natural Sciences and Oceanography
Reef ecosystems symbolize diversity and provide billions in societal services. However, thermal anomalies have favored hard coral phase shifts to alternative organisms. Yet, we scarcely comprehend coral reefs ecological succession following thermal anomalies and how benthic community functionality, heterogeneity, and stability are affected. The aim of this research was to evaluate to what level macroalgae, hard and soft coral, and sponge states compose future reefs and what is their propensity for interaction at the microhabitat level using predictions concordant with the IPCC RCP 4.5 and 8.5. An ST-Sim was created using annual benthos transitions in nine photoquadrats from 2003-2018 in Broward County, Florida. State-transition matrices (n=124) spanning 197 transitions across 15 states parameterized the model. A submatrix encapsulating the 2014-17 global bleaching event was incorporated to perturb the 2018 community for the following 100 years. Model outputs were validated against empirical proportions. Sensitivity analysis highlighted the responsiveness of succession, recruitment, and mortality to input variation. Annual severe bleaching respective to RCP 8.5 is predicted to increase specific interactions by 7% in 2043. Solitary hard corals will persist at low proportions and will experience competitive exclusion due to a 44% and 80% increase in macroalgae and soft coral-sponge interactions, respectively. Results suggest thermal anomalies trigger competitive interactions between aggressive, thermally adapted species of the sponge-dominated reef community. This model constitutes an application of ST-Sim to predict coral reef community succession and changes in competitive interactions.
Authors: Camille L. Stagg1, Colin Daniel2, Bronwyn Rayfield2, Eric Ward1, Benjamin Sleeter3, Melissa M. Baustian1, Bingqing Liu4, Yushi Wang4 & Allison DeJong4
Affiliations: (1) US Geological Survey, Wetland and Aquatic Research Center, (2) ApexRMS, (3) US Geological Survey, Western Geographic Science Center, (4) The Water Institute, (5) Louisiana Coastal Protection and Restoration Authority
Ecosystem- and landscape-level assessments of carbon sequestration are increasingly required by local, state, and federal decision makers to inform land management and climate mitigation policies. Because coastal wetland ecosystems can effectively sequester carbon, land management that enhances wetland carbon sequestration has been increasingly recognized as a viable solution for climate mitigation. Scenarios that focus on carbon sequestration in wetlands will play an important role in climate action planning; therefore, the ability to quantify historic, current, and future carbon sequestration in wetland ecosystems is critical to developing an accurate and effective mitigation strategy. Developed over the past decade, the Land Use Carbon Simulator (LUCAS) model has informed management planning in terrestrial ecosystems at various scales. The focus of this presentation is to highlight recent advances in the LUCAS model development to incorporate critical wetland-specific carbon fluxes, including soil carbon accumulation and lateral flux of dissolved carbon. We will present restoration scenarios from multiple case studies to highlight the importance of these wetland carbon fluxes to overall ecosystem- and landscape-level carbon assessments of land management. Finally, we will illustrate how these spatially-explicit projections can be used in concert with national, regional and state restoration plans to directly inform climate mitigation policies.
Authors: Chris Stockdale1
Affiliations: (1) Natural Resources Canada
Over the past 17 years, the primary tool used to evaluate wildfire likelihood throughout Canada has been the Burn-P3 model. Burn-P3 is a Monte Carlo simulation model that uses probabilistic draws of fire ignition location, fire weather, and duration of burning, and then feeds this information to a deterministic fire growth model (Prometheus) in order to reveal fundamental patterns of wildfire spread on a given landscape. While innovative when created by the Canadian Forest Service (CFS) in 2001, it has not kept pace with evolution in computing power and architecture. In order to speed up processing time, introduce numerous new features, and increase model flexibility, the CFS redesigned this model in partnership with ApexRMS and released the new BurnP3+ in October 2022. This talk will describe the expanded new features and potential applications of BurnP3+. BurnP3+ is no longer a stand-alone entity, but instead embeds itself in the SyncroSim modeling conductor platform developed by ApexRMS. SyncroSim is a proprietary freeware application that enables models to interact with each other, has a GUI, and is fully R-compatible. The core elements of BurnP3+ that make the various draws of weather, ignition location, burning conditions, etc., are now written as R-scripts, enabling users to customize how the model functions. While Burn-P3 was dependent on the Prometheus fire growth model (FGM), BurnP3+ users can select either Prometheus, or a cellular-based FGM called Cell2Fire, and other FGMs can be added in the future with relative ease. We have also linked BurnP3+ to the ST-Sim vegetation dynamics simulator, which now enables stochastic fire dynamics to interact with vegetation succession. The model can be hosted on cloud servers or run on high performance clusters to cut runtime dramatically. We have also built in automated routines for creating model inputs, as well as an in-depth results explorer. Running multiple scenarios is as simple as swapping out the desired inputs for new ones.
Authors: Randy Swaty1, Priscilla Nyamai2 & Megan Dettenmaier1
Affiliations: (1) The Nature Conservancy, (2) Grand Valley State University
Given the complexity of natural ecosystems, instructors are tasked with finding creative ways to teach students key processes such as disturbances and succession. Since 2020, we have developed and experimented with SyncroSim-based curricula as a tool for educating undergraduates on the complexities of ecological modeling and process-based learning. As part of the course, students run the models, interpret results, introduce model perturbations, and explore data visualizations and conclusions. Based on our experience, we developed a conceptual teaching model that can guide the process of integrating ecological modeling into any hands-on learning environment. Our talk will summarize best practices for delivering successful learning opportunities informed by real-world teaching experience while outlining next steps for instructors looking for new tools to add to their toolbox for teaching and experimenting with ecosystem functions in a lab environment.
Authors: Bryan Tarbox1, Elizabeth Orning1, Catherine Jarnevic1, Cameron Aldridge1 & James Meldrum1
Affiliations: (1) US Geological Survey
Cheatgrass (Bromus tectorum L.) and other invasive annual grasses (IAG) continue to spread within the sagebrush (Artemisa spp.) biome of the western United States, degrading plant communities and wildlife habitat, decreasing forage for ranching livelihoods, and heightening wildfire risk. Effective management of IAGs requires long-term strategic planning and action across the sagebrush biome, but the cost-benefit implications of potential treatments and spatial prioritizations are not well understood, especially cumulative effects over broad spatiotemporal extents outlined for strategies like the Sagebrush Conservation Design (SCD). To evaluate the costs and effects of implementing SCD strategies (“Defend and Grow” core sagebrush areas, “Mitigate” IAG impacts) across the biome, we are developing a spatially explicit state-and-transition simulation model (STSM) of IAGs (e.g., cheatgrass) informed by expert knowledge and empirical research. In consultation with natural resource managers and other stakeholders, we developed four scenarios that vary according to different budget allocations, types of IAG treatments, and SCD management strategies. We highlight the benefits of engaging local and regional rangeland experts in the model development process, as well as the influence management strategies have on the ability to reverse, slow, or minimize IAG impacts to sagebrush systems. Outputs from our model will provide insights for implementation of the SCD and help managers compare the cost effectiveness of contrasting approaches to IAG management.
Using the LUCAS-BLUE model to estimate the carbon impacts of wetland loss in coastal Louisiana
Authors: Eric Ward1, Camille Stagg1, Colin Daniel2, Bronwyn Rayfield2, Rachel Sleeter3, Lisamarie Windham-Myers3, Kevin Kroeger4, Benjamin Sleeter5, Jinxun Liu5, William Conner6, Richard Day1, Ken Krauss1, Meagan Eagle4, Sheel Bansal7, Karen Thorne8, Kevin Buffington8, Scott Jones9, Bergit Uhran10 & Zhiliang Zhu11
Affiliations: (1) US Geological Survey, Wetland and Aquatic Research Center, (2) ApexRMS, (3) US Geological Survey, Water Resources Mission Area, (4) US Geological Survey, Woods Hole Coastal and Marine Science Center, (5) US Geological Survey, Western Geographic Science Center, (6) Clemson University, Baruch Institute of Coastal Ecology and Forest Science, (7) US Geological Survey, Northern Prairie Research Center, (8) US Geological Survey, Western Ecological Research Center, (9) University of North Florida, (10) University of Tennessee Knoxville, (11) US Geological Survey, Ecosystems Mission Area
Coastal wetlands store and sequester large amounts of carbon that are at risk due to wetland loss from sea-level rise. We developed a model of carbon cycling in tidal wetlands of the conterminous United States (CONUS) to assess 1) baseline carbon pools and fluxes in coastal wetlands and 2) land use change impacts on carbon sequestration in coastal wetlands. We adapted the Land Use and Carbon Simulator (LUCAS) model for use in tidal wetland ecosystems using both site-level carbon cycle data and remotely-sensed land use and land cover (LULC) data. This new version called LUCAS-BLUE (for Burial, Lateral flux, Uptake and Emissions) employs a modified carbon stock and flow model that reflects the complex carbon dynamics of coastal wetlands. As a test case, we calibrated LUCAS-BLUE for the tidal portions of the Mississippi River Alluvial Plain (MRAP), using measurements of carbon pools and fluxes across 24 sites. This region contains approximately a third of the tidal marshes in CONUS and has experienced a high rate of wetland loss to open water. While the estimated carbon lost to LULC change (primarily wetland to water conversions) over 20 years represents only 1% of ecosystem carbon stores, net sequestration estimates would have been 25% greater in the absence of LULC change. Our results highlight the sensitivity of carbon sequestration estimates to assumptions about the fate of soil carbon when coastal wetlands transition to open water. LUCAS-BLUE provides a platform for projecting the carbon impacts of future wetland losses in MRAP and throughout CONUS.
Authors: Tamara S. Wilson1, Elliott Matchett2, Kristin Byrd1, Erin Conlisk3, Matthew Reiter3, Cynthia Wallace1, Lorraine E. Flint1, Alan L. Flint1, Brian Joyce4 & Monica M. Moritsch1
Affiliations: (1) Western Geographic Science Center, (2) Western Ecological Research Center, (3) Point Blue Conservation Science, (4) Stockholm Environment Institute
Approximately 90% of naturally occurring wetlands in California’s Central Valley have been lost or fragmented because of human land use. Despite this degradation, the region remains a critical North American migratory corridor for wintering waterfowl, sustained through a complex system of managed wetlands and post-harvest flooded agriculture. Climate variability and human water demand directly impact the amount of water available to create this essential habitat. To identify potential habitat availability given projected future climate and land use change, we integrated a hydrologic and water-use model with a spatially-explicit land use change model. The Water Evaluation and Planning model, adapted for Central Valley’s waterbird habitat (WEAP-CVwh), was used to model future land use and climate scenarios from 2011 to 2101. The WEAP-CVwh outputs were summarized and ingested as land use transitions and flooding probabilities for the spatially explicit Land Use and Carbon Scenario Simulator (LUCAS) model. We modeled 5 stakeholder-informed scenarios representing varied climate, restoration, and land change, comparing divergent outcomes at 270 m2 resolution, generating annual projections of future land use and flood duration probabilities. This ensemble modeling approach has produced the first future waterfowl habitat maps based on climate-driven water availability, human land-use related water demand, and historical flooding information. Declining water availability is the dominant driver of habitat loss across scenarios. The hot/dry scenarios showed the greatest declines in January flooded area by 2101 — an important month for overwintering waterbirds. In contrast, higher water supplies in wet climates drive perennial cropland conversion which also leads to potential habitat losses. Potential flooded cropland declined (25 and 33%) under warmer/wetter climate conditions due to this conversion to perennial crops, exposing habitat vulnerability. Overall, climate-driven loss of water availability had a greater impact on flooded habitat availability than land-use change. When combined, climate change and the conversion of potentially flooded cropland to perennial cropland will threaten future waterbird habitat particularly in January, the peak of the migratory bird season, even when current habitat restoration goals are met. Our analysis demonstrates that stakeholder-informed scenario analysis can identify target areas for potential habitat change, vulnerability, and conservation. By examining competing demands for water from social and ecological systems under a changing climate, we can better inform land managers as to likely future outcomes for restoration goal setting and mitigation planning.