[Serial Number Game Plant Firefighter Simulator 2014 34
Iberio Ralda
Abstract. The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.
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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.
Invasive species, like native species, can be influenced by many interacting abiotic and biotic factors. These factors, including climate, can influence rates of spread across a landscape and patch infilling in established locations, adding variability to invasion dynamics (e.g.,6). A patch can be defined as the perimeter of an infested area, and infilling is the increase in cover within that defined patch. Spread occurs when patch perimeters expand or when new satellite patches establish. Spread and infill, particularly in the arid southwestern United States, may be tied to fluctuating resources such as interannual variation in precipitation7. Patch infilling is likely tied to the number of seeds produced by a patch and seedling germination and survival, which can be influenced by climate8.
There are many types of models that can be used to evaluate ecological change. Spatially explicit models include, among others, invasive species spread models, individual based models, network models, or potential distribution models. There are also aspatial models such as vegetation dynamics models used to quantify vegetation class amounts within a landscape. Area- or state- based models that inform how the condition or composition of a piece of land may change over time can provide key information to managers who are concerned with the future condition of a landscape.
Buffelgrass is an invasive perennial grass native to Africa that has been introduced widely as a forage species and for erosion control16. Following its introduction, buffelgrass has spread and become invasive in many natural areas globally where it has various impacts on native ecosystems. Various species distribution models exist for buffelgrass, including global and regional models under current and future climate that provide information on its potential distribution17,18,19. In the Sonoran Desert, conversion of native vegetation to buffelgrass savanna has altered ecohydrology20, altered fire regimes21,22, and negatively impacted populations of native species23,24,25. Altered fire regimes and impacts to native populations have also been observed in Australia26,27,28.
Experts on the buffelgrass invasion in southern Arizona have identified vegetation conversion, fire, and the loss of biodiversity and native species, especially the loss of saguaro cacti (Carnegiea gigantea (Engelm.) Britton & Rose), as the primary threats caused by the buffelgrass invasion in the Sonoran Desert29. The introduction of buffelgrass to the Sonoran Desert, which includes many non-fire adapted species, leaves managers with a high degree of uncertainty about the trajectory of the invasion and associated landscape changes because no analog ecological conditions exist that would allow them to make more than broad, general predictions30. There is a critical need to understand the nature of the threat posed to native ecosystems by this invasive species to effectively allocate control efforts and ensure long-term land management goals are met. Misjudging the dynamics of the situation may waste scarce resources and allow priority resources or locations to be adversely and irreversibly impacted.
Buffelgrass growth and vigor in desert ecosystems can be influenced by the amount of precipitation during a growing season31,32, and the effect of variable precipitation on buffelgrass infill rates is a primary uncertainty identified by local experts29. The southwest region has exhibited wide annual variation in monsoon season precipitation33, with the late 1970s and 1980s being relatively wet compared to past and current decades34. Previous simulation modeling to evaluate the buffelgrass problem in Saguaro National Park did not include an evaluation of the sensitivity of the simulations to model initialization or to uncertainties in model parameterization, limiting the ability of simulations to capture the range of potential future landscape conditions29. Model initialization describes landscape starting conditions, including landscape susceptibility to buffelgrass invasions and where and how much buffelgrass is on the landscape. Uncertainties in model parameterization include uncertainty in patch infill rates and uncertainty in how these rates may vary with precipitation29.
Saguaro National Park (here forth referred to as SAGU), located in the Sonoran Desert in southern Arizona, is divided into two units separated by the city of Tucson (Supplementary Figure S1 online). The 27,279 ha Rincon Mountain District (RMD) located to the east of Tucson has a greater elevational difference and includes a desert ecosystem, grassland ecotone, and high-elevation forest. The 9726 ha Tucson Mountain District (TMD) located to the west of Tucson is smaller, sits at a lower elevation, and includes only the desert ecosystem. Despite the geographic separation the two units are managed as a whole, so we modeled the two districts together in our simulations. Climate, recorded by the Tucson International Airport Weather Station (period of record 6/1/1946 to 6/9/2016 from Western Regional Climate Center), is arid/ semi-arid characterized by monsoonal precipitation (average of 29 cm/year) with an average January minimum temperature of 3.7 C and average July maximum temperature of 37.4 C.
Regional experts defined the transition between buffelgrass cover classes as deterministic based on amount of time spent in a state class, but expressed uncertainty related to the amount of time required in each state before transitioning. We elicited values from regional experts related to the time required before transitioning to the next buffelgrass cover class including lower-quartile, median, and upper-quantile estimates for each transition time29. We refer to these transition times as the patch infill rate.
We implemented the STSM described above using the stsim base package (version 3.1.219) with the stsim-farsite add-on package (version 3.1.21) running on SyncroSim version 2.0.41. The stsim-farsite package integrates the FARSITE fire area simulator software version 4.1.05536 into ST-Sim. We provided FARSITE with current time step fuel model attributes of each cell in the landscape along with the number of ignitions (one per time step) and weather information (see37 for details), and FARSITE then produced fire perimeters at each time step. If ignitions occurred in non-burnable areas, the perimeter would be zero for that time step.
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