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ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks.
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Two fundamental challenges have persisted since the inception of FLMs: (1) balancing realistic simulation of ecological processes at broad spatial and temporal scales with computing capacity, and (2) validating modeled results using independent, spatially explicit time series data.
Because the STATSGO database has less detailed information than the SSURGO database, the soil organic matter and nutrient supplies differ, which affects the simulation of ecological processes such as net primary production and soil organic decomposition.
The worked example developed in our simulations converts informal notions about the evolutionary and historical determinants of ecological processes into a model that makes specific predictions about how past ecological conditions alter the selective pressures on the component species and hence modifies their future ecological behaviours.
Complications involving a variety of ecological processes are discussed.
By understanding the multiplicative and stochastic nature of ecological processes, scientists can better understand the structure and dynamics of Earth's largest and most diverse ecological systems.
Predator-prey interaction has always been an important issue in mathematical modeling of ecological processes [1].
Empirical data quantifying the feedbacks of ecological processes are rare and require long-term observations.
The combination of ecological process models and satellite-derived information can involve several strategies.
Hydro-ecological modelers often use spatial variation of soil information derived from conventional soil surveys in simulation of hydro-ecological processes over watersheds at mesoscale (10 100 km2).
Our present simulations of ecological tasks show that this trade-off also exists in more complex chemotactic scenarios.
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