Modeling diel vertical migration with membrane computing

Abstract

Diel vertical migration (DVM) is an important ecological phenomenon in which zooplankton migrate vertically to deal with trade-offs associated with greater food availability in shallow waters and lower predator risk in deep waters due to lower light availability. Because of these trade-offs, DVM dynamics are particularly sensitive to changes in light intensity at the water surface. Therefore, changes in the proportion of cloudy and sunny days have the potential to disrupt DVM dynamics. We propose a new membrane computing model that captures the effect of cloud cover on DVM in Daphnia, and we use it to explore the impacts of an increased proportion of cloudy days that are predicted to occur with climate change. Our 2-dimensional, spatially explicit model integrates multiple trophic levels from abiotic nutrients to Daphnia predators. We analyzed the effect that different proportions of cloudy and sunny days throughout the summer have on our model. The model simulations suggest that an increase in sunny days promotes a high phytoplankton concentration near the surface but does not necessarily promote an increased abundance of Daphnia. Our model also suggests that a higher proportion of cloudy days would increase Daphnia abundance due to a shift in the vertical distribution of Daphnia populations towards superficial waters. Our results highlight that climate changes in multiple regions will affect animal migrations leading to altered food web dynamics in freshwater ecosystems, and emphasize the potential of membrane computing as a modeling framework for spatially and temporally explicit ecological processes.

A Representation of Membrane Computing with a Clustering Algorithm on the Graphical Processing Unit

“…According to Step 2 of Balancing_Occup_Sync_Approach (Figure 7, line 0), all three dependent objects are assigned to one thread. For a case involving six objects within a membrane, all six would be assigned to N Tx = 2 threads, meaning that N Ty = 64 membranes are needed for assignment to the same thread block, resulting in NTx × NTy ≈ 128 threads according to Equation (2). Communication between threads is a very time-consuming process.…”

“…Membrane systems are a class of computational models that inspired their computation from cell biology. Membrane systems have been applied in different areas [1], including zooplankton migrate vertically in system biology [2], image processing [3,4], robot path planning problem [5], power systems as well as address highly-complex computational problems such as traveling salesman, knapsack, Hamiltonian path and satisfiability [6][7][8][9][10]. The main elements of a membrane system include (i) structure, including its delimiting compartments; (ii) multisets of objects; (iii) biochemically-inspired rules.…”

Homeostasis tissue-like P systems with cell separation

“…To design biocomputers based on membrane computing, some scholars have studied arithmetic operations [16] and logical expressions [17]. Based on the existing theory of membrane computing, many practical applications have been achieved, such as optimization algorithms [18,19], biology [20,21], fault diagnosis [22,23], and mobile robots [24]. Recently, there have been some excellent results in the field of machine learning [25][26][27] .…”