Research Article

A Review of Membrane Computing Models for Complex Ecosystems and a Case Study on a Complex Giant Panda System

Table 1

Summary of studies that have used a new frontier approach, termed PDP systems with different constraints, to assess the number of endangered species under conditions of different types.

Case studyRegion/conditionComments

Colomer et al. [71]
Bearded vulture
Region: the cliff-nesting and territorial mountains in the Catalan Pyrenees (Northeastern Spain)
Condition: single-environment
(2, 1) with two electrical charges (0 or +), where the skin region is used to fix reproduction and mortality and the inner one to fix feeding; five wild and domestic ungulates are included as carrion (prey) species.

Cardona et al. [72]
Bearded vulture
Region: Catalan Pyrenees (NE)
Condition: single-environment
The structure of this system is the same as that of [69]. The only difference is this system is a dynamic P system with the probabilistic approach, while the former used stochastic constants (a rule can be used when the reaction condition reaches a given constant).

Cardona et al. [73]
Scavenger birds
Region: Catalan Pyrenees (NE)
Condition: single-environment
(2, 1) with two charges. This system considers not-nomadic species (also called invasion alien species—see part (b) in Section 3) and density regulation in order to coexist. Subsequently, this model contains 13 species including two new scavenger birds in competition.

Colomer et al. [70]
Pyrenean chamois
Region: Catalan Pyrenees (NE)
Condition: multienvironment
(11, 4, 1) with three electrical charges (−, 0, +). The model mainly considers four influencing factors: introduced disease such as pestivirus infection, climate change (refer to part (a) in Section 3), hunting, and migrations between areas.

Colomer et al. [74]
Bearded vulture
Region: the cliff-nesting and territorial mountains in the Catalan Pyrenees (Northeast, Spain).
Condition: multienvironment
The computational model of the probabilistic P system is the same as that of [70] (refer to the third case in this table for the detailed introduction about the model of a P system).

Cardona et al. [75]
Scavengers/zebra mussel
Region: Catalan Pyrenees (NE Spain)/a fluvial reservoir (Riba-roja-Ebro river, NE Spain)
Condition: multienvironment
For the scavengers, the structure is the same as [69]; hence, many details have been skipped. For mussels, the structure is (5, 17, 1) with tree electrical charges. This model mainly focuses on factors such as water temperature and its effect on reproduction (see part (a) in Section 3 for impacts of the factor), fixation of the mussel to the substrate, movement of larvae, and density regulations.

Colomer et al. [76]
Scavenger birds
Region: Catalan Pyrenees (Spain)/Pyrenean and pre-Pyrenean mountains
Condition: multienvironment
(2, 2) with the environment change module, where any of species will move to another area when the capacity reaches a threshold. The model studied: (a) 13 species, including three avian scavengers (three types of vultures) as predator species plus six wild ungulates and four domestic ungulates as prey species; (b) the interactions between species; (c) the communication between two areas; and (d) load capacity regulation.

Colomer et al. [77]
Plant communities
Region: (sub) Alpine (NE Spain)
Condition: multienvironment
(5, 5) with climatic variability (part (a) in Section 3) and orographic factors (part (c)). More importantly, the model first emphasizes on the impact of the plant community module on population dynamics. The remaining modules are similar to those in the previous models.

Colomer et al. [78]
A carnivore that predates on ungulates and five ungulates
Region: Catalan Pyrenees (NE)
Condition: single-environment
(11, 2) with three electrical charges. This model mainly considers the impacts of environment factors such as weather, orography, and soil conditions on carnivore size.

Margalida et al. [79]
Scavenger birds
Region: Catalan Pyrenees (NE)
Condition: multienvironment
The model only considers wild ungulates due to the limitation of domestic carcasses. Undoubtedly, this causes an impact on the biomass. The model of the (2, 2) structure verified that when considering only wild ungulates, the ecosystem cannot offer enough food for predators.

Margalida and Colomer [80]
European vultures
(i) Bearded vulture
(ii) Egyptian vulture
(iii) Cinereous vulture
Regions: 10 municipalities in Catalonia, Northern Spain
Food source: the four scenarios of food availability considered
Condition: multienvironment
Taking 10 areas and 4 avian scavengers as the research object, the model considers the impact of climate variations, such as seasons (summer and winter) (part (a) in Section 3), food shortage, density regulation, and changes in species habitats (insufficient resources), on population dynamics.

Colomer et al. [81]
Zebra mussel
Region: reservoir of Ribarroja
Condition: multienvironment
(40, 17), where the first 20 membranes are used for 20 weeks of reproductive cycle, 16 for the weeks of the second reproductive cycle, and the last two membranes are used to handle regulation and mortality.

Huang et al. [82]
Captive giant panda
Two regions: Chengdu Research Base of Giant Panda Breeding (GPBB)/China Conservation and Research Centre for Giant Panda (CCRCGP) (Wolong)
Condition: single-environment
(2, 1), where two membranes are used to evolve and store object information; the evolution process of the species: RMF + rescue module, where RMF is also modified as RFM, FMR, or other forms, showing the robustness of the system independently on the order of the modules.

Tian et al. [99]
Captive giant panda
Two regions: GPBB/CCRCGP
Condition: single-environment
The membrane structure is the same as in [82], and the only difference is that the release module is added to the previous module, that is, RMF + rescue module + release module.

Bernardini and Gheorghe [7]
The quorum-sensing regulatory networks of the bacterium Vibrio fischeri
Region: marine
Condition: single-environment
Evolutionary rule choices: in the stochastic way
(9, 1), where multisets of objects are used to model bags or soups of chemicals, whereas rules are used to model generic biochemical processes.

Romero-Campero and Pérez-Jiménez [83]
Quorum sensing in Vibrio fischeri
Region: marine
Condition: multienvironment
Rule choices: stochastic approach
(N, 25), multicompartmental P system, where N bacteria are randomly placed inside a multienvironment with 25 different regions, that is, there is an uncertain number of bacteria in each region.

Valencia-Cabrera et al. [84]
Gene regulatory networks
Condition: single-environmentThe first membrane computing model applied to reconstruct the behaviour of logic networks of species with PDP systems.

Valencia-Cabrera et al. [85]
Gene regulatory networks
Case study: Arabidopsis thaliana
Condition: single-environment
Based on [84], P systems are used to reproduce a logic gene network of (real) Arabidopsis thaliana in order to regulate the flowering processes.