An approximate Bayesian algorithm for training fuzzy cognitive map models of forest responses to deer control in a New Zealand adaptive management experiment

Ecological Modelling

Volumn 240, Issue , 2012, Pages 93-104

  Ramsey, David S L ^a   Forsyth, David M ^a   Veltman, Clare J ^b   Nicol, Simon J ^a,f   Todd, Charles R ^a   Allen, Robert B ^c   Allen, Will J ^c   Bellingham, Peter J ^c   Richardson, Sarah J ^c   Jacobson, Chris L ^d   Barker, Richard J ^e  

^a ARTHUR RYLAH INSTITUTE FOR ENVIRONMENTAL RESEARCH   (Australia)

^b DEPARTMENT OF CONSERVATION   (New Zealand)

^c LANDCARE RESEARCH   (New Zealand)

^d UNIVERSITY OF QUEENSLAND   (Australia)

^e UNIVERSITY OF OTAGO   (New Zealand)

^f SECRETARIAT OF THE PACIFIC COMMUNITY   (New Caledonia)

Author keywords

Approximate Bayesian Computation; Fuzzy logic; Herbivory; Seedling growth

Indexed keywords

ABC MODEL; ADAPTIVE MANAGEMENT; APPROXIMATE BAYESIAN; CANDIDATE MODELS; ECOLOGICAL PROCESS; EXPERT KNOWLEDGE; FOREST ECOSYSTEM; FOREST RESPONSE; FUZZY COGNITIVE MAP; HERBIVORY; INITIAL STAGES; LIGHT AVAILABILITY; MANAGEMENT DECISIONS; MARKOV CHAIN MONTE CARLO ALGORITHMS; MODEL SELECTION; NEW ZEALAND; PARAMETER INFERENCE; PLANT COMPETITION; RELIABLE MODELS; SEEDLING GROWTH; SIMULATED DATA; SOIL NUTRIENTS; STRUCTURAL UNCERTAINTY; TREE SEEDLINGS; UNDERSTOREY;

ALGORITHMS; BAYESIAN NETWORKS; COMPUTER SIMULATION; EXPERIMENTS; FUZZY LOGIC; FUZZY RULES; FUZZY SYSTEMS; GEOLOGIC MODELS; INFERENCE ENGINES; LARGE SCALE SYSTEMS; MODEL STRUCTURES; SEED; UNCERTAINTY ANALYSIS;

FORESTRY;

ADAPTIVE MANAGEMENT; ALGORITHM; BAYESIAN ANALYSIS; COMPUTER SIMULATION; DECISION MAKING; DEER; FOREST ECOSYSTEM; FUZZY MATHEMATICS; GROWTH RATE; HABITAT CONSERVATION; NUMERICAL MODEL; SEEDLING; SOIL NUTRIENT; UNDERSTORY;

ALGORITHMS; COMPUTATION; ECOLOGY; FORESTRY; FUZZY LOGIC; NEW ZEALAND; SEEDLINGS;

NEW ZEALAND;

CERVIDAE;

EID: 84861814016     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2012.04.022     Document Type: Article

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