area restrict biroi
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Modeling the Area RestrictSearching Strategy of StinglessBees, Trigona biroi, as aQuasi-Random Walk Process
9th Annual National ConventionPhilippine Society for the Study of Nature (PSSN)12-15 November 2009Mindanao State University Iligan Institue of Technology
(MSU-IIT) Ilagan City, Lanao del Norte, Philippines
Jomar F. RabajanteMath Division, Institute of Mathematical Sciences andPhysics
University of the Philippines Los BaosRoberto B. Figueroa Jr.Institute of Computer ScienceUniversity of the Philippines LosBaos
Arian J. JacildoInstitute of Computer Science
University of the Philippines Los Baos
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Outline
Outline
Introduction
Model Formulation
Optimal Foraging Theory Biroi Preference Algorithm
Area Restrict Searching strategy
Visualization using Netlogo (demo) Conclusions and Recommendations
References
2009 University of the Philippines at Los
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Outline
Introduction
Interdisciplinary research collaboration
Mathematics
Mathematical Modeling
Computer Science
Computer Visualization
Biological Science
Tool for teaching UPLB Bee Program
Aid in planning for beekeeping
2009 University of the Philippines at Los
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Outline
Introduction: Pollination
If the bees disappeared off the surface of the globe, thenman would only have four years of life left. No more bees,
no more pollination, no more plants, no more animals, no
more man- Eistein
Bees are good natural cross-pollinators
Pollination helps provide adequate food
supply for human (Can increase cropproduction by 40%)
Pollination helps sustain biodiversity of
plant species 2009 University of the Philippines at Los
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Outline
Introduction: Pollination
2009 University of the Philippines at Los
Why study bees foraging behavior? Pollination usually happens during the
foraging activity of bees.
Trigona biroiFriese stingless (Meliponini) native in the Philippines better pollinator than the honeybees (Apis)
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Outline
Introduction: Pollination
2009 University of the Philippines at Los
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OutlineModel Formulation
Foraging Behavior of bees
Optimal Foraging Theory
Bees are maximizing the benefits that can beobtained from the food vis--vis the costs needed
in foraging
Marginal Value Theorem
Bees find another food source when the
profitability of the food is diminishing
2009 University of the Philippines at Los
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OutlineModel Formulation
Foraging Behavior of bees
Patch hopping
2009 University of the Philippines at Los
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OutlineModel Formulation
Foraging Behavior of bees
Determining the
paths throughexperiments:
Compare the
skewness of the
distributions of
time visitation
of bees 2009 University of the Philippines at Los
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OutlineModel Formulation
Stochastic Process
Probabilities
2009 University of the Philippines at Los
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OutlineModel Formulation
Stochastic Process
Not Purely Random - the chances of
going to certain feeders are not allequal
Bees have preferences (following the
Optimal Foraging Theory)
2009 University of the Philippines at Los
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i i f l i h
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OutlineBiroi Preference Algorithm(AHP)
2009 University of the Philippines at Los
CRITERIA Height SucroseConcentration
Distance
Height 1 5 1/3
SucroseConcentration
1/5 1 1/9
Distance 3 9 1
0.267399
0.063736
0.668864
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Outline
2009 University of the Philippines at Los
Food1
Values for Food1
Distance = 5m
Height = 6m
Sucrose% = 40%
Hive
Values for Food2
Distance = 6m
Height = 6m
Sucrose% = 50%
Food2
Values for Food3
Distance = 7m
Height = 3m
Sucrose% = 60%
Food3
AHP
Height Sucrose% Distance
Height 1 5 1/3
Sucrose% 1/5 1 1/9
Distance 3 9 1
?
Biroi Preference
Algorithm
Probabilities
??
Biroi Preference Algorithm
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OutlineArea Restrict Searching
2009 University of the Philippines at Los
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OutlineNetLogo Simulation
2009 University of the Philippines at Los
Scouts
Randomly
Search Food
Sources
Foragers Select Food
Source via Biroi
Preference Algorithm
plus
Area Restrict Searching
Use simulation than exhaustive
enumeration of possibilities
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OutlineNetLogo Simulation (demo)
2009 University of the Philippines at Los
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OutlineConclusions
We have improved our model for bee
foraging behavior by incorporating area
restrict searching.
We have implemented a software to
visualize our model using Netlogo, anagent based simulation tool.
2009 University of the Philippines at Los
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OutlineRecommendations
Incorporateother
parameters (e.g.
environmental
factors)
Improve the
multi-agent
design (e.g. 3Dview)
2009 University of the Philippines at Los
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OutlineAcknowledgement
UPLB Bee Program
Institute of Mathematical Sciences and
Physics
Institute of Computer Science
College of Arts and Sciences
2009 University of the Philippines at Los
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OutlineResearch Team
2009 University of the Philippines at Los
Arian J. Jacildo
Jomar F. Rabajante
Roberto B. Figueroa
Jr.
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OutlineSelected References
Biroi Preference Algorithm
Rabajante, et al. (2009)
Bee Behavior
Nieh, et al. (2000) Roubik, et al. (1995)
AHP
Taha, H. A. (2007)
Netlogo Wilensky, U. (1999)
http://ccl.northwestern.edu/netlogo
2009 University of the Philippines at Los
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