Modelling Aquatic Rates In Natural Ecosystems BIOL471

Slides:



Advertisements
Similar presentations
Point Value : 20 Time limit : 2 min #1 Find. #1 Point Value : 30 Time limit : 2.5 min #2 Find.
Advertisements

Using Virtual Laboratories to Teach Mathematical Modeling Glenn Ledder University of Nebraska-Lincoln
Exploitation.
Josh Durham Jacob Swett. Dynamic Behaviors of a Harvesting Leslie-Gower Predator-Prey Model Na Zhang, 1 Fengde Chen, 1 Qianqian Su, 1 and Ting Wu 2 1.
POPULATION DYNAMICS READINGS: FREEMAN, 2005 Chapter 52 Pages
© 2014 Carl Lund, all rights reserved A First Course on Kinetics and Reaction Engineering Class 15.
Predator-Prey Interaction in Structured Models Glenn Ledder J. David Logan University of Nebraska-Lincoln
Predation (Chapter 18) Predator-prey cycles Models of predation
458 Multispecies Models (Introduction to predator-prey dynamics) Fish 458, Lecture 26.
Predation – Chapter 13. Types of Predators Herbivores – animals that prey on green plants or their seed and fruits. –Plants are usually damaged but not.
Functional Response Lab 10 Turn in proposals on front table.
بسم الله الرحمن الرحيم وقل ربِ زدني علماً صدق الله العظيم.
Population Interactions Competition for Resources: –Exploitative competition: Both organisms competing for the same resource(s). –Interference competition.
Living organisms exist within webs of interactions with other living creatures, the most important of which involve eating or being eaten (trophic interactions).
Objectives - Chapter What is an exploitative interaction?
Chapter 15 Predation. I. Terminology Predation = one organism is food for another Carnivory = feeding on animal tissue Parasitoidism = killing of host.
LURE 2009 SUMMER PROGRAM John Alford Sam Houston State University.
Theoretical Impacts of Habitat Fragmentation and Generalist Predation on Predator-Prey Cycles Kelsey Vitense “Current Challenges for Mathematical Modelling.
© 2014 Carl Lund, all rights reserved A First Course on Kinetics and Reaction Engineering Class 9.
Alternative Lotka-Volterra competition Absolute competition coefficients dN i / N i dt = r i [1 –  ii N i -  ij N j ] equivalent to: dN i / N i dt =
Title Bo Deng UNL. B. Blaslus, et al Nature 1999 B. Blaslus, et al Nature 1999.
Lecture 5 Curve fitting by iterative approaches MARINE QB III MARINE QB III Modelling Aquatic Rates In Natural Ecosystems BIOL471 © 2001 School of Biological.
Modeling food-web dynamics The time evolution of species’ biomasses in a food web: Basal species exhibit exponential growth bounded by a carrying capacity.
RC (Resistor-Capacitor) Circuits
Physics 2015: Rolling Motion and Moment of Inertia Purpose  Investigate which factors affect moments of inertia (such as length, mass, and shape).  Calculate.
INTRODUCTORY MATHEMATICAL ANALYSIS For Business, Economics, and the Life and Social Sciences  2011 Pearson Education, Inc. Chapter 4 Exponential and Logarithmic.
1. Section 1.4 Formulas for Linear Functions 2 A grapefruit is thrown into the air. Its velocity, v, is a linear function of t, the time since it was.
Population Modeling Mathematical Biology Lecture 2 James A. Glazier (Partially Based on Brittain Chapter 1)
Rabbits, Foxes and Mathematical Modeling Peter Pang University Scholars Programme and Department of Mathematics, NUS SMS Workshop July 24, 2004.
Differentiation Recap The first derivative gives the ratio for which f(x) changes w.r.t. change in the x value.
INTRODUCTORY MATHEMATICAL ANALYSIS For Business, Economics, and the Life and Social Sciences  2007 Pearson Education Asia Chapter 4 Exponential and Logarithmic.
Electric Potential of Uniform Charge Distributions Part II AP Physics C Montwood High School R. Casao.
TUTORIALS LESSONS 2-3. Vocabulary Add each word to last weeks vocabulary. Adapt/adaptation: the process of change in response to a given environmental.
Section 7.4: Exponential Growth and Decay Practice HW from Stewart Textbook (not to hand in) p. 532 # 1-17 odd.
Mark J Gibbons, Room 4.102, BCB Department, UWC
FW364 Ecological Problem Solving Class 21: Predation November 18, 2013.
Miscellaneous examples 1. Given that a = log 10 2 and b = log 10 5, find expressions in terms of a and b for: (i) log (ii) log (iii) log 10.
© 2014 Carl Lund, all rights reserved A First Course on Kinetics and Reaction Engineering Class 23.
Biol 304 Week 3 Equilibrium Binding Multiple Multiple Binding Sites.
Trophic Ecosystem Models. Overview Logistic growth model Lotka volterra predation models Competition models Multispecies production models MSVPA Size.
Background to Foraging. C.S. Buzz Holling aka "the man" Functional response was developed based on a 1959 paper These eating These.
Derivation of the Quadratic Formula The following shows how the method of Completing the Square can be used to derive the Quadratic Formula. Start with.
Example 1 Find the derivative of Function is written in terms of f(x), answer should be written in terms of f ′ (x) Continue 
September Club Meeting Thursday, Sept. 16 7:30pm English Building Room 104 “To foster respect and compassion for all living things, to promote understanding.
Fall 2009 IB Workshop Series sponsored by IB academic advisors IB Opportunities in C-U Tuesday, Sept. 15 4:00-5:00pm 135 Burrill There are many local opportunities.
MATH3104: Anthony J. Richardson.
7.4. 5x + 2y = 16 5x + 2y = 16 3x – 4y = 20 3x – 4y = 20 In this linear system neither variable can be eliminated by adding the equations. In this linear.
Measuring and Modelling Population Change. Fecundity Fecundity Fecundity - the potential for a species to produce offspring in one lifetime  this relates.
What can parameters about a fish can we measure that relate to feeding? What environmental factors influence fish feeding? What biotic factors influence.
Community Level Effects
CSE 2813 Discrete Structures Solving Recurrence Relations Section 6.2.
Population Ecology. What is a Population? An interbreeding group of the same species living in the same general area may be distinguished by natural or.
4.1 Exponential Functions I can write an exponential equation from an application problem I can use an exponential equation to solve a problem.
© 2014 Carl Lund, all rights reserved A First Course on Kinetics and Reaction Engineering Class 9.
Algebra Review. Systems of Equations Review: Substitution Linear Combination 2 Methods to Solve:
C. Population Density 2. Habitat Selection Fretwell – Lucas model of habitat selection (1972)
Equations Quadratic in form factorable equations
First order non linear pde’s
FW364 Ecological Problem Solving
FW364 Ecological Problem Solving
Solve a system of linear equation in two variables
Joohee Kim IB Biology Sec. II
Arithmetic Sequences as functions
Writing Linear Equations Given Two Points
Differentiation Recap
Solving Equations 3x+7 –7 13 –7 =.
WORK.
Example Make x the subject of the formula
Equations Quadratic in form factorable equations
Presentation transcript:

Modelling Aquatic Rates In Natural Ecosystems BIOL471 Prey dependent responses School of Biological Sciences © 2001 School of Biological Sciences, University of Liverpool

Add examples

Prey-dependent responses Solomon (1949) separated consumer response to prey density into 2 types: Functional the consumption rate of individual consumers with respect to resource density Numerical the per capita reproductive rate with resource density Holling (1959) identified 3 types of functional responses Ingestion Prey Growth rate Prey + -

Prey-dependent responses Type I (linear) response The attack rate of the individual consumer increases linearly with prey density but then reaches a constant value when the consumer is satiated Ingestion Diatoms (ml-1) Prey

Prey-dependent responses Type II (cyrtoid) functional response The attack rate increases at a decreasing rate with prey density until it becomes constant at satiation Cyrtoid responses are typical of predators that specialise on one or a few prey Ingestion Prey

Prey-dependent responses Type III (sigmoid) functional response The attack rate accelerates at first and then decelerates towards satiation Sigmoid responses are typical of generalists that switch from one prey species to another and/or increase their feeding when resources are abundant Ingestion Prey

C = aH 1+ThaH Prey-dependent responses The “Disk” Equation Holling (1959) derived a mechanistic mathematical model for the Type II response from experiments in which blindfolded people acted as predators by searching a table top with their finger tips for sandpaper disk prey We can derive the disk equation C = 1+ThaH aH

Ttotal = Tsearch + Thandle Prey-dependent responses Let us assume that there are two activities involved in consuming a prey: Searching for the prey Handling or processing the prey Then the total time (Ttotal) to capture prey is: Ttotal = Tsearch + Thandle But we want to know the prey consumed (Hc) over time Ttotal Then we can determine a consumption rate C (HT-1)

Thandle = Hc*Th Prey-dependent responses A predator will consume Hc prey in time T There is a handling time (Th) Total time handling (Thandle) will be the product of handling time (Th) and the prey consumed (Hc) Thandle = Hc*Th Where: Hc prey consumed (H) Th is the handling time of one prey (TH-1)

Hc = a * H * Tsearch Hc Tsearch = aH Prey-dependent responses Also a predator will capture a number of prey (Hc) over a searching time (Tsearch) if it has a constant searching rate (a) But this will depend on how many prey (H) there are This can be expressed as Hc = a * H * Tsearch Where a is the searching rate (L2T-1) H is the prey density (HL-2) and Tsearch = Hc aH

Ttotal = Tsearch + Thandle Prey-dependent responses We can now substitute into Ttotal = Tsearch + Thandle Thandle = HcTh Tsearch = Hc aH Ttotal = + HcTh Hc aH

= = Prey-dependent responses We can now rearrange this equation to solve for Hc T = + HcTh Hc aH Hc = prey captured (H) a is the searching rate (L2T-1) H is the prey density (HL-2) Th is the handling time (TH-1) T is total time (T) = 1 C is consumption rate (HT-1) T = + HcThaH aH Hc T = Hc + HcThaH aH = 1+ThaH aH Hc T T = Hc(1+ThaH) aH = 1+ThaH aH C Hc = 1+ThaH aHT

Prey-dependent responses We can now rearrange this equation to solve for Ha C= 1+ThaH aH C = ( + H) H 1 Th aTh C = (1+ThaH) aH 1 a If = Cmax 1 Th aTh If = k C = ( +ThH) H 1 a C= ( +ThH) H 1 a Th C = k+ H CmaxH

Prey-dependent responses Cmax C = k+ H CmaxH C k Cmax 1 2 Cmax is the maximum grazing rate k is the half-saturation constant H

The experimental approach We run experiments to determine grazing rates Then we can use these rates in models We can also use these experiments to determine constants that tell us about the biology of the organisms The formula we just examined was based on biological mechanisms It is called a mechanistic equation Other models that are not based on mechanisms are called phenomenological equations C H C = k+ H CmaxH

a is the searching rate (L3T-1) Th is the handling time (TH-1) Prey-dependent responses + a Th a is the searching rate (L3T-1) Th is the handling time (TH-1) http://www.aad.gov.au/asset/mme/movies/CiliateFeed.mov

Prey-dependent responses H = Ct Beads (H) C= H t Time (t)

Prey-dependent responses H = Ct Beads (H) C= H t Time (t)

Prey-dependent responses C = k+ H CmaxH C (HT-1) [H ] (HL-3)

The experimental approach Determine the rate of eating Smarties Provide various amounts to students Experiment (consume Smarties) Plot data Determine a mechanistic equation Examine biological parameters

Prey-dependent responses C = k+ H CmaxH Smarties min-1 Smarties density (H L-2)

* The experimental approach a the searching rate (L2T-1) The time it takes to touch your nose and then the desk the area encounter Th the handling time (TH-1) This is the time it takes you to eat a Smarties *