Primer of Ecological Theory

by Roughgarden, Joan

• ISBN13: 9780134420622
• ISBN10: 0134420624
• Edition: 1st
• Format: Paperback
• Copyright: 1997-04-18
• Publisher: Pearson

Summary

Presents an overview of ecological modeling as it relates to current ecological theory.A Primer of Ecological Theorymaintains its scientific objectivity while covering the full extent of current ecological modeling theory. The book introduces the use of computer technology to ecological modeling through MATLAB. This allows all work to be verified and the skills transferred to other disciplines.A valuable resource book for ecologists, resource managers, and economists.

Table of Contents

Preface	ix
1 Getting Comfortable Outdoors	1	(24)
1.1 Equilibrium Body Temperature	1	(5)
1.2 Climate Space	6	(4)
1.3 Living at the Edge	10	(10)
1.3.1 Symbolic Analysis	10	(2)
1.3.2 Numerical Analysis	12	(2)
1.3.3 Systems Analysis	14	(6)
1.4 Further Readings	20	(1)
1.5 Application: Tomorrow's Extinctions of Mammals	21	(4)
2 Time For a Byte of Food?	25	(30)
2.1 Searching Predator	25	(17)
2.1.1 What Should Be Done	26	(9)
2.1.2 How To Go About It	35	(7)
2.2 Sit-and-Wait Predator	42	(10)
2.2.1 What to Do	42	(5)
2.2.2 How To Do It	47	(5)
2.3 Further Readings	52	(1)
2.4 Application: The Traveling Bumblebee	52	(3)
3 The Sky's the Limit	55	(38)
3.1 The Population Bomb	55	(5)
3.1.1 Discrete Time	56	(2)
3.1.2 Continuous Time	58	(2)
3.2 Keeping Track of the Years	60	(16)
3.2.1 The Leslie Matrix for Discrete Time	61	(9)
3.2.2 Have Red Deer Run Amok?	70	(3)
3.2.3 Euler's Equation for Continuous Time	73	(3)
3.3 Living Through Good Times and Bad	76	(10)
3.3.1 Environmental Stochasticity	77	(3)
3.3.2 Spreading the Risk in a Metapopulation	80	(4)
3.3.3 Demographic Stochasticity	84	(2)
3.4 The Invading Wave	86	(3)
3.5 Further Readings	89	(1)
3.6 Application: Eigenvalues Save Endangered Turtles	90	(3)
4 Got'ta Stop Somewhere	93	(58)
4.1 Measuring Abundance	93	(2)
4.2 Detecting Limits to Growth	95	(7)
4.2.1 Real Birds	95	(5)
4.2.2 Null Models	100	(2)
4.3 The Logistic Model of Limits to Growth	102	(6)
4.3.1 Discrete Time	102	(5)
4.3.2 Continuous Time	107	(1)
4.4 Using the Logistic Model with Data	108	(12)
4.4.1 The Growth of Laboratory Paramecium	109	(3)
4.4.2 Fitting Natural Production to Stock Size	112	(4)
4.4.3 Fitting Trajectories Through Time	116	(4)
4.5 Comparing the Logistic to Other Models	120	(4)
4.6 The Logistic Weed	124	(1)
4.7 Ecological Stability	125	(15)
4.7.1 Continuous Time	126	(2)
4.7.2 The Logistic Model without Harvesting	128	(3)
4.7.3 Harvesting a Logistic Resource	131	(6)
4.7.4 Discrete Time	137	(3)
4.8 Ecological Chaos	140	(5)
4.9 Further Readings	145	(1)
4.10 Application: Avoiding the Collapse of Wildebeest	146	(5)
5 Ecology Evolving	151	(74)
5.1 Genetic Variation	152	(4)
5.1.1 The Hardy-Weinberg Law	153	(3)
5.2 Natural Selection	156	(26)
5.2.1 Predicting What Natural Selection Does	156	(3)
5.2.2 Evolutionary Scenario for Global Warming	159	(7)
5.2.3 Classification of Evolutionary Outcomes	166	(4)
5.2.4 Illustration of Evolutionary Outcomes	170	(5)
5.2.5 The Fundamental Theorem of Natural Selection	175	(7)
5.3 Genetic Drift	182	(10)
5.3.1 Sampling Error	182	(6)
5.3.2 Drift Mixed with Selection	188	(4)
5.4 Mutation and Recombination	192	(5)
5.4.1 Recurrent Mutation Mixed with Selection	193	(4)
5.5 Does Evolution Optimize?	197	(2)
5.6 Natural Selection and Population Size	199	(4)
5.6.1 r- and K-selection	202	(1)
5.7 Natural Selection and Age	203	(13)
5.7.1 The True Meaning of Death	210	(2)
5.7.2 When to Have Children	212	(1)
5.7.3 Fitting Life History to Environment	213	(3)
5.8 Hot Links to Other Evolutionary Topics	216	(2)
5.9 Further Readings	218	(2)
5.10 Application: Slowing Evolution of Pesticide Resistance	220	(5)
6 Populations at Play	225	(106)
6.1 Two-Species Lotka-Volterra Model of Competition	226	(26)
6.1.1 Using the Lotka-Volterra Model with Data	227	(6)
6.1.2 Outcome of Two-Species Competition	233	(6)
6.1.3 Ecological Stability With Multiple Species	239	(5)
6.1.4 Altitudinal Zonation and Species Borders	244	(4)
6.1.5 Intermediate Disturbance Principle	248	(4)
6.2 Three-Species Lotka-Volterra Competition	252	(9)
6.2.1 Limiting Similarity	252	(2)
6.2.2 Diffuse Competition	254	(1)
6.2.3 Hierarchical Competition	255	(1)
6.2.4 Competitive Oscillations	255	(6)
6.3 Resource-Based Competition Models	261	(5)
6.3.1 The R(*) Principle	261	(3)
6.3.2 Lotka-Volterra Weeds	264	(2)
6.4 Predator-Prey Interaction	266	(22)
6.4.1 Volterra Predator-Prey Model	266	(5)
6.4.2 Adding Density Dependence to the Prey	271	(5)
6.4.3 Tricks of Stability Analysis with Two Variables	276	(4)
6.4.4 Adding Satiation to Predators	280	(8)
6.5 Host-Parasitoid Interaction	288	(14)
6.5.1 The Nicholson-Bailey Model	291	(3)
6.5.2 Stability Analysis in Discrete Time	294	(1)
6.5.3 The Negative-Binomial Model	295	(5)
6.5.4 Host and Parasitoid as Weeds	300	(2)
6.6 Host-Pathogen Interaction	302	(8)
6.6.1 Kermack-McKendrick SIR Model	302	(8)
6.7 Mutualism and Symbiosis	310	(9)
6.8 Further Readings	319	(3)
6.9 Application: Abundance is No Guarantee of Safety	322	(4)
6.10 Application: How to Control a Pest	326	(5)
7 Ecosystems at Work	331	(96)
7.1 Biodiversity in Ecological Communities	332	(47)
7.1.1 Niche Spacing in Guilds	333	(12)
7.1.2 Randomly Constructed Communities	345	(9)
7.1.3 Species-Area Curves and Island Biogeography	354	(9)
7.1.4 Succession and Disturbance	363	(7)
7.1.5 Food Webs and Trophic Dynamics	370	(9)
7.2 Biogeochemical Function in Earth Systems	379	(39)
7.2.1 Nonequilibrium Thermodynamics	380	(6)
7.2.2 Carbon Exchange in the Biosphere	386	(16)
7.2.3 The Gaia Hypothesis	402	(16)
7.3 Further Readings	418	(3)
7.4 Application: Many Small or One Large Nature Reserve?	421	(2)
7.5 Application: Disturbance Affects Food Webs	423	(4)
Programming in MATLAB	427	(16)
Index	443