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Latitudinal Gradients in Species Diversity
Latitudinal Gradients in Species Diversity
Regional<—>Local <—> Point diversity
Four ways two systems can differ in diversity
Saturation with species, MacArthur’s foliage height diversity vs. birds
Latitudinal gradients in diversity, primary vs. secondary mechanisms
Time theories
Climatic stability and climatic predictability
Spatial heterogeneity
Productivity and stability of productivity
Competition —> specialization, narrow niches, higher diversity
Disturbance, intermediate disturbance hypothesis
Predation-induced diversity
Various Hypothetical Mechanisms for the Determination
of Species Diversity and Their Proposed Modes of Action
__________________________________________________________________
Level
Hypothesis or theory
Mode of action
__________________________________________________________________
Primary
Primary
Primary
Primary
Primary or
secondary
Secondary
1. Evolutionary time
2. Ecological time
3. Climatic stability
4. Climatic predictability
5. Spatial heterogeneity
Degree of unsaturation with species
Degree of unsaturation with species
Mean niche breadth
Mean niche breadth
Range of available resources
6. Productivity
Secondary
7. Stability of primary
production
8. Competition
9. Disturbance
Especially mean niche breadth, but
also range of available resources
Mean niche breadth and range of
available resources
Mean niche breadth
Degree of allowable niche overlap
and level of competition
Tertiary
Primary,
secondary,
or tertiary
Tertiary
10. Predation
Degree of allowable niche overlap
Intermediate Disturbance Hypothesis
Tree Species Diversity in Tropical Rain Forests
Seed Predation Hypothesis
Nutrient Mosaic Hypothesis
Circular Networks Hypothesis
Disturbance Hypothesis
(Epiphyte Load Hypothesis)
Sea Otter (Enhydra lutris)
Amchitka
Shemya
Sea Otters
20-30 km2
only vagrants
Kelp
dense mats
heavily grazed
Sea Urchins 8/m2, 2-34mm
78/m2, 2-86mm
Chitons
1/m2
38/m2
Barnacles
5/m2
1215/m2
Mussels
4/m2
722/m2
Greenling
abundant
scarce or absent
Harbor Seals 8/km
l.5-2/km
Bald Eagles abundant
scarce or absent
Community Stability
Traditional Ecological Wisdom
Diversity begats stability (Charles Elton)
More complex ecosystems with more
species have more checks and balances
Types of Stability
Point Attractors <——> Repellers
Domains of Attraction, Multiple Stable States
Local Stability <——> Global Stability
Types of Stability
1. Persistence
2. Constancy = variability
3. Resistance = inertia
4. Resilience = elasticity (rate of return, Lyapunov stability)
5. Amplitude stability (Domain of attraction)
6. Cyclic stability, neutral stability, limit cycles, strange attractors
7. Trajectory stability
Types of Stability
Point Attractors <——> Repellers
Domains of Attraction, Multiple Stable States
Local Stability <——> Global Stability
Types of Stability
Constancy = variability
Resistance = inertia
Resilience = elasticity (rate of return, Lyapunov stability)
Amplitude stability (Domain of attraction)
Cyclic stability, neutral stability, limit cycles, strange attractors
Trajectory stability
Edward Lorenz
Strange
Attractor
Generalized Lotka-Volterra Equations:
dNi/dt = Ni (bi + S aij Nj)
Jacobian Matrix
Partial Derivatives ∂Ni / ∂Nj , ∂Nj / ∂Ni
Sensitivity of species i to changes in density of species j
Sensitivity of species j to changes in density of species i
Traditional Ecological Wisdom:
Diversity begats Stability
MacArthur’s idea
Stability of an ecosystem should increase
with both the number of different trophic
links between species and with the
equitability of energy flow up various food
chains
Robert MacArthur
Robert May challenged
conventional ecological
thinking and asserted that
complex ecological systems
were likely to be less stable
than simpler systems
May analyzed sets of randomly assembled Model
Ecosystems. Jacobian matrices were
Assembled as follows: diagonal elements were defined
as – 1. All other interaction terms were equally likely to
be + or – (chosen from a uniform random distribution
ranging from +1 to –1). Thus 25% of interactions were
mutualisms, 25% were direct interspecific competitors
and 50% were prey-predator or parasite-host
interactions. Not known for any real ecological system!
May varied three aspects of community complexity:
1. Number of species
(dimensionality of the Jacobian matrix)
2. Average absolute magnitude of elements
(interaction strength)
3. Proportion of elements that were non-zero
(connectedness)
Real communities are far from random in construction,
but must obey various constraints.
Can be no more than 5-7 trophic levels, food chain loops
are disallowed, must be at least one producer in every
ecosystem, etc.
Astronomically large numbers of random systems : for
only 40 species, there are 10764 possible networks
of which only about 10500 are biologically reasonable —
realistic systems are so sparse that random sampling is
unlikely to find them. For just a 20 species network, if
one million hypothetical networks were generated on a
computer every second for ten years, among the
resulting 31.513 random systems produced, there is a
95% expectation of never encountering even one
realistic ecological system!
Latitudinal gradients in species diversity
Tropical tree species diversity
Seeding rings
Nutrient mosaic
Circular networks
Disturbance (epiphyte loads)
Connectance and number of species
Sea otters as keystone species, alternative stable states
Types of stability
Constancy = variability
Inertia = resistance
Elasticity = resilience (Lyapunov stability)
Amplitude (domain of attraction)
Cyclic stability (neutral stability, limit cycles, strange attractors)
Trajectory stability (succession)
Traditional ecological wisdom: diversity begats stability
May’s challenge using random model systems
Real systems not constructed randomly