Transcript Predator-prey interactions: lecture content

Complex interactions and population
control in nature: Lecture Content

We’ll talk about three issues relevant to population
control in nature, issues that expand our understanding of
the complexity of ecological systems beyond what we’ve
discussed so far…
 What
factor(s) have the greatest impact controlling
populations?
 What are “metapopulations”, and how does a population’s
spatial distribution influence its stability and control?
 What is the relative impact of “top down” versus “bottomup” (trophic-dynamic) control of populations?
What factor(s) control or influence
population size in nature?

Suppose you were studying the population of Nephila
spiders in LaFitte National Historical Park
 Method:
circular quadrats, as in lab (control for habitat,
season)
 Density per quadrat dropped from 5 in 2001 to 0.5 in
2002

What factors would you need to investigate as
possible explanations for the population stability or
dynamics in this species?
 Population
interactions
 Spatial impacts
 Weather

How would you distinguish the most important
factor(s)?
Key-factor analysis

Define key-factor analysis = method to identify which
mortality factor has greatest impact shifting population
away from equilibrium (i.e., limiting population)
 Identifies
relative strengths of all mortality factors (ki)
 k-values = “killing power”, defined as log(Nt) -log(Nt+1),
where Nt = population size at time t, before mortality
factor i acts; Nt+1 = population at time t+1, after it acts
 Ki’s are mortality factor (like qx); their value is that they
are additive, allow partition of mortality into components

Method of analysis
 k-values
measured for a number of years; graphed
 Key factor is the k-value that most closely mirrors
overall mortality, K
 Regression of k ’s against total annual mortality, K
Example of key-factor analysis


Data from classic study by Varley, Gradwell, and
colleagues on oak winter moth
Methods
 A number
of cohorts followed in field over 13 years
 Number of insects lost to variety of mortality factors
quantified using several methods (see text)
 k-values calculated as described

Results
 Loss
of larvae over winter (k1) was largest k-factor,
mirroring K; and also in regressions showed greatest
(statistically significant) slope when plotted against K
 See example calculations of k-factors for one year
(next slide)
Oak winter moth data for one year
(from Varley, Gradwell, & colleagues; see Stiling
Table 13.1)
Life-history s tage
Adult females, 1955
Eggs (=females*150)
Larvae (after winter loss)
Killed by Cyzenis
Killed by other parasites
Killed by microsporidians
Pupae
Killed by predators
Killed by Cratichneumon
Adulte fem ales , 1956
Number alive/m^2
4.39
658
96.4
90.2
87.6
883
83
28.4
15
7.5
Log(no. alive)
2.82
1.98
1.95
1.94
1.92
1.92
1.45
1.18
k-value
0.84 = k1
0.03 = k2
0.01 = k3
0.02 = k4
0.47 = k5
0.27 = k6
K =1.64
Density-dependence of mortality factors
(k-values) is next step in analysis, after
identification of key factor(s)


Density dependence identifies those mortality factors
that could regulate population, i.e., return population
size to some constant value (carrying capacity)
In oak winter moth example, only two factors were
regulatory (see overhead, Fig. 13.6, Stiling text)
 Pupal
predation (k5) was positively density-dependent
(mortality increases with density, log(N), i.e. regulatory
 Other larval parasites (k3) was inversely densitydependent, and thus potentially destabilizing to
population growth(less mortality with increasing
population is a positive feedback on population size!)
Surveys of different organisms in
nature reveals few generalizations

Key factors in diverse populations?
 Some
examples
 Sand
dune annual plant--seed mortality in soil
 Colorado potato beetle--adult emigration
 Tawny owl--reduction in egg clutch size from max. size
 Gradd-mirid insect--no obvious key factor identified
 Few

generalizations have emerged overall
Density-dependence? (see Fig. 13.7,Stiling)
 Insects
disproportionately regulated by parasites,
diseases, predators
 Small birds and mammals by limited space, crowding
 Large mammals by mortality associated with limited
food
Spatial distribution of populations is
another, new aspect of complexity that
can stabilize or de-stabilize abundance

Metapopulation
 Defined:
group of isolated, interconnected populations
 Each sub-population may or may not act as an
independent population
 Potential to stabilize total population (colonization rate >
extinction rate)

Classification of metapopulations (diagram, next slide)
 Classic
metapopulation (rare; Richard Levins, 1969)
 Core-satellite metapopulation (common)
 Patchy population (common)
 Nonequilibrium metapopulation (rare)
 Source-sink populations (common; Ron Pulliam et al.)
Classification of metapopulations
Core-satellite
metapopulation
Classic metapopulation
l>1
l<1
l<1
l<1
l>1
Source-sink
populations
Patchy population
Nonequilibrium
metapopulation
Classic metapopulation can stabilize
population

Mechanism of stability?
 Dp/dt
= mp(1-p) - xp, where p = number of occupied
patches, m = rate of movement between patches, x
= extinction rate of occupied patches
 At
equilibrium, Dp/dt = 0 ==> p = 1- (x/m)
 Equilibrium reached if x < m

Examples?
 Few
examples of classic metapopulation have been
described
 Best known is population of Bay ckeckerspot
butterfly (Euphydryas editha) studied on Jasper
Ridge,California, and other areas
 Its
food plant found on serpentine soils (hi in Mg, Fe)
 Both extinction & re-colonization documented
Spotted owl population--example of
classic metapopulation?
This is an
endangered
species,occupying
patches of oldgrowth coniferous
forest in W. U.S.;
little is known
about patch-patch
dispersal
Example of subdivided
population--Everglades kite
Trophic structure adds a third set of
complex interactions among species


Trophic structure of ecosystems is concept formalized
by Lindeman: trophic-dynamics
Flow of nutrients, energy in food chain from ultimate
source (sun, or center of Earth)-->plants (1º
producers) -->herbivores (1º consumers)-->2º
consumers-->3º consumers-->detritivores
 Such
trophic structure adds complexity:multiple controls
 “Bottom-up” control of populations is hypothesis (put
forth by Lindeman) that all populations are controlled by
entities lower in food chain
 E.g.,
plants controlled by energy in sunlight (& nutrients,
water, of course)
 Top predators ultimately controlled by total energy in food
chain
Trophodynamics, continued

“Top-down” control involves higher entities in food
chain (or web) as control agents--e.g., predators,
herbivores
 Hairston,
Smith, & Slobodkin (HSS) ideas, already
discussed, involve top-down control
 Marquis & Whelan study of birds eating caterpillars on
white oak saplings (again, already discussed)
 Another example: Kelp-->sea urchins-->sea otters
 Pelagic marine food webs, often four trophic levels,
also illustrate top-down forces: top predators
(piscivores) reduce abundance of zooplankton
feeders, which releases pressure on zooplankton,
which become abundant enough to crop
phytoplankton (oceans not “green”, unlike terrestrial
ecosystems--see next slide)
Diagramatic illustration of bottomup & top-down trophic control
Top-down control allows for possibility
of indirect trophic effects
Carnivore
-
+
Herbivore
+
-
Plant
Indirect effect of
+ carnivore on plant
via control of
herbivore
Bottom-up control of zooplankton
abundance: more algae-->more
zooplankton feeding on the algae (from
Ricklefs 2001)
0.1
1
10
100
Chlorophyll (mg per L)
1000
Top-down control of zooplankton:
addition of fish (predators) leads to
decrease zooplankton, increase algae
Synthesis of bottom-up & top-down
forces?

One scheme is Ecosystem Exploitation Hypothesis
(EEH)--Oksanen, Fretwell, and others
 Biomass
at a given trophic level depends on how many
trophic levels present (both bottom-up & top-down
forces--see Fig. 13.12 Stiling text)
 The number of trophic levels present depends on total
ecosystem (environmental) productivity
 Foregoing slides illustrate importance of both bottom-up
& top-down forces in freshwater zooplankton-fish
communities, supporting these ideas

Algae in aquatic & marine food chains tend to be
relatively edible (no woody support tissue, as in
trees!), allowing more biomass, and longer food
chains
Conclusions:

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Multiple factors control populations of most, if not all
organisms, necessitating methods (like key-factor
analysis) to assess relative strengths of control
Key factors identify factors that perturb populations,
density-dependence identifies those that regulate
Metapopulations add spatial-temporal complexity to
population dynamics, and come in a variety of flavors,
some of which can help stabilize population (e.g.,
satellite-core, source-sink, classic metapopulation)
Trophic-dynamics adds complexity in terms of multiple
possible controls (bottom-up, top-down), and indirect
interactions (e.g., predators help plants by controlling
herbivores)
Acknowledgements:
Some illustrations for this lecture
from R.E. Ricklefs. 2001. The
Economy of Nature, 5th Edition.
W.H. Freeman and Company, New
York.