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Transcript of Multiple-species interactions Left: Image from Wikimedia Commons of one of the earliest known...
Multiple-species interactions
Left: Image from Wikimedia Commons of one of the earliest known depictions of a food web, by Victor Summerhayes & Charles Elton (1923) for Bear Island, NorwayRight: Provenance of “A simplified food web for Northwest Atlantic” unknown
Trophic (energy & nutrition) relationships among organisms
LinksFlow of material (including
energy-rich molecules)
NodesTaxonomic or functional categories
Paine, R. T. (1966) – Food webs are the “ecologically flexible scaffolding
around which communities are assembled and structured”
Food Webs
Provenance of image unknown
Pyramid could represent numbers,
biomass, energy consumed per year,
etc.
Elton’s hypothesis: Predators must be larger than prey to subdue them
Image from http://mrskingsbioweb.com/ecology.html
Elton (1927) observed that predators tend to be larger & less numerous than their prey – “pyramid of numbers” (a.k.a. “Eltonian pyramid”)
Food Webs
Food Webs
Inverted pyramids of biomass can occur (e.g., whales, krill, phytoplankton in southern oceans), but only when productivity and turnover of producers is extremely high
Lindeman (1942) introduced the “energy-efficiency hypothesis” – the fraction of energy entering one trophic level that passes to the next higher level is low (~ 5 - 15%)
The first and second laws of thermodynamics predict inefficiency:
1st Law = Conservation of Energy
2nd Law = Energy transformations result in an increase in entropy, i.e., only a fraction of the energy captured by one trophic level is available to do work in the next
“Green” or livingfood web
“Brown” or detrital food web
1 Producers
1 Consumers
2 Consumers
1 Consumers
2 Consumers
Trophic levelswithin a simple
food chain;donor levels
supply energy or nutrients to
recipient levels
Levin, S. A. (1992) – “Is a taxonomic subdivision most appropriate… would a functional one serve better? Should subdivision… consider different demographic classes, be partitioned according to genotype, etc.?”
Food Webs
Web jargon:
Connectance (c): Number of links (L) or connections between species (S) or nodes – expressed as a proportion of maximum connectance:
c = L / [S(S-1)/2]Maximum connectance = S(S-1)/2
Linkage density (L/S): Average number of trophic links per species
Compartmentation: Degree of isolation of subwebs – the number of species that interact with any given pair of species versus those that interact with only one member of the pair
Food Webs
Same-chainomnivory
Web jargon:
Omnivory: Feeding on more than one trophic level
Different-chainomnivory
Food Webs
4
3
2
1
4
3
2
1
3’
2’
1’
A B
A B
C
Web jargon:
Cycles & loops: Species have reciprocal feeding relationships
Cycle E.g., wasps that prey
on spiders that in turn catch wasps in their webs
Loop E.g., “rock-paper-scissors” interactions among plankton (see Huisman refs.)
Food Webs
Predators
PreyIf every series of three
predators were to complete a triangle in the predator overlap graph, the food web
would exhibit the “rigid circuit property;”
this one comes close
Food Webs
Web jargon:
Circuit properties: Overlaps in prey consumption among predators
Predatoroverlapgraph
5 6 7 8 9
1 2 3 4
2
4
1
3
1
2
3
4 1 2 3 4
1 - - 0 0
2 + 0 - 0
3 0 + 0 -
4 0 0 + 0
0 = no connection / no interaction+ = positive effect; prey supplying energy to predator- = negative effect; predation
Values corresponded to interaction strengths
May (1973) and Pimm & Lawton (1977, 1978) used multispecies Lotka-Volterra models to examine various configurations for stability
Modeling food webs:
Which food web configurations promote stable equilibria?
Food Webs
Food Webs
Simulations generally examine the influence of small changes in predator & prey populations away from equilibria
Two criteria for assessing stability:
Do populations return to equilibrium sizes?
How long does the system take to return to equilibrium?
The way in which the matrices are constructed (e.g., lengths of food chains, connectedness, etc.) determines stability
Do real-world food webs yield repeated patterns? If so, do the patterns have ecological significance?
Food Webs
Are ratios of species at different trophic levels constant across communities?
This may simply reflect greater lumping into functional groups for prey than predators
Cohen (1978) reviewed published community webs – relatively high consistency of predators to prey (4:3)
How long are food chains?
As expected, relatively short; rarely more than 5 trophic levels (Pimm & Lawton 1977; Pimm 1982)
Invertebrate ectotherms vs. vertebrate ectotherms vs. vertebrate endotherms at trophic level 2
Energy-conversion efficiency:
invert. ectotherms > vert. ecototherms > vert. endotherms (invert. ectotherms are about an order of magnitude more efficient than vert. endotherms)
Percent of chains supporting consumer(s): 23% > 9% > 6%
invert. ectotherms > vert. ecototherms > vert. endotherms
Food Webs
How long are food chains?
Yodzis (1984) – meta-analysis of 34 published food webs (Briand 1983) to examine the influence of energy efficiency on food-chain length
Natural tree-holes contain 4-level trophic chains: litter -- mosquito larvae -- larvae of predatory midge -- tadpoles
Litter at 100% natural level (938 g/m2/yr), 10% natural level, 1% natural level
Well-replicated study tracked for 48 wk
If efficiency of energy transfer primarily determines food chain length, then manipulating productivity should influence food chain length
Plastic buckets in an Australian forest to resemble water-filled tree-holes with different amounts of litter to generate a productivity gradient
Food Webs
How long are food chains?
Jenkins et al. (1992) – direct test of the energy-efficiency hypothesis
Food Webs
Figure from Jenkins et al. (1992)
How long are food chains?
Jenkins et al. (1992) – direct test of the energy-efficiency hypothesis
Decreased productivity resulted in decreased number of coexisting species & decreased number of trophic levels & links
Polis (1991) – a skeptic of food web theory – characterized desert food webs in great detail
Two-species cycles and three-species loops occur, and are especially common in communities characterized by size-dependent predation
Role reversals between predators and prey are not uncommon
Omnivory is quite common
Food Webs
Modeling suggested that cycles, loops, and omnivory would destabilize food webs
Do cycles and loops occur in nature?Is omnivory common?
Interaction Webs(We can broaden our scope to include more than trophic links)
A B
Competition
-
-
Influence of species A
Infl
ue
nce
of
Sp
eci
es
B
+ (positive)0 (neutral/null)- (negative)
A B
Amensalism
0
-A B
Antagonism(Predation/Parasitism)
+
-
A B
Commensalism
+
0A B
Neutralism(No interaction)
0
0
A B
Commensalism
0
+A B
Mutualism
+
+
A B
Amensalism
-
0
A B
Antagonism(Predation/Parasitism)
-
+
-
0
+
Redrawn from Abrahamson (1989); Morin (1999, pg. 21)
Unlike the randomly defined interaction strengths of the earliest modeling approaches, interaction strengths are not normally distributed; they are heavily skewed toward weak interactions
“…weak interactions may be the glue that binds natural communities together” (McCann, Hastings & Huxel 1998)
This shows that evaluating interaction strength (of combined direct & indirect effects) and not merely trophic links is essential to understanding population dynamics and stability within food webs
Interaction Webs
The distribution of interaction strengths is very important for determining modeling outcomes
How are interaction strengths distributed in nature?
Dissecting exploitation competition reveals its indirect nature
H
-
P
Solid arrows indicate direct effects, dotted arrows indicate indirect effects
-+ +
- H
Direct & Indirect Effects
Redrawn from Menge (1995)
Dissecting the ant-acacia mutualism reveals its indirect components
ant
-
P
Solid arrows indicate direct effects, dotted arrow indicates indirect effect
-+ +
-
Direct & Indirect Effects
As consumers, ants have direct negative effects on acacias (eating Beltian bodies, etc.), but indirect positive effects mediated through herbivores
H
+
P
Apparent Competition
H
Tri-trophic Interactionor Trophic Cascade
-
P
Solid arrows indicate direct effects, dotted arrows indicate indirect effects
-++
-
H
P
C
- +
- +
++
Direct & Indirect Effects
Redrawn from Menge (1995) & Morin (1999)
P
H
-
P
Solid arrows indicate direct effects, dotted arrows indicate indirect effects
++
-
KeystonePredation
HabitatFacilitation
H
P
-+ - (e.g., inhibits
feeding)
+H
Direct & Indirect Effects
Redrawn from Menge (1995) – found 83 distinct types of indirect interactions in 23 communities
IndirectMutualism
P
-
P
+
-
H + H
+ -
Direct & Indirect Effects
Definitions from Strauss (1991)
How ‘one species alters the effect that another species has on a third’
Or
‘How and to what degree pairwise species interactions are influenced by the presence and density of other species in the
community’
Direct & Indirect Effects
Figure modified from Wootton (1993)
Interaction chain indirect effect – results from “linked direct interactions”(e.g., bird predators enhance barnacle abundance b/c they consume limpets that dislodge & sometimes consume barnacles); relatively predictable from the direct interactions
bird
bird
limpet
limpet
barnacle
barnacle
Interaction modification indirect effect – “a third species changes how a pair of species interacts;” the third species changes the per capita effect of one species on another (e.g., when barnacles are present, limpets are harder for birds to find); difficult to predict a priori
Direct & Indirect Effects(It’s useful to know the natural history!)
Figure modified from Wootton (1993)
birds (esp. Black Oystercatchers & Glaucous-Winged Gulls)
limpet barnacle
Direct & Indirect Effects
Werner & Peacor (2003)
Density-mediated indirect interactions– “indirect effects… propagated by changes in densities of intervening species” e.g., “keystone predator effects, trophic cascades, and exploitative competition… [as] traditionally conceived”
Same as interaction chain indirect effect
Trait-mediated indirect interactions– “If a species reacts to the presence of a second species by altering its phenotype [phenotypic plasticity], the trait changes in the reacting species can alter the per capita effect of the reacting species on other species…”
Same as interaction modification indirect effect
Experiment: Continually transplanted bivalves to maintain high densities of bivalves in sites with high densities of gastropods
Prediction (if apparent competition operates): Predator density will increase, gastropod density will decrease
Direct & Indirect Effects
Apparent competition (an example from Schmitt 1987)
Prey species: Sessile bivalve filter feeders occur mostly in crevices
Gastropods occur on rock surfaces and graze algae
(Limited opportunities for direct competition, since neither diet nor space requirements overlap greatly)
Common predators: Lobsters, octopi, whelks
P
Apparent competition
C
-
P
-++
-
Control sites
Sites with added bivalves
Direct & Indirect Effects
Figure modified from Schmitt (1987)
Apparent competition (an example from Schmitt 1987)
Found increased predator density and decreased gastropod density when bivalves were added relative to control sites
Direct & Indirect Effects
Indirect commensalism or mutualism
Dodson (1970) noted that communities found in small alpine ponds fall into two groups:
1. Ponds containing larval salamanders (Ambystoma; that feed primarily on larger zooplankton) and planktivorous midges (Chaoborus; that feed on small zooplankton – that don’t normally coexist with the large zooplankton)
2. Ponds with only Ambystoma (ponds with only Chaoborus did not occur)
Results: Removal of Ambystoma resulted in a shift in body size of plankton and a decline in Chaoborus abundance in the single pond that could be manipulated (Giguere 1979)
Hypothesis: Size selective predation of plankton by Ambystoma maintains the feeding niche of Chaoborus
Direct & Indirect Effects
Menge (1995) reviewed 23 experimental studies of rocky intertidal habitats that were sufficiently well replicated and long enough in duration for indirect effects to become evident
Considered only “ecologically significant” effects (that caused at least a 10% change in the abundance of one or more species)
How important are indirect effects?
Found that 83 types of indirect effects accounted for 40% of the observed changes in community structure caused by manipulations (e.g., predator or prey removal)
Most of the indirect effects were cases of keystone predation (35%) and apparent competition (25%)
Exploitative competition constituted only 3% of indirect effects!
Bottom-Up vs. Top-Down
Are abundances or distributions of organisms controlled by resources (bottom-up processes) or by predation & disease (top-down processes)?
Bottom-up view: Organisms at each trophic level are food limited
Top-down view: Top level is food limited, lower levels are alternately predator vs. food limited (originated with Hairston, Smith & Slobodkin 1960 – HSS)
See Murdoch’s (1966) critique of HSS
Dyer & Letourneau (2003) is an example of using top-down and bottom-up thinking to examine the controls on diversity at different trophic levels
Trophic cascade
H
P
C
- +
- +
++
Are Trophic Cascades “All Wet”?
Polis (1991), Strong (1992) & etc. argued that the idea of discrete trophic levels, which trophic cascades are predicated on, is invalid b/c of the prevalence of omnivory
Strong (1992) posed the question above, in part b/c omnivory appeared more prevalent in terrestrial communities (making trophic cascades more likely in aquatic communities)
Photo of Gary Polis from http://science.marshall.edu/fet/euscorpius/images/polis.JPG
A likely example of a terrestrial trophiccascade (McLaren & Peterson 1994)
500 km2 Isle Royale National Parkin Lake Superior
Primary producer: Balsam fir
Herbivore: Moose (59% of winter diet is Balsam fir)
Carnivore: Wolf (colonized island in 1959)
A Terrestrial Trophic Cascade
Photo of Isle Royale from Wikipedia
Figure from McLaren & Peterson (1994)
McLaren & Peterson (1994):
“The shaded areas highlight intervals of forage suppression
that… are closely tied to periods of elevated moose density, which in
turn follow periods of low wolf density (note the lags…)… these intervals have no correspondence
to AET [climatic fluctuations]”
A Terrestrial Trophic Cascade
A change in behavior of a top predator cascades through a community (Post et al. 1999)
On Isle Royale, fluctuations in North Atlantic Oscillation (NAO) result in changes in winter snow accumulation
Annual aerial surveys show close correlation between wolf pack size and the status of the NAO
Photo of winter wolf pack (in Yellowstone National Park) from Wikipedia
A Terrestrial Trophic Cascade
Figure from Post (1999)
Post (1999):
“a, Increase in the mean size of wolf packs in snowy (negative
NAO) winters…”
“b, Increase in the winter kill rate of wolf packs with pack size… kill rate per individual wolf also
increased during snowy winters”
“c, Decline in moose density one year after increase in size of winter
wolf packs”
“d, Increased growth of fir trees one year after decline in moose density” [notice reversed x-axis]
A Terrestrial Trophic Cascade
Changes in wolf behavior have ecosystem-level effects on Isle Royale because moose dramatically influence net primary production, litter
production & edaphic nutrient dynamics (Post et al. 1999)
Photo of moose from Wikipedia
A Terrestrial Trophic Cascade
A Trophic Cascade Owing to the “Ecology of Fear”
Trophic cascade without prey consumption, i.e., through interaction modification indirect effect (Beckerman et al. 1997)
Constructed 3 trophic levels: Grasses & non-grass “herbs,” generalist leaf chewing grasshopper and hunting spider in Connecticut old-fields
Problem: How to create a predator that cannot consume prey, but can display hunting behavior or signal “risk” to its prey?
Solution: Glue the spider’s mouth parts! - No effect on spider hunting behavior, except the spiders cannot
capture, kill and consume prey - Spiders can survive up to 2 months with glued mouth parts
Experiment: Mesh enclosures for 3 trophic groupings: - Plants only - Plants + grasshoppers - Plants + grasshoppers + glued (“risk”) or unglued (“predation”) spiders
A Trophic Cascade Owing to the “Ecology of Fear”
Trophic cascade without prey consumption, i.e., through interaction modification indirect effect (Beckerman et al. 1997)
Figure from Beckerman et al. (1997)
Results: Grasshopper densities with / without spiders did not differ
Significant positive effect of spiders on grass biomass – consistent with a trophic cascade; treatments with spiders had significantly less herbivore damage on grass than treatments with grasshoppers alone
A Trophic Cascade Owing to the “Ecology of Fear”
Trophic cascade without prey consumption, i.e., through interaction modification indirect effect (Beckerman et al. 1997)
Figure from Beckerman et al. (1997)
Results: Grasshopper densities with / without spiders did not differ
Significant positive effect of spiders on grass biomass – consistent with a trophic cascade; treatments with spiders had significantly less herbivore damage on grass than treatments with grasshoppers aloneSignificant negative effect of spiders on non-grass “herb” biomass, since grasshoppers shifted activity to more structurally complex herbs to avoid spiders
Bottom-Up vs. Top-Down
Hunter and Price (1992) – we should always start with a bottom-up template: “the removal of higher trophic levels leaves lower levels present (if perhaps greatly modified), whereas the removal of primary producers leaves no system at all”
Echoed in John McPhee’s (1998) Annals of the Former World, pg. 84: “Break the food chain and creatures die out above the link”
Fretwell (1977) & Oksanen et al. (1981) – OFAN – proposed a reconciliation: productivity determines the number of trophic levels that can be supported in a community; plant productivity therefore ultimately dictates when top-down forces could cascade back down
In general the top-down vs. bottom-up question applies to NPP, but in principal could be asked of a variety of variables at a variety of
trophic levels.
Foundation Species
Photo from Wikipedia; definitions from Ellison et al. (2005)
Figure from Whitham et al. (2008)
“Foundation Genotypes”
Keystone predator – a predator whose activities maintain species diversity at lower trophic levels by disallowing competitive exclusion (Paine 1966)
Keystone resource – first applied to plant species that sustain frugivores through periods of food scarcity in tropical forests, e.g., figs (Terborgh 1986)
Keystone Species
Photos from Wikipedia
Pisaster eating mussel
Barbet eating fig
An ecosystem engineer has a large impact beyond simply assimilating and dissimilating material
The definition is especially useful when applied to organisms that modify the environment through means other than trophic activities
Ecosystem Engineers
Photo of Clive Jones from Cary Institute of Ecosystem Studies
Ecosytem engineer – an organism that creates, modifies, or maintains habitat (or microhabitat) by causing physical state changes in biotic or abiotic materials that, directly or indirectly, modulate the availability of resources to other species (Jones et al. 1994)
Ecosystem Engineers
Photo of beaver dam on Tierra del Fuego from Wikipedia
Allogenic ecosystem engineer – organism that changes the environment by transforming living or nonliving materials from one physical state to another, via mechanical or other means (Jones et al. 1994)
E.g., Beaver
Ecosystem Engineers
Autogenic ecosystem engineer – organism that changes the environment via its own physical structures, i.e., living & dead tissues (Jones et al. 1994)
E.g., Long-leaf pines
K. Harms’ photo of Pinus palustris at Camp Whispering Pines, Tangipahoa Parish, LA
Assembly Rules
Photo of Jared Diamond from Wikipedia
Diamond (1975) coined the term for broad patterns of bird species distributions in the Bismark Archipelago & Solomon Islands
Wilson & Whittaker (1995; pg. 801): “generalised restrictions on species presence or absence that are based on the presence or absence of one or several other species, or types of species (not simply the response of individual species to the environment)…”
Connor & Simberloff (1979) kicked off a long and continuing debate about assembly rules and testing for them
E. Weiher (quoted in Stokstad’s piece in Science, 2009, v. 326, pg. 34):“I think what we’re going to find out is that assembly rules are vague, gentle constraints”
Priority Effects
Petraitis et al. (2009) provide an experimental example of priority effects and multiple stable states in the Gulf of Maine
Ice scour can create open patches; experiments mimicked these disturbances (rockweed stands cleared in 1996 and followed through 2005)
In sheltered bays, rockweed stands or mussel beds established, depending on which arrived first, and were not invaded by the other species
Figure from Petraitis et al. (2009)
As required by Peterson (1984) to establishmultiple stable states, “the very same site could come to be occupied by different, self-replicating communities”
Community Assembly / Coalescence
From: J. N. Thompson et al. 2001. Frontiers of Ecology. BioScience 51:15-24.
“We use the term community coalescence to refer to the development ofcomplex ecological communities from a regional species pool. This
coalescence depends on inter- actions among species availability, physical environment, evo- lutionary history, and temporal
sequence of assembly.”