ECOLOGY -- INTERACTIONS UNIT                                    
Chapter 13: Competition -- don’t forget my images page on my website for chapter 13
             Intra-/interspecific; interference, resource (exploitative) competition

Intra- within individuals of the same species; inter- between individuals of different species.
Resource (exploitative) – does not have to be direct fighting; this can be different plants competing for the same
          soil nutrients but not DIRECT interference competition, where individuals do directly interact

        Damsel (and other) fish example – on page 283.  This is interference competition where the fish directly compete for space in the coral reef.  This can be both within (intra-) and between (inter-) species of fish.

        Pine forest root trenching experiment – also on page 283.  When a trench was cut between some pine trees in the forest, and the roots of these nearby pine trees cut, there was a sudden burst of growth in the herbaceous plant growth and seedlings of trees in the trench.  This suggests that these plants, whose seeds were lying dormant in a seed bank, have been released from the resource competition and “allowed” to grow.

    Intraspecific Competition -- the logistic growth curve can have the assumption with it that intraspecific
        competition for limited resources largely determines K.
      Examples:       PLANTS
            Sorghastrum nutans (competing for N in soil); Medicago sativa (Alfalfa)

See second and third images (figs. 13.3 and 13.5 in your text)--

With Sorghastrum nutans, when grown in low density, increasing nitrogen content of the soil (to a point) resulted in increased size of the plants.  Not so at high density of the plants, where there is still not enough nitrogen for individual plants to grow larger.  With Medicago sativa, the density of plants gets lower and lower as they mature, suggesting that some have a distinct advantage and crowd out others (others die) as they get bigger.  This process is called, as you will see below, self-thinning.

        Two important results can occur as plants are grown in increasing density:
            1.  Low density -- plants of same species may be larger than when grown under higher
                density.  WHY?  (S. nutans example above)
2.  Self-thinning -- exhibited by many plants; the idea being that as a patch of one species
                grows, more and more of the biomass is in fewer and fewer large individuals.  WHY?
    (M. sativa example above)
      Examples:       ANIMALS
            Homopterans -- aphids, planthoppers, leafhoppers.  All share a feeding habit almost unique
                in the insect world -- can tap into flowing "sap" with a very flexible "beak"
                At higher densities, these insects experience reduced survivorship, slower growth and
                development, resulting from reduced protein, water content and photosynthetic capability
                of host plants.  (see figure 13.6 in text; fourth and fifth images on my Chapter 13 webpage)
            Isopods (Grosholz) -- supplementing food APPEARED to have little effect on survivorship
                (though Grosholz used what turned out to be rather low densities of isopods – 50 or 100 in a third of a
                square meter plot; densities can be as high as 2000 per square meter in nature
), but higher
                density decreased survivorship, apparently because of cannibalism.  Is there a possible
                paradox here?  Should Grosholz have done further experiments to clarify food limitation?
With such low densities compared to natural populations, supplementing food may not have been necessary at ALL in the plots, so it is possible that at higher densities extra food WOULD have made a difference.

     Niches -- a niche consists of all the necessary factors to allow a species to subsist in a particular
        place and time.  Another way of looking at the word niche would be that the niche represents the
        role the species plays in the ecosystem -- all its interactions, including what it eats and, in turn,
        acting as food for other predators.  One important result of this definition is that the niche does
        not exist
without the species.  Although you may see the discussion of empty "niches" in various
        ecosystems, technically this is strictly an incorrect usage of the term as there IS no niche without
        the species, as indicated, and there may be no single species that can "fill" the "niche" that is
        being considered empty -- instead, IF species "fill" the niche, it could be many species that divide
        up the "empty niche".
      Fundamental vs. Realized Niche -- realized niche breadth necessarily narrower than fundamental
            niche breadth.  We discussed this before; the realized niche is what an organism actually does in a given
            place and time, and the same organism in different places can have different realized niches.

      The Competitive Exclusion Principle -- local extinction; as opposed to resource partitioning re-
            sulting from character displacement (remember MacArthur's warbler study in Chapter 1?)

The idea here is that if you have two species utilizing the same resources in a given place, that one may be a superior competitor and ultimately exclude the other species in that place.  (The other alternative is, as we discussed before, not only with the warblers but with Darwin’s finches (see Fig. 13.8, and the image on my webpage), that the two species partition the resources, with the two species evolving to use different parts of the available resources, a phenomenon called character displacement).

      Examples:        ANIMALS
            the warbler example mentioned above
            the classic: Galapagos (Darwin's) Finches -- Beak width and seed size.  Different species
        feed on different sized seeds based on beak width and length.  During drought times (remember
        from Chapter 11), smaller & softer seeds eaten first, leaving larger & harder seeds.  So drought
        may impact the smaller species more severely, and within species, it may be the larger, stronger
        individuals that survive through the drought.  So, food and water availability largely shape the
        niche of the finches (of course, many, many organisms are largely influenced by food/water)
Interspecific Competition -- Mathematical Models.  (an extension of the Lotka/Volterra models)
                  This involves modifying the logistic growth curve to include competitive effects.
        dN1/dt = rmax1 N1 ((K1 - N1- α12N2)/K1)    This represents growth of species 1 with affects
                                                                               on numbers from competition with species 2.
        dN2/dt = rmax2 N2 ((K2 - N2- α21N1)/K2)    This represents growth of species 2 with affects
                                                                               on numbers from competition with species 1.
        α12  &  α21 are competition coefficients, where the first represents competitive effects of species
            2 on species 1, and the second represents competitive effects of species 1 on species 2.
        If α12 > 1, then competitive effects of species 2 on 1 are greater than intraspecific effects.
        If α12 < 1, then competitive effects of species 2 on 1 are less than intraspecific effects.

        Likewise, if α21 > 1, then competitive effects of species 1 on 2 are greater than intraspecific effects.
        and, if α21 < 1, then competitive effects of species 2 on 1 are less than intraspecific effects.

It should also be obvious (hopefully) that α12 and α21 can BOTH be less than one, meaning that individuals compete for resources more with individuals of their own species and not others. Indeed, in communities where species have been interacting for a long time, this is what we would EXPECT, as different species should have somewhat different needs from each other, whereas individuals of the same species will have the SAME resource needs, and therefore higher levels of competition.  If either competition coefficient is > 1, then you ultimately might expect competitive exclusion of the species with the lower competition coefficient.  Understand that BOTH competition coefficients cannot be >1; if one is >1 then the other WILL BE <1.
Also understand if α12 = 1, then α21 will also = 1 (meaning they equal each other) which means individuals of these two species are equivalent competitors, and one individual of one species will have the same competitive effect as an individual of the other.

        Zero population growth will occur for each species when:
            N1 = K1 - α12N2    (for species 1)          and            N2 = K2 - α21N (for species 2)

Let me help break this down.  The whole idea here is that the higher number of another species of competitor there is, and the stronger the competition (indicated by the coefficient), the lower the possible number of the first species.  So, if either N2 or α12 is low, then there will be little impact on the carrying capacity for species one.  The higher either of those numbers get, then the greater the impact on species one.  Indeed, you can look at K1 - α12N2 as representing the current lower carrying capacity for species one because of species two.

On the test, you will be GIVEN the above equations, and be expected to indicate what each of the factors represents.  And you would be expected to find out what N1 and N2 would be at the new carrying capacity (zero population growth) given the competition coefficient, carrying capacity and number of the other species.

        Hopefully, it is obvious that with the added competition from another species, the ACTUAL
            value for K COULD go down for both species.  Also, needless to say, if you added other
            competitive species, the equation becomes more complex, but K COULD "decline"  for
            EACH species involved.  However, depending on competitive capabilities of the species,
            one could exclude the other, or they could partition the resources and coexist (see pg. 290)
        Laboratory Examples:
            Paramecium species: aurelia and caudatum  See Figure 13.15
                Grown separately, both species quickly reached a K based on intraspecific competition,
                    and K was higher for aurelia on both half (HS) and full strength (FS) growth media.
                Grown together, aurelia outcompetes caudatum, w/ complete exclusion on HS in 16 days.
            Tribolium (flour) beetles:  confusum and castaneum See Figure 13.16
                Grown separately, the species both did approximately equally as well.
                Grown together, castaneum outcompetes confusum when conditions were warm and
                    humid, but confusum outcompetes castaneum when conditions were cool and drier.
                Under intermediate conditions, the species first establishing a pop with greater numbers
                    typically wins out -- the priority effect.

There will NOT always be a priority effect, but it is a real phenomenon in many cases.

Clearly, competition can have a very strong influence on shaping niches in the lab.  What
            about in nature?
    Competition and Niches
        Natural examples:          PLANTS     See Figure 13.18
            Bedstraw (Galium) species on acidic (saxatile "wins") vs. basic (sylvestre "wins") soils
                Both establish healthy populations on a variety of soils when grown separately
        Natural examples:          ANIMALS   See Figure 13.19 and 13.20, and my webpage
            Barnacles:  Chthamalus and Balanus (mentioned before in Chap 9, pg. 203)
                Competition critically important in middle intertidal, but desiccation-resistance becomes
                more important in upper intertidal, and predation becomes more important lower.

So the dessication-resistant Chthamalus does better in the upper intertidal, and Balanus is a better competitor in the middle intertidal (and more predation-resistant in the lower intertidal).

            Desert Rodents:  Dipodomys (Kangaroo rats; large granivores); Perognathus (Pocket
                mice; small granivores); and Onychomys (insectivorous rodents)
                    very ambitious study in SE AZ with large plots and removal strategies; we'll discuss
                    this example at some length (make sure to read pages 295 and 296 carefully, and
                    understand figures on page 297).  See also my webpage.

In enclosures constructed in the natural environment, when both Dipodomys and Perognathus were together, Perognathus numbers were always very low, suggesting Dipodomys is a better competitor than Perognathus. When Dipodomys was removed, numbers of Perognathus went up quickly.  The Onychomys were unaffected by numbers of Dipodomys or Perognathus (high or low), because they feed on a different resource (insects).

        Character Displacement -- will expand further on our previous discussion of Geospiza
            finches and then other organisms.  A definitive example of character displacement must meet
            several criteria (page 296, 298; figures on page 298). 

The criteria are numbered 1-6 on the bottom of page 296 and top of page 298.  The example (Fig. 13.25) shows that two separate species of finches, when they were the only species on a particular island, showed a similar range of beak depths (though fuliginosa is a bit smaller than fortis).  However, when both occur together on an island, fuliginosa beak depth shifted downward a bit and fortis beak depth shifted up.  This suggests that when they occur together, they evolve to use separate species of seeds, instead of overlapping and competing.

Chapter 14:  Exploitative Interactions -- Predation, Herbivory, Parasitism, Disease
  See my webpage:

Trophic levels in the ecosystem:
    Plants (the producers), herbivores (first order consumers; depending on plant consumed,
        may or may not eat entire plant), predators (second and higher level consumers; DO kill
        food), parasites (feed on, but do not usually kill, host), parasitoids (larva consumes host,
        often from inside, and matures as the host dies; functionally equivalent to predators), pathogens (induce
        disease; for the most part, functionally equivalent to . . . ?  -- that would be parasites most often).  All
        consumers are exploitative, i.e., make their living at the expense of others.

    Complex Interactions -- There are far more interactions than numbers of species.  WHY?
        Pathogens/Parasites that alter Host Behavior
            Examples:   ANIMALS
                Starling (Sturnus vulgaris), Isopod (Armadillidium vulgare), and a parasite (a spiny-
                    headed worm [acanthocephalan], Plagiorhynchus cylindraceus).  The parasite
                    changes the phototactic behavior (- to +) in the isopod.  WHY?  (See Fig. 14.2).
                Fungal parasites of moth caterpillars.  Near maturation of the fungus inside the host, the
                    caterpillar crawls to top of a plant, becomes stiff and dies.   WHY?

In the first case, the parasite inside the isopod (pillbug) makes the isopod crawl into the light, which makes the isopod an easy target to get eaten by the starling.  The worm WANTS the isopod to do this, because to complete its (the worm’s) development, it must do so inside the starling.  The worm then lays eggs in the starling’s gut, which are pooped out, and then consumed by the isopods (and the cycle starts again).  In the second case, the larva is “coerced” to crawl up, so that when the caterpillar dies, the skin will split open and allow the tiny fungus spores to be carried away by the wind and affect others.

            Examples:   PLANTS 
                Mustard (Arabis sp.) host and a rust fungus (Puccinia monoica).  Puccinia alters life
                    history of infected individual, causing plant to form a pseudoflower, with sweet sticky
                    hyphae that attract "pollinators" to move spermatia from one fungus to another.  Flies
                    are the most common and effective rust fertilizers, but bees and butterflies also can.
                    Infected plants may be killed, though some survive . . . however, those that do never
                    produce an actual flower, so fitness of infected plants is zero.  See Figs 14.4 and 14.5.
        Competition/Predation/Parasitism overlap
                Obviously, it will be difficult to untangle the different interactions and their individual
                    effects on organisms; some experiments, however, show clear alterations in numbers
                    and success due to competitive and exploitative interactions.
            Examples:    Tribolium castaneum/confusum   See Fig 14.6.
                Besides being affected by humidity/temperature (see the competition information in Chapter 13 above
                    for this example)
, a parasite (Adelina tribollii) also influences the competitive balance.  Both
                    species of Tribolium are a bit cannibalistic on eggs, but T. castaneum strongly prefers T. confusum
                    eggs when present (explains a LOT about the competition experiments).  The Adelina parasite
                    strongly affects castaneum but not confusum, largely shifting the competition in favor of confusum.

    Exploitation and Abundance -- Predator and prey abundance intimately tied together
        Already talked about several examples (like the Canadian Lynx, Snowshoe Hare, Dwarf
            Willow example -- see below); more examples presented here in Chapter 14:
            1.  Bats and birds and arthropod densities on plants (in Panama).

See Fig 14.10.  Birds are largely daytime predators of insects and bats are nighttime predators of insects.  When birds are excluded, arthropod density increased 65%, but when bats are excluded, arthropod density increased 150%.  Bats have a greater influence on overall arthropod density (but we don’t know for sure if each bat eats a lot more than each bird, or if there are just MORE bats [or both]).

            2.  Cactoblastis cactorum and Opuntia stricta in Australia; the moth was introduced
        from South America as a biocontrol agent.  Larval feeding introduces both fungal and
        bacterial pathogens into the Opuntia.  Extremely effective -- reduced pops from 12,000 per
        hectare to 27, and from area of infestation of 24 million hectares to a few thousand. This same
        moth, however, has turned out to be a potential threat to North American Opuntia, as the
        moth is now spreading out from Florida north and westward. 
            Similarly, rabbits overran parts of Australia as well early in the last century, but were largely
        brought under control by introduction of the rabbit papilloma virus.
            Both rabbits and Opuntia are now in low abundance in Australia, where much lower density
        allows them to escape the moth/virus for a while (probably similar to where they naturally occur).

See images on my webpage for both Cactoblastis and the rabbit papilloma virus

            3.  Foxes, Hares and Mange Mites (Sarcoptes scabiei) in Sweden; as mange spread across
        Sweden, reduction of fox populations resulted in increased hare populations, as well as other
        prey species of the fox (grouse, deer fawns).  See Figs. 14.11 and 14.12, page 312.

This is a common effect – if you reduce the populations of a particular predator, it only makes sense that some prey species will become more abundant.
    Dynamics -- Virtually all interactions are dynamic; as indicated previously, parasites may reduce
        host populations which may increase populations of prey (what would happen to a predator
        whose prey was affected by a parasite/pathogen?).  However, very few of these interactions
        result in some sort of continuously stable population levels for all species involved; instead, the
        populations are temporally dynamic.
      Example:  The classic example of the Canadian Lynx/Snowshoe Hare/Dwarf Willow (and
        other shrubs) shows how abundances of each species are tied to each other, and may change
        through time. See Fig. 14.14.  The up and down fluctuations run at about 10-year cycles, with the lynx
        lagging behind the hare, and the hare lagging behind the dwarf willow. The main reason is that as dwarf
        willow numbers go up, then hare numbers follow since they eat the dwarf willow, and then lynx numbers
        go up since they eat the hares. As hare numbers go up, competition stiffens and dwarf willow numbers go
        down.  This causes hare numbers to decline, especially as lynx numbers are increasing. In turn, the lynx
        numbers then crash.  We have this data going all the way back into the middle 1800’s because of
        trapping data and pelt counts. 
An added interactive effect we had not discussed before is that the shoots of
        the Dwarf Willow (and others) that the Snowshoe hares browse on increase their terpenoids and
        phenolic resins in response to high rates of feeding, making the plants less tolerable to hares,
        effects which can persist for up to two years.
            On the predator side of the story, there are other predators which feed on Snowshoe Hares,
        such as foxes, coyotes, goshawks, owls, and mink/weasel.  It appears as though these predators
        experience some population cycling as well.  Coyote diet may be 2/3 Snowshoe hares at peak
        hare density, suggesting a predatory functional and numerical response to hare density.  Both
        coyote and lynx numbers increase 6 - 7 fold during high hare densities, though the functional
        responses were a bit different.  Both killed more than they could eat at the highest hare densities,
        with coyotes in particular caching for later, though coyotes kill the most during hare increases
        (and apparently would kill more if they could as their predatory response showed no sign of
        levelling off), while lynx killed the more when hare pops were declining already (probably
        attacking already weakened individuals).  Experimental manipulation of food abundance and
        predator abundance led to expected results (see Fig. 14.15).
    Mathematical Modelling of population cycles:  (more Lotka/Volterra "stuff")
        The host/prey equation is as follows:
        dNh/dt = rhNh - pNhNp where "h" refers to host & "p" refers to predators/parasites/pathogens
                                                 "p" is the  RATE of predation/parasitism, which means that "pNhNp"
                                                 is the rate at which exploiters destroy hosts in the whole population.
        Similarly for the predator/parasite/pathogen population numbers:
         dNp/dt = cpNhNp  - dpNp where "c" is a conversion factor representing rate at which exploiters
                                                    convert hosts to offspring; "d" represents death rate

As before, with the modified competition equations, on the tests I’ll provide you with these equations but you must be able to identify the different variables. Remember that this equation started out as simply dN/dt = rN.  If you ignore immigration and emigration, you can rewrite this equation as dN/dt = (b-d)N (birth and death). Realize the host equation can be rewritten dNh/dt = (rh - pNp)Nh. As such, for the host equation equation , “r” (the intrinsic rate of increase) in this case is the birth rate . . . which means that pNp represents the death rate.  This makes sense because death should increase as p (the rate of predation) and Np (the number of predators) goes up.  Similarly, for the predator/parasite equation, it can be rewritten dNp/dt = (cpNh  - dp)Np, which again makes sense because birth rate of the predator/parasites, namely cpNh, will increase as predation rate, conversion efficiency and number of prey/hosts go up.

            SEE Figs. 14.17 & 14.18.  These equations tie numbers of hosts to numbers of exploiters --
        indeed, as Nh increases, so, too, does exploitation rate (pNhNp), which, in turn, declines Nh and, 
        in turn, Np.  So, increasing host and exploiter population numbers in this model lead to significant
        decrease in numbers later -- a cycle that is repeated.  Though this model has some obvious utility,
        remember again, however, that NO system in nature is so simple as to be ONE prey item with
        just ONE predator or parasite/pathogen.

            Laboratory attempts to produce cyclic fluctuations in exploiter/host populations have proved
        extremely difficult, though Utida was able to show remarkable cyclic fluctuations between prey
        bean weevils (Callosobruchus chinensis) and it's parasitoid wasp (Heterospilus prosopidis) for up to 112 generations in very small, simple, environmentally controlled, petri dish habitats.  See Fig. 14.18.

    Refuges -- to persist in the face of exploitation, prey/hosts need refuges 
            1.  Didinium nasutum (predators) and their prey Paramecium aurelia (see Fig. 14.19)
        Gause was able to produce oscillations, but only if there was a refuge for the Paramecium, and
        an immigration source (lab cultures) for the Didinium.
            2.  Huffaker and the ballooning/crawling herbivorous mite (Eotetranychus sexmaculatus) and its
        crawling predatory mite (Typhlodromus occidentalis).  The ballooning capability of the herbivore
        allowed it to get to at least temporary refuges on other fruits ahead of the predator, and resulted in
        oscillations of predator-prey populations (see Fig. 14.20)

For this experiment, the refuges were the tops of oranges covered in petroleum jelly, making it difficult (but not impossible) for the predatory mites to discover some (but not all) of the ballooning mites.

      Spatial Refuges -- typically what we think of in terms of refuges; Opuntia has not been driven
          extinct in Australia as a result of the introduction of the moth Cactoblastis cactorum.  Why?  It 
          has spatial refuges where, at least momentarily, it has escaped the moth.

Spatial refuges include any place that an organism of any kind can “hide”.

      Numerical Refuges -- "safety in numbers".  Hosts/prey can overwhelm exploiters, resulting in
            predator satiation.  Schools of fish, flocks of birds, etc.
          Examples:  1. The thirteen and seventeen year periodical Cicadas           See Figure 14.22

These types of Cicadas only emerge on these multiple year cycles.  They emerge in such massive numbers that no predator can eat even a small fraction of these. Here’s a link to an image of such a cicada:

              2.  Masting by plants (synchronous seed/fruit production), often after disturbance (eg., fire)
      Size as a refuge – Elephants, Redwood trees, etc.
        Though young may fall prey to predators, many species reach an ultimate adult size that puts them
            outside the range of prey that can be handled by the predator.
        This has led to "appear big" behaviors -- cat defensive posture

Chapter 15: Mutualism -- Interactions where both benefit
                Commensalism -- interaction where one benefits, and other is largely unaffected
        OBVIOUS examples of mutualism:  You and your E. coli; pollinators and flowers;

Make sure you spend some time looking at my webpage, and the different shapes of flowers and the types of organisms that pollinate them.  These images are at the beginning of the Chapter 15 images.

             fruits and seed dispersers; many plant (cellulose) eaters and their digestive microorganisms – termites for instance; the termites themselves cannot digest the wood (cellulose), but their gut has microbes that can; in turn, the microbes get a safe nutrient-rich environment to live in.
    Facultative vs. Obligate  (A facultative mutualism is when the mutualism is not required by one or both of the organisms, but they make use of each other when possible; an obligate mutualism is when the two organisms cannot live without each other)
        Margulis (and others) and the endosymbiont theory (now "proven" by DNA analysis)   

The endosymbiont theory is that mitochondria and chloroplasts were once separate organisms. It turns out that mitochondrial DNA/ribosomes are indeed shared with bacteria, and chloroplast DNA/ribosomes are indeed shared with cyanobacteria. This shows that these organelles did indeed originate as separate organisms.

Plant Mutualisms -- (some already mentioned above)
      Plants and Mycorrhizal Fungi -- a 400 million± year relationship         [a facultative mutualism]
            Some plants grow root "chambers" for the fungi, other types form a network around roots.
        These fungi help plants w/ water extraction; nitrogen and phosphorus/copper/zinc sequestration;
        access to more phosphorus allows plants to grow more roots, which allow them to claim more
        water.  The fungi, in turn, get carbohydrates produced by the plant.    See Fig. 15.7
            Conflict of interest?  The balance sheet is not always nice and equal.  Different mycorrhizal
        species and even different strains within the same species may not "treat" their hosts the same, and
        may parasitize the host plant.  Fungi may be more likely to act parasitically in more fertile soils,
        as plants release less soluble carbs in root exudates in more fertile soils, which apparently has
        selected for more aggressively carbohydrate sequestering mycorrhizae.  In Andropogon (bunch-
        grass), both shoot growth and inflorescence production are maximized when grown with associated
        mycorrhizae from unfertilized soils rather than fertilized. 

This suggests that as long as the fungi are limited by resources in the soil, that the interaction is truly mutualistic, as the fungi truly “need” the plants under these circumstances.

      Bullhorn Acacias and ant (Pseudomyrmex) symbiotes               [an obligate mutualism for the ant]
            Hollow thorns for ant abodes.  The ants are fast, aggressive, agile climbers, that vigorously attack
        growing vines/epiphytes or other animals (caterpillars) that grow/eat the tree, which is already well
        protected by nasty spines!  Additionally, the Acacias provide foliar nectaries and Beltian bodies
        to "keep" ants fed and on the host tree.  Acacias without ants both grow slower (leaves, shoots,
        thorns, etc.) and show higher infestation (by other insects) and lower propagation.  See Figs. 15.8 – 15.11
        and my webpage
            Conflict of interest?  The ants may be at odds with pollinators, both in competition for nectar and
        driving them away.  However, inflorescences offer scant nectar, and have an ant repellant chemical.
      Aspen Sunflowers (Helianthella) and Formica (and other) ants in the temperate zone    See Fig. 15.13/14
            Ants are attracted to this Rocky Mtn. sunflower because of extrafloral nectaries, with nectar
        rich in sucrose and numerous amino acids, sufficient to keep the ants attention.  During times when
        the flowers are budding and just opening, ants rigorously patrol the flowers and help deter potential
        bud/seed predators, but once flowers are open, the rays form a "shield" between the nectaries and
        the open face of the flower, so the ants do not generally interfere with pollinators.
            There are several species of ants involved here, and NONE have an obligate relationship with
        Helianthella.  The reason probably has to do with, at least in some populations, late frosts which
        kill the flowers (including the nectaries; see Fig. 15.15) -- if ants were obligate, the ants would die
        at that point.  This event actually helps the sunflower, as it kills any and all seed predators in that
        year.  Clearly, the TEMPERATE climate plays a significant role in the nature of this mutualism.

    Coral Mutualisms -- a mutualism between the coral and algae (zooxanthellae)
            Coral reefs have exceptional diversity, and among the highest productivity of any ecosystem, even
                though surrounded by the nutrient poor ocean.  How?
      The mutualism:  dinoflagellates that are photoautotropic, and therefore productive.  They live within
        coral tissues, and receive nutrients from the coral animal, while the coral receives organics from the
        zooxanthellae produce during PS.  Corals induce release of nutrients from zooxanthellae when
        needed by coral with chemicals that change zooxanthellae cell membrane permeability, whereby they 
        release large amounts of fixed carbon.  The corals also keep growth of the zooxanthellae at 1/10 to 
        1/100 that of individuals cultured separately, because of higher levels of carbon fixation.  Doesn't
        sound like a mutualism so far, but . . .
              The zooxanthellae appear to get access to higher levels of nutrients, especially nitrogen (in
        ammonia waste).  Corals with zooxanthellae partners, don't APPEAR to release ammonia, as it is
        metabolized by the zooxanthellae. 
      Crab/Shrimp mutualism with coral:
              The coral gain protection, and the crab/shrimp mutualists get food (extra fat bodies produced)
         and shelter.

Other examples of mutualisms:  Orchids and orchid bees (obligate, see video link), Yucca and Yucca Moths
    (obligate), Mullerian mimicry (facultative), the honeyguide and humans (see the "Applications" section
    of chapter 15).

See the end photos on the webpage:

Orchids are pollinated exclusively by orchid bees (see this video Orchids and orchid bees), and the orchids provide male bees with chemicals that they use to make pheromones to attract female bees. 

Yucca plants are pollinated exclusively by Yucca moths; the Yucca moth females do not feed as adults, but appear to “purposely” pollinate the flowers (the anthers are reflective in UV and therefore VERY easy for females to locate); once pollinated, the female moth will lay one egg in one of three seed chambers, and she marks it with a pheromone so that no other females will lay an egg in that seed pod.  Apparently, sacrificing one set of seeds (which benefits the larva of the moth) is offset by getting pollinated and producing two other sets of seeds.  Again, see the images at the end of my webpage.

Mullerian mimicry, which we have talked about before, where two+ “bad” organisms look like one another, benefits all of the members of the mimicry complex.

The Honeyguide example is an interesting one.  Originally, the honeyguide, a bird that likes honey (!) evolved to call when it located beehives, which attracted honey badgers which would come and open nests, which would allow the bird access.  Turns out, however, that humans started using this strategy, and honeyguide birds have evolved to call to humans instead of honey badgers to guide the humans to the hives.

    Evolution of Mutualism -- in general, we would expect mutualism to evolve and persist in a population
        when and where mutualistic individuals have a higher fitness than non-mutualistic individuals.  This
        will happen when the benefits to the two organisms exceeds the costs of the relationship.