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Chapter II-2 (4) Species interactions Chapter 4 Relation to the book themes? System development: rules for incorporation of species to an emerging community and elemental processes that are involved Scale: all processes discussed here are local scale processes but how we see them may depend on scale Contents 1. Queen of trees example 2. Direct interactions refreshed 3. Review of indirect interaction types 4. The role of indirect interactions Major points to remember Indirect effects come in a greater variety of designs than direct interactions. Indirect interactions pose a far greater challenge to understanding and predicting effects of a species on other species than direct, two-species interactions. Indirect interactions increase in number and relative importance to a community as species diversity increases; thus they contribute to turning a species assemblage into a complex interactive system. As species arrive and settle in the new habitat, they begin to interact. The first plant and microbial colonizers may, for a short time, have to deal with the physical environment alone but soon consumers will discover them as food, population growth will lead to competition for resources, modification of the environment will facilitate success of the new wave of newcomers. Exploitation, competition, and mutualism become common. Some of these interactions, particularly the direct ones, are well understood theoretically and supported by numerous observations from nature. While their examination provides important insights into how action of one species results in the state of another, whether in space, population size, or reproductive success, they appear insufficient to understand intricacies of community construction and persistence. These pair wise interactions between species understate the complexity of indirect interactions that can propagate through chains of three or more species in complex communities. Indirect effects describe how the consequences of pair wise direct interactions between species are transmitted to other species either through behavioral modifications, altered spatial distributions, or altered abundances in the food web. Behavioral or other phenotypic modifications such as change of coloration, size, and defensive chemistry are often discussed as trait mediated effects. Indirect effects are a logical consequence of the fact that interacting species are embedded in larger food webs. Indirect effects throw a challenge to experimental ecologists who try to interpret community level experiments, since responses to the additions or removals of species can result from both direct and indirect effects. However, knowledge of the potential pathways of indirect interactions can be used to generate testable hypotheses that can illuminate which indirect interactions probably account for a particular response. Furthermore, indirect effects of different levels of intensity and different number of participating species may be the dominant type of interaction – a type that makes a community a community. In fact, it is difficult to imagine that an interaction between two species would not have impact on other species. In this chapter we will introduce a number of identified indirect interactions to illustrate the potential complexity of such interactions within an ecological system. As before, we will start with an example. The Queen of Trees – interactions of a single tree To show the rich texture of interactions in an apparently simple system we will Fig. 4.1. Sycamore fig, Sycomoros ficus, the locus of many unusual and important interactions. use an example. The information below is extracted from a Public Broadcasting Service series Nature entitled “The Queen of Trees” filmed by Mark Deeble and Victoria Stone in Kenya (produced by Deeble & Stone Productions, Thirteen/WNET New York, NHK, Granada International, BBC and ZDF). The New York Times commented on the documentary: „Sex, drunkenness, treachery, murder. Not bad for a nature program about a fig tree‟. Ficus sycomorus is a common large tree that grows in much of Africa where there is sufficient water (Fig. 4.1). It has an important mutualistic relationship with a fig wasp that is a Fig. 4.**. Fig wasp life cycle. The cycle begins with a flying wasp crawling into an immature fig where she brings pollen and lays eggs. The cycle ends with a young fertilized female wasp leaving a fig via a tunnel and carries pollen to find another tree. Compiled from various sources. billion times smaller than its host. Yet, the two are codependent and together provide a basis for many other species and interactions. The tree is home for many animals and many more visit and use its products. Numerous and bizarre insects, lizards, snakes and monkeys are the regulars. Different birds, including a pair of hornbills, who maintain their chicks inside the tree‟s trunk, nest in the tree or just come to feed. Yet, all this life depends on the tree‟s reproduction that is tied to the hidden life of the microscopic fig wasp that lives, mates and dies within the confines of a fig. The wasps lead unusual lives - the female mates with her brother before she is born. She never feeds, but must make a single flight across Africa carrying pollen, to ensure the survival of the fig tree and perpetuate her species. The tree provides home and sustenance for the wasps. Yet, throughout their short lives, the wasps are under attack from predators and parasites. Once the fig tree has produced its pollen, it proceeds to producing its fruit. Female wasps carry pollen to other trees. However, the fig tree must still disperse the seed and dispersing seeds involves attracting animals to nutritious fruit. This provides the biggest fruit feast on the continent, up to 1000 kilograms a year. Animals converge on the tree from throughout the bush. Of the millions of figs wasps that set off with their cargo of pollen and eggs only a few ever find a receptive fig tree. Just before dying, a female fig wasp pollinates the fig tree flowers. But the flowers are not of the ordinary kind. They are hidden inside a developing fig. Once wasps enter the fig, they lay their eggs and the eggs develop entirely inside the fig (Fig. 4.***). The interdependence of the fig and wasp is the culmination of millions of years of co-evolution between the two partners. Without it, many other animals would not survive or would face much greater challenges. The fig tree, its fruit, leaves, wasps and other animals associated with it have an impact on the local environment and on other animals. The connections are surprising. For example, mature figs may fall into the High infection success by parasitic wasps prevents fig wasp males from opening the fig and so all die, including parasites Sycamore tree or leaves Longhorn beetle Bandit wasps Dragon flies Cadidae bugs Birds Hilda bugs Ants Parasitic wasps Spiders Nematodes Gecko Mutualism (farming) Seed dispersal Fruit bats Giraffes Green pigeon +100 other bird species Preying mantis People Pollination Snakes Fig wasp Elephants Food and shelter Seed dispersal Antelopes Large predators Competition Tiger beetles Baboons Bees Hornbills Figs Cicadas Seed bugs Vinegar flies kill seedlings under the tree no reproduction directly under the tree Catfish Butterflies Crocodiles Fig. 4.**). The fig tree and its network of interactions with other organisms and among those organisms. Arrows indicate direction of action by a network component. Not all interactions are shown (for instance, insufficient predators are indentified for Cadidae bugs, seed bugs, butterflies,birds, spiders, fruit bats, preying mantis, and others. stream where they are eaten by catfish. Catfish in turn move over larger distances and disperse seeds along stream banks – a preferred habitat for fig seedlings. Furthermore, catfish are food for crocodiles. Thus, catfish pass the energy and nutrients to the aquatic system, with positive impacts on a range of organisms from aquatic algae and top predators (see Fig. 4.**). Negative feedbacks provide elements of control for some processes. For example, large concentration of seed bugs near the tree, where most fruits fall, prevents seeds from successful germination in the immediate proximity of the parent tree. Here, predation prevents competition between the parent tree and its offspring. Another case of a three way control loop forms between the fig wasp and its parasitic nematodes. Nematodes infect female and male larvae and eat them alive, however slowly, such that many manage to reach maturity, free themselves from the fig, and travel to another tree to deliver pollen, eggs, and nematodes, too. However, when the nematodes are too successful, they kill or weaken wasps still in the fig. Death of males has particularly negative consequence as they are needed to burrow a tunnel through the fig outer tissues. The tunnel is necessary to allow females to exit and fly away. When nematodes kill most or all males, no tunnel is chewed through and both wasps and nematodes die without dispersing and producing offspring. This insures that nematodes do not kill all the wasps and guarantees that there always are pollinated figs and fig seeds to perpetuate the tree. The trees role is not trivial. By evolving thick fig walls, the tree provides a trap for the enemies of its partner. The multitude of interactions illustrated by the species living of, in, and around the fig tree is great. Fig wasps are consumed by numerous species of birds, spiders, insects including dragonflies, preying mantis, ants, parasitic wasps, and geckos. Figs are consumed by fruit bats, catfish, monkeys, giraffes, elephants, green pigeons, and about a 100 other bird species, and vinegar flies. Figs also provide bees with latex resin and butterflies with sugar. Then, cicadas suck the sap from the tree and spray sugary liquid that is collected by bees, liked by monkeys, and, which diverts predation on cicadas by ants. At the same time cicadas fall prey to hornbills, which in turn directly compete with bees for tree holes. While many species contribute to seed dispersal by fig consumption, some species eat seeds directly (seed bugs). Because seed consumption occurs on the ground and concentrates disproportionately on areas where seed lie in high density, it ultimately controls fig tree reproduction directly under the tree. Thus, predation on seeds reduces potential competition between seedlings and the parental tree. Other ecological systems may still reveal many other interactions and their permutations. It is the interactions that weave species into a community and that affect its assembly and development. As with all attempts of dealing with the diversity of nature, and the diversity of interactions, it is useful to identify some general terms that can be applied to known and newly discovered situations. Ecologists have such a terminology and continue to develop it. Below, we shall try to review familiar and introduce new concepts to the discussion of species interactions. Direct interactions Introductory ecology courses define and explore dynamics and consequences of predation, competition, and mutualism. These are direct interactions. Sometimes interference competition and provision are also mentioned and can be depicted as arrows of different colors and signs (Fig. 4.**). Before we discuss indirect interactions, a brief refresher of the basic concepts and assumptions that underlie our understanding of direct interactions will be useful. Predation. Predation is one of the several types of exploitation. Within Fig. 4.**. Direct interactions exploitation and depending on the need, ecologists distinguish also herbivory, parasitism, parasitoism, and disease. Disease does not have a logical justification because it is very similar to parasitism except that, traditionally, the term is employed when the parasites are very small, usually microbial and viral, with numerous exceptions. Exploitation has many known consequences. Predators affect prey age structure, behavior, phenotypic traits, population dynamics, genetics, spatial distribution, food choices, and many other aspects. When predator and prey coexist in a system, their numbers are believed to follow cyclic fluctuations whose regularity and dynamics depend on other species as well as environmental conditions and the abundance of the players themselves. Theoretical models of predation have been well developed and their predictions tested in a variety of situations. They are known as Lotka-Volterra models. Before we look at them, first recall the population growth model for exponential growth dN rN dt or for logistic (density-dependent) growth K N dN rN dt K The basic model of predation is derived from the exponential model of the population growth and consists of two population growth equations, one for the prey or host and one for the predator or parasite (Fig. 4.** and 4.**). The prey is assumed to grow without any limitation due to shortage of resources. Its growth is however affected by losses due to predation. These losses are calculated in proportion to the number of predators while the predation rate (number of prey lost to a single predator in a single time step) is assumed constant. Assumptions for the dN p dt cpN h N p d p N p predator population dynamics are somewhat different. The predator is assumed to grow as a Host to predator conversion rate; analog of r Predator death rate function of its ability to convert prey to new predators. This conversion is, indeed, a great and smart simplification because, in reality, it stands for the ability to subdue prey, to consume it in peace, and to process it to create a new predator. Death rate is considered constant. Fig. 4.**. Predator growth model. Two new terms are dp and c, or predator death rate and host-to-predator conversion rate, respectively. Thus, the growth of predator population is a product of how many predators there are, how many prey, how well predator captures prey (p), and how well this capture transforms into new predators. Deaths are proportional to the number of predators. This pair of equations is capable of producing predator –prey cycles under certain sets of parameters in spite of the fact that some important factors are not considered. Nevertheless, the Lotka-Volterra model offers a good framework for examining the role of other species and abiotic conditions on the dynamics of two species interactions. Such influences can be incorporated into the model dN h rh N h pN h N p dt Prey per capita rate of increase Predation rate Number of predators Number of prey (hosts) Fig. 4.**. Prey or host growth model. Nh is the number of prey, rh is the intrinsic rate of growth of prey, p is predation rate and Np is the number of predators. Thus, the rate of change in prey population is determined by density independent growth of prey less the losses due to predation, with the losses being a product of predation rate, predator numbers, and prey numbers. by making birth rate, predation rate, conversion rate, and death rates dependent on the current densities of either population, or dependent on the environmental conditions, or dependent on the population size and activity of a third species. Thus, the Lotka-Volterra equations provide and excellent spring board for consideration of community complexities. For example, models exist that include functional responses, time lags in recruitment, self-limitation when the numbers are high, and a number of other terms that add to the realism of the equations (for some examples see Case, 2000). While the purpose of this text is not to examine all such fine details of species interactions, keeping their existence in mind will help, however, to put the addition of species to a community in a richer perspective. Competition. It will come as little surprise that we also have Lotka-Volterra competition equations. For two competing species we need two equations. Terms and coefficients for Species 1 are denoted by subscript 1 and those for Species 2 are denoted by 2. The competition model relies on the logistic form of growth as it assumes that increasing numbers of either Species 1 dN 1 r 1 N 1 ( K 1 - N 1 - 12 N 2 ) = dt K1 Carrying capacity of Species 1 Competition coefficient Effect of interspecific competition on Species 1 Fig. 4.**. Competitor 1 growth model. Note two new terms: K and . K denotes the carrying capacity or the maximum number of individuals of Species 1 that the environment can support. is a competition coefficient that specifies the effect of one individual of Species 2 on the rate of population growth of Species 1. The term 12N2 represents the reduction of growth of Species 1 due to the competition from individuals of Species 2. or Species 2, or both, impose limitations to further growth of populations using shared resource (a condition for competition). Recall that the logistic growth model has a built-in density dependence. The latter means that as the population growth, the per capita rate of increase declines. Generally, it is assumed that the main cause of such decline is exhaustion of resources. The equation for Species 2 looks similar, except that now the competition coefficient represents the effect of one individual of Species 1 on the rate of population growth of Species 2: dN 2 r 2 N 2 ( K 2 - N 2 - 21 N 1 ) = dt K2 These two equations can conveniently be converted to graphs that allow a visual analysis of the competition between two species. An example of such analysis is shown in Figure 4.**. Different carrying capacities and different competition coefficients will lead to different arrangement of isoclines and hence different outcomes of competition. Mutualism. While predation and competition are important interactions in most ecological systems, mutualism appears to be indispensable ingredient of life on Earth. Without pollination, coral reefs, lichens settling on rocks, seed Fig. 4.**. Graphical interpretation of competition model. The blue and red lines are isoclines for Species 1 and 2, respectively. Consider first the rightmost point. The point represents N1 and N2 (densities of Species 1 and 2 read on respective axes). Because the point indicates densities of both species exceeding their isoclines, both must decline along the colored vectors (blue for species 1, red for 2). The derived vector leads to a new point. By producing a sequence of points that behave over time according their position with respect to the isoclines, it is possible to find out what the outcome of competition will be. As exercise, try to draw the movement of other three points shown on the graph. Box. 4.**. To consider… Isoclines in competition models – An isocline defines the density of a species above which its r>1, that is where the population will decline. Specifically, isoclines run along a combination of densities of both species such that a growth of a species of interest equals 0. The simplest isocline connects carrying capacity of a species when it lives alone (e.g., K1 on axis of Species 1) and the density of its competitor on axis of Species 2 that is sufficient to stop growth of Species 1 (the density of species 2 is expressed in units of Species 1 and takes the form K1/. For derivation of isoclines see introductory ecology texts. dispersal, ants defending plants, fungi and vascular plants associations, mycorrhizae (nitrogen fixing bacteria and plant roots), termite gut microorganisms, and many other obvious or subtle relations among species, life would not be similar to what we see today. Mutualism differs from competition and predation in one crucial consequence. This is particularly clear when we think of obligatory mutualists. Loss of one species makes the survival of its partner impossible. In contrast, loss of predator or a competitor may change many things, including intra-specific competition, but allows the continuation of the other species. Only the lost of prey for a specialized predator may have similar consequences to those seen in mutualism. Mutualistic relationships may be modeled in a way very similar to that of dN 1 r 1 N 1 ( K 1 - N 1 12 N 2 ) = dt K1 completion. The only significant difference Carrying capacity of Species 1 lies in the sign defining the impact of Species 2 on Species 1 (Fig. 4.**). In obligatory mutualism may be assumed constant while in facultative (optional) mutualism will vary from 0 (mutualistic relationship is dormant) to some value greater than zero depending on the contribution of one species to the success of the other. Coefficient of mutualism Effect of interspecific mutualism on Species 1 Fig. 4.**. Mutualist 1 growth model. One of the two terms K, is the same as in competition model. is a mutualism coefficient that specifies the effect (positive in this case) of one individual of Species 2 on the rate of population growth of Species 1. The term 12N2 represents the improvement of growth of Species 1 due to the beneficial activity of individuals of Species 2. Sometimes11 is added in front of N1 to capture intraspecific competition effects. Mutualism occurs when 11 > 12 (negative effect of intraspecific competition is greater than the beneficial effect of another species. Equation for Species 2 is similar and hence omitted here. competition in that it creates greater interdependence among species. Such interdependence brings risks to a species should its partner be in trouble for some reasons external to the mutualistic relationship. Consequently, species should not engage in mutualism haphazardly but only when it really makes a positive difference. Figure 4:** captures this idea in Frequency of competitive interactions mutualism is different from predation and Frequency of positive interactions Earlier, we mentioned that Mutualistic defenses Mutualistic habitat improvement Increasing physical stress Increasing consumer pressure Fig. 4.**. Mutualism tends to be most frequent when species are under stress, whether from other species (predation, grazing, competition) or from physical environment (drought, nutrient scarcity, difficulty in dispersing seeds or pollen). Bertness and Callaway 1994, TREE 9: 191-193. a generalized sense (combines expectations and observations). It also makes the point that mutualism (as well as exploitation and competition) do not function in isolation. In fact, a simulation study of mutualism between yucca and yucca moth (Bronstein et al. 2003) examined the effects of two species with antagonistic relationship with yucca. Yucca moths (Tegeticula alba) adults hide inside yucca flowers during the daytime and fly at night. Between dusk and midnight females gather pollen from flowers using their maxillary palps. They form balls of sticky pollen and push them into the receptive tips of yucca pistils. Mating also occurs within yucca flowers. Larvae grow inside developing yucca fruits. Larvae feed on developing yucca seeds, consuming a small percentage of the hundreds of seeds within capsules. Here, moths gain shelter and food and in exchange they provide yucca with an efficient pollination. Of the two antagonistic relationships studied by Bronstein et al. (2003) one involved flower eating insects (florivores) and another involved a seed parasite that also pollinates. The researchers were interested if the antagonistic interactions interfered with the mutualism. They found it did. The study indicated that those antagonistic species may lead to major fluctuations in the populations of mutualists and to patchy spatial patterns in their population densities. The lesson from this study is that mutualistic relationships are vulnerable to biological and, perhaps, abiotic factors. Indirect interactions Earlier in Fig. 4.** we introduced arrows to represent various interactions among species. Discussion of indirect interactions will make use of these arrows. The species at the beginning of an arrow is called the donor and the species receiving its impact is the receiver. In a symmetric or reciprocal competition or in mutualism both species are donors and receivers at the same time. From the perspective of community and ecosystem ecology we want to think of these interactions as building blocks for the whole biological activity. Because, however, such interactions are embedded in a complex network of activity (just think of the fig tree again), their models are not realistic and cannot be easily used to understand dynamics and patterns of the whole system, even if we had sufficient information on all the individual pairs. As a further step, and perhaps more interesting, we can examine what other modules have been already discovered or suggested. This will help to paint the picture of the potential relations among species as they assemble to create and maintain a new community. Many of those additional modules belong to a class of interactions we call indirect. Indirect interaction involve a third (or more) species that transmits and transforms the effect onto the receiver. Whenever more species are added, the number of combinations the arrows in Figure 4.*** can be arranged in greatly increases. Nevertheless, some situations are more common than others and we will review some typical cases. Fig. 4.**. Keystone predation. B – a basal Keystone predation (prey, host) species, P - predator. Broken line Keystone predation refers to situations – indirect effect (Menge 1995). where a predator plays a major role in the maintenance of some important features of a community. The predator may reduce fluctuations among other species, it may increase the productivity of the system, or it may maintain higher species diversity than it would be possible without its presence. This last effect may occur when a predator controls a superior competitor and thus indirectly protects another species - the inferior competitor - from being out competed. Robert Pain has demonstrated such a case experimentally. By removing star fish, Pisaster ochraceus, the predator on the Pacific rocky shores of North America, he showed that its absence led to the reduction of species Box. 1.1. To consider… Regulation of Keystone Predation by Small Changes in Ocean Temperature Eric Sanford [email protected] Key species interactions that are sensitive to temperature may act as leverage points or amplifiers through which small changes in climate could generate large changes in natural communities. Field and laboratory experiments showed that a slight decrease in water temperature dramatically reduced the effects of a keystone predator, the sea star Pisaster ochraceus, on its principal prey. Ongoing changes in patterns of cold water upwelling, associated with El Niño events and longer term geophysical changes, may thus have far-reaching impacts on the composition and diversity of these rocky intertidal communities. Science 26 March 1999: Vol. 283. no. 5410, pp. 2095 - 2097 DOI: 10.1126/science.283.5410.2095 richness from 15 to 8 species of major sedentary invertebrates. He found that this happened because competitors started excluding each other. The presence of predator prevented such an outcome under natural conditions by reducing competition and promoting coexistence of competing species. Further research (see Box 4.**) showed that this effect itself depends on environmental conditions such as temperature. Keystone mutualism The fig wasp and the fig tree are an excellent example. The effects of removal of one of either one species would spill on many other species indirectly. Certain species - keystone mutualists involved in mutualistic interactions may sometimes assume great importance in the community. For example, during the dry season in the tropical forest at the Cocha Cashu Biological Station in Manu National Park of southeastern Peru, only 12 of the approximately 2,000 plant species support the entire fruit-eating community of mammals and birds. Mutualism here consists of provision of food in exchange for seed dispersal. During this period, fruit production drops to less than 5 percent of the peak production, so the food available to the fruit-eating species is severely restricted. The 12 plant species still producing fruit and nectar meet the food needs of as much as 80 percent of the entire mammal community and a major fraction of the avian species at the site. Clearly, the loss of one or more of these "keystone mutualists" could significantly harm vertebrate frugivore populations. While the identification of keystone predators may be extremely difficult, keystone mutualists can generally be identified through non-experimental observations of the resources that the species use. Once identified, keystone mutualists can be managed to ensure the survival of the species dependent upon them. By increasing the abundance of the keystone mutualists for instance, it might be possible to increase populations of dependent species. Apparent competition This situation arises whenever a predator switches between two non-competing prey. They reciprocal fluctuations give an apparent picture of competition but are not due to actual competition but to the fluctuating preferences of the predator. This happens because many Fig. 4.**. Apparent competition. B – a basal (prey, host) species, P - predator. Broken line – indirect effect (Menge 1995). predators prefer more abundant prey. It would not be surprising to see squirrel and rabbit population to vary in a reciprocal manner, which might suggest competition while in fact these two species do not compete at all as they feed on different foods and require different shelters. As an example, consider the case of two sessile bivalves or clams (Chama and Mytilus) and two actively moving gastropods or snails (Tegula and Astraea). The clams occur mostly on reefs with many nooks and crannies. The gastropods are more abundant in low-relief reefs composed of rocky cobbles. While the clams use shelters from predators in crevices of the rock they tend to occupy, snails usually do not seek shelter. This spatial separation does not appear to be due to competition between the clams and gastropods. The clams and gastropods consume different kinds of food. The clams filter particles from the water column while the gastropods scrape algae from the rocks. Competition for space is also unlikely, because clams and gastropods favor different substrates. Gastropods need to feed on the surface of the rocks, while clams occupy crevices. Both clams and gastropods are food for many invertebrate predators, including lobsters, octopi, and whelks. The clams appear much more vulnerable to predators. This is additionally corroborated by the observation that both predators and clams are more abundant on reefs with rich texture and crevices. Because the pattern of distribution suggests that the two categories of species exclude each other, Russell Schmitt (1987) performed several experiments to confirm or exclude competition as the cause of the patterns. First, he transferred the clams Chama and Mytilus to the gastropoddominated rocky cobble reefs and observed Fig. 4.**. Decrease in snail density (solid circles) at sites receiving alternate prey (clams) contrasted to unchanged snail densities (open circles) at control sites without alternate prey. The decrease is attributed to apparent competition. (Reprinted from Schmitt, 1987, with (not yet) permission of the Ecological Society of America.) the impact of this transfer on gastropod mortality and predator abundance. He maintained high density of clams by replacing individuals lost to predators. As it was not possible to perform the reciprocal transfer of gastropods to the high-relief reefs where Chama and Mytilus usually occurred, Schmitt transplanted clams to areas with high and low natural densities of snails. This, he anticipated, would allow him to measure possible interactions between the clams and snails at low predator densities. As expected, when he transplanted clams to cobble reefs, he recorded increased predator abundance. Snails densities declined significantly over the 65-day duration of the experiment (Fig. 4.**). Snails had a similar indirect negative effect on bivalves, with more bivalves being consumed by predators in areas of high gastropod density (45.1 snails/m2) than in areas of low snail density (4.7 snails/m2). The results are consistent with an asymmetric indirect negative effect of bivalves on snails, mediated by the rapid aggregation of predators in areas with high densities of their preferred prey, the clams. Tri-trophic interactions This situation is a specific case of a trophic cascade. It arises when a predator consumes a predator of a third species. An increase in predation on the „transmitter‟ causes the basal species (the prey at the bottom of the interaction chain) to benefit. In fact, the triFig. 4.**. Tri-trophic interaction or trophic cascade. B – a basal (prey, host) species, P – predator, H –prey, host, or predator. Broken It is possible to see several such modules line – indirect effect (Menge 1995). arranged on top of each other and forming a trophic cascade. trophic interaction can be seen as a module. A good illustration of this sort of relationship comes from freshwater lakes. In lakes, the basic food chain runs from algae to zooplankton to planktivorous fish to piscivorous fish. High piscivory (predation on fish) pressure from fish such as pike maintains low zooplanktivore (fish that eat zooplankton such as minnows) abundances. Low zooplanktivore abundances exert weak predatory effects on zooplankton. As a result, the planktivore zooplankton population density (e.g., Daphia) increases and often clears water of phytoplankton. However, the predicted cascading effects seldom appear as decreased phytoplankton abundance (Carpenter et al. 1987). One reason is that the phytoplankton consists of an array of species that differ in their vulnerability to grazing by zooplankton, and differences in zooplankton grazing pressure simply select for complementary communities of algae that differ in grazer resistance. This situation has been modeled by Mathew Leibold (1989). When zooplankton is abundant, the phytoplankton is dominated by grazer resistant species. When zooplankton is less abundant, the phytoplankton is dominated by competitively superior species that are vulnerable to grazing. Phytoplankton remains abundant, but is dominated by different sets of species. Such a shift is reminiscent of „keystone predation‟ we have presented earlier but differs from it in that Fig. 4.**. Exploitative competition. B – a basal (prey, host) species, P – predator . Broken line – indirect effect (Menge 1995). diversity of species remains the same while composition changes. Additional indirect effects may also take place. For example, in presence of numerous planktivores, zooplankton such as copepods and cladocerans, undertake daily migrations. During the night they move towards the water surface where they feed on algae while they migrate to deeper water to hide in the zone of poor visibility from their fish predators. The best example of a terrestrial trophic cascade comes from a study by Robert Marquis and Christopher Whelan (1994). They found strong effects of insectivorous birds that were transmitted through herbivorous insects to white oak trees. Birds were excluded from some trees by netting (cage treatment), while other trees remained available to the birds (control treatment). Birds significantly reduced the abundance of herbivorous insects on the oaks. In turn, oaks with birds and reduced herbivorous insects had less leaf damage from insects and subsequently attained a higher biomass. Exploitative competition This interaction can be direct and indirect, depending on the nature of the resource. If the resource is space or some other non-consumable resource, the interaction is direct because a third species is not involved. When, however, a third species or a collection of species such as plant food is involved, the interaction fits the definition of indirect type because a „transmitter‟ is present - the distinction comes from the definition of indirect interaction. For example, most tropical fish reproduce through mass spawning – the eggs and sperm float to the surface where fertilization takes place. Ocean currents carry the fertilized eggs and then larvae and, after a period of planktonic life, the larvae settle in a new location. However, they can only succeed if they are lucky at finding undefended space on the reef and they can out compete many other new arrivals representing various species. Because they compete with many species, this kind of competition is often term diffused. In this case it is a diffused direct exploitative competition. Habitat facilitation It occurs when activity of one or several species improves habitat of some other + P P species by altering the abundance or activity of a third interactor. The Large Blue lays its eggs in the buds of thyme - the culinary herb that grows wild in Europe - in the tight-bud stage. The butterfly must lay its B Fig. 4.**. Habitat facilitation. B – a basal (prey, host) species, P – predator. Broken line – indirect effect (Menge 1995). eggs after the thyme buds have started to open – otherwise the brood is lost. The eggs hatch after one or two weeks, depending on the weather; warm weather speeds hatching. The young caterpillars feed on thyme flowers for about two weeks during late July and early August, then fall to the ground where they are "adopted" by red ants (Myrmica sabuleti) attracted by a sugary substance secreted from a dorsal gland. The ants carry the caterpillar back to their nest, where it then gorges on ant larvae. While hidden from its predators, the caterpillar spends 10 months as a predator in the ant nest, and then pupates there. Until now, the Large Blue acts as a clever predator that cons ants into a case of deceptive mutualism. After three weeks and after it changed from caterpillar to chrysalis, the Fig. 4.**. Large Blue – a European butterfly whose caterpillars feed initially on plants and then on ant larvae after seducing ant workers with liquid containing sugar. insect emerges from its chrysalis and leaves the red ant nest to find a mate. Usually, red ants will escort the newly emerged butterfly to the surface, taking it to a low plant or shrub nearby. The red ants will encircle the butterfly and ward off any predators that attempt to attack the butterfly as it dries out. After the butterfly is ready to fly away, the ants will retreat back into their nest. This relationship does not always benefit Large Blue well because M. sabuleti is a warmth-loving ant that thrives only in short, dry grassland on hot south-facing slopes that are heavily grazed. For example, 52% of caterpillars survive in ant nests in newly burned patches as compared to 27% in long-established turf. If the grass grows higher than 3-4 cm and shades the ground, cooling it, this ant dies out and other species of ant take over - ants that are not interested in providing free food and lodging for Large Blue caterpillars. Specifically, with black ant species, caterpillar survival dropped from 15% to less than 2% of the entire population. Taller grass also crowds out thyme. Events in Britain brought changes of fortune to Large Blue. One was the Large Blue is a predator of ants, with which it has a complex relationship increased use of chemical fertilizers that promote vigorous grass growth, which smother off small wild flowers such as thyme. Then, sheep were pulled off the land by a change in livestock farming. For a few years, rabbits spread and kept the grass short in habitats favored by the butterfly, but in the 1950s myxomatosis (a viral disease of rabbits) was introduced and eliminated them. Pastures also were previously burned over, which kept the grass short, but this is no longer done. This sequence of changes exposed the second layer of relationships: grazers (P) change the composition and size of meadows (B) such that it favors red ants which in turn benefit Large Blue (P). Habitat facilitation appears to be very common in nature whenever a species has major impact on some other species or abiotic habitat, there will almost always be other species that benefit from the change. Elephants thin gallery forests to Habitat facilitation is very common and important create habitat for grasses and grassland animals, ants living in symbiosis with Acacias prune seedlings of other plants around to improve Acacia access to nutrients, water, and light, or beavers cut trees and open riparian habitat for a variety of plants that could not live in the shaded environment. Indeed, beavers also create aquatic habitat for pond and stream organisms. P - Apparent predation When predation on one species results in a decline of another, a potential but not actual prey, we can think of apparent predation. B B Fig. 4.**. Apparent predation. B – a basal (prey, host) species, P – predator. Broken line – indirect effect (Menge 1995). This situation is clearly illustrated by whelk, a large marine snail, that preys on barnacles. Whelk has the ability to penetrate barnacle plates and eat them. Barnacles, being sedentary on hard substrates such as rocks, Fig. 4.**. Apparent predation. Barnacles, whelk (right inset) and Littorina sp.(left inset). logs, and ships often form dense beds of organisms and provide shelter for much smaller Littorina snails that live in the same environment. The predation of whelk on barnacles leads reduced protective habitat and, in consequence, to decline of Littorina. In this situation we see a habitat modification by one species that produces a negative effect. This is in contrast to the effect observed in the case of habitat facilitation. Indirect mutualism It arises when two species benefit each other by acting on other species. Interactions between two predators on two competitors in freshwater ponds constitute a case of indirect mutualism. A salamander larva is a Fig. 4.**. Indirect mutualism. voracious predator of copepod crustaceans. These copepods are more efficient in consuming algae than cladocerans such as Daphnia. In natural ponds, Ambystoma and Chaoborus are almost always found together, and Chaoborus usually does not occur in ponds without Ambystoma. Dodson (1970) explained this pattern as a consequence of Ambystoma maintaining the feeding niche provided by small-bodied prey consumed by Chaoborus. Presumably, the large-bodied zooplankton that predominate in ponds without Fig. 4.**. Indirect mutualism. Salamanders reduce copepods (upper left)- competitors of cladocera (upper right) – a shift that benefits phantom midges (Chaoborus, lower photo). Ambystoma are inappropriate prey for Chaoborus. Comparing ponds with and without salamanders, Ambystoma, Dodson (1970) discovered that when salamanders reduce copepod population, cladocerans increase in numbers and benefit their own predator – phantom midge larva (transparent hunter). Indirectly, salamander benefits phantom midge. Conversely, reduction of Daphnia improves food supply for copepods and thus food for salamanders. However, there is a twist. Dethier and Duggins (1984) suggest that the conditions favoring indirect mutualism or commensalism as opposed to competition for prey are predictable if one knows whether the predators are specialized in Fig. 4.**. Indirect commensalism. their prey items or not. If the consumers are generalists that feed on both kinds of resources, the consumers will simply compete. If the consumers are sufficiently specialized so that each requires different sets of competing resources, as is the case in the case of the salamander and phantom midge, then a positive indirect effect will result. Whether the effect is reciprocal (a mutualism) or asymmetric (a commensalism) depends on the extent to which the resource species compete in an asymmetric fashion. Asymmetric competition among the resource species should favor an indirect commensalism, whereas symmetric competition among the resources should lead to a more mutualistic interaction among highly specialized consumers. Indirect commensalism (joint feeding) For this interaction to take place we need prey that are competitors such that the superior prey excludes inferior in absence of predation from the generalist. There must also be another predator that specializes on the inferior competitor. Parrot fish feed on coral and algae. By doing so, they expose coral skeleton that is a necessary substrate for tunicates to colonize and thrive. Tunicates will not settle unless parrot fish clear some space. Tunicates are however food for another reef predator, the surgeon fish. Parrots then provides indirectly food for surgeon fish, even though it may also feed on tunicates. A similar situation has been observed in the rocky intertidal system. Here, Katharina, a chiton that consumes larger competitively dominant algae, positively affects the abundance of limpets. This happens because limpets, graze on small diatoms that are competitively excluded by larger algae. The limpets have no reciprocal indirect Fig. 4.**. Indirect commensalism. Parrot fish (on the left) creates space for tunicates (purple barrels) to settle. Surgeon fish is the primary beneficiary. effect on Katharina, which is what makes this interaction an indirect commensalism. If they did, we could classify this interaction as a case of mutualism. Picture and process may depend on scale Yet, as illuminating and as useful in organizing the different situations as the above examples can be, things inevitably may be more complicated in nature. Let us revisit one of the many relationships of the fig tree. Recall that there are nematodes that parasitize the wasp. If we try to apply our graphical convention, we will Fig. 4.**. Interpretation of direct and indirect interactions depends on scale. Relationships among the same three species of the fig tree ecosystem can be represented differently depending whether small or large scale (time, space) is considered. soon realize that fitting such interactions into a straight jacket of formal arrows is not easy (Fig. 4.**). At small time scale, that of one tree or one wasp generation, fig tree indirectly benefits the nematode by providing its partner, the wasp, as food for the parasite. At a larger scale though, the tree competes with nematode for the wasp. The tree needs the wasp as a partner while the nematode might greatly reduce the number of emerging female wasps. Yet, the tree has a weapon, whether evolved directly for this purpose or not, it limits success of nematodes to the level that they cannot interfere in a detrimental way with the wasp life cycle and thus tree reproduction. Furthermore, all the specific models presented above included a minimum number of hypothetical species needed for the particular interaction to occur. However, it is easy to imagine, and many situations in nature exemplify it, that more than on transmitter may be involved. It is also possible to imagine that transmitters themselves might interact or that there are alternative transmitters in the same system. In such situation, indirect interaction would be much more diffused and much more difficult to detect unambiguously. Box. 4.**. To consider… Model estimating lions’ food intake under various scenarios of prey density and prey and predator grouping behavior. How this is done? In order to find out how much lions eat, we need to consider how much area they can cover searching for prey, how long it will take them to stalk, capture, eat, and digest the prey, and how many prey are available in area investigated by lions. Thus, if lions hunt alone, they are expected to capture and eat the quantity of wildebeest according to ( ) (1) ( ) where a is the area of effective search per unit of time, h1 is the expected time to attack and subdue each prey item, h2 is the expected time to consume and digest each prey item, N is wildebeest density per km2, and ( ) is prey intake per lion per day (in kilograms). Equation 1 is the example of type II functional response explained in detail in most introductory ecology texts. Essentially, it says that lions should be eating more wildebeest if they check more area, waste less time on killing and eating, and wildebeest are more numerous. However, when lions hunt in groups, which is the most common situation, the time to stalk, kill, and eat prey (handling time) becomes shorter and the amount of food each lions takes changes according to ( ) (2) ( ) where G is the number of lions in a group. If you analyze this equation, you will see that denominator becomes larger, which means lions take less food in groups. This is because group hunting does not significantly increase the chance of finding prey. But what happens when wildebeests aggregate? This question can be answered by changing the encounter rate (measured by aN in equation (2) to the new term acNb. The two coefficients in this term, c and b, are borrowed from a function that relates number of wildebeest groups per km2 to the number of wildebeests per km2 (density). It is reasonable to think that more groups will form when more wildebeests are present. However, the relationship is curvilinear and needs to be ‘straightened up’ by employing natural logs. Only then c and b can be found. By inserting the new encounter rate into Equation 1 we produce ( ) ( (3) ) Finally, we can combine Equations 2 and 3 to calculate how many kilograms of wildebeest each lion will eat when both the lions and wildebeest interact as groups ( ) ( ) (4) Issues like this may go beyond the choice of analytical scale. Processes that occur at different scales may also produce apparently puzzling patterns. Classical analysis of predatorprey interactions between lions and wildebeests suggest great fluctuations of both populations, with a possible collapse of the whole system. However, Fryxell and colleagues (2007) found that several factors ranging from climate patterns to group behavior act jointly to smooth out population variability that would otherwise be caused by predation. In Serengeti (Tanzania) wildebeests migrate in response to seasonal migration of rains and thus suitable grasses. Lions live if large prides in order to defend territories where they hunt. Wildebeests may pass through those territories at the time of migration but their availability is unpredictable from the lion perspective. The model developed by the Fryxell‟s group (Box 4.**) shows that lions would benefit greatly from solitary hunting, especially should wildebeest forage individually (Fig. 4.**). However, daily food acquisition turns Rather, they give priority to long-term stability of food delivery and reproduction via maintenance and defense of well marked hunting territories. To maintain those territories lions need to cooperate and forming permanent groups (prides) fulfills that need. Thus, need to migrate (wildebeest) and maintain territory (lions) jointly reduce the effectiveness of lions as hunters but ensure a large and fairly stable wildebeest population. Wildebeest aggregative behavior Kg of prey per lion/day out to be a secondary consideration for lions. 0.7 a 0.6 b 0.5 c 0.4 0.3 d 0.2 0.1 0 100 200 300 400 500 Prey density (individuals per km2) Fig. 4.**. Predicted predation success by Serengeti lions on wildebeests depending on tendency to form groups: a – both predators and prey are solitary; b – only predators act in groups; c – only prey are gregarious; d – both predators and prey are gregarious. Note that lions would enjoy the greatest rewards if both, lions and wildebeests were solitary. However, both tend to form groups in a natural setting, which reduces wildebeest losses to lions. Based on Equation 4 from Box 4.**) provides additional protection against predation. Thus, temporal, spatial, and organizational scales affect fundamentally the dynamics we observe. Things might turn out differently in parts of Africa where wildebeests do not engage in major seasonal migrations. Overall picture Total direct links how common various indirect interactions Links/S () numerous communities in order to assess Links () Menge (1995) has compared data from are (Fig. 4.**). Panel A shows that total number of all known direct interactions S not surprising as such a growth of the number of links is simply expected by chance – more species can have more Indirect only interactions. The number of links per Indirect effects/S () number of species, S, increases. This is Indirect effects () (links) among species increases as the S species grows also but appears to slow Fig. 4.**. Interactive links as a function of down. This may indicate that species stop richness, S, of a community. Each point is a engaging in additional interactions even as community. Open circles stand for mean the number of potential partners, prey number of links per species. Black circles are items, or enemies increases. In other all links found in a community. Curves were words, direct links decline relative to their fitted by eye to help visualize trends. A – direct potential number. A different picture links; B – indirect links. emerges when one looks at the indirect interactions (panel B). Here, the links show no tendency to decline on a per species bases. The more species in a community, the more indirect links they appear to engage in. A message from this points to the consequences of biodiversity: Box. 4.**. To consider… Methodological issue (related to scale) –it is possible that the number of direct links per species grows in proportion to S but, as S becomes large, each interaction is weaker or less frequent and hence more difficult to record. The trend might thus be a consequence of researcher’s inability to detect some interactions an increase in species nubmer leads to an increase in links among them but, in particular, indirect links. Such links form and integrated and complex network of interactions. This network can be analized in small steps by using elementary interactions types discussed earlier but its behavior as a whole is indeed much harder to understand. Elementary interactions are of great interest for conceptual and theoretical reasons. In nature however things may be much more complicated (cf. sycamore fig interaction diagram) as any single species may have numerous direct and indirect interactions that involve a number of steps. Sometimes, or perhaps often, such interactions can be mediated by physical processes, with community wide consequences. For example, studies of coral bleaching (loss of mutualistic zooxantellae) have shown that reef building corals are not affected directly by increased nutrients that are most often associated with eutrophication (high nitrogen and phosphorus availability) (e.g., Smith et al. 2006). Instead they find that dissolved organic carbon (DOC) will cause coral mortality as a result of increased microbial activity and subsequent smothering and hypoxia. This mechanism may explain how shifts (commonly called phase-shifts) from coral to algal dominance occur. It could be that by setting up a positive feedback loop whereby increases in algae (caused by overfishing, nutrient Direct interactions enrichment, bleaching, etc.) fuel microbial Predator-prey, competition, mutualism activity and cause local coral mortality; this opens up more space for algal colonization Structure of indirect Importance Multiple mechanisms Three or more species, transmitter Common, increase with richness Contributory processes act at several scales and thus more exudation and microbial activity and so on until a phase shift has Types occurred . Many combinations possible; only some have names Fig. 4.**. Graphical summary of concepts appearing in this chapter. Self-test questions 1. Are you able to explain the difference between the competition equation and the mutualism equation? 2. Do direct links among species increase per species when community richness increases? 3. Can you give a hypothetical example of habitat facilitation using indirect interactions convention? 4. Under what circumstances mutualism fails? Suggested readings/viewings The Queen of Trees video from PBS. Points to think about when considering the video Are the links shown in the video a complete representation of the complexity of interactions involving the fig tree? Would removal or loss of some of the interacting species cause a cascade of undesirable consequences, that is negative consequences for the fig tree or some of its major users? Can you think of some possibilities? What are the different means of seed dispersal a fig tree uses? Indirect effects in marine rocky intertidal interaction webs: patterns and importance. B.A. Menge. Ecological Monographs, (1995) 65: 21-74. Points to think about when reading the paper: Which types of interactions may be most common, direct or indirect? Would indirect effects be easy to detect? Is rocky intertidal habitat unusual – speculate. Tri-Trophic Interactions – some additional examples Robert Paine (1980) coined the term trophic cascade to describe how the top-down effects of predators could influence the abundances of species in lower trophic levels. Others have focused on indirect effects that propagate from the bottom up through multiple trophic levels, called tri-trophic effects when the interaction involves three trophic levels (Price et al. 1980). Regardless of the direction of transmission, once an effect proceeds beyond the adjacent trophic level, it becomes indirect. Hairston et al. (1960) and Fretwell (1977) clearly invoke the trophic cascade phenomenon in their writings about population regulation, although they did not call the process by this particular name. Evidence for top-down trophic cascades is surprisingly scarce, and comes primarily from aquatic systems (Strong 1992). There is at least one convincing terrestrial example (Marquis and Whelan 1994). It has been suggested that the scarcity of trophic cascades in terrestrial systems represents a real difference in the structure of terrestrial and aquatic food webs. Strong (1992) suggests that aquatic food webs may tend to be more linear than terrestrial ones. Trophic cascades might be likely to develop in linear food chains, in which effects of one trophic level are readily passed on to other levels. In contrast, in reticulate food webs, distinctions between trophic levels are blurred and effects of one species are likely to diffuse over many adjacent species. Studies of stream communities provide some of the best examples of trophic cascades. Power et al. (1985) showed that a top predator, in this case largemouth bass, had strong indirect effects that cascaded down through the food web to influence the abundance of benthic algae in prairie streams. The system is best caricatured as a simple three-level food chain, running from algae (mostly Spirogyra) to herbivorous minnows (Campostoma sp.) to bass (Micropterus sp.). The prairie streams typically experience periods of low water flow, during which the streams become series of isolated pools connected by shallow riffles. At such times, two categories of pools become obvious: bass pools with bass and luxuriant algae, and minnow pools with abundant herbivorous minnows but without bass or much algae. The pattern suggests a cascading effect of bass, which prey on minnows and could thereby promote algal growth by eliminating an important herbivore. To test this idea, Power et al. selected three pools for observation and experimental manipulations. The manipulations consisted of the addition of bass to a minnow pool and the removal of bass from a bass pool, which was then divided in half. One half of the pool received minnows; the other half remained minnow free. A third minnow pool remained unmanipulated as a control. The response of interest was the height of filamentous algae in the pools over time. After bass removal, Campostoma greatly reduced algal abundance to low, heavily grazed levels similar to those observed in a natural control pool with abundant minnows. Addition of bass to a minnow pool resulted in a rapid increase in algal abundance, whereas algae remained scarce in the control pool without bass. These results are consistent with a cascading indirect effect of bass transmitted through minnows to the algae. The actual mechanism involved appears to be largely a behavioral avoidance of bass by minnows. Minnows leave pools with bass, and, when confined with bass, limit their foraging to shallow water where the risk of bass predation is least. Similar kinds of trophic cascades may occur in lakes (Carpenter et al. 1985; McQueen et al. 1989) and have been proposed as a possible way to control nuisance blooms of algae in eutrophic waters. Trophic cascades are less dramatic in lakes than in prairie streams, and the influence of top predators generally fails to propagate all the way down to the algae. In lakes, the basic food chain (ignoring the microbial loop) runs from algae to zooplankton to planktivorous fish to piscivorous fish. Where strong trophic cascades occur, lakes with abundant piscivorous fish should have less algae than lakes in which planktivorous fish form the top trophic level, since zooplankton should be more abundant and should reduce phytoplankton to lower levels. However, the predicted cascading effects seldom appear as decreased phytoplankton abundance (Carpenter et al. 1987). One reason is that the phytoplankton consists of an array of species that differ in their vulnerability to grazing by zooplankton, and differences in zooplankton grazing pressure simply select for complementary communities of algae that differ in grazer resistance. This situation has been modeled by Mathew Leibold (1989). When zooplankton are abundant, the phytoplankton is dominated by grazer resistant species. When zooplankton are less abundant, the phytoplankton is dominated by competitively superior species that are vulnerable to grazing. Phytoplankton remains abundant, but is dominated by different sets of species. Consequently, the prospects for manipulating fish populations to control the abundance of nuisance algae seem limited. The best example of a terrestrial trophic cascade comes from a study by Robert Marquis and Christopher Whelan (1994). They found strong effects of insectivorous birds that were transmitted through herbivorous insects to white oak trees. Birds were excluded from some trees by netting (cage treatment), while other trees remained available to the birds (control treatment). Birds significantly reduced the abundance of herbivorous insects on the oaks. In turn, oaks with birds and reduced herbivorous insects had less leaf damage from insects and subsequently attained a higher biomass. The effect of birds on insects was further corroborated by including an insect removal treatment (spray treatment) consisting of applications of a spray insecticide combined with the hand removal of remaining insects.