Trade-offs in community ecology: linking spatial scales and species coexistence

Authors


* E-mail: kneitel@biology2.wustl.edu

Abstract

Trade-offs in species performances of different ecological functions is one of the most common explanations for coexistence in communities. Despite the potential for species coexistence occurring at local or regional spatial scales, trade-offs are typically approached at a single scale. In recent years, ecologists have increasingly provided evidence for the importance of community processes at both local and regional spatial scales. This review summarizes the theoretical predictions for the traits associated with trade-offs under different conditions and at different spatial scales. We provide a spatial framework for understanding trade-offs, coexistence and the supportive empirical evidence. Predictions are presented that link the patterns of diversity observed to the patterns of trade-offs that lead to coexistence at different spatial scales. Recent evidence for the evolution of trade-offs under different conditions is provided which explores both laboratory microcosm studies and phylogenetic tests. Examining trade-offs within a spatial framework can provide a strong approach to understanding community structure and dynamics, while explaining patterns of species diversity.

Introduction

In evolutionary biology, the ‘Darwinian demon’ reigns supreme in the world of life histories, by asexually reproducing with immeasurable frequency and number while living forever. Trade-offs between survival and reproduction, however, constrain any organism from realistically resembling that creature. Similarly, community ecology could have its analogous, ‘Hutchinsonian demon’, whereby one species in a community dominates because it is the best at colonizing new patches, utilizing all the resources, avoiding predators and resisting stresses (Tilman 1982 termed these ‘superspecies’). Here, interspecific trade-offs are invoked to tame this demon, in that the benefits of performing one ecological function well (e.g. consuming one type of resource) comes at a cost of performing another function (e.g. consuming a different type of resource). Trade-offs within this community context represent niche differentiation among species, which emerge from individual-level constraints within an environmental context (e.g. resources, abiotic factors, presence of competitors or predators; Chase & Leibold 2003).

Trade-offs are ultimately exhibited as a negative functional interaction between traits (e.g. growth and reproduction; Stearns 1989; Zera & Harshman 2001). These differences in life-history traits can have consequences for population parameters (growth rate and carrying capacity), body size differences and ecological traits (MacArthur & Wilson 1967; Pianka 1970; Boyce 1984; Gleeson & Tilman 1990). For example, the trade-off between seed size and seed number has been used as a proxy for the competition–colonization trade-off for species coexistence (Turnbull et al. 1999; Levine & Rees 2002); competitive ability is enhanced by production of fewer, larger seeds, whereas colonization ability is improved by production of many small seeds. Other examples include allocation to aboveground–belowground growth (e.g. Gleeson & Tilman 1990) and power-efficiency growth (growth at low and high resource levels; e.g. Sommer 1985). However, it is not always necessary to invoke character divergences because habitat characteristics (e.g. refugia; Mouquet et al. in press) and neutral models (e.g. Hubbell 2001) can also explain coexistence. Nevertheless, we argue that niche differences exhibited as trade-offs among species provide a more convincing explanation for species diversity patterns, especially when viewed within a spatial context.

Interspecific trade-offs are typically thought to be a requirement for species coexistence in communities at small spatial scales (MacArthur 1972; Tilman 1982, 2000; Petraitis et al. 1989; Tilman & Pacala 1993; Chesson & Huntly 1997; Grover 1997). Examples of local-scale trade-offs include differential use of resource types (MacArthur 1972; Tilman 1982), susceptibility to predators (Holt et al. 1994; Leibold 1996), and fitness in a temporally variable environment (Chesson & Huntly 1997). Recent studies, however, have focused on larger spatial scales, and in particular, the relative importance of processes acting at the local and regional scales (Caswell 1978; Ricklefs 1987; Cornell & Lawton 1992; Ricklefs & Schluter 1993; Tilman & Kareiva 1997; Loreau 2000).

A meta-community contains a group of species that potentially interact, and that are spatially segregated into distinct patches connected by dispersal (Wilson 1992). Within the meta-community context, trade-offs are still often heralded as essential for coexistence at a regional scale rather than local scale (but see Bell 2001; Hubbell 2001). For example, species can trade-off in their relative ability to compete and persist in patches and to colonize new patches (e.g. the competition–colonization trade-off; Levins & Culver 1971; Slatkin 1974; Hastings 1980; Tilman 1994; Yu & Wilson 2001). Similarly, species can be favoured in some habitats and disfavoured in others, and thus coexist either regionally as a result of partitioning of habitats (Tilman 1982; Chase & Leibold 2003) or locally as a result of source-sink relationships (Loreau & Mouquet 1999; Amarasekare & Nisbet 2001; Mouquet & Loreau 2002, 2003).

Despite the recognition that trade-offs can lead to coexistence at different spatial scales, theoretical and empirical studies have largely examined trade-offs for one spatial scale or the other (Amarasekare 2003). Hubbell (2001) has challenged the notion that trade-offs are necessary for understanding broad patterns of species diversity and relative abundance (see also Bell 2001). As a means to open a dialog, and provide a null model for communities, Hubbell developed a ‘neutral’ model which assumes that species have equal per capita fitnesses: species have no niche differences, and thus no trade-offs. In this article, we argue that a better understanding of the range, variation and interactions of trade-offs at multiple spatial scales will allow the development of a more synthetic view of diversity; within this explicit spatial framework, this niche theory provides an alternative to neutral models to explain high levels of diversity at different spatial scales (Fig. 1).

Figure 1.

Habitat type and possible traits associated with trade-offs that lead to coexistence at that scale. Trait trade-offs at lower organizational levels are included in higher levels.

There have been several summaries of theoretical and empirical support for trade-offs in specific systems (insects: Futuyma & Moreno 1988; desert mammals: Kotler & Brown 1988; Vincent et al. 1996; plants: Gleeson & Tilman 1990; Tilman 1990; Tilman & Pacala 1993; Grover 1997; aquatic animals: McPeek 1996; Wellborn et al. 1996; microbes: Bohannan et al. 2002). Therefore, to avoid redundancy, this review will emphasize the conceptual aspects of trade-offs and spatial scale while using empirical studies to better understand this relationship. Additionally, as we are not trying to explain patterns of diversity across trophic levels, we limit discussion to trade-offs among competing species within a trophic level. This review addresses four main points. First, we will summarize the trade-offs expected to lead to coexistence at a variety of spatial scales. The mathematical details of each model will not be discussed; our emphasis will be on the assumptions of the models that predict certain species traits. Secondly, the empirical evidence is also assessed for consistency with trade-off predictions, as well as their implications for community structure. Additionally, we address what these studies tell us about trade-offs and the scale of coexistence. Thirdly, we make predictions for the relationship between scale-dependent trade-offs and species diversity at multiple spatial scales (e.g. alpha, beta, and gamma diversity, sensu Whittaker 1972; Lande 1996; Loreau 2000). Finally, we discuss how evolutionary processes may influence trade-offs at multiple scales, and suggest avenues for future theoretical and empirical studies.

Trade-Offs and scale

Local-scale coexistence and trade-offs

The reductionist paradigm which focuses on controlled experimentation has dominated community ecology for over 25 years (e.g. Simberloff 1983; Strong et al. 1984): until recently, community ecology has focused on local-scale phenomena, implicitly assuming that systems are closed and that spatial processes are unimportant. The simplest of the models predict that in a spatially homogeneous locality, the number of coexisting species should be equal to or less than the number of limiting factors (MacArthur & Levins 1964; Levin 1970; Armstrong & McGehee 1980; Tilman 1982). This idea is a simple extension of the competitive exclusion principle as tested by Gause (1934).

A wide variety of limiting factors, and trade-offs among them, have been discussed as prerequisites for coexistence at local spatial scales (Fig. 1). Some of the most common, and potentially important, trade-offs among species include differential utilization of resources (i.e. different nutrients or prey items), susceptibility to predators, use of the abiotic environment (e.g. soil pH or temperature) and responses to disturbance or stress (Fig. 1). We briefly overview the traits associated with these trade-offs.

Resources

When a community is composed of a single trophic level, coexistence is possible between two species when there is more than one resource for which those species compete (MacArthur 1972; Tilman 1982). For example, each species’ ability to persist and compete for limiting resources can be derived by the amount of resource where a species’ death rate is exactly replaced by its birth rate. This level of resource, known as a species’ R*, represents the equilibrial level of resource expected when consumers have population growth, and the resource is depletable (Tilman 1982; Grover 1997; Chase & Leibold 2003). If there are two limiting resources, the species can coexist only when one species has a lower R* (superior competitive ability) for one resource, and the other has a lower R* for the other resource. Note, however, that this trade-off alone does not guarantee coexistence, as the ability of species to reduce resources, and the relative supply of the two different resources also influences coexistence.

Numerous empirical tests have been conducted to measure trade-offs among species’ use of resources (see review in Grover 1997). Most evidence comes from freshwater microorganisms (algae) that coexist under certain ratios of differentially used nutrients (Tilman 1982; Grover 1997). Some direct evidence for trade-offs among resource use in other systems (plants and animals) is weaker, some direct evidence exists for such trade-offs (e.g. Rothhaupt 1988), along with considerable indirect evidence (e.g. Werner & Platt 1976; Brown & Davidson 1977; Gleeson & Tilman 1990).

Resources and abiotic factors

Abiotic factors in communities can also influence interactions between species (Dunson & Travis 1990). For example, species can trade-off in their ability to utilize a limiting resource or to tolerate a stressful abiotic factor such as temperature, drought, or pH (Tilman & Pacala 1993; Chase & Leibold 2003). While abiotic factors are different from resources in that they are not consumed, the basic conclusion that such a trade-off is necessary for coexistence holds. Empirical evidence for such trade-offs include trade-offs between resource use and thermal tolerance (ants: Bestelmeyer 2000; invertebrates: Bengtsson 1991) or desiccation tolerance (marine invertebrates: Connell 1961; mosquito larvae: Juliano et al. 2002).

Resources and predation

A trade-off between competitive ability and predator invulnerability among species is often required for species to coexist; good competitors are negatively affected (individual or population growth rate) by predation and poor competitors are less vulnerable to predation (Paine 1966; Vance 1978; Armstrong 1979; Holt et al. 1994; Leibold 1996; Uriate et al. 2002). Predator invulnerability can be exhibited in a variety of ways, including avoidance, tolerance, or resistance (Brooks & Dodson 1965; Fritz & Simms 1992; Wellborn et al. 1996; Strauss & Agrawal 1999; Chase et al. 2000a; Tiffin 2000). These invulnerability traits then inhibit the prey species’ ability to gather resources, reduce their growth rates, or require higher levels of resources, which ultimately reduces its competitive ability. Although the interaction between predation and competition can result in coexistence by several related trade-offs and mechanisms, they only promote coexistence under certain circumstances (Abrams 1999; Chase et al. 2002).

Direct empirical evidence for this trade-off is common across terrestrial and aquatic systems (Leibold 1989; Balciunas & Lawler 1995; Kraajeveld & Godfray 1998; McPeek 1998; Schmitz 1998; Baldwin & Hamilton 2000; Bohannan & Lenski 2000a,b; Peacor & Werner 2001; Steiner 2003), and indirect evidence, in the response of different groups of species to removal of predators or increases of resources, is also prevalent (Paine 1966; Morin 1983; Lewis 1986; Leibold 1999; Carson & Root 2000; Chase et al. 2000b; Chase 2003).

Temporal variation

When there is temporal variation in environmental conditions, and when species trade-off in their ability to thrive under those different environmental conditions, many species can persist on few resources because of their being differentially favoured in different temporal windows (Chesson & Warner 1981; Caceres 1997; Chesson & Huntly 1997; Chesson 2000). One such mechanism by which such temporal variation can allow species to coexist is the ‘storage effect’ (Chesson & Warner 1981; Warner & Chesson 1985). The storage effect allows species to persist during unfavourable time periods by reproducing and growing rapidly during favourable time periods. Persistence during unfavourable time periods requires the organism to have some life-stage that can withstand the unfavourable conditions. For example, many organisms have resting eggs or dormant seeds, and others have long-lived adults that can persist during times of famine. Empirical examples of local coexistence thought to occur by means of mechanisms similar to the storage effect include two species of Daphnia that persist in the long term because of temporal variation in recruitment from resting eggs which result from environmental fluctuations (Caceres 1997), and several species of desert annual plants that vary in their recruitment and levels of seed dormancy among years with highly variable amounts of rainfall (Pake & Venable 1995, 1996).

Local trade-offs in a spatial context

All of the trade-offs at the local level discussed above can be used to help explain diversity at larger spatial scales. If the environmental factors or resources are spatially variable, then different species can be favoured in different localities, and thus can coexist regionally. For example, a plant species will be favoured when the ratio of two limiting nutrients, such as phosphorus and nitrogen, is low, and a different species will be favoured when the ratio is high. In a region where some localities have low N : P and others high N : P both species can persist. Similarly, when prey show a trade-off between competitive ability and predator resistance, the stronger competitor is favoured in environments with low resource supply, the more resistant species is favoured in environments with high resource supply and predators, and the species can coexist in regions that have both low and high resource localities with and without predators (Holt et al. 1994; Leibold 1996). In fact, Chase & Leibold (2003) have shown that these basic principles hold for a wide variety of combinations of limiting factors, including resources, predators and stresses. This simple result crystallizes the problem of scale in the principle that ‘the number of species coexisting cannot exceed the number of limiting factors’ (Levin 1970). Instead, when there is spatial heterogeneity, there can be many more species coexisting regionally than the number of limiting resources. Empirical evidence is provided by studies in several systems (Tilman 1982; Kotler & Brown 1988; Sommer 1993, 1994; Wellborn et al. 1996).

Trade-offs along multiple axes

Trade-offs are typically addressed among two traits, but there are potentially numerous environmental conditions along which species can segregate (Grime 1977; Tilman & Pacala 1993). These trade-offs are predicted to lead to coexistence at different spatial scales, but without any explicit connection among the scales. As examples, we consider McPeek's studies of interspecific interactions among larval damselflies living in lakes, and Tilman's studies on herbaceous plants living in old fields. Among genera of damselflies in the family Coenagrionidae, McPeek (1998) has found that species within genera trade-off in their relative ability to compete for limiting resources (zooplankton) and to avoid predators. This work illustrates how it allows certain groups of damselfly species to coexist within a single lake. However, the story gets more complicated, because different types of lakes have different types of predators: dragonflies or fish. Some species within the genera have avoidance strategies that are effective against dragonflies, but ineffective against fish, and other species have the opposite set of traits. Thus, these species coexist regionally by partitioning habitats with different types of top predators.

In a similar manner, Tilman and colleagues have discussed a variety of trade-offs in which herbaceous plant species trade-off in their ability to compete for nutrients and compete for light (Tilman 1982, 1988; Gleeson & Tilman 1990; Wedin & Tilman 1993), colonize new habitats (Tilman 1994), or their susceptibility to herbivores (Ritchie et al. 1998). Trade-offs in a meta-community with heterogeneous local communities may not necessarily require explicit dispersal among patches. These examples point to a potential explanation for high diversity: heterogeneity of local patches which results in different types of trade-offs required for coexistence among patches.

Regional-scale coexistence and trade-offs

When a system is spatially explicit, additional trade-offs can be incurred where space can also be partitioned (see reviews in Kareiva 1990; Tilman & Pacala 1993; Tilman & Kareiva 1997; Amarasekare 2003). Effectively, space increases the dimensionality of a community where interactions occur within local communities and differential dispersal or movement may occur among local communities (Fig. 1).

Competition–colonization

This trade-off holds that species differ in their ability to disperse to and colonize new habitats vs. their ability to compete once in a habitat; strong competitors are weaker colonizers (dispersers) and weak competitors are strong colonizers (dispersers; Hutchinson 1951; Skellam 1951; Levins & Culver 1971; Slatkin 1974; Armstrong 1976; Hastings 1980; Hanski 1983; Nee & May 1992; Tilman 1994; Kinzig et al. 1999; Yu & Wilson 2001; Chave et al. 2002; Levine & Rees 2002; Wang et al. 2002). Coexistence among the species then occurs at the regional scale. For species that show this trade-off, there must be a rate of extinction of the superior competitor species within patches that exceeds the rate of colonization and competitive exclusion of the inferior competitor. This allows the better colonizer to persist as a fugitive in those habitats where the superior competitor has recently gone extinct or not yet colonized. Although originally envisioned at a patch level, where entire populations of species have colonization and extinction probabilities (Levins & Culver 1971; Horn & MacArthur 1972), this trade-off has also been used to discuss coexistence at scales where patches consist of a single species, such as a sessile plant, that has a probability of establishing at a site and a probability of death at that site (Hastings 1980; Loreau & Mouquet 1999).

Dispersal ability is a difficult trait to measure as it occurs over large spatial and temporal scales. In theoretical studies, the better disperser arrives in empty patches by colonizing (1) more distant patches (Levins & Culver 1971; Holmes & Wilson 1998), or (2) new patches more quickly (Armstrong 1976; Tilman 1994). This may be achieved by occupying more patches in a region, producing numerous propagules, or having greater movement rates. The direct measurement of dispersal is for most organisms and systems a logistical nightmare. Consequently, empirical studies have used numerous surrogates for dispersal ability. Some have measured developmental and allocation strategies of individuals: early reproduction (Armstrong 1976), seed size and number (Turnbull et al. 1999), allocation to aboveground tissue in plants (Gleeson & Tilman 1990), and development rate (Sevenster & van Alphen 1993). Other studies measure dispersal directly or indirectly by clonal spread (Brewer et al. 1998), distance (Rabinowitz & Rapp 1981; Lei & Hanski 1998), regional distribution (Hanski & Ranta 1983; Yu et al. 2001), propagule number (Marino 1991a,b), or arrival time at a patch (Bengtsson 1991; Marshall et al. 2000; Miller & Kneitel in press). These measures have their own biases, and multiple measurements should be considered when determining a species’ colonization ability (Higgins & Cain 2002). In addition, colonization rates must be interpreted in the context of the temporal scale of competitive exclusion (Hanski 1983; Kneitel & Miller 2003) and the spatial movement of colonists (Higgins & Cain 2002).

Most studies do not find the competitive/dispersal ability trade-off, but instead find species’ differences in habitat use (Marino 1991a,b; Harrison et al. 1995; Turnbull et al. 1999; Amarasekare 2000; Marshall et al. 2000; Yu et al. 2001). These cases (along with those with similar conclusions at the local scale) point to the potential importance of spatial heterogeneity for species coexistence in many communities (Levine & Rees 2002); care must be taken to understand the scale at which organisms disperse and interact with their environment. Finally, as there are many systems in which species interact and coexist at different scales, empirical studies need to examine the potential for species trade-offs at different scales.

The interaction between local and regional trade-offs

Where environments are heterogeneous and patchy, species can exhibit trade-offs in their ability to utilize local habitats and to exploit patches regionally. In these cases, the interaction between local and regional trade-offs can complicate patterns of coexistence. For example, Mouquet & Loreau (2002, 2003) have discussed a theoretical framework where organisms differ in their ability to utilize different habitat types and also in their ability to disperse among habitats. In this model, when dispersal rates are low, each species persists only in the habitat type in which they are favoured; local diversity is low (one per patch type), but regional diversity is high (equal to the number of patch types). With intermediate rates of dispersal, however, local diversity increases, because species are able to persist as sink populations in patches where they are unfavoured if they have migration from source populations where they are favoured. Finally, at the highest rates of dispersal, species that are better at colonizing empty patches can dominate and drive other species extinct, even though those species could persist in the local habitat in the absence of spatial effects.

Variation among habitat patches in the presence or absence of top predators can also create a situation where local and regional trade-offs interact. Theoretically, the presence of a keystone predator can release the constraint that a competition–colonization trade-off is necessary for coexistence (Shurin & Allen 2001); also see Shurin (2001) for experimental results in support of this model with aquatic zooplankton. Similarly, an empirical study on protists that interact and coexist at different spatial scales in the water-filled leaves of pitcher-plants indicated that trade-offs at local and regional scales may both be exhibited, potentially allowing these organisms to coexist at both scales (Miller & Kneitel in press).

The scale at which coexistence occurs is more easily seen with certain trade-offs than others. Several types of trade-offs potentially allow coexistence at the local or regional scales. Although the colonization–extinction trade-off has been primarily discussed as a concept relevant to sessile organisms (e.g. trees), or organisms that live their entire lives within a patch, similar trade-offs have been discussed in the context of differential exploitation of patches by mobile organisms. Examples of these trade-offs include desert rodents, which have been classified as having a ‘cream-skimmer-crumb-picker’ trade-offs (Kotler & Brown 1988), and marine and freshwater snails, which have been classified to have a ‘digger-grazer’ trade-off (Wilson et al. 1999; Chase et al. 2001). In these examples, foragers trade-off the ability to find new patches (the cream-skimmer or grazer) with the ability to consume resources down to low levels once in a patch (the crumb-picker or digger), and qualitative patterns of coexistence are quite similar to that predicted from the colonization–extinction trade-off (similar trade-offs include milker–killer, van Ballen & Sabelis 1995; sitter–rover, Sokolowski 1980; gleaner–exploiter, Fredrickson & Stephanopoulos 1981).

A related trade-off occurs between species that differ in their ability to consume resources when resources are abundant vs. rare (Tilman & Pacala 1993; Tessier & Woodruff 2002). Thus, when resources are very abundant, as they would be in a previously unoccupied habitat or in recently created forest gaps awash with light, some species are superior competitors for this abundant resource (Pacala & Rees 1998; Bolker & Pacala 1999). These species have a set of traits that allow them to exploit very abundant resources, such as steep functional responses. Other species, however, are more efficient at consuming resources when they are rare, and exhibit traits such as low metabolism and resource extraction efficiency. In such cases, the former species can occupy and outcompete the latter species early, but not late, in the successional process. Likewise, they can only coexist regionally because of variation in the abundance of resources and the time since colonization (Whittaker & Levin 1977). In many ways, this trade-off is mechanistically similar to the competition–colonization trade-off and even the predictions of r-K selection strategies (MacArthur & Wilson 1967; Pianka 1970). Finally, this sort of trade-off can allow two species to coexist on a single resource when their consumption of that resource causes it to cycle between high and low abundances (Armstrong & McGehee 1980; Huisman & Weissing 1999; Abrams & Holt 2002).

Trade-offs and patterns of diversity

The interaction between local and regional scale trade-offs are also reflected by a characteristic pattern of alpha (local) and beta (compositional turnover) diversity (Table 1; see also Mouquet & Loreau 2002, 2003). When trade-offs are primarily at the local scale, alpha diversity should be relatively high, because these trade-offs often promote local coexistence. Beta diversity, however, is expected to be low because there should be little turnover in species composition because coexistence is primarily at the local scale. Alternatively, when trade-offs are primarily at the regional scale, alpha diversity should be relatively low, as only the good competitors or good dispersers inhabit each locality. However, beta diversity should be relatively higher because there is turnover in species composition across patches that result from species differences in dispersal rates (homogeneous patches) or specialization (heterogeneous patches; Table 1). High beta diversity could also be produced if environmental conditions vary among different patches and different species are favoured under different environments. Finally, a combination of trade-offs at local and regional scales will produce coexistence at the local community scale (high alpha diversity) along with high turnover among patches (high beta diversity; Table 1).

Table 1.  Expected patterns of diversity resulting from the trade-offs that lead to coexistence. See text for specific information on trade-offs at different scales
Coexistence scaleTrade-offExpected pattern of diversity
αβγ
LocalResources, predator invulnerability, abiotic factorsHighLow
RegionalHomogeneous or heterogeneous local communitiesLowHigh
 Mixture (local and regional)HighHigh

A similar argument presented by Frank & Amarasekare (1998) predicted that an increase in dimensionality (number of resources available for specialization) would alter the types of traits that were expected, the scale at which dynamics were important, and the resulting pattern of diversity. As dimensionality increased, control of community dynamics was predicted to shift from local (competition) to regional (specialization and dispersal) processes. Furthermore, the patterns in diversity were predicted to shift from high local diversity to low local diversity with an increase in regional diversity because of specialization (trade-offs among patches; Frank & Amarasekare 1998). Thus, linking species traits with emergent coexistence patterns should be reflected in the diversity patterns at different spatial scales. These patterns merit further empirical and theoretical exploration.

Species can coexist at the local and regional scale by specializing on a specific habitat (Futuyma & Moreno 1988). Specialists, by definition, have highest fitness in a particular habitat and the trade-off is then exhibited across habitat types, whereas generalists do not exhibit trade-offs across habitat types (McPeek 1996; Caley & Munday 2003). However, within any given community type, trade-offs are required between the specialist and generalist for coexistence (Fig. 2). The expected composition of communities should then include coexistence of a habitat specialist and generalist whose identity can differ depending on the type of community (presence of different predators, resources, etc.; McPeek 1996). Therefore, coexistence at the local scale will occur between habitat generalists and specialists, while regional scale coexistence will occur between different habitat specialists and possibly generalists (Fig. 2).

Figure 2.

Species A–C ranked in their performances in two patch types. Species A and C are habitat specialists in having high fitness in a respective patch or trait, but poor performance of the other patch or trait. By comparison, species B is a generalist of both patches or traits.

Dispersal rates among patches can also play an important role in affecting patterns of alpha, beta and gamma (regional) diversity, interacting with local and regional trade-offs (Loreau 2000; Kneitel & Miller 2003). For example, increasing connectedness among patches may decrease beta diversity and increase alpha diversity in certain situations (Loreau & Mouquet 1999; Mouquet & Loreau 2002, 2003); dispersal rates essentially shift the relative importance of local and regional scale trade-offs. However, the neutral theory (e.g. Hubbell 2001), which assumes no local or regional trade-offs, can predict similar patterns under varying rates of dispersal. Therefore, diversity variation cannot be used to determine the specific mechanisms of trade-offs that create patterns of coexistence in the absence of other information.

Evolution of trade-offs

The evolution of ecological traits in a community context has had a long and contentious history in ecology (e.g. Strong et al. 1984). In recent years, the evolution of trade-offs has been specifically addressed both theoretically and empirically (Futuyma & Moreno 1988; Bohannan & Lenski 2000a,b; Bohannan et al. 2002). Furthermore, understanding this in the context of community dynamics is one of the most difficult, but important challenges for community ecology (Bohannan & Lenski 2000a,b; Thompson et al. 2001; Bohannan et al. 2002; Tessier & Woodruff 2002).

Evidence for the evolution of trade-offs has come from a variety of studies in experimental microcosms. For example, there is good evidence for the evolution of the competitive ability-predator invulnerability trade-off in simple artificial communities using different genotypes of bacteria (Shikano et al. 1990; Nakajima & Kurihara 1994; Bohannan & Lenski 1999, 2000a,b), algae (Yoshida et al. 2003), and Drosophila melanogaster (Kraaijeveld & Godfray 1998). Mutations that lead to ‘predator’ resistance in these studies have come at the cost of their efficient use of resources. In addition, the bacterial studies have shown complex interactions and feedback between these traits and community dynamics.

Rainey and colleagues’ (Rainey & Travisano 1998; Buckling et al. 2000; Kassen et al. 2000) studies on the bacteria Pseudomonas spp. have shown that in a spatially heterogeneous environment, different morphologies emerge that allow them to utilize different parts of the environment better. Although there is no specific evidence for trade-offs leading to these different morphologies, the indirect evidence is quite compelling; for example, the number of morphologies that emerge depend on the level of resources in the habitat (Kassen et al. 2000) and the degree of heterogeneity (Rainey & Travisano 1998; Buckling et al. 2000).

Another approach to the evolution of trade-offs in communities stems from a historical perspective (Ricklefs 1987; Webb et al. 2002; Losos et al. 2003). Advances in phylogenetic analyses have facilitated these new approaches to understanding patterns of diversity in communities (Losos 1996; McPeek & Brown 2000; Webb et al. 2002). One recent example, Silvertown et al. (1999) found trade-offs among plant species along moisture gradients in meadow communities. To better understand the nature of these trade-offs in structuring this community, Silvertown et al. (2001) calculated niche overlap among all 64 species and compared the pattern of overlap at different taxonomic levels to determine where niche differentiation occurred. Understanding contemporary trait differences of coexisting species within this larger phylogenetic framework will certainly contribute to a broader understanding of the role of evolution in niche differentiation in structuring communities (Webb et al. 2002; Losos et al. 2003).

The study of the evolution of trade-offs could be advanced along two fronts. First, simple systems can be further explored while increasing the complexity in community structure (Bohannan et al. 2002). This would most easily be performed in microcosm experiments where the interplay between species traits and community dynamics could be easily followed. Adding more competing species into these communities that are less related or different types of predators may expand our understanding of the emergence and maintenance of trade-offs. Secondly, the evolution of trade-offs needs to be explored further in natural communities that include different species. Much of the work in this field has been conducted on different genotypes of a species. Comparative approaches can also be used to examine differences in selection regimes in guilds of coexisting species.

Conclusions

Trade-offs among ecological traits at some spatial scale are a prerequisite for species coexistence in the majority of community ecology theories. In many ways, we are revisiting old questions when it comes to thinking about the trade-offs in community ecology as it relates to ecological niches (Chase & Leibold 2003, and Fig. 2). Our current understanding of communities has, in recent years, integrated processes at different spatial scales (e.g. Ricklefs & Schluter 1993; Tilman & Kareiva 1997). Further, alternative trade-off predictions have recently been proposed for empirically testing mechanisms of coexistence in a spatial community (Amarasekare 2003). We have argued that this momentum should also extend to linking species traits to diversity patterns by examining the trade-offs that lead to coexistence at local (e.g. Tilman 1982; Leibold 1996) and regional scales (e.g. Levins & Culver 1971; Slatkin 1974; Tilman 1994).

Hubbell (2001) has challenged the view that niche differences are important for understanding broad patterns of species diversity and relative abundance (see also Bell 2001). Although quite contentious (Abrams 2001; Enquist et al. 2002; Whitfield 2002; Norris 2003), Hubbell's neutral model has achieved some success in a variety of systems (Hubbell 1979; Hubbell et al. 1999; Bell 2001; Hubbell 2001; Volkov et al. 2003), but less success in other systems (Condit et al. 2002; McGill 2003; Tuomisto et al. 2003). One of the primary motivations for Hubbell's neutral model was because of the perception that there is too much diversity in many natural systems (particularly tropical forests) to be explained by traditional equilibrial models of niche differences and trade-offs.

In an attempt to reconcile niche and neutral theories, Hubbell (2001) proposed that trade-offs among species could be the very mechanism that leads to fitness equality under neutral dynamics. This is because life-history trade-offs (e.g. growth vs. survival) act to make all organisms fitness’ approximately the same in a given environment. However, for long-term coexistence, two processes are required: equalizing and stabilizing effects (Chesson 2000). Hubbell is right that life-history trade-offs, which are characteristic of niche models, can lead to equalizing effects. However, the types of trade-offs that we have discussed here and the differences in the scale at which they are manifested, lead to stabilizing effects (e.g. density and frequency dependence). These stabilizing effects allow species to coexist in the long term, whereas all but one species will eventually go on a random walk to extinction if just equalizing effects are present (Chesson 2000).

In contrast to Hubbell's neutral theory, we argue that species traits are meaningful relative to its environmental context, and that these differences along with habitat heterogeneity can explain patterns of diversity; the evidence for habitat segregation and changes in relative abundance among species are clear in numerous systems (e.g. Kotler & Brown 1988; Wellborn et al. 1996; McPeek 1998). When trade-offs are considered in an explicitly spatial context (both local and regional trade-offs as well as their interactions), many more species can coexist locally and regionally than predicted from the classical niche theory that was based on local species interactions (e.g. Gause 1934; Levin 1970). Furthermore, recent analyses based on trade-offs, including colonization–competition dynamics (Chave et al. 2002) and source-sink interactions (Mouquet & Loreau 2003), as well more generalized models of species interactions (Wilson et al. 2003), can provide predictions nearly indistinguishable from those predicted by the neutral theory. Placing these theoretical predictions into a spatial framework will provide insight into the scale or scales of coexistence, as well as to compare among the various mechanisms that create and maintain species diversity and composition in communities.

Acknowledgements

We thank M. Holyoak, N. Mouquet and two anonymous reviewers for comments, and M. Leibold, T. Knight and T. Miller for discussions that helped us to clarify our ideas of trade-offs at different spatial scales. J. M. K. was supported by a Tyson Research Center Postdoctoral Fellowship from Washington University, and J. M. C. was supported in part by NSF (DEB 0108118).

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