Bibliographic record
Abstract
But should an animal kindly render a service to his neighbor, whether keeping his set of teeth in order or in removing the detritus which encumbers certain organs, we cannot say that it is a parasite. … There are also mutual services rendered among several species, services performed by reciprocal kindness, and mutualism can even take its place by the side of commensalism. Two decades later, Roscoe Pound (1893) cited Van Beneden in the first literature review devoted to “symbiosis and mutualism” (Boucher et al., 1982). In spite of these early considerations of mutualism as a major force in evolutionary ecology (e.g., Darwin, 1872; Kropotkin, 1902), a formal theory of mutualism did not emerge until after the Modern Synthesis (Trivers, 1971; Soberon and Martinez del Rio, 1981; Axelrod and Hamilton, 1981; reviewed by Boucher et al., 1982 and Bronstein, 1994). Empirical demonstrations of key evolutionary dynamics in specialized mutualistic interactions—specifically, mechanisms by which mutualists prevent exploitation by noncooperating partners—appeared still more recently (Pellmyr and Huth, 1994; Kiers et al., 2003; Bever et al., 2009; Goto et al., 2010; Jandér and Herre, 2010), and understanding the historical and ecological contexts in which mutualism can evolve is an area of ongoing research (e.g., Pellmyr and Thompson, 1992; Pellmyr and Leebens-Mack, 1999; Marchetti et al., 2010; Yoder et al., 2010; Sachs et al., 2011; reviewed by Bronstein, 2015). Starting with the earliest writings on the subject, botanical research has made key contributions to advances in understanding the ecology and evolution of mutualisms. Pound's inaugural review of mutualism research was first presented to the Botanical Seminar of the University of Nebraska, and the examples he describes all involve plants: the fungus–algae symbiosis of lichens, mycorrhizal mutualists of trees and orchids, nitrogen-fixing rhizobial bacteria hosted in the roots of clover, and the pollination of plants in the genus Yucca by specialized seed-feeding moths (Pound, 1893). Although mutualistic interactions between animal species are among the textbook examples—Van Beneden (1874) cited plovers that clean the teeth of crocodiles, among others—a large portion of research on mutualisms has always focused on interactions involving plants (Bronstein, 1994). This focus on plants probably reflects the fact that interactions are that much more tractable for study if one partner is rooted in place for field experiments or easily propagated in the greenhouse, but it is also likely the result of plants’ foundational trophic role as primary producers. Even during decades when relatively few ecologists or evolutionary biologists explicitly studied mutualism, many contributed to basic research on mutualistic interactions as they reported the natural history of plants’ pollination, seed dispersal, and other interactions with animals (Bronstein, 1994). Whatever the reason, much research on mutualistic interactions involves plants and their mutualist partners. The papers collected in this Special Section of the American Journal of Botany grew from a colloquium on the ecology, genetics, and coevolution of intimate mutualisms, held at the Botany 2015 meetings in Edmonton, Alberta, Canada. The work presented at the colloquium, and now in these pages, delves into an array of specialized plant-hosted mutualisms, including some of those reviewed by Pound well over a century ago. These papers reveal how research on mutually beneficial species interactions is, like all of evolutionary biology, being reshaped by the ongoing revolution in sequencing and computational approaches, and demonstrate the importance of historical and ecological context in shaping present outcomes for hosts and their mutualistic symbionts. Together, they show how our understanding of the ecological and evolutionary dynamics of intimate mutualisms has changed since Van Beneden first identified “reciprocal kindness” as an important feature of the natural world. With a few notable exceptions, the species involved in “classic” mutualisms are not typical “model organisms”. That is, they have lacked the genomic resources and functional genomic technologies available for Arabidopsis thaliana (L.) Heynh., Drosophila melanogaster Meigen, and Homo sapiens L. Rapidly evolving high-throughput DNA sequencing methods are now dramatically reducing the cost of developing these resources, even for species with larger and more complex genomes (see Glenn, 2011; Weigel and Nordborg, 2015). The first benefit of new sequencing technologies has been to resolve long-standing questions of evolutionary history. As a prime example, McKain et al. (2016) report a new, high-confidence resolution of intergeneric relationships within the Agavoideae (Asparagaceae), using new chloroplast genome assemblies for 20 species. The resolved topology and inferred divergence times lend further support for the hypothesis that active, obligate pollination by yucca moths evolved independently in the ancestors of genera Yucca and Hesperoyucca. These genera last shared a common ancestor 18–34 million years ago, McKain et al. (2016) estimate, a period that overlaps with prior estimates for the origin of active pollination by yucca moths (Pellmyr and Leebens-Mack, 1999). If the common ancestor of Yucca and Hesperoyucca was pollinated by yucca moths, however, the topology implies three independent losses of the association. This hypothesis is rejected in favor of the inference that yucca moth pollination was independently derived in the ancestors of these two host genera (McKain et al., 2016). A second example of the utility of genomic analyses for investigating the evolutionary ecology of mutualisms is presented by Royer et al. (2016), who use a rigorous “genomic scan” approach to identify single-nucleotide polymorphisms associated with variation in floral style length in two parapatric species of Joshua tree, Yucca brevifolia Engelm. and Y. jaegeriana (McKelvey) Lenz, associated with different yucca moth species. This work reveals that style-length-associated SNPs are overrepresented in genome regions exhibiting elevated differentiation between the two species. The RAD-seq data collected by Royer et al. (2016) is the first application of population genomic methods in the context of an obligate pollination mutualism, and it provides new evidence to support the hypothesis that the two Joshua tree species are isolated by contrasting selection exerted by different pollinator species (Godsoe et al., 2008; Smith et al., 2009; Yoder et al., 2013). Finally, Yoder (2016) describes how population genomic data made available by high-throughput sequencing can be applied not only to identify candidate loci for key mutualist traits, but also to understand the history of natural selection that has acted on those loci. This approach, Yoder proposes, may be the most tractable for understanding the selective dynamics that stabilize many intimate mutualisms against invasion by noncooperating “cheaters”, particularly in interactions with long-lived hosts or hard-to-manipulate symbionts. Another promising frontier in the study of mutualism has been opened by research that places mutualism in context among other ecological and evolutionary processes, both to identify the unique outcomes of mutually beneficial interactions and to understand how they are changed by historical and environmental circumstances. This line of inquiry has its roots in the geographic mosaic theory of coevolution (Thompson, 1988, 1999, 2005), which has emphasized that temporal and geographic variation in the outcomes of coevolutionary interactions are determined not by the interaction itself, but by the habitat and biological community in which it occurs (Thompson and Pellmyr, 1992; Nuismer et al., 1999, 2003). Many of the papers in this Special Section directly address the broader contexts of mutualism. One important context is the cost of resources offered to mutualists, and, reciprocally, the value of resources provided by them. As with many other host–symbiont interactions, fig trees sanction pollinating fig wasps that fail to provide pollen by selectively aborting unpollinated figs and reducing wasp offspring survival in retained figs (Jandér and Herre, 2010). Here, Jandér and Herre (2016) report new results from an experiment with quantitatively varying pollen provision to show that reduced wasp survival in under-pollinated figs is likely due to reduced resource allocation to those figs. If this is indeed the case, it is conceivable that mutualism outcomes—the strictness of fig tree sanctioning—could be shaped as much by resource availability as by the quality of wasp-provided pollination services. A similar line of research found that legumes may alter their response to rhizobia when provided with sufficient free nitrogen (Heath and Tiffin, 2007; Heath et al., 2010). However, Grillo et al. (2016) reported an experiment in which nitrogen supplementation does not alter the specificity of the model legume Medicago truncatula for symbiosis with particular strains of rhizobia. This result is not alone in suggesting that there are elements of mutualists’ interaction with each other that remain independent of the realized cost or benefit of mutualism (e.g., Regus et al., 2014). The genomic architecture of traits influencing species interactions is another important consideration in studies of possibly coevolving mutualists. Powell and Doyle (2016) test the symbiotic compatibility of allopolyploid Glycine dolichocarpa Tateishi & H.Ohashi with a set of novel strains of nitrogen-fixing rhizobial bacteria. Relative to its diploid parents, G. tomentella Hayata and G. syndetika B.E.Pfeil & Craven, G. dolichocarpa showed root-hair deformation responses (an early stage of symbiosis initiation) after inoculation with a wider range of rhizobia, and greater biomass gains from the addition of nitrogen fertilizer, both factors that the authors suggest could facilitate the allopolyploid's success in colonizing new habitats (Powell and Doyle, 2016). Understanding how whole-genome duplication and other major genomic rearrangements can alter both host–symbiont signaling and broader metabolic processes that determine mutualism success is a major goal for future genomic analysis in this and other mutualisms (Young et al., 2011; Cannon et al., 2015). It may also be that traits playing a central role in mutualistic interactions are under selection for functions other than mutualism or are pleiotropic with traits under such selection. Some models of mutualism stability propose that symbiont exploitation is prevented not by active sanctioning, but by host responses to resource limitations that predate the origin of the mutualism (“partner fidelity feedback”; Weyl et al., 2010; Archetti et al., 2011). Such preexisting host resource allocation strategies could be an alternative explanation for resource-limitation as a “sanction” against cheating fig wasps Jandér and Herre's (2016), if fig trees simply invest less in fruits that are less likely to produce quality seed, whether because of insufficient pollination or other reasons. Intriguingly, in addition to finding evidence for divergent selection on loci associated with floral trait variation, Royer et al. (2016) found that loci associated with vegetative traits are candidates for divergent selection between the two species of Joshua tree, and that dozens of divergent selection candidates are associated with both floral and vegetative traits. These results may hint at epistatic interactions between genes influencing vegetative traits shaped by abiotic selection pressures, and floral traits relating to pollinator success (Smith et al., 2009). Such interactions could either constrain or amplify responses to diversifying coevolutionary selection. Hembry and Althoff (2016) examined the literature on the possible relationship between coevolution in brood pollination mutualisms—interactions in which pollinators lay eggs in fertilized flowers, which serve as a larval food source— and speciation. Studies of highly specialized interactions such as yucca or fig pollination should provide the best available test of the hypothesis that mutualistic interactions can drive divergence and reproductive isolation. However, Hembry and Althoff (2016) found little evidence that coevolution between mutualists has caused speciation in these systems. Rather, geographic isolation and host-switching by pollinators have been identified as drivers of diversification in multiple brood pollination mutualism systems, including the leafflower–Epicephala interaction (Hembry et al., 2013), figs and fig wasps (e.g., Moe and Weiblen, 2010; Chen et al., 2012; Yang et al., 2015), and even yuccas and yucca moths (Althoff et al., 2012). Hembry and Althoff (2016) concluded that phylogenetic associations between specialized mutualism and increased diversification (Sargent, 2004) may be due to interaction of mutualism with other evolutionary forces to strengthen otherwise transient reproductive barriers. Mutualism studies are also elucidating how outcomes of interactions are determined by more than the resources or services exchanged. Mutualists also communicate via signals that may or may not reflect their performance in partnership. Signaling factors produced by rhizobia and recognized by legumes have long been a focus of study in this system (Triplett and Sadowsky, 1992); but we also know that volatiles produced by host plants play an important signaling role in brood pollination (Svensson et al., 2005, 2016; Soler et al., 2011) and ant–plant protection mutualisms (Edwards et al., 2007) among others. In the yucca–yucca moth brood pollination interaction, a key signal is floral scent, which may be species-specific (Svensson et al., 2005). The floral scent of the two Joshua tree species contains compounds not isolated from other yuccas, and the cocktail of volatiles produced by Yucca brevifolia is distinct from that of Yucca jaegeriana (Svensson et al., 2016). Hybrids between the two species, identified using genetic and morphological data, have ambiguous scent profiles, which may explain why pollinators visit both species in a narrow contact zone between their parapatric ranges — floral morphology or post-pollination survival of pollinator moth larvae are more likely to maintain pollinator specificity in this case (Smith et al., 2009; Svensson et al., 2016). Similarly, the yucca moth Tegeticula yuccasella Riley visits and pollinates Yucca species on which it is unable to complete larval development (Althoff, 2016). This latter result points to another layer of processes that determine outcomes in intimate mutualism: in addition to signaling hosts and providing resources or services, symbiotic mutualists coevolve with host systems that defend against herbivores and other antagonists, which may not discriminate between seed-feeding by a pollinator's offspring and attack by an outright parasite. Both Grillo et al. (2016) and Powell and Doyle (2016) discuss findings from investigations of legume–rhizobium interactions that are consistent with a model in which signals between the host and symbiont shape the outcomes before the exchange of resources. Allopolyploid Glycine has stronger root hair deformation responses to novel rhizobia strains than do its two parental species and forms nodules with strains that do not elicit nodulation from one or both parents, both expected results of novel receptor allele combinations made possible in the polyploid (Powell and Doyle, 2016). Meanwhile, three lines of Medicago truncatula Gaertn. did not change in their specificity for particular strains of rhizobia across different levels of soil nitrogen (Grillo et al., 2016), consistent with host recognition of symbiont signals that operates independently of a host's need for the resource provided by the symbiont. Indeed, in the analysis of genome-wide genetic variation in M. truncatula, genes with putative symbiotic function showed signs of varying forms of selection: some are consistent with coevolution of host–symbiont signaling, while some fit expectations from coevolution of symbiont cooperation and host sanctions (Yoder, 2016). Our understanding of mutualism has become considerably more complex than the earliest descriptions of “mutual aid” among living things—we now see most interactions as transactions between self-interested individuals, with numerous conditions and clauses to be fulfilled for the final “deal” to be mutually beneficial (Axelrod and Hamilton, 1981; Bronstein, 1994; Sachs et al., 2004; Heath and Stinchcombe, 2014; Jones et al., 2015). The total picture of processes involved in an interaction that is, over many individual encounters, beneficial for members of two separate species offers many approaches for future research (Fig. 1). Interacting mutualists must exchange and respond to compatible signals, have access to resources to offer a possible partner, and then must offer those resources or services. Even then, the interaction is only successful as a mutualism if rewards provide benefit to both partners. It is appropriate (and probably not a coincidence) that this more complex, nuanced picture has emerged as we develop new approaches to gain mechanistic understanding of the ecological dynamics that drive evolution within intimate mutualisms. The work presented in this collection clearly illustrates that investigations of plants (e.g., figs, yuccas, legumes, and many others) and their interaction partners will continue to play an important role in elucidating the evolutionary ecology of species interactions more generally. Processes shaping the evolutionary trajectory of an intimate mutualism. A mutualistic interaction is initiated through the exchange of host and symbiont signals that determine whether individuals will interact. If interaction is initiated, individuals exchange resources (or services). At this stage, symbionts may or may not prove cooperative, hosts may or may not sanction symbionts, and the reward provided by hosts may or may not be accessible to the symbiont. Host and symbiont environments contribute to these dynamics and ultimately to the ecological (i.e., fitness) impact for each partner. Together, host and symbiont benefits determine the strength or weakness of the mutualism—the degree to which the interaction is beneficial for both species. The authors thank the Botanical Society of America and the Editor in Chief of the American Journal of Botany for inviting us to organize the colloquium on intimate mutualisms, and this Special Section, and we are grateful for the contributions of the participating authors. Pamela Diggle and Amy McPherson provided invaluable support in the editorial process, and many anonymous reviewers contributed time and expertise to improve every contribution. J.Y. is a postdoctoral fellow with the AdapTree Project, supported by the Genome Canada Large Scale Applied Research Project program with co-funding from Genome BC and the Forest Genetics Council of BC (S. N. Aitken and A. Hamann, co-Project Leaders). Finally, we dedicate this Special Section of papers to Olle Pellmyr, who introduced both of us to the study of mutualisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".