Abstract
Community ecology is traditionally species-based and assumes that species comprise identical individuals. However, intraspecific variation is ubiquitous in nature because of ontogenetic growth and critical in food-we dynamics. To understand individual interaction-mediated food webs, researchers have recently focused on body size as the most fundamental biological aspect and assessed a parameter called the predator–prey mass ratio (PPMR). Herein, I review the conceptual development of the PPMR and suggest four major concerns regarding its measurement: (1) PPMR should be measured at the individual level because species-averaged values distort actual feeding relationships, (2) individual-level PPMR data on gape-unconstrained predators (e.g., terrestrial carnivores) are limited because previous studies have targeted gape-limited fish predators, (3) predators’ prey size selectivity (preferred PPRM) is conceptually different from dietary prey size (realized PPMR) and should be distinguished by incorporating environmental prey abundance information, and (4) determinants of preferred PPMR, rather than those of realized PPMR, should be identified to describe size-dependent predation. Future studies are encouraged to explore not only predation but also other interaction types (e.g., competition, mutualism, and herbivory) at the individual level. However, this is not likely to occur while ecological communities are still considered to be interspecific interaction networks. To resolve this situation and more comprehensively understand biodiversity and ecosystem functioning, I suggest that community ecology requires a paradigm shift in the unit of interaction from species to individuals, similar to evolutionary biology, which revolutionized the unit of selection, because interactions occur between individuals.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Ecology, particularly community ecology, has traditionally been species-based. That is, researchers classify organisms according to species-specific representative traits, measure interaction strengths among species, and enumerate coexisting species or quantify their functional diversity (Begon et al. 2006; Verhoef and Morin 2010). An implicit assumption in this approach is that species comprise identical individuals with invariant traits or that trait variations within species are virtually negligible compared with those between species. However, intraspecific trait variations are common in nature and sometimes substantially exceed interspecific variations. This suggests that our current understanding of biodiversity and ecosystem functioning based on species-level community ecology is fundamentally flawed or at least incomplete (Bolnick et al. 2011; Violle et al. 2012; Hart et al. 2016).
To address this issue, some ecologists have recently emphasized body size as the most fundamental functional trait of an organism. The reason for this is two-fold. First, many organisms are multicellular and exhibit ontogenetic growth, indicating that intraspecific size variation is ubiquitous. Second, and more importantly, body size is associated with other biological aspects, such as morphology, physiology, and behavior (LaBarbera 1989; Brown et al. 2004). Therefore, body size largely determines demographic performances (e.g., birth, death, and mobility) and ecological niches (e.g., diet and habitat) as well as interactions with other organisms (e.g., predation, competition, and mutualism) (Wilbur 1980; Werner and Gilliam 1984). Currently, there is a growing interest in how the ontogenetic growth of organisms mediates community structure and dynamics (Hildrew et al. 2007; Miller and Rudolf 2011; de Roos and Persson 2013; Nakazawa 2014, 2015a).
Herein, I review recent progress and problems regarding this ontogenetic perspective in community ecology. More specifically, I focus on a key parameter in this research field, the predator–prey mass ratio (PPMR). The PPMR measures the body mass ratio of interacting predators and prey. Body size can be linked with interaction strength, which allows us to describe food webs mediated by size-dependent predation (Brose 2010; Nakazawa et al. 2011). In this review, body size represents individual size, including the concept of age or developmental stage, rather than species-specific representative body size, because this review concerns the community consequences of ontogenetic growth. The main problem with the PPMR is that very few studies have appropriately quantified it. Thus, reliable theoretical predictions accompanied by empirically supported assumptions are not available for any food web patterns. The objective of this review is to address this problem by introducing recent empirical measurements of PPMR and stimulating further research efforts toward its solution.
Ontogenetic niche shift matters in community ecology
First, before beginning the review of PPMR studies, I remark that ontogenetic niche shifts critically affect community dynamics (see Miller and Rudolf 2011; de Roos and Persson 2013; Nakazawa 2014, 2015a for more details). Studies have predicted that an ontogenetic shift of a predator species between the juvenile and adult stages can generate alternative community states, thereby reducing community resilience and causing regime shifts under environmental changes (Schreiber and Rudolf 2008; Guill 2009; Nakazawa 2011a, b). The mechanism involves positive feedback caused by the apparent competition-like interactions between the resources of the juveniles and adults. Suppose that the resource of juveniles increases. This promotes maturation of the juveniles and negatively affects the resource of the adults, which in turn leads to a decrease in reproduction and a further increase in the resource of the juvenile. Thus, a positive feedback loop is created (see Schreiber and Rudolf 2008; Guill 2009; Nakazawa 2011a, b for details). This represents the simplest possible scenario (i.e., trophic module) for a stage-structured community. However, the concept applies to various community contexts, such as aquatic food webs, in which ontogenetic diet shifts of predatory fish from planktivore to benthivore couple energy flows in the surface and bottom waters (Nakazawa et al. 2010, Briones et al. 2012), plant–insect interactions, in which stage structures entangle herbivory and pollination networks (Altermatt and Pearse 2011; Ke and Nakazawa, unpublished data), and interface areas, in which metamorphosis of amphibians or aquatic insects connect aquatic and terrestrial ecosystems (Baxter et al. 2005; Nakazawa 2015b).
However, little is known about the community consequences of ontogenetic niche shifts because previous community models have used the simple assumption that only a single species undergoes an ontogenetic niche shift only once at the timing of maturation (Schreiber and Rudolf 2008; Guill 2009; Nakazawa 2011a, b). However, the reality is more complex. Nearly all species, including plants (Barton and Koricheva 2010; Boege et al. 2011), exhibit ontogenetic niche shifts. Furthermore, ontogenetic niche shifts may occur more than once or continuously in an organism’s lifespan, irrespective of maturation, due to increasing body mass (e.g., Nakazawa et al. 2010, Briones et al. 2012). In such situations, an ecological community can be considered a network of interactions among individuals rather than of species because each interspecific interaction is redefined as a network of individuals at different ontogenetic stages (Fig. 1). This community view is in sharp contrast to the conventional view that species comprise identical individuals. How can we describe such a complex system (i.e., individual interaction-mediated food web) and understand its dynamics or environmental responses?
Predator–prey mass ratio as a tool for describing size-based food webs
A promising approach for describing individual interaction-mediated food webs is to analyze the PPMR in a focal system (Brose 2010; Nakazawa et al. 2011). This idea is reasonable because a predator cannot efficiently utilize excessively large prey because of physical constraints on feeding (e.g., gape limitation) and because a predator should not target excessively small prey because of their limited nutritional values (Brose 2010). In brief, interaction strength will be maximized at a moderate PPMR (Fig. 2). Based on this expectation, numerous studies have examined the predator–prey size relationship (Cohen et al. 1993, 2005; Brose et al. 2005, 2006a; Woodward and Warren 2007; Barnes et al. 2008, 2010; Owen-Smith and Mills 2008; Scharf et al. 2010; de Visser et al. 2011; Naisbit et al. 2011; Nakazawa et al. 2011; Riede et al. 2011; Lurgi et al. 2012; Reum and Hunsicker 2012; Klecka and Boukal 2013; Nakazawa et al. 2013; Tsai et al. 2016) and applied the PPMR to food web models (Andersen and Beyer 2006; Brose et al. 2006b; Otto et al. 2007; Blanchard et al. 2009, 2011; Hartvig et al. 2011; Thierry et al. 2011; Zhang et al. 2013; Guiet et al. 2016).
Nevertheless, according to my review of relevant literature, very few studies have appropriately quantified the PPMR or tested its fundamental assumptions. To illustrate this point, I present four practical considerations that must be addressed in empirical measurements of the PPMR: (1) definition dependence, (2) gape-unconstrained predation, (3) prey size preference, and (4) variability determinants.
Definition dependence of the predator–prey mass ratio
First, it is important to recognize that the PPMR can be defined at various biological scales depending on the manner in which the predator and prey body masses are measured (Nakazawa et al. 2011). Ideally, the PPMR should be measured using the individual body masses of the predator and prey as follows:
This is called the individual-link PPMR and it is typically obtained using gut content analysis that can provide body size information for both predators and prey (Barnes et al. 2008, 2010; Scharf et al. 2010; Nakazawa et al. 2011; Reum and Hunsicker 2012; Tsai et al. 2016).
However, individual-link PPMR data are very limited because most previous studies have evaluated the PPMR at the scale of predator–prey species pairs using species-averaged body masses (Cohen et al. 1993; Brose et al. 2005, 2006a; Owen-Smith and Mills 2008; de Visser et al. 2011; Lurgi et al. 2012). This is called the species-averaged PPMR:
This PPMR definition only requires descriptive information about species-based food web topology and independent information on species-averaged body masses. In brief, the species-averaged PPMR does not require time-consuming gut content analysis. Mathematically, these different definitions yield different values (Fig. 3). Previous studies have reported that the individual-link PPMR is larger than the species-averaged PPMR by approximately one order of magnitude in freshwater invertebrates (Woodward and Warren 2007) and marine fish predators (Nakazawa et al. 2011). However, this is not always the case (see Fig. 3 for an example of the opposite case). Nakazawa et al. (2013) reported that individual-link and species-averaged PPMRs were comparable for aquatic hemipteran bugs. Theoretically, whether species averaging underestimates or overestimates the PPMR depends on the elements of the data used, such as body masses and sample numbers of predator and prey individuals and species (Nakazawa et al. 2011). Although other definitions are also possible (not shown), the individual-link PPMR is considered to represent the most realistic definition (see Nakazawa et al. 2011 for details).
The definition problem raises another concern: what determines PPMR? In contrast to the original theoretical assumption, PPMRs may not be identical among predators. The individual-link PPMR typically varies with individual predator size (i.e., ontogenetic changes in PPMR) (Barnes et al. 2010; Nakazawa et al. 2011, 2013; Reum and Hunsicker 2012; Tsai et al. 2016). By contrast, species-averaged PPMR tends to be size-invariant (Nakazawa et al. 2011, 2013) but varies according to other factors, such as ecosystem type (e.g., aquatic versus terrestrial), taxonomic identity (e.g., vertebrate versus invertebrate), trophic level, and climatic conditions (Brose et al. 2006a; Naisbit et al. 2011; Riede et al. 2011; Lurgi et al. 2012). These patterns imply that species averaging masks the size-dependent variability of the PPMR, thereby generating a misleading picture of actual feeding relationships (Fig. 3; also see Nakazawa et al. 2011, 2013). Overall, the PPMR should ideally be measured at the individual level (Woodward and Warren 2007; Nakazawa et al. 2011, 2013) and great caution should be exercised when using species-averaged PPMR to parameterize food web models (Andersen and Beyer 2006; Brose et al. 2006b; Otto et al. 2007; Blanchard et al. 2009, 2011; Hartvig et al. 2011; Thierry et al. 2011; Zhang et al. 2013; Guiet et al. 2016).
Predator–prey mass ratio of gape-unconstrained predators
The available data sets on individual-link PPMR are highly biased toward aquatic predators such as fish (Barnes et al. 2008, 2010; Scharf et al. 2010; Nakazawa et al. 2011; Reum and Hunsicker 2012; Tsai et al. 2016). This is because fish predators are typically gape-limited and swallow smaller prey whole; thus, gut content analysis can be used to estimate the individual body masses of prey in predator guts. However, this is not feasible for gape-unconstrained predators (e.g., terrestrial carnivores) because they often attack relatively large prey by using hunting tools (e.g., fangs and claws), and prey body tissues are bitten off or sucked out. To assess the individual prey sizes for such predators, observing each hunting event or converting residual body tissues in predator guts to whole-prey body mass is necessary. According to the current literature, the individual-link PPMR for gape-unconstrained predators is not yet available, except for parasitoid wasps (Cohen et al. 2005) and aquatic hemipteran bugs (Nakazawa et al. 2013). This implies that our understanding of size-dependent predator–prey interactions is limited, particularly regarding terrestrial food webs.
Individual-link PPMR may change ontogenetically, irrespective of whether predators are gape-unconstrained or -limited. By monitoring hunting events and estimating the body masses of interacting predators and prey individuals, Nakazawa et al. (2013) reported that the individual-link PPMR of gape-unconstrained hemipteran bugs varied according to individual predator size. Notably, this finding (i.e., size-dependent PPMR) is similar to that reported for gape-limited fish predators (Barnes et al. 2010; Nakazawa et al. 2011; Reum and Hunsicker 2012; Tsai et al. 2016). Thus, it is suggested that the original theoretical assumption of size-invariant PPMR is oversimplified. Irrespective of the feeding mode of predators (e.g., gape-limited or -unconstrained) or ecosystem type (e.g., aquatic or terrestrial), size-dependently parameterizing PPMR may be necessary. However, this finding contrasts with the initial objective of simplifying the complex structure of individual-based food webs (Fig. 1).
Realized versus preferred predator–prey mass ratio
Do we actually require such complex models assuming size-dependent PPMR? Although there are limited data to answer this question, available data suggest not (Tsai et al. 2016). This is because the aforementioned inconsistency between theoretical assumption and empirical measurement of PPMR arises because of conceptual confusion. The PPMR was originally invented to represent a preference for relative prey size. Nevertheless, PPMR has been measured using only dietary data (i.e., the realized PPMR) such as gut content analysis or observations of hunting, as previously mentioned. The relative size of prey in the diet is determined not only by the predator’s prey size selection (i.e. the preferred PPMR) but also by the prey size composition in the environment (Fig. 4). For example, the realized PPMR increases not only when a predator selectively feeds on small prey but also when small prey are abundant in the environment. Thus, the assessment of the realized PPMR does not automatically yield the preferred PPMR, and the preferred PPMR may be size-invariant even when the realized PPMR depends on predator body size.
To test this hypothesis, Tsai et al. (2016) reanalyzed long-term dietary data for an omnivorous predatory fish species collected from a lake ecosystem over four decades (Briones et al. 2012) by incorporating environmental abundance data for its major prey, zooplankton and zoobenthos (Ishikawa et al. 2004; Hsieh et al. 2011). Specifically, they compared prey size compositions in predator guts and the environment (i.e., the realized versus the environmental PPMR) to detect deviations between these elements as effects of the preferred PPMR. Notably, their results revealed that preferred PPMR was size-invariant if predators were classified into plankton and benthos feeders, whereas realized PPMR varied depending on the individual predator size irrespective of the feeding mode (Tsai et al. 2016). This is the first evidence of size-invariant prey size preference. Furthermore, in contrast to the previous arguments based on realized PPMR (discussed above), their finding supports the original assumption of a constant PPMR in food web models.
Variability and determinants of the preferred predator–prey mass ratio
Previous studies have argued about what determines the variability of the realized PPMR (refer to “Definition dependence of the predator–prey mass ratio”), but all such arguments are invalid for characterizing prey size preference (refer to “Realized versus preferred predator–prey mass ratio”). We can, however, approach determinants of prey size preference by distinguishing between realized and preferred PPMRs (Fig. 4) using environmental prey abundance information. In this sense, research on the PPMR has just begun and future studies will need to reanalyze its determinants using environmental prey abundance information. In a pioneering study, Tsai et al. (2016) showed that preferred PPMR was not significantly affected by predator body size, but varied according to major prey type, such as zooplankton versus zoobenthos, likely because of different foraging modes. Because their study focused on only a single predator species, it will be crucial to test the robustness of their findings by analyzing other predator species. It may turn out that preferred PPMR tends to be size-invariant according to the original theoretical assumptions, whereas prey size preference may depend on the taxonomic identity of predators if they exploit morphologically or behaviorally distinct prey types or have qualitatively different foraging modes. We expect that gape-unconstrained predators will exhibit different patterns of the preferred PPMR from that of the gape-limited predators (refer to “Predator–prey mass ratio of gape-unconstrained predators”). Testing this hypothesis will be essential for understanding differences between aquatic and terrestrial food webs (Shurin et al. 2006). Future studies are encouraged to identify determinants of preferred PPMRs for varied organisms and systems.
Conclusions and future perspectives
In this review, I have briefly outlined how the concept of the PPMR has been developed and refined. The ultimate goal of my arguments is to establish effective ways of describing food webs mediated by individual interactions (i.e., ontogenetic niche shifts). Herein, I have highlighted the following points:
-
1.
The PPMR should be measured at the individual level because species-averaged values distort real feeding relationships.
-
2.
Individual-level PPMR data on gape-unconstrained predators (e.g., terrestrial carnivores) are limited because previous studies have targeted gape-limited fish predators.
-
3.
The preferred PPRM is conceptually different from the realized PPMR and should be distinguished by using environmental prey abundance information.
-
4.
Determinants of preferred PPMR, rather than those of realized PPMR, should be identified to describe size-dependent predation.
Overall, the study of PPMR is still at an early stage of development and application. Further research efforts are needed to collect individual interaction data in addition to environmental prey abundance information on various systems.
Below I offer additional future research directions to more firmly establish the ontogenetic perspective in community ecology (Fig. 1). Most importantly, although previous studies and the present review have exclusively focused on prey–predator interactions (i.e., trophic interactions between animals), other types of biological interactions, such as competition (e.g., nutrients and space), mutualism (e.g., pollination and seed dispersal), and herbivory (i.e., trophic interactions between plants and animals) should be considered. For these interaction types, quantifying the body mass ratio of interacting individuals may not always be easy, especially when interaction strengths (preferences) are determined by ages or developmental stages rather than body masses. Nevertheless, it is still possible and would be useful to link age (or stage) relationships to interaction strength, as with the approach using PPMR. Terrestrial plants are commonly involved in the above interactions types. Therefore, I suggest that research on plant–plant or plant–animal interactions could be ontogenetically explicit as model systems. For plant–plant interactions, point pattern analysis has been recently applied to infer mechanisms underlying spatial vegetation structure at the individual level (Wiegand and Moloney 2014). Extending this technique to include developmental stage information (e.g., diameter at breast height and life-history stage) is useful for determining the extent to which plant–plant interactions are size-dependent (Tsai et al. 2015). Plant–animal interactions also change ontogenetically. For example, defense strategies (e.g., chemical and physical) and herbivore type (e.g., insects and mammals) vary during ontogenetic growth of plants (Barton and Koricheva 2010; Boege et al. 2011). Furthermore, many plants require animals for pollination or seed dispersal at the reproductive stage, suggesting that plant–animal interactions change not only quantitatively but also qualitatively from antagonism to mutualism. Similarly, plants have stage-specific interactions with parasitic and mutualistic soil microbes (Ke et al. 2015). Note also that the herbivorous larvae of some insects (e.g., Lepidoptera) become pollinators at the adult stage (Altermatt and Pearse 2011; Ke and Nakazawa, unpublished data). Such information on ontogenetic changes in interaction patterns remains scattered and should be compiled for various systems to promote the ontogenetic perspective in community ecology.
The present ontogenetic perspective has broad applications not only in community ecology but also in other basic and applied ecologies. For example, incorporating the ontogenetic perspective can provide novel insights into physiological (Nakazawa 2011c) and evolutionary ecology (Chou et al. 2016) by highlighting functional traits (e.g., growth ratio and duration) or processes (e.g., maturation and reproduction) that have otherwise been ignored. Recently, pioneering studies have experimentally or theoretically reported that ontogenetic functional diversity can influence ecosystem functioning more strongly than interspecific functional diversity (Rudolf and Rasmussen 2013a, b; Reichstein et al. 2015), suggesting that the ontogenetic perspective is critical in ecosystem ecology. Furthermore, community ecology plays a crucial role in various applications that concern ecosystem management, such as agriculture (Gliessman 1990), fishery (Mangel and Levins 2005), epidemiology (Nakazawa et al. 2012; Johnson et al. 2015), and biodiversity conservation under global climate change (Nakazawa and Doi 2012; Post 2013). However, these areas have not yet been fully considered from the ontogenetic perspective, except for fisheries management (Hsieh et al. 2010). Future studies should investigate the ecosystem consequences of ontogenetic processes, which will contribute to better ecosystem management.
I conclude this review with more philosophical and challenging questions for future ecologists. A major problem of current interest is the limited availability of individual interaction data. I consider that this lack of data ultimately stems from our stereotype that an ecological community must be considered as a network of interspecific interactions. What is the rationale for the community view when interactions occur between individuals? Such fundamental inconsistency in assumption could result in erroneous conclusions. The species-based community theory has faced persistent problems, such as the paradoxes of enrichment (Rosenzweig 1971) and the complexity–stability debate (May 1972). There is even debate on whether general patterns exist in community ecology (Lawton 1999; Roughgarden 2009). I do not contend that the ontogenetic perspective can be used to solve all ecological problems. In evolutionary biology, however, the unit of selection has already switched from species to individuals or genes (Williams 1966; Brandon and Burian 1984; Sober and Wilson 1994). Considering that ontogenetic growth and niche shift are ubiquitous and critical in ecological dynamics, I envision that community ecology also requires a similar paradigm shift in the future. Collecting individual-level interaction data requires enomous time and effort. However, such efforts would be warranted from the viewpoint of the long-term development of ecology. I pose the following questions: (1) Why must community ecology be species-based? (2) Do we require a paradigm shift in the unit of biological interaction? (3) If so, how could such a shift be achieved? If this paradigm shift occurred, individual interaction data would be accumulated more widely, which has the intriguing potential to revolutionize our understanding of biodiversity and ecosystem functioning.
References
Altermatt F, Pearse IS (2011) Similarity and specialization of the larval versus adult diet of European butterflies and moths. Am Nat 178:372–382
Andersen KH, Beyer JE (2006) Asymptotic size determines species abundance in the marine size spectrum. Am Nat 168:54–61
Barnes C, Bethea DM, Brodeur RD, Spitz J, Ridoux V, Pusiner C, Chase BC, Hunsicker ME, Juanes F, Kellermann A, Lancaster J, Ménard F, Bard F-X, Munk P, Pinnegar JK, Scharf FS, Rountree RA, Stergiou KI, Sassa C, Sabates A, Jennings S (2008) Predator and prey body sizes in marine food webs. Ecology 89:881
Barnes C, Maxwell D, Reuman DC, Jennings S (2010) Global patterns in predator-prey size relationships reveal size dependency of trophic transfer efficiency. Ecology 91:222–232
Barton K, Koricheva J (2010) The ontogeny of plant defense and herbivory: characterizing general patterns using meta-analysis. Am Nat 175:481–493
Baxter CV, Fausch KD, Saunders WC (2005) Tangled webs: reciprocal flows of invertebrate prey link streams and riparian zones. Freshwat Biol 50:201–220
Begon M, Townsend CR, Harper JL (2006) Ecology: from individuals to ecosystems, 4th edn. Blackwell, Oxford
Blanchard JL, Jennings S, Law R, Castle MD, McCloghrie P, Rochet M-J, Benoît E (2009) How does abundance scale with body size in coupled size-structured food webs? J Anim Ecol 78:270–280
Blanchard JL, Law R, Castle MD, Jennings S (2011) Coupled energy pathways and the resilience of size-structured food webs. Theor Ecol 4:289–300
Boege K, Barton KE, Dirzo R (2011) Influence of tree ontogeny on plant-herbivore interactions. In: Meinzer FC, Lachenbruch B, Dawson TE (eds) Size- and age-related changes in tree structure and function. Springer, Dordrecht, pp 132–214
Bolnick DI, Amarasekare P, Araújo MS, Bürger R, Levine JM, Novak M, Rudolf VHW, Schreiber SJ, Urban MC, Vasseur DA (2011) Why intraspecific trait variation matters in community ecology. Trend Ecol Evol 26:183–192
Brandon RN, Burian RM (1984) Genes, organisms, populations: controversies over the units of selection. MIT Press, Cambridge
Briones JC, Tsai CH, Nakazawa T, Sakai Y, Papa RD, Hsieh CH, Okuda N (2012) Long-term changes in the diet of Gymnogobius isaza from Lake Biwa, Japan: effects of body size and environmental prey availability. PLoS One 7:e53167
Brose U (2010) Body-mass constraints on foraging behaviour determine population and food-web dynamics. Funct Ecol 24:28–34
Brose U, Cushing L, Berlow EL, Jonsson T, Banasek-Richter C, Bersier L-F, Blanchard JL, Brey T, Carpenter SR, Cattin Blandenier M-F, Cohen JE, Dawah HA, Dell T, Edwards F, Harper-Smith S, Jacob U, Knapp RA, Ledger ME, Memmott J, Mintenbeck K, Pinnegar JK, Rall BC, Rayner T, Ruess L, Ulrich W, Warren P, Williams RJ, Woodward G, Yodzis P, Martinez ND (2005) Body sizes of consumers and their resources. Ecology 86:2545
Brose U, Jonsson T, Berlow EL, Warren P, Banasek-Richter C, Bersier LF, Blanchard JL, Brey T, Carpenter SR, Blandenier MFC, Cushing L, Dawah HA, Dell T, Edwards F, Harper-Smith S, Jacob U, Ledger ME, Martinez ND, Memmott J, Mintenbeck K, Pinnegar JK, Rall BC, Rayner TS, Reuman DC, Ruess L, Ulrich W, Williams RJ, Woodward G, Cohen JE (2006a) Consumer-resource body-size relationships in natural food webs. Ecology 87:2411–2417
Brose U, Williams RJ, Martinez ND (2006b) Allometric scaling enhances stability in complex food webs. Ecol Lett 9:1228–1236
Brown JH, Gillooly JF, Allen AP, Savage VM, West GB (2004) Toward a metabolic theory of ecology. Ecology 85:1771–1789
Chou C-C, Iwasa Y, Nakazawa T (2016) Incorporating an ontogenetic perspective into evolutionary theory of sexual size dimorphism. Evolution 70:369–384
Cohen JE, Pimm SL, Yodzis P, Saldañ J (1993) Body sizes of animal predators and animal prey in food webs. J Anim Ecol 62:67–78
Cohen JE, Jonsson T, Müller CB, Godfray HC, Savage VM (2005) Body sizes of hosts and parasitoids in individual feeding relationships. Proc Natl Acad Sci USA 102:684–689
de Roos AM, Persson L (2013) Population and community ecology of ontogenetic development. Princeton University Press, Princeton
de Visser SN, Freymann BP, Olff H (2011) The Serengeti food web: empirical quantification and analysis of topological changes under increasing human impact. J Anim Ecol 80:484–494
Gliessman SR (1990) Agroecology: researching the ecological basis for sustainable agriculture. Springer, New York
Guiet J, Poggiale JC, Maury O (2016) Modelling the community size-spectrum: recent developments and new directions. Ecol Model 337:4–14
Guill C (2009) Alternative dynamical states in stage-structured consumer populations. Theor Popul Biol 76:168–178
Hart SP, Schreiber SJ, Levine JM (2016) How variation between individuals affects species coexistence. Ecol Lett. doi:10.1111/ele.12618 (in press)
Hartvig M, Andersen KH, Beyer JE (2011) Food web framework for size-structured populations. J Theor Biol 272:113–122
Hildrew AG, Raffaelli DR, Edmonds-Brown R (2007) Body size: the structure and function of aquatic ecosystems. Cambridge University Press, Cambridge
Hsieh CH, Yamauchi A, Nakazawa T, Wang WF (2010) Fishing effects on age and spatial structures undermine population stability of fishes. Aquat Sci 72:165–178
Hsieh CH, Sakai Y, Ban S, Ishikawa K, Ishikawa T, Ichise S, Yamamura N, Kumagai M (2011) Eutrophication and warming effects on long-term variation of zooplankton in Lake Biwa. Biogeosciences 8:593–629
Ishikawa T, Narita T, Urabe J (2004) Long-term changes in the abundance of Jesogammarus annandalei (Tattersall) in Lake Biwa. Limnol Oceanogr 49:1840–1847
Johnson PT, de Roode JC, Fenton A (2015) Why infectious disease research needs community ecology. Science 349:1259504
Ke PJ, Miki T, Ding TS (2015) The soil microbial community predicts the importance of plant traits in plant–soil feedback. New Phytol 206:329–341
Klecka J, Boukal DS (2013) Foraging and vulnerability traits modify predator–prey body mass allometry: freshwater macroinvertebrates as a case study. J Anim Ecol 82:1031–1041
LaBarbera M (1989) Analyzing body size as a factor in ecology and evolution. Annu Rev Ecol Syst 20:97–117
Lawton JH (1999) Are there general laws in ecology? Oikos 84:177–192
Lurgi M, López BC, Montoya JM (2012) Climate change impacts on body size and food web structure on mountain ecosystems. Phil Trans Roy Soc B 367:3050–3057
Mangel M, Levins PS (2005) Regime, phase and paradigm shifts: making community ecology the basic science for fisheries. Phil Trans Roy Soc B 360:95–105
May RM (1972) Will a large complex system be stable? Nature 238:413–414
Miller TEX, Rudolf VHW (2011) Thinking inside the box: community-level consequences of stage structured populations. Trend Ecol Evol 26:457–466
Naisbit RE, Kehrli P, Rohr RP, Bersier LF (2011) Phylogenetic signal in predator–prey body-size relationships. Ecology 92:2183–2189
Nakazawa T (2011a) Ontogenetic niche shift, food-web coupling, and alternative stable states. Theor Ecol 4:479–492
Nakazawa T (2011b) Alternative stable states generated by ontogenetic habitat coupling in the presence of multiple resource use. PLoS One 6:e14667
Nakazawa T (2011c) The ontogenetic stoichiometric bottleneck stabilizes herbivore-autotroph dynamics. Ecol Res 26:209–216
Nakazawa T (2014) A dynamics resilience perspective toward integrated ecosystem management: biodiversity, landscape, and climate. In: Okuda N (ed) Biodiversity in aquatic systems and environments: lake Biwa. Springer Japan, Tokyo, pp 69–91
Nakazawa T (2015a) Ontogenetic niche shifts matter in community ecology: a review and future perspectives. Popul Ecol 57:347–354
Nakazawa T (2015b) Introducing stage-specific spatial distribution into the Levins metapopulation model. Sci Rep 5:7871
Nakazawa T, Doi H (2012) A perspective on match/mismatch of phenology in community contexts. Oikos 121:489–495
Nakazawa T, Sakai Y, Hsieh CH, Koitabashi T, Tayasu I, Yamamura N, Okuda N (2010) Is the relationship between body size and trophic niche position time-invariant in a predatory fish? First stable isotope evidence. PLoS One 5:e9120
Nakazawa T, Ushio M, Kondoh M (2011) Scale dependence of predator–prey mass ratio: determinants and applications. Adv Ecol Res 45:269–302
Nakazawa T, Yamanaka T, Urano S (2012) Model analysis for plant disease dynamics co-mediated by herbivory and herbivore-borne phytopathogens. Biol Lett 8:685–688
Nakazawa T, Ohba S, Ushio M (2013) Predator-prey body size relationships when predators can consume prey larger than themselves. Biol Lett 9:20121193
Otto SB, Rall BC, Brose U (2007) Allometric degree distributions facilitate food-web stability. Nature 450:1226–1229
Owen-Smith N, Mills MGL (2008) Predator–prey size relationships in an African large-mammal food web. J Anim Ecol 77:173–183
Post E (2013) Ecology of climate change: the importance of biotic interactions. Princeton University Press, Princeton
Reichstein B, Persson L, de Roos AM (2015) Ontogenetic asymmetry modulates population biomass production and response to harvest. Nat Commun 6:6441
Reum JCP, Hunsicker ME (2012) Season and prey type influence size dependency of predator − prey body mass ratios in a marine fish assemblage. Mar Ecol Progr Ser 466:167–175
Riede JO, Brose U, Ebenman B, Jacob U, Thompson R, Townsend CR, Jonsson T (2011) Stepping in Eltons footprints: a general scaling model for body masses and trophic levels across ecosystems. Ecol Lett 14:169–178
Rosenzweig ML (1971) Paradox of enrichment: destabilization of exploitation ecosystems in ecological time. Science 171:385–387
Roughgarden J (2009) Is there a general theory of community ecology? Biol Philos 24:521–529
Rudolf VHW, Rasmussen NL (2013a) Population structure determines functional differences among species and ecosystems processes. Nat Commun 4:2318
Rudolf VHW, Rasmussen NL (2013b) Ontogenetic functional diversity: size-structure of a keystone predator alters functioning of a complex ecosystem. Ecology 94:1046–1056
Scharf FS, Juanes F, Rountree RA (2010) Predator size-prey size relationships of marine fish predators: interspecific variation and effects of ontogeny and body size on trophic-niche breadth. Mar Ecol Prog Ser 208:229–248
Schreiber S, Rudolf VHW (2008) Crossing habitat boundaries: coupling dynamics of ecosystems through complex life cycles. Ecol Lett 11:576–587
Shurin JB, Gruner DS, Hillebrand H (2006) All wet or dried up? Real differences between aquatic and terrestrial food webs. Proc R Soc B 275:1–9
Sober E, Wilson D (1994) A critical review of philosophical work on the units of selection problem. Phil Sci 61:534–555
Thierry A, Petchey OL, Beckerman AP, Warren PH, Williams RJ (2011) The consequences of size dependent foraging for food web topology. Oikos 120:493–502
Tsai C-H, Lin Y-C, Wiegand T, Nakazawa T, Su S-H, Hsieh C-H, Ding T-S (2015) Individual species-area relationship of woody plant communities in a heterogeneous subtropical monsoon rainforest. PLoS One 10:e0124539
Tsai CH, Hsieh CH, Nakazawa T (2016) Predator-prey mass ratio revisited: does preference of relative prey body size depend on predator body size? Funct Ecol. doi:10.1111/1365-2435.12680 (in press)
Verhoef HA, Morin PJ (2010) Community ecology: processes, models and applications. Oxford University Press, Oxford
Violle C, Enquist BJ, McGill BJ, Jiang L, Albert CH, Hulshof C, Jung V, Messier J (2012) The return of the variance: intraspecific variability in community ecology. Trend Ecol Evol 27:244–252
Werner EE, Gilliam JF (1984) The ontogenetic niche and species interactions in size-structured populations. Annu Rev Ecol Syst 15:393–425
Wiegand T, Moloney KA (2014) A handbook of spatial point pattern analysis in ecology. Chapman and Hall/CRC Press, New York
Wilbur HM (1980) Complex life cycles. Annu Rev Ecol Syst 11:67–93
Williams GC (1966) Adaptation and natural selection. Princeton University Press, Princeton
Woodward G, Warren PH (2007) Body size and predatory interaction in freshwaters: scaling from individuals to communities. In: Hildrew AG, Raffaelli D, Edmonds-Brown R (eds) Body size: the structure and function of aquatic ecosystems. Cambridge University Press, Cambridge, pp 97–117
Zhang L, Thygesen UH, Knudsen K, Andersen KH (2013) Trait diversity promotes stability of community dynamics. Theor Ecol 6:57–69
Acknowledgements
I am greatly honored to receive the 20th Miyadi Award of the Ecological Society of Japan. I thank my many collaborators and colleagues at Center for Ecological Research, Kyoto University and Institute of Oceanography, National Taiwan University for their active collaboration and fruitful discussions. This review is based on my past research, which was funded mainly by the Japan Society for the Promotion of Science and the Ministry of Science and Technology of Taiwan.
Author information
Authors and Affiliations
Corresponding author
Additional information
Takefumi Nakazawa is the recipient of the 20th Denzaburo Miyadi Award.
Rights and permissions
This article is published under an open access license. Please check the 'Copyright Information' section either on this page or in the PDF for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.
About this article
Cite this article
Nakazawa, T. Individual interaction data are required in community ecology: a conceptual review of the predator–prey mass ratio and more. Ecol Res 32, 5–12 (2017). https://doi.org/10.1007/s11284-016-1408-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11284-016-1408-1