Ecosystem Self-Organization: Free Order for Nothing?

Ecological Complexity 38 (2019) 24–30

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Ecological Complexity

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Short Note ☆ Ecosystem spatial self-organization: Free order for nothing? T ⁎ Dong Xiaolia,b, , Fisher Stuart G.a a School of Life Sciences, Arizona State University, Tempe, 85287 AZ, USA b Department of Environmental Science and Policy, University of California, Davis, 95616 CA, USA

ARTICLE INFO ABSTRACT

Keywords: Ecosystems are complex adaptive systems (CAS) by nature, which means that macroscopic patterns and prop- Agent erties emerge from, and feed back to affect, the interactions among adaptive individual ecological agents. These Complex adaptive systems agents then further adapt (genetically) to the outcomes of those interactions. The concept of self-organization Eco-evolutionary feedbacks has become increasingly important for understanding ecosystem spatial heterogeneity and its consequences. It is Regular patterning well accepted that ecosystems can self-organize, and that resulting spatial structures carry functional con- Self-organization sequences. Feedbacks from the outcome of spatial pattern to the individual agents from which patterns emerge, Spatial ecology are an essential component of the definition of CAS but have been rarely examined for ecosystems. We explore whether spatial self-organization provides a mechanism for such feedback for ecosystems as CAS, that is, whether ecosystem-level outcomes of self-organized patterning could feed back to affect or even reinforce local pattern-forming processes at the agent level. Diffuse feedbacks of ecological and evolutionary significance ensue as a result of spatial heterogeneity and regular patterning, whether this spatial heterogeneity results from an underlying template effect or from self-organization. However, feedbacks directed specifically at pattern-forming agents to enhance pattern formation—reinforcing feedback—depend upon the level of organization of agents. Reinforcing evolutionary feedbacks occur at the individual level or below. At the ecosystem level, evidence for mechanisms of feedback from outcomes to patterning to agents forming the patterning remain tenuous. Spatial self-organization is a powerful dynamic in ecosystem and landscape science but feedbacks have been only loosely integrated so far. Self-organized patterns influencing dynamics at the ecosystem level represent “order for free”. Whether or not this free order generated at the ecosystem level carries evolutionary function or is merely epiphenomenal is a fundamental question that we address here.

1. Introduction ecosystem selection) and are rooted in a tradition of wishful thinking derived from systems theory and cybernetics. The idea of long term holistic ecosystem control and directional For many years, the ecosystem was studied as a “black box,” change has a long history in ecology (e.g., 'community of interest' by wherein ecosystem ecologists measured inputs and outputs of material Forbes (1925); 'ecosystems as superorganisms' by Clements (1936)). It and energy without explicit reference to spatial pattern (e.g., Odum, has been hypothesized that there are directional and predicable 1957; Bormann and Likens, 1967; Fisher and Likens, 1972; Bormann changes in many ecosystem properties over successional time et al., 1977). In contrast, ecology has a long tradition of understanding (Odum 1969). Some of the specific predictions of Odum (1969) were the spatial pattern of organisms at a variety of scales (e.g., Watt, 1947; later modified in light of empirical studies (e.g., Vitousek and Reiners, Whittaker, 1956; Curtis, 1959). In fact, ecology has been defined as the 1975; Fisher et al., 1982), but others remain untested. Similarly, the study of the distribution and abundance of living organisms strong Gaia hypothesis (Lovelock and Margulis, 1974) largely fails as a (Andrewartha and Birch, 1986). Consideration of spatial dynamics re- model for understanding nature, as it treats the biosphere as if biolo- ceived increased attention in the late 1970s and early 1980s with the gically mediated feedbacks necessarily enhance the environment to ascendance of landscape ecology (White, 1979; Paine and Levin, 1981; make it more suitable for life, although certain forms of weaker Gaia Pickett and White, 1985). Landscape ecology brought a particular focus are accepted (Kirchner, 2002). These views of ecosystem change often to spatial heterogeneity with attempts to link it with its functional invoke unspecified or controversial mechanisms (e.g., group selection, consequences (Turner, 2005). Two ecosystems with identical

☆ This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. ⁎ Corresponding author at: Department of Environmental Science and Policy, University of California, 1 Shields Ave, Davis, 95616 CA, USA. E-mail addresses: [email protected] (X. Dong), s.fi[email protected] (S.G. Fisher). https://doi.org/10.1016/j.ecocom.2019.01.002 Received 25 August 2018; Received in revised form 6 January 2019; Accepted 10 January 2019 1476-945X/ © 2019 Published by Elsevier B.V. X. Dong and S.G. Fisher Ecological Complexity 38 (2019) 24–30 components could have very different ecological functioning if the 2002). Depending on the network of flowpaths generating SDF re- components were arranged differently in space (e.g., Irlandi et al., sponses, spatial patterns emerge. When the resource is no longer lim- 1995; van Nes and Scheffer, 2005; Virah-Sawmy et al., 2009). For ex- iting, self-organized patterns (resource islands) resulting from this ample, the spatial arrangement of grassy and bare soil areas influences mechanism disappear. Regular patterning is also found in environments patterns of sediment losses from a semiarid savanna landscape with physical stress, such as in freshwater macrophyte patches in (Ludwig et al., 2007). The classic perspective on formation of spatial lowland streams and rivers exposed to shear stress (Schoelynck et al., heterogeneity emphasizes physical conditions set by the landscape as 2012). At short range, amelioration of physical stress by plants en- the main determining factor, i.e. the template effect (Buxbaum and hances sediment accretion, insulating plants. At longer-range, stress Vanderbilt, 2007; Manolaki and Papastergiadou, 2012; Ropars and forms erosion troughs around the plant tussock restricting its lateral Boudreau, 2012). But heterogeneity can also emerge from completely expansion. Erosion decreases as sediment accumulates in the plant homogeneous conditions through interactions among ecosystem com- tussock, which in turn improves local habitat (short-range positive ponents, i.e., by the process of self-organization. feedback). Meanwhile, in the area beyond vegetation patches, sheer Ecosystems are considered complex adaptive systems, which means stress and erosion greatly increase, preventing plant establishment that “spatial patterns emerge from, and feed back to affect, the actions (long-range negative feedback). Whereas scale-dependent feedbacks are of adaptive individual agents” (Levin, 1998, 2005). Although this de- often considered a general mechanism for pattern formation, finition has been widely used, the essence of it, i.e., feedback that Tarnita et al. (2017) and Pringle and Tarnita (2017) recently argue that crosses levels of organization (e.g. between the level of ecosystem and other mechanisms (such as territorial interference competition between the level of individual agent), has not been scrutinized. What is the colonies of social-insect ecosystem engineers) could interplay with SDF mechanism for such feedback? Is the feedback directional—that is, is in a dynamic way to contribute to landscape pattern formation under there feedback from the consequences of an ecosystem spatial property certain conditions. There is also a relatively rich body of literature on to the actions of individual agents that generated the spatial pattern. noise-induced pattern formation (that is, regular patterns emerge from And does this intensify patterning or reinforce ecosystem functioning stochastic noise), but it has had limited applications to the environ- and thus render the system ‘adaptive’? If so, what are the mechanisms of mental sciences (Borgogno et al., 2009). this? Lastly, if ecosystems are complex adaptive systems, does such feedback provide a source of system-level ‘adaption’? In this paper, we 3. Ecosystem consequences of self-organized patterns examine the mechanisms of feedback from the consequences of self- organized patterns to agents of pattern formation and assess whether Spatial heterogeneity has been shown to influence a range of eco- self-organization, through these feedbacks, could contribute to a me- system properties regardless of whether spatial variety is generated by chanism for directional ecosystem change akin to cybernetic control or an underlying template or is self-organized. In resource-limited en- to Gaia or to some other mechanisms of ecosystem control or direc- vironments (e.g., deserts), self-organized heterogeneous patterning re- tionality. lies on movement of a limiting resource (e.g., water, nutrient) along flow paths, and is realized as organisms themselves affect the avail- 2. Origin of spatial heterogeneity ability and spatial distribution of the resources upon which they depend. With the emergence of patterns, the structure of flow paths is also Other than the commonly studied template effects, where the ex- altered, as well as consequent ecosystem nutrient retention. This altered isting geomorphic, hydrologic, or climatic variables determine biolo- ecosystem nutrient retention is caused by the modified pathway of gical patchiness, spatial heterogeneity can arise in other ways, with flows among patches, evolving patch geometry, nonlinear biogeo- some degree of randomness or stochasticity. Spatial heterogeneity can chemical processing rates with distance along a flow path, and their also arise from a homogeneous template by spatial self-organization. collective consequences at the ecosystem level. When several patch For example, in many arid ecosystems, vegetation forms regular stripes types are present, the results can be a complex function of the spatial (‘tiger bush’), labyrinths, spots (‘leopard bush’), and gaps (Rietkerk and arrangement of patch types transected by operant flowpaths that in- van de Koppel, 2008). In the Florida Everglades, ridges and sloughs are tegrate patch variety (Reiners and Driese, 2001; Fisher et al., 2004; self-organized into a regularly interspersed pattern, parallel to the di- Fisher and Welter, 2005). As a consequence, banded vegetation in arid rection of flow (Larsen et al., 2007). In the Namib Desert of south- and semiarid ecosystems can retain more runoff and sediments than western Africa, fairy circles—nearly circular barren patches within a non-patterned ecosystems (Ludwig et al., 1999; Ludwig et al., 2005). sparse matrix of small short-lived grass species surrounded by a halo of Patterned landscapes also have implications for trophic structure in taller grass, are regularly spaced, and extend for kilometers across the communities. Pringle et al. (2010) suggested that evenly spaced termite landscape (Tschinkel, 2012). In mussel beds on intertidal flats, regular mounds produced dramatically greater abundance, biomass, and re- patterns develop at two scales, banded patterns occurring at the eco- productive output of consumers across trophic levels than would be system level, and net-shaped patterns at the smaller scale of mussel obtained in landscapes with randomly distributed mounds. assemblages (Liu et al., 2014). In all these cases, self-organized spatial Regular patterns also can alter ecosystem stability and resilience, patterns arise by the mechanism of scale-dependent feedbacks (SDF; which are among the most holistic of ecosystem properties. Self-orga- Fig. 1). Scale-dependent feedbacks couple short-range positive feed- nized landscapes exhibit catastrophic shifts from self-organized backs with long-range negative feedbacks (Rietkerk and van de patchiness to a homogeneous state in response to altered levels of stress Koppel, 2008). Depending on the sources for “activation” and “inhibi- (e.g., amount of precipitation; Rietkerk et al., 2004). Patterned mussels tion”, there are two basic mechanisms for scale-dependent feedback; in intertidal flats are more resilient to wave action and have higher one is through resource distribution and the other through amelioration productivity at landscape scales than non-patterned mussels (van de of physical stress. Koppel et al., 2008). Whether self-organization leads to increased re- In resource-limited environments, positive feedback results from the silience and stability or to increased vulnerability may depend on the local interaction between the resource-consumer agent (e.g., individual ecosystem involved. Mathematical models predict that the emergent plants) and its limiting resource, resulting in long-distance depletion of self-organization of mussel beds affects the functioning of mussel bed the resource. This is the negative feedback. In arid systems, for ex- ecosystems by enhancing productivity and resilience against wave ample, vertical infiltration of water is locally enhanced by plants, which disturbance (van de Koppel et al., 2005a). Van de Koppel et al. (2005b) improves local conditions for plant growth. At a longer distance along found that self-organization induced by local positive feedbacks be- the hydrologic flow path, this local depletion of water and gradual tween clay accumulation and plant growth enhanced the resilience of drying limits growth (Couteron and Lejeune, 2001; Rietkerk et al., salt marsh ecosystems on short time scales. On longer time scales,

25 X. Dong and S.G. Fisher Ecological Complexity 38 (2019) 24–30

Fig. 1. (A) Schematic of scale-dependent feedback (SDF) giving rise to regular patterning, and (B) self-organized patterns: (B1) ribbon forests; (B2) sand ripples; (B3) evenly spaced termite mounds; (B4) regularly-spaced stripes on zebra fish; (B5) banded mussel bed; (B6) spiral waves formed by the Min protein in E. coli. however, self-organization led to the destruction of salt marsh vegeta- and are subject to natural selection at the level of the individual. tion. Using an evolutionary host-pathogen model, Jackson et al. (2014) In the realm of ecology, self-organization can form spatial patterns showed that patterned landscapes have higher resistance to the spread at a range of organizational levels. Populations can act as pattern- of pathogens. These and other examples illustrate that self-organized forming agents. For example, ant and termite colonies form regular spatial patterns have a significant effect on several ecosystem properties spaced nests on the landscapes (Ryti and Case, 1986; Tarnita et al., (e.g., nutrient retention, stability) considered to be essential ecosystem 2017). Communities of mixed species can also act as agents. For ex- attributes (Odum, 1969). But the question remains, are individual ample, banded vegetation in deserts (often characterized by a mix of agents of patterning themselves influenced or even rewarded for pat- species, e.g., tarbush, sod grasses, mesquite, juniper brush etc.; tern generation? If so, how? Penny et al., 2013), ribbon forests in subalpine environments (Bekker and Malanson, 2009), and coral reefs (Mistr and Bercovici, 2003)—all exhibit patterns generated by communities. In 4. Taxonomy of pattern-forming agents some cases, an agent can be considered an ecosystem itself, with both biotic and abiotic components, such as regular patterned cypress de- Spatial self-organization is driven by a system of agents. This system pressions embedded in Big Cypress National Preserve in South Florida initiates change that is distributed across a relatively homogeneous (Watts et al., 2014) or ridge and slough configurations in the nearby platform interacting with a propagating vector (wind, flow of water, Everglades (Larsen et al., 2007)(Table 1). resource movement along a concentration gradient) to set up the spa- As we discussed earlier, all of the changes resulting from patterning tially distributed feedback network upon which spatial patterns emerge can have substantial ecological consequences (e.g., resource retention, (symmetry-breaking instability). The agent itself is a component of productivity, resilience, and stability). These changes alter the “ecolo- patches in the self-organized landscape. Patterns do not instantly gical theater’ (sensu Hutchinson, 1965) and change the evolutionary emerge, but develop at a rate commensurate with agent and patch adaptive landscape, thereby potentially affecting all species of the growth and/or movement constants (e.g., fast with sand ripples on a ecosystem—some positively, and others negatively—to varying de- stream bed; slower with banded forest vegetation). Once formed, the grees. In this diffuse manner, self-organization alters the “evolutionary patterned landscape may eventually disappear, for example when nu- play” for all organisms, pattern-forming agents included. This feedback trient or water limitation is relaxed, and re-form when it reoccurs is what we call diffuse feedback II (Fig. 2). Our focal question, however, (Meron, 2017). Such self-organized dynamics in time is similar to the concerns feedback I (Fig. 2), a reinforcing feedback between the con- dynamics described by the theory of the adaptive cycle (Gunderson and sequences of spatial patterns and the evolution of traits contributing to Holling, 2002). self-organization (pattern forming traits). Can consequences of self-or- Self-organized patterning can occur by a variety of agents, some ganized patterns feedback specifically to reinforce the activities of simple and purely physical and others biological and more complex pattern-generating agents? And in cases where pattern formation is self- (Table 1). For example, sand grains form regularly spaced dunes and limiting, might pattern formation represent a control system, defining a ripples driven by wave or wind action. These undulating patterned set point and holding fluctuation within certain limits? For example, systems may affect organisms, but are not themselves biological—and when patterns emerge in a nutrient-limited landscape such that nutrient they have also been observed on the presumably lifeless Mars and uptake is enhanced as pattern develops, the agent benefits from in- Venus (Hanes et al., 2001). Clouds display regular patterns by self-or- creased nutrients. When nutrients surpass limiting levels, the pattern ganization (Garay et al., 2004). Dye added to water in a shallow pan, breaks down and nutrient retention declines, only to resume when instead of mixing, forms intricate patterns such as labyrinthine stripes limiting levels are again reached. In this hypothetical example, the (Strombom et al., 2012). Clearly, lifeless systems can self-organize to patterning agent regulates ecosystem nutrients by turning patterning on form order. and off. Will it work? The answer to this question depends on the Self-organization can involve sub-organismal biological levels of properties of agent-pattern-feedback system. organization. Cells, organelles, and organs can act as agents of self-organization and patterns can appear in these same subsystems (Table 1). At the subcellular level, the Min protein forms regular wave patterns on 5. Evaluating feedbacks the cell membrane of Escherichia coli (Loose et al., 2008). Cells form regular stripes at the growth zone of the mammalian palate 5.1. Agents at different organizational levels (Economou et al., 2012). At the organismal level, pigment cells form Turing patterns on the skin of Zebrafish (Nakamasu et al., 2009), and Below we consider agents of different categories and at different presumably other vertebrates. These examples involve biological agents organizational levels (abiotic agents, biotic agents at the sub-orga- forming regular patterns at the sub-organismal and organismal level. As nismal/organismal level, biotic agents above the organismal level in- we shall see, these examples involve investment on the part of agents cluding populations, communities, and ecosystems, and also the case of

26 X. Dong and S.G. Fisher Ecological Complexity 38 (2019) 24–30 Category of agents Abiotic particles Plants Plants Plants Colony of social insects Mobile animals Bacteria of the same genotype Cells Protein Hanes et al., 2001 Bekker and Malanson, 2009 Watts et al., 2014 Larsen et al., 2007 Bonachela et al., 2015 van de Koppel et al. 2005a Ben-Jacob et al., 2000 Nakamasu et al., 2009 Loose et al., 2008 )

Fig. 2. Consequence of and feedbacks in self-organization by agents at the sub- organismal/organismal levels and at the ecosystem level (or levels above organismal level). Feedbacks I (reinforcing feedback): agents form regular patterns, and the outcome of the pattern formation feeds back to reinforce the traits Cladium jamaicense governing pattern formation, which further alters the spatial patterns. Feedback II (diffuse feedback): agents form regular patterns, and the outcome of pattern formation feeds back to influence the pattern-forming agents. Such influence Trees Sand grains Pattern-forming Agent involved References Termites Mussels Sawgrass ( Microorganisms Pigment cells Trees Protein does not result in directional changes in the spatial patterns. At the sub-organismal or organismal level, feedback I is possible realized via natural selection on the formed patterning. At the above-organismal level (e.g., population, community, and ecosystem), regular patterns can have ecological and evolutionary consequences on pattern-forming agents, as well as on all other organisms in the ecosystem (feedback II). Reinforcing feedback by natural se-

Abies lasiocarpa, lection on individual pattern-forming agents (feedback I) requires further investigation.

bacteria colony of the same genotype) to evaluate whether reinforcing feedback (feedback I in Fig. 2) and diﬀuse feedback (feedback II) are possible.

5.1.1. Abiotic agents etc. For a feedback to reinforce the ability of an agent to form patterns, there must be (i) a signal detectable by agents from outcomes of the spatial patterning that returns to the agent, and (ii) a capacity for the agent to change its patterning capacity in response to the detected signal and to store information specifying that capacity. Apparently, abiotic agents such as sand grains forming sand dunes and ripples do not possess any of these capabilities. While regular patterns can emerge spontaneously in the inanimate world, they only involve simple physical forces and properties of the agent system, with no purpose (evo- Sand grain aggregation Tree aggregation, including a range of subalpine species,Cypress e.g., domes, including cypress trees and other wetland species Termite mounds Patches in pattern Picea engelmannii, Pinus contorta Sawgrass on accumulated peat (ridge) Microorganism aggregations Pigment aggregations Protein aggregations lutionary beneﬁt or drive)—they are mere epiphenomena.

E. coli 5.1.2. Biotic agents at the organismal level At the organismal level (e.g., Turing patterns on animal coat and protein patterns on cell membranes), feedback reinforcement of self- organized patterns does occur by evolution and natural selection. Pattern formation of individual agents (e.g., protein or pigment cells) at this level is fundamentally controlled by genes. The agents form patterns that are functional traits of adaptive signiﬁcance. Natural selection occurs at the level of the individual, operating on the variation of these functional traits, resulting in diﬀerential survival and reproduc- sh skin

fi tion, enhanced fitness, and ultimately a change in the frequency of genes controlling such patterning. In these cases, the pattern formed is an adaptation (sensu Williams, 1966) and feedback can select among these pattern-forming adaptations and intensify the self-organized South Florida plate pattern. For example, a zebra with self-organized stripes may enjoy Sand ripples in nearshoreRibbon and forest inner-shelf in regions subalpine environments Self-organized patterns Overdispersed cypress domes on a landscape Ridge-slough pattern in the Everglades National Park in Overdispersed termite mounds on landscapes Mussel population forming banding in inter-tidal zone Mussel clumps Microorganism colony forming branching patterns on agar Stripes on zebra Spiral waves formed by Min proteins in bacterium fi Table 1 Taxonomy of patterns, patches in patterns, and pattern-forming agents. higher survival, reproductive output, and thus tness than its non-

27 X. Dong and S.G. Fisher Ecological Complexity 38 (2019) 24–30 striped conspecifics. 5.1.5. Organisms at the community level Agents involved in pattern formation may belong to multiple species (a community) or may also include the physical environments in which 5.1.3. Microorganism at the colony level (same genetic information) biological agents reside (an ecosystem). In these cases, can the pattern- Self-organized pattern formation is observed in bacterial colonies of forming agents receive reinforcement via the favorable changes their identical genotype (reviewed by Ben-Jacob et al., 2000). When nutrient formed patterns have wrought (feedback I in Fig. 2)? To form periodic levels are high, the bacteria behave as any independent unicellular patterns, long-distance negative feedback is essential. Short-distance organisms. Under hostile environmental conditions, self-organized positive feedback alone, unaccompanied by long-distance feedback, is patterns begin to form, as shown in Bacillus subtilis, Escherichia, and not sufficient to form periodic patterns (Rietkerk and van de Salmonella typhimurium (Fujkawa and Matsushita, 1991). The pattern Koppel, 2008). For example, plants of arid ecosystems invest in a root formation of the bacterial systems is a consequence of attractive che- system that takes up water and nutrients but also can prevent erosions motaxis (Gloag et al., 2013), which is heritable (Ben-Jacob et al., 1994). and increase water infiltration. This extra investment in the root system In this case, reinforcing feedbacks between pattern and pattern-forming acts to improve soil condition (that is, local facilitation). In terms of its agents occur, as a result of selection acting on a specialized signaling effect on landscape patterning, the strength of local facilitation could system to assist pattern formation by the bacteria colony of same gen- affect the sharpness of the patch (Eppinga et al., 2009); however, it is otype. When a foreign group of a different genotype is present, regular not essential for forming the periodic patterning. A large body of lit- patterns disappear, and the non-patterned mixture of bacteria strains erature has shown that local facilitation has important evolutionary exhibit less efficient resource use and lower productivity (Xavier et al., implications both theoretically and empirically (Laland et al., 1999; van 2009), akin to an evolutionary tragedy of the commons (Rankin et al., Nuland et al., 2017). Local facilitation is costly and is subject to chea- 2007). ters (which do not invest to facilitate, but benefit from the facilitation of others; Kéfi et al., 2008). Unlike the example of pattern formation in mussel beds, where the resource ‘stability’ produced by the group is 5.1.4. Organisms at the population level exclusive to cooperating members, many resources created by local Genetically unrelated individuals of the same species may form facilitation—e.g., physical protection, improved soil texture, shade, and regular patterns in ecosystems. For example, mussels (Mytilus edulis)on increased resource availability in harsh environments (e.g., arid eco- intertidal flats form patterns by two opposing mechanisms: cooperation systems)—are available to all and are subject to exploitation by chea- and competition (van de Koppel et al., 2005a). Through movement into ters. Kéfi et al. (2008) examined such eco-evolutionary feedback in cooperative aggregations, mussels increase their local density, which scale-free vegetation patterns of dryland ecosystems and suggested that decreases wave stress and predation risk. Conversely, competition for the direction of this eco-evolutionary feedback does not necessarily algal food places an upper limit on the size of clumps. Mussels actively enhance patterning at the local patch scale. Instead, it could lead to self-organize into large-scale labyrinth-like patterns, aggregating into a extinction of the local plant population as a result of cheaters taking group of conspecifics and employing byssal threads to attach to the advantage of local facilitation invested by facilitators in the population shells of conspecifics within reach. Formation of local clustering relies when dispersal is widespread. Regardless of the complex eco-evolu- on specific traits of agents: movement strategy and attachment by by- tionary feedback between traits of pattern-forming agents and char- ssal threads, which requires investment. Both traits are robust against acteristics of patches at the local scale, at the landscape-scale, the free-riders (cheaters). Here, the ‘resource’ generated by the group is emergence of periodic patterning occurs as individual agents assort ‘stability’ (resistance to wave disturbances), which is exclusive: mussels uniformly relative to resource availability. The heterogeneity of re- which do not get into the clump fast enough or those who do not de- source availability is generated by long-distance negative feedback with velop enough byssal threads get ‘punished’ (high mortality, fewer off- no need to invoke eco-evolutionary feedback. Hence spatial patterning spring) immediately. is an incidental consequence of ordinary biological processes (e.g., The number of byssal threads (hence the size and tightness of water uptake by roots), requires no additional investment. clusters) responds to the stress level of the environment until it reaches Across a wide variety of agents from the sub-organismal to eco- an evolutionarily stable state (De Jager et al., 2017). Order emerges at system levels as we examined above, spatial patterning resulting from the landscape scale as a result of individuals assorting uniformly re- local interactions of agents all suggests evolutionary consequences for lative to resource availability, and the eco-evolutionary feedback occurs the agents—that is, diffuse feedback is ubiquitous. Reinforcing feed- between the clustering and traits involved in forming clusters at the backs—patterning outcomes that would reinforce pattern for- patch scale, instead of at the landscape scale—that is, the landscape- mation—would occur at or below the organismal level by natural se- scale spatial order forms without cost and is not likely a function (sensu lection. This includes the bacterial colony of a single genotype, which Williams, 1966). However, the study by De Jager et al. (2011) on the can be viewed as one organism. For levels above the organismal le- rise of Lévy walk in regular musselbeds implied the likelihood of direct vel—population, community, and ecosystems—a few existing studies feedback between individual search behaviors and order at the land- suggest a theoretical possibility for feedback I; however, definitive re- scape scale (as opposed to the patch scale). Lévy walk improves the search is still limited and we remain skeptical. survival chances of individual mussels by allowing them to form a group faster, which in turn decreases predation risk (De Jager et al., 5.2. Free order for nothing? 2011). Theoretical models imply Lévy walk results from feedback between animal behavior and mussel-generated environmental com- Kauffman (1993, 1996) coined the phrase “order for free” to describe plexity. The fitness of individual mussels is assumed to be the product of self-organized patterning: meaning that order (regular spatial pattern) individual mussel survival, which is proportional to short-range mussel spontaneously forms through combined physical forces and properties density and fecundity, which is inversely proportional to long-range of individual agents. Ecosystem spatial self-organization is different mussel density and the energy invested in movement (De Jager et al., from pattern formation by non-living agents (e.g., sand grains), which 2011). These studies indicate the possibility of the promotion of spatial are not subject to natural selection. It is also distinct from self-organi- patterning over time by natural selection at the level of individual zation at the level of the individual organism, which relies on external constituent agents, similar to the selfish herd theory proposed by molecules specialized in forming patterns. For example, assisted self- Hamilton (1971) that animal grouping behavior could evolve if in- organization is involved in formation of stripes on the skin of zebra fish, dividuals selfishly avoided predation. In the example of mussel ag- a process that relies on investment in specialized melanophores and gregation here, it is to avoid being washed away by wave action. xanthophores that act as inhibitor and activator at local and distal

28 X. Dong and S.G. Fisher Ecological Complexity 38 (2019) 24–30 points; Nakamasu et al., 2009). Order formed by assisted self-organi- ecosystem structure and thereby ecological functioning and has strong zation apparently requires an investment, hence, is not free, and the implications for enhanced understanding and effective management, formed pattern is of adaptive significance, through natural selection at relationships as yet largely unexplored. the level where patterning occurs (i.e., the level of the individual organism). Declarations of interest Is the order formed in ecosystems free? More importantly, is Kauffman's free order in ecosystems of adaptive significance, or it is None. order for nothing?Diffuse feedback (feedback II) occurs in patterned landscapes and influences evolutionary change (Fig. 2). There are sig- Ethical statement nificant pattern-related ecological and evolutionary dynamics at similar overlapping temporal scales that can profoundly influence ecosystems. We have followed all the required duties of authors, including: However, reinforcing feedback (feedback I) realized through strong, direct selection operating on the entire ecosystem level to enhance 1 Reporting standards: our article presents an accurate account of spatial patterns or the processes that generated them to make ecosys- the work performed as well as an objective discussion of its sig- tems ‘adaptive’ is unlikely, as it would require natural selection at the nificance. level of population, community, and ecosystems, which remains at least 2 Data access and retention: the article doesn't include any data. controversial and widely disputed (Williams, 1966; Wilson, 1983; 3 Originality and acknowledgement of sources: we ensured that Stevens et al., 1995; Johnson and Boerlijst, 2002; Price, 2012). the article is original, and in places where we used the work and/or A few studies have proposed the possibility of such reinforcing words of others, they were appropriately cited or quoted. feedbacks realized via natural selection at the level of individual agents 4 Multiple, redundant or concurrent publication: this article was (De Jager et al., 2011, 2017; Kéfi et al., 2008). Order emerges at the only submitted to Ecological Complexity. landscape scale as a result of individuals assorting uniformly relative to 5 Confidentiality: not applicable to our article. stress or resource availability (long-distance negative feedback). The 6 Authorship of the paper: both authors contributed substantially to eco-evolutionary feedback however occurs at the patch scale to re- the paper. inforce the characteristics of individual patches/clusters. The direct 7 Hazards and human or animal subjects: the research doesn't in- interaction and feedback between the free order at the landscape scale volve any human or animal subjects in the study. and the clustering at the patch scale at which eco-evolutionary feed- 8 Declaration of competing interests: none. backs occur remains to be demonstrated. 9 Notification of fundamental errors: if we discover a significant Ecosystems are often considered complex adaptive systems, sug- error or inaccuracy in our work, we will notify the journal editor or gesting that “spatial patterns emerge from, and feed back to affect, the publisher and cooperate with the editor to retract or correct the actions of adaptive individual agents” (Levin, 1998, 2005). In view of paper. the prediction of complexity theory that patterns emerge as epipheno- 10 Image integrity: we didn't enhance, obscure, move, remove, or mena in the inanimate world (e.g., strikingly regular patterning of sand introduce a specific feature within an image. dunes formed by sand grains), it is hard to argue that every self-orga- 11 Clinical trial transparency: not applicable to our article. nized spatial pattern involving biological agents has a functional purpose (in an evolutionary sense). Which patterns confer fitness and Supplementary materials which are simply epiphenomena is a fundamental question. Further examples from a variety of ecosystems (other than mussel beds and Supplementary material associated with this article can be found, in dryland vegetation) displaying spatial self-organization—e.g., ridge- the online version, at doi:10.1016/j.ecocom.2019.01.002. slough pattern in peatlands (Larsen et al., 2007), cypress dome pattern in South Florida (Watts et al., 2014), and fairy cycles References (Tschinkel, 2012)—formed by very different biophysical processes have yet to be examined. A theoretical framework addressing the eco-evo- Andrewartha, HG, Birch, LC, 1986. The Ecological Web: More on the Distribution and lutionary dynamics in spatially self-organized ecosystems and its re- Abundance of Animals. University of Chicago Press. Bekker, MF, Malanson, GP, 2009. Linear forest patterns in subalpine environments. Prog. lationship with ecosystems as complex adaptive systems is needed. Phys. Geogr. 32, 635–653. 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