Indexically Structured Ecological Communities Indexically Structured Ecological Communities Christopher Hunter Lean*y Ecological communities are seldom, if ever, biological individuals. They lack causal boundaries as the populations that constitute communities are not congruent and rarely have persistent functional roles regulating the communities’ higher-level properties. In- stead we should represent ecological communities indexically, by identifying ecological communities via the network of weak causal interactions between populations that unfurl from a starting set of populations. This precisification of ecological communities helps identify how community properties remain invariant, and why they have robust charac- teristics. This respects the diversity and aggregational nature of these complex systems while still vindicating them as units worthy of investigation. 1. Introduction. The gullies of Namadgi National Park seem like distinct ecological communities from the peaks of the Snowy Mountains National Park. Wildflowers are scattered across the subalpine landscape of the Snowy Mountains, punctuated by grizzled snow gums, and introduced brumbies; while Namadgi’s dense gum forests, dominated by red stringybark and scribble gums, line broken granite creek sides holding a diverse assemblage of reptiles and insects. Both of these national parks are of high conservation value, and legislation is built around the need to preserve their unique iden- tities. Yet these two communities are linked within the larger metacommu- nity of the Australian Alps, sharing many species and being connected by forested parks. Despite this, it is assumed that their local populations interact more strongly with each other, leading to the natural conclusion that the pop- ulations in Namadgi are strongly policed in their distribution, abundance, *To contact the author, please write to: Department of Philosophy, Australian National University, 2601 ACT, Australia; e-mail: christopher.lean@anu.edu.au. yThanks to Justin Bruner, Carl Brusse, John Matthewson, Roberta Millstein, Jay Oden- baugh, Ron Planer, Kim Sterelny, and two anonymous reviewers for their feedback on this article. Received January 2017; revised December 2017. Philosophy of Science, 85 (July 2018) pp. 501–522. 0031-8248/2018/8503-0009$10.00 Copyright 2018 by the Philosophy of Science Association. All rights reserved. 501 This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 502 CHRISTOPHER HUNTER LEAN All u and persistence by the other populations of Namadgi; likewise for the pop- ulations in the Snowy Mountains. Combining this causal assumption with the differing description of habitats leads to the seemingly not very radical conclusion that these habitats comprise distinct ecological communities. Ecology studies the distribution and abundance of populations across landscapes and over time. Community ecology often studies the way “local” or spatially congruent interactions within an assemblage result in demo- graphic changes (Leibold et al. 2004). Local ecological communities act as a core unit of investigation for community ecology. Community ecology has long operated with the implicit assumption of “local determinism”: that is, that ecological patterns are primarily explained by the rule-governed inter- action of local populations within a community (Drake 1990; Ricklefs 2008).1 It is thought that these interactions operate within certain boundaries (Roughgarden 1989). Once we identify these boundaries, we can make in- ferences about how the local community polices species’ identity and abun- dance. Therefore, the local interactions and identity of the species in Namadgi distinguish the Namadgi ecological system from the Snowy Mountains eco- logical system. Ecological communities are thought to have discrete boundaries, stable composition, and predictable dynamics over time, and these characteristics allow for inferences to be made from one community to the next. But there have been many dissenting voices within the ecological research tradition who instead argue for ecological individualism, emphasizing that popula- tions generally move around a landscape of their own accord driven by chance and by abiotic factors without being heavily influenced by their local neighbors.2 The implication is that ecological communities are largely ephemeral compositions of populations. This debate drives considerations whether there are law-like regularities in community ecology (see Lawton 1999; Linquist et al. 2016). If ecological communities have shared proper- ties, then we can make robust generalizable inferences about how they act. On the other hand, if assemblages are just collections of largely independent populations, then there will be little robust to say about communities. 1. My description of “local determinism” and “local ecological communities” is derived from the arguments by Robert Ricklefs (2005, 18–21). He argues that Robert Mac- Arthur’s legacy is the conceptual separation of the region species pool and local ecolog- ical communities. Local scale population composition was thought to be explained at this local level by processes such as competition and ecological filtering without refer- ence to the regional level. 2. The scale and stochasticity of the processes that determine the distribution and abun- dance of populations do not necessarily covary. Deterministic processes include species filtering, competition, and mutualism. Stochastic processes include dispersal, speciation, and extinction. We could have stochastic or deterministic processes on both the regional and local ecological scales. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 503 To arbitrate this debate philosophers and biologists have provided an analysis of the conditions for an assemblage—a collection of populations in a space—to be an ecological community. Namely, assemblages should be a biological individual just like an individual organism, population, or lin- eage (Hull 1976; Millstein 2009; Clarke 2013). If an ecological community is a biological individual, then it is the cohesive and distinct entity that local determinism presupposes.3 Kim Sterelny (2006) and Jay Odenbaugh (2007) independently specified the conditions under which an ecological assem- blage is a natural entity, an ecological community. I shall argue that ecological communities so rarely satisfy these condi- tions that we need an alternative framework. Ecological systems are largely aggregations of individual populations that fail to be linked by stable, strong causal interactions. Consequently, they are better described indexically, as causal networks that unfurl from a specific point of reference. This acts to fix the reference of these somewhat unsystematic systems and allows for the identification of the robust parts and robust properties of ecological sys- tems. Indexically specified communities provide a precise account of the iden- tity that allows for inferences to be made between communities. This acts as a third option between the two opposing pictures of ecology: one that treats communities as fictions, or takes an even stronger antirealist position, and the other that treats them as individuals. My view does not, however, dictate that ecological communities can never be biological individuals; there will be limiting cases. But these cases lie so far from the norm that we need a framework that better represents the degree of variation in ecological assem- blages. 2. Communities as Biological Individuals. Ecological communities fea- ture as distinct and countable entities in ecological science and in normative theories about the preservation of the natural environment. One way to es- tablish that a biological entity has these features is to view it as a ‘biological individual’. While biological individuality has become a contested topic in philosophy of biology, with multiple attempts to precisify its description, generally biological individuals are spatiotemporally bound units that exhibit internal cohesion (Hull 1976). This internal cohesion in ecology is expected to be a product of the causal interactions of populations within the commu- nity regulating its overall features. Ecological communities as individuals fea- ture in major hypotheses across the related ecological sciences. And it is this causal and explanatory distinctness that undergirds the normative value of 3. A further required assumption is that the group of individuals must have features in common to support induction. Defining boundaries is the first step to determine the properties possessed by a community. Similarities can then be identified in conspecific communities for inductive reasoning. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 504 CHRISTOPHER HUNTER LEAN All u these communities. This section notes the roles that ecological communities have played in ecology and conservation and then turns to the communities as individuals thesis that Sterelny and Odenbaugh present. Community ecology has produced multiple research programs that posit that there are distinct countable ecological communities. Most famous is Fredrick Clements’s (1916) treatment of ecological communities as super- organisms with a developmental sequence of populations facilitating the es- tablishment of the next population (e.g., grasses releasing nutrients into the soil facilitating larger trees). This process of succession was thought to yield a mature ecosystem that has stable self-preserving system properties (Eliot 2007). While Clements’s superorganismal ecology has fallen by the way- side, many successors have taken up aspects of his program. Both niche the- ory and the diversity-stability hypothesis have relied on an assumption that communities form tight-knit economies with positions that can be filled in- terchangeably by populations (MacArthur 1955; Herbold and Moyle 1986). When the positions in the economy are filled the economy is ‘stable’, ex- plaining the persistence of the assemblage and its resistance to invasion by alien populations. All these theories assume that ecological communities are the right size of object to analyze changes in a population’s abundance and distribution. The local community as a result plays an explanatory role in the ecological science. Ecological communities have been seriously discussed as bearers of nor- mative worth since Aldo Leopold’s (1949) “Land Ethic,” which demanded the extension of ethical concern to ecological communities, not just individ- ual populations. And while many nebulous versions of the relation between ethics and ecological holism have been posited in the following 70 years, ecological communities do play a serious role in conservation science.4 Con- servation is widely taken to have the goal of preserving biodiversity (Soulé 1985). Describing ecological communities as distinct entities also allows them to be individual bearers of biodiversity, and many conservation pro- grams are explicit about their aim to preserve not just the inter- and intra- diversity of lineages but also diversity of kinds of communities. For exam- ple, in the Australian Capital Territory, Blakely’s Red Gum Grassy Woodland is an endangered ecological community that is afforded legal protection. Thus ecological communities appear in conservation decision making as en- tities that are quantifiable and distinguishable. Communities as individuals have played an important role in both the ecological sciences and conservation. But what are the criteria that an assem- blage needs to fulfill to be an individual? Sterelny (2006) and Odenbaugh (2007) present similar accounts, which I condense into a single view. While 4. Millstein (forthcoming) systematically defends Leopold’s “Land Communities” as real scientific entities. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 505 they provide a set of conditions that if fulfilled counts an ecological commu- nity as an individual, they leave it open as to whether any actual ecological community satisfies these conditions. The conditions they present follow. 2.1. Boundaries. Individuals, as spatiotemporal entities composed of interacting subparts, have boundaries. For interacting parts to make a whole there must be strong causal interactions creating internal cohesion within the system and factors that aid its isolation from external influences. The system parts in community ecology are the populations that causally interact, creat- ing feedback loops maintaining local populations and excluding external populations from invading the local system. Sterelny particularly notes that local niche construction is one way populations can maintain an assemblage (2006, 226). Famously, Australian plants including gums, banksias, and mel- aleucas are adapted to fire and facilitate the presence of each other by mak- ing their local environment more fire-prone. Under this conception of bound- aries, ecological communities are bound by interaction strength between populations (Levins and Lewontin 1985). While this does not necessarily mean that populations in the system will be congruent, strong causal inter- action is associated with spatial overlap, so congruence, or at least approx- imate congruence, of community populations is expected. 2.2. Internally Structured. The populations that belong to an ecologi- cal community should act in ways that police the composition and stability of that community, functioning as homeostatic mechanisms for self-maintenance. Interspecific interactions—such as predation, competition, and mutualism— are thought to form a lattice of positive and negative feedback loops, regulat- ing the community and creating stability. When you couple these interactions with stable geographic ranges of the populations, you gain a picture of a stable economy of nature in which there is persistence of local population identity due to the specific roles that these populations play. Internal structure is the product of both feedback loops that act to maintain population identity in an area and the persistence of specific populations playing particular roles in this local community. 2.3. System-Level Properties. If we wish to include local ecological communities in our general scientific ontology, there has to be a reason to talk about communities rather than just talk about the populations that make up communities. There should be predicates and properties that are needed for describing phenomena at the community level. System-level properties are an explanandum to be explained by the assemblage and an explanans for ecological and evolutionary hypotheses. Properties generally discussed on the community level are associated with the maintenance of multispecies in- teraction networks such as food webs (community network structures), the This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 506 CHRISTOPHER HUNTER LEAN All u maintenance of composition identity or aggregative features (emergent com- munity properties), or the various material outputs that the joint assemblage creates (community outputs). Odenbaugh treats system-level properties as necessary for community existence: “species populations form an ecological community just in case . . . they possess a community level property” (2007, 636). He primarily mentions interspecific interactions and feedback loops they create as community-level properties. Sterelny (2006, 221) describes emergent community properties, identifying several candidate emergent prop- erties from the diversity-stability hypothesis such as community population stability and community biomass production. The productivity and abiotic fea- tures ecological communities produce have become an area of keen interest for conservation science. Many ecologists have attempted to justify the preser- vation of ecological communities by appealing to the ‘ecosystem services’— capacities commonly attributed to the community as a whole. These system- level properties feature in ecological explanation, and they are properties of something, namely, a community. 3. Problems with Individuality. According to Sterelny and Odenbaugh, communities are individuals if they have three features: they should be caus- ally bound, they should have internal regulation, and they should have system-level properties. Sterelny represents these criteria hyperdimension- ally, with each criterion occupying an axis, noting that all of them can be more or less instantiated. This is partially true, but these axes are not inde- pendent, as both authors independently note (Maclaurin and Sterelny 2008; Odenbaugh 2016). Internal regulation and boundaries are mutually depen- dent, spatial clustering allows regulatory interaction to be efficacious, and regulation maintains community composition. This implies that if an eco- logical assemblage does not have boundaries with internal regulation, then it is not a biological individual. Equating community identity with a stable self-regulating unit is substantial theoretical commitment; it is an open em- pirical question whether communities self-regulate (Cooper 2003, chap. 3). System-level properties are thought to be the product of this bound and stable community. I aim to sever this relation arguing that communities do not in general have robust boundaries and their internal structure is not as stable as individuality requires; but despite this, ecological systems can have system- level properties. To establish that ecological systems lack the same boundaries and internal structure of biological individuals, consider how we can identify the bound- aries and composition of objects generally (Wimsatt 2007, chap. 9). Simple objects like a granite pebble have quite neat boundaries; there is strong causal discontinuity between the pebble’s interior and exterior. This allows for the unit to act as a whole; that is, when thrown the pebble acts as a single unit, uniformly going in a direction. The various structural and dispositional prop- This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 507 erties are neatly congruent within the pebble. Properties such as tensile strength, electrical conductivity, or crystal structure are all colocated through- out its structure. This is due to there being a fairly simple compositional struc- ture. Compare this with paradigmatic biological individuals. Researching these biological objects requires different theoretical perspectives, or ways of rep- resenting the system. These aid in identifying the differing sets of disposi- tions a system possesses. These are discovered by intervening on the sys- tem’s different structures with different techniques. Think of the difference between the way a developmental biologist and physical biologist inquire into an Arabidopsis. One maps out the sequential developmental pathways that lead to the growth of cells and the other the way in which, for instance, the plant surfaces reflect and capture light. These two scientists will have very different spatial maps of the distribution of properties relevant to their inquiry into that organism. The fact that the two theoretical perspectives have different spatial maps of the plant’s relevant properties indicates that the plant is a complex system. In the case of the Arabidopsis, despite the different perspectives used to un- derstand the plant, all accounts roughly agree on the overall boundaries of the organism itself. This shows that, despite the various subparts of the sys- tem being noncongruent, including its differentiated cells and appendages, the plant as a whole is robust. There is a causal cohesion that holds the entire Arabidopsis structure together (the same for the granite pebble). This is what I contend is lacking in ecological communities. Different points of inquiry into the properties of ecological communities will not yield a congruent structure of the overall system. Instead they yield different networks of causal interaction between populations, which are very sensitive to our initial de- scription of the community. 3.1. Nonrobust Communities. The lack of robust boundaries in ecolog- ical systems is revealed by the differing causal profiles of colocated popula- tions. In the Kosciuszko National Park the distribution and abundance of mountain pygmy possums is causally determined by its predators, foxes, and prey, bogong moths, while the northern corroboree frog population is strongly determined by negative interactions with niche-constructing hoofed animals. Despite being apparently part of the same local community, the causal profiles of what populations are relevant to them will be quite different. Each popula- tion will belong to an ecological system consisting of just those populations to which they are counterfactually sensitive. Borrowing from Bill Wimsatt’s (2007, chap. 9) description of complex systems, I argue an ecological community is an individual when it is descrip- tively robust: if multiple different streams of evidence describe a congruent structure. If we claim that a local assemblage of populations belong to the This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 508 CHRISTOPHER HUNTER LEAN All u same individual, then those populations should map into a single ecological system and describe the same patterns of causal relationships between pop- ulations. The discordance between descriptions of ecological systems can be seen in both the spatial discordance between population ranges and the causal discordance. If populations have causal interaction profiles that describe the same eco- logical community with congruent boundaries and the same subparts, then we have discovered a descriptively robust individual. The problem is that colocated populations often belong to radically different ecological systems. The reason is that causal relations in ecology are often asymmetrical and population distributions rarely spatially coincide. Evidence of the spatial dis- cordance of different populations has been developed since the 1950s with Robert Whittaker’s (1967) ‘gradient analyses’ being the first step toward re- jecting the idea that ecological communities comprise neatly congruent pop- ulations. Whittaker graphed the abundance of different populations along abiotic gradients finding that populations occupy separate unique ranges rather than clustering into discrete communities. Since then Whittaker’s findings have been heavily contested, with some going as far as to say that his data support the opposite conclusion (Wilson, Agnew, and Sykes 2004). But considerably more evidence has emerged, particularly through biogeographic research, showing the lack of spatial congruence between populations. Paul Colinvaux’s (2007) research displays that populations within the Amazon have historically moved independently in response to climate change. With the increasing availability of biogeo- graphic data, the independent nature of population ranges is something that we can check ourselves.5 Indeed, Dan Simberloff (1982) famously declared that ecological communities were not real in the way species are real, as pop- ulations have continuous distributions over their ranges and species bound- aries do not coincide. When these conditions are violated, he claims, it is due to discontinuity in the abiotic environment. The explanatory importance of community boundaries is debated. Historically they were very important to the projects outlined by G. E. Hutchinson (Odenbaugh 2007). But they ap- pear to be not as central to modern community ecology, playing a more mod- est role (see Yarrow and Marín 2007). Ecological systems are also not causally cohesive as change in one pop- ulation will often not influence other local populations in a consistent way. The reason is that populations in a community often have asymmetrical and intransitive causal relations. Asymmetrical causal relations are called com- mensalist (0, 1) and amensalist (0, 2), and their impact on food web stabil- ity is an ongoing area of research (e.g., Mougi 2016). Intransitivity is equally well studied with populations existing in rock-paper-scissors relations (e.g., 5. See the Atlas of Living Australia (http://www.ala.org.au/). This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 509 Kerr et al. 2002). As a result local ecological populations rarely form equiv- alence relations in which the populations that form a community are reflex- ive, symmetrical, and transitive with respect to each other (Godfrey-Smith 2008). Causal networks that lack equivalence relations do not form strongly bound groups that respond in unified ways. Populations, therefore, often have asymmetrical causal relations and non- congruent boundaries. As there is no ecological community we can imme- diately identify a priori, we need to study populations to identify an ecolog- ical community. For there to be a distinct and robust ecological community, a set of populations will have to act as a causally cohesive unit. To identify whether populations are part of the same causally cohesive unit, we would intervene on them and see whether the other populations are also affected and vice versa. But when there are asymmetrical relations between popula- tions and noncongruent boundaries, populations do not form causally co- hesive units. Different causal communities appear given different starting points. As a result, ecological boundaries are deeply dependent on the par- ticular populations we are interested in, the populations that we causally start with. This idea that ecological boundaries are relative to populations of in- terest is not new; it has previously been defended by Steven Peck, who states that we must “recognize that [ecological] borders are always relative to spe- cies or groups of them” (2009, 275). Causal relations determine spatial relation, and spatial relations can deter- mine the strength and structure of causal relationships. Consider the factors relevant to a population of spotted quolls compared to their occasional prey, greater gliders. Individual quolls roam over home ranges up to 3,500 hect- ares moving between habitat fragments via wildlife corridors, while a glider’s home range is only 2 hectares and is locked within a local habitat fragment. Unless there is a very strong counterfactual dependence between these two populations, the network of populations relevant to the quolls will be radically different from that of the gliders, as quolls interact with populations that in- tersect with their large home ranges. Further, due to the radically different ranges and population densities, there is a strong asymmetry between these populations. Differential changes in a local glider population are unlikely to affect the quoll population because the quoll’s range would include several glider populations as well as other prey since they are generalist predators. However, differential changes that increase the quoll population would af- fect the glider population as increased predation can have large impacts on small local populations. This creates an asymmetry: intervention on glid- ers has little impact on quolls but intervention on quolls significantly affects gliders. Consequently, population boundaries radically differ, and the causal rela- tions between populations are often asymmetrical and intransitive. When both these conditions are met, congruent boundaries are rare, and identifying This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 510 CHRISTOPHER HUNTER LEAN All u the population network, and the space that network occupies, will be highly dependent on the initial choice of referent. Varying the starting population will yield radically different descriptions of the ecological community. 3.2. Robust Explanation in Nonrobust Systems. The lack of ecological community boundaries could be taken to indicate that we need to adopt a Gleasonian view of ecology and reduce all ecological explanation to the com- ponents of these systems, the populations, and their abiotic environment (Gleason 1926). I resist this conclusion by providing some ways in which complex systems, which do not display the cohesion of individuals, can still require higher-level, or compositional, explanation. Local communities appear to have clusters of stably interacting popula- tions or consistent abiotic outputs that need to be explained. Such outputs are often not just the simple aggregation of component populations’ actions. Diverse local species assemblages can have nonlinear ecosystem outputs. Combinations of populations nonadditively result in explosive combustion in forest fires or retain water in the understory (Michel et al. 2012; Van Al- tena et al. 2012). Further, the statistical aggregation of the actions of local populations can have system-level effects such as stabilizing ecological out- put by statistical averaging effects, biological insurance, and sampling ef- fects (Bryant 2010). Community-level properties as a result appear to be ubiq- uitous in ecological systems even if there are no clear boundaries for these systems and the internal composition is unstable. I describe two types of ex- planatory robustness that can help sort through the heterogeneous structure of ecological assemblages to find the parts of these loose systems that con- tribute to these system-level features. Explaining ecological communities is difficult because of their heteroge- neous composition (Matthewson 2011). They are heterogeneous systems as they are composed of many different populations, which vary phenotypically between each other and to a less extent internally. Each component popula- tion of an ecological community can act differently: a brush-tail possum pop- ulation acts differently than a magpie population, and these populations can vary in composition and density area to area. Heterogeneous features of the populations and varying community compositions allow for many to many causal relations. Within any area we find populations interacting, even if of- ten only weakly, with many other populations. For us to explain the action of such systems we need a way of sorting through this heterogeneous compo- sition to identify the parts that contribute to an emergent property of the sys- tem or an output of the overall system. We can explain the system-level properties of these heterogeneous sys- tems by machine robustness and ensemble robustness. Machine robustness occurs when we explain the outputs of a system through describing a causal chain of parts in the system that sequentially cause changes in each other This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 511 bringing about this output (Levy 2014). The parts that produce this output are each stable, in both their properties and relative location, and are persis- tent in the system and unlikely to be perturbed. As a result of the stability and persistence of relevant system parts, the outputs of the system are robust. Complex systems made of heterogeneous parts can be explained by machine robustness. Think of an Airbus A380: the parts of the plane are quite varied, and the output of staying in the air is fortunately quite robust as by and large each individual part of the plane is persistent and stable in its effect and lo- cation (Elliot-Graves 2016). Alternatively, we can explain the output of compositionally complex sys- tems by ensemble robustness. Ensemble robustness occurs when we have many different causal actors that can fill the same functional role in the sys- tem bringing about system-level properties or outputs. These types of expla- nation often feature overdetermination; if one subpart of the system did not bring about the system-level feature, then another would. Ensemble robust- ness occurs when the subparts are similar. For example, steam being forced out of the top of a kettle is a product of the collision of many different water molecules. But ensemble robust outputs do not require the components bringing about the effect to be exactly the same. All that is required is func- tional similarity; the same effect can be reached by extremely heterogeneous actors. To use an ecological example, gum trees can be pollinated by ex- tremely taxonomically and anatomically varied populations such as pygmy possums, bees, ants, and honeyeaters (birds).6 Ecology aims to explain how populations and their interactions result in system-level properties such as diversity, stability, or ecological services, for example, water retention and biomass production. Local determinism sup- poses that stable relationships between persistent populations produce these properties; stable internal structure produces system-level properties. Expla- nations of this type are machine robust: the system-level property is a result of a particular causal sequence of interactions between persistent parts. These can be serial interactions or, alternatively, allow for feedback. Systems that are organized in this manner and display complex behavior are required to be modular. For highly persistent and stable parts to act in multiple ways, there needs to be some way of introducing structural manipulability, and modularity is the common way this is done. For example, the composition of a brick is stable and persistent, but there are not too many complex actions a brick can do. The Airbus A380 also has stable parts in persistent relation- ships, but there are degrees of freedom introduced into the actions of the plane, for example, by having modular structures like wing flaps, which are able to move up and down on their hinges. Modularity creates boundaries 6. Functional similarity comes in degrees. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 512 CHRISTOPHER HUNTER LEAN All u in systems, and if ecological communities are to be bound, we would expect modular machine robust structures. The assumption of persistent stable relationships in ecological commu- nities is problematic as populations are often highly transient. In one study of 100 biomes across earth, 75% of these systems had at least one in 10 spe- cies disappear locally per decade (Dornelas et al. 2014). This is often cou- pled with little change in regional diversity as populations simply shift their distribution across the larger landscape (Thuiller et al. 2007). This is further evidence for those who believe that local ecological communities are the wrong scale for law-like generalities in ecology (Ricklefs 2008; Lean and Sterelny 2016). They claim that regional patterns better explain the local distribution and abundance of organisms than local patterns that are ephem- eral and stochastic. These views explicitly reject the idea that local commu- nity identity is primarily maintained by internal composition. Despite the highly aggregational quality of ecological systems, ecologi- cal community properties are not uniformly a product of ensemble robust- ness; specific populations are sometimes necessary for ecological output. Keystone species, which have disproportionate impacts on assemblage com- position, function like mechanisms with particular populations playing a necessary and causally specific role in maintaining whole system features. The importance of keystone species is controversial, with some ecologists pressing that there are not such strong relationships between single popula- tions and assemblage features (Mills, Soulé, and Doak 1993). But there is strong evidence that in some systems particular populations do play strong roles in regulating a cluster of populations in their assemblage (Ripple et al. 2001). Classic cases of this are the strong top-down effect of apex predators suppressing mesopredators and herbivore populations permitting diversity lower in the food chain. We see evidence of this in cases such as the reintro- duction of wolves to Yellowstone National Park and dingoes suppressing fe- ral cat populations in Australia. Predators can cause a local system’s species composition to be more deterministic as they police the identity of the local inhabitants. This leads to similarity in systems with predators compared to those that lack predators, whose composition is more subject to stochastic processes (Chase et al. 2009). Given this evidence, we should think of local ecological communities as highly unsystematic systems; they lack clear boundaries and persistent inter- nal identity, but they do have robust parts and robust system outputs via the variant aggregative interactions of their constituents. Most ecological sys- tems will sit somewhere between the extremes of machine robustness and ensemble robustness. Some will not be robust at all. Both forms of robust- ness come in degrees. We can ask, how much redundancy is in the system? How similar are the parts that achieve a robust effect? And how persistent are these parts? This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 513 Any account of ecological community identity needs to be able to identify explanatorily important properties and identify the components of the sys- tem that produce these properties. This is difficult as population networks will not in general be congruent over different choices of starting population as small changes in initial focal population can result in quite a different net- work. But ecological communities are still causal systems. Indexical com- munities describe communities via the network of causal interactions be- tween populations and provide a way to represent their causal structure. This methodology aims to do the diversity of ecological causal structure credit and identify the salient features for explanation. 4. Indexical Communities. On a first pass of the philosophy of ecology literature, accounts of ecological communities appear to split between treat- ing populations as largely independent of each other and describing them within an individuality framework. There are, however, other options that sit between these extremes. I consider and expand Sterelny’s (2006) ‘indexical communities’ as a contrasting framework to ecological individuality. My ac- count of ecological communities supplements and develops indexical com- munities as described by Sterelny by providing the conceptual apparatus to identify robustness and utilizing the Woodwardian interventionist frame- work to fix the reference of the causal system involved (Woodward 2005). 4.1. Simple Indexical Communities. Simple indexical communities are ecological units that aim to describe the conditions that affect the demo- graphics of single populations. Indexically described communities are one of the most useful and utilized ecological techniques in conservation sci- ence. To preserve the critically endangered hairy nosed wombats, we need to know how much native grass and how many tubers they eat, what is an unusual parasite load, and how to separate them from wild dog populations and competing grazers. These populations are indexed to the wombat pop- ulation as they have a causal impact on them. This framework has become commonplace due in part to conservation funding being directed to indi- vidual species preservation. This is due to government funding entering con- servation from Endangered Species Act legislation and nongovernment funding being raised by appealing to the public’s love of charismatic mega- fauna such as blue whales, giant pandas, and bald eagles. Conservation sci- ence as a result often aims to find the conditions that lead to the preservation of a focal population. These simple indexical communities are not thought to be very informa- tive for community-level properties as they are constructed with limited ep- istemic aims, that is, explaining the influences on a single population. Due to the limited scope of such causal units, they remain silent on certain, hopefully generalizable, community-level features such as the relationship between di- This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 514 CHRISTOPHER HUNTER LEAN All u versity and stability (Sterelny 2006, 227). Further, it is thought that informa- tion about one indexical community is difficult to apply to other assemblages due to the apparent limited nature of their scope and their heterogeneity. We can rectify these problems by building into indexical communities the means for identifying machine robustness and ensemble robustness when they are present. This is done by intervening on communities, starting from multiple dif- ferent populations of interest to identify robust community features. The aim is to find what community-level properties the populations contribute to, be they community outputs, boundaries, or causal networks. By intervening on different populations, treating them as nodes in a causal network, we can identify which relations in an assemblage either are highly central, acting as a causal hub, or have strong causal effects. Once we identify which causal re- lations are relevant, we map where these causal actors are distributed geo- graphically, which is the information needed to identify the spatial bound- aries of the community. The innovation here is that by using multiple starting points, we can build in robustness and avoid the explanatory fragility of indexical communities built around a single population. Section 4.2 will describe the procedure for describing an indexical community built from a starting set of populations. Section 4.3 provides a guide for what populations can or should be used for this starting set. 4.2. Identifying Indexical Communities. The stepwise procedure for identifying the relevant ecological community appears below (summary 1), but I will elaborate through this section. Take the starting set of populations and identify the indexical community for each individual population in the set (starting sets are discussed in sec. 4.3). The indexical community for a population is identified by intervention, in which we systematically change the variable representing the population. These interventions can of course take many shapes including removing populations or reducing or increasing a population’s spatial range or altering their accessibility to other popula- tions; but for the purposes of this article, I will use the example of interven- tions being used to alter population numbers. To identify the indexical com- munity of the focal population variable, A, we intervene on populations suspected to be causally efficacious for A. An alternative population vari- able, B, is said to be part of the same community as A, as well as a cause of A, if systematic intervention on B brings about change in A. So if we shoot some feral cats in an area, it will have a positive impact on the population of bilbies due to the causal relevance of the cat population to the bilby popula- tion. These causal relations will be ‘causal influence’ relations as there are continuous values the exogenous population variable can take, and this al- lows for modulation of the response variable. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 515 Once we identify that a population variable, say B, has causal influence on the focal population, A, we can ask whether intervention on populations that affect B also have ‘downstream’ effects on A. If so, then that population is also part of the community. For example, if population C causally influences B to the extent that the variable change it yields in B causally affects A, then C is part of A’s indexical community. So if in a region dingoes suppress cats and cats suppress bilbies, more dingoes will mean more bilbies. Each pop- ulation node introduced between the focal population and a population of interest will necessarily reduce the counterfactual relationship between the distant variables. This process yields a directed graphical map of the causal network in- dexed to population A. We repeat this procedure for all the populations in the starting set. The different causal maps built from each population in the starting set are then compared. All the populations that causally contribute to a starting population are counted as part of the community. The scope of the boundaries of these maps can be tweaked by varying the strength of the causal effect required for inclusion (Levins and Lewontin 1985). By setting this parameter moderately high we avoid ecological holism, where each in- dexical community has numerous nodes and, as a result, each indexical com- munity will overlap each other. Actual intervention will sometimes be problematic; it is often difficult or downright dangerous to reduce or increase population sizes. Further, it can be difficult to get accurate records of the changes in population size. Inter- ventionist theories of causation have long been troubled by the problem of ‘actual’ intervention; for example, if we are not willing or able to intervene on the moon, can we know it causes the tides (Woodward 2016)? In the eco- logical case, natural experiments can be used to infer and model casual rela- tions as populations repeatedly move in and out of areas as they cycle a larger geographic region (see sec. 3.2). Humans repeatedly intervene on communi- ties by reducing populations or introducing invasive species in fairly system- atic ways. More scientific interventions are preferable, with Robert Paine (1992) providing an early archetype; he made repeat interventions to identify the ‘interaction strength’ of populations in an intertidal rock pool. As such, practical limitations make data collection difficult but not impossible. Once we have directed causal maps from the different populations in the starting set, we can compare their causal structure. The comparison of causal maps is done in two ways. The first is identifying whether populations, the nodes of these maps, sit within the same set of causal relations in strength and direction. This can identify stable causal clusters of populations, which act cohesively. Population network structures that appear in the directed graphs from multiple different indexed populations are robust in Wood- ward’s sense (2005, chap. 6): something to be robust according to Woodward This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 516 CHRISTOPHER HUNTER LEAN All u if a wide range of initial conditions identify the same event. Here the event is a particular causal relationship between populations. By varying the local populations we intervene on, we vary the initial conditions of the system. Ro- bustly connected populations are ecologically important, often acting as key- stone species, and playing a role in maintaining the population network struc- ture. Another way of displaying the indexical community is mapping the pop- ulations that causally contribute spatially. This allows for a visual depiction of the actual physical space that the causal processes of the community act over; it acts as an anatomy of the ecological community. By mapping the spatial arrangement of populations that causally contribute, we can also see if the community is ‘descriptively robust’ in Wimsatt’s sense (Wimsatt 2007, chap. 9). A community is robust according to Wimsatt’s view if multiple dif- ferent ‘theoretical perspectives’ identify objects that are spatially congruent. By varying the populations that we are interested in, we vary the perspective we inquire into the system with. If the different causal systems identified from different populations occupy the same space, they are robust in Wim- satt’s sense. se sub Summary 1. Procedure for identifying indexical communities: ject t Define the starting set of populations and/or a system-level property (e.g., ecosystem output) that the causal relations are to be indexed to. a. If a system-level property, then identify the set of populations that contribute to the property. Identify the populations that are causally salient for the set of pop- ulations via intervention. Overlay the different networks of counterfactual dependencies from the specific populations. If multiple interventions, pick out the same connection; these are the robust relationships in a community. i. This o Un ii. iii. iv. 4.3. The Starting Set. So what determines the starting set of popula- tions? This is in part researcher or local community stakeholder interest de- fined, but there are some obvious candidates described below. Having the initial scope of systems determined by research interest better represents the practice of scientists and the differing intuitions around ecological com- munities. While many scientists and the public are interested in ecological communities, they clearly differ in what they are referring to. This account of communities has the flexibility to make precise the many different notions content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM iversity of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 517 of community at play in these different discourses. Here are some different notions of ecological communities that can be described through varying the starting set. Local Ecological Communities. If we wish to determine whether a local assemblage is a unified and integrated community, we would look at the indexical community built around a set of local populations. By identifying the network of populations that emanate out of cohabiting populations, we can see to what extent this local ecological community is a causally cohesive unit. This also acts to identify the ecological bounds of otherwise arbitrary units. National parks are usually bound by geographically arbitrary borders, and we may be interested in locating the causal boundaries of the ecological assemblage that inhabits this space. If we are interested in the ecological boundaries of the assemblages inhabiting a region of the Namadgi National Park, we take a census of the local populations in that region and map out the causal structure they are related to. Community-Level Properties. Alternatively, we can look at community- level properties or outputs by starting with the set of populations that are thought to contribute to this community-level feature. Often this is a partic- ular output of the ecological community such as water filtration around a lake. Man-made lakes produced by damming have ecological systems main- tained around their border for this role. The Warragamba Dam supplies Syd- ney’s water, and the Yerranderie State Conservation Area protects this water supply from contamination. If we wish to identify the relevant populations in the Yerranderie State Conservation Area to maintaining this ‘ecosystem ser- vice’, we identify the populations that affect this output and the population relevant to the maintenance of those populations. Other higher-level proper- ties can similarly be assessed. For instance, individual populations can have disproportionate impacts on species diversity, maintaining many populations through critical services. By varying the populations in indexical communi- ties, we can see who contributes to this higher-level feature. Biodiverse Communities. Particularly important kinds of communities are those that conserve biodiversity. Often communities are conserved by protecting populations indexically relevant to some charismatic fauna. But we may also wish to specifically target preserving the populations that con- stitute biodiversity. There are many different biological features that can rep- resent biodiversity, including species functions, morphology, phylogenetic diversity, and so forth. But for whatever features count toward biodiversity, we can identify the combination of populations that best represent these fea- tures and therefore represent biodiversity in a particular area. Then using the This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 518 CHRISTOPHER HUNTER LEAN All u indexical communities procedure, we can find the ecological features rele- vant to the preservation of biodiversity. This causal structure is critical to minimize biodiversity loss from secondary extinctions (Dunne and Williams 2009). Phenomenological Communities. People experience ecological commu- nities as hikers, birders, hunters, and participants within these systems. En- vironmentalists and the public often have an interest in preserving particular assemblages that are familiar from their experience of the wild. Phenomeno- logical communities are the midsized ecological objects that people think of when they are asked if we should preserve ecosystems. But these entities are referentially underdetermined; people struggle to describe the particular fea- tures of this system in a precise way or give an account of their extent past arbitrary boundaries. We can clarify the description of phenomenological communities through using indexical communities. Typically phenomeno- logical communities are described through reference to assemblages includ- ing charismatic mammals, audible birdlife, visually stimulating angiosperms, and imposing trees. To fix the reference of such local assemblages we include in the starting set the phenomenologically prominent populations in a local area. For example, if you want to find the community of a blue gum forest, you include blue gums, lyrebirds, and waratahs and identify the populations relevant to them. By then building in the populations that maintain the expe- rientially salient aspects of wildlife, we can identify the condition for preserv- ing the environment the public immediately desires. This directly speaks to the practice of conserving ecological communities described by legislation. The Blakely’s Red Gum Grassy Woodland is a legally protected endangered community.7 This community is identified by a list of tree species and under- story plants that are “commonly associated” with the community. Indexical communities are able to represent this unique assemblage and the way the law describes it, indexed to a set of populations. I have no doubt that there will be other ways of and reasons for describing other starting sets for indexical communities. By allowing the starting set to be determined by the interested parties, we are able to tailor the indexical community to fulfill both the epistemic and normative roles that community ecology and conservation science require. This is a significant step forward; ecological communities as they are described by ecological sciences and the public appear to diverge, but the presented conceptual system allows for us to both describe their differences and unify them in a single explanatory sys- tem. 7. See http://www.environment.gov.au/epbc/publications/white-box-yellow-box -blakelys-red-gum-grassy-woodlands-and-derived-native-grasslands. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 519 5. Assessing Indexical Communities. Built into the indexical community methodology is the means of assessing an ecological community in several ways. First, for the ontological question of whether communities are real, in- dexical communities provide an answer. It is only when the same causal structure appears from multiple starts and has robust boundaries that we have a robust ecological community. It is, however, more likely that we will find that we have only partial overlap between the causal maps. This acts to identify the descriptively robust subsystems within the community. Conse- quently, this framework provides a fine-grained way to identify the extent to which a particular local ecological community is a system that acts like an individual, an organism, or an aggregate, like gas particles heating in a bea- ker. If there are no causal connections between the starting populations, then this is not a unitary community. So it acts not just as a descriptive tool but also as an existence test. Depending on referent choice, there can be multiple precisifications of a unitary community or none. The robustness of the causal structure of populations allows for us to ex- plain how system-level properties are produced. It provides a bridge be- tween the study of single populations and the resilient generalizations in community ecology catalogued by Linquist et al. (2016). To explain how the assemblage produces a particular system-level property, be it the resil- ience of community composition or a community output like fire likelihood, we need to identify which counterfactual interventions affect that system- level property. Multiple interventions on the system from different indexed populations identify what affects the system-level property. The primary question is whether system-level property invariance is a product of popula- tion network structure invariance or compositional invariance. Or to say it in another way, are these features machine robust or ensemble robust? Machine robust parts of ecological networks are descriptively robust with multiple starting points identifying the causal structure between particular populations of a fixed identity. But weak aggregational interactions are ex- tremely common, producing system-level phenomena through numerous causal relations of modest strength. The actual causal actors involved in pro- ducing these phenomena can be hard to identify as many different parts couldbe contributingto thesystem-level property. To understandtherelation- ship between aggregational systems and system-level properties we need to fix the identity of the system in question. Indexical communities provide a precise way to refer to such weak “systems,” which provides a guide for fur- ther research into the relations between populations and system-level proper- ties. Some ecological assemblages may not feature any robust causal relations or outputs. In these cases they will not be machine or ensemble robust. These systems are better explained at the level of populations, with little reference to their local neighbors. In these cases ecological communities are not vin- This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). 520 CHRISTOPHER HUNTER LEAN All u dicated as units worthy of unique investigation in themselves. Instead we would be better off studying autoecology, the dynamics of particular popu- lations. Finally, the representation of ecological communities with this causal net- work structure has further advantages. By describing communities using a causal graph network description, we open them up to a range of formal methods of assessment. Robust networks of populations form modules or modular network structures. Strongly covarying clusters of populations make a system more bounded and can account for particular system outputs. For- mal methods familiar to the social sciences like the Girvan-Newman algo- rithm (2002) can quantify such structures identifying modular grouping and boundaries in complex systems. But there are also rich tools available for de- scribing the causal structure of ecological communities within the ecological sciences particularly from food web theory and mutualism networks. Peter Morin’s (2011, chap. 6) introduction to food web theory provides a wealth of these formal tools with measures for a system’s connectance, linkage den- sity, and compartmentalization. This is all to say that indexical ecological communities open up modes and opportunities for assessing communities, which are not available to bi- ological individuals. I do not claim that no assemblages will ever be a bio- logical individual. But these cases will be rare. The majority of communities will not, and these are still entities that play central roles in ecology and con- servation. We need a way to discuss and inquire into these ecological sys- tems that does not treat individuality as the natural endpoint of all complex biological interactions. There is more to biology than just the study of indi- viduals, and this proposal gives an alternative framework to describe such complex biological systems. REFERENCES Bryant, Rachael. 2010. “What If Ecological Communities Are Not Wholes?” In The Environment: Philosophy, Science, and Ethics, ed. W. Kabasenche, M. Oourke, and M. Slater. Cambridge, MA: MIT Press. Chase, Jonathan M., Elizabeth G. Biro, Wade A. Ryberg, and Kevin G. Smith. 2009. “Predators Temper the Relative Importance of Stochastic Processes in the Assembly of Prey Metacom- munities.” Ecology Letters 12 (11): 1210–18. Clarke, Ellen. 2013. “The Multiple Realizability of Biological Individuals.” Journal of Philosophy 110 (8): 413–35. Clements, Frederick E. 1916. Plant Succession: An Analysis of the Development of Vegetation. Washington, DC: Carnegie Institution of Washington. Colinvaux, Paul A. 2007. Amazon Expeditions: My Quest for the Ice-Age Equator. New Haven, CT: Yale University Press. Cooper, Gregory J. 2003. The Science of the Struggle for Existence: On the Foundations of Ecol- ogy. Cambridge: Cambridge University Press. Dornelas, Maria, Nicholas J. Gotelli, Brian McGill, Hideyasu Shimadzu, Faye Moyes, Caya Sie- vers, and Anne E. Magurran. 2014. “Assemblage Time Series Reveal Biodiversity Change but Not Systematic Loss.” Science 344 (6181): 296–99. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1111%2Fj.1461-0248.2009.01362.x&citationId=p_9 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.5840%2Fjphil2013110817&citationId=p_10 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1126%2Fscience.1248484&citationId=p_14 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.5962%2Fbhl.title.56234&citationId=p_11 INDEXICALLY STRUCTURED ECOLOGICAL COMMUNITIES 521 Drake, James A. 1990. “Communities as Assembled Structures: Do Rules Govern Pattern?” Trends in Ecology and Evolution 5 (5): 159–64. Dunne, Jennifer A., and Richard J. Williams. 2009. “Cascading Extinctions and Community Col- lapse in Model Food Webs.” Philosophical Transactions of the Royal Society of London, B: Biological Sciences 364 (1524): 1711–23. Eliot, Christopher. 2007. “Method and Metaphysics in Clements’s and Gleason’s Ecological Expla- nations.” Studies in History and Philosophy of Science, part C, Studies in History and Philos- ophy of Biological and Biomedical Sciences 38 (1): 85–109. Elliott-Graves, Alkistis. 2016. “The Problem of Prediction in Invasion Biology.” Biology and Phi- losophy 31 (3): 373–93. Girvan, Michelle, and Mark E. J. Newman. 2002. “Community Structure in Social and Biological Networks.” Proceedings of the National Academy of Sciences 99 (12): 7821–26. Gleason, Henry A. 1926. “The Individualistic Concept of the Plant Association.” Bulletin of the Torrey Botanical Club, 7–26. Godfrey-Smith, Peter. 2008. “Varieties of Population Structure and the Levels of Selection.” British Journal for the Philosophy of Science 59 (1): 25–50. Herbold, Bruce, and Peter B. Moyle. 1986. “Introduced Species and Vacant Niches.” American Naturalist 128 (5): 751–60. Hull, David L. 1976. “Are Species Really Individuals?” Systematic Biology 25 (2): 174–91. Kerr, Benjamin, Margaret A. Riley, Marcus W. Feldman, and Brendan J. M. Bohannan. 2002. “Lo- cal Dispersal Promotes Biodiversity in a Real-Life Game of Rock-Paper-Scissors.” Nature 418 (6894): 171–74. Lawton, John H. 1999. “Are There General Laws in Ecology?” Oikos 84 (2): 177. Lean, Christopher H., and Kim Sterelny. 2016. “Ecological Hierarchy and Biodiversity.” In The Routledge Handbook of Biodiversity, ed. J. Garson, A. Plutynski, and S. Sarkar. London: Routledge. Leibold, Mathew A., Marcel Holyoak, Nicolas Mouquet, Priyanga Amarasekare, Jonathan M. Chase, Martha F. Hoopes, and Michel Loreau. 2004. “The Metacommunity Concept: A Frame- work for Multi-scale Community Ecology.” Ecology Letters 7 (7): 601–13. Leopold, Aldo. 1949. A Sand County Almanac. New York: Oxford University Press. Levins, Richard, and Richard C. Lewontin. 1985. The Dialectical Biologist. Cambridge, MA: Har- vard University Press. Levy, Arnon. 2014. “Machine-Likeness and Explanation by Decomposition.” Philosophers’ Im- print 14 (6). Linquist, Stefan, T. Ryan Gregory, Tyler A. Elliott, Brent Saylor, Stefan C. Kremer, and Karl Cottenie. 2016. “Yes! There Are Resilient Generalizations (or ‘Laws’) in Ecology.” Quarterly Review of Biology 91 (2): 119–31. MacArthur, Robert. 1955. “Fluctuations of Animal Populations and a Measure of Community Sta- bility.” Ecology 36 (3): 533–36. Maclaurin, James, and Kim Sterelny. 2008. What Is Biodiversity? Chicago: University of Chicago Press. Matthewson, John. 2011. “Trade-Offs in Model-Building: A More Target-Oriented Approach.” Studies in History and Philosophy of Science A 42 (2): 324–33. Michel, Pascale, William G. Lee, Heinjo J. During, and Johannes H. C. Cornelissen. 2012. “Species Traits and Their Non-additive Interactions Control the Water Economy of Bryophyte Cush- ions.” Journal of Ecology 100 (1): 222–31. Mills, L. Scott, Michael E. Soulé, and Daniel F. Doak. 1993. “The Keystone-Species Concept in Ecology and Conservation.” BioScience 43 (4): 219–24. Millstein, Roberta L. 2009. “Populations as Individuals.” Biological Theory 4 (3): 267–73. ———. Forthcoming. “Is Aldo Leopold’s ‘Land Community’ an Individual?” In Individuation across Experimental and Theoretical Sciences, ed. O. Otávio Bueno, R. Chen, and M. Fagan. Oxford: Oxford University Press. Morin, Peter J. 2011. Community Ecology. 2nd ed. Oxford: Wiley Blackwell. Mougi, Akihiko. 2016. “The Roles of Amensalistic and Commensalistic Interactions in Large Eco- logical Network Stability.” Scientific Reports 6 (July): 29929. Odenbaugh, Jay. 2007. “Seeing the Forest and the Trees: Realism about Communities and Ecosys- tems.” Philosophy of Science 74 (5): 628–41. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM All use subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2F0169-5347%2890%2990223-Z&citationId=p_15 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2F0169-5347%2890%2990223-Z&citationId=p_15 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2Fj.shpsa.2010.11.040&citationId=p_34 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1073%2Fpnas.122653799&citationId=p_19 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1111%2Fj.1461-0248.2004.00608.x&citationId=p_27 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F686809&citationId=p_31 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1098%2Frstb.2008.0219&citationId=p_16 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F686809&citationId=p_31 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1098%2Frstb.2008.0219&citationId=p_16 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.2307%2F2479933&citationId=p_20 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.2307%2F2479933&citationId=p_20 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1111%2Fj.1365-2745.2011.01898.x&citationId=p_35 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1038%2Fnature00823&citationId=p_24 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.2307%2F1929601&citationId=p_32 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2Fj.shpsc.2006.12.006&citationId=p_17 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2Fj.shpsc.2006.12.006&citationId=p_17 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1093%2Fbjps%2Faxm044&citationId=p_21 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1093%2Fbjps%2Faxm044&citationId=p_21 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.2307%2F1312122&citationId=p_36 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1038%2Fsrep29929&citationId=p_40 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.2307%2F3546712&citationId=p_25 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1007%2Fs10539-015-9504-0&citationId=p_18 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1007%2Fs10539-015-9504-0&citationId=p_18 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F284600&citationId=p_22 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F284600&citationId=p_22 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1162%2Fbiot.2009.4.3.267&citationId=p_37 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F525609&citationId=p_41 522 CHRISTOPHER HUNTER LEAN All u ———. 2016. “Conservation Biology.” In The Stanford Encyclopedia of Philosophy, ed. Edward N. Zalta. Stanford, CA: Stanford University. Paine, Robert T. 1992. “Food-Web Analysis through Field Measurement of per Capita Interaction Strength.” Nature 355:73. Peck, Steven L. 2009. “Whose Boundary? An Individual Species Perspectival Approach to Bor- ders.” Biological Theory 4 (3): 274–79. Ricklefs, Robert E. 2005. “Phylogenetic Perspectives on Patterns of Regional and Local Species Richness.” In Tropical Rainforests: Past, Present, and Future, ed. E. Bermingham, C. Dick, and C. Moritz. Chicago: University of Chicago Press. ———. 2008. “Disintegration of the Ecological Community.” American Naturalist 172 (6): 741– 50. Ripple, William J., Eric J. Larsen, Roy A. Renkin, and Douglas W. Smith. 2001. “Trophic Cascades among Wolves, Elk and Aspen on Yellowstone National Park’s Northern Range.” Biological Conservation 102 (3): 227–34. Roughgarden, Jonathan. 1989. “The Structure and Assembly of Communities.” In Perspectives in Ecological Theory, ed. J. Roughgarden, R. May, and S. Levin, 203–26. Princeton, NJ: Prince- ton University Press. Simberloff, Daniel. 1982. “A Succession of Paradigms in Ecology: Essentialism to Materialism and Probabilism.” In Conceptual Issues in Ecology, ed. Esa Saarinen, 63–99. Amsterdam: Springer. Soulé, Michael E. 1985. “What Is Conservation Biology? A New Synthetic Discipline Addresses the Dynamics and Problems of Perturbed Species, Communities, and Ecosystems.” BioSci- ence 35 (11): 727–34. Sterelny, Kim. 2006. “Local Ecological Communities.” Philosophy of Science 73 (2): 215–31. Thuiller, Wilfried, Jasper A. Slingsby, Sean D. J. Privett, and Richard M. Cowling. 2007. “Stochas- tic Species Turnover and Stable Coexistence in a Species-Rich, Fire-Prone Plant Community.” PloS One 2 (9): e938. Van Altena, Cassandra, Richard van Logtestijn, William Cornwell, and Hans Cornelissen. 2012. “Species Composition and Fire: Non-additive Mixture Effects on Ground Fuel Flammability.” Frontiers in Plant Science 3:63. Whittaker, Robert Harding. 1967. “Gradient Analysis of Vegetation.” Biological Reviews 42 (2): 207–64. Wilson, J. Bastow, Andrew D. Q. Agnew, and Martin Sykes. 2004. “Ecology or Mythology? Are Whittaker’s ‘Gradient Analysis’ Curves Reliable Evidence of Continuity in Vegetation?” Preslia 76 (3): 245–53. Wimsatt, William C. 2007. Re-engineering Philosophy for Limited Beings: Piecewise Approxima- tions to Reality. Cambridge, MA: Harvard University Press. Woodward, James. 2005. Making Things Happen: A Theory of Causal Explanation. Oxford: Ox- ford University Press. ———. 2016. “Causation and Manipulability.” In The Stanford Encyclopedia of Philosophy, ed. Edward N. Zalta. Stanford, CA: Stanford University. Yarrow, Matthew, and Victor H. Marín. 2007. “Toward Conceptual Cohesiveness: A Historical Analysis of the Theory and Utility of Ecological Boundaries and Transition Zones.” Ecosys- tems 10 (3): 462–76. This content downloaded from 128.110.184.042 on July 09, 2018 16:40:03 PM se subject to University of Chicago Press Terms and Conditions (http://www.journals.uchicago.edu/t-and-c). https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F593002&citationId=p_46 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1111%2Fj.1469-185X.1967.tb01419.x&citationId=p_54 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1038%2F355073a0&citationId=p_43 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2FS0006-3207%2801%2900107-0&citationId=p_47 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1016%2FS0006-3207%2801%2900107-0&citationId=p_47 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&system=10.1086%2F510819&citationId=p_51 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1162%2Fbiot.2009.4.3.274&citationId=p_44 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1007%2Fs10021-007-9036-9&citationId=p_59 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1007%2Fs10021-007-9036-9&citationId=p_59 https://www.journals.uchicago.edu/action/showLinks?doi=10.1086%2F697746&crossref=10.1371%2Fjournal.pone.0000938&citationId=p_52