Ecological and evolutionary responses in complex communities: implications for invasions and eco‐evolutionary feedbacks

It is easier to predict the ecological and evolutionary outcomes of interactions in less diverse communities. As species are added to communities, their direct and indirect interactions multiply, their niches may shift, and there may be increased ecological redundancy. Accompanying this complexity in ecological interactions, is also complexity in selection and subsequent evolution, which may feed back to affect the ecology of the system, as species with different traits may play different ecological roles. Drawing from my own work and that of many others, I first discuss what we currently understand about ecology and evolution in light of simple and diverse communities, and suggest the importance of escape from community complexity per se in the success of invaders. Then, I examine how community complexity may influence the nature and magnitude of eco‐evolutionary feedbacks, classifying eco‐evolutionary dynamics into three general types: those generating alternative stable states, cyclic dynamics, and those maintaining ecological stasis and stability. The latter may be important and yet very hard to detect. I suggest future directions, as well as discuss methodological approaches and their potential pitfalls, in assessing the importance and longevity of eco‐evolutionary feedbacks in complex communities. Synthesis The ecology, evolution and eco‐evolutionary dynamics of simple and diverse communities are reviewed. In more diverse communities, direct and indirect interactions multiply, species’ niches often shift, ecological redundancy can increase, and selection may be less directional. Community complexity may influence the magnitude and nature of eco‐evolutionary dynamics, which are classified into three types: those generating alternative stable states, cyclic dynamics, and those maintaining ecological stasis and stability. Strengths and pitfalls of approaches to investigating eco‐evolutionary feedbacks in complex field communities are discussed.     

Measuring ecological complexity

Complexity is an elusive term in ecology that is often used in different ways to describe the state of an ecosystem. Ecological complexity has been linked to concepts such as ecological integrity, diversity and resilience and has been put forth as a candidate ecological orientor. In this article, the concept of complexity as a system attribute is presented and candidate measures of ecological complexity are reviewed. The measures are distinguished by their ability to characterize the spatial, temporal, structural or spatiotemporal signatures of an ecosystem. Many of these measures have been adapted from disciplines such as physics and information theory that have a long history of quantifying complexity, however more work needs to be done to develop techniques adapted to ecological data. It is argued that if appropriate measures are developed and validated for ecosystems, ecological complexity could become a key ecological indicator.     

Quantifying the complexity of simulated spatiotemporal population dynamics

Spatially explicit models in ecology permit the investigation of population dynamics in both space and time. The resultant spatiotemporal dynamics is often irregular and patchy, giving rise to intricate spatial patterns that can be difficult to characterise. Here, the question of how to characterise the spatiotemporal dynamics of simulated populations is addressed and a method of quantifying the complexity of patchy vegetation dynamics is proposed. The method is inspired by information-based measures of complexity and entropy and can distinguish between ordered, disordered (random) and complex (patchy) spatiotemporal mosaics. The method is demonstrated using data generated by the individual-based, multi-species model WIST.     

The Green Design Apprenticeship

In order to convey the results of our industrial ecology research to broader audiences, the Green Design Institute research group at Carnegie Mellon University offers the Green Design Apprenticeship for local high school students. The Green Design Apprenticeship introduces participants to industrial ecology concepts and how they intersect with engineering. The content of the program has evolved to include the topics of life cycle assessment, energy and water resources, transportation, and the built environment. The program has resulted in exposing a new generation of scholars to industrial ecology and has also benefited the research of graduate students involved with the program. The process of developing the instructional materials for younger, novice students based on complex industrial ecology research was a challenging task requiring thoughtful and iterative planning. Through the development and delivery of the program, we have experienced awareness of where our own research fits into the larger industrial ecology scope, have improved our communication of complex industrial ecology concepts into simple terms, and have gained valuable insight for engaging students in our teaching.     

A landscape theory for food web architecture

Ecologists have long searched for structures and processes that impart stability in nature. In particular, food web ecology has held promise in tackling this issue. Empirical patterns in food webs have consistently shown that the distributions of species and interactions in nature are more likely to be stable than randomly constructed systems with the same number of species and interactions. Food web ecology still faces two fundamental challenges, however. First, the quantity and quality of food web data required to document both the species richness and the interaction strengths among all species within food webs is largely prohibitive. Second, where food webs have been well documented, spatial and temporal variation in food web structure has been ignored. Conversely, research that has addressed spatial and temporal variation in ecosystems has generally ignored the full complexity of food web architecture. Here, we incorporate empirical patterns, largely from macroecology and behavioural ecology, into a spatially implicit food web structure to construct a simple landscape theory of food web architecture. Such an approach both captures important architectural features of food webs and allows for an exploration of food web structure across a range of spatial scales. Finally, we demonstrated that food webs are hierarchically organized along the spatial and temporal niche axes of species and their utilization of food resources in ways that stabilize ecosystems.     

Interactions matter—complexity in landscapes and ecosystems

In this review we argue that theories and methodology arising from the field of complex systems form a new paradigm for ecology. Patterns and processes resulting from interactions between individuals, populations, species and communities in landscapes are the core topic of ecology. These interactions form complex networks, which are the subject of intense research in complexity theory, informatics and statistical mechanics. This research has shown that complex natural networks often share common structures such as loops, trees and clusters. The observed structures contribute to widespread processes including feedback, non-linear dynamics, criticality and self-organisation. Simulation modelling is a key tool in studying complex networks and has become popular in ecology, especially in adaptive management. Important techniques include cellular automata and individual-based models. The complex systems paradigm has led to advances in landscape ecology, including a deeper understanding of the dynamics of spatial pattern formation, habitat fragmentation, epidemic processes, and genetic variation. Network analysis reveals that underlying patterns of interactions, such as small worlds and clusters, in food webs and ecosystems have strong implications for their stability and dynamics. These investigations illustrate how complexity theory and associated methodologies are transforming ecological research, providing new perspectives on old questions as well as raising many new ones.     

Derived vocalizations of geladas (Theropithecus gelada) and the evolution of vocal complexity in primates

Primates are intensely social and exhibit extreme variation in social structure, making them particularly well suited for uncovering evolutionary connections between sociality and vocal complexity. Although comparative studies find a correlation between social and vocal complexity, the function of large vocal repertoires in more complex societies remains unclear. We compared the vocal complexity found in primates to both mammals in general and human language in particular and found that non-human primates are not unusual in the complexity of their vocal repertoires. To better understand the function of vocal complexity within primates, we compared two closely related primates (chacma baboons and geladas) that differ in their ecology and social structures. A key difference is that gelada males form long-term bonds with the 2-12 females in their harem-like reproductive unit, while chacma males primarily form temporary consortships with females. We identified homologous and non-homologous calls and related the use of the derived non-homologous calls to specific social situations. We found that the socially complex (but ecologically simple) geladas have larger vocal repertoires. Derived vocalizations of geladas were primarily used by leader males in affiliative interactions with 'their' females. The derived calls were frequently used following fights within the unit suggesting that maintaining cross-sex bonds within a reproductive unit contributed to this instance of evolved vocal complexity. Thus, our comparison highlights the utility of using closely related species to better understand the function of vocal complexity.     

Range structure analysis: unveiling the internal structure of species’ ranges

Assessing risks of local extinction and shifts in species ranges are fundamental tasks in ecology and conservation. Most studies have focused either on the border of species’ range or on complex spatiotemporal dynamics of populations within the spatial distribution of species. The internal properties of species ranges, however, have received less attention due to a general lack of simple tools. We propose a novel approach within a metapopulation framework to study species ranges based on simple mathematical rules. We formulate and test a model of population fluctuations through space to identify key factors that regulate population density. We propose that spatial variability in species abundance reflects the interaction between temporal variability in population dynamics and the spatial variability of population parameters. This approach, that we call range structure analysis, integrates temporal and spatial properties to diagnose how each parameter contributes to species occupancy throughout its geographic range.     

A parsimonious view of the parsimony principle in ecology and evolution

The idea that simplicity of explanation is important in science is as old as science itself. However, scientists often assume that parsimonious theories, hypothesis and models are more plausible than complex ones, forgetting that there is no empirical evidence to connect parsimony with credibility. The justification for the parsimony principle is strongly dependent on philosophical and statistical inference. Parsimony may have a true epistemic value in the evaluation of correlative and predictive models, as simpler models are less prone to overfitting. However, when natural mechanisms are explicitly modelled to represent the causes of biological phenomena, the application of the parsimony principle to judge the plausibility of mechanistic models would entail an unsupported belief that nature is simple. Here, we discuss the challenges we face in justifying, measuring, and assessing the trade‐off between simplicity and complexity in ecological and evolutionary studies. We conclude that invoking the parsimony principle in ecology and evolution is particularly important in model‐building programs in which models are viewed primarily as an operational tool to make predictions (an instrumentalist view) and in which data play a prominent role in deciding the structure of the model. However, theoretical advances in ecology and evolutionary biology may be derailed by the use of the parsimony principle to judge explanatory mechanistic models that are designed to understand complex natural phenomena. We advocate a parsimonious use of the parsimony principle.     

"What watch? ... such much!"* Complexity and evolution of circadian clocks

This review uses three examples to summarise our knowledge about the complexity and the evolution of circadian systems. The first example describes the ecology of unicellular algae, which use their circadian system to optimise the daily exploitation of resources that are spatially separated. The second example looks at the role of clocks in tissues and cells within a complex organism, and the third speculates on how the circadian system may have evolved.     

Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability

The evolution of complex organismal traits is obvious as a historical fact, but the underlying causes—including the role of natural selection—are contested. Gould argued that a random walk from a necessarily simple beginning would produce the appearance of increasing complexity over time. Others contend that selection, including coevolutionary arms races, can systematically push organisms toward more complex traits. Methodological challenges have largely precluded experimental tests of these hypotheses. Using the Avida platform for digital evolution, we show that coevolution of hosts and parasites greatly increases organismal complexity relative to that otherwise achieved. As parasites evolve to counter the rise of resistant hosts, parasite populations retain a genetic record of past coevolutionary states. As a consequence, hosts differentially escape by performing progressively more complex functions. We show that coevolution''s unique feedback between host and parasite frequencies is a key process in the evolution of complexity. Strikingly, the hosts evolve genomes that are also more phenotypically evolvable, similar to the phenomenon of contingency loci observed in bacterial pathogens. Because coevolution is ubiquitous in nature, our results support a general model whereby antagonistic interactions and natural selection together favor both increased complexity and evolvability.     

What are genes “for” or where are traits “from”? What is the question?

For at least a century it has been known that multiple factors play a role in the development of complex traits, and yet the notion that there are genes “for” such traits, which traces back to Mendel, is still widespread. In this paper, we illustrate how the Mendelian model has tacitly encouraged the idea that we can explain complexity by reducing it to enumerable genes. By this approach many genes associated with simple as well as complex traits have been identified. But the genetic architecture of biological traits, or how they are made, remains largely unknown. In essence, this reflects the tension between reductionism as the current “modus operandi” of science, and the emerging knowledge of the nature of complex traits. Recent interest in systems biology as a unifying approach indicates a reawakened acceptance of the complexity of complex traits, though the temptation is to replace “gene for” thinking by comparably reductionistic “network for” concepts. Both approaches implicitly mix concepts of variants and invariants in genetics. Even the basic question is unclear: what does one need to know to “understand” the genetic basis of complex traits? New operational ideas about how to deal with biological complexity are needed.     

Lessons from the size efficiency hypothesis II. The mire of complexity

Over the years, models and concepts developed to explain the behaviour of lake plankton have been generalized and extended to most parts of the limnetic community. This development has now fused with parallel research programs into stream and marine benthos and fish, to yield an imposing literature dealing with complex interactions in aquatic communities. Although the size of this literature has grown, its basic elements, i.e. the allometries of organismal capacity and environmental opportunity, remain those associated with the seminal size efficiency hypothesis. Unfortunately, the difficulties that eventually buried that hypothesis in a welter of detail and special cases were not resolved, so the newer, broader concepts associated with complex interactions remain difficult or impossible to test. Those concepts are so subjective, poorly defined, and variably interpreted that they are more effective in explaining our observations after the fact than in predicting them before-hand. Despite predictive failure, such explanatory models have achieved wide acceptance. Once accepted as substitutes for predictive theory, they mire the advance of science by hiding its deficiencies. One solution to this cloying complexity is insistence that the theories of ecology specify simple, observable response variables so that theories may be evaluated by their predictive power. Components of a general refuge concept illustrate the point. This policy has implications for environmental science well beyond the confines of plankton ecology.Dedicated to Dr Karl Banse, School of Oceanography, University of Washington on his 60th Birthday.     

Species: kinds of individuals or individuals of a kind

The “species‐as‐individuals” thesis takes species, or taxa, to be individuals. On grounds of spatiotemporal boundedness, any biological entity at any level of complexity subject to evolutionary processes is an individual. From evolutionary theory flows an ontology that does not countenance universal properties shared by evolving entities. If austere nominalism were applied to evolving entities, however, nature would be reduced to a mere flow of passing events, each one a blob in space–time and hence of passing interest only. Yet if there is genuine biodiversity in nature, if nature is genuinely carved into species, and taxa, then these evolutionary entities will be genuinely differentiated into specific kinds, each species being one of its kind. Given the fact that evolving entities have un‐sharp boundaries, an appropriately weak, “non‐essentialist” concept of natural kind has to be invoked that does not allow for strong identity conditions. The thesis of this paper is that species are not either individuals, or natural kinds. Instead, species are complex wholes (particulars, individuals) that instantiate a specific natural kind. © The Willi Hennig Society 2007.     

视觉皮层复杂细胞时空编码特性

针对输入在视皮层的编码表达,在地空滤波窗口基础上构建了一个复杂细胞时空编码模型,对几种特殊的输入函数进行了编码仿真实验,结果说明了视皮层复杂细胞时空整合编码序列的精细时间结构进行视觉输入的神经表象。     

Increasing community size and connectance can increase stability in competitive communities

The relationship between community complexity and stability has been the subject of an enduring debate in ecology over the last 50 years. Results from early model communities showed that increased complexity is associated with decreased local stability. I demonstrate that increasing both the number of species in a community and the connectance between these species results in an increased probability of local stability in discrete-time competitive communities, when some species would show unstable dynamics in the absence of competition. This is shown analytically for a simple case and across a wider range of community sizes using simulations, where individual species have dynamics that can range from stable point equilibria to periodic or more complex. Increasing the number of competitive links in the community reduces per-capita growth rates through an increase in competitive feedback, stabilising oscillating dynamics. This result was robust to the introduction of a trade-off between competitive ability and intrinsic growth rate and changes in species interaction strengths. This throws new light on the discrepancy between the theoretical view that increased complexity reduces stability and the empirical view that more complex systems are more likely to be stable, giving one explanation for the relative lack of complex dynamics found in natural systems. I examine how these results relate to diversity-biomass stability relationships and show that an analytical solution derived in the region of stable equilibrium dynamics captures many features of the change in biomass fluctuations with community size in communities including species with oscillating dynamics.     

Foraging in highly dynamic environments: leaf‐cutting ants adjust foraging trail networks to pioneer plant availability

Major shifts in the availability of palatable plant resources are of key relevance to the ecology of leaf‐cutting ants in human‐modified landscapes. However, our knowledge is still limited regarding the ability of these ants to adjust their foraging strategy to dynamic environments. Here, we examine a set of forest stand attributes acting as modulating forces for the spatiotemporal architecture of foraging trail networks developed by Atta cephalotes L. (Hymenoptera: Formicidae: Attini). During a 12‐month period, we mapped the foraging systems of 12 colonies located in Atlantic forest patches with differing size, regeneration age, and abundance of pioneer plants, and examined the variation in five trail system attributes (number of trails, branching points, leaf sources, linear foraging distance, and trail complexity) in response to these patch‐related variables. Both the month‐to‐month differences (depicted in annual trail maps) and the steadily accumulating number of trails, trail‐branching points, leaf sources, and linear foraging distance illustrated the dynamic nature of spatial foraging and trail complexity. Most measures of trail architecture correlated positively with the number of pioneer trees across the secondary forest patches, but no effects from patch age and size were observed (except for number of leaf sources). Trail system complexity (measured as fractal dimension; Df index) varied from 1.114 to 1.277 along the 12 months through which ant foraging was monitored, with a marginal trend to increase with the abundance of pioneer stems. Our results suggest that some leaf‐cutting ant species are able to generate highly flexible trail networks (via fine‐tuned adjustment of foraging patterns), allowing them to profit from the continuous emergence/recruitment of palatable resources.