Annual Review of Ecology, Evolution, and Systematics - Volume 48, 2017

Most species have one or more natural enemies, e.g., predators, parasites, pathogens, and herbivores, among others. These species in turn typically attack multiple victim species. This leads to the possibility of indirect interactions among those victims, both positive and negative. The term apparent competition commonly denotes negative indirect interactions between victim species that arise because they share a natural enemy. This indirect interaction, which in principle can be reflected in many facets of the distribution and abundance of individual species and more broadly govern the structure of ecological communities in time and space, pervades many natural ecosystems. It also is a central theme in many applied ecological problems, including the control of agricultural pests, harvesting, the conservation of endangered species, and the dynamics of emerging diseases. At one end of the scale of life, apparent competition characterizes intriguing aspects of dynamics within individual organisms—for example, the immune system is akin in many ways to a predator that can induce negative indirect interactions among different pathogens. At intermediate scales of biological organization, the existence and strength of apparent competition depend upon many contingent details of individual behavior and life history, as well as the community and spatial context within which indirect interactions play out. At the broadest scale of macroecology and macroevolution, apparent competition may play a major, if poorly understood, role in the evolution of species’ geographical ranges and adaptive radiations.

To put marine disease impacts in context requires a broad perspective on the roles infectious agents have in the ocean. Parasites infect most marine vertebrate and invertebrate species, and parasites and predators can have comparable biomass density, suggesting they play comparable parts as consumers in marine food webs. Although some parasites might increase with disturbance, most probably decline as food webs unravel. There are several ways to adapt epidemiological theory to the marine environment. In particular, because the ocean represents a three-dimensional moving habitat for hosts and parasites, models should open up the spatial scales at which infective stages and host larvae travel. In addition to open recruitment and dimensionality, marine parasites are subject to fishing, filter feeders, dose-dependent infection, environmental forcing, and death-based transmission. Adding such considerations to marine disease models will make it easier to predict which infectious diseases will increase or decrease in a changing ocean.

Secondary tropical forests that are in a state of regeneration following clearing for agriculture are now more abundant than primary forests. Yet, despite their large spatial extent and important role in the global carbon (C) cycle, secondary tropical forests are understudied, which challenges our ability to predict how tropical landscapes will respond to future disturbance and global change. We summarize research advances on alterations to C and nutrient dynamics during reforestation and how these are influenced by ecosystem state factors. During forest succession, aboveground biomass stocks and litter fluxes increase in a predictable way, but patterns in soil C dynamics are highly variable. The heterogeneous response of nutrients to reforestation is influenced by multiple factors, including losses incurred during prior land use and management. In contrast to primary tropical forests, where productivity is often limited by rock-derived nutrients, secondary forest growth may be more limited by nutrients from the atmosphere. Future research should identify which nutrients constrain forest regrowth.

Most ecosystems have multiple-plant invaders rather than single-plant invaders, yet ecological studies and management actions focus largely on single invader species. There is a need for general principles regarding invader interactions across varying environmental conditions, so that secondary invasions can be anticipated and managers can allocate resources toward pretreatment or postremoval actions. By reviewing removal experiments conducted in three Hawaiian ecosystems (a dry tropical forest, a seasonally dry mesic forest, and a lowland wet forest), we evaluate the roles environmental harshness, priority effects, productivity potential, and species interactions have in influencing secondary invasions, defined here as invasions that are influenced either positively (facilitation) or negatively (inhibition/priority effects) by existing invaders. We generate a conceptual model with a surprise index to describe whether long-term plant invader composition and dominance is predictable or stochastic after a system perturbation such as a removal experiment. Under extremely low resource availability, the surprise index is low, whereas under intermediate-level resource environments, invader dominance is more stochastic and the surprise index is high. At high resource levels, the surprise index is intermediate: Invaders are likely abundant in the environment but their response to a perturbation is more predictable than at intermediate resource levels. We suggest further testing across environmental gradients to determine key variables that dictate the predictability of postremoval invader composition.

We give an overview of recently developed methods to reconstruct phylog-enies of taxa that include allopolyploids that have originated in relatively recent times—in other words, taxa for which at least some of the parental lineages of lower ploidy levels are not extinct and for which ploidy information is clearly shown by variation in chromosome counts. We review how these methods have been applied to empirical data, discuss challenges, and outline prospects for future research. In the absence of recombination between parental subgenomes, the allopolyploid phylogenetic histories can in principle be treated as genome tree inference. However, without whole genome or whole chromosome data, sequences must be assigned from genes sampled to parental subgenomes. The new version of the AlloppNET method, which now can handle any number of species at the diploid and tetraploid level and any number of hybridizations, is a promising attempt that can also treat gene tree discordance due to the coalescent process. The ongoing development of models that take migration, paralogy, and uncertainties in species delimitations into account offers exciting opportunities for the future of inference of species networks.

Ecological networks depict the interactions between species, mainly based on observations in the field. The information contained in such interaction matrices depends on the sampling design, and typically, compounds preferences (specialization) and abundances (activity). Null models are the primary vehicles to disentangle the effects of specialization from those of sampling and abundance, but they ignore the feedback of network structure on abundances. Hence, network structure, as exemplified here by modularity, is difficult to link to specific causes. Indeed, various processes lead to modularity and to specific interaction patterns more generally. Inferring (co)evolutionary dynamics is even more challenging, as competition and trait matching yield identical patterns of interactions. A satisfactory resolution of the underlying factors determining network structure will require substantial additional information, not only on independently assessed abundances, but also on traits, and ideally on fitness consequences as measured in experimental setups.

Receiver bias in plant–animal interactions is here defined as “selection mediated by behavioral responses of animals, where those responses have evolved in a context outside the interactions.” As a consequence, the responses are not necessarily linked to fitness gains in interacting animals. Thus, receiver bias can help explain seemingly maladaptive patterns of behavior in interacting animals and the evolution of plant traits that trigger such behavior. In this review, I discuss principles of receiver bias, show its overlap with mimicry and how it differs from mimicry, and outline examples in different plant–animal interactions. The most numerous and best documented examples of receiver bias occur within plant–pollinator interactions. I elaborate on the ability of some plants to heat up their flowers (i.e., floral thermogenesis) and argue that this trait likely evolved under receiver bias, especially in pollination systems with oviposition mimicry. Further examples include signals in insect-mediated seed dispersal and plant defense through repellence of aphids. These examples show that receiver bias is widespread in different plant–animal interactions. For a broader understanding of the role of receiver bias in those interactions, we need more data on how animals respond to plant signals, the context and evolutionary history of those behaviors, and the evolutionary patterns of plant signals.

Populations that experience severe stress may avoid extinction through adaptation by natural selection. This process is called evolutionary rescue and has been studied under different names in medicine, agriculture, and conservation biology. It is a component of the emerging field of eco-evolutionary dynamics, which investigates how the ecological attributes of species may evolve rapidly under strong selection. Its distinguishing feature is to combine the evolutionary concept of relative fitness with the ecological concept of absolute fitness in a synthetic theory of persistent adaptation. The likelihood of rescue will depend both on attributes of the population, particularly abundance and variation, and on properties of the environment, particularly the rate and severity of deterioration. Medical interventions (e.g., the administration of antibiotics), agricultural practices (e.g., the application of pesticides), and population ecology (e.g., the effects of species introductions) provide numerous examples of evolutionary rescue. The general theory of rescue has been tested in laboratory experiments with microbes, in which experimental evolution shows how different treatments affect the frequency of rescue. Overall, these experiments have supported the predictions of general theory: In particular, abundance, variation, and dispersal have pronounced and repeatable effects on the rescue of populations and communities. Extending these laboratory results to the field is a major task for future research.