Variation in Avian Predation Pressure as a Driver for the Diversification of Periodical Cicada Broods.

AbstractPeriodical cicadas live 13 or 17 years underground as nymphs, then emerge in synchrony as adults to reproduce. Developmentally synchronized populations called broods rarely coexist, with one dominant brood locally excluding those that emerge in off years. Twelve modern 17-year cicada broods are believed to have descended from only three ancestral broods following the last glaciation. The mechanisms by which these daughter broods overcame exclusion by the ancestral brood to synchronously emerge in a different year, however, are elusive. Here, we demonstrate that temporal variation in the population density of generalist predators can allow intermittent opportunities for new broods to invade, even though a single brood remains dominant most of the time. We show that this mechanism is consistent, in terms of the type and frequency of brood replacements, with the distribution of periodical cicada broods throughout North America today. Although we investigate one particularly charismatic case study, the mechanisms involved (competitive exclusion, Allee effects, trait variation, predation, and temporal variability) are ubiquitous and could contribute to patterns of species diversity in a range of systems.

How public can public goods be? Environmental context shapes the evolutionary ecology of partially private goods.

The production of costly public goods (as distinct from metabolic byproducts) has largely been understood through the realization that spatial structure can minimize losses to non-producing "cheaters" by allowing for the positive assortment of producers. In well-mixed systems, where positive assortment is not possible, the stable production of public goods has been proposed to depend on lineages that become indispensable as the sole producers of those goods while their neighbors lose production capacity through genome streamlining (the Black Queen Hypothesis). Here, we develop consumer-resource models motivated by nitrogen-fixing, siderophore-producing bacteria that consider the role of colimitation in shaping eco-evolutionary dynamics. Our models demonstrate that in well-mixed environments, single "public goods" can only be ecologically and evolutionarily stable if they are partially privatized (i.e., if producers reserve a portion of the product pool for private use). Colimitation introduces the possibility of subsidy: strains producing a fully public good can exclude non-producing strains so long as the producing strain derives sufficient benefit from the production of a second partially private good. We derive a lower bound for the degree of privatization necessary for production to be advantageous, which depends on external resource concentrations. Highly privatized, low-investment goods, in environments where the good is limiting, are especially likely to be stably produced. Coexistence emerges more rarely in our mechanistic model of the external environment than in past phenomenological approaches. Broadly, we show that the viability of production depends critically on the environmental context (i.e., external resource concentrations), with production of shared resources favored in environments where a partially-privatized resource is scarce.

Modeling and prediction of phase shifts in noisy two-cycle oscillations.

Understanding and predicting ecological dynamics in the presence of noise remains a substantial and important challenge. This is particularly true in light of the poor quality of much ecological data and the imprecision of many ecological models. As a first approach to this problem, we focus here on a simple system expressed as a discrete time model with 2-cycle behavior, reflecting alternating high and low population sizes. Such dynamics naturally arise in ecological systems with overcompensatory density dependence. We ask how the amount of detail included in the population estimates affects the ability to forecast the likelihood of changes in the phase of oscillation, meaning whether high populations occur in odd or in even years. We adjust the level of detail by converting continuous population levels to simple, coarse-grained descriptions using two-state and four-state models. We also consider a cubic noisy over-compensatory model with three parameters. The focus on phase changes is what distinguishes the question we are asking and the methods we use from more standard time series approaches. Obviously, adding observation states improves the ability to forecast phase shifts. In particular, the four-state model and cubic model outperform the two-state model because they include a transition state, through which the dynamics typically pass during a phase change. Nonetheless, at high noise levels the improvement in forecast skill is relatively modest. Additionally, the frequency of phase changes depends strongly on the noise level, and is much less affected by the parameter determining amplitude in the population model, so phase shift frequencies could possibly be used to infer noise levels.

Noise-induced versus intrinsic oscillation in ecological systems.

Studies of oscillatory populations have a long history in ecology. A first-principles understanding of these dynamics can provide insights into causes of population regulation and help with selecting detailed predictive models. A particularly difficult challenge is determining the relative role of deterministic versus stochastic forces in producing oscillations. We employ statistical physics concepts, including measures of spatial synchrony, that incorporate patterns at all scales and are novel to ecology, to show that spatial patterns can, under broad and well-defined circumstances, elucidate drivers of population dynamics. We find that when neighbours are coupled (e.g. by dispersal), noisy intrinsic oscillations become distinguishable from noise-induced oscillations at a transition point related to synchronisation that is distinct from the deterministic bifurcation point. We derive this transition point and show that it diverges from the deterministic bifurcation point as stochasticity increases. The concept of universality suggests that the results are robust and widely applicable.

Perfect Compensation Is Sufficient to Explain Insect Outbreaks Previously Attributed to Overcompensation : (A Comment on Stieha et al., "The Effects of Plant Compensatory Regrowth and Induced Resistance on Herbivore Population Dynamics").

AbstractIn "The Effects of Plant Compensatory Regrowth and Induced Resistance on Herbivore Population Dynamics," which appeared in The American Naturalist in 2016, Stieha et al. argued that overcompensatory regrowth of plant tissues lost to herbivory ("overcompensation") promotes cyclic herbivore outbreaks. In contrast, they concluded that partial regrowth ("tolerance") stabilizes herbivore dynamics, preventing outbreaks. These conclusions were based on a comparison between two plant-herbivore models that differed in two properties: (1) whether biomass could ever be higher after herbivory and regrowth than before herbivory (i.e., is overcompensatory regrowth possible?) and (2) how much herbivory the plants could withstand before only being able to partially compensate for losses (for overcompensating plants, there was a threshold herbivory level above which this occurred, whereas tolerant plants always showed partial compensation). While Stieha et al. supposed that difference 1 was responsible for the increased propensity for outbreaks in their overcompensation model, we show here that, in fact, difference 2 is responsible. Thus, we conclude that Stieha et al.'s results about "overcompensating" plants apply more broadly: the risk of herbivore outbreaks is elevated whenever plants with low-enough herbivore loads can perfectly compensate or overcompensate for losses to herbivory.

Microbiome influence on host community dynamics: Conceptual integration of microbiome feedback with classical host-microbe theory.

Microbiomes have profound effects on host fitness, yet we struggle to understand the implications for host ecology. Microbiome influence on host ecology has been investigated using two independent frameworks. Classical ecological theory powerfully represents mechanistic interactions predicting environmental dependence of microbiome effects on host ecology, but these models are notoriously difficult to evaluate empirically. Alternatively, host-microbiome feedback theory represents impacts of microbiome dynamics on host fitness as simple net effects that are easily amenable to experimental evaluation. The feedback framework enabled rapid progress in understanding microbiomes' impacts on plant ecology, and can also be applied to animal hosts. We conceptually integrate these two frameworks by deriving expressions for net feedback in terms of mechanistic model parameters. This generates a precise mapping between net feedback theory and classic population modelling, thereby merging mechanistic understanding with experimental tractability, a necessary step for building a predictive understanding of microbiome influence on host ecology.

When and Where We Can Expect to See Early Warning Signals in Multispecies Systems Approaching Tipping Points: Insights from Theory.

AbstractEarly warning signals (EWSs) have the potential to predict tipping points where catastrophic changes occur in ecological systems. However, EWSs are plagued by false negatives, leading to undetected catastrophes. One reason may be because EWSs do not occur equally for all species in a system, so whether and how strongly EWSs are detected depends on which species is being observed. Here, we illustrate how the strength of EWSs is determined by each species' relationship to properties of the noise, the system's response to that noise, and the occurrence of critical slowing down (the dynamical phenomenon that gives rise to EWSs). Using these relationships, we present general rules for maximizing EWS detection in ecological communities. We find that for two-species competitive and mutualistic systems, one should generally monitor the species experiencing smaller intraspecific effects to maximize EWS performance, while in consumer-resource systems, one should monitor the species imposing the smaller interspecific effects. These guidelines appear to hold for at least some larger communities as well. We close by extending the theoretical basis for our rules to systems with any number of species and more complex forms of noise. Our findings provide important guidance on how to monitor systems for EWSs to maximize detection of tipping points.

Better baboon break-ups: collective decision theory of complex social network fissions.

Many social groups are made up of complex social networks in which each individual associates with a distinct subset of its groupmates. If social groups become larger over time, competition often leads to a permanent group fission. During such fissions, complex social networks present a collective decision problem and a multidimensional optimization problem: it is advantageous for each individual to remain with their closest allies after a fission, but impossible for every individual to do so. Here, we develop computational algorithms designed to simulate group fissions in a network-theoretic framework. We focus on three fission algorithms (democracy, community and despotism) that fall on a spectrum from a democratic to a dictatorial collective decision. We parameterize our social networks with data from wild baboons (Papio cynocephalus) and compare our simulated fissions with actual baboon fission events. We find that the democracy and community algorithms (egalitarian decisions where each individual influences the outcome) better maintain social networks during simulated fissions than despotic decisions (driven primarily by a single individual). We also find that egalitarian decisions are better at predicting the observed individual-level outcomes of observed fissions, although the observed fissions often disturbed their social networks more than the simulated egalitarian fissions.

Density dependent Resource Budget Model for alternate bearing.

Alternate bearing, seen in many types of plants, is the variable yield with a strongly biennial pattern. In this paper, we introduce a new model for alternate bearing behavior. Similar to the well-known Resource Budget Model, our model is based on the balance between photosynthesis or other limiting resource accumulation and reproduction processes. We consider two novel features with our model, 1) the existence of a finite capacity in the tree's resource reservoir and 2) the possibility of having low (but non-zero) yield when the tree's resource level is low. We achieve the former using a density dependent resource accumulation function, and the latter by removing the concept of the well-defined threshold used in the Resource Budget Model. At the level of an individual tree, our model has a stable two-cycle solution, which is suitable to model plants in which the alternate bearing behavior is pronounced. We incorporate environmental stochasticity by adding two uncorrelated noise terms to the parameters of the model associated with the nutrient accumulation and reproduction processes. Furthermore, we examine the model's behavior on a system of two coupled trees with direct coupling. Unlike the coupled Resource Budget Model, for which the only stable solution is the out-of-phase solution, our model with direct coupling has stable in-phase period-2 solutions. This suggests that our model might serve to explain spatial synchrony on a larger scale.

Sharp boundary formation and invasion between spatially adjacent periodical cicada broods.

Periodical cicadas, Magicicada spp., are a useful model system for understanding the population processes that influence range boundaries. Unlike most insects, these species typically exist at very high densities (occasionally >1000/ m2) and have unusually long life-spans (13 or 17 years). They spend most of their lives underground feeding on plant roots. After the underground period, adults emerge from the ground to mate and oviposit over a period of just a few days. Collections of populations that are developmentally synchronized across large areas are known as "broods". There are usually sharp boundaries between spatially adjacent broods and regions of brood overlap are generally small. The exact mechanism behind this developmental synchronization and the sharp boundary between broods remain unknown: previous studies have focused on the impacts of predator-driven Allee-effects, competition among nymphs, and their impacts on the persistence of off-synchronized emergence events. Here, we present a nonlinear Leslie-type matrix model to additionally consider cicada movement between spatially separated broods, and examine its role in maintaining brood boundaries and within-brood developmental synchrony that is seen in nature. We successfully identify ranges of competition and dispersal that lead to stable coexistence of broods that differ between spatial patches.

Pathogens and Mutualists as Joint Drivers of Host Species Coexistence and Turnover: Implications for Plant Competition and Succession.

The potential for either pathogens or mutualists to alter the outcome of interactions between host species has been clearly demonstrated experimentally, but our understanding of their joint influence remains limited. Individually, pathogens and mutualists can each stabilize (via negative feedback) or destabilize (via positive feedback) host-host interactions. When pathogens and mutualists are both present, the potential for simultaneous positive and negative feedbacks can generate a wide range of possible effects on host species coexistence and turnover. Extending existing theoretical frameworks, we explore the range of dynamics generated by simultaneous interactions with pathogens and mutualists and identify the conditions for pathogen or mutualist mediation of host coexistence. We then explore the potential role of microbial mutualists and pathogens in plant species turnover during succession. We show how a combination of positive and negative plant-microbe feedbacks can generate a coexistence state that is part of a set of alternative stable states. This result implies that the outcomes of coexistence from classical plant-soil feedback experiments may be susceptible to disturbances and that empirical investigations of microbially mediated coexistence would benefit from consideration of interactive effects of feedbacks generated from different distinct components of the plant microbiome.

The glycosyltransferase GnT-III activates Notch signaling and drives stem cell expansion to promote the growth and invasion of ovarian cancer.

Glycosylation changes associated with cellular transformation can facilitate the growth and progression of tumors. Previously we discovered that the gene Mgat3 encoding the glycosyltransferase GnT-III is elevated in epithelial ovarian carcinomas (EOCs) and leads to the production of abnormal truncated N-linked glycan structures instead of the typical bisected forms. In this study, we are interested in discovering how these abnormal glycans impact the growth and progression of ovarian cancer. We have discovered using stable shRNA gene suppression that GnT-III expression controls the expansion of side-population cells, also known as cancer stem cells. More specifically, we found that GnT-III expression regulates the levels and activation of the heavily glycosylated Notch receptor involved in normal and malignant development. Suppression of GnT-III in EOC cell lines and primary tumor-derived cells resulted in an inhibition of Notch signaling that was more potent than pharmacologic blockage of Notch activation via γ-secretase inhibition. The inhibition resulted from the redirection of the Notch receptor to the lysosome, a novel mechanism. These findings demonstrate a new role for bisecting glycosylation in the control of Notch transport and demonstrate the therapeutic potential of inhibiting GnT-III as a treatment for controlling EOC growth and recurrence.

No appendix necessary: Fecal transplants and antibiotics can resolve Clostridium difficile infection.

The appendix has been hypothesized to protect the colon against Clostridium difficile infection (CDI) by providing a continuous source of commensal bacteria that crowd out the potentially unhealthy bacteria and/or by contributing to defensive immune dynamics. Here, a series of deterministic systems comprised of ordinary differential equations, which treat the system as an ecological community of microorganisms, model the dynamics of colon microbiome. The first model includes migration of commensal bacteria from the appendix to the gut, while the second model expands this to also include immune dynamics. Simulations and simple analytic techniques are used to explore dynamics under biologically relevant parameters values. Both models exhibited bistability with steady states of a healthy state and of fulminant CDI. However, we find that the appendix size was much too small for migration to affect the stability of the system. Both models affirm the use of fecal transplants in conjunction with antibiotic use for CDI treatment, while the second model also suggests that anti-inflammatory drugs may protect against CDI. Ultimately, in general neither the appendiceal migration rate of commensal microbiota nor the boost to antibody production could exert an appreciable impact on the stability of the system, thus failing to support the proposed protective role of the appendix against CDI.

Why are demographic Allee effects so rarely seen in social animals?

Allee effects in group-living species are common, but little is known about the way in which Allee effects at the group-level scale up to influence population dynamics. Most notably, it remains unclear whether component Allee effects within groups (where some component of fitness in small groups decreases with decreasing group size) will translate into a population-level demographic Allee effect (where per capita fitness in small populations decreases with decreasing overall population size). The African wild dog (Lycaon pictus) is an obligate cooperative breeder that lives in packs and has a multitude of group-level component Allee effects. With the African wild dog as a case study, we use models to determine the effect that group structure has on the population dynamics of social animals and, specifically, whether Allee effects operating at the group level lead to a demographic Allee effect at the population level. We developed a suite of models to analyse the population dynamics of group-living species, as well as comparable "packless" models lacking group structure. By comparing these models, we can identify how Allee effects within groups influence population-level dynamics. Our results show that group structure buffers populations against a demographic Allee effect, because mechanisms affecting birth and mortality are more strongly influenced by group size than population size. We find that interactions between groups are vital in determining the relationship between density dependence within groups and density dependence at the population level. As sufficiently large groups provide protection against positive density dependence, even at low overall population sizes, our results have conservation implications for group-living species, as they suggest group size is a necessary population feature to consider in efforts to manage population size. Furthermore, we provide novel insight regarding the role that dispersal and pack size variation play in the buffering nature of social structure in groups subject to Allee effects.

Moving forward in circles: challenges and opportunities in modelling population cycles.

Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer-resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research.

The Effects of Plant Compensatory Regrowth and Induced Resistance on Herbivore Population Dynamics.

Outbreaks of herbivorous insects are detrimental to natural and agricultural systems, but the mechanisms driving outbreaks are not well understood. Plant responses to herbivory have the potential to produce outbreaks, but long-term effects of plant responses on herbivore dynamics are understudied. To quantify these effects, we analyze mathematical models of univoltine herbivores consuming annual plants with two responses: (1) compensatory regrowth, which affects herbivore survival in food-limited situations by increasing the amount of food available to the herbivore; and (2) induced resistance, which reduces herbivore survival proportional to the strength of the response. Compensatory regrowth includes tolerance, where plants replace some or all of the consumed biomass, and overcompensation, where plants produce more biomass than was consumed. We found that overcompensation can cause bounded fluctuations in the herbivore density (called outbreaks here) by itself, whereas neither tolerance nor induced resistance can cause an outbreak on its own. Food limitation and induced resistance can also drive outbreaks when they act simultaneously. Tolerance damps these outbreaks, but overcompensation, by contrast, qualitatively changes the conditions under which the outbreaks occur. Not properly accounting for these interactions may explain why it has been difficult to document plant-driven insect outbreaks and could undermine efforts to control herbivore populations in agricultural systems.

Balls, cups, and quasi-potentials: quantifying stability in stochastic systems.

When a system has more than one stable state, how can the stability of these states be compared? This deceptively simple question has important consequences for ecosystems, because systems with alternative stable states can undergo dramatic regime shifts. The probability, frequency, duration, and dynamics of these shifts will all depend on the relative stability of the stable states. Unfortunately, the concept of "stability" in ecology has suffered from substantial confusion and this is particularly problematic for systems where stochastic perturbations can cause shifts between coexisting alternative stable states. A useful way to visualize stable states in stochastic systems is with a ball-in-cup-diagram, in which the state of the system is represented as the position of a ball rolling on a surface, and the random perturbations can push the ball from one basin of attraction to another. The surface is determined by a potential function, which provides a natural stability metric. Systems amenable to this representation, called gradient systems, are quite rare, however. As a result, the potential function is not widely used and other approaches based on linear stability analysis have become standard. Linear stability analysis is designed for local analysis of deterministic systems and, as we show, can produce a highly misleading picture of how the system will behave under continual, stochastic perturbations. In this paper, we show how the potential function can be generalized so that it can be applied broadly, employing a concept from stochastic analysis called the quasi-potential. Using three classic ecological models, we demonstrate that the quasi-potential provides a useful way to quantify stability in stochastic systems. We show that the quasi-potential framework helps clarify long-standing confusion about stability in stochastic ecological systems, and we argue that ecologists should adopt it as a practical tool for analyzing these systems.

Glycomic analysis of membrane glycoproteins with bisecting glycosylation from ovarian cancer tissues reveals novel structures and functions.

Biomarkers capable of detecting and targeting epithelial ovarian cancer cells for diagnostics and therapeutics would be extremely valuable. Ovarian cancer is the deadliest reproductive malignancy among women in the U.S., killing over 14 000 women each year. Both the lack of presenting symptoms and high mortality rates illustrate the need for earlier diagnosis and improved treatment of this disease. The glycosyltransferase enzyme GnT-III encoded by the Mgat3 gene is responsible for the addition of GlcNAc (N-acetylglucosamine) to form bisecting N-linked glycan structures. GnT-III mRNA expression is amplified in ovarian cancer tissues compared with normal ovarian tissue. We use a lectin capture strategy coupled to nano-ESI-RPLC-MS/MS to isolate and identify the membrane glycoproteins and unique glycan structures associated with GnT-III amplification in human ovarian cancer tissues. Our data illustrate that the majority of membrane glycoproteins with bisecting glycosylation are common to both serous and endometrioid histological subtypes of ovarian cancer, and several have been reported to participate in signaling pathways such as Notch, Wnt, and TGFß.

Trade-offs and coexistence in fluctuating environments: evidence for a key dispersal-fecundity trade-off in five nonpollinating fig wasps.

The ecological principle of competitive exclusion states that species competing for identical resources cannot coexist, but this principle is paradoxical because ecologically similar competitors are regularly observed. Coexistence is possible under some conditions if a fluctuating environment changes the competitive dominance of species. This change in competitive dominance implies the existence of trade-offs underlying species' competitive abilities in different environments. Theory shows that fluctuating distance between resource patches can facilitate coexistence in ephemeral patch competitors, given a functional trade-off between species dispersal ability and fecundity. We find evidence supporting this trade-off in a guild of five ecologically similar nonpollinating fig wasps and subsequently predict local among-patch species densities. We also introduce a novel colonization index to estimate relative dispersal ability among ephemeral patch competitors. We suggest that a dispersal ability-fecundity trade-off and spatiotemporally fluctuating resource availability commonly co-occur to drive population dynamics and facilitate coexistence in ephemeral patch communities.

Phenological and geographical shifts have interactive effects on migratory bird populations.

For many taxa, ranges are shifting toward the poles and the timing of seasonal reproduction is advancing in response to climate change. For migratory birds, changes such as these could produce particularly strong impacts because of their potential to affect migratory timing and distance. Due to the relatively complex life histories of migratory species, however, it is difficult to intuit exactly what these impacts will be. Here, we develop a general population model for a long-distance migrant, introducing a framework for understanding the potential implications of changes in both phenology and migratory distance for bird abundances. We find that population sizes may increase with either shorter or longer migratory distances, depending on the nature of any concurrent phenological changes. This interaction between timing and distance suggests a need to consider multiple potential responses to climate change simultaneously in order to understand the overall impact of climate change on migratory populations. Our results reveal a degree of variability in the qualitative nature of this phenology-distance interaction, suggesting a possible explanation for observed variation in how migratory birds have already responded to climate change.