Managing aquatic habitat structure for resilient trophic interactions.

Structural habitat (the three-dimensional arrangement of physical matter, abiotic and biotic, at a location) is a foundational element for the resilience and maintenance of biodiversity, yet anthropogenic development is driving the global simplification of aquatic environments. Resource managers regularly seek to conserve aquatic food webs by increasing structural habitat complexity with expected benefits to fisheries; however, the global effectiveness of such actions is unclear. Our synthesis and theoretical analyses found that the response of a consumer-resource interaction (predatory sportfish and forage fish prey) to the addition of prey refuge habitat differed among systems with low and high rates of biomass transfer from resource to consumer (i.e., biomass potential); stabilization was not the rule. Greater prey refuge habitat availability tended to stabilize systems characterized by high biomass potential while simultaneously increasing consumer densities. In contrast, increasing prey refuge habitat availability in systems characterized by low biomass potential tended to mute energy transfer and moved consumer densities toward local extinction. Importantly, biomass potential and prey refuge can have antagonistic effects on stability and relative consumer densities, and it is therefore important to consider the local conditions of a system when using habitat manipulation as a management measure. Further development of our context-dependent perspective to whole food webs, and across different environments, may help to guide structural habitat management to better restore and protect aquatic ecosystems.

The Effect of Predator Population Dynamics on Batesian Mimicry Complexes.

AbstractUnderstanding Batesian mimicry is a classic problem in evolutionary biology. In Batesian mimicry, a defended species (the model) is mimicked by an undefended species (the mimic). Prior theories have emphasized the role of predator behavior and learning as well as evolution in model-mimic complexes but have not examined the role of population dynamics in potentially governing the relative abundances and even persistence of model-mimic systems. Here, we examined the effect of the population dynamics of predators and alternative prey on the prevalence of warning-signaling prey composed of models and mimics. Using optimal foraging theory and signal detection theory, we found that the inclusion of predator and alternative prey population dynamics could reverse traditional theoretical predictions: as alternative prey increase in numbers, mimics suffer because larger populations of predators are maintained, resulting in apparent competition. Under some circumstances, apparent competition affects model populations as well, although not as severely as it affects mimics. Our results bear on the intriguing puzzle that in nature warning signals are relatively scarce, yet experiments suggest that such signals can be highly advantageous. The availability of alternative prey and numerical responses by predators can overwhelm advantages observed in experiments to keep warning signals in model-mimic systems relatively scarce.

The Ubiquitous Soil Terpene Geosmin Acts as a Warning Chemical.

Known as the smell of earth after rain, geosmin is an odorous terpene detectable by humans at picomolar concentrations. Geosmin production is heavily conserved in actinobacteria, myxobacteria, cyanobacteria, and some fungi, but its biological activity is poorly understood. We theorized that geosmin was an aposematic signal used to indicate the unpalatability of toxin-producing microbes, discouraging predation by eukaryotes. Consistent with this hypothesis, we found that geosmin altered the behavior of the bacteriophagous nematode Caenorhabditis elegans on agar plates in the absence of bacteria. Normal movement was restored in mutant worms lacking differentiated ASE (amphid neurons, single ciliated endings) neurons, suggesting that geosmin is a taste detected by the nematodal gustatory system. In a predation assay, geosmin and the related terpene 2-methylisoborneol reduced grazing on the bacterium Streptomyces coelicolor. Predation was restored by the removal of both terpene biosynthetic pathways or the introduction of C. elegans that lacked differentiated ASE taste neurons, leading to the apparent death of both bacteria and worms. While geosmin and 2-methylisoborneol appeared to be nontoxic, grazing triggered bacterial sporulation and the production of actinorhodin, a pigment coproduced with a number of toxic metabolites. In this system, geosmin thus appears to act as a warning signal indicating the unpalatability of its producers and reducing predation in a manner that benefits predator and prey. This suggests that molecular signaling may affect microbial predator-prey interactions in a manner similar to that of the well-studied visual markers of poisonous animal prey. IMPORTANCE One of the key chemicals that give soil its earthy aroma, geosmin is a frequent water contaminant produced by a range of unrelated microbes. Many animals, including humans, are able to detect geosmin at minute concentrations, but the benefit that this compound provides to its producing organisms is poorly understood. We found that geosmin repelled the bacterial predator Caenorhabditis elegans in the absence of bacteria and reduced contact between the worms and the geosmin-producing bacterium Streptomyces coelicolor in a predation assay. While geosmin itself appears to be nontoxic to C. elegans, these bacteria make a wide range of toxic metabolites, and grazing on them harmed the worms. In this system, geosmin thus appears to indicate unpalatable bacteria, reducing predation and benefiting both predator and prey. Aposematic signals are well known in animals, and this work suggests that metabolites may play a similar role in the microbial world.

End-to-End Train Horn Detection for Railway Transit Safety.

The train horn sound is an active audible warning signal used for warning commuters and railway employees of the oncoming train(s), assuring a smooth operation and traffic safety, especially at barrier-free crossings. This work studies deep learning-based approaches to develop a system providing the early detection of train arrival based on the recognition of train horn sounds from the traffic soundscape. A custom dataset of train horn sounds, car horn sounds, and traffic noises is developed to conduct experiments and analysis. We propose a novel two-stream end-to-end CNN model (i.e., THD-RawNet), which combines two approaches of feature extraction from raw audio waveforms, for audio classification in train horn detection (THD). Besides a stream with a sequential one-dimensional CNN (1D-CNN) as in existing sound classification works, we propose to utilize multiple 1D-CNN branches to process raw waves in different temporal resolutions to extract an image-like representation for the 2D-CNN classification part. Our experiment results and comparative analysis have proved the effectiveness of the proposed two-stream network and the method of combining features extracted in multiple temporal resolutions. The THD-RawNet obtained better accuracies and robustness compared to those of baseline models trained on either raw audio or handcrafted features, in which at the input size of one second the network yielded an accuracy of 95.11% for testing data in normal traffic conditions and remained above a 93% accuracy for the considerable noisy condition of-10 dB SNR. The proposed THD system can be integrated into the smart railway crossing systems, private cars, and self-driving cars to improve railway transit safety.

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.

Conspicuous animal signals avoid the cost of predation by being intermittent or novel: confirmation in the wild using hundreds of robotic prey.

Social animals are expected to face a trade-off between producing a signal that is detectible by mates and rivals, but not obvious to predators. This trade-off is fundamental for understanding the design of many animal signals, and is often the lens through which the evolution of alternative communication strategies is viewed. We have a reasonable working knowledge of how conspecifics detect signals under different conditions, but how predators exploit conspicuous communication of prey is complex and hard to predict. We quantified predation on 1566 robotic lizard prey that performed a conspicuous visual display, possessed a conspicuous ornament or remained cryptic. Attacks by free-ranging predators were consistent across two contrasting ecosystems and showed robotic prey that performed a conspicuous display were equally likely to be attacked as those that remained cryptic. Furthermore, predators avoided attacking robotic prey with a fixed, highly visible ornament that was novel at both locations. These data show that it is prey familiarity-not conspicuousness-that determine predation risk. These findings replicated across different predator-prey communities not only reveal how conspicuous signals might evolve in high predation environments, but could help resolve the paradox of aposematism and why some exotic species avoid predation when invading new areas.

Distinctive patterns and signals at major environmental events and collapse zone boundaries.

We studied the patterns of pre-collapse communities, the small-scale and the large-scale signals of collapses, and the environmental events before the collapses using four paleoecological and one modern data series. We applied and evaluated eight indicators in our analysis: the relative abundance of species, hierarchical cluster analysis, principal component analysis, total abundance, species richness, standard deviation (without a rolling window), first-order autoregression, and the relative abundance of the dominant species. We investigated the signals at the probable collapse triggering unusual environmental events and at the collapse zone boundaries, respectively. We also distinguished between pulse and step environmental events to see what signals the indicators give at these two different types of events. Our results show that first-order autoregression is not a good environmental event indicator, but it can forecast or indicate the collapse zones in climate change. The rest of the indicators are more sensitive to the pulse events than to the step events. Step events during climate change might have an essential role in initiating collapses. These events probably push the communities with low resilience beyond a critical threshold, so it is crucial to detect them. Before collapses, the total abundance and the species richness increase, the relative abundance of the species decreases. The hierarchical cluster analysis and the relative abundance of species together designate the collapse zone boundaries. We suggest that small-scale signals should be involved in analyses because they are often earlier than large-scale signals.

Ventral hippocampus inactivation enhances the extinction of active avoidance responses in the presence of safety signals but leaves discrete trial operant active avoidance performance intact.

The acquisition of active avoidance (AA) behavior is typically aided by the presence of two signals-the warning signal, which predicts the future occurrence of an aversive event (e.g., shocks), and the safety signal, which is presented upon successful avoidance of oncoming shocks. While the warning signal could be conceived to act as a Pavlovian fear cue, and is likely mediated by brain areas that underlie Pavlovian fear cue conditioning, the neural substrates underlying safety signaling are less clear, largely due to the unavailability of AA tasks that are devoid of an explicit warning signal. The present study sought to investigate the role of the ventral hippocampus (VH) in safety signaled AA performance acquired without an explicit warning signal, using a novel discrete trial paradigm. Adult male Long Evans rats were divided into two groups and trained to acquire AA responses with, or without a safety signal. Analysis of the acquisition and stable state performance data revealed that the availability of a safety signal alone did not improve the acquisition or performance of AA responses. Furthermore, post-training, reversible VH inactivation did not impact stable state avoidance behavior. However, extinction of avoidance responses was facilitated in the group trained with a safety signal, and this effect was further potentiated by VH inactivation. Additional elevated plus maze (EPM), light-dark box, and locomotor tests demonstrated that VH inactivation reduced anxiety without affecting locomotor activity. Taken together, these results demonstrate the importance of VH in the extinction of persistent pathological avoidance behavior when safety is signaled.

Forecasting semi-arid biome shifts in the Anthropocene.

Shrub encroachment, forest decline and wildfires have caused large-scale changes in semi-arid vegetation over the past 50 years. Climate is a primary determinant of plant growth in semi-arid ecosystems, yet it remains difficult to forecast large-scale vegetation shifts (i.e. biome shifts) in response to climate change. We highlight recent advances from four conceptual perspectives that are improving forecasts of semi-arid biome shifts. Moving from small to large scales, first, tree-level models that simulate the carbon costs of drought-induced plant hydraulic failure are improving predictions of delayed-mortality responses to drought. Second, tracer-informed water flow models are improving predictions of species coexistence as a function of climate. Third, new applications of ecohydrological models are beginning to simulate small-scale water movement processes at large scales. Fourth, remotely-sensed measurements of plant traits such as relative canopy moisture are providing early-warning signals that predict forest mortality more than a year in advance. We suggest that a community of researchers using modeling approaches (e.g. machine learning) that can integrate these perspectives will rapidly improve forecasts of semi-arid biome shifts. Better forecasts can be expected to help prevent catastrophic changes in vegetation states by identifying improved monitoring approaches and by prioritizing high-risk areas for management.

Biased predation could promote convergence yet maintain diversity within Müllerian mimicry rings of Oreina leaf beetles.

Müllerian mimicry is a classic example of adaptation, yet Müller's original theory does not account for the diversity often observed in mimicry rings. Here, we aimed to assess how well classical Müllerian mimicry can account for the colour polymorphism found in chemically defended Oreina leaf beetles by using field data and laboratory assays of predator behaviour. We also evaluated the hypothesis that thermoregulation can explain diversity between Oreina mimicry rings. We found that frequencies of each colour morph were positively correlated among species, a critical prediction of Müllerian mimicry. Predators learned to associate colour with chemical defences. Learned avoidance of the green morph of one species protected green morphs of another species. Avoidance of blue morphs was completely generalized to green morphs, but surprisingly, avoidance of green morphs was less generalized to blue morphs. This asymmetrical generalization should favour green morphs: indeed, green morphs persist in blue communities, whereas blue morphs are entirely excluded from green communities. We did not find a correlation between elevation and coloration, rejecting thermoregulation as an explanation for diversity between mimicry rings. Biased predation could explain within-community diversity in warning coloration, providing a solution to a long-standing puzzle. We propose testable hypotheses for why asymmetric generalization occurs, and how predators maintain the predominance of blue morphs in a community, despite asymmetric generalization.

Defense of bombardier beetles against avian predators.

Bombardier beetles (Coleoptera, Carabidae, Brachininae) possess a remarkable defense mechanism where a hot chemical spray is released from the tip of their abdomen, with an audible explosive sound. To date, the repellent properties of these chemicals have been tested against a limited number of taxa, such as amphibians and insects. To investigate the impact of bombardier beetle defenses on avian predators, feeding trials were conducted using the bombardier beetle (Pheropsophus jessoensis) and the Japanese quail (Coturnix japonica), a sympatric and generalist predator. All naïve, hand-reared quail attacked live beetles, indicating the absence of an innate aversion to them. However, most of the quail rejected consuming the beetles whether or not the beetles sprayed them with chemicals. Naïve quail also rejected dead P. jessoensis individuals. These results support the recent hypothesis that it is not essential for P. jessoensis to spray noxious chemicals to deter predators. We also found that some of the quail exposed to live P. jessoensis remembered to avoid them for up to 5 weeks. Our results provide the first evidence of the repelling effects of bombardier beetle defense mechanisms on avian predators.

Detecting early-warning signals of influenza outbreak based on dynamic network marker.

The seasonal outbreaks of influenza infection cause globally respiratory illness, or even death in all age groups. Given early-warning signals preceding the influenza outbreak, timely intervention such as vaccination and isolation management effectively decrease the morbidity. However, it is usually a difficult task to achieve the real-time prediction of influenza outbreak due to its complexity intertwining both biological systems and social systems. By exploring rich dynamical and high-dimensional information, our dynamic network marker/biomarker (DNM/DNB) method opens a new way to identify the tipping point prior to the catastrophic transition into an influenza pandemics. In order to detect the early-warning signals before the influenza outbreak by applying DNM method, the historical information of clinic hospitalization caused by influenza infection between years 2009 and 2016 were extracted and assembled from public records of Tokyo and Hokkaido, Japan. The early-warning signal, with an average of 4-week window lead prior to each seasonal outbreak of influenza, was provided by DNM-based on the hospitalization records, providing an opportunity to apply proactive strategies to prevent or delay the onset of influenza outbreak. Moreover, the study on the dynamical changes of hospitalization in local district networks unveils the influenza transmission dynamics or landscape in network level.

Warning signals are under positive frequency-dependent selection in nature.

Positive frequency-dependent selection (FDS) is a selection regime where the fitness of a phenotype increases with its frequency, and it is thought to underlie important adaptive strategies resting on signaling and communication. However, whether and how positive FDS truly operates in nature remains unknown, which hampers our understanding of signal diversity. Here, we test for positive FDS operating on the warning color patterns of chemically defended butterflies forming multiple coexisting mimicry assemblages in the Amazon. Using malleable prey models placed in localities showing differences in the relative frequencies of warningly colored prey, we demonstrate that the efficiency of a warning signal increases steadily with its local frequency in the natural community, up to a threshold where protection stabilizes. The shape of this relationship is consistent with the direct effect of the local abundance of each warning signal on the corresponding avoidance knowledge of the local predator community. This relationship, which differs from purifying selection acting on each mimetic pattern, indicates that predator knowledge, integrated over the entire community, is saturated only for the most common warning signals. In contrast, among the well-established warning signals present in local prey assemblages, most are incompletely known to local predators and enjoy incomplete protection. This incomplete predator knowledge should generate strong benefits to life history traits that enhance warning efficiency by increasing the effective frequency of prey visible to predators. Strategies such as gregariousness or niche convergence between comimics may therefore readily evolve through their effects on predator knowledge and warning efficiency.

Early warning signals of regime shifts in coupled human-environment systems.

In complex systems, a critical transition is a shift in a system's dynamical regime from its current state to a strongly contrasting state as external conditions move beyond a tipping point. These transitions are often preceded by characteristic early warning signals such as increased system variability. However, early warning signals in complex, coupled human-environment systems (HESs) remain little studied. Here, we compare critical transitions and their early warning signals in a coupled HES model to an equivalent environment model uncoupled from the human system. We parameterize the HES model, using social and ecological data from old-growth forests in Oregon. We find that the coupled HES exhibits a richer variety of dynamics and regime shifts than the uncoupled environment system. Moreover, the early warning signals in the coupled HES can be ambiguous, heralding either an era of ecosystem conservationism or collapse of both forest ecosystems and conservationism. The presence of human feedback in the coupled HES can also mitigate the early warning signal, making it more difficult to detect the oncoming regime shift. We furthermore show how the coupled HES can be "doomed to criticality": Strategic human interactions cause the system to remain perpetually in the vicinity of a collapse threshold, as humans become complacent when the resource seems protected but respond rapidly when it is under immediate threat. We conclude that the opportunities, benefits, and challenges of modeling regime shifts and early warning signals in coupled HESs merit further research.

Spatial correlation as an early warning signal of regime shifts in a multiplex disease-behaviour network.

Early warning signals of sudden regime shifts are a widely studied phenomenon for their ability to quantify a system's proximity to a tipping point to a new and contrasting dynamical regime. However, this effect has been little studied in the context of the complex interactions between disease dynamics and vaccinating behaviour. Our objective was to determine whether critical slowing down (CSD) occurs in a multiplex network that captures opinion propagation on one network layer and disease spread on a second network layer. We parameterized a network simulation model to represent a hypothetical self-limiting, acute, vaccine-preventable infection with short-lived natural immunity. We tested five different network types: random, lattice, small-world, scale-free, and an empirically derived network. For the first four network types, the model exhibits a regime shift as perceived vaccine risk moves beyond a tipping point from full vaccine acceptance and disease elimination to full vaccine refusal and disease endemicity. This regime shift is preceded by an increase in the spatial correlation in non-vaccinator opinions beginning well before the bifurcation point, indicating CSD. The early warning signals occur across a wide range of parameter values. However, the more gradual transition exhibited in the empirically-derived network underscores the need for further research before it can be determined whether trends in spatial correlation in real-world social networks represent critical slowing down. The potential upside of having this monitoring ability suggests that this is a worthwhile area for further research.

Regime shifts and ecological catastrophes in a model of plankton-oxygen dynamics under the climate change.

It is estimated that more than a half of the total atmospheric oxygen is produced in the oceans due to the photosynthetic activity of phytoplankton. Any significant decrease in the net oxygen production by phytoplankton is therefore likely to result in the depletion of atmospheric oxygen and in a global mass mortality of animals and humans. In its turn, the rate of oxygen production is known to depend on water temperature and hence can be affected by the global warming. We address this problem theoretically by considering a model of a coupled plankton-oxygen dynamics where the rate of oxygen production slowly changes with time to account for the ocean warming. We show that, when the temperature rises sufficiently high, a regime shift happens: the sustainable oxygen production becomes impossible and the system's dynamics leads to fast oxygen depletion and plankton extinction. We also consider a scenario when, after a certain period of increase, the temperature is set on a new higher yet apparently safe value, i.e. before the oxygen depletion disaster happens. We show that in this case the system dynamics may exhibit a long-term quasi-sustainable dynamics that can still result in an ecological disaster (oxygen depletion and mass extinctions) but only after a considerable period of time. Finally, we discuss the early warning signals of the approaching regime shift resulting in the disaster.

Response of three cyprinid fish species to the Scavenger Deterrent Factor produced by the mutualistic bacteria associated with entomopathogenic nematodes.

The symbiotic bacteria, Photorhabdus and Xenorhabdus associated with entomopathogenic nematodes (EPNs) in the genera Heterorhabditis and Steinernema, respectively, produce a compound(s) called the Scavenging Deterrent Factor (SDF). SDF deters a number of terrestrial insect scavengers and predators and one bird species from feeding on host insects killed by the nematode-bacterium complex but has not been tested against aquatic vertebrates. Moreover, the Heterorhabditis-Photorhabdus association is believed to have evolved in an aquatic environment. Accordingly, we hypothesized that SDF will deter fish from feeding on nematode-killed insects and tested the responses of three omnivorous fresh water fish species, Devario aequipinnatus, Alburnoides bipunctatus, and Squalius pursakensis, to SDF in the laboratory. When the fish were exposed to Galleria mellonella larvae killed by the Heterorhabditis- or Steinernema-bacterium complex at 2 or 4days post-infection, all three fish species made several attempts to consume the cadavers but subsequently rejected them. However, all fish species consumed freeze-killed control larvae. In a choice test, when D. aequipinnatus or A. bipunctatus were offered a pair of nematode-killed larvae, both fish species rejected these cadavers; when offered a nematode-killed larva and a freeze-killed larva, both fish species consumed the freeze-killed larva but not the nematode-killed one. In further tests with D. aequipinnatus, there was no significant difference in the number of 2-day-old Bacillus thuringiensis subsp. kurstaki-killed (Btk) larvae consumed compared to freeze-killed larvae, but significantly fewer 4-day-old Btk-killed larvae were consumed compared to freeze-killed larvae. When D. aequipinnatus was fed G. mellonella larvae killed by the symbiotic bacteria, the fish rejected the cadavers. When given freeze-killed or nematode-killed mosquito (Aedes aegypti) larvae, the fish consumed significantly more of the former larvae (99%) compared to the latter (55%). When D. aequipinnatus was placed in a symbiotic cell-free supernatant for 18h, a significant reduction in consumption of freeze-killed larvae compared to cell-free Btk or control broth supernatant was observed. We showed that SDF protects the nematode-killed insects from being consumed by omnivorous fishes and suggests that they will have minimal effects on recycling of EPNs in the aquatic environment.

Early warning of critical transitions in biodiversity from compositional disorder.

Global environmental change presents a clear need for improved leading indicators of critical transitions, especially those that can be generated from compositional data and that work in empirical cases. Ecological theory of community dynamics under environmental forcing predicts an early replacement of slowly replicating and weakly competitive "canary" species by slowly replicating but strongly competitive "keystone" species. Further forcing leads to the eventual collapse of the keystone species as they are replaced by weakly competitive but fast-replicating "weedy" species in a critical transition to a significantly different state. We identify a diagnostic signal of these changes in the coefficients of a correlation between compositional disorder and biodiversity. Compositional disorder measures unpredictability in the composition of a community, while biodiversity measures the amount of species in the community. In a stochastic simulation, sequential correlations over time switch from positive to negative as keystones prevail over canaries, and back to positive with domination of weedy species. The model finds support in empirical tests on multi-decadal time series of fossil diatom and chironomid communities from lakes in China. The characteristic switch from positive to negative correlation coefficients occurs for both communities up to three decades preceding a critical transition to a sustained alternate state. This signal is robust to unequal time increments that beset the identification of early-warning signals from other metrics.

Costs and benefits of plant allelochemicals in herbivore diet in a multi enemy world.

Sequestration of plant defensive chemicals by herbivorous insects is a way of defending themselves against their natural enemies. Such herbivores have repeatedly evolved bright colours to advertise their unpalatability to predators, i.e. they are aposematic. This often comes with a cost. In this study, we examined the costs and benefits of sequestration of iridoid glycosides (IGs) by the generalist aposematic herbivore, the wood tiger moth, Parasemia plantaginis. We also asked whether the defence against one enemy (a predator) is also effective against another (a parasitoid). We found that the larvae excrete most of the IGs and only small amounts are found in the larvae. Nevertheless, the amounts present in the larvae are sufficient to deter ant predators and also play a role in defence against parasitoids. However, excreting and handling these defensive plant compounds is costly, leading to longer development time and lower pupal mass. Interestingly, the warning signal efficiency and the amount of IGs in the larvae of P. plantaginis are negatively correlated; larvae with less efficient warning signals contain higher levels of chemical defence compounds. Our results may imply that there is a trade-off between production and maintenance of coloration and chemical defence. Although feeding on a diet containing IGs can have life-history costs, it offers multiple benefits in the defence against predators and parasitoids.

Cancer systems biology in the genome sequencing era: part 2, evolutionary dynamics of tumor clonal networks and drug resistance.

A tumor often consists of multiple cell subpopulations (clones). Current chemo-treatments often target one clone of a tumor. Although the drug kills that clone, other clones overtake it and the tumor recurs. Genome sequencing and computational analysis allows to computational dissection of clones from tumors, while singe-cell genome sequencing including RNA-Seq allows profiling of these clones. This opens a new window for treating a tumor as a system in which clones are evolving. Future cancer systems biology studies should consider a tumor as an evolving system with multiple clones. Therefore, topics discussed in Part 2 of this review include evolutionary dynamics of clonal networks, early-warning signals (e.g., genome duplication events) for formation of fast-growing clones, dissecting tumor heterogeneity, and modeling of clone-clone-stroma interactions for drug resistance. The ultimate goal of the future systems biology analysis is to obtain a 'whole-system' understanding of a tumor and therefore provides a more efficient and personalized management strategies for cancer patients.