Identification of jellyfish from Continuous Plankton Recorder samples

Previous analysis of the Continuous Plankton Recorder (CPR) long-term data set for the presence of ‘coelenterate’ tissue revealed changes in the frequency of jellyfish occurrence in the North Atlantic Ocean and North Sea; however, the identities of the jellyfish were unknown, causing uncertainty in interpreting these findings. To improve the utility of the ‘coelenterate’ data from the CPR, 62 CPR samples were selected for re-analysis from an area where the widespread occurrence of the holoplanktonic scyphomedusan, Pelagia noctiluca (Forsskål, 1775), was previously documented from net tows to test if the CPR sampled P. noctiluca. Examination of the samples revealed smears (<1 mm) of golden gelatinous tissue on the sampling mesh. Subsequent microscopic examination and measurement of nematocysts identified most of the smears as P. noctiluca. Indeed, P. noctiluca was identified on 53% of the CPR samples from the area that best coincided with the documented bloom area. Although hydrozoans were also identified in the samples, the characteristic golden colour of P. noctiluca and its distinct suite of nematocysts allowed identification to species level. The identification of other jellyfish may be more complicated due to the labour-intensive examination of samples and unclear delineation of nematocyst types when multiple similar species are present. Nevertheless, re-analysis of CPR samples holds great promise for identifying the underlying reason for increases in jellyfish occurrence in the CPR records.     

Analysis of <Emphasis Type="Italic">Pelagia noctiluca</Emphasis> proteome Reveals a Red Fluorescent Protein,a Zinc Metalloproteinase and a Peroxiredoxin

Pelagia noctiluca is the most venomous jellyfish in the Mediterranean Sea where it forms dense blooms. Although there is several published research on this species, until now none of the works has been focused on a complete protein profile of the all body constituents of this organism. Here, we have performed a detailed proteomics characterization of the major protein components expressed by P. noctiluca. With that aim, we have considered the study of jellyfish proteins involved in defense, body constituents and metabolism, and furthered explore the significance and potential application of such bioactive molecules. P. noctiluca body proteins were separated by1D SDS–PAGE and 2DE followed by characterization by nanoLC-MS/MS and MALDI-TOF/TOF techniques. Altogether, both methods revealed 68 different proteins, including a Zinc Metalloproteinase, a Red Fluorescent Protein (RFP) and a Peroxiredoxin. These three proteins were identified for the first time in P. noctiluca. Zinc Metalloproteinase was previously reported in the venom of other jellyfish species. Besides the proteins described above, the other 65 proteins found in P. noctiluca body content were identified and associated with its clinical significance. Among all the proteins identified in this work we highlight: Zinc metalloproteinase, which has a ShK toxin domain and therefore should be implicated in the sting toxicity of P. noctiluca.; the RFP which are a very important family of proteins due to its possible application as molecular markers; and last but not least the discovery of a Peroxiredoxin in this organism makes it a new natural resource of antioxidant and anti-UV radiation agents.     

Jellyfish Stings Trigger Gill Disorders and Increased Mortality in Farmed Sparus aurata (Linnaeus, 1758) in the Mediterranean Sea

Jellyfish are of particular concern for marine finfish aquaculture. In recent years repeated mass mortality episodes of farmed fish were caused by blooms of gelatinous cnidarian stingers, as a consequence of a wide range of hemolytic, cytotoxic, and neurotoxic properties of associated cnidocytes venoms. The mauve stinger jellyfish Pelagia noctiluca (Scyphozoa) has been identified as direct causative agent for several documented fish mortality events both in Northern Europe and the Mediterranean Sea aquaculture farms. We investigated the effects of P. noctiluca envenomations on the gilthead sea bream Sparus aurata by in vivo laboratory assays. Fish were incubated for 8 hours with jellyfish at 3 different densities in 300 l experimental tanks. Gill disorders were assessed by histological analyses and histopathological scoring of samples collected at time intervals from 3 hours to 4 weeks after initial exposure. Fish gills showed different extent and severity of gill lesions according to jellyfish density and incubation time, and long after the removal of jellyfish from tanks. Jellyfish envenomation elicits local and systemic inflammation reactions, histopathology and gill cell toxicity, with severe impacts on fish health. Altogether, these results shows P. noctiluca swarms may represent a high risk for Mediterranean finfish aquaculture farms, generating significant gill damage after only a few hours of contact with farmed S. aurata. Due to the growth of the aquaculture sector and the increased frequency of jellyfish blooms in the coastal waters, negative interactions between stinging jellyfish and farmed fish are likely to increase with the potential for significant economic losses.     

High‐resolution genetic analysis reveals extensive gene flow within the jellyfish Pelagia noctiluca (Scyphozoa) in the North Atlantic and Mediterranean Sea

Despite the importance of gelatinous zooplankton as components of marine ecosystems, both ecologically and socio‐economically, relatively little information is known about population persistence or connectivity in jellyfish. In the present study, we employed a combination of nuclear microsatellite markers and sequence data from the mitochondrial cytochrome oxidase I (COI) gene to determine levels and patterns of population genetic structuring in the holoplanktonic jellyfish Pelagia noctiluca across the northeast Atlantic Ocean and Mediterranean Sea. Our results indicate a high degree of connectivity in P. noctiluca, with little evidence of geographical structuring of genetic variation. A small but significant differentiation of Atlantic Ocean and Mediterranean stocks was detected based on the microsatellite data, but no evidence of differentiation was observed with the mtDNA, probably due to the higher power of the microsatellites to detect low levels of genetic structuring. Two clearly distinct groups of genotypes were observed within the mtDNA COI, which probably diverged in the early Pleistocene, but with no evidence of geographical structuring. Palaeodistribution modelling of P. noctiluca at the Last Glacial Maximum (LGM; c. 21 Kya) indicated large areas of suitable habitat south of the species’ current‐day distribution, with little reduction in area. The congruent evidence for minimal genetic differentiation from the nuclear microsatellites and the mtDNA, coupled with the results of the palaeodistribution modelling, supports the idea of long‐term population stability and connectivity, thus providing key insights into the population dynamics and demography of this important species.     

Jellyfish as Prey: Frequency of Predation and Selective Foraging of Boops boops (Vertebrata,Actinopterygii) on the Mauve Stinger Pelagia noctiluca (Cnidaria,Scyphozoa)

In recent years, jellyfish blooms have attracted considerable scientific interest for their potential impacts on human activities and ecosystem functioning, with much attention paid to jellyfish as predators and to gelatinous biomass as a carbon sink. Other than qualitative data and observations, few studies have quantified direct predation of fish on jellyfish to clarify whether they may represent a seasonally abundant food source. Here we estimate predation frequency by the commercially valuable Mediterranean bogue, Boops boops on the mauve stinger jellyfish, Pelagia noctiluca, in the Strait of Messina (NE Sicily). A total of 1054 jellyfish were sampled throughout one year to quantify predation by B. boops from bite marks on partially eaten jellyfish and energy density of the jellyfish. Predation by B. boops in summer was almost twice that in winter, and they selectively fed according to medusa gender and body part. Calorimetric analysis and biochemical composition showed that female jellyfish gonads had significantly higher energy content than male gonads due to more lipids and that gonads had six-fold higher energy content than the somatic tissues due to higher lipid and protein concentrations. Energetically, jellyfish gonads represent a highly rewarding food source, largely available to B. boops throughout spring and summer. During the remainder of the year, when gonads were not very evident, fish predation switched towards less-selective foraging on the somatic gelatinous biomass. P. noctiluca, the most abundant jellyfish species in the Mediterranean Sea and a key planktonic predator, may represent not only a nuisance for human leisure activities and a source of mortality for fish eggs and larvae, but also an important resource for fish species of commercial value, such as B. boops.     

Habitat dependence and correlations between elasticities of long-term growth rates

In population biology, elasticity is a measure of the importance of a demographic rate on population growth. A relatively small amount of stochasticity can substantially impact the dynamics of a population whose growth is a function of deterministic and stochastic processes. Analyses of natural populations frequently neglect the latter. Even in a population that fluctuates substantially with time, the results of a deterministic perturbation analysis correlated strongly with results of a perturbation analysis of the long-run stochastic growth rate. Population growth was, however, not uniformly sensitive to demographic rates across different environmental conditions. The overall correlation between deterministic and stochastic perturbation analysis may be high, but environmental variability can dramatically alter the contributions of demographic rates in different environmental conditions. This potentially informative detail is neglected by deterministic analysis, yet it highlights one difficulty when extrapolating results from long-term analysis to shorter-term environmental change.     

A blooming jellyfish in the northeast Atlantic and Mediterranean

A long-term time series of plankton records collected by the continuous plankton recorder (CPR) Survey in the northeast Atlantic indicates an increased occurrence of Cnidaria since 2002. In the years 2007 and 2008, outbreaks of the warm-temperate scyphomedusa, Pelagia noctiluca, appeared in CPR samples between 45° N to 58° N and 1° W to 26° W. Knowing the biology of this species and its occurrence in the adjacent Mediterranean Sea, we suggest that P. noctiluca may be exploiting recent hydroclimatic changes in the northeast Atlantic to increase its extent and intensity of outbreaks. In pelagic ecosystems, Cnidaria can affect fish recruitment negatively. Since P. noctiluca is a highly venomous species, outbreaks can also be detrimental to aquaculture and make bathing waters unusable, thus having profound ecological and socio-economic consequences.     

Disentangling the importance of ecological niches from stochastic processes across scales

Deterministic theories in community ecology suggest that local, niche-based processes, such as environmental filtering, biotic interactions and interspecific trade-offs largely determine patterns of species diversity and composition. In contrast, more stochastic theories emphasize the importance of chance colonization, random extinction and ecological drift. The schisms between deterministic and stochastic perspectives, which date back to the earliest days of ecology, continue to fuel contemporary debates (e.g. niches versus neutrality). As illustrated by the pioneering studies of Robert H. MacArthur and co-workers, resolution to these debates requires consideration of how the importance of local processes changes across scales. Here, we develop a framework for disentangling the relative importance of deterministic and stochastic processes in generating site-to-site variation in species composition (β-diversity) along ecological gradients (disturbance, productivity and biotic interactions) and among biogeographic regions that differ in the size of the regional species pool. We illustrate how to discern the importance of deterministic processes using null-model approaches that explicitly account for local and regional factors that inherently create stochastic turnover. By embracing processes across scales, we can build a more synthetic framework for understanding how niches structure patterns of biodiversity in the face of stochastic processes that emerge from local and biogeographic factors.     

Relative Importance of Deterministic and Stochastic Processes in Driving Arbuscular Mycorrhizal Fungal Assemblage during the Spreading of a Toxic Plant

Both deterministic and stochastic processes are expected to drive the assemblages of arbuscular mycorrhizal (AM) fungi, but little is known about the relative importance of these processes during the spreading of toxic plants. Here, the species composition and phylogenetic structure of AM fungal communities colonizing the roots of a toxic plant, Ligularia virgaurea, and its neighborhood plants, were analyzed in patches with different individual densities of L. virgaurea (represents the spreading degree). Community compositions of AM fungi in both root systems were changed significantly by the L. virgaurea spreading, and also these communities fitted the neutral model very well. AM fungal communities in patches with absence and presence of L. virgaurea were phylogenetically random and clustered, respectively, suggesting that the principal ecological process determining AM fungal assemblage shifted from stochastic process to environmental filtering when this toxic plant was present. Our results indicate that deterministic and stochastic processes together determine the assemblage of AM fungi, but the dominant process would be changed by the spreading of toxic plants, and suggest that the spreading of toxic plants in alpine meadow ecosystems might be involving the mycorrhizal symbionts.     

Allee effect makes possible patchy invasion in a predator–prey system

The dynamics of interacting ecological populations results from the interplay between various deterministic and stochastic factors and this is particularly the case for the phenomenon of biological invasion. Whereas the spread of invasive species via propagation of a population front was shown to appear as a result of deterministic processes, the spread via formation, interaction and movement of separate patches has been recently attributed to the influence of environmental stochasticity. An appropriate understanding of the comparative importance of deterministic and stochastic mechanisms is still lacking, however. In this paper, we show that the patchy invasion appears to be possible also in a fully deterministic predator–prey model as a result of the Allee effect.     

Partitioning the effects of deterministic and stochastic processes on species extinction risk

Species populations are subjected to deterministic and stochastic processes, both of which contribute to their risk of extinction. However, current understanding of the relative contributions of these processes to species extinction risk is far from complete. Here, we address this knowledge gap by analyzing a suite of models representing species populations with negative intrinsic growth rates, to partition extinction risk according to deterministic processes and two broad classes of stochastic processes – demographic and environmental variance. Demographic variance refers to random variations in population abundance arising from random sampling of events given a particular set of intrinsic demographic rates, whereas environmental variance refers to random abundance variations arising from random changes in intrinsic demographic rates over time. When the intrinsic growth rate was not close to zero, we found that deterministic growth was the main driver of mean time to extinction, even when population size was small. This contradicts the intuition that demographic variance is always an important determinant of extinction risk for small populations. In contrast, when the intrinsic growth rate was close to zero, stochastic processes exerted substantial negative effects on the mean time to extinction. Demographic variance had a greater effect than environmental variance at low abundances, with the reverse occurring at higher abundances. In addition, we found that the combined effects of demographic and environmental variance were often substantially lower than the sum of their effects in isolation from each other. This sub-additivity indicates redundancy in the way the two stochastic processes increase extinction risk, and probably arises because both processes ultimately increase extinction risk by boosting variation in abundance over time.     

Disentangling the Spatio-Environmental Drivers of Human Settlement: An Eigenvector Based Variation Decomposition

The relative importance of deterministic and stochastic processes driving patterns of human settlement remains controversial. A main reason for this is that disentangling the drivers of distributions and geographic clustering at different spatial scales is not straightforward and powerful analytical toolboxes able to deal with this type of data are largely deficient. Here we use a multivariate statistical framework originally developed in community ecology, to infer the relative importance of spatial and environmental drivers of human settlement. Using Moran’s eigenvector maps and a dataset of spatial variation in a set of relevant environmental variables we applied a variation partitioning procedure based on redundancy analysis models to assess the relative importance of spatial and environmental processes explaining settlement patterns. We applied this method on an archaeological dataset covering a 15 km² area in SW Turkey spanning a time period of 8000 years from the Late Neolithic/Early Chalcolithic up to the Byzantine period. Variation partitioning revealed both significant unique and commonly explained effects of environmental and spatial variables. Land cover and water availability were the dominant environmental determinants of human settlement throughout the study period, supporting the theory of the presence of farming communities. Spatial clustering was mainly restricted to small spatial scales. Significant spatial clustering independent of environmental gradients was also detected which can be indicative of expansion into unsuitable areas or an unexpected absence in suitable areas which could be caused by dispersal limitation. Integrating historic settlement patterns as additional predictor variables resulted in more explained variation reflecting temporal autocorrelation in settlement locations.     

Temporal Changes in Randomness of Bird Communities across Central Europe

Many studies have examined whether communities are structured by random or deterministic processes, and both are likely to play a role, but relatively few studies have attempted to quantify the degree of randomness in species composition. We quantified, for the first time, the degree of randomness in forest bird communities based on an analysis of spatial autocorrelation in three regions of Germany. The compositional dissimilarity between pairs of forest patches was regressed against the distance between them. We then calculated the y-intercept of the curve, i.e. the ‘nugget’, which represents the compositional dissimilarity at zero spatial distance. We therefore assume, following similar work on plant communities, that this represents the degree of randomness in species composition. We then analysed how the degree of randomness in community composition varied over time and with forest management intensity, which we expected to reduce the importance of random processes by increasing the strength of environmental drivers. We found that a high portion of the bird community composition could be explained by chance (overall mean of 0.63), implying that most of the variation in local bird community composition is driven by stochastic processes. Forest management intensity did not consistently affect the mean degree of randomness in community composition, perhaps because the bird communities were relatively insensitive to management intensity. We found a high temporal variation in the degree of randomness, which may indicate temporal variation in assembly processes and in the importance of key environmental drivers. We conclude that the degree of randomness in community composition should be considered in bird community studies, and the high values we find may indicate that bird community composition is relatively hard to predict at the regional scale.     

Environmental control of phase transition and polyp survival of a massive-outbreaker jellyfish

A number of causes have been proposed to account for the occurrence of gelatinous zooplankton (both jellyfish and ctenophore) blooms. Jellyfish species have a complex life history involving a benthic asexual phase (polyp) and a pelagic sexual phase (medusa). Strong environmental control of jellyfish life cycles is suspected, but not fully understood. This study presents a comprehensive analysis on the physicochemical conditions that control the survival and phase transition of Cotylorhiza tuberculata; a scyphozoan that generates large outbreaks in the Mediterranean Sea. Laboratory experiments indicated that the influence of temperature on strobilation and polyp survival was the critical factor controlling the capacity of this species to proliferate. Early life stages were less sensitive to other factors such as salinity variations or the competitive advantage provided by zooxanthellae in a context of coastal eutrophication. Coherently with laboratory results, the presence/absence of outbreaks of this jellyfish in a particular year seems to be driven by temperature. This is the first time the environmental forcing of the mechanism driving the life cycle of a jellyfish has been disentangled via laboratory experimentation. Projecting this understanding to a field population under climatological variability results in a pattern coherent with in situ records.     

Parameter estimation and inference for stochastic reaction-diffusion systems: application to morphogenesis in D. melanogaster

Background  

Reaction-diffusion systems are frequently used in systems biology to model developmental and signalling processes. In many applications, count numbers of the diffusing molecular species are very low, leading to the need to explicitly model the inherent variability using stochastic methods. Despite their importance and frequent use, parameter estimation for both deterministic and stochastic reaction-diffusion systems is still a challenging problem.     

Defining marine bacterioplankton community assembly rules by contrasting the importance of environmental determinants and biotic interactions

Bacterioplankton communities govern marine productivity and biogeochemical cycling, yet drivers of bacterioplankton assembly remain unclear. Here, we contrast the relative contribution of deterministic processes (environmental factors and biotic interactions) in driving temporal dynamics of bacterioplankton diversity at three different oceanographic time series locations, spanning 15° of latitude, which are each characterized by different environmental conditions and varying degrees of seasonality. Monthly surface samples (5.5 years) were analysed using 16S rRNA amplicon sequencing. The high- and mid-latitude sites of Maria Island and Port Hacking were characterized by high and intermediate levels of environmental heterogeneity, respectively, with both alpha diversity (72%; 24% of total variation) and beta diversity (32%; 30%) patterns within bacterioplankton assemblages explained by day length, ammonium, and mixed layer depth. In contrast, North Stradbroke Island, a sub-tropical location where environmental conditions are less variable, interspecific interactions were of increased importance in structuring bacterioplankton diversity (alpha: 33%; beta: 26%) with environment only contributing 11% and 13% to predicting diversity, respectively. Our results demonstrate that bacterioplankton diversity is the result of both deterministic environmental and biotic processes and that the importance of these different deterministic processes varies, potential in response to environmental heterogeneity.     

Physiological analysis on oscillatory behavior of glucose-insulin regulation by model with delays

Despite temporally forced transmission driving many infectious diseases, analytical insight into its role when combined with stochastic disease processes and non-linear transmission has received little attention. During disease outbreaks, however, the absence of saturation effects early on in well-mixed populations mean that epidemic models may be linearised and we can calculate outbreak properties, including the effects of temporal forcing on fade-out, disease emergence and system dynamics, via analysis of the associated master equations. The approach is illustrated for the unforced and forced SIR and SEIR epidemic models. We demonstrate that in unforced models, initial conditions (and any uncertainty therein) play a stronger role in driving outbreak properties than the basic reproduction number R₀, while the same properties are highly sensitive to small amplitude temporal forcing, particularly when R₀ is small. Although illustrated for the SIR and SEIR models, the master equation framework may be applied to more realistic models, although analytical intractability scales rapidly with increasing system dimensionality. One application of these methods is obtaining a better understanding of the rate at which vector-borne and waterborne infectious diseases invade new regions given variability in environmental drivers, a particularly important question when addressing potential shifts in the global distribution and intensity of infectious diseases under climate change.     

Homing behaviour by destructive crown-of-thorns starfish is triggered by local availability of coral prey

Corallivorous crown-of-thorns starfishes (Acanthaster spp.) can decimate coral assemblages on Indo-Pacific coral reefs during population outbreaks. While initial drivers of population irruptions leading to outbreaks remain largely unknown, subsequent dispersal of outbreaks appears coincident with depletion of coral prey. Here, we used in situ time-lapse photography to characterize movement of the Pacific crown-of-thorns starfish (Acanthaster cf. solaris) in the northern and southern Great Barrier Reef in 2015, during the fourth recorded population outbreak of the starfish, but prior to widespread coral bleaching. Daily tracking of 58 individuals over a total of 1117 h revealed all starfish to move a minimum of 0.52 m, with around half of all tracked starfish showing negligible daily displacement (less than 1 m day⁻¹), ranging up to a maximum of 19 m day⁻¹. Movement was primarily nocturnal and daily displacement varied spatially with variation in local availability of Acropora spp., which is the preferred coral prey. Two distinct behavioural modes emerged: (i) homing movement, whereby tracked paths (as tested against a random-walk-model) involved short displacement distances following distinct ‘outward'' movement to Acropora prey (typically displaying ‘feeding scars'') and ‘homebound'' movement to nearby shelter; versus (ii) roaming movement, whereby individuals showed directional movement beyond initial tracking positions without return. Logistic modelling revealed more than half of all tracked starfish demonstrated homing when local abundance (percentage cover) of preferred Acropora coral prey was greater than 33%. Our results reveal facultative homing by Acanthaster with the prey-dependent behavioural switch to roaming forays providing a mechanism explaining localized aggregations and diffusion of these population irruptions as prey is locally depleted.     

Stochastic S-system modeling of gene regulatory network

Microarray gene expression data can provide insights into biological processes at a system-wide level and is commonly used for reverse engineering gene regulatory networks (GRN). Due to the amalgamation of noise from different sources, microarray expression profiles become inherently noisy leading to significant impact on the GRN reconstruction process. Microarray replicates (both biological and technical), generated to increase the reliability of data obtained under noisy conditions, have limited influence in enhancing the accuracy of reconstruction . Therefore, instead of the conventional GRN modeling approaches which are deterministic, stochastic techniques are becoming increasingly necessary for inferring GRN from noisy microarray data. In this paper, we propose a new stochastic GRN model by investigating incorporation of various standard noise measurements in the deterministic S-system model. Experimental evaluations performed for varying sizes of synthetic network, representing different stochastic processes, demonstrate the effect of noise on the accuracy of genetic network modeling and the significance of stochastic modeling for GRN reconstruction . The proposed stochastic model is subsequently applied to infer the regulations among genes in two real life networks: (1) the well-studied IRMA network, a real-life in-vivo synthetic network constructed within the Saccharomycescerevisiae yeast, and (2) the SOS DNA repair network in Escherichiacoli.