Long-term cyclic persistence in an experimental predator-prey system.

Predator-prey cycles rank among the most fundamental concepts in ecology, are predicted by the simplest ecological models and enable, theoretically, the indefinite persistence of predator and prey1-4. However, it remains an open question for how long cyclic dynamics can be self-sustained in real communities. Field observations have been restricted to a few cycle periods5-8 and experimental studies indicate that oscillations may be short-lived without external stabilizing factors9-19. Here we performed microcosm experiments with a planktonic predator-prey system and repeatedly observed oscillatory time series of unprecedented length that persisted for up to around 50 cycles or approximately 300 predator generations. The dominant type of dynamics was characterized by regular, coherent oscillations with a nearly constant predator-prey phase difference. Despite constant experimental conditions, we also observed shorter episodes of irregular, non-coherent oscillations without any significant phase relationship. However, the predator-prey system showed a strong tendency to return to the dominant dynamical regime with a defined phase relationship. A mathematical model suggests that stochasticity is probably responsible for the reversible shift from coherent to non-coherent oscillations, a notion that was supported by experiments with external forcing by pulsed nutrient supply. Our findings empirically demonstrate the potential for infinite persistence of predator and prey populations in a cyclic dynamic regime that shows resilience in the presence of stochastic events.

Estimation of functional diversity and species traits from ecological monitoring data.

The twin crises of climate change and biodiversity loss define a strong need for functional diversity monitoring. While the availability of high-quality ecological monitoring data is increasing, the quantification of functional diversity so far requires the identification of species traits, for which data are harder to obtain. However, the traits that are relevant for the ecological function of a species also shape its performance in the environment and hence, should be reflected indirectly in its spatiotemporal distribution. Thus, it may be possible to reconstruct these traits from a sufficiently extensive monitoring dataset. Here, we use diffusion maps, a deterministic and de facto parameter-free analysis method, to reconstruct a proxy representation of the species' traits directly from monitoring data and use it to estimate functional diversity. We demonstrate this approach with both simulated data and real-world phytoplankton monitoring data from the Baltic Sea. We anticipate that wider application of this approach to existing data could greatly advance the analysis of changes in functional biodiversity.

Comment on "Indirect Fitness Benefits Enable the Spread of Host Genes Promoting Costly Transfer of Beneficial Plasmids".

Plasmid transfer contributes significantly to bacterial evolution, but the forces selecting such generosity are poorly understood; this Formal Comment revisits a study which examined these forces both analytically and experimentally, making a correction to the algebra and reaching strikingly different results.

Dynamic scaling and stochastic fractal in nucleation and growth processes.

A class of nucleation and growth models of a stable phase is investigated for various different growth velocities. It is shown that for growth velocities v ≈ s ( t ) / t and v ≈ x / τ ( x ), where s ( t ) and τ are the mean domain size of the metastable phase (M-phase) and the mean nucleation time, respectively, the M-phase decays following a power law. Furthermore, snapshots at different time t that are taken to collect data for the distribution function c ( x , t ) of the domain size x of the M-phase are found to obey dynamic scaling. Using the idea of data-collapse, we show that each snapshot is a self-similar fractal. However, for v = const ., such as in the classical Kolmogorov-Johnson-Mehl-Avrami model, and for v ≈ 1 / t, the decays of the M-phase are exponential and they are not accompanied by dynamic scaling. We find a perfect agreement between numerical simulation and analytical results.

Shape matters: the relationship between cell geometry and diversity in phytoplankton.

Size and shape profoundly influence an organism's ecophysiological performance and evolutionary fitness, suggesting a link between morphology and diversity. However, not much is known about how body shape is related to taxonomic richness, especially in microbes. Here we analyse global datasets of unicellular marine phytoplankton, a major group of primary producers with an exceptional diversity of cell sizes and shapes and, additionally, heterotrophic protists. Using two measures of cell shape elongation, we quantify taxonomic diversity as a function of cell size and shape. We find that cells of intermediate volume have the greatest shape variation, from oblate to extremely elongated forms, while small and large cells are mostly compact (e.g. spherical or cubic). Taxonomic diversity is strongly related to cell elongation and cell volume, together explaining up to 92% of total variance. Taxonomic diversity decays exponentially with cell elongation and displays a log-normal dependence on cell volume, peaking for intermediate-volume cells with compact shapes. These previously unreported broad patterns in phytoplankton diversity reveal selective pressures and ecophysiological constraints on the geometry of phytoplankton cells which may improve our understanding of marine ecology and the evolutionary rules of life.

Global rise in emerging alien species results from increased accessibility of new source pools.

Our ability to predict the identity of future invasive alien species is largely based upon knowledge of prior invasion history. Emerging alien species-those never encountered as aliens before-therefore pose a significant challenge to biosecurity interventions worldwide. Understanding their temporal trends, origins, and the drivers of their spread is pivotal to improving prevention and risk assessment tools. Here, we use a database of 45,984 first records of 16,019 established alien species to investigate the temporal dynamics of occurrences of emerging alien species worldwide. Even after many centuries of invasions the rate of emergence of new alien species is still high: One-quarter of first records during 2000-2005 were of species that had not been previously recorded anywhere as alien, though with large variation across taxa. Model results show that the high proportion of emerging alien species cannot be solely explained by increases in well-known drivers such as the amount of imported commodities from historically important source regions. Instead, these dynamics reflect the incorporation of new regions into the pool of potential alien species, likely as a consequence of expanding trade networks and environmental change. This process compensates for the depletion of the historically important source species pool through successive invasions. We estimate that 1-16% of all species on Earth, depending on the taxonomic group, qualify as potential alien species. These results suggest that there remains a high proportion of emerging alien species we have yet to encounter, with future impacts that are difficult to predict.

Power-law distribution in the number of confirmed COVID-19 cases.

COVID-19 is an emerging respiratory infectious disease caused by the coronavirus SARS-CoV-2. It was first reported on in early December 2019 in Wuhan, China and within three months spread as a pandemic around the whole globe. Here, we study macro-epidemiological patterns along the time course of the COVID-19 pandemic. We compute the distribution of confirmed COVID-19 cases and deaths for countries worldwide and for counties in the US and show that both distributions follow a truncated power-law over five orders of magnitude. We are able to explain the origin of this scaling behavior as a dual-scale process: the large-scale spread of the virus between countries and the small-scale accumulation of case numbers within each country. Assuming exponential growth on both scales, the critical exponent of the power-law is determined by the ratio of large-scale to small-scale growth rates. We confirm this theory in numerical simulations in a simple meta-population model, describing the epidemic spread in a network of interconnected countries. Our theory gives a mechanistic explanation why most COVID-19 cases occurred within a few epicenters, at least in the initial phase of the outbreak. By combining real world data, modeling, and numerical simulations, we make the case that the distribution of epidemic prevalence might follow universal rules.

Non-native species spread in a complex network: the interaction of global transport and local population dynamics determines invasion success.

The number of released individuals, which is a component of propagule pressure, is considered to be a major driver for the establishment success of non-native species. However, propagule pressure is often assumed to result from single or few release events, which does not necessarily apply to the frequent releases of invertebrates or other taxa through global transport. For instance, the high intensity of global shipping may result in frequent releases of large numbers of individuals, and the complexity of shipping dynamics impedes predictions of invasion dynamics. Here, we present a mathematical model for the spread of planktonic organisms by global shipping, using the history of movements by 33 566 ships among 1477 ports to simulate population dynamics for the comb jelly Mnemiopsis leidyi as a case study. The degree of propagule pressure at one site resulted from the coincident arrival of individuals from other sites with native or non-native populations. Key to sequential spread in European waters was a readily available source of propagules and a suitable recipient environment. These propagules were derived from previously introduced 'bridgehead' populations supplemented with those from native sources. Invasion success is therefore determined by the complex interaction of global shipping and local population dynamics. The general findings probably hold true for the spread of species in other complex systems, such as insects or plant seeds exchanged via commercial trade or transport.

Amino Acid and Sugar Catabolism in the Marine Bacterium Phaeobacter inhibens DSM 17395 from an Energetic Viewpoint.

Growth energetics and metabolic efficiency contribute to the lifestyle and habitat imprint of microorganisms. Roseobacters constitute one of the most abundant and successful marine bacterioplankton groups. Here, we reflect on the energetics and metabolic efficiency of Phaeobacter inhibens DSM 17395, a versatile heterotrophic roseobacter. Fourteen different substrates (five sugars and nine amino acids) and their degradation pathways were assessed for energetic efficiencies based on catabolic ATP yields, calculated from net formed ATP and reducing equivalents. The latter were converted into ATP by employing the most divergent coupling ratios (i.e., ions per ATP) currently known for F1Fo ATP synthases in heterotrophic bacteria. The catabolic ATP yields of the pathways studied in P. inhibens differed ∼3-fold. The actual free energy costs for ATP synthesis were estimated at 81.6 kJ per mol ATP (3.3 ions per ATP) or 104.2 kJ per mol ATP (4.3 ions per ATP), yielding an average thermodynamic efficiency of ∼37.7% or ∼29.5%, respectively. Growth performance (rates, yields) and carbon assimilation efficiency were determined for P. inhibens growing in process-controlled bioreactors with 10 different single substrates (Glc, Man, N-acetylglucosamine [Nag], Phe, Trp, His, Lys, Thr, Val, or Leu) and with 2 defined substrate mixtures. The efficiencies of carbon assimilation into biomass ranged from ∼28% to 61%, with His/Trp and Thr/Leu yielding the lowest and highest levels. These efficiencies correlated with catabolic and ATP yields only to some extent. Substrate-specific metabolic demands and/or functions, as well as the compositions of the substrate mixtures, apparently affected the energetic costs of growth. These include energetic burdens associated with, e.g., slow growth, stress, and/or the production of tropodithietic acid.IMPORTANCE Heterotrophic members of the bacterioplankton serve the marine ecosystem by transforming organic matter, an activity that is governed by the bacterial growth efficiencies (BGEs) obtained under given environmental conditions. In marine ecology, the concept of BGE refers to the carbon assimilation efficiency within natural communities. The marine bacterium studied here, Phaeobacter inhibens DSM 17395, is a copiotrophic representative of the globally abundant Roseobacter group, and the 15 catabolic pathways investigated are widespread among these marine heterotrophs. Combining pathway-specific catabolic ATP yields with in-depth quantitative physiological data could (i) provide a new baseline for the study of growth energetics and efficiency in further Roseobacter group members and other copiotrophic marine bacteria in productive coastal ecosystems and (ii) contribute to a better understanding of the factors controlling BGE (including the additional energetic burden arising from widespread secondary-metabolite formation) based on laboratory studies with pure cultures.

Predicting the spread of marine species introduced by global shipping.

The human-mediated translocation of species poses a distinct threat to nature, human health, and economy. Although existing models calculate the invasion probability of any species, frameworks for species-specific forecasts are still missing. Here, we developed a model approach using global ship movements and environmental conditions to simulate the successive global spread of marine alien species that allows predicting the identity of those species likely to arrive next in a given habitat. In a first step, we simulated the historical stepping-stone spreading dynamics of 40 marine alien species and compared predicted and observed alien species ranges. With an accuracy of 77%, the model correctly predicted the presence/absence of an alien species in an ecoregion. Spreading dynamics followed a common pattern with an initial invasion of most suitable habitats worldwide and a subsequent spread into neighboring habitats. In a second step, we used the reported distribution of 97 marine algal species with a known invasion history, and six species causing harmful algal blooms, to determine the ecoregions most likely to be invaded next under climate warming. Cluster analysis revealed that species can be classified according to three characteristic spreading profiles: emerging species, high-risk species, and widespread species. For the North Sea, the model predictions could be confirmed because two of the predicted high-risk species have recently invaded the North Sea. This study highlights that even simple models considering only shipping intensities and habitat matches are able to correctly predict the identity of the next invading marine species.

The intermediate distance hypothesis of biological invasions.

Biological invasions are a worldwide phenomenon, but the global flows between native and alien regions have rarely been investigated in a cross-taxonomic study. We therefore lack a thorough understanding of the global patterns of alien species spread. Using native and alien ranges of 1380 alien species, we show that the number of alien species follows a hump-shaped function of geographic distance. We observe distinct variations in the relationship between alien species exchanges and distance among taxonomic groups, which relate to the taxa-specific dispersal modes and their pathways of introduction. We formulate a simple statistical model, combining trade volume and biogeographic dissimilarity, which reproduces the observed pattern in good agreement with reported data and even captures variations among taxonomic groups. This study demonstrates the universality of the intermediate distance hypothesis of alien species spread across taxonomic groups, which will help to improve the predictability of new alien species arrivals.

Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

Food web persistence in fragmented landscapes.

Habitat destruction, characterized by patch loss and fragmentation, is a key driver of biodiversity loss. There has been some progress in the theory of spatial food webs; however, to date, practically nothing is known about how patch configurational fragmentation influences multi-trophic food web dynamics. We develop a spatially extended patch-dynamic model for different food webs by linking patch connectivity with trophic-dependent dispersal (i.e. higher trophic levels displaying longer-range dispersal). Using this model, we find that species display different sensitivities to patch loss and fragmentation, depending on their trophic position and the overall food web structure. Relative to other food webs, omnivory structure significantly increases system robustness to habitat destruction, as feeding on different trophic levels increases the omnivore's persistence. Additionally, in food webs with a dispersal-competition trade-off between species, intermediate levels of habitat destruction can enhance biodiversity by creating refuges for the weaker competitor. This demonstrates that maximizing patch connectivity is not always effective for biodiversity maintenance, as in food webs containing indirect competition, doing so may lead to further species loss.

Robustness of metacommunities with omnivory to habitat destruction: disentangling patch fragmentation from patch loss.

Habitat destruction, characterized by patch loss and fragmentation, is a major driving force of species extinction, and understanding its mechanisms has become a central issue in biodiversity conservation. Numerous studies have explored the effect of patch loss on food web dynamics, but ignored the critical role of patch fragmentation. Here we develop an extended patch-dynamic model for a tri-trophic omnivory system with trophic-dependent dispersal in fragmented landscapes. We found that species display different vulnerabilities to both patch loss and fragmentation, depending on their dispersal range and trophic position. The resulting trophic structure varies depending on the degree of habitat loss and fragmentation, due to a tradeoff between bottom-up control on omnivores (dominated by patch loss) and dispersal limitation on intermediate consumers (dominated by patch fragmentation). Overall, we find that omnivory increases system robustness to habitat destruction relative to a simple food chain.

Diverse responses of species to landscape fragmentation in a simple food chain.

Habitat destruction, characterized by habitat loss and fragmentation, is a key driver of species extinction in spatial extended communities. Recently, there has been some progress in the theory of spatial food webs, however to date practically little is known about how habitat configurational fragmentation influences multi-trophic food web dynamics. To explore how habitat fragmentation affects species persistence in food webs, we introduce a modelling framework that describes the site occupancy of species in a tri-trophic system. We assume that species dispersal range increases with trophic level, exploiting pair-approximation techniques to describe the effect of habitat clustering. In accordance with the trophic rank hypothesis, both habitat loss and fragmentation generally cause species extinction, with stronger effects occurring at higher trophic levels. However, species display diverse responses (negative, neutral or positive) to habitat loss and fragmentation separately, depending on their dispersal range and trophic position. Counter-intuitively, prey species may benefit from habitat loss due to a release in top-down control. Similarly, habitat fragmentation has almost no influence on the site occupancy of the intermediate consumer in the tri-trophic system, though it decreases those of both basal species and top predator. Consequently, species' responses to habitat destruction vary as other species become extinct. Our results reiterate the importance of the interplay between bottom-up and top-down control in trophically linked communities, and highlight the complex responses occurring in even a simple food chain.

Analysis of membrane-protein complexes of the marine sulfate reducer Desulfobacula toluolica Tol2 by 1D blue native-PAGE complexome profiling and 2D blue native-/SDS-PAGE.

Sulfate-reducing bacteria (SRB) obtain energy from cytoplasmic reduction of sulfate to sulfide involving APS-reductase (AprAB) and dissimilatory sulfite reductase (DsrAB). These enzymes are predicted to obtain electrons from membrane redox complexes, i.e. the quinone-interacting membrane-bound oxidoreductase (QmoABC) and DsrMKJOP complexes. In addition to these conserved complexes, the genomes of SRB encode a large number of other (predicted) membrane redox complexes, the function and actual formation of which is unknown. This study reports the establishment of 1D Blue Native-PAGE complexome profiling and 2D BN-/SDS-PAGE for analysis of the membrane protein complexome of the marine sulfate reducer Desulfobacula toluolica Tol2. Analysis of normalized score profiles of >800 proteins in combination with hierarchical clustering and identification of 2D BN-/SDS-PAGE separated spots demonstrated separation of membrane complexes in their native form, e.g. ATP synthase. In addition to the QmoABC and DsrMKJOP complexes, other complexes were detected that constitute the basic membrane complexome of D. toluolica Tol2, e.g. transport proteins (e.g. sodium/sulfate symporters) or redox complexes involved in Na(+) -based bioenergetics (RnfABCDEG). Notably, size estimation indicates dimer and quadruple formation of the DsrMKJOP complex in vivo. Furthermore, cluster analysis suggests interaction of this complex with a rhodanese-like protein (Tol2_C05230) possibly representing a periplasmic electron transfer partner for DsrMKJOP.

High performance CCD camera system for digitalisation of 2D DIGE gels.

An essential step in 2D DIGE-based analysis of differential proteome profiles is the accurate and sensitive digitalisation of 2D DIGE gels. The performance progress of commercially available charge-coupled device (CCD) camera-based systems combined with light emitting diodes (LED) opens up a new possibility for this type of digitalisation. Here, we assessed the performance of a CCD camera system (Intas Advanced 2D Imager) as alternative to a traditionally employed, high-end laser scanner system (Typhoon 9400) for digitalisation of differential protein profiles from three different environmental bacteria. Overall, the performance of the CCD camera system was comparable to the laser scanner, as evident from very similar protein abundance changes (irrespective of spot position and volume), as well as from linear range and limit of detection.

Native plasmids restrict growth of Phaeobacter inhibens DSM 17395: Energetic costs of plasmids assessed by quantitative physiological analyses.

Plasmid carriage is associated with energetic costs, and thus only those plasmids providing fitness benefits are stably maintained in the host lineage. Marine bacteria of the Roseobacter clade harbor up to 11 extrachromosomal replicons, adding lifestyle-relevant and possibly habitat success-promoting functions to their genomic repertoire. Phaeobacter inhibens DSM 17395 is a nutritionally versatile representative, carrying three stable and functionally distinct plasmids (65, 78, and 262 kb). The present study investigates the physiological and energetic consequences of plasmid carriage in P. inhibens DSM 17395, employing mutants cured from all native plasmids in every possible combination (seven different). Cultivation in process-controlled bioreactors with casamino acids as organic substrate revealed a complex physiological response, suggesting existence of functional interconnections between the replicons. Deletion of the 262 kb plasmid boosted growth rate (>3-fold) and growth efficiency (yields for carbon, O2 and CO2 ), which was not observed for the 65 or 78 kb plasmid. Carriage of the 262 kb plasmid was most costly for the wild type, i.e. contributing ∼50% to its energetic (dissimilatory) expenditures. Cost-benefit analysis of plasmid carriage reflects the high value of plasmids for niche specialization of P. inhibens DSM 17395 and most likely also for related Phaeobacter species.

Environmental and trait variability constrain community structure and the biodiversity-productivity relationship.

There is still considerable debate about which mechanisms drive the relationship between biodiversity and ecosystem function (BEF). Although most scientists agree on the existence of two underlying mechanisms, complementarity and selection, experimental studies keep producing contrasting results on the relative contributions of the two effects. We present a spatially explicit resource competition model and investigate how the strength of these effects is influenced by trait and environmental variability, resource distribution, and species pool size. Our results demonstrate that the increase of biomass production with increasing species numbers depends on the concurrence of environmental and trait variability: BEF relationships are stronger if functionally different species coexist in a landscape with heterogeneous resource supply. These large biodiversity effects arise from complementarity effects, whereas selection effects are maximized when broad trait ranges coincide with narrow ranges of resource supply ratios. Our results will therefore help to resolve the debate on complementarity and selection mechanisms.

A new dimension: Evolutionary food web dynamics in two dimensional trait space.

Species within a habitat are not uniformly distributed. However this aspect of community structure, which is fundamental to many conservation activities, is neglected in the majority of models of food web assembly. To address this issue, we introduce a model which incorporates a second dimension, which can be interpreted as space, into the trait space used in evolutionary food web models. Our results show that the additional trait axis allows the emergence of communities with a much greater range of network structures, similar to the diversity observed in real ecological communities. Moreover, the network properties of the food webs obtained are in good agreement with those of empirical food webs. Community emergence follows a consistent pattern with spread along the second trait axis occurring before the assembly of higher trophic levels. Communities can reach either a static final structure, or constantly evolve. We observe that the relative importance of competition and predation is a key determinant of the network structure and the evolutionary dynamics. The latter are driven by the interaction-competition and predation-between small groups of species. The model remains sufficiently simple that we are able to identify the factors, and mechanisms, which determine the final community state.