Detecting shifts in nonlinear dynamics using Empirical Dynamic Modeling with Nested-Library Analysis.

Abrupt changes in system states and dynamical behaviors are often observed in natural systems; such phenomena, named regime shifts, are explained as transitions between alternative steady states (more generally, attractors). Various methods have been proposed to detect regime shifts from time series data, but a generic detection method with theoretical linkage to underlying dynamics is lacking. Here, we provide a novel method named Nested-Library Analysis (NLA) to retrospectively detect regime shifts using empirical dynamic modeling (EDM) rooted in theory of attractor reconstruction. Specifically, NLA determines the time of regime shift as the cutting point at which sequential reduction of the library set (i.e., the time series data used to reconstruct the attractor for forecasting) optimizes the forecast skill of EDM. We illustrate this method on a chaotic model of which changing parameters present a critical transition. Our analysis shows that NLA detects the change point in the model system and outperforms existing approaches based on statistical characteristics. In addition, NLA empirically detected a real-world regime shift event revealing an abrupt change of Pacific Decadal Oscillation index around the mid-1970s. Importantly, our method can be easily generalized to various systems because NLA is equation-free and requires only a single time series.

Spatiotemporal variations and influential factors affecting reproductive dynamics of Pacific saury in the Northwest Pacific during fishing season.

This study examined the spatial and monthly variations in reproductive dynamics of Pacific saury collected in the high sea (40°N-49°N, 149°E-168°E) of the northwestern Pacific during the fishing season of the Taiwanese stick-held dip-net fisheries (July-November) from 2018 to 2019. Generalized additive mixed-effects models (GAMMs) were applied to explore the relationship between the probability of maturing and spawning occurrence (PMOS ) and the explanatory variables (month, body length, sea-surface temperature [SST] as fixed effects, and fishing set as a random effect) for the age 0 and age 1 fish, respectively. In addition, the impact of the geographical difference in growth rates of age 0 fish, quantified as the radius of the otolith annual ring, on the PMOS of age 1 fish was explored in the GAMMs. Results showed that the mean values of the condition factor (CF) varied by months, and higher mean CFs were observed north of 45°N. However, the mean values of the gonado-somatic index did not show a clear spatiotemporal pattern. The spatial distribution of the ovarian maturation states revealed that the spawning ground of Pacific saury during July-November was broader than that previously known and had partly overlapped with the high-sea fishing ground. The best GAMM showed that the predicted PMOS of the age 0 fish were generally low (mean = 19%, standard deviation [SD] = 10%) and tended to increase with increasing body length. In contrast, the predicted PMOS were relatively higher (mean = 37%, SD = 10%) for the age 1 fish and increased with increasing SST and decreasing latitude. Two candidate GAMMs, which are equally supported as the best model (ΔAIC < 2), provide evidence that a higher growth rate of age 0 fish may result in higher reproductive activity in age 1 fish. This is one of few studies focusing on the reproductive dynamics of Pacific saury during the fishing season; current limitations, future directions, and conservation implications were discussed.

Trade-Offs between Competitive Ability and Resistance to Top-Down Control in Marine Microbes.

Trade-offs between competitive ability and resistance to top-down control manifest the "kill-the-winner" hypothesis that explains how mortality caused by protists and viruses can promote bacterial diversity. However, the existence of such trade-offs has rarely been investigated in natural marine bacterial communities. To address this question, we conducted on-board dilution experiments to manipulate top-down control pressure (protists only or protists plus viruses [protists+viruses] combined) and then applied 16S rRNA gene high-throughput sequencing techniques to assess the responses of each bacterial taxon. Dilution experiments enabled us to measure the top-down-control-free growth rate as the competitive ability and top-down-control-caused mortality as the reverse of resistance to top-down control. Overall, bacterial taxa with higher top-down-control-free growth rates were accompanied by lower top-down-control-caused resistance. Furthermore, competition-resistance trade-offs were stronger and more consistent when top-down control was caused by protists+viruses combined than by protists only. When protists+viruses were diluted, the bacterial rank abundance distribution became steepened and evenness and richness were decreased. However, when protists were diluted, only richness decreased. Our results indicate the existence of competition-resistance trade-offs in marine microbes and demonstrate the positive impacts of such trade-offs on bacterial diversity. Regardless, the strength of the competition-resistance trade-offs and the impacts on bacterial diversity were contingent on whether top-down control was caused by protists+viruses combined or protists only. IMPORTANCE We addressed the "kill-the-winner" hypothesis from the perspective of its principle (the competition-resistance trade-off) in marine bacterial communities incubated in situ. Our results supported the existence of competition-resistance trade-offs and the positive effect on bacterial community diversity. The study linked theoretical expectations and complex natural systems and provided new knowledge regarding how top-down controls and competition trade-offs shaped natural bacterial communities.

Anticipating the occurrence and type of critical transitions.

Critical transition can occur in many real-world systems. The ability to forecast the occurrence of transition is of major interest in a range of contexts. Various early warning signals (EWSs) have been developed to anticipate the coming critical transition or distinguish types of transition. However, no effective method allows to establish practical threshold indicating the condition when the critical transition is most likely to occur. Here, we introduce a powerful EWS, named dynamical eigenvalue (DEV), that is rooted in bifurcation theory of dynamical systems to estimate the dominant eigenvalue of the system. Theoretically, the absolute value of DEV approaches 1 when the system approaches bifurcation, while its position in the complex plane indicates the type of transition. We demonstrate the efficacy of the DEV approach in model systems with known bifurcation types and also test the DEV approach on various critical transitions in real-world systems.

Deterministic Assembly Processes Strengthen the Effects of ß-Diversity on Community Biomass of Marine Bacterioplankton.

The presence of more species in the community of a sampling site (α diversity) typically increases ecosystem functions via nonrandom processes like resource partitioning. When considering multiple communities, we hypothesize that higher compositional difference (ß diversity) increases overall functions of these communities. Further, we hypothesize that the ß diversity effect is more positive when ß diversity is increased by nonrandom assembly processes. To test these hypotheses, we collected bacterioplankton along a transect of 6 sampling sites in the southern East China Sea in 14 cruises. For any pairs of the 6 sites within a cruise, we calculated the Bray-Curtis index to represent ß diversity and summed bacterial biomass as a proxy to indicate the overall function of the two communities. We then calculated deviation of observed mean pairwise phylogenetic similarities among species in two communities from random to represent the influences of nonrandom processes. The bacterial ß diversity was found to positively affect the summed bacterial biomass; however, the effect varied among cruises. Cross-cruise comparison indicated that the ß diversity effect increased with the nonrandom processes selecting for phylogenetically dissimilar species. This study extends biodiversity-ecosystem functioning research to the scale of multiple sites and enriches the framework by considering community assembly processes. IMPORTANCE The implications of our analyses are twofold. First, we emphasize the importance of studying ß diversity. We expanded the current biodiversity-ecosystem functioning framework from single to multiple sampling sites and investigated the influences of species compositional differences among sites on the overall functioning of these sites. Since natural ecological communities never exist alone, our analyses allow us to more holistically perceive the role of biodiversity in natural ecosystems. Second, we took community assembly processes into account to attain a more mechanistic understanding of the impacts of biodiversity on ecosystem functioning.

Allometric scaling of interspecific RNA transcript abundance to extend the use of metatranscriptomics in characterizing complex communities.

Metatranscriptomics allows profiling of community mRNA and rRNA transcript abundance under certain environmental conditions. However, variations in the proportion of RNA transcripts across different community size structures remain less explained, thus limiting the possible applications of metatranscriptomics in community studies. Here, we extended the assumptions of the growth-rate hypothesis (GRH) and the metabolic theory of ecology (MTE) to validate the allometric scaling of interspecific RNA transcript (mRNA and rRNA) abundance through metatranscriptomic analysis of mock communities consisting of model organisms. The results suggest that body size imposes significant constraints on RNA transcript abundance. Interestingly, the relationship between the total mitochondrial transcript abundance (mRNA and rRNA slopes were -0.30 and -0.28, respectively) and body size aligned with the MTE assumptions with slopes close to -», while the nuclear transcripts displayed much steeper slopes (mRNA and rRNA slopes were -0.33 and -0.40, respectively). The assumed temperature dependence was not observed in this study. At the gene level, the allometric slopes range from 0 to -1. Overall, the above results showed that larger individuals have lesser RNA transcript abundance per tissue mass than smaller ones regardless of temperature. Analyses of field-collected microcrustacean zooplankton samples demonstrated that the correction of size effect, using the allometric exponents derived from the model organism mock community, explains better the patterns of interspecific RNA transcripts abundance within the metatranscriptome. Integrating allometry with metatranscriptomics can extend the use of RNA transcript reads in estimating ecological processes within complex communities.

Effects of Tropical Cyclone Passage on Plankton Community Respiration in a Phosphate-Limited Freshwater Ecosystem.

Plankton community respiration (CR) in aquatic ecosystems varies with environmental factors, which could be altered during tropical cyclones (TCs). A potential increase in CR resulting from the effects of TCs is generally understudied. Here, we examined the relationship between plankton CR and environmental factors, including during TC-affected periods, in a phosphate-limited freshwater ecosystem. We conducted an intensive in situ sampling in Fei-Tsui Reservoir (FTR) from January 2010 to December 2015 during TC periods and non-TC periods. Our results showed a consistent temporal pattern that plankton CR increased between March to October and declined between November to February. These changes in plankton CR, primarily supported by bacterial biomass, were positively influenced by euphotic depth-averaged temperature. The CR also significantly increased with euphotic depth-averaged NO2-concentrations and decreased with euphotic depth-averaged NO3-concentrations. These results indicated that these factors typically influenced CR dynamics in the FTR. During TC periods, plankton CR was increased further due to a higher and ideal euphotic depth-averaged temperature (23-27°C) and increased supply of limiting nutrient resources via stream runoff. Overall, this study showed that a TC positively influences plankton CR by creating favorable water conditions. Notably, with a higher frequency of intense TCs projected for the Western North Pacific in most climate change scenarios, the impact of TCs on CR may increase in the near future.

Plankton Community Respiration and Particulate Organic Carbon in the Kuroshio East of Taiwan.

Biological organic carbon production and consumption play a fundamental role in the understanding of organic carbon cycling in oceans. However, studies on them in the Kuroshio, the western boundary current in the North Pacific Ocean, are scarce. To better understand the variations of plankton community respiration (CR) and particulate organic carbon (POC), eight cruises. which covered four seasons over a 2-year period, were surveyed across the Kuroshio at the KTV1 transect east of Taiwan. Spatially, a coastal uplift of isotherms (i.e., onshore lifting and offshore deepening) was observed along the KTV1 transect. During the uplift, the cold and nutrient-rich deep waters shoal to shallow water and enhance phytoplankton growth, resulting in higher values of phytoplankton, POC, and plankton CR on the onshore side. In this study, phytoplankton was dominated by picophytoplankton including Prochlorococcus, Synechococcus, and picoeukaryotes. Plankton CR was low, and its mean depth-normalized integrated rate (the upper 100 m water depth) ranged from 7.07 to 22.27 mg C m-3 d-1, to which the picophytoplankton and heterotrophic bacteria contributed the most. The mean depth-normalized integrated value of POC ranged from 12.7 to 21.6 µg C L-1. POC is mainly associated with phytoplankton biomass with a mean carbon ratio of chlorophyll a/POC ≈ 1.03. All results suggest that plankton CR and POC variations may be associated with picoplankton dynamics in the Kuroshio.

New index of functional specificity to predict the redundancy of ecosystem functions in microbial communities.

An ecosystem function is suggested to be more sensitive to biodiversity loss (i.e. low functional redundancy) when focusing on specific-type functions than broad-type functions. Thus far, specific-type functions have been loosely defined as functions performed by a small number of species (facilitative species) or functions involved in utilizing complex substrates. However, quantitative examination of functional specificity remains underexplored. We quantified the functional redundancy of 33 ecosystem functions in a freshwater system from 76 prokaryotic community samples over 3 years. For each function, we used a sparse regression model to estimate the number of facilitative Amplicon Sequence Variants (ASVs) and to define taxon-based functional specificity. We also used Bertz structural complexity to determine substrate-based functional specificity. We found that functional redundancy increased with the taxon-based functional specificity, defined as the proportion of facilitative ASVs (= facilitative ASV richness/facilitative ASV richness + repressive ASV (ASVs reducing functioning) richness). When using substrate-based functional specificity, functional redundancy was influenced by Bertz complexity per se and by substrate acquisition mechanisms. Therefore, taxon-based functional specificity is a better predictive index for evaluating functional redundancy than substrate-based functional specificity. These findings provide a framework to quantitatively predict the consequences of diversity losses on ecosystem functioning.

Causal networks of phytoplankton diversity and biomass are modulated by environmental context.

Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24◦~N58◦) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management.

Using metatranscriptomics to estimate the diversity and composition of zooplankton communities.

DNA metabarcoding is a rapid, high-resolution tool used for biomonitoring complex zooplankton communities. However, diversity estimates derived with this approach can be biased by the co-detection of sequences from environmental DNA (eDNA), nuclear-encoded mitochondrial (NUMT) pseudogene contamination, and taxon-specific PCR primer affinity differences. To avoid these methodological uncertainties, we tested the use of metatranscriptomics as an alternative approach for characterizing zooplankton communities. Specifically, we compared metatranscriptomics with PCR-based methods using genomic (gDNA) and complementary DNA (cDNA) amplicons, and morphology-based data for estimating species diversity and composition for both mock communities and field-collected samples. Mock community analyses showed that the use of gDNA mitochondrial cytochrome c oxidase I (mtCO1) amplicons inflates species richness due to the co-detection of extra-organismal eDNA. Significantly more amplicon sequence variants, nucleotide diversity, and indels were observed with gDNA amplicons than with cDNA, indicating the presence of putative NUMT pseudogenes. Moreover, PCR-based methods failed to detect the most abundant species in mock communities due to priming site mismatch. Overall, metatranscriptomics provided estimates of species richness and composition that closely resembled those derived from morphological data. The use of metatranscriptomics was further tested using field-collected samples, with the results showing consistent species diversity estimates among biological and technical replicates. Additionally, temporal zooplankton species composition changes could be monitored using different mitochondrial markers. These findings demonstrate the advantages of metatranscriptomics as an effective tool for monitoring diversity in zooplankton research.

How Communities of Marine Stramenopiles Varied with Environmental and Biological Variables in the Subtropical Northwestern Pacific Ocean.

MArine STramenopiles (MASTs) have been recognized as parts of heterotrophic protists and contribute substantially to protist abundances in the ocean. However, little is known about their spatiotemporal variations with respect to environmental and biological factors. The objectives of this study are to use canonical correspondence analysis to investigate how MASTs communities are shaped by environmental variables, and co-occurrence networks to examine their potential interactions with prokaryotic communities. Our dataset came from the southern East China Sea (sECS) in the subtropical northwestern Pacific, and involved 14 cruises along a coastal-oceanic transect, each of which sampled surface water from 4 to 7 stations. MASTs communities were revealed by metabarcoding of 18S rDNA V4 region. Most notably, MAST-9 had a high representation in warm waters in terms of read number and diversity. Subclades of MAST-9C and -9D showed slightly different niches, with MAST-9D dominating in more coastal waters where concentrations of nitrite and Synechococcus were higher. MAST-1C was a common component of colder water during spring. Overall, canonical correspondence analysis showed that MASTs communities were significantly influenced by temperature, nitrite and Synechococcus concentrations. The co-occurrence networks showed that certain other minor prokaryotic taxa can influence MAST communities. This study provides insight into how MASTs communities varied with environmental and biological variables.

Reconstructing large interaction networks from empirical time series data.

Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality is usually high. However, these pose a challenge to existing methods that can quantify only small interaction networks. Here, we proposed a novel approach to reconstruct high-dimensional interaction Jacobian networks using empirical time series without specific model assumptions. This method, named "multiview distance regularised S-map," generalised the state space reconstruction to accommodate high dimensionality and overcome difficulties in quantifying massive interactions with limited data. When evaluating this method using time series generated from theoretical models involving hundreds of interacting species, estimated strengths of interaction Jacobians were in good agreement with theoretical expectations. Applying this method to a natural bacterial community helped identify important species from the interaction network and revealed mechanisms governing the dynamical stability of a bacterial community. The proposed method overcame the challenge of high dimensionality in large natural dynamical systems.

Age-specific habitat preference, carrying capacity, and landscape structure determine the response of population spatial variability to fishing-driven age truncation.

Understanding the mechanisms underlying spatial variability of exploited fish is critical for the sustainable management of fish stocks. Empirical studies suggest that size-selective fishing can elevate fish population spatial variability (i.e., more heterogeneous distribution) through age truncation, making the population less resilient to changing environment. However, species differ in how their spatial variability responds to age truncation and the underlying mechanisms remain unclear.We hypothesize that age-specific habitat preference, together with environmental carrying capacity and landscape structure, determines the response of population spatial variability to fishing-induced age truncation. To test these hypotheses, we design an individual-based model of an age-structured fish population on a two-dimensional landscape under size-selective fishing. Individual fish reproduces and survives, and moves between habitats according to age-specific habitat preference and density-dependent habitat selection.Population spatial variability elevates with increasing age truncation, and the response is stronger for populations with stronger age-specific habitat preference. On a gradient landscape, reducing carrying capacity elevates the relative importance of density dependence in habitat selection, which weakens the response of spatial variability to age truncation for populations with strong age-specific habitat preference. On a fragmented landscape, both populations with strong and weak age-specific habitat preferences are restricted at local optimal habitats, and reducing carrying capacity weakens the responses of spatial variability to age truncation for both populations. Synthesis and applications. We demonstrate that to track and predict the changes in population spatial variability under exploitation, it is essential to consider the interactive effects of age-specific habitat preference, carrying capacity, and landscape structure. To improve spatial management in fisheries, it is crucial to enhance empirical and theoretical developments in the methodology to quantify age-specific habitat preference of marine fish, and to understand how climatic change influences carrying capacity and landscape continuity.

Change in rheotactic behavior patterns of dinoflagellates in response to different microfluidic environments.

Plankton live in dynamic fluid environments. Their ability to change in response to different hydrodynamic cues is critical to their energy allocation and resource uptake. This study used a microfluidic device to evaluate the rheotactic behaviors of a model dinoflagellate species, Karlodinium veneficum, in different flow conditions. Although dinoflagellates experienced forced alignment in strong shear (i.e. "trapping"), fluid straining did not play a decisive role in their rheotactic movements. Moderate hydrodynamic magnitude (20 < |uf| < 40 µm s-1) was found to induce an orientation heading towards an oncoming current (positive rheotaxis), as dinoflagellates switched to cross-flow swimming when flow speed exceeded 50 µm s-1. Near the sidewalls of the main channel, the steric mechanism enabled dinoflagellates to adapt upstream orientation through vertical migration. Under oscillatory flow, however, positive rheotaxis dominated with occasional diversion. The varying flow facilitated upstream exploration with directional controlling, through which dinoflagellates exhibited avoidance of both large-amplitude perturbance and very stagnant zones. In the mixed layer where water is not steady, these rheotactic responses could lead to spatial heterogeneity of dinoflagellates. The outcome of this study helps clarify the interaction between swimming behaviors of dinoflagellates and the hydrodynamic environment they reside in.

Importance of prey size on investigating prey availability of larval fishes.

Prey availability plays an important role in determining larval fish survival. Numerous studies have found close relationships between the density of mesozooplankton and larval fishes; however, emerging studies suggest that small-size zooplankton are more important prey for some larval fish species. One arising question is whether the size of zooplankton determines the relationship between zooplankton and larval fish community in natural environments. To address this question, we collected small-size (50-200 µm) zooplankton, mesozooplankton (> 330 µm), and larval fish using three different mesh-size (50, 330, 1000 µm, respectively) nets in the East China Sea, and examined their relationships in density. Both meso- and small-size zooplankton densities showed positive relationships with larval fish density, while the relationship is much stronger for the small-size zooplankton. Specifically, the smallest size classes (50-75 and 75-100 µm) of small-size zooplankton showed the highest positive relationships with larval fish density. Temperature, salinity, and chlorophyll-a concentration did not significantly explain larval fish density. Based on these findings, we demonstrate the importance of considering prey size when investigating prey availability for larval fishes.

Long-term warming destabilizes aquatic ecosystems through weakening biodiversity-mediated causal networks.

Understanding how ecosystems will respond to climate changes requires unravelling the network of functional responses and feedbacks among biodiversity, physicochemical environments, and productivity. These ecosystem components not only change over time but also interact with each other. Therefore, investigation of individual relationships may give limited insights into their interdependencies and limit ability to predict future ecosystem states. We address this problem by analyzing long-term (16-39 years) time series data from 10 aquatic ecosystems and using convergent cross mapping (CCM) to quantify the causal networks linking phytoplankton species richness, biomass, and physicochemical factors. We determined that individual quantities (e.g., total species richness or nutrients) were not significant predictors of ecosystem stability (quantified as long-term fluctuation of phytoplankton biomass); rather, the integrated causal pathway in the ecosystem network, composed of the interactions among species richness, nutrient cycling, and phytoplankton biomass, was the best predictor of stability. Furthermore, systems that experienced stronger warming over time had both weakened causal interactions and larger fluctuations. Thus, rather than thinking in terms of separate factors, a more holistic network view, that causally links species richness and the other ecosystem components, is required to understand and predict climate impacts on the temporal stability of aquatic ecosystems.