Diversity and coexistence are influenced by time-dependent species interactions in a predator-prey system

Abundant top predators increase species interaction network complexity in northeastern Chinese forests

Species interactions remain a cornerstone in shaping community dynamics and structure, alongside other factors, such as climate conditions and human activities. Although network structure is known to influence community stability and ecosystem functioning, the roles of top predators in shaping interaction network structure remain obscure. We examined a 5-7-year time series of species detections for mammal communities in multiple protected areas to investigate the association between top predators and interaction network structure. Our findings suggest that abundant species, day-active species and species with wide habitat breadth interact with more species, as did species that were more affected by vehicle disturbance. With increased densities of top predators, interaction networks exhibited greater complexity, with increased connectance, nestedness and average degree. An increased density of mesopredators, such as yellow-throated martens and badgers, was associated with sparser, less nested, but more centralized interaction networks. Top predators reduced the degree of highly interactive species, making them more specialized, and increased the degree of less abundant species, making them more general. In particular, this redistribution of interactions was not driven by direct changes in species density of top predators but seemingly by non-consumptive or indirect effects. Our findings emphasize the pivotal role of the main predators in structuring interactions within northeastern China's mammal communities, with large implications for conservation and management.

Coaggregation dynamics in drinking water biofilms and implications for chlorine disinfection

Biofilms in drinking water (DW) systems persistently challenge traditional disinfection methods due to intricate microbial interactions, with coaggregation playing a crucial role in forming multispecies biofilms. This study examined the implications of coaggregation on tolerance towards sodium hypochlorite (NaOCl) disinfection. Dual-species biofilms were formed for seven days on polyvinyl chloride coupons, comprising a strain of the emerging pathogen Stenotrophomonas maltophilia and the coaggregating strain Delftia acidovorans 005 P. For comparison, dual-species biofilms were also formed with a non-coaggregation strain (D. acidovorans 009 P). The minimum bactericidal concentration (MBC) for each planktonic strain varied (D. acidovorans: 1 mg/L, S. maltophilia: 1.5 mg/L) below the safe DW treatment limits. However, high NaOCl doses (10 ×MBC and 100 ×MBC,) showed low efficacy against dual-species biofilms, indicating significant biofilm tolerance to disinfection. Membrane damage occurred at sub-MBC without culturability loss, underscoring biofilm resilience. The biofilm analysis revealed a complex interplay between the composition of extracellular polymeric substances and the architecture, which was influenced by the presence of the coaggregating strain. Overall, coaggregation significantly influenced biofilm formation and resilience, impacting NaOCl disinfection. These findings underscore the challenges of microbial interactions in biofilms, emphasizing the need for improved disinfection strategies to control biofilms in drinking water systems.

Rapid prey manipulation and bite location preferences in three species of wandering spiders

Predator-prey interactions are the interspecific relationships of greatest interest in ecology. Spiders are among the most diverse and ubiquitous terrestrial predators on the planet. Their large dietary breadth is often linked with the development of specific predatory behaviors and morphological adaptations. However, studies on the predatory behavior of spiders have mostly focused on specialist species, leaving behind the ethological variability occurring in generalist species that allow them to respond to the different prey types. For three species of generalist wandering spiders, we searched images of predation events on the Internet to determine the most common prey. Subsequently, the focal predator species were then used in behavioral experiments. Using high-speed videos, handling patterns for different prey types (spider and cricket) were analyzed. Our results show a notable difference in handling patterns between prey types. We found that the spider prey was often rotated around the axis allowing the predator to bite in the ventral region of the prey and thus avoid a counterattack. Contrary, crickets were arbitrarily rotated. Our work may be an indication that these three species of generalist spiders have a preference for manipulating prey differently with a preference to rotate spiders, allowing them to exploit prey with various defensive mechanisms.

Explaining empirical dynamic modelling using verbal, graphical and mathematical approaches

Empirical dynamic modelling (EDM) is becoming an increasingly popular method for understanding the dynamics of ecosystems. It has been applied to laboratory, terrestrial, freshwater and marine systems, used to forecast natural populations and has addressed fundamental ecological questions. Despite its increasing use, we have not found full explanations of EDM in the ecological literature, limiting understanding and reproducibility. Here we expand upon existing work by providing a detailed introduction to EDM. We use three progressively more complex approaches. A short verbal explanation of EDM is then explicitly demonstrated by graphically working through a simple example. We then introduce a full mathematical description of the steps involved. Conceptually, EDM translates a time series of data into a path through a multi-dimensional space, whose axes are lagged values of the time series. A time step is chosen from which to make a prediction. The state of the system at that time step corresponds to a 'focal point' in the multi-dimensional space. The set (called the library) of candidate nearest neighbours to the focal point is constructed, to determine the nearest neighbours that are then used to make the prediction. Our mathematical explanation explicitly documents which points in the multi-dimensional space should not be considered as focal points. We suggest a new option for excluding points from the library that may be useful for short-term time series that are often found in ecology. We focus on the core simplex and S-map algorithms of EDM. Our new R package, pbsEDM, enhances understanding (by outputting intermediate calculations), reproduces our results and can be applied to new data. Our work improves the clarity of the inner workings of EDM, a prerequisite for EDM to reach its full potential in ecology and have wide uptake in the provision of advice to managers of natural resources.

Community assembly of organisms regulates soil microbial functional potential through dual mechanisms

Unraveling the influence of community assembly processes on soil ecosystem functioning presents a major challenge in the field of theoretical ecology, as it has received limited attention. Here, we used a series of long-term experiments spanning over 25 years to explore the assembly processes of bacterial, fungal, protist, and nematode communities using high-throughput sequencing. We characterized the soil microbial functional potential by the abundance of microbial genes associated with carbon, nitrogen, phosphorus, and sulfur cycling using GeoChip-based functional gene profiling, and determined how the assembly processes of organism groups regulate soil microbial functional potential through community diversity and network stability. Our results indicated that balanced fertilization (NPK) treatment improved the stochastic assembly of bacterial, fungal, and protist communities compared to phosphorus-deficient fertilization (NK) treatment. However, there was a nonsignificant increase in the normalized stochasticity ratio of the nematode community in response to fertilization across sites. Our findings emphasized that soil environmental factors influenced the assembly processes of the biotic community, which regulated soil microbial functional potential through dual mechanisms. One mechanism indicated that the high phosphorus levels and low soil nutrient stoichiometry may increase the stochasticity of bacterial, fungal, and protist communities and the determinism of the nematode community under NPK treatment, ultimately enhancing soil microbial functional potential by reinforcing the network stability of the biotic community. The other mechanism indicated that the low phosphorus levels and high soil nutrient stoichiometry may increase the stochastic process of the bacterial community and the determinism of the fungal, protist, and nematode communities under NK treatment, thereby enhancing soil microbial functional potential by improving the β-diversity of the biotic community. Taken together, these results provide valuable insights into the mechanisms underlying the assembly processes of the biotic community that regulate ecosystem functioning.

Dispersal mediates trophic interactions and habitat connectivity to alter metacommunity composition

Dispersal contributes vitally to metacommunity structure. However, interactions between dispersal and other key processes have rarely been explored, particularly in the context of multitrophic metacommunities. We investigated such a metacommunity in naturally fragmented habitats populated by butterfly species (whose dispersal capacities were previously assessed), flowering plants, and butterfly predators. Using data on butterfly species abundance, floral abundance, and predation (on experimentally placed clay butterfly models), we asked how dispersal ability mediates interactions with predators, mutualists, and the landscape matrix. In contrast to expectations, high densities of strong dispersers were found in more isolated sites and sites with low floral resource density, while intermediate dispersers maintained similar densities across isolation and floral gradients, and higher densities of poor dispersers were found in more connected sites and sites with higher floral density. These findings raise questions about how strong dispersers experience the landscape matrix and the quality of isolated and low-resource sites. Strong dispersers were able to escape habitat patches with high predation, while intermediate dispersers maintained similar densities along a predation gradient, and poor dispersers occurred at high densities in these patches, exposing them to interactions with predators. This work demonstrates that species that vary in dispersal capacities interact differently with predators and mutualist partners in a landscape context, shaping metacommunity composition.

Phosphorus Fertilization Boosts Mineral-Associated Soil Organic Carbon Formation Associated with Phagotrophic Protists

Long-term fertilization affects soil organic C accumulation. A growing body of research has revealed critical roles of bacteria in soil organic C accumulation, particularly through mineral-associated organic C (MAOC) formation. Protists are essential components of soil microbiome, but the relationships between MAOC formation and protists under long-term fertilization remain unclear. Here, we used cropland soil from a long-term fertilization field trial and conducted two microcosm experiments with 13C-glucose addition to investigate the effects of N and P fertilizations on MAOC formation and the relationships with protists. The results showed that long-term fertilization (especially P fertilization) significantly (P < 0.05) increased 13C-MAOC content. Compared with P-deficient treatment, P replenishment enriched the number of protists (mainly Amoebozoa and Cercozoa) and bacteria (mainly Acidobacteriota, Bacteroidota, and Gammaproteobacteria), and significantly (P < 0.001) promoted the abundances of bacterial functional genes controlling C, N, P, and S metabolisms. The community composition of phagotrophic protists prominently (P < 0.001) correlated with the bacterial community composition, bacterial functional gene abundance, and 13C-MAOC content. Co-occurrence networks of phagotrophic protists and bacteria were more connected in soil with the N inoculum added than in soil with the NP inoculum added. P replenishment strengthened bacterial 13C assimilation (i.e., 13C-phospholipid fatty acid content), which negatively (P < 0.05) correlated with the number and relative abundance of phagotrophic Cercozoa. Together, these results suggested that P fertilization boosts MAOC formation associated with phagotrophic protists. Our study paves the way for future research to harness the potential of protists to promote belowground C accrual in agroecosystems.

Distinct life history strategies underpin clear patterns of succession in microparasite communities infecting a wild mammalian host

Individual animals in natural populations tend to host diverse parasite species concurrently over their lifetimes. In free-living ecological communities, organismal life histories shape interactions with their environment, which ultimately forms the basis of ecological succession. However, the structure and dynamics of mammalian parasite communities have not been contextualized in terms of primary ecological succession, in part because few datasets track occupancy and abundance of multiple parasites in wild hosts starting at birth. Here, we studied community dynamics of 12 subtypes of protozoan microparasites (Theileria spp.) in a herd of African buffalo. We show that Theileria communities followed predictable patterns of succession underpinned by four different parasite life history strategies. However, in contrast to many free-living communities, network complexity decreased with host age. Examining parasite communities through the lens of succession may better inform the effect of complex within host eco-evolutionary dynamics on infection outcomes, including parasite co-existence through the lifetime of the host.

Relationships of temperature and biodiversity with stability of natural aquatic food webs

Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects.

Resource-dependent biodiversity and potential multi-trophic interactions determine belowground functional trait stability

BACKGROUND

For achieving long-term sustainability of intensive agricultural practices, it is pivotal to understand belowground functional stability as belowground organisms play essential roles in soil biogeochemical cycling. It is commonly believed that resource availability is critical for controlling the soil biodiversity and belowground organism interactions that ultimately lead to the stabilization or collapse of terrestrial ecosystem functions, but evidence to support this belief is still limited. Here, we leveraged field experiments from the Chinese National Ecosystem Research Network (CERN) and two microcosm experiments mimicking high and low resource conditions to explore how resource availability mediates soil biodiversity and potential multi-trophic interactions to control functional trait stability.

RESULTS

We found that agricultural practice-induced higher resource availability increased potential cross-trophic interactions over 316% in fields, which in turn had a greater effect on functional trait stability, while low resource availability made the stability more dependent on the potential within trophic interactions and soil biodiversity. This large-scale pattern was confirmed by fine-scale microcosm systems, showing that microcosms with sufficient nutrient supply increase the proportion of potential cross-trophic interactions, which were positively associated with functional stability. Resource-driven belowground biodiversity and multi-trophic interactions ultimately feedback to the stability of plant biomass.

CONCLUSIONS

Our results indicated the importance of potential multi-trophic interactions in supporting belowground functional trait stability, especially when nutrients are sufficient, and also suggested the ecological benefits of fertilization programs in modern agricultural intensification. Video Abstract.

Rapid eco-phenotypic feedback and the temperature response of biomass dynamics

Biomass dynamics capture information on population dynamics and ecosystem-level processes (e.g., changes in production over time). Understanding how rising temperatures associated with global climate change influence biomass dynamics is thus a pressing issue in ecology. The total biomass of a species depends on its density and its average mass. Consequently, disentangling how biomass dynamics responds to increasingly warm and variable temperatures ultimately depends on understanding how temperature influences both density and mass dynamics. Here, we address this issue by keeping track of experimental microbial populations growing to carrying capacity for 15 days at two different temperatures, and in the presence and absence of temperature variability. We develop a simple mathematical expression to partition the contribution of changes in density and mass to changes in biomass and assess how temperature responses in either one influence biomass shifts. Moreover, we use time-series analysis (Convergent Cross Mapping) to address how temperature and temperature variability influence reciprocal effects of density on mass and vice versa. We show that temperature influences biomass through its effects on density and mass dynamics, which have opposite effects on biomass and can offset each other. We also show that temperature variability influences biomass, but that effect is independent of any effects on density or mass dynamics. Last, we show that reciprocal effects of density and mass shift significantly across temperature regimes, suggesting that rapid and environment-dependent eco-phenotypic dynamics underlie biomass responses. Overall, our results connect temperature effects on population and phenotypic dynamics to explain how biomass responds to temperature regimes, thus shedding light on processes at play in cosmopolitan and abundant microbes as the world experiences increasingly warm and variable temperatures.

Response of soil protists to antimony and arsenic contamination

Microorganisms can mediate antimony (Sb) and arsenic (As) transformation and thus change their mobility and toxicity. Having similar geochemical behavior, Sb and As are generally considered to exert similar environmental pressure on microbiome. However, it needs further validation, especially for protists. In this study, the responses of protistan communities to Sb and As were investigated by collecting soils from Xikuangshan Sb mine and Shimen As mine in China. Antimony and As contamination taxonomically and functionally (consumer and phototroph) changed the alpha and beta diversities of protistan communities, but exerted different impacts on the parasitic community. Based on multiple statistical tools, As contamination had a greater impact on protistan communities than Sb. The ecological networks of highly contaminated sites were less complex but highly positively connected compared to less contaminated sites. High As contamination raised the ratio of consumers and decreased the ratio of phototrophs in ecological networks, while the opposite tendency was observed in Sb contaminated soils. High Sb and As contamination enriched different keystone taxa resistant to Sb and As. These results demonstrate that protistan community respond differently to Sb and As.

Fertilization drives distinct biotic and abiotic factors in regulating functional groups of protists in a 5-year fertilization system

INTRODUCTION

Protists play an important role in nutrient cycling, microbiome stability and soil fertility maintenance. However, the driving force of protistan functional groups remains poorly understood in agricultural ecosystems.

METHODS

We investigated the impacts of fertilization regimes on the diversity, composition and functional groups of protists and further disentangled the effects of multiple factors shaping the community composition of functional groups in a 5-year fertilization regime (CK, no fertilization; M, organic fertilization; MNPK, combined inorganic and organic fertilization; NPK, inorganic fertilization).

RESULTS

Fertilization significantly changed the community composition of protists rather than diversity. The MNPK treatment significantly increased the relative abundance of phototrophs and decreased that of the parasites and consumers. Partial least squares path modeling indicated that fertilization indirectly regulated protistan consumers via changes in the P content, which affected the composition of consumers mainly by regulating fungal community composition. Soil moisture (SM) and available phosphorus (AP) were identified as the top predictors for the composition of parasites, and the composition of phototrophs was mainly affected by SM, indicating that parasites and phototrophs were more sensitive to abiotic factors in the fertilization system.

DISCUSSION

Taken together, our findings highlight that fertilization significantly affects the composition of functional groups of protists and their biotic or abiotic regulatory processes, which have implications for the potential changes in their ecosystem functions for soil management systems.

Differences in initial abundances reveal divergent dynamic structures in Gause's predator-prey experiments

Improved understanding of complex dynamics has revealed insights across many facets of ecology, and has enabled improved forecasts and management of future ecosystem states. However, an enduring challenge in forecasting complex dynamics remains the differentiation between complexity and stochasticity, that is, to determine whether declines in predictability are caused by stochasticity, nonlinearity, or chaos. Here, we show how to quantify the relative contributions of these factors to prediction error using Georgii Gause's iconic predator-prey microcosm experiments, which, critically, include experimental replicates that differ from one another only in initial abundances. We show that these differences in initial abundances interact with stochasticity, nonlinearity, and chaos in unique ways, allowing us to identify the impacts of these factors on prediction error. Our results suggest that jointly analyzing replicate time series across multiple, distinct starting points may be necessary for understanding and predicting the wide range of potential dynamic types in complex ecological systems.

Reconstruction of a Soil Microbial Network Induced by Stress Temperature

The microbial community is viewed as a network of diverse microorganisms connected by various interspecific interactions. While the stress gradient hypothesis (SGH) predicts that positive interactions are favored in more stressful environments, the prediction has been less explored in complex microbial communities due to the challenges of identifying interactions. Here, by applying a nonlinear time series analysis to the amplicon-based diversity time series data of the soil microbiota cultured under less stressful (30°C) or more stressful (37°C) temperature conditions, we show how the microbial network responds to temperature stress. While the genera that persisted only under the less stressful condition showed fewer positive effects, the genera that appeared only under the more stressful condition received more positive effects, in agreement with SGH. However, temperature difference also induced reconstruction of the community network, leading to an increased proportion of negative interactions at the whole-community level. The anti-SGH pattern can be explained by the stronger competition caused by increased metabolic rate and population densities. IMPORTANCE By combining amplicon-based diversity survey with recently developed nonlinear analytical tools, we successfully determined the interaction networks of more than 150 natural soil microbial genera under less or more temperature stress and explored the applicability of the stress gradient hypothesis to soil microbiota, shedding new light on the well-known hypothesis.

Primary Succession Changes the Composition and Functioning of the Protist Community on Mine Tailings, Especially Phototrophic Protists

Primary succession in mine tailings is a prerequisite for tailing vegetation. Microorganisms, including bacteria, fungi, and protists, play an important role in this process in the driving force for improving the nutritional status. Compared to bacteria and fungi, protist populations have rarely been investigated regarding their role in mine tailings, especially for those inhabiting tailings associated with primary succession. Protists are the primary consumers of fungi and bacteria, and their predatory actions promote the release of nutrients immobilized in the microbial biomass, as well as the uptake and turnover of nutrients, affecting the functions of the wider ecosystems. In this study, three different types of mine tailings associated with three successional stages (original tailings, biological crusts, and Miscanthus sinensis grasslands) were selected to characterize the protistan community diversity, structure, and function during primary succession. Some members classified as consumers dominated the network of microbial communities in the tailings, especially in the original bare land tailings. The keystone phototrophs of Chlorophyceae and Trebouxiophyceae showed the highest relative abundance in the biological crusts and grassland rhizosphere, respectively. In addition, the co-occurrences between protist and bacterial taxa demonstrated that the proportion of protistan phototrophs gradually increased during primary succession. Further, the metagenomic analysis of protistan metabolic potential showed that abundances of many functional genes associated with photosynthesis increased during the primary succession of tailings. Overall, these results suggest that the primary succession of mine tailings drives the changes observed in the protistan community, and in turn, the protistan phototrophs facilitate the primary succession of tailings. This research offers an initial insight into the changes in biodiversity, structure, and function of the protistan community during ecological succession on tailings.

Generalism drives abundance: A computational causal discovery approach

A ubiquitous pattern in ecological systems is that more abundant species tend to be more generalist; that is, they interact with more species or can occur in wider range of habitats. However, there is no consensus on whether generalism drives abundance (a selection process) or abundance drives generalism (a drift process). As it is difficult to conduct direct experiments to solve this chicken-and-egg dilemma, previous studies have used a causal discovery method based on formal logic and have found that abundance drives generalism. Here, we refine this method by correcting its bias regarding skewed distributions, and employ two other independent causal discovery methods based on nonparametric regression and on information theory, respectively. Contrary to previous work, all three independent methods strongly indicate that generalism drives abundance when applied to datasets on plant-hummingbird communities and reef fishes. Furthermore, we find that selection processes are more important than drift processes in structuring multispecies systems when the environment is variable. Our results showcase the power of the computational causal discovery approach to aid ecological research.

Spatial and Ecological Scaling of Stability in Spatial Community Networks

There are many scales at which to quantify stability in spatial and ecological networks. Local-scale analyses focus on specific nodes of the spatial network, while regional-scale analyses consider the whole network. Similarly, species- and community-level analyses either account for single species or for the whole community. Furthermore, stability itself can be defined in multiple ways, including resistance (the inverse of the relative displacement caused by a perturbation), initial resilience (the rate of return after a perturbation), and invariability (the inverse of the relative amplitude of the population fluctuations). Here, we analyze the scale-dependence of these stability properties. More specifically, we ask how spatial scale (local vs. regional) and ecological scale (species vs. community) influence these stability properties. We find that regional initial resilience is the weighted arithmetic mean of the local initial resiliences. The regional resistance is the harmonic mean of local resistances, which makes regional resistance particularly vulnerable to nodes with low stability, unlike regional initial resilience. Analogous results hold for the relationship between community- and species-level initial resilience and resistance. Both resistance and initial resilience are “scale-free” properties: regional and community values are simply the biomass-weighted means of the local and species values, respectively. Thus, one can easily estimate both stability metrics of whole networks from partial sampling. In contrast, invariability generally is greater at the regional and community-level than at the local and species-level, respectively. Hence, estimating the invariability of spatial or ecological networks from measurements at the local or species level is more complicated, requiring an unbiased estimate of the network (i.e., region or community) size. In conclusion, we find that scaling of stability depends on the metric considered, and we present a reliable framework to estimate these metrics.

The composition, biotic network, and assembly of plastisphere protistan taxonomic and functional communities in plastic-mulching croplands

The increasing use of plastic film mulching has caused the accumulation of plastic film residue in soil. To date, most researches on the plastisphere have focused on bacterial and fungal communities, with few on protistan community, especially in terrestrial ecosystems. To understand plastisphere protistan communities, we collected plastic film residues from plastic-mulching croplands. The plastisphere significantly altered the alpha-diversity, structure, and composition of taxonomic and functional (consumers, phototrophs, and parasites) communities. In both the plastisphere and surrounding soil, although some consumers dominated the protistan community network, while their performance was weakened by mulch application. The ecological networks of the plastisphere community presented higher modularity, less complexity, and a lower proportion of positive connections than the networks of surrounding soil. In addition, the enriched plant pathogens (e.g., Spongospora) and keystone taxa classified as plant pathogens (e.g., Pythium) in the plastisphere imply that plastic film residues may pose a risk to soil health and plant performance. Neutral-based processes dominated the assembly of the plastisphere protistan communities, whereas niche-based processes governed the protistan community assembly of surrounding soil. This study reveals that plastic film residues generate a unique niche for protistan colonization, which disturbs protistan communities and threatens agricultural ecosystem health and function.

Floral diversity increases butterfly diversity in a multitrophic metacommunity

The impact of multitrophic interactions on metacommunity structure, despite extensive theory and modelling/manipulative studies, has remained largely unexplored within naturally occurring metacommunities. We investigated the impacts of mutualistic partners and predators on a butterfly metacommunity, as well as the impacts that local and landscape characteristics have across three trophic levels: flowering plants, butterflies, and butterfly predators. Using data for butterfly diversity/richness, flowering plant diversity/richness, and butterfly predation (on clay butterfly models) across 15 grassland sites, we asked 3 questions: 1) How do mutualist metacommunity structure, predation pressure, and local and regional habitat characteristics affect butterfly metacommunity structure? 2) How do local and regional habitat characteristics affect flowering plant metacommunity structure? 3) How do local and regional habitat characteristics affect predation pressure? Floral diversity and richness had a positive effect on butterfly diversity and richness (Question 1). Site size positively affected floral diversity and richness (Question 2), and through this relationship site size had an indirect positive effect on butterfly diversity and richness (Question 1). In contrast with previous work, no other variables impacted butterfly diversity/richness. This result was particularly surprising for predation pressure: our results suggest that within our study system butterfly community diversity and richness is not strongly impacted by predation. Predator attacks occurred more in larger and more isolated sites (Question 3), suggesting that predators respond more strongly to landscape characteristics than abundance or diversity of butterfly prey species. This decoupling of predation pressure and butterfly communities suggests that conserving and restoring healthy predator populations may not negatively impact butterfly communities. If diverse plant communities are maintained, even small and isolated habitat patches can be valuable for butterfly conservation, which may influence reserve design and habitat restoration strategies.

Nonlinear causal analysis reveals an effective water level regulation approach for phytoplankton blooms controlling in reservoirs

Reservoirs are a rapidly increasing water body providing water supply, irrigation, and many other benefits for human societies globally. However, due to changes in hydrological conditions, building reservoirs tends to bring adverse effects such as eutrophication and phytoplankton blooms, reducing the ecosystem service values. This study focuses on using the empirical dynamic modeling (EDM), an emerging approach for nonlinear analysis, to investigate the nonlinear causal relationship of water level fluctuation (WLF) on phytoplankton biomass and then develop a quantitative model guiding effective phytoplankton blooms controlling based on water level regulations in reservoirs. Specifically, with 9-year continued daily observed data in the Three Gorges Reservoir, we examined the causal effects of different WLF parameters on the dynamics of phytoplankton blooms for the first time. We found that the water level change in the past 24 h (ΔWL) has the strongest causal effect on the daily dynamics of phytoplankton biomass among all WLF parameters (ΔWL, |ΔWL|, and the water level), with a time lag of 2 days. Moreover, EDM revealed a nonlinear relationship between ΔWL and daily dynamics of phytoplankton biomass and achieved a successful prediction for the chlorophyll a concentration 2-day ahead. Further scenario analyses found that both the rise and fall of water level will significantly reduce the chlorophyll a concentration when phytoplankton blooms occur. Nevertheless, on the whole, the rising water level has a more substantial effect on phytoplankton blooms than falling the water level. This result reveals that regulating ΔWL is a simple and effective approach in controlling phytoplankton blooms in reservoirs. Our study reported the nonlinear causal effect of ΔWL on the dynamics of chlorophyll a and provided a quantitative approach guiding effective phytoplankton blooms controlling based on the water level regulation, which might have a broad application in algal blooms controlling in reservoirs and similar waterbodies.

General statistical scaling laws for stability in ecological systems

Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance. These relationships can be calibrated using random or representative samples measured at individual scales, and projected to predict average stability at other scales across a wide range of contexts. Moreover deviations between observed vs. extrapolated scaling relationships can reveal information about unobserved heterogeneity across time, space, or species. We anticipate that these methods will be useful for cross-study synthesis of stability data, extrapolating measurements to unobserved scales, and identifying underlying causes and consequences of heterogeneity.

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.

Fertilization alters protistan consumers and parasites in crop-associated microbiomes

Crop plants carry an enormous diversity of microbiota that provide massive benefits to hosts. Protists, as the main microbial consumers and a pivotal driver of biogeochemical cycling processes, remain largely understudied in the plant microbiome. Here, we characterized the diversity and composition of protists in sorghum leaf phyllosphere, and rhizosphere and bulk soils, collected from an 8-year field experiment with multiple fertilization regimes. Phyllosphere was an important habitat for protists, dominated by Rhizaria, Alveolata and Amoebozoa. Rhizosphere and bulk soils had a significantly higher diversity of protists than the phyllosphere, and the protistan community structure significantly differed among the three plant-soil compartments. Fertilization significantly altered specific functional groups of protistan consumers and parasites. Variation partitioning models revealed that soil properties, bacteria and fungi predicted a significant proportion of the variation in the protistan communities. Changes in protists may in turn significantly alter the compositions of bacterial and fungal communities from the top-down control in food webs. Altogether, we provide novel evidence that fertilization significantly affects the functional groups of protistan consumers and parasites in crop-associated microbiomes, which have implications for the potential changes in their ecological functions under intensive agricultural managements.

gauseR: Simple methods for fitting Lotka-Volterra models describing Gause's "Struggle for Existence"

Point 1: The ecological models of Alfred J. Lotka and Vito Volterra have had an enormous impact on ecology over the past century. Some of the earliest-and clearest-experimental tests of these models were famously conducted by Georgy Gause in the 1930s. Although well known, the data from these experiments are not widely available and are often difficult to analyze using standard statistical and computational tools. Point 2: Here, we introduce the gauseR package, a collection of tools for fitting Lotka-Volterra models to time series data of one or more species. The package includes several methods for parameter estimation and optimization, and includes 42 datasets from Gause's species interaction experiments and related work. Additionally, we include with this paper a short blog post discussing the historical importance of these data and models, and an R vignette with a walk-through introducing the package methods. The package is available for download at github.com/adamtclark/gauseR. Point 3: To demonstrate the package, we apply it to several classic experimental studies from Gause, as well as two other well-known datasets on multi-trophic dynamics on Isle Royale, and in spatially structured mite populations. In almost all cases, models fit observations closely and fitted parameter values make ecological sense. Point 4: Taken together, we hope that the methods, data, and analyses that we present here provide a simple and user-friendly way to interact with complex ecological data. We are optimistic that these methods will be especially useful to students and educators who are studying ecological dynamics, as well as researchers who would like a fast tool for basic analyses.