Beyond species: why ecological interaction networks vary through space and time

Spatially explicit predictions of food web structure from regional-level data

Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated spatial data for species interactions. Yet, recent developments in metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to using the current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large-scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from global databases. We investigated how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Species richness and interactions followed a similar latitudinal gradient across ecoregions but simultaneously identified contrasting diversity hotspots. Network motifs revealed additional areas of variation in network structure compared with species richness and number of links. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Networking nutrients: How nutrition determines the structure of ecological networks

Nutrients can shape ecological interactions but remain poorly integrated into ecological networks. Concepts such as nutrient-specific foraging nevertheless have the potential to expose the mechanisms structuring complex ecological systems. Nutrients also present an opportunity to predict dynamic processes, such as interaction rewiring and extinction cascades, and increase the accuracy of network analyses. Here, we propose the concept of nutritional networks. By integrating nutritional data into ecological networks, we envisage significant advances to our understanding of ecological processes from individual to ecosystem scales. We show that networks can be constructed with nutritional data to illuminate how nutrients structure ecological interactions in natural systems through an empirical example. Throughout, we identify fundamental ecological hypotheses that can be explored in a nutritional network context, alongside methods for resolving those networks. Nutrients influence the structure and complexity of ecological networks through mechanistic processes and concepts including nutritional niche differentiation, functional responses, landscape diversity, ecological invasions and ecosystem robustness. Future research on ecological networks should consider nutrients when investigating the drivers of network structure and function.

Interspecific interaction network of mites associated with mango trees

Direct and indirect ecological interactions, environmental factors, and the phenology of host plants can shape the way mites interact. These relationships interfere with species occurrence and consequently alter the structure and stability of the intraplant community. As predatory mites act as regulators of herbivorous mites, we hypothesized that these mites may occupy a central position in a network of interactions among mite species associated with mango trees, and the occurrence of these species is mediated by environmental variables and the phenological stage of the host plant. We evaluated the global structure of the interaction network of mites associated with individual Mangifera indica plants and analyzed the interspecific relationships of the species using an undirected Bayesian network approach. Additionally, we observed a correlation between mite population density and plant phenological stage. Environmental variables, such as average monthly temperature, monthly precipitation, and average monthly relative humidity at different sampling date were used in the correlation analysis. The modularity at the mite-plant network level showed a low specialization index H2 = 0.073 (generalist) and high robustness (R = 0.93). Network analysis revealed that Amblyseius largoensis, Bdella ueckermanni, Parapronematus acaciae, and Tuckerella ornata occupied central positions in the assembly of mites occurring on mango trees. Environmental variables, average monthly temperature, and monthly precipitation were correlated with the occurrence of Brachytydeus formosa, Cisaberoptus kenyae, Oligonychus punicae, T. ornata, and Vilaia pamithus. We also observed a correlation between the plant phenological stage and population densities of Neoseiulus houstoni, O. punicae, P. acaciae, and V. pamithus.

Biodiversity in changing environments: An external-driver internal-topology framework to guide intervention

Accompanying the climate crisis is the more enigmatic biodiversity crisis. Rapid reorganization of biodiversity due to global environmental change has defied prediction and tested the basic tenets of conservation and restoration. Conceptual and practical innovation is needed to support decision making in the face of these unprecedented shifts. Critical questions include: How can we generalize biodiversity change at the community level? When are systems able to reorganize and maintain integrity, and when does abiotic change result in collapse or restructuring? How does this understanding provide a template to guide when and how to intervene in conservation and restoration? To this end, we frame changes in community organization as the modulation of external abiotic drivers on the internal topology of species interactions, using plant-plant interactions in terrestrial communities as a starting point. We then explore how this framing can help translate available data on species abundance and trait distributions to corresponding decisions in management. Given the expectation that community response and reorganization are highly complex, the external-driver internal-topology (EDIT) framework offers a way to capture general patterns of biodiversity that can help guide resilience and adaptation in changing environments.

Latitudinal specificity of plant-avian frugivore interactions

Broad-scale assessments of plant-frugivore interactions indicate the existence of a latitudinal gradient in interaction specialization. The specificity (i.e. the similarity of the interacting partners) of plant-frugivore interactions could also change latitudinally given that differences in resource availability could favour species to become more or less specific in their interactions across latitudes. Species occurring in the tropics could be more taxonomically, phylogenetically and functionally specific in their interactions because of a wide range of resources that are constantly available in these regions that would allow these species to become more specialized in their resource usage. We used a data set on plant-avian frugivore interactions spanning a wide latitudinal range to examine these predictions, and we evaluated the relationship between latitude and taxonomic, phylogenetic and functional specificity of plant and frugivore interactions. These relationships were assessed using data on population interactions (population level), species means (species level) and community means (community level). We found that the specificity of plant-frugivore interactions is generally not different from null models. Although statistically significant relationships were often observed between latitude and the specificity of plant-frugivore interactions, the direction of these relationships was variable and they also were generally weak and had low explanatory power. These results were consistent across the three specificity measures and levels of organization, suggesting that there might be an interplay between different mechanisms driving the interactions between plants and frugivores across latitudes.

The propagation of disturbances in ecological networks

Despite the development of network science, we lack clear heuristics for how far different disturbance types propagate within and across species interaction networks. We discuss the mechanisms of disturbance propagation in ecological networks, and propose that disturbances can be categorized into structural, functional, and transmission types according to their spread and effect on network structure and functioning. We describe the properties of species and their interaction networks and metanetworks that determine the indirect, spatial, and temporal extent of propagation. We argue that the sampling scale of ecological studies may have impeded predictions regarding the rate and extent that a disturbance spreads, and discuss directions to help ecologists to move towards a predictive understanding of the propagation of impacts across interacting communities and ecosystems.

Structural dynamics of plant-pollinator mutualistic networks

The discourse surrounding the structural organization of mutualistic interactions mostly revolves around modularity and nestedness. The former is known to enhance the stability of communities, while the latter is related to their feasibility, albeit compromising the stability. However, it has recently been shown that the joint emergence of these structures poses challenges that can eventually lead to limitations in the dynamic properties of mutualistic communities. We hypothesize that considering compound arrangements-modules with internal nested organization-can offer valuable insights in this debate. We analyze the temporal structural dynamics of 20 plant-pollinator interaction networks and observe large structural variability throughout the year. Compound structures are particularly prevalent during the peak of the pollination season, often coexisting with nested and modular arrangements in varying degrees. Motivated by these empirical findings, we synthetically investigate the dynamics of the structural patterns across two control parameters-community size and connectance levels-mimicking the progression of the pollination season. Our analysis reveals contrasting impacts on the stability and feasibility of these mutualistic communities. We characterize the consistent relationship between network structure and stability, which follows a monotonic pattern. But, in terms of feasibility, we observe nonlinear relationships. Compound structures exhibit a favorable balance between stability and feasibility, particularly in mid-sized ecological communities, suggesting they may effectively navigate the simultaneous requirements of stability and feasibility. These findings may indicate that the assembly process of mutualistic communities is driven by a delicate balance among multiple properties, rather than the dominance of a single one.

Dissimilarity in flea and host assemblages and their interaction networks along a spatial distance gradient: different patterns revealed by different network dissimilarity metrics

We investigated the distance-decay pattern (an increase in dissimilarity with increasing geographic distance) in regional assemblages of fleas and their small mammalian hosts, as well as their interaction networks, in four biogeographic realms. Dissimilarity of assemblages (βtotal) was partitioned into species richness differences (βrich) and species replacement (βrepl) components. Dissimilarity of networks was assessed using two metrics: (a) whole network dissimilarity (βWN) partitioned into species replacement (βST) and interaction rewiring (βOS) components and (b) D statistics, measuring dissimilarity in the pure structure of the networks, without using information on species identities and calculated for hosts-shared-by-fleas networks (Dh) and fleas-shared-by-hosts networks (Df). We asked whether the distance-decay pattern (a) occurs among interactor assemblages or their interaction networks; (b) depends on the network dissimilarity metric used; and (c) differs between realms. The βtotal and βrepl of flea and host assemblages increased with distance in all realms except for host assemblages in the Afrotropics. βrich for flea and host assemblages increased with distance in the Nearctic only. In networks, βWN and βST demonstrated a distance-decay pattern, whereas βOS was mainly spatially invariant except in the Neotropics. Correlations of Dh or Df and geographic distance were mostly non-significant. We conclude that investigations of dissimilarity in interaction networks should include both types of dissimilarity metrics (those that consider partner identities and those that consider the pure structure of networks). This will allow elucidating the predictability of some facets of network dissimilarity and the unpredictability of other facets.

Fungal and bacterial communities and their associations in snow-free and snow covered (sub-)alpine Pinus cembra forest soils

BACKGROUND

In Europe, Pinus cembra forests cover subalpine and alpine areas and they are of high conservational and ecological relevance. These forests experience strong seasonality with alternating snow-free and snow covered periods. Although P. cembra is known for mycorrhization and mycorrhizae usually involve fungi, plants and bacteria, the community compositions of fungi and bacteria and their associations in (sub-)alpine P. cembra forests remain vastly understudied. Here, we studied the fungal and bacterial community compositions in three independent (sub-)alpine P. cembra forests and inferred their microbial associations using marker gene sequencing and network analysis. We asked about the effect of snow cover on microbial compositions and associations. In addition, we propose inferring microbial associations across a range of filtering criteria, based on which we infer well justified, concrete microbial associations with high potential for ecological relevance that are typical for P. cembra forests and depending on snow cover.

RESULTS

The overall fungal and bacterial community structure was comparable with regards to both forest locations and snow cover. However, occurrence, abundance, and diversity patterns of several microbial taxa typical for P. cembra forests differed among snow-free and snow covered soils, e.g. Russula, Tetracladium and Phenoliphera. Moreover, network properties and microbial associations were influenced by snow cover. Here, we present concrete microbial associations on genus and species level that were repeatedly found across microbial networks, thereby confirming their ecological relevance. Most importantly, ectomycorrhizal fungi, such as Basidioascus, Pseudotomentella and Rhizopogon, as well as saprobic Mortierella changed their bacterial association partners depending on snow cover.

CONCLUSION

This is the first study researching fungal-bacterial associations across several (sub-)alpine P. cembra forests. The poorly investigated influence of snow cover on soil fungi and bacteria, especially those mycorrhizing P. cembra roots, but also saprobic soil organisms, underlines the relevance of forest seasonality. Our findings highlight that the seasonal impact of snow cover has significant consequences for the ecology of the ecosystem, particularly in relation to mycorrhization and nutrient cycling. It is imperative to consider such effects for a comprehensive understanding of the functioning resilience and responsiveness of an ecosystem.

Plant interaction networks reveal the limits of our understanding of diversity maintenance

Species interactions are key drivers of biodiversity and ecosystem stability. Current theoretical frameworks for understanding the role of interactions make many assumptions which unfortunately, do not always hold in natural, diverse communities. This mismatch extends to annual plants, a common model system for studying coexistence, where interactions are typically averaged across environmental conditions and transitive competitive hierarchies are assumed to dominate. We quantify interaction networks for a community of annual wildflowers in Western Australia across a natural shade gradient at local scales. Whilst competition dominated, intraspecific and interspecific facilitation were widespread in all shade categories. Interaction strengths and directions varied substantially despite close spatial proximity and similar levels of local species richness, with most species interacting in different ways under different environmental conditions. Contrary to expectations, all networks were predominantly intransitive. These findings encourage us to rethink how we conceive of and categorize the mechanisms driving biodiversity in plant systems.

Elevational and seasonal patterns of plant pollinator networks in two highland tropical ecosystems in Costa Rica

Many plant species in high montane ecosystems rely on animal pollination for sexual reproduction, however, our understanding of plant-pollinator interactions in tropical montane habitats is still limited. We compared species diversity and composition of blooming plants and floral visitors, and the structure of plant-floral visitor networks between the Montane Forest and Paramo ecosystems in Costa Rica. We also studied the influence of seasonality on species composition and interaction structure. Given the severe climatic conditions experienced by organisms in habitats above treeline, we expected lower plant and insect richness, as well as less specialized and smaller pollination networks in the Paramo than in Montane Forest where climatic conditions are milder and understory plants are better protected. Accordingly, we found that blooming plants and floral visitor species richness was higher in the Montane Forest than in the Paramo, and in both ecosystems species richness of blooming plants and floral visitors was higher in the rainy season than in the dry season. Interaction networks in the Paramo were smaller and more nested, with lower levels of specialization and modularity than those in the Montane Forest, but there were no seasonal differences within either ecosystem. Beta diversity analyses indicate that differences between ecosystems are likely explained by species turnover, whereas within the Montane Forest differences between seasons are more likely explained by the rewiring of interactions. Results indicate that the decrease in species diversity with elevation affects network structure, increasing nestedness and reducing specialization and modularity.

Using individual-based trait frequency distributions to forecast plant-pollinator network responses to environmental change

Determining how and why organisms interact is fundamental to understanding ecosystem responses to future environmental change. To assess the impact on plant-pollinator interactions, recent studies have examined how the effects of environmental change on individual interactions accumulate to generate species-level responses. Here, we review recent developments in using plant-pollinator networks of interacting individuals along with their functional traits, where individuals are nested within species nodes. We highlight how these individual-level, trait-based networks connect intraspecific trait variation (as frequency distributions of multiple traits) with dynamic responses within plant-pollinator communities. This approach can better explain interaction plasticity, and changes to interaction probabilities and network structure over spatiotemporal or other environmental gradients. We argue that only through appreciating such trait-based interaction plasticity can we accurately forecast the potential vulnerability of interactions to future environmental change. We follow this with general guidance on how future studies can collect and analyse high-resolution interaction and trait data, with the hope of improving predictions of future plant-pollinator network responses for targeted and effective conservation.

Matrix community models for ecology and evolution

Ecological communities are shaped by biotic interactions as well as environmental forces, and both must be incorporated to obtain models capable of forecasting realistic community dynamics. Many community models first specify pairwise biotic interactions and then secondarily examine how extrinsic factors such as abiotic conditions affect species abundances. A disadvantage of this approach is that the species interactions themselves are often environment and context specific, making parameterization difficult. We propose an alternative approach, matrix community models (MCMs), which are sets of matrix population models linked by an assumption of aggregate density dependence. MCMs incorporate detailed species autecology but are neutral with respect to pairwise species interactions, instead allowing interactions to be revealed within the model structure. These model-revealed species interactions, including competitive exclusion, facilitation, and interference competition, shape the distribution and abundance of species within communities and generate empirically testable predictions about species interactions. We develop a framework for building MCMs using vital rates in a stochastic, multispecies framework. Single-species matrix population models are connected via an assumption of aggregate density dependence, pairwise species interactions are estimated with sensitivity analysis, and community trajectories are analyzed under different environmental regimes using standard statistical tools and network analysis. MCMs have the advantage that pairwise species interactions need not be specified a priori, and that mechanistic demographic-environment linkages permit forecasting of community dynamics under novel, non-stationary environmental regimes. A challenge is that species' autecological vital rates, such as fecundity, growth and survivorship, must be measured under a diverse range of environmental conditions to parameterize the models. We illustrate the approach with examples and discuss prospects for future theoretical and empirical developments.

Temporal change in floral availability leads to periods of resource limitation and affects diet specificity in a generalist pollinator

Generalist species are core components of ecological networks and crucial for the maintenance of biodiversity. Generalist species and networks are expected to be more resilient, and therefore understanding the dynamics of specialization and generalization in ecological networks is a key focus in a time of rapid global change. Whilst diet generalization is frequently studied, our understanding of how it changes over time is limited. Here we explore temporal variation in diet specificity in the honeybee (Apis mellifera), using pollen DNA metabarcoding of honey samples, through the foraging season, over two years. We find that, overall, honeybees are generalists that visit a wide range of plants, but there is temporal variation in the degree of specialization. Temporal specialization of honeybee colonies corresponds to periods of resource limitation, identified as a lack of honey stores. Honeybees experience a lack of preferred resources in June when switching from flowering trees in spring to shrubs and herbs in summer. Investigating temporal patterns in specialization can identify periods of resource limitation that may lead to species and network vulnerability. Diet specificity must therefore be explored at different temporal scales in order to fully understand species and network stability in the face of ecological change.

Ecological network structure in response to community assembly processes over evolutionary time

The dynamic structure of ecological communities results from interactions among taxa that change with shifts in species composition in space and time. However, our ability to study the interplay of ecological and evolutionary processes on community assembly remains relatively unexplored due to the difficulty of measuring community structure over long temporal scales. Here, we made use of a geological chronosequence across the Hawaiian Islands, representing 50 years to 4.15 million years of ecosystem development, to sample 11 communities of arthropods and their associated plant taxa using semiquantitative DNA metabarcoding. We then examined how ecological communities changed with community age by calculating quantitative network statistics for bipartite networks of arthropod-plant associations. The average number of interactions per species (linkage density), ratio of plant to arthropod species (vulnerability) and uniformity of energy flow (interaction evenness) increased significantly in concert with community age. The index of specializationH 2 ' has a curvilinear relationship with community age. Our analyses suggest that younger communities are characterized by fewer but stronger interactions, while biotic associations become more even and diverse as communities mature. These shifts in structure became especially prominent on East Maui (~0.5 million years old) and older volcanos, after enough time had elapsed for adaptation and specialization to act on populations in situ. Such natural progression of specialization during community assembly is probably impeded by the rapid infiltration of non-native species, with special risk to younger or more recently disturbed communities that are composed of fewer specialized relationships.

Plant Growth-Promoting Bacteria of Soil: Designing of Consortia Beneficial for Crop Production

Plant growth-promoting bacteria are commonly used in agriculture, particularly for seed inoculation. Multispecies consortia are believed to be the most promising form of these bacteria. However, designing and modeling bacterial consortia to achieve desired phenotypic outcomes in plants is challenging. This review aims to address this challenge by exploring key antimicrobial interactions. Special attention is given to approaches for developing soil plant growth-promoting bacteria consortia. Additionally, advanced omics-based methods are analyzed that allow soil microbiomes to be characterized, providing an understanding of the molecular and functional aspects of these microbial communities. A comprehensive discussion explores the utilization of bacterial preparations in biofertilizers for agricultural applications, focusing on the intricate design of synthetic bacterial consortia with these preparations. Overall, the review provides valuable insights and strategies for intentionally designing bacterial consortia to enhance plant growth and development.

Effect of altitude and spatial heterogeneity on the host-parasite relationship in anurans from a remnant humid forest in the brazilian semiarid

In the present study, we investigated the effect of habitat heterogeneity, elevation gradient, and phylogenetic distance of host species on the abundance and richness of anuran endoparasites, assuming that parasites follow the distribution of their hosts independently of environmental variation. We collected 192 anurans distributed in three altitude ranges: 100-200 m, 400-500 m, and 700-800 m. We performed discriminant principal component analysis to analyze the interrelationships between environmental heterogeneity and the distribution of parasite and host species in the formation of species groups in each altitude range. We estimated the niche width and parasite overlap, using host species as a variable, and assessed whether parasite abundance is more influenced by historical (distance host phylogeny) or ecological effects in each altitude category and overall. Finally, we use network analyses to understand how interactions between parasites and hosts are formed along the altitude gradient. We found 22 parasite species, and the overall prevalence of infection was 74%. In our study, we did not identify environmental (altitude gradients and heterogeneity) or phylogenetic effects acting on the parasite species diversity. Overall, our results suggest that the parasites are distributed following the dispersal of their hosts and are dispersed among most anuran species.

Ecological network analysis reveals cancer-dependent chaperone-client interaction structure and robustness

Cancer cells alter the expression levels of metabolic enzymes to fuel proliferation. The mitochondrion is a central hub of metabolic reprogramming, where chaperones service hundreds of clients, forming chaperone-client interaction networks. How network structure affects its robustness to chaperone targeting is key to developing cancer-specific drug therapy. However, few studies have assessed how structure and robustness vary across different cancer tissues. Here, using ecological network analysis, we reveal a non-random, hierarchical pattern whereby the cancer type modulates the chaperones' ability to realize their potential client interactions. Despite the low similarity between the chaperone-client interaction networks, we highly accurately predict links in one cancer type based on another. Moreover, we identify groups of chaperones that interact with similar clients. Simulations of network robustness show that this group structure affects cancer-specific response to chaperone removal. Our results open the door for new hypotheses regarding the ecology and evolution of chaperone-client interaction networks and can inform cancer-specific drug development strategies.

What constrains food webs? A maximum entropy framework for predicting their structure with minimal biases

Food webs are complex ecological networks whose structure is both ecologically and statistically constrained, with many network properties being correlated with each other. Despite the recognition of these invariable relationships in food webs, the use of the principle of maximum entropy (MaxEnt) in network ecology is still rare. This is surprising considering that MaxEnt is a statistical tool precisely designed for understanding and predicting many types of constrained systems. This principle asserts that the least-biased probability distribution of a system's property, constrained by prior knowledge about that system, is the one with maximum information entropy. MaxEnt has been proven useful in many ecological modeling problems, but its application in food webs and other ecological networks is limited. Here we show how MaxEnt can be used to derive many food-web properties both analytically and heuristically. First, we show how the joint degree distribution (the joint probability distribution of the numbers of prey and predators for each species in the network) can be derived analytically using the number of species and the number of interactions in food webs. Second, we present a heuristic and flexible approach of finding a network's adjacency matrix (the network's representation in matrix format) based on simulated annealing and SVD entropy. We built two heuristic models using the connectance and the joint degree sequence as statistical constraints, respectively. We compared both models' predictions against corresponding null and neutral models commonly used in network ecology using open access data of terrestrial and aquatic food webs sampled globally (N = 257). We found that the heuristic model constrained by the joint degree sequence was a good predictor of many measures of food-web structure, especially the nestedness and motifs distribution. Specifically, our results suggest that the structure of terrestrial and aquatic food webs is mainly driven by their joint degree distribution.

Dynamics of species-rich predator-prey networks and seasonal alternations of core species

In nature, entangled webs of predator-prey interactions constitute the backbones of ecosystems. Uncovering the network architecture of such trophic interactions has been recognized as the essential step for exploring species with great impacts on ecosystem-level phenomena and functions. However, it has remained a major challenge to reveal how species-rich networks of predator-prey interactions are continually reshaped through time in the wild. Here, we show that dynamics of species-rich predator-prey interactions can be characterized by remarkable network structural changes and alternations of species with greatest impacts on community processes. On the basis of high-throughput detection of prey DNA from 1,556 spider individuals collected in a grassland ecosystem, we reconstructed dynamics of interaction networks involving, in total, 50 spider species and 974 prey species and strains through 8 months. The networks were compartmentalized into modules (groups) of closely interacting predators and prey in each month. Those modules differed in detritus/grazing food chain properties, forming complex fission-fusion dynamics of belowground and aboveground energy channels across the seasons. The substantial shifts of network structure entailed alternations of spider species located at the core positions within the entangled webs of interactions. These results indicate that knowledge of dynamically shifting food webs is crucial for understanding temporally varying roles of 'core species' in ecosystem processes.

metanetwork: A R package dedicated to handling and representing trophic metanetworks

Trophic networks describe interactions between species at a given location and time. Due to environmental changes, anthropogenic perturbations or sampling effects, trophic networks may vary in space and time. The collection of network time series or networks in different sites thus constitutes a metanetwork. We present here the R package metanetwork, which will ease the representation, the exploration and analysis of trophic metanetwork data sets that are increasingly available. Our main methodological advance consists in suitable layout algorithm for trophic networks, which is based on trophic levels and dimension reduction in a graph diffusion kernel. In particular, it highlights relevant features of trophic networks (trophic levels, energetic channels). In addition, we developed tools to handle, compare visually and quantitatively and aggregate those networks. Static and dynamic visualisation functions have been developed to represent large networks. We apply our package workflow to several trophic network data sets.

The reliability of regional ecological knowledge to build local interaction networks: a test using seed-dispersal networks across land-bridge islands

Building ecological networks is the fundamental basis of depicting how species in communities interact, but sampling complex interaction networks is extremely labour intensive. Recently, indirect ecological information has been applied to build interaction networks. Here we propose to extend the source of indirect ecological information, and applied regional ecological knowledge to build local interaction networks. Using a high-resolution dataset consisting of 22 locally observed networks with 17 572 seed-dispersal events, we test the reliability of indirectly derived local networks based on regional ecological knowledge (REK) across islands. We found that species richness strongly influenced 'local interaction rewiring' (i.e. the proportion of locally observed interactions among regionally interacting species), and all network properties were biased using REK-based networks. Notably, species richness and local interaction rewiring strongly affected estimations of REK-based network structures. However, locally observed and REK-based networks detected the same trends of how network structure correlates to island area and isolation. These results suggest that we should use REK-based networks cautiously for reflecting actual interaction patterns of local networks, but highlight that REK-based networks have great potential for comparative studies across environmental gradients. The use of indirect regional ecological information may thus advance our understanding of biogeographical patterns of species interactions.

An integrative approach to understanding diversity patterns and assemblage rules in Neotropical bats

Understanding the mechanisms shaping species composition of assemblages is critical for incorporating ecological and evolutionary perspectives into biodiversity conservation. Thus, we quantified the relative support of community assembly mechanisms by assessing how species richness relates to the functional and phylogenetic biodiversity of Neotropical bat assemblages. We assessed the association of functional diversity for functional categories and phylogenetic diversity with species richness for 20 assemblages of Neotropical bats. In addition, we contrasted functional and phylogenetic diversity against null models to determine the mechanisms that structure the assemblages. We hypothesize functional/phylogenetic overdispersion for high species sites and a positive relationship between those dimensions of diversity and richness. Functional divergence increased with species richness, indicating that the variability in ecological attributes among abundant bats increases as the assemblages contain more species. Taxa were more distantly related as richness increases, but distances among closely related species remained constant. We found a consistent tendency of clustering of functional traits in site assemblages, particularly in abundant species. We proposed competition between clades as a possible mechanism modulating the community structure in Neotropical bat assemblages. Our results suggest that decreasing overlap in functional traits between abundant species could promote coexistence with rare species that can buffer ecosystem function due to species loss.

Variation in body size drives spatial and temporal variation in lobster-urchin interaction strength

How strongly predators and prey interact is both notoriously context dependent and difficult to measure. Yet across taxa, interaction strength is strongly related to predator size, prey size and prey density, suggesting that general cross-taxonomic relationships could be used to predict how strongly individual species interact. Here, we ask how accurately do general size-scaling relationships predict variation in interaction strength between specific species that vary in size and density across space and time? To address this question, we quantified the size and density dependence of the functional response of the California spiny lobster Panulirus interruptus, foraging on a key ecosystem engineer, the purple sea urchin Strongylocentrotus purpuratus, in experimental mesocosms. Based on these results, we then estimated variation in lobster-urchin interaction strength across five sites and 9 years of observational data. Finally, we compared our experimental estimates to predictions based on general size-scaling relationships from the literature. Our results reveal that predator and prey body size has the greatest effect on interaction strength when prey abundance is high. Due to consistently high urchin densities in the field, our simulations suggest that body size-relative to density-accounted for up to 87% of the spatio-temporal variation in interaction strength. However, general size-scaling relationships failed to predict the magnitude of interactions between lobster and urchin; even the best prediction from the literature was, on average, an order of magnitude (+18.7×) different than our experimental predictions. Harvest and climate change are driving reductions in the average body size of many marine species. Anticipating how reductions in body size will alter species interactions is critical to managing marine systems in an ecosystem context. Our results highlight the extent to which differences in size-frequency distributions can drive dramatic variation in the strength of interactions across narrow spatial and temporal scales. Furthermore, our work suggests that species-specific estimates for the scaling of interaction strength with body size, rather than general size-scaling relationships, are necessary to quantitatively predict how reductions in body size will alter interaction strengths.

Colonization-competition dynamics of basal species shape food web complexity in island metacommunities

Exploring how food web complexity emerges and evolves in island ecosystems remains a major challenge in ecology. Food webs assembled from multiple islands are commonly recognized as highly complex trophic networks that are dynamic in both space and time. In the context of global climate change, it remains unclear whether food web complexity will decrease in a monotonic fashion when undergoing habitat destruction (e.g., the inundation of islands due to sea-level rise). Here, we develop a simple yet comprehensive patch-dynamic framework for complex food web metacommunities subject to the competition-colonization tradeoff between basal species. We found that oscillations in food web topological complexity (characterized by species diversity, mean food chain length and the degree of omnivory) emerge along the habitat destruction gradient. This outcome is robust to changing parameters or relaxing the assumption of a strict competitive hierarchy. Having oscillations in food web complexity indicates that small habitat changes could have disproportionate negative effects on species diversity, thus the success of conservation actions should be evaluated not only on changes in biodiversity, but also on system robustness to habitat alteration. Overall, this study provides a parsimonious mechanistic explanation for the emergence of food web complexity in island ecosystems, further enriching our understanding of metacommunity assembly.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-023-00167-0.

Direct and indirect viral associations predict coexistence in wild plant virus communities

Viruses are a vastly underestimated component of biodiversity that occur as diverse communities across hierarchical scales from the landscape level to individual hosts. The integration of community ecology with disease biology is a powerful, novel approach that can yield unprecedented insights into the abiotic and biotic drivers of pathogen community assembly. Here, we sampled wild plant populations to characterize and analyze the diversity and co-occurrence structure of within-host virus communities and their predictors. Our results show that these virus communities are characterized by diverse, non-random coinfections. Using a novel graphical network modeling framework, we demonstrate how environmental heterogeneity influences the network of virus taxa and how the virus co-occurrence patterns can be attributed to non-random, direct statistical virus-virus associations. Moreover, we show that environmental heterogeneity changed virus association networks, especially through their indirect effects. Our results highlight a previously underestimated mechanism of how environmental variability can influence disease risks by changing associations between viruses that are conditional on their environment.

Disruption of ecological networks in lakes by climate change and nutrient fluctuations

Climate change interacts with local processes to threaten biodiversity by disrupting the complex network of ecological interactions. While changes in network interactions drastically affect ecosystems, how ecological networks respond to climate change, in particular warming and nutrient supply fluctuations, is largely unknown. Here, using an equation-free modelling approach on monthly plankton community data in ten Swiss lakes, we show that the number and strength of plankton community interactions fluctuate and respond nonlinearly to water temperature and phosphorus. While lakes show system-specific responses, warming generally reduces network interactions, particularly under high phosphate levels. This network reorganization shifts trophic control of food webs, leading to consumers being controlled by resources. Small grazers and cyanobacteria emerge as sensitive indicators of changes in plankton networks. By exposing the outcomes of a complex interplay between environmental drivers, our results provide tools for studying and advancing our understanding of how climate change impacts entire ecological communities.

Pan-Arctic marine biodiversity and species co-occurrence patterns under recent climate

The Arctic region is experiencing drastic climatic changes bringing about potential ecological shifts. Here, we explored marine biodiversity and potential species associations across eight Arctic marine areas between 2000 and 2019. We compiled species occurrences for a subset of 69 marine taxa (i.e., 26 apex predators and 43 mesopredators) and environmental factors to predict taxon-specific distributions using a multi-model ensemble approach. Arctic-wide temporal trends of species richness increased in the last 20 years and highlighted potential emerging areas of species accrual due to climate-driven species redistribution. Further, regional species associations were dominated by positive co-occurrences among species pairs with high frequencies in the Pacific and Atlantic Arctic areas. Comparative analyses of species richness, community composition, and co-occurrence between high and low summer sea ice concentrations revealed contrasting impacts of and detected areas vulnerable to sea ice changes. In particular, low (high) summer sea ice generally resulted in species gains (loss) in the inflow and loss (gains) in the outflow shelves, accompanied by substantial changes in community composition and therefore potential species associations. Overall, the recent changes in biodiversity and species co-occurrences in the Arctic were driven by pervasive poleward range shifts, especially for wide-ranging apex predators. Our findings highlight the varying regional impacts of warming and sea ice loss on Arctic marine communities and provide important insights into the vulnerability of Arctic marine areas to climate change.

Worldwide host associations of the tick genus Ixodes suggest relationships based on environmental sharing rather than on co-phylogenetic events

BACKGROUND

This study aims to capture how ticks of the genus Ixodes gained their hosts using network constructs. We propose two alternative hypotheses, namely, an ecological background (ticks and hosts sharing environmentally available conditions) and a phylogenetic one, in which both partners co-evolved, adapting to existing environmental conditions after the association took place.

METHODS

We used network constructs linking all the known pairs of associations between each species and stage of ticks with families and orders of hosts. Faith's phylogenetic diversity was used to evaluate the phylogenetic distance of the hosts of each species and changes occurring in the ontogenetic switch between consecutive stages of each species (or the extent of the changes in phylogenetic diversity of hosts for consecutive stages of the same species).

RESULTS

We report highly clustered associations among Ixodes ticks and hosts, supporting the influence of the ecological adaptation and coexistence, demonstrating a lack of strict tick-host coevolution in most cases, except for a few species. Keystone hosts do not exist in the relationships between Ixodes and vertebrates because of the high redundancy of the networks, further supporting an ecological relationship between both types of partners. The ontogenetic switch of hosts is high for species with enough data, which is another potential clue supporting the ecological hypothesis. Other results suggest that the networks displaying tick-host associations are different according to the biogeographical realms. Data for the Afrotropical region reveal a lack of extensive surveys, while results for the Australasian region are suggestive of a mass extinction of vertebrates. The Palearctic network is well developed, with many links demonstrating a highly modular set of relationships.

CONCLUSIONS

With the obvious exceptions of Ixodes species restricted to one or a few hosts, the results point to an ecological adaptation. Even results on species linked to groups of ticks (such as Ixodes uriae and the pelagic birds or the bat-tick species) are suggestive of a previous action of environmental forces.

Phylogenetic and functional constraints of plant facilitation rewiring

Facilitative interactions bind community species in intricate ecological networks, preserving species that would otherwise be lost. The traditional understanding of ecological networks as static components of biological communities overlooks the fact that species interactions in a network can fluctuate. Analyzing the patterns that cause those shifts can reveal the principles that govern the identity of pairwise interactions and whether they are predictable based on the traits of the interacting species and the local environmental contexts in which they occur. Here we explore how abiotic stress and phylogenetic and functional affinities constrain those shifts. Specifically, we hypothesize that rewiring the facilitative interactions is more limited in stressful than in mild environments. We present evidence of a distinct pattern in the rewiring of facilitation-driven communities at different stress levels. In highly stressful environments with a firm reliance on facilitation, rewiring is limited to growing beneath nurse species with traits to overcome harsh stressful conditions. However, when environments are milder, rewiring is more flexible, although it is still constrained to nurses that are close relatives. Understanding the ability of species to rewire their interactions is crucial for predicting how communities may respond to the unprecedented rate of perturbations on Earth.

Combining Geographic Distribution and Trait Information to Infer Predator–Prey Species-Level Interaction Properties

Biotic interactions are a key component of the proper functioning of ecosystems. However, information on biotic interactions is spatially and taxonomically biased and limited to several groups. The most efficient strategy to fill these gaps is to combine spatial information (species ranges) with different sources of information (functional and field data) to infer potential interactions. This approach is possible due to the fact that there is a correspondence between the traits of two trophic levels (e.g., predator and prey sizes are correlated). Therefore, our objective was to evaluate the performance of the joint use of spatial, functional and field data to infer properties of the predator–prey interaction for five neotropical cats. To do this, we used presence–absence matrices to obtain lists of potential prey species per grid-cell for each predator range. These lists were filtered according to different criteria (models), and for each model, an interaction property was estimated and compared with field observations. Our results show that the use of functional information and co-occurrence allows us to generate values similar to those observed in the field. We also observed that there were differences in model performance related to the intrinsic characteristics of the predator (body size) and the interaction property being evaluated.

Structure and characteristics of the plant-frugivore bird network from the Guilin Botanical Garden

The interaction between plants and frugivores is crucial to ecosystem function and community diversity. However, little is known about the interaction between plants and frugivorous bird species in urban green spaces. We observed interactions between plants and frugivorous birds in the Guilin Botanical Garden for one year and determined the structure and characteristics of the interaction network. We also analyzed the impact of species traits on their network roles. Interactions between 14 frugivorous birds and 13 fruit plant species were recorded in the study area. Autumn interactions comprised 38.79% of the overall network, and winter interactions comprised 33.15%. The modularity (Q, z-score) of the network was higher in autumn; the weighted nestedness (wNODF, z-score) and interaction evenness (E₂ , z-score) of the network were higher in winter; the connectance (C, z-score) and interaction diversity (z-score) of the network were higher in spring; and the specialization (H₂', z-score) of the network was higher in summer. The observed network showed lower C, lower interaction H₂ , lower E₂ , lower wNODF, higher H₂' and higher Q when compared to the random networks. The bird species most important to network stability were Hemixos castanonotus, Parus venustulus, and Pycnonotus sinensis. The most important plant species were Alocasia macrorrhiza, Cinnamomum camphora, and Machilus nanmu. Of all the bird and plant traits included in this study, only plant color had a significant impact on species strength, with black fruit having a higher species strength. Our results suggest that interaction networks in urban green spaces can be temporally complex and variable and that a network approach can be an important monitoring tool for detecting the status of crucial ecosystem functions.

DNA metabarcoding of gut contents reveals key habitat and seasonal drivers of trophic networks involving generalist predators in agricultural landscapes

BACKGROUND

Understanding the networks of trophic interactions into which generalist predators are embedded is key to assessing their ecological role of in trophic networks and the biological control services they provide. The advent of affordable DNA metabarcoding approaches greatly facilitates quantitative understanding of trophic networks and their response to environmental drivers. Here, we examine how key environmental gradients interact to shape predation by Lycosidae in highly dynamic vegetable growing systems in China.

RESULTS

For the sampled Lycosidae, crop identity, pesticide use and seasons shape the abundance of prey detected in spider guts. For the taxonomic richness of prey, local- and landscape-scale factors gradients were more influential. Multivariate ordinations confirm that these crop-abundant spiders dynamically adjust their diet to reflect environmental constraints and seasonal availability to prey.

CONCLUSION

Plasticity in diet composition is likely to account for the persistence of spiders in relatively ephemeral brassica crops. Our findings provide further insights into the optimization of habitat management for predator-based biological control practices. © 2022 Society of Chemical Industry.

Natural Populations from the Phytophthora palustris Complex Show a High Diversity and Abundance of ssRNA and dsRNA Viruses

We explored the virome of the “Phytophthora palustris complex”, a group of aquatic specialists geographically limited to Southeast and East Asia, the native origin of many destructive invasive forest Phytophthora spp. Based on high-throughput sequencing (RNAseq) of 112 isolates of “P. palustris” collected from rivers, mangroves, and ponds, and natural forests in subtropical and tropical areas in Indonesia, Taiwan, and Japan, 52 putative viruses were identified, which, to varying degrees, were phylogenetically related to the families Botybirnaviridae, Narnaviridae, Tombusviridae, and Totiviridae, and the order Bunyavirales. The prevalence of all viruses in their hosts was investigated and confirmed by RT-PCR. The rich virus composition, high abundance, and distribution discovered in our study indicate that viruses are naturally infecting taxa from the “P. palustris complex” in their natural niche, and that they are predominant members of the host cellular environment. Certain Indonesian localities are the viruses’ hotspots and particular “P. palustris” isolates show complex multiviral infections. This study defines the first bi-segmented bunya-like virus together with the first tombus-like and botybirna-like viruses in the genus Phytophthora and provides insights into the spread and evolution of RNA viruses in the natural populations of an oomycete species.

Changes in invertebrate food web structure between high- and low-productivity environments are driven by intermediate but not top-predator diet shifts

Predator-prey interactions shape ecosystem stability and are influenced by changes in ecosystem productivity. However, because multiple biotic and abiotic drivers shape the trophic responses of predators to productivity, we often observe patterns, but not mechanisms, by which productivity drives food web structure. One way to capture mechanisms shaping trophic responses is to quantify trophic interactions among multiple trophic groups and by using complementary metrics of trophic ecology. In this study, we combine two diet-tracing methods: diet DNA and stable isotopes, for two trophic groups (top predators and intermediate predators) in both low- and high-productivity habitats to elucidate where in the food chain trophic structure shifts in response to changes in underlying ecosystem productivity. We demonstrate that while top predators show increases in isotopic trophic position (δ15N) with productivity, neither their isotopic niche size nor their DNA diet composition changes. Conversely, intermediate predators show clear turnover in DNA diet composition towards a more predatory prey base in high-productivity habitats. Taking this multi-trophic approach highlights how predator identity shapes responses in predator-prey interactions across environments with different underlying productivity, building predictive power for understanding the outcomes of ongoing anthropogenic change.

Causality and correlation analysis for deciphering the microbial interactions in activated sludge

Time series data has been considered to be a massive information provider for comprehending more about microbial dynamics and interaction, leading to a causality inference in a complex microbial community. Granger causality and correlation analysis have been investigated and applied for the construction of a microbial causal correlation network (MCCN) and efficient prediction of the ecological interaction within activated sludge, which thereby exhibited ecological interactions at the OTU-level. Application of MCCN to a time series of activated sludge data revealed that the hub species OTU56, classified as the one belonging to the genus Nitrospira, was responsible for nitrification in activated sludge and interaction with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. The phylogenetic tree suggested a mutualistic relationship between Nitrospira and denitrifiers. Zoogloea displayed the highest ncf value within the classified OTUs of the MCCN, indicating that it could be a foundation for activated sludge through the formation of characteristic cell aggregate matrices where other organisms embed during floc formation. Inclusively, the research outcomes of this study have provided a deep insight into the ecological interactions within the communities of activated sludge.

Fleshy fruit traits and seed dispersers: which traits define syndromes?

BACKGROUND AND AIMS

Fruit traits and their inter-relationships can affect foraging choices by frugivores, and hence the probability of mutualistic interactions. Certain combinations of fruit traits that determine the interaction with specific seed dispersers are known as dispersal syndromes. The dispersal syndrome hypothesis (DSH) states that seed dispersers influence the combination of fruit traits found in fruits. Therefore, fruit traits can predict the type of dispersers with which plant species interact. Here, we analysed whether relationships of fruit traits can be explained by the DSH. To do so, we estimated the inter-relationships between morphological, chemical and display groups of fruit traits. In addition, we tested the importance of each trait group defining seed dispersal syndromes.

METHODS

Using phylogenetically corrected fruit trait data and fruit-seed disperser networks, we tested the relationships among morphological, chemical and display fruit traits with Pearson's correlations and phenotypic integration indices. Then, we used perMANOVA to test if the fruit traits involved in the analysis supported the functional types of seed dispersers.

KEY RESULTS

Morphological traits showed strong intragroup relationships, in contrast to chemical and display traits whose intragroup trait relationships were weak or null. Accordingly, only the morphological group of traits supported three broad seed disperser functional types (birds, terrestrial mammals and bats), consistent with the DSH.

CONCLUSIONS

Altogether, our results give some support to the DSH. Here, the three groups of traits interacted in different ways with seed disperser biology. Broad functional types of seed dispersers would adjust fruit consumption to anatomical limitations imposed by fruit morphology. Once this anatomical filter is sovercome, seed dispersers use almost all the range of variation in chemical and display fruit traits. This suggests that the effect of seed dispersers on fruit traits is modulated by hierarchical decisions. First, morphological constraints define which interactions can actually occur; subsequently, display and composition determine fruit preferences.

Signals of Potential Species Associations Offer Clues about Community Organisation of Stream Fish across Seasons

Simple Summary

Species interactions are one of the main factors affecting community assembly, yet the role of such interactions remains mostly unknown. Here, we investigated roles of potential species associations in fish community assembly in the Qiupu River, China. Our results suggested that potential species associations might have been underestimated in stream fish community assembly. The contribution of potential species associations to fish community assembly can be reflected by interaction network structures. Omnivorous species play an important role in maintaining network structure as they may have more associations with other species. This study highlights the importance of capturing species associations in river ecosystems across different geographical and environmental settings.

Abstract

Environmental filtering, spatial factors and species interactions are fundamental ecological mechanisms for community organisation, yet the role of such interactions across different environmental and spatial settings remains mostly unknown. In this study, we investigated fish community organisation scenarios and seasonal species-to-species associations potentially reflecting biotic associations along the Qiupu River (China). Based on a latent variable approach and a tree-based method, we compared the relative contribution of the abiotic environment, spatial covariates and potential species associations for variation in the community structure, and assessed whether different assembly scenarios were modulated by concomitant changes in the interaction network structure of fish communities across seasons. We found that potential species associations might have been underestimated in community-based assessments of stream fish. Omnivore species, since they have more associations with other species, were found to be key components sustaining fish interaction networks across different stream orders. Hence, we suggest that species interactions, such as predation and competition, likely played a key role in community structure. For instance, indices accounting for network structure, such as connectance and nestedness, were strongly correlated with the unexplained residuals from our latent variable approach, thereby re-emphasising that biotic signals, potentially reflecting species interactions, may be of primary importance in determining stream fish communities across seasons. Overall, our findings indicate that interaction network structures are a powerful tool to reflect the contribution of potential species associations to community assembly. From an applied perspective, this study should encourage freshwater ecologists to empirically capture and manage biotic constraints in stream ecosystems across different geographical and environmental settings, especially in the context of the ever-increasing impacts of human-induced local extinction debts and species invasions.

Effects of spatial distance and woody plant cover on beta diversity point to dispersal limitation as a driver of community assembly during postfire succession in a Mediterranean shrubland

Beta diversity, and its components of turnover and nestedness, reflects the processes governing community assembly, such as dispersal limitation or biotic interactions, but it is unclear how they operate at the local scale and how their role changes along postfire succession. Here, we analyzed the patterns of beta diversity and its components in a herbaceous plant community after fire, and in relation to dispersal ability, in Central Spain. We calculated multiple-site beta diversity (βSOR) and its components of turnover (βSIM) and nestedness (βSNE) of all herbaceous plants, or grouped by dispersal syndrome (autochory, anemochory, and zoochory), during the first 3 years after wildfire. We evaluated the relationship between pairwise beta diversity (βsor), and its components (βsim, βsne), and spatial distance or differences in woody plant cover, a proxy of biotic interactions. We found high multiple-site beta diversity dominated by the turnover component. Community dissimilarity increased with spatial distance, driven mostly by the turnover component. Species with less dispersal ability (i.e., autochory) showed a stronger spatial pattern of dissimilarity. Biotic interactions with woody plants contributed less to community dissimilarity, which tended to occur through the nestedness component. These results suggest that dispersal limitation prevails over biotic interactions with woody plants as a driver of local community assembly, even for species with high dispersal ability. These results contribute to our understanding of postfire community assembly and vegetation dynamics.

Predator-prey landscapes of large sharks and game fishes in the Florida Keys

Interspecific interactions can play an essential role in shaping wildlife populations and communities. To date, assessments of interspecific interactions, and more specifically predator-prey dynamics, in aquatic systems over broad spatial and temporal scales (i.e., hundreds of kilometers and multiple years) are rare due to constraints on our abilities to measure effectively at those scales. We applied new methods to identify space-use overlap and potential predation risk to Atlantic tarpon (Megalops atlanticus) and permit (Trachinotus falcatus) from two known predators, great hammerhead (Sphyrna mokarran) and bull (Carcharhinus leucas) sharks, over a 3-year period using acoustic telemetry in the coastal region of the Florida Keys (USA). By examining spatiotemporal overlap, as well as the timing and order of arrival at specific locations compared to random chance, we show that potential predation risk from great hammerhead and bull sharks to Atlantic tarpon and permit are heterogeneous across the Florida Keys. Additionally, we find that predator encounter rates with these game fishes are elevated at specific locations and times, including a prespawning aggregation site in the case of Atlantic tarpon. Further, using machine learning algorithms, we identify environmental variability in overlap between predators and their potential prey, including location, habitat, time of year, lunar cycle, depth, and water temperature. These predator-prey landscapes provide insights into fundamental ecosystem function and biological conservation, especially in the context of emerging fishery-related depredation issues in coastal marine ecosystems.

Anthropogenic Induced Beta Diversity in Plant–Pollinator Networks: Dissimilarity, Turnover, and Predictive Power

Biogeography has traditionally focused on the distribution of species, while community ecology has sought to explain the patterns of community composition. Species interactions networks have rarely been subjected to such analyses, as modeling tools have only recently been developed for interaction networks. Here, we examine beta diversity of ecological networks using pollination networks sampled along an urbanization and agricultural intensification gradient in east Leinster, Ireland. We show, for the first time, that anthropogenic gradients structure interaction networks, and exert greater structuring force than geographical proximity. We further showed that species turnover, especially of plants, is the major driver of interaction turnover, and that this contribution increased with anthropogenic induced environmental dissimilarity, but not spatial distance. Finally, to explore the extent to which it is possible to predict each of the components of interaction turnover, we compared the predictive performance of models that included site characteristics and interaction properties to models that contained species level effects. We show that if we are to accurately predict interaction turnover, data are required on the species-specific responses to environmental gradients. This study highlights the importance of anthropogenic disturbances when considering the biogeography of interaction networks, especially in human dominated landscapes where geographical effects can be secondary sources of variation. Yet, to build a predictive science of the biogeography of interaction networks, further species-specific responses need to be incorporated into interaction distribution modeling approaches.

Inter-cluster competition and resource partitioning may govern the ecology of Frankia

Microbes live in a complex communal ecosystem. The structural complexity of microbial community reflects diversity, functionality, as well as habitat type. Delineation of ecologically important microbial populations along with exploration of their roles in environmental adaptation or host-microbe interaction has a crucial role in modern microbiology. In this scenario, reverse ecology (the use of genomics to study ecology) plays a pivotal role. Since the co-existence of two different genera in one small niche should maintain a strict direct interaction, it will be interesting to utilize the concept of reverse ecology in this scenario. Here, we exploited an 'R' package, the RevEcoR, to resolve the issue of co-existing microbes which are proven to be a crucial tool for identifying the nature of their relationship (competition or complementation) persisting among them. Our target organism here is Frankia, a nitrogen-fixing actinobacterium popular for its genetic and host-specific nature. According to their plant host, Frankia has already been sub-divided into four clusters C-I, C-II, C-III, and C-IV. Our results revealed a strong competing nature of CI Frankia. Among the clusters of Frankia studied, the competition index between C-I and C-III was the largest. The other interesting result was the co-occurrence of C-II and C-IV groups. It was revealed that these two groups follow the theory of resource partitioning in their lifestyle. Metabolic analysis along with their differential transporter machinery validated our hypothesis of resource partitioning among C-II and C-IV groups.

Linking multi-level population dynamics: state, role, and population

The dynamics of an ecological community can be described at different focal scales of the species, such as individual states or the population level. More detailed descriptions of ecological dynamics offer more information, but produce more complex models that are difficult to analyze. Adequately controlling the model complexity and the availability of multiple descriptions of the concerned dynamics maximizes our understanding of ecological dynamics. One of the central goals of ecological studies is to develop links between multiple descriptions of an ecological community. In this article, starting from a nonlinear state-level description of an ecological community (generalized McKendrick-von Foerster model), role-level and population-level descriptions (Lotka-Volterra model) are derived in a consistent manner. The role-level description covers a wider range of situations than the population-level description. However, using the established connections, it is demonstrated that the population-level description can be used to predict the equilibrium status of the role-level description. This approach connects state-, role-, and population-level dynamics consistently, and offers a justification for the multiple choices of model description.