Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks

Rising temperature drives tipping points in mutualistic networks

The effect of climate warming on species' physiological parameters, including growth rate, mortality rate and handling time, is well established from empirical data. However, with an alarming rise in global temperature more than ever, predicting the interactive influence of these changes on mutualistic communities remains uncertain. Using 139 real plant-pollinator networks sampled across the globe and a modelling approach, we study the impact of species' individual thermal responses on mutualistic communities. We show that at low mutualistic strength plant-pollinator networks are at potential risk of rapid transitions at higher temperatures. Evidently, generalist species play a critical role in guiding tipping points in mutualistic networks. Further, we derive stability criteria for the networks in a range of temperatures using a two-dimensional reduced model. We identify network structures that can ascertain the delay of a community collapse. Until the end of this century, on account of increasing climate warming many real mutualistic networks are likely to be under the threat of sudden collapse, and we frame strategies to mitigate this. Together, our results indicate that knowing individual species' thermal responses and network structure can improve predictions for communities facing rapid transitions.

Impacts on food web properties of island invertebrate communities vary between different human land uses

Human land use is of growing concern for island ecosystems. Besides direct impacts on biodiversity, land uses can alter the functioning and structure of ecosystems. Central to this are impacts on food webs. The release of additional nutrients from human origin, habitat homogenization, or environmental filtering due to human land use can change the diet of individual consumer species (i.e., their trophic niches) and the distribution and overlap of trophic niches within a food web. However, it remains largely unclear whether the effects on food web properties vary between the different and predominant human land uses present on islands. Here, we investigated the impact of two dominant human land uses on small oceanic islands (i.e., urban and tourism development) and tested if and how different land uses on islands affect food web structure. To disentangle human land uses, we investigated islands, which were either privately owned by a tourist facility (i.e., exclusively tourism land use) or experienced urban development from the local population (i.e., urban land use), or remained uninhabited, serving as reference sites free of direct land use. Using stable isotope analysis, we show that isotope signature, trophic (isotopic) niches, and overall food web properties of the investigated island invertebrate communities were significantly changed under both land use regimes. While trophic diversity was reduced and trophic niche widths increased under tourism land use, the investigated food webs showed reduced trophic diversity at the food web base and a more uneven trophic niche distribution under urban land use. In summary, these findings show that different human land uses can have contrasting impacts on oceanic island food webs. As oceanic islands experience rapidly growing human land conversion, our results indicate that they may also face increasing yet unpredictable long-term changes in food web dynamics.

The Coexistence Relationship Between Plants and Soil Bacteria Based on Interdomain Ecological Network Analysis

The relationship between plants and their associated soil microbial communities plays a crucial role in maintaining ecosystem processes and function. However, identifying these complex relationships is challenging. In this study, we constructed an interdomain ecology network (IDEN) of plant–bacteria based on SparCC pairwise associations using synchronous aboveground plant surveys and belowground microbial 16S rRNA sequencing among four different natural forest types along the climate zones in China. The results found that a total of 48 plants were associated with soil bacteria among these four sites, and soil microbial group associations with specific plant species existed within the observed plant–bacteria coexistence network. Only 0.54% of operational taxonomy units (OTUs) was shared by the four sites, and the proportion of unique OTUs for each site ranged from 43.08 to 76.28%, which occupied a large proportion of soil bacterial community composition. The plant–bacteria network had a distinct modular structure (p < 0.001). The tree Acer tetramerum was identified as the network hubs in the warm temperate coniferous and broad-leaved mixed forests coexistence network and indicates that it may play a key role in stabilizing of the community structure of these forest ecosystems. Therefore, IDEN of plant–bacteria provides a novel perspective for exploring the relationships of interdomain species, and this study provides valuable insights into understanding coexistence between above-ground plants and below-ground microorganisms.

Constraints and variation in food web link-species space

Predicting food web structure in future climates is a pressing goal of ecology. These predictions may be impossible without a solid understanding of the factors that structure current food webs. The most fundamental aspect of food web structure-the relationship between the number of links and species-is still poorly understood. Some species interactions may be physically or physiologically 'forbidden'-like consumption by non-consumer species-with possible consequences for food web structure. We show that accounting for these 'forbidden interactions' constrains the feasible link-species space, in tight agreement with empirical data. Rather than following one particular scaling relationship, food webs are distributed throughout this space according to shared biotic and abiotic features. Our study provides new insights into the long-standing question of which factors determine this fundamental aspect of food web structure.

Pathways for Novel Epidemiology: Plant-Pollinator-Pathogen Networks and Global Change

Multiple global change pressures, and their interplay, cause plant-pollinator extinctions and modify species assemblages and interactions. This may alter the risks of pathogen host shifts, intra- or interspecific pathogen spread, and emergence of novel population or community epidemics. Flowers are hubs for pathogen transmission. Consequently, the structure of plant-pollinator interaction networks may be pivotal in pathogen host shifts and modulating disease dynamics. Traits of plants, pollinators, and pathogens may also govern the interspecific spread of pathogens. Pathogen spillover-spillback between managed and wild pollinators risks driving the evolution of virulence and community epidemics. Understanding this interplay between host-pathogen dynamics and global change will be crucial to predicting impacts on pollinators and pollination underpinning ecosystems and human wellbeing.

The Importance of Eco-evolutionary Potential in the Anthropocene

Humans are dominant global drivers of ecological and evolutionary change, rearranging ecosystems and natural selection. In the present article, we show increasing evidence that human activity also plays a disproportionate role in shaping the eco-evolutionary potential of systems—the likelihood of ecological change generating evolutionary change and vice versa. We suggest that the net outcome of human influences on trait change, ecology, and the feedback loops that link them will often (but not always) be to increase eco-evolutionary potential, with important consequences for stability and resilience of populations, communities, and ecosystems. We also integrate existing ecological and evolutionary metrics to predict and manage the eco-evolutionary dynamics of human-affected systems. To support this framework, we use a simple eco–evo feedback model to show that factors affecting eco-evolutionary potential are major determinants of eco-evolutionary dynamics. Our framework suggests that proper management of anthropogenic effects requires a science of human effects on eco-evolutionary potential.

Diversity of Dominant Soil Bacteria Increases with Warming Velocity at the Global Scale

Understanding global soil bacterial diversity is important because of its role in maintaining a healthy global ecosystem. Given the effects of environmental changes (e.g., warming and human impact) on the diversity of animals and plants, effects on soil bacterial diversity are expected; however, they have been poorly evaluated at the global scale to date. Thus, in this study, we focused on the dominant soil bacteria, which are likely critical drivers of key soil processes worldwide, and investigated the effects of warming velocity and human activities on their diversity. Using a global dataset of bacteria, we performed spatial analysis to evaluate the effects of warming velocity and human activities, while statistically controlling for the potentially confounding effects of current climate and geographic parameters with global climate and geographic data. We demonstrated that the diversity of the dominant soil bacteria was influenced globally, not only by the aridity index (dryness) and pH but also by warming velocity from the Last Glacial Maximum (21,000 years ago) to the present, showing significant increases. The increase in bacterial diversity with warming velocity was particularly significant in forests and grasslands. An effect of human activity was also observed, but it was secondary to warming velocity. These findings provide robust evidence and advance our understanding of the effects of environmental changes (particularly global warming) on soil bacterial diversity at the global scale.

Relative effects of anthropogenic pressures, climate, and sampling design on the structure of pollination networks at the global scale

Pollinators provide crucial ecosystem services that underpin to wild plant reproduction and yields of insect-pollinated crops. Understanding the relative impacts of anthropogenic pressures and climate on the structure of plant-pollinator interaction networks is vital considering ongoing global change and pollinator decline. Our ability to predict the consequences of global change for pollinator assemblages worldwide requires global syntheses, but these analytical approaches may be hindered by variable methods among studies that either invalidate comparisons or mask biological phenomena. Here we conducted a synthetic analysis that assesses the relative impact of anthropogenic pressures and climatic variability, and accounts for heterogeneity in sampling methodology to reveal network responses at the global scale. We analyzed an extensive dataset, comprising 295 networks over 123 locations all over the world, and reporting over 50,000 interactions between flowering plant species and their insect visitors. Our study revealed that anthropogenic pressures correlate with an increase in generalism in pollination networks while pollinator richness and taxonomic composition are more related to climatic variables with an increase in dipteran pollinator richness associated with cooler temperatures. The contrasting response of species richness and generalism of the plant-pollinator networks stresses the importance of considering interaction network structure alongside diversity in ecological monitoring. In addition, differences in sampling design explained more variation than anthropogenic pressures or climate on both pollination networks richness and generalism, highlighting the crucial need to report and incorporate sampling design in macroecological comparative studies of pollination networks. As a whole, our study reveals a potential human impact on pollination networks at a global scale. However, further research is needed to evaluate potential consequences of loss of specialist species and their unique ecological interactions and evolutionary pathways on the ecosystem pollination function at a global scale.

Analyzing Macro-Level Ecological Change and Micro-Level Farmer Behavior in Manas River Basin, China

Environmental degradation is closely related to unreasonable land use behaviors by farmers. In this study, participatory rural assessment (PRA) is used to conduct a detailed survey of farmers and plots and to collect relevant natural and social statistics. The accuracy of remote sensing data is verified by comparative analysis, and the change in status of various land use types in each research period is reflected by the change in the dynamic degree and change in range. We examine how farmers’ attitudes and behaviors affect environmental degradation, using a sample of 403 farmers in China’s Manas River Basin. Due to age, education, income and other differences, farmers’ land use behaviors, as well as their attitude toward and feelings about environmental degradation, vary greatly. We found that most farmers considered the environment to be very important to their lives and crop production, but nearly 21% did not know the causes of environmental degradation and nearly 8% did not consider the environmental impacts of their crop production activities. A new model for oasis expansion—land integration—is presented here. This model can increase the area of cultivated land, reduce cultivated land fragmentation, save irrigation water, improve the field microclimate and form a good ecological cycle. Through land transfer, ecological compensation and ecological protection incentives, the government should guide farmers’ land use behaviors toward cooperation with the river basin’s ecological protection and land use planning.

Difficulty in inferring microbial community structure based on co-occurrence network approaches

BACKGROUND

Co-occurrence networks-ecological associations between sampled populations of microbial communities inferred from taxonomic composition data obtained from high-throughput sequencing techniques-are widely used in microbial ecology. Several co-occurrence network methods have been proposed. Co-occurrence network methods only infer ecological associations and are often used to discuss species interactions. However, validity of this application of co-occurrence network methods is currently debated. In particular, they simply evaluate using parametric statistical models, even though microbial compositions are determined through population dynamics.

RESULTS

We comprehensively evaluated the validity of common methods for inferring microbial ecological networks through realistic simulations. We evaluated how correctly nine widely used methods describe interaction patterns in ecological communities. Contrary to previous studies, the performance of the co-occurrence network methods on compositional data was almost equal to or less than that of classical methods (e.g., Pearson's correlation). The methods described the interaction patterns in dense and/or heterogeneous networks rather inadequately. Co-occurrence network performance also depended upon interaction types; specifically, the interaction patterns in competitive communities were relatively accurately predicted while those in predator-prey (parasitic) communities were relatively inadequately predicted.

CONCLUSIONS

Our findings indicated that co-occurrence network approaches may be insufficient in interpreting species interactions in microbiome studies. However, the results do not diminish the importance of these approaches. Rather, they highlight the need for further careful evaluation of the validity of these much-used methods and the development of more suitable methods for inferring microbial ecological networks.

Network resilience of mutualistic ecosystems and environmental changes: an empirical study

It is theorized that a mutualistic ecosystem's resilience against perturbations (e.g. species extinction) is determined by a single macroscopic parameter (network resilience), calculable from the network. Given that such perturbations occur owing to environmental changes (e.g. climate change and human impact), it has been predicted that mutualistic ecosystems that exist despite extensive environmental changes exhibit higher network resilience; however, such a prediction has not been confirmed using real-world data. Thus, in this study, the effects of climate change velocity and human activities on mutualistic network resilience were investigated. A global dataset of plant-animal mutualistic networks was used, and spatial analysis was performed to examine the effects. Moreover, the potential confounding effects of network size, current climate and altitude were statistically controlled. It was demonstrated that mutualistic network resilience was globally influenced by warming velocity and human impact, in addition to current climate. Specifically, pollination network resilience increased in response to human impact, and seed-dispersal network resilience increased with warming velocity. The effect of environmental changes on network resilience for plants was remarkable. The results confirmed the prediction obtained based on the theory and imply that real-world mutualistic networks have a structure that increases ecosystem resilience against environmental changes. These findings will enhance the understanding of ecosystem resilience.

Rethinking the importance of the structure of ecological networks under an environment-dependent framework

A major quest in network and community ecology has been centered on understanding the importance of structural patterns in species interaction networks-the synthesis of who interacts with whom in a given location and time. In the past decades, much effort has been devoted to infer the importance of a particular structure by its capacity to tolerate an external perturbation on its structure or dynamics. Here, we demonstrate that such a perspective leads to inconsistent conclusions. That is, the importance of a network structure changes as a function of the external perturbations acting on a community at any given point in time. Thus, we discuss a research agenda to investigate the relative importance of the structure of ecological networks under an environment-dependent framework. We hypothesize that only by studying systematically the link between network structure and community dynamics under an environment-dependent framework, we can uncover the limits at which communities can tolerate environmental changes.

Decomposing the effects of ocean environments on predator-prey body-size relationships in food webs

Body-size relationships between predators and their prey are important in ecological studies because they reflect the structure and function of food webs. Inspired by studies on the impact of global warming on food webs, the effects of temperature on body-size relationships have been widely investigated; however, the impact of environmental factors on body-size relationships has not been fully evaluated because climate warming affects various ocean environments. Thus, here, we comprehensively investigated the effects of ocean environments and predator-prey body-size relationships by integrating a large-scale dataset of predator-prey body-size relationships in marine food webs with global oceanographic data. We showed that various oceanographic parameters influence prey size selection. In particular, oxygen concentration, primary production and salinity, in addition to temperature, significantly alter body-size relationships. Furthermore, we demonstrated that variability (seasonality) of ocean environments significantly affects body-size relationships. The effects of ocean environments on body-size relationships were generally remarkable for small body sizes, but were also significant for large body sizes and were relatively weak for intermediate body sizes, in the cases of temperature seasonality, oxygen concentration and salinity variability. These findings break down the complex effects of ocean environments on body-size relationships, advancing our understanding of how ocean environments influence the structure and functioning of food webs.

Why are some plant-pollinator networks more nested than others?

Empirical studies have found that the mutualistic interactions forming the structure of plant-pollinator networks are typically more nested than expected by chance alone. Additionally, theoretical studies have shown a positive association between the nested structure of mutualistic networks and community persistence. Yet, it has been shown that some plant-pollinator networks may be more nested than others, raising the interesting question of which factors are responsible for such enhanced nested structure. It has been argued that ordered network structures may increase the persistence of ecological communities under less predictable environments. This suggests that nested structures of plant-pollinator networks could be more advantageous under highly seasonal environments. While several studies have investigated the link between nestedness and various environmental variables, unfortunately, there has been no unified answer to validate these predictions. Here, we move from the problem of describing network structures to the problem of comparing network structures. We develop comparative statistics, and apply them to investigate the association between the nested structure of 59 plant-pollinator networks and the temperature seasonality present in their locations. We demonstrate that higher levels of nestedness are associated with a higher temperature seasonality. We show that the previous lack of agreement came from an extended practice of using standardized measures of nestedness that cannot be compared across different networks. Importantly, our observations complement theory showing that more nested network structures can increase the range of environmental conditions compatible with species coexistence in mutualistic systems, also known as structural stability. This increase in nestedness should be more advantageous and occur more often in locations subject to random environmental perturbations, which could be driven by highly changing or seasonal environments. This synthesis of theory and observations could prove relevant for a better understanding of the ecological processes driving the assembly and persistence of ecological communities.

Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions

Background

Host–pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected.

Results

We re-evaluated the importance of the reverse ecology method for evaluating host–pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host–pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures.

Conclusion

These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host–pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host–pathogen interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1696-7) contains supplementary material, which is available to authorized users.

Exosomes in mammals with greater habitat variability contain more proteins and RNAs

Factors determining habitat variability are poorly understood despite possible explanations based on genome and physiology. This is because previous studies only focused on primary measures such as genome size and body size. In this study, we hypothesize that specific gene functions determine habitat variability in order to explore new factors beyond primary measures. We comprehensively evaluate the relationship between gene functions and the climate envelope while statistically controlling for potentially confounding effects by using data on the habitat range, genome, body size and metabolism of various mammals. Our analyses show that the number of proteins and RNAs contained in exosomes is predominantly associated with the climate envelope. This finding indicates the importance of exosomes to habitat range expansion of mammals and provides a new hypothesis for the relationship between the genome and habitat variability.

The combined effects of biotic and abiotic stress on species richness and connectance

Food web structure and species richness are both subject to biotic (e.g. predation pressure and resource limitation) and abiotic stress (e.g. environmental change). We investigated the combined effects of both types of stress on richness and connectance, and on their relationship, in a predator-prey system. To this end, we developed a mathematical two trophic level food-web model to investigate the effects of biotic and abiotic stress on food web connectance and species richness. We found negative effects of top-down and bottom-up control on prey and predator richness, respectively. Effects of top-down and bottom-up control were stronger when initial connectance was high and low, respectively. Bottom-up control could either aggravate or buffer negative effects of top-down control. Abiotic stress affecting predator richness had positive indirect effects on prey richness, but only when initial connectance was low. However, no indirect effects on predator richness were observed following direct effects on prey richness. Top-down and bottom-up control selected for weakly connected prey and highly connected predators, thereby decreasing and increasing connectance, respectively. Our simulations suggest a broad range of negative and positive richness-connectance relationships, thereby revisiting the often found negative relationship between richness and connectance in food webs. Our results suggest that (1) initial food-web connectance strongly influences the effects of biotic stress on richness and the occurrence of indirect effects on richness; and (2) the shape of the richness-connectance relationship depends on the type of biotic stress.