Trophic network structure emerges through antagonistic coevolution in temporally varying environments

Understanding the mechanisms underlying ecological specialization is central to our understanding of community ecology and evolution. Although theoretical work has investigated how variable environments may affect specialization in single species, little is known about how such variation impacts bipartite network structure in antagonistically coevolving systems. Here, we develop and analyse a general model of victim-enemy coevolution that explicitly includes resource and population dynamics. We investigate how temporal environmental heterogeneity affects the evolution of specialization and associated community structure. Environmental productivity influences victim investment in resistance, which will shape patterns of specialization through its regulating effect on enemy investment in infectivity. We also investigate the epidemiological consequences of environmental variability and show that enemy population density is maximized for intermediate lengths of productive seasons, which corresponds to situations where enemies can evolve higher infectivity than victims can evolve defence. We discuss our results in the light of empirical studies, and further highlight ways in which our model applies to a range of natural systems.     

Long-term observation of a pollination network: fluctuation in species and interactions, relative invariance of network structure and implications for estimates of specialization

We analysed the dynamics of a plant-pollinator interaction network of a scrub community surveyed over four consecutive years. Species composition within the annual networks showed high temporal variation. Temporal dynamics were also evident in the topology of the network, as interactions among plants and pollinators did not remain constant through time. This change involved both the number and the identity of interacting partners. Strikingly, few species and interactions were consistently present in all four annual plant-pollinator networks (53% of the plant species, 21% of the pollinator species and 4.9% of the interactions). The high turnover in species-to-species interactions was mainly the effect of species turnover (c. 70% in pairwise comparisons among years), and less the effect of species flexibility to interact with new partners (c. 30%). We conclude that specialization in plant-pollinator interactions might be highly overestimated when measured over short periods of time. This is because many plant or pollinator species appear as specialists in 1 year, but tend to be generalists or to interact with different partner species when observed in other years. The high temporal plasticity in species composition and interaction identity coupled with the low variation in network structure properties (e.g. degree centralization, connectance, nestedness, average distance and network diameter) imply (i) that tight and specialized coevolution might not be as important as previously suggested and (ii) that plant-pollinator interaction networks might be less prone to detrimental effects of disturbance than previously thought. We suggest that this may be due to the opportunistic nature of plant and animal species regarding the available partner resources they depend upon at any particular time.     

Invariant properties of mycobiont-photobiont networks in Antarctic lichens

Aim

Lichens are often regarded as paradigms of mutualistic relationships. However, it is still poorly known how lichen-forming fungi and their photosynthetic partners interact at a community scale. We explored the structure of fungus-alga networks of interactions in lichen communities along a latitudinal transect in continental Antarctica. We expect these interactions to be highly specialized and, consequently, networks with low nestedness degree and high modularity.

Location

Transantarctic Mountains from 76° S to 85° S (continental Antarctica).

Time Period

Present.

Major Taxa Studied

Seventy-seven species of lichen-forming fungi and their photobionts.

Methods

DNA barcoding of photobionts using nrITS data was conducted in 756 lichen specimens from five regions along the Transantarctic Mountains. We built interaction networks for each of the five studied regions and a metaweb for the whole area. We explored the specialization of both partners using the number of partners a species interacts with and the specialization parameter d'. Network architecture parameters such as nestedness, modularity and network specialization parameter H₂' were studied in all networks and contrasted through null models. Finally, we measured interaction turnover along the latitudinal transect.

Results

We recovered a total of 842 interactions. Differences in specialization between partners were not statistically significant. Fungus-alga interaction networks showed high specialization and modularity, as well as low connectance and nestedness. Despite the large turnover in interactions occurring among regions, network parameters were not correlated with latitude.

Main Conclusions

The interaction networks established between fungi and algae in saxicolous lichen communities in continental Antarctica showed invariant properties along the latitudinal transect. Rewiring is an important driver of interaction turnover along the transect studied. Future work should answer whether the patterns observed in our study are prevalent in other regions with milder climates and in lichen communities on different substrates.     

Motifs in bipartite ecological networks: uncovering indirect interactions

Indirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about bipartite ecological networks, we show that this shift is supported by analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight differences missed by the current index paradigm that may be ecologically important. We extend this finding to empirical plant–pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need to not rely solely on network‐ and species‐level indices for characterising the structure of bipartite ecological networks.     

Global patterns in anuran–prey networks: structure mediated by latitude

Life on Earth is supported by an infinite number of interactions among organisms. Species interactions in these networks are influenced by latitude, evolutionary history and species traits. We performed a global‐scale literature analysis to build up a database of interactions between anuran communities and their preys, from a wide range of geographical areas, using a network approach. For this purpose, we compiled a total of 55 weighted anuran–prey interaction networks, 39 located in the tropics and 16 in temperate areas. We tested the influence of latitude, as well as anuran taxonomic, functional and phylogenetic richness on network metrics. We found that anuran–prey networks are not nested, exhibit low complementary specialization and modularity and high connectance when compared to other types of networks. The main effects on network metrics were related to latitude, followed by anuran taxonomic, functional and phylogenetic richness, a pattern similar to the emerging in mutualistic networks. Our study is the first integrated analysis of the structural patterns in anuran–prey antagonistic interaction networks in different parts of the world. We suggest that different processes, mediated mainly by latitude, are modeling the architecture of anuran–prey networks across the globe.     

The dimensionality of ecological networks

How many dimensions (trait‐axes) are required to predict whether two species interact? This unanswered question originated with the idea of ecological niches, and yet bears relevance today for understanding what determines network structure. Here, we analyse a set of 200 ecological networks, including food webs, antagonistic and mutualistic networks, and find that the number of dimensions needed to completely explain all interactions is small ( < 10), with model selection favouring less than five. Using 18 high‐quality webs including several species traits, we identify which traits contribute the most to explaining network structure. We show that accounting for a few traits dramatically improves our understanding of the structure of ecological networks. Matching traits for resources and consumers, for example, fruit size and bill gape, are the most successful combinations. These results link ecologically important species attributes to large‐scale community structure.     

Effects of climate‐driven primary production change on marine food webs: implications for fisheries and conservation

Climate change is altering the rate and distribution of primary production in the world's oceans. Primary production is critical to maintaining biodiversity and supporting fishery catches, but predicting the response of populations to primary production change is complicated by predation and competition interactions. We simulated the effects of change in primary production on diverse marine ecosystems across a wide latitudinal range in Australia using the marine food web model Ecosim. We link models of primary production of lower trophic levels (phytoplankton and benthic producers) under climate change with Ecosim to predict changes in fishery catch, fishery value, biomass of animals of conservation interest, and indicators of community composition. Under a plausible climate change scenario, primary production will increase around Australia and generally this benefits fisheries catch and value and leads to increased biomass of threatened marine animals such as turtles and sharks. However, community composition is not strongly affected. Sensitivity analyses indicate overall positive linear responses of functional groups to primary production change. Responses are robust to the ecosystem type and the complexity of the model used. However, model formulations with more complex predation and competition interactions can reverse the expected responses for some species, resulting in catch declines for some fished species and localized declines of turtle and marine mammal populations under primary productivity increases. We conclude that climate‐driven primary production change needs to be considered by marine ecosystem managers and more specifically, that production increases can simultaneously benefit fisheries and conservation. Greater focus on incorporating predation and competition interactions into models will significantly improve the ability to identify species and industries most at risk from climate change.     

Analysing ecological networks of species interactions

Network approaches to ecological questions have been increasingly used, particularly in recent decades. The abstraction of ecological systems – such as communities – through networks of interactions between their components indeed provides a way to summarize this information with single objects. The methodological framework derived from graph theory also provides numerous approaches and measures to analyze these objects and can offer new perspectives on established ecological theories as well as tools to address new challenges. However, prior to using these methods to test ecological hypotheses, it is necessary that we understand, adapt, and use them in ways that both allow us to deliver their full potential and account for their limitations. Here, we attempt to increase the accessibility of network approaches by providing a review of the tools that have been developed so far, with – what we believe to be – their appropriate uses and potential limitations. This is not an exhaustive review of all methods and metrics, but rather, an overview of tools that are robust, informative, and ecologically sound. After providing a brief presentation of species interaction networks and how to build them in order to summarize ecological information of different types, we then classify methods and metrics by the types of ecological questions that they can be used to answer from global to local scales, including methods for hypothesis testing and future perspectives. Specifically, we show how the organization of species interactions in a community yields different network structures (e.g., more or less dense, modular or nested), how different measures can be used to describe and quantify these emerging structures, and how to compare communities based on these differences in structures. Within networks, we illustrate metrics that can be used to describe and compare the functional and dynamic roles of species based on their position in the network and the organization of their interactions as well as associated new methods to test the significance of these results. Lastly, we describe potential fruitful avenues for new methodological developments to address novel ecological questions.     

EcologicalNetworks.jl: analysing ecological networks of species interactions

Networks are a convenient way to represent many interactions among ecological entities. The analysis of ecological networks is challenging for two reasons. First, there is a plethora of measures that can be applied (and some of them measure the same property). Second, the implementation of these measures is sometimes difficult. We present ’EcologicalNetworks.jl’, a package for the ‘Julia’ programming language. Using a layered system of types to represent several types of ecological networks, this packages offers a solid library of basic functions which can be chained together to perform the most common analyses of ecological networks.     

Alien plants have greater impact than habitat fragmentation on native insect flower visitation networks

Aim

Habitat fragmentation and alien species are among the leading causes of biodiversity loss. In an attempt to reduce the impact of forestry on natural systems, networks of natural corridors and patches of natural habitat are often maintained within the afforested matrix, yet these can be subject to degradation by invasion of non‐native species. Both habitat fragmentation and alien invasive species disrupt the complex interaction networks typical of native communities. This study examines whether an invasive plant and/or the fragmented nature of the forestry landscape influences natural flower visitation networks (FVNs), flower–visitor abundance and richness or flower/visitor species composition.

Location

The species rich and diverse grasslands in the KwaZulu‐Natal Midlands, South Africa is under threat from transformation, particularly by commercial forestry plantations, restricting much of the remaining untransformed grasslands into remnant grassland patches (RGPs). Remaining patches are under additional threat from the invasive Rubus cuneifolius Pursh (bramble). Sites were established in RGPs and in a nearby protected area (PA), with and without brambles present for both areas.

Results

Flower abundance and flower area of native plant species were greater within RGP than in PA, but only in the absence of R. cuneifolius. Flower–visitor assemblages differed between invaded and uninvaded sites and also differed between PA and RGP sites. Both areas lost specialist flower–visitor species in the presence of brambles. Network modularity was greatly reduced by the presence of bramble, indicating a reduction in complexity and organization. The structure of FVNs was otherwise unaffected by presence of bramble or being located in RGPs or the PA.

Main conclusions

The RPGs contribute to regional biodiversity conservation through additional compositional diversity and intact FVNs. Rubus cuneifolius reduces ecological complexity of both RGPs and PAs, however, and its removal must be prioritized to conserve FVNs.     

基于物种分布的北京平原生态网络构建

高强度的城市化活动导致了生物栖息地破碎化、退化和消失,是生物多样性减少的主要原因。建立城市地区生态网络是保护生物多样性的重要途径。因其他物种数据可获得性差,以观测的典型鸟类群落为指示物种,探讨构建生态网络,可为城市生物多样性保护提供新思路。以北京市平原区为研究范围,重点基于86种鸟类分布大数据,通过Maxent模型掩膜生成栖息地源地并进行分级,在GIS技术的支撑下,以土地利用数据建立鸟类活动阻力面,采用最小累积阻力模型算法,模拟并形成了平原地区分级的生物多样性保护网络。研究结果表明,河湖湿地和城市公园组成了北京平原地区生态网络的优势景观类型,占平原区生态空间的81%。基于景观类型大小与物种数量的线性关系筛选出分级生物栖息地,其中一级生物栖息地58个,二级生物栖息地146个,通过模型模拟形成了平原地区生物多样性保护的一二级生态网络,共948条网络,长3760km。筛选出重要生态节点12处,关键生态廊道6条,是保护平原地区生物多样性的重要生态设施。该生态网络的实施对于提升首都平原区的生物多样性具有重要价值,研究结果可为国土生态空间优化提供重要科学依据和参考。     

Forbidden versus permitted interactions: Disentangling processes from patterns in ecological network analysis

Several studies have identified the tendency for species to share interacting partners as a key property to the functioning and stability of ecological networks. However, assessing this pattern has proved challenging in several regards, such as finding proper metrics to assess node overlap (sharing), and using robust null modeling to disentangle significance from randomness. Here, we bring attention to an additional, largely neglected challenge in assessing species’ tendency to share interacting partners. In particular, we discuss and illustrate with two different case studies how identifying the set of “permitted” interactions for a given species (i.e. interactions that are not impeded, e.g. by lack of functional trait compatibility) is paramount to understand the ecological and co‐evolutionary processes at the basis of node overlap and segregation patterns.     

The effect of space in plant–animal mutualistic networks: insights from a simulation study

The topology of plant–animal mutualistic networks has the potential to determine the ecological and evolutionary dynamics of interacting species. Many mechanisms have been proposed as explanations of observed network patterns; however, the fact that plant–animal interactions are inherently spatial has so far been ignored. Using a simulation model of frugivorous birds foraging in spatially explicit landscapes we evaluated how plant distribution and the scale of bird movement decisions influenced species interaction probabilities and the resulting network properties. Spatial aggregation and limited animal mobility restricted encounter probabilities, so that the distribution of animal visits per plant deviated strongly from the binomial distribution expected for a well-mixed system. Lack of mixing in turn resulted in a strong decrease in network connectance, a weak decrease in nestedness, stronger interactions, greater strength asymmetry and the unexpected presence/absence of some interactions. Our results suggest that spatial processes may contribute substantially to structure plant–animal mutualistic networks.     

For flux's sake: General considerations for energy‐flux calculations in ecological communities

Global change alters ecological communities with consequences for ecosystem processes. Such processes and functions are a central aspect of ecological research and vital to understanding and mitigating the consequences of global change, but also those of other drivers of change in organism communities. In this context, the concept of energy flux through trophic networks integrates food‐web theory and biodiversity‐ecosystem functioning theory and connects biodiversity to multitrophic ecosystem functioning. As such, the energy‐flux approach is a strikingly effective tool to answer central questions in ecology and global‐change research. This might seem straight forward, given that the theoretical background and software to efficiently calculate energy flux are readily available. However, the implementation of such calculations is not always straight forward, especially for those who are new to the topic and not familiar with concepts central to this line of research, such as food‐web theory or metabolic theory. To facilitate wider use of energy flux in ecological research, we thus provide a guide to adopting energy‐flux calculations for people new to the method, struggling with its implementation, or simply looking for background reading, important resources, and standard solutions to the problems everyone faces when starting to quantify energy fluxes for their community data. First, we introduce energy flux and its use in community and ecosystem ecology. Then, we provide a comprehensive explanation of the single steps towards calculating energy flux for community data. Finally, we discuss remaining challenges and exciting research frontiers for future energy‐flux research.     

Non‐linear relationship between intensity of plant–animal interactions and selection strength

The shape of the relationship between intensity of biotic interactions and strength of selection is important for spatial variation in selection, but is little explored. We quantified interactions and selection in 69 populations of the short‐lived herb Primula farinosa. As predicted because of saturation and depletion effects, the strength of selection on a discrete and on a continuously varying floral display trait were in several cases significantly non‐linearly related to the mean intensity of mutualistic and antagonistic interactions. Strength of selection was strongest at low levels of fruit initiation and at high intensities of seed predation. Seed predation varied more among populations than did fruit initiation and could explain a larger proportion of the among‐population variation in strength of selection. Our results support the contention that interaction intensity affects selection strength, and suggests that for mutualistic and antagonistic interactions that can be saturated or depleted, this relationship is sometimes non‐linear.