Comparing species interaction networks along environmental gradients

Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co‐variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant–hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis‐based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.     

结构稳定性: 概念、方法和应用

群落内物种间相互作用的结构是高度组织化的。群落结构对多物种共存的影响机制是群落生态学的核心科学问题之一。目前生态学界在这一问题上存在多种不同的观点。一个可能的原因是, 由于环境因子的复杂性, 大部分研究忽略了环境因子对群落结构和物种共存的重要影响。在这一背景下, 近期发展起来的结构稳定性理论系统地联系了群落结构、环境因子和物种共存, 并在此基础上建立了一个和经验数据紧密结合的理论框架。本文首先简要回顾了当前关于群落结构研究的争鸣, 然后介绍了结构稳定性的理论框架和计算方法, 最后详细介绍了结构稳定性理论在不同生态群落和不同生态学问题中的应用。在全球气候变化的背景下, 结构稳定性理论提供了一种新的视角来理解群落层面的生物多样性维持机制。     

The ecological and evolutionary implications of merging different types of networks

Interactions among species drive the ecological and evolutionary processes in ecological communities. These interactions are effectively key components of biodiversity. Studies that use a network approach to study the structure and dynamics of communities of interacting species have revealed many patterns and associated processes. Historically these studies were restricted to trophic interactions, although network approaches are now used to study a wide range of interactions, including for example the reproductive mutualisms. However, each interaction type remains studied largely in isolation from others. Merging the various interaction types within a single integrative framework is necessary if we want to further our understanding of the ecological and evolutionary dynamics of communities. Dividing the networks up is a methodological convenience as in the field the networks occur together in space and time and will be linked by shared species. Herein, we outline a conceptual framework for studying networks composed of more than one type of interaction, highlighting key questions and research areas that would benefit from their study.     

Modelling dendritic ecological networks in space: an integrated network perspective

Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2‐D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2‐D space can be used to explore the influence of multi‐scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).     

Network spandrels reflect ecological assembly

Ecological networks that exhibit stable dynamics should theoretically persist longer than those that fluctuate wildly. Thus, network structures which are over‐represented in natural systems are often hypothesised to be either a cause or consequence of ecological stability. Rarely considered, however, is that these network structures can also be by‐products of the processes that determine how new species attempt to join the community. Using a simulation approach in tandem with key results from random matrix theory, we illustrate how historical assembly mechanisms alter the structure of ecological networks. We demonstrate that different community assembly scenarios can lead to the emergence of structures that are often interpreted as evidence of ‘selection for stability’. However, by controlling for the underlying selection pressures, we show that these assembly artefacts—or spandrels—are completely unrelated to stability or selection, and are instead by‐products of how new species are introduced into the system. We propose that these network‐assembly spandrels are critically overlooked aspects of network theory and stability analysis, and we illustrate how a failure to adequately account for historical assembly can lead to incorrect inference about the causes and consequences of ecological stability.     

Species traits and abundances predict metrics of plant–pollinator network structure,but not pairwise interactions

Plant–pollinator mutualistic networks represent the ecological context of foraging (for pollinators) and reproduction (for plants and some pollinators). Plant–pollinator visitation networks exhibit highly conserved structural properties across diverse habitats and species assemblages. The most successful hypotheses to explain these network properties are the neutrality and biological constraints hypotheses, which posit that species interaction frequencies can be explained by species relative abundances, and trait mismatches between potential mutualists respectively. However, previous network analyses emphasize the prediction of metrics of qualitative network structure, which may not represent stringent tests of these hypotheses. Using a newly documented temporally explicit alpine plant–pollinator visitation network, we show that metrics of both qualitative and quantitative network structure are easy to predict, even by models that predict the identity or frequency of species interactions poorly. A variety of phenological and morphological constraints as well as neutral interactions successfully predicted all network metrics tested, without accurately predicting species observed interactions. Species phenology alone was the best predictor of observed interaction frequencies. However, all models were poor predictors of species pairwise interaction frequencies, suggesting that other aspects of species biology not generally considered in network studies, such as reproduction for dipterans, play an important role in shaping plant–pollinator visitation network structure at this site. Future progress in explaining the structure and dynamics of mutualistic networks will require new approaches that emphasize accurate prediction of species pairwise interactions rather than network metrics, and better reflect the biology underlying species interactions.     

Ecological network analysis of urban–industrial ecosystems

Sustainability of urban areas is paramount in the coming years as cities continue to grow in population and resource consumption. A number of methods to model cities have been developed, including material flow analysis and urban metabolism, but these accounting methods do not fully analyze the complex network dynamics present within cities. Ecological network analysis (ENA) provides a new perspective into these urban areas by using metrics designed for analysis of natural ecosystems. This study analyzes 29 urban–industrial ecosystems using ENA, comparing the networks to each other as well as comparing them to previously analyzed eco‐industrial parks and natural food webs. It is found that these systems perform similar to other human‐designed systems, which consistently lack in ecological performance when compared with the natural ecosystems. Additionally, the impact of specific actor types within these networks is shown indicating the importance of industry, agriculture, and the natural environment. Finally, the types of networks are determined to affect the ecological metrics, with the more linear‐based energy networks having the worst performance. This new dataset of ecologically analyzed networks provides a deeper understanding of urban networks and their infrastructure, while providing useful information on how to potentially improve their sustainability.     

Unifying facilitation and recruitment networks

Ecological network studies are providing important advances about the organization, stability and dynamics of ecological systems. However, the ecological networks approach is being integrated very slowly in plant community ecology, even though the first studies on plant facilitation networks (FNs) were published more than a decade ago. The study of interaction networks between established plants and plants recruiting beneath them, which we call Recruitment Networks (RNs), can provide new insights on mechanisms driving plant community structure and dynamics. RNs basically describe which plants recruit under which others, so they can be seen as a generalisation of the classic FNs since they do not imply any particular effect (positive, negative or neutral) of the established plants on recruiting ones. RNs summarise information on the structure of sapling banks. More importantly, the information included in RNs can be incorporated into models of replacement dynamics to evaluate how different aspects of network structure, or different mechanisms of network assembly, may affect plant community stability and species coexistence. To allow an efficient development of the study of FNs and RNs, here we unify concepts, synthesise current knowledge, clarify some conceptual issues, and propose basic methodological guidelines to standardise sampling methods that could make future studies of these networks directly comparable.     

Removing interactions,rather than species,casts doubt on the high robustness of pollination networks

In the last 15 years, a complex networks perspective has been increasingly used in the robustness assessment of ecological systems. It is therefore crucial to assess the reliability of such tools. Based on the traditional simulation of node (species) removal, mutualistic pollination networks are considered to be relatively robust because of their 1) truncated power‐law degree distribution, 2) redundancy in the number of pollinators per plant and 3) nested interaction pattern. However, species removal is only one of several possible approaches to network robustness assessment. Empirical evidence suggests a decline in abundance prior to the extinction of interacting species, arguing in favour of an interaction removal‐based approach (i.e. interaction disruption), as opposed to traditional species removal. For simulated networks, these two approaches yield radically different conclusions, but no tests are currently available for empirical mutualistic networks. This study compared this new robustness evaluation approach based on interaction extinction versus the traditional species removal approach for 12 alpine and subalpine pollination networks. In comparison with species removal, interaction removal produced higher robustness in the worst‐case extinction scenario but lower robustness in the best‐case extinction scenario. Our results indicate that: 1) these two approaches yield very different conclusions and 2) existing assessments of ecological network robustness could be overly optimistic, at least those based on a disturbance affecting species at random or beginning with the least connected species. Therefore, further empirical study of plant–pollinator interactions in disturbed ecosystems is imperative to understand how pollination networks are disassembled.     

Observing frugivores or collecting scats: a method comparison to construct quantitative seed dispersal networks

Mutualistic interactions form the basis for many ecological processes and are often analyzed within the framework of ecological networks. These interactions can be sampled with a range of methods and first analyses of pollination networks sampled with different methods showed differences in common network metrics. However, it is yet unknown if metrics of seed dispersal networks are similarly affected by the sampling method and if different methods detect a complementary set of frugivores. This is necessary to better understand the (dis-)advantages of each method and to identify the role of each frugivore for the seed dispersal process. Here, we compare seed removal networks based on the observation of 2189 frugivore visits on ten focal plant species with seed deposition networks constructed by DNA barcoding of plant seeds in 3094 frugivore scats. We were interested in whether both methods identify the same disperser species and if species-level network metrics of plant species were correlated between network types. Both methods identified the same avian super-generalist frugivores, which accounted for the highest number of dispersed seeds. However, only with DNA barcoding, we detected elusive but frequent mammalian seed dispersers. The overall networks created by both methods were congruent but the plant species' degree, their interaction frequency and their specialization index (d′) differed. Our study suggests that DNA barcoding of defecated and regurgitated seeds can be used to construct quantitative seed deposition networks similar to those constructed by focal observations. To improve the overall completeness of seed dispersal networks it might be useful to combine both methods to detect interactions by both birds and mammals. Most importantly, the DNA barcoding method provides information on the post-dispersal stage and thus on the qualitative contribution of each frugivore for the plant community thereby linking species interactions to regeneration dynamics of fleshy-fruited plant species.     

The assembly and disassembly of ecological networks

Global change has created a severe biodiversity crisis. Species are driven extinct at an increasing rate, and this has the potential to cause further coextinction cascades. The rate and shape of these coextinction cascades depend very much on the structure of the networks of interactions across species. Understanding network structure and how it relates to network disassembly, therefore, is a priority for system-level conservation biology. This process of network collapse may indeed be related to the process of network build-up, although very little is known about both processes and even less about their relationship. Here we review recent work that provides some preliminary answers to these questions. First, we focus on network assembly by emphasizing temporal processes at the species level, as well as the structural building blocks of complex ecological networks. Second, we focus on network disassembly as a consequence of species extinctions or habitat loss. We conclude by emphasizing some general rules of thumb that can help in building a comprehensive framework to understand the responses of ecological networks to global change.     

A conceptual guide to measuring species diversity

Three metrics of species diversity – species richness, the Shannon index and the Simpson index – are still widely used in ecology, despite decades of valid critiques leveled against them. Developing a robust diversity metric has been challenging because, unlike many variables ecologists measure, the diversity of a community often cannot be estimated in an unbiased way based on a random sample from that community. Over the past decade, ecologists have begun to incorporate two important tools for estimating diversity: coverage and Hill diversity. Coverage is a method for equalizing samples that is, on theoretical grounds, preferable to other commonly used methods such as equal-effort sampling, or rarefying datasets to equal sample size. Hill diversity comprises a spectrum of diversity metrics and is based on three key insights. First, species richness and variants of the Shannon and Simpson indices are all special cases of one general equation. Second, richness, Shannon and Simpson can be expressed on the same scale and in units of species. Third, there is no way to eliminate the effect of relative abundance from estimates of any of these diversity metrics, including species richness. Rather, a researcher must choose the relative sensitivity of the metric towards rare and common species, a concept which we describe as ‘leverage.' In this paper we explain coverage and Hill diversity, provide guidelines for how to use them together to measure species diversity, and demonstrate their use with examples from our own data. We show why researchers will obtain more robust results when they estimate the Hill diversity of equal-coverage samples, rather than using other methods such as equal-effort sampling or traditional sample rarefaction.     

Estimating co-extinction threats in terrestrial ecosystems

The biosphere is changing rapidly due to human endeavour. Because ecological communities underlie networks of interacting species, changes that directly affect some species can have indirect effects on others. Accurate tools to predict these direct and indirect effects are therefore required to guide conservation strategies. However, most extinction-risk studies only consider the direct effects of global change—such as predicting which species will breach their thermal limits under different warming scenarios—with predictions of trophic cascades and co-extinction risks remaining mostly speculative. To predict the potential indirect effects of primary extinctions, data describing community interactions and network modelling can estimate how extinctions cascade through communities. While theoretical studies have demonstrated the usefulness of models in predicting how communities react to threats like climate change, few have applied such methods to real-world communities. This gap partly reflects challenges in constructing trophic network models of real-world food webs, highlighting the need to develop approaches for quantifying co-extinction risk more accurately. We propose a framework for constructing ecological network models representing real-world food webs in terrestrial ecosystems and subjecting these models to co-extinction scenarios triggered by probable future environmental perturbations. Adopting our framework will improve estimates of how environmental perturbations affect whole ecological communities. Identifying species at risk of co-extinction (or those that might trigger co-extinctions) will also guide conservation interventions aiming to reduce the probability of co-extinction cascades and additional species losses.     

Measurement of the Girth of Coniferous Trees at Braemar in 1894

ABSTRACT

Background: Plant communities are usually characterised by species composition and abundance, but also underlie a multitude of complex interactions that we have only recently started unveiling. Yet, we are still far from understanding ecological and evolutionary processes shaping the network-level organisation of plant diversity, and to what extent these processes are specific to certain spatial scales or environments.

Aims: Understanding the systemic mechanisms of plant–plant network assembly and their consequences for diversity patterns.

Methods: We review recent methods and results of plant–plant networks.

Results: We synthetize how plant–plant networks can help us to: (a) assess how competition and facilitation may balance each other through the network; (b) analyse the role of plant–plant interactions beyond pairwise competition in structuring plant communities, and (c) forecast the ecological implications of complex species dependencies. We discuss pros and cons, assumptions and limitations of different approaches used for inferring plant–plant networks.

Conclusions: We propose novel opportunities for advancing plant ecology by using ecological networks that encompass different ecological levels and spatio-temporal scales, and incorporate more biological information. Embracing networks of interactions among plants can shed new light on mechanisms driving evolution and ecosystem functioning, helping us to mitigate diversity loss.     

A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape

Graph structures and habitat availability metrics are two recent and complementary approaches for analysing landscape connectivity. They have gained rapid popularity and provided significant conceptual improvements for decision making in conservation planning. We present a further methodological development of the habitat availability concept and metrics by partitioning them into three separate fractions that quantify the different ways in which individual landscape elements can contribute to overall habitat connectivity and availability in the landscape, including stepping stone effects. These fractions are derived from the same concept, are measured in the same units and can be directly compared and combined within a unifying framework. This avoids the problematic and, so far, usual combination of metrics coming from different backgrounds and the arbitrary weighting of connectivity considerations in a broader context of conservation alternatives. We analyse how the relative importance of each fraction varies with species traits. In addition, we show how the critical patches differ for each of the fractions by analysing various forest habitats in the province of Lleida (NE Spain). We discuss the conceptual and conservation implications of this approach, which can be adapted to different degrees of ecological and spatial detail within the graph while still maintaining a coherent framework for the identification of critical elements in the landscape network.     

Can plant-pollinator network metrics indicate environmental quality?

Plant-pollinator interaction networks may be more informative than the diversity of species in the evaluation of the effects of environmental change. Considering that networks vary with the integrity of ecosystems, their changes may help to predict the consequences of anthropogenic impacts on biodiversity and ecological processes. This characteristic highlights its use as environmental quality indicator. However, to employ interaction networks as ecological indicators it is necessary to identify the most sensitive metrics and understand how and why they vary with environmental changes. This review aimed to identify, in empirical studies, which network metrics have been evidenced as being more sensitive to changes in environmental quality. We analyzed published empirical studies, that applied the network approach on environmental quality gradients. In addition to the network metric behavior, we studied the interactions between them and possible causes of their variation. The available empirical data indicated that degree, nestedness and connectance did not have a simple, linear or unidirectional response to habitat degradation. Conversely, the metrics interaction asymmetry, d' (reciprocal specialization index of the species) showed the most consistent responses to environmental change. The role of the species changed, ranging between generalists and specialists under different conditions. In addition, specialist species with morphological and behavioral constraints were lost in worse environmental quality situations. The identity of interacting species and their role in the network, with a further specification of groups and interactions most affected, are the properties with greater potential to indicate changes in environmental quality. Most of the available studies focused on metrics at the network level, but several studies and this review indicate that the patterns at the network level can be better understood in the light of metrics analyzed at the species level. Our results provide information that enrich the network analysis, highlighting the need to consider important features that are often neglected. Discussions and information compiled here are important for deciding how to look at empirical data and what to look for, as well as to indicate some caveats when interpreting data on plant-pollinator interactions with a complex network approach. Network metrics can be good indicators of environmental quality if the underlying ecological causes of the numerical changes are carefully analyzed.     

Forecasting species range dynamics with process‐explicit models: matching methods to applications

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process–explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process–explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs – regulatory planning, extinction risk, climate refugia and invasive species – we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process‐explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised.     

Seasonal consistency of the assembling rules in a bird-fruiting plant network

There is an ongoing debate on whether species' traits or neutrality generate recurrent patterns of mutualistic networks. Although there have been recent advances on the issue, many studies neglect the seasonal dynamics of these drivers. In this study, we investigated how pervasive are the drivers (i.e. species’ size, phenological overlap and species relative abundance) of the frequency of pairwise interactions and the aggregate metrics of seasonal seed dispersal networks in a semideciduous forest from the savannahs of Southeastern Brazil. We used a likelihood approach and built probability matrices based on different drivers to compare how they fit in the frequency and structure of the seasonal observed networks. We found that in both seasons trait-based processes, especially phenological overlap between species, best predicted the frequency of pairwise interactions. However, species relative abundances performed better than species traits in explaining most of aggregate network metrics in both seasons, except for the interaction evenness. These findings suggest that ecological and evolutionary processes are seasonally pervasive and determine the ability of species to interact with their partners. Besides, the general structure of the seasonal networks is less sensitive to species traits and its drivers remain seasonally constant. We conclude that our ability to understand the complexity of plant-frugivore interactions depends on assessing the contribution of species traits and their relative abundances to the structure of seasonal-detailed networks.