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.     

Discovering biogeographic and ecological clusters with a graph theoretic spin on factor analysis

Factor analysis (FA) has the advantage of highlighting each semi‐distinct cluster of samples in a data set with one axis at a time, as opposed to simply arranging samples across axes to represent gradients. However, in the case of presence–absence data it is confounded by absences when gradients are long. No statistical model can cope with this problem because the raw data simply do not present underlying information about the length of such gradients. Here I propose an easy way to tease out this information. It is a simple emendation of FA called stepping down, which involves giving an absence a negative value when the missing species nowhere co‐occurs with the species found in the relevant sample. Specifically, a binary co‐occurrence graph is created, and the magnitude of negative values is made a function of how far the graph must be traversed in order to link the missing species with each species that is present. Simulations show that standard FA yields inferior results to FA based on stepped‐down matrices in terms of mapping clusters into axes one‐by‐one. Standard FA is also uninformative when applied to a global bat inventory data set. Step‐down FA (SDFA) easily flags the main biogeographic groupings. Methods like correspondence analysis, non‐metric multidimensional scaling, and Bayesian latent variable modelling are not commensurate with SDFA because they do not seek to find a one‐to‐one mapping of axes and clusters. Stepping down seems promising as a means of illustrating clusters of samples, especially when there are subtle or complex discontinuities in gradients.     

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.     

基于生态安全格局的南京都市区生态控制边界划定

以南京都市区为例,通过生态敏感性分析获取了研究区既有的高生态敏感空间,采用最小费用路径方法辨识了对研究区具有重要生态意义的潜在生态廊道和生态关键区,采用图谱理论中的景观连接度指数辅助确定生态廊道宽度,构建了研究区潜在的生态网络。在此基础上,整合既有和潜在生态空间,科学划定生态控制边界,实现了研究区现存和潜在的重要自然生态空间保护。研究结果表明:1)生态敏感性分析能够识别出研究区既有的高生态敏感性区域,并指出其呈现出"大而孤立,小且分散,连接性不佳"的空间特征。2)遴选出的71处生态源地、119条重要廊道和61个关键生态斑块共同组成了研究区的生态网络,显著提升了原有生态空间的景观连接性和研究区域的总体生态安全水平。3)生态网络分析可以弥补敏感性分析只考虑既有自然生态空间的局限,二者的组合使用可为不同尺度上生态控制边界的划定提供简明的分析框架。研究结果可为南京都市区生态控制线划定和生态环境保护提供重要的参考,对其他城市生态控制边界的划定也具有一定的借鉴意义。     

Ecotone formation through ecological niche construction: the role of biodiversity and species interactions

Rapid changes in species composition, also known as ecotones, can result from various causes including rapid changes in environmental conditions, or physiological thresholds. The possibility that ecotones arise from ecological niche construction by ecosystem engineers has received little attention. In this study, we investigate how the diversity of ecosystem engineers, and their interactions, can give rise to ecotones. We build a spatially explicit dynamical model that couples a multispecies community and its abiotic environment. We use numerical simulations and analytical techniques to determine the biotic and abiotic conditions under which ecotone emergence is expected to occur, and the role of biodiversity therein. We show that the diversity of ecosystem engineers can lead to indirect interactions through the modification of their shared environment. These interactions, which can be either competitive or mutualistic, can lead to the emergence of discrete communities in space, separated by sharp ecotones where a high species turnover is observed. Considering biodiversity is thus critical when studying the influence of species–environment interactions on the emergence of ecotones. This is especially true for the wide range of species that have small to moderate effects on their environment. Our work highlights new mechanisms by which biodiversity loss could cause significant changes in spatial community patterns in changing environments.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

城市生态网络功能性连接辨识方法

城市生态网络是景观生态学应用领域研究的热点和重点之一,识别、评估生境之间的连接是构建生态网络的关键环节。在总结已有连接辨识方法的基础上,提出采用最小费用模型和图论分析相结合的方法,探讨功能性连接的辨识和优先恢复途径。以新西兰基督城为案例,分别利用景观发展强度指数建立阻力面,新西兰鸡毛松(Dacrycarpus dacrydioides)种子最大传播距离作为连接阈值来模拟、评价网络连接。结果表明:在1200 m距离阈值下,共有408条连接,其重要性分为10类。其中Richmond—Petrie公园,Hansons—Auburn保护地,Centaurus公园—King George保护地是整个生态网络的关键连接;若去除,景观整体连接度将下降31.73%。此外,研究发现连接重要值与两端的源面积之和没有显著相关性,即面积大的源斑块之间的连接不一定对网络构建起关键作用,这一结论还有待进一步证明。针对缺少动物迁移资料的城市环境,改进最小费用模型和网络连接分析的部分参数;可操作性与实用性强,对中国城市区域生态恢复建设、栖息地选择具有借鉴意义。     

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。     

Using ecological networks to answer questions in global biogeography and ecology

Ecological networks have classically been studied at site and landscape scales, yet recent efforts have been made to collate these data into global repositories. This offers an opportunity to integrate and upscale knowledge about ecological interactions from local to global scales to gain enhanced insights from the mechanistic information provided by these data. By drawing on existing research investigating patterns in ecological interactions at continental to global scales, we show how data on ecological networks, collected at appropriate scales, can be used to generate an improved understanding of many aspects of ecology and biogeography—for example, species distribution modelling, restoration ecology and conservation. We argue that by understanding the patterns in the structure and function of ecological networks across scales, it is possible to enhance our understanding of the natural world.     

The niche, biogeography and species interactions

In this paper, I review the relevance of the niche to biogeography, and what biogeography may tell us about the niche. The niche is defined as the combination of abiotic and biotic conditions where a species can persist. I argue that most biogeographic patterns are created by niche differences over space, and that even ‘geographic barriers’ must have an ecological basis. However, we know little about specific ecological factors underlying most biogeographic patterns. Some evidence supports the importance of abiotic factors, whereas few examples exist of large-scale patterns created by biotic interactions. I also show how incorporating biogeography may offer new perspectives on resource-related niches and species interactions. Several examples demonstrate that even after a major evolutionary radiation within a region, the region can still be invaded by ecologically similar species from another clade, countering the long-standing idea that communities and regions are generally ‘saturated’ with species. I also describe the somewhat paradoxical situation where competition seems to limit trait evolution in a group, but does not prevent co-occurrence of species with similar values for that trait (called here the ‘competition–divergence–co-occurrence conundrum’). In general, the interface of biogeography and ecology could be a major area for research in both fields.     

Insights into the historical construction of species-rich biomes from dated plant phylogenies, neutral ecological theory and phylogenetic community structure

Analytical methods are now available that can date all nodes in a molecular phylogenetic tree with one calibration, and which correct for variable rates of DNA substitution in different lineages. Although these techniques are approximate, they offer a new tool to investigate the historical construction of species-rich biomes. Dated phylogenies of globally distributed plant families often indicate that dispersal, even across oceans, rather than plate tectonics, has generated their wide distributions. By contrast, there are indications that animal lineages have undergone less long distance dispersal. Dating the origin of biome-specific plant groups offers a means of estimating the age of the biomes they characterize. However, rather than a simple emphasis on biome age, we stress the importance of studies that seek to unravel the processes that have led to the accumulation of large numbers of species in some biomes. The synthesis of biological inventory, systematics and evolutionary biology offered by the frameworks of neutral ecological theory and phylogenetic community structure offers a promising route for future work.     

Good predictors for the fixation probability on complex networks of multi-player games using territorial interactions

In 2012 Broom and Rychtar developed a new framework to consider the evolution of a population over a non-homogeneous underlying structure, where fitness depends upon multiplayer interactions amongst the individuals within the population played in groups of various sizes (including one). This included the independent model, and as a special case the territorial raider model, which has been considered in a series of subsequent papers. Here individuals are based upon the vertex of a graph but move to interact with their neighbours, sometimes meeting in large groups. The most important single property of such populations is the fixation probability, the probability of a single mutant completely replacing the existing population. In a recent paper we considered the fixation probability for the Birth Death Birth (BDB) dynamics for three games, a Public Goods game, the Hawk–Dove game and for fixed fitnesses for a large number of randomly generated graphs, in particular seeing if important underlying graph properties could be used as predictors. We found two good predictors, temperature and mean group size, but some interesting and unusual features for one type of graph, Barabasi–Albert graphs. In this paper we use a regression analysis to investigate (the usual) three alternative evolutionary dynamics (BDD, DBB, DBD) in addition to the original BDB. In particular, we find that the dynamics split into two pairs, BDB/DBD and BDD/DBB, each of which give essentially the same results and found a good fit to the data using a quadratic regression involving the above two variables. Further we find that temperature is the most important predictor for the Hawk–Dove game, whilst for the Public Goods game the group size also plays a key role, and is more important than the temperature for the BDD/DBB dynamics.     

On the semiotic dimension of ecological theory: The case of island biogeography

The Macarthur-Wilson equilibrium theory of island biogeography has had a contradictory role in ecology. As a lasting contribution, the theory has created a new way of viewing insular environments as dynamical systems. On the other hand, many of the applications of the theory have reduced to mere unimaginative curve-fitting. I analyze this paradox in semiotic terms: the theory was mainly equated with the simple species-area relationship which became a signifier of interesting island ecology. The theory is, however, better viewed as a theoretical framework that suggests specific hypotheses on the ecology of colonization of insular environments. This paradox is inherent in the use of simplifying analytic models. Analytic models are necessary and fruitful in the work of ecologists, but they ought to be supplemented with a broader, pluralistic appreciation of the role of theories in general.     

Interdomain ecological networks between plants and microbes

While macroscopic interkingdom relationships have been intensively investigated in various ecosystems, the above–belowground ecology in natural ecosystems has been poorly understood, especially for the plant–microbe associations at a regional scale. In this study, we proposed a workflow to construct interdomain ecological networks (IDEN) between multiple plants and various microbes (bacteria and archaea in this study). Across 30 latitudinal forests in China, the regional IDEN showed particular topological features, including high connectance, nested structure, asymmetric specialization and modularity. Also, plant species exhibited strong preference to specific microbial groups, and the observed network was significantly different from randomly rewired networks. Network module analysis indicated that a majority of microbes associated with plants within modules rather than across modules, suggesting specialized associations between plants and microorganisms. Consistent plant–microbe associations were captured via IDENs constructed within individual forest locations, which reinforced the validity of IDEN analysis. In addition, the plant–forest link distribution showed the geographical distribution of plants had higher endemicity than that of microorganisms. With cautious experimental design and data processing, this study shows interdomain species associations between plants and microbes in natural forest ecosystems and provides new insights into our understanding of meta‐communities across different domain species.     

Coevolutionary dynamics shape the structure of bacteria‐phage infection networks

Coevolution—reciprocal evolutionary change among interacting species driven by natural selection—is thought to be an important force in shaping biodiversity. This ongoing process takes place within tangled networks of species interactions. In microbial communities, evolutionary change between hosts and parasites occurs at the same time scale as ecological change. Yet, we still lack experimental evidence of the role of coevolution in driving changes in the structure of such species interaction networks. Filling this gap is important because network structure influences community persistence through indirect effects. Here, we quantified experimentally to what extent coevolutionary dynamics lead to contrasting patterns in the architecture of bacteria–phage infection networks. Specifically, we look at the tendency of these networks to be organized in a nested pattern by which the more specialist phages tend to infect only a proper subset of those bacteria infected by the most generalist phages. We found that interactions between coevolving bacteria and phages become less nested over time under fluctuating dynamics, and more nested under arms race dynamics. Moreover, when coevolution results in high average infectivity, phages and bacteria differ more from each other over time under arms race dynamics than under fluctuating dynamics. The tradeoff between the fitness benefits of evolving resistance/infectivity traits and the costs of maintaining them might explain these differences in network structure. Our study shows that the interaction pattern between bacteria and phages at the community level depends on the way coevolution unfolds.     

生态群落物种共存的进化机制

本文概述了目前对生态群落的物种共存研究中存在的若干问题及动、植物群落物种共存机制的研究进展。植物群落的物种共存主要介绍与环境、种子再迁移、生态位分化、竞争平衡理论、种库假设、再生生态位等有关的几种假设、生态学上相似种的共存及“原”群落概念等。动物群落的物种共存机制主要从以下几方面叙述：（1）异质环境中的资源分割,主要指动物斑状滋养的不同利用;（2）避免竞争排斥的行为机制,如边缘效应、聚群效应、扩散行为、相互作用和干扰;（3）特化者和泛化者的共存,包括：竞争是物种向多功能进化的作用力、最佳觅食理论与生态学特化及特化概念的发展。最后指出进一步研究的方向。     

EDENetworks: A user‐friendly software to build and analyse networks in biogeography,ecology and population genetics

The recent application of graph‐based network theory analysis to biogeography, community ecology and population genetics has created a need for user‐friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy‐to‐use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray‐Curtis or Sorensen distance, or population genetic metrics such as F_ST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data.