Network isolation and local diversity in neutral metacommunities

Biologists seek an understanding of the biological and environmental factors determining local community diversity. Recent advances in metacommunity ecology, and neutral theory in particular, highlight the importance of dispersal processes interacting with the spatial structure of a landscape for generating spatial patterns and maintaining biodiversity. The relative spatial isolation of a community is traditionally thought to have a large influence on local diversity. However, isolation remains an elusive concept to quantify, particularly in metacommunities with complex spatial structure. We represent the metacommunity as a network of local communities, and use network centrality measures to quantify the isolation of a local community. Using spatially explicit neutral theory, we examine how node position predicts variation in alpha diversity across a metacommunity. We find that diversity increases with node centrality in the network, but only when centrality is measured on a given scale in the network that widens with increasing dispersal rates and narrows with increasing evolutionary rates. More generally, complex biodiversity patterns form only when the underlying geography has structure on this critical scale. This provides a framework for understanding the influence of spatial geographic structure on global biodiversity patterns.     

Moving beyond abundance distributions: neutral theory and spatial patterns in a tropical forest

Assessing the relative importance of different processes that determine the spatial distribution of species and the dynamics in highly diverse plant communities remains a challenging question in ecology. Previous modelling approaches often focused on single aggregated forest diversity patterns that convey limited information on the underlying dynamic processes. Here, we use recent advances in inference for stochastic simulation models to evaluate the ability of a spatially explicit and spatially continuous neutral model to quantitatively predict six spatial and non-spatial patterns observed at the 50 ha tropical forest plot on Barro Colorado Island, Panama. The patterns capture different aspects of forest dynamics and biodiversity structure, such as annual mortality rate, species richness, species abundance distribution, beta-diversity and the species–area relationship (SAR). The model correctly predicted each pattern independently and up to five patterns simultaneously. However, the model was unable to match the SAR and beta-diversity simultaneously. Our study moves previous theory towards a dynamic spatial theory of biodiversity and demonstrates the value of spatial data to identify ecological processes. This opens up new avenues to evaluate the consequences of additional process for community assembly and dynamics.     

Theory predicts a rapid transition from niche-structured to neutral biodiversity patterns across a speciation-rate gradient

A central challenge in community ecology is to predict patterns of biodiversity with mechanistic models. The neutral model of biodiversity is a simple model that appears to provide parsimonious and accurate predictions of biodiversity patterns in some ecosystems, even though it ignores processes such as species interactions and niche structure. In a recent paper, we used analytical techniques to reveal why the mean predictions of the neutral model are robust to niche structure in high diversity but not low-diversity ecosystems. In the present paper, we explore this phenomenon further by generating stochastic simulated data from a spatially implicit hybrid niche-neutral model across different speciation rates. We compare the resulting patterns of species richness and abundance with the patterns expected from a pure neutral and a pure niche model. As the speciation rate in the hybrid model increases, we observe a surprisingly rapid transition from an ecosystem in which diversity is almost entirely governed by niche structure to one in which diversity is statistically indistinguishable from that of the neutral model. Because the transition is rapid, one prediction of our abstract model is that high-diversity ecosystems such as tropical forests can be approximated by one simple model—the neutral model—whereas low-diversity ecosystems such as temperate forests can be approximated by another simple model—the niche model. Ecosystems that require the hybrid model are predicted to be rare, occurring only over a narrow range of speciation rates.     

Dispersal and neutral sampling mediate contingent effects of disturbance on plant beta‐diversity: a meta‐analysis

A major challenge in ecology, conservation and global‐change biology is to understand why biodiversity responds differently to similar environmental changes. Contingent biodiversity responses may depend on how disturbance and dispersal interact to alter variation in community composition (β‐diversity) and assembly mechanisms. However, quantitative syntheses of these patterns and processes across studies are lacking. Using null‐models and meta‐analyses of 22 factorial experiments in herbaceous plant communities across Europe and North America, we show that disturbance diversifies communities when dispersal is limited, but homogenises communities when combined with increased immigration from the species pool. In contrast to the hypothesis that disturbance and dispersal mediate the strength of niche assembly, both processes altered β‐diversity through neutral‐sampling effects on numbers of individuals and species in communities. Our synthesis suggests that stochastic effects of disturbance and dispersal on community assembly play an important, but underappreciated, role in mediating biotic homogenisation and biodiversity responses to environmental change.     

Human impacts on the species-area relationship in reef fish assemblages

The relationship between species richness and area is one of the oldest, most recognized patterns in ecology. Here we provide empirical evidence for strong impacts of fisheries exploitation on the slope of the species–area relationship (SAR). Using comparative field surveys of fish on protected and exploited reefs in three oceans and the Mediterranean Sea, we show that exploitation consistently depresses the slope of the SAR for both power-law and exponential models. The magnitude of change appears to be proportional to fishing intensity. Results are independent of taxonomic resolution and robust across coral and rocky reefs, sampling protocols and statistical methods. Changes in species richness, relative abundance and patch occupancy all appear to contribute to this pattern. We conclude that exploitation pressure impacts the fundamental scaling of biodiversity as well as the species richness and spatial distribution patterns of reef fish. We propose that species–area curves can be sensitive indicators of community-level changes in biodiversity, and may be useful in quantifying the human imprint on reef biodiversity, and potentially elsewhere.     

A primer of community ecology using the R language

Community ecology beginners often struggle to understand theories expressed in complex mathematical formulas and to master computer programming. To remedy this situation, this article provides a practical, R-based introduction to community ecology by illustrating core concepts (vital rates, carrying capacity, and density dependence) and models that can be used to explore the patterns of species abundance and diversity. The structure of this article consists of three modeling exercises, each asking a general question that can be answered by a combination of theory and R programming: (1) what determines the abundance of species, and what makes a population persist and go extinct?; (2) what determines the distribution of species and species diversity?; (3) what determines the relative abundance of species and what allows species to coexist? Through the exercises, I discuss the following five concepts and ideas that provide valuable insights into the questions: (i) the tragedy of the commons, (ii) the theory of island biogeography, (iii) competitive exclusion, (iv) the neutral theory of biodiversity, and (v) frequency dependence. These materials are thus designed to guide the reader in developing an intuition for ecological thinking that will help capture the essence of the global environmental and biodiversity crisis. Although this article does not delineate the scope and depth of the vast field of community ecology, I hope that it will motivate the reader to step up to a more formal introduction to community ecology.     

β‐diversity scaling patterns are consistent across metrics and taxa

β‐diversity (variation in community composition) is a fundamental component of biodiversity, with implications for macroecology, community ecology and conservation. However, its scaling properties are poorly understood. Here, we systematically assessed the spatial scaling of β‐diversity using 12 empirical large‐scale datasets including different taxonomic groups, by examining two conceptual types of β‐diversity and explicitly considering the turnover and nestedness components. We found highly consistent patterns across datasets. Multiple‐site β‐diversity (i.e. variation across multiple sites) scaling curves were remarkably consistent, with β‐diversity decreasing with sampled area according to a power law. For pairwise dissimilarities, the rates of increase of dissimilarity with geographic distance remained largely constant across scales, while grain size (or scale level) had a stronger effect on overall dissimilarity. In both analyses, turnover was the main contributor to β‐diversity, following total β‐diversity patterns closely, while the nestedness component was largely insensitive to scale changes. Our results highlight the importance of integrating both inter‐ and intraspecific aggregation patterns across spatial scales, which underpin substantial differences in community structure from local to regional scales.     

声景生态学研究进展和展望

声景生态学以景观中的声音为研究对象, 探讨其在不同时空维度上的分布和变化模式, 从而揭示自然环境、野生动物和人类活动的相互作用关系。本文通过系统检索声景生态学研究的相关文献, 回顾了该学科的研究框架和研究方法, 总结了目前常用的声学指标, 重点归纳了声景生态学的研究内容, 包括声景组成和各组分间的相互作用, 声景的时空格局, 以及声景生态学在生物多样性监测中的应用。目前, 声景监测中存在的问题主要包括监测的生态系统类型和物种类群有限、声学指标效力有待提高等。建议未来着重推进建立系统性的声景监测网络和数据管理平台, 开发和完善音频数据采集、分析方法和评估指标, 并重视声景数据的采集, 将声景视作一种资源进行研究和保护。     

From species distributions to meta‐communities

The extent that biotic interactions and dispersal influence species ranges and diversity patterns across scales remains an open question. Answering this question requires framing an analysis on the frontier between species distribution modelling (SDM), which ignores biotic interactions and dispersal limitation, and community ecology, which provides specific predictions on community and meta‐community structure and resulting diversity patterns such as species richness and functional diversity. Using both empirical and simulated datasets, we tested whether predicted occurrences from fine‐resolution SDMs provide good estimates of community structure and diversity patterns at resolutions ranging from a resolution typical of studies within reserves (250 m) to that typical of a regional biodiversity study (5 km). For both datasets, we show that the imprint of biotic interactions and dispersal limitation quickly vanishes when spatial resolution is reduced, which demonstrates the value of SDMs for tracking the imprint of community assembly processes across scales.     

A simulation‐based approach to understand how metacommunity characteristics influence emergent biodiversity patterns

To understand controls over biodiversity, it is necessary to take a multi‐scale approach to understand how local and regional factors affect the community assembly processes that drive emergent patterns. This need is reflected in the growing use of the metacommunity concept to interpret multi‐scale measures of biodiversity, including metrics derived from diversity partitioning (e.g. α, β and γ diversity) and variation partitioning (e.g. spatial and environmental components of compositional turnover) techniques. However, studies have shown limited success using these metrics to characterize underlying community assembly dynamics. Here we demonstrate how a metacommunity simulation package (MCSim) can be used to evaluate when and how biodiversity metrics can be used to make inferences about metacommunity characteristics. We examined a wide range of parameter settings representing ecologically relevant scenarios. We used artificial neural networks (ANNs) to assess the sensitivity of diversity and variation partitioning metrics (calculated from simulation outcomes) to metacommunity parameter settings. In the scenarios examined in this study, the niche‐neutral gradient strongly influenced most biodiversity metrics, metacommunity size exhibited a marginal influence over some metrics, and dispersal dynamics only affected a subset of variation partitioning outcomes. Variation partitioning response curves along the niche‐neutral gradient were not monotonic; however, simulation outcomes suggest other biodiversity metrics (e.g. dissimilarity saturation) can be used in combination with variation partitioning metrics to make inferences about metacommunity properties. With the growing availability of archived ecological data, we expect future work will apply simulation‐based techniques to better understand links between biodiversity and the metacommunity characteristics that are presumed to control the underlying community assembly processes.     

Morphological complexity affects the diversity of marine microbiomes

Large eukaryotes support diverse communities of microbes on their surface—epibiota—that profoundly influence their biology. Alternate factors known to structure complex patterns of microbial diversity—host evolutionary history and ecology, environmental conditions and stochasticity—do not act independently and it is challenging to disentangle their relative effects. Here, we surveyed the epibiota from 38 sympatric seaweed species that span diverse clades and have convergent morphology, which strongly influences seaweed ecology. Host identity explains most of the variation in epibiont communities and deeper host phylogenetic relationships (e.g., genus level) explain a small but significant portion of epibiont community variation. Strikingly, epibiota community composition is significantly influenced by host morphology and epibiota richness increases with morphological complexity of the seaweed host. This effect is robust after controlling for phylogenetic non-independence and is strongest for crustose seaweeds. We experimentally validated the effect of host morphology by quantifying bacterial community assembly on latex sheets cut to resemble three seaweed morphologies. The patterns match those observed in our field survey. Thus, biodiversity increases with habitat complexity in host-associated microbial communities, mirroring patterns observed in animal communities. We suggest that host morphology and structural complexity are underexplored mechanisms structuring microbial communities.Subject terms: Microbial ecology, Biodiversity     

Top predators determine how biodiversity is partitioned across time and space

Natural ecosystems are shaped along two fundamental axes, space and time, but how biodiversity is partitioned along both axes is not well understood. Here, we show that the relationship between temporal and spatial biodiversity patterns can vary predictably according to habitat characteristics. By quantifying seasonal and annual changes in larval dragonfly communities across a natural predation gradient we demonstrate that variation in the identity of top predator species is associated with systematic differences in spatio‐temporal β‐diversity patterns, leading to consistent differences in relative partitioning of biodiversity between time and space across habitats. As the size of top predators increased (from invertebrates to fish) habitats showed lower species turnover across sites and years, but relatively larger seasonal turnover within a site, which ultimately shifted the relative partitioning of biodiversity across time and space. These results extend community assembly theory by identifying common mechanisms that link spatial and temporal patterns of β‐diversity.     

Effect of Landscape Structure on Species Diversity

The effects of habitat fragmentation and their implications for biodiversity is a central issue in conservation biology which still lacks an overall comprehension. There is not yet a clear consensus on how to quantify fragmentation even though it is quite common to couple the effects of habitat loss with habitat fragmentation on biodiversity. Here we address the spatial patterns of species distribution in fragmented landscapes, assuming a neutral community model. To build up the fragmented landscapes, we employ the fractional Brownian motion approach, which in turn permits us to tune the amount of habitat loss and degree of clumping of the landscape independently. The coupling between the neutral community model, here simulated by means of the coalescent method, and fractal neutral landscape models enables us to address how the species–area relationship changes as the spatial patterns of a landscape is varied. The species–area relationship is one of the most fundamental laws in ecology, considered as a central tool in conservation biology, and is used to predict species loss following habitat disturbances. Our simulation results indicate that the level of clumping has a major role in shaping the species–area relationship. For instance, more compact landscapes are more sensitive to the effects of habitat loss and speciation rate. Besides, the level of clumping determines the existence and extension of the power-law regime which is expected to hold at intermediate scales. The distributions of species abundance are strongly influenced by the degree of fragmentation. We also show that the first and second commonest species have approximately self-similar spatial distributions across scales, with the fractal dimensions of the support of the first and second commonest species being very robust to changes in the spatial patterns of the landscape.     

Temporal scaling of bacterial taxa is influenced by both stochastic and deterministic ecological factors

Microorganisms operate at a range of spatial and temporal scales acting as key drivers of ecosystem properties. Therefore, many key questions in microbial ecology require the consideration of both spatial and temporal scales. Spatial scaling, in particular the species-area relationship (SAR), has a long history in ecology and has recently been addressed in microbial ecology. However, the temporal analogue of the SAR, the species-time relationship, has received far less attention even in the science of general ecology. Here we focus upon the role of temporal scaling in microbial ecological patterns by coupling molecular characterization of bacterial communities in discrete island (bioreactor) systems with a macroecological approach. Our findings showed that the temporal scaling exponent (slope), and therefore taxa turnover of the bacterial taxa-time relationship decreased as selective pressure (industrial wastewater concentration) increased. Also, as the concentration of industrial wastewater increased across the bioreactors, we observed a gradual switch from stochastic community assembly to more deterministic (niche)-based considerations. The identification of broad-scale statistical patterns is particularly relevant to microbial ecology, as it is frequently difficult to identify individual species or their functions. In this study, we identify wide-reaching statistical patterns of diversity and show that they are shaped by the prevalent underlying ecological factors.     

Metacommunity patterns in larval odonates

The growth of metacommunity ecology as a subdiscipline has increased interest in how processes at different spatial scales structure communities. However, there is still a significant knowledge gap with respect to relating the action of niche- and dispersal-assembly mechanisms to observed species distributions across gradients. Surveys of the larval dragonfly community (Odonata: Anisoptera) in 57 lakes and ponds in southeast Michigan were used to evaluate hypotheses about the processes regulating community structure in this system. We considered the roles of both niche- and dispersal-assembly processes in determining patterns of species richness and composition across a habitat gradient involving changes in the extent of habitat permanence, canopy cover, area, and top predator type. We compared observed richness patterns and species distributions in this system to patterns predicted by four general community models: species sorting related to adaptive trade-offs, a developmental constraints hypothesis, dispersal assembly, and a neutral community assemblage. Our results supported neither the developmental constraints nor the neutral-assemblage models. Observed patterns of richness and species distributions were consistent with patterns expected when adaptive tradeoffs and dispersal-assembly mechanisms affect community structure. Adaptive trade-offs appeared to be important in limiting the distributions of species which segregate across the habitat gradient. However, dispersal was important in shaping the distributions of species that utilize habitats with a broad range of hydroperiods and alternative top predator types. Our results also suggest that the relative importance of these mechanisms may change across this habitat gradient and that a metacommunity perspective which incorporates both niche- and dispersal-assembly processes is necessary to understand how communities are organized. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Do generalized scaling laws exist for species abundance distribution in mountains?

Knowing the global pattern of species diversity is a central goal of the science of ecology, and scaling laws can be useful for analysis of cross-scale biodiversity patterns. An elevational gradient in a warm temperate zone of the Donglingshan mountains (China) is used to test the scaling laws of species abundance distribution using multifractal analysis. We show that the power law scaling relationship holds for not just the classical SAR (species–area relationship for richness), but also for Shannon and Simpson diversity. In fact, we find power-laws in the generalized species abundance distribution at all stratal levels of the forest (trees, shrubs and herbs). The fact that these laws exist across a heterogeneous landscape representing a strong bioclimatic gradient suggests that biodiversity scaling laws may be more robust than previously thought.     

Non-randomness in the species–area relationship: testing the underlying mechanisms

The species–area relationship (SAR) is one of the best documented patterns in ecology. However, interrelations between the SAR and species distributions are largely unexplored. This research was aimed (1) to assess if the SAR for a group of sedentary insects is associated to a random or non-random distribution of species across islands in a land-bridge archipelago, and (2) to investigate possible factors responsible for the non-randomness. Communities of tenebrionid beetles on the Aegean Islands (Greece) were studied as a case of a relict fauna. Three aspects of non-randomness were analysed: (1) non-random variation of species richness in the SAR, (2) degree of nestedness and (3) presence of special patterns of co-occurrence. Species co-occurrence and nestedness analyses indicated that historical aspects, as opposed to interspecific competition or distance-mediated colonization events, have moulded these species distributions.     

Developing a flexible learning activity on biodiversity and spatial scale concepts using open‐access vegetation datasets from the National Ecological Observatory Network

Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.     

Patterns of parasite community dissimilarity: the significant role of land use and lack of distance‐decay in a bat–helminth system

Increasing community dissimilarity across geographic distance has been described for a wide variety of organisms and understanding its underlying causes is key to understanding mechanisms driving patterns of biodiversity. Both niche‐based and neutral processes may produce a distance decay relationship; however, disentangling their relative influence requires simultaneous examination of multiple potential drivers. Parasites represent a unique opportunity in which to study distance decay because community dissimilarity may depend on environmental requirements and dispersal capability of parasites as well also those of their hosts. We used big brown bats Eptesicus fuscus and their intestinal helminths to investigate: 1) independent contributions of geographic and environmental distances on dissimilarity of intestinal helminth component communities between populations of big brown bats; 2) which environmental variables best explained variation in community dissimilarity; and 3) whether similar patterns of decay with geographic or environmental distance were observed for within‐host population and within‐individual host parasite communities. We used compositional measures of community dissimilarity to examine how parasite communities may change with geographic distance and varying environmental conditions. Non‐spatial variables strongly influenced compositional parasite community dissimilarity over multiple community scales, and we observed little evidence for spatial processes such as distance decay. Environment surrounding roost sites better predicted helminth community dissimilarity than any other class of variables and landcover classes representing anthropogenic modification consistently explained variation in community structure. Our results indicate that human disturbance drives significant patterns of parasite community dissimilarity, most likely by changing the presence or abundance of intermediate hosts in an area.     

生物多样性理论最新进展

生物多样性是生态系统复杂性的重要特征, 理解多样性的形成和维持机制一直是理论生态学研究的核心议题。本文从三方面概述了生物多样性理论的最新进展。一是物种共存和群落构建, 总结了现代共存理论和基于过程的群落构建理论的新进展。二是物种相互作用, 综述了利用经验数据推断物种相互作用关系和强度的最新方法。三是生态-进化动态, 介绍了生态-进化模型的一般框架及其在生物多样性研究中的应用。最后对生物多样性理论的发展趋势做了展望, 特别是多尺度整合理论和全球变化下的预测理论。