Grazing and the vanishing complexity of plant association networks in grasslands

Interactions are key drivers of the functioning and fate of plant communities. A traditional way to measure them is to use pairwise experiments, but such experiments do not scale up to species-rich communities. For those, using association networks based on spatial patterns may provide a more realistic approach. While this method has been successful in abiotically-stressed environments (alpine and arid ecosystems), it is unclear how well it generalizes to other types of environments. We help fill this knowledge gap by documenting how the structure of plant communities changes in a Mediterranean dry grassland grazed by sheep using plant spatial association networks. We investigated how the structure of these networks changed with grazing intensity to show the effect of biotic disturbance on community structure. We found that these grazed grassland communities were mostly dominated by negative associations, suggesting a dominance of interference over facilitation regardless of the disturbance level. The topology of the networks revealed that the number of associations were not evenly-distributed across species, but rather that a small subset of species established most negative associations under low grazing conditions. All these aspects of spatial organization vanished under high level of grazing as association networks became more similar to null expectations. Our study shows that grazed herbaceous plant communities display a highly non-random organization that responds strongly to disturbance and can be measured through association networks. This approach thus appears insightful to test general hypotheses about plant communities, and in particular understand how anthropogenic perturbations affect the organization of ecological communities.     

Genetic evidence that culling increases badger movement: implications for the spread of bovine tuberculosis

The Eurasian badger (Meles meles) has been implicated in the transmission of bovine tuberculosis (TB, caused by Mycobacterium bovis) to cattle. However, evidence suggests that attempts to reduce the spread of TB among cattle in Britain by culling badgers have mixed effects. A large-scale field experiment (the randomized badger culling trial, RBCT) showed that widespread proactive badger culling reduced the incidence of TB in cattle within culled areas but that TB incidence increased in adjoining areas. Additionally, localized reactive badger culling increased the incidence of TB in cattle. It has been suggested that culling-induced perturbation of badger social structure may increase individual movements and elevate the risk of disease transmission between badgers and cattle. Field studies support this hypothesis, by demonstrating increases in badger group ranges and the prevalence of TB infection in badgers following culling. However, more evidence on the effect of culling on badger movements is needed in order to predict the epidemiological consequences of this control strategy. Here, analysis of the genetic signatures of badger populations in the RBCT revealed increased dispersal following culling. While standard tests provided evidence for greater dispersal after culling, a novel method indicated that this was due to medium- and long-distance dispersal, in addition to previously reported increases in home-range size. Our results also indicated that, on average, badgers infected with M. bovis moved significantly farther than did uninfected badgers. A disease control strategy that included culling would need to take account of the potentially negative epidemiological consequences of increased badger dispersal.     

Landscape modelling spatial bottlenecks: implications for raccoon rabies disease spread

A landscape genetic simulation modelling approach is used to understand factors affecting raccoon rabies disease spread in southern Ontario, Canada. Using the Ontario Rabies Model, we test the hypothesis that landscape configuration (shape of available habitat) affects dispersal, as indicated by genetic structuring. We simulated range expansions of raccoons from New York into vacant landscapes in Ontario, in two areas that differed by the presence or absence of a landscape constriction. Our results provide theoretical evidence that landscape constriction acts as a vicariant bottleneck. We discuss implications for raccoon rabies spread.     

A modeling framework for the establishment and spread of invasive species in heterogeneous environments

Natural and human‐induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross‐study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework—MDIG ) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS ), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small‐grain landscape characteristics, such as habitat size and habitat connectivity, interact with life‐history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.     

Detecting plant spatial pattern change after disperser loss: A simulation and a case study

Disruption of seed dispersal processes may affect plant population spatial structure. We used a spatial simulation model and an empirical case study to assess the conditions under which the loss of seed dispersers has a detectable effect on a species' spatial pattern. Our simulation experiments suggested that detecting spatial change following disperser loss will be difficult, except when rates of fruit removal are initially high and then completely disappear. To contextualize the simulation modeling, we used spatial point pattern analyses to characterize the spatial pattern of two large-seeded species (Leucopogon nutans, a fire-killed seeder shrub and Macrozamia riedlei, a long-lived, resprouting cycad) in the jarrah (Eucalyptus marginata) forests of southwestern Australia. The plant species' primary disperser, the emu (Dromaius novaehollandiae), was absent from one of the sites we considered, but present at the other two. There was no detectable difference for either plant species in the strength of aggregation between sites with and without emu. However, even if disperser loss may not greatly affect local spatial structure for most plant species, it is likely to be important for long distance dispersal and genetic structuring of populations, so accurate characterization of the dispersal kernel is critical, especially in terms of plant emigration.     

The dynamics of sexual contact networks: effects on disease spread and control

Sexually transmitted pathogens persist in populations despite the availability of biomedical interventions and knowledge of behavioural changes that would reduce individual-level risk. While behavioural risk factors are shared between many sexually transmitted infections, the prevalence of these diseases across different risk groups varies. Understanding this heterogeneity and identifying better control strategies depends on an improved understanding of the complex social contact networks over which pathogens spread. To date, most efforts to study the impact of sexual network structure on disease dynamics have focused on static networks. However, the interaction between the dynamics of partnership formation and dissolution and the dynamics of transmission plays a role, both in restricting the effective network accessible to the pathogen, and in modulating the transmission dynamics. We present a simple method to simulate dynamical networks of sexual partnerships. We inform the model using survey data on sexual attitudes and lifestyles, and investigate how the duration of infectiousness changes the effective contact network over which disease may spread. We then simulate several control strategies: screening, vaccination and behavioural interventions. Previous theory and research has advanced the importance of core groups for spread and control of STD. Our work is consistent with the importance of core groups, but extends this idea to consider how the duration of infectiousness associated with a particular pathogen interacts with host behaviours to define these high risk subpopulations. Characteristics of the parts of the network accessible to the pathogen, which represent the network structure of sexual contacts from the “point of view” of the pathogen, are substantially different from those of the network as a whole. The pathogen itself plays an important role in determining this effective network structure; specifically, we find that if the pathogen’s duration of infectiousness is short, infection is more concentrated in high-activity, high-concurrency individuals even when all other factors are held constant. Widespread screening programmes would be enhanced by follow-up interventions targeting higher-risk individuals, because screening shortens the expected duration of infectiousness and causes a greater relative decrease in prevalence among lower-activity than in higher-activity individuals. Even for pathogens with longer durations of infectiousness, our findings suggest that targeting vaccination and behavioural interventions towards high-activity individuals provides comparable benefits to population-wide interventions.     

Modelling cacao pod growth: implications for disease control

Cacao trees are affected by diseases that attack either their vegetative parts, their fruits or both. In cacao pod diseases, several factors are involved in disease susceptibility, such as the fruiting cycle, fruit size, age, position on the tree and cacao genotype. To gain a clearer understanding of how these characteristics influence cacao pod diseases, four models describing pod growth in several cacao genotypes were evaluated. Three models used to estimate pod volume or surface area were also compared. Observed pod growth was of a sigmoid form and fitted best to the Richards model, well to the Logistic and Beta growth models, and least to the Gompertz model. Pod volume and probably pod surface area were best estimated using a prolate spheroid model. Pod growth models can help improve pod disease management and thereby cacao production. They can help to predict yield, as well as provide information for the timing and frequency of control operations. Information on pod size, surface area and susceptibility will help to improve dose transfer and spray deposit studies intended to optimise control efficiency.     

Functional brain networks: great expectations,hard times and the big leap forward

Many physical and biological systems can be studied using complex network theory, a new statistical physics understanding of graph theory. The recent application of complex network theory to the study of functional brain networks has generated great enthusiasm as it allows addressing hitherto non-standard issues in the field, such as efficiency of brain functioning or vulnerability to damage. However, in spite of its high degree of generality, the theory was originally designed to describe systems profoundly different from the brain. We discuss some important caveats in the wholesale application of existing tools and concepts to a field they were not originally designed to describe. At the same time, we argue that complex network theory has not yet been taken full advantage of, as many of its important aspects are yet to make their appearance in the neuroscience literature. Finally, we propose that, rather than simply borrowing from an existing theory, functional neural networks can inspire a fundamental reformulation of complex network theory, to account for its exquisitely complex functioning mode.     

Biological control of weeds by means of plant pathogens: Significance for integrated weed management in modern agro-ecology

Biological control of weeds by using plant pathogens has gainedacceptance as a practical, safe, environmentally beneficial, weedmanagement method applicable to agro-ecosystems. The interest in thisweed control approach from public and private groups, and support forresearch and developmental effort, are on the upswing. This increasinginterest is stimulated largely due to major economic, social, andenvironmental forces that are directing our choices in crop productionpractices. Some of these changes are market-driven while others aresocial and ecological in nature. These changes are in turn influencingthe choices in weed control methods. In this regard, biocontrol withplant pathogens has been proven a feasible, albeit minor, component ofmodern integrated weed-management systems. This environmentallybeneficial method should be promoted and exploited further to meet thecurrent and future challenges in weed management in agro-ecosystems.     

Living in the branches: population dynamics and ecological processes in dendritic networks

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.     

植物病害防治相关微生物组研究进展与展望

微生物是人类活动过程中重要的生物资源。植物及其根围土壤中生存着大量多种多样的微生物,这些微生物与植物健康之间存在着密不可分的关系。近年来,基因测序技术的快速发展为植物微生物组结构和功能的研究提供了极大的便利,多种植物相关的微生物组得到了解析。同时更多研究者聚焦于植物病害相关的微生物组研究,通过差异分析,发现了一些特定的有益于植物健康的微生物菌群。此外,植物根围或根内微生物塑造的内在原理也得到了进一步的揭示。一系列植物微生物组研究为植物病害防治和新的微生物资源的挖掘提供了更多思路。     

An empirical assessment of tree branching networks and implications for plant allometric scaling models

Several theories predict whole‐tree function on the basis of allometric scaling relationships assumed to emerge from traits of branching networks. To test this key assumption, and more generally, to explore patterns of external architecture within and across trees, we measure branch traits (radii/lengths) and calculate scaling exponents from five functionally divergent species. Consistent with leading theories, including metabolic scaling theory, branching is area preserving and statistically self‐similar within trees. However, differences among scaling exponents calculated at node‐ and whole‐tree levels challenge the assumption of an optimised, symmetrically branching tree. Furthermore, scaling exponents estimated for branch length change across branching orders, and exponents for scaling metabolic rate with plant size (or number of terminal tips) significantly differ from theoretical predictions. These findings, along with variability in the scaling of branch radii being less than for branch lengths, suggest extending current scaling theories to include asymmetrical branching and differential selective pressures in plant architectures.     

Habitat loss and the structure of plant-animal mutualistic networks

Recent papers have described the structure of plant–animal mutualistic networks. However, no study has yet explored the dynamical implications of network structure for the persistence of such mutualistic communities. Here, we develop a patch-model of a whole plant–animal community and explore its persistence. To assess the role of network structure, we build three versions of the model. In the first version, we use the exact network of interactions of two real mutualistic communities. In the other versions, we randomize the observed network of interactions using two different null models. We show that the community response to habitat loss is affected by network structure. Real communities start to decay sooner than random communities, but persist for higher destruction levels. There is a destruction threshold at which the community collapses. Our model is the first attempt to describe the dynamics of whole mutualistic metacommunities interacting in realistic ways.     

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).     

Influence of nutrition on disease development caused by fungal pathogens: implications for plant disease control

A great deal of information is available in the literature on the effects of nutrition on disease development in plants and crops. However, much of this information is contradictory and although it is widely recognised that nutrition can influence disease in crops, limited progress has been made in the manipulation of crop nutrition to enhance disease control. Achieving this aim requires a sound understanding of the effects of fertilisation on nutrient levels and availability in crop tissues, and in turn, how the nutrient status of such tissues influences pathogen infection, colonisation and sporulation. Some of these details are known for a number of crop plants under controlled conditions, but very little of this type of information is available for crops under field conditions. This review focuses on nitrogen, sulphur, phosphorus, potassium and silicon, examines the availability of these nutrients in plant tissues to support pathogen growth and development, and reviews the effects of the different nutrients on disease development. The review also examines the potential for manipulating crop nutrition to enhance disease control in conventional and organic cropping systems.     

Social networks of disease spread in the lower Illinois valley: a simulation approach

This study illustrates the use of disease modeling and simulation techniques to the study of the spread of disease within and between social networks. A Reed-Frost type model of disease spread is used to construct a simulation of the spread of tuberculosis within three prehistoric populations of the Lower Illinois River Valley during Middle Woodland, Late Woodland, and Mississippian times. A high and low population size was modeled for each time period. Late Woodland model 2 (low population estimate) is the only model that experienced pathogen extinction with host survival. The rest of the models experienced rapid and severe host population decline. The results of the simulation suggest that a social network size of between 180 and 440 persons is required under the conditions of this model for host-pathogen coexistence (i.e., endemicity) to occur. The severe population decline experienced by these populations suggests that tuberculosis as modeled here could not have existed in these populations. Future refinements of modeling and simulation techniques can provide additional insights into how disease spreads among social contacts.