Amenity and ecological management: A framework for policy and practice

Amenity is a term that has re‐emerged within both public policy and environmental management organisations in response to an increasing emphasis on the human benefits derived from ecosystems. However, practical implementation of amenity management has been difficult due to a lack of definitional clarity within operational and academic literature. This article discusses the need for definitional clarity and understanding of the component elements of amenity that are integral to ecological management and reviews the literature on the perceptions and definitions of amenity in varied contexts. This study argues that positive perceptions of amenity benefits of a place are influenced by both physical elements such as sight, sound and smell and social elements such as age, education and cultural values. These elements should be considered by management agencies in a structured manner in order for the full potential of amenity to be realised. We present a conceptual framework to provide definitional clarity to the concept of amenity and highlight the interactions among its constituent elements. For the management of human‐dominated landscapes, considering the relationship between amenity and biodiversity may improve the integration of ecological and social goals.     

Epidemic outbreaks on structured populations

Our chances to halt epidemic outbreaks rely on how accurately we represent the population structure underlying the disease spread. When analysing global epidemics this force us to consider metapopulation models taking into account intra- and inter-community interactions. Here I introduce and analyze a metapopulation model which accounts for several features observed in real outbreaks. First, I demonstrate that depending on the intra-community expected outbreak size and the fraction of social bridges the epidemic outbreaks die out or there is a finite probability to observe a global epidemics. Second, I show that the global scenario is characterized by resurgent epidemics, their number increasing with increasing the intra-community average distance between individuals. Finally, I present empirical data for the AIDS epidemics supporting the model predictions.     

Geographic distribution of surnames and genetic structure: the county of Ardeche at the beginning of the twentieth century

The analysis of the geographical distribution of surnames (whose transmission in the European societies is similar to that of the Y chromosome) allows to study in an exhaustive way the spatial and temporal human population structure and the influence of environmental variations on this structure. The genetic structure of the Ardèche county was analysed through a study of the surname characteristics (diversity, frequency, geographical dispersion, etc.) of individuals born between 1891 and 1915. The estimation of the intra-community average consanguinity and the inter-district genetic relationships reveals a clear differentiation between populations of the mountainous part (geographically isolated, highly inbred) and those of the Rh?ne valley (less isolated, weakly inbred). As predicted by the isolation by distance model, inter-population coefficients of kinship decreases as distance increases, confirming the presence of a spatial structure, characterized by neighborhood exchange and resulting from former migratory flow.     

Contrasting effects of different landscape characteristics on population growth of a perennial forest herb

Anthropogenic changes in landscape structure, such as habitat loss, habitat subdivision and edge increase, can strongly affect the performance of plants, leading to population declines and extinctions. Many studies to date have focused on single characteristics of landscape structure or single life‐cycle phases, but they poorly discern the different pathways through which landscape change influences plant population dynamics via different vital rates. In this study, we evaluated the effect of two structural characteristics (habitat quantity and edge length) on vital rates and population growth rates of a perennial forest plant (Primula vulgaris) in a historically managed landscape. Areas with higher amounts of forest habitat had higher population growth rates due to higher recruitment, survival and growth of seedlings, while increased forest edge length was positively associated with population growth rates primarily due to a higher survival of reproductive individuals. Effects were stronger during the first of the two transition intervals studied. The results demonstrate that changes in different landscape structural characteristics may result in opposing effects acting via different vital rates, and highlight the need for integrative analyses to evaluate the effects of rapid landscape transformation on the current and long term plant population dynamics.     

An Efficient Immunization Strategy for Community Networks

An efficient algorithm that can properly identify the targets to immunize or quarantine for preventing an epidemic in a population without knowing the global structural information is of obvious importance. Typically, a population is characterized by its community structure and the heterogeneity in the weak ties among nodes bridging over communities. We propose and study an effective algorithm that searches for bridge hubs, which are bridge nodes with a larger number of weak ties, as immunizing targets based on the idea of referencing to an expanding friendship circle as a self-avoiding walk proceeds. Applying the algorithm to simulated networks and empirical networks constructed from social network data of five US universities, we show that the algorithm is more effective than other existing local algorithms for a given immunization coverage, with a reduced final epidemic ratio, lower peak prevalence and fewer nodes that need to be visited before identifying the target nodes. The effectiveness stems from the breaking up of community networks by successful searches on target nodes with more weak ties. The effectiveness remains robust even when errors exist in the structure of the networks.     

High Differentiation among Eight Villages in a Secluded Area of Sardinia Revealed by Genome-Wide High Density SNPs Analysis

To better design association studies for complex traits in isolated populations it''s important to understand how history and isolation moulded the genetic features of different communities. Population isolates should not “a priori” be considered homogeneous, even if the communities are not distant and part of a small region. We studied a particular area of Sardinia called Ogliastra, characterized by the presence of several distinct villages that display different history, immigration events and population size. Cultural and geographic isolation characterized the history of these communities. We determined LD parameters in 8 villages and defined population structure through high density SNPs (about 360 K) on 360 unrelated people (45 selected samples from each village). These isolates showed differences in LD values and LD map length. Five of these villages show high LD values probably due to their reduced population size and extreme isolation. High genetic differentiation among villages was detected. Moreover population structure analysis revealed a high correlation between genetic and geographic distances. Our study indicates that history, geography and biodemography have influenced the genetic features of Ogliastra communities producing differences in LD and population structure. All these data demonstrate that we can consider each village an isolate with specific characteristics. We suggest that, in order to optimize the study design of complex traits, a thorough characterization of genetic features is useful to identify the presence of sub-populations and stratification within genetic isolates.     

Seasonal variations in the diversity and abundance of diazotrophic communities across soils

The nitrogen (N)-fixing community is a key functional community in soil, as it replenishes the pool of biologically available N that is lost to the atmosphere via anaerobic ammonium oxidation and denitrification. We characterized the structure and dynamic changes in diazotrophic communities, based on the nifH gene, across eight different representative Dutch soils during one complete growing season, to evaluate the amplitude of the natural variation in abundance and diversity, and identify possible relationships with abiotic factors. Overall, our results indicate that soil type is the main factor influencing the N-fixing communities, which were more abundant and diverse in the clay soils (n=4) than in the sandy soils (n=4). On average, the amplitude of variation in community size as well as the range-weighted richness were also found to be higher in the clay soils. These results indicate that N-fixing communities associated with sandy and clay soil show a distinct amplitude of variation under field conditions, and suggest that the diazotrophic communities associated with clay soil might be more sensitive to fluctuations associated with the season and agricultural practices. Moreover, soil characteristics such as ammonium content, pH and texture most strongly correlated with the variations observed in the diversity, size and structure of N-fixing communities, whose relative importance was determined across a temporal and spatial scale.     

Global gene expression in Escherichia coli biofilms

It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance to antimicrobial treatments and host immune defence responses. Escherichia coli has been used as a model organism to study the mechanisms of growth within adhered communities. In this study, we use DNA microarray technology to examine the global gene expression profile of E. coli during sessile growth compared with planktonic growth. Genes encoding proteins involved in adhesion (type 1 fimbriae) and, in particular, autoaggregation (Antigen 43) were highly expressed in the adhered population in a manner that is consistent with current models of sessile community development. Several novel gene clusters were induced upon the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces.     

Characterizing the Community Structure of Complex Networks

Background

Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has been so far devoted to the investigation of communities in real networks.

Methodology/Principal Findings

We present a systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks. We find that the mesoscopic organization of networks of the same category is remarkably similar. This is reflected in several characteristics of community structure, which can be used as “fingerprints” of specific network categories. While community size distributions are always broad, certain categories of networks consist mainly of tree-like communities, while others have denser modules. Average path lengths within communities initially grow logarithmically with community size, but the growth saturates or slows down for communities larger than a characteristic size. This behaviour is related to the presence of hubs within communities, whose roles differ across categories. Also the community embeddedness of nodes, measured in terms of the fraction of links within their communities, has a characteristic distribution for each category.

Conclusions/Significance

Our findings, verified by the use of two fundamentally different community detection methods, allow for a classification of real networks and pave the way to a realistic modelling of networks'' evolution.     

Emergence of bursts and communities in evolving weighted networks

Understanding the patterns of human dynamics and social interaction and the way they lead to the formation of an organized and functional society are important issues especially for techno-social development. Addressing these issues of social networks has recently become possible through large scale data analysis of mobile phone call records, which has revealed the existence of modular or community structure with many links between nodes of the same community and relatively few links between nodes of different communities. The weights of links, e.g., the number of calls between two users, and the network topology are found correlated such that intra-community links are stronger compared to the weak inter-community links. This feature is known as Granovetter's "The strength of weak ties" hypothesis. In addition to this inhomogeneous community structure, the temporal patterns of human dynamics turn out to be inhomogeneous or bursty, characterized by the heavy tailed distribution of time interval between two consecutive events, i.e., inter-event time. In this paper, we study how the community structure and the bursty dynamics emerge together in a simple evolving weighted network model. The principal mechanisms behind these patterns are social interaction by cyclic closure, i.e., links to friends of friends and the focal closure, links to individuals sharing similar attributes or interests, and human dynamics by task handling process. These three mechanisms have been implemented as a network model with local attachment, global attachment, and priority-based queuing processes. By comprehensive numerical simulations we show that the interplay of these mechanisms leads to the emergence of heavy tailed inter-event time distribution and the evolution of Granovetter-type community structure. Moreover, the numerical results are found to be in qualitative agreement with empirical analysis results from mobile phone call dataset.     

The fungal fast lane: common mycorrhizal networks extend bioactive zones of allelochemicals in soils

Allelopathy, a phenomenon where compounds produced by one plant limit the growth of surrounding plants, is a controversially discussed factor in plant-plant interactions with great significance for plant community structure. Common mycorrhizal networks (CMNs) form belowground networks that interconnect multiple plant species; yet these networks are typically ignored in studies of allelopathy. We tested the hypothesis that CMNs facilitate transport of allelochemicals from supplier to target plants, thereby affecting allelopathic interactions. We analyzed accumulation of a model allelopathic substance, the herbicide imazamox, and two allelopathic thiophenes released from Tagetes tenuifolia roots, by diffusion through soil and CMNs. We also conducted bioassays to determine how the accumulated substances affected plant growth. All compounds accumulated to greater levels in target soils with CMNs as opposed to soils without CMNs. This increased accumulation was associated with reduced growth of target plants in soils with CMNs. Our results show that CMNs support transfer of allelochemicals from supplier to target plants and thus lead to allelochemical accumulation at levels that could not be reached by diffusion through soil alone. We conclude that CMNs expand the bioactive zones of allelochemicals in natural environments, with significant implications for interspecies chemical interactions in plant communities.     

Network structural properties mediate the stability of mutualistic communities

Key advances are being made on the structures of predator–prey food webs and competitive communities that enhance their stability, but little attention has been given to such complexity–stability relationships for mutualistic communities. We show, by way of theoretical analyses with empirically informed parameters, that structural properties can alter the stability of mutualistic communities characterized by nonlinear functional responses among the interacting species. Specifically, community resilience is enhanced by increasing community size (species diversity) and the number of species interactions (connectivity), and through strong, symmetric interaction strengths of highly nested networks. As a result, mutualistic communities show largely positive complexity–stability relationships, in opposition to the standard paradox. Thus, contrary to the commonly-held belief that mutualism's positive feedback destabilizes food webs, our results suggest that interplay between the structure and function of ecological networks in general, and consideration of mutualistic interactions in particular, may be key to understanding complexity–stability relationships of biological communities as a whole.     

An Adaptive Complex Network Model for Brain Functional Networks

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution.     

The population genomic basis of geographic differentiation in North American common ragweed (Ambrosia artemisiifolia L.)

Common ragweed (Ambrosia artemisiifolia L.) is an invasive, wind‐pollinated plant nearly ubiquitous in disturbed sites in its eastern North American native range and present across growing portions of Europe, Africa, Asia, and Australia. Phenotypic divergence between European and native‐range populations has been described as rapid evolution. However, a recent study demonstrated major human‐mediated shifts in ragweed genetic structure before introduction to Europe and suggested that native‐range genetic structure and local adaptation might fully explain accelerated growth and other invasive characteristics of introduced populations. Genomic differentiation that potentially influenced this structure has not yet been investigated, and it remains unclear whether substantial admixture during historical disturbance of the native range contributed to the development of invasiveness in introduced European ragweed populations. To investigate fine‐scale population genetic structure across the species' native range, we characterized diallelic SNP loci via a reduced‐representation genotyping‐by‐sequencing (GBS) approach. We corroborate phylogeographic domains previously discovered using traditional sequencing methods, while demonstrating increased power to resolve weak genetic structure in this highly admixed plant species. By identifying exome polymorphisms underlying genetic differentiation, we suggest that geographic differentiation of this important invasive species has occurred more often within pathways that regulate growth and response to defense and stress, which may be associated with survival in North America's diverse climatic regions.     

Evolution of nesting strategies of ants: genetic evidence from different population types of Formica ants

Genetic population structure was studied in two types of populations in the ants Formica exsecta and F. pressilabris: populations consisting of single-nest colonies (monodomy) and populations consisting of multi-nest colonies (polydomy). These characteristics seem to be associated with the number of egg-laying females (gynes) in a nest, mating structure of the population, sex ratio and male size variation. The monodomous populations are characterized by single-gyne nests, the population sex ratio is either I:1 or female-biased, males are mainly large-sized, and there is slight inbreeding in the population. The polydomous populations have multi-gyne nests with gynes related to each other, sex ratio is strongly male-biased, most males are small-sized, and there is slight genetic microdifferentiation within the populations. Diploid males found in a polydomous F. pressilabris population suggest that the population is inbred and isolated. Habitat localization is presented as a plausible explanation for the evolution of the polygynous and polydomous population structure.     

Host community structure and the maintenance of pathogen diversity

Community structure has been widely identified as a feature of many real-world networks. It has been shown that the antigenic diversity of a pathogen population can be significantly affected by the contact network of its hosts; however, the effects of community structure have not yet been explored. Here, we examine the congruence between patterns of antigenic diversity in pathogen populations in neighbouring communities, using both a deterministic metapopulation model and individual-based formulations. We show that the spatial differentiation of the pathogen population can only be maintained at levels of coupling far lower than that necessary for the host populations to remain distinct. Therefore, identifiable community structure in host networks may not reflect differentiation of the processes occurring upon them and, conversely, a lack of genetic differentiation between pathogens from different host communities may not reflect strong mixing between them.     

A neutral‐niche theory of nestedness in mutualistic networks

Recently, there has been a vigorous interest in community ecology about the structure of mutualistic networks and its importance for species persistence and coevolution. However, the mechanisms shaping mutualistic networks have been rarely explored. Here we extend for the first time the neutral theory of biodiversity to a multi trophic system. We focus on nestedness, a distinctive pattern of mutualistic community assembly showing two characteristics, namely, asymmetrical specialization (specialists interacting with generalists) and a generalist core (generalists interacting with generalists). We investigate the importance of relative species abundance (RSA) for the nested assembly of plant–animal mutualistic networks. Our results show that neutral mutualistic communities give rise to networks considerably more nested than real communities. RSA explains 60–70% of nested patterns in two real communities studied here, while 30–40% of nestedness is still unexplained. The nested pattern in real communities is better explained when we introduce interaction‐specific species traits such as forbidden links and intensity of dependence (relative importance of fruits for the diet of a frugivore) in our analysis. The fact that neutral mutualistic communities exhibit a perfectly nested structure and do not show a random or compartmentalized structure, underlines the importance of RSA in the assembly of mutualistic networks.     

Movement of protistan trophic groups in soil–plant continuums

Protists, functionally divided into consumers, phototrophs, and parasites act as integral components and vital regulators of microbiomes in soil–plant continuums. However, the drivers of community structure, assembly mechanisms, co-occurrence patterns, and the associations with human pathogens and different protistan trophic groups remain unknown. Here, we characterized the phyllosphere and soil protistan communities associated with three vegetables under different fertilization treatments (none and organic fertilization) at five growth stages. In this study, consumers were the most diverse soil protist group, had the role of inter-kingdom connector, and were the primary biomarker for rhizosphere soils which were subjected to decreasing deterministic processes during plant growth. In contrast, phototrophs had the greatest niche breadth and formed soil protistan hubs, and were the primary biomarkers for both bulk soils and the phyllosphere. Parasites had minimal input to microbial co-occurrence networks. Organic fertilization increased the relative abundance (RA) of pathogenic protists and the number of pathogen–consumer connections in rhizosphere soils but decreased protistan richness and the number of internal protistan links. This study advances our understanding of the ecological roles and potential links between human pathogens and protistan trophic groups associated with soil–plant continuums, which is fundamental to the regulation of soil–plant microbiomes and maintenance of environmental and human health.     

The Role of Viral Introductions in Sustaining Community-Based HIV Epidemics in Rural Uganda: Evidence from Spatial Clustering,Phylogenetics, and Egocentric Transmission Models

Background

It is often assumed that local sexual networks play a dominant role in HIV spread in sub-Saharan Africa. The aim of this study was to determine the extent to which continued HIV transmission in rural communities—home to two-thirds of the African population—is driven by intra-community sexual networks versus viral introductions from outside of communities.

Methods and Findings

We analyzed the spatial dynamics of HIV transmission in rural Rakai District, Uganda, using data from a cohort of 14,594 individuals within 46 communities. We applied spatial clustering statistics, viral phylogenetics, and probabilistic transmission models to quantify the relative contribution of viral introductions into communities versus community- and household-based transmission to HIV incidence. Individuals living in households with HIV-incident (n = 189) or HIV-prevalent (n = 1,597) persons were 3.2 (95% CI: 2.7–3.7) times more likely to be HIV infected themselves compared to the population in general, but spatial clustering outside of households was relatively weak and was confined to distances <500 m. Phylogenetic analyses of gag and env genes suggest that chains of transmission frequently cross community boundaries. A total of 95 phylogenetic clusters were identified, of which 44% (42/95) were two individuals sharing a household. Among the remaining clusters, 72% (38/53) crossed community boundaries. Using the locations of self-reported sexual partners, we estimate that 39% (95% CI: 34%–42%) of new viral transmissions occur within stable household partnerships, and that among those infected by extra-household sexual partners, 62% (95% CI: 55%–70%) are infected by sexual partners from outside their community. These results rely on the representativeness of the sample and the quality of self-reported partnership data and may not reflect HIV transmission patterns outside of Rakai.

Conclusions

Our findings suggest that HIV introductions into communities are common and account for a significant proportion of new HIV infections acquired outside of households in rural Uganda, though the extent to which this is true elsewhere in Africa remains unknown. Our results also suggest that HIV prevention efforts should be implemented at spatial scales broader than the community and should target key populations likely responsible for introductions into communities. Please see later in the article for the Editors'' Summary