Search

Food sharing and distribution organization systems provide critical resources for local communities and food-insecure households. In this article, we investigate a newly collected data set of the Thrive Network in southwestern Virginia, which links forty food security organizations through fifty-one connections, using a theoretical framework of organization science within geographic space. We first test whether more central and higher degree organizations are toward the geographic center of the network, near convenient points of interest. We then measure whether organizations are likely to form connections based on nearness and logistical effectiveness of moving goods, and where this occurs. Finally, we find “missed connections,” defined as sets of organizations that are nearby but highly disconnected in the network. We find that important nodes are not necessarily in the center of the network, but are located on the periphery, and that relatively few organizations are connected to their nearby neighbors. We find that important nodes are not necessarily in the center of the network, but are located on the periphery, and that relatively few organizations are connected to their nearby neighbors. As such, this system could be predicated on bottom-up personal relationships rather than a hub-and-spoke supply chain configuration, and new ties might make the system more effective. We use our findings to help the Thrive Network build a more resilient food-sharing system and better serve vulnerable clients. [ABSTRACT FROM AUTHOR]

Copyright of Anuario Turismo y Sociedad is the property of Universidad Externado de Colombia, Facultad de Empresas Turísticas y Hoteleras and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Integer ambiguity resolution (IAR) plays a key role in high‐precision Global Navigation Satellite System (GNSS). While GNSS network analysis is usually achieved through double‐difference (DD) IAR, undifferenced (UD) IAR has also been developed in recent years to achieve network analysis station by station. It is normally acquiesced in that DD‐IAR and UD‐IAR should achieve equivalent results, which is however not the case in a number of studies. We investigated four representatives DD‐IAR and UD‐IAR strategies using 1 year of GPS data from 192 globally distributed stations, where the position repeatability and the root mean squares error (RMSE) against the International GNSS Service weekly solutions were both quantified. We found that the position repeatability and the RMSE of DD‐IAR were both worse than those of UD‐IAR at over 90% of stations for the east component, though the largest deteriorations were only 0.6 and 0.7 mm, respectively. We demonstrate that it is the incorrectly resolved DD ambiguities, though accounting for far less than 1%, that degrade DD‐IAR. Identifying such problematic ambiguities requires sophisticated quality control for DD‐IAR, because the integer offset of an incorrect DD ambiguity might have been absorbed evenly by the cross‐connected mass of DD ambiguities throughout the network, and consequently does not manifest as an outlier in the ambiguity‐fixed solution. We, therefore, recommend UD‐IAR for GNSS network analysis since it is immune to the error propagation resulting from incorrect integer ambiguities at other stations and thus more efficient to achieve ambiguity‐fixed solutions. Plain Language Summary: Integer ambiguity resolution (IAR), that is, fixing the unknown full cycles of carrier signal waves to integers, is significant to Global Navigation Satellite System precise positioning. There are two types of IAR, that is, double‐difference (DD) and undifferenced IAR. DD IAR is achieved by differencing between satellite pairs and station pairs, whereas undifferenced IAR is achieved without differencing observations between stations. In theory, the two IAR strategies can achieve equivalent results, but some studies showed that undifferenced IAR can achieve more precise positions than DD IAR. We demonstrate that it is the DD ambiguities fixed to incorrect integers that degrade the positioning precision. To identify all those incorrect ambiguities requires sophisticated quality control. In contrast, undifferenced IAR is far less affected by incorrect ambiguities. Besides, when processing a massive network, DD IAR is quite slow in computation. Therefore, we recommend undifferenced IAR since it is more resistant to incorrect ambiguity resolution and more efficient in achieving high‐precision positioning. Key Points: Conventional Global Navigation Satellite System (GNSS) network analysis is subject to robust double‐difference ambiguity resolutionUndifferenced ambiguity resolution is more robust in quality control and hence more efficient in massive network analysisPRIDE precise point positioning ‐AR has been open‐sourced with undifferenced ambiguity resolution capability for GNSS network analysis [ABSTRACT FROM AUTHOR]

Yeast Snf1 (Sucrose non-fermenting1), mammalian AMPK (5′ AMP-activated protein kinase) and plant SnRK1 (Snf1-Related Kinase1) are conserved heterotrimeric kinase complexes that re-establish energy homeostasis following stress. The hormone abscisic acid (ABA) plays a crucial role in plant stress response. Activation of SnRK1 or ABA signaling results in overlapping transcriptional changes, suggesting these stress pathways share common targets. To investigate how SnRK1 and ABA interact during stress response in Arabidopsis thaliana, we screened the SnRK1 complex by yeast two-hybrid against a library of proteins encoded by 258 ABA-regulated genes. Here, we identify 125 SnRK1- interacting proteins (SnIPs). Network analysis indicates that a subset of SnIPs form signaling modules in response to abiotic stress. Functional studies show the involvement of SnRK1 and select SnIPs in abiotic stress responses. This targeted study uncovers the largest set of SnRK1 interactors, which can be used to further characterize SnRK1 role in plant survival under stress. Carianopol et al. construct a detailed protein interaction network for the SnRK1 kinase complex to investigate the interaction of SnRK1 and ABA during stress response. They identify 125 proteins that interact with SnRK1, which can be used further to characterise the role of SnRK1 in plant survival under stress. [ABSTRACT FROM AUTHOR]

Copyright of Strategy & Development Review is the property of Strategy & Development Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We quantify the spatiotemporal evolution of the substorm ionospheric current system utilizing the SuperMAG 100+ magnetometers. We construct dynamical directed networks from this data for the first time. If the canonical cross‐correlation between vector magnetic field perturbations observed at two magnetometer stations exceeds a threshold, they form a network connection. The time lag at which canonical cross‐correlation is maximal determines the direction of propagation or expansion of the structure captured by the network connection. If spatial correlation reflects ionospheric current patterns, network properties can test different models for the evolving substorm current system. We select 86 isolated substorms based on nightside ground station coverage. We find, and obtain the timings for, a consistent picture in which the classic substorm current wedge forms. A current system is seen premidnight following the substorm current wedge westward expansion. Later, there is a weaker signal of eastward expansion. Finally, there is evidence of substorm‐enhanced convection. Plain Language Summary: Space weather makes beautiful auroral displays (the northern and southern lights), but with these come large‐scale electrical currents in the ionosphere, which generate disturbances of magnetic fields on the ground. These are observed by >100 magnetometer stations on the ground, and the challenge is to extract the important information from these many observations and present it as a few key parameters that indicate how severe the ground impact will be. Networks are now a common analysis tool in societal data, where people are linked based on various social relationships. Other examples of networks include the world wide web, where websites are connected via hyperlinks, or maps, where places are linked via roads. We have constructed networks from the magnetometer observations of space weather events (geomagnetic substorms), where magnetometers are linked if there is significant correlation between the observations. There has been considerable debate as to how the ionospheric pattern evolves during a geomagnetic substorm. We are able to use the networks to resolve some of these controversies. Key Points: The first dynamical network analysis of substorm current systems is directed, hence quantifying both formation and expansionBoth the 100+ SuperMAG ground-based magnetometers and Polar VIS are utilized to obtain the full spatiotemporal pattern from isolated substormsWe identified timings of a consistent sequence in which the classic substorm current wedge forms [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Adding an external source under low C/N can significantly improve nitrogen removal efficiency. • N transformation processes were coupled at the functional genes level. • The vertical distribution of the microbial community in CWs was a remarkable discrepancy. • Adding rice husk as a carbon source could be conducive to the complete nitrification process. Abstract The effect of adding rice husk as an electron donor on the genetic and metabolic diversity of denitrifying communities in a long-term flooded constructed wetland (D1) was compared with the control group without external carbon source addition (D2). The underlying molecular mechanisms responsible for nitrate removal were quantified under different nitrate loading rates. The results showed that D1 achieved higher and more stable removal efficiencies for NO 3 −-N (90–97%) and total nitrogen (73–87%) under different nitrate loading rates, which were approximately 10 times higher than those of D2. This corresponded with much higher absolute abundances of bacterial and nitrogen functional genes in D1 than D2. Additionally, the vertical distribution of microbial communities in D1 and D2 showed significant differences. This pattern suggested that adding rice husk in flooded CWs had beneficial effects on the denitrifying community. Quantitative response relationships and network analysis indicated that denitrification was the dominant nitrogen removal pathway. Moreover, the present study indicated that using rice husk as an external carbon source could be conducive to completing the nitrification process, which was first confirmed at the molecular level. The present study indicated that using rice husk as an external carbon source can significantly enhance denitrification rates and thus improve nitrogen removal in CWs for wastewater treatment process. [ABSTRACT FROM AUTHOR]

Abstract Cities have gained prominence in global sustainability discourses. The United Nations '2030 Agenda' highlights in at least four key agreements the need to engage local stakeholders as key partners for the implementation of global policy objectives. As a result, the rise of a 'cities agenda' has led not only to an increased role for cities in global politics but also to a reshaping of the knowledge-base underpinning international agreements and their implementation. This paper argues that the contemporary willingness to move beyond the "territorial trap" of modern geopolitics, by emphasizing cities' agency in global affairs and by calling for the production of globally comparable urban data, induces a process of reframing and rescaling existing understandings of the global. In that sense, the question of urban knowledge production – especially that of urban data creation – is an essentially geopolitical one. However, insights from critical geopolitics have been rarely used in current debates on global urban policy and urban data politics. This work, we posit, can inform current academic and policy discussions, as it invites us to explore three interrelated questions: how is the urban being written into contemporary global politics? What type of 'urban' issues are made salient/invisible in that process? Which geopolitical actors are currently dominating the production of urban knowledge globally? This paper offers to start addressing those themes, through the study of 28 global urban databases, digging into the technical as well as human components of those. In doing so, we offer a preliminary assessment of techno-political apparatus that underpins the construction of a global 'urban gaze' which in turn shapes - as much as it is maintained by - global urban policy frameworks and hegemonic forms of knowledge production. [ABSTRACT FROM AUTHOR]

Background and aims: Biocrust morphology is often used to infer ecological function, but morphologies vary widely in pigmentation and thickness. Little is known about the links between biocrust morphology and the composition of constituent microbial community. This study aimed to examine these links using dryland crusts varying in stage and morphology.Methods: We compared the microbial composition of three biocrust developmental stages (Early, Mid, Late) with bare soil (Bare) using high Miseq Illumina sequencing. We used standard diversity measures and network analysis to explore how microbe-microbe associations changed with biocrust stage.Results: Biocrust richness and diversity increased with increasing stage, and there were marked differences in the microbial signatures among stages. Bare and Late stages were dominated by Alphaproteobacteria, but Cyanobacteria was the dominant phylum in Early and Mid stages. The greatest differences in microbial taxa were between Bare and Late stages. Network analysis indicated highly-connected hubs indicative of small networks.Conclusions: Our results indicate that readily discernible biocrust features may be good indicators of microbial composition and structure. These findings are important for land managers seeking to use biocrusts as indicators of ecosystem health and function. Treating biocrusts as a single unit without considering crust stage is likely to provide misleading information on their functional roles. [ABSTRACT FROM AUTHOR]

This paper examines the position of the ‘interlocking network model’ for studying world-city networks in the context of an increasingly diverse literature on cities in globalization. The argument builds on the position that although world-city network analysis deals with a very specific process both functionally and temporally, it can nonetheless be interpreted as a particular example of a generic practice of inter-city relations. Conceptually, this is achieved through discussions about the notion of ‘central flow theory’ and the position of the model in quantitative research on city networks. Empirically, this achieved through a comparison of connectivities of cities created by producer services firms, non-governmental organizations, maritime-producer services firms and global media firms. These multiple analyses represent a decomposition of the current global expression of central flow theory, and examining parallels and differences between these networks allows the stress testing of the model’s more generic potential for assessing the increased salience of flows for cities across the world economy. Drawing on the observation that various cities are placed ‘on and off the map’ in relation to their specific interlocking to the world economy, we engage with two important critiques of the relevance of this research for understanding cities in globalization, i.e., the post-colonial critique formulated by Jennifer Robinson in 2002 and a denunciation for missing out the state by Göran Therborn in 2011. The paper concludes with a discussion of the ways in which our conceptual modelling and results might begin to be theoretically integrated into a wider theoretical framework centred on ‘central flow theory’. [ABSTRACT FROM AUTHOR]

Given different types of constraints on human life, people must make decisions that satisfy social activity needs. Minimizing costs (i.e. distance, time, or money) associated with travel plays an important role in perceived and realized social quality of life. Identifying optimal interaction locations on road networks when there are multiple moving objects (MMO) with space-time constraints remains a challenge. In this research, we formalize the problem of finding dynamic ideal interaction locations for MMO as a spatial optimization model and introduce a context-based geoprocessing heuristic framework to address this problem. As a proof of concept, a case study involving identification of a meetup location for multiple people under traffic conditions is used to validate the proposed geoprocessing framework. Five heuristic methods with regard to efficient shortest-path search space have been tested. We find that the R* tree-based algorithm performs the best with high quality solutions and low computation time. This framework is implemented in a geographic information systems environment to facilitate integration with external geographic contextual information, e.g. temporary road barriers, points of interest, and real-time traffic information, when dynamically searching for ideal meetup sites. The proposed method can be applied in trip planning, carpooling services, collaborative interaction, and logistics management. [ABSTRACT FROM AUTHOR]

Although Earth’s surface parameters obtained from satellite data have become more and more precise, it is still difficult to guarantee temporal consistency and spatial continuity for large-scale geoscience phenomena. Developing new Earth observation platforms is a feasible way to improve the consistency and continuity of such data. As the planet’s only natural satellite, the Moon has special advantages as a platform for observing Earth, including long lifetime, whole disk view, tectonic stability and unique perspective. After presenting the observation geometry constructed by using the ephemeris, this paper mainly discusses the characteristics of a lunar platform and the proper Moon-based sensors, as well as the scientific objectives of Moon-based Earth observation. Solid Earth dynamics, the energy budget of Earth, Earth’s environmental elements and the Earth-space environment are four potential applications analysed in this paper. [ABSTRACT FROM AUTHOR]

Matching multi-scale road networks in the same area is the first step in merging two road networks or updating one based upon the other. The quality of the merge or update depends greatly on the matching accuracy of the two road networks. We propose an improved probabilistic relaxation method, considering both local and global optimizations for matching multi-scale of road networks. The aim is to achieve local optimization, as well as to address the identification of the M:N matching pattern by means of inserting virtual nodes to achieve global optimization effects. Then, by adding two attribute-related evaluation indicators, we developed four evaluation indicators to evaluate the matching accuracy, considering both geographic and attribute information. This paper also provides instructions on how to identify the proper buffer threshold during matching procedures. Extensive experiments were conducted to compare the proposed method with the traditional approach. The results indicate that: (1) the overall matching accuracy of each evaluation indicator exceeds 90%; (2) the overall matching accuracy increases by 6-12% after an M:N matching pattern is added, and by 4-6% following the addition of topology indicators; and (3) the proper buffer threshold is about twice the average value of the closest distance from all nodes. [ABSTRACT FROM AUTHOR]

A site in Oak Ridge, TN, USA, has sediments that contain >3% iron oxides and is contaminated with uranium (U). The U(VI) was bioreduced to U(IV) and immobilized in situ through intermittent injections of ethanol. It then was allowed to reoxidize via the invasion of low-pH (3.6 to 4.0), high-nitrate (up to 200 mM) groundwater back into the reduced zone for 1,383 days. To examine the biogeochemical response, high-throughput sequencing and network analysis were applied to characterize bacterial population shifts, as well as cooccurrence and coexclusion patterns among microbial communities. A paired t test indicated no significant changes of α-diversity for the bioactive wells. However, both nonmetric multidimensional scaling and analysis of similarity confirmed a significant distinction in the overall composition of the bacterial communities between the bioreduced and the reoxidized sediments. The top 20 major genera accounted for >70% of the cumulative contribution to the dissimilarity in the bacterial communities before and after the groundwater invasion. Castellaniella had the largest dissimilarity contribution (17.7%). For the bioactive wells, the abundance of the U(VI)-reducing genera Geothrix, Desulfovibrio, Ferribacterium, and Geobacter decreased significantly, whereas the denitrifying Acidovorax abundance increased significantly after groundwater invasion. Additionally, seven genera, i.e., Castellaniella, Ignavibacterium, Simplicispira, Rhizomicrobium, Acidobacteria Gp1, Acidobacteria Gp14, and Acidobacteria Gp23, were significant indicators of bioactive wells in the reoxidation stage. Canonical correspondence analysis indicated that nitrate, manganese, and pH affected mostly the U(VI)-reducing genera and indicator genera. Cooccurrence patterns among microbial taxa suggested the presence of taxa sharing similar ecological niches or mutualism/commensalism/synergism interactions. [ABSTRACT FROM AUTHOR]

Agricultural soils with (M+) or without (M−) organic amendment were collected from four long-term field experiments to investigate soil fungal community composition and its relationship to the soil ionome by employing both the sequencing of fungal internal transcription spacer (ITS) fragments and inductively coupled plasma mass spectrometry (ICP-MS). Fungal community composition was primarily impacted by physical location while organic amendment triggered community shifts in the same direction in all four sites. Overall, the fungal community was strongly correlated to soil pH that, conversely, impacted soil ion availability. Fungal community dissimilarity was strongly correlated to soil ionome (ionic profile) variability. Network analysis has been conducted to explore the biotic interactions in soil ecosystem, in which species (nodes) are connected by pairwise interactions (links). The results revealed that organic amendment led to a higher number of correlated nodes to soil ions, links, modules (a group of nodes more densely connected to each other than to nodes outside the group), and positive links within and between modules. Moreover, specific fungal modules were independently correlated with soil ions, suggesting that each module represents a functional guild or collection of similar fungal ecotypes. Module size (number of nodes in a module) exhibited no apparent influence on the scale of these correlations. The increase in cooperative/synergistic interactions with organic amendment suggests that application results in a better-organized and more efficient community with enhanced potential soil fungal interactions mediated by alterations in the soil ionome. Overall, this study indicates that these less commonly measured soil ions play an important role and may be used to reveal previously undetermined drivers of the soil microbial community. [ABSTRACT FROM AUTHOR]

The paper employs measures and tools from complex network analysis to enhance the understanding and interpretation of structural characteristics pertaining to the Global Value Chains (GVCs) during the period 1995–2011. The analysis involves the country, sector and country-sector value chain networks to identify main drivers of structural change. The results indicate significant intertemporal changes, mirroring the increased globalization in terms of network size, strength and connectivity. They also demonstrate higher clustering and increased concentration of the most influential countries and country-sectors relative to all others in the GVC network, with the geographical dimension to prevail over the sectoral dimension in the formation of value chains. The regionalization and less hierarchical organization drive country-sector production sharing, while the sectoral value chain network has become more integrated and more competitive over time. The findings suggest that the impact of country-sector policies and/or shocks may vary with the own-group and network-wide influence of each country, take place in multiple geographical scales, as GVCs have a block structure, and involve time dynamics. [ABSTRACT FROM AUTHOR]

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network "in"-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger inweighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables. [ABSTRACT FROM AUTHOR]

Modeling water resources networks is often input-intensive because of network size and complexity. This paper introduces a ranking automation for networks (RANK) tool that weights node connections based on flow capacity and direction and that automates the process to rank nodes that are stable, topologically significant, and redundant. Application to the 55-node, 73-link lower Bear River water system that stretches from southern Idaho to the Great Salt Lake, Utah shows that stable nodes do not depend on other nodes and are typically middle junctions; unstable nodes are located downstream. The most topologically significant nodes make other nodes unstable when added or removed, and they occur throughout the network. The most redundant node pairs have few but identical connections. Results can help water system modelers and planners identify and prioritize locations to (1) transfer water; (2) build, expand, remove, or abandon plans for dams; (3) adopt conservation measures; (4) develop alternative supplies; (5) monitor flows; and (6) protect environmental features. Network spatial resolution, link direction, and data used to weight links influence RANK results. [ABSTRACT FROM AUTHOR]

The impact of connectivity in past societies has long been a focus of archaeological studies. Well-established approaches have been developed over the years to understand emergent connections and entanglement between distant communities, including world system, culture contact, post-colonial theories and network analyses. Our understanding of connectivity remains partial, however, because researchers have focussed on the establishment and consequences of contact and largely ignored the dynamics that often led to its interruption. Yet these processes of 'disentanglement' are just as complex and far-reaching as their converse and need to be understood in their own right. This paper shows that a thorough analysis of disentanglement processes can contribute to our understanding of the very nature of the interrupted contacts, as well as shed light on the social dynamics that engender long-term changes in contact patterns. The concept of disentanglement is discussed in the light of current theories of connectivity and explored through regional case studies in Late Bronze Age Italy (Salento) and Greece (Achaea). [ABSTRACT FROM AUTHOR]

We address the Thrust Network Analysis (TNA), i.e. the methodology for modeling masonry vaults as a discrete network of forces in equilibrium with gravitational loads, first contributed by O’Dwyer and fully developed by Block and coworkers. Reducing the bias by the quoted authors in favor of a graphical interpretation of the method, we reformulate the original version of the TNA by discarding the dual grid and focusing only on the primal grid, thus significantly enhancing the computational performances. The proposed reformulation of the TNA is also extended by including horizontal forces in the analysis as well as holes or free edges in the vault. Furthermore, the coefficient matrices entering the solution scheme are obtained by assembling the separate contribution of each branch, thus avoiding the ad hoc node numbering and branch orientation required by alternative implementations. Numerical examples, some of which referred to vaults having a particularly complex geometry, show the effectiveness and robustness of the proposed approach in assessing the safety conditions of existing masonry vaults or in designing new ones. [ABSTRACT FROM AUTHOR]

Stream ordering is a technique for characterizing the constituent parts of a drainage network. Network analysis remains one of the most popular and persistent research and application areas in geographic information science. In this study, a new stream ordering approach based on geographic information systems tools and network analysis operations is proposed. The new method combines the concepts of modern network analysis operations, which mainly deal with derivations of the best route solution, and the previous stream ordering techniques. In this context, the method readily identifies the channel heads hierarchically in order to derive main stream channel and its tributaries, and assigns a unique order for each stream on the network. [ABSTRACT FROM AUTHOR]

Various indicators rooted in the concepts of information and entropy have been proposed to be used for ecological network analysis. They are theoretically well grounded and widely used in the literature, but have always been difficult to interpret due to an apparent lack of strict relations with node and link weight. We generated several sets of 10,000 networks in order to explore such relations and work towards a sounder interpretation. The indices we explored are based on network composition (i.e., type and importance of network compartments), or network flows (i.e., type and importance of flows among compartments), including Structural Information (SI), Total System Throughput (TST), Average Mutual Information (AMI), Flow Diversity (H), and Ascendency (ASC). A correlation analysis revealed a lack of strict relationships among the responses of the investigated indicators within the simulated space of variability of the networks. However, fairly coherent patterns of response were revealed when networks were sorted by following a “bottom-up” criterion, i.e. by increasing the dominance of the large-sized top predator in the network. This ranking is reminiscent of ecosystem succession, along which the prominence of higher trophic level organisms progressively increases. In particular, the results show that a simple increase in organisms having large size and low consumption rates is potentially able to simultaneously lead to an increase of different types of information (as SI, H and AMI), thus also emphasizing the importance of bionomic traits related to body size in affecting information-related properties in a trophically connected community. The observed trends suffer from a certain dispersion of data, which was diminished by imposing specific and ecologically meaningful constraints, such as mass balancing and restriction to certain range of the ratio A/C, an index related to the viability of ecological networks. These results suggest that the identification of a set of effective constraints may help to identify improved conditions for applicability of the investigated flow-based indicators, and also provide indication on how to normalise them with respect to meaningful network properties or reference states. Thus, in order to increase confidence in the derived network metrics describing a particular ecosystem state, and thus increase their applicability, it is advisable to construct replicate networks by taking the variability of input data into account, and by applying uncertainty and sensitivity analyses. [ABSTRACT FROM AUTHOR]

The article presents the results of research aimed at defining the potential effectiveness of fire services in the city space. The spatial scope of the analysis comprised the city of Łódź and a 20-kilometre ring around it, which was introduced in order to avoid an artificial barrier in the form of a city boundary. The study comprised all fire departments located within this area as well as individual elements of its built environment, which may be subjected to or otherwise pertinent to interventions of fire fighters. The use of the ArcMap Network Analyst tool and the 2SFCA method allowed us to specify time accessibility of fire service operations; spatial accessibility of individual elements of the city infrastructure to fire service activities; the load of individual fire stations; and the minimum number of departments necessary to take action within the assumed, defined arrival time for intervention. [ABSTRACT FROM AUTHOR]

This work aims to show the trophic structure of a real plankton community from Angra dos Reis estuary using in situ flow cytometry for data acquisition, and how competition, as a non-trophic interaction, is structured amid the trophic interactions – predation and herbivory. As no previous information is given, a great research challenge is how to mathematically represent such relations and their interaction strengths. For this purpose, such data were modeled by a fuzzy complex network through a multigraph view. To reduce its complexity, an ant colony algorithm was employed to detect its substructures called communities or compartiments. These approaches have allowed the discrimination and the quantification of relevant linkages and process, search into topological characteristics as triangles or loop distribution to the node degrees, and access the number of communities within network. Futhermore, it was considered the distribution of organisms acording to their sizes and ecological roles. Comparisons with other network indices and patterns found in the literature and in nature, respectively, indicate that our approach is adequate. [ABSTRACT FROM AUTHOR]

Indonesia has endorsed spatial planning law and introduced "strategic areas" to promote development in lagging region. One of the regency that has strategic values (areas) is Sambas regency. This paper attempts to explore the "overlap" interaction in the perspective of the network between strategic areas. As a part of an ongoing study, we explore the resident social activity movement and the medium to support it (road) by applying urban network analysis. From findings, there are two different main orientations on each strategic area. Based on the orientation, it is necessary to improve "the potency" of interaction among strategic areas by increasing their interaction and create multiple choices (plans) and allowing partial transfer to other areas. A direct interaction between strategic areas is the best solutions. However, as one of the considerations, the connection to other areas (in-between the strategic areas) can be also applied to provide and share benefits to certain areas. [ABSTRACT FROM AUTHOR]

The resilience literature often assumes that social-ecological reorganization will result in either the removal of deficient system elements (components, interactions) or social learning. Major perturbations are expected to lead to either adaptation or, if accompanied by a regime shift, transformation. This has led to a conflation of the concepts of resilience and adaptation, which has in turn made it difficult to quantitatively distinguish between cases in which a system returned to a previous state, and adaptation or learning occurred, and cases in which the system was resilient but adaptation or learning did not occur., We used a network analysis of nine years of ostrich movement data to explore the social-ecological resilience of the Western Cape ostrich industry, which nearly collapsed following an outbreak of highly pathogenic avian influenza in 2011 and has gradually rebuilt., The system that emerged following the outbreak contained fewer farms but was more connected than at any period prior to the outbreak. As system reorganization proceeded, network traits began to fluctuate seasonally and to approach values similar to those observed prior to the outbreak. It was estimated that it would take 4-5 full seasonal cycles for the system to return to a similar state to that prior to the disease outbreak. In other words, although the system reorganized following the system collapse, it remained within the same regime and showed no obvious evidence of adaptation or learning., Policy implications. The majority of previous work on studying system response to disturbance has focused on outcome-based adaptation and learning. This study highlights the need to understand systems that respond to disturbance without learning or adaptation. Network analysis offers a useful quantitative tool for exploring social-ecological resilience and tracking changes in vulnerability. However, the development of better ways of incorporating additional data from multiple scales into network analysis remains an important priority for improving the predictive power and policy relevance of network approaches to analysing resilience. [ABSTRACT FROM AUTHOR]

Aim To study the relationships between Uruguay and neighbouring geographical areas based on distributions of Ephemeroptera species (mayflies: an ancient order of aquatic insects). We wanted to evaluate whether Uruguay more closely represents (1) the southern limit of the tropical (Paranense and Amazonian) fauna or (2) the northern limit of the temperate (Pampean-Bonaerense) fauna. Location South America with an emphasis on Uruguay. Methods We compiled more than 5000 collection records of mayfly species throughout South America and evaluated these using current taxonomy and geographical validity. We used the Network Analysis Method ( NAM) on these data to identify units of co-occurrence ( UCs: mutually exclusive groups of co-distributed species, with each group connected through strong links of sympatry and disconnected from the others). We focused solely on those UCs that included Uruguay in their spatial ranges and used these to infer the vicinity relationships. Results We recovered four UCs consisting of many species that link Uruguay with tropical areas of Brazil and NE Argentina. These groups followed a geographically nested pattern. The results contradict the previously held view that the Uruguayan fauna holds strong affinities to that of temperate grasslands that lie to the south in central oriental Argentina (i.e. the currently accepted concept of Pampas). A comparison of the genera known from Uruguay and Buenos Aires Province further reinforces the distinction between Uruguay and temperate areas to the south. Main conclusions The hypothesis that Uruguay represents the southern limit of tropical affinities is strongly supported by mayfly distributions, indicating that a reappraisal of the Pampas as a cohesive biogeographical province is needed. We suggest that Uruguay and Buenos Aires should belong to different provinces, the former aligned with tropical provinces and the latter aligned with more temperate areas. [ABSTRACT FROM AUTHOR]

Ectomycorrhizal ( EM) fungi are ubiquitous in temperate and boreal forests, comprising over 20,000 species forming root symbiotic associations with Pinaceae and woody angiosperms. As much as 100 different EM fungal species can coexist and interact with the same tree species, forming complex multispecies networks in soils. The degree of host specificity and structural properties of these interaction networks (e.g., nestedness and modularity) may influence plant and fungal community assembly and species coexistence, yet their structure has been little studied in northern coniferous forests, where trees depend on EM fungi for nutrient acquisition. We used high-throughput sequencing to characterize the composition and diversity of bulk soil and root-associated fungal communities in four co-occurring Pinaceae in a relic foredune plain located at Îles de la Madeleine, Québec, Canada. We found high EM fungal richness across the four hosts, with a total of 200 EM operational taxonomic units ( OTUs), mainly belonging to the Agaricomycetes. Network analysis revealed an antinested pattern in both bulk soil and roots EM fungal communities. However, there was no detectable modularity (i.e., subgroups of interacting species) in the interaction networks, indicating a low level of specificity in these EM associations. In addition, there were no differences in EM fungal OTU richness or community structure among the four tree species. Limited shared resources and competitive exclusion typically restrict the number of taxa coexisting within the same niche. As such, our finding of high EM fungal richness and low host specificity highlights the need for further studies to determine the mechanisms enabling such a large number of EM fungal species to coexist locally on the same hosts. [ABSTRACT FROM AUTHOR]

Aim We sought to reconstruct the biogeographical structure and dynamics of a hyperdiverse ant genus, Pheidole, and to test several predictions of the taxon cycle hypothesis. Using large datasets on Pheidole geographical distributions and phylogeny, we (1) inferred patterns of biogeographical modularity (clusters of areas with similar faunal composition), (2) tested whether species in open habitats are more likely to be expanding their range beyond module boundaries, and (3) tested whether there is a bias of lineage flow from high- to low-diversity areas. Location The Old World. Methods We compiled and jointly analysed a comprehensive database of Pheidole geographical distributions, the ecological affinities of different species, and a multilocus phylogeny of the Old World radiation. We used network modularity methods to infer biogeographical structure in the genus and comparative methods to evaluate the hypotheses. Results The network analysis identified eight biogeographical modules, and a suite of species with anomalous ranges that are statistically more likely to occur in open habitat, supporting the hypothesis that open habitats promote range expansion. Phylogenetic analysis shows evidence for a cascade pattern of colonization from Asia to New Guinea to the Pacific, but no 'upstream' colonization in the reverse direction. Main conclusions The distributions of Pheidole lineages in the Old World are highly modular, with modules generally corresponding to biogeographical regions inferred in other groups of organisms. However, some lineages have expanded their ranges across module boundaries, and these species are more likely to be adapted to open habitats rather than interior forest. In addition, there is a cascade pattern of dispersal from higher to lower diversity areas during these range expansions. Our findings are consistent with the taxon cycle hypothesis, although they do not rule out alternative interpretations. [ABSTRACT FROM AUTHOR]

In a recent editorial, Whittaker (2014, Journal of Biogeography, 41, 1-5) suggested that biogeography is in the process of adopting a 'big science' model, characterized by increasing levels of individual specialization and international collaboration. Using network analysis based on co-authored articles and bibliometrics, we trace this transformation, identifying where biogeographical knowledge is produced and how the global biogeography community is connected. Our data reveal dramatic increases in biogeographical research over the last 30 years, with a trend of increasing diversity of countries and institutions. Moreover, an analysis of keywords suggests that the widening availability of molecular phylogenies and the ubiquitous threat of climate change are increasingly driving biogeographical research agendas. These trends are associated with diverse social and technological forces, notably advances in communication technology and the increasing availability and quality of biogeographical data. [ABSTRACT FROM AUTHOR]

In 1942, after a series of directives from General MacArthur's Headquarters, the Allied Geographical Section (AGS) was formed with the task of compiling all the available geographical intelligence on the largely unmapped and underexplored south-west Pacific area. During its lifespan (1942-45), the AGS produced 3 major types of publications: Terrain Studies; Special Reports; and Terrain Handbooks. The Terrain Studies were the most important and complex works, designed to give the most comprehensive information. Thus, they contained text, diagrams, photographs and various sized and coloured maps. In 2012, Monash University Library initiated a project to digitise its substantial collection of Terrain Studies and make them available via the Monash University Research Repository (http://arrow.monash.edu) to complement its online collections for the ANZAC Centenary. This paper explores a number of aspects of the project: its genesis; challenges, given the format of the material; the scanning process; metadata creation and changing geography (role of gazetteers); how it complements existing WWI exhibits; and methods of access. [ABSTRACT FROM AUTHOR]

This study proposes a method for evaluating shelter plan for emergency evacuation prior to a tsunami based on service area analysis. The evacuation service areas are generated using both spatial and network analysis based on Geographic Information System (GIS). A case study in Pacitan city, East Java Province, Indonesia which is located in the South coastal area of Java Island, is picked as study area. The field has a possibility of suffering tsunami disaster because of the movement of Indo-Australian plate and Eurasian plate. The simulation result shows that the current evacuation shelters arranged by local government are not easy to access if tsunami occurs. About 50% of the residents do not have enough time to evacuate to the shelters because many shelters are located far from residential area. Utilizing public buildings around residential area for temporary shelters proposed in this study, about 96% residents in inundation area have sufficient time to evacuate to the shelters. [ABSTRACT FROM AUTHOR]

This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two-thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power-law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling. [ABSTRACT FROM AUTHOR]

Central Business District (CBD) is the core area of urban planning and decision management. The cartographic definition and representation of CBD is of great significance in studying the urban development and its functions. In order to facilitate these processes, the Kernel Density Estimation (KDE) is a very efficient tool as it considers the decay impact of services and allows the enrichment of the information from a very simple input scatter plot to a smooth output density surface. However, most existing methods of density analysis consider geographic events in a homogeneous and isotropic space under Euclidean space representation. Considering the case that the physical movement in the urban environment is usually constrained by a street network, we propose a different method for the delimitation of CBD with network configurations. First, starting from the locations of central activities, a concentration index is presented to visualize the functional urban environment by means of a density surface, which is refined with network distances rather than Euclidean ones. Then considering the specialties of network distance computation problem, an efficient way supported by flow extension simulation is proposed. Taking Shenzhen and Guangzhou, two quite developed cities in China as two case studies, we demonstrate the easy implementation and practicability of our method in delineating CBD. [ABSTRACT FROM AUTHOR]

In an emergency situation shelter space is crucial for people affected by natural hazards. Emergency planners in disaster relief and mass care can greatly benefit from a sound methodology that identifies suitable shelter areas and sites where shelter services need to be improved. A methodology to rank suitability of open spaces for contingency planning and placement of shelter in the immediate aftermath of a disaster is introduced. The Open Space Suitability Index uses the combination of two different measures: a qualitative evaluation criterion for the suitability and manageability of open spaces to be used as shelter sites and another quantitative criterion using a capacitated accessibility analysis based on network analysis. For the qualitative assessment implementation issues, environmental considerations and basic utility supply are the main categories to rank candidate shelter sites. A geographic information system is used to reveal spatial patterns of shelter demand. Advantages and limitations of this method are discussed on the basis of an earthquake hazard case study in the Kathmandu Metropolitan City. According to the results, out of 410 open spaces under investigation, 12.2%have to be considered not suitable (Category D and E) while 10.7% are Category A and 17.6% are Category B. Almost two-thirds (59.55%) are fairly suitable (Category C). [ABSTRACT FROM AUTHOR]

Drawing on the 'local buzz and global pipeline' perspective on the geographies of production in knowledge-intensive industries, our analysis associates observed network patterns with exogenous city characteristics (e.g., GDP and population) and endogenous local network structures (e.g., 'star' network structures) through exponential random graph models ( ERGMs). Our analysis contributes to the quantitative analysis of urban systems and locational strategies of producer service firms, as we: ( i) perform a direct two-mode network analysis of intercity corporate networks; ( ii) explore the association between macro network patterns and local formation processes; and ( iii) identify regional dynamics in network formation. [ABSTRACT FROM AUTHOR]

An effective governance of protected areas should include not only the involvement of the different institutional actors but also the local community as a whole, through a participatory approach that ensures the effective involvement in the management process and decision-making. Through the examination of a case study represented by the natural reserve "Sambughetti Campanito" in Sicily (Italy), we evaluated how the local community perceives the presence of a protected area within its territory, and how it feels involved in its governance process. The results obtained showed that the local community welcomes the presence of a protected area within its territory. However, some problems arise relating to the insufficient degree of involvement in the management process and decision-making and scarce role that, with few exceptions, is attributed to public and private entities involved in various capacities in the management of the aforesaid protected area. Overcoming these issues is a prerequisite to ensure sharing and transparency in the governance of protected areas whose benefits fall on the territory and the community in which it lives and works. [ABSTRACT FROM AUTHOR]

Determining network path is important for different purposes such as determination of road traffic, the average speed of vehicles, and other network analysis. One of the required input data is information about network path. Nevertheless, the data collected by the positioning systems often lead to the discrete points. Conversion of these points to the network path have become one of the challenges which different researchers, presents many ways for solving it. This study aims at investigating geometry-based methods to estimate the network paths from the obtained points and improve an existing point to curve method. To this end, some geometry-based methods have been studied and an improved method has been proposed by applying conditions on the best method after describing and illustrating weaknesses of them. [ABSTRACT FROM AUTHOR]

Archaeological network analysts often represent archaeological data as static networks and explore their structure. However, most networks changed through time and static network representations do not allow archaeologists to test assumptions about the dynamic processes driving this change. The study of visibility networks in archaeology is a good example of this. Archaeologists propose hypotheses of the role of lines of sight between settlements, which imply dynamic processes for the establishment of the observed visibility networks. However, commonly used methods do not allow us to evaluate these hypotheses. In this paper we introduce exponential random graph modelling (ERGM) as a method for bridging static and dynamic approaches to interpreting visibility networks. This method offers a number of advantages: (1) it explicitly addresses the assumptions inherent in visibility network creation about what relationships between nodes mean and the types of processes they allow for; (2) it allows one to investigate the range of network structures that these assumptions give rise to; and (3) it explores the dynamic processes that might have led to observed networks. This method is used to evaluate hypotheses of the role of lines of sight in facilitating visual control and communication during the later Iron Age in Southern Spain. This study shows that ERGMs can be used as a reflective technique to evaluate competing hypotheses, and that ERGM results subsequently require more contextualised evaluation. Future work on ERGMs should focus on incorporating geographical constraints to further enhance its potential for studying visibility networks. [ABSTRACT FROM AUTHOR]

The Mackenzie Basin in northwestern Canada is a high-latitude region, with one of the largest watersheds in the world. The Mackenzie great lakes, consisting of Great Bear Lake, Great Slave Lake and Lake Athabasca form the large lake complex. The human presence in the area is small in terms of population and industry and thus these ecosystems remain comparatively pristine and show no major changes in the fish communities. Ecopath with Ecosim (EwE), the most important and most used ecosystem trophic network modelling tool to study the ecosystem-level responses to changes, and information available in the scientific literature together with traditional knowledge about Great Slave Lake and Great Bear Lake was used to elucidate the ecosystem attributes. Our models give a cohesive view of these two ecosystems that will allow researchers and decision makers to explore questions regarding the stability of fisheries and future ecological change. The moderate trophic level of fish catch along with the small percentage of primary production required to sustain fisheries in both lakes demonstrated that fisheries were sustainable during the time period modelled. The ecosystem indices and attributes of the comparatively pristine Mackenzie great lakes were compared with those of two Laurentian Great Lakes having similar types of Ecopath ecosystem models. The metrics utilized to assess comparatively the ecosystem's maturity, stability and health indicated a decline in ecosystem maturity and stability from pristine Great Bear Lake to transitioning Lake Ontario. [ABSTRACT FROM AUTHOR]

Abstract: The goal of this work is to understand the structure and characteristics of technological knowledge flows between countries, institutions, and technology fields in the field of organic photovoltaic cells. This study was conducted in three stages: data collection, network creation, and network analysis. For network analysis, network visualization, network topological analysis, and node centrality analysis were performed in sequence. The network topological analysis revealed that all three citation networks, i.e., countries, institutions, and technology fields, are scale-free networks that follow the power law and display, to a greater or lesser extent, a more efficient knowledge transfer capability than a random network of the same size. The node centrality analysis showed that the United States, Japan, and Germany are the most important citation centers in the country citation network, while Boeing, Konarka Technologies, Eastman Kodak, and Sharp are the most important in the institution citation network, and the U.S. patent classification (USPC) classes of 136, 257, and 428 are the most important in the technology field citation network, each playing critical roles in each the network as core nodes. In this study, we applied various concepts of centrality to the analysis of individual nodes and found that the results from the network topological analysis and the node centrality analysis are not significantly different. The proposed analysis framework in this paper is applicable to different science and technology domains. [Copyright &y& Elsevier]

Highlights: [•] We modeled 3 coastal lagoons with distinctive salinities and ranges of variation. [•] We examined differences in functional properties of ecosystems using ECOPATH. [•] In winter, high salinity lagoons are plant-limited and more dependent on detritus. [•] Seasonal differences are lower at low salinity, suggesting more stable functioning. [•] Submersed plants may help to counteract nutrients' effects on phytoplankton growth. [Copyright &y& Elsevier]

One of the features of Geographic Information Systems is related to optimal paths searches. This kind of functionality is implemented on models that do not guarantee scalability and efficiency when networks are large. This article proposes a model for network representation in Geographic Information Systems. It is based on the concept of reduced graph. This model allows efficient and scalable optimal path searches in large networks. A relevant feature of the proposed model is the capability to perform scale analysis on the network. [ABSTRACT FROM AUTHOR]

The purpose of this work is to determine whether spatial modeling can be used to model the spread of the Black Death. The study is limited to models for the propagation of the disease in Sweden in 1350. Geographic data of Swedish water bodies and medieval road networks, historical data on the population in Swedish parishes, including their medieval boundaries, along with historical notes and disease characteristics, were used to build alternative models for spatial distribution. Three different models are presented: one radial, one cost-based and one combining network analysis and radial propagation. Simulations were made to depict different scenarios on the spread of the disease, as well as the drastic changes in the overall population of Sweden, over a couple of hundred years. For purpose of validation the population decrease estimated in each parish is compared with independent historical documents. Results from model scenarios are visualized in maps of propagation, animated video sequences and a web map service. Our analyses clearly demonstrate the power of spatial analysis and geographic information systems to describe, model and visualize epidemiologic processes in space and time. [ABSTRACT FROM AUTHOR]