scholarly journals Revealing biases in the sampling of ecological interaction networks

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7566 ◽  
Author(s):  
Marcus A.M. de Aguiar ◽  
Erica A. Newman ◽  
Mathias M. Pires ◽  
Justin D. Yeakel ◽  
Carl Boettiger ◽  
...  
Keyword(s):  
Large Scale ◽  
Sampling Design ◽  
Species Interaction ◽  
Ecological Networks ◽  
Interaction Networks ◽  
Sampling Effort ◽  
Large Species ◽  
Ecological Interactions ◽  
Underlying Network ◽  
High Degree

The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases with respect to both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These ecological and statistical issues directly affect ecologists’ abilities to accurately construct ecological networks. However, statistical biases introduced by sampling are difficult to quantify in the absence of full knowledge of the underlying ecological network’s structure. To explore properties of large-scale ecological networks, we developed the software EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different mathematical sampling designs that correspond to methods used in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties depends strongly both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, modules with nested structure were the easiest to detect, regardless of the sampling design used. Sampling a network starting with any species that had a high degree (e.g., abundant generalist species) was consistently found to be the most accurate strategy to estimate network structure. Because high-degree species tend to be generalists, abundant in natural communities relative to specialists, and connected to each other, sampling by degree may therefore be common but unintentional in empirical sampling of networks. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. To reduce biases introduced by sampling methods, we recommend that these findings be incorporated into field design considerations for projects aiming to characterize large species interaction networks.

scholarly journals Revealing biases in the sampling of ecological interaction networks

2018 ◽  
Author(s):  
Marcus A. M. de Aguiar ◽  
Erica A. Newman ◽  
Mathias M. Pires ◽  
Justin D. Yeakel ◽  
David H. Hembry ◽  
...  
Keyword(s):  
Network Topology ◽  
Large Scale ◽  
Sampling Design ◽  
Sampling Error ◽  
Interaction Networks ◽  
Ecological Interactions ◽  
Modular Networks ◽  
Underlying Network ◽  
Full Knowledge ◽  
Sampling Biases

AbstractThe structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases in both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These issues may affect the accuracy of empirically constructed ecological networks. Yet statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying ecological network’s structure. To explore properties of large-scale modular networks, we developed EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different sampling designs that may be employed in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties accurately depends both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, the modules with nested structure were the easiest to detect, regardless of sampling design. Sampling according to species degree (number of interactions) was consistently found to be the most accurate strategy to estimate network structure. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. We recommend that these findings be incorporated into field sampling design of projects aiming to characterize large species interactions networks to reduce sampling biases.Author SummaryEcological interactions are commonly modeled as interaction networks. Analyses of such networks may be sensitive to sampling biases and detection issues in both the interactors and interactions (nodes and links). Yet, statistical biases introduced by sampling error are difficult to quantify in the absence of full knowledge of the underlying network’s structure. For insight into ecological networks, we developed software EcoNetGen (available in R and Python). These allow the generation and sampling of several types of large-scale modular networks with predetermined topologies, representing a wide variety of communities and types of ecological interactions. Networks can be sampled according to designs employed in field observations. We demonstrate, through first uses of this software, that underlying network topology interacts strongly with empirical sampling design, and that constructing empirical networks by starting with highly connected species may be the give the best representation of the underlying network.

scholarly journals Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiring

2021 ◽  
Author(s):  
Timothée Poisot
Keyword(s):  
Numerical Experiments ◽  
Species Turnover ◽  
Species Interaction ◽  
Relative Effect ◽  
Ecological Networks ◽  
Interaction Networks ◽  
Mathematical Arguments ◽  
Β Diversity ◽  
Fit For Purpose

Despite having established its usefulness in the last ten years, the decomposition of ecological networks in components allowing to measure their β-diversity retains some methodological ambiguities. Notably, how to quantify the relative effect of mechanisms tied to interaction rewiring vs. species turnover has been interpreted differently by different authors. In this contribution, I present mathematical arguments and numerical experiments that should (i) establish that the decomposition of networks as it is currently done is indeed fit for purpose, and (ii) provide guidelines to interpret the values of the components tied to turnover and rewiring.

scholarly journals Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing

BMC Biology ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Amrita Srivathsan ◽  
Emily Hartop ◽  
Jayanthi Puniamoorthy ◽  
Wan Ting Lee ◽  
Sujatha Narayanan Kutty ◽  
...  
Keyword(s):  
Dna Sequences ◽  
Large Scale ◽  
Low Cost ◽  
Small Body ◽  
Small Subset ◽  
Similar Species ◽  
Large Species ◽  
Morphological Examination ◽  
Species Discovery ◽  
Short Period

Abstract Background More than 80% of all animal species remain unknown to science. Most of these species live in the tropics and belong to animal taxa that combine small body size with high specimen abundance and large species richness. For such clades, using morphology for species discovery is slow because large numbers of specimens must be sorted based on detailed microscopic investigations. Fortunately, species discovery could be greatly accelerated if DNA sequences could be used for sorting specimens to species. Morphological verification of such “molecular operational taxonomic units” (mOTUs) could then be based on dissection of a small subset of specimens. However, this approach requires cost-effective and low-tech DNA barcoding techniques because well-equipped, well-funded molecular laboratories are not readily available in many biodiverse countries. Results We here document how MinION sequencing can be used for large-scale species discovery in a specimen- and species-rich taxon like the hyperdiverse fly family Phoridae (Diptera). We sequenced 7059 specimens collected in a single Malaise trap in Kibale National Park, Uganda, over the short period of 8 weeks. We discovered > 650 species which exceeds the number of phorid species currently described for the entire Afrotropical region. The barcodes were obtained using an improved low-cost MinION pipeline that increased the barcoding capacity sevenfold from 500 to 3500 barcodes per flowcell. This was achieved by adopting 1D sequencing, resequencing weak amplicons on a used flowcell, and improving demultiplexing. Comparison with Illumina data revealed that the MinION barcodes were very accurate (99.99% accuracy, 0.46% Ns) and thus yielded very similar species units (match ratio 0.991). Morphological examination of 100 mOTUs also confirmed good congruence with morphology (93% of mOTUs; > 99% of specimens) and revealed that 90% of the putative species belong to the neglected, megadiverse genus Megaselia. We demonstrate for one Megaselia species how the molecular data can guide the description of a new species (Megaselia sepsioides sp. nov.). Conclusions We document that one field site in Africa can be home to an estimated 1000 species of phorids and speculate that the Afrotropical diversity could exceed 200,000 species. We furthermore conclude that low-cost MinION sequencers are very suitable for reliable, rapid, and large-scale species discovery in hyperdiverse taxa. MinION sequencing could quickly reveal the extent of the unknown diversity and is especially suitable for biodiverse countries with limited access to capital-intensive sequencing facilities.

The academic profession in Russia’s two capitals: The impact of 20 years of transition

2017 ◽  
Vol 16 (5) ◽  
pp. 626-644 ◽  
Author(s):  
Elizaveta Sivak ◽  
Maria Yudkevich
Keyword(s):  
Large Scale ◽  
Academic Career ◽  
Academic Profession ◽  
University Faculty ◽  
Key Characteristics ◽  
Personal Strain ◽  
High Degree ◽  
The Impact ◽  
Russian Universities

This paper studies the dynamics of key characteristics of the academic profession in Russia based on the analysis of university faculty in the two largest cities in Russia – Moscow and St Petersburg. We use data on Russian university faculty from two large-scale comparative studies of the academic profession (‘The Carnegie Study’ carried out in 1992 in 14 countries, including Russia, and ‘The Changing Academic Profession Study’, 2007–2012, with 19 participating countries and which Russia joined in 2012) to look at how faculty’s characteristics and attitudes toward different aspects of their academic life changed over 20 years (1992–2011) such as faculty’s views on reasons to leave or to stay at a university, on university’s management and the role of faculty in decision making. Using the example of universities in the two largest Russian cities, we demonstrate that the high degree of overall centralization of governance in Russian universities barely changed in 20 years. Our paper provides comparisons of teaching/research preferences and views on statements concerning personal strain associated with work, academic career perspectives, etc., not only in Russian universities between the years 1992 and 2012, but also in Russia and other ‘Changing Academic Profession’ countries.

Research on Moving Target Monitoring Collaborative Simulation Technology Based on Multi-Channel

2010 ◽  
Vol 20-23 ◽  
pp. 700-705
Author(s):  
Tian Yuan ◽  
Shang Guan Wei ◽  
Zhi Zhong Lu
Keyword(s):  
Large Scale ◽  
Target Space ◽  
Laboratory Simulation ◽  
Moving Target ◽  
Simulation Technology ◽  
Collaborative Simulation ◽  
Mobile Target ◽  
Target Monitoring ◽  
Six Degree Of Freedom ◽  
High Degree

Multi-channel Virtual reality simulation technology is a kind of simulation technology, which support the grand scene and high degree of immersion, has better visualization effect. In this paper, a moving target monitoring collaboratory simulation technology based on multi-channel is studied. Firstly, study the mathematical modeling foundation of Multi-Channel technology systematically, based on the mobile target spatial model and co-simulation technology, select the appropriate applications of multi-channel technology, building laboratory simulation platform and achieved a space-based six-degree of freedom simulation of multi-channel moving target monitoring simulation. The experiment has proved that in multi-channel target monitoring co-simulation technology used in this paper has strong practicality, combine with a moving target-space model and co-simulation technology, the advantages of objective observation to solve the requirements like large-scale, realism, immersion requirements, etc.

scholarly journals Uncovering the structure and temporal dynamics of information propagation

2014 ◽  
Vol 2 (1) ◽  
pp. 26-65 ◽  
Author(s):  
MANUEL GOMEZ RODRIGUEZ ◽  
JURE LESKOVEC ◽  
DAVID BALDUZZI ◽  
BERNHARD SCHÖLKOPF
Keyword(s):  
News Media ◽  
Information Diffusion ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Inference Algorithm ◽  
Information Propagation ◽  
Transmission Rates ◽  
Diffusion Dynamics ◽  
Underlying Network ◽  
News Events

AbstractTime plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion—when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on-going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.

Landscape analysis through pictorial transects in degraded lands.

2021 ◽  
Author(s):  
Juan Antonio Campos ◽  
Jaime Villena ◽  
Marta M. Moreno ◽  
Jesús D. Peco ◽  
Mónica Sánchez-Ormeño ◽  
...  
Keyword(s):  
Large Scale ◽  
Fine Particles ◽  
Plant Cover ◽  
Degraded Lands ◽  
Ecological Resources ◽  
Allochthonous Species ◽  
Ecological Patterns ◽  
Good Characterization ◽  
Photosynthetic Potential ◽  
High Degree

<p>Understanding the dynamics of plant populations and their relationship with the characteristics of the terrain (slope, texture, etc.) and with particular phenomena (erosion, pollution, environmental constrains, etc.) that could affect them is crucial in order to manage regeneration and rehabilitation projects in degraded lands. In recent years, the emphasis has been placed on the observation and assessment of microtopographic drivers as they lead to large-scale phenomena. All the ecological variables that affect a given area are interconnected and the success in unraveling the ecological patterns of operation relies on making a good characterization of all the parameters involved.</p><p>It is especially interesting to study the natural colonization processes that take place in Mediterranean areas with a high degree of seasonality, to whose climatic restrictions, the presence of pollutants and various anthropic actions, can be added. Over these degraded areas, we propose using a new tool, what we have come to call "<strong>pictorial transects</strong>", that is, one-dimensional artificial transects built from low-scale photographs (2 m<sup>2</sup>) taken along a line of work (transect) where you can see the points where ecological resources are generated, stored and lost, and their fluctuation throughout time. A derivative of these would be the "<strong>green transects</strong>" in which the green color has been discriminated using the open software Image I. It is an inexpensive, fast and straightforward pictorial method that can be used to research and monitor the spatial and temporal fluctuation of the potential input of resources (organic matter, water, fine particles, etc.) to the ecosystem.</p><p>The information obtained from pictorial transects not only refers to the measurement of the photosynthetic potential per unit area or the location of the critical points (generate, storage or sink of resources) but also makes it possible to monitor the specific composition of the plant cover. For an appropriate use of this methodology, the criteria to determine the direction and length of the different transects must be previously and carefully established according to the objectives proposed in the study. For example: a radial transect in a salty pond will give us information on the changes in the plant cover as we move away from the center and the salinity decreases. In the same pond, a transect parallel to the shore will give us information on those changes that occur in the vegetation that do not depend on the degree of salinity. There are some cases in which this method could be very useful, as in the natural colonization of a degraded mine site or to assess the progression area affected by allochthonous species or weeds in extensive crops.</p>

ON METHODOLOGICAL APPROACHES TO TRAINING FUTURE TEACHERS OF KAZAKHSTAN FOR UPBRINGING WORK

2021 ◽  
Vol 70 (2) ◽  
pp. 14-22
Author(s):  
Zh. KolumbayevaSh. ◽  
Keyword(s):  
Professional Training ◽  
Large Scale ◽  
Educational Process ◽  
Educational Organizations ◽  
Spiritual Renewal ◽  
Future Teachers ◽  
Leading Role ◽  
Public Consciousness ◽  
The University ◽  
High Degree

Globalization, informatization, digitalization, led to large-scale changes that have problematized the modern process of upbringing. The modern practice of upbringing in Kazakhstan is aimed at solving the problem of forming an intellectual nation. The key figure in the upbringing process is the teacher. The modernization of public consciousness taking place in Kazakhstan, the renewal of both the content of education and the system of upbringing require understanding not only the content, but also the methodology of the professional training of teachers for the upbringing of children, for the organization of the upbringing system in educational organizations. We believe that the analysis of traditional and clarification of modern methodological foundations of professional training of future teachers of Kazakhstan for upbringing work will give us the opportunity to develop a strategy for training future teachers in the conditions of spiritual renewal of Kazakhstan's society. The article reveals the experience of Abai KazNPU. As a result of the conducted research, we came to the conclusion that the process of training a teacher in Kazakhstan, who has a high degree of ethnic, cultural, and religious diversity, requires strengthening the upbringing and socializing components of the educational process of the university. The strategy of professional training of a modern teacher should be a polyparadigmatic concept with the leading role of ideas of personality-oriented, competence paradigm.

scholarly journals Vlsi Interconnection Modelling Using a Finite Element Approach

1995 ◽  
Vol 18 (3) ◽  
pp. 179-202
Author(s):  
Umesh Kumar
Keyword(s):  
Integrated Circuit ◽  
Large Scale ◽  
Low Complexity ◽  
Stratified Medium ◽  
Base Function ◽  
Large Scale Integration ◽  
Element Approach ◽  
Scale Integration ◽  
High Degree ◽  
Important Shift

In the last decade, an important shift has taken place in the design of hardware with the advent of smaller and denser integrated circuit packages. Analysis techniques are required to ensure the proper electrical functioning of this hardware. An efficient method is presented to model the parasitic capacitance of VLSI (very large scale integration) interconnections. It is valid for conductors in a stratified medium, which is considered to be a good approximation for theSi−SiO2system of which present day ICs are made. The model approximates the charge density on the conductors as a continuous function on a web of edges. Each base function in the approximation has the form of a “spider” of edges. Here the method used [1] has very low complexity, as compared to other models used previously [2], and achieves a high degree of precision within the range of validity of the stratified medium.

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