Predicting trophic relations in ecological networks: a test of the Allometric Diet Breadth Model

Few of food web theory hypotheses/predictions can be readily tested using empirical data. An exception is represented by simple probabilistic models for food web structure, for which the likelihood has been derived. Here I test the performance of a more complex model for food web structure that is grounded in the allometric scaling of interactions with body size and the theory of optimal foraging (Allometric Diet Breadth Model - ADBM). This deterministic model has been evaluated measuring the fraction of trophic relations correctly predicted. I contrast this value with that produced by simpler models based on body sizes and find that the data does not favor the more complex model: the information on allometric scaling and optimal foraging does not significantly increase the fit to the data. Also, I take a different approach and compute the p-value for the fraction of trophic interactions correctly predicted by ADBM with respect to three probabilistic null models. I find that the ADBM is clearly better at predicting links than random graphs, but other models can do even better. Although optimal foraging and allometric scaling could improve our understanding of food webs, the models need to be ameliorated to find support in the data.Comment: 28 pages, 3 figures, 4 table

Skim reading: an adaptive strategy for reading on the web

It has been suggested that readers spend a great deal of time skim reading on the Web and that if readers skim read they reduce their comprehension of what they have read. There have been a number of studies exploring skim reading, but relatively little exists on the skim reading of hypertext and Webpages. In the experiment documented here, we utilised eye tracking methodology to explore how readers skim read hypertext and how hyperlinks affect reading behaviour. The results show that the readers read faster when they were skim reading and comprehension was reduced. However, the presence of hyperlinks seemed to assist the readers in picking out important information when skim reading. We suggest that readers engage in an adaptive information foraging strategy where they attempt to minimise comprehension loss while maintaining a high reading speed. Readers use hyperlinks as markers to suggest important information and use them to read through the text in an efficient and effective way. This suggests that skim reading may not be as damaging to comprehension when reading hypertext, but it does mean that the words we choose to hyperlink become very important to comprehension for those skim reading text on the Web

How Do Web-Active End-User Programmers Forage?

Web-active end-user programmers spend substantial time and cognitive effort seeking information while debugging web mashups, which are platforms for creating web applications by combining data and functionality from two or more different sources. The debugging on these platforms is challenging as end user programmers need to forage within the mashup environment to find bugs and on the web to forage for the solution to those bugs. To understand the foraging behavior of end-user programmers when debugging, we used information forging theory. Information foraging theory helps understand how users forage for information and has been successfully used to understand and model user behavior when foraging through documents, the web, user interfaces, and programming environments. Through the lens of information foraging theory, we analyzed the data from a controlled lab study of eight web-active end-user programmers. The programmers completed two debugging tasks using the Yahoo! Pipes web mashup environment. On analyzing the data, we identified three types of cues: clear, fuzzy, and elusive. Clear cues helped participants to find and fix bugs with ease while fuzzy and elusive cues led to useless foraging. We also identified the strategies used by the participants when finding and fixing bugs. Our results give us a better understanding of the programming behavior of web-active end-users and can inform researchers and professionals how to create better support for the debugging process. Further, this study methodology can be adapted by researchers to understand other aspects of programming such as implementing, reusing, and maintaining code

Footprints of information foragers: Behaviour semantics of visual exploration

Social navigation exploits the knowledge and experience of peer users of information resources. A wide variety of visual–spatial approaches become increasingly popular as a means to optimize information access as well as to foster and sustain a virtual community among geographically distributed users. An information landscape is among the most appealing design options of representing and communicating the essence of distributed information resources to users. A fundamental and challenging issue is how an information landscape can be designed such that it will not only preserve the essence of the underlying information structure, but also accommodate the diversity of individual users. The majority of research in social navigation has been focusing on how to extract useful information from what is in common between users' profiles, their interests and preferences. In this article, we explore the role of modelling sequential behaviour patterns of users in augmenting social navigation in thematic landscapes. In particular, we compare and analyse the trails of individual users in thematic spaces along with their cognitive ability measures. We are interested in whether such trails can provide useful guidance for social navigation if they are embedded in a visual–spatial environment. Furthermore, we are interested in whether such information can help users to learn from each other, for example, from the ones who have been successful in retrieving documents. In this article, we first describe how users' trails in sessions of an experimental study of visual information retrieval can be characterized by Hidden Markov Models. Trails of users with the most successful retrieval performance are used to estimate parameters of such models. Optimal virtual trails generated from the models are visualized and animated as if they were actual trails of individual users in order to highlight behavioural patterns that may foster social navigation. The findings of the research will provide direct input to the design of social navigation systems as well as to enrich theories of social navigation in a wider context. These findings will lead to the further development and consolidation of a tightly coupled paradigm of spatial, semantic and social navigation

Investigating the Effects of Exploratory Semantic Search on the Use of a Museum Archive

Recently, there has been a great deal of interest in how new technologies can support the more effective use of online museum content. Two particularly relevant developments are exploratory search and semantic web technologies. Exploratory search tools support a more undirected and serendipitous interaction with the content. Semantic web technology, when applied in this context, allows the exploitation of metadata and ontologies to provide more intelligent support for user interaction. Bletchley Park Text is a museum web application supporting a semantic driven, exploratory approach to the search and navigation of digital museum resources. Bletchley Park Text uses semantics to organise selected content (i.e. stories) into a number of composite pages that illustrate conceptual patterns in the content, and from which the content itself can be accessed. The use made of Bletchley Park Text over an eight month period was analysed in order to understand the kinds of trajectories across the available resources that users could make with such a system. The results identified two distinct strategies of exploratory search. A risky strategy was characterised as incorporating: conceptual jumps between successive queries, a larger number of shorter queries and the use of the stories themselves to acclimatise to a new set of search results. A cautious strategy was characterised as incorporating: small conceptual shifts between queries, a smaller number of longer queries and the use of composite pages to acclimatise to a set of new search results. These findings have implications for the intelligent scaffolding of exploratory search

Food Webs: Experts Consuming Families of Experts

The question what determines the structure of natural food webs has been listed among the nine most important unanswered questions in ecology. It arises naturally from many problems related to ecosystem stability and resilience. The traditional view is that population-dynamical stability is crucial for understanding the observed structures. But phylogeny (evolutionary history) has also been suggested as the dominant mechanism. Here we show that observed topological features of predatory food webs can be reproduced to unprecedented accuracy by a mechanism taking into account only phylogeny, size constraints, and the heredity of the trophically relevant traits of prey and predators. The analysis reveals a tendency to avoid resource competition rather than apparent competition. In food webs with many parasites this pattern is reversed.Comment: 16 pages, 3 figures, 1 table + Appendix of 36 pages, 18 figures. movie available from http://ag.rossberg.net/matching.mp

Towards a Model of Understanding Social Search

Search engine researchers typically depict search as the solitary activity of an individual searcher. In contrast, results from our critical-incident survey of 150 users on Amazon's Mechanical Turk service suggest that social interactions play an important role throughout the search process. Our main contribution is that we have integrated models from previous work in sensemaking and information seeking behavior to present a canonical social model of user activities before, during, and after search, suggesting where in the search process even implicitly shared information may be valuable to individual searchers.Comment: Presented at 1st Intl Workshop on Collaborative Information Seeking, 2008 (arXiv:0908.0583