If You’ve Got It,Flaunt It: Humans Flaunt Attractive Partners to Enhance Their Status and Desirability

Mating decisions are influenced by conspecifics’ mate choices in many species including humans. Recent research has shown that women are more attracted to men with attractive putative partners than those with less attractive partners. We integrate these findings with traditional accounts of social signaling and test five hypotheses derived from it. In our study, 64 men and 75 women were paired with attractive and unattractive opposite-sex putative partners and asked whether they would prefer to give surveys to peers or to older adults. Consistent with predictions, both men and women wanted to show off (flaunt) attractive partners by administering surveys to peers and both men and women wanted to hide (conceal) unattractive partners from peers by administering surveys to older adults. These decisions were mediated by how participants expected others to evaluate their status and desirability when they administered the surveys, consistent with partners serving a social signaling function in humans.     

You Wouldn’t Spawn in a Septic Tank, Would You?

Environmental effects of salmon farming are controversial issues. In Northern Norway, cod fishers argue that the location of salmon pens in fjords results in the cessation of local cod spawning. Research supporting or rejecting such statements is scant. There is an absence of both short-term and long-term studies on the effects that salmon farming may have on wild fish stocks. There are few studies of local ecosystem relationships in general. This article explores fishers’ arguments about the effects of salmon farming. It discusses methods of assessing the reliability and validity of fisher knowledge, and contributes to the discussion on assets and limitations of narrative data and experiential knowledge.     

What You See Is What You Get? Exclusion Performances in Ravens and Keas

Background

Among birds, corvids and parrots are prime candidates for advanced cognitive abilities. Still, hardly anything is known about cognitive similarities and dissimilarities between them. Recently, exclusion has gained increasing interest in comparative cognition. To select the correct option in an exclusion task, one option has to be rejected (or excluded) and the correct option may be inferred, which raises the possibility that causal understanding is involved. However, little is yet known about its evolutionary history, as only few species, and mainly mammals, have been studied.

Methodology/Principal Findings

We tested ravens and keas in a choice task requiring the search for food in two differently shaped tubes. We provided the birds with partial information about the content of one of the two tubes and asked whether they could use this information to infer the location of the hidden food and adjust their searching behaviour accordingly. Additionally, this setup allowed us to investigate whether the birds would appreciate the impact of the shape of the tubes on the visibility of food. The keas chose the baited tube more often than the ravens. However, the ravens applied the more efficient strategy, choosing by exclusion more frequently than the keas. An additional experiment confirmed this, indicating that ravens and keas either differ in their cognitive skills or that they apply them differently.

Conclusion

To our knowledge, this is the first study to demonstrate that corvids and parrots may perform differently in cognitive tasks, highlighting the potential impact of different selection pressures on the cognitive evolution of these large-brained birds.     

“If You Tell People That You Had Sex with a Fellow Man,It Is Hard to Be Helped and Treated”: Barriers and Opportunities for Increasing Access to HIV Services among Men Who Have Sex with Men in Uganda

Background

Despite the high HIV prevalence among men who have sex with men (MSM) in sub-Saharan Africa, little is known about their access to HIV services. This study assessed barriers and opportunities for expanding access to HIV services among MSM in Uganda.

Methods

In October-December 2013, a cross-sectional qualitative study was conducted in 12 districts of Uganda. Semi-structured in-depth interviews were conducted with 85 self-identified MSM by snowball sampling and 61 key informants including HIV service providers and policy makers. Data were analysed using manifest content analysis and Atlas.ti software.

Results

Three quarters of the MSM (n = 62, 72.9%) were not comfortable disclosing their sexual orientation to providers and 69 (81.1%) felt providers did not respect MSM. Half (n = 44, 51.8%) experienced difficulties in accessing health services. Nine major barriers to access were identified, including: (i) unwelcoming provider behaviours; (ii) limited provider skills and knowledge; (iii) negative community perceptions towards MSM; (iv) fear of being exposed as MSM; (v) limited access to MSM-specific services; (vi) high mobility of MSM, (vii) lack of guidelines on MSM health services; viii) a harsh legal environment; and ix) HIV related stigma. Two-thirds (n = 56, 66%) participated in MSM social networks and 86% of these (48) received support from the networks to overcome barriers to accessing services.

Conclusions

Negative perceptions among providers and the community present barriers to service access among MSM. Guidelines, provider skills building and use of social networks for mobilization and service delivery could expand access to HIV services among MSM in Uganda.     

Thank You from the Tuček Family

Note

Thank You from the Tuek Family     

What Can Article-Level Metrics Do for You?

Article-level metrics (ALMs) provide a wide range of metrics about the uptake of an individual journal article by the scientific community after publication. They include citations, usage statistics, discussions in online comments and social media, social bookmarking, and recommendations. In this essay, we describe why article-level metrics are an important extension of traditional citation-based journal metrics and provide a number of example from ALM data collected for PLOS Biology.The scientific impact of a particular piece of research is reflected in how this work is taken up by the scientific community. The first systematic approach that was used to assess impact, based on the technology available at the time, was to track citations and aggregate them by journal. This strategy is not only no longer necessary—since now we can easily track citations for individual articles—but also, and more importantly, journal-based metrics are now considered a poor performance measure for individual articles [1],[2]. One major problem with journal-based metrics is the variation in citations per article, which means that a small percentage of articles can skew, and are responsible for, the majority of the journal-based citation impact factor, as shown by Campbell [1] for the 2004 Nature Journal Impact Factor. Figure 1 further illustrates this point, showing the wide distribution of citation counts between PLOS Biology research articles published in 2010. PLOS Biology research articles published in 2010 have been cited a median 19 times to date in Scopus, but 10% of them have been cited 50 or more times, and two articles [3],[4] more than 300 times. PLOS Biology metrics are used as examples throughout this essay, and the dataset is available in the supporting information (Data S1). Similar data are available for an increasing number of other publications and organizations.Open in a separate windowFigure 1Citation counts for PLOS Biology articles published in 2010.Scopus citation counts plotted as a probability distribution for all 197 PLOS Biology research articles published in 2010. Data collected May 20, 2013. Median 19 citations; 10% of papers have at least 50 citations.Scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator [2],[5],[6]. To this end, PLOS has collected and displayed a variety of metrics for all its articles since 2009. The array of different categorised article-level metrics (ALMs) used and provided by PLOS as of August 2013 are shown in Figure 2. In addition to citations and usage statistics, i.e., how often an article has been viewed and downloaded, PLOS also collects metrics about: how often an article has been saved in online reference managers, such as Mendeley; how often an article has been discussed in its comments section online, and also in science blogs or in social media; and how often an article has been recommended by other scientists. These additional metrics provide valuable information that we would miss if we only consider citations. Two important shortcomings of citation-based metrics are that (1) they take years to accumulate and (2) citation analysis is not always the best indicator of impact in more practical fields, such as clinical medicine [7]. Usage statistics often better reflect the impact of work in more practical fields, and they also sometimes better highlight articles of general interest (for example, the 2006 PLOS Biology article on the citation advantage of Open Access articles [8], one of the 10 most-viewed articles published in PLOS Biology).Open in a separate windowFigure 2Article-level metrics used by PLOS in August 2013 and their categories.Taken from [10] with permission by the authors.A bubble chart showing all 2010 PLOS Biology articles (Figure 3) gives a good overview of the year''s views and citations, plus it shows the influence that the article type (as indicated by dot color) has on an article''s performance as measured by these metrics. The weekly PLOS Biology publication schedule is reflected in this figure, with articles published on the same day present in a vertical line. Figure 3 also shows that the two most highly cited 2010 PLOS Biology research articles are also among the most viewed (indicated by the red arrows), but overall there isn''t a strong correlation between citations and views. The most-viewed article published in 2010 in PLOS Biology is an essay on Darwinian selection in robots [9]. Detailed usage statistics also allow speculatulation about the different ways that readers access and make use of published literature; some articles are browsed or read online due to general interest while others that are downloaded (and perhaps also printed) may reflect the reader''s intention to look at the data and results in detail and to return to the article more than once.Open in a separate windowFigure 3Views vs. citations for PLOS Biology articles published in 2010.All 304 PLOS Biology articles published in 2010. Bubble size correlates with number of Scopus citations. Research articles are labeled green; all other articles are grey. Red arrows indicate the two most highly cited papers. Data collected May 20, 2013.When readers first see an interesting article, their response is often to view or download it. By contrast, a citation may be one of the last outcomes of their interest, occuring only about 1 in 300 times a PLOS paper is viewed online. A lot of things happen in between these potential responses, ranging from discussions in comments, social media, and blogs, to bookmarking, to linking from websites. These activities are usually subsumed under the term “altmetrics,” and their variety can be overwhelming. Therefore, it helps to group them together into categories, and several organizations, including PLOS, are using the category labels of Viewed, Cited, Saved, Discussed, and Recommended (Figures 2 and ​and4,4, see also [10]).Open in a separate windowFigure 4Article-level metrics for PLOS Biology.Proportion of all 1,706 PLOS Biology research articles published up to May 20, 2013 mentioned by particular article-level metrics source. Colors indicate categories (Viewed, Cited, Saved, Discussed, Recommended), as used on the PLOS website.All PLOS Biology articles are viewed and downloaded, and almost all of them (all research articles and nearly all front matter) will be cited sooner or later. Almost all of them will also be bookmarked in online reference managers, such as Mendeley, but the percentage of articles that are discussed online is much smaller. Some of these percentages are time dependent; the use of social media discussion platforms, such as Twitter and Facebook for example, has increased in recent years (93% of PLOS Biology research articles published since June 2012 have been discussed on Twitter, and 63% mentioned on Facebook). These are the locations where most of the online discussion around published articles currently seems to take place; the percentage of papers with comments on the PLOS website or that have science blog posts written about them is much smaller. Not all of this online discussion is about research articles, and perhaps, not surprisingly, the most-tweeted PLOS article overall (with more than 1,100 tweets) is a PLOS Biology perspective on the use of social media for scientists [11].Some metrics are not so much indicators of a broad online discussion, but rather focus on highlighting articles of particular interest. For example, science blogs allow a more detailed discussion of an article as compared to comments or tweets, and journals themselves sometimes choose to highlight a paper on their own blogs, allowing for a more digestible explanation of the science for the non-expert reader [12]. Coverage by other bloggers also serves the same purpose; a good example of this is one recent post on the OpenHelix Blog [13] that contains video footage of the second author of a 2010 PLOS Biology article [14] discussing the turkey genome.F1000Prime, a commercial service of recommendations by expert scientists, was added to the PLOS Article-Level Metrics in August 2013. We now highlight on the PLOS website when any articles have received at least one recommendation within F1000Prime. We also monitor when an article has been cited within the widely used modern-day online encyclopedia, Wikipedia. A good example of the latter is the Tasmanian devil Wikipedia page [15] that links to a PLOS Biology research article published in 2010 [16]. While a F1000Prime recommendation is a strong endorsement from peer(s) in the scientific community, being included in a Wikipedia page is akin to making it into a textbook about the subject area and being read by a much wider audience that goes beyond the scientific community. PLOS Biology is the PLOS journal with the highest percentage of articles recommended in F1000Prime and mentioned in Wikipedia, but there is only partial overlap between the two groups of articles because they focus on different audiences (Figure 5). These recommendations and mentions in turn show correlations with other metrics, but not simple ones; you can''t assume, for example, that highly cited articles are more likely to be recommended by F1000Prime, so it will be interesting to monitor these trends now that we include this information.Open in a separate windowFigure 5 PLOS Biology articles: sites of recommendation and discussion.Number of PLOS Biology research articles published up to May 20, 2013 that have been recommended by F1000Prime (red) or mentioned in Wikipedia (blue).With the increasing availability of ALM data, there comes a growing need to provide tools that will allow the community to interrogate them. A good first step for researchers, research administrators, and others interested in looking at the metrics of a larger set of PLOS articles is the recently launched ALM Reports tool [17]. There are also a growing number of service providers, including Altmetric.com [18], ImpactStory [19], and Plum Analytics [20] that provide similar services for articles from other publishers.As article-level metrics become increasingly used by publishers, funders, universities, and researchers, one of the major challenges to overcome is ensuring that standards and best practices are widely adopted and understood. The National Information Standards Organization (NISO) was recently awarded a grant by the Alfred P. Sloan Foundation to work on this [21], and PLOS is actively involved in this project. We look forward to further developing our article-level metrics and to having them adopted by other publishers, which hopefully will pave the way to their wide incorporation into research and researcher assessments.     

Do tigers displace leopards? If so, why?

We investigated predictions concerning the competitive relationships between tigers Panthera tigris and leopards Panthera pardus in Bardia National Park, Nepal, based on spatial distributions of scats and territorial markings (sign), analyses of scat content and census of wild ungulate prey. Medium-sized ungulates, in particular chital Axis axis, was the main food of both predators, but leopards consumed significantly larger proportions of domestic animals, small mammals, and birds than tigers. Tiger sign were never found outside the park, while leopard sign occurred both inside and outside, and were significantly closer to the park border than tiger sign. Significantly higher prey densities at locations of tiger sign than that of leopards were mainly due to a preference of the latter species for the park border areas. Our results imply that interference competition––and not competition for food––was a limiting factor for the leopard population, whose distribution was restricted to the margins of the tiger territories. We suggest that the composition of the prey base is a key factor in understanding the different results and interpretations reported in studies on tiger/leopard coexistence. There are two potential mechanisms that link interference competition and prey: (1) low abundance of large ungulate prey decreases foraging efficiency of tigers, leading to increased energetic stress and aggression towards leopards; and (2) increased diet overlap due to scarcity of large prey leads to increased encounter rates and increased levels of interference competition.     

What Doesn't Kill You Makes You Wary? Effect of Repeated Culling on the Behaviour of an Invasive Predator

As a result of being hunted, animals often alter their behaviour in ways that make future encounters with predators less likely. When hunting is carried out for conservation, for example to control invasive species, these behavioural changes can inadvertently impede the success of future efforts. We examined the effects of repeated culling by spearing on the behaviour of invasive predatory lionfish (Pterois volitans/miles) on Bahamian coral reef patches. We compared the extent of concealment and activity levels of lionfish at dawn and midday on 16 coral reef patches off Eleuthera, The Bahamas. Eight of the patches had been subjected to regular daytime removals of lionfish by spearing for two years. We also estimated the distance at which lionfish became alert to slowly approaching divers on culled and unculled reef patches. Lionfish on culled reefs were less active and hid deeper within the reef during the day than lionfish on patches where no culling had occurred. There were no differences at dawn when removals do not take place. Lionfish on culled reefs also adopted an alert posture at a greater distance from divers than lionfish on unculled reefs. More crepuscular activity likely leads to greater encounter rates by lionfish with more native fish species because the abundance of reef fish outside of shelters typically peaks at dawn and dusk. Hiding deeper within the reef could also make remaining lionfish less likely to be encountered and more difficult to catch by spearfishers during culling efforts. Shifts in the behaviour of hunted invasive animals might be common and they have implications both for the impact of invasive species and for the design and success of invasive control programs.