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1. Rates of human–macaque interactions affect grooming behavior among urban‐dwelling rhesus macaques ( Macaca mulatta )

   https://doi.org/10.1002/ajpa.23722  

   Kaburu, Stefano S. K. ; Marty, Pascal R. ; Beisner, Brianne ; Balasubramaniam, Krishna N. ; Bliss‐Moreau, Eliza ; Kaur, Kawaljit ; Mohan, Lalit ; McCowan, Brenda ( October 2018 , American Journal of Physical Anthropology)

   The impact of anthropogenic environmental changes may impose strong pressures on the behavioral flexibility of free‐ranging animals. Here, we examine whether rates of interactions with humans had both adirectandindirectinfluence on the duration and distribution of social grooming in commensal rhesus macaques (Macaca mulatta).

   Data were collected in two locations in the city of Shimla in northern India: an urban setting and a temple area. We divided these two locations in a series of similar‐sized physical blocks (N = 48) with varying rates of human–macaque interactions. We conducted focal observations on three free‐ranging rhesus macaque groups, one in the urban area and two in the temple area.

   Our analysis shows that macaques engaged in shorter grooming bouts and were more vigilant while grooming in focal sessions during which they interacted with people more frequently, suggesting that humans directly affected grooming effort and vigilance behavior. Furthermore, we found that in blocks characterized by higher rates of human–macaque interactions grooming bouts were shorter, more frequently interrupted by vigilance behavior, and were less frequently reciprocated.

   Our work shows that the rates of human–macaque interaction had both a direct and indirect impact on grooming behavior and that macaques flexibly modified their grooming interactions in relation to the rates of human–macaque interaction to which they were exposed. Because grooming has important social and hygienic functions in nonhuman primates, our work suggests that human presence can have important implications for animal health, social relationships and, ultimately, fitness. Our results point to the need of areas away from people even for highly adaptable species where they can engage in social interactions without human disruption.

    

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2. Focal accuracy estimates and landscape metrics for built-up areas from the GHS-BUILT R2018A in Massachusetts, USA.

   https://doi.org/10.6084/m9.figshare.19785877.v1  

   Uhl, Johannes H. ; Leyk, Stefan ( January 2022 , figshare)

   These files are supplementary data for this publication:

   Uhl JH & Leyk S (2022). "Assessing the relationship between morphology and mapping accuracy of built-up areas derived from global human settlement data (https://doi.org/10.1080/15481603.2022.2131192).

   Each geopackage (GPKG) file contains a set of point locations (in EPSG:3857) attributed with focal accuracy metrics of the GHS-BUILT-R2018A epochs 1975 and 2014, calculated within different levels of spatial support (i.e., focal window size) and for different analytical units (i.e., 30m grid cells, and 3x3 grid cell blocks). Moreover, each location is attributed with focal landscape metrics of built-up areas calculated in the same focal windows using the software Fragstats. These landscape metrics are calculated based on both, GHS built-up areas and reference built-up areas. Reference built-up areas were derived from the Multi-temporal building footprint database for 33 U.S. counties (MTBF-33). These datasets can be used for spatially explicit predictive modeling of the GHS-BUILT R2018A data accuracy using landscape metrics as predictor variables.

   File nomenclature:

   lsm_ref_accuracy_sample_2014_1000.gpkg : landscape metrics calculated from the reference built-up areas, for the epoch 2014, using a quadratic focal window of 1,000m x 1,000m.

   lsm_ghs_accuracy_sample_1975_10000.gpkg : landscape metrics calculated from the ghs built-up areas, for the epoch 1975, using a quadratic focal window of 10,000m x 10,000m.

   
   

   Data processing: Johannes H. Uhl, University of Colorado Boulder (USA), 2020-2022.

   
   

    

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3. User recommendation in healthcare social media by assessing user similarity in heterogeneous network

   https://doi.org/http://dx.doi.org/10.1016/j.artmed.2017.03.002  

   Jiang, Ling ; Yang, Christopher C. ( September 2017 , Artificial intelligence in medicine)

   Objective: The rapid growth of online health social websites has captured a vast amount of healthcare information and made the information easy to access for health consumers. E-patients often use these social websites for informational and emotional support. However, health consumers could be easily overwhelmed by the overloaded information. Healthcare information searching can be very difficult for consumers, not to mention most of them are not skilled information searcher. In this work, we investigate the approaches for measuring user similarity in online health social websites. By recommending similar users to consumers, we can help them to seek informational and emotional support in a more efficient way. Methods: We propose to represent the healthcare social media data as a heterogeneous healthcare information network and introduce the local and global structural approaches for measuring user similarity in a heterogeneous network. We compare the proposed structural approaches with the content-based approach. Results: Experiments were conducted on a data set collected from a popular online health social website,and the results showed that content-based approach performed better for inactive users, while structural approaches performed better for active users. Moreover, global structural approach outperformed local structural approach for all user groups. In addition, we conducted experiments on local and global structural approaches using different weight schemas for the edges in the network. Leverage performed the best for both local and global approaches. Finally, we integrated different approaches and demonstrated that hybrid method yielded better performance than the individual approach. Conclusion: The results indicate that content-based methods can effectively capture the similarity of inactive users who usually have focused interests, while structural methods can achieve better performance when rich structural information is available. Local structural approach only considers direct connections between nodes in the network, while global structural approach takes the indirect connections into account. Therefore, the global similarity approach can deal with sparse networks and capture the implicit similarity between two users. Different approaches may capture different aspects of the similarity relationship between two users. When we combine different methods together, we could achieve a better performance than using each individual method. 

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4. Social network position experiences more variable selection than weaponry in wild subpopulations of forked fungus beetles

   https://doi.org/10.1111/1365-2656.13322  

   Formica, Vincent ; Donald, Hannah ; Marti, Hannah ; Irgebay, Zhazira ; Brodie, III, Edmund ; Vander Wal, ed., Eric ( October 2020 , Journal of Animal Ecology)

   The phenotypic expression and fitness consequences of behaviours that are exhibited during social interactions are especially sensitive to their local social context. This context‐dependence is expected to generate more variation in the sign and magnitude of selection on social behaviour than that experienced by static characters like morphology. Relatively few studies, however, have examined selection on behavioural traits in multiple populations.

   We estimated sexual selection in the wild to determine if the strength and form of selection on social phenotypes is more variable than that on morphology.

   We compared selection gradients on social network position, body size, and weaponry of male forked fungus beetlesBolitotherus cornutusas they influenced mating success across nine natural subpopulations.

   Male horn length consistently experienced positive sexual selection. However, the sign and magnitude of selection on individual measures of network centrality (strength and betweenness) differed significantly among subpopulations. Moreover, selection on social behaviours occurred at a local scale (‘soft selection’), whereas selection on horn length occurred at the metapopulation scale (‘hard selection’).

   These results indicate that an individual with a given social phenotype could experience different fitness consequences depending on the network it occupies. While individuals seem to be unable to escape the fitness effects of their morphology, they may have the potential to mediate the pressures of selection on behavioural phenotypes by moving among subpopulations or altering social connections within a network.

    

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5. Revealing hazard-exposure heterophily as a latent characteristic of community resilience in social-spatial networks

   https://doi.org/10.1038/s41598-023-31702-9  

   Liu, Chia-Fu ; Mostafavi, Ali ( December 2023 , Scientific Reports)

   We present a latent characteristic in socio-spatial networks, hazard-exposure heterophily, to capture the extent to which populations with dissimilar hazard exposure could assist each other through social ties. Heterophily is the tendency of unlike individuals to form social ties. Conversely, populations in hazard-prone spatial areas with significant hazard-exposure similarity, homophily, would lack sufficient resourcefulness to aid each other to lessen the impact of hazards. In the context of the Houston metropolitan area, we use Meta’s Social Connectedness data to construct a socio-spatial network in juxtaposition with flood exposure data from National Flood Hazard Layer to analyze flood hazard exposure of spatial areas. The results reveal the extent and spatial variation of hazard-exposure heterophily in the study area. Notably, the results show that lower-income areas have lower hazard-exposure heterophily possibly caused by income segregation and the tendency of affordable housing development to be located in flood zones. Less resourceful social ties in hazard-prone areas due to their high-hazard-exposure homophily may inhibit low-income areas from better coping with hazard impacts and could contribute to their slower recovery. Overall, the results underscore the significance of characterizing hazard-exposure heterophily in socio-spatial networks to reveal community vulnerability and resilience to hazards.

    

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