Comparing pre- and post-copulatory mate competition using social network analysis in wild crickets

This is the final version of the article. Available from the publisher via the DOI in this record.Data accessibility: Data are available through Open Research Exeter, http://hdl.handle.net/10871/19103Sexual selection results from variation in success at multiple stages in the mating process, including competition before and after mating. The relationship between these forms of competition, such as whether they trade-off or reinforce one another, influences the role of sexual selection in evolution. However, the relationship between these 2 forms of competition is rarely quantified in the wild. We used video cameras to observe competition among male field crickets and their matings in the wild. We characterized pre- and post-copulatory competition as 2 networks of competing individuals. Social network analysis then allowed us to determine 1) the effectiveness of precopulatory competition for avoiding postcopulatory competition, 2) the potential for divergent mating strategies, and 3) whether increased postcopulatory competition reduces the apparent reproductive benefits of male promiscuity. We found 1) limited effectiveness of precopulatory competition for avoiding postcopulatory competition; 2) males do not specifically engage in only 1 type of competition; and 3) promiscuous individuals tend to mate with each other, which will tend to reduce variance in reproductive success in the population and highlights the trade-off inherent in mate guarding. Our results provide novel insights into the works of sexual competition in the wild. Furthermore, our study demonstrates the utility of using network analyses to study competitive interactions, even in species lacking obvious social structure.Funding for this research was provided by NERC (studentship no.: NE/H02249X/1; grant no.: NE/H02364X/1). Further support was provided by the University of Exeter’s Postgraduate Research Enhancement Fund, awarded to D.N.F

Application of Stereo-Photogrammetric Methods to the Advanced Along Track Scanning Radiometer for the Atmospheric Sciences

This thesis studies photogrammetric techniques applied to the ATSR instruments for the extraction of atmospheric parameters with the objective of generating new scientific datasets. The atmospheric parameters under observation are cloud top height, smoke plume injection height, and tropospheric wind components. All have important applications in various tasks, including the initialisation and validation of climate models. To generate accurate stereo measurements from the ATSR imagery the forward and nadir views need to be accurately co-registered. Currently this is not the case, with differences of up to 2 pixels in both axes recorded. In this thesis an automated image tie-pointing and image warping algorithm that improves ATSR co-registration to ≤1 pixel is presented. This thesis also identifies the census stereo matching algorithm for application to the ATSR instruments. When compared against a collocated DEM, census outperforms the previous stereo matching algorithm applied to the ATSR instrument, known as M4, significantly: RMSE ~700m vs. ~1200m; bias ~60m vs ~600m; R2 ~0.9 vs ~0.7. Furthermore, this thesis reviews the M6 algorithm developed for application within the ESA ALANIS Smoke Plume project. Using census a climatological cloud fraction by altitude dataset over Greenland is generated and demonstrated to agree well with current observational datasets from MISR, MODIS and AATSR. The 11μm channel stereo output provides insights into high cloud characteristics over Greenland and appears to be, in comparison with CALIOP, practically unbiased. The ALANIS Smoke plume project is introduced and the inter-comparison of the M6 algorithm against MISR and CALIOP is presented. M6 demonstrates some ability for determining smoke plumes injection heights above 1km in elevation. However, the smoke plume masking approach currently employed is demonstrated to be lacking in quality. Finally, this thesis presents the determination of cloud tracked tropospheric winds from the ATSR2-AATSR tandem operation using the Farneback optical flow algorithm. This algorithm offers accuracy on the order of 0.5 ms-1 at full image resolution, which is unprecedented in comparison to similarly derived datasets

Analysing animal social network dynamics: the potential of stochastic actor-oriented models

This is the final version of the article. Available from the publisher via the DOI in this record.Animals are embedded in dynamically changing networks of relationships with conspecifics. These dynamic networks are fundamental aspects of their environment, creating selection on behaviours and other traits. However, most social network-based approaches in ecology are constrained to considering networks as static, despite several calls for such analyses to become more dynamic. There are a number of statistical analyses developed in the social sciences that are increasingly being applied to animal networks, of which stochastic actor-oriented models (SAOMs) are a principal example. SAOMs are a class of individual-based models designed to model transitions in networks between discrete time points, as influenced by network structure and covariates. It is not clear, however, how useful such techniques are to ecologists, and whether they are suited to animal social networks. We review the recent applications of SAOMs to animal networks, outlining findings and assessing the strengths and weaknesses of SAOMs when applied to animal rather than human networks. We go on to highlight the types of ecological and evolutionary processes that SAOMs can be used to study. SAOMs can include effects and covariates for individuals, dyads and populations, which can be constant or variable. This allows for the examination of a wide range of questions of interest to ecologists. However, high-resolution data are required, meaning SAOMs will not be useable in all study systems. It remains unclear how robust SAOMs are to missing data and uncertainty around social relationships. Ultimately, we encourage the careful application of SAOMs in appropriate systems, with dynamic network analyses likely to prove highly informative. Researchers can then extend the basic method to tackle a range of existing questions in ecology and explore novel lines of questioning

The performance of permutations and exponential random graph models when analyzing animal networks

This is the author accepted manuscript. The final version is available from Oxford University Press via the DOI in this record.The R code used to simulate and analyze the networks are available as supplemental files. Simulation R code, and necessary summary data and R code to reproduce the analyses reported in this article are provided by (Evans et al. 2020).Social network analysis is a suite of approaches for exploring relational data. Two approaches commonly used to analyze animal social network data are permutation-based tests of significance and exponential random graph models. However, the performance of these approaches when analyzing different types of network data has not been simultaneously evaluated. Here we test both approaches to determine their performance when analyzing a range of biologically realistic simulated animal social networks. We examined the false positive and false negative error rate of an effect of a two-level explanatory variable (e.g., sex) on the number and combined strength of an individual’s network connections. We measured error rates for two types of simulated data collection methods in a range of network structures, and with/without a confounding effect and missing observations. Both methods performed consistently well in networks of dyadic interactions, and worse on networks constructed using observations of individuals in groups. Exponential random graph models had a marginally lower rate of false positives than permutations in most cases. Phenotypic assortativity had a large influence on the false positive rate, and a smaller effect on the false negative rate for both methods in all network types. Aspects of within- and between-group network structure influenced error rates, but not to the same extent. In "grouping event-based" networks, increased sampling effort marginally decreased rates of false negatives, but increased rates of false positives for both analysis methods. These results provide guidelines for biologists analyzing and interpreting their own network data using these methods

A customisable pipeline for continuously harvesting socially-minded Twitter users

On social media platforms and Twitter in particular, specific classes of users such as influencers have been given satisfactory operational definitions in terms of network and content metrics. Others, for instance online activists, are not less important but their characterisation still requires experimenting. We make the hypothesis that such interesting users can be found within temporally and spatially localised contexts, i.e., small but topical fragments of the network containing interactions about social events or campaigns with a significant footprint on Twitter. To explore this hypothesis, we have designed a continuous user profile discovery pipeline that produces an ever-growing dataset of user profiles by harvesting and analysing contexts from the Twitter stream. The profiles dataset includes key network and content-based users metrics, enabling experimentation with user-defined score functions that characterise specific classes of online users. The paper describes the design and implementation of the pipeline and its empirical evaluation on a case study consisting of healthcare-related campaigns in the UK, showing how it supports the operational definitions of online activism, by comparing three experimental ranking functions. The code is publicly available.Comment: Procs. ICWE 2019, June 2019, Kore

On The Phase Structure and Thermodynamic Geometry of R-Charged Black Holes

We study the phase structure and equilibrium state space geometry of R-charged black holes in $D = 5$, 4 and 7 and the corresponding rotating $D3$, $M2$ and $M5$ branes. For various charge configurations of the compact black holes in the canonical ensemble we demonstrate new liquid-gas like phase coexistence behaviour culminating in second order critical points. The critical exponents turn out to be the same as that of four dimensional asymptotically AdS black holes in Einstein Maxwell theory. We further establish that the regions of stability for R-charged black holes are, in some cases, more constrained than is currently believed, due to properties of some of the response coefficients. The equilibrium state space scalar curvature is calculated for various charge configurations, both for the case of compact as well as flat horizons and its asymptotic behaviour with temperature is established.Comment: 1 + 33 pages, LaTeX, 25 figures. References adde

Acceptability of HIV self-sampling kits (TINY vial) among people of black African ethnicity in the UK: a qualitative study

Background: Increasing routine HIV testing among key populations is a public health imperative, so improving access to acceptable testing options for those in need is a priority. Despite increasing targeted distribution and uptake of HIV self-sampling kits (SSKs) among men who have sex with men in the UK, little is known about why targeted SSK interventions for black African users are not as wide-spread or well-used. This paper addresses this key gap, offering insight into why some groups may be less likely than others to adopt certain types of SSK interventions in particular contexts. These data were collected during the development phase of a larger study to explore the feasibility and acceptability of targeted distribution of SSKs to black African people. Methods: We undertook 6 focus groups with members of the public who self-identified as black African (n = 48), 6 groups with specialists providing HIV and social services to black African people (n = 53), and interviews with HIV specialist consultants and policy-makers (n = 9). Framework analysis was undertaken, using inductive and deductive analysis to develop and check themes. Results: We found three valuable components of targeted SSK interventions for this population: the use of settings and technologies that increase choice and autonomy; targeted offers of HIV testing that preserve privacy and do not exacerbate HIV stigma; and ensuring that the specific kit being used (in this case, the TINY vial) is perceived as simple and reliable. Conclusions: This unique and rigorous research offers insights into participants’ views on SSK interventions, offering key considerations when targeting this population.. Given the plethora of HIV testing options, our work demonstrates that those commissioning and delivering SSK interventions will need to clarify (for users and providers) how each kit type and intervention design adds value. Most significantly, these findings demonstrate that without a strong locus of control over their own circumstances and personal information, black African people are less likely to feel that they can pursue an HIV test that is safe and secure. Thus, where profound social inequalities persist, so will inequalities in HIV testing uptake – by any means

Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

This is the final version. Available from the American Meteorological Society via the DOI in this recordTerrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.This paper is financially supported by the Research and Development Special Fund for Public Welfare Industry of the Ministry of Water Research in China (201501028). JBF and CRS were supported in part by NASA’s Carbon Cycle Science program. JBF was also supported in part by NASA’s Terrestrial Ecology and Carbon Monitoring System programs. JT acknowledges RCN funded project EVA (229771) and BCCR-BIGCHANGE

Sources of uncertainty in modeled land carbon storage within and across three MIPs: Diagnosis with three new techniques

This is the final version. Available from the American Meteorological Society via the DOI in this recordTerrestrial carbon cycle models have incorporated increasingly more processes as a means to achieve more-realistic representations of ecosystem carbon cycling. Despite this, there are large across-model variations in the simulation and projection of carbon cycling. Several model intercomparison projects (MIPs), for example, the fifth phase of the Coupled Model Intercomparison Project (CMIP5) (historical simulations), Trends in Net Land-Atmosphere Carbon Exchange (TRENDY), and Multiscale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), have sought to understand intermodel differences. In this study, the authors developed a suite of new techniques to conduct post-MIP analysis to gain insights into uncertainty sources across 25 models in the three MIPs. First, terrestrial carbon storage dynamics were characterized by a three-dimensional (3D) model output space with coordinates of carbon residence time, net primary productivity (NPP), and carbon storage potential. The latter represents the potential of an ecosystem to lose or gain carbon. This space can be used to measure how and why model output differs. Models with a nitrogen cycle generally exhibit lower annual NPP in comparison with other models, and mostly negative carbon storage potential. Second, a transient traceability framework was used to decompose any given carbon cycle model into traceable components and identify the sources of model differences. The carbon residence time (or NPP) was traced to baseline carbon residence time (or baseline NPP related to the maximum carbon input), environmental scalars, and climate forcing. Third, by applying a variance decomposition method, the authors show that the intermodel differences in carbon storage can be mainly attributed to the baseline carbon residence time and baseline NPP (>90% in the three MIPs). The three techniques developed in this study offer a novel approach to gain more insight from existing MIPs and can point out directions for future MIPs. Since this study is conducted at the global scale for an overview on intermodel differences, future studies should focus more on regional analysis to identify the sources of uncertainties and improve models at the specified mechanism level.This paper is financially supported by the Research and Development Special Fund for Public Welfare Industry of the Ministry of Water Research in China (201501028). JBF and CRS were supported in part by NASA’s Carbon Cycle Science program. JBF was also supported in part by NASA’s Terrestrial Ecology and Carbon Monitoring System programs. JT acknowledges RCN funded project EVA (229771) and BCCR-BIGCHANGE