The validity of network observations is sometimes of concern in empirical studies, since observed networks are prone to error and may not represent the population of interest. This lack of validity is not just a result of random measurement error, but often due to systematic bias that can lead to the misinterpretation of actors’ preferences of network selections. These issues in network observations could bias the estimation of common network models (such as those pertaining to influence and selection) and lead to erroneous statistical inferences. In this study, we proposed a simulation-based sensitivity analysis method that can evaluate the robustness of inferences made in social network analysis to six forms of selection mechanisms that can cause biases in network observations—random, homophily, anti-homophily, transitivity, reciprocity, and preferential attachment. We then applied this sensitivity analysis to test the robustness of inferences for social influence effects, and we derived two sets of analytical solutions that can account for biases in network observations due to random, homophily, and anti-homophily selection.

Hydrilla is an invasive aquatic plant that has rapidly spread through many inland water bodies across the globe by outcompeting native aquatic plants. The negative impacts of hydrilla invasion have become a concern for water resource management authorities, power companies, and environmental scientists. The early detection of hydrilla infestation is very important to reduce the costs associated with control and removal efforts of this invasive species. Therefore, in this study, we aimed to develop a tool for rapid, frequent, and large-scale monitoring and predicting spatial extent of hydrilla habitat. This was achieved by integrating in situ and Landsat 8 Operational Land Imager satellite data for Lake J. Strom Thurmond, the largest US Army Corps of Engineers lake east of the Mississippi River, located on the border of Georgia and South Carolina border. The predictive model for presence of hydrilla incorporated radiometric and physical measurements, including remote-sensing reflectance, Secchi disk depth (SDD), light-attenuation coefficient (Kd), maximum depth of colonization (Zc), and percentage of light available through the water column (PLW). The model-predicted ideal habitat for hydrilla featured high SDD, Zc, and PLW values, low values of Kd. Monthly analyses based on satellite images showed that hydrilla starts growing in April, reaches peak coverage around October, begins retreating in the following months, and disappears in February. Analysis of physical and meteorological factors (i.e., water temperature, surface runoff, net inflow, precipitation) revealed that these parameters are closely associated with hydrilla extent. Management agencies can use these results not only to plan removal efforts but also to evaluate and adapt their current mitigation efforts.

A clean hot-water drill was used to gain access to Subglacial Lake Whillans (SLW) in late January 2013 as part of the Whillans Ice Stream Subglacial Access Research Drilling (WISSARD) project. Over 3 days, we deployed an array of scientific tools through the SLW borehole: a downhole camera, a conductivity–temperature–depth (CTD) probe, a Niskin water sampler, an in situ filtration unit, three different sediment corers, a geothermal probe and a geophysical sensor string. Our observations confirm the existence of a subglacial water reservoir whose presence was previously inferred from satellite altimetry and surface geophysics. Subglacial water is about two orders of magnitude less saline than sea water (0.37–0.41 psu vs 35 psu) and two orders of magnitude more saline than pure drill meltwater (<0.002 psu). It reaches a minimum temperature of –0.55~C, consistent with depression of the freezing point by 7.019 MPa of water pressure. Subglacial water was turbid and remained turbid following filtration through 0.45 µm filters. The recovered sediment cores, which sampled down to 0.8 m below the lake bottom, contained a macroscopically structureless diamicton with shear strength between 2 and 6 kPa. Our main operational recommendation for future subglacial access through water-filled boreholes is to supply enough heat to the top of the borehole to keep it from freezing.

The large diversity of farms and farming systems in sub-Saharan Africa calls for agricultural improvement options that are adapted to the context in which smallholder farmers operate. The socio-ecological niche concept incorporates the agro-ecological, socio-cultural, economic and institutional dimensions and the multiple levels of this context in order to identify which options fit best. In this paper, we illustrate how farming systems analysis, following the DEED cycle of Describe, Explain, Explore and Design, and embedding co-learning amongst researchers, farmers and other stakeholders, helps to operationalize the socio-ecological niche concept. Examples illustrate how farm typologies, detailed farm characterization and on-farm experimental work, in combination with modelling and participatory approaches inform the matching of options to the context at regional, village, farm and field level. Recommendation domains at these gradually finer levels form the basis for gradually more detailed baskets of options from which farmers and other stakeholders may choose, test and adjust to their specific needs. Tailored options identified through the DEED cycle proof to be more relevant, feasible and performant as compared to blanket recommendations in terms of both researcher and farmer-identified criteria. As part of DEED, on-farm experiments are particularly useful in revealing constraints and risks faced by farmers. We show that targeting options to the niches in which they perform best, helps to reduce this risk. Whereas the conclusions of our work about the potential for improving smallholders’ livelihoods are often sobering, farming systems analysis allows substantiating the limitations of technological options, thus highlighting the need for enabling policies and institutions that may improve the larger-scale context and increase the uptake potential of options.

This study tested the hypothesis that phenylbutazone would block the exercise-induced increase in cytokine markers of inflammation in blood. Blood samples were obtained from unfit Standardbred mares (age 10 ± 4 years, ~500 kg) before and after three different trials (standing control (CON), n = 9; exercise with phenylbutazone (EX-bute), n = 9; and exercise with water, n = 9). Comparisons were made for data collected in three trials, one where each horse underwent an incremental exercise test (graded exercise test (GXT)) where they were administered water as a placebo, a GXT following phenylbutazone administration (2 g given orally 2 h before the GXT) or standing parallel control where they stood quietly in stalls. During the GXT, horses ran on a treadmill (1 m s− 1 increases each min until fatigue, 6% grade). Blood samples were obtained 30 min before exercise, immediately after exercise and at 0.5, 1, 2, 4 and 24 h post-GXT or at matched time points during the parallel control trials. Samples were analysed using real-time PCR for measurement of mRNA expression of interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α) and interleukin (IL)-6 in samples collected during all three trials, and for IL-1 and IL-10 in samples collected for the CON and EX-bute trials. Data were analysed using ANOVA for repeated measures, and where appropriate, post hoc separation of means utilized the Student–Newman–Keuls test. The null hypothesis was rejected when P < 0.05. There were no changes (P>0.05) in IL-1, IL-6, IFN-γ or TNF-α during CON or following phenylbutazone administration. During the water trial, exercise resulted in significant increases in IFN-γ, IL-1 and TNF-α. It was concluded that high-intensity exercise results in a transient increase in the expression of inflammatory cytokines in blood that is blocked when phenylbutazone is administered to horses.