DadeMatthews, O., F. K. Neal, P. J. Agostinelli, S. O. Oladipupo, R. M. Hirschhorn, A. E. Wilson, and J. M. Sefton. 2022. Systematic review and meta-analyses on the effects of whole-body vibration on bone health. Complementary Therapies in Medicine 65:102811.
Oladipupo, S. O., A. E. Wilson, X. P. Hu, and A. G. Appel. 2022. Why do insects close their spiracles? A meta-analytic evaluation of the adaptive hypothesis of discontinuous gas exchange in insects. Insects 13(2):117.
Insects breathe with the aid of thin capillary tubes that open out to the exterior of their body as spiracles. These spiracles are often modulated in a rhythmic gas pattern known as the discontinuous gas exchange cycle. During this cycle, spiracles are either firmly shut to allow no gaseous exchange or slightly open/fully open to allow for gaseous exchange. Two explanations are put forward to rationalize this process, namely, the rhythmic pattern is to (1) reduce water loss or (2) facilitate gaseous exchange in environments with high carbon dioxide and low oxygen. Interestingly, certain insects (such as some desert insects) do not use this rhythmic pattern where it would have been most beneficial and logical. Such an observation has led to the questioning of the explanations of the discontinuous gas exchange cycle. Consequently, we attempt to resolve this controversy by conducting a meta-analysis by synthesizing apposite data from across all insects where a discontinuous gas exchange cycle has been reported. A meta-analysis allows for a shift from viewing data through the lens of a single species to an order view. Thus, our goal is to use this holistic view of data to examine the explanations of the discontinuous gas exchange cycle across multiple groups of insects.
Wang, Y., A. E. Wilson, and N. Liu. 2022. A new method to address the importance of detoxified enzyme in insecticide resistance – meta-analysis. Frontiers in Physiology 13:818531.
Insect-borne diseases, such as malaria, and plant pathogens, like the tobacco mosaic virus, are responsible for human deaths and poor crop yields in communities around the world. The use of insecticides has been one of the major tools in the insect pest control. However, the development of insecticide resistance has been a major problem in the control of insect pest populations that threaten the health of both humans and plants. The overexpression of detoxification genes is thought to be one of the major mechanisms through which pests develop resistance to insecticides. Hundreds of research papers have explored how overexpressed detoxification genes increase the resistance status of insects to an insecticide in recent years. This study is, for the first time, a synthesis of these resistance and gene expression data aimed at 1) setting up an example for the application of meta-analysis in the investigation of the mechanisms of insecticide resistance and 2) seeking to determine if the overexpression detoxification genes are responsible for insecticide resistance in insect pests in general. A strong correlation of increased levels of insecticide resistance has been observed in tested insects with cytochrome P450 (CYP), glutathione-S-transferase (GST), and esterase gene superfamilies, confirming that the overexpression of detoxification genes is indeed involved in the insecticide resistance through the increased metabolism of insecticides of insects, including medically (e.g., mosquito and housefly) and agriculturally (e.g., planthopper and caterpillar) important insects.
Fernandez-Figueroa, E. G., and A. E. Wilson. 2022. Local adaptation mediates direct and indirect effects of multiple stressors on consumer fitness. Oecologia 198(2):483-492.
Fernandez-Figueroa, E. G., A. E. Wilson, and S. R. Rogers. 2022. Commercially available unoccupied aerial systems for monitoring harmful algal blooms: a comparative study. Limnology and Oceanography: Methods 20:146-158. (Top Cited Paper; Top Downloaded Article during first year post publication)
Reliable remote sensing platforms and methods for monitoring phytoplankton are needed for mitigating the detrimental impacts of cyanobacterial harmful algal blooms on small inland waterbodies. Commercial unoccupied aerial systems (UASs) present an affordable high-resolution solution for the rapid assessment of cyanobacterial abundance in small aquatic systems by recording the reflectance of photosynthetic pigments found in all phytoplankton (i.e., chlorophyll a [Chl a]) and those related to cyanobacteria (i.e., phycocyanin). This study evaluates the performance of four sensors, including visible light spectra (red, green, blue – [RGB]) sensors on the Phantom 4 and Phantom 4 Professional platforms, the MAPIR Survey3W modified multispectral (i.e., near-infrared, green, blue) sensor, and the Parrott Sequoia multispectral (i.e., green, red, near-infrared, red-edge) sensor for estimating cyanobacterial abundance. The performance of each sensor was determined by comparing 26 vegetation indices to Chl a and phycocyanin measurements of 54 ponds that varied in size and productivity. Vegetation indices that included the red and near-infrared wavelengths generated from Parrot Sequoia aerial images provided the best Chl a (i.e., Normalized Difference Vegetation Index, r2 = 0.79, p < 0.0001) and phycocyanin (i.e., Green Normalized Difference Vegetation Index, r2 = 0.64, p < 0.0001) estimates. The RGB sensors were moderately effective for estimating Chl a, whereas the MAPIR Survey3W generated poor estimates of both pigments due to differences in recorded wavelengths. Results suggest commercial multiband multispectral UAS sensors provide a low-cost, plug-and-play alternative for managers and researchers interested in integrating remote sensing tools for quantitatively estimating phytoplankton abundance in small inland systems.
Cabral, D. A. R., A. E. Wilson, and M. W. Miller. 2022. The effect of implicit learning on motor performance under psychological pressure: A systematic review and meta-analysis. Sport, Exercise, and Performance Psychology 11(3): 245–26.
Motor skills learned implicitly should be less susceptible to deterioration under psychological pressure (i.e., choking) than skills learned more explicitly. In this systematic review and meta-analysis, we investigated that prediction. A systematic search was conducted for articles that had participants learn a motor skill implicitly relative to a comparison group and had both groups perform the skill under low- and high-pressure conditions. Ten studies with a median of nine participants/group met inclusion criteria. Seven of ten studies reported an advantage of learning a motor skill implicitly when performing under psychological pressure. Moreover, a multivariate random-effects metaanalysis revealed that participants who learned a motor skill implicitly performed better under a high-pressure condition than a low-pressure condition, Hedges’ gav = −1.17, 95% lower CI [−1.61], upper CI [−0.74], whereas participants in the comparison group performed similarly between conditions, Hedges’ gav = 0.19, 95% lower CI [ −0.33], upper CI [ 0.71]. For the implicit learning group, a funnel plot of the relationship between effect size and standard error showed an asymmetrical distribution and a significant relationship, indicating bias. In conclusion, results confirm the prediction that implicit motor learning benefits performance under pressure. However, this effect might be distorted by bias and driven by underpowered studies, likely causing it to be overestimated. We suggest the advantage of learning a motor skill implicitly versus explicitly on performance under pressure be assumed to be moderately sized, pending future research, and encourage preregistered studies with larger sample sizes to estimate the effect more accurately.
Belfiore, A., R. P. Buley, E. G. Fernandez-Figueroa, M. Gladfelter, and A. E. Wilson. 2021. Zooplankton as an alternative method for controlling phytoplankton in catfish pond aquaculture. Aquaculture Reports 21:100897.
In pond aquaculture, production of toxins and off-flavor compounds by cyanobacteria can negatively affect fish health and production. Studies have explored chemical or physical methods for controlling algal blooms in aquaculture ponds, which although effective, may be short-lived and can negatively impact non-target organisms, including aquaculture species. Food web manipulations have a long history in lake and fisheries management to improve water quality, but have been rarely considered in aquaculture. This study examined zooplankton and phytoplankton communities, cyanobacterial toxins, and nutrients in nine catfish aquaculture farm-ponds in west Alabama, USA. The goal of this project was to track phytoplankton and zooplankton abundances with respect to each other, with and without efforts to reduce zooplanktivorous fish in some of the ponds. During this project, farm managers reduced zooplanktivorous fish abundance in select ponds to create a large-scale field experiment that addressed the role of zooplankton control of phytoplankton in hypereutrophic catfish aquaculture ponds when zooplanktivorous fish were or were not excluded. There was a strong negative effect of zooplankton on phytoplankton, including cyanobacteria, despite high nutrient concentrations. Although high zooplankton ponds sustained elevated zooplankton biomass during much of this study, including when pond temperatures exceeded 30 °C, the effect of zooplankton on phytoplankton was most pronounced during the non-growing season (November–April). In addition, total ammonia nitrogen was significantly higher in high zooplankton ponds, which could lead to ammonia toxicity in fish at elevated temperature and pH. Our findings suggest that zooplankton biomanipulation may be an efficient method to control algal blooms in farm-pond catfish aquaculture.
Green, W. R., A. B. Hoos, A. E. Wilson, and E. N. Heal. 2021. Development of a screening tool to examine lake and reservoir susceptibility to eutrophication in selected watersheds of the eastern and southeastern United States. U.S. Geological Survey Scientific Investigations Report 2021–5075, 59 pages
This report describes a new screening tool to examine lake and reservoir susceptibility to eutrophication in selected watersheds of the eastern and southeastern United States using estimated nutrient loading and flushing rates with measures of waterbody morphometry. To that end, the report documents the compiled data and methods (R-script) used to categorize waterbodies by Carlson’s Trophic State Index. Assessments were completed for 232 lakes and reservoirs having a surface area greater than or equal to 0.1 square kilometer in watersheds that drain to the Atlantic and eastern Gulf of Mexico coasts of the United States and in watersheds within the Tennessee River Basin. Waterbodies were categorized by type—natural lakes, headwater reservoirs, and downstream reservoirs—and were assessed independently. Recursive partitioning and the model-based boosting routine were used to create four-node regression trees to group waterbodies into five endpoints from low-to-high measures of Secchi depth, and concentrations of chlorophyll a and microcystin according to shared nutrient loading, flushing rate, and morphometric characteristics. Trophic state designations were assigned based on the average value within each of the five endpoints. An application (procedure) is provided using the tool to examine the susceptibility of a given waterbody of interest to eutrophication. Results of this study can aid water-resource managers in prioritizing lake and reservoir protection and restoration efforts based on the susceptibility of these waterbodies to eutrophication relative to nutrient loading, flushing rate, and morphometric characteristics.
Buley, R. P., H. E. Correia, A. Abebe, T. B. Issa, and A. E. Wilson. 2021. Predicting microcystin occurrence in freshwater lakes and reservoirs: assessing environmental variables. Inland Waters 11(3):430-444.
Determining the environmental conditions that influence the occurrence and concentration of the cyanobacterial toxin microcystin (MC) is a critical step for predicting cases in which the toxin will adversely affect drinking water sources, recreational waterbodies, and other freshwater ecosystems. Although widely studied, little consensus exists regarding the factors that influence MC on a global scale. The objective of this study was to identify the environmental variables most strongly associated with MC concentrations using observational data from lakes and reservoirs around the world while also addressing the substantial proportions of missing values that a large aggregated dataset often involves. A total of 124 studies containing data from an estimated 2040 lakes and reservoirs in 22 countries was used to construct a global dataset. Variables including <35% of non-missing observations were removed prior to analysis. Missing values for the remaining 12 predictors of MC were imputed using an iterative imputation algorithm based on a random forest approach. Variable selection was performed with generalized additive modeling on the complete case and imputed datasets. Models applied to the imputed data produced lower prediction errors than those fit to the complete dataset. Variables of greatest significance to MC concentration included location (longitude–latitude pairs), total nitrogen, turbidity, and pH. Total phosphorus was not found to be a strong predictor of MC. In addition to assisting water resource managers in protecting their waterbodies against MC, the presented methodologies may provide a useful framework for future water quality modeling while accounting for varying proportions of missing data.
Odom, S., H. Boso, S. Bowling, S. Cotner, C. Creech, A. G. Drake, S. Eddy, S. Fagbodun, S. Hebert, A. James, J. Just, J. R. St. Juliana, M. Shuster, S. Thompson, R. Whittington, B. Wills, A. Wilson, K. R. Zamudio, M. Zhong, and C. J. Ballen. 2021. Meta-analysis of gender performance gaps in undergraduate natural science courses. CBE-Life Sciences Education 20(2):ar40.
To investigate patterns of gender-based performance gaps, we conducted a meta-analysis of published studies and unpublished data collected across 169 undergraduate biology and chemistry courses. While we did not detect an overall gender gap in performance, heterogeneity analyses suggested further analysis was warranted, so we investigated whether attributes of the learning environment impacted performance disparities on the basis of gender. Several factors moderated performance differences, including class size, assessment type, and pedagogy. Specifically, we found evidence that larger classes, reliance on exams, and undisrupted, traditional lecture were associated with lower grades for women. We discuss our results in the context of natural science courses and conclude by making recommendations for instructional practices and future research to promote gender equity.