Testing a post-copulatory pre-zygotic reproductive barrier in a passerine species pair

Sexual selection may drive speciation, but most research focuses on pre-copulatory sexual selection, overlooking post-copulatory processes. Post-copulatory sexual selection in allopatric populations could drive divergence in post-copulatory pre-zygotic (PCPZ) phenotypes, limiting gene flow upon secondary contact. Here, we performed in vitro experiments examining one potential PCPZ barrier between two closely related passerine species, house sparrows (Passer domesticus) and Spanish sparrows (Passer hispaniolensis). In birds, crossing in the vagina may be particularly challenging for sperm, so we tested the effect of female reproductive tract fluids on sperm swimming speed and motility. If a PCPZ barrier exists at this stage of the fertilization process, heterospecific female fluids are predicted to reduce sperm swimming speed or motility relative to conspecific female fluid. We found that house sparrow female fluids affected the two species’ sperm asymmetrically, depending on the control sperm velocity and male species. Overall, however, sperm performed equally in conspecific and heterospecific female fluids, and the species had similar sperm morphology and sperm swimming performance. Low divergence in PCPZ phenotypes between species, perhaps because post-copulatory sexual selection is stabilizing or only moderately strong in these taxa, may be insufficient to cause an overall PCPZ barrier. Reinforcement may be unlikely to drive PCPZ barriers for this species pair, because relatively effective pre-copulatory barriers exist between the species, and because hybrids can be quite successful. Testing the role of PCPZ barriers in birds with more divergent PCPZ phenotypes will improve our understanding of speciation in passerines.     

Gonadal histology and reproductive steroidogenesis in Lithobates pipiens exposed to atrazine

Abstract

Atrazine, an endocrine-disrupting compound and environmental pollutant, can have adverse effects on amphibian reproductive development and function. To determine the effects of atrazine on anuran gonadal development, Lithobates pipiens larvae were exposed from Gosner stage 25 through 1-month post metamorphosis to 0, 2, 20, or 200?μg/L atrazine or estradiol. Exposure to atrazine did not markedly alter tadpole growth, development, gonadal histology, or reproductive steroidogenesis. Testicular ovarian follicles appeared in L. pipiens metamorphs following all treatments, including controls, whereas ovotestes occurred only in positive controls. Testicular ovarian follicles may be a natural ontogenetic occurrence in this species while ovotestes indicate disruption in development. Establishing the normal pattern of reproductive development for anuran species and conducting comparisons in fully sexually differentiated animals is necessary to clarify the influence of endocrine disrupting compounds.     

Energy expenditure and food consumption of foraging Imperial cormorants in Patagonia, Argentina

Energy management during the breeding season is crucial for central place foragers since parents need to feed themselves and their offspring while being spatially and temporally constrained. In this work, we used overall dynamic body acceleration as a measure of activity and also to allude to the foraging energy expenditure of breeding Imperial cormorants Phalacrocorax atriceps. We also analyzed how changes in the time or energy allocated to different activities affected the foraging trip energy expenditure and estimated the daily food requirements of the species. Birds spent 42 % of the total energy flying to and from the feeding areas and 16 % floating at sea. The level of activity underwater was almost 1.5 times higher for females than for males. The most expensive diving phase in terms of rate of energy expenditure was descending though the water column. The total foraging trip energy expenditure was particularly sensitive to variation in the amount of time spent flying. During the breeding season, adult cormorants breeding along the Patagonian coast would consume approximately 10,000 tons of food.     

Prenatal diagnosis of congenital non-bullous ichthyosiform erythroderma (lamellar ichthyosis)

We report the first positive prenatal diagnosis ofcongenital non-bullous ichthyosiform erythroderma or lamellar ichthyosis. Fetal skin samples were obtained by fetoscopy at 21 weeks' gestation and examined by light and electron microscopy. Light microscopy revealed a thickened interfollicular epidermis with multiple layers of flattened cells and excessive keratinization of the epidermal lining of the follicular infundibulum. Electron microscopy of the thickened epidermis revealed granular cells that contained larger-than-normal keratohyalin granules and multiple layers of parakeratotic cornified cells. Although there was regional variation in the degree of interfollicular keratinization, follicles from all regions showed greater and more complete keratinization, indicating that they express the abnormality early enough in development to permit prenatal diagnosis at about 20 weeks' gestation.     

Estimating Relevance of Organic Carbon,Nitrogen, and Phosphorus Loads to a Blackwater River Estuary1

Abstract: In blackwater river estuaries, a large portion of external carbon, nitrogen, and phosphorus load are combined in complex organic molecules of varying recalcitrance. Determining their lability is essential to establishing the relationship between anthropogenic loads and eutrophication. A method is proposed in which organic C, N, and P are partitioned into labile and refractory forms, based upon first‐order decay estimated by biochemical oxygen demand relative to total organic carbon, and C:N and C:P ratios as a function of organic carbon lability. The technique was applied in developing total maximum daily loads for the lower St. Johns, a blackwater Atlantic coastal plain river estuary in Northeast Florida. Point source organic nutrients were determined to be largely labile. Urban runoff was found to have the highest relative labile organic N and P content, followed by agricultural runoff. Natural forest and silviculture runoff were high in refractory organic N and P. Upstream labile C, N, and P loads were controlled by autochthonous production, with 34‐50% of summer total labile carbon imported as algal biomass. Differentiation of labile and refractory organic forms suggests that while anthropogenic nutrient enrichment has tripled the total nitrogen load, it has resulted in a 6.7‐fold increase in total labile nitrogen load.     

Comparison of Machine Learning Models Performance on Simulating Reservoir Outflow: A Case Study of Two Reservoirs in Illinois,U.S.A.

Reservoir outflow is an important variable for understanding hydrological processes and water resource management. Natural streamflow variation, in addition to the streamflow regulation provided by dams and reservoirs, can make streamflow difficult to understand and predict. This makes them a challenge to accurately simulate hydrologic processes at a daily scale. In this study, three Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), were examined and compared to model reservoir outflow. Past, current, and future hydrologic and meteorological data were used as model inputs, and the outflow of next day was used as prediction. Simulation results demonstrated that all three models can reasonably simulate reservoir outflow. For Carlyle Lake, the coefficient of determination and Nash–Sutcliffe efficiency were each close to one for the three models. The coefficient of determination, relative mean bias, and root mean square error indicated that the SVM performed better than the RF and ANN, but the SVM output displayed a larger relative mean bias than that from RF and ANN. For Lake Shelbyville, the ANN model performed better than RF and SVM when considering the coefficient of determination, Nash–Sutcliffe efficiency, relative mean bias, and root mean square error. The study results demonstrate that the three ML algorithms (RF, SVM, and ANN) are all promising tools for simulating reservoir outflow. Both the accuracy and efficacy of the three ML algorithms are considered to support practitioners in planning reservoir management.