The gut microbiome is an integral part of a species' ecology, but we know little about how host characteristics impact its development in wild populations. Here, we explored the role of such intrinsic factors in shaping the gut microbiome of northern elephant seals (Mirounga angustirostris) during a critical developmental window of 6 weeks after weaning, when the pups stay ashore without feeding. We found substantial sex differences in the early‐life gut microbiome, even though males and females could not yet be distinguished morphologically. Sex and age both explained around 15% of the variation in gut microbial beta diversity, while microbial communities sampled from the same individual showed high levels of similarity across time, explaining another 40% of the variation. Only a small proportion of the variation in beta diversity was explained by health status, assessed by full blood counts, but clinically healthy individuals had a greater microbial alpha diversity than their clinically abnormal peers. Across the post‐weaning period, the northern elephant seal gut microbiome was highly dynamic. We found evidence for several colonization and extinction events as well as a decline in Bacteroides and an increase in Prevotella, a pattern that has previously been associated with the transition from nursing to solid food. Lastly, we show that genetic relatedness was correlated with gut microbiome similarity in males but not females, again reflecting early sex differences. Our study represents a naturally diet‐controlled and longitudinal investigation of how intrinsic factors shape the early gut microbiome in a species with extreme sex differences in morphology and life history.

34The gut microbiome is an integral part of a species' ecology, but we know little about how host characteristics 35 impact its development in wild populations. Here, we explored the role of such intrinsic factors in shaping the gut 36 microbiome of northern elephant seals during a critical developmental window of six weeks after weaning, when 37 the pups stay ashore without feeding. We show that the early-life gut microbiome is already substantially different 38 in male and female pups, even though males and females cannot yet be distinguished morphologically. Sex and 39 age both explain around 15% of the variation in gut microbial beta diversity, while microbial communities sampled 40 from the same individual show high levels of similarity across time, explaining another 40% of the variation. Only 41 a small proportion of the variation in beta diversity is explained by health status, but healthy individuals have a 42 greater microbial alpha diversity than their non-healthy peers. Across the post-weaning period, the elephant seal 43 gut microbiome is highly dynamic. We found evidence for several colonisation and extinction events as well as a 44 decline in Bacteriodes and an increase in Prevotella, a pattern that has previously been associated with the 45 transition from nursing to solid food. Lastly, we show that genetic relatedness is correlated with gut microbiome 46 similarity in males but not females, again reflecting substantial early sex-differences. Our study represents a 47 naturally diet-controlled and longitudinal investigation of how intrinsic factors shape the early gut microbiome in 48 a species with extreme sex differences in morphology and life history. 49 50 51 promoting the development of organs, assisting nutrient uptake and priming and modulating the immune system 57

Modeling of irrigation and agricultural drainage requires knowledge of the soil hydraulic properties. However, uncertainty in the direct measurement of the saturation moisture content (θs) has been generated in several methodologies for its estimation, such as Pedotransfer Functions (PTFs) and Artificial Neuronal Networks (ANNs). In this work, eight different PTFs were developed for the (θs) estimation, which relate to the proportion of sand and clay, bulk density (BD) as well as the saturated hydraulic conductivity (Ks). In addition, ANNs were developed with different combinations of input and hidden layers for the estimation of θs. The results showed R2 values from 0.9046≤R2≤0.9877 for the eight different PTFs, while with the ANNs, values of R2>0.9891 were obtained. Finally, the root-mean-square error (RMSE) was obtained for each ANN configuration, with results ranging from 0.0245≤RMSE≤0.0262. It was found that with particular soil characteristic parameters (% Clay, % Silt, % Sand, BD and Ks), accurate estimate of θs is obtained. With the development of these models (PTFs and ANNs), high R2 values were obtained for 10 of the 12 textural classes.

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in the unit of time per unit of the aquifer L 3 , υ = υ (H) is the drainable porosity as a head function, and K s is the saturated hydraulic conductivity L T −1. The storage capacity, see [24], is: μ (H) = θ s − θ(H − H s), where θ s is the saturated volumetric water content L 3 L −3 , and θ(H − H s) represents the water content evolution in the position z = H s , while the free surface decreases, and z is the elevation of ground surface L. 2.2. The drainable porosity To calculate the storage capacity and the drainable porosity it is necessary to provide the soil water retention curve. The model of van Genuchten [25] was accepted in field and laboratory Agroecology 102 Soil Salinity Control in Irrigated Land with Agricultural Drainage Systems