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Here we focused on the co-occurrence pattern on regional and local scales, and on the niche differences of two species of congeneric beetles ( Ochthebius quadricollis and O. lejolisii , Hydraenidae) exclusive of supratidal rockpools. Abundances of adults and larval stages from both species and environmental variables were obtained in 10 pools from 12 localities along the Iberian Mediterranean coast. To determine the local co-existence pattern, we monthly sampled two localities in an annual cycle. On regional and local scales, we found negative correlations between both species’ pool abundances, which suggest spatio-temporal segregation based on their different environmental responses. The OMI analysis detected interspecific niche differences, larger in larvae than adults. The best regression models obtained for O. quadricollis larvae included depth, conductivity, and fine sediments as the main explanatory variables with a positive effect, and distance to sea and CPOM with a negative effect. For O. lejolisii larvae, the best models included CPOM and periphyton with positive effects, while pool area, depth and conductivity negatively affected. Our results suggest that subtle interspecific differences in ecological niches, mainly those related to pool hydroperiod and salinity, could determine spatio-temporal storage effects as the principal mechanisms of co-existence on local and regional scales.

Under shut-in conditions in deepwater drilling, the gas invading the bottomhole ascends along the wellbore and accumulates at the wellhead, forming a high-pressure trap, challenging wellbore pressure prediction and control. The accurate prediction of bottomhole pressure is essential for well control during shut-in conditions. In this study, a new bottomhole pressure prediction model that considers wellbore storage effects was developed to address gas invasion issues during shut-in conditions in deepwater drilling. This model incorporates factors such as the wellbore elasticity, fluid compressibility, and drilling fluid filtration loss. The calculated values show good agreement with experimental values, with the average absolute and relative errors of 2.095 × 10−2 MPa and 3.71%, respectively. Meanwhile, the results indicate that the bottomhole pressure initially increases logarithmically over time and then transitions to a linear increase, and the residual flow and gas ascent significantly influence the bottomhole pressure. Finally, the effects of various parameters on the bottomhole pressure were evaluated. Larger initial pressure differential, exposed thickness, and formation permeability accelerate the increase in bottomhole pressure during residual flow stage, while smaller filter cake permeability and drilling fluid viscosity quicken its increase during gas ascent stage. Drilling fluid density affects the initial pressure and the residual flow duration. The findings of this study would provide theoretical support for well control operations in deepwater drilling.

Rainfall–runoff modelling is one of the key challenges in the field of hydrology. Various approaches exist, ranging from physically based over conceptual to fully data-driven models. In this paper, we propose a novel data-driven approach, using the Long Short-Term Memory (LSTM) network, a special type of recurrent neural network. The advantage of the LSTM is its ability to learn long-term dependencies between the provided input and output of the network, which are essential for modelling storage effects in e.g. catchments with snow influence. We use 241 catchments of the freely available CAMELS data set to test our approach and also compare the results to the well-known Sacramento Soil Moisture Accounting Model (SAC-SMA) coupled with the Snow-17 snow routine. We also show the potential of the LSTM as a regional hydrological model in which one model predicts the discharge for a variety of catchments. In our last experiment, we show the possibility to transfer process understanding, learned at regional scale, to individual catchments and thereby increasing model performance when compared to a LSTM trained only on the data of single catchments. Using this approach, we were able to achieve better model performance as the SAC-SMA + Snow-17, which underlines the potential of the LSTM for hydrological modelling applications.

The metabolic theory of ecology assumes that rates of selection and adaptation for organisms are functions of temperature. Niche theory predicts that strong selection pressure should simplify assemblages as species are extirpated and taxa pre‐adapted for the new environment thrive. Here, we use closed mesocosms to test the prediction that higher temperatures decrease species richness and increase assemblage similarity more and faster than lower temperatures. We incubated two temperate forest soil types at constant temperatures from 10° to 35°, destructively sampling mesocosms at 30, 180, and 440 d. We quantified taxonomic richness and assemblage similarity of soil bacteria using 16S rRNA gene amplicons. As predicted, mesocosms at higher temperatures lost more taxa than those at lower temperature. Contrary to predictions, the simplified assemblages at higher temperatures became less similar to each other over time. After 440 d of incubation, the number of taxa lost was a linear function of the difference between treatment temperature and site mean annual temperature, while assemblage similarity decreased as an accelerating function of this temperature difference.

We give a comprehensive review of Chesson's coexistence theory, summarizing, for the first time, all its fundamental details in one single document. Our goal is for both theoretical and empirical ecologists to be able to use the theory to interpret their findings, and to get a precise sense of the limits of its applicability. To this end, we introduce an explicit handling of limiting factors, and a new way of defining the scaling factors that partition invasion growth rates into the different mechanisms contributing to coexistence. We explain terminology such as relative nonlinearity, storage effect, and growth-density covariance, both in a formal setting and through their biological interpretation. We review the theory's applications and contributions to our current understanding of species coexistence. While the theory is very general, it is not well suited to all problems, so we carefully point out its limitations. Finally, we critique the paradigm of decomposing invasion growth rates into stabilizing and equalizing components: we argue that these concepts are useful when used judiciously, but have often been employed in an overly simplified way to justify false claims.

Telomeres, DNA structures located at the end of eukaryotic chromosomes, shorten with each cellular cycle. The shortening rate is affected by factors associated with stress, and, thus telomere length has been used as a biomarker of ageing, disease, and different life history trade-offs. Telomere research has received much attention in the last decades, however there is still a wide variety of factors that may affect telomere measurements and to date no study has thoroughly evaluated the possible long-term effect of a storage medium on telomere measurements. In this study we evaluated the long-term effects of ethanol on relative telomere length (RTL) measured by qPCR, using blood samples of magpies collected over twelve years and stored in absolute ethanol at room temperature. We firstly tested whether storage time had an effect on RTL and secondly we modelled the effect of time of storage (from 1 to 12 years) in differences in RTL from DNA extracted twice in consecutive years from the same blood sample. We also tested whether individual amplification efficiencies were influenced by storage time, and whether this could affect our results. Our study provides evidence of an effect of storage time on telomere length measurements. Importantly, this effect shows a pattern of decreasing loss of telomere sequence with storage time that stops after approximate 4 years of storage, which suggests that telomeres may degrade in blood samples stored in ethanol. Our method to quantify the effect of storage time could be used to evaluate other storage buffers and methods. Our results highlight the need to evaluate the long-term effects of storage on telomere measurements, particularly in long-term studies.

This study presents a comprehensive investigation of wellbore storage effects and non‐Darcy flow in pumping well systems using a multiphysics numerical model. The model incorporates the Reynolds‐averaged Navier‐Stokes equations coupled with a moving free surface to simulate the flow field and drawdown in the wellbore. Hydraulic behavior of the system, including well and aquifer drawdown, pumped water ratio, aquifer flow nonlinearity, and wellbore flow field, is analyzed and compared with simplified 1‐D models. This study highlights the presence of a vortex in the wellbore flow field induced by large Reynolds number and the uneven stress distribution at the screen. This vortex influences the wellbore drawdown and introduces 2‐D flow in the surrounding aquifer, which further contributes to the longer travel paths for groundwater particles and increased hydraulic pressure consumption. The results show that non‐Darcy flow, coupled with wellbore storage effects, leads to higher drawdown in the pumping well compared to Darcy flow cases. The aquifer drawdown exhibits a similar temporal pattern but with decreasing deviation at larger distances due to the cone of depression. The pumped water ratio indicates the challenge of supplying outflow at the intake from aquifer storage, with nonlinear flow resulting in a smaller ratio compared to linear cases. A nonlinearity ratio is defined to illustrate the expansion of nonlinear flow regions over time, their convergence to a predictable quasi‐steady‐state shape, which is influenced by the Forchheimer parameter, and the gradual transition to Darcy flow away from the wellbore. Plain Language Summary This study focuses on understanding the behavior of water flow in pumping wells considering two important factors: wellbore storage and non‐Darcy flow. Wellbore storage refers to the amount of water stored inside the well, while non‐Darcy flow describes the flow behavior in the surrounding aquifer. Using a computer model, the researchers found that as pumping continues, the areas of nonlinear flow expand and eventually settle into a stable pattern. This transition from nonlinear flow to a more predictable behavior is influenced by the properties of the aquifer. The study also revealed that the presence of wellbore storage and the flow patterns near the well have a significant impact on the overall hydraulic performance. These findings have practical implications for improving the design and operation of pumping wells. Key Points This study investigates the combined effects of wellbore storage and non‐Darcy flow in pumping well systems using a multiphysics model The findings reveal the expansion of nonlinear flow regions, transition to a quasi‐steady‐state, and the gradual shift toward Darcy flow The study highlights the formation of vortices and 2D flow near the wellbore, which affect flow paths and hydraulic pressure consumption

Buildings often affect overland flow propagation in urban areas. Building walls change the direction and velocity of flow and can exclude interior spaces from flooding. However, water may intrude buildings when the flood level exceeds the height of protection. This study develops an inundation model that represents the resistance and the storage effects of buildings. This model was applied to central Taipei City, which is surrounded by the Danshui and Keelung Rivers. The inundation depth and extent were compared from models where the effects of buildings were included and excluded. Rainfall data from the Typhoon Nari event in 2001 was used in the simulation. The results showed that in the case where the effects of buildings were excluded inundation was underestimated in the metropolitan areas. Where the effects of buildings were considered in the model, the presented inundation model reproduces the inundation results more comparable with the observed flooding situation.

Understanding the origins and maintenance of biodiversity remains one of biology’s grand challenges. From theory and observational evidence, we know that variability in environmental conditions through time is likely critical to the coexistence of competing species. Nevertheless, experimental tests of fluctuation-driven coexistence are rare and have typically focused on just one of two potential mechanisms, the temporal storage effect, to the neglect of the theoretically equally plausible mechanism known as relative nonlinearity of competition. We combined experiments and simulations in a system of nectar yeasts to quantify the relative contribution of the two mechanisms to coexistence. Resource competition models parameterized from single-species assays predicted the outcomes of mixed-culture competition experiments with 83% accuracy. Model simulations revealed that both mechanisms have measurable effects on coexistence and that relative nonlinearity can be equal or greater in magnitude to the temporal storage effect. In addition, we show that their effect on coexistence can be both antagonistic and complementary. These results falsify the common assumption that relative nonlinearity is of negligible importance, and in doing so reveal the importance of testing coexistence mechanisms in combination.

Biomass pellets provide a pivotal opportunity in promising energy transition scenarios as a renewable source of energy. A large share of the current utilization of pellets is facilitated by intensive global trade operations. Considering the long distance between the production site and the end-user locations, pellets may face fluctuating storage conditions, resulting in their physical and chemical degradation. We tested the effect of different storage conditions, from freezing temperatures (−19 °C) to high temperature (40 °C) and humidity conditions (85% relative humidity), on the physicochemical properties of untreated and torrefied biomass pellets. Moreover, the effect of sudden changes in the storage conditions on pellet properties was studied by moving the pellets from the freezing to the high temperature and relative humidity conditions and vice versa. The results show that, although storage at one controlled temperature and RH may degrade the pellets, a change in the temperature and relative humidity results in higher degradation in terms of higher moisture uptake and lower mechanical strength.