Most of the robust artificial intelligence (AI)-based constitutive models are developed with synthetic datasets generated from traditional constitutive models. Therefore, they fundamentally rely on the traditional constitutive models rather than laboratory test results. Also, their potential use within geotechnical engineering communities is limited due to the unavailability of datasets along with the model code files. In this study, the data-driven constitutive models are developed using only laboratory test databases and deep learning (DL) techniques. The laboratory database was prepared by conducting cyclic direct simple shear (CDSS) tests on reconstituted sand, that is, PDX sand. The stacked long short-term memory (LSTM) network and its variants are considered for developing the predictive models of the shear strain (gamma [%]) and excess pore pressure ratio (ru) time histories. The suitable input parameters (IPs) are selected based on the physics behind the generation of ru and gamma (%) of the liquefiable sands. The predicted responses of gamma (%) and ru agree well in most cases and are used to predict the dynamic soil properties of the PDX sand. The same modeling framework is extended for other sand and compared with existing AI-based constitutive models to verify its practical applicability. In summary, it is observed that though the trained models predicted the time histories of ru and gamma reasonably well; however, they struggled to predict the hysteresis loops at higher cycles. Therefore, more research is needed to verify and enhance the predictability of existing AI-based models in the future before using them in practice for simulating cyclic response.

White grubs are known as the National pest of India due to their wide distribution and economic damage. Brahmina coriacea grubs are restricted to Tibet, China and the Himalayan region in Jammu and Kashmir, Himachal Pradesh and Uttarakhand. The grubs of B. coriacea were collected from the soil of Solanum tuberosum, Zea mays, Pisum sativum, Rosa rubiginosa, Phaseolus vulgaris, Malus pumila and Pyrus communis from different ecosystems of eight different locations in Himachal Pradesh, India, by the pit sampling method. The grubs of B. coriacea were identified by examining the raster pattern. There was variation in the morphology and biology among different populations of B. coriacea in Himachal Pradesh. The morphological parameters and biological differences were also recorded, such as fecundity rate and damage potential among different ecotypes of B. coriacea collected from various locations. A total of 102 morphologically distinct bacterial isolates were isolated from the gut of different populations of B. coriacea. The gut microbial diversity and abundance were recorded as maximum in the hind gut, compared to other gut compartments. A total of 11 cellulolytic bacterial isolates were identified using morphological, biochemical and 16S rRNA molecular methods. The cellulolytic index of bacterial strains ranged from 0.33 to 2.0. The 11 gut cellulolytic bacteria were identified by using morphological, biochemical and 16S rRNA gene analysis. Staphylococcus haemolyticus was isolated from the Nauni population of B. coriacea, and it is the first report from the gut of scarabaeids. This is an opportunistic human pathogen but a useful endosymbiont in the grubs of B. coriacea. Bacillus thuringiensis as a biological agent, Staphylococcus cohnii, Ralstonia mannitolilytica and some Bacillus sp. were reported for the first time from B. coriacea grubs in India. The potent cellulose-degrading bacteria can be used in industries for decomposing agricultural waste, in pulp and paper industries and for biofuel production.

Colorado potato beetle, Leptinotarsa decemlineata, wireworms and white grubs are important pests of potato that are challenging to manage. This study evaluated three endemic entomopathogenic nematodes (EPNs) (Steinernema carpocapsae 'NY01', S. feltiae 'NY04', and Heterorhabditis bacteriophora 'Oswego') as biocontrol agents against L. decemlineata, wireworms and white grubs in New York. The efficacy of individual EPN species and their combinations on L. decemlineata larval mortality was assessed via soil-based bioassays in the laboratory. Additionally, L. decemlineata survival and percentage of tubers damaged by wireworms and white grubs were evaluated in field trials in which combinations of pairs of EPN species were applied to the soil at least one month prior to initiating the experiment. Results from bioassays indicated that among the three EPN species, L. decemlineata late instars were most susceptible to H. bacteriophora 'Oswego'. Additionally, larval mortality was generally higher (14% on average) using pairs of EPN species compared to single species. Soil applications of pairs of EPN species prior to potato planting did not affect L. decemlineata adult survival either during the summer or following spring. However, tuber damage caused by wireworms and white grubs was reduced by 40% using a combination of H. bacteriophora 'Oswego' and S. feltiae 'NY04'. Overall, EPNs applied in soil have potential as biocontrol agents for soil-dwelling pests like wireworms and white grubs in potato, and their efficacy also may extend beyond a single cropping season, but do not seem to be an effective tool for L. decemlineata management in potato.

Featured Application The Middle European ecotype of Cd hyperaccumulator Solanum nigrum L. ssp. nigrum was found to show extraordinarily strong tolerance to high contents of Cd in soil (over 50 mg kg-1 Cd) and high Cd accumulation capacity at this concentration range. Its adapted A50 variety obtained from the seeds of first-generation plants grown in soil with 50 mg kg-1 Cd appeared to display further considerable enhancement of resistance to Cd stress, accumulation capacity, and healthy state. This makes the Middle European ecotype and its adapted variety A50 particularly useful to sustainable decontamination of heavily polluted hot spots in degraded post-industrial areas.Abstract The Cd hyperaccumulator Solanum nigrum L. exhibits a cosmopolitan character and proven high and differentiated efficiency. This suggests the possibility of optimizing its Cd phytoremediation capacity and applicability through searching among remote ecotypes/genotypes. However, the extensive studies on this hyperaccumulator have been limited to Far East (Asian) regions. Pioneer pot experiments on the Middle European ecotype of S. nigrum within a concentration range of 0-50 mg kg-1 Cd in soil revealed its Cd phytoremediation capacity to be comparable to Asian ecotypes but with a fundamentally different Cd tolerance threshold. While biomass of the Asian ecotypes declined sharply at Csoil approximate to 10 mg kg-1 Cd, in the Middle European ecotype, a gradual mild biomass decrease occurred within the whole Csoil approximate to 0-50 mg kg-1 Cd range with no toxic symptoms. Its adapted A50 variety was obtained from the seeds of first-generation plants grown in soil with Csoil approximate to 50 mg kg-1 Cd. In this variety, Cd tolerance, accumulation performance, and all physiological parameters (chlorophyll, carotenoids, RuBisCO, and first- and second-line defense anti-oxidant activity) were significantly enhanced, while cell damage by ROS was considerably lesser. This makes the Middle European ecotype and its adapted variety A50 particularly useful to sustainable decontamination of heavily polluted hot spots in degraded post-industrial areas.

We report for the first time that larvae of the genus Bothynus Hope (Coleoptera: Melolonthidae) caused economic damage to lucerne (Medicago sativa L., Fabaceae) crops in General Acha, province of La Pampa, Argentina. In two consecutive years (2021 and 2022), this insect infested 150 ha of lucerne, causing seedling losses of 80 ha. Based on soil sampling and laboratory insect rearing, the species was identified as Bothynus striatellus (Faimaire) (Coleoptera: Melolonthidae). Information is given here on the damage recorded in this forage crop, the density of the larvae observed at the time of damage assessment and the morphological characteristics of the third instar larvae reported in this crop in Argentina.

Soil disturbances caused by large animals impact soil biodiversity and potentially alter forest ecosystem functioning and productivity. However, most studies have focused on the effects of wild boar infestations on aboveground vegetation and soil physical and chemical properties. Little is known about the influence of wild boar grubbing on the soil faunal community within forested ecosystems. To address this knowledge gap, we conducted a long-term (10-year) exclosure experiment to investigate the responses of soil nematode communities to wild boar grubbing and seasonal variations in a broad-leaved Korean pine forest in Changbai Mountain, China. The results indicated that wild boar grubbing did not significantly impact soil nematode abundance, genus richness, diversity indices (Shannon-Wiener diversity index, Simpson index, and evenness index), and ecological indices (enrichment index, channel index, structural index, and basal index). However, we observed that grubbing reduced the relative abundance of plant parasites while increased that of bacterivores and the maturity index (MI), leading to changes in nematode community composition. Notably, the influence of grubbing was more pronounced in the spring than in the autumn. Although season itself did not significantly affect soil nematode genus richness and diversity indices, it did affect soil nematode relative abundance, bacterivores, omnivorespredators, plant parasites, K-strategistis, r-strategistis, MI, enrichment index, and channel index. Long-term wild boar grubbing appeared to mitigate seasonal effects on soil nematode communities, resulting in higher MI and increased stability in nematode community abundance. Our findings suggest that changes in soil parameters, such as soil NH4+, soil pH, and soil NO3-, likely mediate the observed impact of wild boars on the soil nematode community. In summary, our study demonstrated that wild boar grubbing altered the structure of soil nematode communities, albeit with seasonal variations, indicating that the effects of wild boar activity on forest soil ecosystems influence biogeochemical cycles through changes in nematode community composition rather than nematode genera richness.

Robust streamflow simulation at glacial basins is essential for the improvement of water sustainability assessment, water security evaluation, and water resource management under the rapidly changing climate. Therefore, we proposed a hybrid modelling framework to link the SWAT+ model considering glacial hydrological processes (GSWAT+) with Gated Recurrent Unit (GRU) neural networks to improve the model simulations and to establish a framework for the robust simulation and forecast of high and low flows in glacial river basins, which could be further used for the explorations of extreme hydrological events under a warming climate. The performance of different models (GSWAT+, GRU, and GRU-GSWAT+, respectively) were thoroughly investigated based on numerical experiments for two data-scarce glacial watersheds in Northwest China. The results suggested that the hybrid model (GRU-GSWAT+) outperformed both the individual deep learning (DL) model (GRU) and the conventional hydrological model (GSWAT+) in terms of simulation and prediction accuracy. Notably, the proposed hybrid model considerably enhanced the simulations of low and high flows that the conventional GSWAT+ failed to capture. Furthermore, utilizing suitable data integration (DI) schemes on feature and target sequences can substantially help to strengthen model stability and representativeness for monthly and annual streamflow sequences. Specifically, introducing one order differential method and decomposition approach, such as ensemble empirical signal decomposition (EEMD) and complete EEMD with adaptive noise (CEEMDAN), into feature and target sequences enriched the learnable ancillary information, which consequently strengthened the predictive performance of the proposed model. Overall, the proposed hybrid model with the suitable DI scheme has the potential to significantly enhance the accuracy of streamflow simulation in data-scarce glacial river basins. This hybrid model not only upheld the fundamental physical principles from the GSWAT+ model, but also considerably mitigated the accumulated bias errors, which caused by the shortage of climate data and inadequate hydrological principles, by using DL based model and DI schemes.

Broad-scale changes in arctic-alpine vegetation and their global effects have long been recognized and labeled one of the clearest examples of the terrestrial impacts of climate change. Arctic-alpine dwarf shrubs are a key factor in those processes, responding to accelerated warming in complex and still poorly understood ways. Here, we look closely into such responses of deciduous and evergreen species, and for the first time, we make use of high-precision dendrometers to monitor the radial growth of dwarf shrubs at unprecedented temporal resolution, bridging the gap between classical dendroecology and the underlying growth physiology of a species. Using statistical methods on a five-year dataset, including a relative importance analysis based on partial least squares regression, linear mixed modeling, and correlation analysis, we identified distinct growth mechanisms for both evergreen (Empetrum nigrum ssp. hermaphroditum) and deciduous (Betula nana) species. We found those mechanisms in accordance with the species respective physiological requirements and the exclusive micro-environmental conditions, suggesting high phenotypical plasticity in both focal species. Additionally, growth in both species was negatively affected by unusually warm conditions during summer and both responded to low winter temperatures with radial stem shrinking, which we interpreted as an active mechanism of frost protection related to changes in water availability. However, our analysis revealed contrasting and inter-annually nuanced response patterns. While B. nana benefited from winter warming and a prolonged growing season, E. hermaphroditum showed high negative sensitivity to spring cold spells after an earlier growth start, relying on additional photosynthetic opportunities during snow-free winter periods. Thus, we conclude that climate-growth responses of dwarf shrubs in arctic-alpine environments are highly seasonal and heterogenic, and that deciduous species are overall likely to show a positive growth response to predicted future climate change, possibly dominating over evergreen competitors at the same sites, contributing to the ongoing greening trend.