Ecological Applications Research Articles

Coexistence and Co-prosperity: Ecological Perspectives and Application to Irony Picture Books

Coexistence and Co-prosperity: Ecological Perspectives and Application to Irony Picture Books

Ecological vulnerability assessment and spatial-temporal variations analysis in typical ecologically vulnerable areas of China

Ecological vulnerability assessment is crucial for environment protection, ecological restoration and resource utilization. However, many former studies have limitations in the indicator system of the assessment, which were not comparable for different types of ecologically vulnerable areas. It is difficult to apply directly to the ecological vulnerability assessment of different types and in various regions. Aiming to solve these problems, the study proposed a well-established and comprehensive indicator system for ecological vulnerability assessment and conducted ecological vulnerability assessment application of five types of typical ecologically vulnerable areas of China based on remote sensing, meteorological, geographic and other data. The results show that the average EVIs value of Zhangbei County ranging from 0.525 to 0.559 are the highest among the five research areas during the four periods, followed by Zoige region and Xiamen bay. However, the region with the lowest average EVI value varies. In 2005 and 2015, it was Taihe County, while in 2010 and 2020, it was the Sanjiangyuan region. The variation of average EVIs in the five typical areas presents slight fluctuation and remains generally stable from 2005 to 2020. It indicates that the environmental protection measures and projects undertaken by the Chinese government in recent years have had a striking effect, curbing the trend of ecological environment deterioration.

Protein Set Transformer: A protein-based genome language model to power high diversity viromics.

Exponential increases in microbial and viral genomic data demand transformational advances in scalable, generalizable frameworks for their interpretation. Standard homology-based functional analyses are hindered by the rapid divergence of microbial and especially viral genomes and proteins that significantly decreases the volume of usable data. Here, we present Protein Set Transformer (PST), a protein-based genome language model that models genomes as sets of proteins without considering sparsely available functional labels. Trained on >100k viruses, PST outperformed other homology- and language model-based approaches for relating viral genomes based on shared protein content. Further, PST demonstrated protein structural and functional awareness by clustering capsid-fold-containing proteins with known capsid proteins and uniquely clustering late gene proteins within related viruses. Our data establish PST as a valuable method for diverse viral genomics, ecology, and evolutionary applications. We posit that the PST framework can be a foundation model for microbial genomics when trained on suitable data.

Application and prospect of landscape ecology in territorial spatial planning.

Territorial spatial planning could achieve the integration of various plans, resulting in a unified "multi-plan integration" map. Such planning emphasizes the efficient use of territorial spatial patterns and structures to ensure functional perfection, and serves as the spatial framework for building a modern socialist country, particularly in the areas of ecological security and ecological civilization. The past few decades have seen rapid advances in the development of landscape ecology in China. The core concept of "pattern-process-function" has gained significant progress and been widely applied in the initial phase of territorial spatial planning at various levels. We outlined the advancements in the territorial spatial planning system and the core research theories and technologies in landscape ecology. We discussed the progress and shortcomings of key theories and methods of landscape ecology in practical applications of territorial spatial planning, such as ecological security patterns, pattern and process, and scale effects. We proposed the future application of landscape ecology theories and technologies in territorial spatial planning, including overall ecological effects, scale effects, and regional ecological network optimization. Future developments in landscape ecology, especially research on the "human-place-ecology" coupling based on the latest Big Data and AI technology for sustainable development, will provide robust theoretical and methodological supports for the scientific formulation of territorial spatial planning in China.

Latitudinal responses of litter decomposition to solar radiation.

Photodegradation driven by solar radiation has been confirmed as an important driving factor for litter decomposition. However, previous single-site studies could not quantify the relative contribution of variation in solar radiation to litter decomposition. To address it, we conducted a field experiment in Heshan National Field Research Station of Forest Ecosystem, Guangdong (Heshan Station, south subtropical climate), Jigongshan Ecological Research Station, Xinyang, Henan (Jigongshan Station, north subtropical climate) and Daqinggou Ecological Research Station, Institute of Applied Ecology, Chinese Academy of Sciences (Daqinggou Station, temperate climate) at intervals of 10 degrees. We examined litter decomposition of Populus davidiana and Larix olgensis, two species with significant differences in initial litter quality through an in-situ spectral-attenuation experiment. Treatments included full-spectrum, No-UV-B (attenuating UV-B radiation <315 nm) and No-UV & Blue (attenuating all UV and blue wavelengths <500 nm). After nearly 1-year decomposition, litter dry mass remaining of P. davidiana and L. olgensis under full-spectrum treatment was lowest at Heshan (30.2% and 36.3%), and highest at Jigongshan (37.3% and 45.8%). Among all sites, litter dry mass remaining was lowest under the full-spectrum, and lower than that of No-UV-B and No-UV & blue. UV and blue light significantly increased litter mass loss of P. davidiana and L. olgensis, with contributions of 59.7% and 57.0% (Heshan), 46.4% and 42.1% (Jigongshan), and 39.0% and 45.9% (Daqinggou), respectively. The contribution of UV-A and blue light (315-500 nm) was greater than UV-B (280-315 nm); the cumulative irradiance, soil temperature and moisture were the main driving factors for litter photodegradation.

Exploring run-and-tumble movement in confined settings through simulation.

Motion in bounded domains is a fundamental concept in various fields, including billiard dynamics and random walks on finite lattices, and has important applications in physics, ecology, and biology. An important universal property related to the average return time to the boundary, the Mean Path Length Theorem (MPLT), has been proposed theoretically and experimentally confirmed in various contexts. We investigated a wide range of mechanisms that lead to deviations from this universal behavior, such as boundary effects, reorientation, and memory processes. This study investigates the dynamics of run-and-tumble particles within a confined two-dimensional circular domain. Through a combination of theoretical approaches and numerical simulations, we validate the MPLT under uniform and isotropic particle inflow conditions. This research demonstrates that although the MPLT is generally applicable for different step length distributions, deviations occur for non-uniform angular distributions, non-elastic boundary conditions, or memory processes. These results underline the crucial influence of boundary interactions and angular dynamics on the behavior of particles in confined spaces. Our results provide new insights into the geometry and dynamics of motion in confined spaces and contribute to a better understanding of a broad spectrum of phenomena ranging from the motion of bacteria to neutron transport. This type of analysis is crucial in situations where inhomogeneity occurs, such as multiple real-world scenarios within a limited domain.

Characterizing the structural complexity of the Earth’s forests with spaceborne lidar

Forest structural complexity is a key element of ecosystem functioning, impacting light environments, nutrient cycling, biodiversity, and habitat quality. Addressing the need for a comprehensive global assessment of actual forest structural complexity, we derive a near-global map of 3D canopy complexity using data from the GEDI spaceborne lidar mission. These data show that tropical forests harbor most of the high complexity observations, while less than 20% of temperate forests reached median levels of tropical complexity. Structural complexity in tropical forests is more strongly related to canopy attributes from lower and middle waveform layers, whereas in temperate forests upper and middle layers are more influential. Globally, forests exhibit robust scaling relationships between complexity and canopy height, but these vary geographically and by biome. Our results offer insights into the spatial distribution of forest structural complexity and emphasize the importance of considering biome-specific and fine-scale variations for ecological research and management applications. The GEDI Waveform Structural Complexity Index data product, derived from our analyses, provides researchers and conservationists with a single, easily interpretable metric by combining various aspects of canopy structure.

The molecular regulatory mechanism of reed canary grass under salt, waterlogging, and combined stress was analyzed by transcriptomic analysis

BackgroundReed canary grass has been identified as a suitable species for restoring plateau wetlands and understanding plant adaptation mechanisms in wetland environments. In this study, we subjected a reed canary grass cultivar ‘Chuanxi’ to waterlogging, salt, and combined stresses to investigate its phenotypic characteristics, physiological indices, and transcriptome changes under these conditions.ResultsThe results revealed that the growth rate was slower under salt stress than under waterlogging stress. The chlorophyll content and energy capture efficiency of the PS II reaction center decreased with prolonged exposure to each stress. Conversely, while the activities of enzymes associated with respiratory metabolism, as well as MDA, PRO, Na+, and K+-ATPase, increased. The formation of distinct aerenchyma was observed under waterlogging stress and combined stress. Transcriptome sequencing analysis identified 5,379, 4,169, and 14,993 DEGs under CK vs. W, CK vs. S, and CK vs. SW conditions, respectively. The WRKY was found to be the most abundant under waterlogging stress, whereas the MYB predominated under salt stress and combined stress. Glutathione metabolic pathways and Plant hormone signal transduction have also been found to play important roles in stress.ConclusionBy integrating phenotypic, physiological, anatomical, and transcriptomic, this research provides valuable insights into how reed canary grass responds to salt, waterlogging, and combined stresses. These findings may inform the ecological application of reed canary grass in high-altitude wetlands and for breeding purposes.

Harnessing artificial intelligence for efficient systematic reviews: A case study in ecosystem condition indicators

Effective evidence synthesis is important for the integration of scientific research into decision-making. However, fully depicting the vast mosaic of concepts and applications in environmental sciences and ecology often entails a substantial workload. New Artificial Intelligence (AI) tools present an attractive option for addressing this challenge but require sufficient validation to match the vigorous standards of a systematic review. This article demonstrates the use of generative AI in the selection of relevant literature as part of a systematic review on indicators of ecosystem condition. We highlight, through the development of an optimal prompt to communicate inclusion and exclusion criteria, the need to describe ecosystem condition as a multidimensional concept whilst also maintaining clarity on what does not meet the criteria of comprehensiveness. We show that, although not completely infallible, the GPT-3.5 model significantly outperforms traditional literature screening processes in terms of speed and efficiency whilst correctly selecting 83 % of relevant literature for review. Our study highlights the importance of precision in prompt design and the setting of query parameters for the AI model and opens the perspective for future work using language models to contextualize complex concepts in the environmental sciences. Future development of this methodology in tandem with the continued evolution of the accessibility and capacity of AI tools presents a great potential to improve evidence synthesis through gains in efficiency and possible scope.

The riverscape on a chip: High-throughput qPCR enables basin-wide fishery assessments

To achieve reliable detection of environmental DNA from multiple species, a method which combines the specificity of single-taxon assays with the broad taxonomic coverage of metabarcoding is needed. High-throughput quantitative PCR (HT-qPCR) has emerged as one such method that holds particular promise for ecological applications. Here, we present the development and validation of a HT-qPCR biochip (i.e., biochip) protocol for a suite of western North American fishes with high cultural, economic, and ecological significance. Coupling this biochip with systematically distributed eDNA samples collected by citizen scientists, we evaluated the distribution of multiple species throughout a large river basin in the U.S. Pacific Northwest. Patterns of detection using the biochip were comparable to those using single-taxon qPCR (ST-qPCR; mean concordance = 0.917), despite the biochip using 90% less DNA per taxon and reducing costs by an estimated 40%. Comparisons between biochip results and distributions derived from conventional methods demonstrate that this approach not only offers more reliable and high-resolution distribution data for these species but also achieves this more efficiently than traditional sampling methods.

Biotechnological frontiers in harnessing allelopathy for sustainable crop production.

Allelopathy, the phenomenon in which plants release biochemical compounds that influence the growth and development of neighbouring plants, presents promising opportunities for revolutionizing agriculture towards sustainability. This abstract explores the role of biotechnological advancements in unlocking the potential of allelopathy for sustainable crop production and its applications in agriculture, ecology, and natural resource management. By combining molecular, genetic, biochemical, and bioinformatic tools, researchers can unravel the complexities of allelopathic interactions and their potential for sustainable crop production and environmental stewardship. The development of novel management methods for weed control is getting a lot of attention with the introduction of new genetic technologies such as Gene drive, Transgene technologies, Gene silencing, Marker-assisted selection (MAS), and Clustered regularly interspaced short palindromic repeats (CRISPR-Cas9). By strengthening competitive characteristics these tools hold great promise for boosting crops' ability to compete with weeds. Considering recent literature, this review highlights the genetic, transcriptomics, and metabolomics approaches to allelopathy. Employing allelopathic properties in agriculture offer sustainable benefits like natural weed management, pest management, and reduced chemical pollution, but challenges include environmental factors, toxicity, regulatory hurdles, and limited resources. Effective integration requires continued research, regulatory support, and farmer education​. Also, we aimed to identify the biotechnological domains requiring more investigation and to provide the basis for future advances through this assessment.

Comparative genomics of Metarhizium brunneum strains V275 and ARSEF 4556: unraveling intraspecies diversity.

Entomopathogenic fungi belonging to the Order Hypocreales are renowned for their ability to infect and kill insect hosts, while their endophytic mode of life and the beneficial rhizosphere effects on plant hosts have only been recently recognized. Understanding the molecular mechanisms underlying their different lifestyles could optimize their potential as both biocontrol and biofertilizer agents, as well as the wider appreciation of niche plasticity in fungal ecology. This study describes the comprehensive whole genome sequencing and analysis of one of the most effective entomopathogenic and endophytic EPF strains, Metarhizium brunneum V275 (commercially known as Lalguard Met52), achieved through Nanopore and Illumina reads. Comparative genomics for exploring intraspecies variability and analyses of key gene sets were conducted with a second effective EPF strain, M. brunneum ARSEF 4556. The search for strain- or species-specific genes was extended to M. brunneum strain ARSEF 3297 and other species of genus Metarhizium, to identify molecular mechanisms and putative key genome adaptations associated with mode of life differences. Genome size differed significantly, with M. brunneum V275 having the largest genome amongst M. brunneum strains sequenced to date. Genome analyses revealed an abundance of plant-degrading enzymes, plant colonization-associated genes, and intriguing intraspecies variations regarding their predicted secondary metabolic compounds and the number and localization of Transposable Elements. The potential significance of the differences found between closely related endophytic and entomopathogenic fungi, regarding plant growth-promoting and entomopathogenic abilities, are discussed, enhancing our understanding of their diverse functionalities and putative applications in agriculture and ecology.

Exploring the potential of chestnut (Castanea sativa Mill.): a comprehensive review and conceptual mapping

BackgroundCastanea sativa Mill. is important for ecosystems and societies. Its rich historical and cultural significance, remarkable ecological contributions, and diverse applications have inspired scientific research. This comprehensive review and conceptual mapping of chestnut research consolidates existing knowledge, identifies emerging trends, and highlights untapped potential to inform future investigations. First, the Scopus database was searched to retrieve all data-driven articles in English related to C. sativa published in English from 1951 to 2023. Second, the R language, Scopus Analytics, and VOSviewer were used to analyze the year of publication, authors, countries, affiliations, keywords, and citations. Finally, network analysis was performed to evaluate the hotspots and developmental trends of C. sativa. A total of 1889 research articles were recovered.ResultsThe articles showed an exponential progression, with a regression coefficient of 0.9435 (R2) and an annual growth rate of 6.28%. Italy (19.87%), Spain (15.56%), Portugal (13.39%), Turkey (6.92%), and Switzerland (5.17%) were the most prolific countries. C. sativa (798), sweet chestnut (54), cryphonectria parasitica (44), honey (38), phenolic compounds (35), chestnut blight (33) and antioxidant activity (31) are the keywords that occur the most frequently. The main research groups in the thematic map are "forest management," "Cryphonectria parasitica," "wood," "Spain" and "ethnobotany." Research on C. sativa has all the basic, motor, niche, and emerging or declining themes. Forest management, drought, Gnomoniopsis smithogilvyi, C. sativa shells, amino acids, honey, phenolic compounds, hydrolyzable tannins, antioxidant capacity, antioxidants, and extractives are trending topics.ConclusionsThis bibliometric analysis highlights the importance of C. sativa research, revealing its ecological contributions, cultural significance, and diverse applications. Future studies should focus on forest management, drought resistance, and bioactive properties to ensure sustainable utilization.

Everywhere we look around: Aerial eDNA to capture fungal diversity

AbstractResearch Highlight discussing: Runnel, K., Lõhmus, P., Küngas, K., Marmor‐Ohtla, L., Palo, A., Pütsepp, G., Tamm, H., Tammekänd, I., &amp; Lõhmus, A. (2024). Aerial eDNA contributes vital information for fungal biodiversity assessment. Journal of Applied Ecology, https://doi.org/10.1111/1365‐2664.14691. Fungi play key roles in ecosystems, yet it is not clear how best to capture their diversity or monitor their presence, especially for those species of particular conservation concern. In this issue of the Journal of Applied Ecology Runnel et al. address this problem by comparing different methodologies to estimate the diversity of lichen‐forming fungi and wood‐inhabiting basidiomycetes at a forest stand scale. Pairing aerial eDNA sampling with visual observation‐based surveys better captured the full spectrum of fungal diversity, including cryptic species and those of particular conservation interest. Certain fungal groups that are underrepresented in air samples might be better captured by sampling eDNA directly from wood or soil, but visual surveys should be considered as a more cost‐effective complementary method at least at a local scale. Their results highlight the importance of using multiple methods simultaneously in biodiversity assessments and the need for standardized methods to study and monitor fungal diversity.

Analysis of Evolving Technologies and Impact of Smart Shipping on the Future Workforce in the Maritime Industry

Purpose: There is a shift in phase within the maritime industry toward smart shipping, where IoT and AI are used. The real question revolved around these technologies' impact on future employees in ships and shipping. The reason is to understand how this rapidly changing technological world affects these maritime professionals. Study design/methodology/approach: A systematic review was performed according to the system of Preferred Reporting Items for Systematic Reviews and Meta−Analyses (PRISMA). The literature review aimed at analysing a comprehensive spectrum from academic publications to industry reports and white papers in order… The Smart Shipping case studies were studied to provide practical knowledge on the integration of IoT and AI in maritime operations. Findings: The resulting analysis was a diverse and changing technological environment, including blockchain, AI, IoT, autonomous vessels, and innovations that are driven by sustainability. The use of blockchain applications allows for achieving increased transparency, while AI-based developments bring improvements in navigation, logistics and maintenance. The introduction of IoT allows industries to transform via the collection of data in real time. Autonomous vessels offer both challenges and opportunities designed to impact seafaring jobs. Sustainability innovations aim at clean energies and more ecological applications. Smart Shipping case studies demonstrated various positive outcomes on the deployment of IoT and AI applications that are realised in terms of operational efficiency gains up to issues with workforce adaptation. Originality/value: The paper sheds light on the maritime environment as well as its potential impact on determining the future workforce. The strategies to deal with the changes, such as job role change, workforce adaptation strategy and overcoming challenges, should be considered essential. Whereas merits arising from technical development enable the companies to benefit as far as efficiency is concerned, missing opportunities for careers in seafaring imply that active measures to build workforce capacities have become inevitable. The paper ends with recommendations for policy-makers, industrial representatives, and researchers who can help take successful steps in the face of changing fields associated with technology use encompassing maritime operations.

Estimation of spatial demographic maps from polymorphism data using a neural network.

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.

An exploration of ecoacoustics and its applications in conservation ecology

Our planet is facing unprecedented adversity due to the global impacts of climate change and an emerging sixth mass extinction. These impacts are exacerbated by population and industrial growth, where increased resource extraction is required to meet our insatiable demands. Yet, the tangible elements of our lone inhabited planet in the solar system are not the only things disappearing or being modified. The sounds of Earth are being altered in ways that may never be recovered. Indeed, we occupy a noisier world in this age of machines that comes at a great expense in the form of sonic extinctions. It is profoundly apparent, yet not widely recognized, that conservation efforts must consider the importance of the sonic environment (i.e., sonosphere). Although sound has been integral to life for millions of years, our understanding of its ecological role has only just begun. Sounds are one of the most important extensions of the organismic inner world, becoming testimonials of environmental complexity, integration, and relationships between apparently separated parts. From a semiotic perspective, sounds are signals utilized by many organisms to save energy in patrolling, defending, exploring, and navigating their surroundings. Sounds are tools that establish dynamic biological and ecological competencies through refined partitioning in the natural selection process of evolution. Ecoacoustics is a recent scientific discipline that aims to investigate the role of sound in ecological processes. Despite its youth, Ecoacoustics has had rapid theoretical and applied growth, consolidating a diverse array of research on the ecology of sounds across many disciplines. Here, we present how Ecoacoustics plays a significant role in conservation ecology by exploring the discipline's theoretical framework, new descriptors of sonic complexity, and innovative methods for supporting conservation efforts from singular species to entire landscapes across local and global scales. The combination of automated recording units and ecoacoustic indices present a very promising approach to the study of remote areas, rare species, and data rich analyses. While Ecoacoustics scientists continue to explore this new scientific horizon, we encourage others to consider Ecoacoustics in their conservation agendas because of its application to the study and management of terrestrial, marine, and freshwater habitats.

Review of the Proteomics and Metabolic Properties of Corynebacterium glutamicum.

Corynebacterium glutamicum (C. glutamicum) has become industrially important in producing glutamic acid and lysine since its discovery and has been the subject of proteomics and central carbon metabolism studies. The proteome changes depending on environmental conditions, nutrient availability, and stressors. Post-translational modification (PTMs), such as phosphorylation, methylation, and glycosylation, alter the function and activity of proteins, allowing them to respond quickly to environmental changes. Proteomics techniques, such as mass spectrometry and two-dimensional gel electrophoresis, have enabled the study of proteomes, identification of proteins, and quantification of the expression levels. Understanding proteomes and central carbon metabolism in microorganisms provides insight into their physiology, ecology, and biotechnological applications, such as biofuels, pharmaceuticals, and industrial enzyme production. Several attempts have been made to create efficient production strains to increase productivity in several research fields, such as genomics and proteomics. In addition to amino acids, C. glutamicum is used to produce vitamins, nucleotides, organic acids, and alcohols, expanding its industrial applications. Considerable information has been accumulated, but recent research has focused on proteomes and central carbon metabolism. The development of genetic engineering technologies, such as CRISPR-Cas9, has improved production efficiency by allowing precise manipulation of the metabolic pathways of C. glutamicum. In addition, methods for designing new metabolic pathways and developing customized strains using synthetic biology technology are gradually expanding. This review is expected to enhance the understanding of C. glutamicum and its industrial potential and help researchers identify research topics and design studies.

Xerogel mesoporous materials based on ultrastable Blatter radicals for efficient sorption of nitric oxide

The reduction of hazardous nitric oxide emissions remains a significant ecological challenge. Despite the variety of possibilities, sorbents able to capture low concentrations of NO from flue gas with high selectivity are still in demand. In this work a new type of mesoporous xerogel material highly loaded with ultrastable Blatter radicals (BTR, >60 % by mass) that act as selective NO sorption sites is developed. Electron Paramagnetic Resonance (EPR) spectroscopy evidences reversible NO sorption in nanometer-scale pores of BTR-based xerogels and indicates the high NO capacity of such radical-rich sorbent. Efficient NO capture from model flue gas mixture is also evidenced in experiments with a fixed bed reactor. Such advanced properties of new materials as selectivity, strong binding with NO and an ability for mild regeneration via thermodesorption promote them for future ecological applications.

Comprehensive compositional analysis of liquid organic product prepared by industrialized hydrothermal cracking of biomass waste and its potential application as fertilizer

Hydrothermal cracking involves the conversion of organic waste into efficient fertilizer through hydrolysis at temperatures ranging from 180 to 220 °C and pressures of 1.5 to 2.45 MPa, which offers significant advantages in shortening the production cycle, enhancing efficiency, and decomposing antibiotics. As a result, it holds immense practical value for promoting organic fertilizer manufacturing processes globally. The products derived from hydrothermal cracking can be categorized into solid and liquid components. Extensive research has focused on the composition and use of solids, while studies on liquids have mainly examined basic characteristics. The study aimed to comprehensively analyze the components in liquid products prepared through hydrothermal cracking and evaluate their suitability as liquid fertilizers. Specifically, we employed rigorous analytical techniques to accurately identify and quantify medium and trace elements, organic acids, amino acids, and plant growth regulators. Furthermore, we carried out a planting experiment to assess the yield and soil changes following the application of liquid products in maize cultivation. The experimental data revealed that the liquid product contained abundant medium and trace elements, along with 6.22 g/L free amino acids and 9.22 g/L organic acids. It is noteworthy that this liquid product contained 1.22 × 105 pg/mL ABA, 6.26 × 103 pg/mL IAA, 1.07 × 102 pg/mL IBA, and 3.60 × 10−2 pg/mL GA3. The utilization of this liquid product has the potential to enhance the disease resistance of maize crops and promote the accumulation of nitrate nitrogen in the soil. By understanding the composition of liquid products via hydrothermal cracking, valuable insights can be gained into their potential benefits for agricultural and ecological applications.