Natural Environmental Changes Research Articles

Improvement of multiscale decomposition for space-based gravitational wave signal processing technology.

During the process of detecting gravitational waves in space, addressing noise issues caused by terrestrial vibrations, natural environmental changes, and the factors intrinsic to the detectors, this paper proposes a multiscale variational mode adaptive denoising algorithm based on momentum gradient descent. This algorithm integrates momentum factors and multiscale concepts into the variational mode algorithm to resolve the issue of multiple local optima encountered during operation, reduce oscillations in regions with large or unstable gradient changes, and improve convergence speed. Additionally, the algorithm combines the least mean squares algorithm to automatically adjust weights, thereby mitigating the impact of noise, addressing the issue of noise from multiple and random sources, effectively suppressing noise in the gravitational wave signal, and enhancing the quality and reliability of the gravitational wave signal. Experimental results demonstrate that this algorithm performs better than other algorithms in noise suppression, effectively reducing noise in gravitational wave signals and meeting the noise suppression requirements for space-based gravitational wave detection.

Seaweed burial mitigated the release of organic carbon and nutrients by regulating microbial activity

Seaweed debris is susceptible to being buried in sediments due to natural environmental changes and human activities. So far, the effect of buried seaweeds on the environment and its decomposition mechanism remains unclear. This study simulated the decomposition of seaweed Gracilariopsis lemaneiformis for 180 days with different burial depths (0 cm and 10 cm) and burial weights (10 g and 20 g). Our findings revealed that compared with Gracilariopsis decomposition on the sediment surface, the seaweed buried in sediment slowed down the release of N, P, and dissolved organic carbon (DOC) by enhancing the activity of diverse anaerobic microbes (i.e. Draconibacterium, Desulfuromusa, Sediminispirochaeta), which were associated with organic matter decomposition. The enhanced burial quantity of Gracilariopsis resulted in a 3.28 % increase in sediment OC and enriched the humification degree of DOC in seawater. These results highlight the role of seaweed burial in enhancing OC sequestration in marine environments.

Beyond BiCIKL: Towards Building an AI-Assisted “Biodiversity Supergraph”

BiCIKL (Biodiversity Community Integrated Knowledge Library) is a European Union (EU) Horizon 2020 project (2021–2024) building a new community of research infrastructures (RIs), researchers and other stakeholders, through improved access to interlinked, open and FAIR (Findable, Accessible, Interoperable, Reusable) biodiversity data along the biodiversity research cycle (specimens, sequences, taxon names, publications) (Penev et al. 2022). The project’s 14 partners developed or substantially improved 16 tools and services currently in process of onboarding to the European Open Science Cloud (EOSC), presented in the FAIR Data Place (FDP) of BiCIKL’s flagship product, the Biodiversity Knowledge Hub (BKH). The tools and data were used in Open Call projects, performed by research groups worldwide. A key achievement of BiCIKL is the establishment of several new bi-directional links between the participating RIs through shared and interoperable data standards and web services. The sustainability of the BiCIKL services and especially of the strong collaborative spirit developed through the project will be ensured by a membership agreement for the BKH maintenance and further development. The results of BiCIKL are diverse and tackle various aspects of the implementation of open science practices in biodiversity research. The project partners and external collaborators from the Open Call projects published more than 80 papers and conference abstracts (see the article collections in Penev et al. 2022a and Thessen et al. 2023), two policy briefs (Penev et al. 2024, Agosti et al. 2024), three Biodiversity Information Science (TDWG) symposia (2021, 2023, 2024), several videos and factsheets and other training materials, guidelines and best practice recommendations, and so on. In the special focus of BiCIKL was the extraction and liberation of data from the PDFs of several thousands of published biodiversity articles making it accessible and re-usable. The new BiCIKL community proved to be successful in both technological innovation and long-lasting spirit of collaboration between biodiversity and genomics researchers, data repositories, RIs, publishers and other stakeholders. Beyond BiCIKL, we envisage our work towards further integration and interoperability between data domains by embracing human-in-the-loop collaborations, enhanced by Artificial Intelligence (AI). The implementation of AI and Large Language Models (LLM) should be possible when considering an important condition: to understand the complexity of past, recent and future changes in biodiversity and natural environments the use of AI tools should be based on аdequately curated, semantically structured and interlinked biodiversity data. We see this radical new step as a concerted community effort towards building a “Biodiversity Supergraph” (Fig. 1), understood here as a two-component ecosystem consisting of: centrally orchestrated system of tools and services, and distributed sources of transformed, semantically enhanced FAIR Linked Open Data, supplied by the partnering RIs. centrally orchestrated system of tools and services, and distributed sources of transformed, semantically enhanced FAIR Linked Open Data, supplied by the partnering RIs. The “Biodiversity Supergraph'' will provide integration of the biodiversity data on a scale and operational level that has never been attempted before. It is key for the next decade, to enable a baseline of global, biodiversity-related information serving organisations, academia, industry and society.

Cost-efficient PCR based DNA barcoding of marine invertebrate specimens with NovaSeq amplicon sequencing.

The marine environment harbors high biodiversity; however, it is poorly understood. Nucleotide sequence data of all marine organisms should be accumulated before natural and/or anthropogenic environmental changes jeopardize the marine environment. In this study, we report a cost-effective and easy DNA barcoding method. This method can be readily adopted without using library preparation kits. It includes multiplex PCR of short targets, indexing PCR, and outsourcing to a sequencing service using the NovaSeq system. We targeted four mitochondrial genes [cytochrome c oxidase subunit I (COI), COIII, 16S rRNA (16S), and 12S rRNA (12S)] and three nuclear genes [18S rRNA (18S), 28S rRNA (28S), internal transcribed spacer 2 (ITS2)] in 95 marine invertebrate specimens, which were primarily annelids. The primers, including adapters and indices for NovaSeq sequencing, were newly designed. Two PCR runs were conducted. The 1st PCR amplified specific loci with universal primers and the 2nd added sequencing adapters and indices to the 1st PCR products. The gene sequences obtained from the FASTQ files were subjected to BLAST search and phylogenetic analyses. One run using 95 specimens yielded sequences averaging 2816bp per specimen for a total length of six loci. Nuclear genes were more successfully assembled compared with mitochondrial genes. A weak but significantly negative correlation was observed between the average length of each locus and success rate of the assembly. Some of the sequences were almost identical to the sequences obtained from specimens collected far from Japan, indicating the presence of potentially invasive species identified for the first time. We obtained gene sequences efficiently using next-generation sequencing rather than Sanger sequencing. Although this method requires further optimization to increase the success rate for some loci, it is used as a first step to select specimens for further analyses by determining the specific loci of the targets.

Guaranteed cost control for a class of composite hybrid aerial/terrestrial precise manipulator with stochastic switching payloads

AbstractThis article investigates the modeling and attitude control of a class of composite hybrid aerial/terrestrial precise manipulator (Chat‐PM) with stochastic switching payloads when attaching to a vertical surface. The dynamics of the Chat‐PM for aerial locomotion are modeled by transferring the force and moment of the end‐effector to the body based on the recursive Newton–Euler equations. Furthermore, the attitude dynamics of the Chat‐PM under the wall‐attachment condition is obtained by limiting the attitude angle/angular velocity and introducing the friction torque acting on the passive wheels for the first time. Taking into consideration the complexity of the task and the stochastic nature of environmental changes, the payload attached to the end‐effector is modeled as a continuous‐time Markov process with mode‐dependent fixed sojourn time in this study. The proposed guaranteed cost controller results in the Chat‐PM capable of stably attaching to a wall under random switching loads, while guaranteeing the quadratic performance cost with an attainable upper bound. Additionally, a convex‐optimization‐based guaranteed cost controller is proposed to optimize the performance cost in the random switching part. Finally, the effectiveness of the proposed guaranteed cost controllers is demonstrated by illustrative examples.

A quantitative research on climate resilience in coastal airports from the perspective of adaptation

Because of its distinct function and geographic conditions, the impact of climate change on the operation, safety, and income of airports in coastal areas is becoming increasingly significant. The measurement of climate resilience can help identify priority needs and measures to adapt to climate change, which is a crucial step in developing an aviation adaptation plan. At present, the concept of climate resilience is relatively complex and lacks a clear uniformity of composition, which has made it challenging to effectively support the development of adaptation strategies. Based on the definition of climate resilience, our first step was to construct an evaluation system for coastal airports to visually represent the level of climate resilience. Next, in this study, we introduced a coupling coordination and obstacle degree model to analyze the coordinated development and key drivers of climate resilience, which could be used to develop a targeted improvement strategy based on the calculation results. In the future, additional measures can be combined from the natural environment, socioeconomics, governance capacity, and climate change risk to enhance the capacity development of the aviation industry to address climate change and foster the establishment of a sustainable development model between the industry and the environment.

The Potential of Using Artificial Intelligence (AI) to Analyse the Impact of Construction Industry on the Carbon Footprint

AbstractConstruction is an important sector of human activity that significantly impacts the environment. The impact of this sector can be analysed from different perspectives, such as consumption of natural resources, waste generation, energy intensity, and environmental change. The sector is increasingly promoting using renewable materials, energy-efficient practices, and planning those respects ecological processes and biodiversity. Against this background, it is important to take coordinated action across the sector and move to net-zero carbon standards through immediate action to raise awareness, implement innovation, and improve carbon management and reporting processes. Tools supporting the reduction of the adverse impacts of construction activities include artificial intelligence tools. The construction industry has long been considered a conservative and traditional industry but is now experiencing a technological revolution. Gradually, artificial intelligence (AI) principles and tools are beginning to be integrated into the various lifecycle processes of construction projects. This paper analyses the AI tools used to analyse carbon footprinting in the construction sector in terms of selected functionalities. The results of the research will form the basis for the development of a strategic plan for the development of AI within the research activities at the Faculty of Civil Engineering in Košice.

A short-training method for monitoring axially-loaded beams in presence of unknown and large thermal variations

Tie-rods are axially loaded beams often used in building to balance the lateral forces in vaults and arches and their good state of health is therefore essential for the integrity of the entire structure in which they are inserted. In the literature, there are few works treating the damage identification in tie-rods, which is nonetheless a difficult task because of the large natural environmental changes the tie-rods are subject to. Indeed, often, these axially loaded beams are placed outside from buildings and could experience more than 40 °C of thermal variation in a year. Such a temperature variation does not only change the mechanical and geometrical features of the tie-rod, as occurs for most of the structures, but also implies a large change of axial load, in turn causing a significant change of beam dynamics able to mask the effects of a possible damage. This paper aims at presenting a new approach for monitoring the health condition of tie-rods using a single accelerometer to measure beam dynamics and a short training in order to avoid the need of collecting a large amount of data to describe all the possible temperature conditions. The method requires to identify few beam eigenfrequencies through operational modal analysis and processes them by means of principal component analysis and Mahalanobis squared distance. This allows building a proper damage index with reliable confidence intervals. The effectiveness of the proposed method in finding damages with a short training period is demonstrated at first with numerically generated data and, then, using signals coming from a laboratory set-up. In both the cases, the proposed method is compared to a more traditional approach.

Review of the high bed–low ditch system as an alternative to lowland paddy in tropical and subtropical Asia

Many forms of traditional raised bed systems could be found around the world. Several of them have been identified as Globally Important Agricultural Heritage Systems (GIAHS) sites by Food and Agriculture Organization of the United Nations. Unlike traditional raised bed systems with similar structures in the Americas, the high bed–low ditch (HBLD) system in tropical and subtropical Asia, which is originated and developed from rice production, has been playing an important role in enhancing food security and maintaining farmer livelihood for centuries. Moreover, products provided by HBLD system are not only important for the livelihood of the local farmers, but also important for people living in the nearby towns and cities especially for vegetable and fruit supply. In this system, the ditches or sunken beds can be used to lower the groundwater table, retain nutrients and soil particles washed from the bed, grow rice or aquatic vegetables, and raise fish or shrimp. The HBLD system can also help to reduce salinity in coastal lowlands due to the presence of ditches. The raised beds can be used to grow various upland crops. Compared with rice monocropping, the adoption of HBLD system significantly improves the cropping intensity, productivity, employment, and income of farmers. Famers’ long-term practices fully demonstrate that this system is a type of sustainable agriculture with strong adaptability to the changes of natural environment. However, it should also be noted that the large-scale development of HBLD systems is not simply dependent on natural conditions, but is also determined by specific socioeconomic factors, such as good transportation facilities, a well market system, and a sufficient supply of labor. As a model of equilibrium between food production and high levels of biodiversity maintenance, the HBLD system is an important agricultural heritage system with global significance, and it should be well preserved and utilized in new ways to realize its important multiple functions under conditions of rapid urbanization in lowland and coastal regions.

China's vegetation restoration programs accelerated vegetation greening on the Loess Plateau

The vegetation greening on the Loess Plateau, China, over recent decades, has been primarily driven by a series of vegetation restoration programs (VRPs) and other natural environmental changes (including climate change, rising atmospheric CO2 concentration, and nitrogen deposition, etc.). However, accurate determination of the contributions of natural environmental change and the VRPs to this greening has been challenging due to the lack of the exact time of policy implementation in different areas. Herein, we extracted the starting time of greening (SOG) from different sources of remote sensing data and used it as the starting time of the VRPs. Then, we employed a difference-in-differences (DID) method to ascertain the relative contributions of the VRPs on the observed vegetation greening. Results showed that the contribution of the VRPs to vegetation greening on the Loess Plateau was 23.8–35.8 %, with a greater contribution potentially originating from natural environmental factors. Our findings contribute to a better understanding of the complex relationships among vegetation restoration policies and climate change, and offer a platform to quantify the climate effects on vegetation greening.

A Cross-Decadal Change in the Fish and Crustacean Community of Lower Yaquina Bay, Oregon, USA

Natural environmental change, anthropogenic development, and inter-annual variability can affect the ecology of estuarine fish and invertebrates. Yaquina Bay, Oregon, a well-studied estuary, has undergone intense development, as well as deep-draft dredging during the latter half of the 20th century, resulting in the alteration of ~45% of the lower estuary’s natural shoreline. In 1967, the United States Environmental Protection Agency (USEPA) conducted a 21-month survey of Yaquina Bay to characterize the demersal fishes and epibenthic crustaceans that occupy the bay. From 2003 to 2005, we conducted a 25-month survey to replicate that work and provide a comparative snapshot of the demersal fish and epibenthic crustacean community in the bay. A comparison of the trawl survey datasets reveals a 91% decline in total catch per unit effort (CPUE) between surveys, as well as a decline in multiple measures of biodiversity. Furthermore, the fishes and crustaceans of Yaquina Bay have experienced a shift in species dominance from demersal fishes in the late 1960s to epibenthic crustaceans in the 2000s, marked most notably by a nine-fold increase in the Dungeness crab CPUE. While this work does not establish a causal relationship between changes in the demersal communities of this West Coast estuary and human or natural events, it does document substantial changes in both the diversity and total abundance of animals in that community over a three-plus decade period of development and environmental variability. Hence, this forms a second baseline for continued long-term monitoring.

THE IMPACT OF ARTIFICIAL INTELLIGENCE ON FMCG DISTRIBUTION

Economic Impact-Many examinations have investigated the monetary ramifications of man-made intelligence and ML reception. Research frequently centres around efficiency gains, work market elements, and the potential for work uprooting and creation. A few examinations propose that while Artificial intelligence and ML can prompt expanded effectiveness and development, they may likewise disturb customary business designs, requiring labour force transformation and re-skilling. Business and Industry: Writing in this space looks at how Artificial intelligence and ML advances are changing business tasks, including promoting, finance, store network the board, and client care. Reads up feature the potential for artificial intelligence and ML to improve dynamic cycles, enhance asset designation, customize client encounters, and drive upper hand. Medical care: Artificial intelligence and ML have huge ramifications for medical care, including sickness determination, therapy arranging, drug disclosure, and customized medication. Research in this space investigates the potential for Artificial intelligence and ML to work on clinical results, diminish clinical blunders, lower medical services expenses, and upgrade patient consideration through prescient examination, picture acknowledgment, and normal language handling. Education and Learning: The effect of Artificial intelligence and ML on schooling and learning is likewise a subject of interest. Writing in this field looks at how artificial intelligence fueled devices and stages can work with customized growth opportunities, versatile coaching, robotized reviewing, and instructive substance creation. Research additionally investigates the difficulties and moral contemplations related with man-made intelligence driven instructive innovations. Ethical and social implications-Researchers have raised worries about the moral and cultural ramifications of Artificial intelligence and ML, including issues connected with protection, predisposition, decency, straightforwardness, responsibility, and algorithmic administration. Research in this space looks to foster structures, rules, and guidelines to alleviate likely dangers and guarantee capable man-made intelligence advancement and arrangement. Environmental Impact few examinations explore how simulated intelligence and ML can be utilized to address natural difficulties, for example, environmental change, asset preservation, contamination control, and manageable turn of events. Research in this area investigates uses of computer based intelligence and ML in energy the board, savvy horticulture, natural checking, and preservation endeavours’ lawful and administrative parts of simulated intelligence and ML are likewise a subject of insightful request. Writing in this field looks at licensed innovation privileges, risk issues, information assurance regulations, and the moral and lawful obligations of artificial intelligence designers and clients. Research intends to lay out legitimate systems and rules to successfully administer artificial intelligence and ML advancements.

Interannual Monitoring of Cropland in South China from 1991 to 2020 Based on the Combination of Deep Learning and the LandTrendr Algorithm

Timely and accurate acquisition of spatial distribution and changes in cropland is of significant importance for food security and ecological preservation. Most studies that monitor long-term changes in cropland tend to overlook the rationality in the process of cropland evolution, and there are conflicts between the interannual cropland data, so they cannot be used to analyze land use change. This study focuses on the rationality of annual identification results for cropland, considering the long-term evolution and short-term variations influenced by natural environmental changes and human activities. An approach for annual monitoring of cropland based on long time series and deep learning is also proposed. We acquired imagery related to cropland’s vegetation lush period (VLP) and vegetation differential period (VDP) from Landsat images on the Google Earth Engine (GEE) platform and used the ResUNet-a structural model for training. Finally, a long-time-series cropland correction algorithm based on LandTrendr is introduced, and interannual cropland maps of Guangdong Province from 1991 to 2020 were generated. Evaluating the cropland monitoring results in Guangdong Province every five years, we found an overall accuracy of 0.91–0.93 and a kappa coefficient of 0.80–0.83. Our results demonstrate good consistency with agricultural statistical data. Over the past 30 years, the total cropland area in Guangdong Province has undergone three phases: a decrease, significant decrease, and stabilization. Significant regional variations have also been observed. Our approach can be applied to long-time-series interannual cropland monitoring in the southern regions of China, providing valuable data support for the further implementation of cropland protection.

Impacts of anthropogenic eutrophication on the carbon transfers in lacustrine food webs: A paleolimnological assessment in four mountain lakes

Over the last decades, the intensification of anthropogenic activities and associated disturbances on lake watersheds have led to major changes in lakes trophic functioning through accelerated eutrophication. In many lakes, these changes are characterized by an unprecedented increase in organic carbon fluxes, potentially leading to a shift in biogeochemical cycles and in the balance between carbon sequestration and greenhouse gas emissions. Understanding the response of the carbon cycle to natural and anthropogenic environmental changes is becoming a crucial challenge in the context of increasing global pressures. In this study, we reconstructed the changes in the trophic functioning of the benthic and pelagic food web, in response to accelerated eutrophication in four lakes over the last millenium. Changes in carbon pathways in food webs were assessed using stable carbon isotope analysis of chitinous subfossil remains of Daphnia, Bosmina, and Chironomini archived in sedimentary records. Changes in the trophic state were inferred from sedimentary geochemical analysis, including carbon accumulation rates, Chl a accumulation rates and carbon-to-nitrogen ratios. Agro-pastoral activities were tracked by analysis of coprophilous ascospores. Results provided by this multi-proxy approach highlight recent disruptions in carbon sources and transfer pathways in lakes food webs. In particular, changes in the carbon isotopic signature of pelagic consumers suggest a recent increase in the use of 13C-depleted carbon sources such as methanogenic or respiration-derived carbon linked to recent changes in trophic state under the intensification of anthropogenic pressures.

Opportunities and challenges of interdisciplinarity in river water environmental ethics and integrated river basin management

AbstractThis paper examines the ethical issues of water environment in the context of river management in practical engineering and technological applications. In particular, three important issues are discussed in this paper referring to two actual engineering cases in ancient and modern China, that is, the construction of ancient Dujiangyan irrigation project in Sichuan, China, and the modern practice of integrated operation of flood control and pollution prevention in Huai River Basin. The three issues include how to consider the trade‐offs between flood control and irrigation, how to balance flood control and contamination prevention related to sudden water pollution incident, and how to ensure the protection of water environments and ecology in rivers under the grand challenges of natural environmental changes and high‐intensity human activities. Finally, this paper concludes by emphasizing the future development of water environmental ethics and its interdisciplinary integration with modern science & technology in smart river management in China.

Landscape sensitivity assessment within spatial development scenarios. Latvia case study

European countries have different experience in landscape characterisation and assessment. Comparing the different approaches used in different European countries, it is proposed to use the method developed and validated in the United Kingdom - Landscape Character Assessment, adapted and modified for the Latvian situation. This approach has also been used in most other European countries, which have chosen to use the UK approach to landscape characterisation, adapting it to their specific national situation. The need for a landscape assessment in Latvia is highlighted in the Latvian Landscape Policy Guidelines 2013-2019 and Latvian Landscape Policy Implementation Plan 2024-2027, taking into account the actions set out in the European Landscape Convention to be taken by all Parties to the Convention. The purpose of the research was to carry out the analysis of Latvian landscape sensitivity within spatial planning scenarios important for local municipalities. It is of high importance to assess landscape sensitivity for changes of build and natural environment influencing pace and scale of development of the rural areas of Latvia. As local municipalities set different goals for their spatial development, common spatial development scenarios were chosen to make analysis of landscape sensitivity in Latvian landscapes. Results from the analysis of landscape sensitivity show variation of suitable actions to be implemented if different places in Latvia. The results also can be used for defining landscape quality goals to harmonise scope of activities to be implemented by local municipalities of Latvia.

영남지역 청동기시대 조·전기 주거형태의 변화와 특징

A research on Bronze age in S.Korea has made remarkable progress, but most of the
 achievements are confined on recording chronologically by pottery. It is so difficult to
 understand transition in housing type more than pottery because it is so conservative to
 change compared with pottery. Also it is changing by climate, environment, economic
 structure, development of technology, human preference and so on. The research method is
 order by fundamental concept of housing type of early Bronze age in S.Korea, case
 review, transition and feature in housing type and implication of archaeology.
 First of all, to set up typical housing feature of four types, and making a division for
 Misari, Garakdong, Kwansanri and Heunamri type. In sequence, to observe transition and
 feature of all housing type in Youngnam region especially the middle and upper streams
 of the Nakdonggang River, inland area, the southwestern area and south-east coast. The
 housing type of Misari demonstrate for transition of floor plan, number of fire pit and
 structure. The housing type of Garakdong demonstrate for becoming longer and
 disappearing of foundation stone. The housing type of Kwansanri also demonstrate for
 disappearing stone fire pit and standardizing of wooden column. On the other hand,
 housing type of Heunamri demonstrate for reduced fire pit and becoming re-smaller floor
 plan. And it turns to type of Gumdanri that is the latter part of Bronze age in the
 southeastern region. In conclusion, I analyzed for transition and feature in housing type as
 characteristics of early Bronze age in the Korean Peninsula also as universality of
 hunting-gathering society. In other words, the appearance of early Misari type is
 characteristics for deportation and settlement especially Korean Peninsula while type of
 Kwansanri is understood for universality by being expanded floor plan, division of fire
 range, structure transition, standardization of intercolumniation, that is also understood
 longhouse culture where living high latitude area. Popularly, in such society is understood
 as a complex incipient agriculture and hunting-gathering society. This research regard that
 society as universality of prehistoric culture of Korean Peninsula.
 And a pull-factor of transition in housing type occurs by complex causes such as population
 growth, development of technology, natural environment change, livelihood strategy and so on.

Analysis of the Ongoing Effects of Disasters in Urbanization Process and Climate Change: China’s Floods and Droughts

Urban development and climate change have strengthened the possibility of floods and droughts in cities. In this study, we evaluated the influences of these disasters and related social damage in nine major basins during the past 50 years. Unusually, the following conclusions were drawn from the analysis of relevant indicators before and after urbanization: (1) agricultural loss area (flood), grain loss, and direct economic loss showed an upward trend, while other indicators showed the opposite. (2) Floods most often occur in the Yangtze River Basin (58, 26.2%), followed by the Liaohe River Basin (49, 22.2%), which is closely related to the topography and economic progress of the area. (3) The modified Mann–Kendall (MK) analysis results are consistent with the indicators trend. Finally, the regularity of the climate change and urbanization process is revealed by the migration of the standard deviation ellipse and the mean center of the four indicators. China needs to integrate urban water/drought policy development with sustainable urbanization policy development to cope with the changing natural and social environment and to minimize urban ecological risks.

Discordant patterns between nitrogen-cycling functional traits and taxa in distant coastal sediments reveal important community assembly mechanisms.

A central question in microbial ecology is how immense microbes are assembled in changing natural environments while executing critical ecosystem functions. Over the past decade, effort has been made to unravel the contribution of stochasticity and determinism to the compositional of microbial communities. However, most studies focus on microbial taxa, ignoring the importance of functional traits. By employing shotgun metagenomic sequencing and state-of-the-art bioinformatics approaches, this study comprehensively investigated the microbially mediated nitrogen (N) cycling processes in two geographically distant coastal locations. Both shotgun and 16S rRNA gene amplicon sequencing demonstrated significantly differed taxonomic compositions between the two sites. The relative abundance of major microbial phyla, such as Pseudomonadota, Thaumarchaeota, and Bacteroidota, significantly differed. In contrast, high homogeneity was observed for N-cycling functional traits. Statistical analyses suggested that N-cycling taxonomic groups were more related to geographic distance, whereas microbial functional traits were more influenced by environmental factors. Multiple community assembly models demonstrated that determinism strongly governed the microbial N-cycling functional traits, whereas their carrying taxonomic groups were highly stochastic. Such discordant patterns between N-cycling functional traits and taxa demonstrated an important mechanism in microbial ecology in which essential ecosystem functions are stably maintained despite geographic distance and stochastic community assembly.

The Canonical Discriminant Model of the Environmental Security Threats

The existence of modern humanity directly depends on environmental security. Human society, biodiversity, ecosystems, and climate safety are interdependent. The anthropogenic influence that causes irreversible climate change threatens both the ecosystem’s existence and humans’ survival. To maintain a balance between human well-being and a safe environment, it is important to have a diverse knowledge of the interrelations between the technological impact on the natural environment and climate change and an understanding of action strategies to mitigate climate change and ensure sustainable development. Applying a scientific approach, data analytics, and data science tools can effectively support climate change mitigation and prevent a climate disaster. Based on the components of the climate change performance index (CCPI) 2023 for 59 countries and the EU, a canonical discriminant model was built to identify the significant factors that influence the assessment of the effectiveness of climate protection in a particular country or region and the assessment of climate risks. It can be used to assess the level of climate protection effectiveness of countries that have not defined the CCPI 2023. Based on empirical data, we have determined the real weights of the relevant CCPI components in relation to the effectiveness of actions aimed at reducing global warming. We have established that there are additional factors important for assessing climate protection, but the CCPI rating does not consider them. We conducted a comparative analysis of the CCPI index and the sustainable development goals (SDG) index. The study establishes that the differences in environmental protection among the world’s countries do not determine the assessment of the level of sustainable development of the world’s countries. The obtained results can provide information to support decision-making in developing effective strategies and urgent actions to ensure climate protection.