Ecological Indicators Research Articles

Monitoring arthropods under the scope of the LIFE-BEETLES project: I - Baseline data with implementation of the Index of Biotic Integrity.

The urgent need for conservation efforts in response to the global biodiversity crisis is exemplified by initiatives, such as the EU LIFE BEETLES project. This project aims to preserve endangered arthropod species that are crucial for ecosystem functionality, with a focus on endemic beetle species in Flores, Pico and Terceira Islands (Azores, Portugal): Tarphiusfloresensis Borges & Serrano, 2017, Pseudanchomenusaptinoides (Tarnier, 1860) and Trechusterrabravensis Borges, Serrano & Amorim, 2004. These species are single island endemics respectively from Flores, Pico and Terceira. They are threatened by environmental degradation, facing the dual challenge of restricted distribution and habitat degradation due to the spread of invasive plants.The project aims to enhance habitat quality and biodiversity conservation through habitat restoration and plant invasive species control measures. These measures are funded by the European Commission and coordinated by the Azorean Environment Directorate-General. The current Data Paper evaluates the effectiveness of the LIFE BEETLES project in improving habitat quality and offers insights into the balance between habitat restoration efforts and endangered species conservation in island ecosystems, utilising as ecological indicator the Index of Biotic Integrity (IBI) framework. This study establishes a comprehensive database derived from a long-term arthropod monitoring survey that used SLAM (Sea, Land and Air Malaise) traps and pitfall traps. Our findings present a proxy for assessing the overall habitat quality for endemic invertebrates, using arthropods as main indicators.From September 2020 to June 2023, a total of 31 SLAM traps were monitored. The traps were set up as follows: seven in Flores (three in mixed forest and four in native forest), 10 in Pico (four in mixed forest and six in native forest) and 14 in Terceira (three in mixed forest and 11 in native forest). Traps were monitored every three months.In addition, we surveyed the epigean fauna in 19 transects with 15 non-attractive pitfall traps per transect. The transects were set up during two weeks at the end of August every year between 2020 and 2023. Eight transects were established in Flores, consisting of one in pasture, four in mixed forest and three in native forest. Six transects were established in Pico, consisting of two in pastures and four in native forest. Five transects were established in Terceira, consisting of two in mixed forest and three in native forest.A total of 243 arthropod taxa were recorded, with 207 identified at the species or subspecies level. These taxa belonged to four classes, 24 orders and 101 families. Out of the 207 identified taxa, 46 were endemic, 60 were native non-endemic, 80 were introduced and 21 were of indeterminate status. Habitat information is also provided, including general habitat and dominant species composition. This publication contributes to the conservation of highly threatened endemic beetles by assessing habitat quality, based on arthropod communities and habitat description (e.g. native or exotic vegetation).Using the Index of Biotic Integrity (IBI) to comparing pre- and post-intervention data, we found no significant change within the epigean community. In contrast, the understorey community sampled with SLAM traps experienced a slight global decrease in biotic integrity over the study period. These findings suggest that the short duration of the study may not be sufficient to detect significant changes, as ecosystem recovery often requires long-term monitoring. The observed changes in the understorey community may be attributed to disturbances from intervention activities, highlighting the need for ongoing monitoring to assess long-term ecological resilience and recovery.

Seasonal sonic patterns reveal phenological phases (sonophases) associated with climate change in subarctic Alaska

Given that ecosystems are composed of sounds created by geophysical events (e.g., wind, rain), animal behaviors (e.g., dawn songbird chorus), and human activities (e.g., tourism) that depend on seasonal climate conditions, the phenological patterns of a soundscape could be coupled with long-term weather station data as a complimentary ecological indicator of climate change. We tested whether the seasonality of the soundscape coincided with common weather variables used to monitor climate. We recorded ambient sounds hourly for five minutes (01 January–30 June) over three years (2019–2021) near a weather station in a subarctic ecosystem in south-central Alaska. We quantified sonic information using the Acoustic Complexity Index (ACItf), coupled with weather data, and used machine learning (TreeNet) to identify sonic-climate relationships. We grouped ACItf according to time periods of prominent seasonal events (e.g., days with temperatures >0°C, no snow cover, green up, dawn biophony, and road-based tourism) and identified distinct sonic phenophases (sonophases) for groups with non-overlapping 95% confidence intervals. In general, sonic activity increased dramatically as winter transitioned to spring and summer. We identified two winter sonophases, a spring sonophase, and a summer sonophase, each coinciding with hours of daylight, temperature, precipitation, snow cover, and the prevalence of animal and human activities. We discuss how sonophases and weather data combined serve as a multi-dimensional, systems-based approach to understanding the ecological effects of climate change in subarctic environments.

Nematode Communities in Soils of the Same Volcanic Origin across a Gradient of Naturalization: From Intensive Agriculture to Forest

Nematodes play a key role in ecological environments. Biotic indices based on soil nematode community are effectively used for assessing soil health status. This work represents the opportunity to investigate three different management practices continuously maintained for 40 or more decades on soils with the same geological origin. This unique feature allows us to reduce variables and link biotic with abiotic factors. Therefore, the nematode communities of three neighboring volcanic soils under different managements were examined. The maximum values in soil biodiversity were found in the forest environment in which all the trophic groups were detected and well balanced. Instead, in permanent grassing and carnation crop greenhouse (CG), biodiversity indices progressively decreased with the intensification of agricultural practices. Furthermore, CG showed a stronger dominance of a specific plant-parasitic nematode identified as Heterodera daverti. Nematode indicators demonstrated that changes in the nematode community gradually varied from anthropic to natural environments whereas soil properties were feebly correlated to nematode community indicators. In conclusion, we demonstrated that biodiversity and ecological indices applied to the soil nematode community are effective at detecting alterations due to anthropogenic impact. Nematodes seem to be susceptible to perceiving the soil dynamics.

Agricultural Landscapes: A Pattern-Process-Design Approach to Enhance Their Ecological Quality and Ecosystem Services through Agroforestry

Agricultural landscapes are currently suffering and generating severe ecological issues. This is especially true in intensively managed alluvial contexts, where biodiversity is declining and ecosystem services (ES) delivery capacity is being depleted. The aim of our study is to set up and test a synthetic analytical methodology that allows us to: understand current agricultural landscape ecological quality drivers (structural and functional traits); identify context-specific strategies to correct current negative trends (landscape ecology design approach); and assess the changes in the landscape ecological behavior provided by design scenarios. The applied methodology is low-cost and low-time-demanding and is based on multi-scale landscape ecology and land-use-based ES assessment; it implements a pattern-process-design approach. Analyses are applied to four northern Italian alluvial agricultural landscape systems. We specifically address landscape biodiversity support functions (landscape ecology indicators) and landscape multifunctionality (ES spatial assessment). We test the agroforestry approach (landscape feature insertions and crop diversification) as a key strategy to enhance ecological quality and ES, and we account for its contributions to context-specific design scenarios. This analytical toolkit might serve for future applications on similar case studies.

Spatio-Temporal Evolution of Ecological Environment Quality Based on High-Quality Time-Series Data Reconstruction: A Case Study in the Sanjiangyuan Nature Reserve of China

The Sanjiangyuan Nature Reserve of China (SNRC) is recognized as one of the most fragile and sensitive terrestrial ecosystems in China, posing challenges for obtaining reliable and complete Moderate Resolution Imaging Spectro Radiometer (MODIS) data for ecological environment quality (EEQ) monitoring due to adverse factors like clouds and snow. In this study, a complete high-quality framework for MODIS time-series data reconstruction was constructed utilizing the Google Earth Engine (GEE) cloud platform. The reconstructed images were used to compute the Remote Sensing based Ecological Index (RSEI) on a monthly scale in the SNRC from 2001 to 2020. The results were as follows: The EEQ of the study area exhibited a “first fluctuating decline, then significant improvement” trend, with the RSEI values increasing at a rate of 0.84%/a. The spatial pattern of the EEQ displayed significant spatial heterogeneity, characterized by a “low in the west and high in the east” distribution. The spatial distribution pattern of the RSEI exhibited significant clustering characteristics. From 2001 to 2020, the proportion of “high–high” clustering areas exceeded 35%, and the proportion of “low–low” clustering areas exceeded 30%. Poor ecological conditions are mainly associated with population agglomerations, cultivated land, unutilized land, and bare ground, while grasslands and forests have higher RSEI values. The result of the trend analysis revealed a significant trend in RSEI change, with 62.96% of the area significantly improved and 6.31% significantly degraded. The Hurst Index (HI) results indicated that the future trend of the RSEI is predominantly anti-persistence. The proportion of areas where the EEQ is expected to continue improving in the future is 33.74%, whereas 21.21% of the area is forecasted to transition from improvement to degradation. The results showed that the high-quality framework for MODIS time-series data reconstruction enables the effective continuous monitoring of EEQ over long periods and large areas, providing robust scientific support for long time-series data reconstruction research.

Quantitatively exploring the influence of geographical conditions on ecological quality using a novel remote sensing model: a comparison between two geographical disparity regions in China

ABSTRACT The ecological quality of a region is significantly influenced by its geographical conditions, which can yield different effects on ecosystems. Nevertheless, the lack of adequate technology has impeded quantitative investigations into these differences. Consequently, there is an increasing demand for effective techniques to quantitatively measure differences in ecological quality resulting from variations in geographical conditions. This study applied the novel Remote Sensing-based Ecological Index (RSEI) concurrently to two distinct provincial-level regions in China, Fujian and Ningxia, to quantitatively detect their ecological differences. These two regions possess contrasting geographical conditions, with Fujian having high forest coverage and abundant rainfall, while Ningxia features low forest coverage and extensive loess plateau and desert terrain. By linking geographical factors with their corresponding ecological responses, we conducted a comprehensive analysis to determine whether the contrasting geographical conditions between the two regions had caused significant disparities in their ecological status. The results indicate that the contrasting geographical conditions have indeed led to marked ecological differences, with Fujian exhibiting excellent ecological status, while Ningxia lags behind due to unfavorable geographical conditions. In terms of RSEI scores, Fujian consistently achieved higher RSEI values (>0.8) in the study years, reaching an excellent ecological level, whereas Ningxia recorded scores lower than 0.45 during the comparable years, corresponding to a poor to moderate ecological level. Regarding the impact of geographical factors on ecological conditions, the positive contributions of greenness and wetness indicators to the ecology in Fujian were significantly greater than those in Ningxia (58% vs. 39%), whereas the contributions of negative indicators, dryness and hotness, were notably higher in Ningxia compared to Fujian (|–61|% vs. |–42|%). The successful concurrent application of RSEI to these two geographically distant regions also demonstrates the robustness of the RSEI technique.

Vulnerability assessment of natural heritage in the North-Eastern Ecuadorian Amazon using land use cover and nature protection status

This study evaluates the vulnerability of natural heritage in the Northeast Ecuadorian Amazon (NEA), from the perspective of intrinsic vulnerability. Therefore, two proxy indicators of vulnerability were established: (i) the ecological integrity vulnerability index (EIVI), indicating the potential loss of ecological integrity, assessed by protection status (2018); (ii) the biological diversity vulnerability index (BVI), deriving the potential loss of biological diversity, using land cover/land use (2014). Biodiversity values were derived with land cover-related biodiversity data, and (iii) and compared with spatial congruence/correlation between (i) and (ii). The EIVI was directly derived using protection status, which defines vulnerability levels by ranking them according to corresponding levels of anthropic development allowance. A robust relationship between land use classes and species richness was found for both endemic vascular plants in neotropical regions and multi-taxa in tropical forests worldwide, validating the BVI. Furthermore, the moderate spatial correlation between protection status and land cover (r = 0.52) may be partially explained by 3,060 km2 of unprotected primary forest. Overall, 42 % of the NEA have a high degree of congruence between potential biodiversity and protection status. In conclusion, this study provides insights into nature conservation efforts in areas with sparse biodiversity data using readily available geographic information.

Analysis of Driving Factors for Vegetation Ecological Quality Based on Bayesian Network

Vegetation is a crucial component of ecosystems, and understanding the drivers and spatial optimization patterns of its ecological quality is vital for environmental management in the middle reaches of the Yangtze River Urban Agglomeration. Traditional evaluations employing single indices may not fully capture the complexity of vegetation elements and require evaluation through various indicators. Therefore, this study introduced the Multi Criteria Vegetation Ecological Quality Index (VEQI), coupled with vegetation cover and vegetation ecological function indicators, to explore the driving factors of vegetation quality in the middle reaches of the Yangtze River and identify key areas where vegetation quality declines or improves. By constructing a Bayesian network for VEQI, we identified the driving variables that influence the index. Additionally, we delineated spatial optimization zones for VEQI. The results indicate that the VEQI exhibits a trend of transitioning from low values in urban centers to high values in suburban and rural areas. Over 20 years, the average VEQI of the study region ranged from 10.85% to 94.94%. Slope, DEM, and vegetation type were identified as significant drivers of VEQI, while precipitation, temperature, and nighttime light were considered secondary factors. Notably, areas in Hunan, Jiangxi, and Hubei provinces, especially the western part of Hunan, were pinpointed as spatial optimization regions. This research not only enhances the understanding of vegetation’s ecological quality in the urban agglomeration of the middle reaches of the Yangtze River but also provides scientific insights for the protection and management of vegetation.

Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China

As global climate change intensifies and human activities escalate, changes in vegetation cover, an important ecological indicator, hold significant implications for ecosystem protection and management. Shandong Province, a critical agricultural and economic zone in China, experiences vegetation changes that crucially affect regional climate regulation and biodiversity conservation. This study employed normalized difference vegetation index (NDVI) data, combined with climatic, topographic, and anthropogenic activity data, utilizing trend analysis methods, partial correlation analysis, and Geodetector to comprehensively analyze the spatiotemporal variations and primary driving factors of vegetation cover in Shandong Province from 2001 to 2020.The findings indicate an overall upward trend in vegetation cover, particularly in areas with concentrated human activities. Climatic factors, such as precipitation and temperature, exhibit a positive correlation with vegetation growth, while land use changes emerge as one of the key drivers influencing vegetation dynamics. Additionally, topography also impacts the spatial distribution of vegetation to a certain extent. This research provides a scientific basis for ecological protection and land management in Shandong Province and similar regions, supporting the formulation of effective vegetation restoration and ecological conservation strategies.

Spatiotemporal Variation in Ecological Environmental Quality and Its Response to Different Factors in the Xia-Zhang-Quan Urban Agglomeration over the Past 30 Years

The interactions between economic development, environmental sustainability, population growth, and urbanization are vital in assessing the ecological dynamics of urban agglomerations. This study explores the relationship between economic development, environmental sustainability, population growth, and urbanization within the Xia-Zhang-Quan urban agglomeration in Fujian Province from 1989 to 2022. Utilizing Landsat remote sensing images, we calculated the Remote Sensing Ecological Index (RSEI) to evaluate changes in ecological quality. The results show that the average RSEI values for 1989, 2000, 2010, and 2022 were 0.5829, 0.5607, 0.5827, and 0.6195, respectively, indicating an initial decline followed by a significant increase, culminating in an overall upward trend. The spatial distribution of RSEI classification shows that the study area has the largest proportion of mainly “good” ecological quality. The proportion of areas with “excellent” ecological environmental quality has increased (13.41% in 1989 and 25.12% in 2022), while those with “general” quality has decreased (28.03% in 1989 and 21.21% in 2022). Over the past three decades, Xiamen experienced substantial ecological degradation (RSEI change of −0.0897), Zhangzhou showed marked improvement (RSEI change of 0.0519), and Quanzhou exhibited slight deterioration (RSEI change of −0.0396). Central urban areas typically had poorer ecological conditions but showed signs of improvement, whereas non-central urban regions demonstrated significant environmental enhancement. The factor detector analysis identified land use as the dominant factor influencing ecological environmental quality, with precipitation having a relatively minor impact. Interaction analysis revealed that all other factors demonstrated bi-variable enhancement or nonlinear enhancement, suggesting that the interactive effects of these factors are greater than the effects of individual factors alone. Land use consistently showed solid explanatory power. Temperature also exhibited significant influence in 2022 when interacting with other factors. Due to urban planning that can plan for land use, these findings suggest that effective urban planning can harmonize economic development with ecological protection within the Xia-Zhang-Quan urban agglomeration.

Microbial nutrient limitation and carbon use efficiency changes under different degrees of litter decomposition.

Alpine ecosystems are important terrestrial carbon (C) pools, and microbial decomposers play a key role in litter decomposition. Microbial metabolic limitations in these ecosystems, however, remain unclear. The objectives of this study aim to elucidate the characteristics of microbial nutrient limitation and their C use efficiency (CUE), and to evaluate their response to environmental factors. Five ecological indicators were utilized to assess and compare the degree of microbial elemental homeostasis and the nutrient limitations of the microbial communities among varying stages of litter decomposition (L, F, and H horizon) along an altitudinal gradient (2800, 3000, 3250, and 3500m) under uniform vegetation (Abies fabri) on Gongga Mountain, eastern Tibetan Plateau. In this study, microorganisms in the litter reached a strictly homeostatic of C content exclusively during the middle stage of litter decomposition (F horizon). Based on the stoichiometry of soil enzymes, we observed that microbial N- and P-limitation increased during litter degradation, but that P-limitation was stronger than N-limitation at the late stages of degradation (H horizon). Furthermore, an increase in microbial CUE corresponded with a reduction in microbial C-limitation. Additionally, redundancy analysis (RDA) based on forward selection further showed that microbial biomass C (MBC) is closely associated with the enzyme activities and their ratios, and MBC was also an important factor in characterizing changes in microbial nutrient limitation and CUE. Our findings suggest that variations in MBC, rather than N- and P-related components, predominantly influence microbial metabolic processes during litter decomposition on Gongga Mountain, eastern Tibetan Plateau.

Assessment of Ecological Quality and Analysis of Influencing Factors in Coal-Bearing Hilly Areas of Northern China: An Exploration of Human Mining and Natural Topography

The Changhe Basin is located in the earth–rock mountainous area in southeastern Shanxi, China, and represents a characteristic northern coal-bearing hilly area. The terrain is complex, and the area is rich in coal mines. It plays an indispensable role in maintaining ecological balance and sustainable development in North China. To investigate the changes in ecological quality in the Changhe Basin, as well as the impact of human mining activities and natural topography on ecological quality, this study constructs the Remote Sensing Ecological Index (RSEI) based on Landsat remote sensing images from 2001, 2008, 2015, and 2022, undertaking an analysis of the spatial–temporal distribution characteristics of the ecological quality and its changing trends over the past 20 years. Additionally, spatial autocorrelation distribution features are revealed using Moran’s I. The exploration extends to examining the relationship between mining activities and the surrounding ecological quality. Subsequently, we study the relationship between Topographic Wetness Index (TWI) and RSEI. The results indicate the following: (1) On the temporal scale, the average proportion of RSEIs categorized as excellent and good from 2001 to 2022 is 46.78%. Types showcasing stable ecological conditions average 52.49%. The level of overall ecological quality of the basin has remained consistently high. On the spatial scale, the western part of the Changhe River, particularly in mountainous areas, exhibits higher ecological quality. Poorer areas concentrate in Chuandi Town in the southwestern part, and are significantly impacted by mining activities. The eastern region manifests areas undergoing either rapid or gradual degradation. (2) The four-phase Moran index results reveal a robust positive correlation in the spatial distribution of ecological quality within the basin. High–High and Low–Low clusters dominate, while High–Low and Low–High distributions are scattered. (3) Mining activities exert a discernible impact on the surrounding ecological quality. As the distance from the buffer zone outside the mining area increases, RSEI gradually decreases. The impact level exhibits an initial increase and subsequent decrease from 2001 to 2022.

Dynamic evaluation of the ecological evolution and quality of arid and semi-arid deserts in the Aibugai River Basin based on an improved remote sensing ecological index

The ecological quality of arid and semi-arid regions (ASRs) is fragile, and the evaluation of dynamic changes in the multi-factor, long-time-series ecological quality of these regions can provide a scientific basis for sustainable regional development. Based on the remote sensing ecological index (RSEI) and its derivative indices dedicated to monitoring ecological quality in ASRs, this study proposes a new modified RSEI (nmRSEI) suitable for ASRs. We used the nmRSEI to evaluate the dynamic changes in the ecological quality and analyse the factors driving these changes in the Aibugai River Basin in the middle of the Inner Mongolian Plateau in the arid core of Asia from 1986 to 2022. The results led to the following conclusions: (1) the use of the nmRSEI helps solve the problems related to the original greenness index, i.e. normalised difference vegetation index, which was readily affected by the soil background in areas with low vegetation coverage; (2) the new dryness index can meet the evaluation requirements for the surface dryness degree in >98.65% of the study area; (3) the introduced salinity index showed a significant negative correlation with the nmRSEI; (4) the nmRSEI exhibits a gradual downward trend (Slope = −0.00326/10a); and (5) temperature was the main factor controlling the ecological quality during the research period. The nmRSEI provides a fast and effective new method for regularly monitoring ecological quality in ASRs. In addition, driving factor analysis can provide theoretical support for ecological protection in ASRs and the realisation of the United Nations 2030 Sustainable Development Goals.

Ecosystem health assessment of East Kolkata Wetlands, India: Implications for environmental sustainability

The East Kolkata Wetlands (EKW) in Kolkata, India, span 12,500 ha and are a vital ecological zone providing several benefits, including water purification, flood control, and biodiversity support. This study investigated land use and land cover (LULC) alterations in the EKW from 1991 to 2023, using a random forest (RF) machine learning model. Significant LULC changes were observed over the 32 years, with wetland areas decreasing from 91.2 km2 in 1991 to 33.4 km2 in 2023, reflecting substantial habitat loss and reduced ecosystem services. Conversely, agricultural land expanded from 27.8 km2 to 58.7 km2, driven by economic and food production needs, and built-up areas increased dramatically from 0.2 km2 to 10.5 km2, indicating rapid urbanization. This study evaluated the health, resilience, and ecosystem functionality of EKW by analysing human-induced land use changes and using ecological indicators and landscape metrics. Landscape and class level metrics such as PLAND, largest patch index (LPI), total edge (TE), edge density (ED), number of patches (NP), and patch density (PD) were used to analyse the spatiotemporal dynamics of the wetlands. This study revealed a significant increase in fragmentation, with the number of patches increasing from 2689 in 1991 to 4532 in 2023, despite a consistent decrease in core wetland areas. Ecosystem health indicators, such as the ecosystem structure index (ESI) and landscape deviation degree (LDD), were used to assess landscape metrics and fragmentation changes. The ESI and other metrics revealed significant temporal fluctuations, providing insights into landscape structure, connectivity, and heterogeneity. The ESI improved from 0.87 in 1991 to 1.03 in 2023, indicating enhanced connectivity and diversity. Conversely, the LDD increased from 20.6% to 56.85%, indicating a shift towards impervious surfaces. The vegetation productivity and ecosystem health index (EHI) decreased, indicating biodiversity loss and reduced carbon sequestration. The EHI also dropped from 0.67 to 0.55, signifying ongoing environmental stress. This study emphasizes the need for conservation efforts to maintain the ecological integrity of the EKW amidst urbanization and land use changes and recommends a balanced approach for sustainable urban development and enhanced wetland resilience.

A new multi-method decision framework for anchor selection and tenant mix allocation optimisation in shopping malls

The increasing urbanisation and fast-paced lifestyle have heightened the importance of shopping malls in retail industry, altering traditional shopping patterns by designing efficient space and optimise time of shoppers. Due to this newly-acquired importance, these malls have become critical players in the retail industry sector. Despite their significance, current research lacks comprehensive scientific methods in two critical aspects: the classification of anchors (or magnet shops) and regular tenants, and the detailed analysis of interrelations among anchors and tenants within the shopping malls. Both aspects are heavily related to the strategic allocation of shops position within malls. For addressing these gaps, this paper introduces a multi-method framework expert system to classify anchors and tenants and to optimise their positions in the shopping mall, considering their categories and existing product relationships. This framework comprises a new sorting method, a modified ranking method, a product correlation technique based on implementing ecological dynamics, an ecological interrelation index, and a metaheuristic allocation algorithm. The practical application of this framework is demonstrated through a real-world case study, highlighting its potential to significantly improve shopping mall management and retail efficiency. The effect of the proposed framework is subject to empirical tests and comparison between layout modifications.

Composition and distribution of nutrients and environmental capacity in Dapeng Bay, northern South China Sea

Seawater physicochemical parameters and environmental capacity are important ecological indicators and typical features of the marine environment. It has great significance in the marine material cycle and ecological health. In September 2021 (wet season) and March 2022 (dry season), two voyage investigations were conducted at 12 stations (D1-D12) on Dapeng Bay (DPB), northern South China Sea. The distribution of nutrient, water-quality status, environmental capacity, and impact of ecological environment were discussed. Results showed that NH4-N was the main form of dissolved inorganic nitrogen (DIN) during the wet season, with concentrations ranging from 0.008 mg/L to 0.109 mg/L, accounting for ~53 % of DIN. Conversely, NO3-N was the main form of DIN during the dry season, with concentrations ranging from 0.005 mg/L to 0.117 mg/L, accounting for ~50 % of DIN. The DIP concentration ranged from 0.002 mg/L to 0.019 mg/L, accounting for ~51 % and 31 % of the total dissolved phosphorus in the wet and dry seasons, respectively. The distributions of NH4-N, NO3-N, NO2-N, and DIP were relatively similar, decreasing from the inner bay to the outer bay. The eutrophication indices of 12 stations <1, indicating a poor eutrophication state. Single-factor indices including chemical oxygen demand (COD), DIN, and dissolved inorganic phosphorus (DIP) were less than the class I seawater-quality standard. However, except for station D1, the overall water quality was good. Dissolved oxygen with DIP had a significantly negative correlation during the dry season, indicating that DIP was primarily dominated by marine biological activity and organic-matter decomposition. The remaining environmental capacities of COD, DIN, and DIP in DPB were calculated to be 13,742, 1418, and 141 tons, respectively. Based on the functional-zone division of the sea area, the remaining environmental capacities of COD, DIN, and DIP were exceeded 75 % of the total environmental capacity. This study provided a scientific basis for the protection of marine ecological environment and the sustainable development of DPB.

Exergetic, economic and exergy-based sustainability analysis of a power generation system with CO2 capture and methanol production

This study proposes a new biomass-based Combined Heat and Power (CHP)/renewable methanol production through captured carbon dioxide. A liquid organic hydrogen carrier (LOHC) stores and releases hydrogen. Literature review shows that LOHC has been integrated into such a system for the first time. The exergetic, exergoeconomic, and economic performance are researched. On average, results show that the exergetic efficiency of the system is 6.6 %. Depletion ratio (DR) is the depletion rate of the exergy source given to the system, which is desired to have low values. The sustainability index (SI) is the DR's reverse, representing the required exergy source per exergy destruction (exergy depletion). High values of this index indicate less exergy source consumed in the system. Exergetic ecological index (EECI) compares the useful products or depleted exergy per consumed exergy source destruction. The negative value of EECI means that the depletion of the exergy source is more significant than the product exergy and vice versa. The exergy-based sustainability indices, including DR, SI, and EECI, are found as 0.934, 1.071, and −0.868, respectively. Exergoeconomic analysis reveals that the exergy destruction rate at the system's capital cost (REX) value is 0.087×102. Heat Recovery Steam Generator (HRSG), gasifier, and Heat Exchanger 1 (HE1) are obtained as 5.153×10−2 (kW/€), 1.707×10−2 (kW/€), 3.094×10−2 (kW/€) respectively. The payback period and the REX are 14.56 years and 0.087×10−2 (kW/€), respectively; it seems long for an engineering application, but these technologies are relatively new, and their costs might decrease soon. Exergy destruction or lost power per capita, which means depleted investment, costs much less than 1. Although the thermodynamic values of the system seem low because irreversibilities occurred in chemical reactions, CO2 saved and produced methanol and cannot be ignored in terms of its environmental and economic benefits, considering CO2 taxes and the methanol economy.

Mapping China's reserved arable lands and its sustainable cropping layout.

Reserved arable lands in China is of great significance for rationally allocating crop planting structures, alleviating the pressure of grain imports, and protecting food security. Owing to data acquisition limitations, obtaining the spatial distribution of reserved arable lands at large spatial scales is relatively rare, and there is little information on predicting the suitability, production capacity, and ecological effects of crop cultivation in reserved arable lands. This study obtained the distribution of reserved arable lands in China by applying restrictive factors, and used the Food and Agriculture Organisation of the United Nations (FAO) suitability index for eight crops to obtain a spatial distribution map of suitable crops, proposed a cropland ecological efficiency index (CEEI) to analyse the ecological impact of crop cultivation in reserved arable lands. China possesses approximately 3.93 million hectares of viable reserved arable lands comprising primarily grasslands (67.68%), sandy land (8.11%), saline-alkali land (20.68%), and bare land (3.53%). The average CEEI for the eight crops under irrigation conditions ranges from 0.844 to 0.865, and that under rain-fed conditions (excluding rice) ranges from 0.609 to 0.779. We proposed the development of rain-fed agriculture with sorghum as the primary crop in the central part of Shanxi and Inner Mongolia, while promoting the cultivation of rapeseed and soybeans in the eastern parts of Heilongjiang, Jilin, and Inner Mongolia. Overall, the development of irrigation agriculture focusing on wheat and barley should be pursued only when water resources are guaranteed, particularly in north-western regions such as Gansu, Ningxia, Xinjiang, Qinghai, and Shaanxi. © 2024 Society of Chemical Industry.

Vegetation structure of associated flora in Amorphophallus gigas Teijsm. &amp; Binn. (Araceae) habitats, North Padang Lawas Regency, North Sumatra

Amorphophallus gigas, a native aroid species found in the tropical forests of Sumatra, Indonesia, lacks robust population data despite previous spatial distribution studies. While not officially protected, A. gigas is considered rare in field documentation and faces potential habitat loss due to its proximity to the popular corpse flower. This 2023 study conducted in Halongonan District, North Padang Lawas Regency, North Sumatra, Indonesia, aimed to gather information on the habitat characteristics and associated flora of A. gigas to guide land conservation initiatives. The research focused on a forested area within three villages: Bargot Topong Julu, Napa Lancat, and Pangirkiran, utilizing a purposive random sampling approach. Plots covering 1 ha each were selected based on Amorphophallus in the generative phase across various land covers. Ecological analysis and indices were derived from collected vegetation data. The survey unveiled varying numbers of generative and vegetative A. gigas individuals across the three study sites. The understorey community at each site exhibited different levels of association with A. gigas, with Selaginella willdenowii, Clidemia hirta, and Leersia virginica showing strong positive correlations. The floral community in A. gigas habitats displayed diverse species richness and diversity across different growth stages and locations. Findings suggest that altitude, slope, pH, light intensity, air temperature, and humidity may influence A. gigas abundance in distinct ways. This study offers valuable insights into the biological and ecological factors influencing the distribution and abundance of A. gigas populations, providing guidance for conservation and management efforts.

Ecological influence of oasisation on peripheral regions

Sustainable development of oases enhances the capability of ecosystems to reverse land degradation in arid regions. However, it is unclear to what extent oasisation leads to ecological quality (EQ) degradation in the peripheral environment. To comprehensively evaluate the ecological effects of oasisation, this study developed a remote sensing ecological quality index to characterise spatiotemporal patterns and driving mechanisms of EQ in different oasis-type areas. Results show that the oasis area has increased by 37.4 % in the past 22 years. The EQ of the core area was stable, but EQ declined in newly developed urban areas. The effect range of the oasis on the peripheral regions EQ is 12 km, and the expansion of the oasis is improving the EQ of peripheral regions. The driving factors of EQ varied widely among different oasis areas. The vegetation index showed significant explanatory power (q-mean is 0.45) in each oasis area. Human activities and soil moisture showed the most significant explanatory power (0.76) in the core area, but weak power is observed in the changed and peripheral areas. Climate factors have the strongest influence on the changed and peripheral areas. The findings provide an in-depth understanding of the spatial heterogeneity of EQ and could be implemented in Oasis urban planning and sand prevention belt construction.