Environmental and Sustainability Indicators最新文献

Global metropolises and their needs for green space are rising due to demographic urbanization. Some phenomena contradicted to prevailing understanding have been observed in metropolises, such as the “sprawl shrinkage” associated with the increasing built-up area despite declining populations, and the positive relationship between population and greenness. To study these storylines, we conceptualized and mapped 5 urban dynamics by cross-referencing the“increase, stable, and decrease”of built-up area and population density based on threshold values of an introduced Normalized Difference Index (NDI). Furthermore, Kruskal-Wallis H Test was used to analyze the influence of different urban dynamic patterns on 3 greenness trends (greening, browning, and stable greenspace). From 1995 to 2021, Tokyo Metropolitan Area (TMA) gradually transited from intense urban expansion to a stabilization of built-up area and population density in the city center, declining urbanization in the peri-urban areas, and “sprawl shrinkage” in the far-outskirts. Moreover, compared to other urban dynamics, the pattern of built-up areas increases with a population density reduction of over 5% were conducive to maintaining NDVI values of 0.75 or higher. In the future, the ongoing demographic urbanization is highly likely to further exacerbate the phenomenon of urban-suburban disparity and intra-suburban differentiation. We propose that Asian metropolises should enhance regional cooperation and public-private partnerships to address potential regional ecological imbalances. Additionally, it is necessary to maximize the greenness within the given urban dynamics through figuring out the spatial impact mechanisms of urban development on greenness change from a long-term perspective.

Pakistan is the fifth most populous country in the world. Its ecological environment is facing numerous stresses such as climate change, rapid urbanization, natural disasters, and a decline in air quality. Thus, the scientific understanding of spatial and temporal changes in Pakistan's ecological environment is crucial for formulating an informed strategy for regional sustainability. This study used the Google Earth Engine platform and the Remote Sensing Ecological Index (RSEI) to investigate ecological vulnerability in three provinces of Pakistan for 1990, 2000, 2010, and 2020. Landsat 5 and Landsat 8 datasets are used to construct RSEI indicators and Principal Component Analysis (PCA) is adopted to objectively compute RSEI for the past three decades. The results indicated that (1) the ecological vulnerability of the Punjab province exhibited a slightly improved trend from 1990 to 2020 with overall dominance of ‘moderate’ level vulnerability in all four years; (2) The Sindh province has exhibited a declining trend of the ecological environment with ‘poor’ ecological vulnerability contributing to 28.6% of the total area in 2020 as compared to 1.04% of the total area in 1990; and (3) The ecological environment of Balochistan province has shown resilience to some extent during 1900–2010 with the dominance of a ‘moderate’ level of ecological vulnerability. However, a decline is observed between 2010 and 2020. These research results can provide support for the Punjab, Sindh, and Balochistan provinces in achieving sustainable development while conserving the regional ecological environment.

Natural systems face human pressures, demanding urgently Ecological Integrity (EI) assessments. EI assessments identify the state of an ecosystem through biotic and abiotic indicators. Fauna is a key element in the functioning of ecosystems, and therefore, their inclusion in the indicator stock may enhance EI evaluations. We conducted a systematic literature review to evaluate the use of terrestrial vertebrate-derived information as indicators of EI. Fifty-eight publications used information on terrestrial vertebrates as EI. Birds (39) were the group most frequently used as an indicator, followed by mammals (16), amphibians (5), and reptiles (3). Species composition was the most frequently evaluated element of EI, and community metrics such as richness, diversity, indicator species, and abundance stand out as the most frequently used for evaluating the relation of the EI to a terrestrial vertebrate group. The Index of Biological Integrity (IBI) and indices derived from it were the most frequently used to identify the state of integrity of an ecosystem using vertebrates. Few studies have developed a conceptual model that explains the causal relationship between EI and metrics associated with terrestrial vertebrates. EI assessments are a valuable tool for identifying the state of a system. However, it is necessary to complement them with faunal indicators that include various taxonomic groups. The inclusion of more than one taxonomic group would allow for the identification of changes at different levels and generate biological hypotheses of relationships between measurable variables at the faunal level and their incorporation into IE analysis.

In Latin America, there is a lack of green infrastructure (GI) to enhance urban resilience and reduce the contagion levels, particularly in times of pandemic. Therefore, a simplified method is needed to define GI in critical public health risk scenarios, especially when access to geospatial information is limited. The objective of this study is to propose a simplified method called GreenNet-Covid19 in Peru during critical public health scenarios using spatial analysis methods to define the global GI index (GGII) and select the potential integration areas for GI (PIAGI). This method is based on the approach proposed by Aguileraet al. (2018), which utilized spatial analysis in Metropolitan Arequipa and its surroundings during the COVID-19 pandemic. In this study, in addition to the four dimensions proposed Aguilera et al. (2018), a fifth dimension called ‘risk due to COVID-19’ was introduced, allowing to obtain the GGII and define the PIAGI. The GGII showed high ecological and biodiversity potentials at the vegetation cover level. However, the loss of GGII connectivity in urban areas posed a threat to the intricate connectivity of the highlands, thus increasing the risk of COVID-19 spread. Meanwhile, the PIAGI exhibited relatively low values compared with those of the GGII. Yet, the loss of PIAGI connectivity in urban areas strengthened the factors contributing to COVID-19 propagation. The intersection between the COVID-19 and PIAGI risk layers at the ‘very high,’ ‘high,’ and ‘medium’ levels demonstrated a high capability for reducing the contagion risk in future pandemics. The introduction and implementation of this method in territorial planning is facilitated by its applicability to any Latin American territory.

Indoor environments can pose a substantial respiratory infection risk, especially in densely populated areas. It is therefore vital to evaluate and predict infection risks for mobile individuals engaging in indoor activities. However, previous studies have primarily focused on assessing viral transmission probabilities between relatively stationary individuals, disregarding the dynamic features of pedestrian trajectories. To address this issue, we propose an approach that uses precise trajectory data and digital twin technology to evaluate and forecast indoor infection risks for mobile individuals. Our approach involves the utilization of high-precision trajectory data to develop a time-varying virus density field map (VDFM), forming the basis for infection risk assessment. Additionally, we present a deep-learning model that employs the transformer method to predict future time-varying VDFMs and associated infection risks. Furthermore, we introduce digital twin to comprehend real-time interactions between the physical and digital realms within the structure. To validate our approach, we conducted a case study at the Wuhan International Exposition Center, serving as the control room. We performed a sensitivity analysis on various preventive measures, including mask-wearing, social distancing, and indoor infection control. The results highlighted the significant impact of these measures on individual infection risks associated with indoor activities. Our research contributes to the development of tailored prevention and control strategies, which play a critical role in mitigating the spread of respiratory infections. Thus, this study holds significant implications for technology-facilitated public health services.

The underground transfer of nitrogen from non-food crop residues to cash crops is an important tool to ensure decent crop yields and balance N use in agroecosystems. Laboratory experiments were performed to determine nitrogen migration in spring wheat at different growth stages using labelled nitrogen. In the first stage of the experiment, Artemisia dubia was grown in climate chambers (Climacell CLC-707-TV), with air temperature cycles of 8 h at 15 °C and 16 h at 20 °C, and fertiliz using ¹⁵N isotope enriched ammonia nitrate. In the second stage of the experiment, spring wheat was sown and grown to full maturity in two soils of differing soil acidity (pH 3.93 ± 0,04 and pH 7.07 ± 0,08) and mixed with the chopped pieces (3–5 cm mean length) of Artemisia dubia above-ground biomass obtained in the first stage of the experiment. Each soil had four experimental treatments: non-enriched biomass; non-enriched biomass and fertilizer (170 N kg h⁻¹); biomass enriched by ¹⁵N and no fertilizer, and ¹⁵N enriched biomass and fertilizer (170 N kg h⁻¹). Spring wheat and soil were sampled every two weeks for dry matter (DM), total N and ¹⁵N content measurements during the experiment (13 weeks). The results showed that improved crop nitrogen utilization from Artemisia dubia residues were achieved when additional crop fertilizers was not used. It implies that adding additional nitrogen might increase the degradation of plant biomass, but at the same time cause environmental pollution by leaching as plants use it slightly for their growth.

Climate change is triggering shifts in species distribution eventually altering communities' biogeography. The composition of a community in terms of its species' ecological niche informs of a community's response to environmental conditions and impacts, which is central for a timely conservation. While the thermal niche has been widely explored, given it offers a direct link of warming effects on an assemblage, acknowledging the multivariate nature of a species niche can provide relevant insights of the reorganizations taking place at a community-level. We studied the mean and variance of 10 ecological traits at the community level in two regional ecosystems in the temperate East-Atlantic and the Mediterranean Sea, characterized by a distinct exposure to warming. Our findings revealed major temporal changes and spatial structuring in the traits and ranges explored over the last decades. Apart from confirming the expected general poleward, deep-ward shift, our results highlighted a widening of thermal and latitudinal ranges, possibly related to a ‘flexibilitation’ of the communities in a context of global change. In addition, temporal patterns reflected how communities have adjusted around regime shifts known in both areas. Regional differences arose concerning the variance of depth ranges and area of distribution, as well as to the global evolution of the communities, which we argue are consequence of their different geographical features and ecological history. The comparison of two large multitaxon assemblages has disclosed a broad-scale motion of response to warming in the bentho-demersal domain. We expect this study will contribute to the understanding of the multivariate nature of global-change effects on marine fauna, which ultimately informs adaptive management.

Wind erosion increases risks to soil productivity and food security, which have large implications for ecosystems and human well-being. However, the spatial patterns of how ecological restoration and climate change affect wind erosion remain poorly understood. Here, we combined scenario analysis with wind erosion assessment to evaluate the spatial associations of wind erosion with ecological restoration and climatic factors on the Tibetan Plateau. A structural equation model (SEM) was developed to determine the major driver of wind erosion. We identified an overall decrease of wind erosion modulus during 2001–2018, followed by increases of 7.2–19.4% under different climate change scenarios in 2030. Nearly two-thirds of the study area was characterized by wind erosion primarily driven by climate change, while ecological restoration accounted for the wind erosion in almost two-fifths of the study area. The SEM revealed a dominating role played by wind speed in affecting wind erosion directly and indirectly by modulating soil and vegetation conditions. Our study highlights the importance of embracing the spatial variations in the impacts of ecological restoration and climatic factors into the systematic planning of soil conservation and management. Results of this study could inform response strategies aiming to prevent and control wind erosion by identifying the location and extent of affected ecosystem services in the context of climate change.

Rural decline is a global concern, and Ecosystem Services (ES) play a crucial role in both rural revitalization and the Human Well-being (HW) of residents. This study investigated 9 revitalization cases in Shandong province, China, employing both quantitative and qualitative methods. It confirmed the effect on HW based on ES, using a comprehensive assessment framework covering local ecosystem services contribution and economic/social effect derived from the Millennium Ecosystem Service Assessment (MA) and Japan Biodiversity Outlook (JBO) and consolidated variations into four ES dimensions from a HW perspective. As a result, 4 common types of rural revitalization were identified: (A) Large-scale Agriculture, (B) Local Specialty/Brand Making, (C) Industry Integration, and (D) Urbanization Village, based on actors, core industries, and key revitalization activities. According to interviews with local residents, the residents express high levels of satisfaction with revitalization activities. Using TOPSIS analysis, we found that urbanization-led revitalization (D) excels in “economic/social” dimensions but falls short in “Interaction with nature and health" and “Life and culture with nature." In contrast, agriculture-based revitalization activities (A and B) offer a more balanced impact across various ES dimensions. The well-being of residents varies depending on how they utilize and connect with nature. These findings underscore the potential of large-scale agricultural development to address rural population decline and suggest that fostering a positive exchange of ES, HW and capital between rural and urban areas can enhance the resilience of the rural-urban system. These insights are especially relevant for addressing the urban-rural imbalances in developing countries experiencing urban expansion and rural decline.

Water Quality Indices (WQIs) are increasingly being applied for reporting on the suitability of water for a variety of human uses including agriculture. This systematic review identified and compared 42 examples of Agricultural use Water Quality Indices (AgWQIs) for surface waters in published literature. The review confirmed the growing popularity in AgWQI reporting, particularly in the last six years. All studies incorporated the suitability of water for irrigated cropping into their AgWQI with three also addressing stock watering. The review confirmed that all parameter thresholds adopted by AgWQI studies originated from either the Food and Agriculture Organisation of the United Nations publication Water quality for agriculture publication or National Standards. An AgWQI common key was developed to overcome interstudy method variability and facilitate comparative assessment. This assessment determined that all study methods originated from two sources, the Canadian Council of Ministers of the Environment Water Quality Index, and the National Sanitation Foundation Water Quality Index. For studies adopting the latter method, a further three strategies for parameter weightings and eight functions for developing water quality ratings were identified. Our assessment also identified and explored limitations with some equations, including a method known as the proportionality constant. Significant variation in parameters, classes, thresholds, subindices, and weightings between studies was found, but also some areas of agreement. Based on the review findings, a guide has been developed to assist in future AgWQI development.