Environmental Management最新文献

Conservation agriculture (CA) is promoted by various organisations and scholars as alternative to conventional agriculture to meet growing food demand with minimal damage on environment; but its factors of adoption have not been well identified. The study uses the recent composite index of adoption of CA developed by Takam Fongang et al. (2023) to analyse the factors of adoption of conservation agriculture among maize and soybean farmers in Quebec. Using data from 93 maize and soybean producers and a Fractional logit model, the study shows that adoption of CA increases with farmer’s favourable perceptions of yield and easiness of implementing CA, off-farm employment and higher education. The study therefore indicates that higher education, technical assistance and popularisation of performance of CA can play a significant role in boosting adoption of CA in Quebec.

Semi-natural grasslands (SNGLs) in Estonia are threatened by abandonment. This threat is leading to concerns about the degradation of biodiversity within grassland communities. Despite the high relevance of economic incentives in this context, how such incentives influence land managers’ decision-making regarding the agricultural use of SNGLs has not been investigated. To obtain its socio-ecological implications for policy-making, we developed regionally specific agricultural scenarios (compensation payments, livestock capacity, hey export, and bioenergy production) and an interdisciplinary modelling approach that made it possible to simulate agricultural land use changes through land managers' responses to varied economic conditions. Through this approach, we found that some economic factors hampered the use of SNGLs: the moderate profitability of beef production, labour shortages, and the relatively high profitability of mulching. We observed a positive relationship between SNGLs and habitat suitability for breeding and feeding birds. However, due to the high maintenance costs of SNGLs, the modelling results indicated that increasing the use of SNGLs through public budgets caused crowding-out effects, i.e., the deteriorating market integration of regional agriculture. This study emphasises the need for policy measures aimed at cost-effective, labour-efficient management practices for SNGLs.

The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in mitigating climate change, there are very few studies that have assessed the overall spatial distribution of cover crops and tillage practices based on the farm’s pedoclimatic and topographic characteristics. Hence, the primary objective of this study was to use multiple satellite-derived indices and environmental drivers to infer the level of tillage intensity and identify the presence of cover crops in eastern South Dakota (SD). We used a machine learning classifier trained with in situ field samples and environmental drivers acquired from different remote sensing datasets for 2022 and 2023 to map the conservation agriculture practices. Our classification accuracies (>80%) indicate that the employed satellite spectral indices and environmental variables could successfully detect the presence of cover crops and the tillage intensity in the study region. Our analysis revealed that 4% of the corn (Zea mays) and soybean (Glycine max) fields in eastern SD had a cover crop during either the fall of 2022 or the spring of 2023. We also found that environmental factors, specifically seasonal precipitation, growing degree days, and surface texture, significantly impacted the use of conservation practices. The methods developed through this research may provide a viable means for tracking and documenting farmers’ agricultural management techniques. Our study contributes to developing a measurement, reporting, and verification (MRV) solution that could help used to monitor various climate-smart agricultural practices.

In many developed and developing nations, lakes are the primary source of drinking water. In the current scenario, due to rapid mobilization in anthropogenic activities, lakes are becoming increasingly contaminated. Such practices not only destroy lake ecosystems but also jeopardize human health through water-borne diseases. This study employs advanced hierarchical clustering through multivariate analysis to establish a novel method for concurrently identifying significantly polluted lakes and critical pollutants. A systematic approach has been devised to generate rotating component matrices, dendrograms, monoplots, and biplots by combining R-mode and Q-mode analyses. This enables the identification of contaminant sources and their grouping. A case study analyzing five lakes in Bengaluru, India, has been conducted to demonstrate the effectiveness of the proposed methodology. Additionally, one pristine lake from Jammu & Kashmir, India, has been included to validate the findings from the aforementioned five lakes. The study explored correlations among various physical, chemical, and biological characteristics such as temperature, pH, dissolved oxygen, conductivity, nitrates, biological oxygen demand (BOD), fecal coliform (FC), and total coliform (TC). Critical contaminants forming clusters included conductivity, nitrates, BOD, TC, and FC. Factor analysis identified four primary components that collectively accounted for 85% of the overall variance. Following identification of pollution hotspots, the study recommends source-based pollution control and integrated watershed management, which could significantly reduce lake pollution levels. Continuous monitoring of lake water quality is essential for identifying actual contaminant sources. These findings provide practical recommendations for maximizing restoration efforts, enforcing regulations on pollutant sources, and improving water quality conditions to ensure sustainable development of lakes.

This study examines the relationship between institutional trust from an individual and societal perspective and perceived corruption and climate attitudes of individuals in Latin America. To this end, multilevel modeling was used to test whether the attitudes of individuals from 285 regions of Latin America are influenced by these constructs. Based on the results, it was found that in contrast to studies in developed countries, where institutional trust is positively associated with pro-climate attitudes, in Latin America institutional trust acts as an inhibiting factor and is inversely related to climate attitudes. Furthermore, the perception of corruption in public institutions was also identified as a factor inhibiting collective action to combat climate change. Moderation analysis revealed that individuals’ level of education significantly influences this relationship, with a notable difference in climate attitudes between individuals with low and high levels of trust, especially among those with less education. These findings highlight the importance of taking regional specificities into account when examining the relationship between institutional trust, perceptions of corruption, and climate attitudes, and underscore the need for public policies that promote transparency and accountability of institutions to foster effective collective action on climate change.

The illegal wildlife trade (IWT) is a global phenomenon that adversely affects biodiversity and human well-being. Understanding how institutions manage this trade is crucial for reducing its negative impacts. Latin America has the fewest IWT studies globally; thus, science in support of more effective institutional management of IWT is limited. This study aims to bridge the researcher-practitioner gap by providing applicable results and involving control institutions. To this end, we examine the strengths and weaknesses of Uruguay’s institutions in addressing this issue, introducing the concept of institutional management competence to the knowledge base about IWT. Based on this case study, we aimed to generate inputs to guide policymakers in achieving better control of the IWT, contributing to reduce the researcher-practitioner gap. From an interdisciplinary perspective that articulates qualitative and quantitative methods, the study presents the following results: (a) Uruguay’s network for addressing illegal wildlife trade involves numerous institutions whose articulation has a high degree of informality; (b) these institutions address different stages of trafficking based on their roles, jurisdiction, and engagement; (c) main weaknesses include insufficient state-level prioritisation, weak institutional coordination, inadequate training, insufficient infrastructure, space and personnel to handle the volume of seized animals, lack of proper facilities for seized animals, and a need for better-organised information. Our results help shed light on the IWT management structures in Uruguay and identifies where direct improvements can be made to strengthen the institutional responses to global IWT.

The impacts of landscape patterns on river water quality are commonly acknowledged, but understanding the complex processes by which landscape patterns affect water quality is still limited, especially in densely populated urban areas. Exploring the mechanisms through which landscape characteristics influence water quality changes in urbanized rivers will benefit regional water resource protection and landscape-scale resource development and utilization. Utilizing daily water quality monitoring data from rivers in the urbanized area of the Pearl River Delta in 2020, our research employed canonical analysis and partial least squares structural equation modeling (PLS-SEM) to explore the processes and mechanisms of the influence of urbanized river landscape patterns on surface water quality. The results indicated that total nitrogen (TN) was the critical indicator limiting the water quality of rivers in the Pearl River Delta. The landscape composition and configuration indexes exhibited non-linear variations with scale, and the landscape fragmentation was higher closer to the river. Landscape patterns had the most significant influence on water quality under the characteristic scale of a 5.50 km circular buffer zone, and landscape composition dominated the change of water quality of urbanized rivers, among which 30.64% of the percentage patch area of construction (C_PLAND) contributed 46.40% to the explanation rate of water quality change, which was the key landscape index affecting water quality. Moreover, landscape patterns had a higher interpretive rate of 39.29% on water quality in the wet season compared to 36.62% in the dry season. Landscape composition had an indirect negative impact on water quality, with a value of 0.47, by affecting the processes of runoff and nutrient migration driven by human activities, while landscape configuration had an indirect negative impact on water quality, with a value of 0.11. Our research quantified the impacts of landscape patterns driven by human activities on surface water quality and proposed management measures to optimize the allocation of landscape resources in riparian zones of urbanized rivers. The results provide a scientific basis for water quality management and protection in urbanized rivers.

This paper examines the impacts of human-wildlife conflict (HWC) in the Kakum Conservation Area (KCA), Ghana. The primary focus is on crop-raiding by elephants. Using ethnographic methodologies, the findings shed light on the broader impacts of HWC in rural communities. These include food insecurity characterized by a notable decline in the quality and quantity of food accessible to individuals and families affected by crop-raiding. The study also underscores the negative impacts on mental and physical wellbeing as residents contend with stress, anxiety and fear due to crop-raiding and encounters with elephants. Furthermore, this research uncovers how coping mechanisms employed by locals in response to these challenges may result in problem drinking. Also, efforts taken to mitigate crop-raiding unintentionally result in health consequences for farmers who face risks of contracting diseases such as malaria and suffer from sleep deprivation due to guarding their fields at night. More importantly, this study provides an in-depth examination of the broader vulnerabilities caused by HWC which are often ignored and underscores the importance of looking beyond the direct impacts in HWC hotspots like KCA.

Despite changing paradigms in nature conservation, protected areas, such as national parks, remain key tools for nature conservation. Today, protected areas are perceived as socio-ecological systems, therefore using an ecosystem services approach may help in their designation. Here, we focus on the planned Turnicki National Park located in the far eastern part of the Polish Carpathian Mountains and conflict between proponents of the park establishment and local stakeholders. We used an ecosystem services-driven questionnaire survey among local communities to analyze interactions between the perception of ecosystem services and opinions about national parks, and the role of social and economic status in shaping these opinions. We found links between opinions towards national parks and other factors: age, life span in a municipality, level of education, and an average net income. Respondents who perceived benefits from nature were more positive towards national parks in general and the Turnicki National Park specifically; however, those who prioritized provisioning services were more skeptical. Also, we distinguished four Fuzzy-Set Qualitative Comparative Analysis models which describe factors shaping opinions on national parks, respectively. The study has shown that the ecosystem services lens perspective can help in exploring the factors crucial while establishing the protected areas in specific social and economic context. The main implication for the study is careful consideration of the role of national park to protect the local environment in harmony with social needs and economic development.

The main objective of the current study was to use seven lots in Hartford, CT that are planned for community reuse to determine the optimal sampling density that allows for the detection of hotspots of lead pollution while limiting the labor of the sampling process. The sampling density was investigated using soil Pb measured by in situ X-ray Fluorescence as the indicator to evaluate soil health, with a new threshold of 200-mg/kg proposed by the USEPA in January of 2024. Even though this study takes place in an urban setting, where the new USEPA policy requires the use of a 100-mg/kg threshold for Pb due to the fact that there are other identifiable sources of the contaminant, only the 200-mg/kg threshold is discussed because it is evident from the analysis that compliance of a 100 mg/kg threshold in urban plots is highly unlikely (five out of seven sites would require complete site excavation prior to reuse). Using the inverse distance weighted geospatial interpolation of in situ pXRF determined lead measurements, grid sampling resolutions of 3-m, 4-m, 5-m, 6-m, 8-m, 10-m, and 12-m were compared. Ultimately, the case study finds that the largest grid resolution that can be implemented for soil screening to maintain hotspots of pollution to properly inform soil management decisions is a 6-m grid, or a density of approximately 1/36-m².