Regional Management Strategies Research Articles

Spatiotemporal pattern of NPP and its response to climatic factors in the Yangtze River Economic Belt

Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally.

Strategi Pengelolaan Lanskap Wisata di Perkampungan Budaya Betawi Setu Babakan Jakarta

Setu Babakan Betawi Cultural Village (PBBSB) is a built landscape to save and maintain Betawi cultural traditions, including religion, culture, and Betawi arts with a community. It is fostered by the culture which includes all the results of ideas and works, both physical and non-physical, such as art, customs, folklore, literature, culinary, clothing, and architecture that are characterized by Betawi. PBBSB is an area designated by the government as a sustainable Betawi cultural preservation area with diverse tourism potential. This research aimed to map the existing conditions, inventory the potential tourist attractions, to calculate the carrying capacity, and to develop a management strategy for the PBBSB area. The research method used descriptive quantitative and qualitative analysis, carrying capacity assessment, and SWOT analysis. Based on the results of the study, the existing condition of the PBBSB area still remained to facilitate the activities that take place in this area, obtained several types of tourism that can attract the attention of visitors to the PBBSB area to realize and learn more about Betawi culture, the value obtained the carrying capacity of PCC &gt; RCC &gt; ECC = 22,923 &gt; 4,031 &gt; 3,084. This value indicates that the current carrying capacity of the PBBSB allows the area to move towards the sustainability of the Betawi cultural preservation area. More over several regional management strategies can be used to preserve the area of Setu Babakan Betawi Cultural Village.

A combined methodological approach to characterize pig farming and its influence on the occurrence of interactions between wild boars and domestic pigs in Corsican micro-regions.

The pig sector in Corsica is based by a wide range of farming systems, mainly characterized on traditional extensive practices, which favor contacts between domestic and wild individuals. These contacts are suspected to influence the maintenance and the transmission of shared infectious diseases between both populations. Therefore, it is important to develop methods that allow to understand and anticipate their occurrence. Modeling these interactions requires accurate data on the presence, location and use of land on pig farms and farming practices, but such data are often unavailable, incomplete or outdated. In this study, we suggest a method to collect and analyze pig farming information that combines approaches from social sciences and epidemiology and enables a spatial representation of an index of potential interaction (IPI) between wild and domestic pigs at municipality level in the Corsican territory. As a first step of the process, interviews were conducted to gather information from 103 pig farms. Then, using hierarchical clustering, we identified five different clusters of pig farming practices which were evaluated and validated by local experts using participatory tools. The five pig farming clusters with their respective estimated levels of direct and indirect interactions with wild boars were combined in a linear equation with pig density to estimate a hypothetical index of potential interaction (IPI) in 155 municipalities. Our results revealed the diversity of pig farming practices across the island of Corsica and pointed out potential hotspots of interaction. Our method proved to be an effective way to collect and update information on the presence and typology of pig farms which has the potential to update official livestock production statistics. The spatial representation of an IPI between wild boars and domestic pigs in the Corsican territory could help design regional disease management strategies and policies to improve the control of certain shared pig pathogens in pig farms from Corsica.

Application of machine learning in the assessment of landslide susceptibility: A case study of mountainous eastern Mediterranean region, Syria

Landslide is a considerable geomorphological risk in terrain systems worldwide. Advanced techniques present a unique tool for predicting landslide susceptibility with unbiased and precise outputs. However, the application of this tool to analyze landslide susceptibility in the eastern Mediterranean landscape is still not sufficiently understood. This study aimed to assess the implementation of three machine learning (ML) algorithms, i.e., support vector machine (SVM), random forest (RF) and extreme gradient boost (XGBoost), in landslide susceptibility mapping in the mountainous area of western Syria. In this regard, 200 landslide events were inventoried from historical data, aerial images and conducted fieldworks. Sixteen triggering factors were selected according to the literature and geographical features (Monsoon period). The receiver operating characteristic (ROC) outcomes revealed that the RF achieved better performance with an area under curve (AUC) of 0.96, pursued by XGBoost and SVM with AUC of 0.94 and 0.90, respectively. This assessment presents an essential understanding of the effective implementation of ML in landslide assessment in the mountainous region of the eastern Mediterranean. We emphasized, hence, that the RF algorithm has the most robust performance of landslide susceptibility prediction in the western Syria. Moreover, the outputs of this study will provide local decision-makers with insights to produce regional management strategies for the landslide, especially after the Syrian war phase.

Carbapenem-resistant Enterobacterales among hospitalized patients in Cape Town, South Africa: clinical and microbiological epidemiology.

Carbapenem-resistant Enterobacterales (CRE) are a substantial problem in Cape Town. CRE epidemiology is largely unknown and mortality remains high. To describe and characterize the clinical and microbiological epidemiology of CRE within Cape Town hospitals to better inform therapy with regard to current and novel antibiotics, as well as improve antimicrobial stewardship (AMS), and infection prevention and control (IPC). This prospective, multicentre study performed between 1 November 2020 and 30 November 2022, across three public and three private hospitals included hospitalized participants with CRE from clinical cultures. Participant demographics, clinical information and microbiology results were collected and analysed. Ninety percent of participants were from public hospitals. The age distribution ranged from 7 days to 88 years. Notable risk factors for CRE infection included recent exposure to antibiotics, medical devices and surgery. The most prevalent species was Klebsiella pneumoniae. However, a higher proportion of Serratia marcescens compared with previous reports was identified. The detected carbapenemases were blaOXA-48-like (80%) and blaNDM (11%). With the exception of amikacin (63%), tigecycline (65%), colistin (95%) and ceftazidime/avibactam (87%), susceptibility to antibiotics was low. This study identified common risk factors for CRE infection and generated a description of carbapenemase enzymes, species distribution and antibiograms, enabling a better understanding of CRE epidemiology. This provides insights into transmission patterns and resistance determinants of CREs, beneficial to informing data-driven regional patient management, AMS and IPC strategies.

REALISASI PENANGANAN PERUBAHAN IKLIM DI INDONESIA MELALUI IMPLEMENTASI SUSTAINABLE DEVELOPMENT GOALS (SDGs): TUJUAN-13.1.3

This article aims to know the realization of handling climate change in Indonesia through the implementation of Sustainable Development Goals (SDGs): Goals-13.1.3 which focuses on implementing regional disaster management strategies in Indonesia in the 2017-2019 period. The method used in this research is a qualitative method and a literature review of various literature discussing handling climate change in Indonesia. The green theory perspective is used in analyzing the realization of Goals-13.1.3 in Indonesia. The research results show that the realization of handling climate change through the implementation of SDGs Goals-13.1.3 falls into the category of anthropocentric understanding and shallow environmental understanding; as well as placing greater emphasis on environmental sustainability by aligning people's consumption levels without excessive consumption; Regular environmental preservation and implementation of regional disaster management strategies will shape sustainable development in Indonesia

Sustainable Regional Straw Utilization: Collaborative Approaches and Network Optimization

The SDGS repeatedly emphasizes the importance of reducing greenhouse gas emissions such as carbon dioxide. The strategic utilization of straw resources to curtail open-air burning not only epitomizes optimal resource deployment but also constitutes a significant stride in environmental preservation and sustainable development. Globally, the imperative of this challenge is increasingly recognized, prompting nations to enhance straw resource utilization technologies, devise regional management strategies, and extend requisite policy support. Regional straw utilization encapsulates a comprehensive concept involving an array of stakeholders including governments, farmers, corporations, brokers, and rural cooperatives, with each one of these uniquely contributing to a multifaceted network that is influenced by their respective resource utilization intentions. This heterogeneity, coupled with the diverse roles of these stakeholders, renders the identification of the pivotal participants and their specific functions within the intricate network. To navigate this complexity, this study employed text analysis and social network analysis, uncovering 30 robust associative rules within this domain. Our findings elucidate that the stakeholder network in regional straw resource utilization exhibits characteristics akin to the NW small-world network model. The key network entities identified include farmers, corporations, governments, and rural cooperatives. Furthermore, the study systematically categorizes the principal entities and elucidates the dynamics of this multi-stakeholder network. This research delineates four developmental models that are pertinent to regional straw resource utilization, which is a framework that is instrumental in pinpointing the accountable parties and optimizing the overarching benefits derived from these resources. The significance of this research lies not only in showcasing the potential of straw resources for environmental conservation but also in underscoring the importance of collaborative strategies and network optimization in order to achieve sustainable development goals.

Recognition of the Specialties of the Kingdom of Yogyakarta and the Practice of Asymmetric Decentralization in Indonesia

Objective: Yogyakarta Palace is a kingdom that existed before Indonesia became independent. Generally, a country can adopt a monarchy as a system of government that applies nationally. However, uniqueness emerged in recognizing the privileges of the Kingdom of Yogyakarta in Indonesia, which still has the authority to regulate its territory but is also under the auspices of the Republic of Indonesia. In response to this phenomenon, this article was created to answer questions regarding (1) a comparison of monarchical systems in the world, (2) the Validity of the Yogyakarta Palace area as a Special Region in Indonesia, and (3) DIY Government Policy Strategy in maintaining and managing the unique features of Yogyakarta. From the results of this analysis, this study aims to provide alternative recommendations for recognizing the kingdom's authority based on practices that occur in Indonesia.&#x0D;  &#x0D; Method: The study uses normative juridical research methods with a conceptual and statutory approach. The theory of asymmetric decentralization is the analytical tool used to see the chain of validity of the privileges of the Yogyakarta Palace.&#x0D;  &#x0D; Result: The results of the analysis show that the authority of the King of the Yogyakarta Palace to lead the Yogyakarta Special Region Province is a form of asymmetric decentralization practice that is different from the implementation of other monarchical systems in the world.&#x0D;  &#x0D; Conclusion: Based on these findings, it can be concluded that a King's authority to regulate his territory does not have to be within the realm of a monarchical system of government. Recognition of the unique features of the Yogyakarta Palace in Indonesia has proven that a kingdom can exist within the territory of a Republic that practices an asymmetric decentralized system. For this reason, further research is needed that can examine unique regional management strategies to strengthen regional autonomy and fiscal independence.

Assessment of rock glaciers and their water storage in Guokalariju, Tibetan Plateau

Abstract. Rock glaciers are important hydrological reserves in arid and semi-arid regions. Their activity states can indicate the existence of permafrost. To help further explore the development mechanisms of rock glaciers in semi-arid and humid transition regions, this paper provides a detailed rock glacier inventory of the Guokalariju (also known as Goikarla Rigyu) area of the Tibetan Plateau (TP) using a manual visual interpretation of Google Earth Pro remote sensing imagery. We also estimated the water volume equivalent (WVEQ) in the study area for the first time. Approximately 5057 rock glaciers were identified, covering a total area of ∼404.69 km2. Rock glaciers are unevenly distributed within the three sub-regions from west to east, with 80 % of them concentrated in the central region, where climatic and topographic conditions are most favorable. Under the same ground temperature conditions, increases in precipitation are conducive to rock glaciers forming at lower altitudes. Indeed, the lower limit of rock glaciers' mean altitude decreased eastward with increasing precipitation. Estimates of the water storage capacity of rock glaciers obtained by applying different methods varied considerably, but all showed the potential hydrological value of rock glaciers. The possible water storage in the subsurface ice of rock glacier permafrost was 1.32–3.60 km3. The ratio between the amount of subsurface ice stored in rock glaciers and surface ice stored in local glaciers falls within the range of 1:2.32 to 1:1.26, with an average ratio of 1:1.69. In the west region, where the climate is the driest, the water storage capacity of rock glaciers was estimated to be up to twice as large as that of the sub-region's glaciers. Changes in water resources and permafrost stability in the area where rock glaciers occur will have implications for regional water resource management, disaster prevention, and sustainable development strategies.

Spatial-temporal heterogeneity in the influence of landscape patterns on trade-offs/synergies among ecosystem services: a case study of the Loess Plateau of northern Shaanxi.

Exploring the role of landscape patterns in the trade-offs/synergies among ecosystem services (ESs) is helpful for understanding ES generation and transmission processes and is of great significance for multiple ES management. However, few studies have addressed the potential spatial-temporal heterogeneity in the influence of landscape patterns on trade-offs/synergies among ESs. This study assessed the landscape patterns and five typical ESs (water retention (WR), food supply (FS), habitat quality (HQ), soil retention (SR), and landscape aesthetics (LA)) on the Loess Plateau of northern Shaanxi and used the revised trade-off/synergy degree indicator to measure trade-offs/synergies among ESs. The multiscale geographically weighted regression (MGWR) model was constructed to determine the spatial-temporal heterogeneity in the influence of landscape patterns on the trade-offs/synergies. The results showed that (1) from 2000 to 2010, the increase in cultivated land and the decrease in forestland and grassland increased landscape diversity and decreased landscape heterogeneity and fragmentation. During 2010-2020, the change range decreased, the spatial distribution was homogeneous, and the landscape diversity and fragmentation in the northwestern area increased significantly. (2) The supply of the five ESs continued to increase from 2000 to 2020. During 2000-2010, FS-SR, FS-LA and SR-LA were dominated by synergies. From 2010 to 2020, the proportion of trade-off units in all relationships increased, and HQ-FS, HQ-SR and HQ-LA were dominated by trade-offs. (3) Landscape patterns had complex impacts on trade-offs/synergies, and the same landscape variable could have the opposite impact on specific trade-offs/synergies in different periods and areas. The results of this study will inform managers in developing regional sustainable ecosystem management strategies and advocating for more research to address ecological issues from a spatial-temporal perspective.

Influence of fiscal decentralization, fintech, and mineral resources on green productivity of G5 countries

The study explores how regional financial autonomy, financial technologies, and resource management strategies intersect to influence sustainable practices and environmental efficiency in G5 economies. The yearly data from 1990 to 2021 has been taken for Canada, Japan, Germany, the United Kingdom, and the United States of America. Empirical analysis of the Cross-sectional Augmented Distributed Lag (CS-ARDL) modeling framework has been performed after a preliminary investigation regarding the variables' cross-sectional dependence, slope heterogeneity, and unit root properties. The outcomes of long-run estimation reveal the positive impact of fintech and revenue decentralization, while mineral resources and expenditure decentralization negatively influence green productivity. Similar results are observed in the short-run; however, their marginal effects are relatively lower. Moreover, the error correction term is negative and significant, indicating an 81.4% speed of adjustment annually to restore the obtained model's equilibrium system. These estimates are validated by the Augmented Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG) estimators. A bi-directional causality of fintech and revenue decentralization is observed, which offers valuable policy implications.

Estimating Fine Fuel Load Using Sentinel-2A Imagery and Machine Learning: A Case Study in the Mountainous Forests of Changsha, China

Fine fuel load (FFL) is a crucial variable influencing the occurrence of wildfire. Accurate knowledge of the distribution of FFL in mountainous forests is essential for ongoing wildfire risk management and the stability of mountain ecosystems. Traditional methods of estimating forest fuel load typically involve ground surveys combined with remote sensing, which can be costly and inefficient. Therefore, low-cost, large-scale FFL estimation remains challenging. In this study, Sentinel-2A satellite imagery from the Changsha forest region was used as the data source. Firstly, different feature variables were constructed based on false-color (B843), true-color (B432), four-band (B8432) combinations, and the Normalized Difference Water Index (NDWI). Subsequently, a machine learning approach based on random convolution was employed to estimate FFL. This study also included accuracy assessments of the estimation results and the creation of FFL maps for the study area. The results showed that the FFL estimation based on the B8432 band combination achieved the highest accuracy, with RMSE and R2 values of 5.847 t·hm−2 and 0.656, respectively. FFL estimation results based on false-color imagery followed, with true-color imagery and NDWI index-based estimation results exhibiting lower accuracy. This study offers critical FFL insights using random convolution techniques applied to Sentinel-2A imagery, enhancing the ability to monitor and manage forest fuel conditions effectively, thereby facilitating more informed regional wildfire risk management strategies.

Effects of land use/cover changes on soil organic carbon stocks in Qinghai-Tibet plateau: A comparative analysis of different ecological functional areas based on machine learning methods and soil carbon pool data

Understanding the process of land use/cover changes (LUCC) can provide experience on the enhancement of soil organic carbon (SOC) stocks and carbon sequestration potential for different areas. This study is uniquely to divide different ecological functional areas, and originally combine the machine learning method and soil carbon pool dataset for regional comparative analysis, to compare and quantitatively analyze the drivers of LUCC and the changes in SOC stocks effected by LUCC over 30 years. The results show that topography and climate changes are the main drivers affecting LUCC in four natural areas, while soil factors and population changes do not cause significant effects. The total SOC stocks in Qinghai was increased by 71.18 Tg C and 107.19 Tg C in 0–30 cm and 0–300 cm layers, respectively, and the highest SOC stocks within 0–300 cm were in Pastoral area. Desert and Gobi area had the lowest SOC stocks in both 0–30 cm and 0–300 cm layers. SOC stocks increased in both 0–30 cm and 0–300 cm layers only in Sanjiangyuan Natural Reserve, while the Desert and Gobi area showed a decrease in both over 30 years. This study emphasizes the significant impact of grassland changes on SOC stocks, indicating the importance of considering these changes in land management and ecological protection policies. The initial and original SOC stocks of pre-LUCC may influence the SOC stocks in post-LUCC. The response of SOC stocks changes to LUCC was varies in different areas. The heterogeneity of different ecological functional areas is affected by multiple factors and SOC stocks will become more complex among these areas in the future. These findings contribute to the development of ecological protection policies and the enhancement of regional land management strategies.

Identifying eco-functional zones on the Chinese Loess Plateau using ecosystem service bundles

Optimizing the function of ecosystem services (ESs) is vital for implementing regional ecological management strategies. In this study, we used multi-source data and integrated modelling methods to assess the spatiotemporal variations in eight typical ESs on the Chinese Loess Plateau from 2000 to 2015, including grain production, raw material provision, water conservation, carbon storage service, soil conservation, oxygen production, recreation, and net primary productivity (NPP) services. Then, we divided the ecosystem service bundles (ESBs) according to relationships among the eight ESs, obtaining four types of eco-functional areas at the county (city or banner or district) level based on the spatial clustering of similarities in different ES types. We also identified and assessed the contributions of influencing factors to these eco-functional areas using principal component analysis (PCA) across spatiotemporal scales. We found that the spatiotemporal variations in different ESs were noticeable, with an overall increase in grain production and soil conservation services, no significant change in carbon storage service, and overall decreases in raw material provision, water conservation, oxygen production, recreation, and NPP services. From 2000 to 2015, the number of significant synergistic ES pairs decreased, while that of significant trade-off pairs increased. To the changes of ESBs in the eco-functional areas, the results indicated that the indirect loss of these ESs from forest and grassland due to urban expansion should be reduced in ecological development area (ESB 2) and multi ecological functional area (ESB 3). Meanwhile, crop planting structures and planting densities should be adjusted to reduce ES trade-offs associated with water conservation service in grain-producing area (ESB 4). Lastly, ESB-based eco-functional zoning can be used to improve ecological restoration management strategies and optimize ecological compensation schemes in ecologically fragile area (ESB 1).

관광 빅데이터를 활용한 지역관광 소비지출액 결정요인에 대한 연구

This study examined changes in domestic regional tourism occurring after COVID-19, with a particular focus on the Gyeongnam region which has been recognized as a hub for marine leisure and industrial tourism. By doing so, it tried to provide empirical analysis results applicable to the formulation of regional tourism management and marketing strategies by using a non-parametric model. To overcome situations where the linear models commonly used in big data analysis are difficult to apply and to diversify the methodological aspects of big data analysis, this study proposed an additive model to represent nonlinear relationships. Key study procedures are as follows. Firstly, 22 cities in the Gyeongnam region were classified into four clusters based on a cluster analysis of visitor increase and decrease patterns. Subsequently, using an additive model for non-Euclidean variables, the impact of age group-specific visitor ratios and navigation search type ratios, extracted from big data on tourism expenditure by industry, in each of the four clusters were examined. Notable findings include a recent slight increase in the proportion of visitors in their 50s in the Gyeongnam region compared to pre-COVID-19. In Cluster 3, where the most significant differences in tourism patterns pre- and post-COVID-19 were observed, sectors such as accommodation and shopping were significantly related to tourism expenditure. Furthermore, except for one cluster, those aged 50 or older had the most influence on expenditure in most regions. Based on these results, the study suggests that designing models considering the nonlinear characteristics of diverse data can be valuable in big data analysis. Along with this, the study proposes the necessity of formulating big data-based strategies in regional tourism policies and practical fields, taking into account the insights derived from the analysis.

Yield and growth rates of pastures grown in the Bay of Plenty region over 35 years

Bay of Plenty district, and particularly the Rotorua Lakes area, has a diverse terrain and soil types which influence pasture production. Regular measurement of pasture production enables short term decision making on a farm scale and is invaluable for catchment,district and regional long term management strategies. Thomas (Tom) M. Gee, was a retired farmer with more than 18 years of field trial experience with MAF Field Research Division. He collected data from more than 30 farms after he retired. Data from other sites in the district were collected in the early 1970s by MAF technicians stationed in Whakatane and Tauranga and later by AgResearch staff and a farm consultant based in Rotorua. Tom Gee’s mission was to use these measurements to provide farmers with rates of growth (ROG) data to inform them about their farm. The Gee farm (Fairbank) of 200 ha was originally leased from Ngati Whakaue Tribal Lands in 1916 and then purchased before much of it was sold back to the Incorporation in 1970. Tom retired in 1989 but kept meticulously recording pasture growth rates on different farms up to ~ 2007. Some field notes were lost, but datasets with gaps are still useful to assist monthly growth rates calculations. His valuable and extensive (almost 25 years) on farm field records have been retrieved, compiled, assembled, and digitised, to be saved electronically, and entered into the AgYields National Database hosted at Lincoln University. Part of this legacy dataset has been summarised and dry matter yields and growth rates calculated, consistent withprevious methods, to provide a quantified description of mean monthly pasture growth rates across the Bay of Plenty region, in New Zealand.

Climate change and collapsing thermal niches of desert reptiles and amphibians: Assisted migration and acclimation rescue from extirpation

Recent climate change should result in expansion of species to northern or high elevation range margins, and contraction at southern and low elevation margins in the northern hemisphere, because of local extirpations or range shifts or both. We combined museum occurrence records from both the continental U.S. and Mexico with a new eco-physiological model of extinction developed for lizard families of the world to predict the distributions of 30 desert-endemic reptile and amphibian species under climate change scenarios. The model predicts that 38 % of local populations will go extinct in the next 50 years, across all 30 species. However, extinctions may be attenuated in forested sites and by the presence of montane environments in contemporary ranges. Of the 30 species, three were at very high risk of extinction as a result of their thermal limits being exceeded, which illustrates the predictive value of ecophysiological modeling approaches for conservation studies. In tandem with global strategies of limiting CO2 emissions, we propose urgent regional management strategies for existing and new reserves that are targeted at three species: Barred Tiger Salamander (Ambystomatidae: Ambystoma mavortium stebbinsi), Desert Short-horned Lizard (Phrynosomatidae: Phrynosoma ornatissimum), and Morafka's Desert Tortoise (Testudinidae: Gopherus morafkai), which face a high risk of extinction by 2070. These strategies focus on assisted migration and preservation within climatic refugia, such as high-elevation and forested habitats. We forecast where new reserves should be established by merging our model of extinction risk with gap analysis. We also highlight that acclimation (i.e., phenotypic plasticity) could ameliorate risk of extinction but is rarely included in ecophysiological models. We use Ambystoma salamanders to show how acclimation can be incorporated into such models of extinction risk.

Formulation Of Regional Management Singbebas

The formulation of regional management strategies plays a pivotal role in the sustainable development and growth of a region. This abstract introduces the concept of "Singbebas Regional Management" as a framework for the effective governance and development of a specific region. It outlines the key components and strategies involved in the formulation of Singbebas Regional Management, focusing on regional autonomy, economic development, and social well-being. This abstract provides a brief overview of the comprehensive study that delves into the principles and practices of Singbebas Regional Management and its potential implications for regional development.

A high-resolution energy use efficiency assessment of China’s staple food crop production and associated improvement potential

Improving production efficiency of existing agricultural systems is key to promoting sustainable agricultural production. Energy use efficiency in crop production is a key and widely applied index used to measure agricultural production efficiency. Understanding the current status of energy use efficiency in crop production at high spatial resolutions is requisite for developing energy-saving and efficient crop production optimization strategies. This study provides a first attempt at systematically evaluating the county-level energy use efficiency status of China’s three staple food crops (i.e., wheat, maize, and rice) and their associated improvement potential based on the Energy Return on Investment (EROI) method. Results show that average EROI values of wheat, maize, and rice production (i.e., 0.94, 1.1, and 1.3, respectively) substantiate low energy use efficiency under a high improvement potential. Moreover, the energy use efficiency of staple food crop production exhibits considerable spatial heterogeneity. The top 25% counties with the highest EROI values are mainly concentrated in wheat-producing areas of the North China Plain, maize-producing areas of northeastern China and Inner Mongolia, and rice-producing areas of the central Yangtze River region. Crop yields and agricultural machinery inputs are the main EROI driving factors. Furthermore, scenario analysis shows that regional EROI gaps in wheat, maize, and rice production could be narrowed by increasing yields and improving agricultural machinery operation efficiency. Overall, this study provides an improved understanding of the current energy use efficiency status of staple food crop production in China. Recommended solutions are also proposed to improve the EROI of staple food crops. This provides scientific support in formulating regional optimal management strategies for crop production and guidance for farmers to conduct more efficient production practices. Additionally, our framework can also be adopted and built upon in regions throughout the world that experience similar low energy use efficiency conditions in agricultural production.

Characterization of emamectin benzoate resistance in the diamondback moth, Plutella xylostella (Lepidoptera: Plutellidae).

Plutella xylostella (L.) is a destructive pest of cruciferous crops worldwide that has evolved resistance to many insecticides. Here we examined the mode of inheritance, cross-resistance profile, and potential mechanisms of emamectin benzoate resistance in a field-derived strain of P. xylostella from Japan. A field-collected population of P. xylostella, was found to exhibit strong (> 150-fold) resistance to emamectin benzoate in insecticide bioassays when compared with a laboratory susceptible strain. Genetic analysis showed that resistance is inherited as an autosomal, recessive trait, and is conferred by a single or a few closely linked loci. The emamectin benzoate resistant strain also exhibited resistance to abamectin, lepimectin, chlorantraniliprole, lufenuron, spinetoram, indoxacarb, fipronil, dieldrin, endosulfan and lambda-cyhalothrin, demonstrating a remarkable multi-resistance profile. Insecticide bioassays employing inhibitors of detoxification enzymes revealed that piperonyl butoxide (PBO) increased the toxicity of emamectin benzoate in the resistant strain by ten-fold indicating the potential involvement of cytochrome P450 monooxygenases in avermectin resistance. Furthermore, cloning and sequencing of the primary receptor of avermectins, the GluCl channel, revealed the absence of target-site mutations in the resistant strain. Our data on the mode of inheritance and mechanisms of resistance to emamectin benzoate in a P. xylostella strain from Japan provide a foundation for the development of regional resistance management strategies. However, the high levels of phenotypic resistance in this strain to a diverse range of other insecticide classes available for control illustrate the challenges associated with the sustainable control of this important pest. © 2023 Society of Chemical Industry.