Greenhouse Gas Emissions of Tourism-Based Leisure Farms in Taiwan

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

In Taiwan the importance of agriculture is decreasing, compared to other industries. This change worsened in 2002 after Taiwan joined the World Trade Organization (WTO). Due to the increase in National Income and the implementation of the five-day workweek, the tourist population is growing. Beginning in 1989, the Council of Agriculture of Taiwan selected 31 rural areas in which to develop leisure farms for the purpose of creating and promoting agricultural tourism and to help sustain agriculture. This is intended to be achieved by utilizing their natural beauty, by promoting awareness of their ecology and by understanding their environmental resources. Agricultural tourism could generate income, create jobs and encourage retail growth. The purpose of this paper is: (1) to better understand the development of leisure farms in Taiwan, (2) to describe leisure farm visitors in terms of their demographic and socio-economic characteristics and knowledge about leisure farms, (3) to profile the leisure farm visitors by the number of visits, (4) to measure levels of visitor satisfactions with leisure farm performance, and (5) to identify the main factors of products and services for the leisure farms. The results clearly identify the characteristics of leisure farm tourists, demonstrate the problems of insufficient knowledge about agricultural tourism and leisure farming, and conclude with six important factors for product and service strategies.

Leisure agricultural tourism has become a new way for people in modern society to alleviate the pressure in daily life in holidays. Meanwhile, the investment in the construction of leisure farms is increasing rapidly. In terms of farm management, a differentiated management strategy can make projects on the development and construction of leisure farms stand out, and thus brings huge benefits and value. The Leisure Farm Customer Journey Map (CJM) is an effective strategic management tool for farm operators to understand the satisfaction degree of tourists. In this study, through many visits to leisure farms in Taiwan, 20 representative leisure farms are selected as research samples for case study, of which the analysis of touch points is conducted in order to find out visitors’ preference. In addition, through questionnaires, we try to find out which factors are the core motivations for tourists to visit leisure farms. This study hopes to help leisure farm operators understand the importance of the planning and design of these touch points for tourists’ experience through combining touch points in service design with tourists’ core motivations, and aims at optimizing the resource allocation of leisure farms and promoting the sustainable operation of leisure farms.

This study examines the effect of weather on outdoor recreation and specifically leisure farms in Taiwan. We find that temperature has a complex effect on visits, revenues, and occupancy rates. Cool temperatures are the least desirable, very cold temperatures and warm temperatures are the most beneficial, and hot temperatures are less beneficial. Sites designed for winter activities benefit the most from cold temperatures whereas sites designed for walking and boating do best in warm temperatures. Global warming is likely to harm the sites suited for winter activities but should prolong the outdoor season for most leisure farms in Taiwan. But leisure farms may want to find ways to cope with hot temperatures.

In the context of global warming, the Wuhan Urban Agglomeration is actively responding to China’s carbon peak and carbon neutrality goals and striving to achieve a reduction in carbon sources and an increase in carbon sinks. Therefore, it is critical to investigate carbon emissions from land use. This study uses the carbon emission coefficient method to calculate carbon emissions from land use in the Wuhan Urban Agglomeration, analyzes its temporal and spatial changes and differences in urban structure, and couples with the Markov–PLUS model to simulate and predict the carbon emissions of four scenarios of land use in 2035. The research found the following: (1) during the Wuhan “1+8” City Circle stage, carbon sources and emissions increased steadily, with average annual growth rates of 1.92% and 1.99%, respectively. Carbon sinks remained stable and then decreased, with an average annual growth rate of −0.46%. (2) During the Wuhan Metropolitan Area stage—except for 2020 and 2021, which were affected by COVID-19—carbon sources, sinks, and emissions continued to grow in general, and the average annual growth rates increased to 4.46%, 1.58%, and 4.51%, respectively. (3) In terms of urban structure differences, Wuhan is a high-carbon optimization zone; Xianning, Huangshi, and Huanggang are ecological protection zones; other cities, such as Ezhou, Xiaogan, and Xiantao are comprehensive optimization zones; and there is no low-carbon development zone. (4) The multi-scenario simulation results show that carbon sources and emissions are the highest under the economic development scenario, with values of 100.2952 and 9858.83 million tons, respectively, followed by cropland protection, natural development, and low-carbon development scenarios. Under low-carbon development, carbon sinks were the highest, with values of 1.9709 million tons, followed by natural development, economic development, and cropland protection scenarios. The research results are conducive to the formulation of carbon peak and neutrality goals as well as low-carbon development plans for the Wuhan Urban Agglomeration.

Combining the principles of systemicity, cyclicity, and diversity in agroecosystem theory, we constructed an analytical framework for the ecological co-culture model (rice-fish + livestock + fruit mix), and attempted to reveal its synergistic mechanism and evolutionary pathway in low-carbon agriculture by bibliometric methods. The COVID-19 pandemic, which emerged in 2019, has significantly impacted agricultural production and food security, emphasizing the urgent need for high-quality, sustainable agricultural development. Although agriculture is not the largest contributor to energy use or carbon emissions, its sustainable development can reduce global energy dependency, accelerate the energy transition, and contribute to achieving carbon neutrality. Moreover, a green, low-carbon energy structure is crucial for supporting sustainable agricultural practices. This study systematically reviews current research on ecological co-culture models in low-carbon agriculture in China, offering theoretical foundations for future research and strategic insights for promoting sustainable agricultural development. Using the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) Core Collection for data retrieval and employing CiteSpace software for bibliometric analysis, the study reveals the following key findings: (1) Research is highly concentrated, with approximately 52% of studies focused on the “rice-fish symbiosis” model, while research on the “fruit trees + poultry ecological co-culture” model remains relatively sparse. Although approximately one-third of the literature addresses “low-carbon agriculture,” only 2% of the articles explore the relationship between “ecological co-culture” and “low-carbon agriculture,” with approximately 8% covering “vertical cultivation.” (2) Both domestic and international publications primarily focus on ecology, life sciences, agriculture, and aquaculture, with minimal representation in geographical journals. (3) The CiteSpace analysis of research publications between 2008 and 2023 found that China Agricultural University and the Institute of Geographic Sciences and Natural Resources Research of the Chinese Academy of Sciences were in a leading position in the field of agriculture and life sciences. (4) There are 255 principal authors with 319 cooperative connections, indicating that there are extensive collaboration networks among scholars and significant potential for advancing research on low-carbon agriculture and ecological co-culture models in China. (5) The most prominent keywords from 2014 to 2023 include “rice,” “rice-fish symbiosis,” and “ecological symbiosis.” Additional keywords such as “rural revitalization” and “low-carbon agricultural technology” have attracted considerable attention, with a peak intensity value of 4.8. These results reflect the evolving focus of research on low-carbon agriculture in the post-pandemic era. Over time, research priorities have shifted from vertical farming and paddy-field fish farming to food security under peak carbon and green finance, while international studies have increasingly emphasized on genetic diversity. Through a quantitative review of domestic and international literature, this paper addresses a critical gap in the study of low-carbon ecological co-culture. In conclusion, our findings underscore that research on ecological co-culture models within low-carbon agriculture remains a critical area of focus both domestically and internationally. Continued exploration in this field will not only improve sustainable agriculture but also provide valuable insights for future research directions.

Leisure farms in Taiwan are currently undergoing a fast development. The utilization of distinctive strategies to create successful operational competitiveness is becoming the guiding policy of enterprises for their future development. This study adopts the value chain perspective to develop criteria for different dimensions and to develop a strategic hierarchical structure by using the fuzzy Delphi method. Through the FANP (Fuzzy Analytic Network Process) method, this study discovers the critical factors influencing the competitive advantages of leisure farms in Taiwan: (1) the uniqueness of the landscape and ecological resources, (2) the richness of agricultural resources, (3) the attractiveness of the landscape and ecological resources, (4) service quality, (5) the convenience of the accommodation, (6) the provision of education and guiding services, and the like. Finally, according to the research results of the study, the authors make suggestions on the corresponding developmental strategies of leisure farms, including (1) creating the characteristics of a leisure farm through the development and utilization of the farm’s internal and surrounding environmental resources and (2) perceiving the tourists’ needs and improving the service quality. With the suggestions made and the reference data concluded in this study, the authors expect to enhance effectively the current competitive advantages of leisure farms.  

China is the biggest emitter of greenhouse gases (GHGs) in the world, and agricultural GHG emission accounts for nearly a fifth of the total emission in China. To understand the carbon absorption and emission characteristics of agricultural production systems in those arid oasis areas, a typical representative city in northwestern China, Zhangye City, was selected for study.The emission factor method was used to analyze and calculate the characteristics of changing carbon emission dynamics in the whole agricultural production system in Zhangye city region (38,592 km2) from 2010 to 2021.The results revealed that carbon emissions during agricultural planting mainly come from fertilizers, which account for the highest proportion (47.9%) of total carbon emissions in agricultural planting. Animal enteric fermentation emissions from local livestock farming are the main contributor (86%) to GHG emissions. The annual average carbon absorption intensity is 4.4 t C-eq ha−1 for crop and 2.6 t C-eq ha−1 for the agricultural production system. The ratio of total carbon emissions from agricultural production to carbon sequestration of crops is 1:1.7. We find that the total carbon sequestration slightly exceeds its total carbon emissions in the study region, with an annual average of 41% for its sustainable development index. Carbon emissions of the agricultural production system in this oasis area are mainly driven by the livestock industry, mostly CH4 emissions from cattle raising.Reducing the local carbon emissions from the livestock industry, typically the cattle raising, will play a crucial role in reducing carbon emissions from this local agricultural production system and maintaining its net positive carbon balance.

Global warming has become one of the major threats to the security of human survival, security, and sustainable development. Agricultural production has been widely suspected as one of the main sources of anthropogenic carbon emissions. Analyzing the changing characteristics and influencing factors of agricultural carbon emissions is of great significance for the mitigation of global climate change and the sustainable development in agriculture. Taking China, a large agricultural country, as an example, this study used the empirical model to quantify carbon emissions from agricultural inputs from 1991 to 2019, and analyzed the driving factors using ridge regression. We found that agricultural carbon emissions in China have been on the rise in the past 30 years, but at a markedly slower pace. From 2008 to 2019, the average annual growth rate of agricultural carbon emissions was 1.47%, down significantly from 2.92% between 1991 and 2007. The carbon emissions per unit of planting area showed an overall increasing trend, which grew from 179.35 t ce/km2 to 246.26 t ce/km2, with an average annual growth rate of 1.13%. The carbon emissions per unit of agricultural output mainly showed a decreasing trend, which decreased from 0.52 kg ce/CNY to 0.06 kg ce/CNY, with an average annual rate of change of −7.42%. China’s agricultural carbon emissions were closely related to macro-policies. Fertilizer inputs, agricultural industry structure, and energy use intensity were significantly positively correlated with carbon emission intensity. The degree of urban feedback to rural areas, public investment in agriculture, and large-scale planting were significantly negatively correlated with carbon emission intensity, but the impacts of these factors had a “lag effect”. In order to reduce carbon emissions from agriculture and promote development in green agriculture, we suggest that the government should further increase the degree of urban feedback to rural and public investment in the agricultural sector. In addition, large-scale agricultural production should be encouraged to increase resource efficiency and reduce carbon emissions.

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Promoting low-carbon agriculture is vital for climate action and food security. State farms serve as crucial agricultural production bases in China and are essential in reducing China’s carbon emissions and boosting emission efficiency. This study calculates the carbon emissions of state farms across 29 Chinese provinces using the IPCC method from 2010 to 2022. It also evaluates emission efficiency with the Super-Slack-Based Measure (Super-SBM model) and analyzes influencing factors using the Logarithmic Mean Divisia Index (LMDI) method. The findings suggest that the three largest carbon sources are rice planting, chemical fertilizers, and land tillage. Secondly, agricultural carbon emissions in state farms initially surge, stabilize with fluctuations, and ultimately decline, with higher emissions observed in northern and eastern China. Thirdly, the rise of agricultural carbon emission efficiency is driven primarily by technological progress. Lastly, economic development and industry structure promote agricultural carbon emissions, while production efficiency and labor scale reduce them. To reduce carbon emissions from state farms in China and improve agricultural carbon emission efficiency, the following measures can be taken: (1) Improve agricultural production efficiency and reduce carbon emissions in all links; (2) Optimize the agricultural industrial structure and promote the coordinated development of agriculture; (3) Reduce the agricultural labor scale and promote the specialization, professionalization, and high-quality development of agricultural labor; (4) Accelerate agricultural green technology innovation and guide the green transformation of state farms. This study enriches the theoretical foundation of low-carbon agriculture and develops a framework for assessing carbon emissions in Chinese state farms, offering guidance for future research and policy development in sustainable agriculture.

The livestock industry is a pillar industry of the rural economy and an important industry of the national economy in Yunnan Province, so it is important to study the spatial and temporal characteristics of carbon emissions from the livestock industry in Yunnan Province for the development of a modern, lowcarbon and recycling livestock industry. This study draws on provincial greenhouse gas emission factors to calculate the carbon dioxide equivalents generated by enteric fermentation and manure management of cattle, sheep, pigs and poultry in each state and city of Yunnan Province. The results show that: (1) the total carbon emissions from the livestock sector in Yunnan Province decreased from 25, 643, 900 t in 2008 to 24, 758, 200 t in 2018, with an average annual carbon emission of 30, 534, 500 t and an average annual growth rate of The average annual growth rate was 0.35%, showing a characteristic of “rising first then falling”. (2) In terms of spatial and temporal evolution, the layout of the low and high livestock carbon emission areas in Yunnan is stable, while the medium and high livestock carbon emission areas fluctuate frequently and the spatial and temporal differences in carbon emissions are obvious. Finally, based on the conclusions, targeted countermeasure suggestions are put forward.

How to obtain the useful business intelligence and enhance their competitiveness during the competitive environment had known as an important issue to be addressed for all enterprises. In this study, we proposed the architecture based on Kano’s two dimension model and value expansion/prediction model to mine the hidden business intelligence and enhance the enterprise’s competitiveness. The hidden information including the important benefits and products/services attributes can be then obtained by using value expansion model; and the possible relationships among values, benefits and products/services attributes can also be modeled by using value prediction model. Finally, an illustrative example owing to the leisure farming in Taiwan is then taken to demonstrate the feasibility and rationality of the proposed architecture.