Dynamic evolution analysis of recreational fisheries development in China

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. Fisheries Management and Ecology published by John Wiley & Sons Ltd. 1Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture and Rural Affairs; Shandong Provincial Key Laboratory of Fishery Resources and Ecological Environment, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China 2Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China 3School of Biosciences, The University of Melbourne, Parkville, Vic., Australia 4Periodical Agency, Shanghai University of Finance and Economics, Shanghai, China

there is a serious imbalance of development of recreational fisheries between regions.
Specifically, the combined economic value of recreational fisheries in the main provinces of Shandong, Hubei and Guangdong accounted for 53.4% of recreational value for the whole country, whereas the combined contribution for the bottom 20 of the 31 provinces in the country together accounted for only 10.1%. Analysis of temporal variation at four points in time by kernel density estimation revealed that the development of recreational fisheries exhibited a polarised tendency both among the provinces within the eastern, central and western regions and among the 31 provinces of China. Based on the results of the Theil index decomposition, the overall differences in China's recreational fisheries economy mostly came from differences within each region, which accounted for over 90% of the overall difference. This study provided a means to understand and visualise how key dimensions of recreational fisheries development vary within each region and within the 31 provinces of China, and provides a basis for making short-term and long-term policies aimed at promoting coordinated and sustainable development of recreational fisheries in China.

K E Y W O R D S
Gini coefficient, Kernel density estimate, regional difference, Theil index

| INTRODUC TI ON
Recreational fishing is defined as fishing for aquatic animals (mainly fish) that do not constitute the individual's primary resource to meet basic nutritional needs and are not generally sold or otherwise traded on export, domestic or black markets (FAO, 2012).
Recreational fishing occurs around the globe in inland, estuarine and marine waters, spanning developed and increasingly, developing countries, involving high numbers of participants and making a considerable economic contribution to national economies (FAO, 2012;Cooke et al., 2018;Pita et al., 2018). Approximately, one tenth of the population across all countries engages regularly in recreational fishing, providing many social, economic and ecological benefits to society and harvesting millions of fish on a global scale (Aas et al., 2008;Arlinghaus et al., 2015). In China, recreational fishing is an activity with high socioeconomic importance, While not large in terms of tonnage compared with commercial capture fisheries, recreational fisheries have substantial economic impacts through value-added activities (Freire et al., 2020).
In addition to contributing to economies and general well-being, recreational fisheries also play an important role in aquatic conservation (FAO, 2018;Brownscombe et al., 2019). Its sustainably managed expansion offers an effective way for providing more employment to local fishers seeking to transfer their skills and utilise experience gained from less lucrative commercial fishing, and who remain demographically dependent upon aquatic resources for their livelihoods. In China, surveys of sea anglers in Shandong Province found that the ratio of economic value directly from recreational fishing, that is, value of fish caught, to allied consumption (boat charter; purchase of angling equipment) was 1:53, and per sea angling location promotes potential job transfer opportunities for more than 27 fishers (Yu, 2016). Therefore, recreational fishing in China is an important leisure activity that contributes economic, ecological and social benefits to the Chinese society.
Recreational fisheries in China have been developing rapidly, especially over the past decade, but this rapid overall development has been accompanied by widening discrepancies in its extent among regions (Fisheries Bureau of the Ministry of Agriculture & Rural Affairs, 2018). Nevertheless, to date, the dynamic evolution (see Nowak (2006)) of recreational fisheries in China remains unknown, hampering progress in promoting a coordinated, evidence-based approach to policies for developing recreational fisheries to reach their potential. To address this lack of quantitative information, this paper provides a comprehensive analysis of the dynamic spatial distribution and evolving trends in recreational fisheries among China's provinces to enable a broader understanding of recreational fisheries development. It is anticipated that this will provide a scientific reference for promoting coordinated and sustainable development of recreational fisheries throughout China.

| Indicators and data sources
Total economic value and per capita economic value of recreational fisheries were selected as indicators to investigate changing trends and regional disparities among China's provinces. No data are available on the number/weight of fish caught so total economic value is used here to assess the progress of the fishery. According to China's official statistics, economic value of recreational fisheries refers to the economic value of the fishery-related tourism service industry in this study. A kernel density estimation model was constructed to quantify the dynamic evolution of recreational fisheries development in China. Then, a series of techniques, including the Gini coefficient and Theil index decomposition, were applied to illustrate the relative differences among provinces. All recreational fisheries data were acquired from the China Fishery Statistical Yearbook. Data on human population size were sourced from the China Statistical Yearbook.
To illustrate the provincial differences and regional disparities in

| Kernel density estimate
Kernel density estimation (KDE) is a non-parametric method used in probability theory to estimate a probability density function (Pennino et al., 2017;Wang et al., 2018). In this paper, The KDE model was used to study the temporal trend of the recreational fisheries in China (Edge et al., 2017). In a random sample x 1 , x 2 , …, x n , the KDE is given by This reveals a dynamic convergence characteristic, showing that the decomposition gap of the studied indicator in the region narrows, and vice versa.
As Silverman (1986) pointed out, in the case of large samples, usually the non-parametric estimation is not sensitive to the choice of kernel, but the choice of bandwidth h has greater influence on the estimator. In this study, a normal kernel with bandwidth chosen by Silverman's rule (option "nrd0" in the density function in R) was applied to the matrix entries (Edge et al., 2017). "nrd0" is the standard bandwidth selector for symmetric kernels with constant parametric starts.

| Gini coefficient
The Gini coefficient is an indicator widely used by economists and is derived from the Lorentz curve (Drezner et al., 2009;Liu et al., 2017). The Gini coefficient measures the inequality among values of a frequency distribution. The larger the value, the larger the disparity among regions, and vice versa. The formula is: where Gini represents the Gini coefficient. n represents the total number of study areas (which equals 31 provinces in this paper). y i , y j (i = 1, 2, …, n) represents the selected indictor (which refers to the total economic value of recreational fisheries or per capita economic value of recreational fisheries) of province i or province j. u = 1∕n ∑ n i = 1 y i represents the national average value of selected indictor.

| The Theil index and its decomposition method
The Theil index measures regional differences (Theil, 1967;Bhattacharya & Sinha, 2016;Yu & Zhou, 2018), where higher values of the index refer to larger disparities. One advantage of the Theil index is that the total regional disparity can be decomposed into inter-regional disparity and intra-regional disparity; hence, it provides a better representation of imbalance in heterogeneous regional structures. The inter-regional index measures the disparity between different regions, whereas the intra-regional index is a weighted average of provincial disparities within each region. Within this context, the overall regional disparities of the recreational fisheries economy in China can be decomposed into the within eastern region differences, within central region differences, within western region differences and between-regions differences.
Taking the province as a basic spatial unit, the Theil index indicating national overall difference is: where I theil represents the Theil index, I (inter) represents disparities among the eastern, central and western regions, I i(intra) represents the disparities among provinces within the region i (which refers to eastern, central, or western regions), m represents the number of regions which equals to 3 in this study, and ∑ m i = 1 ( Yi∕Y ) I i (intra) represents the weighted average value of the internal differences of the three regions.
where i represents the studied region (i = 1, 2, 3 for the eastern, central and western regions, respectively); j represents the provinces in region i; Y i is the value of studied indicator (total economic value of recreational fisheries or per capita economic value of recreational fisheries) in region i; Y is the total value of the studied indicator in China. X i is the total population in i region; and X is the total population of the whole country; y j is the value of studied indicator in province j; x j is the human population size in province j.

| General developmental trends in economic value
China's recreational fisheries experienced rapid development be- Although the economic value of recreational fisheries in China grew sharply between 2003 and 2018, differences in regional development were evident (Table 1)

| Regional disparities among provinces in China's recreational fisheries development
The ily arose from the differences within each region, which accounted for more than 90% of the overall difference.
In terms of intra-regional differences in economic value of recreational fisheries, the within-region difference of the eastern region

| DISCUSS ION
This study provides a nationwide assessment of evolution of recreational fisheries in China. Participation in recreational fisheries has expanded rapidly in many developing countries in accordance with the expansion of the middle class (Gupta et al., 2015;Freire et al., 2016;FAO, 2017). However, the phenomenon of imbalanced development of regional recreational fisheries is of concern and is reflected in the kernel Recreational fisheries are a relevant and valuable sector of fisheries and need better governance and management (Arlinghaus et al., 2019;Potts et al., 2020).
Individuals and governments around the world value the conservation and sustainable use of recreational fisheries (Hughes, 2015). Many industrialised countries have already developed Countries that experience sustained economic growth and rising levels of income, such as China, have typically shown substantial growth in demand for leisure and recreational activities, and in demand for the resources and goods needed to satisfy these demands.
Overall, recreational fisheries development in China is still at the initial stage, the economic contribution of recreational fisheries to total fisheries value is still relatively small at less than 5%. A great potential is yet to be tapped in terms of both the depth of the indus-

Strengthening brand building and improving facilities construction.
Increasing brand publicity using emerging media such as social media and hosting fishery festivals for fishing culture will expand the influence of recreational fisheries. In addition, deep tapping the local cultural resources and increasing the heterogeneity of recreational fisheries products and services will have positive outcomes. In addition, the infrastructure in many fishing ports and fishing villages of China is too poor to provide services. In addition, talents among the recreational fisheries industry sector related to management, operation, marketing, scientific research and service are seriously lacking. It is of vital importance to improve the professional qualities of recreational fisheries sector employees and cultivate a host of recreational fisheries leaders and management talents, thereby boosting the rapid and sustainable development of the recreational fisheries.

| CON CLUS ION
The Chinese government has attached great importance to recreational fisheries development, especially in the past ten years.
However, limited research has been conducted on the quantification of regional differences in the development of China's recreational fisheries. Within this context, this study used a series of techniques, including Kernel density estimate, Gini coefficient and Theil index to illustrate the provincial differences and regional dis- . We also thank two anonymous reviewers for constructive comments that improved this manuscript.