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Journal of Resources and Ecology >

2019 , Vol. 10 >Issue 4: 353 - 361

DOI: https://doi.org/10.5814/j.issn.1674-764X.2019.04.002

Water and Soil Resources

Study of the Population Carrying Capacity of Water and Land in Hainan Province

  • HAO Qing , 1, 2, 3, 4 ,
  • FENG Zhiming 1, 3, 4 ,
  • YANG Yanzhao 1, 3, 4 ,
  • YOU Zhen 1 ,
  • CHENG Ping 2 ,
  • DENG Ling , 2, *
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  • 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2. Chinese Academy of Natural Resource Economics, Beijing 101149, China
  • 3. Key Laboratory of Carrying Capacity Assessment for Resource and Environment, MNR, Beijing 101149,China
  • 4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
*Corresponding author: DENG Ling, E-mail:

First author: HAO Qing, E-mail:

Received date: 2018-09-26

  Accepted date: 2018-11-30

  Online published: 2019-07-30

Supported by

Strategic Pilot Science and Technology Project of Chinese Academy of Sciences (XDA20010201).

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Abstract

In recent years, the rapid growth of population in Haikou and Sanya has caused extensive concern about the carrying capacity of Hainan Province. To formulate scientific population and environmental policies, it is necessary to research the relationship between population, carrying capacity and economic growth. In this paper, three indicators, grain production, nutrient composition of agricultural products and water resources, are used to measure carrying capacity quantitatively; the employment elasticity coefficient method is used to set the employment elasticity coefficient and the growth rate of regional GDP to estimate the total population needed to support economic growth; PADIS-INT population forecasting software that has parameters to track total fertility rate and net migration rate is used to predict demographic changes. The results show that, as of 2050, the total population of Hainan Province will not have exceeded the upper limit of the carrying capacity of land and water resources. In general, there is no overpopulation problem in the province, but there may be structural problems related to population, such as a large proportion of elderly people, labor shortages, and a high social dependency ratio. It is suggested that the local government should adopt positive population policies, improve the management of natural resources and the environment, and guide the balanced development of population in the province.

Key words： carrying capacity; economic growth; population; Hainan

Cite this article

HAO Qing , FENG Zhiming , YANG Yanzhao , YOU Zhen , CHENG Ping , DENG Ling . Study of the Population Carrying Capacity of Water and Land in Hainan Province[J]. Journal of Resources and Ecology, 2019 , 10(4) : 353 -361 . DOI: 10.5814/j.issn.1674-764X.2019.04.002

1 Introduction

It has been over a century since the concept “carrying capacity” appeared and relevant studies began being published (Feng et al., 2017). Some researchers have traced the origin of the concept to range managers who were concerned with the use of land for grazing livestock (Price, 1999). Bartelset traced it back to the 1906 Yearbook of the U.S. Department of Agriculture (USDA, 1907). The term soon began to be used in relation to herbivores management and in wild animal research (Leopold, 1933). Over time, the concept acquired broad currency after being introduced in biology and ecology textbooks. In these books, carrying capacity was defined as the maximum number of biological identities thatcan be supported by a given area without damaging environmental quality. In short, it was concerned mainly with issues like the limit of biotic population growth and human population capacity with food restrictions.
Before the concept of carrying capacity appeared, there were studies on the ecological and human impacts of population growth. In his An Essay on the Principle of Population in 1798, Malthus discussed the theory of population growth, which was later considered to be the bedrock of carrying capacity. Malthus argued that a population would tend to increase geometrically, whereas the means of subsistence would increase only linearly. This was the reality he observed in the North America at that time and he took it as a natural law. Eventually, food would be in short supply and this, in turn, would limit population growth. In 1920, Pearl and Reed used the theory of population growth to calculate that the population of the United States would level out at about 197 million in the twenty-first century (Pearl and Reed, 1920). In fact, this number was reached in 1966. Actually U.S. population continued to increase and reached 325 million in 2016, far beyond the upper limit predicted by Pearl and Reed. In some other developed countries, population growth has also not adhered to Malthusian theory. As a matter of fact, some countries with higher income have shown low or even negative population growth, which could not be explained by limiting factors. Hence, beginning in the 1950s and 1960s, a number of scholars became dubious about the value of Malthusian theory, believing that it did not apply to higher-income countries (Grebenik and Leibenstein, 1957).
By the late 1960s and early 1970s, pressure on resources and the environment brought about by population and economic growth had made the carrying capacity of the earth a global concern. The concept began being applied to the resource and environmental crisis caused by human activities. The concept of carrying capacity was rapidly introduced into a number of fields, and concepts like resource carrying capacity, environmental carrying capacity, ecological carrying capacity and resources and environmental carrying capacity emerged. After the United Nations Conference on Environment and Development, which was held in Brazil in 1992, carrying capacity became a focus of academics in the fields of resources and environment (Cohen, 1996). However, Arrow and other researchers argued that it was of little significance to carry out research on the carrying capacity of population due to the unpredictability of human innovation and bio-evolution (Arrow et al., 1995). Today, carrying capacity is no longer just an academic concept, but has been widely disseminated and used in news reports and government documents. The politicization, socialization and generalization of the concept have led some people to suspect that the scientific basis of the concept has been corrupted and doubt evaluation results produced by its use (Mcleod, 1997).
Our planet is the resource base for economic and social development. Natural resource consumption, environmental deterioration and ecosystem degradation endanger the planet. The finite supply of resources finally determines the upper limit of population on earth. As such, carrying capacity remains useful when it indicates current population size or the relationship between population and economic density and resources and the environment. For this reason, it is necessary to re-examine the connotations of carrying capacity using its original meaning—the maximum population load that can be sustained in a certain region within a certain environment and with a certain amount of resources under certain social and economic conditions. We can use carrying capacity studies of a region to understand the pressure human activities puts on the regional resources and environment under certain social and economic conditions, and then take steps to balance population, economic, and resource and environmental needs to coordinate growth (Feng et al., 2018). This paper has used Hainan Province in China as an example. Located in the southernmost part of China, Hainan is an island province with a relatively independent natural system. Hainan has an area of 35354 km2 and had a total population of 9.17 million at the end of 2016. When Hainan Province was established in 1988, because of the island’s superb natural environment, real estate became the leading industry. In 1994, the national government implemented macroeconomic regulations and control. Under these circumstances, the property market collapsed, and a large number of projects were disbanded due to lack of funds. Many enterprises withdrew from Hainan. After this recession of the property market, the economy of Hainan Province took a downturn, and the economic growth rate was lower than the national average for three consecutive years. After 1996, Hainan Province reconsidered its development ideas and sought new economic growth points. In 1998, Hainan selected ecotourism and tropical agriculture as key industrial pillars. Since then, the economic development of Hainan had has gradually turned into a positive direction. On December 31, 2009, the State Council issued “Several Opinions on Promoting the Construction and Development of Hainan International Tourism Island”, which gave a strong push to Hainan’s economic and social leap-forward development. On April 14, 2018, the Central Committee of the Communist Party of China and the State Council issued the “Guiding Opinions on Supporting Hainan’s Comprehensive Deepening of Reform and Opening-up” and proposed building a China (Hainan) Free Trade Pilot Zone. The economic and social development of Hainan Province has entered a new historical development stage. At the same time, in recent years, with the development of the economy and society, Hainan’s population is growing faster than the national average. In particular, the populations of the island’s major tourist cities, such as Haikou and Sanya, have soared. From 2006 to 2016, the number of permanent residents in Haikou increased by 27.13%, from 1.77 million to 2.25 million, while Sanya increased by 40.73%, from 5.36 million to 7.54 million. Hainan Province is a relatively independent geographical unit, and its rapid population growth has brought a series of resource and environmental problems. A study of carrying capacity and population policy is necessary in order to answer the following questions: What is the carrying capacity of Hainan Province? Will population surpass carrying capacity due to rapid growth? What kind of population policy and resources and environmental measures should be adopted in the future?

2 Methodology and data

2.1 Methods

2.1.1 Hypothesis
The total population during a certain period should be controlled within a reasonable range that neither surpasses the upper limit of natural resources availability, nor fails to meet economic growth target. Based on this hypothesis, the population development goal for Hainan Province is set at:
${{P}_{\text{rmax}}}\ge {{P}_{\text{t}}}\ge {{P}_{\text{emin}}}$ (1)
Prmax: The maximum population that a region carries in a certain period;
Pt: The actual population size in a certain period and a certain region;
Pemin: The minimum population that a region carries in a certain period.
2.1.2 Carrying capacity model
It is assumed that Hainan, as an island, is a relatively closed and independent system, in which natural resources will limit population growth. The population growth limit Prmax is expressed as follows:
$~{{P}_{\text{rmax}}}=\text{min}\{{{P}_{r1}},{{P}_{r2}},\cdots ,{{P}_{ri}}\cdots {{P}_{rm}}\}$(2)
Pri is upper limit of population growth given certain resource and environmental constraints. This study chose food and available water resources as constraining factors. The reasoning and formulas used are as follows:
(1) Population size and the food constraint
Food is a basic need for human survival and development. Some areas can solve food shortages by imports. But this will create the illusion that all areas can sustain more than their own carrying capacity, resulting in global overloading (Hui, 2015). Therefore, each region needs to consider the capacity of its own resources. Hainan Province is subject to the influences of transportation and other factors, and it is more necessary than in any other part of China to ensure food security. To calculate the food limit, we use:
${{P}_{f}}=\frac{F}{{{C}_{f}}}$(3)
Pf: Population size that the food can load in the region;
F: Total food amount;
Cf: Per capita food consumption.
(2) Population size within the water resource constraint
Because it is an island, Hainan is almost entirely dependent on its own water resources to supply water. The equation for water resource carrying capacity is,
${{P}_{w}}=\frac{W}{{{C}_{w}}}$(4)
Pw: Population size that the water can load in the region;
W: Available water resources;
Cw: Per capita water consumption.
2.1.3 Population model for economic development
Population is an active factor of economic development (Cai, 2004). When the total population in a region is smaller than what is needed, this will have a negative impact on economic and social development. Economic growth requires a population larger than minimum Pemin to achieve specific economic development goals, and the employment elasticity coefficient method is commonly used to measure the labor force needed for economic growth (Qi, 2010). The formula is as follows:
${{L}_{t}}={{L}_{0}}(1+{{\alpha }_{i}}{{g}_{i}})$(5)
Lt: Total labor force in the period t;
L0: Total labor force in the initial period;
gi: Growth rate of GDP.
ai: Employment elasticity coefficient, the ratio between the growth rate of employment and the rate of economic growth, determined by the equation:
$\alpha =\frac{\Delta L/L}{\Delta GDP/GDP}$ (6)
The minimum population size Pemin under a specific economic development goal is:
${{P}_{\text{emin}}}={{L}_{t}}/{{R}_{t}}$(7)
Where, Rt is proportion of the total population that is employed.
2.1.4 Population growth model
The population growth model is as follows:
${{P}_{t}}={{P}_{0}}{{(1+r)}^{t}}={{P}_{0}}{{(1+{{r}_{1}}+{{r}_{2}})}^{t}}$(8)
P0: Population size in base period;
Pt: Population size in period t;
r1: The annual average natural growth rate of population,
r2: The annual average mechanical growth rate of population.

2.2 Data sources and data processing

Basic data such as population, employment, gross domestic product (GDP), food production and available water resources of China and Hainan Province are found in databases of the National Bureau of Statistics and the Hainan Provincial Bureau of Statistics.
From the perspective of development, when Hainan Province was established, economic growth and population inflow were strongly influenced by policy factors, and the main economic indicators fluctuated greatly. For this study, researchers visited Hainan Province many times and discussed the situation with experts from Hainan. This research indicates that policy factors must be considered in Hainan's population growth and economic and social development. However, for economic and population forecasting, it is more appropriate to select the economic development of Hainan had has gradually turned into a positive direction from 1997. Therefore, the economic data such as GDP and GDP growth rate used in this study were for the years 1997 to 2016.

3 Results and discussion

3.1 Carrying capacity

3.1.1 Carrying capacity of food
(1) Carrying capacity of grain
From its establishment to the end of the 20th century, Hainan’s total grain production generally increased, from 1.20 million tons in 1988 to 2.31 million tons in 1999, representing 93.47 percent growth. However after 2000, grain yields began to decline with only 1.53 million tons produced in 2005. Although there were up and down fluctuations, overall yields continued to decline from 2006 to 2012. Assuming average per capita grain consumption of 400kg per year, grain in Hainan can load a population of 3 to 5.57 million (Fig. 1). Fig. 1 shows that the food produced in 2016 could carry 4.45 million people, which was only 48.49% of the total population of the province at end of 2016.
Fig. 1 Changes in population loads of grain production and actual population in Hainan (1988-2016)
The main reason for the decline of grain yields in Hainan was a decreasing amount of land available for cultivation. This peaked at 721100 ha in 1973, and had stabilized at around 550000 ha by the end of the 1990s. More recently, however, the amount of cultivatable land has been declining. In 2016, the sowing area for grain in the entire province was only 360400 ha, a reduction of 49.98% of the 1973 total. At the same time, the ratio of grain sown area to crop planting area also declined from a peak of over 97.14% to 43.77% in 2016 (Fig. 2).
Fig. 2 Grain sown area and its proportion to crop area in Hainan 1949-2016
At the end of 2016, the total area of cultivated land in Hainan was 837200 ha. Because the average multiple cropping indexes for the years 2012-2016 were 2.0, it can be calculated that the total sowing area in Hainan could reach 1.67 million ha. About 60% of Hainan's total area of cultivated land is sown with grain and average annual grain yields are 4.84 ton ha-1 (the average for 2017), meaning annual grain output can reach as much as 4.86 million tons. With per capita grain consumption of 400kg per year, Hainan can load a population of more than 12.16 million people. In fact, Hainan has great potential to boost grain yield and increase the carrying capacity of population by adjusting planting structure.
(2) Carrying capacity of food by nutrition
With social development and the improvement of living standards, the structure of Hainan residents’ food consumption is becoming more and more diversified, including foods of plant origin like grain, vegetable oil, sugar, vegetable, fruit and foods of animal origin such as meat, eggs, milk and aquatic products. This means that land conversions are common and that more and more land is being used to produce food types other than grain. Hence grain consumption alone cannot objectively reflect the overall carrying capacity situation in the region. It would be better to include all major agricultural products in the calculation to determine carrying capacity. Based on the characteristics and the changing patterns of residents’ food consumption and the nutrition structure in local diets, this study calculated carrying capacity based on demands for energy, protein and fat to show the actual capacity.
In 2001, the Dietary Nutrition Group of Chinese Academy of Agricultural Sciences released an adjusted table of food energy and nutrition composition based on the food consumption structure of Chinese residents at that time (Xu, 2001) (Table 1). The table shows food consumed by residents divided into nine categories. The energy and nutrient components of each food are shown as weighted averages based on nutrient content.
Table 1 Energy and nutrient composition of food
Item Grain Vegetable oil Sugar Vegetable Fruit Meat Eggs Milk Aquatic products
Energy (kcal kg-1) 3553 9000 3776 180 436 3915 1468 690 782
Protein (g kg-1) 93 0 4.6 11.4 6.2 99.5 123.8 33.6 125
Fat (g kg-1) 25.7 1000 0 1.6 2.4 387.8 101.4 40.2 24.2
We calculated the energy and nutrition of agricultural products produced in Hainan from 2007 to 2016 by using dietary energy and nutrition requirements for Chinese residents given in the Chinese DRIs Handbook (2013). Adult males and females who are moderately active require daily average energy (2400 kcal), protein (60 g) and fat (30 g), so we figured the calorific value of nine major agricultural products in Hainan, and then the carrying capacity based on energy and nutrition demands (Table 2).
Table 2 Carrying capacity of agricultural products’ energy and nutrition in Hainan 2007-2016
Year Energy (108 kcal) Protein (108 g) Fat (108 g) Energy loaded people (million) Protein loaded people (million) Fat loaded people (million)
2007 137550.71 4480.58 3350.46 15.7021 20.4593 30.5978
2008 150319.43 4738.55 3728.15 17.1598 21.6372 34.0471
2009 154042.72 4949.02 3972.77 17.5848 22.5983 36.2810
2010 149941.59 5001.40 4085.48 17.1166 22.8375 37.3104
2011 156751.29 5286.37 4283.87 17.8940 24.1387 39.1221
2012 168101.57 5680.18 4681.64 19.1897 25.9369 42.7547
2013 169561.83 5801.32 4846.83 19.3564 26.4900 44.2632
2014 166649.04 5919.28 4767.94 19.0239 27.0287 43.5428
2015 157849.18 5985.61 4711.76 18.0193 27.3316 43.0298
2016 152333.67 6024.85 4648.00 17.3897 27.5107 42.4475
Average 156310.10 5386.72 4307.69 17.8436 24.5969 39.3396
The average number of people could be supported by energy, protein and fat were 17.8436 million, 24.5969 million and 39.3960 million in Hainan during 2007 to 2016, respectively. They are the lowest carrying capacity with the three items supporting populations of 15.7021 million, 20.4593 million and 30.5978 million in 2007 respectively. Cheng and others cited FAO data that put the global food wastage rate at 30 percent (Cheng et al., 2017). Taking this ratio into account, the average population sizes that average annual energy, protein and fat of agricultural products in Hainan Province could support from 2007-2016 were 12.4347 million, 16.9784 million and 27.1291 million, respectively (Fig. 3).
Fig. 3 Sustaining population of agricultural products’ energy and nutrients in Hainan Province 2007-2016
3.1.2 Carrying capacity of water
Hainan has abundant water resources with average annual water volume of about 30.73 billion m3 over time. However, the water distribution is uneven within any given year, and the amount of water resources vary greatly between wet years and dry years, with the variation coefficient between 0.40 and 0.55. The ratio between maximum and minimum annual runoffs is as high as 4 to 7 times. During the last 20 years, Hainan has had an average of 36.435 billion m3 of water resources per year. The year 2004 was the low point for water resources with only 17.114 million m3, while 2013 with 50.2 billion m3 was the best year for water resources. The year 2004 had no tropical cyclones, resulting in low annual precipitation that led, in turn, to a severe drought that affected the whole province. After calculating the standardized precipitation index (SPI), some scholars regarded the catastrophic drought that occurred from September 2004 to May 2005 in Hainan as China’s worst drought since 1961. Such drought conditions are unlikely to happen more than once in a hundred years (Li et al., 2009).
The average amount of water per person proposed by Swedish hydrologist Malin Falkenmark in 1992, which has been adopted by various countries and international organizations including China, was recognized as an indicator of whether water supply and demand in a country or region were strained (Chen and Qian, 2003). According to the index, there is a risk of water shortage when the average fresh water per person per year is less than 1000 m3. Based on this, Hainan’s average amount of water resources per year can support a population of 30.73 million. Because the principle of carrying capacity depends on having available a minimum supply of resources, this study used the water amount in 2004 to calculate the carrying capacity of Hainan Province. This resulted in carrying capacity for a population of 17.114 million.

3.2 The labor force and population size needed for economic growth

The employment elasticity coefficient is influenced by industrial structure. Generally, the employment elasticity coefficient is lower in primary industries and higher in service industries. In recent years, Hainan has seen a rapid development in tertiary industry, with value added by tertiary industry exceeding 50% of provincial GDP. This has contributed to increasing the employment elasticity coefficient for the whole region (Table 3). Based on changes of the coefficient in different periods, it is assumed that the employment elasticity coefficient in Hainan Province from 2018 to 2020 will be 0.24, and it will drop to 0.10 in 2021-2035, and fall further to 0.05 in 2036-2050.
Table 3 The changes of employment elasticity coefficient
Years Total Primary sector Industrial sector Service sector
1986-2016 0.05 0.02 0.04 0.13
1996-2016 0.10 0.04 0.09 0.25
2006-2016 0.24 0.06 0.33 0.43
In 2017, the GDP growth rate of Hainan Province was 7.0%, the lowest in nearly 20 years, and only 0.1 percent higher than the national level. Per capita GDP for the province was 44347 Yuan, only 82.15% of the national level. To truly play the role of special economic zone and become a leader in economic and social development, Hainan must accelerate the pace of its the economic development. This means the provincial economic growth rate should be greater than the national average. With the meeting of this requirement in mind, this study proposes hypothetical targets for Hainan’s future economic growth (Table 4). We call for a growth rate no lower than the 2017 rate of 7.0%; a growth rate of 7.5%, which is slightly higher than the average annual growth rate of 7.43% during the years 2014-2017, as the mid-range target; and a growth rate of 8.5%, which is slightly higher than the average annual growth rate of 8.30% during the years 2011-2017, as the high-range target.
Table 4 Hypothetical targets for economic growth rates in Hainan 2018-2050
2018-2020 (%) 2021-2035 (%) 2036-2050 (%)
Lowest plan 7.0 6.5 6.0
Medium plan 7.5 7.0 6.5
Highest plan 8.5 7.5 7.0
In addition, during the last three years, about 61% of Hainan’s total population was employed. As the population of Hainan ages, the proportion of the working population to the entire population will decrease, but a proactive employment policy could raise the province's employment rate. With both of these factors in mind, we assumed that the future employment rate in the province would remain at 61%.
Drawing on the above assumptions, to ensure economic growth goals, the size of the population in Hainan should be maintained as follows (Fig. 4).
Fig. 4 Population prediction based on economic goals
To achieve the lowest economic growth rate, the population of Hainan Province should be no less than 9.83 million in 2020, 10.58 million in 2030, 11.00 million in 2040 and 11.75 million in 2050. To achieve the mid-range growth target, the population numbers should be more than 9.87million in 2020, 10.83 million in 2030, 11.30 million in 2040 and 12.19 million in 2050. To achieve the high-range target, the population should be greater than 9.96 million in 2020, 11.01 million in 2030, 11.54 million in 2040 and 12.59 million in 2050. That is, only if the population in Hainan reaches the numbers noted here can it support the achievement of the economic growth targets presented here without relying on a migrant labor force.

3.3 Prediction on population growth

This study uses PADIS-INT population forecasting software. We take the gender and age structure from the sixth census in Hainan in 2010 and set parameters such as total fertility rate and rate of net migration to calculate future population changes of Hainan Province. Employing a cohort-component method, the PADIS-INT software supports ultra-long-term population forecasting (Staff, 2011; Zhai et al., 2017).
Based on the actual changes of the population of Hainan from 2011 to 2015, the study used PADIS-INT software to calculate total fertility rates of 1.77, 1.76, 1.76, 1.77 and 1.80 for each of the five years. They were generally stable at the level of 1.80, and so we set the total fertility rate of Hainan as 1.80 per year between 2016 and 2050, which would allow for achievement of the mid-range growth target, while the minimum growth target requires a fertility rate of 1.60 and the high-range target one of 2.0. The latter fertility rate would require policies to encourage fertility.
From 2000 to 2016, the average annual net migration to Hainan was 15 thousand people, and this was set as the initial value of the net migration rate for the mid-range growth target. Considering factors like industry, investment, household registration system reform and the fact that climatic conditions in Hainan are suitable for elderly people, for reaching the mid-range growth target, we assumed that annual net migration increases linearly to 30 thousand by 2020 and 50 thousand by 2050. To reach the minimum growth target, we assumed half of the initial value for the mid-range target would be adequate, meaning a net inflow of 7 thousand people. To reach the high-range target, we set a value double of the mid-range target’s initial value. That is, migration would increase linearly from 15 thousand in 2017 to 60 thousand in 2020 and 100 thousand in 2050.
Taking the fertility and migration rates needed to reach the minimum growth target, Hainan’s population will peak in 2040, and the population sizes will be 9.46 million, 9.81 million, 9.91 million and 9.76 million in 2020, 2030, 2040 and 2050, respectively. Using the fertility and migration rates need to achieve the mid-range target offer the most likely outcome for the province’s population. In this case, the population of the whole province peaks in 2046 at about 10.69 million. The population in 2020, 2030, 2040 and 2050 will be 9.56 million, 10.21 million, 10.64 million and 10.64 million, respectively. If we use the fertility and migration rates needed to achieve the high-range growth target, Hainan’s population will not peak before 2050. The population in 2020, 2030, 2040 and 2050 will be 9.69 million, 10.74 million, 11.59 million and 11.96 million, respectively (Fig. 5).
Fig. 5 Population prediction results with the three different growth rate targets

4 Conclusions and suggestions

4.1 Main conclusions

By comparing carrying capacity, the labor demand needed to support economic growth and population forecasts for Hainan Province, we drew the following conclusions (Fig. 6):
Fig. 6 Carrying population, labor-demand population and predicted population in Hainan
(1) Hainan is rich in resources, with a capacity of more than 12 million people based on food (land) and water resources. With the high-range forecast for population growth, the population will not exceed carrying capacity before 2050.
(2) The minimum population required to support economic growth in Hainan is greater than that forecasted by the mid-range and high-range population growth forecasts. Only in the case of rapid population growth can population size be adequate to achieve the minimum economic growth target. When it comes to the mid-range target for economic growth and population growth, there are likely to be problems caused by labor shortages. To sum up, the total population of Hainan will not exceed the carrying capacity of land and water resources in the future. However, it cannot support the labor force demand for economic development. In other words, Hainan will not be troubled by the problem of overpopulation, but there may be structural population problems such as a large proportion elderly people, insufficient labor supply, and a high social dependency ratio. The illusion of overpopulation in Hainan may derive from unbalanced population distribution. More than 42.7% of Hainan’s population is concentrated in Haikou and Sanya, and population in other areas is relatively low.

4.2 Policy suggestions

(1) We suggest that Hainan adopt a positive population policy. Firstly, Hainan can develop a proactive policy that attracts talent from other provinces and regions to come to Hainan to work or start businesses. Secondly, Hainan should make appropriate changes to relax family planning policy, choosing some cities and counties with low fertility rates to carry out pilot programs that fully liberalize fertility restrictions. Furthermore, Hainan must continue to improve social services and local governance capabilities to respond to an aging society in a timely manner.
(2) We suggest that Hainan implement effective resource management and spatial governance measures. Firstly, Hainan needs to strengthen the construction of water conservation facilities, develop desalination projects, and effectively respond to annual changes in precipitation. Secondly, Hainan should protect the productive capacity of agricultural land, arable land in particular. Thirdly, Hainan needs to optimize spatial development by promoting balanced development between regions.
(3) Hainan needs to improve its ability to use resources that are outside the province. Food security offers an example. First, Hainan Province should strengthen exchanges and cooperation with the inland provinces in the agricultural sector, establish an extension agricultural product production base, develop order farming and base construction projects, and improve the level of production and marketing of major agricultural products. Second, Hainan needs to establish and improve a food reserve system consisting of government reserves, commercial reserves and farmer reserves. All cities and counties must establish a government-level low-temperature reserve center of a certain scale to ensure food supply in the event of an important event such as a typhoon. Third, Hainan should promote the construction of large-scale agricultural cooperatives on the island and extension production bases, develop transportation systems such as cold chain logistics, and ensure the safe and stable supply of agricultural products.

4.3 Research deficiencies and future improvement

This study took Hainan as an example to discuss the relationship between carrying capacity, population growth and economic growth, providing references to the development of population policies in Hainan Province. In the study, carrying capacity only took into account two elements—food and water resources. It is necessary to further evaluate the carrying capacity of ecological systems, water environments, living spaces and other factors. Carrying capacity is influenced by policy systems, culture, science and technology, the production and consumption structure, and other cultural and social factors, which taken together represent the integrated, dynamic and complex relationship between human activity and resources and the environment (Feng and Li, 2018). The predictions in this study have a higher reliability in the short time. Longer term forecasts for years after 2035 may include a large bias. Actual economic development may cause population forecasts based on labor demand to deviate greatly due to the influence of uncertain factors such as changes to industrial structure and the economic development mode. Actual population growth, influenced by the changes of child-bearing willingness and migration intention, may deviate from the population forecasts based on PADIS-INT. Therefore, we need to develop carrying capacity monitoring and early warning mechanisms for resources and the environment, make timely adjustments to the relevant parameters depending on changes of economic growth and population growth, and provide scientific support for resource management and spatial governance (Zhou et al., 2017).

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