Does Out-Migration Really Affect Forestry Ecological Security? An Empirical Case Study Based on Heilongjiang Province, China

Abstract

In the new era, coordinating the relationship between population flow and forestry ecological security has become an important challenge. In this study, we take Heilongjiang Province in China as an example, and through the combination of macro data and micro in-depth interviews, we explore whether population mobility really affects the intrinsic mechanism of forestry ecological security from the perspective of population exodus from forest areas. Based on the DPSIR model, we constructed a forestry ecological security evaluation index system, used the TOPSIS multi-objective decision analysis method to quantify the forestry ecological security status from 2000 to 2022, and utilized the impulse response function of the VAR model to explore the dynamic response relationship between population outflow and forestry ecological security. The results of this study show that, firstly, the comprehensive index of forestry ecological security level in Heilongjiang Province exhibits a fluctuating upward trend from 2000 to 2022. Second, forestry ecological security has a lagged effect on population outflow, and population outflow has almost no effect on forestry ecological security at present. Third, while the population outflow of Luobei County reduces the interference of human activities on the natural environment, it also brings about the pressures of insufficient forestry ecological resource management and forestry personnel. The Dongfanghong Forestry Bureau has effectively improved the efficiency of ecological construction and ecological security through the introduction of digitalized and intelligent equipment, which has effectively compensated for the negative impact of population outflow on the reduction in ecological management personnel. These findings will help realize the coordinated development of population, economy and society, and ecology.

1. Introduction

Forestry ecological security is an important component of national ecological security and plays an important role in regional sustainable development and ecological civilization [1,2]. With regard to the definition of ecological security in forestry, there is a distinction between a narrower sense, which refers exclusively to the health, integrity, and sustainability of the forest ecosystems themselves, and a broader sense, which emphasizes the maintenance of the security of forest ecosystems in the context of ensuring human and economic stability. This refers not only to forest ecosystems but also to the management of wetland and desert ecosystems, with the aim of securing the biological functioning of the planet and the terrestrial ecosystems [3]. Forestry ecological security encompasses multiple responsibilities such as maintaining forest ecosystem management and restoration, managing wetlands, ameliorating desertification, and protecting biodiversity [4,5]. In terms of the conceptual definition, studies by scholars from New Zealand, Canada, the United States, and other countries mainly focus on the health status of the forest ecosystem itself [6,7,8,9]. Chinese scholars have further considered the coordination and interaction of various subsystems in the forest ecology–forestry industry composite system and have thus constructed a forestry ecological security evaluation index system and conducted comprehensive evaluations [10,11,12]. In this study, forestry ecological security refers to the narrower sense; namely, it only includes forest ecosystem security (FES), which is defined as a state in which the ecological services provided by forest ecosystems are able to satisfy the needs of human survival and sustainable socio-economic utilization under the conditions of structural and functional completeness, so that human production, life, and development are not threatened [10,13,14]. The higher the level of stability and security of a forestry ecosystem, the more it protects the environment as a whole [13]. Currently, research on forestry ecological security mainly focuses on its evaluation. Most researchers construct evaluation index systems based on the broad concept of forestry ecological security and PSR (Pressure–State–Response) theory [15]. Academics and research institutions have widely used PSR [10], DPSIR [16], PSIR–TOPSIS [17], the Lotka–Volterra model, and spatial analysis [18] to evaluate the ecological security of ecological regions at different scales, such as the whole country, multiple provinces, and counties [19,20,21].

In natural ecosystems, the emergence and development of human beings, together with resources and the environment, form the cornerstone of the ecosystem, but there is an inherent contradiction between the population growth numbers, its activities, and the maintenance of the ecological environment [22]. The root causes of ecological problems are often closely linked to human activities, so how to properly harmonize the relationship between humans and ecology in the new era has become a crucial challenge. The existing literature on the relationship between population mobility and forestry ecosystems is mostly controversial, with most studies adopting a qualitative analysis approach. There are three mainstream points of view. First, the relationship between population flow and ecology shows an inverse relationship; that is, population increases and the intensification of human activities pose a threat to ecological security. For example, population inflow and increased activities may lead to the heat island effect, urban flooding, atmospheric pollution, and water pollution [2,23,24]. Secondly, population outflow affects the protection of resources and the environment in border areas; weak population mobility and a growth rate that is too high will also put pressure on the resources and environment in border areas [4,25,26]. Third, the impact of population mobility on the ecological environment is not an exclusively positive or negative relationship.

Heilongjiang Province, as a major forest resources province and an important ecological function safeguard area in China, is rich in forest resources, with a total area of 21.5 million hectares. It plays a pivotal role in maintaining ecological security, and it is responsible not only for the construction and protection of forest ecosystems but also for the management and restoration of wetland ecosystems, the improvement and management of desert ecosystems, and the maintenance and development of biodiversity. Therefore, in order to guarantee the continued stabilization of these ecological functions, it is necessary to ensure that a sufficient number and level of expertise measures are involved in the care and restoration of ecological resources, including the protection of specific species and their habitats, the restoration of damaged ecosystems, and the reconstruction of ecosystems that have lost the ability to repair themselves. These efforts are of value in promoting sustainable regional development and ecological construction. However, Heilongjiang Province is experiencing severe conditions of low fertility and negative population growth. Based on the latest statistics in 2023, the province has a significant negative natural population growth while the size of its resident population continues to shrink, and the problem of aging is becoming increasingly prominent as the urbanization process accelerates. In view of this phenomenon, we need to analyze the reasons behind it and explore corresponding strategies to optimize the demographic structure and achieve sustainable development in the future. At the same time, the weakening of the forest economy has led to a large number of people being unemployed or earning less, exacerbating the phenomenon of population exodus and creating a vicious cycle of economic and population contraction [27,28,29]. The roots of this problem can be traced back to the early years of the founding of New China, when the lack of integrated planning in Heilongjiang Province led to the large-scale exploitation of natural resources, resulting in resource depletion. To address this challenge, in 1998, the province began to reposition itself from primarily timber production to a greater emphasis on ecological development. This new phase represented a functional change to environmental construction and economic and social development [30]. In 2014, Heilongjiang Province, the largest key state-owned forest area in China, took the lead in a nationwide pilot project for the implementation of a new policy to completely stop the commercial logging of natural forest resources, following the International Union for Conservation of Nature policies [31]. In 2015, China issued the Guiding Opinions on the Reform of State-owned Forest Areas, which promoted the reform of the management system of state-owned forest areas by separating the government from the enterprises and completely halting the commercial logging of natural forests [32]. This policy shift has had a profound impact on the economic development structure of state-owned forest areas in Heilongjiang Province, where the development of the secondary forestry industry has been significantly restricted. Under the active promotion of a series of policies, the protection of forest resources and their ecological environment in Heilongjiang Province has been effectively strengthened. However, for the forest resources in the protected areas, it is particularly important to implement reasonable management strategies. The phenomenon of population exodus has led to the aging and relatively low education level of the ecological protection workforce, and at the same time, the willingness of the young population in the county to participate in ecological protection work is generally low. In addition, the full deployment of digital intelligent monitoring equipment has not yet been completed. Whether these factors pose a potential threat to ecological security deserves in-depth exploration.

Based on the above research background and demographic push–pull theory, conservation biology, restoration ecology, and symbiosis theory, this study will innovatively start from the perspective of population flow, combined with macro data and micro in-depth interviews, to conduct a comprehensive analysis of whether population flow affects the regional development of the forested area and the maintenance of ecological security, and to explore in depth the intrinsic mechanism of the role between population flow and ecological security [33]. At the macro level, taking Heilongjiang Province in China as an example, we measured the number of population flows and the level of forestry ecological security, explored the impact of population flows on forestry ecological security based on a 23-year time series data model, and selected the income level of forestry workers, foreign direct investment, and the proportion of secondary and tertiary industries as the control variables in order to reveal the actual impacts of population flows on forestry ecological security in different time periods, thus deepening the study of the human–ecological relationship, namely between people and ecology. At the micro level, this study selects Luobei County and Dongfanghong Forestry Bureau in Heilongjiang Province as a case study to further verify the relationship between population outflow and ecological security. In the end, it will reveal the intrinsic connection and influence the mechanism between them and provide a scientific basis for the formulation and implementation of relevant policies.

2. Materials and Methods

2.1. Study Area

Heilongjiang Province is located in the border area of northeast China and is rich in forest resources, with a total forestry land area of 31.75 million hectares, accounting for two-thirds of the total area of the province, of which the forested area has reached 1.844 million hectares, with the forest coverage rate stabilized at 43.78%. There are 12 prefecture-level cities and one district city in Heilongjiang Province. There are 67 counties (cities) in the province, including 21 county-level cities. In terms of the economy, according to the latest data, the gross domestic product (GDP) of Heilongjiang Province will reach CNY 158.839 billion in 2023. In terms of demographic structure, according to the results of the 2023 “5 per 1000 Population Change Sample Survey”, the total resident population of the province at the end of the year was about 30.62 million people, of which the urban population was about 20.549 million people and the rural population was about 10.071 million people, with the urbanization rate reaching 67.1%, an increase of 0.9 percentage points over the previous year (https://www.hlj.gov.cn/, accessed on 1 July 2024).

Luobei County, under the jurisdiction of Hegang City, Heilongjiang Province, is located in the northeastern part of the province, which happens to be at the intersection of the southern edge of the Xiaoxinganling Mountains and the Sanjiang Plain. Laobei County is a typical multi-ethnic settlement, where 19 ethnic groups, including Han, Korean, Manchu, Hui, and Mongolian, coexist harmoniously, with a total population of about 230,000 people. In terms of administrative division, Luobei County has five towns, five townships, and one ethnic township with special characteristics, and its administrative jurisdiction covers 91 administrative villages. The county also contains six state-owned farms under the direct management of the Baoquanling Branch and eight industrial forest farms under the jurisdiction of the Hebei Forestry Bureau. Located in the forest belt of Xiaoxinganling, Luobei County has rich forest resources, with a woodland area of 4.7 million mu and a wide variety of forest trees.

The Dongfanghong Forestry Bureau, subordinate to Hulin City, is located in the east of Heilongjiang, close to the Wandashan forest area along the Ussuri River. It has a vast area of 580,000 hectares, spanning Hulin, Raohe, and Baoqing counties and cities belonging to Jixi and Shuangyashan. Its geographic scope is from the beginning of the East Ussuri River, west to Bao Rao highway, south from the Abuqin River, north to the Weishan Daling, east–west span of 68.5 km, north–south up to 93.5 km long. Headquartered in Dongfanghong Township, Hulin City, the Forestry Bureau is an important part of the forest industry in Heilongjiang Province, relying on the rich resources of the Wandashan forest area, and it continues to contribute to the regional economy and ecological construction.

2.2. Data Sources

The indicators are obtained from the Heilongjiang Statistical Yearbook (2000–2022), China Forestry Statistical Yearbook, China Forestry and Grassland Statistical Yearbook (2000–2022) (https://data.cnki.net/yearBook/single, accessed on 1 July 2024), and the National Bureau of Statistics (Heilongjiang Provincial Bureau of Statistics) (www.forestry.gov.cn/, accessed on 1 July 2024). The data on the number of population flows and migration in existing studies mainly come from the China Statistical Yearbook, provincial statistical yearbooks, and national population census or sample survey data. Since the data from the national census or sample survey data all lack temporal continuity [34], this study chooses to utilize the data from the Heilongjiang Statistical Yearbook to calculate the number of urban population migrations based on, in addition to the use of, continuous data and methods in previous studies [35,36]. In addition, the indicator data of different development programs in this study refer to the Outline of the 14th Five-Year Plan for National Economic and Social Development (2021–2025) and the 14th Five-Year Plan for Ecological Environmental Protection in Heilongjiang Province, Vision 2035 (https://www.hlj.gov.cn/, accessed on 1 July 2024). The data collection process was not easy. In the process of data collection, there were a few indicators that were not counted in the statistical yearbooks and bulletins. When the missing values were small, the mean value method or linear interpolation method was chosen to interpolate according to the pattern of the missing parts. When there were too many missing values or the interpolation was too difficult, the sample was deleted.

2.3. Research Methods

2.3.1. Calculate Natural Growth

In measuring population movement, the specific formulae for the relevant indicators are as follows. A positive value indicates a net inflow of population, while a negative value indicates a net outflow of population. The natural population growth rate is equal to the difference between the birth rate and the death rate, and the number of population movements is equal to the product of the population at the end of the current year minus the population at the end of the previous year minus the population at the end of the previous year and the natural population growth rate.

(1) Calculate natural growth rate of population:

$${\mathrm{N}\mathrm{G}\mathrm{R}\mathrm{O}\mathrm{P}}_{\mathrm{j}}={\mathrm{B}\mathrm{R}}_{\mathrm{j}}-{\mathrm{D}\mathrm{R}}_{\mathrm{j}}$$

(1)

(2) Calculate natural growth rate of population:

$${\mathrm{N}\mathrm{M}}_{\mathrm{j}}={\mathrm{P}\mathrm{o}\mathrm{p}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_{\mathrm{j}}-{\mathrm{P}\mathrm{o}\mathrm{p}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_{\mathrm{j}-1}(1+{\mathrm{N}\mathrm{G}\mathrm{R}\mathrm{O}\mathrm{P}}_{\mathrm{j}})$$

(2)

$${\mathrm{N}\mathrm{M}}_{\mathrm{j}}={\mathrm{P}\mathrm{o}\mathrm{p}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_{\mathrm{j}}-{\mathrm{P}\mathrm{o}\mathrm{p}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_{\mathrm{j}-1}{-\mathrm{P}\mathrm{o}\mathrm{p}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}_{\mathrm{j}-1}\times {\mathrm{N}\mathrm{G}\mathrm{R}\mathrm{O}\mathrm{P}}_{\mathrm{j}}$$

(3)

2.3.2. DPSIR Logical Framework and Construction of the Indicator System

The DPSIR model, created by the European Environment Agency (EEA), is a structured theoretical model based on the synthesis of the advantages of PSR, DSR (DSP), etc., and is a model applied to the measurement of the safety of ecological environmental systems and risk evaluation [37,38]. The advantage of the model is that it can comprehensively consider economic, social, ecological, and environmental factors and deeply reflect the interaction mechanism between the natural environment and human beings [39]. Driving force refers to the fundamental impetus that triggers ecological environment changes, life, and production styles; pressure refers to the direct factors that affect the environment, such as resource consumption and pollution emission [40]; state refers to the natural state of natural resources; impact refers to the influence produced by the state under the action of the driving force and pressure; and response refers to the positive measures taken by human beings to promote sustainable development. The evaluation index system of forestry ecological security in Heilongjiang Province based on the DPSIR model describes a causal chain that reveals the interactions between the economy, ecological security, and population and social development in border forest areas. The five baseline indicators interact with each other, reflecting the relationship between the natural environment, human activities, and economic and social development [41,42].

This study will determine the indicators based on the research results of the forestry ecological security indicator system at home and abroad, unlike previous studies, based on the unique natural and economic and social conditions and the current development status of Heilongjiang Province, and with reference to documents such as Indicators for Ecological Counties, Ecological Municipalities, and Ecological Provinces (Revised) [43]; and Indicators for Pilot and Demonstration Zones for the Construction of the State’s Ecological Civilization (for Trial Implementation) [44], so as to determine the evaluation system of the ecological security of forestry in the region, including three levels, i.e., target level (A), guideline level (B), and indicator level (C), and five aspects, i.e., driving force (D), pressure (P), state (S), impact (I), and response (R). With the actual situation of Heilongjiang Province as the basis for selecting indicators, 23 ecological security indicators of Heilongjiang Province were initially selected. In order to ensure the scientific, systematic, and availability aspects of the indicators, it was finally determined that the indicator layer contained 18 indicators, and their positive and negative properties were determined with respect to the characteristics of the indicators.

Driving force (D) is the fundamental reason for promoting the development of the system. It is the endogenous power and pursuit of economic and social development, but also the fundamental driving force of forestry ecological security pressure. In the economic and social aspects of the driving force, their indicators include per capita disposable income, per capita GDP, and Engel’s coefficient, reflecting the macro-environment of the forestry ecological composite system within the economic and social development, but also indirectly reflecting the production and consumption of forest resources, the destruction of the ecological environment, and the general impacts on it. Pressure (P) refers to the direct cause of environmental change, and it is divided into social development pressure and forestry industry development pressure. Indicators of pressure on human social development include population density and urbanization level, while indicators of pressure on forestry industry development include total forestry output value. State (S) refers to the reality of the forest ecosystem under the action of driving forces and pressures, and forest state indicators include forest stock, forest area, and forest cover. Impact (I) refers to the impact of the state of the system on the socio-economic and normal life of the residents and the impact of external forces, and the impact indicators include the areas covered by forest pests, the incidence rate of forest pests, and the forest area affected by forest fires. The response (R) process is the measures taken by human beings and the policies formulated by the government to promote the maintenance and improvement of forestry ecological security level. Response indicators include the area of forest pest control, the rate of forest pest control, the proportion of new afforestation, and the amount of completed forestry investment.

2.3.3. TOPSIS Methods

The entropy weight method, an objective assignment method based on mathematical statistics, is considered from the information point of view, which determines the weight of an indicator according to the degree of disorder of the information provided by the indicator, with a clear physical meaning, reflecting the degree of internal difference of each indicator and the relative intensity in the sense of competition. According to the basic principle of information theory, the degree of ordering of the system is divided into two states, ordered and disordered, in which the degree of order is expressed by information, while the degree of disorder is measured by entropy, and the smaller the value of entropy, the greater the amount of information provided by the indicator [45,46,47]. The entropy weighting method has the advantage of objective assignment and can effectively avoid the subjective influence of weight setting. The confidence and accuracy of the factor weights derived by this method are higher than those derived using other subjective weighting methods [48]. Since various types of indicators have different scales, it is not possible to directly carry out the entropy weight method weight calculation, so it is necessary to standardize the original data [49]. The data should be made dimensionless, and the information entropy of all factors can be calculated to determine their weights [50].

TOPSIS (the Technique for Order Preference by Similarity to an Ideal Solution) method (see Equations (6)–(13)) is a multi-objective decision-making method based on evaluation technology [51]. It consists of approximating the ideal solution ordering method in order to provide an objective, fair, and impartial evaluation of a particular item. The essence is to judge the development level of the system by measuring the Euclidean distance between the real state of the system and the ideal state [52].

In this study, based on the entropy weight method and TOPSIS method, the forestry ecological security index is calculated to comprehensively evaluate the overall level of forestry ecological security development.

• In this study, the data were normalized using the method of polar deviation normalization, and the forward and reverse indicators were normalized separately [15].

  $${x^{\prime }}_{ij}={\displaystyle \frac{x_{ij}-\mathit{min}(x_j)}{\mathit{max}(x_j)-\mathit{min}(x_j)}} (\mathrm{Positive} \mathrm{indicators})$$

  (4)

  $${x^{\prime }}_{ij}={\displaystyle \frac{\mathit{max}(x_j)-x_{ij}}{\mathit{max}(x_j)-\mathit{min}(x_j)}} (\mathrm{Negative} \mathrm{indicators})$$

  (5)

2.

Calculate the share P of indicator j in year i:

$$P_{ij}={\displaystyle \frac{{x^{\prime }}_{ij}}{{\sum }_{\alpha }{\sum }_i{x^{\prime }}_{ij}}}$$

(6)

3.

Calculate the information entropy of the jth indicator:

$$e_j=-k\sum _i{P}_{ij}\mathit{ln}(P_{ij})$$

(7)

4.

Calculate the redundancy of the information entropy of the jth indicator:

$$d_j=1-e_j$$

(8)

5.

Calculation of the weight of the jth indicator:

$${\omega }_j={\displaystyle \frac{d_j}{{\sum }_j{d}_j}}$$

(9)

6.

Calculate the weighting matrix:

$$X_{ij}={x^{\prime }}_{ij}\times {\omega }_j$$

(10)

7.

Calculate the Euclidean distance:

$${D_i}^{+}=\sqrt{\sum (Z_{ij}-{Z_j}^{*+}{)}^2}$$

(11)

$${D_i}^{-}=\sqrt{\sum (Z_{ij}-{Z_j}^{*-}{)}^2}$$

(12)

8.

Calculate the composite score:

$$C_i={\displaystyle \frac{D_i^{-}}{D_i^{+}+D_i^{-}}}$$

(13)

2.3.4. An Empirical Study on the Impact of Population Outflow on Forestry Ecological Security

(1) VAR Model construction

The VAR model was introduced by Christopher A. Sims, the Nobel Prize winner in economics, in 1980. In the process of traditional regression analysis, exogenous and endogenous variables need to be identified in advance, but in a system wherein variables interact with each other, it is very difficult to clearly distinguish between exogenous and endogenous variables, and misidentification can lead to erroneous conclusions. Therefore, in a complex system wherein the effects of various factors on economic growth are studied, it is necessary to put these variables together and forecast them as a whole in order to obtain reasonable forecasting results [53,54]. The impulse response and variance decomposition can be used to further explain and analyze the relationship between the variables.

The most general mathematical expression for a VAR model is as follows:

$$Y_t=C+{{\varphi }_{1}y}_{t-1}+{\varphi }_p{Y}_{t-1}+{\epsilon }_t (t=1978, 1979\dots , 2019)$$

where $Y_t$ is an n-dimensional vector time series, $C$ is an n-dimensional vector of constants, $p$ is the lag order, and $t$ is the sample. ${\varphi }_1$…${\varphi }_p$ are k × k dimensional coefficient matrices to be estimated, and ${\epsilon }_t$ is a k-dimensional vector of randomly perturbed columns, which can be contemporaneously correlated with each other but are not correlated with their own lagged values and are not correlated with the variables on the right-hand side of the equation [55,56,57].

(2) Selection of variables

In this study, forestry ecological security (FES), the number of net population migration (OUT-FLO), the income level of forestry workers (WEG), and the proportion of secondary and tertiary industries (EST) are selected as research samples from 2000 to 2022. Forestry ecological security (FES) is the explanatory variable, and the number of net population migrations (OUT-FLO) is the main explanatory variable. The income level of forestry workers (WEG) and the proportion of secondary and tertiary industries (EST) are the control variables. The income level of forestry workers (WEG) and the proportion of secondary and tertiary industries (EST) are important evaluation indicators to measure the sustainable development of the economy. Among them, the income level of forestry workers = the average annual wage of on-the-job forestry workers/the average annual wage of urban workers in Heilongjiang Province.

3. Results

3.1. Population Movement in Heilongjiang Province

Since 2000, the population of Heilongjiang Province in China has only seen a positive population growth in 2000 and 2010, with a negative growth in all other years (see

Table 1. Population change in Heilongjiang Province, 2000–2022.

Year	Population at Year-End (Persons)	Birth Rate (‰)	Death Rate (‰)	Natural Growth Rate of Population (‰)	Net Migration (Persons)
1999	37,920,000	10.55	5.49	5.06
2000	38,070,000	9.43	5.50	3.93	974
2001	38,110,000	8.48	5.49	2.99	−73,829
2002	38,130,000	7.98	5.44	2.54	−76,799
2003	38,150,000	7.48	5.45	2.03	−57,404
2004	38,168,000	7.27	5.45	1.82	−51,433
2005	38,200,000	7.87	5.20	2.67	−69,909
2006	38,230,000	7.57	5.18	2.39	−61,298
2007	38,240,000	7.88	5.39	2.49	−85,193
2008	38,250,000	7.91	5.68	2.23	−75,275
2009	38,260,000	7.48	5.42	2.06	−68,795
2010	38,330,000	7.35	5.83	1.52	11,845
2011	37,820,000	6.99	5.92	1.07	−551,013
2012	37,240,000	7.30	6.03	1.27	−628,031
2013	36,660,000	6.86	6.08	0.78	−609,047
2014	36,080,000	7.37	6.46	0.91	−613,361
2015	35,290,000	6.00	6.60	−0.60	−768,352
2016	34,630,000	6.12	6.61	−0.49	−642,708
2017	33,990,000	6.22	6.63	−0.41	−625,802
2018	33,270,000	5.98	6.67	−0.69	−696,547
2019	32,550,000	5.73	6.74	−1.01	−686,397
2020	31,710,000	3.75	8.23	−4.48	−694,176
2021	31,250,000	3.59	8.70	−5.11	−297,962
2022	30,990,000	3.34	9.09	−5.75	−80,313

). Compared with other provinces, Heilongjiang Province entered the negative growth stage early, and the level of negative population growth has been increasing since 2010. From the relevant data, it can be seen that the problem of population outflow in Heilongjiang Province has been present for a long time, and the level of population outflow has increased exponentially, which not only implies the loss of population quality but also a reduction in the total population. This affects not only economic development but also regional social balance and is a challenge to demographic security. Since the net migration of the population is negative, the population movement assumed thereafter refers mainly to the outflow of the population (OUT-FLO).

3.2. Data Analysis of Forestry Ecological Safety in Heilongjiang Province

(1) Indicator system analysis

Indicators are determined through the specific methods described above (see

Table 2. Forestry ecological security evaluation index system and its weights.

Target Level	Criterion Level	Indicator Level	Index Nature	Formulas
Forestry ecological security	Driving force indicators	Urban disposable income per capita	+	Heilongjiang Statistical Yearbook (2000–2022)
		Rural disposable income per capita	+	Heilongjiang Statistical Yearbook (2000–2022)
		GDP per capita	+	Heilongjiang Statistical Yearbook (2000–2022)
		Urban Engel’s coefficient	+	Heilongjiang Statistical Yearbook (2000–2022)
		Rural Engel’s coefficient	+	Heilongjiang Statistical Yearbook (2000–2022)
	Pressure indicators	Population density	−	Total population at the end of the year/country area (persons/square kilometer)
		Urbanization level	−	(Urban population at the end of the year/total population of the region at the end of the year) × 100 percent
		Total forestry output	−	China Forestry and Grassland Statistical Yearbook (2000–2022)
	Status indicators	Forest stock	+	China Forestry and Grassland Statistical Yearbook (2000–2022)
		Forest area	+	China Forestry and Grassland Statistical Yearbook (2000–2022)
		Rate of forest cover	+	Forest area/land area
	Impact indicators	Area of forest pests	−	Forestry pest occurrence and control by region, including forestry diseases, forestry pests, forestry rodent (rabbit) pests, and harmful plants
		Incidence of forest pests	−	China Forestry and Grassland Statistical Yearbook (2000–2022)
		Fire-affected forest area	−	China Forestry and Grassland Statistical Yearbook (2000–2022)
	Response indicators	Area of forest pest control	+	China Forestry and Grassland Statistical Yearbook (2000–2022)
		Forestry pest control rate	+	China Forestry and Grassland Statistical Yearbook (2000–2022)
		Additional afforestation area	+	China Forestry and Grassland Statistical Yearbook (2000–2022)
		Forestry investment completion	+	China Forestry and Grassland Statistical Yearbook (2000–2022)

). Pressure indicators are all caused by human activities, which will have a negative impact on forestry ecological security, so reducing human activities to improve economic construction and thus bring about forest destruction will have a positive significance in improving the forestry ecological security index. The intensity of government investment in forestry accounts for a larger proportion of the response indicators, indicating that government investment and the introduction of supportive policies to maintain forestry ecological security are conducive to the construction of forestry ecological security.

(2) Comprehensive level analysis

The forestry ecological security index value of Heilongjiang Province each year is in the range of [0, 1], and a larger value indicates that the regional forest ecological security is more secure (see Figure 1). The 2000–2022 forestry ecological security level of the composite index shows a fluctuating upward trend. The trend of change is different in part of the time period, among which the forestry ecological security level of the composite level is the highest in 2022 at 0.722. The first and second phases of the natural forest resource protection project ensure that the investment in forest ecological maintenance reaches its maximum. The first and second phases of the natural forest resources protection project have maximized the investment in forest ecological maintenance. In 2000–2007, the composite index of the ecological security level of forestry in Heilongjiang Province decreased slightly, and in 2008–2022 it showed an upward trend, with the composite index increasing from 0.267 to 0.722. The ecological security level of forestry increased from 0.267 to 0.722 since 2013 and has exceeded the average value of 0.722. The forestry ecological security level has exceeded the average value of 0.444 since 2013, which is a safer forestry ecological security level. Increased awareness of ecological protection has also led to a fluctuating upward trend in the forestry ecological security index of Heilongjiang Province. Twenty-three years ago, the operation mechanism of the natural forest resources protection project was constantly revised and improved in the intertwined evolution of practice and policy, and the ecological security of forestry in Heilongjiang Province has also decreased from the beginning of the implementation of the policy to the subsequent gradual increase. With the evolution of the policy, i.e., from natural forest protection project to natural forest protection and restoration system and from pure natural forest protection to the comprehensive management of mountains, water, forests, fields, lakes, and grasses, the forestry ecological security index will also continue to rise. At the end of this study, the data of the comprehensive evaluation level of the multi-indicator forestry ecological security index conducted by the TOPSIS method are selected as the values of the following explanatory variables.

3.3. Empirical Study on the Impact of Population Outflow on Forestry Ecological Security

(1) Unit root test

This study utilizes the VAR model to study the relationship between population outflow (FLO) and forestry ecological security (FES) [58,59]. The unit root test is needed first. The purpose of the unit root test is to examine the smoothness of the data. Most of the time series are not smooth, and in order to avoid pseudo-regression in the regression equation, the unit root test is conducted before proceeding with the analysis to select the smooth variables for regression. Non-smooth series may produce the spurious regression phenomenon, and smoothing the time series is a prerequisite for the subsequent econometric analysis using impulse effects and variance decomposition. In this study, we use STATA software (Stata17.0) to construct a VAR model. The unit root smoothness test (Augmented Dickey–Fuller Test, or ADF for short) is first performed on the four variables. This study utilizes the ADF unit root test to conduct the test. The four variables OUT-FLO, INVEST, EST, and FES are non-smooth. After first-order differencing, the variables all show smoothness.

In order to explore the long-term relationship, an autocorrelation test is conducted. The p-value is greater than 0.05, which means that the original hypothesis is accepted. Additionally, there is no autocorrelation.

(2) VAR modeling

In order to effectively establish the VAR model, the lag order test must be carried out on the VAR model (see

Table 3. Determination of the lag order of the VAR model.

Lag	LL	LR	FPE	AIC	HQIC	SBIC
0	−151.304		147.916	16.3478	16.3814	16.5466
1	−95.0404	112.53	2.24506	12.1095	12.2778	13.1037
2	−69.5882	50.904	1.09642	11.1146	11.4174	12.904
3	−39.4054	60.366 *	0.601897	9.62162 *	10.0591 *	12.2064 *

* indicates statistically significant at 10%.

). According to the optimal lag criterion (AIC, SC, LR), the optimal lag order is determined to be of the third order.

(3) Granger causality test:

The VAR model constructed from the variables is tested for smoothness (see Figure 2). The points all fall within the unit circle, the VAR model is stable, and the variables are smooth, so the Granger causality test can be used [53]. Figure 2 shows that all points fall within the unit circle. Therefore, the model is stable.

There are some variables in the economic variables that are significantly correlated but not necessarily in a meaningful way. Granger proposed a test for determining causality that addresses the question of whether x causes y. In essence, it is a test to see whether the lagged variables of one variable can be introduced into the equation of the other variables. A variable is said to have Granger causality if it is affected by lags of other variables. The test is based on the VAR (2) model according to the actual situation.

The lag order given by FPE, AIC, SC, and HQ criteria is 3. After determining the optimal lag period, the Granger causality test is performed. When the original hypothesis is “OUT-FLO is not the Granger cause of FES”, the p-value is 0.032, which is less than 0.05, indicating that the original hypothesis is rejected at the 5% level of significance. Therefore, the past value of FLO can be used to predict the future value of FES. When the original hypothesis is “EST is not the Granger cause of FES”, the p-value is 0.601, which is greater than 0.05, indicating that the original hypothesis is accepted at the 5% level of significance. When the original hypothesis is “WEG is not a Granger cause of FES”, the p-value is 0.128, which is greater than 0.05, indicating that the original hypothesis is accepted at the 5% significance level.

The Granger causality test shows that population outflow is a Granger cause of forestry ecological security, and forestry ecological security is also a Granger cause of population outflow. It can be concluded that population outflow and forestry ecological security influence each other as far as the current stage of China is concerned. The income level of forestry workers (WEG) and the proportion of secondary and tertiary industries (EST) have an effect on forestry ecological security, but forestry ecological security has almost no effect on the income level of forestry workers (WEG) and the proportion of secondary and tertiary industries (EST). Analyzing from the perspective of economics, this may be due to the stage and exogenous nature of China’s urbanization development. At present, China’s urbanization process is at the fastest development rate in history, and the population and economic activities are rapidly concentrating in large towns, which will inevitably generate external economics in many aspects due to the scale effect. It makes the construction and investment in forestry ecological security decrease accordingly, which is not conducive to the guarantee of ecological security. As for the income level of forestry workers (WEG) and the proportion of secondary and tertiary industries (EST), they have an impact on forestry ecological security, indicating that forestry ecological security and economic development are still not coordinated at this stage in China.

(4) Impulse response

The main function of the VAR model is not to interpret the significance of the regression coefficients but to illustrate the effect of a shock to a random new variable on the endogenous variable and its relative importance, variables which need to be further analyzed with an impulse response function. The impulse response function can describe an endogenous response to an error, portraying the effect of a shock of a standard deviation size on the current and future values of the endogenous variable in a VAR model. Since, in the VAR model, all variables are correlated with other variables, a shock to any one variable will not only affect its own change but also have an impact on all the variables in the other vectors. Based on the above research, the main analysis is the impact of population mobility on forestry ecological security. Ecological security has a perturbing effect on population movement (see Figure 3). Period 0 to period 1 is a declining negative response; from period 1 to period 2, the response value rises slowly, and then it begins to decline again after period 2. Thereafter, it continues to fluctuate negatively to converge to 0. The long response time indicates that forestry ecological security does not reflect the effect of population outflow for a short period of time, which suggests that it is reflected with a lag. Additionally, population outflow has no response to forestry ecological security.

(5) Variance decomposition

The variance contribution of forestry ecological security to itself is always the largest, and the number of net population migration (OUT-FLO), the income level of forestry workers (WEG), and the proportion of secondary and tertiary industries (EST) have a smaller impact (see Figure 4). The outflow of population has the largest variance contribution to the income level of forestry workers (WEG), followed by the proportion of secondary and tertiary industries (EST), which has remained stable since the third period and has a relatively small impact on forestry ecological security.

3.4. In-Depth Interviews

At the micro level, this study selects Luobei County and the Dongfanghong Forestry Bureau in Hulin City as cases to further verify the relationship between population outflow and forestry ecological security. From 19 to 25 May 2024, the team went to Luobei County and Hulin City for research. The research mainly focused on the current situation of economic and social development and construction in forest areas, population loss problems, ecological construction, etc. The research was carried out through the investigation of the existing population, natural resource environment, income channels of residents, relevant policies, and management status of the typical areas. The research on the existing population, natural resources environment, residents’ income channels, related policies, and management of the current situation was used to identify the main contradictions and pain points, and then through the investigation of diverse villages, to find ways to help regional development and ecological construction. The research method was divided into meetings and talks and typical areas of field household surveys.

Case Study 1: Luobei County is facing a serious problem of population loss, especially in villages and areas inhabited by ethnic minorities. Influenced by multiple economic and social factors, young laborers generally choose to go out to work, exacerbating the population loss phenomenon. Take the Dongming Korean Township as an example; although its household population reaches more than 600 people, the actual resident population is only 90 people, and this mainly includes the elderly. Due to the geographic proximity to South Korea, coupled with the similarity of language and the relaxation of visa policy, a large number of Korean villagers choose to go to South Korea to work in pursuit of higher income. According to statistics, their average annual income in South Korea can be as high as CNY 200,000, far more than the average annual income of CNY 50,000 in the county. With its remote location, inconvenient transportation, and lagging industrial development, residents of Luobei County rely mainly on agriculture and fisheries for their livelihood. The low demand for travel and unprofitable bus networks in some remote villages has led to the removal of bus stops, further exacerbating the travel difficulties, especially for those in Arrival Village, who have to travel to their jobs in the county town. In addition, the lack of a train station in the county town requires foreign tourists to make several transfers to get there, severely restricting the development of the local tourism industry and other industries. In terms of education, due to the loss of young people, the number of school-age children in some remote villages has plummeted to the point where they are unable to maintain the operation of the elementary school in the villages, resulting in the need for children to go to elementary school in the townships and causing inconvenience to their parents. At the same time, the attraction of high-quality educational resources in county towns and big cities has prompted young families to choose to work outside the village. In terms of medical care, although villages have clinics, village doctors have a limited professional capacity and can only address simple illnesses. As the population ages, more village doctors are taking retirement, while the difficult conditions and low wages in remote villages make doctors from county hospitals reluctant to work in villages, leading to a shortage of manpower in village health clinics. Most of Luobei County belongs to a national nature reserve, and most of its land is covered by the reserve, resulting in limited arable land. Villagers mainly rely on selling wild vegetables to make a living, with a low per capita income.

Luobei County, as an important management unit of national nature reserves and state-owned forests, has an important ecological mission due to its unique geographical location and rich natural resources. However, in recent years, the county has faced a serious problem of population exodus. While mitigating the human-made economic impact on the natural environment, this phenomenon has also brought many challenges to the care of forestry ecological resources and the development of the forestry business. First of all, the population exodus has directly led to a serious shortage of personnel for the care of forest ecological resources. As a core area of state-owned forests, Luobei County is crucial for the protection and management of forestry resources. However, due to the exodus of a large number of young laborers, the number of professionals engaged in the management of forestry ecological resources has decreased sharply. This not only affects the daily management and maintenance of forestry resources but also increases the risk of forestry disasters and ecological damage. Second, the exodus of people has exacerbated the vulnerability of the livelihoods of the population in the forestry ecological region. In Luobei County, many villages and communities are located within the forestry ecoregion, and residents in these areas have long depended on forestry resources for their livelihoods. However, with the exodus of the population, the number of residents in these areas has decreased, and there is a shortage of labor, resulting in their livelihood sources becoming more homogenous and vulnerable. In the event of damage to forestry resources or changes in the market, there will be greater risks to these residents’ livelihoods. Finally, the exodus may also trigger negative effects such as structural imbalances in society. With the exodus of young laborers, the labor structure in Luobei County is gradually aging, and social vitality is declining. At the same time, the economic pressure and resource shortage caused by the population outflow may lead to an increase in social instability. In addition, the population outflow may aggravate the problems of the urban–rural gap and unbalanced regional development, which will adversely affect the socio-economic development of Luobei County. To summarize, the problem of population exodus in Luobei County, while mitigating the anthropogenic economic impact on the natural environment, also brings serious challenges to the management of forestry ecological resources and the development of forestry business. In order to cope with these challenges, it is necessary to take effective measures to attract and retain talents, strengthen the protection and management of forestry ecological resources, and promote the sustainable development of local socio-economy.

Case 2: The Dongfanghong Forestry Bureau, located in the Wandashan forest area along the Ussuri River in the eastern part of Heilongjiang Province, is committed to the full implementation of the “Smart Forestry” strategy to promote the modernization and informatization of forestry management. Driven by the wave of informationization, the Dongfanghong Forestry Bureau deeply recognizes that the traditional forestry management mode has made it difficult to meet the needs of modern forestry development. Therefore, the Bureau actively responded to the national call for intelligent forestry construction and optimized and enhanced the efficiency and precision of its forest resource management through the establishment of a series of integrated systems for forest resource file management, resource management, pest prevention and control, seedling production management, intelligent fire prevention, and so on. In the construction of intelligent forestry, the Dongfanghong Forestry Bureau makes full use of big data, cloud computing, artificial intelligence, and other cutting-edge technologies to lead the enterprise production and operation management mode to a profound change. The application of these technologies not only accelerates the digital transformation process of the enterprise but also provides strong support for the realization of more efficient and accurate resource management. By constructing a precise geographic information system for forest resources, the Bureau’s big data integrated information management platform realizes the precise positioning of each tree within each operation, thus ensuring the real-time monitoring and early warning forecasting of changes in forest resources. In order to further enhance the intelligent level of forest resources protection, the Dongfanghong Forestry Bureau has added a large visual screen and an electronic sand table on the basis of the fire prevention monitoring system. The application of this advanced equipment enables the video monitoring and electronic sand table to display the dynamic information in the forest area in real time and realize dynamic visualization monitoring through precise positioning. This innovative initiative has greatly enhanced the convenience and intelligence of fire-fighting work, enabling real-time information to be rapidly extracted, transmitted, and stored, thus providing strong technical support for the comprehensive protection of forest resources.

In addition, the Dongfanghong Forestry Bureau has also established an intelligent information system and working platform for forest managers by constructing a precise big data geographic information system in the form of “one map” and continuously improving the information content. The use of this platform not only realizes real-time monitoring of changes in forest resources but also improves early warning and forecasting and the ability to investigate and deal with problems as well as provide all-around technical support for fire prevention, pest control, and wildlife protection.

Although the Dongfanghong Forestry Bureau is still inevitably facing serious challenges such as population loss and labor shortage, these challenges pose certain pressure on the ecological construction, resource management, and ecological security of the forest area. However, in addressing these challenges, the DFB has demonstrated a forward-looking strategic vision and strong determination to achieve significant improvements in ecological construction and ecological safety and security through the active introduction of digital and intelligent equipment and technologies. Specifically, the Dongfanghong Forestry Bureau has realized real-time and accurate monitoring of resource changes in forest areas by introducing advanced forest resource monitoring equipment, intelligent data analysis systems, and efficient information management platforms. This equipment and these technologies not only enhance the accuracy and efficiency of data collection and analysis but also provide more scientific and rational decision-making support for forest management. In terms of ecological construction, the application of digitalized and intelligent equipment and technology enables the Dongfanghong Forestry Bureau to more accurately assess the ecological status of the forest area as well as identify and address ecological problems in a timely manner. Through scientific planning and rational layout, the Bureau has achieved remarkable results in promoting ecological restoration and protecting biodiversity. At the same time, these equipment and technologies also help monitor and prevent the occurrence of natural disasters such as forest fires, pests, and diseases, providing a strong guarantee for the ecological safety of forest areas. In terms of management processes, the application of digitalized and intelligent equipment and technologies has also brought about significant improvements. Through the establishment of a unified information management platform, integrated management of forest area resources, personnel, equipment, and other information has been realized. This not only improves management efficiency but also helps optimize resource allocation and reduce management costs. At the same time, the Bureau has also simplified office processes by introducing automated and intelligent office equipment, further enhancing work efficiency. The implementation of this series of initiatives not only promotes the modernization and informatization process of forestry management in the Dongfanghong Forestry Bureau but also lays a solid foundation for achieving sustainable forestry development. Through the introduction of digital and intelligent equipment and technology, the Bureau has achieved remarkable results in ecological construction, ecological safety and security, and management processes, providing strong support for the sustainable development of forest areas. At the same time, these initiatives also provide experience and inspiration for other forestry units and are of great significance in promoting the modernization and informatization process of the entire forestry industry.

4. Discussion

Via an in-depth analysis, this study systematically compares and discusses its results with related studies in the existing literature, and the specific comparison and analysis process is described below.

In the results of this study, the impact of the income level of forestry workers and the proportion of secondary and tertiary industries on the ecological security of forestry further reveals that there is still a lack of coordination between the ecological security of China’s forestry industry and its economic development, which also highlights the imbalance between China’s forestry ecological security and its economic development. The existing literature suggests that when forest land resources face multiple challenges, such as total scarcity, imbalanced distribution, variable quality, significant degradation, and increased reversal, they pose a threat to the ecological security of the national society and the sustainable development of the industrial economy [60]. As the contradiction between natural resource conservation and exploitation becomes increasingly acute, economic development, as one of the key factors driving ecological changes, needs to be urgently addressed in terms of its harmonious symbiosis with the ecological environment [61,62]. Therefore, it is widely believed that sustained economic growth also requires the coupled and coordinated development of the ecological environment [63,64,65,66]. Combined with the research in this study, for the topic of ecological security and economic development, we should uphold the core concepts of “harmonious coexistence of man and nature” and “green mountains are golden mountains” [67] and explore new paths of green development [68] to ensure ecological security, and support the sustainable socio-economic development [69]. The stage of turning ecological advantages into economic advantages to form an integrated and harmonious relationship belongs to a higher realm [70]. The ultimate goal is to reach the upward spiral presented by the stage-by-stage evolutionary trajectory of the interaction between ecological and environmental protection and economic development [71].

There is an interaction between population mobility and forestry ecological security, but the effect is not significant in the short term. Since Malthus put forward the negative theory of the relationship between population growth and material resource growth at the end of the 18th century, the relationship between population and the ecological environment has become the focus of long-term academic discussion. However, the relationship between population and ecological environment is not a simple causal link but has evolved with changes in human activities and social development [72]. Differentiated regulatory policies should be adopted for different types of regional functions based on the characteristics, causes, and dynamics of population flows [73]. In the context of the theme of this paper, while population reductions and out-migration from key ecological reserves have helped to reduce the pressure of human economic activities on forest ecosystems, population losses may also pose a series of problems [74,75], particularly in relation to the constraints posed by the shortage of management personnel on effective resource management and ecological restoration. In addition, the exodus phenomenon has led to a weakening of the dynamics of economic growth and a lag in the pace of social development in these areas, which has magnified the vulnerability of the population’s livelihoods and exacerbated the imbalances in the ecoregional structure. In view of this, maintaining a balanced population growth over the long term remains a core objective of China’s population development strategy [76].

Considering the wave of urbanization and rapid economic development, we must deeply understand the delicate and critical balance between population flow and forestry ecological security and actively take strategic measures to guide the population to move in an orderly manner within a reasonable range. At the same time, we should increase the investment and protection of forestry ecological security to ensure that, while pursuing economic prosperity, we can also maintain a healthy and stable ecological environment and ultimately realize the harmonious symbiosis and coordinated development among population, economy, and ecology.

For a region where population loss has resulted in a negative impact on forestry ecological security, it is necessary to consider the threat from three perspectives: the pressure of the population gap in ecological resource management, the vulnerability of the population’s livelihood in the forestry ecological region, and the imbalance of the social structure in the ecological region due to population loss. It is recommended that, firstly, policy guidance and support should be strengthened, and a series of preferential policies for the development of forest areas should be introduced as a key area of concern for the coordinated development of the region and the construction of common prosperity, such as the provision of tax exemptions and tax breaks, financial subsidies, and the increase in employment opportunities in forest areas, in order to attract and retain talented people. At the same time, a long-term and stable financial guarantee mechanism has been established to ensure adequate financial support for the development of forest areas. Second, we recommended promoting industrial transformation and upgrades and encouraging the development of industries with local characteristics in forest areas, such as eco-tourism and under-forest economy, so as to realize the diversification of the industrial structure. At the same time, we recommended increasing investment in forestry science and technology research and development, improving the added value of forestry products, and increasing the source of income of forest area residents. Thirdly, we should improve the infrastructure of forest areas and increase the construction of roads and communication, water, electricity, and other infrastructure in forest areas so as to improve the quality of life and convenience for forest area residents. In particular, it is necessary to improve transportation networks, reduce the distance between forest areas and central cities, and improve the accessibility of forest areas. Fourthly, education and training and the introduction of talents should be strengthened, and the education and training of forest area residents should be increased to improve their vocational skills and comprehensive quality. At the same time, external talents are actively introduced to provide intellectual support for the development of forest areas. Through the exchange of talent and collaborative research, we can promote the connection and cooperation between forest areas and the outside world. Finally, it is recommended to establish a monitoring and evaluation mechanism to monitor and evaluate population losses in forest areas, regularly collect and analyze relevant data, and provide a scientific basis for policy formulation and adjustment. At the same time, supervision and inspection of the implementation of the policy will be strengthened to ensure that the measures are put into practice.

For key ecological function areas, i.e., areas where population loss has a positive impact on forestry ecological security, the recommendations are as follows. First, the allocation of resources should be adjusted, population movements should be reasonably guided, and population contraction should be appropriately implemented. Second, natural recovery is the main focus, supplemented by artificial intervention. The natural recovery process should be encouraged in forest areas, and unnecessary artificial interventions should be reduced. For bottlenecks in the ecological restoration process, such as invasive alien species, pests, and diseases, appropriate artificial intervention measures can be taken. Third, ecological monitoring and protection should be strengthened, and a good ecological monitoring system should be established to monitor the ecological changes in forest areas in real time. Digital intelligence construction, integrated systems for resource management and protection, pest prevention and control, seedling production management, intelligent fire prevention, etc., should be improved to comprehensively optimize forest resource management. Fourth, on the premise of not destroying the ecology, eco-tourism should be developed in moderation so that more people can understand and participate in ecological construction. Through eco-tourism, local economic development is promoted, and residents’ enthusiasm for ecological protection increases. Considering the actual conditions of the forest area, a sustainable development mode that is suitable for the local area should be explored, for example, the development of forest economy, forest recreation, and other industries, to benefit both ecology and the economy.

5. Conclusions

The contribution of this study lies in the fact that, by integrating demographic data and forestry-related data and using a combination of empirical evidence and interviews, the impact of population outflow on forestry ecological security in Heilongjiang Province is deeply explored. When analyzing population change in forest areas, we notice that the trend of change is particularly significant, which is mainly manifested in the phenomenon of significant population contraction. This contraction is not only reflected in the reduction in total population but also affects the balance of the age structure of the population at a deeper level, which leads to an imbalance in the age structure of the population. Both natural population increases and decreases and population migration and mobility have exacerbated this trend to varying degrees. Therefore, it is necessary for us to carry out in-depth research and strategy planning for this current situation. It is recommended that great importance should be attached to the balance between population flow and forestry ecological security and that effective measures should be taken to ensure that population flow is within a reasonable range while increasing the investment in and protection of forestry ecological security so as to realize the coordinated development of population, economy and society, and ecology.