Characteristics of Spatial–Temporal Differences and Measurement of the Level of Forestry Industry Integration in China

Abstract

The integration of the forestry industry can effectively resolve the conflict between ecological protection and socioeconomic development while bringing new vitality and growth to traditional forestry. In this study, the level of forestry industry integration in 31 provinces in China from 2005 to 2019 was measured using the Herfindahl index method. With ArcGIS and exploratory spatial data analysis methods, the spatial-temporal distribution characteristics, dynamic change trends, spatial correlation characteristics, and existing problems in China’s forestry industry integration development were analyzed. The results showed that the total output value of forestry integrated products and the output value of each product segment increased, but the proportion of product development was imbalanced, and it was concentrated in the understory planting and collection industry and wood processing and manufacturing industry, leaving substantial room for improvement and integration. The value of the forestry industry integration index also increased overall, but the level of integration was low or moderate. In terms of time, the integration index of most provinces trended upward but failed to break through 0.73, leaving a significant gap between it and deep integration. Spatially, the level of integration of the forestry industry varied across the northeast, central, west, and east, with the central and northeast showing a higher integration degree than the east and west. China’s forestry industry integration showed a significant positive spatial correlation, indicating that spatial factors had become an important factor affecting the development of the forestry industry in various regions. Therefore, it is necessary to strengthen the relevant mechanisms of cross-border cooperation and benefit sharing. Lastly, we identified problems with the integration development of the forestry industry, including insufficient and imbalanced integration, unreasonable structural layout of integration development, and insufficient driving capacity for integration. As a result, there were phased and regional differences in the evolution of forestry industry integration.

1. Introduction

High-quality development has become a part of China’s national strategy [1]. As an important basic industry of the national economy, the forestry industry is gradually moving towards the stage of high-quality development. However, there are several challenges facing China’s forestry industry, including a large and weak structure, low efficiency improvement, poor forest quality, and the long-term inability of forest farmers to benefit from traditional forestry practices. The current situation of the forestry industry highlights the need to fully utilize the forest’s main role in improving the ecological environment, accelerate the industry’s development, improve forestry management efficiency, increase the income of forest farmers, and meet economic and societal demands for forest products to the fullest extent [2]. These are significant practical issues that need to be addressed in the process of promoting the forestry industry’s high-quality development.

To address these issues, it is essential to identify new drivers of forestry development and explore new economic growth opportunities. Industry integration, as an inevitable trend in industrial development, has various economic, social, and ecological benefits, such as promoting efficiency, increasing farmers’ income, and improving the ecological environment. China’s forestry has already moved beyond the traditional primary industry category of providing raw materials, and there is a trend of accelerating the infiltration and integration of forestry with other industries. Industry integration within the forestry industry and between forestry and other industries is an effective approach to move from the low-quality supply of forest resources through single wood processing to the high-quality utilization of forest resources. Promoting the integration and upgrading of forestry and related industries can effectively solve the contradiction between the ecological protection and socioeconomic development of the forestry industry; satisfy the diversified needs for economic development, ecological construction, and social development; and bring new vitality to traditional forestry [3]. It is important for the forestry industry to conduct thorough analyses of the level of integration and development, as well as its spatial–temporal evolutionary characteristics, to achieve high-quality development.

The academic community has been interested in industry integration since the 1960s, when the American scholar Rosenberg proposed the concept of technological integration in the evolution of technology in the American mechanical tool industry [4]. In 1978, Negroponte, the founder of MIT’s Media Lab, used three overlapping circles to describe the technological integration among the computing, printing, and broadcasting industries, which drew attention to the intersection of these industries as a fast-growing area; since then, foreign scholars have conducted numerous similar studies mainly focusing on communication, media, entertainment, commerce, agriculture, and other fields [5]. Commonly used measurement methods include the Herfindahl index method, multiple linear regression model analysis method, patent coefficient method, and input–output method [5].

In China, relevant research on this topic began relatively late. In recent years, however, scholars have made significant achievements in information technology integration, internet integration, financial industry integration, manufacturing industry integration, service industry integration, agricultural industry integration, and regarding the integration of other fields at the national, regional, provincial, and urban levels [6]. Measurement methods have included the input–output method [7], patent coefficient method [8], Herfindahl index method [5], grey correlation method [9], coupling coordination model [10], and comprehensive index method [11].

Although research on forestry industry integration is still in development, academics have made noteworthy efforts to promote development in this field. For example, Li (2007) defined the concept of forestry industry integration and pointed out that promoting the integration of forestry and other industries can realize forestry industrialization [3]. Thoroe and Dieter (2003) believed that the integration of forestry and forest industry sectors was characterized by integrated development through cross integration, creating more value for practitioners [12]. Lyu et al. (2018) measured the integration of the forestry industry in state-owned forest areas of Heilongjiang Province using the Herfindahl index method and analyzed the main factors affecting said integration and the extent of their impact using the principal component analysis method [13]. Wu and Zhang (2020) discussed theoretically the integration path of “internet + forestry” in China [14]. Other scholars have examined the integration of forestry from the perspective of tourism. For example, Ahtikoski et al. (2011) explored a potential trade-off between natural tourism and forestry in Northern Finland; they found that tourism can generate real economic value for regions that also possess abundant ecosystem services [6]. Li et al. (2021) analyzed the advantages and disadvantages of the forest tourism industry in Heilongjiang Province as the integration of tourism and forestry and proposed reasonable strategic suggestions [15].

Overall, research on industry integration has made significant progress. However, there are still deficiencies in the research on forestry industry integration, including the following:

(i)

Previous studies have not quantitatively investigated the spatial distribution and evolution of the level of forestry industry integration development based on comprehensive dynamic and static analyses combined with mathematical models, geographic information systems (GIS), and other spatial analysis technologies;

(ii)

There is a lack of comprehensive research on dynamic monitoring, spatial–temporal evolution, spatial correlation, and problem analysis of forestry industry integration;

(iii)

Most existing studies focus on the whole country or a single province and rarely involve all 31 provinces in China [13,14,15]. There is also a lack of sufficient analysis on the regional internal differences in the level of forestry industry integration, which cannot provide support for the development of differentiated policies in a given region.

To address these deficiencies, this paper used data for 31 provinces (cities and districts) in China from 2005 to 2019 to calculate the level of the integrated development of the forestry industry in different regions from the perspective of integrated products using the Herfindahl index method. We comprehensively analyzed the spatial and temporal distribution characteristics, dynamic change trends, and spatial correlation characteristics of China’s forestry industry integration development using ArcGIS statistical software and the exploratory spatial data analysis method. We identified the obstacles and demands in the process of forestry industry integration development, with the aim of providing decision support for China’s forestry industry integration development.

2. Materials and Methodology

2.1. Concept Definition

Forestry industry integration refers to the dynamic development process in which forestry and other industries, or the three forestry industries, break through their original boundaries via mutual penetration and intersection to create new forms of forestry industry or new development models [13]. An integrated forestry industry is an inevitable outcome of this process; it is a new model that results from the intersection and infiltration between forestry and other related industries such as forest tourism. The products of this integrated forestry industry are “forestry integrated products”.

2.2. Methodology

2.2.1. Measurement of Forestry Industry Integration Level

Measuring the level of industry integration accurately and scientifically is a key concept relevant to this topic. Currently, several methods are widely used, including the Herfindahl index, patent coefficient, coupling evaluation method, input–output method, and comprehensive index method [16]. However, as research on forestry industry integration is in its early stages, each method has unique advantages and disadvantages; a unified research approach has not yet formed. The Herfindahl index and input–output methods have become the mainstream measurement techniques for forestry industry integration [5,7]. The input–output method relies on an input–output table for the forestry industry, which is compiled in China only once every five years, preventing it from fully reflecting the continuous changes in the degree of integration among industries and resulting in large errors. Moreover, the input–output table does not directly account for the forestry sector, and it is difficult to systematically determine the intermediate demand or input of forestry and other various industries only through personal research.

Although technological diffusion does have an impact on industry integration, the primary manifestation of forestry industry integration is resource sharing rather than technological integration. However, many regions do not classify patents according to industrial patent statistics, which makes it difficult to apply the patent coefficient method with sufficient precision. In contrast, the Herfindahl index is commonly used by scholars to measure the integration levels of primary, secondary, and tertiary industries within agriculture due to the ease of data acquisition and processing [17]. Therefore, in this study, we found it reasonable and applicable to measure the level of forestry industry integration.

The Herfindahl index method was created by Gambardella and Torrisi (1998) and can be expressed as follows [5]:

$$HHI={{\displaystyle \sum _{i=1}^N\left(\frac{X_i}{X}\right)}}^2$$

(1)

where HHI represents the sum of the squares of all variable values and the overall proportion. Product integration is measured by integrating products; X refers to the total output value of forestry industry integrated products; and X_i represents the total output value of the ith-integrating product [18].

Although the concept of forestry industry integration was proposed fairly recently, the process itself is already well underway. Forestry integrated products include the understory planting and collection industry (X₁) formed by the integration of forestry and agriculture (planting and collection), the forest animal breeding and utilization industry (X₂) formed by the integration of forestry and animal husbandry, the wood processing and manufacturing industry (X₃) formed by the integration of forestry and the processing and manufacturing industry, the forest ecotourism industry (X₄) formed by the integration of forestry and the tourism industry, and the forestry production technology management industry (X₅) formed by the integration of forestry and the science and technology service industry [14].

The Herfindahl index is an inverse indicator of the level of industry integration, so its value ranges from 0 to 1. The closer the value is to 0, the higher the level of industry integration; the closer the value is to 1, the lower the level of industry integration [18]. To intuitively represent changes in the integration level of the forestry industry, the expression of the forestry industry integration index (FIII) is set as:

$$FIII=1-HHI$$

(2)

In addition, in order to ensure proper comparison, the integration degree classification used by most scholars was adopted, with 0.20, 0.40, 0.60, and 0.80 as the critical classification points. The integration degree of the forestry industry was divided into five grades corresponding to five integration degree intervals: low fusion, medium–low fusion, medium fusion, medium–high fusion, and deep fusion [19]. The specific details are listed in

Table 1. Integration level classification.

Fusion Interval	<0.20	0.20–0.40	0.40–0.60	0.60–0.80	0.80–1.00
Fusion level	I	II	III	IV	V
Type	Low fusion	Medium–low fusion	Medium fusion	Medium–high fusion	Deep fusion

.

2.2.2. Measurement of Spatial Autocorrelation

To analyze the spatial correlation of the level of forestry industry integration, the exploratory spatial data analysis (ESDA) was used to assess the global Moran’s I index and the local Moran’s I index [20]. The global Moran’s I index reflects the relevance of research objects or phenomena in the entire research field [21], while the local Moran’s I index reveals the relationship between a given region and its surrounding regions [22]. The value range of both indices is [−1, 1]. A global Moran’s I index value closer to 1 or −1 indicates stronger spatial correlation in the sample space, while a value closer to 0 suggests a lower spatial autocorrelation of the sample enterprises. A positive value indicates a positive correlation among levels of forestry industry integration development in the sample space, while a negative value indicates negative correlation; a zero value indicates a random distribution [23].

The local Moran’s I index measures the spatial homogeneity or heterogeneity of the sample area, with a higher value indicating stronger spatial homo- or heterogeneity between the level of forestry industry integration in a given region and its neighboring regions. Conversely, a value closer to 0 indicates that there is no significant spatial correlation between the level of forestry industry integration of the sample region and that of the neighboring regions. The local Moran’s I index can be used to classify spatial autocorrelation into four types: HH (high and high concentration), HL (high and low concentration), LH (low and high concentration), and LL (low and low concentration) [24]. They can be expressed as follows:

$$\begin{array}{cc}{\mathrm{Moran}}^{’}\mathrm{s}& I\end{array}=\frac{n{\displaystyle \sum _{i=1}^n{\displaystyle \sum _{j=1}^n{w}_i{}_j(x_i-\overline{x})(x_j-\overline{x})}}}{\left({\displaystyle \sum _{i=1}^n{\displaystyle \sum _{j=1}^n{w}_i{}_j}}\right){\displaystyle \sum _{i=1}^n{(x_i-\overline{x})}^2}}$$

(3)

$$I_i=\frac{n(x_i-\overline{x}){\displaystyle \sum _{j=1}^n{w}_i{}_j(x_j-\overline{x})}}{{\displaystyle {\sum }_i{(x_i-\overline{x})}^2}}$$

(4)

where x_i and x_j represent the levels of the integrated development of the forestry industry in different provinces; $\overline{x}$ is the average industry integration level; w_ij is a spatial weight matrix, which represents the spatial relationship of provinces in China; n denotes China’s 31 provinces (cities and districts); $\frac{n}{{\sum }_{i=1}^n{\left(x_i-\overline{x}\right)}^2}$ indicates the variance in the observed data; and $\sum _{i=1}^n\sum _{j=1}^n{w}_{ij}$ indicates the sum of the spatial weights.

2.3. Data Declaration

Considering availability, this paper selected panel data for 31 provinces (cities and districts) in China from 2005 to 2019 for analysis from the China Forestry Statistical Yearbook and China Forest Resources Report (2005–2019) and the EPS data platform. Data on the understory planting and collection industry, forest animal breeding and utilization industry, and wood processing and manufacturing industry were the output value data available in the annual statistical yearbook. For forest ecotourism and forestry production technology management, this paper referred to data processing methods used in previous studies to summarize and sort industries with similar natures or inappropriately small output values, ultimately obtaining the output value of each forestry integration industry, as shown in

Table 2. Classification description and characteristics of forestry integrated products.

Forestry Integrated Products	Classification Description	Characteristics
Understory planting and collecting industry	Understory planting and collecting industry formed by the integration of forestry and agriculture (i.e., planting and collecting)	Relies on forest land and forest resources to integrate the planting industry within the industry, as well as on collecting and processing plants and resources in and under the forest. A new form of ecological forestry business is established, mainly including the planting, collection, and processing of edible fungi, wild vegetables, and medicinal materials to achieve the integrated development of forest and planting practices. Double harvesting of trees and crops planted in the forest on limited land.
Forest animal breeding and utilization industry	Forest animal breeding and utilization industry formed by the integration of forestry and animal husbandry	Relies on forest land resources with science and technology as a productive force; uses idle land under the forest to integrate aquaculture and animal husbandry within the industry through the biological chain; cultivates and utilizes under-forest areas for the benefit of forestry and animal husbandry.
Wood processing and manufacturing industry	Wood processing and manufacturing industry formed by the integration of forestry with the processing and manufacturing industry	Relies on rich forest resources, artificially collecting and selecting plants with economic value under the forest, deploying technology and other industries to extend the industrial chain and increase added value to meet consumer needs.
Forest ecotourism	Forest ecotourism formed by the integration of forestry tourism, leisure services, and forestry ecological services	Uses the existing environment, terrain, climate, animals, and plants of the forest to form a natural landscape; prioritizes full development of forest resources with sightseeing and tourism value; provides tourists with leisure, sightseeing, and other services; management activities and protection activities for ornamental forest animals, plants, and landscapes; forms a cross-type integrated industry combining forestry and tourism.
Forestry production technology management industry	Forestry production technology management industry formed by the integration of forestry production service industry, forestry professional technical services, forestry public management, and other organizational services	Generates production auxiliary services by ensuring production activities; develops and experiments with new technologies and processes for the sustainable development of the forestry industry; and applies new forestry industry production and management technologies and processes to actual production.

.

To test for regional heterogeneity, the 31 provincial areas in China (apart from Hong Kong, Macao, and Taiwan, which lack data and were not included) were divided into four major regions according to the divisions of the National Bureau of Statistics: Eastern Region (Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, and Hainan), Central Region (Shanxi, Anhui, Jiangxi, Henan, Hubei, and Hunan), Western Region (Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, Inner Mongolia, and Guangxi), and Northeast Region (Liaoning, Jilin, and Heilongjiang).

3. Results of Forestry Industry Integration Development

3.1. Analysis of the Results of Forestry Integrated Products at the Overall Level

From 2005 to 2019, the total output value of China’s five industry integration products changed from CNY 646.2951 billion to CNY 7,177,391.9 billion, with an average annual growth rate of 18.76%. Among them, the output value of the understory planting and collecting industry and the wood processing and manufacturing industry is relatively large, accounting for more than 74% of the total output value of forestry integrated products. In contrast, the output value of the forest animal breeding and utilization industry and the forestry production technology management industry is relatively small, accounting for less than 6% of the total. From the perspective of subdivided product development, the annual growth rates of the output value of the understory planting and collecting, forest animal breeding and utilization, wood processing and manufacturing, forest ecotourism, and forestry production technology management industries are 14.489%, 16.440%, 18.190%, 55.041%, and 13.883%, respectively, as shown in

Table 3. Output values of forestry integrated products.

Time	Area	Understory Planting and Collecting Industry	Forest Animal Breeding and Utilization Industry	Wood Processing and Manufacturing Industry	Forest Ecotourism	Forestry Production Technology Management Industry	Total Value of Output
2005	Nationwide	26,729,040	596,045	34,111,117	352,558	2,840,752	64,629,512
	Eastern Region	13,305,979	179,373	22,287,264	60,746	781,085	36,614,447
	Central Region	5,605,784	134,644	5,617,040	131,696	1,187,073	12,676,237
	Western Region	6,400,618	17,390	3,571,422	81,006	695,317	10,765,753
	Northeast Region	1,409,758	264,638	2,537,858	71,441	174,876	4,458,571
2019	Nationwide	177,695,564	5,020,076	353,999,404	163,492,209	17,531,939	717,739,192
	Eastern Region	56,063,957	816,545	203,387,623	53,283,035	3,920,409	317,471,569
	Central Region	47,128,626	1,457,457	78,160,942	50,044,136	8,194,010	184,985,171
	Western Region	65,069,856	1,293,261	61,696,098	55,626,659	4,313,671	187,999,545
	Northeast Region	9,319,542	1,431,251	10,707,902	4,313,845	1,028,103	26,800,643

Data were compiled from the 2005 and 2019 China Forestry Statistical Yearbooks.

.

In general, the five integrated products have developed rapidly. The growth of forest ecotourism products is most significant, followed by wood processing and manufacturing industry products; the development of the forestry production technology management industry is relatively slow. Although the proportion of the understory planting and collecting industry in the downstream industry is declining, it remains the second highest among the industries we measured. However, the proportion of the forest ecotourism and forestry production technology management industry, which has higher added value, is consistently small. This indicates that forestry integrated products are mostly promoted to the market in the form of primary forest products, while other products with more potential economic value have not yet been developed.

3.2. Analysis of the Results of Forestry Integrated Products at the Regional Level

From 2005 to 2019, the proportions of the output value of the understory planting and collecting industry, forest animal breeding and utilization industry, wood processing and manufacturing industry, forest ecotourism industry, and forestry production technology management industry in the Eastern Region changed from 36.341%, 0.490%, 60.870%, 0.166%, and 2.133% to 17.660%, 0.257%, 64.065%, 16.784%, and 1.235%, respectively. The proportions of the Central Region changed from 44.223%, 1.062%, 44.312%, 1.039%, and 9.365% to 25.477%, 0.788%, 42.253%, 27.053%, and 4.430%, respectively. The proportions of the Western Region changed from 59.454%, 0.162%, 33.174%, 0.752%, and 6.459% to 34.612%, 0.688%, 32.817%, 29.589%, and 2.295%, respectively. The proportions of the Northeast Region changed from 31.619%, 5.935%, 56.921%, 1.602%, and 3.922% to 34.774%, 5.340%, 39.954%, 16.096%, and 3.836%, respectively.

From Figure 1, it can be seen that the output value of the five major integrated products in each region is increasing. The proportion of the total output value of forestry integrated products in each region is also consistent with that of the whole country; that is, the understory planting and collecting and wood processing and manufacturing industries are relatively large, while the proportions of the forest animal breeding and utilization industry and forest production technology management industry are relatively small. Apart from a decline in the Northeast Region, the proportion of the understory planting and collecting industry in all regions is on the rise, with the highest in the Western Region, at approximately 40%. As for the forest animal breeding and utilization industry, which accounts for a relatively small proportion (except in the Northeast Region, at 4.5–7.5%), all regional proportions fell below 1.5%. The proportion of the wood processing and manufacturing industry is highest in the Eastern Region, at approximately 60%, and it is increasing; this industry is on the decline in the Central, Western, and Northeast Regions. Forest ecotourism appears to be trending upwards in the four major regions. The proportions of the Central and Western Regions are increasing faster than in the Eastern and Northeast Regions. Interestingly, the proportions of the forestry production technology management industry and forest ecotourism have changed in the opposite direction, with a downward trend in all major regions.

3.3. Analysis of the Results of Forestry Integrated Products at the Provincial Level

In 2005, there were 20 provinces wherein understory planting and collecting was the leading industry. Wood processing and manufacturing was the leading industry in the remaining 11 provinces. In 18 provinces (i.e., more than half), the output value of the understory planting and collecting industry accounted for more than 50% of the total output value of forestry integrated products. Among them, Beijing, Tianjin, Shanxi, Shanghai, Shaanxi, Tibet, Gansu, Qinghai, and Ningxia accounted for more than 80% of the output value of the understory planting and collecting industry. The wood processing and manufacturing industry in Hebei, Inner Mongolia, Heilongjiang, Jilin, Zhejiang, Jiangsu, Fujian, and Hunan accounted for more than half of the total output value. In addition, in Beijing, Tianjin, Shanghai, Tibet, and Ningxia, a forest animal breeding and utilization industry did not form; in Qinghai, a wood processing and manufacturing industry did form; in Tianjin, Tibet, and Ningxia, a forest ecotourism industry did not form; and in Tianjin, a forestry production technology management industry did not form, as shown in Figure 2.

In 2019, there were 12 provinces with understory planting and collecting as the leading industry, 15 provinces with wood processing and manufacturing as the leading industry, and forest ecotourism became the leading industry in Beijing, Sichuan, Guizhou, and Tibet. There were seven provinces wherein the output value of the understory planting and collecting industry accounted for more than 50% of the total output value of forestry integrated products; among them, the value accounted for more than 70% in Tianjin, Shaanxi, Gansu, and Xinjiang provinces. The wood processing and manufacturing industries in Hebei, Jilin, Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Shandong, Guangdong, and Guangxi accounted for more than 50% of the total output value. In addition, in Shanghai and Tibet, a forest animal breeding and utilization industry had not yet formed; in Beijing and Tianjin, a wood processing and manufacturing industry did not form; and in Tianjin, a forestry production technology management industry did not form, as shown in Figure 3.

In general, although the leading industries in most provinces are concentrated in understory planting and collecting, as well as wood processing and manufacturing, the proportion of leading industries varies significantly across different provinces. Provinces with different forestry integrated products as their leading industry also show different change trends. The number of provinces with understory planting and collecting as the leading industry is trending downward but is still relatively high, while the number of provinces with wood processing and manufacturing as the leading industry is on the rise. Additionally, the number of provinces with forest ecotourism as the leading industry increased from zero to four over the study period.

4. Analysis and Discussion on the Spatial and Temporal Evolution Characteristics of Forestry Industry Integration Level

4.1. Analysis and Discussion on the Temporal Evolution Characteristics

Although the value of China’s forestry industry integration index increased from 0.415 to 0.548 between 2005 and 2019, marking a growth rate of 32.05%, the level of integration remained consistently moderate, as shown in Figure 4. To this effect, China’s forestry industry integration development has generally been strong in recent years, but the level of integration remains low; it is still far from the ideal value of 1. This may be attributable to the oversized proportion of the understory planting and collecting industry and the slow growth rate of the wood processing and manufacturing industry, while the proportions of the forest ecotourism and forestry production technology management industries, which have a strong driving role in the understory planting and collecting and wood processing and manufacturing industries, are relatively small and lagging behind others in terms of growth rate. There is significant room for transformation in the layout of the forestry industry integration structure which, to some extent, currently hinders any further improvement in the forestry industry integration level. It is also necessary to further activate forestry resources and promote the integrated development of the forestry industry overall.

In terms of the average value of the integration index, the Central Region (0.590) and Northeast Region (0.580) had much higher values than the national average (0.488) during the study period. However, the Eastern (0.421) and Western (0.469) Regions had lower values than the national average. All regions, as well as the national average, were in a state of moderate integration. The forestry industry integration index in each region showed varying degrees of growth, with the Western Region showing the highest growth rate followed by the Northeast, Central, and Eastern Regions. In 2005, the forestry industry integration index was highest in the Central (0.510) and Northeast (0.509) Regions and lowest in the Eastern (0.378) and Western (0.375) Regions. In 2019, this index was highest in the Northeast (0.665), followed by the Central (0.639), Western (0.544), and Eastern (0.464) Regions.

The degree of integration of the four major regions improved over the study period, with the Eastern and Western Regions moving from “medium and low” to “medium” degrees of integration. The Central and Northeast Regions moved from “medium” to “medium and high” degrees of integration. The Central and Northeast Regions showed higher integration degrees than the Eastern and Western Regions, with the Eastern Region having the lowest. This is mainly because, although the wood processing and manufacturing industry in the Eastern Region is developed, it mostly operates in the “two ends on the outside, big import and big export” mode. There is still room to improve the utilization rate of local forest resources, and the scale advantage of the manufacturing industry has not been translated into a higher level of integration with the primary and tertiary industries of forestry.

Furthermore, over the study period, the wood processing and manufacturing industry in the Eastern Region accounted for approximately 66% of the total; most of the raw materials came from New Zealand, Germany, Russia, Australia, the Czech Republic, the United States, Papua New Guinea, the Solomon Islands, Canada, Japan, and elsewhere. The utilization ratio of forest resources in the region was not high relative to the scale of its manufacturing industry. The scale of the eastern forestry processing and manufacturing industry still has substantial room for improvement in terms of driving other forestry industries, and the integration effect is weak. For example, the understory planting and collection industry accounts for approximately 20% of the total value of local integrated products; the forest ecotourism industry and subsequent supporting forestry production technology management industry account for less than 14%. Imported timber has, to some extent, compensated for the shortage of forest resources in China and alleviated the contradiction between the supply and demand of timber.

It is important to note that major timber-exporting countries around the world have begun to restrict or even ban timber exports in the context of environmental protection and sustainable development strategies. This prompts a need to reduce China’s excessive reliance on foreign resources in the “two ends on the outside” model. This model has weak bargaining power and consumes a significant amount of energy during processing, leading to excess carbon emissions and hindering the green transformation of the forestry processing industry, as well as limiting its development potential. To overcome this challenge, all regions should revitalize their high-quality forest resources and prioritize the development of resource-based forestry economies such as tourism and leisure. It is also necessary to extend the value chain of resource endowment, deepen the integration of the forestry industry, and improve the collaborative development ability of the primary, secondary, and tertiary industries.

The forestry industry integration index value in each region increased to varying extents from 2005 to 2019, with the Western, Northeast, Central, and Eastern Regions ranking from high to low, respectively. Overall, the integration degree of the four major regions improved during this period. However, the Central and Northeast Regions generally achieved a higher level of integration than the Eastern or Western Regions, with the latter having the lowest level of integration. Therefore, it is crucial for all regions to revitalize their high-quality forest resources and promote the integrated development of the forestry industry.

At the provincial level, the forestry industry integration index varied substantially from 2005 to 2019, ranging from 0.027 to 0.725 (

Table 4. Forestry industry integration levels in China’s provinces.

Area	Province	2005	Rank	2019	Rank
Eastern Region	Beijing	0.182	Low degree	0.639	Medium and high degree
	Tianjin	0.260	Medium and low degree	0.034	Low degree
	Hebei	0.522	Medium degree	0.571	Medium degree
	Shanghai	0.191	Low degree	0.263	Medium and low degree
	Jiangsu	0.277	Medium and low degree	0.488	Medium degree
	Zhejiang	0.482	Medium degree	0.589	Medium degree
	Fujian	0.402	Medium degree	0.479	Medium degree
	Shandong	0.519	Medium degree	0.514	Medium degree
	Guangdong	0.457	Medium degree	0.497	Medium degree
	Hainan	0.485	Medium degree	0.562	Medium degree
	Average	0.378	Medium and low degree	0.464	Medium degree
Central Region	Shanxi	0.173	Low degree	0.499	Medium degree
	Anhui	0.525	Medium degree	0.640	Medium and high degree
	Jiangxi	0.577	Medium degree	0.633	Medium and high degree
	Henan	0.504	Medium degree	0.650	Medium and high degree
	Hubei	0.653	Medium and high degree	0.714	Medium and high degree
	Hunan	0.626	Medium and high degree	0.699	Medium and high degree
	Average	0.510	Medium degree	0.639	Medium and high degree
Western Region	Guangxi	0.506	Medium degree	0.609	Medium and high degree
	Chongqing	0.510	Medium degree	0.685	Medium and high degree
	Sichuan	0.624	Medium and high degree	0.678	Medium and high degree
	Guizhou	0.533	Medium degree	0.527	Medium degree
	Yunnan	0.487	Medium degree	0.590	Medium degree
	Tibet	0.279	Medium and low degree	0.511	Medium degree
	Shaanxi	0.141	Low degree	0.419	Medium degree
	Gansu	0.142	Low degree	0.307	Medium and low degree
	Qinghai	0.234	Medium and low degree	0.482	Medium degree
	Ningxia	0.027	Low degree	0.648	Medium and high degree
	Xinjiang	0.442	Medium degree	0.377	Medium and low degree
	Inner Mongolia	0.575	Medium degree	0.696	Medium and high degree
	Average	0.375	Medium and low degree	0.544	Medium degree
Northeast Region	Liaoning	0.586	Medium degree	0.666	Medium and high degree
	Jilin	0.446	Medium degree	0.604	Medium and high degree
	Heilongjiang	0.495	Medium degree	0.725	Medium and high degree
	Average	0.509	Medium degree	0.665	Medium and high degree
Average		0.415	Medium degree	0.548	Medium degree

), and the integration status ranged between low and medium–high. No prefecture or municipality was categorized as having achieved deep integration. Hubei, Hunan, and Sichuan Provinces showed a higher level of industry integration than the national level, while Tianjin, Shanghai, and Gansu fell below the national level (

Table 5. Changes in the levels of forestry industry integration by province.

Time	Provinces/Number	Low Degree	Medium and Low Degree	Medium Degree	Medium and High Degree
2005	Provinces	Beijing, Shanghai, Shanxi, Shaanxi, Gansu, Ningxia	Tianjin, Jiangsu, Tibet, Qinghai	Hebei, Zhejiang, Fujian, Shandong, Guangdong, Hainan, Anhui, Jiangxi, Henan, Guangxi, Chongqing, Guizhou, Yunnan, Xinjiang, Inner Mongolia, Liaoning, Jilin, Heilongjiang	Hunan, Hubei, Sichuan
	Number	6	4	18	3
2019	Provinces	Tianjin	Shanghai, Gansu, Xinjiang	Hebei, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan, Shanxi, Guizhou, Yunnan, Tibet, Shaanxi, Qinghai	Beijing, Anhui, Jiangxi, Henan, Hubei, Hunan, Guangxi, Chongqing, Sichuan, Ningxia, Inner Mongolia, Liaoning, Jilin, Heilongjiang
	Number	1	3	13	14

). In terms of the inter-annual change index, from 2005 to 2019, the forestry industry integration index of Tianjin, Shandong, Guizhou, and Xinjiang decreased, while that of the other 27 provinces and cities increased. Tianjin’s integration index decreased the most, at 0.226. The number of provinces experiencing low integration decreased from 6 to 1, the number of provinces experiencing medium and low integration decreased from 4 to 3, the number of provinces experiencing medium integration decreased from 18 to 13, and the number of provinces at medium and high integration levels increased from 3 to 14 between 2005 and 2019.

Most provinces showed an upwards trend in the value of the forestry industry index from 2005 to 2019, except for Tianjin, Shandong, Guizhou, and Xinjiang. The level of forestry industry integration improved on the whole, but the highest level of integration remained at the medium and high level, and the integration index failed to break through 0.73. The level of integration in some provinces was unstable, indicating that the forestry industry integration has not yet entered the mature development stage in most provinces. For industry integration development to play an effective role in the economy, further efforts should be made to vigorously promote the level of forestry industry integration development.

4.2. Analysis and Discussion of the Spatial Evolution Characteristics

To more clearly illustrate their spatial evolution characteristics in 31 provinces in China from 2005 to 2019, ArcGIS software was used to create a sub-map of the levels of forestry industry integration. The interval division standard for the industry integration level was divided into four categories with breakpoints of 0.2, 0.4, 0.6, and 0.8, and a color scheme was designed with a gradient from light to dark to represent different integration levels (Figure 5).

In terms of spatial pattern, the level of forestry industry integration in different areas showed obvious regional characteristics, with significant differences between provinces and regions. In 2005, the majority of provinces showed level III integration. Only three provinces and cities reached level IV, which were scattered in the Central and Western Regions. Hubei showed the highest integration level, at 0.652. By 2019, the number of provinces and cities with integration levels below level III dropped to 17, but the number still exceeded half of the total. Provinces with integration levels above IV showed a “strip” distribution, mainly concentrated in the Central and Northeast Regions. The integration index values of Heilongjiang, Hunan, and Hubei were higher than in other provinces.

The grades of 11 provinces and cities remained unchanged over the study period, while the grades of 20 provinces and cities increased or decreased, except Tianjin and Xinjiang, which decreased from II and III to I and II, respectively. Other provinces and cities showed varying degrees of increase. The provinces in which the forestry industry at IV reached medium–high integration are mainly distributed in the Central and Northeast Regions, while provinces in which the forestry industry is located at the medium and low level of integration are mainly distributed in the Eastern and Northwest Regions.

In general, the integration index and degree of integration of different provinces evolved differently over the study period. The forestry industry integration index increased on the whole both for China and for its four major regions. The forestry industry integration level differed in the Northeast, Central, Western, and Eastern Regions. The overall integration index and degree of Central and Northeast Regions were higher than those of the Western and Eastern Regions. Most provinces showed medium or medium–high integration. The level of integration declined in a few provinces but increased in most; at the national level, it improved.

4.3. Analysis and Discussion of the Spatial–Temporal Correlation

(1)

Global autocorrelation

In general, China’s provincial forestry industry integration showed an obvious spatial correlation pattern. Except for 2008–2009 and 2018–2019, all other years were significant at the 10% level, at least. In effect, forestry industry integration development had a centralized spatial distribution for most years of the study period; the provinces and regions with a high (low) level of forestry industry integration had high (low) neighborhoods. We also found that the positive spatial correlation pattern of provincial forestry industry integration changed from strong to weak over time.

From 2005 to 2008, the global Moran’s I index showed a downward trend, though it was greater than 0 in general, indicating a concentrated distribution trend in provincial forestry industry integration, though the degree became weaker. From 2009 to 2012, the global Moran’s I index was greater than 0 and trended upward, indicating that the positive spatial correlation pattern of forestry industry integration was constantly strengthened and that there was a certain synergy in the integration across various provinces and regions.

However, the global Moran’s I value dropped significantly to 0.036 between 2013 and 2019 and failed to pass the significance test, indicating that the spatial positive correlation of provincial forestry industry integration had gradually weakened or even disappeared (

Table 6. Moran’s I index of China’s forestry industry integration in 2005–2019.

Index	2005	2006	2007	2008	2009	2010	2011	2012
Moran’s I	0.230 **	0.214 **	0.157 *	0.080	0.115	0.128 *	0.139 *	0.177 **
Z value	2.198	2.083	1.577	0.951	1.236	1.357	1.453	1.788
p-Value	0.014	0.019	0.057	0.171	0.108	0.087	0.073	0.037
Index	2013	2014	2015	2016	2017	2018	2019	2005–2019
Moran’s I	0.239 **	0.236 **	0.169 **	0.183 **	0.130 *	0.046	0.036	0.211 **
Z value	2.300	2.285	1.735	1.856	1.374	0.736	0.622	2.032
p-Value	0.011	0.011	0.041	0.032	0.085	0.231	0.267	0.042

** Significant at the 5% level; * significant at the 10% level.

). This may be due to the different practical needs and priorities in promoting forestry-related economic development, adjusting the industrial structure of forestry, promoting technological progress, and implementing environmental regulations in various provinces and regions after 2013. Before 2013, the high-value areas of forestry industry integration effectively promoted integration in the forestry industries of neighboring regions through resource sharing, factor flow, and technology transfer. The establishment of a new spatial correlation pattern has yet to be achieved.

(2)

Local autocorrelation

According to the local Moran’s I scatter chart (Figure 6), 67.74% of China’s provincial forestry industry integration showed a positive correlation in geographical space in 2005, with 45.16% of provinces following the HH model and 22.58% following the LL model. In 2019, 58.06% of China’s provincial forestry industry integration showed a positive correlation in geographical space, with the proportion of provinces in the HH mode accounting for 38.71% and the LL mode accounting for 19.35%. The slope of the Moran’s I scatter chart corresponds to the Moran’s I value; a larger slope indicates stronger spatial correlation. Comparing the slopes in the chart shows where they were positive in both years but higher in 2005 than in 2019, indicating that while the integration of the provincial forestry industry was positively correlated in geographical space, the intensity of the spatial agglomeration weakened over time.

From the perspective of spatial evolution, Liaoning, Jilin, Heilongjiang, Anhui, Jiangxi, Hubei, Hunan, Chongqing, and Yunnan (mainly in the Northeast and Central Regions) followed the HH model. These provinces showed not only a high level of industry integration but also promoted development in neighboring regions. The LL clusters were mostly concentrated in Shanghai, Gansu, and Qinghai, where integration and development need to be improved; these areas also appear to have not cooperated effectively with neighboring provinces, creating a low level of inter-regional agglomeration. The LH cluster area is mainly represented by Shanxi and Fujian. Although Sichuan and Hebei showed high levels of integration and development, they did not exchange frequently with surrounding provinces, which restricted any improvement in the integration of neighboring provinces following the HL model.

The above analysis reveals a close relationship between spatial correlation and forestry economic development, indicating that spatial factors have become important in the development of forestry industries in various regions. Overall, China’s forestry industry integration has a significant positive spatial correlation. Regions with high levels of forestry industry integration are clustered together in space, while regions with low levels also show a tendency to agglomerate. However, the spatial correlation shows a trend from strong to weak, in general. Therefore, it is necessary to strengthen the relevant mechanisms of cross-border cooperation and benefit sharing to improve the level of the integrated development of the forestry industry.

5. Problems in the Integrated Development of the Forestry Industry

Although the precise levels in most provinces and cities improved, China’s overall forestry industry integration development is still in its initial stage, and the degree of integration remains moderate to low. The overall integration development is not ideal, and there is room for further improvement. Common problems in China’s forestry industry integration development include the following.

(1)

There is an inadequate and imbalanced level of integrated development of the forestry industry. Most provinces with large forestry planting areas have medium or low degrees of integration, with a serious imbalance in the spatial distribution. Currently, regions with high levels of forestry industry integration and development are concentrated in the Central Region. Although over half of China’s provinces have reached a moderate or higher level of industry integration, most of the top 10 provinces in China’s understory economic forest planting area still have only a moderate integration level (including Yunnan, Hebei, Hainan, and Shaanxi). The level of industry integration in most regions with large understory economic planting areas have substantial room for improvement. Further, there are still many shortcomings in the utilization of forestry industrial resources and the exploitation of their potential. The presently imbalanced spatial distribution of China’s forestry industry integration makes it difficult to achieve the goal of industrial development and ecological prosperity, particularly in forested and mountainous areas which depend on their forestry industries to alleviate poverty. The problem of low forestry industry integration levels in these provinces has yet to be resolved, making it difficult for the forestry industry to develop in these areas.

(2)

The structural layout of forestry industry integration development is unreasonable. The proportion of understory planting and collecting industry integrated products is oversized, the growth rate of the wood processing and manufacturing industry is slow, and the development of forest ecotourism and forestry production technology management industry products is severely lagging behind those of other industries, which has created an unreasonable structure of forestry industry integration development; this hinders any improvement in industry integration levels and impedes the further development of the forestry industry.

The proportion of the understory planting and collecting industry is too high, which reflects China’s policies that encourage the planting of economic forests in recent years. However, it also reflects problems in China’s forestry industry, such as over-extensive management and the low added value of products, especially in areas with low levels of integration and where forest farmers in the economic forest planting and collection industry are still engaged in selling raw materials. The proportion of the wood processing and manufacturing industry is low in most regions, which indicates widespread low levels of processing and manufacturing in the forestry industry; the deepening of forest products should be encouraged. A lack of processing types for forest products prevents the forestry processing and manufacturing industry chain from extending, so it remains in the stage of primary forest product processing. A lack of processing technology and outdated manufacturing equipment further hinders the forestry industry from converting raw materials into products, which restricts economic benefits.

The forest ecotourism and production technology management industries had the highest added value among the industries we analyzed. Their industrial development can accelerate the application of advanced technology, which has a strong driving effect on the planting and collecting and the processing and manufacturing industries. Although the proportions of forest ecotourism and forestry production technology management industries in the forestry industry have increased, they are still relatively low, which indicates significant space for transformation in the layout of the forestry industry integration structure. To rationalize this structure, it is necessary to further activate forestry resources and strengthen the level of forestry industry integration development.

(3)

The driving force behind forestry industry integration is limited. The output value of China’s forestry integrated products increased overall during the study period, but the growth rate trended downward. This suggests that the economic benefits derived from the development of forestry industry integration are declining. At present, China’s forestry industry integration lacks the driving capacity required. In addition, the trend in China’s forestry industry integration level suggests that the driving force of forestry industry integration among neighboring regions is weakening, particularly in the Central Region, where the forestry industry integration level is high. However, its influence on improving the development level of forestry industry integration in neighboring regions is limited. This is primarily due to the limited mobility of labor, technology, capital, and other essential elements among China’s forestry industrial regions, as well as the poor foundation of forestry development in regions with low levels of forestry industry integration, which hinders the full diffusion and flow of these elements. High-value regions are unable to serve as central points and spread to surrounding low-value regions, which is necessary to drive neighboring provinces towards higher levels of industry integration.

6. Conclusions and Implications

6.1. Conclusions

(1)

The total output value of China’s five major forestry integrated products and their individual segments showed growth, with forest ecotourism experiencing the most significant growth, while the forestry production technology management industry is developing at a relatively slower pace. However, the product development was imbalanced over the study period, with a concentration in the understory planting and collecting and wood processing and manufacturing industries. The proportion of the forestry production technology management industry with supporting services remained small, and its related technology and production management services with high added value were not well-developed, leaving room for improvement and further integration.

(2)

From 2005 to 2019, China’s forestry industry integration index increased from 0.415 to 0.548, at a rate of 32.05%. Despite this growth, the level of integration remains at only a moderate level, thus necessitating measures to enhance and regulate it. Although the integration index values of most provinces, with the exception of Tianjin, Shandong, Guizhou, and Xinjiang, have increased, they failed to surpass 0.73, representing a significant gap from high integration. The level of integration development remains in the early growth stage. The degree of integration across the four main regions of the country improved, but there were differences in the level of integration in a northeast–central–west–east cascade. This level was typically higher in the Central and Northeast Regions than in the Eastern and Western Regions. The Eastern and Western Regions progressed from “medium and low integration” to “medium integration”, while the Central and Northeast Regions advanced from “medium integration” to “medium and high integration”.

(3)

The spatial correlation analysis revealed that the integration of China’s forestry industry was significantly influenced by spatial factors at both the overall and local levels. The global autocorrelation analysis showed a positive spatial correlation in the integration of China’s forestry industry, but the strength of the correlation varied across different regions. Local autocorrelation analysis revealed that provinces in Northeast and Central China had high levels of forestry industry integration, as indicated by the presence of HH clusters. In contrast, provinces such as Shanghai, Gansu, and Qinghai had low levels of integration manifesting as LL clusters. To enhance the level of integrated development of the forestry industry, it is necessary to establish effective mechanisms for cross-border cooperation and benefit sharing.

(4)

There are issues with China’s forestry industry integration, including an inadequate and imbalanced development of said integration, an unreasonable layout of its development structure, and insufficient driving capacity. Therefore, there were stage and regional differences in the evolution of forestry industry integration. Most provinces with large forestry planting areas remained at medium or low levels of integration, with a serious imbalance in spatial distribution. The proportion of the understory planting and collecting industry was too large among all integrated products, the development of the wood processing and manufacturing industry was slow, and the forest ecotourism and forestry production technology management industries were seriously lagging behind others. The structural layout of the forestry industry integration development was found to be unreasonable, which hinders any improvement to the level of forestry industry integration. Additionally, the change trend of the sub-map of the forestry industry integration level showed that the mobility of labor, technology, capital, and other key elements among regions with forestry industries declined. Regions with high levels of forestry industry integration showed a limited effect in promoting the levels of integration and development in neighboring regions.

6.2. Implications

(1)

Given the currently low level of development of China’s forestry industry integration, it is necessary to optimize the forestry industry structure by focusing on the innovation of forest products, emphasizing leisure tourism, technical services, and other aspects. This will help to create an efficient and comprehensive industry integration development model that can increase the proportion of new forms of business, such as the forest ecotourism and forestry production technology management industries, while rationalizing the structural layout of forestry industry integration.

(2)

Considering the regional differences in integration levels, including a “high in the middle and low in the east” phenomenon, each region should leverage its policy advantages and revitalize its high-quality forest resources. This can be accomplished by extending the value chain of resource endowment, deepening the integration of the forestry industry, and improving the comprehensive level of the industry. It is important to continuously improve the cross-regional cooperation benefit-sharing mechanism and gradually reduce the developmental differences among regions.

(3)

To promote the integrated development of the forestry industry, it is necessary to fully leverage the agglomeration effect of areas with already high levels of integration and to strengthen regional exchange and cooperation. For regions with large differences in integration and development, regular experience exchange meetings should be held to promote the free flow of natural resources and labor resources, improve the driving capacity of regions with high integration levels to adjacent regions and, ultimately, realize common development. For regions with similar integration and development, collective training for forestry technology personnel and friendly competitions could be organized to motivate various regions to strengthen their forestry industries.

(4)

At the national level, improving the macroeconomic regulation capacity of the government and the relevant public service system is essential for promoting forestry industry integration. A strong policy system and public services can improve the operational efficiency of the forestry industry, reduce hidden costs, and maximize economic benefits. Firstly, a policy system should be established to promote forestry industry integration development. This can include support in the form of technology project approval, financial support, and financing policies to ensure successful policy implementation. Secondly, regulations on forestry industry integration development should be introduced to solve problems related to resource depletion, food safety, and ecological health. This can be achieved by strictly controlling the quality standards of integrated forestry products, standardizing flow channels, and reducing negative externalities through product certification, inspection, and supervision, thus safeguarding human health and the development of ecological civilization.

(5)

It should be noted that the research on forestry industry integration is still in its early stages, and there are advantages and disadvantages to existing industry integration methods. A unified research method for industry integration has not yet been established. Based on the availability of data and drawing on measurement methods used for agricultural industry integration, economic forest industry integration, animal husbandry industry integration, and existing forestry industry integration, this paper selected the Herfindahl index to measure forestry industry integration.

The Herfindahl index method measures the market share of the output value of various industries within the forestry industry to reflect the dispersion of the forestry industry. It can reveal the integration efficiency and integration effect in the process of integration and development of the forestry industry as a whole. Additionally, it can accurately reflect the integrity of the forestry industry integration chain, the balance and adequacy of the integration and development of the three industries, and the circulation of resource elements between industries. Although this method cannot fully reflect the fusion information generated by the intersection and penetration between the forestry industry and other industries, which may cause certain deviations in the measurement results, it has been widely used in cultural tourism, major agricultural, forestry, and more subdivided industries such as animal husbandry, which indicates strong universality. Moreover, the data required to operate this method are easy to obtain, their processing is relatively convenient, and they have strong operability, which makes it a highly suitable method under the existing conditions.

This paper adopted the output value of forestry industry integration to measure the level of forestry industry integration, but the classification and calculation of forestry industry output values are still relatively rough. In this study, only the categories in the China Forestry and Grassland Statistical Yearbook and China Forest Resources Report (2005–2019) were used. Due to the lack of data, no further refinement was performed. In the future, with increasingly complete data and continuous improvements in measurement methodologies, we will further explore more reasonable and effective methods to improve upon our present work. This may include segmenting the integrated forestry industry for more precise research, conducting a comprehensive analysis considering the relevant impact of technology diffusion on industry integration via Herfindahl index, and researching in key areas where conditions permit to support theoretical analysis and practical development, which may improve the accuracy of our conclusions.