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), 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). 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). 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.