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Article

Landscape Pattern and Succession of Chinese Fir Plantations in Jiangle County, China

by
Zhihui Zhang
1,
Yongde Zhong
1,2,*,
Lingfan Yang
3,
Dali Li
1,4,
Hui Tang
1 and
Jianghua He
1
1
Forestry College, Central South University of Forestry and Technology, Changsha 410004, China
2
State Forestry Administration Engineering Research Center for Forest Tourism, National Forestry and Grassland Administration, Changsha 410004, China
3
Beijing Zoo, Beijing 100044, China
4
Academic Affairs Office, Hunan Open University, Changsha 410004, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(19), 12497; https://doi.org/10.3390/su141912497
Submission received: 18 August 2022 / Revised: 17 September 2022 / Accepted: 26 September 2022 / Published: 30 September 2022
(This article belongs to the Special Issue Environmental Development and Sustainability: Monitoring, Assessment, and Adaptation)
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Abstract

:
Since the early 1980s, in southern China, evergreen broad-leaved forests have been replaced by Chinese fir plantations on a large scale. By analyzing the dynamic change characteristics of the landscape pattern of Chinese fir plantations in the case study, the paper explored the current status and development trend of the landscape pattern of Chinese fir plantations after 40 years of manual intervention and natural succession. The paper, based on the three-period survey data on forest resources in 2010, 2015, and 2020, analyzed the dynamic changes of the landscape pattern of Chinese fir plantations from 2010 to 2020 and, by using a transition matrix and landscape index, simulated and predicted the landscape pattern of Chinese fir plantations in Jiangle County in 2025 by constructing a CA–Markov model with Jiangle County, Fujian Province, China, as the study area. The results showed that the landscape of Chinese fir plantations is the main component of the forest landscape in southern China, accounting for 12%. The landscape quality of Chinese fir plantations degraded, mainly shown in the facts that the Chinese fir plantations were juvenile from 2010 to 2020, and that the young and middle-aged forests became the main part of the landscape of Chinese fir plantations, accounting for 54.8%. The landscape area of Chinese fir plantations showed an increasing trend, which mainly came from other coniferous forests, other woodlands, non-woodlands and non-wood forests, and the replaced Chinese fir plantations were mainly eroded by bamboo forests. The evergreen broad-leaved forests, a kind of zonal vegetation, have been effectively protected in the past 10 years. In the future, the total area of Chinese fir plantations will continue to expand, and a small part of them will continue to be eroded by bamboo forests. In order to improve the landscape quality of Chinese fir plantations, it is necessary to adjust the age group structure of Chinese fir plantations, expand the proportion of mature forests, and, meanwhile, continue to protect evergreen broad-leaved forests and curb the expansion of bamboo forests.

1. Introduction

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is a representative fast-growing species in the subtropical regions of China [1] and a unique species in southern China [2] with a long history. The key reason why the body of Xin Zhui, unearthed at Mawangdui in Changsha, Hunan, did not rot after more than 2100 years, is because she was buried in a coffin made of Chinese fir wood [3], indicating that fir has excellent corrosion resistance and antibacterial properties. In Chengbu Miao Autonomous County, Hunan Province, there is a group of Chinese fir that are thousands of years old, planted in the Eastern Jin Dynasty, containing a total of 38 ancient trees, all planted artificially [4]. The economic value of fir is much higher than that of other forest trees, accounting for 81.47% of the total economic value and the economic value per unit area of storage [5]. Due to its high economic value, Chinese fir has been used for plantation forestry for over a thousand years [6], with a cumulative plantation area of over 12 million hectares [7]. For a long time, in order to pursue economic benefits, projects such as comprehensive development and utilization of forest lands and the infrastructure construction of commercial forests have been implemented. In this way, a large number of evergreen broad-leaved forests have been transformed into artificial forests with single tree species and simple stand structure [8,9,10]. After 40 years of large-scale afforestation, China has become the world’s largest country in terms of planted forests, with China’s planted forests accounting for one-third of the global planted forest area [11]. The Ninth National Forest Resources Inventory showed that the area of Chinese fir plantations reached 986.67 million hectares, with a volume of 755 million m3, accounting for one-quarter and one-third of the total area and volume of artificial arboreal forests in China, respectively. Chinese fir plantations account for 12% of the forests in southern China, second only to Pinus massoniana, and the landscape of Chinese fir plantations is the main component of the forest landscape in southern China.
Forest landscape is of great significance for maintaining regional ecological security patterns, safeguarding resource security, and promoting sustainable development [12,13]. Chinese fir plantations are the main part of the forest landscape in southern China, and the changes in their landscape pattern will have a profound impact on the forest landscape in southern China, which in turn affects ecological processes and forest succession [14]. In addition, a great number of comprehensive studies have shown that there is a correlation between landscape preferences and landscape indicators, that changes in forest landscape patterns affect the aesthetic value of forest landscapes, and that improvements in forest landscape quality not only enhance the aesthetic value of forest landscapes, but also help to improve forest quality and significantly increase forest carbon sequestration capacity [15,16,17,18].
However, there are few studies on the landscape pattern and succession of Chinese fir plantations at home and abroad. The research on Chinese fir plantations mainly focuses on the forest carbon sink and carbon storage [19,20,21,22], pest control [23], the biomass structure [24,25], ice and snow disasters, litterfall, soil fertility, mixed forests, material quality, and genetic breeding [26,27], and the study areas of rare studies involving the landscape pattern of Chinese fir are only limited to the village level or conservation areas. In addition, in the landscape category, Chinese fir is classified as “coniferous forest”, including natural fir forests and Chinese fir plantations, but there is no research on the large-scale Chinese fir plantations landscape [28,29]. Therefore, this paper explored the landscape pattern of Chinese fir plantations at the county scale, aiming to properly recognize the current situation and trends of the landscape pattern of Chinese fir plantations after 40 years of artificial intervention and natural succession and provide a reference for management of Chinese fir plantations, adjustment of local forestry policies, and policies on regional economic development in the future, which would help maintain the regional ecological security pattern, guarantee resource security, and promote sustainable development.
Fujian Province boasts the highest vegetation cover, which is around 65%, and the most complete central subtropical forest ecosystem [30]. Jiangle County enjoys the most forest resources in Fujian Province, with forest cover of 85.2%, ranking at the top of the province [31,32]. The forests of this county have the typical characteristics of mid-subtropical forest, including a variety of important coniferous timber and mixed forests [32]. According to the survey data of forest resources, the area of fir forest in Jiangle County reached 50,355.41 hectares, accounting for 33.96% of the total vegetation area in China, and it is the largest stand in Jiangle County. The area of artificial forests in the Chinese fir forests is 47,161.18 hectares, accounting for 93.65% of the total area of Chinese fir and 31.8% of the total vegetation area in China. The landscape of Chinese fir plantations is the main component of the forest landscape in Jiangle County, and the changes of their landscape pattern play a significant role in the forest landscape of Jiangle County. Therefore, the study of the changes of its landscape pattern will have great reference significance for the research of forest landscape in southern China.
First of all, based on the survey data of forest resources, the proportion of Chinese fir plantations in the forest landscape of Jiangle County was calculated to understand the status of Chinese fir plantations in the forest landscape of the whole county. Secondly, the landscape indices of Chinese fir plantations in 2010, 2015, and 2020 were calculated, respectively, for age group and non-age group, and the landscape indices were analyzed to obtain the current situation of landscape pattern of Chinese fir plantations and the trends in the past 10 years. Third, a land transition matrix was used to quantify the transformation characteristics between Chinese fir plantations and other landscape types from 2010 to 2020. Fourth, the CA–Markov model was used to predict the landscape pattern of Chinese fir plantations in 2025. Fifth, according to the results of the landscape index, land transition matrix, and simulation prediction, the status quo and trends of Chinese fir plantation landscape pattern were discussed. Finally, the practical significance of this paper was summarized, and suggestions were provided for the management of Chinese fir plantations, the adjustment of local forestry policy, and regional economic development policy in the future.

2. Materials and Methods

2.1. Study Area

Jiangle County is located in the northwest of Sanming City, Fujian Province (117°05′~117°40′ E, 26°25′~27°04′ N), at the southeastern foot of the Wuyi Mountains and downstream of the Jinxi River, a tributary of the Minjiang River, which covers an area of 2255.0 km2. The area has a subtropical monsoon climate, with an average annual temperature of 19.8 °C, an average annual rainfall of 2027 mm, and a total rainfall of 3.827 billion m3. In addition, the terrain of the county is rugged; geographical types are primarily hills and low mountains, with the lowest altitude of 73 m and the highest altitude of 1618 m (Figure 1).
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Figure 1. Geographical map of the study area.
Figure 1. Geographical map of the study area.
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2.2. Data Sources and Processing

The research data in this paper are from the forest resources survey of Jiangle County in 2010, 2015, and 2020 in the forest resources database of the State Forestry and Grassland Administration of China. By using ArcGIS 10.8 software (Esri, Redlands, CA, USA), with “Main Tree Species = 310,000” (the forestry code of Chinese fir is “310,000”) as the filter condition, the stand layers of Chinese fir forests in Jiangle County in 2010, 2015, and 2020 were filtered out and merged. In this way, the combined layer, namely all the sublots that have grown Chinese fir during 2010–2020, was obtained. Afterwards, a 5000 m linear buffer zone was made for the merged layer, for this buffer zone usually covered the surrounding environment of Chinese fir forests and met the requirements of the subsequent research on the transformation between Chinese fir plantations and other landscape types. Finally, the merged layer with the buffer zone was cut out with the complete database of Jiangle County in 2010, 2015, and 2020 to obtain the final layer, facilitating the subsequent research on the transformation between Chinese fir forests and other landscape types.

2.3. Classification of Landscape Types

The study of forest landscape patterns is based on the classification of forest landscape types, which is also a key criterion for selecting forest landscape models [33]. A forest landscape classification system was constructed based on factors such as land type [34], vegetation type [35], main tree species [28,29] and other factors, according to the characteristics of forest resources. In order to explore the landscape pattern of Chinese fir plantations, this paper, based on previous studies, divided the main tree species and land types in the 5000 m buffer zone of the merged layer into nine types of landscapes, including “evergreen broad-leaved forest”, “deciduous broad-leaved forest”, “other coniferous forest”, “shrubland”, “non-wood forest”, “non-woodland”, “other woodland”, “bamboo forest”, and “Chinese fir plantation”.

2.4. Research Methods

2.4.1. Landscape Index

Landscape indicators are common tools for reflecting the structural composition and spatial configuration of the landscape pattern [36,37], which has been used in previous studies extensively [38,39,40,41]. As forest landscape patterns are complex and cannot be measured using a single indicator, a set of landscape indicators is usually used to identify forest landscape patterns [42]. In order to characterize the landscape pattern of Chinese fir plantations in Jiangle County from 2010 to 2020, this paper, based on previous studies [38,39,40,41,42], by using Fragstats 4.2 software (Informer Technologies Inc., Gillette, WY, USA) to calculate the landscape index, selected Total Class Area (CA), Number of Patch (NP), Largest Patch Index (LPI), Edge Density (ED), Landscape Shape Index (LSI), and Aggregation Index (AI) (Table 1).

2.4.2. Transition Matrix

The land transition matrix can quantify the transition area and transition probability between different land-use types [43] and is widely used in studies related to land transition changes. In the study of dynamic changes in forest landscape patterns, the transition matrix can effectively represent the relationship between the quantitative changes of different landscape types in two periods, analyze the structural characteristics of regional landscape changes and the change direction of each type, visually reflect the structure of landscape types in a certain region in two periods, and reflect the transition status of each landscape type during the study period [34].The paper used ArcGIS 10.8 software to calculate the transition status of each landscape type.
The calculation method of the proportion of the same landscape area is as follows: Pij = Sij/Ts.
S ij   = [ S 11   S 12   S 13    ···  S 1 n S 21   S 22   S 23    ···  S 2 n S 31   S 32   S 33    ···  S 3 n   ⋮   ⋮   ⋮   ⋮   S n 1   S n 2   S n 3    ···  S n n ]
where Pij indicates the transitional area from land-use type i to type j, where each element in the matrix is characterized, assuming that Pij is non-negative and ∑ j = 1 n P i j = 1 .

2.4.3. CA–Markov Model

(1)
CA model
The CA model is the cellular automata model, which consists of four parts: unit, state, proximity range, and transition rules. The CA model is discrete in time, space, and state. Any cell variable has only limited and discrete states and is synchronously corrected according to the same transition rules. The rules of state change are local features in time and space. The general CA model is: S = (t + 1) = f(S(t),N). In the formula, S is the state set of discrete and finite cells, N is the neighborhood of the cell, T and T + 1 represent two different moments, and f is the cellular state transition rule.
(2)
Markov model
The Markov model, also known as the Markov chain, is an important method used in forest ecology research for the simulation and prediction of dynamic processes in the spatial pattern of the landscape. Without aftereffect, the Markov model is widely used to simulate land-use dynamics. In the study of land-use/cover change, using the Markov process, the calculation formula for predicting land-use/cover change is:
S(T) = Pij + S(T0)
P i j   = [ P 11   P 12   P 13     · · ·   P 1 n P 21   P 22   P 23     · · ·   P 2 n P 31   P 32   P 33     · · ·   P 3 n   ⋮   ⋮   ⋮   ⋮   P n 1   P n 2   P n 3     · · ·   P n n ]  
In the formula: S (T) and S (T0) are the state of the land-use structure at times T and T0, respectively, Pij is the state transition matrix, and 0 < Pij < 1.
Both the CA model and the Markov model are dynamic models with discrete time and state. However, the Markov model does not introduce spatial variables, while the state variables of the CA model are closely related to the spatial position. Both have certain limitations [14]. The CA–Markov model effectively combines the ability of the CA model to simulate the spatial changes of complex systems and the advantages of the long-term prediction of the Markov model, and can effectively simulate and predict the spatial changes of forest landscape patterns [44,45]. The paper used the CA–Markov model in IDRISI software to predict the landscape pattern of Chinese fir plantations in 2025.

3. Results

3.1. Landscape Pattern Changes of Chinese Fir Plantations

On the whole (Table 2), the CA and LPI of Chinese fir plantations showed an increasing trend, while the NP showed a downtrend, indicating that the area of Chinese fir plantations increased, and the fragmentation decreased. The AI showed an increasing trend, indicating that the aggregation degree of Chinese fir plantations increased. The ED and LSI showed an increasing trend, indicating that the patch shapes of the Chinese fir plantations were increasingly complex. From the perspective of different age groups (Table 3), according to CA, young forests, middle-aged forests, and over-mature forests all showed an increasing trend, among which the areas of young and middle-aged forests increased significantly, while near-mature forest and mature forest both showed a large decreasing amount. According to NP, young forests, middle-aged forests, and over-mature forests all showed an increasing trend, and the number of patches in young and middle-aged forest increased significantly, while both near-mature and mature forests showed a downtrend. According to LPI, young and middle-aged forests showed an increasing trend, while near-mature, mature, and over-mature forests showed a downtrend. Overall, these indicators showed an increase in the area and a decrease in fragmentation of young, middle-aged, and over-mature forests.
According to ED, the aggregation index of different age groups was low with slight fluctuations, indicating that the Chinese fir plantations in different age groups were relatively stable with a low degree of patch cutting between each other, low-intensity space expansion, and low-frequency exchange of matter and energy. Young, near-mature, and mature forests showed a downtrend, while middle-aged and over-matured forests showed an increasing trend. According to LSI, young and middle-aged forests showed an increasing trend, while near-mature forests, mature forests, and over-mature forests showed a downtrend, indicating that the patch shapes of young and middle-aged forests were becoming increasingly complex, while the patch shapes of near-mature forests, mature forests, and over-mature forests tended to be simple. According to AI, young forests and middle-aged forests showed an increasing trend, while near-mature forests, mature forests, and over-mature forests showed a downtrend, indicating that the aggregation degree of young and middle-aged forests increased with enhanced connectivity, and the aggregation degree of near-mature forests, mature forests, and over-mature forests decreased with weakened connectivity.

3.2. Changes in Land Transfer

From 2010 to 2015 (Table 4), the landscape types transferred to Chinese fir plantations were other woodland > other coniferous forest > non-woodland > evergreen broad-leaved forest > bamboo forest > non-wood forest > shrub forest > deciduous broad-leaved forest, among which mainly were other woodlands and other coniferous forests, with a transfer area of 2763.9 hectares and 2184.56 hectares, respectively. The landscape types transferred from Chinese fir plantations were other woodland > other coniferous forest > non-woodland > evergreen broad-leaved forest > bamboo forest > non-wood forest > deciduous broad-leaved forest > shrub forest, among which mainly were other woodlands and other coniferous forests, with a transfer area of 1581.67 hectares and 1468.63 hectares, respectively.
In 2015, the area of Chinese fir plantations was 53,712 hectares, an increase of 1694 hectares compared with that in 2010 (Figure 2). According to the transfer-in and transfer-out area of Chinese fir plantations (Figure 3a, Figure 4a and Figure 5a), the area growth came from other woodlands, other coniferous forests, evergreen broad-leaved forests, and shrub forests, among which other woodlands and other coniferous forests were the main sources, with 1182.23 hectares and 715.94 hectares, respectively, and evergreen broad-leaved forests and shrub forests were secondary sources, with 74.79 hectares and 19.69 hectares, respectively. In addition, non-woodlands, non-wood forests, deciduous broad-leaved forests, and bamboo forests eroded part of Chinese fir plantations, among which non-forest lands eroded Chinese fir plantations with the largest area of 275.33 hectares, and non-wood forests, deciduous broad-leaved forests, and bamboo forests eroded a small amount of Chinese fir plantations, with 68.23 hectares, 45.06 hectares, and 27.89 hectares, respectively.
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Figure 2. Landscape pattern of Chinese fir plantations in Jiangle County from 2010 to 2020.
Figure 2. Landscape pattern of Chinese fir plantations in Jiangle County from 2010 to 2020.
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Figure 3. Statistical chart of the transfer−in and transfer−out of the landscape area of Chinese fir plantations in Jiangle County from 2010 to 2020. (a) is from 2010 to 2015, and (b) is from 2015 to 2020.
Figure 3. Statistical chart of the transfer−in and transfer−out of the landscape area of Chinese fir plantations in Jiangle County from 2010 to 2020. (a) is from 2010 to 2015, and (b) is from 2015 to 2020.
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From 2015 to 2020 (Table 5), the landscape types transferred to Chinese fir plantations were other coniferous forest > other woodland > non-wood forest > evergreen broad-leaved forest > non-woodland > bamboo forest > deciduous broad-leaved forest > shrub forest, among which, mainly, were other coniferous forests and other woodlands, with a transfer area of 2443.3 hectares and 1637.05 hectares, respectively. The landscape types transferred from Chinese fir plantations were other woodland > other coniferous forest > evergreen broad-leaved forest > bamboo forest > non-woodland > non-wood forest > deciduous broad-leaved forest > shrub forest, among which, mainly, were other woodlands and other coniferous forests, with 1250.67 hectares and 1204.78 hectares, respectively.
In 2020, the area of Chinese fir plantations was 56,448 hectares, an increase of 2736 hectares compared with that in 2015 (Figure 2). According to the transfer-in and transfer-out area of Chinese fir plantations (Figure 3b, Figure 4b and Figure 5b), the area growth came from other coniferous forests, non-wood forests, other woodlands, non-woodlands, deciduous broad-leaved forests, and shrub forests, among which other coniferous forests and non-wood forests were the main sources, with 1238.52 hectares and 863.5 hectares, respectively. Non-woodlands and other woodlands were the secondary sources, with 386.38 hectares and 170.8 hectares, respectively. Deciduous broad-leaved forests and shrub forests were less, with 94.42 hectares and 10.09 hectares, respectively. In addition, bamboo forests and evergreen broad-leaved forests eroded part of Chinese fir plantations, with 314.83 hectares and 178.29 hectares, respectively.
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Figure 4. Distribution map of landscape transfer-in and transfer-out of Chinese fir plantations in Jiangle County from 2010 to 2020.
Figure 4. Distribution map of landscape transfer-in and transfer-out of Chinese fir plantations in Jiangle County from 2010 to 2020.
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Figure 5. Distribution map of landscape types converted to Chinese fir plantations in Jiangle County from 2010 to 2020. For the convenience of picture expression, the landscape types in the legend of this figure are replaced by acronyms: evergreen broad-leaved forest—EBF; non-wood land—NL; shrubland—S; non-wood forest—NF; deciduous broad-leaved forest—DBF; other woodland—OW; other coniferous forest—OCF; Chinese fir plantations—CFP; bamboo forest—BF.
Figure 5. Distribution map of landscape types converted to Chinese fir plantations in Jiangle County from 2010 to 2020. For the convenience of picture expression, the landscape types in the legend of this figure are replaced by acronyms: evergreen broad-leaved forest—EBF; non-wood land—NL; shrubland—S; non-wood forest—NF; deciduous broad-leaved forest—DBF; other woodland—OW; other coniferous forest—OCF; Chinese fir plantations—CFP; bamboo forest—BF.
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3.3. Spatial Distribution

Analysis of the elevation of fir plantation forest distribution (Figure 6) showed that fir plantation forests in Jiangle County were mainly distributed in areas from 119 m to 1350 m above sea level, except for high-elevation areas and non-forested areas throughout the county. In addition, the patches of new Chinese fir plantations from 2010–2015 and 2015–2020 were mainly located between the original fir plantation patches and expanded outward from the edges of the original patches. The patches of newly added Chinese fir plantations in 2010–2015 were located in the area of 129–1134 m above sea level (Figure 7a), and the patches of newly added Chinese fir plantations in 2015–2020 were located in the area of 119–1350 m above sea level (Figure 7b).
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Figure 6. Altitude distribution map of Chinese fir plantations in Jiangle County from 2010 to 2020.
Figure 6. Altitude distribution map of Chinese fir plantations in Jiangle County from 2010 to 2020.
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Figure 7. Altitude distribution of newly added Chinese fir plantations in Jiangle County from 2010 to 2020.
Figure 7. Altitude distribution of newly added Chinese fir plantations in Jiangle County from 2010 to 2020.
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3.4. Simulation of Landscape Pattern Succession of Chinese Fir Plantations in Jiangle County

The paper, taking the landscape distribution of Chinese fir plantations in Jiangle County in the year of 2015 as initial data, used the 2010–2015 fir plantation landscape transition matrix to obtain the modeling results of the Chinese fir plantations landscape in Jiangle County in 2020 (Figure 8a).
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Figure 8. Prediction results of landscape pattern of Chinese fir plantations in Jiangle County in 2020 and 2025.
Figure 8. Prediction results of landscape pattern of Chinese fir plantations in Jiangle County in 2020 and 2025.
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The modeling results of the Chinese fir plantations forest in Jiangle County in 2020 were compared with the real results of the landscape pattern of the fir plantation in Jiangle County in 2020 to evaluate the accuracy of the modeling results, and the resulting Kappa index was 0.8676, indicating that the modeling results of the CA–Markov model were better and feasible. Therefore, taking the landscape distribution of Chinese fir plantations in Jiangle County in the year of 2020 as initial data, the paper then used the 2015–2020 fir plantation landscape transition matrix to obtain the modeling results of the Chinese fir plantations landscape in Jiangle County in 2025 (Figure 8b).
According to the forecast (Table 6), during 2020–2025 the landscape types transferred to Chinese fir plantations will be non-woodland > other coniferous forest > evergreen broad-leaved forest > bamboo forest > non-wood forest > other woodland > shrub forest > deciduous broad-leaved forest, among which, mainly, will be other coniferous forests and other woodlands, with a transfer area of 670.87 hectares and 584.93 hectares, respectively. The landscape types transferred from Chinese fir plantations will be non-woodland > other coniferous forest > evergreen broad-leaved forest > bamboo forest > other woodland > non-wood forest > shrub forest > deciduous broad-leaved forest, among which, mainly, will be non-woodlands and other coniferous forests, with a transfer area of 617 hectares and 574.78 hectares, respectively. In 2025, Chinese fir plantations will cover an area of 56,585.07 hectares, an increase of 137.07 hectares compared with that in 2020.
In terms of the transfer-in and transfer-out area of Chinese fir plantations (Figure 9), the area growth will come from non-woodlands, non-wood forests, other woodlands, and other coniferous forests, among which non-woodlands and economic forests will be the main sources, with 53.87 hectares and 34.31 hectares, respectively. Non-wood forests, other woodlands, and other coniferous forests will be the secondary sources, with 19.85 hectares, 16.37 hectares, and 10.15 hectares, respectively. Bamboo forests will be the species that erodes the largest amount of Chinese fir plantations, while evergreen broad-leaved forests, shrub forests, and deciduous broad-leaved forests will erode a small amount of Chinese fir plantations, with 3.24 hectares, 2.64 hectares, and 0.43 hectares, respectively.
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Figure 9. Statistical chart of the transfer–in and transfer–out of the landscape area of Chinese fir plantations in Jiangle County from 2020 to 2025.
Figure 9. Statistical chart of the transfer–in and transfer–out of the landscape area of Chinese fir plantations in Jiangle County from 2020 to 2025.
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4. Discussion

The calculation results of the landscape index showed that the past 10 years have seen the degradation of landscape quality of Chinese fir plantations in Jiangle County.
From the perspective of the landscape index, in the past 10 years, the fragmentation degree of Chinese fir plantations has decreased, the aggregation degree has increased, the patch shapes have remained basically stable, and the landscape quality of Chinese fir plantations has improved. However, this is not the case. From 2010 to 2020, the proportion of young and middle-aged forests increased from 26.6% to 54.8%, near-mature and mature forests decreased from 60.7% to 30%, over-mature forests increased from 12.7% to 14.9%, a large number of mature forests were felled, and Chinese fir plantations were shown to be juvenile [46]. The newly added patches of Chinese fir plantations were mainly located between the original fir plantation patches and expanded outward from the edges of the original patches. The newly added patches of Chinese fir plantations connected with the original scattered patches into pieces, which increased the average area and aggregation degree of the patches and reduced the fragmentation degree. However, the patches expanded outward at the edge of the original patch, increasing the patch edge density and shape index. Mei Guangyi’s research [47,48] found that there is a positive correlation between the landscape quality of Chinese fir plantations and age groups, namely, the lower the age group, the lower the landscape quality. As a result, young and middle-aged forests with poor accessibility, low forest volume, and low productivity per unit area [46] became the main part of the Chinese fir plantations landscape; therefore, the landscape quality of Chinese fir plantations was significantly reduced.
From the perspective of the landscape index of each age group, NP, LPI, and AI of young forests showed an increasing trend, indicating that the planting of new Chinese fir plantations had maintained an increasing trend in the past 10 years, presenting the characteristics of concentration and a large scale. The increase of CA value and the decrease of ED value indicate that the young forest is planted artificially, which is largely controlled by humans. The landscape heterogeneity is reduced with the merger of adjacent patches in the process of area expansion. Except for ED, other landscape characteristics of the middle-aged forest maintain the same trend as that of the young forest. The increase of ED value indicates that the middle-aged forest is developed from the young forest, and after a period of time, it tends to grow naturally, and the human interference is weakened. It is worth noting that the CA and NP values of near-mature and mature forests were decreasing, and the average patch area of near-mature forests decreased from 11.1 hm2 in 2010 to 8.83 hm2 in 2020, while the average patch area of mature forests decreased from 14.72 hm2 in 2010 to 11.13 hm2 in 2020, which indicated the increase of degree of fragmentation in near-mature and mature forests. In addition, the decrease in CA values for near-mature and mature forests was greater than that in NP values, with the decrease in CA and NP values for near-mature forests being 64.22% and 55.03%, respectively, and the decrease in CA and NP values for mature forests being 29.99% and 7.45%, respectively, suggesting an increase in degree of fragmentation in near-mature and mature forests. The CA, NP, LPI, ED, LSI, and AI of the near-mature forests and mature forests all decreased continuously, indicating that the area of near-mature forests and mature forests significantly reduced, the degree of fragmentation increased, the degree of aggregations reduced, and the patch shapes tended to be regular, which proved that Chinese fir plantations, as an important timber species, were cut down in large quantities after maturity and the landscape quality significantly degraded due to strong human interference. The CA, NP, LPI, ED, and LSI in over-mature forests all increased, while the AI slightly decreased, indicating that the fragmentation degree of over-mature forests decreased, the patch shapes tended to be complex, and the aggregation degree slightly reduced, which confirmed that less human interference has affected over-mature forests. The increase of area of over-mature forests reminds us that it is necessary to update over-mature forests in time to prevent them from turning into low-quality and low-efficiency forests, reducing landscape quality, occupying forest resources, and damaging the ecological environment.
To sum up, due to the development of regional economy in the past 10 years, as the main timber species, Chinese fir plantations have been cut down in large quantities after maturity, and the area reduced and subject to strong human interference. At the same time, affected by the afforestation policy, a large number of new fir trees were planted, which made the proportion of young and middle-aged forests in the Chinese fir plantations relatively large. Therefore, the landscape quality of Chinese fir plantations in Jiangle County has reduced in the past 10 years.
The results of the land transition matrix showed that other coniferous forests and other woodlands had the most interconversions with Chinese fir plantations over the decade, because fir (Cunninghamia lanceolata) and massoniana (Pinus massoniana) forests were the main plantations in Fujian Province [49], and other coniferous forests transferred to fir plantation were mostly Pinus massoniana. In addition, various economic indicators of Pinus massoniana plantation, including the average yield, outturn percentage, and market price, were not as good as those of Chinese fir plantations; therefore, local people preferred to plant Chinese fir plantations in order to obtain higher economic value, which was an important reason for the transformation of Pinus massoniana plantations to fir plantations [50]. However, Pinus massoniana is a suitable tree species for mixed Chinese fir [51]. In order to improve soil fertility and ensure the increase of stand growth, the planting area of Chinese fir plantations also has to implement a pine and fir rotation system. Therefore, a large part of Chinese fir plantations was reversely transferred into Pinus massoniana plantations [52]. The large area of transformation between other forest lands and Chinese fir plantations was basically because the newly planted Chinese fir plantations were mostly located in sub lands and other suitable forest lands. After maturing and then being heavily logged, the former Chinese fir plantations lands were again transferred to sub lands.
The non-wood forests, non-woodlands, and deciduous broad-leaved forests changed from eroding fir plantations in the first five years to being eroded by Chinese fir plantations in the second five years. From 2010 to 2015, more Chinese fir plantations transferred to non-wood forests and non-forest lands than non-wood forests and non-woodlands transferred to Chinese fir plantations. As far as non-woodland is concerned, the regional economic development during this period was affected by urban development, land acquisition and expansion, illegal occupation, and forest disasters, and a large number of forest lands were reversed into non-woodland, which has been confirmed by relevant research [46,53]. In terms of non-wood forest, affected by the market, farmers focused on planting non-wood forest such as citrus and oil-tea camellia to obtain greater economic benefits from 2010 to 2015. During the period from 2015 to 2020, with the further development of the market economy and the increase in labor demand, a new wave of Chinese laborers appeared in eastern areas and further expanded into the countryside. Farmers went out to work, planting Chinese fir on the lands formerly planted with non-wood forest. At the same time, affected by market factors, the operating income of non-wood forests became low; therefore, farmers would artificially transform these into high forests, uncultivated forest lands, etc. [54]. In addition, the pre-production, production, and post-production of non-wood forest management were relatively complex, and the demand for technical forestry services and the cost of management and maintenance was higher than that of Chinese fir plantations [55]. The decrease of deciduous broad-leaved forests indicated that Chinese fir plantations were expanding to high-altitude areas, and their growth boundaries were increasing.
The evergreen broad-leaved forests have changed from being eroded by Chinese fir plantations in the first five years, to eroding Chinese fir plantations in the next five years. As early as 2001, some scholars paid attention to the serious imbalance of tree species structure in Sanming City, Fujian Province. A large number of natural forests have been felled and replaced with pure artificial forests, and a large number of pure coniferous forests have been serially operated. The proportion of coniferous trees species, especially Chinese fir, was too large [56]. In addition, scholars continuously carried out research on ecological environmental protection and tree species structure adjustment in Fujian Province [57,58,59], and the research results were converted into policies, such as various forms of ecological compensation, perfect legislation, coniferous forests plantation and broad-leaved forests protection, broad-leaved trees thinning and intercropping, artificial promotion of natural regeneration, and closure of mountains for afforestation, and the implementation of these policies helped expand the proportion of broad-leaved tree species. Therefore, we have seen the continuous optimization of tree species structure, the protection of local evergreen broad-leaved forest, the increasing trend of replacement of Chinese fir plantations, and the transformation of Chinese fir plantations to zonal vegetation. At the same time, with China’s emphasis on ecological civilization and green sustainable development, the forestry sector has begun to pay attention to long-term ecological benefits [60], and more forest lands have been designated as nature reserves, forest recreation areas, and parks. As China’s economic fortune is on the rise, people living in rural areas use less wood as fuel, and it is estimated that Fujian Province will continue to adjust the forest structure and plant more broad-leaved forests in the future [61].
The area of bamboo-eroded Chinese fir plantations is increasing. According to related studies, moso bamboo is highly erosive, constantly invading adjacent broad-leaved evergreen and Chinese fir forests, with pure Chinese fir forests gradually transforming into mixed forests of moso bamboo and Chinese fir dominated by bamboo, which occurs in both natural and planted forests [62], and this trend continues in southern China [63]. The trend of the transformation of shrub forests to Chinese fir plantations is alleviated, and shrub forests reversely erode Chinese fir plantations at a slow rate.
The results of the prediction model show that the area of Chinese fir plantations will continue to expand, and most of Chinese fir plantations are transferred from non-woodlands, non-wood forests, other woodlands, and other coniferous forests, which is consistent with the conclusions of the related research [64,65]. It is worth noting that the trend of Chinese fir plantations transferring to evergreen broad-leaved forests continues, and the evergreen broad-leaved forests have been better protected and developed, which is conducive to improving the quality of forest landscapes in the south. The primary threat of the Chinese fir plantations, bamboo forests will continue to erode Chinese fir plantations.

5. Conclusions

Chinese fir plantations are the major component of the forest landscape in southern China, accounting for 12% of the forests in southern China, second only to Pinus massoniana.
Over the past decade, the landscape quality of Chinese fir plantations has declined. From 2010 to 2020, the proportion of young and middle-aged forests increased from 26.6% to 54.8%, a large number of mature forests were felled, and Chinese fir plantations were young, with poor accessibility, and low forest volume and productivity per unit area. Young and middle-aged forests became the main body of the Chinese fir plantations landscape. The area of near-mature forests and mature forests reduced with increased fragmentation degree, strong human disturbance, relatively low spatial aggregation degree, and, thus, the quality of the overall landscape degraded.
The past 10 years have seen the increasing area of Chinese fir plantations, mainly from other coniferous forests, non-woodlands, other coniferous forests, and non-wood forests, and a small amount of deciduous broad-leaved forests have also been transferred into Chinese fir plantations. Both bamboo forests and shrub forests have erosive effects on Chinese fir plantations: bamboo forests erode Chinese fir plantations at a rapid rate, over a large area and long duration; while shrub forest erodes Chinese fir plantations at a slow rate, over a small area and short period of time. The local evergreen broad-leaved forests have been well protected, and the Chinese fir plantations have been transformed into zonal vegetation.
In the next five years, the area of Chinese fir plantations will continue to grow, mainly from non-woodlands, other woodlands, non-wood forests, and other coniferous forests. Evergreen broad-leaved forests will continue to be protected, and bamboo forests and shrub forests will continue to erode Chinese fir plantations.
For subsequent research, it is necessary to further expand the research scale to explore the landscape pattern and succession of Chinese fir plantations in the provincial areas and then the whole country. In addition, further research is needed on the driving factors behind the changes in the landscape pattern of Chinese fir plantations within a larger study area.

6. Practical Implications

From the aesthetic perspective, the landscape quality of Chinese fir plantations decreased, and the decreased aesthetic perception reduced the aesthetic value of Chinese fir plantations, which had a negative impact on the development of ecological tourism. In terms of economic benefits, the Chinese fir plantations were young and their economic value decreased, which hindered the income of community residents. From the ecological perspective, the Chinese fir plantations were young, and the landscape quality was reduced, with low spatial expansion intensity between different age groups, weak material and energy exchange, and strong human interference. In addition, the future area of Chinese fir plantations will continue to expand, mainly eroded by bamboo forests. This has a negative impact on the regional ecological security pattern and resource security, and is not conducive to sustainable development.
In order to improve the landscape quality of Chinese fir plantations, build the regional ecological security pattern, and promote sustainable development, the following suggestions were put forward:
(1)
Adjust the economic development model of community forestry and eliminate the economic development model that relies too much on the profit of harvesting Chinese fir plantations; adjust simple stand structure and protect zonal evergreen broad-leaved forests; under the premise of improvement of the landscape quality of Chinese fir plantations, vigorously develop ecological industries such as ecological tourism and natural education to attract more ecological tourists.
(2)
Adjust the age group structure of Chinese fir plantations, reasonably control the cutting of near-mature forests and mature forests, cut down and update over-mature forest in a timely manner, expand the proportion of near-mature forests and mature forests, reduce the proportion of overmature forest, improve the landscape quality of Chinese fir plantations, make rational use of forest resources, and improve the social ecological environment.
(3)
We will continue to implement various forms of ecological compensation, such as perfect legislation, coniferous forests plantation and broad-leaved forests protection, broad-leaved trees thinning and intercropping, artificial promotion of natural regeneration, and closure of mountains for afforestation. Meanwhile, we will adjust the simple stand structure, expand the proportion of broadleaved trees, protect the growth of zonal evergreen broadleaved forests, and contain the blind and unorderly expansion of bamboo forests.

Author Contributions

Conceptualization, Z.Z. and Y.Z.; data curation, Z.Z. and Y.Z.; formal analysis, Z.Z. and J.H.; investigation, L.Y., D.L. and J.H.; methodology, Z.Z., Y.Z., D.L. and H.T.; project administration, Z.Z. and J.H.; resources, L.Y. and D.L.; software, L.Y., D.L. and H.T.; supervision, Y.Z., H.T. and J.H.; validation, L.Y.; visualization, J.H.; writing—original draft, Z.Z.; writing—review and editing, Y.Z. We attest that all authors contributed significantly to the creation of this manuscript. We confirm that the manuscript has been read and approved by all named authors. We confirm that the order of authors listed in the manuscript has been approved by all named authors. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Key R&D Program: Research on Rural Plant Landscape Construction and Application Technology, grant number 2019YFD1100404.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Please contact the authors via email for the data.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Landscape Index Table.
Table 1. Landscape Index Table.
MetricsIndicesDescriptionUnits
ClassLPIIt quantifies the percentage of total landscape area comprised by the largest patch.%
ClassAIIt shows the connectivity of different pairs of patch types.%
Class/landscapeNPIt shows the number of patches.#
ClassCAIt represents the sum of the areas of all plaques in a plaque type.hm2
Class/landscapeEDIt reflects the complexity of plaque shape.m/hm2
Class/landscapeLSIIt is used to describe the complexity of patch geometry._
Table
Table 2. Overall landscape indicators of Chinese fir plantations.
Table 2. Overall landscape indicators of Chinese fir plantations.
TimeCANPLPIEDLSIAI
201052,00410960.908723.835151.781754.8791
201553,44410671.096724.004651.612155.6738
202056,28810151.438224.832952.222756.3141
Table
Table 3. Landscape indicators of Chinese fir plantations by age group.
Table 3. Landscape indicators of Chinese fir plantations by age group.
Age GroupTimeLandscape Indicators
CANPLPIEDLSIAI
Young forest201060205410.88122.979427.128230.4911
201514,42010861.96922.277639.12434.9274
202016,89211831.5711.853842.438535.2213
Middle-aged forest201051044710.29672.880124.694431.2097
201562485550.48672.9227.2531.0118
202011,5529220.88514.038436.601932.163
Near-mature forest201063965760.22793.178627.57531.8153
201527723130.27232.042119.301927.2318
202022882590.17581.282117.770826.5511
Mature forest201018,94812870.74067.266843.282637.5
201517,92413400.52857.769444.358234.1867
202013,26411910.37666.240439.689731.1234
Overripe forest201053325800.55372.227826.675726.6975
201540044940.15891.797123.859424.5098
202077368540.2543.626932.954525.6085
Table
Table 4. Forest landscape transition matrix of Jiangle County from 2010 to 2015 (area/ha).
Table 4. Forest landscape transition matrix of Jiangle County from 2010 to 2015 (area/ha).
Time 2015
Forest
Landscape Type		Evergreen Broad-Leaved ForestNon-Wood LandShrub ForestNon-Wood ForestDeciduous Broad-Leaved
Forest		Other
Woodland		Other
Coniferous Forest		Chinese Fir PlantationsBamboo Forest
2010Evergreen Broad-Leaved Forest38,137.53304.022.0331.082.6314.81536.42424.29178.76
Non-Woodland184.8224,514.302.941918.066.4745.63405.11547.38212.77
Shrub Forest2.6218.67457.730.431.520.052.1624.649.54
Non-Wood Forest17.46106.160.061970.171.068.8830.9999.6214.30
Deciduous Broad-Leaved Forest1.3215.74 6.67283.06 10.2310.600.53
Other Woodland72.5294.1610.85234.6810.83275.03140.542763.9078.22
Other Coniferous Forest298.78761.775.1885.5293.23275.1337,355.442184.56138.74
Chinese Fir Plantations349.50822.704.94144.6978.831581.671468.6347,224.53266.19
Bamboo Forest117.96325.643.4221.082.927.2298.41238.2921,041.92
Table
Table 5. Forest landscape transition matrix of Jiangle County from 2015 to 2020 (area/ha).
Table 5. Forest landscape transition matrix of Jiangle County from 2015 to 2020 (area/ha).
Time 2020
Forest Landscape TypeEvergreen Broad-Leaved ForestNon-Wood LandShrublandNon-Wood ForestDeciduous Broad-Leaved ForestOther WoodlandOther Coniferous ForestChinese Fir PlantationBamboo Forest
2015Evergreen Broad-Leaved Forest37,066.52139.558.8215.7441.9062.74472.05653.02487.43
Non-Wood Land187.0325,450.424.6981.752.3893.50280.62549.68329.47
Shrubland84.383.01329.151.550.910.2325.4816.2821.16
Non-Wood Forest68.44146.500.832367.1115.7553.00123.36956.98671.19
Deciduous Broad-Leaved Forest147.604.680.017.24195.351.2915.63106.855.23
Other Woodland24.1922.550.803.7812.59421.3676.091637.0531.91
Other Coniferous Forest1239.82282.7513.9064.347.45606.8634,538.862443.30506.99
Chinese Fir Plantation831.31378.885.2093.4812.441250.671204.7849,039.66768.16
Bamboo Forest396.39149.76205.9930.584.8718.67272.91453.3320,342.38
Table
Table 6. Forest landscape transition matrix of Jiangle County in 2020–2025.
Table 6. Forest landscape transition matrix of Jiangle County in 2020–2025.
TimeForest
Landscape Type		2025
Evergreen Broad-Leaved ForestNon-Wood LandShrub ForestNon-Wood ForestDeciduous Broad-Leaved ForestOther WoodlandOther Coniferous ForestsChinese Fir PlantationsBamboo Forest
2020Evergreen Broad-leaved Forest38,860.45173.818.4420.411.7422.05319.14406.80196.35
Non-Wood Land180.9524,916.557.3685.924.5251.02371.02670.87257.07
Shrub Forest4.445.15541.620.250.140.235.749.76
Non-Wood Forest26.42102.000.412379.080.535.3439.7295.2623.40
Deciduous Broad-Leaved Forest2.454.550.030.29274.200.424.956.000.61
Other Woodland25.6656.450.205.840.482286.1040.5993.8913.40
Other Coniferous Forests313.48334.607.3634.113.5035.2635,576.48584.93135.97
Chinese Fir Plantations409.44617.0013.0075.416.4377.52574.7854,331.17250.48
Bamboo Forest209.19274.45622.7822.430.7313.33149.13284.7921,647.17
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Zhang, Z.; Zhong, Y.; Yang, L.; Li, D.; Tang, H.; He, J. Landscape Pattern and Succession of Chinese Fir Plantations in Jiangle County, China. Sustainability 2022, 14, 12497. https://doi.org/10.3390/su141912497

AMA Style

Zhang Z, Zhong Y, Yang L, Li D, Tang H, He J. Landscape Pattern and Succession of Chinese Fir Plantations in Jiangle County, China. Sustainability. 2022; 14(19):12497. https://doi.org/10.3390/su141912497

Chicago/Turabian Style

Zhang, Zhihui, Yongde Zhong, Lingfan Yang, Dali Li, Hui Tang, and Jianghua He. 2022. "Landscape Pattern and Succession of Chinese Fir Plantations in Jiangle County, China" Sustainability 14, no. 19: 12497. https://doi.org/10.3390/su141912497

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