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Article

Impact of Ice-Storms and Subsequent Salvage Logging on the Productivity of Cunninghamia lanceolata (Chinese Fir) Forests

by
Yu Zhu
1,2,3,
Shuguang Liu
1,2,3,*,
Wende Yan
1,2,3,
Deming Deng
4,
Guangyi Zhou
5,6,
Meifang Zhao
1,2,3,
Fei Gao
1,2,3,
Liangjun Zhu
1,2,3,
Zhao Wang
1,2 and
Menglu Xie
1,2
1
College of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China
2
National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China
3
Joint Research Centre of Bangor-Central South University of Forestry and Technology, Central South University of Forestry and Technology, Changsha 410004, China
4
Hunan Prospecting Designing & Research General Institute for Agriculture, Forestry & Industry, Changsha 410007, China
5
Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou 510520, China
6
Beijiangyuan National Forest Ecosystem Research Station, Nanling Mountains, Guangzhou 510520, China
*
Author to whom correspondence should be addressed.
Forests 2022, 13(2), 296; https://0-doi-org.brum.beds.ac.uk/10.3390/f13020296
Submission received: 8 January 2022 / Revised: 9 February 2022 / Accepted: 10 February 2022 / Published: 12 February 2022
(This article belongs to the Special Issue Long-Term Productivity and Landscape Processes of Mixed Conifer Forests)
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Abstract

:
The impacts of ice-storms on forests have received growing attention in recent years. Although there is a wide agreement that ice-storms significantly affect forest structure and functions, how frequent ice-storms and subsequent salvage logging impact productivity of subtropical coniferous forests in the future still remains poorly understood. In this study, we used the Ecosystem Demography model, Version 2.2 (ED-2.2), to project the impact of salvage logging of ice-storm-damaged trees on the productivity of Cunninghamia lanceolata-dominated coniferous forest and C. lanceolata-dominated mixed coniferous and broadleaved forests. The results show that forest productivity recovery is delayed in coniferous forests when there is no shade-tolerant broadleaved species invasion after ice-storms, and C. lanceolata could continue to dominate the canopy in the mixed coniferous and broadleaved forests under high-frequency ice-storms and subsequent salvage logging. The resistance and resilience of the mixed coniferous and broadleaved forests to high-frequency ice-storms and subsequent salvage logging were stronger compared to coniferous forests. Although conifers could continue to dominate the canopy under shade-tolerant broadleaved species invasion, we could not rule out the possibility of a future forest community dominated by shade-tolerant broadleaf trees because there were few coniferous saplings and shade-tolerant broadleaf species dominated the understory. Our results highlight that post-disaster forest management should be continued after high-frequency ice-storms and subsequent salvage logging in C. lanceolata forests to prevent possible shade-tolerant, late successional broadleaf trees from dominating the canopy in the future.

1. Introduction

Ice-storms, freezing rainstorms [1], or icing events [2] could trigger physical damage to forests, including destruction of a whole forest and xylem embolism and desiccation [3], and therefore significantly affect forest structures and functions. The impacts of ice-storms on forests also depend on whether salvage logging is put in place [2]. Forest managers often operate salvage logging after natural disturbances (e.g., ice-storms) to minimize economic loss, and reduce the risk of insect outbreaks and forest wildfire in post-disturbance forests [4,5,6]. Salvage logging has become increasingly prevalent in global forests [7], and it also strongly affects patterns of light transmission and absorption of the canopy in forests [8,9]. Despite the importance of ice-storms and subsequent salvage logging in shaping ecosystems, relatively little is known about their impacts on long-term productivity of mixed conifer forests.
A large number of studies have been carried out on ice-storm disturbance on forests in recent years across the globe. These efforts include, but are not limited to, the assessment of forest greenness [10], damage rate [11], the responses of resprouting [12], forest community succession [13,14], regional forest composition [15], and aboveground biomass damage [16]. Diverse research methods have been employed based on allometry, statistical analysis combined with the field surveys, and/or remotely sensed products. Field controlled experiments and models have been used to elucidate and simulate ecosystem responses to changes in the frequency and severity of ice-storms in forests [17], as an alternative to post facto analyses [18]. Previous studies mainly focused on the concurrent and short-term effects of ice-storms and/or salvage logging on forests. However, climate modeling researches imply that ice-storms may become more frequent and/or more severe in a changing climate [19].
Recent studies reported that storms (e.g., ice, and wind) and/or subsequent salvage logging could alter forest composition, structure, and successional trajectory (e.g., disturbance-mediated accelerated succession) in many forest systems [13,14,20,21,22,23,24,25,26]. Ice-storm-triggered forest damages could slow down forest succession by favoring light-demanding pioneer species and reducing forest biodiversity [27]. At the same time, ice-storms could also accelerate forest successional process, facilitate the advancement of shade-tolerant species into the canopy from understory, and increase biodiversity [16,20,22,24]. Subsequent salvage logging after ice-storms could also impact forest diversity [7,28,29].
The Great 2008 Chinese Ice-storm struck southern and central China [30], a region of prominence for China’s terrestrial carbon storage [31]. The widely distributed Cunninghamia lanceolata (Chinese fir) plantations in the region experienced the most severe damage [11]. How the long-term frequent and severe ice-storms, such as the Great 2008 Chinese Ice-storm, and subsequent salvage logging affect the productivity of coniferous forests in subtropical China (e.g., C. lanceolata forests) under future climate change regimes remains poorly investigated. The C. lanceolata trees usually dominate the canopy in mixed forests, and shade-intolerant broadleaved trees generally grow in the understory. Once damaged trees are removed after an ice storm, could shade-tolerant broadleaves, the dominant species in zonal climax community in subtropical China [32], replace shade-intolerant C. lanceolata to dominate the canopy and then decrease the productivity of the mixed forests with C. lanceolata in the future?
In this study, we used the process-based Ecosystem Demography model, Version 2.2 2 (ED-2.2) dynamic vegetation model to project the impact of salvage logging of multiple frequent ice-storm-damaged trees on species composition and productivity of C. lanceolata forests. We address two questions. Do salvage logging of ice-storm damaged trees delay forest productivity recovery? In addition, would C. lanceolata be replaced by early- and/or late-successional broadleaved trees in the canopy? We hypothesize that the salvage logging of storm damaged trees could put off the forest productivity recovery for both C. lanceolata-dominated coniferous forest and C. lanceolata-dominated mixed coniferous and broadleaved forests, and broadleaved species would replace C. lanceolata and dominate the canopy in the mixed forests.

2. Materials and Methods

2.1. Data Collection

Initial vegetation condition. The study was conducted at subtropical coniferous forests located in southern Hunan Province, China (113° E~114° E, 25° N~27° N), near the Nanling Mountains where the hardest hit of the Great 2008 Chinese Ice-storm occurred. This area was also one of the most optimum growth region for C. lanceolata [32]. We selected three plots of C. lanceolata forests, including one coniferous forest (i.e., Plot 1) and two mixed coniferous and broadleaved forests (i.e., Plot 2 and Plot 3) at the study site (Table 1; Figure 1). The selected forest plots met the following criteria simultaneously: (1) forests struck severely by the Great 2008 Chinese Ice-storm; (2) C. lanceolata plantations; (3) salvage logging removed at least 10% of AGB; (4) mean DBH was equal or greater than 10 cm; and (5) stand density was equal or greater than 1.0 × 103 trees ha−1. In the study, we classified Plot 1 as “coniferous forest” because of containing only coniferous species, and classified Plot 2 and Plot 3 as “mixed coniferous and broadleaved forest”, resulting from including both coniferous and broadleaved species.
The permanent sample plots from the National Forest Inventory of China with the size of 25.82 m × 25.82 m, were surveyed in both the fifth (2004) and sixth inventories (2009), and the inventory time period (i.e., 2004~2009) covered the Great 2008 Chinese Ice-storm. For each forest plot, tree species name, diameter at breast height (DBH, 1.3 m), demography (i.e., growth, survival, and recruitment status) of each trees with DBH ≥ 5 cm were recorded. The salvage logging information were also recorded. The salvage logging after the Ice-storm operated based on “Urgent notice of salvage logging after the Great 2008 Chinese Ice-storm by the State Forestry Administration of China (28 February 2008)” and completed before June 2008. The secondary broadleaved forest had most extensive damage while the C. lanceolata plantation experienced the most severe damage. P. massoniana and C. lanceolata were the most damaged species, followed by broadleaved species. Consequently, C. lanceolata and P. massoniana were relatively more vulnerable than broadleaved species against ice-storm disturbance in subtropical forests of China [11,33]. We only used the inventory data in 2004 as the initial vegetation condition for model simulations, and used the inventory data in 2004 and 2009 for model validation.
Atmospheric and edaphic conditions. We recycled the hourly averaged Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) re-analyses data [35,36,37,38,39] (i.e., pressure, temperature, precipitation, humidity, incoming shortwave and longwave radiation, and winds) in the recent decade (i.e., 2011~2020) as the future (i.e., 2021~2050) meteorological forcing under the baseline scenario (F0; See Section 2.2.3 for more detail of simulation scenarios) to drive the ED-2.2 model. We expected the meteorology of future ice-storm scenarios were the same as that in the Great 2008 Chinese Ice-storm. Because the Great 2008 Chinese Ice-storm mainly occurred in January 2008 [30], we regarded the meteorology of January 2008 as “the historical ice-storm meteorology” and replaced the future baseline meteorological forcing with “the historical ice-storm meteorology” as the future ice-storm meteorology in different ice-storm scenarios (F1~F4; See Section 2.2.3 for more detail of simulation scenarios). The soil texture information (i.e., sand, silt, and clay content) for each plot was from the SoilGrids 2.0 database [40]. Soil depth to bedrock for each plots were derived from a global gridded data set for ecosystem modeling [41]. All the atmospheric and edaphic data were converted to the Hierarchical Data Format 5 (HDF5) to be compatible with the ED-2.2 model.

2.2. Model Configuration and Simulation Setup

2.2.1. Model Overview

In this study, we used the Ecosystem Demography model, Version 2.2 (ED-2.2) [42] to simulate the impacts of frequent ice-storms and subsequent salvage logging on forest net primary productivity (NPP). The ED-2.2 is a cohort-based, terrestrial biosphere model that couples size and age-structured (SAS) plant community dynamics with biophysical and biogeochemical modules [42]. Spatially-implicit ED-2.2 model differs from a regular forest gap model, and it does not have a plot area and all units in ED-2.2 are per unit area based [42]. ED-2.2 incorporates an efficient and sophisticated mechanistic scaling of vegetation dynamics from individual trees to landscapes [43,44,45]. ED-2.2 simulates forest demography, community succession, and ecosystem carbon dynamics, and it also generates multiple types of output at different time scales. ED-2.2 enables us to predict aboveground biomass (AGB) and NPP of subtropical forests as well as forest responses to disturbances (e.g., salvage logging) under future climate change scenarios. ED-2.2 has been successfully evaluated and used in both short-term and long-term studies across the temperate, subtropical, and tropical forests in the world [44,46,47,48,49,50].

2.2.2. Model Calibration, Verification, and Validation

Plant functional types. There are three plant functional types (PFTs) for coniferous species in ED-2.2 model, i.e., mid-latitude (“Northern”) pines (PFT6), subtropical (“Southern”) pines (PFT7), and late-successional conifers (PFT8). We regarded the coniferous species (i.e., Cunninghamia lanceolata and Pinus massoniana) as subtropical (“Southern”) pines (PFT7) in the ED-2.2 model configuration, because C. lanceolata and P. massoniana were shade-intolerant, non-late-successional coniferous species in the subtropical forests of China. We also used the shade-intolerant, early successional broadleaved tropical species (PFT2; e.g., Cinnamomum camphora, etc.) and shade-tolerant, late successional broadleaved tropical species (PFT4; e.g., Cyclobalanopsis spp. etc.) in the ED-2.2 model configuration. We regarded PFT4 as the shade-tolerant invasion broadleaved species that was absent in the three forest plots in 2004, but may invade when forests suffered frequent ice-storms and subsequent salvage logging. The shade-tolerant, late successional broadleaved tropical species (PFT4) was the dominant species in zonal climax community in subtropical China [32]. Successional types for each species were based on the Hunan Provincial Protocol of National Forest Inventory of China [51].
Model calibration. Among the PFT-dependent parameters in ED-2.2 model, specific leaf area (SLA) is a highly sensitive parameter that influences canopy expansion and growth through its effect on total leaf area per plant affecting light interception [52]. We modified SLA parameter for PFT2, PFT4, and PFT7 according to previous studies [53] and TRY plant trait database [54] instead of default ones built-in ED-2.2 (Table 2). Besides, allometric parameters were used to determine tree height, and further calculate aboveground biomass and productivity [42]. We also corrected the DBH-height allometric parameter for PFT7 by refitting empirical allometric equations with the aid of forest inventory data that contained a lot of tree height records for C. lanceolata and P. massoniana. The goodness of fit of the calibrated DBH-height allometry equation (RMSE = 1.50; MAE = 2.21) was better than that of the default (RMSE = 2.43; MAE = 5.89) in the ED-2.2 (Figure A1). Additionally, we also calibrated the heartwood biomass allometric parameters for PFT7 based on the available forest inventory data and previous empirical research [55] (Table 2). We accepted the default allometric parameters for PFT2 and PFT4 in ED-2.2 (Table 2).
Model verification and validation. For AGB verification (qualitative evaluation), we found that there were few coniferous saplings in the understory under both F3 and F4 ice-storm and subsequent salvage logging scenarios (See Section 2.2.3 for more detail of simulation scenarios) in the C. lanceolata mixed coniferous and broadleaved forests (Figure 2), likely resulting from the poor recruitment ability of shade-intolerant C. lanceolata [32]. For AGB validation (quantitative evaluation), we compared the difference in AGB between inventory observation and model simulation under the baseline scenario (RMSE = 0.15 kg C m−2; MAE = 0.13 kg C m−2) (Figure 3). For NPP validation, we found that simulated NPP of Plot 1, Plot 2, and Plot 3 generally fell within the observed NPP range of C. lanceolata coniferous and mixed coniferous and broadleaved forests [56,57]. The NPP values in Plot 2~3 were larger than those of Plot 1 (Table 3), because C. lanceolata mixed coniferous and broadleaved forests generally have higher NPP than C. lanceolata coniferous forest [58]. The model verification and validation results were similar with previous empirical studies and forest inventory records.

2.2.3. Scenarios Setup and Simulation

Ice-storm and frost can suppress tree survival or directly cause tree mortality through physiological damage (e.g., xylem embolism and desiccation) or physical damage [3,59]. Most of the tree mortality caused by the Great 2008 Chinese Ice-storm were owing to physical damage rather than physiological damage [11]. For each forest plot, salvage logging, i.e., salvage logging of ice-storm damaged trees with DBH ≥ 5 cm after the Great 2008 Chinese Ice-storm, was recorded in the forest inventory. We simulated physical damage from the Ice-storm with the aid of those records and calculated the damage proportion of AGB for each plot and set harvest events to simulate salvage logging after ice-storm in ED-2.2 model. Creating scenarios with different frequency and intensity of ice-storms makes it possible to identify critical ecological thresholds necessary for predicting and preparing for ice-storm impacts [60].
In this study, the ice-storm scenarios were based on the ice-storm and salvage logging that occurred in 2008. Salvage logging was assumed to operate in future scenarios in the simulations. Five scenarios: Frequency 0 (F0, baseline), Frequency 1 (F1), Frequency 2 (F2), Frequency 3 (F3), and Frequency 4 (F4) scenarios were defined as zero, once, twice, and thrice (including scenarios with and without shade-tolerant broadleaved species invasion) disasters occurring in the next 10 years (i.e., 2021~2030) (Table 4). For baseline scenario, we did not change any meteorology and there was no ice-storm and salvage logging in the future. For F1 ice-storm scenario, we replaced the meteorology of January 2021 with the historical ice-storm meteorology (i.e., January 2008) and operated salvage logging according to the proportion of AGB removal in 2008 (Table 1); for F2 ice-storm scenario, we replaced the meteorology of January 2021 and January 2024 with the historical meteorology and scheduled two salvage logging events accordingly (the proportion of AGB removal was the same as that in 2008) (Table 1); for F3 ice-storm scenario, we replaced the meteorology of January 2021, January 2024, and January 2027 with the historical meteorology and scheduled three salvage logging events accordingly (Table 1); and for F4 ice-storm scenario, we replaced the meteorology of January 2021, January 2024, and January 2027 with the historical meteorology and operated thrice salvage logging according to the proportion of AGB removal in 2008 (Table 1) and we also considered the shade-tolerant broadleaved species (i.e., late-successional tropical tree, PFT4) invasion after the third ice-storm in 2027, and the initial density of PFT4 was 0.1 seedling m−2 based on the default empirical parameter built-in ED2 model. We regarded F3/F4 (thrice ice-storms) scenarios as the “high-frequency” ice-storms.

3. Results

3.1. Net Primary Productivity

For the condition without shade-tolerant broadleaved species (i.e., PFT4) invasion after the third ice-storm, there was a mild U-shaped NPP time-series, and NPP eventually returned to a quasi-steady state (~0.6 kg C m−2 year−1) regardless of ice-storm and salvage logging frequencies in Plot 1 (Figure 4a). In contrast, salvage logging of ice-storm damaged trees enhanced NPP in Plot 2 (~0.9 kg C m−2 year−1) and Plot 3 (~1.0 kgC m−2 year−1), and NPP eventually returned to an equilibrium condition that was similar to Plot 1 (Figure 4b,c).
When considering shade-tolerant broadleaved species (i.e., PFT4) invasion after the third ice-storm (F4 scenario), forest productivity dramatically increased but eventually returned to a quasi-steady state at the three C. lanceolata forest plots (Figure 4). NPP at Plot 1 and Plot 3 surpassed their pre-disturbance level, but it was not the case at Plot 2 where forest productivity could only recover to its previous level (Figure 4). NPP increased with PFT richness after shade-tolerant broadleaved species invasion (i.e., PFT4) and subsequent salvage logging under the F4 scenario for each plots, especially in Plot 1, followed by Plot 3 and Plot 2 (Figure 5).

3.2. Aboveground Biomass

For the condition without shade-tolerant broadleaved species invasion after the third ice-storm, we found that AGB decreased after F3 ice-storms and subsequent salvage logging (27% AGB removed each time), and AGB recovered to the pre-disaster level around 2040 in Plot 1 (Figure 6a). The forest AGB decreased after frequent ice-storms and subsequent salvage logging (10~20% AGB removed each time), and recovered to pre-disaster level around 2035 in Plot 2 and Plot 3 (Figure 6b,c). There was a hump-shaped AGB time-series for broadleaf species (i.e., PFT2) after disturbances in the mixed coniferous and broadleaved forests, especially at Plot 3 (Figure 6c). When considering shade-tolerant broadleaved species invasion after the third ice-storm, AGB decreased and recovered to pre-disaster level around 2030 in Plot 1, Plot 2, and Plot 3 (Figure 7). It should be noticed that the light-demanding early successional broadleaved species was replaced by the invaded shade-tolerant broadleaved species starting from around 2030, and the latter begun to dominate the subcanopy in Plot 2 and Plot 3 (Figure 7b,c). Although conifers still dominated the canopy around 2050 (Figure 7), there were few coniferous saplings in the understory (Figure 2).

4. Discussion

4.1. Post-Disturbance Forest Productivity: Coniferous Forest vs. Mixed Coniferous and Broadleaved Forests

Salvage logging of ice-storm damaged trees could delay forest productivity recovery to the equilibrium condition in coniferous forests if there is no shade-tolerant broadleaved species (i.e., PFT4) invasion (Figure 4a), but this is not the case for mixed coniferous and broadleaved forests where forest productivity increased with ice-storm frequencies (Figure 4b,c). This illustrates that the resistance and resilience of C. lanceolata mixed coniferous and broadleaved forests to frequent salvage loggings were stronger than that of the C. lanceolata coniferous forest.
Stand density decreases when storm-damaged trees are removed, and therefore NPP could decrease since stand density generally has a positive effect on productivity in subtropical forests of China [61]. Recruitment is generally poor in the coniferous forest compared with the mixed coniferous and broadleaved forests, which likely resulted from the intraspecific competition among phylogenetically close species and conspecific/phylogenetic negative density dependence [62,63,64,65,66], which explains why seedlings have lower survival, growth, and recruitment. In contrast, in mixed coniferous and broadleaved forests, the understory, including broadleaf trees with larger SLA than that of conifers in the mixed coniferous and broadleaved forests, can absorb more fraction of photosynthetically active radiation (FPAR) and therefore produce more biomass and increase productivity once storm-damaged trees are removed and light transmittance is improved due to decreased stand density [67]. In this study, we found that sapling (i.e., DBH ≤ 10 cm) rarely existed in the understory of the coniferous forest after removing the ice-storm damaged trees when there was no shade-tolerant broadleaved species invasion (Figure 2a). The results clearly suggest that the structure of the mixed coniferous and broadleaved forests may improve the resistance and resilience of the forests to ice-storms by enhancing biodiversity in the forests.
Previous studies have shown that unlike severe stand-replacing disturbances (e.g., clear-cut harvest and high-intensity fire, etc.) and small scale gap formation [68,69], moderate-severity disturbances (e.g., ice-storm) may increase the structural (e.g., vertical and horizontal heterogeneity) and functional complexity (e.g., richness of species and plant functional types) [8,70] of mixed forests, and therefore strongly affect ecosystem functioning [9,68,71,72,73,74,75]. Moderate-severity disturbances influence light transmittance in the canopy and therefore forest productivity [9]. Canopy openness and light transmission could increase significantly relative to the pre-disturbance baselines and undisturbed controls [8,69,76]. The moderate disturbance hypothesis holds that the moderate disturbance frequency can maintain the high species diversity [77]. Only at moderate disturbance frequency, early- and late-successional species have the greatest chance to coexist, and biodiversity is also the highest [78].
Forest productivity eventually reached the same quasi-steady state during the study period for the baseline and different ice-storm frequencies scenarios (i.e., F0~F3 scenarios) under the condition without shade-tolerant broadleaved species invasion in the coniferous forest (Figure 4a), and this phenomenon was also observed in the two mixed coniferous and broadleaved forests (Figure 4b,c), illustrating that the impacts of ice-storms and subsequent salvage logging on NPP of C. lanceolata forests were not permanent, although climate extremes (e.g., ice-storm and frost) often have delayed long-term effects on carbon cycle of terrestrial ecosystems [59]. This suggests that C. lanceolata forests, both coniferous forest and mixed coniferous and broadleaved forests, have a certain resilience to this frequent moderate-severity disturbances (i.e., ice-storm and subsequent salvage logging) in the long term.
The shade-tolerant broadleaved species invasion after high-frequency salvage logging of ice-storm damaged trees enhanced the productivity of C. lanceolata coniferous forest and mixed coniferous and broadleaved forests (Figure 4), which likely resulted from increasing PFT richness after the particular shade-tolerant species invasion (Figure 5). The selection effects and complementarity effects underling significant positive biodiversity-productivity relationships (BPRs) may maintain and increase the productivity after salvage logging of storm-damaged trees. Complementarity effects occur when the functioning of individual species is higher in the mixtures than that in monocultures; selection effects occur when species that provide high function levels tend to dominate in diverse communities [79]. Even though under an F4 scenario, however, forest productivity only recovered to its previous level in Plot 2 (with maximum initial stand age than other plots), which may be due to the context-dependency of BPRs in forests [80]. It is difficult to maintain high productivity in an older forest stand, compared with a younger one, even though its biodiversity increases.

4.2. Coniferous Trees Continue to Dominate the Canopy

High-frequency salvage logging after several ice-storms changed forest composition but conifers continued to dominate the canopy regardless of shade-tolerant broadleaved species (i.e., PFT4) invasion after the ice-storm in Plot 2 and Plot 3 (Figure 6b,c and Figure 7b,c), implying that C. lanceolata mixed coniferous and broadleaved forests has strong adaptability and stability to high-frequency salvage logging disturbance.
Recent studies have found that storm disturbances could alter forest successional trajectories in many forest systems [13,14,20,21,22,23,24,25,26]. Storm-induced differential tree mortality may alter the community’s successional process via pushing forest composition back or forward to an earlier—or later—successional state, modifying the rate of species change [23,25]. Studies have shown ice-storm-triggered forest damage slows down succession by favoring shade-intolerant, early-successional species, and reducing forest biodiversity [27]. Ice-storm can also accelerate community’s successional process and increase forest diversity [16,20,22,24]. Stand-specific understanding of pre-disturbance composition should be considered while projecting future forest development following ice-storm disturbance [14].
High-frequency ice-storms and subsequent salvage logging created opportunities and understory conditions for post-disturbance invasion of shade-tolerant, late successional broadleaved trees (i.e., PFT4). There were few coniferous saplings with DBH ≤ 10 cm, and shade-tolerant broadleaf species dominated the understory (Figure 2b), implying that high-frequency ice-storms and subsequent salvage logging may accelerate community successional process in post-disturbance C. lanceolata mixed coniferous and broadleaved forests in the future, although conifers will still continue to dominate the canopy until 2050. We could not rule out the possibility of a future forest community dominated by shade-tolerant broadleaf trees because there were more saplings (PFT4) with DBH ≤ 10 cm compared with conifers (PFT7) in the understory (Figure 2b). C. lanceolata is a subtropical non-late-successional coniferous species, and they will be eventually be replaced by the zonal climax shade-tolerant evergreen broadleaf species in subtropical China [32] without anthropogenic disturbances and post-disaster forest management. As a widespread management practice, salvage logging after ice-storms can trigger the possibility for species invasion, accelerate community succession, increase biodiversity, and therefore improve forest productivity and forest quality [81] in C. lanceolata plantations of subtropical China. Moreover, shade-tolerant broadleaved species (i.e., PFT4) replaced light-demanding (i.e., PFT2) in the subcanopy of C. lanceolata mixed coniferous and broadleaved forests after invasion of late successional broadleaved trees (i.e., PFT4) (Figure 7b,c), illustrating that understory vegetation was well prepared for future succession in C. lanceolata forests. Studies have confirmed that the understory vegetation often plays an important role in forests [82], and it can affect overstory successional process [83] and therefore long-term productivity [84].
There is still room for improvement on the simulation of the impacts of ice-storm and subsequent salvage logging on forest productivity in the future. First, in this study, we mainly focused on the impact of tree mortality through physical damage and subsequent salvage logging rather than frost defoliation and frost mortality through physiological damage on forest productivity. Second, although we had corrected the DBH-height allometric parameter for PFT7 and the calibrated allometry equation (RMSE = 1.50; MAE = 2.21) had a higher accuracy compared with the default (RMSE = 2.43; MAE = 5.89) (Figure A1), dynamic or size/age-specific allometric parameters may be applied to further improve the fit of allometric equations for C. lanceolata in future simulation studies [85,86,87]. Third, although we calibrated SLA at mature stands for PFT7 according to previous literature [53], trait plasticity (i.e., plant traits vary with environment) can be considered in future ED-2.2 simulations [42]. Fourth, the ED-2.2 model has been fully built in the Predictive Ecosystem Analyzer (PEcAn) model analysis toolbox [88,89]. This capability can constrain PFT-dependent parameters (e.g., initial density of seedlings) with more field data (e.g., density of saplings of each species naturally regenerated) and ensemble simulation and analysis can be carried out in the future to reduce the model uncertainties. The ensemble analysis, creating numerous model runs with each having a set of parameters sampled from statistical distributions to represent parameter uncertainty based on a Bayesian meta-analysis, generates a probability distribution of model projections using PEcAn. It allows us to put confidence intervals on the modeled results.

5. Conclusions

In this study, we used the Ecosystem Demography model, Version 2.2 (ED-2.2), to project the impact of salvage logging of ice-storm-damaged trees on the productivity of the C. lanceolata coniferous forest and the mixed coniferous and broadleaved forests. Forest productivity recovery is delayed in coniferous forests when there was no shade-tolerant broadleaved species invasion after ice-storms, and C. lanceolata could continue to dominate the canopy in the mixed coniferous and broadleaved forests under high-frequency ice-storms and subsequent salvage logging of damaged trees. Our results highlight that the resistance and resilience of the C. lanceolata mixed coniferous and broadleaved forests to high-frequency ice-storms and subsequent salvage logging were stronger than those of the C. lanceolata coniferous forests, and the C. lanceolata mixed coniferous and broadleaved forests had stronger adaptability and stability to high-frequency ice-storm disturbance. Although conifers could continue to dominate the canopy under the shade-tolerant broadleaved species invasion scenario, we could not rule out the possibility of a future forest community dominated by shade-tolerant broadleaf trees because there were few coniferous saplings, and shade-tolerant broadleaf species dominated the understory.

Author Contributions

Conceptualization, Y.Z. and S.L.; Data curation, Y.Z.; Formal analysis, Y.Z.; Funding acquisition, Y.Z., S.L. and G.Z.; Investigation, S.L.; Methodology, Y.Z.; Project administration, S.L.; Resources, D.D.; Software, Y.Z.; Supervision, S.L.; Validation, Y.Z.; Visualization, Y.Z.; Writing—original draft, Y.Z.; Writing—review & editing, Y.Z., S.L., W.Y., D.D., G.Z., M.Z., F.G., L.Z., Z.W. and M.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (Grant number 31901241 to Y.Z., U20A2089, 41971152 to S.L., and 31770664 to G.Z.), and the Scientific Research Foundation of Department of Education of Hunan Province (Grant number 21B0277 to Y.Z.), Hunan Innovative Talent Program (Grant number 2019RS1062 to S.L.), and the Start-up Scientific Research Foundation for the Introduction of Talents in Central South University of Forestry and Technology (Grant number 2018YJ010 to Y.Z.).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We appreciate the data support from the TRY initiative, GMAO, ISRIC, and ORNL DAAC. We thank the editor and two anonymous reviewers for the constructive comments.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

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Figure A1. Relationships between DBH and tree height, and the allometry equations for early successional “Southern (Subtropical) Pines” PFT in ED-2.2. The blue line indicates the default allometric relationship in ED-2.2; the red one indicates the calibrated allometric relationship using forest inventory data.
Figure A1. Relationships between DBH and tree height, and the allometry equations for early successional “Southern (Subtropical) Pines” PFT in ED-2.2. The blue line indicates the default allometric relationship in ED-2.2; the red one indicates the calibrated allometric relationship using forest inventory data.
Forests 13 00296 g0a1

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Figure 1. Histograms and density plots showing the distributions of (a) diameter at breast height (DBH, 1.3 m) and (b) tree height in 2004 for Plot 1, Plot2, and Plot 3.
Figure 1. Histograms and density plots showing the distributions of (a) diameter at breast height (DBH, 1.3 m) and (b) tree height in 2004 for Plot 1, Plot2, and Plot 3.
Forests 13 00296 g001
Forests 13 00296 g002 550
Figure 2. Model predicted aboveground biomass [AGB, kg C m−2] of saplings (DBH ≤ 10 cm) for each PFTs under F3 (a) and F4 (b) ice-storm and subsequent salvage logging scenario. PFT2 (early tropical broadleaf); PFT4 (late tropical broadleaf); PFT7 (subtropical pines); total (whole community).
Figure 2. Model predicted aboveground biomass [AGB, kg C m−2] of saplings (DBH ≤ 10 cm) for each PFTs under F3 (a) and F4 (b) ice-storm and subsequent salvage logging scenario. PFT2 (early tropical broadleaf); PFT4 (late tropical broadleaf); PFT7 (subtropical pines); total (whole community).
Forests 13 00296 g002
Forests 13 00296 g003 550
Figure 3. Observed (forest inventory) vs. simulated average aboveground biomass [AGB, kg C m−2] under baseline scenario in Plot 1, Plot 2, and Plot 3 in 2004 and 2009.
Figure 3. Observed (forest inventory) vs. simulated average aboveground biomass [AGB, kg C m−2] under baseline scenario in Plot 1, Plot 2, and Plot 3 in 2004 and 2009.
Forests 13 00296 g003
Forests 13 00296 g004a 550Forests 13 00296 g004b 550
Figure 4. Model predicted site-level averaged net primary productivity [NPP, kg C m−2 year−1] under the baseline (F0), F1~F4 ice-storm and subsequent salvage logging scenarios in (a) Plot 1, (b) Plot 2, and (c) Plot 3.
Figure 4. Model predicted site-level averaged net primary productivity [NPP, kg C m−2 year−1] under the baseline (F0), F1~F4 ice-storm and subsequent salvage logging scenarios in (a) Plot 1, (b) Plot 2, and (c) Plot 3.
Forests 13 00296 g004aForests 13 00296 g004b
Forests 13 00296 g005 550
Figure 5. Model predicted site-level averaged net primary productivity [NPP, kg C m−2 year−1] before and after shade-tolerant broadleaved species invasion (i.e., PFT4) and subsequent salvage logging under the F4 scenario in Plot 1, Plot 2, and Plot 3 in the future.
Figure 5. Model predicted site-level averaged net primary productivity [NPP, kg C m−2 year−1] before and after shade-tolerant broadleaved species invasion (i.e., PFT4) and subsequent salvage logging under the F4 scenario in Plot 1, Plot 2, and Plot 3 in the future.
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Forests 13 00296 g006 550
Figure 6. Model predicted aboveground biomass [AGB, kg C m−2] under F3 ice-storm and subsequent salvage logging scenario. PFT2 (early tropical broadleaf); PFT7 (subtropical pines); total (whole community) in (a) Plot 1, (b) Plot 2, and (c) Plot 3.
Figure 6. Model predicted aboveground biomass [AGB, kg C m−2] under F3 ice-storm and subsequent salvage logging scenario. PFT2 (early tropical broadleaf); PFT7 (subtropical pines); total (whole community) in (a) Plot 1, (b) Plot 2, and (c) Plot 3.
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Forests 13 00296 g007 550
Figure 7. Model predicted aboveground biomass [AGB, kg C m−2] under F4 ice-storm and subsequent salvage logging scenario. PFT2 (early tropical broadleaf); PFT4 (late tropical broadleaf); PFT7 (subtropical pines); total (whole community) in (a) Plot 1, (b) Plot 2, and (c) Plot 3.
Figure 7. Model predicted aboveground biomass [AGB, kg C m−2] under F4 ice-storm and subsequent salvage logging scenario. PFT2 (early tropical broadleaf); PFT4 (late tropical broadleaf); PFT7 (subtropical pines); total (whole community) in (a) Plot 1, (b) Plot 2, and (c) Plot 3.
Forests 13 00296 g007
Table
Table 1. Descriptions of Cunninghamia lanceolata forests plots in the study.
Table 1. Descriptions of Cunninghamia lanceolata forests plots in the study.
Plot No.Plot 1Plot 2Plot 3
Elevation [m]450110440
Mean age [a]152917
Mean DBH [cm]101213
Canopy height [m]16.612.913.1
Species composition (Whole community)CULA; PIMACULA; PIMA; CINN; SATZ; OBLDCULA; PIMA; OBLD
Species composition (Understory)CULACULA; CINN; SATZ; OBLDCULA
Species composition (Recruitment 2004~2009)NullCULA; OBLDCULA; CINN
Basal area [m2 ha−1]CULA (24.2); PIMA (1.9)CULA (10.7); PIMA (0.3); CINN (1.1); SATZ (1.1); OBLD (0.1)CULA (28.1); PIMA (1.1); OBLD (0.1)
Stand density [ha−1] (Whole community)320912093104
Stand density [ha−1] (Understory)18513731343
Stand density [ha−1] (Recruitment 2004~2009)04590
Salvage logging [AGB%]271020
Salvage logging [ha−1]CULA (791); PIMA (45)CULA (75); CINN (15); SATZ (30)CULA (716); PIMA (15); OBLD (30)
Understory: 5 cm ≤ DBH ≤ 10 cm; Recruitment: DBH < 5 cm in 2004 and DBH ≥ 5 cm in 2009. CULA: Cunninghamia lanceolata; PIMA: Pinus massoniana; CINN: Cinnamomum sp.; SATZ: Sassafras tzumu; OBLD: Other broadleaved species with low wood density. PFT2: CINN, SATZ, and OBLD; PFT7: CULA and PIMA. Low wood density is feature typical of early successional species [34] and therefore we regarded OBLD as PFT2 in the study.
Table
Table 2. Eco-physiological and allometric parameters for plant functional types.
Table 2. Eco-physiological and allometric parameters for plant functional types.
Plant Functional TypeSLA [m2 kgC−1]b1Ht [m]b2Ht [cm−1]b1Bs [kgC]b2Bs
PFT224.50.0350.6950.1662.432
PFT436.60.0420.5220.2822.432
PFT77.451.037−0.0140.1172.240
SLA: specific leaf area; b1Ht: height allometry intercept; b2Ht: height allometry slope; b1Bs: heartwood biomass allometry intercept; b2Bs: heartwood biomass allometry slope. The default and calibrated parameters were shown in normal and bold, respectively.
Table
Table 3. Comparisons of net primary productivity [NPP, kg C m−2 year−1] of Cunninghamia lanceolata forests simulated by ED-2.2 and empirical studies for coniferous forest and mixed coniferous and broadleaved forests.
Table 3. Comparisons of net primary productivity [NPP, kg C m−2 year−1] of Cunninghamia lanceolata forests simulated by ED-2.2 and empirical studies for coniferous forest and mixed coniferous and broadleaved forests.
Plot No.ED-2.2 SimulationPrevious StudiesReference
Min.MeanMax.Range
Plot 10.540.610.71[0.45, 0.77][57]
Plot 20.820.951.20[0.69, 1.17][56]
Plot 30.840.921.02[0.69, 1.17][56]
A previous study reported that a mixed coniferous and broadleaved forest (Cunninghamia lanceolata and Michelia macclurei) had a higher (52.3%) productivity compared with C. lanceolata coniferous forest [56]. We computed the empirical NPP range of C. lanceolata mixed coniferous and broadleaved forests based on the range of C. lanceolata coniferous forest [57] and the proportion (52.3%) of C. lanceolata trees [56].
Table
Table 4. Ice-storm and subsequent salvage logging scenarios setup from 2020 to 2050 in this study.
Table 4. Ice-storm and subsequent salvage logging scenarios setup from 2020 to 2050 in this study.
ScenarioIce-Storm and Subsequent Salvage Logging
202120242027
Frequency 0 (F0, baseline)Not occurredNot occurredNot occurred
Frequency 1 (F1)OccurredNot occurredNot occurred
Frequency 2 (F2)OccurredOccurredNot occurred
Frequency 3 (F3)OccurredOccurredOccurred
Frequency 4 (F4)OccurredOccurredOccurred *
* F4 contains shade-tolerant broadleaved species (PFT4) invasion after the third ice-storm in 2027.
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Zhu, Y.; Liu, S.; Yan, W.; Deng, D.; Zhou, G.; Zhao, M.; Gao, F.; Zhu, L.; Wang, Z.; Xie, M. Impact of Ice-Storms and Subsequent Salvage Logging on the Productivity of Cunninghamia lanceolata (Chinese Fir) Forests. Forests 2022, 13, 296. https://0-doi-org.brum.beds.ac.uk/10.3390/f13020296

AMA Style

Zhu Y, Liu S, Yan W, Deng D, Zhou G, Zhao M, Gao F, Zhu L, Wang Z, Xie M. Impact of Ice-Storms and Subsequent Salvage Logging on the Productivity of Cunninghamia lanceolata (Chinese Fir) Forests. Forests. 2022; 13(2):296. https://0-doi-org.brum.beds.ac.uk/10.3390/f13020296

Chicago/Turabian Style

Zhu, Yu, Shuguang Liu, Wende Yan, Deming Deng, Guangyi Zhou, Meifang Zhao, Fei Gao, Liangjun Zhu, Zhao Wang, and Menglu Xie. 2022. "Impact of Ice-Storms and Subsequent Salvage Logging on the Productivity of Cunninghamia lanceolata (Chinese Fir) Forests" Forests 13, no. 2: 296. https://0-doi-org.brum.beds.ac.uk/10.3390/f13020296

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