A Process-Based Approach to Estimate Chinese Fir (Cunninghamia lanceolata) Distribution and Productivity in Southern China under Climate Change

Temporal Variations in Aboveground Biomass, Nutrient Content, and Ecological Stoichiometry in Young and Middle-Aged Stands of Chinese Fir Forests

Understanding the ecological dynamics of forest ecosystems, particularly the influence of forest age structure on soil carbon (C), nitrogen (N), and phosphorus (P) content, is crucial for effective forest management and conservation. This study aimed to investigate the nutrient storage and ecological stoichiometry across different-aged stands of Chinese fir forests. Soil samples were collected from various depths (0-15 cm, 15-30 cm, and 30-45 cm) across four age groups of Chinese fir forests (8-year-old, 12-year-old, 20-year-old, and 25-year-old) in the Forest Farm, Pingjiang County, China. Soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) were measured, and their stoichiometries were calculated. The results showed that both individual tree biomass and stand biomass, along with SOC, TN, and TP content, increased with stand age, highlighting the significant importance of stand age on biomass production and nutrient accumulation in forests. Specifically, soil C and P contents significantly increased as the forest aged, while variation in N content was relatively minor. Soil C/N and C/P ratios exhibited variation corresponding to forest age, suggesting alterations in the ecological stoichiometry characteristics of the forests over time. These findings are crucial for understanding the dynamics of ecosystem functioning and nutrient cycling within Chinese fir forests and provide a solid scientific basis for the effective management and conservation of these vital forest ecosystems.

Transfer learning improves predictions in lignin content of Chinese fir based on Raman spectra

Lignin in biomass plays significant role in substitution of synthetic polymer and reduction of energy expenditure, and the lignin content was usually determined by wet chemical methods. However, the methods' heavy workload, low efficiency, huge consumption of chemicals and use of toxic reagents render them unsuitable for sustainable development and environmental protection. Chinese fir, a prevalent angiosperm tree, holds immense importance for various industries. Since our previous work found that Raman spectroscopy could accurately predict the lignin content in poplar, we propose that the lignin content of Chinese fir can be estimated by similar strategy. The results suggested that the peak at 2895 cm-1 is the optimal choice of internal standard peak and algorithm of XGBoost demonstrates the highest accuracy among all algorithms. Furthermore, transfer learning was successfully introduced to enhance the accuracy and robustness of the model. Ultimately, we report that a machine learning algorithm, combining transfer learning with XGBoost or LightGBM, offers an accurate, high-efficiency and environmental friendly method for predicting the lignin content of Chinese fir using Raman spectra.

Growth characteristics of Cunninghamia lanceolata in China

Chinese fir (Cunninghamia lanceolata) is one of southern China's most important native tree species, which has experienced noticeable climate-induced changes. Published papers (1978-2020) on tree growth of Chinese fir forests in China were collected and critically reviewed. After that, a comprehensive growth data set was developed from 482 sites, which are distributed between 102.19° and 130.07°E in longitude, between 21.87° and 37.24°N in latitude and between 5 and 2260 m in altitude. The dataset consists of 2265 entries, including mean DBH (cm), mean H (m), volume (m³), biomass (dry weight) (kg) (stem (over bark) biomass, branches biomass, leaves biomass, bark biomass, aboveground biomass, roots biomass, total trees biomass) and related information, i.e. geographical location (Country, province, study site, longitude, latitude, altitude, slope, and aspect), climate (mean annual precipitation-MAP and mean annual temperature-MAT), stand description (origin, age, canopy density and stand density), and sample regime (plot size, number and investigation year). Our results showed that (1) the best prediction of height was obtained using nonlinear composite model Height = [Formula: see text], (R² = 0.8715, p < 0.05), (2) the equation Volume = DBH²/(387.8 + 19,190/Height) (R² = 0.9833, p < 0.05) was observed to be the most suitable model for volume estimation. Meanwhile, when the measurements of the variables are difficult to carry out, the volume model Volume = 0.03957 - 0.01215*DBH + 0.00118*DBH² (R² = 0.9573, p < 0.05) is determined from DBH only has a practical advantage, (3) the regression equations of component biomass against DBH explained more significant than 86% variability in almost all biomass data of woody tissues, which were ranked as total trees (97.25%) > aboveground (96.55%) > stems (with bark) (96.17%) > barks (88.95%) > roots (86.71%), and explained greater than 64% variability in branch biomass. The foliage biomass equation was the poorest among biomass components (R² = 0.6122). The estimation equations derived in this study are particularly suitable for the Chinese fir forests in China. This dataset can provide a theoretical basis for predicting and assessing the potential of carbon sequestration and afforestation activities of Chinese fir forests on a national scale.

Predicting Potential Habitat of a Plant Species with Small Populations under Climate Change: Ostryarehderiana

Ostrya rehderiana is a famous plant species with extremely small populations. With ongoing global climate change, the extremely small populations would face more uncertainties and risks, including the loss of genetic diversity and extirpation. Thus, assessing the impact of climate change on suitable habitat of O. rehderiana is particularly important for its conservation and restoration. Here, we built niche models with climate variables and soil and human footprint variables. Furthermore, new methods were applied to avoid confounding effects between climate and soil and human footprint variables to simulate the potential habitats of O. rehderiana in current and future climates. We found that the Hargreaves climatic moisture deficit, degree-days below 0 °C, chilling degree-days, and the temperature difference between mean warmest month temperature and mean coldest month temperature, or continentality, were the most important climate factors. The topsoil USDA texture classification, topsoil cation exchange capacity of (clay), and topsoil sodicity (ESP) were the key soil factors determining the suitable distribution of O. rehderiana. Compared with soil factors, human footprint has less influence on the suitable distribution of O. rehderiana. The niche range of this species was projected to expand and shift to north in the Representative Concentration Pathway (RCP) 4.5 scenario for the 2050s. Our study results could be referenced in further extremely small populations ecological restoration studies and provide the scientific strategies for the conservation and restoration of O. rehderiana.

Estimating the distribution and productivity characters of Larix kaempferi in response to climate change

Understanding the distribution, net primary productivity (NPP) and environmental constraints of Larix kaempferi is crucial to predict how global climate change will affect its growth and future dynamics. We simulated future changes in the globally suitable distribution patterns and the NPP dynamics under different representative concentration pathways (RCPs) using MaxEnt and Physiological Principles in Predicting Growth (3-PG) models. The results showed that suitable distribution areas for Larix kaempferi were concentrated in Europe and Asia, followed by North America, under current climate conditions. Globally, about 33.75% of the suitable area was in China. Suitable areas decreased and shifted northward in Asia, Europe and China in the RCP scenarios. Larix kaempferi could adapt or move to higher latitudes/altitudes to mitigate the negative impacts of climate change. The NPP of Larix kaempferi in China was 241.85-863.57 g m^-2 a^-1 simulated by the 3-PG model after local parameterization, which was consistent with the measured NPP. Changes in NPP were predicted in future climates. When the correlations between climate factors and NPP were examined, under the more optimistic scenarios, NPP would increase significantly. The key parameters of the 3-PG model were the optimal temperature for growth, forest age, and the number of days of lost productivity in each frost period. Therefore, climate change has a quantitative and significant impact on the distribution and productivity of L. kaempferi, which was estimated successfully with the two modeling approaches. Our results will contribute to the improved cultivation, environment and management of L. kaempferi and potentially of other deciduous gymnosperms.

Using 3PG to assess climate change impacts on management plan optimization of Eucalyptus plantations. A case study in Southern Brazil

Eucalyptus plantations around the world have been largely used by the paper industry. Optimizing the management of resources is a common practice in this highly competitive industry and new forest growth models may help to understand the impact of climate change on the decisions of the optimization processes. Current optimized management plans use empirical equations to predict future forest stands growth, and it is currently impractical to replace these empirical equations with physiological models due to data input requirements. In this paper, we present a different approach, by first carrying out a preliminary assessment with the process-based physiological model 3PG to evaluate the growth of Eucalyptus stands under climate change predictions. The information supplied by 3PG was then injected as a modifier in the projected yield that feeds the management plan optimizer allowing the interpretation of climate change impacts on the management plan. Modelling results show that although a general increase of rain with climate change is predicted, the distribution throughout the year will not favor the tree growth. On the contrary, rain will increase when it is less needed (summer) and decrease when it is most needed (winter), decreasing forest stand productivity between 3 and 5%, depending on the region and soil. Evaluation of the current optimized plan that kept constant the relation between wood price/cellulose ton shows a variation in different strategic management options and an overall increase of costs in owned areas between 2 and 4%, and a decrease of cumulated net present value, initially at 15% with later stabilization at 6-8%. This is a basic comparison to observe climate change effects; nevertheless, it provides insights into how the entire decision-making process may change due to a reduction in biomass production under future climate scenarios. This work demonstrates the use of physiological models to extract information that could be merged with existing and already implemented empirical models. The methodology may also be considered a preliminary alternative to the complete replacement of empirical models by physiological models. Our approach allows some insight into forest responses to different future climate conditions, something which empirical models are not designed for.

Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China

Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity. Climate change is considered to be one of the most important threats to global biodiversity in the 21st century and will pose significant challenges to biodiversity conservation in the future. The use of niche modelling to predict changes in the suitable distribution of species under climate change scenarios is becoming a hot topic of biological conservation. In this study, we use data from China’s National Forest Continuous Inventory as well as specimen collection data of Cunninghamia lanceolata (Lamb.) Hook to run optimized Maxent models to predict potential suitable distribution of the species in the present day, 2050s, and 2070s under different climate change scenarios in China. In the modeling process, the most important uncorrelated variables were chosen, and the sample-size-adjusted Akaike information criterion (AICc) was used to select the optimal combination of feature type and regularization multiplier. Variable selection reduced the number of variables used and the complexity of the model, and the use of the AICc reduced overfitting. Variables relating to precipitation were more important than temperature variables in predicting C. lanceolata distribution in the optimal model. The predicted suitable distribution areas of C. lanceolata were different for the different periods under different climate change scenarios, with the centroids showing a degree of northward movement. The suitable distribution area is predicted to become more fragmented in the future. Our results reveal the climate conditions required for the suitable distribution of C. lanceolata in China and the likely changes to its distribution pattern in the future, providing a scientific basis for the sustainable management, protection, and restoration of the suitable habitat of this economically important tree species in the context of climate change.

Simulation of dissolved organic carbon concentrations and fluxes in Chinese monsoon forest ecosystems using a modified TRIPLEX-DOC model

Dissolved organic carbon (DOC) plays an important role in global and regional carbon cycles. However, the quantification of DOC in forest ecosystems remains uncertain. Here, the processed-based biogeochemical model TRIPLEX-DOC was modified by optimizing the function of soil organic carbon distribution with increasing depths, as well as DOC sorption-desorption efficiency. The model was validated by field measurements of DOC concentration and flux at five forest sites and Beijiang River basin in monsoon regions of China. Model validation indicated that seasonal patterns of DOC concentration across climatic zones were different, and these differences were captured by our model. Importantly, the modified model performed better than the original model. Indeed, model efficiency of the modified model increased from -0.78 to 0.19 for O horizon predictions, and from -0.46 to 0.42 for the mineral soils predictions. Likewise, DOC fluxes were better simulated by the modified model. At the site scale, the simulated DOC fluxes were strongly correlated with the observed values (R² = 0.97, EF = 0.91). At the regional scale, the DOC flux predicted in the Beijiang River basin was 16.44 kg C/ha, which was close to the observed value of 17 kg C/ha. Using sensitivity analysis, we showed that temperature, precipitation and temperature sensitivity of DOC decomposition (Q₁₀) were the most sensitive parameters when predicting DOC concentrations and fluxes in forest soils. We also found that both the percentage of DOC flux to forest net ecosystem productivity, and the retention of DOC by mineral soil were highly correlated with the amount of precipitation. Overall, our model validations indicated that the modified TRIPLEX-DOC model is a useful tool for simulating the dynamics of DOC concentrations and fluxes in forest ecosystems. We highlight that more accurate estimates of parameter Q₁₀ in deep mineral soils can reduce model uncertainty, when simulating DOC concentrations and fluxes in forest soils.

Monthly Radial Growth Model of Chinese Fir (Cunninghamia lanceolata (Lamb.) Hook.), and the Relationships between Radial Increment and Climate Factors

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is the most commonly grown afforestation species in subtropical China. It is essential that we understand the response of radial tree growth to climate factors, yet most experiments have been conducted based on total annual growth and not on monthly dynamics, which alone can detail the influence of climatic factors. In this study, we aimed to: (i) construct a monthly growth model and compare the growth rate of different social statuses of trees, and (ii) determine the response of radial increments of different social statuses to climate factors. The radial growth was monitored monthly during four years using manual band dendrometers (MBD). The data were fitted using the Gompertz function. Within-stand differences in the social status of Chinese firs resulted in growing period and growth rate length variations. The radial growth began in March, and suppressed trees—especially groups of AS1 and BS1 (suppressed trees of classes I in sites A and B)—stopped in September, whereas dominant and intermediate trees were delayed and stopped in November. The periodic monthly increment curve showed double peaks, and the maximum growth rate occurred in April and August. The peak values were affected by social status, which showed that dominant trees had the greatest radial growth rates. S-shaped Gompertz meant that monthly increment models were successfully fitted to our data, which explained more than 98% of the variation in increment data and passed the uncertainty test. Temperature and precipitation had a significant influence on radial growth, and the correlation between radial growth and air temperature was the highest. Our results also revealed that temperatures explain the double-peak features of Chinese fir. The limiting factors of radial growth changed with the seasons and were mainly affected by temperature and precipitation, which should be considered in predicting the response of tree growth to climate change.

Effects of Sucrose, Boric Acid, pH, and Incubation Time on in Vitro Germination of Pollen and Tube Growth of Chinese fir (Cunnighamial lanceolata L.)

In vitro pollen germination provides a novel approach and strategy to accelerate genetic improvement of tree breeding. Studies about pollen germination and tube growth of Chinese fir are limited. Therefore, this study aimed to investigate the effects of sucrose, boric acid, pH, and time of incubation on pollen germination and tube growth. Pollen from 9 clones were selected. In vitro germination was performed in basic media as control, and in different concentrations of sucrose (0, 10 and 15%), boric acid (0.01, 0.1 and 0.2%), and pH levels (4.5, 5 and 7). Pollen germination rates and tube growth were recorded periodically at 1, 12, 24, and 48 h. The results showed that sucrose imposes significant effects on pollen germination and tube growth. The effects are most obvious at concentration of 15%. Boric acid significantly promoted germination and tube growth. The promotion was most notable in lower concentration of 0.01%. The media adjusted to pH 7.0 boosted the germination and pollen tube growth. The optimum time of incubation was 24 and 48 h for pollen germination and tube growth, respectively. Sucrose, pH, and time of incubation were positively correlated, whereas boric acid negatively correlated with pollen germination and tube growth. This study provided experimental evidences for selecting viable pollens for Chinese fir breeding.

Desiccation Treatment and Endogenous IAA Levels Are Key Factors Influencing High Frequency Somatic Embryogenesis in Cunninghamia lanceolata (Lamb.) Hook

Cunninghamia lanceolata (Lamb.) Hook (Chinese fir) is an important tree, commercially and ecologically, in southern China. The traditional regenerating methods are based on organogenesis and cutting propagation. Here, we report the development of a high-frequency somatic embryogenesis (SE) regeneration system synchronized via a liquid culture from immature zygotic embryos. Following synchronization, PEM II cell aggregates were developmentally equivalent in appearance to cleaved zygotic embryos. Embryo and suspensor growth and subsequent occurrence of the apical and then the cotyledonary meristems were similar for zygotic and SE embryo development. However, SE proembryos exhibited a more reddish coloration than zygotic proembryos, and SE embryos were smaller than zygotic embryos. Mature somatic embryos gave rise to plantlets on hormone-free medium. For juvenile explants, low concentrations of endogenous indole-3-acetic acid in initial explants correlated with improved proembryogenic mass formation, and high SE competency. Analysis of karyotypes and microsatellites detected no major genetic variation in the plants regenerated via SE, and suggest a potential in the further development of this system as a reliable methodology for true-to-type seedling production. Treatment with polyethylene glycol (PEG) and abscisic acid (ABA) were of great importance to proembryo formation and complemented each other. ABA assisted the growth of embryonal masses, whereas PEG facilitated the organization of the proembryo-like structures. SOMATIC EMBRYOGENESIS RECEPTOR KINASE SERK) and the WUSCHEL homeobox (WOX) transcription factor served as molecular markers during early embryogenesis. Our results show that ClSERKs are conserved and redundantly expressed during SE. SERK and WOX transcript levels were highest during development of the proembryos and lowest in developed embryos. ClWOX13 expression correlates with the critical transition from proembryogenic masses to proembryos. Both SERK and WOX expression reveal their applicability in Chinese fir as markers of early embryogenesis. Overall, the findings provided evidence for the potential of this system in high fidelity Chinese fir seedlings production. Also, SE modification strategies were demonstrated and could be applied in other conifer species on the basis of our hormonal, morphological and molecular analyses.

Somatic Embryogenesis of Immature Cunninghamia lanceolata (Lamb.) Hook Zygotic Embryos

Two efficient somatic embryogenesis systems were developed in Chinese fir, the most important conifer for industrial wood production in China. Three development stages (cleavage polyembryony, dominant embryo, and precotyledon) of immature embryos derived from 25 genotypes of open-pollinated mother trees were used as initial explants. Cleavage polyembryony-stage embryos with a 12.44% induction rate was the most embryogenic response stage. The highest frequency of embryogenic callus (13.86%) induction was obtained from DCR medium supplemented with 1.5 mg L⁻¹ 2,4-dichlorophenoxyacetic acid (2,4-D) and 0.3 mg L⁻¹ kinetin (KN). An average of 53.33 early somatic embryos were produced from approximately 0.2 g (fresh weight) embryogenic callus after 2 weeks of incubation on medium supplemented with 50 μmol L⁻¹ abscisic acid (ABA) and 100 g L⁻¹ polyethylene glycol (PEG) 6000. About 53% dominant embryos have an embryogenic response after a 6-week cultivation on medium supplemented with 1.0–2.0 mg L⁻¹ benzyladenine (BA), 0.2 mg L⁻¹ naphthylacetic acid (NAA) or 2,4-D, and 0.004 mg L⁻¹ thidiazuron (TDZ). After three successive transfer cultures on medium supplemented with 1.5 mg L⁻¹ BA, 0.2 mg L⁻¹ NAA, and 0.004 mg L⁻¹ TDZ, 4.49–16.51% of the embryos developed into somatic embryos.

Effects of elevated mean and extremely high temperatures on the physio-ecological characteristics of geographically distinctive populations of Cunninghamia lanceolata

Conventional models for predicting species distribution under global warming scenarios often treat one species as a homogeneous whole. In the present study, we selected Cunninghamia lanceolata (C. lanceolata), a widely distributed species in China, to investigate the physio-ecological responses of five populations under different temperature regimes. The results demonstrate that increased mean temperatures induce increased growth performance among northern populations, which exhibited the greatest germination capacity and largest increase in the overlap between the growth curve and the monthly average temperature. However,tolerance of the southern population to extremely high temperatures was stronger than among the population from the northern region,shown by the best growth and the most stable photosynthetic system of the southern population under extremely high temperature. This result indicates that the growth advantage among northern populations due to increased mean temperatures may be weakened by lower tolerance to extremely high temperatures. This finding is antithetical to the predicted results. The theoretical coupling model constructed here illustrates that the difference in growth between populations at high and low latitudes and altitudes under global warming will decrease because of the frequent occurrence of extremely high temperatures.