Forest Growth Research Articles

Can triad forestry reconcile Europe's biodiversity and forestry strategies? A critical evaluation of forest zoning.

Balancing increasing demand for wood products while also maintaining forest biodiversity is a paramount challenge. Europe's Biodiversity and Forest Strategies for 2030 attempt to address this challenge. Together, they call for strict protection of 10% of land area, including all primary and old growth forests, increasing use of ecological forestry, and less reliance on monocultural plantations. Using data on country wide silvicultural practices and a new database on strict forest reserves across Europe, we assess how triad forest zoning could help meet these goals. Our analysis reveals that zoning in Europe is overwhelmingly focused on wood production, while there has been little concomitant protection of forests in strict reserves. Moreover, most strict forest reserves are < 50ha in size, likely too small to capture the minimum dynamic area necessary to sustain many taxa. We outline research priorities to meet future demands for timber while minimizing the impact on native biodiversity.

Unveiling coastal ecosystem dependencies: multifactorial analysis of climate change influencing mangrove system in the United Arab Emirates over the period 1990–2020

Mangroves are an integral part of the coastal ecosystems, demonstrating resiliency against adverse anthropogenic and environmental effects. They provide blue carbon stock and security against coastal erosion and act as a nutrient source for many aquatic inhabitants along with providing raw materials for human consumption. However, mangroves continue to perish due to several climate factors. Past research has indicated some environmental factors influencing the growth and sustenance of mangrove forests. This paper aims to study the impact of the climate changes on the UAE mangrove forests during the period 1990–2020. The climate change related factors studied include surface temperature, sea-level rise, salinity, and coastal inundation. Here, remote sensing techniques and supervised machine learning methods were utilized to derive the climatic factors. The correlations between mangrove and these factors were investigated as well. It was revealed that Land Surface Temperature is closely related to mangrove and that mangrove biomass was highest in the land surface temperature range 30–35 °C. Results have not shown a clear correlation between tidal inundation and mangroves. Furthermore, outputs also showed that mangrove biomass was negatively affected by sea-level rise. The analysis showed a general positive relationship between mangrove and salinity corresponding to an increase in mangrove biomass which was only found when conducting spatial analysis, however site-specific analysis (i.e., temporal) showed an increase in mangrove density with decrease in salinity. These findings could potentially aid in facilitating the identification of suitable new sites for plantation or existing sites for rehabilitation of mangroves in UAE in addition to formulating policies at the highest level for mangrove conservation.

Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation

BackgroundModern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative management strategies. We developed plausible future management scenarios based on factorial combinations of restoration-oriented thinning prescriptions, prescribed fire, and wildland fire use. Results were assessed continuously for a 100-year simulation period, which provided a unique assessment of tradeoffs and benefits among seven primary topics representing social, ecological, and economic aspects of resilience.ResultsProjected climatic changes had a substantial impact on modeled wildfire activity. In the Wildfire Only scenario (no treatments, but including active wildfire and climate change), we observed an upwards inflection point in area burned around mid-century (2060) that had detrimental impacts on total landscape carbon storage. While simulated mechanical treatments (~ 3% area per year) reduced the incidence of high-severity fire, it did not eliminate this inflection completely. Scenarios involving wildland fire use resulted in greater reductions in high-severity fire and a more linear trend in cumulative area burned. Mechanical treatments were beneficial for subtopics under the economic topic given their positive financial return on investment, while wildland fire use scenarios were better for ecological subtopics, primarily due to a greater reduction in high-severity fire. Benefits among the social subtopics were mixed, reflecting the inevitability of tradeoffs in landscapes that we rely on for diverse and countervailing ecosystem services.ConclusionsThis study provides evidence that optimal future scenarios will involve a mix of active and passive management strategies, allowing different management tactics to coexist within and among ownerships classes. Our results also emphasize the importance of wildfire management decisions as central to building more robust and resilient future landscapes.

Edge cases: fragmentation and ecosystem processes in temperate forest landscapes

Temperate forests are the most fragmented forest biome, yet current understanding of fragmentation effects on ecosystem processes, such as carbon (C) cycling, is rooted in tropical forest research. We review the effects of persistent fragmentation on temperate forest ecosystem processes and quantify the extent to which the US national forest inventory and land‐cover maps represent forest edge area. We found systematic underrepresentation of forest edges across all methods. As compared with very high resolution (1 m) maps, conventional 30‐m resolution forest cover maps underestimated forest edge area by 16.4%, on average. Accounting for all forest edge area and edge effects on forest structure and growth resulted in a 14.8% median increase in aboveground forest C estimates, with 23.8% and 74.2% increases in agriculturally and urban dominated counties, respectively. We conclude by proposing improvements to forest inventories, maps, and models to better represent the fragmented temperate forest landscape.

Climate-sensitive models of tree mortality based on lifetime analysis and irregular permanent-plot remeasurements

Climate change has driven forest growth modellers to develop different climate sensitivity implementations (CSI) for their models. Among others, a model can rely on annual climate variables or average climate variables, such as 30-year normals. The novelty of this study was to develop a framework based on lifetime analysis to enable annual or average CSI in empirical models of tree mortality. Using this framework, we compared models of individual tree mortality based on an annual CSI with similar models relying on two average CSIs, one using interval-averaged climate variables, and the other, 30-year normals. We fitted these models to permanent-plot data of eight species in Ontario and tested the effects of summer and winter temperature as well as spring and summer precipitation in the models. Our results showed that the annual CSI was not superior to the average CSIs, but could be a valid alternative for some species. Warmer winter temperature was detrimental to the survival of Abies balsamea, Betula papyrifera, Picea glauca, and Pinus strobus, whereas greater spring and summer precipitation resulted in greater mortality occurrence for Picea mariana, Pinus banksiana, and Populus tremuloides. In most cases, the effects of climate variables were contrary to our initial hypotheses. We conclude that the effects of climate on tree mortality occurrence interact with other factors such as species distribution and ecophysiology.

Response of Larix sibirica Radial Growth to Climate Change in Kanas, Northern Xinjiang, China

Understanding how forest ecosystems respond to climate variability is critical for predicting the impacts of climate change on semi-arid and temperate regions. This study examines the climatic drivers of radial growth in Larix sibirica Ledeb in the Kanas Lake region, northern Xinjiang, China, to explore how climate change may alter forest growth patterns. Using tree-ring chronologies, we examine the relationships between temperature, precipitation, and drought conditions, as well as the influence of large-scale atmospheric circulation patterns on growth. Results indicate that high summer temperatures negatively affect tree growth, while adequate precipitation plays a crucial role in mitigating water stress, especially during key growth periods. Positive correlations with the Palmer Drought Severity Index further underscore the importance of long-term moisture availability. Moreover, the study highlights the role of the El Niño-Southern Oscillation in influencing moisture transport, with significant correlations between sea surface temperatures in the Niño 4 region and tree-ring growth. Future growth simulations under two climate scenarios suggest that moderate warming (SSP 2–4.5) may enhance growth, while more extreme warming (SSP 5–8.5) introduces greater uncertainty and potential growth instability. These findings provide critical guidance for forest management strategies in the face of climate change.

An Improved Grid-Based Carbon Accounting Model for Forest Disturbances from Remote Sensing and TPO Survey Data

Forest disturbance is one of the main drivers of forest carbon flux change. How to accurately estimate the carbon flux caused by forest disturbance is an important research problem. In a previous study, the authors proposed a Grid-based Carbon Accounting (GCA) model that used remote sensing data to estimate forest carbon fluxes in North Carolina from 1986 to 2010. However, the original model was unable to track legacy emissions from previously harvested wood products and was unable to consider forest growth conditions before and after forest disturbance. This paper made some improvements to the original GCA model to enable it to track fluxes between all major aboveground live carbon pools, including pre-disturbance growth and growth of undisturbed forests, which were not included in the initial model. Based on existing timber product output (TPO) survey data and annual TPO records inversed from remote sensing data, we also worked to clarify the distribution ratios of removed C between slash and different wood product pools. Specifically, the average slash ratio for North Carolina was calculated from the difference between the C removed and the C flowing into the wood product as calculated from TPO survey data. County- and year-specific ratios were then calculated using the annual TPO records obtained from remote sensing and TPO survey data, dividing the removed remaining C into pools P1, P10, and P100, which were then applied to each 30 m pixel based on the county and year to which the pixel belonged. After compensating for these missing legacy emissions and adjusting forest growth rates from Forest Inventory and Analysis (FIA) data, we estimated a net carbon sink of 218.1 Tg of the flux associated with live aboveground biomass and harvested wood products from North Carolina woodlands over the 25-year study period (1986–2010). This estimate is close to the greenhouse gas emission and sink data provided by the U.S. Department of Agriculture for North Carolina and is comparable to estimates reported by several other studies.

Permafrost instability negates the positive impact of warming temperatures on boreal radial growth

Climate warming can alleviate temperature and nutrient constraints on tree growth in boreal regions, potentially enhancing boreal productivity. However, in permafrost environments, warming also disrupts the physical foundation on which trees grow, leading to leaning trees or "drunken" forests. Tree leaning might reduce radial growth, undermining potential benefits of warming. Here, we found widespread radial growth reductions in southern latitude boreal forests since the 1980s. At mid latitudes, radial growth increased from ~1980 to ~2000 but showed recent signs of decline afterward. Increased growth was evident since the 1980 s at higher latitudes, where radial growth appears to be temperature limited. However, recent changes in permafrost stability, and the associated increased frequency of tree leaning events, emerged as a significant stressor, leading to reduced radial growth in boreal trees at the highest latitudes, where permafrost is extensive. We showed that trees growing in unstable permafrost sites allocated more nonstructural carbohydrate reserves to offset leaning which compromised radial growth and potential carbon uptake benefits of warming. This higher allocation of resources in drunken trees is needed to build the high-density reaction wood, rich in lignin, that is required to maintain a vertical position. With continued climate warming, we anticipate widespread reductions in radial growth in boreal forests, leading to lower carbon sequestration. These findings enhance our understanding of how climate warming and indirect effects, such as ground instability caused by warming permafrost, will affect boreal forest productivity in the future.

Quantifying forest stocking changes in Sundarbans mangrove using remote sensing data

The Sundarbans, the world's largest mangrove ecosystem, faces significant challenges from forest stocking changes due to natural and anthropogenic factors. Scientific studies on these changes are not available. This study uses remote sensing techniques to quantify long-term changes in mangrove forest canopy height, aboveground biomass (AGB), and forest carbon stocks. Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) LiDAR data sets. We assessed canopy height and forest stocking changes, and changes in AGB carbon fluxes over the last two decades in the Sundarbans mangrove. Calibrated SRTM data provided tree canopy height (TCH) estimates for 2000, while calibrated GEDI LiDAR data facilitated assessments of TCH for 2023. The findings show substantial changes in TCH, AGB, and carbon stock distribution in the Sundarbans mangrove between 2000 and 2023. TCH in the 5-10 m class notably increased from 58.3% in 2000 to 70.8% in 2023, while TCH above 15 m decreased, and those under 5 m regrew. Higher AGB carbon classes (>50 tons ha⁻1) decreased, with only the lowest class (<50 tons ha⁻1) increasing, indicating notable forest carbon stock reduction due to deforestation and forest degradation. Approximately 1571 Kt of AGB carbon were lost over 23 years, around 4% of the total stock. The driving forces of forest stocking changes could be changes in the dynamic energy balance from the estuarine river system and the tidal waves, relative sea-level change, increases of salinity in various zones of Sundarbans mangrove, other anthropogenic factors, etc. This research provides valuable insights into Sundarbans mangrove dynamics, aiding global forest degradation and forest growth in understanding forest stocking change and their role in terrestrial carbon flux and global climate change. The results will be helpful for the forest manager in identifying the locations where there is forest degradation or enhancement of forest growing stock and planning any silvicultural operations that are needed in the forest. This is also useful for climate change scientists to understand probable man-made or natural driving forces of the changes in forest stocking in the Sundarbans mangrove forests. It underscores the urgency of integrating deforestation and forest degradation into climate strategies for effective carbon management and conservation efforts, that align with carbon sequestration goals, contributing to broader climate change mitigation strategies.

Podzolization in a 150-year chronosequence of soils under pine timber forest on inland dunes in the Toruń Basin (Northern Poland)

Studies on mechanisms and rates of podzolization have mostly been realized in natural landscapes and chronosequences. In this work, an artificial chronosequence of soils managed as a habitat for regularly planted and clear-cut, even-aged, monocultural pine stands (Pinus sylvestris) varying in age between 27 and 150 years has been investigated to determine changes in soil properties and development of genetic horizons with time and growth of pine trees. The soils in five profiles under 27-, 52-, 70-, 105- and 150-year-old pine stands are developed from poor aeolian quartz sands and situated in similar habitat conditions to one another on northern slopes of inland dunes in the Toruń Basin (northern Poland).The studied soils represent consecutive, early stages of podzolization corresponding to the age of the tree stands. In the organic horizon, the whole sequence of three subhorizons typical of the mor type of humus (Oi-Oe-Oa) develops after ∼100 years. Organic carbon, pedogenic Fe and Al content in the eluvial (AE-E) horizon achieve relative equilibrium after 70 years of forest growth. In the illuvial (Bhs-Bs) horizon, these elements continue to accumulate along the whole chronosequence and its development is certainly not finished after 150 years. Only the soils of more than 100-year-old fulfill the criteria of Podzols according to the WRB (2022) soil classification. Younger soils, although undoubtedly podzolized, have to be classified as Arenosols. The youngest profiles (under 27 and 52-year-old pines) have inherited traces of a former cycle of pedogenesis that ran under the previous generation of pine forest. The soil cover of dune areas in the Torun Basin, which have been managed as productive pine timber forests over the last two centuries, is entirely secondary and polycyclic and does not achieve maximal developmental stage and ecological efficiency, including carbon sequestration.

Vulnerability of Global Pine Forestry's Carbon Sink to an Invasive Pathogen-Vector System.

The substantial contribution of northern forest growth to the global increase of biomass carbon stock is well documented. However, the ecological consequences of pest- and disease-related losses in these forests have not received comparable attention. This study highlights that pine species are major contributors to carbon stocks in Northern Hemisphere. The total carbon storage of Pinus in the Northern Hemisphere was estimated at 70,726 teragrams of carbon (TgC; 17.7% of the total forest carbon 478,012 TgC), accounting for 4.9%, 28.4%, and 12.5% of the total carbon storage in the forests of Asia, Europe, and North America, respectively. However, pine trees were under threat from an invasive complex involving the pine wood nematode (Bursaphelenchus xylophilus) and Japanese pine sawyer beetle (Monochamus spp.). Since 1977, this complex resulted in a carbon sink deficit of 1857 TgC (18% of the carbon currently stored in Europe's live tree biomass) in northern pine ecosystems. The carbon losses attributed to B. xylophilus exceeded those caused by wildfires, which are typically regarded as the primary factor of forest disturbances. Furthermore, the contributions of environmental variables indicate that the expected northward shift in precipitation patterns will exacerbate B. xylophilus threats, endangering 78% of the boreal forests across Eurasia by 2100. Among these high-risk areas, 62% contributed significantly to global carbon sink, and 42% was protected forests. Following the present trend, carbon losses caused by the B. xylophilus complex could exceed 39% of the total carbon storage in terrestrial ecosystems. This study provides comprehensive datasets that detail the global distribution and high-risk habitats of pine species and B. xylophilus vector beetles in affected countries. Our findings underscore the substantial risk of carbon losses posed by B. xylophilus to northern pine forests, with potential implications for global carbon dynamics and the achievement of international goals related to "carbon peak" and "carbon neutrality."

Divergent Ecological Restoration Driven by Afforestation Along the North and South Banks of the Yarlung Zangbo Middle Reach

ABSTRACTOver the past four decades, continuous afforestation in the river valley of the Yarlung Zangbo Middle Reach has effectively migrated the land degradation and enhanced the local eco‐environment. Different orientations of north and south banks (i.e., sun‐facing and shade‐facing) generate microclimates, but the diverse growth patterns of the planted forests along different banks remain unknown. In this study, long‐term Landsat observations were introduced to investigate the microclimatic effects on the growth patterns of planted forests and their subsequent effects on the land restoration during 1988–2020. Results showed that the south bank experienced a higher afforestation‐induced greening trend than the north bank, as indicated by normalized difference vegetation index (NDVI) rates of 0.0117 and 0.0081 year−1, respectively. The growth of planted forests on the north bank was more sensitive to the distance from riverway than that on the south bank, with the NDVI gradients of −0.0708 and −0.0540 km−1, highlighting a server drought stress on the north bank. Benefited from the continuous afforestation, 79% and 95% of sandy lands on the north and south banks had been restored by 2020. In summary, the microclimatic difference between banks, attributed to different solar illuminations and drought stresses, induce the diverse ecological restoration conditions. These findings offer important insights that future afforestation strategies should consider the microclimatic effect to maximize ecological benefits.

Advancing Forest Plot Surveys: A Comparative Study of Visual vs. LiDAR SLAM Technologies

Forest plot surveys are vital for monitoring forest resource growth, contributing to their sustainable development. The accuracy and efficiency of these surveys are paramount, making technological advancements such as Simultaneous Localization and Mapping (SLAM) crucial. This study investigates the application of SLAM technology, utilizing LiDAR (Light Detection and Ranging) and monocular cameras, to enhance forestry plot surveys. Conducted in three 32 × 32 m plots within the Tibet Autonomous Region of China, the research compares the efficacy of LiDAR-based and visual SLAM algorithms in estimating tree parameters such as diameter at breast height (DBH), tree height, and position, alongside their adaptability to forest environments. The findings revealed that both types of algorithms achieved high precision in DBH estimation, with LiDAR SLAM presenting a root mean square error (RMSE) range of 1.4 to 1.96 cm and visual SLAM showing a slightly higher precision, with an RMSE of 0.72 to 0.85 cm. In terms of tree position accuracy, the three methods can achieve tree location measurements. LiDAR SLAM accurately represents the relative positions of trees, while the traditional and visual SLAM systems exhibit slight positional offsets for individual trees. However, discrepancies arose in tree height estimation accuracy, where visual SLAM exhibited a bias range from −0.55 to 0.19 m and an RMSE of 1.36 to 2.34 m, while LiDAR SLAM had a broader bias range and higher RMSE, especially for trees over 25 m, attributed to scanning angle limitations and branch occlusion. Moreover, the study highlights the comprehensive point cloud data generated by LiDAR SLAM, useful for calculating extensive tree parameters such as volume and carbon storage and Tree Information Modeling (TIM) through digital twin technology. In contrast, the sparser data from visual SLAM limits its use to basic parameter estimation. These insights underscore the effectiveness and precision of SLAM-based approaches in forestry plot surveys while also indicating distinct advantages and suitability of each method to different forest environments. The findings advocate for tailored survey strategies, aligning with specific forest conditions and requirements, enhancing the application of SLAM technology in forestry management and conservation efforts.

Does cap-and-trade policy promote Forest cover? Evidence from China

Cap-and-trade policies have been widely implemented in areas such as pollutant emissions, energy, and water rights in order to achieve environmental regulatory objectives. In 2018, Linyi City, China, implemented the Innovative Forest Cover Trading Policy (IFCTP), extending the application of cap-and-trade policies to the forest resources sector in an effort to stimulate afforestation initiatives and increase urban forest coverage. However, the IFCTP's effectiveness in increasing forest coverage remains unproven. This study evaluates the impact of IFCTP on forest cover expansion by improving the Synthetic Control Method (SCM), which incorporates panel data from 283 prefecture-level cities in China (2003–2021) to select cities with similar characteristics to Linyi. This improved SCM allows for a more accurate counterfactual “Synthetic Linyi" for comparison. Additionally, land use data, mediation analysis, and semi-structured interviews are used to explore the mechanisms behind the policy's effects. The analysis reveals that the IFCTP led to a 2.2% increase in Linyi's forest coverage within four years, primarily through labor force input and forest management improvements. These findings provide broader insights into the applicability of similar afforestation policies in regions with comparable ecological and socio-economic conditions, highlighting the potential of market-based policies like IFCTP to combat deforestation and foster sustainable forest growth.

Edge effect and species richness modulate biomass stocks and change over time in secondary forest fragments in the subtropical Atlantic Forest

ABSTRACT Background Above-ground biomass (AGB) and its temporal dynamics are key parameters of forest ecosystems, related to their resilience and capacity to fix atmospheric carbon. AGB is related to species richness, composition, forest structure, soils and climate. In human-modified landscapes, fragmentation and human pressure may change the nature of these relationships. Aims Our aim was to quantify how species richness and composition, leaf area index, and edge effect were related to biomass stocks and growth in fragmented sub-tropical secondary forests. Methods We tested the relationship between leaf area index, tree species richness and composition, edge effect and AGB stocks in secondary forest stands in the Atlantic Forest using multiple linear models on data from 104 sites. Results Our results show that biomass stocks were related to species richness, distance to forest edge and the interaction of both (R2 = 0.25; p < 0.05). Biomass change showed positive relationships with pioneer species richness and distance to edge, and negative relationship with the interaction of total species richness and distance to edge (R2 = 0.15; p < 0.05). Conclusion Edge effect can affect AGB dynamics directly and indirectly, by weakening the positive effects of species richness and composition on biomass. AGB loss at some sites suggests that some fragments are under chronic disturbance or may be experiencing delayed mortality due to fragmentation.

Evaluating forest aboveground biomass estimation model using simulated ALS point cloud from an individual-based forest model and 3D radiative transfer model across continents

Area-based approach (ABA) has been widely employed for estimating forest aboveground biomass (AGB) using airborne laser scanning (ALS) data. However, its scalability is limited due to challenges in model generalization across different forest types and regions. The selection of sensitive variables from ALS data is crucial for constructing robust forest AGB estimation models, yet this selection varies significantly among forest types and regions. Traditionally, assessing the influence of variable selection is hindered by the lack of accurate reference forest AGB values. Computer simulation-based method provides a perspective for exploring these challenges. This study employs an individual-based forest growth process model, FORMIND, coupled with a 3D radiative transfer model (RTM), LESS, to evaluate the transferability of ABA-based forest AGB estimation models and the generalization of ALS-derived variables. We used six virtual 3D forest scenes and two real-world forest sites, representing a range of global forest types, along with their simulated ALS data, to develop a forest AGB estimation model using the random forest algorithm, which allowed us to analyze the importance of various variables. We assessed model transferability through cross-comparison. Additionally, we validated the model using field plots and ALS data collected from two distinct regions. The results showed that the canopy surface area and volume extracted using the α-shape algorithm and parameters fitted from the Weibull distribution are vital variables when using ALS for forest AGB estimation across forest types and regions. Incorporating these variables into the model significantly improves the accuracy of forest AGB estimation. The optimized model achieved a R2 of 0.945, a RMSE of 34.22 t/ha, and a MAE of 20.53 t/ha. Our study not only deepens the understanding of the relationship between forest vertical structural metrics and AGB but also highlights the potential of computer simulation as a tool for refining the estimation of forest structural parameters.

Climate and Altitude Drive Spatial and Temporal Changes in Forests on the Eastern Tibetan Plateau—Evidence from the Shaluli Mountain

Forests are widely distributed in terrestrial ecosystems, covering about one-third of the global land area. They play a key role in sequestering carbon, releasing oxygen, mitigating climate change, and maintaining ecosystem balance. The ecology of the Tibetan Plateau is very fragile, but the impact of environmental change on regional forest ecosystems is not yet clear. Located in the Eastern Tibetan Plateau, the Shaluli Mountain has the richest biodiversity and the widest distribution of forests on the Tibetan Plateau. Assessing the dynamics of forest change is the basis for correctly formulating forest management measures, and is important for regional biodiversity conservation. However, traditional field surveys have the shortcomings of high cost, being time-consuming, and having poor regional coverage in forest dynamics monitoring. Remote sensing methods can make up for these shortcomings. Therefore, in this study, satellite remote sensing images were used to extract forest information from 2000 to 2020 in Shaluli Mountain, and the main drivers of forest change were analyzed with full consideration of the Spatially Stratified Heterogeneity (SSH) of environmental factors. The results found that the forest area increased from 23,144.20 km2 in 2000 to 28,429.53 km2 in 2020, and the average Percentage of Forest Cover (PFC) increased from 19.76% to 21.67%, with significant improvement in forest growth. The annual minimum temperature (TMN), altitude, annual maximum temperature (TMX), and annual precipitation (PRE) were the main driving factors of forest change, with an average driving power (q-value) of 0.4877, 0.2706, 0.2342, and 0.2244, and TMN was the primary limiting factor for forest growth. In addition, the driving power of all environmental factors on forest change increased from 2000 to 2020. The results of this study can provide a basis for the development of forest management strategies, and provide reference materials for regional biodiversity conservation.

Limitation of summer extreme high temperatures on radial growth relieve with increasing latitude in subtropics

Global warming has induced an increase in the intensity and frequency of summer extreme high temperature events in Chinese subtropical forest, which contributes to a large component of net primary ecological production among global forests. However, how summer extreme high temperature events would influence tree radial growth in these humid subtropical forest remains unclear. We investigated the non-linear response of tree radial growth to temperature, soil moisture and their mixed effect across broad latitude gradients in Chinese subtropical forests, using a method of modelling cambial growth kinetics of Schima superba. The results showed that radial growth was constrained by summer extreme high temperatures and this limiting effect relieved from south to north. However, we also found a growth constraint imposed by soil moisture during spring and autumn, which intensified toward northern sites. Coincidentally, the radial growth pattern showed a distinct transition from bimodal to unimodal from South to North sites, with no significant changes in cambium phenology over the time scale from 1986 to 2014 being observed. In general, we determined that limitation of extreme high temperatures on radial growth relieve with increasing latitude in subtropics. This study provides a theoretical basis for promoting the accurate assessment of carbon sink potential and for predicting future forest dynamics in subtropics.

A Study on the Growth Model of Natural Forests in Southern China Under Climate Change: Application of Transition Matrix Model

This study establishes a climate-sensitive transition matrix growth model and predicts forest growth under different carbon emission scenarios (representative concentration pathways RCP2.6, RCP4.5, and RCP8.5) over the next 40 years. Data from the Eighth (2013) and Ninth (2019) National Forest Resource Inventories in Chongqing and climate data from Climate AP are utilized. The model is used to predict forest growth and compare the number of trees, basal area, and stock volume under different climate scenarios. The results show that the climate-sensitive transition matrix growth model has high accuracy. The relationships between the variables and forest growth, mortality, and recruitment correspond to natural succession and growth. Although the number of trees, basal area, and stock volume do not differ significantly for different climate scenarios, the forest has sufficient seedling regeneration and large-diameter trees. The growth process aligns with succession, with pioneer species being replaced by climax species. The proposed climate-sensitive transition matrix growth model fills the gap in growth models for natural secondary forests in Chongqing and is an accurate method for predicting forest growth. The model can be used for long-term prediction of forest stands to understand future forest growth trends and provide reliable references for forest management. Forest growth can be predicted for different harvesting intensities to determine the optimal intensity to guide natural forest management in Chongqing City. The results of this study can help formulate targeted forest management policies to deal more effectively with climate change and promote sustainable forest health.

Differentiated growth of the most widely planted conifer in response to extreme droughts across semi-arid regions in Northern China

Global warming is leading to more frequent and intense drought events, exerting unprecedented pressure on forest growth. Although post-drought recovery in plantation growth has been studied enormously, the variation of planted populations across the whole distribution range of a species is not well understood. In this study, the growth suitability of the most widely planted conifer species in dry lands of northern China, Mongolian Scots pine (Pinus sylvestris var. mongolica), was estimated, based on tree-ring data sampled in 289 plots of afforestation across most of its planting range. According to changes in the hydrothermal condition during the last forty years (1980–2018), the distribution range was divided into three parts: warming, warming-wetting, and non-significant trends (NT) regions. Two severe droughts in 2000 and 2007 were identified using the Standardized Precipitation Evapotranspiration Index (SPEI). Then, the resistance (Rt), recovery (Rc), and resilience (Rs) growth indices were calculated and compared among these three parts. The growth of planted Mongolian Scots pine has overall significantly increased from 1980 to 2018 (p < 0.001). The pine plantations in warming regions were sensitive to annual precipitation, while warming-wetting regions were more influenced by the growing season climate. Pines reverted to pre-drought growth levels within 3 years after the drought event in 2000 but failed in 2007, and populations in the warming region showed significantly lower post-drought recovery. Furthermore, high pre-drought growth levels were linked to low Rs in both drought events (p < 0.001). Post-drought precipitation enhanced the Rc of plantations, compensating for the growth reduction caused by droughts. Soil moisture during the drought events enhanced Rt and Rs. The Rt and Rs indices decreased significantly with the age of plantations (p < 0.05). Overall, our results revealed that pre-drought growth and post-drought precipitation were key factors influencing the resilience of planted Mongolian Scots pine. Besides, the plantations experiencing wetting trends revealed favorable drought resilience and stable radial growth, which indicated promising potential for planted Mongolian Scots pine in those areas. Controlling the age of plantations seems to be crucial for maintaining drought resilience in large-scale plantations and maximizing ecological benefits.