Forest Age Research Articles

Forest age estimation in northern Arkhangelsk region based on machine learning pipeline on Sentinel-2 and auxiliary data

Tree age is one of the key characteristics of a forest, along with tree species and height. It affects management decisions of forest owners and allows researchers to analyze environmental characteristics in support of sustainable development. Although forest age is of primary significance, it can be unknown for remote areas and large territories. Currently, remote sensing (RS) data supports rapid information gathering for wide territories. To automate RS data processing and estimate forest characteristics, machine learning (ML) approaches are applied. Although there are different data sources that can be used as features in ML models, there is no unified strategy on how to prepare a dataset and define a training task to estimate forest age. Therefore, in this work, we aim to conduct a comprehensive study on forest age estimation using remote sensing observations of the Sentinel-2 satellite and two ML-based approaches for forestry inventory data, namely stand-based and pixel-based. We chose the CatBoost algorithm to assess these two approaches. To establish the robustness of the pipeline, an in-depth analysis is conducted, embracing diverse scenarios incorporating dominant species information, tree height, Digital Elevation Model (DEM), and vegetation indices. We performed experiments on forests in the northern Arkhangelsk region and obtained the best Mean Absolute Error (MAE) result of 7 years in the case of the stand-based approach and 6 years in the case of the pixel-based approach. These results are achieved for all available input data such as spectral satellites bands, vegetation indices, and auxiliary forest characteristics (dominant species and height). However, when only spectral bands are used, the MAE metric is the same both for per-pixel and per-stand approaches and equals 11 years. It was also shown that, despite high correlation between forest age and height, only height can not be used for accurate age estimation: the MAE increases to 18 and 26 years for per-pixel and per-stand approaches, respectively. The conducted study might be useful for further investigation of forest ecosystems through remote sensing observations.

Variation in the physical properties of soil in relation to natural and anthropogenic factors in the hilly loess region of China

Soil particle size distribution (PSD), bulk density (BD), saturated hydraulic conductivity (Ks), soil water content (SWC) and generalized soil structure index (GSSI) are key physical properties for vegetation growth and are easily affected by natural and anthropogenic factors. However, how these soil physical properties respond to land use, slope aspect, slope position, and their interactions are less clearly understood. Here, an experiment with three land uses (cropland, grassland, and black locust [Robinia pseudoacacia L.] forests after 4, 9, 15, and 19 years of restoration), two slope aspects (south and north slope) and two slope positions (up and down slope) were conducted in the hilly loess region of China. The results showed the following: (1) The variation in different physical properties were driven by different factors of land use, slope aspect, slope position and their interactions. (2) The 9, 15 and 19 year old locust forests significantly decreased the BD by 6.75 %–19.32 % and increased the Ks by 69.96 %–195.97 % compared with grassland, while the cropland had higher SWC and GSSI values than the grassland and locust forests. (3) Soil physical properties were higher on the north slope than on the south slope and were larger on the down slope than on the up slope. (4) The BD, Ks, SWC, and GSSI of locust forests displayed different changes with the restoration year. (5) The key factor affecting forest growth and soil quality improvement varied with forest ages. Overall, 19 year old locust was the most effective at improving the BD and Ks. Furthermore, slope aspect, slope position and restoration time should be considered when evaluating the response of physical properties to land uses.

Source or decomposition of soil organic matter: what is more important with increasing forest age in a subalpine setting?

Afforestation has been the dominant land-use change in the Swiss Alps during the last decades which has not only the potential to increase soil organic carbon sequestration, but it has also the potential to alter soil organic matter (SOM) dynamics through the vegetation shift and change in organic matter (OM) input into soils. The effects of afforestation on SOM dynamics, however, are still not fully understood as specific sources of OM and modifications of soil processes influencing decomposition and preservation remain largely unknown on alpine to subalpine slopes. Within this study we aimed to identify the potential sources and the decomposition of OM in a subalpine afforestation chrono-sequence (0–130 years) with Norway spruce (Picea abies L.) on a former pasture by using a multi-proxy molecular marker approach. We observed that leaf-derived OM plays an essential role in the pasture areas, while root-derived OM only plays a minor role in pasture and forest areas. Needle-derived OM represents the dominant source of SOM with increasing forest age, while understory shrubs and moss also contribute to the OM input in younger forest stand ages. However, needle litter and buildup of organic layers and subsequently less input of fresh OM from organic horizons to mineral soil can result in increased OM decomposition in mineral soils rather than contributing to additional SOM stabilization in mineral soils. This was most pronounced in the oldest forest stand (130-year-old) in the investigated afforestation sequence, particularly in deeper soil horizons (10–45 cm). Thereby, our study provides new insights into SOM dynamics following afforestation, especially with respect to the long-term SOM sequestration potential of afforestation of subalpine pasture soils.

Ground beetle assemblages inhabiting various age classes of Norway spruce stands in north-eastern Poland.

Assemblages of epigeic ground beetles living in Norway spruce forests in north-eastern Poland in three age ranges: young: 20-30 years (A); middle-aged: 40-50 years (B); old: 70-80 years (C) were investigated. In each age category, 4 plots with 5 Barber traps were set up. Ground beetle assemblages were compared in terms of their abundance, species richness, and the Shannon H' index value. Quantitative ecological description of the carabids captured in the analysed age-classes of Norway spruce forests was performed, and the values of the mean individual biomass (MIB) were calculated. To determine the correlation between mean individual biomass and abundance of various ecological groups of carabid beetles, the Spearman rank correlation coefficient was calculated. The assemblages of ground beetles living in the Norway spruce forests in north-eastern Poland were characterised by quite large species richness (44 species in total). There were significant differences in species richness among the different ages of Norway spruce forests. The oldest Norway spruce stands (70-80 years old) had a smaller number of species and specimens of ground beetles as well as the highest MIB values in comparison with the younger spruce forests A and B. The results revealed that high MIB values were positively correlated with the presence of large ground beetle species with higher moisture requirements. Lower values of the MIB index were due to the presence of smaller open habitat macropterous species, with the spring type of breeding and associated with open areas.

Trade-offs between forest carbon sinks and multidimensional forest values: from assessment to management strategies

Forests are one of the subjects that can effectively mitigate climate change and are important for achieving carbon sequestration. In order to determine the maximum carbon sequestration of forests and the optimal management mode, this paper selected several indicators related to forest carbon sequestration and determined the main influencing indicators and mechanisms through regression significance analysis, and concluded that the selection of forest age and harvesting intensity have an important influence on the carbon sequestration effect and sustainability of forests. Based on the above analysis, we constructed a model of logging intensity and forest carbon sequestration, and brought in the forest data of each province to arrive at the optimal logging intensity of 23%-30%. Second, in order to determine the optimal comprehensive benefits of forests, this paper extends the model to consider forest values in more dimensions and determine the corresponding indicators, and uses the entropy weight method to determine their contribution rates to construct a comprehensive forest evaluation model. Using this model, this study measures and analyzes the Changbai Mountain forest area and Hainan forest area, and then derives the corresponding forest management strategies to maximize their comprehensive benefits.

Remote Sensing Inversion and Mapping of Typical Forest Stand Age in the Loess Plateau

The accuracy of vegetation indices (VIs) in estimating forest stand age is significantly inadequate due to insufficient consideration of the differences in the physiological functions of forest ecosystems, which limits the accuracy of carbon sink simulation. In this study, remote sensing inversion and mapping of forest stand age were carried out on the Loess Plateau under consideration of the remote sensing mechanism of VIs and the physiological function and canopy structure of the forest using multiple linear regression (MLR) and random forest (RF) models. The main conclusions are as follows: (1) The canopy reflectance of different forest stands has a significant change pattern, and the older the forest stands, the lower the NIR reflectance. The relationship between forest stands and red edge is the most significant, and r is 0.53, and the relationship between Simple Ratio Index (SR), near-infrared reflectance of vegetation (NIRv), normalized difference vegetation index (NDVI), Global Vegetation Index and forest stands is more nonlinear than linear. (2) Principal component analysis (PCA) of canopy spectral information shows that SR, NDVI and red edge (B5) could explain 98% of all spectral information. SR, NDVI and red edge (B5) were used to construct a multiple linear regression model and random forest (RF) algorithm model, and RF has high estimation accuracy (R2 = 0.63). (3) The accuracy of the model was evaluated using reference data, and it was found that the accuracy of the RF model (R2 = 0.63) was higher than that of the linear regression model (R2 = 0.61), but both models underestimated the forest stand age when the forest stand age was greater than 50a, which may be caused by the saturation of the reflectance of the old forest canopy. The RF model was used to generate the dataset of forest stand information in the Loess Plateau, and it was found that the forest is dominated by young forests (<20a), accounting for 38.26% of the forest area, and the average age of forests in the Loess Plateau is 56.1a. This study not only improves the method of forest stand age estimation, but also provides data support for vegetation construction in the Loess Plateau.

Modeling forest landscape futures: Full scale simulation of realistic socioeconomic scenarios in Estonia.

For political and administrative governance of land-use decisions, high-resolution and reliable spatial models are required over large areas and for various time horizons. We present a process-centered simulation model 'NextStand' (a forest landscape model, FLM) and its R-script, which predicts regional forest characteristics at a forest stand resolution. The model uses whole area stand data and is optimized for realistic iterative timber harvesting decisions, based on stand compositions (developing over time) and locations. We used the model for simulating spatial predictions of the Estonian forests in North Europe (2.3 Mha, about 2 M stands); the decisions were parameterized by land ownership, protection regimes, and rules of clear-cut harvesting. We illustrate the model application as a potential broad-scale Decision Support Tool by predicting how the forest age composition, placement of clear-cut areas, and connectivity of old stands will develop until the year 2050 under future scenarios. The country-scale outputs had a generally low within-scenario variance, which enabled to estimate some main land-use effects and uncertainties at small computing efforts. In forestry terms, we show that a continuation of recent intensive forest management trends will produce a decline of the national timber supplies in Estonia, which greatly varies among ownership types. In a conservation perspective, the current level of 13% forest area strictly protected can maintain an overall area of old forests by 2050, but their isolation is a problem for biodiversity conservation. The behavior of low-intensity forest management units (owners) and strict governance of clear-cut harvesting rules emerged as key questions for regional forest sustainability. Our study confirms that high-resolution modeling of future spatial composition of forest land is feasible when one can (i) delineate predictable spatial units of transformation (including management) and (ii) capture their variability of temporal change with simple ecological and socioeconomic (including human decision-making) variables.

Profit efficiency in the provision of ecosystem services in the Cross Timbers forests

We focused on modeling the profitability of the Cross Timbers (CT) forests with regards to the provision of ecosystem services, including timber production, carbon sequestration, and water yield. The Cross Timbers region spans from southern Kansas to central Oklahoma into Texas, encompassing marginally productive timberlands. We utilized a translog stochastic profit frontier approach to analyze forest plot data collected from the Forest Inventory Analysis program between 2008 and 2019. Our results indicated that, on average, the CT forests yield around 85% of the maximum profit. Only 12% of the forest plots generated positive revenues, and the average profit across all forest plots was -$484.51 ha−1. This means that even with a 15% reduction in profit losses, the majority of the forest plots in the CT region would still not be economically viable. Forest age, ownership, forest species, and site productivity were statistically significant impacts on profit efficiency. At the margin, we found that profit inefficiency increased under private ownership and with higher levels of site productivity. Furthermore, as forests age, profit efficiency was also reduced. These findings highlight the complexity and variability of forest management systems and underscore the need for further research to fully understand the factors influencing efficiency in different contexts.

Monitoring Seasonal Growth of Eucalyptus Plantation under Different Forest Age and Slopes Based on Multi-Temporal UAV Stereo Images

Eucalyptus grows rapidly and can grow up to 10 m per year, making them an important source of wood supply. Guangxi is a typical karst terrain, with hills and plains being the main growth areas for Eucalyptus. The differences in terrain can affect the seasonal growth of Eucalyptus plantations at different forest ages, which in turn affects the stocking of Eucalyptus. Currently, indiscriminate logging and management not only cause resource waste but also bring economic losses to operators. In this study, an unmanned aerial vehicle (UAV) was used to obtain multi-temporal stereo images to investigate the seasonal growth differences in structural parameters of individual Eucalyptus trees under different forest ages and slopes, providing data support for the precise management of Eucalyptus resources. The results showed that the tree height, crown width, diameter at breast height (DBH), and aboveground biomass (AGB) of individual trees, extracted based on UAV stereo images, are highly correlated with the field measured data, with an R2 of 0.99, 0.78, 0.75, and 0.92, and RMSE of 0.21 m, 0.16 m, 1.17 cm, and 3.79 kg/tree, respectively. The growth of Eucalyptus structural parameters varies in different seasons, with faster growth in spring and autumn, accounting for 76.39%, 73.75%, 73.65%, and 73.68% of the total annual growth, respectively. The growth of different structural parameters of individual trees is closely related to forest age, with tree height, crown width, and DBH gradually slowing down with the increase in forest age, while AGB shows a trend of first increasing and then decreasing. The differences in terrain also have a certain impact on the growth of individual Eucalyptus tree structural parameters. For individual 1-year-old and 3-year-old Eucalyptus trees, those located on gentle slopes grow faster in spring and autumn than those located on flat land. However, those located on flat land grow faster in summer and winter than those located on gentle slopes. For tree height, crown width, DBH, and AGB, the maximum annual growth differences between Eucalyptus trees on gentle slopes and flat are 3.17 m, 0.26 m, 1.9 cm, and 9.27 kg/tree, respectively. The results indicate that based on UAV stereo images, the individual tree structural parameters in Eucalyptus plantations under different forest ages and slopes can be extracted, as well as seasonal growth can be monitored, providing data support for logging, planting, and management of Eucalyptus plantations.

Mapping planted forest age using LandTrendr algorithm and Landsat 5–8 on the Loess Plateau, China

Forest age is a key parameter for understanding the water and carbon cycles and carbon sequestration potential of planted forest ecosystems. However, estimating forest age on a large scale is difficult. This study aims to determine whether the distribution of forest age can be mapped over a large area using the LandTrendr (LT) algorithm. With the LT algorithm, the initial year of forestland (breakpoints) can be determined rather accurately through the yearly trajectory of the normalized burn ratio (NBR) index in the revegetated forest. The results show that the LT algorithm is a convenient, efficient, and reliable method for identifying forests age. Moreover, a comparison with ground truth data on the Chinese Loess Plateau (LP) revealed that the overall accuracy of the error confusion matrix was 89 %, with a root-mean-square error (RMSE) of 2.14 years. Using the LT algorithm, we revealed that the forestland on the Chinese LP in 2020 was dominated by planted forests over 30 years old, accounting for approximately 78.27 %. The forestland area increased by approximately 20,386 km2 from 1990 to 2020, and the increase occurs primarily around the original forestland in the eastern and southern parts of the Chinese LP. This study provides an important parameter for assessing and quantifying biomass and carbon sequestration through afforestation on the Chinese LP.

Balancing Livestock Environmental Footprints with Forestry-Based Solutions: A Review

Livestock production, as one of the oldest and most significant human activities, plays a vital role in fulfilling the global demand for human nutrition and other animal-related products while contributing to poverty reduction. However, it is also important to address the environmental impact of livestock animals. Over 60% of the global biomass harvested annually to support human activity is directed towards this sector, raising concerns about its sustainability. In addition to substantial water and fertilizer usage reported in recent years, it is estimated that 14.5% of global greenhouse gas emissions are generated by the livestock sector. Furthermore, the increasing amount of manure resulting from intensive animal farming raises concerns about its disposal and potential water pollution. The degradation of pasture and rangeland is another significant contributor to soil erosion. Multiple approaches are being studied to reduce the environmental impact of livestock production, but a sustainable alternative may be through forestry. Forests play a vital role in countering livestock emissions by absorbing billions of tons of carbon dioxide each year, and they act as a crucial carbon sink. Furthermore, the diversity and age of forests impact the carbon sequestration process. Forests also help to combat climate change by reducing soil erosion and regulating the water cycle. As such, sustainable forest management is essential as forests provide multiple benefits, including economic, environmental, and social benefits, while also sequestering carbon. In this review, the current impact of modern livestock production is described, along with the potential for mitigating it through forestry-based solutions.

Change in urban forest age structure affects the value of ecosystem services provided

To achieve resilience goals, urban planners and decision-makers need accurate information on the benefits provided by urban trees and on the effects that management may have on them. This study investigates the impacts of management and disturbances on urban forest structure and function in Turku, Finland. Using a comprehensive urban tree database and the i-Tree software suite, we assessed the current structure and estimated the value of ecosystem services provided by Turku's urban forest. Additionally, we simulated changes in the urban forest over a 50-year period, considering different tree planting scenarios and the potential outbreak of the Asian longhorned beetle (ALB). Turku's urban forest comprised 38,438 public trees, dominated by Acer platanoides, Pinus sylvestris, Tilia × europaea, and Betula pendula. The estimated carbon storage was 12,336 t, valued at 1.98 million €, with an annual sequestration rate of 284 t (45,549 €/year). The trees also removed 8.97 t of pollutants annually, with an estimated value of 153,273 €. At the current rate of tree planting, the number of trees would decline over the course of 50 years resulting in a gradual decrease in the provision of ecosystem services. Although doubling the tree planting rate could slowly increase carbon storage and sequestration even under moderate ALB attack, it was insufficient to offset the damage caused by ALB if tree mortality rate reaches 50%. Compared to carbon storage and sequestration, changes in urban forest age structure had a more immediate impact on the removal of air pollution. These findings emphasize the importance of prioritizing investments in urban forests on grounds of their capacity to provide diverse ecosystem services. Incorporating these findings into decision-making processes would promote sustainable and resilient urban environments.

Simulation of the soil water-carrying capacity of Haloxylon ammodendron plantations in the Alxa Desert, China: Implications for afforestation

In recent years, China has achieved remarkable results in curbing desertification through afforestation. However, the dry soil layer resulting from the long-term water consumption of overloaded perennial plants seriously threatens the sustainability of afforestation, and quantifying the maximum vegetation carrying capacity under certain soil moisture conditions is crucial to the sustainability of afforestation in arid areas. Therefore, we aimed to simulate soil water in Haloxylon ammodendron plantations at different growth stages using the simultaneous heat and water transfer (SHAW) model to determine the vegetation carrying capacity threshold. Field-measured soil and vegetation data for 2021 were used to calibrate the SHAW model. Good consistency in soil water content (SWC) was observed between measurements and simulations in the calibration and validation phases of the model, with considerable linear correlation and low prediction error values. Therefore, the soil water dynamics of H. ammodendron plantations in the study area could be accurately predicted using the SHAW model. The simulation results show that, with increasing forest age, the SWC at 0–400 cm gradually decreases and a dry soil layer starts to form when the forest age reaches 11 years. The dry layer thickness reaches 120 cm by 22 years, thus the optimal growth age of artificial H. ammodendron plantations in the study area should not exceed 22 years, and the maximum biomass soil water carrying capacity of vegetation is 1,650 kg/hm2. A vegetation carrying capacity threshold can be determined in this study for the sustainable management of future afforestation activities.

Influence of soil properties and near-surface roots on soil infiltration process in short-rotation eucalyptus plantations in southern subtropical China

Soil infiltration capacity is a measure of the rate of water infiltrating into a soil. The influence of soil properties and near-surface roots on the soil infiltration process remains unclear in short-rotation eucalyptus plantations. A series of field experiments were conducted to determine the soil infiltration capacities of differently aged (1, 2, 3, and 5 years) eucalyptus plantations by using a surface-positioned double-ring infiltration instrument. The biomass of fine root (<2 mm) and medium root (2–10 mm) on near-surface soil (0–50 cm) and soil samples (0–60 cm with 20 cm interval) was collected for analyzing the effects of near-surface fine root biomass (FRB), medium root biomass (MRB), soil organic matter (SOM), soil bulk density (BD), soil total porosity (TP), soil macroaggregate, and water-stable macroaggregate on soil infiltration. Results showed that the average infiltration rate (762–1463 mm h−1), initial infiltration rate (5420–8454 mm h−1, infiltration rate of stage I (3130–5421 mm h−1), infiltration rate of stage II (1594–2257 mm h−1), infiltration rate of stage III (484–934 mm h−1), and steady infiltration rate (318–510 mm h−1) increased with increasing forest age. The near-surface FRB (4.25–14.71 g) decreased with increasing forest age. Near-surface FRB showed a strong plugging effect on soil infiltration in both initial and steady infiltration stages, but this effect weakened with increasing forest age because of FRB decreasing. Near-surface MRB had no significant effects on soil infiltration. The TP and SOM in near-surface soil promoted soil infiltration capacity. The soil infiltration capacity of short-rotation eucalyptus plantations significantly improved after the third year of planting. Our finding contributes to understanding the effects of near-surface root biomass and soil properties on soil infiltration capacity in eucalyptus plantations, and provides a scientific reference for eco-hydrological study in such plantations.

Incomplete recovery of tree community composition and rare species after 120 years of tropical forest succession in Panama.

Determining how fully tropical forests regenerating on abandoned land recover characteristics of old-growth forests is increasingly important for understanding their role in conserving rare species and maintaining ecosystem services. Despite this, our understanding of forest structure and community composition recovery throughout succession is incomplete, as many tropical chronosequences do not extend beyond the first 50 years of succession. Here, we examined trajectories of forest recovery across eight 1-hectare plots in middle and later stages of forest succession (40-120 years) and five 1-hectare old-growth plots, in the Barro Colorado Nature Monument (BCNM), Panama. We first verified that forest age had a greater effect than edaphic or topographic variation on forest structure, diversity and composition and then corroborated results from smaller plots censused 20 years previously. Tree species diversity (but not species richness) and forest structure had fully recovered to old-growth levels by 40 and 90 years, respectively. However, rare species were missing, and old-growth specialists were in low abundance, in the mid- and late secondary forest plots, leading to incomplete recovery of species composition even by 120 years into succession. We also found evidence that dominance early in succession by a long-lived pioneer led to altered forest structure and delayed recovery of species diversity and composition well past a century after land abandonment. Our results illustrate the critical importance of old-growth and old secondary forests for biodiversity conservation, given that recovery of community composition may take several centuries, particularly when a long-lived pioneer dominates in early succession. Abstract in Spanish is available with online material.

How to Simulate Carbon Sequestration Potential of Forest Vegetation? A Forest Carbon Sequestration Model across a Typical Mountain City in China

Due to a series of human activities like deforestation and land degradation, the concentration of greenhouse gases has risen significantly. Forest vegetation is an important part of forest ecosystems with high carbon sequestration potential. Estimates of the carbon sequestration rate of forest vegetation in various provinces and districts are helpful to the regional and global Carbon cycle. How to build an effective carbon sequestration potential model and reveal the spatiotemporal evolution trend and driving factors of carbon sequestration potential is an urgent challenge to be solved in carbon cycle simulation and prediction research. This study characterized the carbon sequestration status of forest vegetation using the modified CASA (Carnegie-Ames Stanford Approach) model and estimated the carbon sequestration potential from 2010 to 2060 using the FCS (Forest Carbon Sequestration) model combined with forest age and biomass under the four future Shared Socioeconomic Pathways (SSP) scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, then proposes natural, social, and economic perspectives. This study found that the average NPP of the forest vegetation in Chongqing from 2000 to 2020 was 797.95 g C/m2, and the carbon storage by 2060 was 269.94 Tg C. The carbon sequestration rate varied between &lt;0.01 Tg C/a and 0.20 Tg C/a in various districts and counties. Over time, forest growth gradually slowed, and carbon sequestration rates also decreased. Under the four future climate scenarios, the SSP5-8.5 pathway had the highest carbon sequestration rate. Natural factors had the greatest influence on changes in carbon sequestration rate. This result provides data support and scientific reference for the planning and control of forests and the enhancement of carbon sequestration capacity in Chongqing.

Calicioid presence in relation to substrate and tree age in forests of northeast Washington, U.S.A.

Calicioid presence in relation to substrate and tree age in forests of northeast Washington, U.S.A.

The effect of mixed forest identity on soil carbon stocks in Pinus massoniana mixed forests

Increased productivity generally promotes the accumulation of soil organic carbon (SOC) stocks. The productivity of mixed forests is mainly influenced by plant species richness (PSR), mixed forest age (MFA), and mixed species proportion (MSP). However, the influence of PSR, MFA, and MSP on SOC stocks along the soil profiles in Pinus massoniana mixed forests remains to be determined. We conducted a meta-analysis employing paired observations of SOC stocks from 1010 paired mixed and pure stands of P. massoniana from 110 publications. The findings revealed that SOC stocks were highly dependent on MFA and increased with increasing MFA in various soil layers, rather than the expected influence of PSR. MFA contributed 48.97 %, 83.20 %, and 38.41 % to the increased SOC stocks in the topsoil, midsoil, and subsoil, respectively. Furthermore, MSP also significantly affected the increase in SOC stock in the topsoil and midsoil when 40 % < MSP ≤ 60 %. Over the next 60 years, subsoil SOC accumulation will be limited by increased PSR and MSP in mixed forests. Mixing between P. massoniana and broadleaf tree species (especially Schima superba and Lespedeza bicolor) significantly enhanced SOC stocks along the soil profiles. SOC stocks along the soil profiles decreased with increasing dominant mixed tree species richness (e.g., broadleaf, deciduous broadleaf, arbuscular mycorrhizal, and the sum of conifer and broadleaf trees). Incorporating lower PSR (e.g., 2 ≤ N ≤ 10) and dominant mixed tree species richness (e.g., N = 2) practices may be optimization options for increasing SOC stocks. Overall, based on the expected goals, including optimizing productivity, enhancing carbon storage, mitigating climate change, and promoting biodiversity conservation, we emphasize the importance of incorporating MFA, MSP, tree species identity, and subsoil into forest management.

The anthropogenic imprint on temperate and boreal forest demography and carbon turnover.

The sweeping transformation of the biosphere by humans over the last millennia leaves only limited windows into its natural state. Much of the forests that dominated temperate and southern boreal regions have been lost and those that remain typically bear a strong imprint of forestry activities and past land-use change, which have changed forest age structure and composition. Here, we ask how would the dynamics, structure and function of temperate and boreal forests differ in the absence of forestry and the legacies of land-use change? Global. 2001-2014, integrating over the legacy of disturbance events from 1875 to 2014. Trees. We constructed an empirical model of natural disturbance probability as a function of community traits and climate, based on observed disturbance rate and form across 77 protected forest landscapes distributed across three continents. Coupling this within a dynamic vegetation model simulating forest composition and structure, we generated estimates of stand-replacing disturbance return intervals in the absence of forestry for northern hemisphere temperate and boreal forests. We then applied this model to calculate forest stand age structure and carbon turnover rates. Comparison with observed disturbance rates revealed human activities to have almost halved the median return interval of stand-replacing disturbances across temperate forest, with more moderate changes in the boreal region. The resulting forests are typically much younger, especially in northern Europe and south-eastern North America, resulting in a 32% reduction in vegetation carbon turnover time across temperate forests and a 7% reduction for boreal forests. The current northern hemisphere temperate forest age structure is dramatically out of equilibrium with its natural disturbance regimes. Shifts towards more nature-based approaches to forest policy and management should more explicitly consider the current disturbance surplus, as it substantially impacts carbon dynamics and litter (including deadwood) stocks.

Persistence of a pine tree with mixed fire-adapted life history strategy in subtropical spring fire-prone habitats

Whether pines can cope with fire depends on either species persistence or individual survival. Pinus yunnanensis is the most widely distributed endemic species in Southwest China, and is well adapted to fire with a mixed fire-adapted strategy of post-fire regeneration and fire resistance. However, whether its regeneration depends on fire disturbances is unclear. We reconstructed the fire history of a P. yunnanensis forest in Yunlong Tianchi National Nature Reserve over the past 100 years using fire scars and forest age structures to determine relationships between historical fires and recruitments. Additionally, post-fire regeneration processes of three burned patches were examined to explore P. yunnanensis dynamics after fires. The P. yunnanensis population in the Reserve had a “discontinuous multi-cohort” structure. There was a 6–16 year gap between cohorts, and each cohort comprised individuals that differed by 1–7 years. The study area experienced seven fires in the past 100 years, with an average interval of about 12 years, with surviving individuals in every fire. These historical fires align with P. yunnanensis cohorts emergence. Post-fire P. yunnanensis regeneration in the burned patches mainly occurred in the first two rainy seasons after the fire, then the number of new individuals significantly dropped and remained very low from the fourth year onward. P. yunnanensis population structure has undergone a shift following the enforcement of a fire suppression policy. Some P. yunnanensis adults appear able to survive low to moderate severity fires, and the population could achieve post fire functional recruitment, thus maintaining a “discontinuous multi-cohort” structure in fire-prone habitats as a result of a mixed fire-adapted strategy. Recurrent fire is the key driving factor in maintaining the long-term persistence of pure P. yunnanensis forests.