Forest Growth Research Articles

Post-fire growth of Pinus halepensis: Shifts in the mode of competition along a precipitation gradient

Competition can intensify the struggle for resources among plants, affecting forest growth and dynamics. The intensity and mode of competition – asymmetric vs. symmetric – can change along environmental gradients and with time, impacting the response of plants to their environment, but this is seldom explicitly considered in management plans. In this study, we aim to (i) disentangle the main environmental and tree-related factors that affect post-fire Pinus halepensis sapling growth; (ii) determine which mode of competition characterizes the species post-fire regeneration; and (iii) elucidate if the mode of competition changes with time, and along climatic gradients. We sampled 148 P. halepensis saplings located in 15 sites affected by wildfires between 1987 and 2013 in Catalonia (NE Spain). We measured their radial growth at the base, and we identified their competitive environment by locating and measuring all the trees in a 3-meter-radius from our target saplings. We modelled the effect of tree size, age, climate, and competitive environment on the post-fire regeneration growth following the neighborhood theory of forest dynamics and using model comparison and information criteria to address our research questions. We used a modification from the Hegyi index to determine the prevalence of symmetric vs. asymmetric competition, and we assessed the support for models in which competition was allowed to vary with age and precipitation. The best model showed that competition, precipitation, age, and target size influenced the radial growth of P. halepensis post-fire regeneration (Akaike weight 0.66, R2 = 0.52). We found evidence that P. halepensis mode of competition is generally asymmetric but can change along a precipitation gradient: it shifts from asymmetric in drier sites to almost fully symmetrical as precipitation increases. Our findings have implications for the management of post-fire P. halepensis stands, enabling the adaptation of silvicultural prescriptions to the climatic environment. In a context of increasing water scarcity, adaptive silviculture is fundamental to foster the resilience of pinewoods to future climatic and disturbance regimes.

The Minimum Target Diameter and the Harvest Age of Oak Natural Secondary Forests in Different Sites Conditions: Case Study in Hunan Province, China

Maintaining permanent forest canopy cover and eventually harvesting timber by predetermined target diameter are often considered as a prototype for future management of the oak natural forest. However, target diameters and harvest age based on average forest growth rates from wide geographical areas often hamper improved management of oak forests. In this study, based on the sampling of 129 target trees from 51 oak natural secondary forest plots in Hunan Province, China, an individual-tree DBH (diameter at breast height) growth model of oak target trees was developed, and the site type (41 levels) was related to the model as random effects by a nonlinear mixed-effects approach. Moreover, the 41 site types were clustered into four site type groups (STG1, STG2, STG3, and STG4) by the K-means clustering algorithm to improve the model performance and practicality. With the help of the model, the five target diameters (including 24, 30, 40, 50, and 60 cm) were simulated in each of the four STGs, and the minimum target diameter was determined for each STG based on the theory of quantitative maturity. In the four STGs, the harvest age of the 24 cm diameter target ranged from 30 to 51 years; the harvest age of the 60 cm target diameter ranged from 131 to 220 years, with the oaks failing to reach 60 cm in the lowest-quality STG4; the minimum target diameter ranged from 21 cm to 29 cm. Results showed that lower-quality sites exclude higher target diameters from optimal harvesting strategies, in contrast to the higher target diameter as a more reasonable strategy in higher quality sites, and that the minimum target diameter is significantly influenced by site conditions. Therefore, it is necessary to develop a diverse target-diameter-harvesting strategy adapted for the complex site conditions of oak forests in Hunan Province towards site-specific timber management to improve the sustainability of timber production in oak forests.

High emissions or carbon neutral? Inclusion of “anthropogenic” forest sinks leads to underreporting of forestry emissions

Recent research has shown forest-related emissions reported in national greenhouse gas inventories are much lower than global estimates from models summarized in Intergovernmental Panel on Climate Change reports. A substantial part of this discrepancy could be explained by conceptual differences in what is counted as part of the anthropogenic forest carbon sink and the way countries report on their forest harvesting sectors. With Canada as a case study, we used published National Inventory Report and Common Reporting Format tables to isolate emissions and removals directly associated with forestry from those associated with forests more broadly. Forestry-related factors that affect CO2 emissions and removals include tree harvesting, post-harvest forest regeneration and growth, and carbon storage in long-lived harvested wood products. We found that between 2005 and 2021, forestry in Canada represented a net source of carbon (annual mean = 90.8 Mt. CO2e), and that total area logged was a significant predictor of net forestry emissions. In contrast, Canada’s NIR reported a small net carbon sink during the same time period (annual mean = −4.7 Mt. CO2e). We show this discrepancy can be explained by Canada’s GHG reporting approach that claims GHG emissions from wildfires are natural, but GHG removals from forests at the age of commercial maturity, despite being primarily natural disturbance origin, are anthropogenic. This reporting approach may lead to climate mitigation policies that are ineffectual or detrimental to reducing net carbon in the global atmosphere.

Effects of Climate Change on Scots Pine (Pinus sylvestris L.) Growth across Europe: Decrease of Tree-Ring Fluctuation and Amplification of Climate Stress

From an economic perspective, Scots pine (Pinus sylvestris L.) is one of Europe’s most important tree species. It is characterized by its wide ecological adaptability across its natural range. This research aimed to evaluate the forest structure, productivity and especially radial growth of heterogenous pine stands in 16 research plots in the Czech Republic, Poland, Spain and Great Britain. The study assessed the tree-ring formation and its relationship to climate change for each country, using 163 dendrochronological samples. The stand volume of mature pine forest ranged between 91 and 510 m3 ha−1, and the carbon sequestration in the tree biomass was 40–210 t ha−1. The stands had a prevailing random distribution of trees, with a high vertical structure close to selection forests (forest stands with typical very diverse height, diameter and age structure). Spectral analyses showed a substantial decrease in fluctuations in the tree-ring index and a loss in natural growth cyclicity in the last thirty years. The results also evinced that mean air temperature was the most important factor influencing the radial growth compared to precipitation totals. Pine thrives in precipitation-stable locations, as shown by the results from Great Britain. The conclusions of this study confirm the fundamental effect of ongoing global climate change on the dynamics and growth of pine forests in Europe.

UAVs for forestry: Metric-semantic mapping and diameter estimation with autonomous aerial robots

To properly monitor the growth of forests and administer effective methods for their cultivation, forestry researchers require access to quantitative metrics such as diameter at breast height and stem taper profile of trees. These metrics are tedious and labor-intensive to measure by hand, especially at the scale of vast forests with thick undergrowth. Autonomous mobile robots can help to scale up such operations and provide an efficient method to capture the data. We present a set of algorithms for autonomous navigation and fine-grained metric-semantic mapping with a team of aerial robots in under-canopy forest environments. Our autonomous UAV system has 3D flight capabilities and relies only on a LIDAR and an IMU for state estimation and mapping. This allows each robot to accurately navigate in challenging forest environments with drastic terrain changes regardless of illumination conditions. Our deep-learning-driven fine-grained metric-semantic mapping module is capable of detecting and extracting detailed information such as the position, orientation, and stem taper profile of trees. This map of tree trunks is represented as a set of sparse cylinder models. Our semantic place recognition module leverages this sparse representation to efficiently estimate the relative transformation between multiple robots, and merge their information to build a globally consistent large-scale map. This ultimately allows us to scale up operations with multiple robots. Our system is able to achieve a mean absolute error of 1.45 cm for diameter estimation and 13.2 cm for relative position estimation between a pair of robots after place recognition and map merging

Two-decadal climate impacts on growth of major forest types of Eastern Himalaya

Forests affect regional climates, livelihoods and global cycles of water, carbon and nitrogen. Anthropogenic activities and climatic change affect forest health and national growth. Therefore, developing effective forest management plans requires understanding of the drivers of forest growth. The primary objective of this study was to understand the long-term effect of abiotic factors on the growth of forests in the region. This study used Moderate Resolution Imaging Spectroradiometer (MODIS) data for vegetation indices like NDVI and EVI and NASA's Land Assimilation datasets (wind speed, evapotranspiration, soil moisture and temperature) to understand their role on forest growth through statistical techniques such as Pearson's correlation and Multiple Linear Regression. The study examined the relationship between standard monthly vegetation indices and abiotic variables (i.e., moisture and temperature at different soil profiles up to 2 m depth, land surface temperature, evapotranspiration, relative humidity, wind velocity, and air temperature at 2 m height) in selected forests of the Eastern Himalayas for two decades (2001–2020, n = 240). Rainfall, temperature, and other associated factors significantly affected forest growth in the region. It was observed that rainfall alone affected forest growth in the region. However, its impact was maximum after two months of the rain events, reflecting a significant lag effect. Soil moisture at different depths affected vegetation growth in all forest types. Reduced soil moisture had a more significant effect on old-growth forests than younger forests. Multiple Linear Regression models developed with the abiotic factors explained higher variability in forest growth. In conclusion, this study reveals that rainfall, temperature, and their associated variables significantly affected forest growth in the study area. The study has significant implications for forest management in the region for formulating better strategies to mitigate climate change effects on forests in the region in future.

Tree regeneration and ontogenetic strategies of northern European hemiboreal forests: transitioning towards closer-to-nature forest management.

Tree ontogeny is the genetic trajectories of regenerative processes in trees, repeating in time and space, including both development and reproduction. Understanding the principles of tree ontogeny is a key priority in emulating natural ecological patterns and processes that fall within the calls for closer-to-nature forest management. By recognizing and respecting the growth and development of individual trees and forest stands, forest managers can implement strategies that align with the inherent dynamics of forest ecosystem. Therefore, this study aims to determine the ontogenetic characteristics of tree regeneration and growth in northern European hemiboreal forests. We applied a three-step process to review i) the ontogenetic characteristics of forest trees, ii) ontogenetic strategies of trees for stand-forming species, and iii) summarise the review findings of points i and ii to propose a conceptual framework for transitioning towards closer-to-nature management of hemiboreal forest trees. To achieve this, we applied the super-organism approach to forest development as a holistic progression towards the establishment of natural stand forming ecosystems. The review showed multiple aspects; first, there are unique growth and development characteristics of individual trees at the pre-generative and generative stages of ontogenesis under full and minimal light conditions. Second, there are four main modes of tree establishment, growth and development related to the light requirements of trees; they were described as ontogenetic strategies of stand-forming tree species: gap colonisers, gap successors, gap fillers and gap competitors. Third, the summary of our analysis of the ontogenetic characteristics of tree regeneration and growth in northern European hemiboreal forests shows that stand-forming species occupy multiple niche positions relative to forest dynamics modes. This study demonstrates the importance of understanding tree ontogeny under the pretext of closer-to-nature forest management, and its potential towards formulating sustainable forest management that emulates the natural dynamics of forest structure. We suggest that scientists and foresters can adapt closer-to-nature management strategies, such as assisted natural regeneration of trees, to improve the vitality of tree communities and overall forest health. The presented approach prioritizes ecological integrity and forest resilience, promoting assisted natural regeneration, and fostering adaptability and connectivity among plant populations in hemiboreal tree communities.

Relações entre o espaçamento arbóreo e características do campo nativo em sistemas silvipastoris no bioma Pampa

ABSTRACT: The current study assessed the association of eucalyptus-tree spacing with forest growth and yield, as well as with the floristic composition, diversity and yield of natural grassland grown in silvopastoral systems in Pampa biome. Data were collected in six family cattle-ranching area in Bagé County (RS). The effect of two different genetic materials (seminal-origin Eucalyptus dunnii plant and one Eucalyptus grandis clone) on shading features of plants grown in 3 planting-spacing dimensions(625, 312 and 208 trees ha-1) was assessed, as well as their association with herbaceous extract (bare soil; green cover; forage dry matter; floristic composition; species richness; and grass, legumes and winter - and summer-growth species rates) and forestry (litter accumulation, diameter at breast height, total height and volume per hectare) variables. Planting carried out at the highest tree density (625 trees ha-1) has increased forest yield. However, it reduced green cover, herbaceous extract dry-matter yield and species richness, mainly in grasses and legumeswith greater forage potential. Conversely, it is possible combining forestry and animal yield to the preservation of native forage species at low tree densities (204 to 312 trees ha-1).

A New Perspective of Trees Competition Network Research

Forest competition is a key factor driving forest dynamics and stand structure, and is one of the core issues in ecological research. Competition is a complex ecological process with temporal changes, which is interrelated and affected with forest growth, stand structure dynamics and environmental changes. Although there have been many researches on competition, tree growth, stand structure and climate, the interactions among trees have been studied by static competition index measurement, which usually lacks temporal variation related to natural forest development and environmental conditions, and the response mechanism and related theory of competition to stand development and environmental fluctuation have been studied insufficiently.(2) Single tree competition index model;(3) Interaction between tree competition and tree growth, stand structure and environment;(4) Tree competition based on complex network. Finally, according to the complex interaction of tree competition, the research strategy of tree competition network structure with “single tree” as node and “single tree competition relationship” as edge is discussed, in order to provide reference for the study of tree interaction and forest ecosystem dynamics.

Planting density and mechanical site preparation effects on understory composition, functional diversity and planted black spruce growth in boreal forests

Mechanical site preparation (MSP) is used prior to planting to control competing vegetation and enhance soil conditions, particularly in areas prone to paludification. Tree planting density can be adapted to the management context and objectives, as it influences yield and wood quality. However, the combined effects of MSP and planting density on understory vegetation composition, functional traits, and diversity remain uncertain. We thus conducted a study in the Clay Belt region of northwestern Quebec, Canada. After careful logging, the study area was divided into nine sites, each receiving one of three treatments: plowing, disc trenching, or no preparation. Sites were further divided into two, with black spruce (Picea mariana [Mill.] Britton, Sterns & Poggenb.) seedlings planted at either a low planting density of 1100 seedlings ha-1 or a high planting density of 2500 seedlings ha-1. After nine years, we assessed understory composition, diversity, key functional traits, sapling density and growth of planted trees. Careful logging alone led to a higher density of naturally established conifers compared to plowing or disc trenching. The interaction between planting density and MSP significantly influenced understory diversity and composition in plowed plots. Understory composition was affected by the soil C/N ratio, coniferous species, and deciduous species density. The growth of black spruce was notably enhanced with higher planting density in the plow treatment only. Neither planting density nor MSP alone affected tree height and diameter. Our results suggest that combining plowing with high-density planting can enhance stand growth and improve forest productivity. These findings guide future research on paludified forests.

Future land use prediction and optimization strategy of Zhejiang Greater Bay Area coupled with ecological security multi-scenario pattern.

The land use changes driven by human activities press a incredible menace to zonal ecological security. As the most active urban cluster, the uncontrolled expansion of cities in the bay area exerts enormous pressure on the ecosystem. Therefore, from the perspective of ecological conservation, exploring future land use optimization patterns and spatial structure is extremely essential for the long-term thriving of the bay area. On this basis, this research integrated the System Dynamics model (SD) as the quantity forecast model and the PLUS model as the spatial emulation model and established the Land Use/Cover Change (LUCC) Simulation Framework by setting the constraints of Ecological Security Multi-Scenario Patterns (ESMP). By setting four scenarios in future, that is, Business As Usual (BAU), Priority of Ecological Protection (PEP), Balanced Development Scenario (BD), and Priority of Urban development (PUD), this research predicts LUCC in the Zhejiang Greater Bay Area (ZGBA) in 2035 and explored land use optimization patterns. The results indicate that by 2035, under the scenarios of BAU, BD, and PUD, the construction land will observably grow by 38.86%, 19.63%, and 83.90%, respectively, distributed mainly around the Hangzhou Bay Area, Taizhou Bay Area, and Wenzhou Bay Area, primarily achieved by sacrificing ecologically sensitive lands such as forests to achieve regional high economic growth. Under PEP, the growth of construction land retards, and forest experiences net growth (11.27%), with better landscape connectivity and more cohesive patches compared to other scenarios. Combining regional planning and analysis at the city scale, Hangzhou Bay area (Hangzhou, Huzhou, Jiaxing, Shaoxing, Ningbo) can adopt the BD development scenario, while Zhoushan, Taizhou, Wenzhou and Fuyang County of Hangzhou can adopt the PEP development scenario. This research furnishes a novel mechanism for optimizing land use pattern in ecological security perspective and offers scientific guidance for land resource management and spatial planning in ZGBA.

Forest yield prediction under different climate change scenarios using data intelligent models in Pakistan.

This study aimed to develop and evaluate data driven models for prediction of forest yield under different climate change scenarios in the Gallies forest division of district Abbottabad, Pakistan. The Random Forest (RF) and Kernel Ridge Regression (KRR) models were developed and evaluated using yield data of two species (Blue pine and Silver fir) as an objective variable and climate data (temperature, humidity, rainfall and wind speed) as predictive variables. Prediction accuracy of both the models were assessed by means of root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (r), relative root mean squared error (RRMSE), Legates-McCabe's (LM), Willmott's index (WI) and Nash-Sutcliffe (NSE) metrics. Overall, the RF model outperformed the KRR model due to its higher accuracy in forecasting of forest yield. The study strongly recommends that RF model should be applied in other regions of the country for prediction of forest growth and yield, which may help in the management and future planning of forest productivity in Pakistan.

Mapping aboveground biomass of Moso bamboo (Phyllostachys pubescens) forests under Pantana phyllostachysae Chao-induced stress using Sentinel-2 imagery

Moso bamboo (Phyllostachys pubescens) stands as a pivotal economic bamboo species globally, holding substantial potential for carbon sequestration. Accurate estimation of aboveground biomass (AGB) in Moso bamboo forests is crucial due to its close ties with the ecosystem's carbon cycle. Despite the maturation of monitoring techniques for Pantana phyllostachysae Chao, a significant pest of Moso bamboo, its interplay with AGB in these forests remains enigmatic. This study addressed this gap by categorizing P. phyllostachysae's impact on Moso bamboo forests into four levels: healthy, mild damage, moderate damage, and severe damage. By scrutinizing field data, we delved into the shifts in Moso bamboo leaf biomass under P. phyllostachysae stress. Leveraging Sentinel-2A/B imagery, we extracted diverse correlation factors, including original wave bands, vegetation indices, texture attributes, and vegetation's physical and chemical parameters. Subsequently, machine learning algorithms-namely, random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) were employed to achieve remote sensing inversion of AGB in Moso bamboo forests, accounting for the presence of insect pests. We analyzed the response of Moso bamboo biomass sensitive factors and to further clarify the changes of AGB of Moso bamboo forests under insect pest stress at the remote sensing level ultimately. The results showed that (1) the degree of Moso bamboo leaf biomass damage was positively related to the damage level, which gradually increased from 15.15 % to 59.42 %; (2) the RF algorithm excelled in estimating Moso bamboo forest AGB, particularly in May, and inclusion of insect pest considerations enhanced AGB estimation accuracy; (3) among the four factor types, Band information and vegetation indices emerged as most impactful, and Band5, Band11, Band12, NDVI68a and MSAVI were selected the most often; (4) at the remote sensing level, AGB in Moso bamboo forests significantly varies under P. phyllostachysae stress. Healthy areas demonstrate an AGB of 66.9037 Mg ha−1, while heavily affected regions drop to 52.6591 Mg ha−1. It can be seen that combining pest factors for Moso bamboo biomass estimation solves the problem of rough biomass estimation, and this study provides a more promising method for forest growth monitoring.

A revamped fitness-based binary bamboo forest growth optimisation for waste water management and control system

A revamped fitness-based binary bamboo forest growth optimisation for waste water management and control system

A Revamped Fitness-based Binary Bamboo Forest Growth Optimisation for Waste Water Management and Control System

A Revamped Fitness-based Binary Bamboo Forest Growth Optimisation for Waste Water Management and Control System

Drivers of spatial structure in thinned forests

BackgroundAs is widely known, an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems. However, previous research on forest management has often overlooked the importance of structure-based. AimsOur objectives were to define the direction of structure-based forest management. Subsequently, we investigated the relationships between forest structure and the regeneration, growth, and mortality of trees under different thinning treatments. Ultimately, the drivers of forest structural change were explored. MethodsOn the basis of 92 sites selected from northeastern China, with different recovery time (from 1 to 15 years) and different thinning intensities (0–59.9%) since the last thinning. Principal component analysis (PCA) identified relationships among factors determining forest spatial structure. The structural equation model (SEM) was used to analyze the driving factors behind the changes in forest spatial structure after thinning. ResultsLight thinning (0–20% trees removed) promoted forest regeneration, and heavy thinning (over 35% of trees removed) facilitated forest growth. However, only moderate thinning (20%–35% trees removed) created a reasonable spatial structure. While dead trees were clustered, and they were hardly affected by thinning intensity. Additionally, thinning intensity, recovery time, and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area. ConclusionCreating larger DBH and canopy area through thinning will promote the formation of complex forest structures, which cultivates healthy and stable forests.

Hydrothermal conditions for forest growth in Iraqi Kurdistan and prediction of extreme droughts

Hydrothermal conditions for forest growth in Iraqi Kurdistan and prediction of extreme droughts

Determining the Environmental Impacts of Extreme Hydrometeorological Events on Fire Management in the Guanacaste Conservation Area, Costa Rica

[Introduction]: The heightened levels of environmental degradation resulting from forest fires and their correlation with climate change are of global concern. In Costa Rica, hydrometeorological events categorized as extreme due to their significant impact, such as Hurricane Otto in 2016 and Tropical Storm Nate in 2017, appear to have induced changes in vegetation and, consequently, forest fuel. [Objective]: Therefore, this study analyzes the impact of extreme hydrometeorological events on the supply of vegetative fuel from 1997 to 2020 in the Platanares, El Avión, and Junquillal sites within the Guanacaste Conservation Area (ACG) in the northwest of the country. [Methodology]: The study utilized data from eight vegetation indices selected for their representation of forest growth. Additionally, field verifications and information collection from official personnel and ACG volunteers were conducted to determine the effect of extreme events on the characteristics of vegetative fuel and its relationship with fire management and climate change adaptation. [Results]: The results obtained suggest that the vegetation in the investigated sites is in a state of natural regeneration but is increasingly exposed to the recurring influence of the ENSO phenomenon in its various phases (Neutral, La Niña, El Niño) and extreme hydrometeorological events, such as Hurricane Otto or Tropical Storm Nate [Conclusions]: These events could be contributing not to the quantity but to the intensity of forest fires.

Spatial and temporal study of estimating carbon stocks distribution of mangrove forest in coastal area of Teluknaga, Tangerang

Coastal mangrove forests play a crucial role in balancing carbon emissions in the atmosphere as they are a significant carbon store. Previous studies have shown that mangroves can absorb carbon four times more efficiently than terrestrial tropical forests. Unfortunately, the massive development and land use changes in Teluknaga District's coastal areas threaten these ecosystems' existence. To address this concern, efforts are being made to increase conservation, including estimating carbon stock. The aim of this study is to analyze the spatial distribution of biomass and carbon stock of mangrove forests in Teluknaga between 2016-2022 based on vegetation indices such as ARVI, EVI, and SAVI. Sentinel-2 was calculated into ARVI, EVI, and SAVI vegetation indices to model biomass. Statistical correlation analysis was also used to determine the best vegetation index to model biomass in the coastal area of Teluknaga District. This study found that the ARVI vegetation index had the best correlation (R = 0.60) for modeling biomass, with an RMSE value of 36.67 kg/pixel. Most mangrove forests in the coastal area of Teluknaga District showed an increase in biomass and carbon stock between 2016-2022, with significant growth in Muara and Lemo villages' mangrove forests, which is in line with an increase in the area and density of mangrove forests.

Stability Analysis of Fixed Points in Forest Biomass Depletion Model

The main focus of this article is to present a model that explains the depletion in forest biomass due to population size , population pressure , and industrialization . This research explores the complex relationship between forest biomass, population growth, and industrialization. The model generates four fixed points that are all non-negative, and they are known as and . The article proceeds to analyze the stability of these fixed points in the context of forest biomass depletion. It is discovered that the fixed points and are saddle points and not stable, while the fixed point is stable if it meets certain conditions. The article concludes by carrying out numerical simulations to determine the equilibrium point of the model, which shows that forest resource biomass stability declines as population size, population pressure, and industrialization increase. The simulations reveal that population growth results in a depletion in forest resource biomass, while the opposite is true for the positive impact that forest resource biomass on population levels. Consequently, it is essential to regulate population density and industrialization to manage population growth and protect forest resources.