Rural forest communities in developing countries face multiple and compounding shocks that increase their vulnerability and reliance on limited coping options. While many studies have examined how socio-economic factors shape coping strategies, few have explored the combined and interacting effects of these factors on strategy selection across diverse shock types. This study investigates the types of shocks experienced by communities surrounding the Kakamega Forest Ecosystem (KFE) in western Kenya, the coping strategies employed, and how socio-economic characteristics and their interactions influence these responses. Using participatory approaches, primary data were collected from 453 households through focus group discussions, key informant interviews, and a structured household survey. Data were analysed using Chi-square tests, ANOVA, poisson, and negative binomial regression models. Economic distress and illness emerged as the most widely acknowledged shocks. Significant differences were found across wealth categories and Community Forest Association (CFA) membership for illness, unemployment, animal disease outbreaks, and economic shocks. Only animal disease shocks varied significantly by gender of household head. Forest harvesting was the most frequently adopted coping strategy, used in response to 78% of shocks, underscoring the forest’s buffering role. Consumption reduction was common among poor households during unemployment and economic distress, while productive asset sales were triggered by economic and health-related shocks. Rich CFA members and male headed households were less likely to adopt costly or asset-depleting strategies. The paper demonstrates that forest resources serve primarily as short-term safety nets, underscoring the importance of reducing socio-economic disparities and enhancing forest governance to avoid poverty traps and foster resilient, context-specific policies.
The building sector is a major contributor to global greenhouse gas emissions. Substituting carbon-intensive materials with timber presents a significant, yet not fully quantified, climate mitigation opportunity.This systematic review synthesizes three decades of global research to quantify the timber substitution effect in the built environment. Its primary objectives are to: (1) consolidate displacement factors and emission reduction ranges from life-cycle assessments, (2) evaluate systemic barriers and enablers for adoption, and (3) provide actionable insights for policy and research.A structured literature search (1990–2024) was performed using Web of Science and Google Scholar. From 12,526 initial records, 12,320 unique studies were screened. Following a full-text review, 80 studies were included in the qualitative synthesis, with 68 providing quantitative data for meta-analysis. A mixed-methods framework combined bibliometric and thematic synthesis.The analysis confirms a robust substitution effect. Replacing steel with wood avoids 2.3 kg of CO₂ per kg of wood, while substituting concrete saves 1.4 kg CO₂/kg. In whole-building systems, emission reductions range from 36 to 530 kg CO₂-equivalents per m³ of wood. When sourced sustainably, timber serves as a long-term carbon store, with life-cycle assessments showing 34–84% lower climate impact in multi-story applications. Scaling timber use could reduce sector emissions by 20–30% by 2050. Key barriers include prescriptive building codes, fire safety perceptions, and uneven forest governance.Timber substitution is a viable, scalable mitigation pathway. Realizing its potential requires updated building codes, carbon pricing mechanisms, and certified sustainable forestry. Future research must standardize life-cycle assessment methods and address geographic literature gaps. This transition can simultaneously advance climate goals, circular economy principles, and green job creation.
Nothofagus pumilio is a native tree from the Andean Patagonia, including Tierra del Fuego archipelago, with exceptional timber quality. In N. pumilio natural forests, harvesting generates changes in structure, which in combination with natural disturbances, particularly windthrown, modify the recovery pathways to face management proposals. Overstory stability and diameter growth of remnant trees (>5 cm diameter), and density and height of natural regeneration (<5 cm) were analysed in stands managed with shelterwood after preparatory cuts (PC), final cuts (FC), and thinning (T) in Tierra del Fuego (Argentina). Overstory stability measured as fallen basal area of remnant trees was evaluated across 10 years-after-harvesting (YAH), diameter growth was evaluated during 2012-2018 and 2019-2022, and regeneration was evaluated before harvesting and 10 YAH. PC (fallen basal area 6.0%) and FC (8.4%) promoted greater stability than T (21.0%), in which higher instability was recorded during the first 4 YAH. Diameter growth did not show significant differences between shelterwood cuts (3.6-4.2 mm yr-1) and thinning (3.7-4.6 mm yr-1). PC and FC showed abundant regeneration (21.8 and 17.0 x 103 ind ha-1, respectively). Our study showed that shelterwood cuts (PC and FC) in N. pumilio forests promoted greater tree stability and natural regeneration while thinning generated greater growth values at stand level.
Our study aimed to assess inter-annual (2016-2020) temporal variability in macromycete species richness, diversity, abundance, and community composition for saprotrophic (SAP) and ectomycorrhizal (ECM) fungi in Norway spruce-dominated stands of different ages (21, 31 and 51 years; a proxy for succession) afforested on former agricultural land (locality Vrchdobro & ccaron;, central Slovakia). We observed significant inter-annual variability in macromycete species richness, diversity, and abundance, depending on ecotrophic fungal groups. Year had a greater influence than fungal group on all characteristics except species richness, where both factors had similar importance. Stand age affected only macromycete abundance, with differences between ecotrophic groups. The models explained more variability in species richness and abundance than in diversity. Inter-annual variability in fungal community composition exceeded the variability attributable to stand age, with ECM macromycete communities exhibiting greater inter-annual variability than SAP macromycete communities. No direct interaction effects between stand age and sampling year were detected, suggesting that macromycete communities may be shaped by processes operating at broader spatial or temporal scales than those captured by the study plots (416.16 m2) and sampling period. Consequently, in short-term studies, high inter-annual variability in macromycete species richness, diversity, abundance, and community composition could obscure the influence of other factors of interest.
Chestnut phytosanitary emergencies are rising in recent years also due to climate changes, which allow new treats to find favourable environmental conditions in previously unsuitable places and the rapidity of movements which aids their survival. Among the emerging fungal pathogens, Sirococcus smithogilvyi the causal agent of chestnut brown rot (CBR), a very damaging chestnut disease, stands out. Between 2023-2024, S. smithogilvyi was frequently isolated from 1200 nuts collected randomly in three chestnut locations of Basilicata region (Southern Italy) and initially identified based on morphology features. Other fungal taxa were less frequently isolated: Alternaria alternata, Botrytis cinerea, Penicillium sp., Neofusicoccum parvum, Mucor sp., Cladosporium sp. and Trichoderma sp. Sequencing of two common fungal barcodes, the Internal Transcribed Spacer (ITS) region of ribosomal DNA and the beta-tubulin (tub2) gene confirmed the morphological identification. Furthermore, phylogenetic analyses of S. smithogilvyi isolates, based on tub2 nucleotide sequences, showed the occurrence of two separate evolutionary lineages in Basilicata, previously recognized as haplotypes A and B. The haplotype A, was predominant registering 86% frequency while the haplotype B registered only a 14% frequency. The prevalent presence of S. smithogilvyi haplotype A (reported to be more aggressive) along with other additional factors could explain the serious damage and the chestnut production losses recorded for the past years in Basilicata, which urges to find and implement suitable measures to control this emerging and very damaging chestnut pathogen.
Forest variables such as aboveground wood volume are usually estimated by applying regression analysis. Nevertheless, in the past decades, new alternatives have been used, for example, artificial neural networks. In this sense, our study aimed to evaluate the efficiency of the Radial Basis Function (RBF) neural network in estimating aboveground wood volume for the Brazilian savanna using the cOptBees training algorithm. We fitted 18 allometric models and trained three Multilayer Perceptron (MLP) networks and two RBF networks using two different algorithms: k-means and cOptBees. We selected the MLP and RBF networks, as well as the allometric model with the best accuracy, for comparison. We verified the methods' accuracy by analysing the statistics of bias, root mean square error (RMSE), and Pearson's correlation coefficient. The lowest bias value was presented by the RBF network using the cOptBees algorithm (5.90 x 10-5). The N & auml;slund model showed the highest correlation (9.45 x 10-1), as well as the lowest RMSE (2.07 x 10-3). The aboveground wood volume estimates provided by the artificial neural networks showed similar results to those provided by classical regression models. Overall, we may infer that RBF networks trained using the cOptBees algorithm can be used to estimate aboveground wood volume in the Brazilian savanna, being as accurate as MLP or RBF networks trained with the k-means algorithm and allometric models. Finally, all methods showed similar aboveground wood volume estimates. However, neural networks offer advantages in optimizing field surveys because they require less sampling effort.
As augmented reality (AR) technology continues to evolve, its application in forestry measurement is gaining increasing attention. While previous research has largely focused on diameter at breast height (DBH) measurements, expanding AR-based tools to other tree parameters is essential for assessing forest structure, biomass, and growth. This study evaluates the effectiveness of ARKit 6 (Arboreal Forest app, AF), a LiDAR-integrated mobile tool, for measuring tree height and crown diameter, by comparing its measurements with those of TruPulse 360B (TP), a professional-grade laser rangefinder. A statistical framework employing probability and cumulative distribution functions was applied to 215 broadleaved and coniferous trees, with goodness-of-fit tests (Kolmogorov-Smirnov and Anderson-Darling) indicating that Weibull and Log-Normal distributions best described the measurements. Agreement between tools was assessed using Bland-Altman analysis and error metrics including bias, mean absolute error (MAE), and root mean square error (RMSE). For height, the bias was -0.01 m, MAE 0.125 m, and RMSE 0.211 m, while for crown diameter, bias -0.59 m, MAE 2.02 m, and RMSE 2.70 m, indicating strong agreement between AF and TP. Descriptive statistics indicated similar means, standard deviations, and skewness values, suggesting that AF provides measurements comparable to TP. Minor differences in kurtosis and skewness suggest how each tool handles extreme values. These findings highlight AF as a cost-efficient and reliable alternative to professional-grade tools for tree height and crown diameter estimation. As AR technology evolves, its role in forestry is expected to expand toward real-time data integration, modeling, and ecological assessments.
Monitoring Forest structure across large and heterogeneous landscapes is essential to understanding ecosystem dynamics, carbon stocks, and the impacts of global change. This study leverages lidar surveys from Spain's national airborne laser scanning (ALS) program to produce harmonized, high-resolution maps of canopy height, canopy cover, and aboveground biomass (AGB) across peninsular Spain over two periods: 2008-2016 and 2015-2021. We developed a consistent processing workflow to overcome challenges posed by heterogeneous lidar acquisitions, and integrate the resulting metrics with National Forest Inventory (NFI) data to model AGB using machine learning algorithms. Validation against field data demonstrated high accuracy for canopy height (R-2 > 0.8; RMSE < 3 m in some regions) and acceptable performance for AGB estimation (RMSE: 23- 44 t ha(-1)). Between the two lidar surveys, forests exhibited structural development in forest canopies, with average annual increases of 0.2 m in height and 0.9% in canopy cover, particularly pronounced in the Atlantic regions. Species-level analysis highlighted the structural and functional contrast between biomes: highbiomass Atlantic species such as Fagus sylvatica and Pinus radiata reached up to 188 t ha(-1) and 126 t ha(-1 )AGB, respectively, while Mediterranean species like Quercus ilex and P. halepensis remained under 35 t ha(-1). Comparisons with global and regional satellite-derived products revealed that airborne lidar offers superior spatial detail and accuracy, especially in structurally complex forests. ALS-based height estimates showed significantly lower mean absolute error (MAE: 1.6- 3.7 m) than global products (MAE: 2.9-7.8 m), while GEDI data consistently overestimated canopy height, 5.9 m on average, across the peninsular Spain. This work highlights the critical role of harmonized lidar datasets for robust forest monitoring, and provides a valuable baseline for future ecological assessments, carbon accounting, and validation of satellite products across the peninsular Spain.
The introduction of closely related species can threaten the genetic integrity of endemic taxa through hybridization and introgression. In Cuba, Swietenia macrophylla was widely planted in the 1970s for its fast growth and high-value timber, raising concerns about its potential genetic impact on the native S. mahagoni and the emergence of hybrids. This study investigates the genetic consequences of introducing S. macrophylla to Cuba by analysing 357 individuals from five populations, including two naturally regenerated S. mahagoni populations, a pure S. macrophylla remnant, and two mixed stands containing both species and morphologically intermediate forms. The two predominant cpDNA haplotypes were shared across all five populations, whereas one mixed stand exhibited the highest diversity, with nine chloroplast DNA haplotypes-suggesting that its establishment involved seeds from multiple sources. cpDNA markers didn't reveal clear specieslevel differentiation. In contrast, nuclear microsatellites indicated moderate genetic differentiation (mean F-ST= 0.15 +/- 0.02) and substantial within-population variability, with expected heterozygosity (He) ranging from 0.46 to 0.85. At the same time, S. mahagoni showed a higher number of alleles (N-a = 12.4-13.3) and expected heterozygosity (H-e = 0.73-0.78) than the remnant S. macrophylla population (N-a = 5.75; He = 0.59), likely reflecting the smaller size of the existing S. macrophylla plantation in Cuba. Based on discriminant analysis of principal components and STRUCTURE results, the two parental species were clearly separated into distinct genetic clusters, while putative hybrid individuals were mainly concentrated in the two mixed stands. Leaf morphological and molecular classifications were highly concordant in parental populations (approximate to 91%), confirming the phenotypic identifiability of S. mahagoni and S. macrophylla. The estimated proportion of hybrids varied: STRUCTURE (7.8-15.1%), whereas NewHybrids (36.1-39.2%). These findings provide a genetic framework for conservation-oriented management of native tree species, which is a tool for implementing long-term genetic monitoring and consolidating certified germplasm banks to safeguard the native Cuban mahogany.
Virgin forests are considered valuable reference areas for studying forest ecosystem structures and functions as they have been naturally grown with no human interventions. In the Mediterranean region there are few such areas and even scarcer data on deadwood which is a key element for multi-functional forest management. Data regarding the amount and variety of standing and lying deadwood were recorded in the core zones of the Frakto virgin forest in the central Rodopi Mountains in eight square plots of 0.25 ha each. The average deadwood volume accounted for 175.71 m3 ha-1 with lying deadwood consisting mainly of conifers and representing over 60% of the total deadwood. The deadwood distribution showed a decreasing trend towards larger size classes while in terms of quality deadwood it was represented by all stages of decay, thus showing high variability. The research outcomes contribute to knowledge standards when adopting management regimes in mixed beech forests aiming at sustainable forest ecosystem management.
In certain instances, forest managers are expected to emulate the structural patterns and disturbance regimes of primary forests. In this context, the forest cycle theory, established during the 20th century and widely adopted by many forest researchers and practitioners with little or no critique, suggests that particular patches (groups of trees) within an old-growth stand develop unidirectionally, progressing through stages from regeneration and initial growth to optimal and, finally, breakdown stage. However, due to the lack of long-term observations with detailed tree position data, little research has been conducted on this subject. Our study focused on proxy small-scale spatial dynamics based on patches of living trees for which exact positions and diameters were recorded from 1993 to 2023. First, we analyzed changes at the stand level in terms of diameter distributions and tree species composition over three decades. The distributions of European beech and silver fir remained relatively stable, while the cumulative distribution changed significantly due to a noticeable decrease in young trees of minor species. Secondly, we investigated the dynamics of basal area (BA) changes at the sub-stand level on small patches ranging from 0.01 ha to 0.0625 ha for each decade and over the entire observation period. At the decadal level, the values of Clark-Evans index indicated spatially random single-tree mortality as the predominant disturbance pattern. However, over a longer period, some of these small disturbances repeatedly occurred and concentrated at the same microlocations within the forest, which eventually resulted in spatially aggregated losses of BA by the end of the observation period. Another important finding from this study was that patches with non-directional BA dynamics were more common than those with continual positive BA accretion and/or continual negative BA trajectories. This finding significantly challenges the premises of unidirectional patch development.
The built environment of a campus is characterized by forest-dominated landscapes, which may determine the competitiveness of host university by influencing the emotional perceptions of experiencers. Relevant evidence has been derived from studies in parks and neighborhood landscapes but less is known about the emotions of experiencers in indoor and outdoor settings. In this study, 50 top universities were randomly chosen from a list of highly competitive rankings along a competition gradient, with campuses distributed over a wide geographical range from mainland China. Volunteers were recruited from indoor and outdoor locations (either number of 50 individuals per campus) to collect facial photos as a source of data used for analyzing expression scores for happy, sad, and neutral emotions (n = 4824). The positive response index (PRI) and emotional nonparametric relation index (ENRI) were calculated to comprehensively assess emotions. The neutral score decreased with an increase in university competition evaluated using the A+ discipline number. The blue space area benefited presentations of PRI and ENRI in the cohort mainly at outdoor places, and the green space area increased the exposure of happy scores for the indoor population. The campuses of top universities with more competitive disciplines were built with larger areas of blue and green spaces and larger cohorts with less calm facial emotions. It is recommended that top universities aiming to enhance competitiveness prioritize incorporating well-designed green and blue spaces with size and distribution tailored to campus usage patterns.
Precise wood measurement and traceability are important for increasing supply chain efficiency and guaranteeing legal compliance in the forest industry. Digitalization has emerged as a transformative trend globally, offering significant potential to address current challenges associated with wood transportation. This study investigates the accuracy of the CIND's Timspec (R) system in measuring the roundwood solid volume at the factory gate. It compares the system's performance using data from a number of 1,300 truckloads, of which 1,292 were retained after outlier removal, and were compared to data sourced by manual measurements performed in the forest and Microtec (R) measurements carried out in the sawmill yard. The study followed a comprehensive methodological framework from outlier removal using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to statistical analysis and heteroskedasticity tests to assess the reliability of the system. The results indicate a high degree of agreement among the used measurement systems. However, it highlights the differences in volume estimations produced by these systems, revealing that while the Timspec system tends to overestimate wood volumes by approximately 0.5 m3 overall, which is likely attributed to operational factors such as truckload gaps and moving speed, Microtec system underestimates by about 0.8 m3 overall, primarily due to observable factors such as bark loss during mechanical handling in the sawmill yard. Based on the findings, Timspec (R) system can be used to effectively check the conformity regarding the quantity of wood delivered to the processing industry by those in charge with tactical and strategic decision making, mainly due to speed, effectiveness, and coverage of measurements. Following improvements, this digital system may stand as an effective tool for the wood supply chain, allowing for fast and accurate estimates of the truckload-based wood deliveries, as well as automation of the measurement processes at the factory gate.
The historical fragmentation of forest ecosystems led to a significant spatial reduction in natural forest biomes. After centuries of exploitation for various purposes, the fragments remaining as national parks have been systematically monitored. This provides a wide range of field data and allows an in-depth understanding of processes responsible for short-and long-term forest dynamics. The existing monitoring systems should be considered unique and worth maintaining because they spanned before the era of remote sensing data acquisition in sufficient spatial and temporal resolution. We explored tree monitoring data from the oldest national park in Poland-Pieniny National Park (PNP) in the Western Carpathians, established in 1932. We assessed stand aboveground increment, recruitment, and mortality for 44 monitoring plots with field observations obtained in 1987, 1998, and 2009. Using a linear mixed-effects model, we assessed differences in stand biomass among sampling years and determined the drivers of biomass dynamics. For relative values of increment, recruitment, and mortality, we developed generalized linear mixed-effects models with a Beta distribution of the dependent variable. We found that stand composition was only slightly affected across 22 years. The mean aboveground biomass increased evenly and significantly (from 168 to 237 Mg/ha). Stand dynamics were mostly affected by stand structure characteristics, especially basal area (BA) and density, while other factors (geomorphometric and climatic characteristics) modified these relationships. The importance of climatic and geomorphometric factors shows local responses of stand dynamics, which can be utilized for fine-scale sites. We found twice higher relative increments in SW than in NE exposition, which can be related to higher insolation (sunlight and temperature) on SW-exposed hillslopes. The aboveground tree biomass change caused by mortality was partly controlled by several variables, among which the most important was BA. With increasing BA, mortality increased and was also slightly related to steeper slopes. Species-specific trends were dominated by species proportion. Fagus sylvatica had higher relative increment and mortality in plots with its dominance, while Abies alba absolute increment decreased. Studying the mountain forest dynamics is crucial for biodiversity, soil and groundwater protection, and tourism. Ground measurements are an accurate way to estimate biomass.
Numerous studies provide evidence of the positive effects of forest recreation on well-being. However, there is a lack of research conducted among sanatorium patients. Some sanatoria organize various exercises for patients, supervised by instructors in the forests surrounding the health resort. This study examined the opinions of patients in these sanatoria regarding the impact of such forest exercises on their well-being. An additional objective was to gain knowledge about the type of exercises held in the forest, as well as their frequency and duration. A total of 293 patients participated in the individual questionnaire interview. Ninety-five percent of respondents declared that forest exercises took place several times a week, while 5% indicated a frequency of 1-2 times a week. Seventy-five percent of patients spent 1 to 2 hours during individual forest exercises, 23% spent more than 2 hours, and 2% less than 1 hour. The most frequently organized forms of forest activities for sanatorium patients were walking (40%) and Nordic walking (31%), followed by exercising in the outdoor gym (17%) and gymnastics (12%). Almost all patients reported improved well-being after forest exercises. Additionally, 92% of patients also visited the forest during their leisure time. The results may pave the way for the potential development of forest bathing as an effective method to enhance the well-being of sanatorium patients, thereby positively influencing the process of improving their health. Considering health promotion, sanatorium management is encouraged to implement various forms of forest recreation, including forest bathing, into sanatorium treatment programs. It is essential to ensure that the form of forest recreation and the duration of sessions (1-2 hours) are tailored to the capabilities of sanatorium patients.
This paper is a comparative synthesis of the gene diversity and gain based on published results of two Eucalyptus camaldulensis breeding programmes (BP 1&2) in India. The dynamics and genetic gain of four first generation (F1) seedling seed orchards (SPA) of BP1 were compared with three second generation (F2) SPAs and two clonal seed orchards (CSO) of BP2. Three F1 orchards (F1 SPAs 1,3&4) of BP1 had low flowering (30%) and high fertility variation (sibling coefficient, Psi = 5-11) whereas F1 SPA2 had 73% fertile trees (Psi = 2.27). No significant gain was obtained in BP1 when the four F1SPA seed crops were evaluated at two locations in genetic gain trials-to estimate the gain obtained in comparison to native provenance and commercial clone checks. For infusing improved seed from BP1 to BP2, three F2SPAs were developed, of which two (F2 SPA 1-2) were thinned genetic gain trials that incorporated bulked seed lots from four F1 SPAs of BP1, and the third (F2 SPA 3) originated from bulked seed of only one F1SPA. Two clone trials of F1 progeny selections were converted to clonal seed orchards (F2 CSO 1&2). Flowering was low (26%) in the F2 SPAs also with high fertility variation (Psi, 9-14). The CSOs had high flowering (81%) but fertility was highly skewed in CSO2 (Ns = 2) compared to CSO1 (Ns = 11). The F2 SPAs 1&2, which originated from four F1 SPAs in genetic gain trials, had higher effective population size (Ns, 95 and 74) than the F2 SPA3 (Ns = 39) and CSOs, and better progeny performance than the native provenance at 3 years. CSO2 had the lowest gene diversity and survival than the other taxa. Genetic composition and fertility status of the orchards affected the performance and genetic diversity of progeny.
The fallow deer (Dama dama) is one of the main species of large herbivores in Romania, with afluctuating presence overtime, particularly during the last century. Population fluctuations have been driven by acombination of factors including climate, habitat quality, interspecific competition, predation, and human activities. While mortality represents a key component in the population dynamics, this study aims to quantify juvenile mortality in fallow deer during their first year of life, representing one of the first investigations of this type conducted in Romania. The study examines juvenile mortality rate in a fallow deer population from the Western Plain of Romania overthe period June 2020-May 2021. Population structure was analyzed by age classes, and temporal variation in reproductive performance was evaluated by examining the number of calves per mature female over one year. The results indicate a juvenile mortality rate of approximately 50% during the first year of life. This level of mortality is considered typical for natural habitats supporting free-ranging ungulate populations in the presence of substantial mesocarnivores populations. The age-class structure of female fallow deer, together with the population dynamics of mesocarnivores, particularly the golden jackal (Canis aureus) and the red fox (Vulpes vulpes), suggests that predation plays a significant role in juvenile mortality within the study area. These findings highlight the importance of continuous monitoring of reproductive indicators and predator populations to ensure more effective wildlife management strategies.
A total of 204 silver fir open-pollinated families from four first-generation seed orchards and 12 natural stands were tested in a nursery experiment. The performances and genetic parameters of the seed orchards (SO) and natural populations progenies (NP) were determined and compared at ages from 3 to 6 years old. Several traits were assessed such as: the total height, the annual height increment, the root collar diameter, the branch length, the number of branches, and the bud burst evaluated during spring 2015-2016. On average, progenies derived from seed orchards outperformed those from natural stands, exhibiting 8-14% greater height and 4-6% greater diameter. Estimates of genetic variance components indicated that most of the variation was attributable to additive genetic effects. Total height and annual height increment showed the highest proportions of additive variance, ranging from 42 to 91% in NP progenies and from 41 to 78% in SO progenies. Narrow-sense individual heritability estimates were generally higher than those previously reported for silver fir, ranging from 0.12 to 0.83 for SO progenies and from 0.23 to 0.91 for NP progenies. Family heritability exceeded individual heritability in both progeny types investigated. Among the studied traits, total height exhibited the highest heritability for both progenies. Heritabilityoftotalheightincreasedmoderatelyfromages3to6,whereasheritability for root collar diameter declined and remained relatively stable for branch-related traits. Phenotypic and genetic correlations between growth traits were relatively high, while those between bud burst and growth traits were positive and weak for both progenies. The correlations between growth traits and branch traits were positive but nonsignificant. A significant correlation was obtained between bud burst in 2016 and elevation of populations. The phenotypic correlations were higher than the genetic ones for both progenies. Genetic gain differed depending on the selection method, intensity, and traits examined. Across all selection methods, total height showed greater genetic gain than root collar diameter. Recurrent selections based on the parental genetic values will bring the greatest genetic gain in the next breeding generation. The genetic gains that could be achieved if the backwards selection will be used at the level of the first-generation seed orchards are between 19-27% for total height, 9-27% for diameter and 40-48% for current height increment. If the backward selection is used in natural populations, a genetic gain of 21-32% for total height, 13-22% for diameter and 42-55% for current height increment could be obtained. The results are discussed linking them to their implications for the development of a silver fir breeding strategy and also for the second-generation seed orchards establishment.
Litter plays a vital role in forest ecosystems, significantly contributing to nutrient cycling through litter production and decomposition. Understanding these processes is crucial for forest management and conservation, especially in the face of global environmental changes. This research is important because it provides insights into the litterfall patterns and nutrient dynamics of different tree species, which are essential for maintaining forest health and productivity. The present study aimed to determine the quantity and pattern of litterfall and nutrient return to the forest floor of Pinus roxburghii, Shorea robusta, and Bambusa tulda. We collected litterfall monthly over two years in three different plantations of P. roxburghii, S. robusta, and B. tulda, and measured the nutrient content of the litter. The mean annual litter production recorded in these plantations was greatest in B. tulda (4652.15 kg ha(-1)yr(-1)), followed by S. robusta (3731.4 kg ha-1yr(-1)) and P. roxburghii (2588.85 kg ha(-1)yr(-1)). The plantations included both the main species and associated understory vegetation, such as herbs and shrubs. Leaf litter from the main species accounted for the highest total litterfall in April. During this period, leaf litter accounted for approximately 24% of the total in S. robusta, 16% in P. roxburghii, and 15% in B. tulda. Minimum mean monthly litterfall was recorded in September and November for P. roxburghii and S. robusta, and in November and December for B. tulda. There was significant monthly variation in nutrient content between the species. Maximum nitrogen (N) was measured during June for P. roxburghii, December for S. robusta, and January for B. tulda, and phosphorus (P) and potassium (K) concentrations also varied significantly. Annual patterns of nutrient return followed the order N > K > P. Maximum nutrient return was observed during April in all species due to higher litter production during that month. There was greater variability in litter quality in the broadleaved forest (S. robusta) than in the coniferous forest (P. roxburghii), indicating the more dynamic functioning of broad-leaved plantations compared to coniferous ones.. This research highlights the critical role of litterfall in nutrient cycling within forest ecosystems and underscores the importance of considering species-specific litter dynamics in forest management and conservation strategies.
Above ground biomass (AGB) estimation is vital for monitoring carbon storage and ecosystem fluxes, especially in tropical forests for climate mitigation in offers high resolution forest monitoring; however, field measurements are crucial to enhance spatial accuracy. This study assessed the limitations of using machine learning models trained on GEDI data to estimate AGB for two distinct forest Reserve (KFR). Our specific objectives were (i) developing Random Forest (RF) machine learning model using GEDI data for training, (ii) comparing GEDI estimates with field measurements, and (iii) quantifying the limitations of using integrated GEDI-RF model. Plots were coincided with GEDI beams for comparison to assess variability and bias in AGB estimates. The p-value of 0.005 for heteroskedasticity in KNFR indicated high variability and bias of the GEDI-RF model relative to the field measured model. In contrast, p-value of 0.195 for heteroskedasticity in KFR indicated low variability and bias of the GEDI-RF model relative to the field measured model. 55% of plots which coincided with GEDI had less than 10% relative difference in AGB estimates between models. Plots outside of GEDI had a relative difference in AGB estimates between models greater than 10%. Relative to the field measured model, the GEDI-RF model overestimated AGB values less than 100 Mg ha-1 and underestimated greater than 200 Mg ha-1. This study contributes to effective forest monitoring, carbon accounting, and conservation in heterogeneous forests.
