National Forest Inventory Research Articles (Page 1)

Abstract. The effect of climate change on tree growth in boreal forests is likely mediated by local climate conditions and species-specific responses that vary according to differences in traits. Here, we assess species-specific tree growth responses to climate along gradients of mean annual temperature and soil moisture. We assessed growth-climate relationships by using tree-ring width data in Norway spruce (Picea abies) and Scots pine (Pinus sylvestris) from the Swedish National Forest Inventory in relation to climatological data along gradients in mean annual temperature and soil moisture. Trees growing in warmer areas responded more negatively to high temperature and more positively to high precipitation. Site-specific soil moisture only showed an effect on the growth responses in areas of high mean annual temperature. The growth-climate response differed between the species; specifically, the growth response to high temperature varied more along the gradient of mean annual temperature for P. abies than for P. sylvestris. Growth responses to extreme weather events did not deviate from non-extreme events along the climatic gradients. Our study suggests that tree growth responses to climate change will depend on tree species and site-specific climate conditions. In warmer areas, high soil moisture may mitigate the adverse effects of warming on tree growth mainly for P. abies. In colder areas, P. abies is likely to benefit more from warming than P. sylvestris. Although the matching between extreme tree growth and extreme temperature or precipitation years was consistently higher than expected if the two variables were independent, an extreme year is unlikely to cause a tree growth response that markedly diverges from predictions based on linear relationships. Thus, the amplification of negative growth-climate responses during extreme years is likely of limited importance for long-term growth, as such events are inherently rare. Nevertheless, extreme years may influence forest productivity by affecting tree mortality, an aspect that was beyond the scope of this study. In the face of climate change, our results emphasize that forest management should consider site-specific climate conditions and species differences to sustain future forest productivity.

ABSTRACT Information on forest growth is critical for understanding forest dynamics and supporting sustainable forest management. The assessment of current annual increment (CAI) of forest stands using repeated measurements on permanent plots is one of the key tasks of national forest inventories; however, such data are often unavailable in many countries or local sites. Therefore, simplified methods based on one-time tree measurements can provide a practical alternative for assessment of CAI. This paper provides an empirical evaluation of the approach for estimating CAI using percentage of volume increment in Scots pine-dominated stands in Ukraine using increment core sampling. The study is based on 927 radial increment measurements obtained from 49 stands of different age and productivity. Based on sampled increment cores, we developed two models of the percentage of the basal area increment as functions of stand age and quadratic mean diameter. The age-dependent model showed a lower root mean squared error (0.76%) than the diameter-dependent model (3.26%) and was therefore selected for CAI estimation. The height growth, which is a second component of volume increment, was predicted using an existing model based on stand age and mean height. Stand-level forest inventory planning data were used to calculate CAI and its age dynamics for the study area. This work demonstrated an effective approach for rapid assessment of CAI using non-destructive sampling, which we recommend for practical application in stand-level forest management planning or prelaminar evaluation of forest growth during early cycles of sample-based forest inventory.

Integrated analysis of harvest statistics provided by remote sensing, national forest inventories and administrative survey systems: An example from Italy

Recovery of carbon dynamics, soil nutrients and tree diversity during secondary succession within the tropical dry forests in the Yucatán Peninsula.

Terrestrial and mobile laser scanning for national forest inventories: From theory to implementation

Tree niche characteristics primarily regulate species, phylogenetic and functional diversity of tree communities across forest types in South Korea.

Annual estimates of wind disturbance in relation to time of observation in a panelized national forest inventory

Abstract. The relationship between net primary productivity (NPP) and forest age varies among forest species, yet there were no available NPP–age relationships established for various forest species in subtropical China for use in forest carbon modeling. This study explored the NPP–age relationships for seven forest species in subtropical China using field survey data from the Strategic Priority Project of Carbon Budget (SPPCB), National Forest Inventory (NFI) Type I (NFI-I), and Type II (NFI-II) data. Forest species included Pinus massoniana (P. massoniana), Cunninghamia lanceolata (C. lanceolata), Eucalyptus robusta (Eucalyptus), Other Coniferous Forests (OCF), Softwood Broadleaf (SWB), Hardwood Broadleaf excluding Eucalyptus (HWB), and Mixed Forests (MF). Based on these three datasets, we were able to derive subtropical forest species-specific NPP–age relationships using the Semi-Empirical Model (SEM). Implementation of these species-specific relationships in the process-based Integrated Terrestrial Ecosystem Carbon Cycle (InTEC) model markedly improved above-ground biomass (AGB) simulations for subtropical forests relative to simulations driven by the previously published China-wide NPP–age relationships. The greatest improvements were observed for P. massoniana, OCF, Eucalyptus, and SWB, where root-mean-square errors (RMSE) declined by 19.1 %–53.3 %. These species-specific NPP–age relationships therefore provide a robust, spatially explicit basis for forest carbon modeling and management in subtropical China.

Key message Natural and anthropogenic pressures, combined with frequent extreme events driven by climate change, are altering the dynamics of forest ecosystems. As a result, social needs, forest policies, and forest management require precise and reliable information that can be obtained through forest monitoring, including national forest inventories (NFIs). In this context, the new Italian NFI introduces multiple innovations: During the preliminary stages of the new NFI, strategy and procedure developments were based on the needs and suggestions of various stakeholders through an effective participatory approach. Transitioning from periodic to annual estimates of forest attributes and their changes has been deemed essential for assessing the effects of increasingly frequent large-scale disturbances, such as major wildfires and extreme weather events. Partial integration with other monitoring programs, such as ICP Forests, has proven beneficial. Given the global climate change and biodiversity loss challenges, dedicated surveys have become essential for enhancing our understanding of forest ecosystem components. The use of remotely sensed data for mapping forest variables as a component of the new NFI (i.e., enhanced NFI) plays a key role in supporting policymakers. Data collected at tree level or aggregated at plot level will be made available, and plot coordinates may be released for scientific purposes and research projects, subject to case-by-case evaluation. The planned updates and modifications in the new forest inventory are outlined. Additionally, these innovations are discussed to support similar national and international advancements, focusing on modernizing forest inventory methods while balancing established best practices with innovation.

Abstract In Mediterranean ecosystems, afforestation efforts have created landscapes with high fuel loads and continuity that, in combination with warmer and drier conditions, may intensify fire activity. Yet, the relative contribution of afforestation to current fire severity remains little explored. We hypothesized that, under Mediterranean conditions, pine plantations can generate high‐intensity fires that increase fire severity and show limited post‐fire recovery compared with other vegetation types. We integrated Sentinel‐2 imagery with digital terrain models, vegetation maps, and national forest inventories to assess fire severity (dNBR) and one‐year post‐fire recovery from three large wildfires in Spain. We then used linear models to investigate the patterns of fire severity and early recovery across vegetation types. Change‐point models were applied to pine plantations to evaluate whether reducing tree density beyond a specific point can limit fire severity. Pine plantations exhibited significantly higher severity and lower early recovery than other vegetation types, particularly in areas with high tree densities and abundant shrub cover. Moreover, proximity to pine plantations was associated with increased fire severity in adjacent vegetation, whereas reducing tree density below a threshold of 440 trees/ha mitigated fire severity within plantation stands. Policy implications . Our findings provide quantitative evidence that pine plantations can exacerbate fire severity under contemporary climate conditions, and that, once burned, these areas seldom recover. Effective spatial planning and management of tree plantations is therefore essential in order to promote more sustainable fire regimes in Mediterranean ecosystems. Therefore, carbon mitigation strategies should carefully consider the risk of establishing dense and continuous pine plantations when implementing future afforestation programmes.

IntroductionIn order to effectively manage ecosystems, it is important to understand how the structure and function of the ecosystem are measured and interpreted, and ecosystem multifunctionality (EMF) is being used as an important indicator for providing sustainable ecosystem functions and managing qualitative stability. The objective of this study is to examine the biotic and abiotic mechanisms underlying the production and regulation of EMF within various forest stand types.MethodsTo this end, we assessed the influence of biotic (tree species, functional, and stand structural diversity of trees), abiotic (elevation, aridity index), and stand age (mean age of the five dominant trees per plot) factors on EMF. A total of 2,859 natural forest plots—comprising coniferous, broadleaved, and mixed stands—were analyzed based on data from the 7th National Forest Inventory of South Korea. To determine the major factors influencing EMF, we applied a multi-model inference approach along with piecewise structural equation modeling.ResultsOur results suggest that higher plant biodiversity was positively associated with EMF. In addition, older forests exhibit greater stand structural diversity, which in turn enhances the maintenance of EMF. The analysis of abiotic factors revealed that EMF increased with elevation. Furthermore, variables related to plant water stress consistently had negative direct and indirect effects across all forest stand types. Finally, the mechanisms controlling EMF differed among forest stand types.DiscussionThese findings suggest that promoting forest succession, maintaining biodiversity, and enhancing stand structural diversity are essential forest management strategies for improving EMF. Furthermore, since the controlling factors of EMF varied among forest stand types, forest-type specific management strategies are required. Lastly, this study provides valuable insights for guiding sustainable forest management that enhances both EMF and specific ecosystem functions, while supporting human well-being.

Current and future carbon stocks of a dominant forest plantation species, Cryptomeria japonica, throughout Japan.

GEDI and Sentinel data integration for quantifying agroforestry tree height and stocks.

ABSTRACT In Europe, the amount of deadwood (DW) varies regionally, hence national estimates of satisfactory level (EU Nature Restoration Law) are necessary. In this study, satisfactory levels of DW for Latvia were estimated based on the National Forest Inventory concerning stand age and management regime: recently managed, recently unmanaged, and stands with restricted management. In these stands, the mean values of 14.8 ± 1.8, 26.3 ± 1.6, and 38.3 ± 2.9 m3 ha−1 in which of 34.4, 42.9, and 36.6% were standing DW, were estimated, respectively. The overall mean was 23.8 ± 1.1 m3 ha−1. The estimates were higher than European mean and corresponded to the commonly applied threshold values (20–30 m3 ha−1) for the hemiboreal zone, suggesting them as satisfactory. The age-related increase in the amount of DW was faster in the recently unmanaged stands, irrespectively of restriction, where the threshold values were reached 10–20 years earlier, suggesting potential for improvements via voluntary reduction of management. The amount and type (lying or standing) of DW were age-dependent, yet the age-relations differed by tree species and management regime. Deciduous stands showed potential to accelerate DW accumulation at younger stands, hence the anticipated increase in abundance of deciduous trees would contribute to amount of DW in Latvia.

ABSTRACTUnderstanding the extent to which land‐use changes (LUC) impact soil organic carbon (SOC) is essential for accurate carbon accounting and global efforts aimed at reducing the negative impact of LUC on climate change. Recognizing that most of the SOC change due to LUC occurs in the topsoil, current efforts to quantify SOC change often overlook subsoils beyond 30 cm depth. We used data from Germany's national agricultural and forest soil inventories to address this sparsity by modeling depth‐dependent, LUC‐induced, SOC stock change down to 90 cm using data‐driven reciprocal modeling. This modeling was carried out using an ensemble approach for prediction and area of applicability assessments to avoid extrapolation. Landscape, climate, and pedological properties were used to predict the equilibrium SOC stock at four depth intervals (0–10, 10–30, 30–60, and 60–90 cm) for all six land‐use change directions between cropland, grassland, and forest. While the greatest change occurred at the surface for all LUC directions, we detected significant SOC stock change down to the sampled depth of 90 cm. Approximately 30% of the detected SOC stock change was found in the subsoil (30–90 cm). For LUC to or from forests, the litter layer dominated the changes in SOC such that for LUC between grassland and forest, SOC stock change in the mineral soil was mostly offset by the addition or removal of the litter layer. For all LUC directions, the World Reference Base soil group was the most important factor for determining the magnitude of SOC stock change. This study underscores the importance of deeper soil sampling for accurate carbon accounting and climate‐change mitigation strategies.

In this study, we used a generalised linear mixed-effects model (GLMER) to establish a predictive pedotransfer function defining the relationship between forest soil bulk density and total organic carbon. More than 950 soil samples were obtained from four forested areas with a wide range of bedrock (limestone, loess, crystalline volcanic, sandstone, alluvial loam, polygenic loam and transported materials rich in organic carbon) and soil types (Leptosols, Cambisols, Fluvisols, Podzols and Technosols). Model validation was performed by testing against 10% of the data randomly selected from the original dataset (10% dataset) and an independent dataset from the Czech national forest inventory (NFI2 dataset). The GLMER including sample origin locality as random effect displayed a highly accurate predictive capacity. Subsequent analysis avoided model simplification by excluding sample origin and retaining the global GLMER only. For all samples, the final model covered a range from 0.16 to 27.70% for total organic carbon and from 0.27 to 1.94g cm- 3 for bulk density. Model residuals based on laboratory values were symmetrical with a median value just 0.09g cm- 3 higher. While validation with the 10% dataset confirmed model parameter validity with high accuracy, validation using the NFI2 dataset indicated slight discrepancies, possibly due to differences in sampling method used. Individual GLMs fitted both validation datasets better than the global GLMER; however, Wilcoxon tests showed better consistency in the original model on the 10% validation data. Consequently, we suggest the global GLMER may prove more suitable for direct use in expressing bulk density from total organic carbon. The pedotransfer functions produced, particularly that based on global GLMER, can be used to express bulk density via total organic carbon content, or vice versa, with high accuracy. While based on a wide range of bedrock/soil types, further studies may be needed in other regions to validate the model for general application.

A scientific evaluation of site quality is essential for the sustainable management of forest ecosystems. However, the absence of a standardized evaluation framework has resulted in site quality assessments that are not comparable across different broadleaf forest types on large spatial scales, impacting forest management decisions related to afforestation, thinning, and carbon sink management. Therefore, establishing a methodological framework for evaluating the site quality of various broadleaf stands could provide practical implications for forestry. Using the data from four cycles of the National Forest Inventory (NFIs) of China, the Richards, Logistic, and Korf models were applied to simulating the growth of 18 major groups of broadleaf trees. We fitted guide curves using the models and constructed site productivity index models for each group. A generalized site productivity index model for broadleaf stands was developed using conversion coefficients between species, with subsequent applicability testing and spatial analysis to assess dynamic changes in site productivity. Results indicate that the Richards model, with an average coefficient of determination (R2) of 0.91, performed better than the Logistic and Korf models. Statistical tests show that the site productivity index models of major broadleaf stands achieve accuracy rates exceeding 90%. The Spearman correlation coefficient is greater than 0.99 between the productivity index classes based on generalized and specific models, demonstrating both the reliability and applicability of the generalized model. Proportional and spatial analyses indicate a continuous trend of improvement in the site productivity of broadleaf stands from 2003 to 2018. The generalized productivity index model based on the relationship between age and biomass was validated by feasibility tests, making it suitable for application in forestry management and prediction. A continuous improvement trend in the site productivity of broadleaf forest was demonstrated, despite fluctuations during short intervals related to uncertainties in our models, which provided a robust, large-scale tool for evaluating forest productivity, offering critical support for sustainable forest management, policy-making, and carbon sequestration strategies in China.

Does UNESCO designation enhance forest protection? Evidence from the Hyrcanian national forest inventory

ABSTRACTAimClimate change is altering forest disturbance regimes across Europe. Structural and species diversity are generally thought to enhance disturbance resistance. However, how disturbances affect stand structure and tree species diversity remains untested across broad spatial gradients and for multiple disturbance agents. Furthermore, determining how disturbance‐induced changes affect resistance to subsequent disturbances is critical for understanding forest dynamics in the face of global change.LocationThe forests of Finland, France and Spain.Time Period1986–2020 ce.Major Taxa StudiedTrees.MethodsWe examined the effects of tree size and tree species diversity on resistance to fire, wind, biotic and snow disturbances using a National Forest Inventory dataset of 4827 disturbed plots. We quantified disturbance resistance as the tree mortality response to different severity disturbances. We modelled the immediate disturbance‐driven changes in structural and tree species diversity, and predicted how these changes affect resistance to subsequent disturbances.ResultsHigh structural diversity increased stand resistance to snow disturbance, and high species diversity decreased resistance to fire. Severe disturbances consistently decreased structural and species diversity across all disturbance agents. However, both diversity metrics increased after low severity snow disturbances, and structural diversity increased after low severity biotic disturbance. Resistance to subsequent disturbance increased after low severity fire and low to moderate severity wind disturbances. Biotic and snow disturbance had the opposite effect, with moderate severity disturbances decreasing resistance to subsequent disturbance more than low severity disturbances.Main ConclusionsStructural and species diversity had little effect on plot‐level disturbance resistance. Severe disturbances consistently decreased structural and species diversity, while low to moderate severity disturbances can increase these diversities. Resistance to subsequent disturbance is contrasted between disturbance agents and disturbance severity. Increasing disturbance severity may decrease structural and species diversity in future forests.

Abstract Recent mortality pulses indicate pathways to restore maladapted forests towards more natural, mixed, resilient ecosystems. Under climate change, carbon sequestering forests serve as forces for mitigation but face threats from disturbances. The uncertain development of this duality complicates stakeholder-relevant predictions of timber yield or tree species compositions. We analyzed uncertainty in forest development over 50 years, focusing primarily– but not exclusively– on Scots pine, the most important tree species in northern Germany,. Thereunto, i. future survival was examined on a site- and climate-specific basis. The novelty of the simulations lies in ii. quantifying the influence of irregular die-off on forests under stand-wise (discrete) or tree-wise (diffuse) mortality patterns to iii. investigate yield and harvest potentials. By spanning a scenario funnel from two management and two climate projections on 17,551 National Forest Inventory plots in northern Germany, we assess prospective uncertainties. The transition of forest composition through space and time with conditional hazard rates resembles a Markov process via Monte Carlo sampling. Prospectively, i. mortality doubles depending on the species. Compared to undisturbed development, ii. forest restoration outcomes are uncertain; stand-losses can accelerate restoration by up to 10%, while tree-losses might slow it down. Under disturbances, iii. volume increment and stand age decrease as harvests rise in the medium-term with large dimensioned timber increasing fivefold. Driven by climate change and forest demographics, the decline in yield and the remaining 40% monocultures are critical. Forest development is inert, therefore we suggest more differentiated silvicultural concepts for actively adapting forests to alarming changes.