•National Forest Inventory data used to evaluate sustainable forest management.•Increase in dead wood in Sweden is small and mainly driven by storm events.•Available dead wood dominated by small ...diameter logs in early stages of decay.•Minor direct impact of forest policy of dead wood volumes in Swedish forests.
Dead wood is a critical resource for forest biodiversity and widely used as an indicator for sustainable forest management. Based on data from the Swedish National Forest Inventory we provide baseline information and analyze trends in volume and distribution of dead wood in Swedish managed forests during 15years. The data are based on ≈30,000 sample plots inventoried during three periods (1994–1998; 2003–2007 and 2008–2012). The forest policy has since 1994 emphasized the need to increase the amount of dead wood in Swedish forests. The average volume of dead wood in Sweden has increased by 25% (from 6.1 to 7.6m3ha−1) since the mid-1990s, but patterns differed among regions and tree species. The volume of conifer dead wood (mainly from Picea abies) has increased in the southern part of the country, but remained stable or decreased in the northern part. Heterogeneity of dead wood types was low in terms of species, diameter and decay classes, potentially negatively impacting on biodiversity. Overall, we found only minor effects of the current forest policy since most of the increase can be attributed to storm events creating a pulse of hard dead wood. Therefore, the implementation of established policy instruments (e.g. legislation and voluntary certification schemes) need to be revisited. In addition to the retention of dead trees during forestry operations, policy makers should consider calling for more large-scale targeted creation of dead trees and management methods with longer rotation cycles.
•Some 1.1 billion ha are covered by all of the SFM tools investigated in FRA 2015.•Policies, laws and regulations supporting SFM cover 98% of permanent forest land.•Forest inventories have recently ...been conducted in 112 countries.•Some 52% of the total forest area was under Forest Management Plan (FMP) in 2010.•International forest certification was most extensive in high income countries.•There are positive increases in most SFM indicators globally.
Sustainable forest management (SFM) is many things to many people – yet a common thread is the production of forest goods and services for the present and future generations. The promise of sustainability is rooted in the two premises; first that ecosystems have the potential to renew themselves and second that economic activities and social perceptions or values that define human interaction with the environment are choices that can be modified to ensure the long term productivity and health of the ecosystem. SFM addresses a great challenge in matching the increasing demands of a growing human population while maintaining ecological functions of healthy forest ecosystems. This paper does not seek to define SFM, but rather provides analyses of key indicators for the national-scale enabling environment to gain a global insight into progress in implementing enabling and implementing SFM at the national and operational levels. Analyses of the Global Forest Resources Assessment 2015 (FRA) country report data are used to provide insights into the current state of progress in implementing the enabling conditions for SFM. Over 2.17 billion ha of the world’s forest area are predicted by governments to remain in permanent forest land use, of which some 1.1 billion ha are covered by all of the SFM tools investigated in FRA 2015. At the global scale, SFM-related policies and regulations are reported to be in place on 97% of global forest area. While the number of countries with national forest inventories has increased over that past ten years from 48 to 112, only 37% of forests in low income countries are covered by forest inventories. Forest management planning and monitoring of plans has increased substantially as has forest management certification, which exceeded a total of over 430 million ha in 2014. However, 90% of internationally verified certification is in the boreal and temperate climatic domains – only 6% of permanent forests in the tropical domain have been certified as of 2014. Results show that more work is needed to expand the extent and depth of work on establishing the enabling conditions that support SFM over the long term and suggests where those needs are greatest.
Soil properties influence plant physiology and growth, playing a fundamental role in shaping species niches in temperate forest ecosystems. Here, we investigated the impact of soil data quality on ...the performance of species distribution models (SDMs) of 41 woody plant species in Swiss forests. We compared models based on measured soil properties with those based on digitally mapped soil properties on regional (Swiss Forest Soil Maps) and global scales (SoilGrids). We first calibrated topo-climatic SDMs with measured soil data and plant species presences and absences from mature temperate forest stand plots. We developed further models using the same soil predictors, but with values extracted from digital soil maps at the nearest neighbouring plots of the Swiss National Forestry Inventory. The predictive power of SDMs without soil information compared to those with soil information, as well as measured soil information vs digitally mapped, was evaluated with metrics of model performance and variable contribution. On average, models with measured and digitally mapped soil properties performed significantly better than those without soil information. SDMs based on measured and Swiss Forest Soil Maps showed higher performance, especially for species with an ‘extreme’ niche position (e.g., preference for high or low pH), compared to those using SoilGrids. Nevertheless, if no regional soil maps are available, SoilGrids should be tested for their potential to improve SDMs. Moreover, among the tested soil predictors, pH, and clay content of the topsoil layers most improved the predictive power of SDMs for forest woody plants. In conclusion, we demonstrate the value of regional soil maps for predicting the distribution of woody species across strong environmental gradients in temperate forests. The improved accuracy of SDMs and insights into drivers of distribution may support forest managers in strategies supporting e.g. biodiversity conservation, or climate adaptation planning.
Display omitted
•We compared SDMs based on measured or mapped soil data at varying quality.•Soil enhanced SDMs of temperate forest woody species with ‘extreme’ niche position.•Regional Swiss Forest Soil Maps improved SDMs similarly to measured soil data.•Global SoilGrids enhanced SDMs to a lesser extent for several forest species.•Topsoil pH and clay content are key predictors for temperate forest woody plants.
Display omitted
•At the plot level, mixed-effects models provided the most accurate tree height predictions.•By grouping similar plots the ANN predictions improved.•The ANNs are more competitive if ...enough tree height measurements are available.•The BAL tree competition variable increased the accuracy of ANN models.
Tree heights are one of the most important aspects of forest mensuration, but data are often unavailable due to costly and time-consuming field measurements. Therefore, various types of models have been developed for the imputation of tree heights for unmeasured trees, with mixed-effects models being one of the most commonly applied approaches. The disadvantage here is the need of sufficient sample size per tree species for each plot, which is often not met, especially in mixed forests. To avoid this limitation, we used principal component analysis (PCA) for the grouping of similar plots based on the most relevant site descriptors. Next, we compared mixed-effects models with height-diameter models based on artificial neural networks (ANN). In terms of root mean square error (RMSE), mixed-effects models provided the most accurate tree height predictions at the plot level, especially for tree species with a smaller number of tree height measurements. When plots were grouped using the PCA and the number of observations per category increased, ANN predictions improved and became more accurate than those provided by mixed-effects models. The performance of ANN also increased when the competition index was included as an additional explanatory variable. Our results show that in the pursuit of the most accurate modelling approach for tree height predictions, ANN should be seriously considered, especially when the number of tree measurements and their distribution is sufficient.
•This study presented new tree basal area increment models for 29 different mixtures along an aridity gradient in Spain.•Higher productivity in mixed than pure stands was found, suggesting that BAI ...values may increase with the increment of species diversity.•Competition was the most representative biological interaction in pine-pine forests; neutralism and facilitation in pine-oak and oak-oakones.•Tree productivity may be also significantly limited by aridity, finding higher values of basal area increment in more humid than arid conditions.•Models presented in this study can be used in the design of guidelines for Mediterranean mixed forests under future climate change scenarios.
Competition plays a key role controlling tree growth in mixed forests. Contrary to monocultures, quantifying species mixing influence on tree growth suppose a challenge since the presence of two or more species requires to estimate the degree of intra- and inter-specific competition among trees. Moreover, it is well known that aridity can also influence tree growth, especially in the Mediterranean Basin. In the present context of climate change, it is essential to take into account species mixing and aridity uncertainty in the design of sustainable management guidelines for Mediterranean mixed forests. To achieve that, data from Spanish National Forest Inventory was used in this study to fit new mixed-effects basal area increment (BAI) models for 29 two-species compositions in Spain. A wide range of different competition structures (intra-specific, inter-specific, size-symmetric and size-asymmetric) and aridity conditions (in terms of the De Martonne Index) were included and tested into the BAI models. Parameter estimations were obtained for all possible species, mixtures and combinations by Maximum Likelihood (ML). Models with all the coefficients being significant (p < 0.05) were first selected. Among these models, we used Akaike Evidence Ratios for selecting the best one by species for each mixture. The best model for each species and mixture was used to analyze the competition and climatic influence on tree growth. Regarding competition influence, a common trend among mixtures was found with higher productivity in mixed than pure stands, suggesting that BAI values may increase with the increment of species diversity. Based on intra and inter-specific competition indexes, competition seemed to be the most representative biological interaction in conifer-conifer mixtures, since neutralism and facilitation may occur more frequently in conifer-broadleaved and broadleaved-broadleaved mixtures. Our findings also suggested that tree growth may be significantly limited by arid conditions, excepting for Pinus halepensis and Pinus pinea. Our rigorous modelling approach successfully uncovered not only possible mixing effect among various species but also help us to understand the effect of aridity on tree growth. Thus, models presented in this study can be used in the design and implementation of management and adaptation guidelines under future climate change scenarios.
Plant functional traits are highly plastic to changes in climatic factors and nutrient availability. However, the intraspecific plant response to abiotic factors and the overall effect on tree growth ...and productivity is still under debate. We studied forest productivity for 30 Quercus ilex subsp. ballota forests in Spain along a broad climatic gradient of aridity (mean annual precipitation from 321 to 858 mm). We used linear mixed models to quantify the effect of climatic and edaphic (soil nutrients, topography, and texture) factors on tree functional traits (leaf and branch traits), and subsequently, the effect of such functional traits and abiotic factors on the relative growth rate (RGR) of adult trees. We used piecewise structural equation models (SEMs) to determine the causal effect of intrinsic and extrinsic factors on forest productivity. Our results showed that tree functional traits were mainly explained by climatic and edaphic factors. Functional traits and tree biomass explained forest biomass and RGR, respectively, which ultimately explained forest productivity. In conclusion, intraspecific variability of functional traits has a significant effect on plant biomass and growth, which ultimately may explain forest productivity in Quercus ilex forests.
Display omitted
•Aridity is the main environmental factor affecting leaf functional traits.•Soil nutrients are the main drivers of the relative growth rate in Quercus ilex.•Forest productivity is explained by forest biomass and relative growth rate.•Trait intraspecific variability has a significant effect on forest biomass.
Abstract
Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest ...carbon capture and storage of landscapes, biomes, and—ultimately—the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.
Effective and comprehensive monitoring of the quantity of deadwood has become an important aspect of forest inventories for studies on structural and demographic dynamics, biodiversity and carbon ...stocks. Assessing dead wood quantity, however, is challenging and time consuming due to the structural complexity of deadwood. To monitor coarse woody debris (CWD) in a 10-year remeasuring cycle, we propose to combine full area sampling, to assess and position large-diameter CWD, with line intersect sampling, to estimate the volume of small-diameter CWD. The aim was to simultaneously I) lower the work load in the field, II) ensure low variability in average CWD volume and III) enable remeasurement of a high share of individual CWD objects to study dead wood dynamics and related biodiversity. Using data from 1601 circular plots measured with full area sampling in 16 temperate forest reserves (Flanders, northern Belgium), we simulated line intersect transects and tested threshold diameters between 10 and 130 cm to subdivide CWD to be measured with full area or line intersect sampling. The work load of the combined sampling with a threshold diameter of 20 to 40 cm was about 50 to 90% of the full area sampling work load respectively. Yet, no significant increase in the coefficient of variation (CV) of the average CWD volume was registered for threshold diameters up to 30 cm (133 %) compared to the full area sampling (125 %). The probability to relocate a 30 cm diameter CWD object after 10 years was 50 % and the probability for remeasuring increased with diameter. Using full area sampling with 10 cm threshold results in only 32 % of the objects relocated and remeasured after 10 years; using the combined sampling, only positioning logs over 30 cm increases this figure to 67 %, thus avoiding idle work. We conclude that combining full area and line intersect sampling has the advantage of lowering the work load, increasing the share of relocated objects over time, while not significantly increasing the variability in average CWD volume. An optimal threshold diameter between both methods was comprised between 20 and 40 cm but might further depend on relative importance of work load, need for relocation, CV, the study setup (e.g. number and size of plots), stand characteristics (e.g. CWD volume, dominant tree species) and decay rate. We propose to use a 30 cm threshold diameter for measuring CWD in temperate forest reserves.
•1601 Full Area Sampling forest reserve plots with simulated Line Intersect Sampling.•Threshold diameter 30 cm to split-up Line Intersect to Full Area Sampling.•Reduced work load in the field of 17–33 %.•Little effect on the variability in average Coarse Woody Debris volume.•Increased share of Coarse Woody Debris objects re-measured after 10 years.
The future biomass carbon sequestration (BCS) in forests were often predicted by the theoretical stand age (TSA, based on the aging of the stand). Due to tree regeneration and various disturbances, ...however, the real stand age (RSA, calculated by averaging the age of single individuals in the stand) is often inconsistent with TSA in a given forest, and its effect on BCS prediction was poorly understood. Here, this study analysed the variations in RSA in three forest types (i.e., coniferous, broadleaf, and mixed broadleaf forests) of two forest origins (i.e., planted and natural forests) using the National Forest Inventory dataset of China between 1999 and 2018, and evaluated their effects on BCS between 2020 and 2060 using a random forest model. The ratio of RSA to TSA differed in forest origins and age groups. For all forest types, the ratio was higher and increased with an increase of age group in planted forests, while it showed opposite trends in natural forests, indicating a high variability in stand age in natural forests. The differences in predicted biomass carbon (C) storage between RSA and TSA varied over time. The enhanced C storage from RSA in natural forests in 2060 was characterized by a trend of mixed broadleaf forests (45.61 TgC) > broadleaf forests (17.62 TgC) > coniferous forests (8.16 TgC). Moreover, the predicted BCS in all forests were higher in the RSA scenario than in the TSA scenario and showed various trends between 2020 and 2060. Especially in natural forests, broadleaf forests showed a high and stable BCS (from 15.14 TgC yr−1 to 15.44 TgC yr−1) and mixed broadleaf forests exhibited an increased BCS (from 60.18 TgC yr−1 to 63.90 TgC yr−1) during this period. Our results confirmed the widespread phenomenon of inconsistency between RSA and TSA in China’s forests and underlined their various effects on future forest BCS. More importantly, these results suggested that considering the RSA rather than the TSA is more scientific for forest C accounting.
•Inconsistency between theoretical and real stand age is common in a given forest.•Ratio of real age to theoretical age differed in forest origins and age groups.•The predicted annual biomass C sinks were higher in the real stand age scenario.•Considering real stand age is more scientific for forest C accounting.
PDF
