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The annual growth of the Finnish forests has doubled in less than a century but the reasons for the increase have been a subject of much debate. Site index aggregates the mid- to long-term impacts of variable edaphic and climatic factors on site productivity and is an important characteristic with regard to the ongoing environmental changes. We quantified changes of site index in Finland over time by applying a new approach developed in our previous study in Germany. A large data base for Norway spruce ( Picea abies (L.) Karst.), Scots pine ( Pinus sylvestris L.) and larch ( Larix spp.) was available from the network of long-term growth and yield experiments in southern and central Finland. For all tree species, site indices fluctuated over time, i.e. they slightly decreased in the 1970s, followed by an increasing trend in the 1980s and a decline again in the 1990s. Apparently, the only significant change was a change point indicated for Scots pine around the year 1944; however, indication was weak due to notable limitations of the database during the respective period. Interestingly, the result of this study in Finland differs from central Europe, where Norway spruce site productivity has displayed a considerable increase since the 1950s. Potentially, the low nitrogen deposition in Finland may be of major importance accounting for the divergent changes in site productivity between Finland and central Europe. Thus, the results indicate that a large share of the growth increase in the Finnish forests might actually be due to altered management. [ABSTRACT FROM AUTHOR]

Mangrove forests, some of the most carbon-dense ecosystems on Earth, play an important role in climate change mitigation through storing carbon in the soil. However, increasing anthropogenic pressures and sea level rise are likely to alter mangrove forest structure and functions, including the major source of carbon in mangrove ecosystems — below-ground soil carbon stocks (BSCS). Although estimating soil carbon stocks has been a popular practice in the mangroves, but poorly understood the (I) the linkage between BSCS and key ecosystem drivers (i.e., biotic, abiotic, and functional) and in (II) determining the pathways of how BSCS and multiple forest variables interact along stress gradients. This lack of understanding limits our ability to predict ecosystem carbon dynamics under future changes in climate. Here, we aimed to understand how abiotic factors (such as salinity, canopy gap fraction, nutrients, and soil pH), biotic factors (e.g., structural parameters, canopy packing, and leaf area index, LAI), and forest functional variables (e.g., growth and aboveground biomass stocks, AGB) affect BSCS (i.e., soil organic carbon, SOC, and root carbon, RC) using spatiotemporal data collected from the Sundarbans Mangrove Forest (SMF) in Bangladesh. We observed that BSCS decreased significantly with increasing salinity (e.g., from 70.6 Mg C ha−1 in the low-saline zone to 44.6 Mg C ha−1 in the high-saline zone). In contrast, the availability of several macronutrients (such as nitrogen, phosphorous, and potassium), LAI, species diversity, AGB, and growth showed a significant positive effect on SOC and RC. Stand properties, including tree height, basal area, density, canopy packing, and structural diversity, had a non-significant but positive impact on RC, while tree height and basal area significantly influenced SOC. Pathway analysis showed that salinity affects BSCS variability directly and indirectly by regulating stand structure and restricting nutrients and forest functions, although basal area, nutrients, and LAI directly enhance RC stocks. Our results indicate that an increase in nutrient content, canopy density, species diversity, and leaf area index can enhance BSCS, as they improve forest functions and contribute to a better understanding of the underlying mechanisms. [Display omitted] • Belowground carbon stocks (BSCs) have been revealed to be driven by biotic, abiotic, and functional variables. • Increasing salinity, gap fraction, and high saline zones negatively affect BSCs. • Nutrients, basal area, leaf area index, functional variables positively affect BSCs. • Structural diversity and canopy packing may indirectly benefit BSCs. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of estimating future stand development in heterogeneously structured forests in Sweden; specifically, multi-layered spruce stands and mature pine stands with advanced spruce undergrowth. We first introduce various supporting concepts and models with their empirical databases, model validation and constraints. Secondly, Swedish single-tree growth functions designed for more heterogeneously structured forest are tested using data from inventory plots, a thinning experiment in an uneven-aged forest stand, and yield plots in pristine forest. Future growth of a managed, multi-layered forest was simulated and is compared with other selected functions. Simulation results, expected errors and time constraints are discussed. For most models, projected stand basal area growth deviated 10-20% from the observed growth in individual stands. In single stands, the deviation ranged from 0 to 60%. Validation periods were often 5-15 years, sometimes even more than 30 years. For Swedish single-tree basal area growth functions, on average, a 5% overestimate was found for heterogeneously structured forest across Sweden. Observed growth in a boreal single-tree selection forest was underestimated by 12.5% fifteen years after thinning from above.

The assessment of the current annual increment of forest standing volume (CAI) is a fundamental tool to support forest management and planning. A suitable approach to such an end is to rely on growth and yield models. However, this kind of models are often not available for many countries and/or locations and/or species. Furthermore, they may become obsolete due to potential changes in the environmental and silvicultural conditions. Such shortcomings may be distinctively detrimental in the context of forest inventories. Several methods have been proposed to inventory CAI on one single occasion, i.e., when repeated measurements of standing volume are not available. A well-known family of methods, still largely exploited in Alpine and Eastern European countries, derives from the estimation of the percentage current annual increment of forest standing volume by the current annual increments of stem diameter and tree height (Δh). In this study an experimental comparison of Δh assessment by three different approaches is presented with reference to a properly designed case study: (i) Δh is measured on felled trees; (ii) Δh is estimated by dynamic height curve (i.e., diameter-height-age model); (iii) Δh is estimated by conventional height curve (i.e., diameter-height model). Under the examined experimental conditions (a pure forest of silver fir on highly fertile soils in southern Italy, aged around 60 years), both simplified approaches (ii) and (iii) have proven to underestimate height increments, with a larger underestimation by the approach based on the conventional height curve. However, the consequent error in the estimation of percentage current annual increment of forest standing volume has proved to be quite limited (4% for the approach based on the dynamic height curve and around 9% for the approach based on the conventional height curve). Hence, such simplified approaches may be rather safely considered for estimating percentage current annual increment of forest standing volume when neither Δh is directly detectable on standing trees nor sample trees can be felled, nor an appropriate model to predict Δh is available. The Δh estimation on the conventional height curve should turn out to be even more suitable in the case of uneven-aged stands, where the position of the height curve remains stationary over time.

The paper suggests and examines a simplified relative indicator of forest production, with special regard to possibilities of its use in projecting future forests. Forest yield index (IY), based on an economic parameter "value of final cutting yield" was proposed, and examined in the model territory of Kysuce in north-western Slovakia. The current values of final cutting yield, dependent on tree species, site index and the length of rotation period served as a basis for the assessment of expected yields. The possibilities and limitations of index applicability in long-term strategic forest management decision-making are discussed, considering the uncertainty of ecological and economic conditions during the long forest production cycle, as well as the complexity of tree species growth and production in the mixed forests, uneven aged forests and forests under climate change.

O objetivo deste trabalho foi estimar a produção de biomassa de eucalipto, para diferentes regiões do Brasil. Foi avaliado o efeito de características climáticas sobre a produtividade de eucalipto utilizando-se o banco de dados do Programa de Pesquisa em Solos e Nutrição de Eucalipto do Departamento de Solos - UFV. Características climáticas e idade do povoamento foram importantes para obtenção do modelo. Houve variação na produção estimada de biomassa entre regiões, sendo a maior produtividade três vezes superior à menor. A produção de biomassa foi menor nas regiões com menor disponibilidade de água. A proporção de copa em relação ao tronco reduziu com a idade da plantação, de maneira acentuada até à idade de 3,6 anos, e de maneira mais lenta a partir desta idade.The aim of this work was to model growth of eucalypt plantations in Brazil. It was intended to evaluate influence of key climatic variables on eucalypt productivity. The database employed was obtained from the Soil and Eucalypt Nutrition Program of the Soil Department of the Federal University of Viçosa. Climatic characteristics and age were a model important component. The region with the highest productivity produced three times more aboveground biomass than the poorest region. Regions with low water availability exhibited the lowest biomass production. Strong reduced in canopy proportion was observed within 3.5 years following planting. After that the canopy proportion reduced more slowly.

Estimation of stand growth is crucial for forest planning. Estimations were usually done using fixed values, and recently growth equations have been used. An alternative is through stand growth models. The objective was to develop a simple model for Nothofagus pumilio stands with full density along site quality and age gradients. The sample was obtained from 125 stands. Data on forest structure and samples for tree-ring measurement were taken in all trees to estimate growths using biometric models previously developed. The growth values of each plot during the last twenty years were calculated to fit the model, using the ratio of total volume increment/basal area as an independent variable. The developed model gives a ratio between stand volume increment and basal area (m/year) in relation to the site quality and stand age. The statistics (r2 = 0.819, mean error = 0.019, absolute mean error = 0.033), residual analysis and biological performance were satisfactory. The obtained stand growths varied between 1 and 20 m3/ha/year. This simple model allowed to estimate growth values at a stand level from easy field measurements from forest inventories.

Aim The intensity and frequency of drought have increased considerably during recent decades in some Northern Hemisphere forested areas, and future climate warming could further magnify drought stress. We quantify how forests resist drought events and recover after them, i.e. we determine their growth resilience. Location North America and Europe. Methods We use a large tree-ring database to study how drought influences forest growth resilience. We selected 775 tree-ring width chronologies and studied the occurrence of years with extremely dry conditions (low soil moisture and/or high evaporative stress; hereafter 'drought') in these forests. For each drought in each forest we calculated three indices that represent different components of growth resilience to drought: resistance ( Rt), recovery ( Rc) and resilience ( Rs). We related the variation in these indices with geographical, topographic, climatic and ecological conditions from each region. Results The three components of forest growth resilience were interrelated. Resistance and recovery were negatively related, and both were positively and nonlinearly related to resilience. Drought resistance increased with latitude, soil moisture and slope, whereas drought recovery decreased with latitude, soil moisture and summer normalized difference vegetation index. Drought resilience increased with elevation and decreased with the variation in soil moisture. Temperate broadleaf forests from wet regions showed a greater growth resistance (e.g. north-eastern USA, central Europe) while conifer forests from dry to semi-arid regions (e.g. south-western USA, southern Europe) presented a greater growth recovery. Main conclusions The geographical patterns of growth resilience indices confirm the existence of different strategies among forests to cope with droughts, depending on the biome, the tree species and the prevailing climatic conditions. Geographical patterns in soil moisture availability tend to override species-specific responses to drought. [ABSTRACT FROM AUTHOR]

This study compared the densest available database of tree-ring growth with the longest Normalized Difference Vegetation Index (NDVI) information available at the global scale to quantify the relationship between annual forest growth and the NDVI across different forest types and regions and to characterize the patterns of response of forest growth to NDVI values at different temporal scales. We found a general positive relationship between the inter-annual NDVI variability and the annual tree growth in most of the analyzed forests. Nevertheless, there were strong differences in the tree growth responses to NDVI, given that the annual tree-ring records in each forest responded in a different way to the magnitude, seasonality and accumulation period of the NDVI values. Thus, we found eight main patterns of tree-ring response to the NDVI, which were related to the forest type and climate conditions of each corresponding site. The identified patterns may be useful for determining early-warning signals of changes in forest growth over large areas based on remote sensing information. [ABSTRACT FROM AUTHOR]

Key message : When predicting forest growth at a regional or national level, uncertainty arises from the sampling and the prediction model. Using a transition-matrix model, we made predictions for the whole Catalonian forest over an 11-year interval. It turned out that the sampling was the major source of uncertainty and accounted for at least 60 % of the total uncertainty. Context: With the development of new policies to mitigate global warming and to protect biodiversity, there is a growing interest in large-scale forest growth models. Their predictions are affected by many sources of uncertainty such as the sampling error, errors in the estimates of the model parameters, and residual errors. Quantifying the total uncertainty of those predictions helps to evaluate the risk of making a wrong decision. Aims: In this paper, we quantified the contribution of the sampling error and the model-related errors to the total uncertainty of predictions from a large-scale growth model in Catalonia. Methods: The model was based on a transition-matrix approach and predicted tree frequencies by species group and 5-cm diameter class over an 11-year time step. Using Monte Carlo techniques, we propagated the sampling error and the model-related errors to quantify their contribution to the total uncertainty. Results: The sampling variance accounted for at least 60 % of the total variance in smaller diameter classes, with this percentage increasing up to 90 % in larger diameter classes. Conclusion: Among the few possible options to reduce sampling uncertainty, we suggest improving the variance-covariance estimator of the predictions in order to better account for the multivariate framework and the changing plot size. [ABSTRACT FROM AUTHOR]

Modelling studies have suggested that atmospheric nitrogen (N) deposition will increase forest carbon sequestration by stimulating tree growth. However, few long-term experiments studying N deposition effects on tree growth in boreal forests have been reported. This study empirically explores the relation between application rates of N, simulating levels of N deposition relevant for Europe, and the growth of Picea abies (L.) Karst. and Pinus sylvestris L. in a low N deposition area (<2 kg N·ha−1·year−1), we manually added 0, 12.5, and 50 kg N·ha−1·year−1 to a forest site dominated by P. abies for 19 years and 0, 3, 6, 12.5, and 50 kg N·ha−1·year−1 to a forest site dominated by P. sylvestris for 10 years. On both sites, linear regression analyses displayed significant relations between mean annual tree growth and N additions: P. abies relative growth rate increased by 1.2% per kg N added and that of P. sylvestris increased by 1.6% per kg N added. The growth response, however, varied over time, highlighting the necessity for long-term experiments to apprehend effects of eutrophication on forests. Generally, our study confirms the results of previous modelling studies assessing forest growth responses to N deposition over Europe. [ABSTRACT FROM AUTHOR]

The use of forest biomass for energy production requires a careful attention to the sustainable silvicultural practices. This is a complex task because of the different environmental and economic issues to be taken into account. To this aim, suitable tools must be used as regards the representation of the dynamics of forest biomass and the economic assessment. In this paper, a user-friendly optimization-based decision support system (DSS) that can help decision makers in the optimal management of forest biomass use for energy production is presented. Attention is focused on the forest system in order to take into account sustainable silvicultural practices and on the minimization of costs for the collection plans over years. Specifically, a non linear optimization model (that includes forest growth models) is formalized, aiming at determining, over a certain period, the optimal exploitation policy of forest biomass through a single plant whose location and size are assumed known, in order to minimize costs and to respect silvicultural constraints. The decision model is solved through a receding horizon approach and is applied to the case study of Val Bormida (Savona Province, Italy). Different tests and sensitivity analysis have been performed to validate the model and the approach. From an application point of view, observing the obtained results, it is evident that results are strongly influenced by the old average age of the vegetation in the specific case study. However, depending on the species, different trends for the results of annual mean increment and harvesting plans are observed. [ABSTRACT FROM AUTHOR]

Concerns about the sustainability of tropical forestry motivated this study on post-logging timber and carbon dynamics over a 20-year period in Paragominas, Pará, Brazil. Previously unlogged forest was subjected to conventional logging (CL), reduced-impact logging (RIL), or was set aside as an unlogged control. All trees ⩾25 cm DBH and all trees of commercial species ⩾10 cm DBH were monitored in a 24.5 ha plot in each treatment, with a 5.25 ha subplot in each for monitoring all trees ⩾10 cm DBH. Above-ground biomass and bole volumes of merchantable species were tracked based on 10 inventories made between 1993 and 2014. Pre-logging biomass and bole volumes of commercial species were estimated as 237, 231, and 211 Mg ha −1 , and 78, 80, and 70 m 3 ha −1 , in the RIL, CL, and unlogged plots, respectively. One year after logging, biomass was reduced 14% by RIL and 24% by CL with corresponding merchantable species volume reductions of 21% and 31%. By 2014, biomass and bole volumes of commercial species had recovered 95% and 98% of their pre-logging stocks in the RIL plot but only 76% and 72% in the CL plot, respectively; timber volumes from large trees (⩾50 cm DBH) were only recovered to 81% in the RIL plot and to 53% in the CL plot. Over the first twenty years after logging, average volume increments from commercial species were substantially higher in the RIL plot (0.72 m 3 ha −1 year −1 ) than in the CL plot (0.08 m 3 ha −1 year −1 ). Recovery of both biomass and timber volumes were temporarily reversed between 2009 and 2014 due to a 4-fold increase in annual mortality rates in the RIL plot and a 5.5-fold increase in the CL plot (as well as a 3-fold increase in the control plot), all presumably related to the extreme drought of 2010. Our findings support the claim that use of RIL techniques accelerates rates of biomass and timber stock recovery after selective logging. [ABSTRACT FROM AUTHOR]

In this paper we consider a one dimensional mathematical model for a mono-species forest growth in an infinite domain. Following [15] we assume that the system can be described by the evolution of the young and old tree density and by the seed concentration. The mathematical formulation consists in a system of ODE's which we study analytically proving global existence and uniqueness. We discuss in some detail the stationary solutions and we perform some numerical simulations to illustrate the behavior of the solution. [ABSTRACT FROM AUTHOR]

Estimating the change in the magnitude and distribution of forest biomass is important for monitoring carbon dynamics and understanding the implications on the terrestrial carbon cycle. In this study, we assessed the capacity of multi-temporal airborne Light Detection and Ranging (LiDAR) data to estimate forest biomass dynamics at a mixed subtropical forest of southeast China, and analyzed the magnitude and spatial patterns of the above ground biomass (AGB) change over a 6-year period. To do so, we evaluated different approaches to estimate change in AGB, specifically direct (i.e., predicting biomass change using the differences in LiDAR metrics) and indirect (i.e., modeling biomass for each point in time and predicting the change as their differences) approaches. Once models were developed, the change in AGB was mapped across the study site and examined in relation to forest type and age. Our results demonstrated that the direct approach (CV- R 2 = 0.63, CV-rRMSE = 25.64%) produced more accurate estimates in change of AGB than the indirect approach (CV- R 2 = 0.59, CV-rRMSE = 28.35%). Canopy height metrics of delta mean height (∆ h mean ) and a number of upper percentile heights (i.e., ∆ h 75 and ∆ h 95 ) , calculated from the LiDAR first returns, were found to be most sensitive to changes in biomass, whereas metrics based on maximum canopy height or canopy density had less predictive power. Furthermore, differences in point cloud densities did not significantly impact the estimations of AGB and change of AGB at the plot-scale (30 × 30 m). Spatial extrapolation of the AGB change indicated that, in general, most of the forest area had an overall gain in biomass. The middle-aged stands (typically dominated by Quercus acutissima between 41 and 60 years old) show marked growth of biomass (median ∆ AGB = 2.29 Mg ha − 1 year − 1 ), followed by mature (typically dominated by Pinus massoniana between 31 and 60 years old) (median ∆ AGB = 1.72 Mg ha − 1 year − 1 ) and young stands (typically consisting of regenerated broadleaved trees younger than 40 years old) (median ∆ AGB = 1.48 Mg ha − 1 year − 1 ), whereas over-mature stands (typically dominated by Cunninghamia lanceolata older than 35 years) show the lowest growth (median ∆ AGB = 0.76 Mg ha − 1 year − 1 ). This study demonstrates benefits of using multi-temporal LiDAR data to help identify specific areas for management interventions, to enhance forest productivity, maintain biomass stocks and optimize carbon sequestration. [ABSTRACT FROM AUTHOR]

Because water availability is a primary factor that influences growth of forest plantations, quantifying plantation water use is an important part of the decision-making process when selecting new plantation areas. The 3-PG model (Landsberg and Waring, Forest Ecology and Management 95: 209-228, 1997) has been used successfully to model forest growth for several species. However, some studies have demonstrated limitations in 3-PG's ability to accurately model the soil and plant water balance. This paper addresses these limitations through the development and validation of a modified water balance submodel that models canopy interception, soil evaporation, tree transpiration, drainage, run-off, soil water content and available soil water in the root and non-root zone. The new submodel was tested and validated using detailed, long-term observed growth and water balance data from contrasting environments in Australia and Brazil and showed improved estimation of available soil water, even when only monthly weather data were available. However, the new submodel requires more soil texture-dependent parameters than the original submodel. Sensitivity analysis of these new parameters shows that values of soil field capacity, wilting point and soil depth may have strong impacts on the prediction of run-off, soil water content and available soil water. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Describing and understanding growth patterns in tropical forests is crucial to assessing their role in carbon balance. Growth and vital rates of a protected gallery forest in central Brazil were estimated, based on six measurement intervals between 1985 and 2009. The sample consisted of all stems ≥ 10 cm diameter at breast height measured in 151 permanent plots (10 × 20 m), distributed in 10 transects perpendicular to the watercourse and 100 m apart from each other. Statistical significance of changes in density, basal area, growth and vital rates were tested using Wilcoxon signed-rank tests. Vital rates oscillated during the study period. Growth, recruitment and turnover rates fluctuated, but had a net decrease over the whole study period, whereas mortality seemed to be affected by a high disturbance event during the 1994–1999 period. The oscillatory behaviour of growth suggests that the forest is pulsating around a stable state (dynamic equilibrium). Nonetheless, persistence of decelerating growth trends may force the site's carrying capacity to a lower density or biomass state. [ABSTRACT FROM PUBLISHER]

Forest management and climate change, directly or indirectly, affect drinking water resources, both in terms of quality and quantity. In this study in the Northern Limestone Alps in Austria we have chosen model calculations (LandscapeDNDC) in order to resolve the complex long-term interactions of management and climate change and their effect on nitrogen dynamics, and the consequences for nitrate leaching from forest soils into the karst groundwater. Our study highlights the dominant role of forest management in controlling nitrate leaching. Both clear-cut and shelterwood-cut disrupt the nitrogen cycle to an extent that causes peak concentrations and high fluxes into the seepage water. While this effect is well known, our modelling approach has revealed additional positive as well as negative impacts of the expected climatic changes on nitrate leaching. First, we show that peak nitrate concentrations during post-cutting periods were elevated under all climate scenarios. The maximal effects of climatic changes on nitrate concentration peaks were 20–24 mg L −1 in 2090 with shelterwood or clear-cut management. Second, climate change significantly decreased the cumulative nitrate losses over full forest rotation periods (by 10–20%). The stronger the expected temperature increase and precipitation decrease (in summer), the lesser were the observed nitrate losses. However, mean annual seepage water nitrate concentrations and cumulative nitrate leaching were higher under continuous forest cover management than with shelterwood-cut and clear-cut systems. Watershed management can thus be adapted to climate change by either reducing peak concentrations or long-term loads of nitrate in the karst groundwater. [ABSTRACT FROM AUTHOR]

Norway spruce ( Picea abies (L.) Karst.) stands in certain areas of Central Europe have experienced substantial dieback since the 1970s. Understanding the reasons for this decline and reexamining the response of forests to acid deposition reduction remains challenging because of a lack of long and well-replicated tree-ring width chronologies. Here, spruce from a subalpine area heavily affected by acid deposition (from both sulfur and nitrogen compounds) is evaluated. Tree-ring width measurements from 98 trees between 1000 and 1350 m above sea level (a.s.l.) reflected significant May–July temperature signals. Since the 1970s, acid deposition has reduced the growth–climate relationship. Efficient pollution control together with a warmer but not drier climate most likely caused the increased growth of spruce stands in this region, the so-called “Black Triangle,” in the 1990s. [ABSTRACT FROM AUTHOR]

The impact of heavy storm events, changed climate and treatment on the productivity of temperate forests was investigated for three representative stands in Southwest Germany. The simulation experiment was conducted on a Norway spruce, a mixed and a Douglas-fir stand. We applied a business-as-usual scheme (BAU), further a storm adapted management (SAM) and an early reduction in the tree density (BFB6). Further, we investigated the effects of two different climates, a current and a climate change scenario based on the A1B emissions with a HeadCM3 model chain. Simulations were run by the core functions of a single-tree growth simulator, with an empirical storm risk model, enabling to predict single-tree probabilities of being damaged. Further growing conditions were changed by modelling site index as a function of climate. The simulations were run over a period from 2010 to 2500, and we investigated standing and harvested volume and net present value (NPV). Results show that storm frequency has a major impact on all output variables, followed by treatment. For the Douglas-fir stand, treatment is even more important for mean harvested volume, while it does not play a major role in the mixed stand. Compared with storm frequency and treatment, change in precipitation and temperature is less influential. There is a clear negative climate change effect on harvest levels for the spruce and mixed stand, while Douglas fir shows a distinct positive reaction. BFB6 shows the highest harvested and standing volume for both coniferous stands, but lower NPVs due to cutting of premature timber. BAU displays the best performance for NPV, while SAM yields the worst results for harvested and mean standing timber as well as for NPV. Assumptions and limitations of the study are discussed mainly referring to the long simulation period, and it is concluded that before implementing extreme strategies-like SAM-with effects similar to those of the disturbances, a forward-looking adaptive management should be considered. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the ability of estimating change in total aboveground biomass (AGB) in young forests using multi-temporal airborne laser scanner data. A field data-set covering 11 growth seasons of 39 circular plots of size 200 m2from young forest in south-eastern Norway was used in the analyses. Different approaches for prediction of the AGB change were tested. One approach was based on modeling AGB for each point in time and predicting change as the difference between separate AGB predictions. We also tested two approaches based on modeling and predicting change directly, and two approaches where growth/reduction rates were modeled and used in prediction. The approach where change was predicted as a difference between biomass predictions seemed to yield the best results (root mean square error [RMSE] 14.8%). The other approaches yielded results that were similar in terms of RMSE, except for the approach where AGB change was predicted using a growth rate. The results indicate that prediction of change as a difference between AGB predictions works satisfactory for a wide range of forest conditions, but that the direct approaches can perform better in some cases. [ABSTRACT FROM PUBLISHER]

The purpose of this study was to develop, test and evaluate a software prototype capable of modeling forest growth in consideration of winter storm disturbance and to simulate storm damage in forests under different forest management regimes. The results of a test application showed that simulated storm damage was more strongly influenced by the input data (e.g. tree species and tree height) than by the different forest management regimes. However, early, intense thinnings as well as reducing target diameters by 10% led to reduced storm damage, with decreases as large as 50% of the damage in certain forest stands. The coupled modeling framework was able to simulate interactions between forest growth, storm damage and forest management regimes. Further testing of the prototype appears necessary to investigate a wider range of tree species, soil and site conditions. Also, the use of computational system resources needs improvement. [ABSTRACT FROM AUTHOR]

The growth enhancing effects of forest fertilizer is considered to level off within 10 years of the application, and be restricted to one forest stand rotation. However, fertilizer induced changes in plant community composition has been shown to occur in the following stand rotation. To clarify whether effects of forest fertilization have residual long-term effects, extending into the next rotation, we compared tree growth, needle N concentrations and the availability of mobile soil N in young (10 years) Pinus sylvestris L. and Picea abies (L.) H. Karst. stands. The sites were fertilized with 150 kg.N.ha-1 once or twice during the previous stand rotation, or unfertilized. Two fertilization events increased tree height by 24% compared to the controls. Needle N concentrations of the trees on previously fertilized sites were 15% higher than those of the controls. Soil N mineralization rates and the amounts of mobile soil NH4-N and NO3-N were higher on sites that were fertilized twice than on control sites. Our study demonstrates that operational forest fertilization can cause residual long-term effects on stand N dynamics, with subsequent effects on tree growth that may be more long-lasting than previously believed, i.e., extending beyond one stand rotation. [ABSTRACT FROM AUTHOR]

The application of terrestrial laser scanning (TLS) in capturing forest inventory parameters such as diameter at breast height, height and diameters along stem profiles, and in monitoring forest growth, was investigated and validated by comparison with conventionally measured individual tree parameters and plot-level forest growth in a stand of Sitka spruce ( Picea sitchensis (Bong.) Carr.) in Ireland. The data acquisition for all the plots with different tree sizes and different slopes was carried out using a terrestrial laser scanner (FARO LS 800 HE80) in November 2007 and November 2009, using the same plot centres and measurement procedures. The point cloud data were processed with Autostem™ software. The results showed that TLS enables the acquisition of forest stand parameters with an acceptable accuracy. Pruning of the lower branches did not improve tree recognition and the number of (partly) occluded trees stayed the same. Over the 2-year period, the average difference between the volume increment of the trees visible to the scanner derived using the conventional method and Autostem™ was 4.77 mha and resulted in scanner-derived estimates that were lower than the estimates obtained by conventional method by 6.1 %. Using a simple correction factor to account for occlusion in the laser scanner data, the difference between these estimates for all trees in the stand became an over-estimation by 6.96 mha (8.1 %). At heights up along the stems >15 m, the errors in stem diameter estimates started to escalate. [ABSTRACT FROM AUTHOR]

Spatial variability in the topoclimate-driven linkage between forest phenology and tree growth in complex terrain is poorly understood, limiting our understanding of how ecosystems function as a whole. To characterize the influence of topoclimate on phenology and growth, we determined the start, end, and length of the growing season (GS _start , GS _end , and GSL, respectively) using the correlation between transpiration and evaporative demand, measured with sapflow. We then compared these metrics with stem relative basal area increment (relative BAI) at seven sites among elevation and aspects in a Colorado montane forest. As elevation increased, we found shorter GSL (−50 d km ^−1 ) due to later GS _start (40 d km ^−1 ) and earlier GS _end (−10 d km ^−1 ). North-facing sites had a 21 d shorter GSL than south-facing sites at similar elevations (i.e. equal to 200 m elevation difference on a given aspect). Growing season length was positively correlated with relative BAI, explaining 83% of the variance. This study shows that topography exerts strong environmental controls on GSL and thus forest growth. Given the climate-related dependencies of these controls, the results presented here have important implications for ecosystem responses to changes in climate and highlight the need for improved phenology representation in complex terrain.