Forest Site Productivity Research Articles

A growth-effective age-based periodic site-index for the estimation of dynamic forest site productivity under environmental changes

Key messageA novel periodic site index is introduced for the quantification of dynamic forest site productivity. The measure is age-independent, sensitive to environmental changes and efficient for the estimation and prediction of stand height and stand volume increment.ContextAccurate and up-to-date prediction of site productivity is crucial for the sustainable management of forest ecosystems, especially under environmental changes.AimsThe aim of this study was to introduce a novel concept: a periodic site index based on growth-effective age for the quantification of dynamic forest site productivity.MethodsThe growth-effective age based periodic site index is estimated from repeated or multi-temporal measurements of stand dominant height. Furthermore, a recursive procedure to update the underlying site index model is presented by using repeated measurements of stand dominant height. The database used in this study comprised repeated measurements of 945 Norway spruce (Picea abies L.) experimental plots at 508 different locations in Southwest Germany.ResultsThe evaluation shows that periodic site index is statistically superior to the conventional site index, based on chronological stand age, for estimating stand height and stand volume increment. The analysis of temporal differences between growth-effective stand age and chronological stand age and between periodic site index and conventional site index in the period 1900 to 2020 reveals trends referring to stand age and site productivity, which corroborate earlier regional studies on forest growth trends due to environmental changes.ConclusionsThe periodic site index is a better indicator for site productivity than conventional site index. Under conditions of environmental changes, conventional site index is biased, whereas the growth-effective age based site index provides an unbiased estimate of stand height development. With the more widespread application of remote sensing techniques, such as airborne laser scanning, the availability of multi-temporal stand height data will increase in the near future. The novel concept provides an adaptive modeling approach perfectly suited to these data for an improved estimation and prediction of forest site productivity under environmental changes and can straightforwardly be applied also to uneven-aged and multi-species stands.

Modelling Climate Effects on Site Productivity and Developing Site Index Conversion Equations for Jack Pine and Trembling Aspen Mixed Stands

Forest site productivity estimates are crucial for making informed forest resource management decisions. These estimates are valuable both for the tree species currently growing in the stands and for those being considered for future stands. Current models are generally designed for pure stands and do not account for the influence of climate on tree growth. Consequently, site index (SI) conversion equations were developed specifically for jack pine (Pinus banksiana Lamb.) and trembling aspen (Populus tremuloides Michx.) trees grown in naturally originated mixed stands. This work involved sampling 186 trees (93 of each species) from 31 even-aged mixed stands (3 trees per species per site) across Ontario, Canada. Stem analysis data from these trees were utilized to develop stand height growth models by incorporating climate variables for each species. The models were developed using a mixed effects modelling approach. The SI of one species was correlated with that of the other species and climate variables to establish SI conversion equations. The effect of climate on site productivity was evaluated by projecting stand heights at four geographic locations (east, center, west, and far west) in Ontario from 2022 to 2100 using the derived stand height growth models. Height projections were made under three emissions scenarios reflecting varying levels of radiative forcing by the end of the century (2.6, 4.5, and 8.5 watts m−2). Climate effects were observed to vary across different regions, with the least and most pronounced effects noted in the central and far western areas, respectively, for jack pine, while effects were relatively similar across all locations for trembling aspen. Stand heights and SIs of jack pine and trembling aspen trees grown in naturally originated mixed stands can be estimated using the height growth models developed here. Similarly, SI conversion equations enable the estimation of the SI for one species based on the SI of another species and environmental variables.

Modeling dominant height growth of teak plantations in the Caribbean region of Colombia

Identifying sites with adequate biological productivity is a critical factor in ensuring timber production and the profitability of forest-based investments. The productivity of forest sites is influenced by climatic, edaphic and topographic variables, as well as by silvicultural practices. Site index is a phytocentric method widely used to assess site productivity and its estimation is based on dominant height growth modeling. Teak is the fifth most planted forest species in Colombia, and its importance is associated with high economic returns and profitability. This study aims to model dominant height growth using the generalized algebraic difference approach for teak plantations established in the Caribbean region of Colombia. The Lundqvist-Korf model, in which the correlation of the residuals was handled with a continuous autoregressive specification of the first order, resulted in a satisfactory statistical estimation of the dominant height growth. The results indicate that in the Caribbean region of Colombia, productive sites for the establishment of teak plantations can be found as productive as in some tropical American countries and better than some sites in Asian countries. This suggests a potential for the expansion of teak plantations and forest-based investments in Colombia.

Assessing Soil Prediction Distributions for Forest Management Using Digital Soil Mapping

Texture, soil organic matter (SOM), and soil depth (SoD) are crucial properties in forest management because they can supply spatial information on forest site productivity and guide fertilizer applications. However, soil properties possess an inherent uncertainty that must be mapped to enhance decision making in management applications. Most digital soil mapping predictions primarily concentrate on the mean of the distribution, often neglecting the estimation of local uncertainty in soil properties. Additionally, there is a noticeable scarcity of practical soil examples to demonstrate the prediction uncertainty for the benefit of forest managers. In this study, following a digital soil mapping (DSM) approach, a Quantile Regression Forest (QRF) model was developed to generate high-resolution maps and their uncertainty regarding the texture, SoD, and SOM, which were expressed as standard deviation (Sd) values. The results showed that the SOM (R2 = 0.61, RMSE = 2.03% and with an average Sd = 50%), SoD (R2 = 0.74 and RMSE = 19.4 cm), clay (R2 = 0.63, RMSE = 10.5% and average Sd = 29%), silt (R2 = 0.59, RMSE = 6.26% and average Sd = 33%), and sand content (R2 = 0.55, RMSE = 9.49% and average Sd = 35%) were accurately estimated for forest plantations in central south Chile. A practical demonstration of precision fertilizer application, utilizing the predictive distribution of SOM, effectively showcased how uncertainty in soil attributes can be leveraged to benefit forest managers. This approach holds potential for optimizing resource allocation and maximizing economic benefits.

Dynamic height growth models for highly productive pedunculate oak (Quercus robur L.) stands: explicit mapping of site index classification in Serbia

Key messageWe applied the generalized algebraic difference approach (GADA) to develop dynamic models of height growth for pedunculate oak (Quercus robur L.) in Serbia. According to the dominant heights, the studied region comprises some of Europe’s most productive sites for pedunculate oak. Therein, we have generated a map showing the current site index class of stands. Such a map could be used to enhance forest management and evaluate climate change impacts.ContextAlthough sustainable forest management requires reliable prediction of forest site productivity, such indicators are currently unavailable for pedunculate oak sites in Serbia. The site index (SI) curves represent the most commonly used indirect scale for site productivity classification. The dynamic equations derived by the Generalized Algebraic Difference Approach (GADA) are the state-of-the-art approach in growth modeling, but they have not been widely applied for studying the height dynamics of pedunculate oak.AimsThe main objectives of this study were to develop the first dynamic site index curves for pedunculate oak in Serbia and subsequently to provide stand-level maps with predicted site indices.MethodsWe have tested five flexible polymorphic equations with variable asymptotes derived by the GADA approach. Models were calibrated using artificially established growth trajectories obtained from 3636 detailed temporary sample plots. The selection of the most suitable model was accomplished according to (1) quantitative measures of goodness of fit, (2) the analysis of residual scattering, and (3) the biological plausibility of obtained height growth curves.ResultsAfter correcting the error terms with a continuous first-order autoregressive structure and conducting a three-stage performance analysis, the GADA dynamic site index model derived from the Hossfeld base equation shows the best overall properties. Insight into the oscillations of relative error suggested that 100 years is the most suitable age for site index referencing. Comparison with existing height growth models revealed greater flexibility and a considerably better representation of the height growth dynamic of pedunculate oak in the studied region. Additionally, we have produced a spatially explicit map showing the expected SI100 for 1907 stands with pedunculate oak within 22 management units.ConclusionDynamic SI-curves based on GADA will serve forest practitioners to update management plans and serve as a reference point for benchmarking the impact of climate change and for developing adaptation strategies. The utilized approach allowed unbiased estimation of SI100 across all age classes so that the results could be mapped at a broader scale. This study provides the second known application of the dynamic model for pedunculate oak in Europe but the first that includes some of the most productive sites in the species distribution range.

Profit efficiency in the provision of ecosystem services in the Cross Timbers forests

We focused on modeling the profitability of the Cross Timbers (CT) forests with regards to the provision of ecosystem services, including timber production, carbon sequestration, and water yield. The Cross Timbers region spans from southern Kansas to central Oklahoma into Texas, encompassing marginally productive timberlands. We utilized a translog stochastic profit frontier approach to analyze forest plot data collected from the Forest Inventory Analysis program between 2008 and 2019. Our results indicated that, on average, the CT forests yield around 85% of the maximum profit. Only 12% of the forest plots generated positive revenues, and the average profit across all forest plots was -$484.51 ha−1. This means that even with a 15% reduction in profit losses, the majority of the forest plots in the CT region would still not be economically viable. Forest age, ownership, forest species, and site productivity were statistically significant impacts on profit efficiency. At the margin, we found that profit inefficiency increased under private ownership and with higher levels of site productivity. Furthermore, as forests age, profit efficiency was also reduced. These findings highlight the complexity and variability of forest management systems and underscore the need for further research to fully understand the factors influencing efficiency in different contexts.

Forest stand-by-environment interaction invalidates the use of space-for-time substitution for site index modeling under climate change

Quantification and prediction of forest site productivity potential under climate changes are core issues of growth and yield modelling and crucial for the effective management of forest stands. Climatic factors typically enter these models as long-term baseline data of mean air temperature and sum of precipitation. Such models frequently are parameterized using spatially distributed data, an approach that can be considered as indirect space-for-time substitution (SFTS), which is based on the assumption that the growth response across spatial environmental gradients is equivalent to the dynamic growth response in time when site factors shift in situ due to environmental changes over time. In site index modelling this assumption has never been thoroughly tested. We applied procedures to test the validity of the SFTS approach using altitudinal transect analysis of data from long-term experimental plots with Norway spruce (Picea abies) in southwest Germany. The following procedures were applied 1. Partitioning of spatial and temporal variance components of site index and air temperature; 2. Test of the equivalence of spatial and temporal variation in models predicting site index from air temperature; 3. Bias analysis of the SFTS- and the altitudinal range-specific individual models. The results show that the response of site index to changes in growing season air temperature as estimated by the SFTS-based approach is significantly different from the observed temporal dynamics within the plots. The estimated sensitivity of site index to changes in growing season air temperature is significantly larger in the SFTS-model. Bias trends increase with increasing air temperature in all altitudinal ranges. We found significant effects of stand-by-environment interaction on site index responses to changing growing season air temperature. Possible reasons for the found differences are discussed. Furthermore, based on an independent data set from the German National Forestry Inventory (NFI), a SFTS-based climate-sensitive site index model was compared to a state-space modelling approach (SSM) which considers the dynamics of environmental changes over time. The results show that the SSM is statistically superior to the SFTS approach, corroborating the findings of the altitudinal transect analysis. Finally, future site index dynamics of Norway spruce were simulated on the basis of climate change scenarios using the SSM approach. We recommend for all climate sensitive forest growth and yield models based on spatially and temporally distributed data to properly account for within- and between-group effects to avoid erroneous model predictions under climate change.

Modeling Climate Effects on Site Productivity of Plantation Grown Jack Pine, Black Spruce, Red Pine, and White Spruce Using Annual/Seasonal Climate Values

Site index (SI) is a commonly used measure of forest site productivity and is affected by climate change. Therefore, climate effects on site productivity were analyzed and modeled for jack pine (Pinus banksiana Lamb.), black spruce (Picea mariana (Mill.) B.S.P.), red pine (Pinus resinosa Ait.), and white spruce (Picea glauca (Moench) Voss) plantations using annual/seasonal values of climate variables. Jack pine and black spruce trees were each sampled from 25 plantations (sites), and red pine and white spruce trees were sampled from 30 and 31 plantations, respectively, from across Ontario, Canada. Stem analysis data collected from 201 jack pine, 211 black spruce, 90 red pine, and 93 white spruce trees were used in this study. To analyze and model climatic effects on site productivity, parameters of the stand height models were expressed in terms of climate variables. A nonlinear mixed-effects modelling approach was applied to fit the stand height models. Climate effects on site productivity was evaluated by predicting stand heights in three areas (the central, eastern/southeastern, and western parts of Ontario) for the period 2021 to 2080 under three emissions trajectories (representative concentration pathways (RCP) 2.6, 4.5, and 8.5 watts m−2). Climate effects on site productivity depended on tree species and location. For jack pine, climate effects were positive and pronounced only in western Ontario under all emissions scenarios. The effects were negative and mild after breast height age (BHA) 50 in central Ontario for black spruce. Similarly, the effects were negative and more pronounced at all areas after BHA 35 for red pine. On the other hand, for white spruce the effects were negative and highly pronounced from a young age under all scenarios, mainly in the southeast. For all species except for jack pine, climate effects were more pronounced under RCP 8.5 than the other two scenarios.

Eucalyptus Growth Responses to Soil Water Storage Capacity in Arenosols and Acrisols Soils: Wood and Biomass Stock Modelling

Eucalyptus is the main fast-growing tree for biomass production in the tropics, providing resources for pulp and paper industries and bioenergy. The potential productivity of forest sites over an eight-year rotation in Brazil was evaluated by the Physiological Principles in Predicting Growth (3-PG) model for two soils, Acrisols and Arenosols, with high and low water storage, respectively, and distinct productive potential capacity. The model was parameterized by data-sets obtained in bimonthly forest inventories performed in stands with 33, 58 and 89 months-old trees, and edaphic surveys. The average volumetric productivity of wood and biomass of the main stem determined at the 89 months-old stand was 374 m3 ha−1 (177 Mg ha−1) for Acrisols and 272.3 m3 ha−1 (130.0 Mg ha−1) for Arenosols. The estimated volumetric production in the Arenosols had a high mean annual increment up to the age of 58 months, with a significant reduction in growth rates after this time. In Acrisols, high incremental rates in wood volume up to age of 89 months (MAIVW > 50 m3 ha−1 year−1) indicate that, under ideal soil conditions, the cutting cycle may exceed 8 years with no productivity impairment. The parameterized model matched well for forest yield (r2 > 0.9) and dendrometric variables (r2 > 0.78). The expected results of lower productivity in Arenosols occurred only after 58 months, while for Acrisols productivity remained high up to 89 months. The results showed the eucalyptus cycle should be shorter in Arenosols, since the lower cutting cycle can provide higher final productivity, when using the mean annual increment to evaluate productivity.

Tracking Individual Scots Pine (Pinus sylvestris L.) Height Growth Using Multi-Temporal ALS Data from North-Eastern Poland

In this study, we analyzed the change in tree height of 2594 Scots pine (Pinus sylvestris L.) trees with respect to the distribution among different forest sites: HCfs—hydrogenic coniferous forest site; MCfs—mineral coniferous forest site; MMfs—mineral mixed forest site. We obtained tree height information from three independent airborne laser scanning (ALS) point clouds acquired in north-eastern Poland over a 5-year interval in 2007, 2012, and 2017 using verified tree crown segments. We performed a comparative analysis of digital terrain models (DTMs) calculated from analyzed point clouds, indicating that the highest elevation differences were observed in the case of data from 2007. The analyses showed that tree growth varies significantly depending on the forest site productivity and the stage of tree development, which was described as initial tree height instead of age—commonly used in such studies. In conclusion, it is possible to indicate the significant information potential of using multitemporal ALS data to track individual tree height changes. These field data, combined with meteorological data, can be successfully used to predict changes in the abundance of stands depending on the forest site productivity. We have built Scots pine growth models for each forest site, which indicates that it is possible to predict the change in the tree stand height.

Climatic and Topographic Variables Improve Estimation Accuracy of Patula Pine Forest Site Productivity in Southern Mexico

Sustainable forest management requires accurate biometric tools to estimate forest site quality. This is particularly relevant for prescribing adequate silvicultural treatments of forest management planning. The aim of this research was to incorporate topographic and climatic variables into dominant height growth models of patula pine stands to improve the estimation of forest stand productivity. Three generalized algebraic difference approach (GADA) models were fit to a dataset from 66 permanent sampling plots, with six re-measurements and 77 temporary inventory sampling plots established on forest stands of patula pine. The nested iterative approach was used to fit the GADA models, and goodness-of-fit statistics such as the root mean square error, Akaike’s Information Criterion, and Bias were used to assess their performance. A Hossfeld IV GADA equation type that includes altitude, slope percentage, mean annual precipitation, and mean annual minimum temperature produced the best fit and estimation. Forest site productivity was negatively affected by altitude, while increasing the mean annual minimum temperature suggested the fastest-growing rates for dominant tree height.

Stem volume by height classes of immature, mature and overmature stands of the main forest-forming species of Ukraine

Generally, it is impossible to measure diameters and heights of all trees in a forest stand. Therefore, models of relationships between heights (h) and diameters (d) of trees are commonly used in practice for stem volume estimation. This study aimed at developing models of tree height-diameter (h-d) relationships as well as corresponding models of the tree stem volume for immature, mature and overmature stands of the main forest-forming species of Ukraine. This paper is a aggregation of long-term studies of the stem volume, which are based on the results of measuring about 10 thousand sample trees. Modelling of the tree height-diameter relationships was performed using relative height values. The methodology used in this study allowed generalising the measurements of sample trees collected in stands of various forest site types, productivity levels, and age categories. The average height of trees with a diameter of 24 cm was taken as the reference during modelling relative heights, while the diameter of 40 cm was chosen as the reference for overmature Scots pine stands. As a result, the parameters of a unified mathematical model of relative heights for immature, mature, and overmature stands of the main forest-forming tree species of Ukraine were established. Based on these models, height-diameter relationships in forest stands of different height classes were predicted. The authors demonstrated that the developed mathematical models substantially simplify the methodology of field work during timber surveys. The paper also presents models of the tree stem volume. These models predict the stem volume outside the bark based on diameters and heights of trees or using the developed models of h-d relationships. In this study, a unified system of mathematical models of stem volume by height classes were created for immature, mature, and overmature stands of the main forest-forming species of Ukraine. The results of the study are introduced to the National Forest Inventory of Ukraine for growing stock volume calculation at sample plot level using measurements of individual trees. The developed models can be used both by operation forestry (estimation of the timber volume during harvesting), and forest management (forecasting the future structure of forests and estimating the growing stock volume), as well as in the forest ecology

Общеевропейские подходы к классификации местообитаний, растительности и типов леса

The article describes the approaches and features of classification of forests, habitats and vegetation at the Pan-European level on the example of the classification of European forest types (EFT), the EUNIS habitat classification and the Europe vegetation classification created by the phytosociologists of the European Vegetation Survey (EVS). The forest type in the EFT classification is a large forest vegetation unit distinguished within biogeographic regions by the similarity of forest site conditions, structure and productivity of the plantation, and the degree of anthropogenic transformation of forests. Accounting for the successional dynamics of forest biogeocoenosis is worked out at the theoretical level, in practice, the accounting is possible due to the information obtained from the EUNIS habitat classification, which is linked to the EVS classification by cross-references. The EUNIS classification is a Pan-European reference set of habitat units. It was created using the results of previous large-scale studies in Europe, which resulted in the creation of a number of classifications of biotopes, soil cover and marine habitats. The EVS classification is a comprehensive hierarchical syntaxonomic system of unions, orders and classes of Brown-Blanquet syntaxonomy for vascular plants, mosses, lichens and algae native to Europe. The great advantage of the EFT classification is the inclusion of anthropogenic impacts among the key diagnostic features of a forest type, which are defined by assessing the degree of naturalness of forests, the number of forest species, the type and intensity of anthropogenic impacts. The strength of the EFT classification is to establish cross-links with other forest type classification systems used both within national forest inventory systems and at the EU level. The use of the Braun-Blanquet ecological and floristic approach implemented in the classification of phytosociological alliances makes it possible to conduct a detailed ecological analysis and taking into account not only the stand productivity, but also the level of stand biodiversity, which makes the classification more useful for scientific research and nature preservation.

Modelling potential yield capacity in conifers using Swedish long-term experiments

Information on forest site productivity is a key component to assess the carbon sequestration potential of boreal forests. While site index (SI) is commonly used to indicate forest site productivity, expressions of SI in the form of yield capacity (potential maximum mean annual volume increment) is desirable since volume yield is central to the economic and ecological analyses of a given species and site. This paper assessed the functional relationship between SI and yield capacity on the basis of yield plot data from long-term experiments measured over several decades for Norway spruce (Picea abies), Scots pine (Pinus sylvestris), Lodgepole pine (Pinus contorta) and Larch (Larix decidua and Larix sibirica) in Sweden. Component models of total basal area and volume yield were also developed. SI was determined by existing height development functions using top height and age, whereas functions for stand-level (m2 ha−1) basal area development were constructed based on age, SI and initial stand density using difference equations and nonlinear mixed-effects models. The relation between volume yield (m3 ha−1) and top height was adjusted with total basal area production through nonlinear mixed-effects models. Species-specific parametric regression models were used to construct functional relationships between SI and yield capacity. The root mean square errors of the species-specific models ranged from 2 to 6% and 10–18% of the average values for the basal area and volume equations, respectively. For the yield capacity functions, the explained variations (R2) were within 80–96%. We compared our yield capacity functions to earlier functions of the species and significant differences were observed in both lower and higher SI classes, especially, for Scots pine and Norway spruce. The new functions give better prediction of yield capacity in current growing conditions; hence, they could later be used for comparing tree species’ production under similar site and management regimes in Sweden.

Site form classification—a practical tool for guiding site-specific tropical forest landscape restoration and management

AbstractReliable estimates of forest productivity at the site scale can guide site-specific forest management. However, the best methods to evaluate productivity of natural forest sites, and in particular secondary natural forests, remain undefined. In this study we: (1) applied an indirect method for estimation of the potential productivity of a forest site (‘site form’) in Dong Nai Biosphere Reserve. In addition, we: (2a) investigated the influence of a range of environmental conditions on site form, (2b) built models to estimate site form from the corresponding environmental variables and (3) generated site form maps for the region. We found that Michaelis–Menten models provided the most consistent representation of tree height–diameter relationships, with reliable anamorphic curves at both plot-scale (50 m × 20 m) and multiplot-scales. Predicted tree height at 25-cm diameter (H25) was selected as the best indicator for site form as 25 cm was both a tree size, which was common in the forests, and for which height could be accurately predicted. H25 was significantly correlated with site environmental conditions, with the dominant influences being factors related to water availability. We generated site form maps for Dong Nai province based on the relationship between known environmental variables and H25. We conclude that maps such as these could have broad application in guiding tropical forest restoration measures elsewhere, particularly where there is limited knowledge of tree ages and species.

Regional height growth models for Scots pine in Poland

Site productivity remains a fundamental concern in forestry as a significant driver of resource availability for tree growth. The site index (SI) reflects the overall impact of all environmental factors that determine tree height growth and is the most commonly used indirect proxy for forest site productivity estimated using stand age and height. The SI concept challenges are local variations in climate, soil, and genotype-environmental interactions that lead to variable height growth patterns among ecoregions and cause inappropriate estimation of site productivity. Developing regional models allow us to determine forest growth and SI more appropriately. This study aimed to develop height growth models for the Scots pine in Poland, considering the natural forest region effect. For height growth modelling, we used the growth trajectory data of 855 sample trees, representing the Scots pine entire range of geographic locations and site conditions in Poland. We compared the development of regional height growth models using nonlinear-fixed-effects (NFE) and nonlinear-mixed-effects (NME) modelling approaches. Our results indicate a slightly better fit to the data of the model built using NFE approach. The results showed significant differences between Scots pine growth in natural forest regions I, II, and III located in northern Poland and natural forest regions IV, V, and VI in southern Poland. We compared the development of regional height growth models using NFE and NME modelling approaches. Our results indicate a slightly better fit to the data of the model built using the NFE approach. The developed models show differences in height growth patterns of Scots pines in Poland and revealed that acknowledgement of region as the independent variable could improve the growth prediction and quality of the SI estimation. Differences in climate and soil conditions that distinguish natural forest regions affect Scots pine height growth patterns. Therefore, extending this research to models that directly describe height growth interactions with site variables, such as climate, soil properties, and topography, can provide valuable forest management information.

Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data

Site index (SI) is a common measure of forest site productivity, serving as a valuable baseline for forest management. The main objective of this study was to develop a SI model for Pinus pinaster Ait. in north-west Spain by combining bi–temporal, low–density airborne laser scanning (ALS) data (acquired in the periods 2009–2011 and 2015–2017) with climatic, edaphic and physiographical data. Site productivity, assessed by site quality curves, was modelled using an age-independent difference equation method based on ALS metrics and environmental variables. For the model development process, we used data from 156 sample plots in pure and even-aged P. pinaster stands distributed throughout Galicia (NW Spain) and measured in the Spanish National Forest Inventory (SNFI). The generalized algebraic difference approach (GADA) formulation was tested by using two different base equations for modelling the dominant height growth (ΔH) from ALS variables. The GADA formulation derived from the Bertalanffy’s base model produced the best estimates of dominant height (H) for P. pinaster stands in Galicia. Use of the proposed model to estimate ΔH for a new pine stand requires two ALS data sets for estimating site-specific (local) parameters. To enable use of the model when such information is not available, the relationship between the values of the site-specific parameter and environmental variables was described using Multivariate Adaptive Regression Splines (MARS). Use of the MARS equation enabled us to develop spatially-explicit predictive maps of the site-specific parameter values, which can be used together with the GADA model to derive ΔH curves and SI estimates for P.pinaster stands in the whole study region.

Modeling dominant height using stand and water balance variables for loblolly pine in the Western Gulf, US

Site-index models based on dominant height and age are commonly accepted measures of site productivity in forest plantations. Therefore, reliable estimates of dominant height over time are critical, as they provide the foundations for site productivity estimates used in growth and yield models. Forest site productivity depends on the combination of many environmental factors, whereas tree height is only a general proxy indicator of these factors interacting over time, and as such, subject to large errors. Hence, selection of appropriate environmental variables along with field-based data is expected to result in more consistent estimates. Although previous studies have incorporated climatic variables into site-index models, there is still a lack of understanding among the forest research community with respect to the selection of suitable climatic variables. Models including climatic water balance components such as water-deficit and excess-water are scarce. These components are especially important to address the influence of drought on plant growth. The main objective of this study is to evaluate the change in dominant height estimates of forest stands with respect to changes in water balance components. High-resolution actual evapotranspiration (AET) and potential evapotranspiration (PET) were combined to determine water excess/deficit of sites. These were incorporated into a loblolly pine polymorphic site index model using a generalized algebraic difference approach and maximum likelihood calibration methods that accounted for long-term uncertainty in the results. Our model further improves the precision in dominant height estimates for loblolly pine in the southeast US.

Evaluation of potential versus realized site productivity of Larix principis-rupprechtii plantations across northern China

Site quality evaluation is a fundamental component of forest management and is also vitally important towards improved understanding of forest growth processes and optimizing silviculture practices. However, most site quality studies have focused on site index which cannot predict potential site productivity. In this study, a methodology that incorporates volume-related potential increment which accounts for optimal stand density index was used for site productivity assessment of Larix principis-rupprechtii plantations across Northern China. Based on 152 permanent sample plots, the models of potential and realized productivity of L. principis-rupprechtii plantation were established, and percentage of available growing space close to potential productivity in different regions were analyzed in different site classes. Growth models of stand dominant height and volume were developed by site classes based on biological and statistical rationality. The potential productivity was between 3.93 m3/ha/year and 6.84 m3/ha/year. The realized productivity was always lower than potential productivity, and the gaps between the two types of productivity measures decreased with increasing stand age. The available growing space percentage of volume productivity was between 0% and 94.52%, and this was higher in stands in the middle and young stage of stand development compared to the mature stage. The available growing space increased with the decline of site class. The values of potential productivity and available growing space could be used to effectively assess forest site productivity, and also provide highly reliable and valuable information for L. principis-rupprechtii plantation management.

Forest Potential Productivity Mapping by Linking Remote-Sensing-Derived Metrics to Site Variables

A fine-resolution region-wide map of forest site productivity is an essential need for effective large-scale forestry planning and management. In this study, we incorporated Sentinel-2 satellite data into an increment-based measure of forest productivity (biomass growth index (BGI)) derived from climate, lithology, soils, and topographic metrics to map improved BGI (iBGI) in parts of North American Acadian regions. Initially, several Sentinel-2 variables including nine single spectral bands and 12 spectral vegetation indices (SVIs) were used in combination with forest management variables to predict tree volume/ha and height using Random Forest. The results showed a 10–12 % increase in out of bag (OOB) r2 when Sentinel-2 variables were included in the prediction of both volume and height together with BGI. Later, selected Sentinel-2 variables were used for biomass growth prediction in Maine, USA and New Brunswick, Canada using data from 7738 provincial permanent sample plots. The Sentinel-2 red-edge position (S2REP) index was identified as the most important variable over others to have known influence on site productivity. While a slight improvement in the iBGI accuracy occurred compared to the base BGI model (~2%), substantial changes to coefficients of other variables were evident and some site variables became less important when S2REP was included.