Forest Site Classification Research Articles

Enhancing Forest Site Classification in Northwest Portugal: A Geostatistical Approach Employing Cokriging

Enhancing Forest Site Classification in Northwest Portugal: A Geostatistical Approach Employing Cokriging

The integration of hierarchical levels of scale in tree species distribution models of silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.) in mountain forests

Taking into account and combining different levels of scale is essential in species distribution models when it comes to the investigation of the environmental niche of a species. The study focuses on two levels of spatial extent, on the one hand the continental level of Europe, and on the other hand the regional level of the federal state of Tyrol in Austria. Mountain forests in the European Alps cover the inner Alpine distribution margins of several tree species and therefore are particularly well-suited to reveal the predictive power of climate, soil, and topographic variables on the shaping of these margins. The potential occurrence of the two investigated tree species, Abies alba and Fagus sylvatica, is an important criterion for the delineation of elevational vegetation zones in forest site classification systems and was modelled with Deep Neural Networks. In the process, we observed a strong imbalance of absence and presence records at the continental level and evaluated different methods to address this issue. The potential predictor variables for species distribution modelling at the different spatial extents were grouped into climate, soil, and topographic information. The combination of the different hierarchical levels of extent and associated spatial resolution was implemented by using the outputs of the continental model as a predictor variable in the regional model. The binary classification of the 30% test dataset showed a True Skill Statistic of 0.73 to 0.76 for the regional level and 0.5 to 0.74 for the continental level, with slightly higher values for F. sylvatica than for A. alba. For both species and extent levels, the climate predictor group showed the greatest contribution (81 to 96%) to the models’ predictive power. At the regional level, climate was followed by soil and then topographic predictor groups. At the continental level however, topography showed stronger effects than soil information. In most cases, the consideration of soil information along climatic gradients led to an increase in the occurrence probability at the climatic distribution margins. There is evidence that soil conditions are more important in determining the inner Alpine distribution margins for F. sylvatica than for A. alba. To improve species distribution models at the regional level, e.g. in the Alpine area, a focus on soil information is proposed. In general, models which combine continental and regional data are preferable.

Approaches to Forest Site Classification as an Indicator of Teak Volume Production

We conducted a study on the dominant height growth of clonal teak (Tectona grandis Linn F.) plantations in the Brazilian Amazon to assess their potential and its agreement with volumetric production. We employed two approaches, ADA (algebraic difference) and GADA (generalized algebraic difference), and analyzed data from 58 permanent plots collected over a 10 year period. To classify the sites, we developed equations and evaluated their accuracy using various criteria, including correlation coefficient, mean square of residual, Akaike’s criterion, distribution of residuals, and validation through equivalence testing (TOST). We also assessed the biological realism of the constructed curves. We used cluster evaluation and dendrogram comparison to assess the agreement between site index and volumetric production for each approach. The Lundqvist–Korf baseline models (M1–ADA and M4–GADA) proved to be accurate and realistic in estimating dominant height in both approaches. Our findings indicate that the approaches utilizing dynamic equations and generating polymorphic curves effectively represent the sites and indicate the volumetric production of the plantations, with 98.3% of agreement rate. Based on our results, we recommend the use of ADA and GADA approaches for estimating the dominant height of clonal teak plantations in the Eastern Brazilian Amazon.

Forecasting production in thinned clonal stands of Tectona grandis in Eastern Amazonia

Aim of the study: We investigated the most suitable thinning ages and intensities to maximize productivity and minimize the rotation age of Tectona grandis clonal plantations in the Brazilian Eastern Amazon.
 Area of study: Capitão Poço, State of Pará, Eastern Amazonia, Brazil.
 Materials and methods: We used diameter, height, and volume data from 72 permanent plots measured on nine occasions. We determined the classification of forest sites using the generalized algebraic difference approach (GADA). Clutter’s segmented model was used to simulate different intensities of basal area reduction, determining the technical ages according to the projected increments.
 Main results: The polymorphic site curves generated by the GADA method revealed that there were sites with different productive characteristics. The Clutter model produced compatible projections of basal area and volume that followed the behavior of the productivity classes. The final production was maximized when three thinning intensities (basal area reductions) were applied: 1st thinning (50%), between the ages of 3.5 to 4.2 years; 2nd thinning (50%), between the ages of 6.1 to 7.3 years; and 3rd thinning (25%), between the ages of 10.6 to 12.8 years. Projected rotation ages ranged from 13.9 to 16.6 years earlier than seminal plantings. The simulations increased the net volume by 8.3%, on average, compared to no thinning.
 Research highlights: Simulations with three thinnings maximized production compared to the no thinning scenario. The time interval between thinnings was less than five years. The research results can help forest management decision-making and reveal production increases of T. grandis clonal stands in a shorter time.

Prediction of forest nutrient and moisture regimes from understory vegetation with random forest classification models

The proper choice of the tree species to be grown in a specific forest site requires a good knowledge of the tree species autecology and a comprehensive description of the local environmental conditions. In Belgium (Western Europe), ecological forest site are classified according to three major gradients: climate, soil nutrient (fertility) and soil moisture regimes. Understory indicator species are used by practitioners to determine nutrient and moisture regimes, but requires a significant expertise of forest ecosystems. The present work aims in a first instance at modelling the nutrient and moisture regimes based on species composition. Secondly, a practical decision support tool is developped and made available in order to predict forest nutrient and moisture regime starting from a floristic relevé. To do so, we collected floristic relevés representing understory vegetation diversity in Belgium and covering all the nutrient and moisture gradient. The combination of soil and topographic measurements with the indicator plants presence/absence support forest scientists in inferring a nutrient and moisture regime to each relevé. The resulting dataset was balanced along the different nutrient or moisture regimes and Random Forest classification models were trained in order to predict the forest site characteristic from indicator species presence (or absence). One model was fitted for the prediction of the nutrient regime, exclusively based on the floristic information. A second one was trained to classify the moisture regime. Accurate predictions confirms the appropriate use of indicator species for the Belgian forest site classification. The two models are intregrated in a web application dedicated to forest practionners. This website enables the automatic determination of nutrient and moisture regimes from the species list of a floristic relevé.

A multi-data ensemble approach for predicting woodland type distribution: Oak woodland in Britain.

Interactions between soil, topography, and climatic site factors can exacerbate and/or alleviate the vulnerability of oak woodland to climate change. Reducing climate‐related impacts on oak woodland habitats and ecosystems through adaptation management requires knowledge of different site interactions in relation to species tolerance. In Britain, the required thematic detail of woodland type is unavailable from digital maps. A species distribution model (SDM) ensemble, using biomod2 algorithms, was used to predict oak woodland. The model was cross‐validated (50%:50% ‐ training:testing) 30 times, with each of 15 random sets of absence data, matching the size of presence data, to maximize environmental variation while maintaining data prevalence. Four biomod2 algorithms provided stable and consistent TSS‐weighted ensemble mean results predicting oak woodland as a probability raster. Biophysical data from the Ecological Site Classification (forest site classification) for Britain were used to characterize oak woodland sites. Several forest datasets were used, each with merits and weaknesses: public forest estate subcompartment database map (PFE map) for oak‐stand locations as a training dataset; the national forest inventory (NFI) “published regional reports” of oak woodland area; and an “NFI map” of indicative forest type broad habitat. Broadleaved woodland polygons of the NFI map were filled with the biomod2 oak woodland probability raster. Ranked pixels were selected up to the published NFI regional area estimate of oak woodland and matched to the elevation distribution of oak woodland stands, from “NFI survey” sample squares. Validation using separate oak woodland data showed that the elevation filter significantly improved the accuracy of predictions from 55% (p = .53) to 83% coincidence success rate (p < .0001). The biomod2 ensemble, with masking and filtering, produced a predicted oak woodland map, from which site characteristics will be used in climate change interaction studies, supporting adaptation management recommendations for forest policy and practice.

An improved quality assessment framework to better inform large-scale forest restoration management

Dynamic monitoring of forest ecosystem quality is necessary for restoration program evaluation but remains challenging for very large-scale programs. Current evaluation methods employ regional forest quality indicators that compare the quality status of targeted forests with benchmarks from remnant old-growth forest communities, however data availability usually limits the application of available methods to small scales. We constructed an improved framework, integrating forest site classification selection and local remnant old-growth forest community delimitation, to quantify and map forest quality using environmental data and remote sensing (RS) based approaches. A classification strength model was introduced to improve the accuracy of forest site classification. The remote-sensing-based method integrates species composition and forest biological productivity characteristics recognition to develop a practical tool for large-scale remnant old-growth forest community delimitation. The new assessment framework was tested across the entire spatially heterogeneous Yangtze River Basin, the largest watershed in China and showed high accuracy in forest quality assessment based on observed field data validation. The forest site classification was selected by considering spatial heterogeneities in climate, topography and soil type, with 37 forest sites classified. The native forest community groups with less human disturbance in each forest site used for forest quality baseline estimation were also selected as forests with top 10% of biomass in protected areas. The case study demonstrated that forest areas of low and poor quality accounted for 34.46% of the total forest area in 2015. Between 2000 and 2015, 55.72% of forest areas experienced increases in quality level, and 7.07% experienced decreases. The improved forest quality assessment framework enhances the scope and accuracy of forest restoration information and can be applied as an evaluation tool for forest restoration management.

Классификация типов лесорастительных условий по индикаторным видам Воробьева-Погребняка: база данных и опыт анализа лесотаксационных данных

Классификация типов лесорастительных условий по индикаторным видам Воробьева-Погребняка: база данных и опыт анализа лесотаксационных данных

Forest Site Classification in the Southern Andean Region of Ecuador: A Case Study of Pine Plantations to Collect a Base of Soil Attributes

Forest site classification adapted to the respective site conditions is one prerequisite for sustainable silviculture. This work aims to initiate the forest site classification for pine plantations in the southern Andean region of Ecuador. Forest productivity, estimated by the dominant height of 20-year-old trees (DH20), was related to data from climate, topography, and soil using 23 plots installed in pine plantations in the province of Loja. Forest site productivity was classified as: low (class C: 13.4 m), middle (class B: 16.6 m), and high (Class A: 22.3 m). Strong determinants to differentiate the forest site classes were: the short to medium term available Ca and K stocks (organic layer + mineral soil standardized to a depth of 60 cm), soil acidity, the C:N ratio, clay and sand content, forest floor thickness, altitude, and slope. The lowest forest productivity (Class C) is mainly associated with the lowest short to medium term available K and Ca stocks. Whereas, in site classes with the highest forest productivity, pines could benefit from a more active microbial community releasing N and P, since the soil pH was about 1 unit less acidic. This is supported by the lowest forest floor thickness and the narrowest C:N ratio.

Morphometric indexes and dendrometric measures for classification of forest sites of Eucalyptus urophylla stands

Morphometric indexes and dendrometric measures for classification of forest sites of Eucalyptus urophylla stands

Variation in selected solid wood properties of young Pinus patula from diverse sites in the Mpumalanga escarpment area in South Africa

Regression analyses identified ‘Growth Days’ (an index expressing site moisture availability) as the only site variable contributing significantly to the prediction to wood density (R2 = 0.57), whereas the model predicting grain angle included only ‘Altitude’ (R2 = 0.60). These results surfaced during an investigative study to quantify various sources of variation in wood properties and to quantify the effect of a number of site factors on wood properties of Pinus patula grown in the Mpumalanga escarpment area of South Africa. For this purpose, 10 trees were sampled from each of 17 diverse sites for wood property analyses. The effects of site, distance from the pith and differences between trees within site on wood density, transverse shrinkage, grain angle and dynamic modulus of elasticity were investigated. The site factors considered included a wide variety of soil and climatic factors. The effect of radial distance from the pith and differences between individual trees within sites were highly significant, accounting for most of the variation in wood properties. Although the effects of a number of site factors were statistically significant, they generally explained relatively small but important variation in wood properties among sites. The study not only quantified the effects of important sources of variation on a few key wood properties, but it also revealed that the extent of differences between sites can be explained in terms of some specific site factors. It is envisaged that the results will contribute significantly towards the refinement of current forest site classification systems for improved decision-making with respect to wood quality in intensively managed plantation systems.

CLASSIFICAÇÃO DA CAPACIDADE PRODUTIVA DE POVOAMENTOS DE EUCALIPTO A PARTIR DE PARCELAS TEMPORÁRIAS

Objetivou-se com este trabalho realizar a classificacao de sitios florestais a partir deuma base de parcelas temporarias. Os dados utilizados no ajuste dos modelosforam provenientes de um povoamento de clones de Eucalyptus urophylla eEucalyptus grandis localizado no Sul da Bahia, com area de aproximadamente96.000 ha. Foram utilizados pares de dados de idade e altura media das arvoresdominantes de 12.050 parcelas distribuidas em todo o povoamento florestal. Foramtestados oito modelos matematicos amplamente utilizados na literatura florestal paraa estimativa da altura dominante: Schumacher, Chapman-Richards, Weibull, SilvaBailey, Prodan, Logistico, Clutter-Jones e Mitscherlich. Os modelos foram avaliadosatraves do erro padrao da estimativa (Syx), dispersao grafica dos residuos atravesdo histograma e do grafico da probabilidade normal dos residuos, Criterio deInformacao de Akaike (AIC) e Criterio de Informacao Bayesiano (BIC). Todos osmodelos apresentaram valores estatisticos e graficos dos residuos comcomportamento semelhante entre si. Foram construidas seis curvas de sitio comamplitude de cinco metros pelo metodo da curva-guia, utilizando a idade dereferencia de sete anos. O modelo de Chapman-Richards foi escolhido porapresentar os melhores resultados estatisticos e por ser um modelo biologico. Aclasse de sitio III apresentou maior representatividade na classificacao por talhao,com indice de sitio de 35,5 m.

Climatic Characteristics of Forest Vegetation Zones of the Czech Republic

Abstract Correct derivation of climatic characteristics of forest vegetation zones is the Achilles heel of Forest site classification in the Czech Republic. A combination of low density of climatic stations, and their unsuitable location (in regard to distribution of forest complexes) make obtaining data problematic. An important contribution to this issue is an application of aladin-climate.cz model materials from the Czech Hydrometeorological Institute (CHMI) for the second time period of normal climate years 1961-1990, and the current period from 1991-2009. Calculation of climatic (temperature, precipitation, etc.) fields was conducted on a basis of observation stations. The original station series were subjected to quality control, meaning they were homogenised and supplemented by missing values in measurements. The actual calculation of the technical series is based on the IDW (Inverse Distance Weighting) method; data is used when surrounding stations are first standardised to altitude point, for which we expect a new line, and then calculated a weighted average of new value. The station data were interpolated using the geostatistical linear kriging method. The outputs are the spatial averages for basic climatic zonal forest vegetation level, occurring in the different Natural Forest Areas (NFA). The individual climate parameters of forest vegetation zones were evaluated by regression analysis. The climate-vegetation segments (CVS) of the Czech Republic, which share similar climatic characteristics of the forest vegetation zones (FVZ), were proposed.

Forest Site Classification for Cultural Plant Harvest by Tribal Weavers Can Inform Management

Do qualitative classifications of ecological conditions for harvesting culturally important forest plants correspond to quantitative differences among sites? To address this question, we blended scientific methods (SEK) and traditional ecological knowledge (TEK) to identify conditions on sites considered good, marginal, or poor for harvesting the leaves of a plant (beargrass; Xerophyllum tenax) used in tribal basket weaving. We relied on voluntary participation of six expert weavers, a stratified, randomized field sample, discriminant analysis (DA), a standardized color system, and paired t-tests. We accepted each weaver’s classification (good, marginal, or poor) of forested sites for beargrass harvest and then measured forest and plant attributes on two plots at each harvest area in each class (n 72). The DA yielded descriptive but not predictive results. Coarse woody debris (CWD) levels and the number of trees (trees per acre [TPA]) differed significantly between good and poor sites across California, Oregon, and Washington, whereas basal area did not. Good sites had less CWD (P 0.0360) and fewer TPA (P 0.001) than poor sites. Variations in leaf color decreased as the site class for plant harvest improved. Results reveal a crosswalk between ecological knowledge derived via SEK and TEK for culturally important plants.

The use of the particle size distribution of soils in estimating quality of mountain forest sites

Abstract The physical and chemical properties of soil are the basic features that are used in the assessment of mountain sites. The aim of this study was to produce a simple key for classifying forest sites in mountain areas using soil particle size distribution. 200 plots (standard typological space) were selected for examination, most of which are typical of the Carpathians - being dominated by flysch rock. A few plots were located in the Sudety and Tatra Mountains, which have a different surface geology, mostly metamorphic rock and granite. The study proved that soil properties (reaction, base saturation, content of base cations, organic carbon and nitrogen) are helpful in distinguishing and assigning soils to particular site types. The particle size distribution of forest mountain sites separated into different categories in terms of productivity. These results can be used to improve the classification of forest mountain sites.

Vegetation diversity of the Scots pine stands in different forest sites in the Turawa Forest District

Abstract The utility of phytocenotic indices in the diagnosis and classification of forest sites might be limited because of vegetation degeneration in managed forests. However, even in secondary communities it may be possible to determine indicator species, although these may differ from typical and well known plant indicators. The aim of this work was to assess the vegetation diversity of Scots pine stands in representative forest site types along a moisture and fertility gradient. In total 120 sample plots from Turawa forests were included in the study. These plots represented young (21-40 years) and old (&gt; 80 years) Scots-pine-dominated stands. The forest sites were categorised according to Polish site classification. Four site categories were studied: Bśw (very nutrient-poor and mesic sites), BMśw (nutrient-poor and mesic sites), BMw (nutrient-poor and moist sites), LMw (quite nutrient-rich and moist sites). The species composition of the forest patches studied hardly differed among forest site types. Almost all of the vegetation in site Bśw was different from both moist site types (BMw and LMw). Sites Bśw and LMw had the exclusive species determined as site indicators. Moreover, young stands had their own site type indicator species which differed from old stands. Numerical classification showed that only two plant communities were widespread: Leucobryo- Pinetum in Bśw and BMśw, and the community of Pinus sylvestris and Molinia caerulea in BMśw, BMw, LMw. In secondary communities typical indicator species may not be useful, but it is possible to determinate species that are locally unique to forest site type. Despite the convergence in the composition of the plant community resulting from tree stand unification, plant communities have the capacity for a more diverse composition. Tree stand conversion can increase phytocenotic diversity

Structure and diversity of psocid taxocenoses (Insecta: Psocoptera) in the forest ecosystems of the Fageta abietis s. lat. zone in the Western Carpathian Mts.

Structure of psocid taxocenoses (Psocoptera) were studied in forest ecosystems of the Western Carpathian Mts. during 1997–2001. Vegetation tiers were used as a study frame. Lower units of forest site classification system (forest type complexes) were used for a classification of ecological conditions as well. Only a part of material, i.e. individuals that was found in the forest ecosystems of Fageta abietis s. lat. communities (= the 4th beech vegetation tier) was evaluated for purpose of this work. This vegetation tier is widespread in large part of Vsetínské vrchy hills, in the highest parts of Podbeskydská pahorkatina hills, and in the foothills of the Moravskoslezské Beskydy Mts. 1774 adults comprising 32 species were found in total in the 4th vegetation tier. As eudominant species, the following ones were found: Caecilius flavidus and C. burmeisteri, as dominant species, the following ones were found: Philotarsus picicornis, Elipsocus moebiusi and Peripsocus subfasciatus. In natural geobiocenoses with the level of naturalness of 1 or 2, the following species were found: as eudominant species: Caecilius flavidus and Elipsocus moebiusi, as dominant species, the following one was found: Mesopsocus unipunctatum. Taxocenoses of psocids were evaluated by Detrended Correspondence analysis (DCA) and Divisive Cluster analysis (DvClA). This material was compared to another material gained from various vegetation tiers in the Western Carpathians Mts. The characteristic species composition of psocids in the 4th vegetation tier was as follows: Caecilius flavidus – Elipsocus moebiusi – Peripsocus parvulus.

Database of Czech Forest Classification System

The Database of the Czech Forest Site Classification System (DCFCS; GIVD ID EU-CZ-002) is focused on data about ecological conditions and structure of forest ecosystems in the territory of the Czech Republic. This database is managed by Forest Management Institute Brandýs nad Labem. DCFCS consists of two parts, the numeric database and the GIS data. The numeric database includes all descriptive data of sample plots used in classification. Each plot is characterized by features of ecotope (information about geomorphology, climate, pedology etc.) and vegetation data (information on composition and structure). Maps of site types with the position of sample plots are represented as GIS data.

Norway spruce in forest ecosystems of the Czech Republic in relation to different forest site conditions

The paper analyses the representation of Norway spruce (Picea abies [L.] Karst.) (hereinafter spruce) in relation to different conditions of forest sites. The analysis is based on data from the National Forest Inventory conducted in the Czech Republic in 2001-2004 (hereinafter NFI), stratified according to units of the Forest Site Classification System (Pl&amp;iacute;va 1971, 2000). Results of the analysis provide a structured image of the current share of spruce. The formerly published information on the natural share of spruce was corroborated and the recommended share of spruce in the target species composition of the spruce management system was analyzed. The analysis documents the applicability of NFI data in the technical discussion concerning the future form of forest ecosystems in the Czech Republic. The results can be used as the groundwork for concrete forest management decision-making and will contribute to the study of the biological diversity of forest ecosystems.

Consistency in the classification of oligotrophic forest sites and forest vegetation in Scots pine stands of successive age classes in Bolesławiec Forest

Przemiany ubogich siedlisk borowych a aktualny stan roślinności runa w drzewostanach sosnowych kolejnych klas wieku w Nadleśnictwie Bolesławiec