Site Index Research Articles

Growth trends of loblolly pine age five or less in relation to soil type and management intensity

We evaluated three objectives for loblolly pine (Pinus taeda L.) trees age five or less: 1) how height growth varies by soil type and silvicultural intensity, 2) the accuracy of predicted base-age 25 site index (SI25) using age one to five heights, and 3) if height dominance exhibited early in the rotation is maintained throughout the rotation. Data from 42 sites across the southeastern United States with an array of soil textures and management intensities (optimal, intensive, and operational) were used. Management intensity and soils significantly affected tree height. Coarse loamy soils were the most responsive to increasing management intensity. At age four, tree heights were greatest in the optimal group (4.63 m), followed by the intensive (4.31 m), and then the operational (3.06 m). Organic soils do not appear to respond to maximum management intensity. Predictability of SI25 was high especially starting at age four, with R2 values ranging from 0.27 for the age four intensive group to 0.78 for the age four operational group. The optimal group had the greatest slope with an expected increase of 2.61, 2.75, 1.88, and 1.78 m in site index per additional meter of height at ages two, three, four, or five, respectively. Data from six different study sites indicate, the tallest (class one) and smallest (class five) trees changed percentile class the least often over time. As early as age two, over 40 % of observations in classes one and five had zero changes in class through age 13. Young tree data were effective in predicting SI25, and height dominance appeared generally set early in the rotation.

Nature vs. nurture: Drivers of site productivity in loblolly pine (Pinus taeda L.) forests in the southeastern US

Forest productivity is one of the most important aspects of forest management, landscape planning, and climate change assessment. However, although there are multiple elements known to affect productivity, most of them rely on the “nature” of the edaphic, climatic, and geographic conditions, and only some specific aspects can be modified through forest management or “nurture”. Through evaluation of site resource availability and an understanding of the main drivers of productivity, management can present solutions to overcome site resource limitations to productivity. Therefore, understanding the implications of a specific management regime requires understanding what drives productivity across large spatial extents and among different management regimes. In this study, we used data from over 1 million hectares of industrial forestland, covering over 6000 different soils and several management regimes of Pinus taeda L. plantations, as well as plot-based data from the Forest Inventory and Analysis (FIA) program, facilitating a comparison of planted and natural Pinus taeda stands. Combined with US Geological Survey LiDAR data, we computed site index and generated wall-to-wall productivity maps for planted Pinus taeda stands in the southeastern US, as well as point-based site index estimates for the FIA dataset. We modeled site index using a random forest algorithm considering edaphic, geologic, and physiographic province information based on the Forest Productivity Cooperative “SPOT” system, and also included climate and management history data. Our model predicted site index with an R2 of 0.701 and RMSE of 1.41 m on the industrial data and R2 of 0.417 and RMSE of 1.84 m for the FIA data. We found that year of establishment of the forest, physiographic province, and geology, were the most important drivers of site index. The soil classification modifier indicating root restrictions were the most important soil-specific variable. Additionally, we found an average increase in site index of 3.05 m since the 1950s for all FIA data, and an average increase of 4.73 m for all industrial data since the 1970s. For the latest period analyzed (2000–2012), average site index in planted FIA plots was 1.2 m higher than naturally regenerated FIA plots, and site index in all industrial forestland had a site index almost 3 m greater than planted FIA plots. Overall, we believe this work sets the foundation for better understanding of forest productivity and highlights the importance of intensive silviculture to improve productivity, and as an additional tool to achieve the economic, environmental, and social objectives.

Precommercial Thinning but Not Commercial Thinning Increases the Merchantable and Large Sawlog Volume Production of Lodgepole Pine on Fair Sites

Abstract The effect of thinning on stand structure and volume production is well studied. However, the effect of combinations of precommercial (PCT) and commercial thinning (CT) on the production of different log grades and differential growth responses is less understood, although it is crucial for forest managers to choose an optimal management regime. Starting with actual operational field data from a lodgepole pine (Pinus contorta var.latifolia) PCT trial on fair quality sites (site index: 16–18 m at 50 years), we used an individual tree growth model to forecast development over the entire rotation. We found thinning changed the structure (density, quadratic mean diameter) of the stands but not the total volume production. However, in terms of merchantable volume and large sawlog volume, stands with only PCT provided the largest volume, more than either CT or a combination of PCT and CT, or the unthinned control. Moreover, our study findings also showed that, by doing only PCT, stands reached maximum merchantable or large sawlog mean annual increment earlier than other thinned or unthinned stands. This indicates that PCT might shorten the rotation length and contribute to an enhanced supply of timber. Study Implications: The effect of commercial thinning (CT) on stand structure and volume production is well studied. However, the effect of combinations of precommercial (PCT) and commercial thinning (CT) on the production of different log grades and differential growth responses is less studied, although it is crucial for forest managers to choose a management option. Starting with actual operational field data from a lodgepole pine (Pinus contorta var.latifolia) PCT trial in a fair-quality site (site index [SI]: 16–18), we used an individual tree growth model to develop the stands over the entire rotation. We found thinning changed the structure (density, quadratic mean diameter) of the stands but not the total volume production. However, in terms of merchantable volume and large sawlog volume, stands with only PCT provided the largest volume, more than either CT or a combination of PCT and CT, or the unthinned control. Moreover, our study findings also showed that, by doing only PCT, stands reached maximum merchantable or large sawlog MAI earlier than other thinned or unthinned stands. This indicates that PCT might shorten the rotation length and contribute to the continuous supply of timber production.

Site index determination using a time series of airborne laser scanning data

Site index determination using a time series of airborne laser scanning data

Development of Polymorphic Index Model for Assessing Subtropical Secondary Natural Oak Forest Site Quality Under Complex Site and Climate Variables

Site and climate conditions are the key determinants controlling dominant height growth and forest productivity, both independently and interactively. Secondary natural oak forests are a typical forest type in China, especially in Hunan Province, but little is known about the site index of this forest under the complex site and climate variables in the subtropics. Based on survey data of dominant trees and site variables from 101 plots in Hunan oak natural secondary forests and climate data obtained using spatial interpolation, we used the random forest method, correlation analysis, and the analysis of variance to determine the main site and climate factors affecting oak forest dominant height and proposed a modeling method of an oak natural secondary forest site index based on the random effect of site–climate interaction type. Of the site variables, elevation affected stand dominant height the most, followed by slope direction and position. Winter precipitation and summer mean maximum temperature had the greatest impact on stand dominant height. To develop the modeling method, we created 10 popular base models but found low performance (R2 ranged from 0.1731 to 0.2030). The optimal base model was Mitscherlich form M3 (R2 = 0.1940) based on parameter significance tests. Since site and climate factors affect the site index curve, the dominant site and climate factors were combined into site types and climate types, respectively, and a nonlinear mixed-effects approach was used to simulate different site types, climate types, site–climate interaction types, and their combinations as random effects. Site–climate interaction type as a random factor enhanced model (M3.4) performance and prediction accuracy (R2 from 0.1940 to 0.8220) compared to the optimum base model. After clustering the 62 site–climate interaction types into three, five, and eight groups using hierarchical clustering, a mixed-effects model with the random effects of eight groups improved model performance (R2 = 0.8265) and applicability. The modeling method developed in this study could be used to assess a regional secondary natural oak forest site index under complex site and climate variables to evaluate the forest productivity.

Spatiotemporal topology of religious spread in a multi‐religious metropolis: A historical religious profile of Taipei City in Taiwan from 1660 to 2020

AbstractReligious identities play an important role in shaping migrants' experiences. Understanding the spatiotemporal distribution of religions enhances our knowledge of both religious expansion and religious cultures. This paper aims to leverage spatiotemporal analysis to characterise the topology of the spread of multiple religions in the Taipei metropolitan area from 1660 to 2020, including Folk Taoism (853 temples/altars, 55.39%), Christianity (306 churches, 19.87%) and Buddhism (332 temples, 21.56%). Three major factors affecting religious distribution are considered: the year of establishment of religious units (churches, temples or altars), the reclamation year of religious locations, and the economic index of religious sites. The results show that Folk Taoism and Buddhism have a long history of development in early reclamation regions with a hopping expansion pattern. However, Christianity expanded later in the later reclaimed and early reclaimed areas. The Christian religious units have highly concentrated spatial patterns and are located in the higher‐income districts, centralised in the core regions of the Taipei metropolis. Modern forms of highly institutionalised religion, such as Buddhism and Christianity, are more prevalent in the relatively higher‐income, later‐cultivated areas, which provide richer social resources for development. Folk Taoism, as a traditional religion, is maintained and developed by local communities. This macroscopic analysis helps to (1) identify the exact chronology of different growth waves and explain them in a historical context, and (2) elucidate the spatial distribution differences between institutionalised religions and folk religion. Our research shows the evolution of religious landscapes from an undeveloped city to a developed city, offering valuable insights for geographical and religious studies, and enhancing understanding of diffused and institutionalised religious expansion.

Soil available phosphorus and pH are key factors affecting the site index of Larix kaempferi plantations in China

Assessing the quality of forest sites is crucial for evaluating the potential productivity of forests and formulating effective management strategies. Therefore, it is essential to understand how environmental variables affect the site quality. This study focuses on quantifying the effects of 44 different environmental variables including climate, topography, and soil properties on the site index of Larix kaempferi plantations in three different climate regions in China, utilizing the random forest algorithm. L. kaempferi site index was determined from stem analysis data by felling dominant trees from 51 even-aged stands. The results indicated that the proposed random forest model explained ~59.47% of site index variations. Among many environmental variables, available phosphorus, pH, degree-days above 5°C (DD5), and spring mean maximum temperature (Tmax_MAM) had significant effects on the site index (P < 0.05), and the importance of soil chemical properties generally exhibits relatively larger effects on the site index than climate variables and topography variables. The partial dependence analysis revealed that the L. kaempferi plantations had maximum values at ~30 mg/kg of available phosphorus in the first soil layers, 30 mg/kg of available phosphorus in the second soil layers, 20 mg/kg of available phosphorus in the third soil layers, the DD5 between 2,600and 3,000°C, and Tmax_MAM ~15°C. Our findings attempt to provide a better understanding of the site–growth relationship.

Dynamic site index models sensitive to ecoregional variability for Scots pine stands in Western Black Sea Region of Türkiye.

Site productivity, defined as the production amount of the stand at a specific age, has a significant impact on the growth of the stand and site index is used as an indicator of site productivity. The objective of this study is to develop ecoregion-based dynamic site index models for Scots pine (Pinus sylvestris L.) stands in the Kastamonu and Sinop regions of Türkiye. The mixed-effects modeling approach allowing for the inclusion of ecoregions in the models was used to develop dynamic site index models, and the models derived from seven base models were tested. The best model was selected based on statistical criteria. As a result of statistical analyses and graphical examinations, the King-Prodan model was found to yield the best predictive results in terms of growth patterns. The site index model based on the King-Prodan method produced a coefficient of determination (R2) of 0.977. The statistical criteria for this model are as follows: Akaike information criterion (AIC) of 4931.052, Bayesian information criterion (BIC) of 4968.933, root mean square error (RMSE) of 1.218, and mean error (ME) of - 0.036. The F-test was used to test whether there was a statistically significant difference in dominant heights between ecoregions. The results demonstrated that the dominant heights exhibited statistically significant differences among the ecoregions. Consequently, it is of paramount importance to utilize ecoregion-based dynamic site index models in order to achieve reliable and accurate predictions.

A low-cost alternative to LiDAR for site index models: applying repeated digital aerial photogrammetry data in the modelling of forest top height growth

Abstract Environmental and forest structural information derived from remote sensing data has been found suitable for modelling forest height growth and site index and therefore forest productivity assessment, with the advances in airborne laser scanning (ALS) playing a major role in this development. While there is growing interest in the use of ALS-derived point clouds, point clouds from high-resolution digital aerial photography (DAP) are also often used for mapping and estimating forest ecosystem properties due to their lower acquisition costs. In this study, we document the applicability of bi-temporal DAP data for developing top height (TH) growth models for Scots pine stands. Our results indicate that DAP data can function as an alternative to traditional TH measurements used in growth modelling when corrected based on a limited sample of field-measured reference TH values. As the correction cannot be constant for each DAP dataset due to the different parameters during data acquisition, we propose a straightforward method for the bias correction of DAP-derived TH estimates. By undertaking iterative random sampling, we were able to find the minimum number of reference measurements needed to calculate the TH correction in order to achieve the desired accuracy of the TH estimations based on DAP. Here, we used ALS data as the reference data; however, the ALS measurements can be replaced by any other reliable source of TH values. The presented method for determining TH can be used not only for site index and forest growth modelling but also in forest inventories.

Effect of SARS-CoV-2 Infection on Incident Diabetes by Viral Variant: Findings From the National COVID Cohort Collaborative (N3C).

The coronavirus 2019 (COVID-19) pandemic has evolved over time by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, disease severity, treatment, and prevention. There is evidence of an elevated risk of incident diabetes after COVID-19; our objective was to evaluate whether this association is consistent across time and with contemporary viral variants. We conducted a retrospective cohort study using National COVID Cohort Collaborative (N3C) data to evaluate incident diabetes risk among COVID-positive adults compared with COVID-negative patients or control patients with acute respiratory illness (ARI). Cohorts were weighted on demographics, data site, and Charlson comorbidity index score. The primary outcome was the cumulative incidence ratio (CIR) of incident diabetes for each viral variant era. Risk of incident diabetes 1 year after COVID-19 was increased for patients with any viral variant compared with COVID-negative control patients (ancestral CIR 1.16 [95% CI 1.12-1.21]; Alpha CIR 1.14 [95% CI 1.11-1.17]; Delta CIR 1.17 [95% CI 1.13-1.21]; Omicron CIR 1.13 [95% CI 1.10-1.17]) and control patients with ARI (ancestral CIR 1.17 [95% CI 1.11-1.22]; Alpha CIR 1.14 [95% CI 1.09-1.19]; Delta CIR 1.18 [95% CI 1.11-1.26]; Omicron CIR 1.20 [95% CI 1.13-1.27]). There was latency in the timing of incident diabetes risk with the Omicron variant; in contrast with other variants, the risk presented after 180 days. Incident diabetes risk after COVID-19 was similar across different SARS-CoV-2 variants. However, there was greater latency in diabetes onset in the Omicron variant era.

Correction to: Modeling dominant height with USGS 3DEP LiDAR to determine site index in even-aged loblolly pine (Pinus taeda L.) plantations in the southeastern US

Correction to: Modeling dominant height with USGS 3DEP LiDAR to determine site index in even-aged loblolly pine (<i>Pinus taeda</i> L.) plantations in the southeastern US

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.

The Role of Blood Group in Cancer Risk: Correlations with Site, Age, and Body Mass Index

Background: Cancer is a complicated group of diseases in which cells grow and divide without being controlled. It is still one of the main reasons of death in the world, which presents major public health issues. Blood group links to cancer risk have been getting more and more attention over the past few years, among other things being studied. Aim of the study: This study aimed to assess the relation between ABO blood groups and the occurrence of different cancer types among the population of Kirkuk city. Patients and methods: This cross-sectional study was carried out in Kirkuk city from the period 15th October 2023 to 15th May 2024 on cancer patients of Kirkuk's Oncology and Hematology Centre. Data was collected from medical records and patient interviews to examine demographic characteristics, lifestyle factors, medical history, and potential exposures. The study included 398 patients diagnosed with cancer within a specified time frame, selected from medical records of healthcare facilities in the target area.. Blood samples were collected from each participant in the study for determination of blood group and Rh. Results: The study reveals that breast cancer is the most prevalent cancer, accounting for 45.98% of all cases. The study presents the distribution of cancer patients according to their blood groups, with O positive and A positive blood types accounting for the highest percentage at 33.67%. Other blood types such as B positive, AB positive, O negative, B negative, AB negative, and A negative are represented in smaller percentages ranging from 1.26% to 20.60%. The duration of cancer is examined in relation to blood groups, providing insights into mean durations across different ABO blood types and Rh factors. Blood type A exhibits the longest mean duration at 1.71 years, followed closely by blood type B at 1.74 years, while blood type O presents a slightly shorter mean duration at 1.52 years. In the current study, blood group A is predominantly seen in brain cancer for males (100%), with a considerable presence in digestive system cancers, split nearly evenly between males (41.94%) and females (58.06%). Blood group B appears infrequently but is represented in the digestive system and female reproductive cancers, demonstrating a minor presence compared to other groups. Skin cancer shows a potential link between blood group distribution and family history of the disease, suggesting a genetic predisposition or a significant association worth further investigation.

Eucalypt production in different rotations, sites and spatial arrangements

This work aimed to evaluate the productivity of eucalypt rotations in different site indexes and spatial arrangements. The database came from continuous forest inventories executed during the first and second rotations of 718 clonal stands (AEC 144®, AEC 224® and AEC 1528®), implanted in the 8.4 m2 plant−1 spacing and distributed in two arrangements: 3.0 × 2.8 m (rectangularity = 1.07) and 6.0 × 1.4 m (rectangularity = 4.29). Height, basal area, and volume differed between rotations as site quality improved and stands aged. In absolute terms, stands with lower site index, and installed under a larger rectangular arrangement showed less volume divergence between rotations. At 84 months of age, the first rotation of sites with the highest productive capacity tended to show 42.63 and 38.67 m3 ha−1 year−1 in smaller and larger rectangularity arrangements, respectively. The volumetric declines between the first and second rotations averaged 6.8 and 41.3 % at 84-month reference point, for arrangements of 6.0 × 1.4 m and 3.0 × 2.8 m, respectively. It is concluded that the less rectangular spatial arrangement (3.0 × 2.8 m) proved to be more productive for conducting a single rotation (high forest). Arrangement 6.0 × 1.4 m showed higher productive potential in stands managed with two rotations within the same cultivation cycle.

Study on the relationship between net primary productivity and site quality in Japanese larch plantations in mountainous areas of eastern Liaoning.

Plantation forests enhance carbon storage in terrestrial ecosystems in China. Larix kaempferi (Lamb.) Carrière (Lamb.) (Larix olgensis Henry) is the main species for afforestation in the eastern Liaoning Province. Therefore, it is important to understand the correlation between the site class and carbon sink potential of Larix kaempferi plantations in Liaoning Province for afforestation and carbon sink in this area. The model was fitted using three classical theoretical growth equations: the Richards model, the Korf model, and the Hossfeld model. This study used the forest resource inventory data for management in Liaoning Province in 2011 to build six dynamic height-age models for a Larix kaempferi plantation in Dandong City regardless of base-age. The optimal model derived by the generalized algebraic difference approach (GADA) method was compared with the model derived by the algebraic difference approach (ADA) method. The superiority of GADA was demonstrated by comparison. The Levenberg-Marquardt algorithm was used to fit the model. The statistical and biological characteristics were considered synthetically when comparing the models. The best model was screened out by statistical analysis and graphic analysis. The results show that the differential height-age model derived from Richards equation can well explain the growth process of Larix kaempferi in Dandong City, Liaoning Province under different conditions. The site index model based on Richards equation and derived by GADA was used to calculate the site class of a Larix kaempferi plantation in Dandong City. The net primary productivity (NPP) value from the past ten years was extracted from the MOD17A3HGF data set. Spearman correlation analysis and Kendall correlation analysis were used to show that there is a significant positive correlation between NPP value and site class of Larix kaempferi plantation in Dandong City. Among them, the highest growth occurred in 2016; NPP increased by about 3.914 gC/m2/year for every two increases in height-age grade; the lowest increase in NPP was in 2014; NPP increased by about 2.113 gC/m2/year for every two increases in height-age grade; and for every two increases in height-age grade in the recent ten years, the average NPP value increased by about 2.731 gC/m2/year.

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.

Bitemporal aerial laser scans as an alternative to site index estimation: A case study in the Bohemian Switzerland National Park

Abstract In this work, we present a study about the application of bi-temporal, large interval aerial laser scans for constructing of tree growth models and estimating site index quality based on the measured increments from the laser scans. We compared two LiDAR scans with 14 years of difference in the national park area, where most areas are unmanaged. We derived the increment curve based on the Chapman-Richard growth formula. We used site index estimates from forest management plans from the national scale as the ground truth (both absolute and relative). We constructed three predictive models for site index estimates from bi-temporal scans, in modalities with and without stand age. Including the stand age improved all models, but even without the age, the models performed relatively well for differentiation between better and worse sites. At this moment, it is not directly possible to estimate age from remotely sensed data, but consistent monitoring, with laser scanning or photogrammetry, undoubtedly detects the harvest or dieback, so in the future, age can be considered as a variable easily estimated from remotely sensed data and so remote sensed material are viable source for understanding of forest growth and production.

Response of leaf anatomical structure of Larix gmelinii to climate warming and provenance variation.

Exploring the response of leaf anatomical structure to climate warming is helpful for understanding the adaptive mechanisms of trees to climate change. We conducted a warming experiment by transplanting seedlings of Larix gmelinii from 11 provenances to two common gardens, and examined the response of leaf anatomical structure to climate warming. The results showed that warming significantly increased leaf thickness (TL), upper epidermal mesophyll thickness (TUEM), lower epidermal mesophyll thickness (TLEM), endodermal thickness (TE), vascular bundle diameter (DVB), transfer tissue thickness (TTT), and the percentage of mesophyll thickness to TL(PMT), and significantly decreased the upper epidermal thickness (TUE) and the percentage of epidermal thickness to TL (PE). The mesophyll thickness was positively associated with chlorophyll concentration and maximum net photosynthetic rate. The responses of TL, TUEM, TLEM, TE, DVB, TTT, TUE, PMT and PE to warming differed among all the provenances.As the aridity index of the original site increased, the magnitude of the warming treatment's effect decreased for TL, TUEM, TLEM, TTT and PMT, and increased for TUE and PE. Warming increased the thickness and proportion of profit tissue (e.g., mesophyll) and decreased the thickness and proportion of defensive tissue (e.g., epidermis), and those changes varied among provenances. L. gmelinii could adapt to climate warming by adjusting leaf anatomical structure, and this ability was weak for trees from provenance with high aridity index.

Relationships between site index modeling of crimean juniper and habitat factors

The aim of this study is to examine the relationships between height growth and some site factors of Crimean juniper in southwestern Anatolia. The data was collected from 130 sample plots selected from 10 districts in western Anatolia. The age and height of the Crimean juniper were measured in each sample plot. Surface soil samples collected from each sample plot were analyzed for pH, organic matter, carbonate content, texture, stoniness, available water capacity, wilting point, and field capacity. All site index values were calculated at a standard age of 100 years old. Spearman and Pearson correlation analyses were used to determine the relationships between plus tree and site factors. According to Spearman's correlation analysis, the site index showed a negative relationship with limestone. According to the results of the Pearson correlation analysis, the numerical variables LATTUD, SLOPE, SURSTON, and HINDEX had a 1% relationship with the site index, and RINDEX had a 5% relationship. Once the binary relationships had been determined, the multivariate relationships were modelled using generalized additive models. The best site index model was obtained using a generalized additive model 1 (R = 0.63), including latitude, longitude, altitude, slope, and stoniness.

Modeling dominant height with USGS 3DEP LiDAR to determine site index in even-aged loblolly pine (Pinus taeda L.) plantations in the southeastern US

Abstract Accurate quantification and mapping of forest productivity are critical to understanding and managing forest ecosystems. Local LiDAR or photogrammetric surveys have been used to obtain reliable estimates of canopy heights, yet these acquisitions can entail substantial expenses. Therefore, we developed models using freely available US Geological survey (USGS) LiDAR data for prediction of dominant height to map site index across loblolly pine (Pinus taeda L.) plantations in the southeastern US. We used 2017–2020 national USGS 3D Elevation Program LiDAR acquisitions and explored how different height percentiles, grid output resolutions, time difference between LiDAR and ground acquisitions, tree height, and dominant height definition affected the proposed model. We built the dominant height models using 1301 ground plots. The final regression model was constructed with the 95th percentile of the height distribution of the first returns above-ground and had values of R2 = 0.89, RMSE = 1.55 m, and RRMSE = 7.66 per cent at a 20-m pixel grid, yet all the examined percentile-resolution combinations were acceptable. No effect evidence was found for time difference when the flight was less than 4 months in advance or after the ground measurement, and it was also found independent of pulse density when this variable was lower than 9.5 pulses m−2. Using the recorded age of the plantations, we assessed the error propagation when translating dominant height to site index in two site index models, obtaining an RRMSE lower than 10 per cent in both. We found that USGS LiDAR acquisitions can be reliably used to map dominant height at a large scale, and consequently used to map forest productivity when age is known. This ability adds more value to a tool proven widely applicable in time and space and offers a great opportunity for stakeholders in different fields of use.