Neighbourhood models are useful tools for understanding the role of positive and negative interactions in maintaining the tree species diversity in mixed forests. Under such a presumption, we aimed at testing several hypotheses concerning the mechanisms of autogenic species coexistence in an old-growth, beech-fir-spruce stand, which is part of the Slătioara forest reserve (eastern Carpathians). Univariate/bivariate spatial point pattern analyses, the individual tree species-area relationship, the species mingling analysis and generalised linear mixed models of neighbour interference were applied on data concerning the position and allometry of all saplings and trees occurring within a 0.24 ha plot.

The monospecific distribution of either beech or spruce saplings did not support the spatial segregation hypothesis. There was no evidence of conspecific negative distance dependence, as no spatial segregation was detected between the saplings and trees of any species. Within 4 m-neighbourhood, the beech saplings appeared as diversity accumulators, which might be indicative of indirect facilitation (e.g., herd protection hypothesis). At tree stage, none of the three species showed either accumulator or repeller patterns in their neighbourhood with respect to sapling species richness. Signals of positive and negative interspecific association were found in tree-sized beech (at scales of 10 to 20 m) and spruce (at scales of 4 to 17 m), respectively. The former, highly interspersed pattern is in accordance with the hypothesis of positive complementary effects, whereas the latter, poorly intermingled pattern is probably linked to the unexpected, positive neighbouring effect of spruce trees on the stem growth of their conspecific saplings. Such self-favouring process might be due to a facilitative below-ground mechanism. Conversely, the beech saplings were suppressed through interference from the neighbouring conspecific trees.

The beech appears to be the key promoter of tree species coexistence in the study forest stand, in contrast to the low interspersion of spruce in the overstorey leading to lower local tree diversity.

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Tree detection is the first step in the appraisal of a forest, especially when the focus is monitoring the growth of tree canopy. The acquisition of annual very high-resolution aerial images by the National Agriculture Imagery Program (NAIP) and their accessibility through Google Earth Engine (GEE) supports the delineation of tree canopies and change over time in a cost and time-effective manner. The objectives of this study are to develop an automated method to detect the crowns of individual western Juniper (Juniperus occidentalis) trees and to assess the change of forest cover from multispectral 1-meter resolution NAIP images collected from 2009 to 2016, in Oregon, USA. The Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Ratio Vegetation Index (RVI), were calculated from the NAIP images, in addition to the red-green-blue-near infrared bands. To identify the most suitable approach for individual tree crown identification, we created two training datasets: one considering yearly images separately and one merging all images, irrespective of the year. We segmented individual tree crowns using a random forest algorithm implemented in GEE and seven rasters, namely the reflectance of four spectral bands as recorded by the NAIP images (i.e., the red-green-blue-near infrared) and three calculated indices (i.e., NDVI, NDWI, and RVI). We compared the estimated location of the trees, computed as the centroid of the crown, with the visually identified treetops, which were considered as validation locations. We found that tree location errors were smaller when years were analyzed individually than by merging the years. Measurements of completeness (74%), correctness (94%), and mean accuracy detection (82 %) show promising performance of the random forest algorithm in crown delineation, considering that only four original input bands were used for crown segmentation. The change in the calculated crown area for western juniper follows a sinusoidal curve, with a decrease from 2011 to 2012 and an increase from 2012 to 2014. The proposed approach has the potential to estimate individual tree locations and forest cover area dynamics at broad spatial scales using regularly collected airborne imagery with easy-to-implement methods.

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Establishing a plantation with varied distances between trees is one way to control stand density. Understanding how stand growth patterns are influenced by initial spacing can help maximize growth and yield. The purpose of this study was to examine the long-term effects of different patterns of initial tree spacing on stand development. A spacing trial with 5 initial distances, namely, treatments I: 1×1 m, II: 2×2 m, III: 3×3 m, IV: 4×4 m and V: 5×5 m, was installed in 1950 on Japanese cedar (Cryptomeria japonica) plantations in central Taiwan, managed by the Experimental Forest of National Taiwan University. Each treatment had 3 repeated plots, and all the plots were surveyed from 1955 to 2014, with 8 records for each time series. We simultaneously employed 6 growth functions to predict stand basal area growth for each plot and assessed their predictability using the root mean square error (RMSE) as a criterion. Consequently, a total of 15 plots covering all the treatments, each with 6 RMSEs resulting from various models, were obtained. The repeated measures analysis of variance approach was adopted to compare predictability among models. The Richards growth function stood out from all the other models. As a result, this model was used to analyze stand development following different initial spacing. We found that the predicted curves could effectively exhibit the growth patterns resulting from different initial spacing. Moreover, the parameters help explain some characteristics of stand development, such as the growth potential and the maximum growth rate achieved (t_max). As a result, a clear trend emerged, showing that the growth potential increased, whereas the tmax decreased with decreasing initial spacing. These results provided valuable information for managing the stand density of this conifer.

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Objectives of this study were to compare transpiration of Anatolian black pine (Pinus nigra Arn. subsp. pallasiana (Lamb.) Holmboe) and sessile oak (Quercus petraea (Matt.) Liebl) tree stands and modelling stand transpiration based on the measured climatic factors. Stand transpirations were calculated from sap flow measurements made by the trunk heat balance method. Mean daily and yearly canopy transpirations (E_c) were 1.05 mm day^-1 and 378.3 mm year^-1 for the pine stand and 3.52 mm day^-1 and 801.7 mm year^-1 for the oak stand, respectively. There was a highly positive correlation between daily stand transpiration and wind speed, global radiation, air vapour pressure deficit and air temperature, but a negative correlation with relative humidity for both stands. Soil water potential had little effect on stand transpiration. We conducted an exploratory factor analysis (PCR) to detect effective meteorological factors of stand transpiration and to develop linear regression equations for predicting transpiration of pine and oak stands. The model equations accounted to 81% of the variations in transpiration for pine stand and 85% for oak stand. Transpiration of forest stands should be considered for effective vegetation management practices and the model equations can be used to estimate transpiration of pine and oak stands in the region.

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Thinning is a common silviculture technology in forestry, but there is considerable uncertainty about the changes of soil nutrients due to thinning practice in different aged forests. The influence of light thinning (reduction of 20% of stand density) on soil organic carbon (SOC) and other mineral elements (N, P, K, Cu, Fe, Zn, Mn and S), as well as soil pH and soil bulk density were investigated in 6-, 13-, and 23-year-old growth stands of Chinese fir forests in subtropical China. Six 10m ×10m plots (three thinning and three non-thinning plots) were set up in each aged forests. Soil samples were taken from different soil layers from these plots for nutrient analysis. Results showed that SOC increased 59.4, 48.9, and 62.0% in topsoil layer (0-30 cm) in 6, 13, and 23 year-old growth stands, respectively when compared to the control, and the content of N increased by 20.5, 44.6, and 54.1% corresponding after two year post-thinning. In the thinned forests, soil P slightly increased at 6- and 23 year-old growth forests dude to microclimates were improved, and K decreased because of leaching. The response of micronutrients Cu, Fe, Zn and Mn to thinning varied in all examined Chinese fir forests. Thinning decreased soil bulk density and soil pH in 6 and 23 year-old growth stands. Our study provided scientific references for sustainable management of soil nutrients under forest operations in Chinese fir forest ecosystem in subtropical China.

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