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Abstract This study aims to assess the spatio-temporal defoliation dynamics of box tree, one of the few evergreen species of the Hyrcanian Forests. For this, we integrated multi-temporal leaf-off optical Sentinel-2 and radar Sentinel-1 data from 2017 to 2021 with elevation data. A state-of-the-art sample migration approach was used to generate annual reference samples of two categories (defoliated and healthy box tree) for a set of target years 2017–2020. This approach is based on field samples of the reference year 2021 and two similarity measures, the Euclidean distance and the spectral angle distance. The analysis of spectral and radar profiles showed that the migrated samples were well representative of both defoliated and healthy box trees categories. The migrated samples were then used for spatially mapping the two classes using support vector machine classification. The results of support vector machine classification indicated a large extent of box tree mortality. The most significant changes from healthy box trees to defoliated ones, or vice versa, occurred during the years 2017 and 2018. In the consecutive years of 2019, 2020, and 2021, no significant changes in the distribution of healthy or defoliated box trees were observed. The statistical assessment also revealed that mortality of evergreen understory tree species can be mapped with practically sufficient overall accuracies reaching from 84% (in 2017) to 91%–92% (in 2020 and 2021) using spaceborne remote sensing data. This information using freely accessible satellite data can benefit forest managers responsible for monitoring landscapes affected by the box moth and facilitates the identification of optimal control programs.

Abstract Central Europe experienced severe droughts from 2018 to 2020, which led to bark beetle infestations in Norway spruce (Picea abies L.). While recent studies have identified these droughts as a major factor in the dieback of spruces, the exact mechanism through which drought stress influences spruce vitality and increases vulnerability to infestations is not well understood. To gain insights into the spatial and temporal relations between infestations and drought stress, this study compared soil moisture index (SMI) data for the entire soil layer from the German Drought Monitor and Sentinel-2 satellite time series for healthy and bark beetle infested spruce stands preceding the infestation. The study used t-tests to compare pre-infestation monthly sums of SMI and vegetation indices (VIs) for healthy and infested stands. Yearly trajectories of six VIs were used to compare the separability between infested and healthy plots. The results showed that the monthly sum values of SMI for healthy spruce plots were statistically significantly higher than the infested plots from May 2017 to January 2018, while the monthly sum values of Inverted Red Edge Chlorophyll Index of healthy spruce plots were significantly higher than infested plots during growing seasons. With these findings, the study provides useful information for the understanding of the relation of soil moisture and remote sensing VIs patterns in relation to bark beetle infestations.

Abstract Combining forest growth models with remotely sensed data is possible under a generalized hierarchical model-based (GHMB) inferential framework. This implies the existence of two submodels: the growth model itself ($\mathcal{M}_{1}$) and a second submodel that links the growth predictions to some remotely sensed variables ($\mathcal{M}_{2}$). Analytical GHMB estimators are available to fit submodel $\mathcal{M}_{2}$ and account for the uncertainty stemming from submodel $\mathcal{M}_{1}$, i.e. the growth model. However, when the growth model is individual based, it is usually too complex to be differentiated with respect to its parameters. As a result, the analytical GHMB estimators cannot be used. In this study, we developed a bootstrap approach for the GHMB inferential framework in order to combine individual-based forest growth models with remotely sensed data. Through simulation studies, we showed that the bootstrap estimators were nearly unbiased when both submodels were linear. The estimator of the parameter estimates remained nearly unbiased when submodel $\mathcal{M}_{1}$ became complex, i.e. non-differentiable, and submodel $\mathcal{M}_{2}$ was nonlinear with heterogeneous variances and correlated error terms. The variance estimator showed some biases but these were relatively small. We further demonstrated through a real-world case study that the predictions of a complex individual-based model could be linked to a Landsat-8 near-infrared spectral band in the boreal forest zone of Quebec, Canada.

Abstract The group selection cutting system provides a promising technique for transforming monospecific even-aged stands into uneven-aged, mixed stands. However, this system has scarcely been used to regenerate Mediterranean shade-intolerant species. In this study, we analyze the height increment patterns of Pinus pinaster seedlings emerging in naturally regenerated gaps. P. pinaster is a shade-intolerant pine species distributed throughout the Mediterranean basin. An experimental trial was established in a 50-year-old P. pinaster (maritime pine) plantation located in the mountains of central Spain. Gaps of two different sizes (diameter equal to 1.5 and 2.5 times the dominant height of the stand, 26 and 44 m, respectively) were opened during winter 2017–18. A total of 531 subplots with a 1-m radius were installed in spring 2018, distributed within the gaps as well as in control plots adjacent to the gaps. Seedlings were tagged individually and variables including height, along with other ecological variables, were collected twice a year (in spring and autumn), providing six time intervals for the development of our models. We applied seemingly unrelated regression to analyze the height growth in this polycyclic species, allowing us to model spring and autumn height increments at the same time. Our results showed that seedling height growth depended on the silvicultural treatment, meteorological conditions during the spring growth season, inter-specific scrub competition, position within the gap, and seedling characteristics, such as the ontogenetic development or the size of the seedling itself. This work, along with germination and survival analysis, aims to provide a holistic perspective on the suitability of the group selection cutting system to regenerate maritime pine stands, taking into account current and future climate change scenarios.

Abstract The Caledonian pinewoods of northern Scotland represent the remnants of once extensive forests found at the western edge of the natural range of Scots pine (Pinus sylvestris L.). The surviving pinewoods are of international significance and are of high conservation and cultural value. However, for many decades, there has been concern about their long-term future because of a lack of regenerating seedlings and young trees. This problem is thought to be driven by high deer populations resulting in intensive browsing and severe damage to young trees, as well as a lack of favourable micro-sites for seedling germination. An experiment was established on the Mar Lodge estate in 2007–08 adjacent to native pinewood stands to test the effects of protection and site cultivation upon seedling numbers and growth. The experiment was located within a regeneration zone where intensive deer control had reduced numbers to <5 animals km−2. Ten years after initiation, occurrence and numbers of both Scots pine and birch seedlings were substantially increased in cultivated treatments compared with uncultivated controls. There were no effects of protection upon seedling numbers. Protection improved height growth of Scots pine, but not of birch. Cultivation had no effect upon the growth of pine seedlings but did influence the height of birch seedlings due to the rapid growth of some pre-existing seedlings in the uncultivated control. Vegetation cover had increased from ~60%to at least 80% cover 6 years after cultivation. The results suggest that site cultivation may be desirable to boost seedling germination within a Caledonian pinewood, but sustained measures to control browsing pressure are a prerequisite for satisfactory establishment of these seedlings.

Abstract Over the last three decades, many growth and yield systems developed for the southeast USA have incorporated methods to create a compatible basal area (BA) prediction and projection equation. This technique allows practitioners to calibrate BA models using both measurements at a given arbitrary age, as well as the increment in BA when time series panel data are available. As a result, model parameters for either prediction or projection alternatives are compatible. One caveat of this methodology is that pairs of observations used to project forward have the same weight as observations from a single measurement age, regardless of the projection time interval. To address this problem, we introduce a variance–covariance structure giving different weights to predictions with variable intervals. To test this approach, prediction and projection equations were fitted simultaneously using an ad hoc matrix structure. We tested three different error structures in fitting models with (i) homoscedastic errors described by a single parameter (Method 1); (ii) heteroscedastic errors described with a weighting factor ${w}_t$ (Method 2); and (iii) errors including both prediction ($\overset{\smile }{\varepsilon }$) and projection errors ($\tilde{\varepsilon}$) in the weighting factor ${w}_t$ (Method 3). A rotation-age dataset covering nine sites, each including four blocks with four silvicultural treatments per block, was used for model calibration and validation, including explicit terms for each treatment. Fitting using an error structure which incorporated the combined error term ($\overset{\smile }{\varepsilon }$ and $\tilde{\varepsilon}$) into the weighting factor ${w}_t$ (Method 3), generated better results according to the root mean square error with respect to the other two methods evaluated. Also, the system of equations that incorporated silvicultural treatments as dummy variables generated lower root mean square error (RMSE) and Akaike’s index values (AIC) in all methods. Our results show a substantial improvement over the current prediction-projection approach, resulting in consistent estimators for BA.

Abstract Adaptive forest management gains importance as climate and disturbance regimes continue to change. Norway spruce monocultures are particularly vulnerable to those changes. Thus, there is a strong demand to convert pure spruce stands toward better adapted forest ecosystems. Silver fir has similar wood properties as Norway spruce, but is less vulnerable to droughts. Yet, little is known how to efficiently admix silver fir into Norway spruce monocultures. We analyzed seedling abundance in mature Norway spruce monocultures 1 year after soil scarification and silver fir seeding in a relatively dry region of southern Germany. Our objectives were to study the effect of soil scarification and seeding on regeneration density and to identify drivers of seedling abundance. We collected data on regeneration, forest structure, as well as soil and light conditions at 103 scarified and 25 untreated control plots. We used non-parametric independence tests to compare scarified and untreated plots. Subsequently, we used boosted regression trees to investigate the drivers of seedling abundance. Norway spruce strongly benefited from soil scarification (P < .001), with seedling numbers even exceeding those of silver fir. Both species thrived in soils with high plant available water capacity. In contrast, seedling numbers were overall negatively affected by light. Moreover, we found a higher density of silver fir regeneration at greater distance from neighboring trees and in soils devoid of carbonate. Our study indicates that water, not light, is the limiting factor for both Norway spruce and silver fir seedlings in the study region. Seeding silver fir will likely be most effective underneath an intact canopy on deep, fine-textured soils without carbonate, while maximizing the distance to Norway spruce trees. In conclusion, silver fir seeding can be optimized to become an effective adaptive measure to diversify Norway spruce monocultures, and thus to create more resistant and resilient forest ecosystems.

Abstract This study challenges a long-standing and often uncontested assertion in the forestry discourse that maximizing financial returns always requires ecologically simplified stands. We developed a high-resolution simulation tool for northern hardwood stands in eastern North America and integrated advanced numerical optimization methods to model the tree-level harvest decisions that maximize financial returns. We modeled each individual tree’s growth and its probability of natural mortality, conditioned on the evolving neighborhood-scale competitive environment it resides in. We developed size-, species-, and grade-specific price functions to assign potential harvest revenue values to each discrete bole section of each standing tree, and we used an evolutionary search algorithm to specify the financially optimal timing of tree-by-tree removals. We modeled three different case studies, representing a broad range of northern hardwood stand conditions, including a hypothetical 50-year-old, even-aged stand and two inventoried stands in northern New York, USA, with contrasting management histories. We observed consistent results across all three cases: maximizing financial returns from northern hardwood forests requires silvicultural finesse and results in ecologically complicated stands.

Abstract Modeling branch taper curve and form factor contributes to increasing the efficiency of tree crown reconstructions: the branch taper, defined as the sequential measure of diameters along the course of the branch, is pivotal to accurately estimate key branch variables such as biomass and volume. Branch diameters or volumes have commonly been estimated from terrestrial laser scanning (TLS) based on automatized voxelization or cylinder-fitting approaches, given the whole branch length is sufficiently covered by laser reflections. The results are, however, often affected by ample variations in point cloud characteristics caused by varying point density, occlusions, and noise. As these characteristics of TLS can hardly be sufficiently controlled or eliminated in automatized techniques, we proposed a new branch taper curve model and form factor, which can be employed directly from the laser reflections and under variable point cloud characteristics. In this paper, the approach is demonstrated on primary branches using a set of TLS-derived datasets from a sample of 20 trees (six species). The results showed an R2 of 0.86 and a mean relative absolute error of 1.03 cm (29%) when validated with field-measured diameters. The approach improved the accuracy of diameter estimates for the fine branch scales (<10 cm) as compared to the quantitative structural model (QSM). Our approach also allowed branch diameter estimation for a relatively larger number of manually recognized primary branches (>85%) from point clouds when validated with panoramic images acquired simultaneously with laser scanning. Frequently used automatized crown reconstructions from QSM, on the other hand, were affected by gaps in the point clouds due to obstruction, with the crown-tops and finer branches being the most critical. Our approach reports mean form factors across the examined species of 0.35 and 0.49, with the diameters determined at 5% and 10% of the total branch length, respectively. Our approach may have the potential to produce branch volume information with reasonable accuracy from only knowing the length and respective diameter of each branch. Our model delivers a first approximation for the taper curve and form factor for primary branches but was developed on a relatively small set of samples. We believe that our approach holds the potential to improve the accuracy of the assessment of branch diameter and volume from TLS data. The approach may also be extended to other branch orders. This could expand the horizon for volumetric calculations and biomass estimates from non-destructive TLS proxies in tree crowns.