Advance Regeneration in the Inland West: Considerations for Individual Tree and Forest Health

2018 ◽  
pp. 411-422
Author(s):  
Dennis E. Ferguson
Keyword(s):  
Forest Health ◽  
Individual Tree ◽  
Advance Regeneration

Persistence of suppression effects on peatland black spruce advance regeneration after overstory removal

2000 ◽  
Vol 30 (5) ◽  
pp. 753-760 ◽  
Author(s):  
Arthur Groot ◽  
Hannu Hökkä
Keyword(s):  
Critical Points ◽  
Black Spruce ◽  
Basal Area ◽  
Growth Patterns ◽  
Diameter Growth ◽  
Individual Tree ◽  
Post Harvest ◽  
Advance Regeneration ◽  
Time Of Harvest ◽  
Suppression Effects

The persistence of suppression effects on peatland black spruce (Picea mariana (Mill.) BSP) advance regeneration following overstory removal was examined (i) by analyzing post-harvest growth patterns and (ii) by comparing observed post-harvest growth with predictions from an individual-tree growth model. Analysis of growth patterns revealed critical points (inflections or maxima) in annual basal area, diameter, and height growth series, and in specific volume increment. Critical points occurred at different times (ranging from 1 to 29 years after harvest) for different variables and often occurred earlier for trees with greater height at time of harvest. These critical points do not necessarily coincide with the cessation of persisting suppression, however, since post-harvest growth patterns also reflect current influences on growth. The comparison of observed basal area and diameter growth with model predictions isolated persisting suppression effects. The effects of suppression on basal area and diameter growth decline linearly with time since harvest and become negligible 12 years after harvest. The persistence of suppression effects on basal area and diameter growth is largely independent of the height of the tree at the time of harvest.

scholarly journals Assessment of Ponderosa Pine Vigor Using Four-Band Aerial Imagery in South Central Oregon: Crown Objects to Landscapes

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 612
Author(s):  
Charlie Schrader-Patton ◽  
Nancy Grulke ◽  
Craig Bienz
Keyword(s):  
Ponderosa Pine ◽  
Forest Health ◽  
Stand Density ◽  
Aerial Imagery ◽  
Individual Tree ◽  
South Central ◽  
Western Us ◽  
Moderate Drought ◽  
Wildfire Suppression ◽  
Gis Software

Ponderosa pine is an integral part of the forested landscape in the western US; it is the dominant tree species on landscapes that provide critical ecosystem services. Moderate drought tolerance allows it to occupy the transition zone between forests, open woodlands, and grasslands. Increases in stand density resulting from wildfire suppression, combined with lengthening, intensifying, and more frequent droughts have resulted in reduced tree vigor and stand health in dry ponderosa pine throughout its range. To address a management need for efficient landscape-level surveys of forest health, we used Random Forests to develop an object-oriented classification of individual tree crowns (ITCs) into vigor classes using existing, agency-acquired four-band aerial imagery. Classes of tree vigor were based on quantitative physiological and morphological attributes established in a previous study. We applied our model across a landscape dominated by ponderosa pine with a variety of forest treatments to assess their impacts on tree vigor and stand health. We found that stands that were both thinned and burned had the lowest proportion of low-vigor ITCs, and that stands treated before the 2014–2016 drought had lower proportions of low-vigor ITCs than stands treated more recently (2016). Upland stands had significantly higher proportions of low-vigor trees than lowland stands. Maps identifying the low-vigor ITCs would assist managers in identifying priority stands for treatment and marking trees for harvest or retention. These maps can be created using already available imagery and GIS software.

scholarly journals Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar

2019 ◽  
Vol 11 (21) ◽  
pp. 2540 ◽  
Author(s):  
Qinan Lin ◽  
Huaguo Huang ◽  
Jingxu Wang ◽  
Kan Huang ◽  
Yangyang Liu
Keyword(s):  
Forest Health ◽  
Pine Forests ◽  
Radiative Transfer Model ◽  
Tree Level ◽  
Lidar Data ◽  
Transfer Model ◽  
Combined Approach ◽  
Individual Tree ◽  
Pine Shoot Beetle ◽  
Individual Trees

In recent years, the outbreak of the pine shoot beetle (PSB), Tomicus spp., has caused serious shoots damage and the death of millions of trees in Yunnan pine forests in southwestern China. It is urgent to develop a convincing approach to accurately assess the shoot damage ratio (SDR) for monitoring the PSB insects at an early stage. Unmanned airborne vehicles (UAV)-based sensors, including hyperspectral imaging (HI) and lidar, have very high spatial and spectral resolutions, which are very useful to detect forest health. However, very few studies have utilized HI and lidar data to estimate SDRs and compare the predictive power for mapping PSB damage at the individual tree level. Additionally, the data fusion of HI and lidar may improve the detection accuracy, but it has not been well studied. In this study, UAV-based HI and lidar data were fused to detect PSB. We systematically evaluated the potential of a hyperspectral approach (only-HI data), a lidar approach (only-lidar data), and a combined approach (HI plus lidar data) to characterize PSB damage of individual trees using the Random Forest (RF) algorithm, separately. The most innovative point is the proposed new method to extract the three dimensional (3D) shadow distribution of each tree crown based on a lidar point cloud and the 3D radiative transfer model RAPID. The results show that: (1) for the accuracy of estimating the SDR of individual trees, the lidar approach (R2 = 0.69, RMSE = 12.28%) performed better than hyperspectral approach (R2 = 0.67, RMSE = 15.87%), and in addition, it was useful to detect dead trees with an accuracy of 70%; (2) the combined approach has the highest accuracy (R2 = 0.83, RMSE = 9.93%) for mapping PSB damage degrees; and (3) when combining HI and lidar data to predict SDRs, two variables have the most contributions, which are the leaf chlorophyll content (Cab) derived from hyperspectral data and the return intensity of the top of shaded crown (Int_Shd_top) from lidar metrics. This study confirms the high possibility to accurately predict SDRs at individual tree level if combining HI and lidar data. The 3D radiative transfer model can determine the 3D crown shadows from lidar, which is a key information to combine HI and lidar. Therefore, our study provided a guidance to combine the advantages of hyperspectral and lidar data to accurately measure the health of individual trees, enabling us to prioritize areas for forest health promotion. This method may also be used for other 3D land surfaces, like urban areas.

scholarly journals Assessment of Ponderosa Pine Vigor Using 4-Band Aerial Imagery in South Central Oregon: Crown Objects to Landscapes

2021 ◽  
Author(s):  
Charlie Schrader-Patton ◽  
Nancy Grulke ◽  
Craig Bienz
Keyword(s):  
Ponderosa Pine ◽  
Forest Health ◽  
Stand Density ◽  
Aerial Imagery ◽  
Individual Tree ◽  
South Central ◽  
Western Us ◽  
Moderate Drought ◽  
Wildfire Suppression ◽  
Gis Software

Ponderosa pine is an integral part of the forested landscape in the western US; it is the dominant tree species on landscapes that provide critical ecosystem services. Moderate drought tolerance allows it to occupy the transition zone between forests and open woodlands and grasslands. Increases in stand density resulting from wildfire suppression, combined with lengthening, intensifying and more frequent droughts have resulted in reduced tree vigor and stand health in dry ponderosa pine throughout its range. To address a management need for efficient landscape-level surveys of forest health, we used Random Forests to develop an object-oriented classification of individual tree crowns (ITCs) into vigor classes using existing, agency acquired 4-band aerial imagery. Classes of tree vigor were based on quantitative physiological and morphological attributes established in a previous study. We applied our model across a landscape dominated by ponderosa pine with a variety of forest treatments to assess their impacts on tree vigor and stand health. We found that stands that were both thinned and burned had the lowest proportion of low vigor ITCs, and that stands treated before the 2014-2016 drought had lower proportions of low vigor ITCs than stands treated more recently (2016). Upland stands had significantly higher proportions of low vigor trees than lowland stands. Maps identifying the low vigor ITCs would assist managers in identifying priority stands for treatment and marking trees for harvest or retention. These maps can be created using already available imagery and GIS software.

scholarly journals Monitoring Fine-Scale Forest Health Using Unmanned Aerial Systems (UAS) Multispectral Models

2021 ◽  
Vol 13 (23) ◽  
pp. 4873
Author(s):  
Benjamin T. Fraser ◽  
Russell G. Congalton
Keyword(s):  
Random Forest ◽  
Forest Health ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Unmanned Aerial Systems ◽  
Multispectral Imagery ◽  
Field Methods ◽  
Individual Tree ◽  
Management Actions ◽  
Aerial Systems

Forest disturbances—driven by pests, pathogens, and discrete events—have led to billions of dollars in lost ecosystem services and management costs. To understand the patterns and severity of these stressors across complex landscapes, there must be an increase in reliable data at scales compatible with management actions. Unmanned aerial systems (UAS or UAV) offer a capable platform for collecting local scale (e.g., individual tree) forestry data. In this study, we evaluate the capability of UAS multispectral imagery and freely available National Agricultural Imagery Program (NAIP) imagery for differentiating coniferous healthy, coniferous stressed, deciduous healthy, deciduous stressed, and degraded individual trees throughout a complex, mixed-species forests. These methods are first compared to assessments of crown vigor in the field, to evaluate the potential in supplementing this resource intensive practice. This investigation uses the random forest and support vector machine (SVM) machine learning algorithms to classify the imagery into the five forest health classes. Using the random forest classifier, the UAS imagery correctly classified five forest Health classes with an overall accuracy of 65.43%. Using similar methods, the high-resolution airborne NAIP imagery achieved an overall accuracy of 50.50% for the five health classes, a reduction of 14.93%. When these classes were generalized to healthy, stressed, and degraded trees, the accuracy improved to 71.19%, using UAS imagery, and 70.62%, using airborne imagery. Further analysis into the precise calibration of UAS multispectral imagery, a refinement of image segmentation methods, and the fusion of these data with more widely distributed remotely sensed imagery would further enhance the potential of these methods to more effectively and efficiently collect forest health information from the UAS instead of using field methods.

scholarly journals Assessment of Dothistroma Needle Blight of Pinus radiata Using Airborne Hyperspectral Imagery

2003 ◽  
Vol 93 (12) ◽  
pp. 1524-1532 ◽  
Author(s):  
N. Coops ◽  
M. Stanford ◽  
K. Old ◽  
M. Dudzinski ◽  
D. Culvenor ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Pinus Radiata ◽  
Accuracy Assessment ◽  
Forest Health ◽  
Aerial Survey ◽  
Individual Tree ◽  
Significant Relationships ◽  
South Wales ◽  
Dothistroma Needle Blight ◽  
Needle Blight

Dothistroma needle blight is a serious foliar disease in Australian Pinus radiata plantations causing defoliation, decreased productivity and, in extreme cases, tree death. Conventional methods of monitoring forest health such as aerial survey and ground assessments are labor intensive, time consuming, and subjective. Remote sensing provides a synoptic view of the canopy and can indicate areas affected by damaging agents such as pests and pathogens. Hyperspectral airborne remote sensing imagery (CASI-2) was acquired over pine stands in southern New South Wales, Australia which had been ground assessed and ranked on an individual tree basis, according to the extent of Dothistroma needle blight. A series of spectral indices were tested using two different approaches for extracting crown-scale reflectance measurements and relating these to ground-based estimates of severity. Dothistroma needle blight is most severe in the lower crown and statistically significant relationships were found between crown reflectance values and ground estimates using a ‘halo’ approach (which ignored each tree crown's brightest central pixels). Independent accuracy assessment of the method indicated that the technique could successfully detect three levels of Dothistroma needle blight infection with an accuracy of over 70%.

Commercial thinning stimulates natural regeneration in spruce–fir stands

2014 ◽  
Vol 44 (3) ◽  
pp. 173-181 ◽  
Author(s):  
Matthew G. Olson ◽  
Spencer R. Meyer ◽  
Robert G. Wagner ◽  
Robert S. Seymour
Keyword(s):  
Natural Regeneration ◽  
Tree Regeneration ◽  
Managed Forests ◽  
Individual Tree ◽  
Thinning Intensity ◽  
Advance Regeneration ◽  
Commercial Thinning ◽  
Individual Tree Growth ◽  
Spruce Stands ◽  
Large Size Class

Understanding the response of tree regeneration following commercial thinning treatments can improve planning in managed forests dependent on natural regeneration. We used long-term commercial thinning experiments in eastern spruce–fir stands of Maine, USA, to test two hypotheses: (1) commercial thinning increases the density of tree regeneration and (2) tree regeneration density increases with increasing thinning intensity. A decade after thinning, densities of softwood and hardwood regeneration were 10 times greater in thinned stands than unthinned stands. The abundance of small softwood (0.11–0.60 m tall) was highest in lower intensity thinning treatments, whereas medium (0.61–1.40 m tall) and large (≥1.41 m tall to 8.90 cm diameter at breast height) softwoods increased proportionally with thinning intensity, a pattern related to a higher rate of recruitment in more open stands created by heavier thinning. Hardwood density generally increased with thinning intensity and developed into a significant component of the large size class. Softwood regeneration density was higher in older spruce stands than younger fir stands, which may be due to greater abundance of advance regeneration, higher residual stand mortality, and greater harvest disturbance in older spruce stands. However, acceptable softwood stocking was achieved in all replicates of thinning treatments. Therefore, in addition to providing higher individual-tree growth and merchantable yield, commercial thinning in eastern spruce–fir stands also increases regeneration density. The rate of recruitment also increased as thinning intensity increased, thus stimulating understory regeneration similar to that of a shelterwood establishment cut.

Forest Management In Mongolia – A Review Of Challenges And Lessons Learned With Special Reference To Degradation And Deforestation

2019 ◽  
Vol 12 (3) ◽  
pp. 133-166 ◽  
Author(s):  
Alexander Gradel ◽  
Gerelbaatar Sukhbaatar ◽  
Daniel Karthe ◽  
Hoduck Kang
Keyword(s):  
Forest Management ◽  
Land Management ◽  
Management Practices ◽  
Forest Health ◽  
Hydrological Regime ◽  
Lessons Learned ◽  
Ecosystem Functions ◽  
Special Focus ◽  
Driven System ◽  
The Status

The natural conditions, climate change and socio-economic challenges related to the transformation from a socialistic society towards a market-driven system make the implementation of sustainable land management practices in Mongolia especially complicated. Forests play an important role in land management. In addition to providing resources and ecosystem functions, Mongolian forests protect against land degradation.We conducted a literature review of the status of forest management in Mongolia and lessons learned, with special consideration to halting deforestation and degradation. We grouped our review into seven challenges relevant to developing regionally adapted forest management systems that both safeguard forest health and consider socio-economic needs. In our review, we found that current forest management in Mongolia is not always sustainable, and that some practices lack scientific grounding. An overwhelming number of sources noticed a decrease in forest area and quality during the last decades, although afforestation initiatives are reported to have increased. We found that they have had, with few exceptions, only limited success. During our review, however, we found a number of case studies that presented or proposed promising approaches to (re-)establishing and managing forests. These studies are further supported by a body of literature that examines how forest administration, and local participation can be modified to better support sustainable forestry. Based on our review, we conclude that it is necessary to integrate capacity development and forest research into holistic initiatives. A special focus should be given to the linkages between vegetation cover and the hydrological regime.

Sign in / Sign up

Export Citation Format

Share Document