Explore the vast range of titles available.

This book identifies typical posture-related weaknesses that can impose limitations on a normally healthy functioning body. It then shows how to rectify these conditions by introducing the intricate body-mechanics and natural postures of Tai Chi.

For jack pine (Pinus banksiana Lamb.) and red pine (Pinus resinosa Aiton) forest types, the goal of this study was to develop and demonstrate enhanced climate-smart crop planning models that are capable of simultaneously addressing both conventional and evolving forest management objectives, i.e., volumetric yield, wood quality, carbon storage-based harvestable wood product (HWP) production, and biodiversity-driven deadwood accumulation objectives. Procedurally, this involved the following: (1) development and integration of species-specific cambial age prediction equations and associated integration of whole-stem fibre attribute prediction equation suites, previously developed for wood density (Wd), microfibril angle (Ma), modulus of elasticity (Me), fibre coarseness (Co), tracheid wall thickness (Wt), tracheid radial (Dr) and tangential (Dt) diameters, and specific surface area (Sa), into climate-sensitive structural stand density management models (SSDMMs); (2) modification of the computational pathway of the SSDMMs to enable the estimation of abiotic stem volume production; and (3) given (1) and (2), exemplifying the potential utility of the enhanced SSDMMs in operational crop planning. Analytically, to generate whole-stem attribute predictions and derive HWP estimates, species-specific hierarchical mixed-effects cambial age models were specified, parameterized, and statistically validated. The previously developed attribute equation suites along with the new cambial age models were then integrated within the species-specific SSDMMs. In order to facilitate the calculation of accumulated deadwood production arising from density-dependent (self-thinning) and density-independent (non-self-thinning) mortality, the computational pathways of the SSDMMs were augmented and modified. The utility of the resultant enhanced SSDMMs was then exemplified by generating and contrasting rotational volumetric yield, wood quality attribute property maps, quantity and quality (grade) of solid wood and non-solid wood HWPs, and deadwood production forecasts, for species–locale–RCP-specific crop plan sets. These analytical model-based innovations, along with the crop planning exemplifications, confirmed the adaptability and potential utility of the enhanced SSDMMs in mitigating the complexities of multiple criteria decision-making when managing jack pine and red pine forest types under climate change.

The objective of this study was to develop spatiotemporal whole-stem wood quality prediction models for a suite of end-product-based fibre attribute determinates for jack pine (Pinus banksiana Lamb.) and red pine (Pinus resinosa Aiton): specifically, for wood density (Wd), microfibril angle (Ma), modulus of elasticity (Me), fibre coarseness (Co), tracheid wall thickness (Wt), tracheid radial diameter (Dr), tracheid tangential diameter (Dt), and specific surface area (Sa). Procedurally, these attributes were determined for each annual ring within pith-to-bark xylem sequences extracted from 610 jack pine and 223 red pine cross-sectional disks positioned throughout the main stem of 61 jack pine and 54 red pine sample trees growing within even-aged monospecific stands in central Canada. Deploying a block cross-validation-like approach in order to reduce serial data dependency and enable predictive performance assessments, species-specific calibration and validation data subsets consisting of cumulative moving average values were systematically generated from the 27,820 jack pine and 11,291 red pine attribute-specific annual ring values. Graphical, correlation, regression and validation analyses were used to specify, parameterize and assess the predictive performance of tertiary-level (ring-disk-tree) hierarchical mixed-effects whole-stem equations for each attribute by species. As a result, the jack pine equations explained 46, 66, 74, 63, 59, 72, 42 and 48% of the variation in Wd, Ma, Me, Co, Wt, Dr, Dt and Sa, respectively. The red pine equations explained slightly higher levels of variation except for Me: 50, 71, 31, 83, 72, 78, 56 and 71% of the variation in Wd, Ma, Me, Co, Wt, Dr, Dt and Sa, respectively. Graphical assessments and statistical metrics related to attribute and species-specific residual error patterns and goodness-of-fit, lack-of-fit and predictive error metrics, revealed an absence of systematic bias, misspecification or aberrant predictive performance. Consequently, the resultant parameterized models were acknowledged as acceptable functional descriptors of the intrinsic spatiotemporal cumulative developmental patterns of the studied end-product fibre attribute determinates, for these two pine species. Although predicted development patterns were similar between the species with the greatest degree of nonlinearity occurring before a cambial age of approximately 30 years, irrespective of attribute, jack pine exhibited a greater degree of nonlinearity in the Wd and Dt developmental trajectories, whereas red pine exhibited a greater degree of nonlinearity in the Ma, Me, Co, Wt, Dr and Sa developmental trajectories. Potential biomechanical linkages underlying the observed attribute distribution patterns, as well as the potential utility of the models in forest management, are also discussed.

The primary objective of this study was to develop a climate-sensitive modular-based structural stand density management model (SSDMM) for red pine (Pinus resinosa Aiton) plantations situated within the western Great Lakes—St. Lawrence and south-central Boreal Forest Regions of Canada. For a given climate change scenario (e.g., representative concentration pathway (RCP)), geographic location (longitude and latitude), site quality (site index) and crop plan (e.g., initial espacement density and subsequent thinning treatments), the resultant hierarchical-based SSDMM consisting of six integrated modules, enabled the prediction of a multitude of management-relevant performance metrics over rotational lengths out to the year 2100. These metrics included productivity measures (e.g., mean annual volume, biomass and carbon increments), volumetric yield estimates (e.g., total and merchantable volumes), pole and log product distributions (e.g., number and size distribution of pulp and saw logs, and utility poles), biomass production and carbon sequestration outcomes (e.g., oven-dried masses of above-ground components and associated carbon mass equivalents), recoverable end-product volumes and associated monetary values (e.g., volumes and economic worth estimates of recovered chip and dimensional lumber products extractable via stud and randomized length mill processing protocols), and crop tree fibre attributes reflective of end-product potential (e.g., wood density, microfibril angle, and modulus of elasticity). The core modules responsible for quantifying stand dynamics and structural change were developed using 491 tree-list measurements and 146 stand-level summaries obtained from 98 remeasured permanent sample plots situated within 21 geographically separated plantation-based initial spacing and thinning experiments distributed throughout southern and north-central Ontario. Computationally, the red pine SSDMM and associated algorithmic analogue (1) produced mathematically compatible stem and end-product volume estimates, (2) accounted for density-dependent as well as density-independent mortality losses, response delay following thinning and genetic worth effects, (3) enabled end-users to specify merchantability standards (log and pole dimensions), product degrade factors and cost profiles, and (4) addressed climate change impacts on rotational yield outcomes by geo-referencing RCP-specific effects on stand dynamical processes via the deployment of a climate-driven biophysical site-based height-age model. In summary, the provision of the red pine SSDMM and its unique ability to account for locale-specific climate change effects on crop planning forecasts inclusive of utility pole production, should be of consequential utility as the complexities of silvicultural decision-making intensify during the Anthropocene.

The objectives of this study were to evaluate and exemplify the potential utility of a climate-sensitive modular-based structural stand density management model (SSDMM) developed for red pine (Pinus resinosa Aiton) in crop planning decision making. Firstly, the model’s predictive ability was assessed using a retrospective validation approach without consideration of climate change effects. Although limited in scope and applicability, the preliminary results revealed that the magnitude of the mean prediction error for the principal determinates governing stand development did not exceed ±15%. Secondly, the potential utility of the model was illustrated within a spatial-based forest management planning context for a range of climate change scenarios. These exemplifications included three conventional crop plan simulations (initial spacing (IS), IS plus one commercial thinning (CT) treatment, and IS plus two CTs) developing under three climate change scenarios (1971–2000 climate norms, and 4.5 and 8.5 representative concentration pathways) over 75-year rotations (2022–2097) at three geographically diverse locales (north-eastern (Kirkland Lake), north-central (Thessalon), and north-western (Thunder Bay) Ontario, Canada). Resultant developmental indices and (or) productivity metrics were contrasted in terms of (1) regional-specific differences in temporal stand dynamical patterns and rotational yields with increasing climatic change severity, and (2) silvicultural effectiveness of the crop plans within and across locales for each climate change scenario. Climate-wise, although the results revealed marginal regional differences across a multitude of rotational outcome metrics, declines in mean tree size and merchantable volume productivity, and most importantly utility pole production within unthinned plantations, were among the most consequential and consistent negative outcomes associated with climate-induced site productivity declines. Silviculturally, crop plans that included thinning treatments relative to their counterparts that did not, yielded trees of greater mean size and were able to maintain utility pole production status while not achieving similar levels of site occupancy or volumetric productivity. Management-wise, maintenance of pole production status along with concurrent increases in fiscal worth even in light of climate change outweighed the marginal decline in volumetric productivity that was associated with the thinning regimes. In summary, the validation results provided a measure of predictive performance relative to the underlying calibration data set whereas the exemplifications illustrated the model’s potential operational utility in spatial-based forest management planning. For managers aspiring to maintain the historical productivity legacy of red pine through optimal density management decision making while acknowledging prediction uncertainty when forecasting stand development trajectories under climate change, the SSDMM provides an optional decision-support tool for designing climate-smart crop plans during the Anthropocene.

A major reduction in global deforestation is needed to mitigate climate change and biodiversity loss. Recent private sector commitments aim to eliminate deforestation from a company’s operations or supply chain, but they fall short on several fronts. Company pledges vary in the degree to which they include time-bound interventions with clear definitions and criteria to achieve verifiable outcomes. Zero-deforestation policies by companies may be insufficient to achieve broader impact on their own due to leakage, lack of transparency and traceability, selective adoption and smallholder marginalization. Public–private policy mixes are needed to increase the effectiveness of supply-chain initiatives that aim to reduce deforestation. We review current supply-chain initiatives, their effectiveness, and the challenges they face, and go on to identify knowledge gaps for complementary public–private policies.

Purpose Flattening of rods is known to reduce the correction capability of the instrumentation, but has not been studied in 3D. The aim is to evaluate the rods shape 3D changes during and immediately after instrumentation, and its effect on 3D correction. Methods The 5.5 mm CoCr rods of 35 right thoracic adolescent idiopathic scoliosis patients were measured from rod tracings prior to insertion, and reconstructed in 3D from bi-planar radiographs taken intra-operatively after the correction maneuvers and 1 week post-operatively. The rod bending curvature, maximal deflection and orientation of the rod’s plane of maximum curvature (RPMC) were computed at each stage. The relation between rod contour, kyphosis and apical vertebral rotation (AVR) was assessed. Results Main thoracic Cobb angle was corrected from 58° ± 10° to 15° ± 8°. Prior to insertion, rods were more bent on the concave side (curvature/deflection: 39° ± 8°/25 ± 6 mm) than the convex side (26° ± 5°/17 ± 3 mm). Only the concave rod shape changed after the correction maneuvers execution (flattening of 21° ± 9°/13 ± 7 mm; p  < 0.001) and stayed unchanged post-operatively. After instrumentation, the RPMC was deviated from the sagittal plane (concave side: 27° ± 19°/convex side: 15° ± 12°). There was a significant association between kyphosis change and the relative concave rod to spine contour (rod curvature—pre-operative kyphosis) ( R 2  = 0.58) and between AVR correction and initial differential concave/convex rods deflection ( R 2  = 0.28). Conclusions Correction maneuvers induce a significant change of the concave rod profile. Both rods end in a plane deviated from the sagittal plane which is representative of the spinal curvature 3D orientation. Differential rod contouring technique has a significant impact on the resulting thoracic kyphosis and transverse plane correction.

Purpose Utilizing 2D measurements, previous studies have found that in AIS, increased thoracic Cobb and decreased thoracic kyphosis contribute to pulmonary dysfunction. Recent technology has improved our ability to measure and understand the true 3D deformity in AIS. The purpose of this study was to evaluate which 3D radiographic measures predict pulmonary dysfunction. Methods One hundred and sixty-three surgically treated AIS patients with preoperative PFTs (FEV, FVC, TLC) and EOS ® imaging were identified at a single center. Each spine was reconstructed in 3D to obtain the true coronal, sagittal, and apical rotational deformities. These were then correlated with the patient’s preoperative PFT measurements. Regression analysis was performed to determine the relative effect of each radiographic measure. Results There were 124 thoracic and 39 lumbar major curves. The range of preoperative thoracic and lumbar 3D coronal angle was 11–115° and 11–98°, respectively. The range of preoperative thoracic 3D kyphosis (T5–T12) and thoracic apical vertebral rotation was −56 to 44° and 0–29°, respectively. Increasing thoracic 3D Cobb and thoracic vertebral rotation and decreasing thoracic 3D kyphosis most significantly correlated with decreasing pulmonary function, especially FEV. In patients with the largest degree of thoracic deformity (3D Coronal Cobb > 80°, 3D thoracic lordosis >20°, and absolute apical rotation >25°), the majority of patients had moderate to severe pulmonary impairment (≤65 % predicted). 3D thoracic kyphosis was the most consistent predictor of FEV ( r 2  = 0.087), FVC ( r 2  = 0.069), and TLC ( r 2  = 0.098) impairment. Conclusions Larger thoracic coronal, sagittal, and axial deformities increase the risk of pulmonary impairment in patients with AIS. Of these, decreasing 3D thoracic kyphosis is the most consistent predictor. This information can guide surgeons in the decision making process for determining which surgical techniques to utilize and which component of the deformity to focus on.

The objectives of this study were to develop a stand density management decision-support software suite for boreal conifers and demonstrate its potential utility in crop planning using practical deployment exemplifications. Denoted CPDSS (CroPlanner Decision-support Software Suite), the program was developed by transcribing algorithmic analogues of structural stand density management diagrams previously developed for even-aged black spruce (Picea mariana (Mill) BSP.) and jack pine (Pinus banksiana Lamb.) stand-types into an integrated software platform with shared commonalities with respect to computational structure, input requirements and generated numerical and graphical outputs. The suite included 6 stand-type-specific model variants (natural-origin monospecific upland black spruce and jack pine stands, mixed upland black spruce and jack pine stands, and monospecific lowland black spruce stands, and plantation-origin monospecific upland black spruce and jack pine stands), and 4 climate-sensitive stand-type-specific model variants (monospecific upland black spruce and jack pine natural-origin and planted stands). The underlying models which were equivalent in terms of their modular structure, parameterization analytics and geographic applicability, were enabled to address a diversity of crop planning scenarios when integrated within the software suite (e.g., basic, extensive, intensive and elite silvicultural regimes). Algorithmically, the Windows® (Microsoft Corporation, Redmond, WA, USA) based suite was developed by recoding the Fortran-based algorithmic model variants into a collection of VisualBasic.Net® (Microsoft Corporation, Redmond, WA, USA) equivalents and augmenting them with intuitive graphical user interfaces (GUIs), optional computer-intensive optimization applications for automated crop plan selection, and interactive tabular and charting reporting tools inclusive of static and dynamic stand visualization capabilities. In order to address a wide range of requirements from the end-user community and facilitate potential deployment within provincially regulated forest management planning systems, a participatory approach was used to guide software design. As exemplified, the resultant CPDSS can be used as an (1) automated crop planning searching tool in which computer-intensive methods are used to find the most appropriate precommercial thinning, commercial thinning and (or) initial espacement (spacing) regime, according to a weighted multivariate scoring metric reflective of attained mean tree size, operability status, volumetric productivity, and economic viability, and a set of treatment-related constraints (e.g., thresholds regarding intensity and timing of thinning events, and residual stocking levels), as specified by the end-user, or (2) iterative gaming-like crop planning tool where end-users simultaneously contrast density management regimes using detailed annual and rotational volumetric yield, end-product and ecological output measures, and (or) an abbreviated set of rotational-based performance metrics, from which they determine the most applicable crop plan required for attaining their specified stand-level objective(s). The participatory approach, modular computational structure and software platform used in the formulation of the CPDSS along with its exemplified utility, collectively provides the prerequisite foundation for its potential deployment in boreal crop planning.