The influence of forest stand characteristics on snow interception in the coastal forests of British Columbia

1988 ◽  
Vol 18 (5) ◽  
pp. 566-573 ◽  
Author(s):  
R. Scott McNay ◽  
Leslie D. Peterson ◽  
J. Brian Nyberg
Keyword(s):  
Snow Depth ◽  
Forest Canopy ◽  
Basal Area ◽  
Related Phenomenon ◽  
Linear Regression Models ◽  
Coastal Forests ◽  
Winter Habitat ◽  
Independent Variables ◽  
Fresh Snow ◽  
Stand Characteristics

The capability of forest stands to intercept snow is an important factor in determining management prescriptions for such hydrologically related phenomenon as avalanches, floods, and water supply as well as suitability for ungulate winter habitat. This study tested the hypothesis that snow interception can be predicted as a function of various stand characteristics and storm sizes. The dependent variable was fresh snow depth under the forest canopy; the independent variables were crown completeness, crown length, crown width, basal area per hectare, tree height, tree density, and storm size. Ten stands were selected for study from two locations on Vancouver Island. Snow depth was monitored over 24 storms ranging from 1.4 to 38.0 cm. The best simple linear regression models that incorporated forest variables were those for individual storms, with fresh snow expressed as a function of mean crown completeness. The best assessments of a particular stand's capability to intercept snow were made using an equation with both storm size and mean crown completeness as independent variables.

scholarly journals A Study on the Prediction of Daily Snowmelt Depth using Multiple Linear Regression

2020 ◽  
Vol 20 (6) ◽  
pp. 311-321
Author(s):  
YeoungRok Oh ◽  
Gyumin Lee ◽  
Kyung Soo Jun ◽  
Wooyeon Sunwoo ◽  
SeungWoo Baek ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Snow Depth ◽  
Meteorological Data ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Fresh Snow ◽  
Humidity Range

In this study, daily snowmelt was predicted using observed meteorological data and multiple regression analysis. Five observation stations (located in Daegwallyeong, Gwangju, Seosan, Mokpo, and Jeonju) were selected to analyze fresh snow depth from 2000 to 2010. The dependent variable used in the multiple regression analysis was daily snowmelt depth, and the independent variables were fresh snow depth, diurnal temperature range, temperature interception, diurnal humidity range, humidity intercept, and solar radiation. Seventy percent of the total observed data was used to develop a multiple regression model and the regression model was verified using the 30% of remaining data. The adjusted R-squared and Root Mean Square Deviation (RMSE) were used to examine the developed regression model. As a result, the adjusted R-squared was higher than 0.769 (except Daegwallyeong); thus the developed model represented well the daily snowmelt depth. Even Jeonju had an adjusted R-squared of 0.869. Also, the RMSE in all of the five stations was lower than 2.5 cm. The lowest value in Seosan was 1.7 cm. From the two types of verification, the developed multiple regression model was judged to be suitable to predict the daily snowmelt depth. However, multicollinearity should be explained, as rapid increases in temperature and sustained high temperature could not be reflected in the model. Therefore, if the limitations were resolved in further research, the model could be used to predict the amount of daily snowmelt depth more reliably.

Prédiction de la composition corporelle post-mortem de cerfs de Virginie (Odocoileus virginianus) à partir de mesures morphologiques et massiques

1997 ◽  
Vol 75 (11) ◽  
pp. 1790-1795 ◽  
Author(s):  
Chantal Bois ◽  
Michel Crête ◽  
Jean Huot ◽  
Jean-Pierre Quellet
Keyword(s):  
Odocoileus Virginianus ◽  
Regression Models ◽  
Carcass Composition ◽  
Chemical Analyses ◽  
Linear Regression Models ◽  
Mass Measurements ◽  
Composition Corporelle ◽  
Independent Variables ◽  
Multiple Linear Regression Models ◽  
Field Stations

Morphologic and mass measurements were taken on 24 complete white-tailed deer (Odocoileus virginianus) carcasses of varying ages and both sexes in southern Quebec. Each carcass was divided into three parts (skin, viscera, rest) to determine water, protein, fat, and ash content by chemical analyses. Fat content of carcasses varied between 0.8 and 17.4%. Multiple linear regression models were selected to predict carcass composition from morphologic and mass measurements. Two situations were considered: measurements taken at the laboratory on whole animals and measurements taken at field stations on eviscerated carcasses provided by hunters. All selected models can be applied to any deer without taking into account age or sex; they include 1 – 4 independent variables. For whole animals, adjusted R2 of models varied between 0.99 (water) and 0.89 (ash); models developed for field stations were less precise, the lowest R2 values being 0.82 and 0.73 for ash and fat, respectively. These models can be useful for research and management purposes.

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

scholarly journals Factors affecting spirometry reference range in growing children

2019 ◽  
Vol 35 (6) ◽  
Author(s):  
Sara Sadiq ◽  
Nadeem Ahmed Rizvi ◽  
Fahad Khalid Soleja ◽  
Muaz Abbasi
Keyword(s):  
Reference Range ◽  
Forced Expiratory Volume ◽  
P Value ◽  
Strong Positive Correlation ◽  
Linear Regression Models ◽  
Factors Affecting ◽  
Independent Variables ◽  
Creative Commons ◽  
Forced Expiratory Flow ◽  
Expiratory Flow

Objectives: To find out the association of weight, height and age with spirometry variables and to generate a regression equation by taking weight as an independent variable beside age and height among children and adolescents of Karachi. Methods: A modified form of ISSAC questionnaire was used. The spirometry variables recorded were Forced vital capacity (FVC), Forced expiratory volume in 1 second (FEV1), FEV1/FVC, Peak expiratory flow rate (PEF), Forced expiratory flow between 25% and 75% expired volume (FEF25-75). A person’s correlation coefficient among boys and girls were calculated for all spirometry variable considering age, height and weight as independent variables. The linear regression models were calculated. Results: The results reported a linear correlation of lung function variables with all three independent variables (i.e. p-value = 0.000), in which age and height manifested a strong positive correlation while weight reported a moderately significant correlation. All spirometry variables such as FVC, FEV1, PEF and FEF25-75 reported a significant coefficient of dependency and coefficient of correlation individually with age, height and weight. Conclusion: It is concluded that beside age, height and weight both also have significant correlation with lung volumes so these should be taken into account when using spirometry as a diagnostic test. doi: https://doi.org/10.12669/pjms.35.6.1212 How to cite this:Sadiq S, Rizvi NA, Soleja FK, Abbasi M. Factors affecting spirometry reference range in growing children. Pak J Med Sci. 2019;35(6):1587-1591. doi: https://doi.org/10.12669/pjms.35.6.1212 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Relationships among burn severity, forest canopy structure and bat activity from spring burns in oak–hickory forests

2017 ◽  
Vol 26 (11) ◽  
pp. 963 ◽  
Author(s):  
Michael J. Lacki ◽  
Luke E. Dodd ◽  
Nicholas S. Skowronski ◽  
Matthew B. Dickinson ◽  
Lynne K. Rieske
Keyword(s):  
Laser Scanning ◽  
Forest Canopy ◽  
Management Practice ◽  
Canopy Structure ◽  
Forest Stand ◽  
Burn Severity ◽  
Prescribed Fires ◽  
Insectivorous Bats ◽  
Conflicting Objectives ◽  
Stand Characteristics

The extent to which prescribed fires affect forest structure and habitats of vertebrate species is an important question for land managers tasked with balancing potentially conflicting objectives of vegetation and wildlife management. Many insectivorous bats forage for insect prey in forested habitats, serving as the primary predators of nocturnal forest insects, and are potentially affected by structural changes in forests resulting from prescribed fires. We compared forest-stand characteristics of temperate oak–hickory forests, as measured with airborne laser scanning (light detection and ranging, LiDAR), with categorical estimates of burn severity from prescribed fires as derived from Landsat data and field-based Composite Burn Indices, and used acoustic monitoring to quantify activity of insectivorous bats in association with varying degrees of burn severity (unburned habitat, low severity and medium severity). Forest-stand characteristics showed greatest separation between low-severity and medium-severity classes, with gap index, i.e. open-air space, increasing with degree of burn severity. Greater mid-storey density, over-storey density and proportion of vegetation in the understorey occurred in unburned habitat. Activity of bats did not differ with burn severity for high-frequency (clutter-adapted or closed-space foragers) or low-frequency (edge or open-space foragers) bats. Results indicate that differing degrees of burn severity from prescribed fires produced spatial variation in canopy structure within stands; however, bats demonstrated no shifts in activity levels to this variation in canopy structure, suggesting prescribed fire during the dormant season, used as a management practice targeting desired changes in vegetation, is compatible with sustaining foraging habitat of insectivorous bats.

scholarly journals Immediate and Delayed Effects of Severe Winds on an Old-Growth Forest in Kentucky: A Forty-Year Retrospective

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 271 ◽  
Author(s):  
Susan Jones-Held ◽  
Michael Held ◽  
Joe Winstead ◽  
William Bryant
Keyword(s):  
Sugar Maple ◽  
Forest Canopy ◽  
Basal Area ◽  
The United States ◽  
Tree Regeneration ◽  
Forest Recovery ◽  
Total Density ◽  
Old Growth Forest ◽  
Long Term Studies

Wind disturbance is an important factor that can affect the development of the forests of the Central Hardwood Region of the United States. However, there have been few long-term studies of the recovery of these systems following wind damage. Long-term studies of protected forest systems, such as Dinsmore Woods in Northern Kentucky, within the fragmented forest of this region are valuable as they provide a resource to document and understand the effect of both abiotic and biotic challenges to forest systems. This study is a 40-year analysis of both overstory and understory changes in the forest system at Dinsmore Woods as the result of damage caused by severe winds in the spring of 1974. The forest was surveyed before and immediately following the windstorm and then at 10-year intervals. Although the windstorm had an immediate effect on the forest, the pattern of damage was complex. The forest canopy (diameter at breast height (DBH) ≥ 30 cm) experienced an irregular pattern of damage while in the subcanopy (DBH ≤ 30 cm) there was a 25% reduction in total basal area. However, the major effects of the windstorm were delayed and subsequently have altered forest recovery. Ten years following the disturbance declines were seen in total density and basal area in the canopy and subcanopy of the forest as a consequence of windstorm damage. In the past 20 years the total basal area of the canopy has increased and exceeds the pre-disturbance total basal area. In contrast, the subcanopy total basal area continued to decline 20 years post-disturbance and has not recovered. Further openings in the canopy and subcanopy due to the delayed windstorm effects helped to establish a dense understory of native shrubs and sugar maple which have affected tree regeneration and is reflected in the continual decline in species diversity in the subcanopy and sapling strata over the 40-year period.

Potential of UltraCamX stereo images for estimating timber volume and basal area at the plot level in mixed European forests

2013 ◽  
Vol 43 (8) ◽  
pp. 731-741 ◽  
Author(s):  
Christoph Straub ◽  
Christoph Stepper ◽  
Rudolf Seitz ◽  
Lars T. Waser
Keyword(s):  
Point Cloud ◽  
Forest Canopy ◽  
Complex Structure ◽  
Mixed Forest ◽  
Basal Area ◽  
Deciduous Tree ◽  
Stereo Images ◽  
Timber Volume ◽  
European Forests ◽  
Forest Attributes

Current technical advances in the field of digital photogrammetry demonstrate the great potential of automatic image matching for deriving dense surface measurements of the forest canopy. In contrast to airborne laser scanning (ALS), aerial stereo images are updated more regularly by national or regional mapping agencies in several countries. Frequently, ALS-based terrain models (DTMs) are available, and thus photogrammetric canopy heights can be derived. However, currently, there is little knowledge as to how accurately forest attributes can be modeled using the aerial stereo images acquired by these official, regular aerial surveys, especially for mixed forests in central Europe. Thus, a photogrammetric point cloud derived from UltraCamX stereo images in combination with an ALS-DTM and a classification of coniferous and deciduous tree regions (based on orthoimages) was used to create a stratified estimation of timber volume and basal area in a mixed forest in Germany. Suitable models were derived at the plot level using explanatory variables from the photogrammetric point cloud (which was normalized using an ALS-DTM). The prior stratification of conifer- and deciduous-dominated field plots slightly improved the estimation accuracy. The results verify that stereo images can be an alternative to ALS data for modeling key forest attributes, even in mixed central European forests with complex structure.

Relationships between tree crown, stem, and stand characteristics in unthinned loblolly pine plantations

1987 ◽  
Vol 17 (6) ◽  
pp. 534-538 ◽  
Author(s):  
Peter T. Sprinz ◽  
Harold E. Burkhart
Keyword(s):  
Loblolly Pine ◽  
Basal Area ◽  
Projection Area ◽  
Diameter Growth ◽  
Tree Crown ◽  
Basal Area Growth ◽  
Area Growth ◽  
Mean Diameter ◽  
Stand Attributes ◽  
Stand Characteristics

Empirical and theoretical relationships between tree crown, stem, and stand characteristics for unthinned stands of planted loblolly pine (Pinustaeda L.) were investigated. Readily measured crown variables representing the amount of photosynthetic area or distance of the translocation process were identified. Various functions of these variables were defined and evaluated with regard to efficacy in predicting stem and stand attributes. Linear models were used to evaluate the contribution of the crown variables in predicting stem and stand characteristics. The stem attributes modeled included basal area, basal area growth, diameter at breast height, and diameter growth, while the stand attributes modeled were basal area, basal area growth, arithmetic mean diameter, and mean diameter growth. Crown diameter and crown projection area were particularly important in contributing to model fit and prediction of individual stem characteristics, while sum of crown projection areas was found especially important in stand level equations. As these crown measures developed over time so did corresponding stem and stand attributes.

A self-perpetuating bamboo disturbance cycle in a neotropical forest

2006 ◽  
Vol 22 (5) ◽  
pp. 587-597 ◽  
Author(s):  
Bronson W. Griscom ◽  
P. Mark S. Ashton
Keyword(s):  
Forest Canopy ◽  
Basal Area ◽  
Size Class ◽  
Tree Canopy ◽  
Physical Damage ◽  
Tree Form ◽  
Madre De Dios ◽  
Neotropical Forest ◽  
The Impact ◽  
Canopy Damage

We investigate a hypothesis for explaining maintenance of forest canopy dominance: bamboo (Guadua weberbaueri and Guadua sarcocarpa) loads and crushes trees, resulting in a self-perpetuating disturbance cycle. Forest inventory data revealed a peculiar pattern of tree form and size class distribution in bamboo-dominated plots within the Tambopata River watershed, Madre de Dios, Peru. Bamboo disproportionately loaded trees 5–29 cm in diameter, and this size class had over seven times more canopy damage than trees in control plots without bamboo. These differences were accompanied by reduced tree basal area and tree density in the 5–29-cm-diameter size class in the presence of bamboo. Elevated tree canopy damage was not apparent for trees ≥30 cm dbh, which are beyond the reach of bamboo. Additional evidence for the impact of bamboo was revealed by an experiment using artificial metal trees. Artificial trees in bamboo-dominated forest plots had nine times higher frequency of physical damage and nine times more plant mass loading as compared with control plots. Our results support the hypothesis that bamboo loading causes elevated physical damage to trees and suppresses tree recruitment, particularly for trees 5–29 cm in diameter.

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