scholarly journals Generalized or general mixed-effect modelling of tree morality of Larix gmelinii subsp. principis-rupprechtii in Northern China

2021 ◽  
Author(s):  
Xiao Zhou ◽  
Liyong Fu ◽  
Ram P. Sharma ◽  
Peng He ◽  
Yuancai Lei ◽  
...  
Keyword(s):  
Tree Mortality ◽  
Basal Area ◽  
Northern China ◽  
Mixed Effects ◽  
Larix Gmelinii ◽  
Important Species ◽  
Dummy Variable ◽  
Dominant Height ◽  
Mortality Models ◽  
Mean Diameter

AbstractTree mortality models play an important role in predicting tree growth and yield, but existing mortality models for Larix gmelinii subsp. principis-rupprechtii, an important species used for regeneration and afforestation in northern China, have overlooked potential regional influences on tree mortality. This study used data acquired from 102 temporary sample plots (TSPs) in natural stands of Prince Rupprecht larch in the state-owned Guandi Mountain Forest (n = 67) and state-owned Boqiang Forest (n = 35) in northern China. To model stand-level tree mortality, we compared seven model forms of county data. Three continuous (dominant height, plot mean diameter, and basal area per hectare) and one dummy variable with two levels (region) were used as fixed effects variables. Tree morality variations caused by forest blocks were accounted for using forest blocks as a random effect in selected models. Results showed that tree mortality significantly positively correlated with stand basal area and dominant height, but negatively correlated with stand mean diameter. Incorporating both the dummy variables and random effects into the tree mortality models significantly increased the fitting improvements, and Hurdle Poisson mixed-effects model showed the most attractive fit statistics (largest R2 and smallest RMSE) when employing leave-one-out cross-validation. These mixed-effects dummy variable models will be useful for accurately predicting Larix tree mortality in different regions.

scholarly journals Basal area growth models for Eucalyptus tereticornis Smith stands on the Colombian Atlantic coast

2020 ◽  
Vol 26 (2) ◽  
Author(s):  
Alonso Barrios-Trilleras ◽  
Ana Milena López-Aguirre
Keyword(s):  
Goodness Of Fit ◽  
Prediction Models ◽  
Growth Models ◽  
Basal Area ◽  
Eucalyptus Tereticornis ◽  
Competition Index ◽  
Important Species ◽  
Dominant Height ◽  
Basal Area Growth ◽  
Area Growth

Eucalyptus tereticornis is an important species used in reforestation programs in Colombia. Information on the dynamics and development of the E. tereticornis stands is required to improve management planning. This study compares nine basal area growth models, evaluating their goodness of fit and prediction, and describes their linkage to a thinning response model for E. tereticornis plantations. The evaluated models showed a good fit to the data, the R2adj ranged between 0.90 - 0.92 and 0.69 - 0.86 for the basal area projection and prediction models, respectively. The root of the mean square error (RMSE) ranged between 1.080 m2 ha-1 - 1.343 m2 ha-1 for basal area projection models and 1.671 m2 ha-1 - 2.206 m2 ha-1 for basal area prediction models. The selected basal area model for unthinned stands depends on the age, stand density, and dominant height. For the thinned stands, the basal area was predicted using a competition index that depends on the age and the dominant height of the stand. The competition index had an R2adj = 0.87, and a standard error of estimate of 0.031%. The system of equations presented a slight tendency to overestimate with a mean error of -0.14 m2 ha-1 and a RMSE of 0.696 m2 ha-1. This way, the developed models have the potential to be applied to unthinned and thinned stands with different ages, productivity, and planting densities. The developed models provide new tools to support forest management and research of the species growing in plantations.

scholarly journals A large database supports the use of simple models of post-fire tree mortality for thick-barked conifers, with less support for other species

Fire Ecology ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
C. Alina Cansler ◽  
Sharon M. Hood ◽  
Phillip J. van Mantgem ◽  
J. Morgan Varner
Keyword(s):  
Tree Mortality ◽  
Characteristic Curve ◽  
Small Diameter ◽  
Fire Effects ◽  
Tree Level ◽  
Clear Understanding ◽  
Bark Thickness ◽  
Mortality Models ◽  
Species Specific ◽  
Stem Mortality

Abstract Background Predictive models of post-fire tree and stem mortality are vital for management planning and understanding fire effects. Post-fire tree and stem mortality have been traditionally modeled as a simple empirical function of tree defenses (e.g., bark thickness) and fire injury (e.g., crown scorch). We used the Fire and Tree Mortality database (FTM)—which includes observations of tree mortality in obligate seeders and stem mortality in basal resprouting species from across the USA—to evaluate the accuracy of post-fire mortality models used in the First Order Fire Effects Model (FOFEM) software system. The basic model in FOFEM, the Ryan and Amman (R-A) model, uses bark thickness and percentage of crown volume scorched to predict post-fire mortality and can be applied to any species for which bark thickness can be calculated (184 species-level coefficients are included in the program). FOFEM (v6.7) also includes 38 species-specific tree mortality models (26 for gymnosperms, 12 for angiosperms), with unique predictors and coefficients. We assessed accuracy of the R-A model for 44 tree species and accuracy of 24 species-specific models for 13 species, using data from 93 438 tree-level observations and 351 fires that occurred from 1981 to 2016. Results For each model, we calculated performance statistics and provided an assessment of the representativeness of the evaluation data. We identified probability thresholds for which the model performed best, and the best thresholds with either ≥80% sensitivity or specificity. Of the 68 models evaluated, 43 had Area Under the Receiver Operating Characteristic Curve (AUC) values ≥0.80, indicating excellent performance, and 14 had AUCs <0.7, indicating poor performance. The R-A model often over-predicted mortality for angiosperms; 5 of 11 angiosperms had AUCs <0.7. For conifers, R-A over-predicted mortality for thin-barked species and for small diameter trees. The species-specific models had significantly higher AUCs than the R-A models for 10 of the 22 models, and five additional species-specific models had more balanced errors than R-A models, even though their AUCs were not significantly different or were significantly lower. Conclusions Approximately 75% of models tested had acceptable, excellent, or outstanding predictive ability. The models that performed poorly were primarily models predicting stem mortality of angiosperms or tree mortality of thin-barked conifers. This suggests that different approaches—such as different model forms, better estimates of bark thickness, and additional predictors—may be warranted for these taxa. Future data collection and research should target the geographical and taxonomic data gaps and poorly performing models identified in this study. Our evaluation of post-fire tree mortality models is the most comprehensive effort to date and allows users to have a clear understanding of the expected accuracy in predicting tree death from fire for 44 species.

scholarly journals A Dynamic Stand Growth Model System for Loblolly Pine Responding to Mid-Rotation Treatments

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 556
Author(s):  
Mauricio Zapata-Cuartas ◽  
Bronson P. Bullock ◽  
Cristian R. Montes ◽  
Michael B. Kane
Keyword(s):  
Growth Model ◽  
Loblolly Pine ◽  
Basal Area ◽  
Model System ◽  
Growth And Yield ◽  
Site Quality ◽  
Response To Treatment ◽  
Plantation Management ◽  
Vegetation Control ◽  
Dominant Height

Intensive loblolly pine (Pinus taeda L.) plantation management in the southeastern United States includes mid-rotation silvicultural practices (MRSP) like thinning, fertilization, competitive vegetation control, and their combinations. Consistent and well-designed long-term studies considering interactions of MRSP are required to produce accurate projections and evaluate management decisions. Here we use longitudinal data from the regional Mid-Rotation Treatment study established by the Plantation Management Research Cooperative (PMRC) at the University of Georgia across the southeast U.S. to fit and validate a new dynamic model system rooted in theoretical and biological principles. A Weibull pdf was used as a modifier function coupled with the basal area growth model. The growth model system and error projection functions were estimated simultaneously. The new formulation results in a compatible and consistent growth and yield system and provides temporal responses to treatment. The results indicated that the model projections reproduce the observed behavior of stand characteristics. The model has high predictive accuracy (the cross-validation variance explained was 96.2%, 99.7%, and 98.6%; and the prediction root mean square distance was 0.704 m, 19.1 trees ha−1, and 1.03 m2ha−1 for dominant height (DH), trees per hectare (N), and basal area (BA), respectively), and can be used to project the current stand attributes following combinations of MRSP and with different thinning intensities. Simulations across southern physiographic regions allow us to conclude that the most overall ranking of MRSP after thinning is fertilization + competitive vegetation control (Fert + CVC) > fertilization only (Fert) > competitive vegetation control only (CVC), and Fert + CVC show less than additive effect. Because of the model structure, the response to treatment changes with location, age of application, and dominant height growth as indicators of site quality. Therefore, the proposed model adequately represents regional growth conditions.

scholarly journals Laurel Wilt: Current and Potential Impacts and Possibilities for Prevention and Management

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 181
Author(s):  
Rabiu O. Olatinwo ◽  
Stephen W. Fraedrich ◽  
Albert E. Mayfield
Keyword(s):  
United States ◽  
Tree Mortality ◽  
The United States ◽  
Persea Americana ◽  
Laurel Wilt ◽  
Important Species ◽  
Invasive Insects ◽  
Raffaelea Lauricola ◽  
Redbay Ambrosia Beetle ◽  
The Impact

In recent years, outbreaks of nonnative invasive insects and pathogens have caused significant levels of tree mortality and disturbance in various forest ecosystems throughout the United States. Laurel wilt, caused by the pathogen Raffaelea lauricola (T.C. Harr., Fraedrich and Aghayeva) and the primary vector, the redbay ambrosia beetle (Xyleborus glabratus Eichhoff), is a nonnative pest-disease complex first reported in the southeastern United States in 2002. Since then, it has spread across eleven southeastern states to date, killing hundreds of millions of trees in the plant family Lauraceae. Here, we examine the impacts of laurel wilt on selected vulnerable Lauraceae in the United States and discuss management methods for limiting geographic expansion and reducing impact. Although about 13 species belonging to the Lauraceae are indigenous to the United States, the highly susceptible members of the family to laurel wilt are the large tree species including redbay (Persea borbonia (L.) Spreng) and sassafras (Sassafras albidum (Nutt.) Nees), with a significant economic impact on the commercial production of avocado (Persea americana Mill.), an important species native to Central America grown in the United States. Preventing new introductions and mitigating the impact of previously introduced nonnative species are critically important to decelerate losses of forest habitat, genetic diversity, and overall ecosystem value.

Modelling tree mortality across diameter classes using mixed-effects zero-inflated models

2018 ◽  
Vol 31 (1) ◽  
pp. 131-140 ◽  
Author(s):  
Yang Li ◽  
Xingang Kang ◽  
Qing Zhang ◽  
Weiwei Guo
Keyword(s):  
Tree Mortality ◽  
Mixed Effects ◽  
Diameter Classes

Inoptimality losses in forest management decisions caused by errors in an inventory based on airborne laser scanning and aerial photographs

2010 ◽  
Vol 40 (12) ◽  
pp. 2427-2438 ◽  
Author(s):  
Md. Nurul Islam ◽  
Mikko Kurttila ◽  
Lauri Mehtätalo ◽  
Timo Pukkala
Keyword(s):  
Input Data ◽  
Laser Scanning ◽  
Basal Area ◽  
Airborne Laser Scanning ◽  
Aerial Photographs ◽  
Stand Age ◽  
Inventory Data ◽  
Airborne Laser ◽  
Mean Diameter ◽  
The Mean

Errors in inventory data may lead to inoptimal decisions that ultimately result in financial losses for forest owners. We estimated the expected monetary losses resulting from data errors that are similar to errors in laser-based forest inventory. The mean loss was estimated for 67 stands by simulating 100 realizations of inventory data for each stand with errors that mimic those in airborne laser scanning (ALS) based inventory. These realizations were used as input data in stand management optimization, which maximized the present value of all future net incomes (NPV). The inoptimality loss was calculated as the difference between the NPV of the optimal solution and the true NPV of the solution obtained with erroneous input data. The results showed that the mean loss exceeded €300·ha–1 (US$425·ha–1) in 84% of the stands. On average, the losses increased with decreasing stand age and mean diameter. Furthermore, increasing errors in the basal area weighted mean diameter and basal area of spruce were found to significantly increase the loss. It has been discussed that improvements in the accuracy of ALS-based inventory could be financially justified.

scholarly journals Tree mortality in the dynamics and management of uneven-aged Norway spruce stands in southern Finland

2020 ◽  
Vol 139 (6) ◽  
pp. 989-998
Author(s):  
Sauli Valkonen ◽  
Lucie Aulus Giacosa ◽  
Juha Heikkinen
Keyword(s):  
Tree Mortality ◽  
Stand Structure ◽  
Basal Area ◽  
Repeated Measurements ◽  
Common Causes ◽  
Single Tree Selection ◽  
Spruce Stands ◽  
Causes Of Mortality ◽  
Number Of Stems ◽  
Adverse Influence

Abstract This study focused on tree mortality in spruce-dominated stands managed using the single-tree selection method in southern Finland. Together with regeneration and tree growth, mortality is one of the basic elements of the stand structure and dynamics in selection stands. The study was based on data acquired from a set of 20 permanent experimental plots monitored with repeated measurements for 20 years. The average mortality in the number of stems (N) was 4.45 trees ha−1a−1, in basal area (G) 0.07 m2 ha−1a−1, and in stemwood volume (V) 0.56 m3 ha−1a−1. In relative terms it was 0.50% of N, 0.30% of G and 0.27% of V, respectively. Wind and snow were the most common causes of mortality, while deaths by biotic causes (mammals, insects, pathogens) were extremely rare. Some 6–10% of the total loss in the number of stems and volume was attributable to the loss or removal of trees that sustained serious damage in harvesting. Most of the mortality occurred in the smallest diameter classes of up to 20 cm. Such a high mortality among small trees can have an adverse influence on the sustainability of selection structures if not successfully checked in harvesting and management.

scholarly journals Tree Mortality Following Mixed-Severity Prescribed Fire Dramatically Alters the Structure of a Developing Pinus taeda Forest on the Mid-Atlantic Coastal Plain

Fire ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 25 ◽  
Author(s):  
David G. Ray ◽  
Deborah Landau
Keyword(s):  
Loblolly Pine ◽  
Prescribed Fire ◽  
Tree Mortality ◽  
Basal Area ◽  
Growing Season ◽  
Pine Forest ◽  
Atlantic Coastal Plain ◽  
Relative Reduction ◽  
Stem Density ◽  
Horizontal Structure

This case study documents the aftermath of a mixed-severity prescribed fire conducted during the growing season in a young loblolly pine forest. The specific management objective involved killing a substantial proportion of the overstory trees and creating an open-canopy habitat. The burn generated canopy openings across 26% of the 25-ha burn block, substantially altering the horizontal structure. Mortality of pines was high and stems throughout the size distribution were impacted; stem density was reduced by 60% and basal area and aboveground biomass (AGB) by ~30% at the end of the first growing season. A nonlinear regression model fit to plot data portrays a positive relationship between high stocking (i.e., relative density > 0.60) and postburn mortality. Survival of individual trees was reliably modeled with logistic regression, including variables describing the relative reduction in the size of tree crowns following the burn. Total AGB recovered rapidly, on average exceeding levels at the time of the burn by 23% after six growing seasons. Intentional mixed-severity burning effectively created persistent canopy openings in a young fire-tolerant precommercial-sized pine forest, meeting our objectives of structural alteration for habitat restoration.

Sign in / Sign up

Export Citation Format

Share Document