Overcoming data sparseness and parametric constraints in modeling of tree mortality: a new nonparametric Bayesian model

Accurately describing patterns of tree mortality is central to understanding forest dynamics and is important for both management and ecological inference. However, for many tree species, annual survival of most individuals is high, so that mortality is rare and, therefore, difficult to estimate. Furthermore, tree mortality models have potentially complex suites of covariates. Here, we extend traditional and recent approaches to modeling tree mortality and propose a new nonparametric Bayesian method. Our model is constrained to both reflect and distinguish known relationships between mortality and its two key covariates, diameter and diameter increment growth, but it remains sufficiently flexible to capture a wide variety of patterns of mortality across these covariates. Our model also allows incorporation of outside information in the form of priors, so that increased mortality of large trees can always be formally modeled even when data are sparse. We present results for our nonparametric Bayesian mortality model for maple ( Acer spp.), holly ( Ilex spp.), sweet gum ( Liquidambar styraciflua L.), and tulip-poplar ( Liriodendron tulipifera L.) populations from North Carolina, USA.

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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 ◽

10.1186/s42408-020-00082-0 ◽

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.

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Biases in the estimation of size-dependent mortality models: advantages of a semiparametric approach

Canadian Journal of Forest Research ◽

10.1139/x09-047 ◽

2009 ◽

Vol 39 (8) ◽

pp. 1430-1443 ◽

Cited By ~ 13

Author(s):

Ghislain Vieilledent ◽

Benoît Courbaud ◽

Georges Kunstler ◽

Jean-François Dhôte ◽

James S. Clark

Keyword(s):

Mortality Rate ◽

Picea Abies ◽

Abies Alba ◽

Mortality Data ◽

Strongly Nonlinear ◽

Semiparametric Approach ◽

Mortality Models ◽

Large Trees ◽

Parametric Functions ◽

Related Mortality

Mortality rate is thought to show a U-shape relationship to tree size. This shape could result from a decrease of competition-related mortality as diameter increases, followed by an increase of senescence and disturbance-related mortality for large trees. Modeling mortality rate as a function of diameter is nevertheless difficult, first because this relationship is strongly nonlinear, and second because data can be unbalanced, with few observations for large trees. Parametric functions, which are inflexible and sensitive to the distribution of observations, tend to introduce biases in mortality rate estimates. In this study we use mortality data for Abies alba Mill. and Picea abies (L.) Karst. to demonstrate that mortality rate estimates for extreme diameters were biased when using classical parametric functions. We then propose a semiparametric approach allowing a more flexible relationship between mortality and diameter. We show that the relatively shade-tolerant A. alba has a lower annual mortality rate (2.75%) than P. abies (3.78%) for small trees (DBH <15 cm). Picea abies, supposedly more sensitive to bark beetle attacks and windthrows, had a higher mortality rate (up to 0.46%) than A. alba (up to 0.30%) for large trees (DBH ≥50 cm).

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An Individual-Tree Mortality Model for Complex Stands of Southeastern British Columbia

Western Journal of Applied Forestry ◽

10.1093/wjaf/20.2.101 ◽

2005 ◽

Vol 20 (2) ◽

pp. 101-109 ◽

Cited By ~ 17

Author(s):

Hailemariam Temesgen ◽

Stephen J. Mitchell

Keyword(s):

British Columbia ◽

Tree Species ◽

Tree Mortality ◽

Model Development ◽

Mortality Rates ◽

Average Deviation ◽

Individual Tree ◽

Permanent Sample Plots ◽

Diameter Increment ◽

Mortality Model

Abstract An individual-tree mortality model was developed for major tree species in complex stands (multi-cohort, multiaged, and mixed species) of southeastern British Columbia (BC), Canada. Data for 29,773 trees were obtained from permanent sample plots established in BC. Average annual diameter increment and mortality rates ranged from 0.08 to 0.17 cm/year and from 0.3 to 2.6%, respectively. Approximately 70% of the trees were used for model development and 30% for model evaluation. After evaluating the model, all 29,773 trees were used to fit the final model. A generalized logistic model was used to relate mortality to tree size, competition, and relative position of trees in a stand. The evaluation test demonstrated that the model appears to be well behaved and robust for the tree species considered in this study. For the eight tree species, the average deviation between observed and predicted annual mortality rates varied from −0.5 to 0.7% in the test data. West. J. Appl. For. 20(2):101–109.

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Feedback loop dominance analysis of two tree mortality models: relationship between structure and behavior

Tree Physiology ◽

10.1093/treephys/27.2.269 ◽

2007 ◽

Vol 27 (2) ◽

pp. 269-280 ◽

Cited By ~ 16

Author(s):

B. Guneralp ◽

G. Gertner

Keyword(s):

Feedback Loop ◽

Tree Mortality ◽

Dominance Analysis ◽

Mortality Models ◽

And Behavior

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Tree mortality: Large trees losing out to drought

Nature Plants ◽

10.1038/nplants.2015.150 ◽

2015 ◽

Vol 1 (10) ◽

Cited By ~ 1

Author(s):

Michael G. Ryan

Keyword(s):

Tree Mortality ◽

Large Trees

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Pertumbuhan Riap Diameter Pohon Bakau Kurap (Rhizophora Mucronata) Di Lampung Mangrove Center

Jurnal Sylva Lestari ◽

10.23960/jsl3497-106 ◽

2016 ◽

Vol 4 (3) ◽

pp. 97 ◽

Cited By ~ 1

Author(s):

Robbi Angger Kesuma ◽

Asihing Kustanti ◽

Rudi Hilmanto

Keyword(s):

Time Series ◽

Key Words ◽

Growth Models ◽

Permanent Plots ◽

Rhizophora Mucronata ◽

Estimation Model ◽

Control Block ◽

Stand Growth ◽

Diameter Increment ◽

Increment Growth

Bakau kurap (R. mucronata) is a true mangrove. The height of this mangrove could reach 27 m and rarely exceed 30 m. The diameter trunk of this mangrove could reach 70 cm. R. mucronata stands was found in Lampung Mangrove Center (LMC), it was located in Margasari Village district Labuhan Maringgai, East Lampung Regency. The purposes of this study were to determine the diameter increment, growth models and stand growth past of R. mucronata at LMC. The research was conducted on July to August 2015. The method used measurement of diameter time series for three years (2013, 2014, and 2015) on circle form permanent plots with a radius 7 m of length are divided into three thinning blocks (A, B, and C). Block C was the control block or block that was not thinned and large thinning in blocks A and B, respectively 54.5% and 41.7%. The results indicated that the biggest diameter increment of three block at the age of 22nd years = 0.467 cm year-1. The estimation model of stand diameter (D) and diameter increment (MAI-d) based on the age of stand (X) could be formulated as follows: 1) Blok A D = 8,996 X0,021; MAI-d = 0,451 X0,035, 2) Blok B D = 8,215 X0,124; MAI-d = 0,412 X0,039, 3) Blok C D = 7,159 X0,074; MAI-d = 0,359 X(-0,012). Forecasting growth stands diameter R. mucronata age of 32nd years on the blocks A, B and C in a row were 10,280cm, 9,463cm, and 7,796cm while the diameter increment were 0,467cm, 0,430cm, and 0,354cm. Key words : Diameter increment, forecasting, Lampung Mangrove Center, Rhizophora mucronata

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How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession?

Forest Ecology and Management ◽

10.1016/j.foreco.2018.11.042 ◽

2019 ◽

Vol 433 ◽

pp. 606-617 ◽

Cited By ~ 9

Author(s):

Marco Vanoni ◽

Maxime Cailleret ◽

Lisa Hülsmann ◽

Harald Bugmann ◽

Christof Bigler

Keyword(s):

Tree Ring ◽

Tree Mortality ◽

Forest Succession ◽

Inventory Data ◽

Mortality Models

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Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes

Biogeosciences ◽

10.5194/bg-15-3377-2018 ◽

2018 ◽

Vol 15 (11) ◽

pp. 3377-3390 ◽

Cited By ~ 16

Author(s):

Victoria Meyer ◽

Sassan Saatchi ◽

David B. Clark ◽

Michael Keller ◽

Grégoire Vincent ◽

...

Keyword(s):

Forest Structure ◽

Aboveground Biomass ◽

Tree Mortality ◽

Forest Disturbance ◽

Basal Area ◽

Selective Logging ◽

Tree Canopy ◽

Crown Area ◽

Large Trees ◽

Canopy Area

Abstract. Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (∼ 25–30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha−1, bias = −0.63 Mg ha−1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA–AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.

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