Optimisation of tree mortality models based on growth patterns

2006 ◽  
Vol 197 (1-2) ◽  
pp. 196-206 ◽  
Author(s):  
Jan Wunder ◽  
Christof Bigler ◽  
Björn Reineking ◽  
Lorenz Fahse ◽  
Harald Bugmann
Keyword(s):  
Tree Mortality ◽  
Growth Patterns ◽  
Mortality Models

Growth-dependent tree mortality models based on tree rings

2003 ◽  
Vol 33 (2) ◽  
pp. 210-221 ◽  
Author(s):  
Christof Bigler ◽  
Harald Bugmann
Keyword(s):  
Norway Spruce ◽  
Tree Mortality ◽  
Time Windows ◽  
Growth Patterns ◽  
Linear Regression Models ◽  
Growth Trends ◽  
Mortality Model ◽  
Recent Growth ◽  
Mortality Models ◽  
The Impact

Mortality is a crucial element of population dynamics. However, tree mortality is not well understood, particularly at the individual level. The objectives of this study were to (i) determine growth patterns (growth levels and growth trends) over different time windows that can be used to discriminate between dead and living Norway spruce (Picea abies (L.) Karst.) trees, (ii) optimize the selection of growth variables in logistic mortality models, and (iii) assess the impact of competition on recent growth in linear regression models. The logistic mortality model that we developed for mature stands classified an average of nearly 80% of the 119 trees from one site correctly as being dead or alive. While more than 50% of the variability of recent growth of living trees can be attributed to the influence of competition, this percentage was only 25% for standing dead trees. The predictive power of the logistic mortality model was validated successfully at two additional sites, where 29 of 41 (71%) and 34 of 42 (81%) trees were classified correctly, respectively. This supports the generality of the mortality model for Norway spruce in subalpine forests of the Alps. We conclude that growth trends in addition to the commonly used growth level significantly improve the prediction of growth-dependent tree mortality of Norway spruce.

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 synthesis of radial growth patterns preceding tree mortality

2016 ◽  
Vol 23 (4) ◽  
pp. 1675-1690 ◽  
Author(s):  
Maxime Cailleret ◽  
Steven Jansen ◽  
Elisabeth M. R. Robert ◽  
Lucía Desoto ◽  
Tuomas Aakala ◽  
...  
Keyword(s):  
Radial Growth ◽  
Tree Mortality ◽  
Growth Patterns

scholarly journals Radial Growth Patterns Associated with Tree Mortality in Nothofagus pumilio Forest

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 489 ◽  
Author(s):  
Milagros Rodríguez-Catón ◽  
Ricardo Villalba ◽  
Ana Srur ◽  
A. Park Williams
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Forest Dynamics ◽  
Radial Growth ◽  
Tree Mortality ◽  
Growth Patterns ◽  
Severe Drought ◽  
Nothofagus Pumilio ◽  
Total Size ◽  
Growth Trends

Tree mortality is a key process in forest dynamics. Despite decades of effort to understand this process, many uncertainties remain. South American broadleaf species are particularly under-represented in global studies on mortality and forest dynamics. We sampled monospecific broadleaf Nothofagus pumilio forests in northern Patagonia to predict tree mortality based on stem growth. Live or dead conditions in N. pumilio trees can be predicted with high accuracy using growth rate as an explanatory variable in logistic models. In Paso Córdova (CO), Argentina, where the models were calibrated, the probability of death was a strong negative function of radial growth, particularly during the six years prior to death. In addition, negative growth trends during 30 to 45 years prior to death increased the accuracy of the models. The CO site was affected by an extreme drought during the summer 1978–1979, triggering negative trends in radial growth of many trees. Individuals showing below-average and persistent negative trends in radial growth are more likely to die than those showing high growth rates and positive growth trends in recent decades, indicating the key role of droughts in inducing mortality. The models calibrated at the CO site showed high verification skill by accurately predicting tree mortality at two independent sites 76 and 141 km away. Models based on relative growth rates showed the highest and most balanced accuracy for both live and dead individuals. Thus, the death of individuals across different N. pumilio sites was largely determined by the growth rate relative to the total size of the individuals. Our findings highlight episodic severe drought as a triggering mechanism for growth decline and eventual death for N. pumilio, similar to results found previously for several other species around the globe. In the coming decades, many forests globally will be exposed to more frequent and/or severe episodes of reduced warm-season soil moisture. Tree-ring studies such as this one can aid prediction of future changes in forest productivity, mortality, and composition.

Tectonic influences on tree growth in northern Patagonia, Argentina: the roles of substrate stability and climatic variation

1995 ◽  
Vol 25 (10) ◽  
pp. 1684-1696 ◽  
Author(s):  
Thomas Kitzberger ◽  
Thomas T. Veblen ◽  
Ricardo Villalba
Keyword(s):  
Tree Ring ◽  
Tree Growth ◽  
Tree Mortality ◽  
Synergistic Effects ◽  
Climatic Variation ◽  
Growth Patterns ◽  
Great Earthquake ◽  
Northern Patagonia ◽  
South Central ◽  
Substrate Stability

In northern Patagonia, Argentina, we examined the influences of climatic variation and inter-site variation in substrate stability on the dendroecological effects of earthquakes. In association with the great earthquake in 1960 centered off the coast of nearby Valdivia, Chile, extensive tree mortality occurred in northern Patagonia in Nothofagusdombeyi–Austrocedruschilensis stands on unstable debris fans. To examine the effects of the 1960 and earlier earthquakes on tree growth, we developed tree-ring chronologies from samples of the surviving A. chilensis on unstable debris fan sites and at adjacent nonfan sites of more stable substrates. For controlling the effects of regional climatic variation, we also produced a tree-ring chronology from this species in a more distant and undisturbed stand. Strong variations in tree-growth patterns on fan sites were associated with the historically documented major seismic events of south central Chile that occurred in 1737, 1751, 1837, and 1960. Tree-ring chronologies from nonfan sites (i.e., sites of greater substrate stability) showed much less response to these earthquakes. On the fan sites, strong growth suppressions were associated with the former three earthquakes, whereas strong releases followed the 1960 earthquake. The difference in response is explained by the occurrence of the 1960 earthquake during a period of drought, which in combination with the violent shaking of the ground, resulted in extensive tree mortality followed by growth releases of the survivors. However, severe droughts in the absence of earthquakes also can produce tree mortality and subsequent release of the survivors. Consequently, the synergistic effects of climatic variation and earthquake events must be carefully considered in developing records of both climatic variation and earthquakes.

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

2019 ◽  
Vol 433 ◽  
pp. 606-617 ◽  
Author(s):  
Marco Vanoni ◽  
Maxime Cailleret ◽  
Lisa Hülsmann ◽  
Harald Bugmann ◽  
Christof Bigler
Keyword(s):  
Tree Ring ◽  
Tree Mortality ◽  
Forest Succession ◽  
Inventory Data ◽  
Mortality Models

scholarly journals Climatic information improves statistical individual-tree mortality models for three key species of Sichuan Province, China

2015 ◽  
Vol 72 (4) ◽  
pp. 443-455 ◽  
Author(s):  
Shuai Qiu ◽  
Ming Xu ◽  
Renqiang Li ◽  
Yunpu Zheng ◽  
Daniel Clark ◽  
...  
Keyword(s):  
Tree Mortality ◽  
Sichuan Province ◽  
Individual Tree ◽  
Mortality Models ◽  
Key Species ◽  
Climatic Information

scholarly journals Towards a common methodology for developing logistic tree mortality models based on ring-width data

2016 ◽  
Vol 26 (6) ◽  
pp. 1827-1841 ◽  
Author(s):  
Maxime Cailleret ◽  
Christof Bigler ◽  
Harald Bugmann ◽  
Jesús Julio Camarero ◽  
Katarina Cˇufar ◽  
...  
Keyword(s):  
Tree Mortality ◽  
Ring Width ◽  
Mortality Models

Improving tree mortality models by accounting for environmental influences

2007 ◽  
Vol 37 (11) ◽  
pp. 2106-2114 ◽  
Author(s):  
Henrik Hartmann ◽  
Christian Messier ◽  
Marilou Beaudet
Keyword(s):  
Tree Mortality ◽  
External Validation ◽  
Growth Patterns ◽  
External Factors ◽  
Model Parameters ◽  
Similar Frequency ◽  
Growth Series ◽  
Recent Growth ◽  
Dead Trees ◽  
The Impact

Tree-ring chronologies have been widely used in studies of tree mortality where variables of recent growth act as an indicator of tree physiological vigour. Comparing recent radial growth of live and dead trees thus allows estimating probabilities of tree mortality. Sampling of mature dead trees usually provides death-year distributions that may span over years or decades. Recent growth of dead trees (prior to death) is then computed during a number of periods, whereas recent growth (prior to sampling) for live trees is computed for identical periods. Because recent growth of live and dead trees is then computed for different periods, external factors such as disturbance or climate may influence growth rates and, thus, mortality probability estimations. To counteract this problem, we propose the truncating of live-growth series to obtain similar frequency distributions of the “last year of growth” for the populations of live and dead trees. In this paper, we use different growth scenarios from several tree species, from several geographic sources, and from trees with different growth patterns to evaluate the impact of truncating on predictor variables and their selection in logistic regression analysis. Also, we assess the ability of the resulting models to accurately predict the status of trees through internal and external validation. Our results suggest that the truncating of live-growth series helps decrease the influence of external factors on growth comparisons. By doing so, it reinforces the growth–vigour link of the mortality model and enhances the model’s accuracy as well as its general applicability. Hence, if model parameters are to be integrated in simulation models of greater geographical extent, truncating may be used to increase model robustness.

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