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

We examined the effects of the 1997–98 El Niño drought on nine rain forests of Mount Kinabalu, Borneo, at four altitudes (700, 1700, 2700 and 3100 m) on contrasting geological substrata (ultrabasic versus non-ultrabasic). Measurements of rainfall and atmospheric aridity indicated that the departure from normal conditions during the drought became greater with increasing altitude. During 1997–99 (drought period) compared to 1995–97 (pre-drought period), median growth rates of stem diameter of trees decreased for both smaller (4.8–10 cm) and larger (≥ 10 cm) diameter classes in the six upland forests (≥ 2700 m on ultrabasic substrata and ≥ 1700 m on non-ultrabasic substrata), but for neither diameter class in the other forests. The majority of species decreased or did not change growth rates during 1997–99, whereas some did increase. Tree mortality increased during 1997–99, at the larger diameter class in the two lowland forests (700 m) on both substrata, and at least at the smaller diameter class in the four upland forests (≥ 1700 m) on non-ultrabasic substrata. In two of these upland forests, mortality was restricted to particular understorey species. Mortality did not significantly increase in the three upland forests (≥ 1700 m) on ultrabasic substrata; this suggests that the adaptation to nutrient-poor soils might have provided the resistance to drought.

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

Journal of Forestry Research ◽

10.1007/s11676-021-01302-2 ◽

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.

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Modeling Intraindividual Variability in Three-Level Multilevel Models

Methodology ◽

10.1027/1614-2241/a000150 ◽

2018 ◽

Vol 14 (3) ◽

pp. 95-108 ◽

Cited By ~ 4

Author(s):

Steffen Nestler ◽

Katharina Geukes ◽

Mitja D. Back

Keyword(s):

Multilevel Model ◽

Multilevel Models ◽

Mixed Effects ◽

Repeated Measurements ◽

Scale Model ◽

Suggested Approach ◽

Psychological Study ◽

Level Data ◽

Ecological Momentary ◽

Momentary Assessment

Abstract. The mixed-effects location scale model is an extension of a multilevel model for longitudinal data. It allows covariates to affect both the within-subject variance and the between-subject variance (i.e., the intercept variance) beyond their influence on the means. Typically, the model is applied to two-level data (e.g., the repeated measurements of persons), although researchers are often faced with three-level data (e.g., the repeated measurements of persons within specific situations). Here, we describe an extension of the two-level mixed-effects location scale model to such three-level data. Furthermore, we show how the suggested model can be estimated with Bayesian software, and we present the results of a small simulation study that was conducted to investigate the statistical properties of the suggested approach. Finally, we illustrate the approach by presenting an example from a psychological study that employed ecological momentary assessment.

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Extremism Leads to Ostracism

Social Psychology ◽

10.1027/1864-9335/a000406 ◽

2020 ◽

Vol 51 (3) ◽

pp. 149-156

Author(s):

Andrew H. Hales ◽

Kipling D. Williams

Keyword(s):

Mixed Effects ◽

Social Connection ◽

Mixed Effects Modeling ◽

Activist Groups

Abstract. Ostracism has been shown to increase openness to extreme ideologies and groups. We investigated the consequences of this openness-to-extremity from the perspective of potential ostracizers. Does openness-to-extremity increase one’s prospects of being ostracized by others who are not affiliated with the extreme group? Participants rated willingness to ostracize 40 targets who belong to activist groups that vary in the type of goals/cause they support (prosocial vs. antisocial), and the extremity of their actions (moderate vs. extreme). Mixed-effects modeling showed that people are more willing to ostracize targets whose group engages in extreme actions. This effect was unexpectedly stronger for groups pursuing prosocial causes. It appears openness-to-extremity entails interpersonal cost, and could increase reliance on the extreme group for social connection.

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