Predicting tree recruitment with negative binomial mixture models

Zhang, Xiongqing; Lei, Yuancai; Cai, Daoxiong; Liu, Fengqiang

doi:10.1016/j.foreco.2012.01.028

Cited by 40 publications

(36 citation statements)

References 40 publications

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“…The NB model can be seen as a generalization of the Poisson model in which the variance (characterized by the dispersion parameter θ) can differ from the expected value. Thus, the mean of the NB distribution is λ as in the Poisson model, but the variance is λ+θλ 2 (Zhang et al 2012). When θ is zero, the NB distribution simplifies to the Poisson distribution.…”

Section: Modeling Techniquesmentioning

confidence: 99%

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Predicting the occurrence of large-diameter trees using airborne laser scanning

et al. 2016

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Large-diameter trees are important for both ecological and economic reasons, but they have become increasingly rare. Thus, there is an interest in easily locating such trees, and for this purpose, the use of airborne laser scanning (ALS) seems suitable. Our objective was to assess the accuracy of area-based ALS estimation in predicting the number of large-diameter Scots pines (Pinus sylvestris L.). A sample of 856 trees with a diameter >35 cm were measured from 1109 sample plots located in eastern Norway. We fitted negative binomial and zero-inflated negative binomial models for predicting large-diameter tree counts. ALS-derived and external variables were used as predictors when fitting the models. The accuracy was assessed based on the weighted kappa coefficient and cross validation. Our best model was based on three ALS height distribution variables, one horizontal ALS variable, and plot elevation. Its overall accuracy was 65.8% and the weighted kappa was 0.55. Although there was a clear relationship between the response and the proposed predictor variables, fairly large errors in the predicted large-diameter tree counts were common.

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Section: Modeling Techniquesmentioning

confidence: 99%

“…non-negative integer) variables (Consul 1989). Examples of studies where the response variable is a count include tree mortality (Affleck 2006), and also the number of seedlings in a regeneration plot (Zhang et al 2012). It is common that real-world count data have more zeroes than a statistical randomization would imply.…”

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confidence: 99%

Predicting the occurrence of large-diameter trees using airborne laser scanning

et al. 2016

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“…However, count data may exhibit a high variability precluding the use of a Poisson distribution. In such a case, a Negative Binomial distribution can be assumed to describe the count component of the model, giving rise to the Zero-Inflated Negative Binomial (ZINB) model (see e.g Rose et al 2006;Minami et al 2007;Zhang et al 2012…”

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confidence: 99%

Crossing the hurdle: the determinants of individual scientific performance

et al. 2014

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An original cross-sectional dataset referring to a medium-sized Italian university is implemented in order to analyze the determinants of scientific research production at individual level. The dataset includes 942 permanent researchers of various scientific sectors for a three-year time-span (2008)(2009)(2010). Three different indicators -based on the number of publications and/or citations -are considered as response variables. The corresponding distributions are highly skewed and display an excess of zero-valued observations. In this setting, the goodness-of-fit of several Poisson mixture regression models are explored by assuming an extensive set of explanatory variables. As to the personal observable characteristics of the researchers, the results emphasize the age effect and the gender productivity gap -as previously documented by existing studies. Analogously, the analysis confirm that productivity is strongly affected by the publication and citation practices adopted in different scientific disciplines. The empirical evidence on the connection between teaching and research activities suggests that no univocal substitution or complementarity thesis can be claimed: a major teaching load does not affect the odds to be a non-active researcher and does not significantly reduce the number of publications for active researchers. In addition, new evidence emerges on the effect of researchers administrative tasks -which seem to be negatively related with researcher's productivity -and on the composition of departments. Researchers' productivity is apparently enhanced by operating in department filled with more administrative and technical staff, and it is not significantly affected by the composition of the department in terms of senior/junior researchers.

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“…Previous studies introduced a two-stage conditional logistic regression: simulating positive counts with Poisson or negative binomial functions, seedling density in this study; simultaneously using zero-inflated model to address the possible zero observations by binomial with a logit link, the occurrence of natural regeneration in this study (Bravo et al 2008;Zuur et al 2009). Compared to Poisson models, zero-inflated negative binomial models (ZINB) perform more satisfactorily because they are more flexible for disperse and asymmetric distributed data and with less restrictions on the variance of positive counts (Zeileis et al 2008;Zhang et al 2012). Model fitting and validation were conducted with the pscl package in R (Jackman et al 2015; R Core Team 2017).…”

Section: Seedling Regeneration Modelsmentioning

confidence: 99%

Natural conifer regeneration patterns in temperate forests across the Inland Northwest, USA

Shen

Nelson

2018

Annals of Forest Science

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& Key message Natural regeneration patterns of conifer species were studied. Seedling regeneration follows patterns responding to stand structure and site condition factors along shade and drought tolerance gradients. Our findings can assist in adaptive forest management for maintaining sustainable regeneration and plant biodiversity. & Context Seedling regeneration can vary with stand factors of overstory trees and understory non-tree vegetation and site conditions. & Aims Natural seedling regeneration patterns of coniferous species were investigated using Forest Inventory and Analysis (FIA) data of 10 common species across the Inland Northwest, USA. & Methods Zero-inflated negative binomial models were developed to understand the responses of natural regeneration to stand factors and site conditions. & Results Seedling occurrence varies along shade and drought tolerance gradients responding to stand structure and site conditions. Two moderate shade-tolerant species of different drought tolerance contributed as a transition. Strong response patterns were revealed for seedling density, in which seedling density was improved with the presence of conspecific trees while limited by competition, especially from the understory vegetation layer. & Conclusion Overstory structure and understory vegetation could improve or hinder natural regeneration of coniferous tree species given different shade tolerance and site conditions. Our findings can be effectively implemented in adaptive forest management for maintaining sustainable regeneration of specific conifers in broad temperate mixed forests.

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Predicting tree recruitment with negative binomial mixture models

Cited by 40 publications

References 40 publications

Predicting the occurrence of large-diameter trees using airborne laser scanning

Predicting the occurrence of large-diameter trees using airborne laser scanning

Crossing the hurdle: the determinants of individual scientific performance

Natural conifer regeneration patterns in temperate forests across the Inland Northwest, USA

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