Aiqin Liu

What drives forest fire in Fujian, China? Evidence from logistic regression and Random Forests

We applied logistic regression and Random Forest to evaluate drivers of fire occurrence on a provincial scale. Potential driving factors were divided into two groups according to scale of influence: ‘climate factors’, which operate on a regional scale, and ‘local factors’, which includes infrastructure, vegetation, topographic and socioeconomic data. The groups of factors were analysed separately and then significant factors from both groups were analysed together. Both models identified significant driving factors, which were ranked in terms of relative importance. Results show that climate factors are the main drivers of fire occurrence in the forests of Fujian, China. Particularly, sunshine hours, relative humidity (fire seasonal and daily), precipitation (fire season) and temperature (fire seasonal and daily) were seen to play a crucial role in fire ignition. Of the local factors, elevation, distance to railway and per capita GDP were found to be most significant. Random Forest demonstrated a higher predictive ability than logistic regression across all groups of factors (climate, local, and climate and local combined). Maps of the likelihood of fire occurrence in Fujian illustrate that the high fire-risk zones are distributed across administrative divisions; consequently, fire management strategies should be devised based on fire-risk zones, rather than on separate administrative divisions.

Comparison of six generalized linear models for occurrence of lightning-induced fires in northern Daxing＇an Mountains, China

The occurrence of lightning-induced forest fires during a time period is count data featuring over-dispersion (i.e., variance is larger than mean) and a high frequency of zero counts. In this study, we used six generalized linear models to examine the relationship between the occurrence of lightning-induced forest fires and meteorological factors in the Northern Daxing’an Mountains of China. The six models included Poisson, negative binomial (NB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), Poisson hurdle (PH), and negative binomial hurdle (NBH) models. Goodness-of-fit was compared and tested among the six models using Akaike information criterion (AIC), sum of squared errors, likelihood ratio test, and Vuong test. The predictive performance of the models was assessed and compared using independent validation data by the data-splitting method. Based on the model AIC, the ZINB model best fitted the fire occurrence data, followed by (in order of smaller AIC) NBH, ZIP, NB, PH, and Poisson models. The ZINB model was also best for predicting either zero counts or positive counts (≥1). The two Hurdle models (PH and NBH) were better than ZIP, Poisson, and NB models for predicting positive counts, but worse than these three models for predicting zero counts. Thus, the ZINB model was the first choice for modeling the occurrence of lightning-induced forest fires in this study, which implied that the excessive zero counts of lightning-induced fires came from both structure and sampling zeros.

Morphological plasticity and phosphorus uptake mechanisms of hybrid Eucalyptus roots under spatially heterogeneous phosphorus stress

In this study, we subjected the root systems of eight Eucalyptus hybrids currently cultivated in southern China to heterogeneous phosphorus stress to provide a scientific basis for the selection of a highly phosphorus-efficient Eucalyptus variety. When the ability of these hybrids to locate phosphorus under different experimental conditions (phosphorus supply in a homogeneous or heterogeneous manner vs. no phosphorus supply) was compared, the main growth characteristics of Eucalyptus, such as plant height, diameter, dry mass, and phosphorus content, significantly improved when the phosphorus supply was increased from no phosphorus or heterogeneous phosphorus (half of the phosphorus amount) to homogeneous phosphorus. Across these three conditions, the growth traits of different Eucalyptus hybrids differed significantly, indicating different adaptabilities of the hybrids to various phosphorus conditions. The growth traits of the aboveground tissues of Eucalyptus under different phosphorus conditions were largely influenced by the morphology of the underground root system. In addition, the root morphology of Eucalyptus under heterogeneous phosphorus treatment suggested that there were two mechanisms for locating nutrients. Eucalyptus hybrids such as Urophylla 3229, Grandis 9, Guanglin 3, 201-2, and Dunn produced more roots proximal to the phosphorus supply; the other hybrids, Urophylla 3216, Grandis 5, and Guanglin 9, relied mainly on the growth of roots opposite the phosphorus supply to obtain adequate nutrients for growth. With these two strategies, a wide range of nutrients was obtained, root distribution was greater, more soil volume was covered, the contact area of the roots with soil phosphorus was increased, and the uptake of phosphorus by the root system was increased. These results demonstrate that Eucalyptus relies on changes to morphological characteristics of the root system to increase accessibility to phosphorus resources.