Browsing by Author "Li, Bai-Lian"

Now showing 1 - 7 of 7
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    Capturing spiral radial growth of conifers using the superellipse to model tree-ring geometric shape
    (Frontiers Media, 2015) Shi, Pei-Jian; Huang, Jian-Guo; Hui, Cang; Grissino-Mayer, Henri D.; Tardif, Jacques C.; Zhai, Li-Hong; Wang, Fu-Sheng; Li, Bai-Lian
    Tree-rings are often assumed to approximate a circular shape when estimating forest productivity and carbon dynamics. However, tree rings are rarely, if ever, circular, thereby possibly resulting in under- or over-estimation in forest productivity and carbon sequestration. Given the crucial role played by tree ring data in assessing forest productivity and carbon storage within a context of global change, it is particularly important that mathematical models adequately render cross-sectional area increment derived from tree rings. We modeled the geometric shape of tree rings using the superellipse equation and checked its validation based on the theoretical simulation and six actual cross sections collected from three conifers. We found that the superellipse better describes the geometric shape of tree rings than the circle commonly used. We showed that a spiral growth trend exists on the radial section over time, which might be closely related to spiral grain along the longitudinal axis. The superellipse generally had higher accuracy than the circle in predicting the basal area increment, resulting in an improved estimate for the basal area. The superellipse may allow better assessing forest productivity and carbon storage in terrestrial forest ecosystems.
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    Effects of agricultural intensification on ability of natural enemies to control aphids
    (Springer Nature, 2015-01-26) Zhao, Zi-Hua; Hui, Cang; He, Da-Han; Li, Bai-Lian
    Agricultural intensification through increasing fertilization input and cropland expansion has caused rapid loss of semi-natural habitats and the subsequent loss of natural enemies of agricultural pests. It is however extremely difficult to disentangle the effects of agricultural intensification on arthropod communities at multiple spatial scales. Based on a two-year study of seventeen 1500 m-radius sites, we analyzed the relative importance of nitrogen input and cropland expansion on cereal aphids and their natural enemies. Both the input of nitrogen fertilizer and cropland expansion benefited cereal aphids more than primary parasitoids and leaf-dwelling predators, while suppressing ground-dwelling predators, leading to an disturbance of the interspecific relationship. The responses of natural enemies to cropland expansion were asymmetric and species-specific, with an increase of primary parasitism but a decline of predator/pest ratio with the increasing nitrogen input. As such, agricultural intensification (increasing nitrogen fertilizer and cropland expansion) can destabilize the interspecific relationship and lead to biodiversity loss. To this end, sustainable pest management needs to balance the benefit and cost of agricultural intensification and restore biocontrol service through proliferating the role of natural enemies at multiple scales.
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    A general method for parameter estimation in light-response models
    (Springer Nature, 2016) Chen, Lei; Li, Zhong-Bin; Hui, Cang; Cheng, Xiaofei; Li, Bai-Lian; Shi, Pei-Jian
    Selecting appropriate initial values is critical for parameter estimation in nonlinear photosynthetic light response models. Failed convergence often occurs due to wrongly selected initial values when using currently available methods, especially the kind of local optimization. There are no reliable methods that can resolve the conundrum of selecting appropriate initial values. After comparing the performance of the Levenberg–Marquardt algorithm and other three algorithms for global optimization, we develop a general method for parameter estimation in four photosynthetic light response models, based on the use of Differential Evolution (DE). The new method was shown to successfully provide good fits (R2 > 0.98) and robust parameter estimates for 42 datasets collected for 21 plant species under the same initial values. It suggests that the DE algorithm can efficiently resolve the issue of hyper initial-value sensitivity when using local optimization methods. Therefore, the DE method can be applied to fit the light-response curves of various species without considering the initial values.
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    Influence of the physical dimension of leaf size measures on the goodness of fit for Taylor's power law using 101 bamboo taxa
    (Elsevier, 2019) Shi, Peijian; Zhao, Lei; Ratkowsky, David A.; Niklas, Karl J.; Huang, Weiwei; Lin, Shuyan; Ding, Yulong; Hui, Cang; Li, Bai-Lian
    ENGLISH ABSTRACT: The mean and variance of ecological measures usually follow a power-law relationship, referred to as Taylor's power law (TPL). Leaves are important organs for photosynthesis, and leaf size is closely related to photosynthetic potential. Leaf size has different physical measures, such as leaf length, area, and fresh or dry weight. However, it has not been reported whether these leaf size measures follow TPL and whether the estimates of the TPL exponent reflect basic topological constraints. Considering that the variation of leaf size can affect the photosynthetic capacity of leaves and plant competitive abilities in communities, we examined the effects of different physical dimensions of leaf size (including leaf length, area, and fresh and dry weight) on the estimate of the scaling exponent and the goodness of fit of TPL for 101 bamboo species, varieties, forms, and cultivars, using 90-100 leaves for each type of plant. All leaf size measures follow TPL. However, the goodness of fit increases with the physical dimension of the leaf size measure (e.g., from 1D leaf length to 3D leaf weight). Interestingly, no significant differences in the estimates of the TPL exponent were detected among any of the physical dimensions (1D to 3D) because the 95% confidence intervals of the differences between any two groups of bootstrap replicates of the exponents of TPL obtained from different leaf size measures did not include 0. In other words, the TPL exponents of leaf size measures from the different physical dimensions could be deemed identical. We found that leaf dry weight provides the best fit of TPL and the most reliable estimate of the exponent among the four leaf size measures used in this study, perhaps because it is the best representative of the energy allocated to individual leaves.
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    An optimal proportion of mixing broad-leaved forest for enhancing the effective productivity of moso bamboo
    (John Wiley & Sons Ltd., 2015-03-17) Cheng, Xiao-Fei; Shi, Pei-Jian; Hui, Cang; Wang, Fu-Sheng; Liu, Guo-Hua; Li, Bai-Lian
    Moso bamboos (Phyllostachys edulis) are important forestry plants in southern China, with substantial roles to play in regional economic and ecological systems. Mixing broad-leaved forests and moso bamboos is a common management practice in China, and it is fundamental to elucidate the interactions between broad-leaved trees and moso bamboos for ensuring the sustainable provision of ecosystem services. We examine how the proportion of broad-leaved forest in a mixed managed zone, topology, and soil profile affects the effective productivity of moso bamboos (i.e., those with significant economic value), using linear regression and generalized additive models. Bamboo's diameter at breast height follows a Weibull distribution. The importance of these variables to bamboo productivity is, respectively, slope (25.9%), the proportion of broad-leaved forest (24.8%), elevation (23.3%), gravel content by volume (16.6%), slope location (8.3%), and soil layer thickness (1.2%). Highest productivity is found on the 25° slope, with a 600-m elevation, and 30% broad-leaved forest. As such, broad-leaved forest in the upper slope can have a strong influence on the effective productivity of moso bamboo, ranking only after slope and before elevation. These factors can be considered in future management practice.
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    An optimization approach to the two-circle method of estimating ground-dwelling arthropod densities
    (Florida Entomological Society, 2014-06) Shi, Pei-Jian; Zhao, Zi-Hua; Sandhu, Hardev S.; Hui, Cang; Men, Xing-Yuan; Ge, Feng; Li, Bai-Lian
    Information on ground-dwelling arthropod densities is important for efficient management in agro-ecosystems. A method of using paired pitfall traps with different inter-trap distances, called the two-circle method (TCM), was proposed recently for accurate and efficient estimation of arthropod densities. Using the numbers of individuals caught in paired traps and the inter-trap distances between the paired traps as input, the TCM can simultaneously estimate the effective trapping radius and the population density by fitting a nonlinear model. However, the previous fitting procedure (using the nonlinear least squares approach) provides the estimates and standard errors of only these two variables, and often suffers from its hypersensitivity to the initial values assigned in the nonlinear regression. To estimate the confidence intervals of these estimates and to assess the effects of the number of replications per distance class and the number of distance classes on the accuracy of density estimates, we provide a new procedure for fitting the model by using the optimization function. Evaluation based on simulated and field data suggests that the TCM could provide a reliable estimate of density by using at least 15 paired traps per distance class and at least 4 distance classes.
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    Weakening density dependence from climate change and agricultural intensification triggers pest outbreaks : a 37-year observation of cotton bollworms
    (John Wiley & Sons Ltd., 2014-08-12) Ouyang, Fang; Hui, Cang; Men, Xin-Yuan; Zhao, Zi-Hua; Shi, Pei-Jian; Zhang, Yong-Sheng; Li, Bai-Lian
    Understanding drivers of population fluctuation, especially for agricultural pests, is central to the provision of agro-ecosystem services. Here, we examine the role of endogenous density dependence and exogenous factors of climate and human activity in regulating the 37-year population dynamics of an important agricultural insect pest, the cotton bollworm (Helicoverpa armigera), in North China from 1975 to 2011. Quantitative time-series analysis provided strong evidence explaining long-term population dynamics of the cotton bollworm and its driving factors. Rising temperature and declining rainfall exacerbated the effect of agricultural intensification on continuously weakening the negative density dependence in regulating the population dynamics of cotton bollworms. Consequently, ongoing climate change and agricultural intensification unleashed the tightly regulated pest population and triggered the regional outbreak of H. armigera in 1992. Although the negative density dependence can effectively regulate the population change rate to fluctuate around zero at stable equilibrium levels before and after outbreak in the 1992, the population equilibrium jumped to a higher density level with apparently larger amplitudes after the outbreak. The results highlight the possibility for exogenous factors to induce pest outbreaks and alter the population regulating mechanism of negative density dependence and, thus, the stable equilibrium of the pest population, often to a higher level, posing considerable risks to the provision of agroecosystem services and regional food security. Efficient and timely measures of pest management in the era of Anthropocene should target the strengthening and revival of weakening density dependence caused by climate change and human activities.