Institution
Nanchang Institute of Technology
Education•Nanchang, China•
About: Nanchang Institute of Technology is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Particle swarm optimization & Computer science. The organization has 2161 authors who have published 2015 publications receiving 16756 citations. The organization is also known as: Nanchang University of Technology.
Topics: Particle swarm optimization, Computer science, Optimization problem, Image segmentation, Firefly algorithm
Papers published on a yearly basis
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Oklahoma State University–Stillwater1, Macquarie University2, University of Sydney3, University of Utah4, Max Planck Society5, University of Alberta6, University of California, Irvine7, University of New Mexico8, University of Nebraska–Lincoln9, United States Geological Survey10, University of Washington11, University of Arizona12, University of Sheffield13, University of Tasmania14, ETH Zurich15, University of California, Davis16, Los Alamos National Laboratory17, Nanchang Institute of Technology18, University of Wyoming19, Swedish University of Agricultural Sciences20, University of Coimbra21, Northern Arizona University22, United States Forest Service23, Swiss Federal Institute for Forest, Snow and Landscape Research24, University of São Paulo25, University of Oxford26, University of California, Santa Cruz27, Humboldt State University28, Fordham University29, Centre national de la recherche scientifique30, University of Edinburgh31, Hobart Corporation32, Spanish National Research Council33, University of Chile34, Idaho State University35, University of Basilicata36, Colorado State University37, United States Department of Agriculture38, University of Montana39, University of Delaware40, University of Western Ontario41, Duke University42, Sonora Institute of Technology43, Pacific Northwest National Laboratory44
TL;DR: It is shown that, across multiple tree species, loss of xylem conductivity above 60% is associated with mortality, while carbon starvation is not universal, indicating that evidence supporting carbon starvation was not universal.
Abstract: Widespread tree mortality associated with drought has been observed on all forested continents and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere-atmosphere interactions of carbon, water and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analysed across species and biomes using a standardized physiological framework. Here, we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought-induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function.
651 citations
TL;DR: In this article, the effects of nitrogen load on trees and soils in a uniquely long-term (30 years) experiment with annual N loading on an unpolluted boreal forest were evaluated.
Abstract: Relations among nitrogen load, soil acidification and forest growth have been evaluated based on short-term (o15 years) experiments, or on surveys across gradients of N deposition that may also include variations in edaphic conditions and other pollutants, which confound the interpretation of effects of N per se. We report effects on trees and soils in a uniquely long-term (30 years) experiment with annual N loading on an unpolluted boreal forest. Ammonium nitrate was added to replicated (N 53) 0.09ha plots at two doses, N1 and N2, 34 and 68kgNha � 1 yr � 1 , respectively. A third treatment, N3, 108kgNha � 1 yr � 1 , was terminated after 20 years, allowing assessment of recovery during 10 years. Tree growth initially responded positively to all N treatments, but the longer term response was highly rate dependent with no gain in N3, a gain of 50m 3 ha � 1 stemwood in N2 and a gain of 100m 3 ha � 1 stemwood in excess of the control (N0) in N1. High N treatments caused losses of up to 70% of exchangeable base cations (Ca 2 1 ,M g 2 1 , K 1 ) in the mineral soil, along with decreases in pH and increases in exchangeable Al 3 1 . In contrast, the organic mor-layer (forest floor) in the N-treated plots had similar amounts per hectare of exchangeable base cations as in the N0 treatment. Magnesium was even higher in the mor of N-treated plots, providing evidence of up-lift by the trees from the mineral soil. Tree growth did not correlate with the soil Ca/Al ratio (a suggested predictor of effects of soil acidity on tree growth). A boron deficiency occurred on N-treated plots, but was corrected at an early stage. Extractable NH4 1 and NO3 were high in mor and mineral soils of on-going N treatments, while NH4 1 was elevated in the mor only in N3 plots. Ten years after termination of N addition in the N3 treatment, the pH had increased significantly in the mineral soil; there were also tendencies of higher soil base status and concentrations of base cations in the foliage. Our data suggest the recovery of soil chemical properties, notably pH, may be quicker after removal of the N-load than predicted. Our long-term experiment demonstrated the fundamental importance of the rate of N application relative to the total amount of N applied, in particular with regard to tree growth and C sequestration. Hence, experiments adding high doses of N over short periods do not mimic the long-term effects of N deposition at lower rates.
403 citations
TL;DR: An enhanced PSO algorithm called GOPSO is presented, which employs generalized opposition-based learning (GOBL) and Cauchy mutation to overcome the problem of premature convergence when solving complex problems.
384 citations
TL;DR: A hybrid PSO algorithm is proposed, called DNSPSO, which employs a diversity enhancing mechanism and neighborhood search strategies to achieve a trade-off between exploration and exploitation abilities.
366 citations
TL;DR: Wang et al. as discussed by the authors proposed two machine learning algorithms, i.e., Support Vector Machine (SVM) and a novel simple tree-based ensemble method named Extreme Gradient Boosting (XGBoost), for accurate prediction of daily H using limited meteorological data.
345 citations
Authors
Showing all 2191 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Wei Li | 78 | 1592 | 31728 |
| Hui Wang | 75 | 917 | 24802 |
| Yuwei Chen | 50 | 292 | 10512 |
| Jeng-Shyang Pan | 50 | 789 | 11645 |
| Jianping Wu | 45 | 585 | 9392 |
| Baochang Zhang | 40 | 294 | 6433 |
| Shifeng Zhang | 38 | 213 | 6228 |
| Hao Liang | 29 | 107 | 3346 |
| Garry Wei-Han Tan | 27 | 54 | 2968 |
| Lifeng Wu | 23 | 46 | 1639 |
| Ping Deng | 20 | 38 | 2825 |
| Haifa Zhai | 20 | 70 | 1294 |
| Xiang Lu | 20 | 61 | 998 |
| Junping Hu | 19 | 41 | 1389 |
| Bin Xu | 19 | 25 | 1193 |