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Impact of Non-Timber Forest Product Use on the Tree Community in North-Western Vietnam

FORESTS 2018年第7期9卷 431-431页

作者： Thi Hoa Hong Dao Hoelscher, Dirk Univ Goettingen Trop Silviculture & Forest Ecol D-37077 Gottingen Germany Vietnam Natl Univ Forestry Fac Silviculture Forest Inventory & Planning Hanoi 024840 Vietnam Univ Goettingen Ctr Biodivers & Sustainable Land Use D-37077 Gottingen Germany

Trees providing non-timber forest products (NTFPs) are valuable forest resources, and their management can support conservation objectives. We analyzed the abundance of tree species providing NTFPs, recognized by local H'mong people, in both the strictly protected core zone and the low-intensity forest use buffer zone in north-western Vietnam. We identified 249 tree species, of which 48% were classified as NTFP species. The abundance of 35% of the NTFP tree species was significantly correlated with footpaths, indicating an influence of human activity. A multiple logistic regression model indicates that using NTFP trees for food, medicine, and root harvesting, increases the probability of an NTFP tree absence in the buffer zone. In contrast, the high density of species, and collections of fruit, leaf, and resin decrease the probability of an NTFP tree absence in the buffer zone. Further assessment with a logistic model indicated that NTFP use has lower impacts on the tree community than timber use. We think that the parameterized models will enable comparisons of different situations and forest types and be particularly helpful in evaluating potential changes in tree communities over time.

关键词： logistic regression model forest management H'mong people conservation

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Understanding fire drivers and relative impacts in different Chinese forest ecosystems

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SCIENCE OF THE TOTAL ENVIRONMENT 2017年 605卷 411-425页

作者： Guo, Futao Su, Zhangwen Wang, Guangyu Sun, Long Tigabu, Mulualem Yang, Xiajie Hu, Haiqing Fujian Agr & Forestry Univ Coll Forestry Fuzhou 350002 Fujian Peoples R China Univ British Columbia Fac Forestry Sustainable Forest Management Lab Vancouver BC V6T 1Z4 Canada Northeast Forestry Univ Coll Forestry Harbin 150040 Heilongjiang Peoples R China Swedish Univ Agr Sci Southern Swedish Forest Res Ctr Box 49 SE-23052 Alnarp Sweden

In this study, spatial patterns and driving factors of fires were identified from 2000 to 2010 using Ripley's K (d) function and logistic regression (LR) model in two different forest ecosystems of China: the boreal forest (Daxing'an Mountains) and sub-tropical forest (Fujian province). Relative effects of each driving factor on fire occurrence were identified based on standardized coefficients in the LR model. Results revealed that fires were spatially clustered and that fire drivers vary amongst differing forest ecosystems in China. Fires in the Daxing'an Mountains respond primarily to human factors, of which infrastructure is recognized as the most influential. In contrast, climate factors played a critical role in fire occurrence in Fujian, of which the temperature of fire season was found to be of greater importance than other climate factors. Selected factors can predict nearly 80% of the total fire occurrence in the Daxing'an Mountains and 66% in Fujian, wherein human and climate factors contributed the greatest impact in the two study areas, respectively. This study suggests that different fire prevention and management strategies are required in the areas of study, as significant variations of the main fire-driving exist. Rapid socio-economic development has produced similar effects in different forest ecosystems within China, implying a strong correlation between socio-economic development and fire regimes. It can be concluded that the influence of human factors will increase in the future as China's economy continues to grow-an issue of concern that should be further addressed in future national fire management. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Daxing'an Mountains Driving factors Fire occurrence logistic regression model Spatial distribution

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AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking

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BMC BIOINFORMATICS 2017年第1期18卷 1-12页

作者： Wisitponchai, Tanchanok Shoombuatong, Watshara Lee, Vannajan Sanghiran Kitidee, Kuntida Tayapiwatana, Chatchai Chiang Mai Univ Fac Associated Med Sci Div Clin Immunol Dept Med Technol Chiang Mai 50200 Thailand Chiang Mai Univ Fac Associated Med Sci Ctr Biomol Therapy & Diagnost Chiang Mai 50200 Thailand Mahidol Univ Fac Med Technol Ctr Data Min & Biomed Informat Bangkok 10700 Thailand Commiss Higher Educ Thailand Ctr Excellence Phys Bangkok 10400 Thailand Univ Malaya Dept Chem Fac Sci Kuala Lumpur 50603 Malaysia Mahidol Univ Fac Med Technol Ctr Res & Innovat Bangkok 10700 Thailand

Background: Computational analysis of protein-protein interaction provided the crucial information to increase the binding affinity without a change in basic conformation. Several docking programs were used to predict the near-native poses of the protein-protein complex in 10 top-rankings. The universal criteria for discriminating the near-native pose are not available since there are several classes of recognition protein. Currently, the explicit criteria for identifying the near-native pose of ankyrin-protein complexes (APKs) have not been reported yet. Results: In this study, we established an ensemble computational model for discriminating the near-native docking pose of APKs named "AnkPlex". A dataset of APKs was generated from seven X-ray APKs, which consisted of 3 internal domains, using the reliable docking tool ZDOCK. The dataset was composed of 669 and 44,334 near-native and non-near-native poses, respectively, and it was used to generate eleven informative features. Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with >= 1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. In addition, feature analysis demonstrated that the van der Waals feature was the dominant near-native pose out of the potential ankyrin-protein docking poses. Conclusion: The AnkPlex model achieved a success at predicting near-native docking poses and led to the discovery of informative characteristics that could further improve our understanding of the ankyrin-protein complex. Our computational study could be useful for predicting the near-native poses of binding proteins and desired targets, especially for ankyrin-protein complexes. The AnkPlex web server is freely accessible at http://***.

关键词： Ankyrin-protein complexes Near-native docking pose Machine learning methods Decision tree logistic regression model AnkPlex

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Probability of surface fire spread in Brazilian rainforest fuels from outdoor experimental measurements

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EUROPEAN JOURNAL OF FOREST RESEARCH 2017年第2期136卷 217-232页

作者： Krieger Filho, Guenther Carlos Bufacchi, Paulo Santos, Jose Carlos Gurgel Veras, Carlos Alberto Alvarado, Ernesto C. Mell, William Carvalho, Joao Andrade, Jr. Univ So Paulo USP Av Prof Mello de Morais 2231 BR-05508030 Sao Paulo SP Brazil Inst Nacl Pesquisas Espaciais INPE Rodovia Presidente Dutra Km 40 BR-12630000 Cachoeira Paulista SP Brazil Univ Brasilia UnB BR-70910900 Brasilia DF Brazil Univ Washington Sch Environm & Forest Sci Mail Box 352100 Seattle WA 98195 USA US Forest Serv Pacific Northwest Res Stn Pacific Wildland Fire Sci Lab Seattle WA USA Univ Estadual Paulista UNESP Av Ariberto Pereira Cunha 333 BR-12516410 Guaratingueta SP Brazil

This paper describes the development of a logistic model to predict the probability of surface fire spread in Brazilian rainforest fuels from outdoor experimental measurements. Surface fires spread over litter composed mostly of dead leaves and twigs. There were 72 individual outdoor experiments in eighteen sites. The fire propagated in 49% of the experiments. In each experiment, the litter height, litter temperature, unburned litter mass, wet and dry litter mass, soil temperature, wet and dry soil mass, ambient wind velocity, ambient air temperature, ambient air relative humidity and duration of fire spread were measured. Using these data, the rate of fire spread, litter bulk density, litter and soil moisture content, litter load and litter residue fraction were determined. For the sake of analysis, experimental results were classified into two groups: one for which the fire propagated and the other one for which the fire self-extinguished. Analyses of a logistic regression model showed that the relevant parameters for fire propagation are litter height and litter moisture content. Concerning the probability of successful fire propagation, the model showed a true positive rate of 71% and a true negative rate of 84%. The outdoor experiments also served to gather data to improve the understanding of surface fires and to provide input data for future computer simulations.

关键词： Surface fire Brazilian rainforest Flammability logistic regression model

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Determinants of forage adoption and production niches among smallholder farmers in Kenya

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AFRICAN JOURNAL OF RANGE & FORAGE SCIENCE 2017年第3期34卷 157-166页

作者： Njarui, Donald M. G. Gatheru, Mwangi Gichangi, Elias M. Nyambati, Elikana M. Ondiko, Clotilda N. Ndungu-Magiroi, Keziah W. Kenya Agr & Livestock Res Org Katumani Machakos Kenya Kenya Agr & Livestock Res Org Headquarters Nairobi Kenya Kenya Agr & Livestock Res Org Mtwapa Mtwapa Kenya Kenya Agr & Livestock Res Org Kitale Kitale Kenya

A study was conducted to assess factors that influence adoption of forages and choice of production niches in smallholder farms in Kenya. A total of 786 farmers (268 from coastal lowlands, 171 from eastern midlands, 132 from central highlands and 215 from north-western highlands) were interviewed using a structured questionnaire between September 2013 and March 2014. The data analysis was carried out using logistic regression models to evaluate the determinants of adoption of forages and production niches. Land tenure, access to formal education and experience in livestock farming positively and significantly (p < 0.1) influenced the adoption of forages. In contrast, distance to market, farm and household size negatively influenced the adoption of forages. Gender, age, off/non-farm income and number of livestock did not influence adoption of forages. Farm size, agro-ecological zone and type of livestock management system influenced the choice of niches for forage production significantly (p < 0.001). Land tenure did not influence the choice of forage production niche. Improving access to education and secure land tenure can enhance the adoption of forages. Research should focus on developing a decision support tool for assisting farmers to select suitable niches for integrating forages in the farming system.

关键词： agro-ecological zones chi-square crop-livestock farming system cultivated forages logistic regression model

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Tool condition monitoring and degradation estimation in rotor slot machining process

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2017年第1-4期91卷 39-48页

作者： Liu, Yingchao Hu, Xiaofeng Yan, Shan Sun, Shixu Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

Tool wear degradation and working status of slotting cutter have a great effect on the surface quality of rotor slot;therefore, tool condition monitoring and its degradation estimation are needed for guaranteeing slot machining quality. This paper proposes a two-phase method based on acoustic emission (AE) signal classification and logistic regression model for slotting cutter condition monitoring and its degradation estimation. In the first phase, the failure reliability estimation models corresponding to different machining processes are established considering the variability of process system like tool regrinding times and material randomness of workpiece. In the second phase, the most appropriate estimation model corresponding to the optimum cluster is selected and used for failure reliability estimation and status determination of slotting cutter. This approach has been validated on a CNC rotor slot machine in a factory. Experimental results show that the proposed method can be effectively used for cutting tool degradation estimation and status determination of slotting cutter with high accuracy.

关键词： Tool condition monitoring Degradation estimation Slotting cutter Acoustic emission logistic regression model

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logistic regression analysis of drought persistence in East China

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INTERNATIONAL JOURNAL OF CLIMATOLOGY 2017年第3期37卷 1444-1455页

作者： Meng, Lei Ford, Trent Guo, Ying Western Michigan Univ Dept Geog Kalamazoo MI 49008 USA Western Michigan Univ Environm & Sustainabil Studies Program Kalamazoo MI 49008 USA Southern Illinois Univ Dept Geog & Environm Resources Carbondale IL USA Chinese Acad Sci Inst Genet & Dev Biol Hebei Key Lab Agr Water Saving Key Lab Agr Water ResourcesCtr Agr Resources Res Shijiazhuang Peoples R China

East China (EC) has experienced a number of severe droughts in recent decades. Understanding the characteristics of droughts and their persistence will provide operational guidelines for water resource management and agricultural production. This study uses a logistic regression model to measure the probability of drought occurrence in the current season given the previous season's Standardized Precipitation Index (SPI) and Southern Oscillation Index (SOI) as well as drought persistence. Results reveal large spatial and seasonal variations in the relationship between the previous season's SPI and the drought occurrence probability in a given season. The drought persistence averaged over the entire study area for all the four seasons is approximately 34% with large variations from season to season and from region to region. The East and Northeast regions have the largest summer drought persistence (approximate to 40%) and lowest fall drought persistence (approximate to 28%). The spatial pattern in winter and spring drought persistence is dissimilar with stronger winter and weaker spring drought persistence in the Southwest and Northeast relative to other regions. logistic regression analysis indicates a stronger negative relationship in summer-to-fall (or between fall drought occurrence and summer SPI) than other inter-season relationships. Most of the stations with significant relationships in summer-to-fall lie in the East and the southern part of the North region. Significant negative relationships in winter-spring and fall-winter are primarily located on the western portion of the study area. A significant negative spring-summer relationship exists in the North region. Further, spring drought occurrence has a statistically significant positive relationship with winter SOI in the Southeast. Fall drought occurrence and summer SOI are negatively correlated in the northwest portion of EC (i.e. the border of North and Southwest regions). Overall, this study demonstrat

关键词： Standardized Precipitation Index drought persistence logistic regression model East China

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Comparison of low-temperature cracks intensity on pavements with high modulus asphalt concrete and conventional asphalt concrete bases

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CONSTRUCTION AND BUILDING MATERIALS 2017年 147卷 478-487页

作者： Rys, Dawid Judycki, Jozef Pszczola, Marek Jaczewski, Mariusz Mejlun, Lukasz Gdansk Univ Technol Fac Civil & Environm Engn Dept Highway Engn Gdansk Poland

High modulus asphalt concrete (HMAC) base courses provide very good resistance to rutting and fatigue but they can increase the risk of low-temperature cracking as compared with conventional asphalt concrete (AC). The article presents the comparison of these two road materials in terms of low-temperature cracking. The statistical method based on the ordered logistic regression model was used. The analysis was based on results of field investigations, that was carried out on 80 selected road sections being in normal service in Poland. The intensity of low-temperature cracking was an analysed parameter. The results of the analysis indicated evident effect of asphalt base type on intensity of low-temperature cracking. Besides the effect of mixture type, the method included influence of climatic condition and pavement age on low-temperature cracking. The essence of the analysis was to compare the probabilities of being of pavement in the group with a given cracks intensity. It was revealed that pavements with high modulus asphalt bases had 2.45 times higher odds of being in the group of cracked pavements than pavements with conventional asphalt concrete bases. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： High modulus asphalt concrete Low-temperature cracking logistic regression model Field investigations

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Does an upper limit to river water temperature apply in all places?

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HYDROLOGICAL PROCESSES 2017年第21期31卷 3729-3739页

作者： Shaw, Stephen B. SUNY Coll Environm Sci & Forestry Dept Environm Resources Engn Syracuse NY 13210 USA

There remains continued use of non-linear, logistic regression models for predicting water temperature from air temperature. A dominant feature of these non-linear models is an upper bound on river water temperature. This upper bound is often attributed to a large increase in evaporative cooling at high air temperatures, but the exact conditions under which such an increase may occur have not been thoroughly explored. To better understand the appropriateness of the non-linear model for predicting river water temperatures, it is essential to understand the physical basis for the upper bound and when it should and should not be included in the statistical model. This paper applies and validates an energy balance model against 8 river systems spread across different climate regions of the United States. The energy balance model is then used to develop a diagram relating vapour pressure deficit and air temperature to water temperature. With knowledge of present or future vapour pressure deficit (difference between saturation and actual vapour content in the atmosphere) conditions in a given climate, the diagram can be used to predict the likelihood of an upper bound in the air-water temperature relationship. This investigation offers a fundamental physical explanation of the most appropriate form of statistical models that should be used for predicting future water temperature from air temperature in different geographic regions with different climate conditions. In general, climatic regions that have only a slight increase in vapour pressure deficit with increasing air temperature (typically humid regions) would not be expected to have an upper bound. Conversely, climatic regions in which vapour pressure deficit sharply increases with increasing air temperature (typically arid regions) would be expected to have an upper bound.

关键词： climate change logistic regression model stream water temperature vapour pressure deficit

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Exploring the factors influencing ecological land change for China's Beijing-Tianjin-Hebei Region using big data

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JOURNAL OF CLEANER PRODUCTION 2017年第Part2期142卷 677-687页

作者： Xie, Hualin He, Yafen Xie, Xue Jiangxi Univ Finance & Econ Coinnovat Ctr Inst Construct Jiangxi Ecocivilizat Nanchang 330032 Jiangxi Peoples R China Jiangxi Univ Finance & Econ Res Ctr Land Management Nanchang 330032 Jiangxi Peoples R China

With the advent of big data, such data regarding the harmonious relationship of "people-land-time" have also gradually entered into the fields of natural resource management. Ecological land is one of the important natural resources and is fundamental to maintaining ecological security. Ecological land change can lead to a series of eco-environmental problems, including water shortages, soil erosion, increased drought intensity, ecosystem damage, and biodiversity loss. Based on relevant sets of big data, including spatial land data, soil data, DEM, climatic data, and socio-economic data, this study explores the factors influencing ecological land change during the period of 2000-2005 in China's Beijing-Tianjin-Hebei Region. The results show that the factors influencing different types of ecological land change have substantial differences. For forest land coverage change, Slope type, Soil organic matter (SOM) content, Farmer's population percentage, and Landform type are the most important independent variables. However, for grassland change, altitude, distance to the primary road and GDP per capita are the most important spatial determinants. Regarding the wetland change, farmer's population percentage, GDP per capita and altitude are the most important factors influencing wetland changes. This study indicates that natural and social-economic factors can affect ecological land change in China's Beijing-Tianjin-Hebei Region. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Ecological land Big data logistic regression model Land resource management

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