Oil-tea camellia, one of the world’s four major edible woody oil trees, is acclaimed as the ’Oriental Olive Oil’ due to its exceptionally high nutritional value. The climate in southern China synchronizes with the ideal conditions for cultivating oil tea, making it the most abundant region globally in terms of its distribution. Consequently, the delineation of oil tea cultivation zones holds paramount significance for agricultural authorities in devising strategic production plans and management. However, the region is often affected by changeable weather and frequent cloud and rain, and there is a lack of continuous optical image data. Moreover, the complex topography primarily characterized by mountainous terrain, extensive coverage of farmlands, and vegetation has fragmented topographic features, posing challenges in accurately extracting semantic information from remote sensing images. To address these challenges, we propose a multi-scale self-attention semantic segmentation network aimed at meticulously identifying the semantic features of oil tea. Specifically, we introduce a self-attention mechanism to enable the model to comprehensively understand the information on feature images, followed by the integration of multi-scale feature images through the ASPP(Atrous Spatial Pyramid Pooloing) module to prevent the oversight of minor terrain features. Finally, the Dice-Loss function is applied to optimize the model’s segmentation of edge details. Experimental evaluations demonstrate that the proposed multi-scale self-attention semantic segmentation model achieved an Intersection over Union (IOU) of 0.93, Pixel Accuracy (PA) of 0.98, and Overall Accuracy (OA) of 94.83% for oil tea extraction on the dataset, showcasing a notable improvement over the original model. Additionally, we explore the method’s data requirements from the perspective of data volume and proportion. Ultimately, the experimental results demonstrate that our proposed method can accurately extract the oil tea cultivation areas in the cloudy and rainy hilly regions of southern China with high precision, thereby serving as a technological means for agricultural departments to oversee oil tea cultivation.

The southern hilly region of China boasts abundant forest resources, which are crucial for maintaining ecological stability. However, the complex vegetation structure and fragmented terrain in this area lead to intricate and disorderly forest types, resulting in semantic confusion among vegetation in remote sensing images. Consequently, accurately classifying forest types poses significant challenges. We propose a semantic segmentation model with multiple attention mechanisms using convolutional neural networks. We enhance the U-Net model's encoder with a deeper convolutional network to expand the receptive field without significant computation increase. Furthermore, we integrate spatial attention within the U-Net's skip connections and multiscale feature fusion. Experimentally, the multiple attention mechanism U-Net model outperforms the original, averaging 90.67% intersection over union, 94.33% pixel accuracy, and 96.00% classification accuracy for 0.5 m resolution forest type classification. These improvements are 8.00%, 4.33%, and 5.00%, respectively. The model accurately distinguishes forest types in the southern hilly region, enabling precise information-based forest supervision.

An extensive number of farmlands in the Poyang Lake region of China have been submerged due to the impact of flood disasters, resulting in significant agricultural economic losses. Therefore, it is of great importance to conduct the long-term temporal monitoring of flood-induced water body changes using remote sensing technology. However, the scarcity of optical images and the complex, fragmented terrain are pressing issues in the current water body extraction efforts in southern hilly regions, particularly due to difficulties in distinguishing shadows from numerous mountain and water bodies. For this purpose, this study employs Sentinel-1 synthetic aperture radar (SAR) data, complemented by water indices and terrain features, to conduct research in the Poyang Lake area. The results indicate that the proposed multi-source data water extraction method based on microwave remote sensing data can quickly and accurately extract a large range of water bodies and realize long-time monitoring, thus proving a new technical means for the accurate extraction of floodwater bodies in the Poyang Lake region. Moreover, the comparison of several methods reveals that CAU-Net, which utilizes multi-band imagery as the input and incorporates a channel attention mechanism, demonstrated the best extraction performance, achieving an impressive overall accuracy of 98.71%. This represents a 0.12% improvement compared to the original U-Net model. Moreover, compared to the thresholding, decision tree, and random forest methods, CAU-Net exhibited a significant enhancement in extracting flood-induced water bodies, making it more suitable for floodwater extraction in the hilly Poyang Lake region. During this flood monitoring period, the water extent in the Poyang Lake area rapidly expanded and subsequently declined gradually. The peak water area reached 4080 km2 at the height of the disaster. The severely affected areas were primarily concentrated in Yongxiu County, Poyang County, Xinjian District, and Yugan County.

为掌握野生见血清种子特性,用光学显微技术研究见血清种子形态结构、种皮细胞壁成分,并用不同浓度氢氧化钠处理种子以确定无菌播种适宜预处理条件.结果 表明:见血清种子由种皮和胚组成,无胚乳,胚为球形胚,种胚占种子体积13.44％,种子气腔体积占86.56％,为轻浮型种子;种皮细胞壁中含有纤维素、木质素和角质.采用0.5％氢氧化钠处理6 min可打破种皮限制,适宜作为无菌播种预处理条件.

The alpine tree line ecotone, reflecting interactions between climate and ecology, is very sensitive to climate change. To identify tree line responses to climate change, including intensity and local variations in tree line advancement, the use of Landsat images with long-term data series and fine spatial resolution is an option. However, it is a challenge to extract tree line data from Landsat images due to classification issues with outliers and temporal inconsistency. More importantly, direct classification results in sharp boundaries between forest and non-forest pixels/segments instead of representing the tree line ecotone (three ecological regions—tree species line, tree line, and timber line—are closely related to the tree line ecotone and are all significant for ecological processes). Therefore, it is important to develop a method that is able to accurately extract the tree line from Landsat images with a high temporal consistency and to identify the appropriate ecological boundary. In this study, a new methodology was developed based on the concept of a local indicator of spatial autocorrelation (LISA) to extract the tree line automatically from Landsat images. Tree line responses to climate change from 1987 to 2018 in Wuyishan National Park, China, were evaluated, and topographic effects on local variations in tree line advancement were explored. The findings supported the methodology based on the LISA concept as a valuable classifier for assessing the local spatial clusters of alpine meadows from images acquired in nongrowing seasons. The results showed that the automatically extracted line from Landsat images was the timber line due to the restriction in spatial autocorrelation. The results also indicate that parts of the tree line in the study area shifted upward vertically by 50 m under a 1 °C temperature increase during the period from 1987 to 2018, with local variations influenced by slope, elevation, and interactions with aspect. Our study contributes a novel result regarding the response of the alpine tree line to global warming in a subtropical region. Our method for automatic tree line extraction can provide fundamental information for ecosystem managers.

This paper analyzed the flora, geographical composition, similarity and difference of the family, genus and species of the stone pines and ferns in the north and south slopes of Wuyi Mountain. The results showed that: (1) there were 277 species of 68 genera and 27 families in the southern slope of Wuyi Mountain. There were 247 species of 71 genera and 28 genera on the northern slope; (2) the flora of the north and south slopes might had the same origin and strong transitional characteristics, with a trend of transition from tropical to pantropical to temperate zone; (3) the similarities of families, genera and species were as high as 94.55％, 96.40％ and 84.35％.

通过11年来对福建武夷山森林生态系统国家定位观测研究站常绿阔叶林凋落物量进行监测所积累的资料的分析,研究了这一地带性植被演替过程中凋落物量动态变化格局及组成特征,并分析了米槠林和甜槠林群落凋落叶的变化规律及其与凋落物总量的联系.结果表明:武夷山中亚热带常绿阔叶林平均年凋落物量为3879.45 kg hm-2,年际波动显著;凋落物的季节变化规律是夏季>冬季>秋季>春季,变化曲线为双峰形,夏季和冬季为两个峰值季;树枝、树叶、花果、树皮、碎屑等5个组成部分以落叶占比最大,年平均落叶量占凋落物总量的72.15％.

以武夷山自然保护区的毛竹林土壤(海拔范围为250～1500 m)为研究对象,选取5个海拔梯度的15块样地,分析了毛竹林土壤有机碳沿海拔梯度的分布特征,探讨了土壤有机碳含量与地形因子、土壤性质的相关关系,并构建了土壤有机碳的回归模型.结果表明:①武夷山毛竹林土壤有机碳含量变化范围为13.29～70.68 g/kg,且海拔>500 m土壤有机碳的分布具有明显的表聚现象;②同一海拔高度内,毛竹林土壤有机碳含量呈现随土层深度的增加而逐渐降低的趋势,且其降幅也随之变小;③同一土层深度的土壤有机碳含量大体呈现随海拔的升高而增加的趋势,而其增幅则随之变小;④不同土层土壤有机碳含量与海拔均呈显著或极显著正相关、与容重均呈极显著负相关,而仅表层(0～10 cm)土壤有机碳含量与坡度呈显著负相关;⑤土壤有机碳多元线性回归模型的拟合优度高于一元线性回归模型,不同因子组合对不同土层有机碳含量变异的解释量介于59％ ～83％.

Six new species of Dolichopeza Curtis, 1825, subgenus Nesopeza Alexander, 1914, are described and illustrated: D. (N.) incisuraloides sp. nov., D. (N.) jiangjinensis sp. nov., D. (N.) lipingensis sp. nov., D. (N.) medionodosa sp. nov., D. (N.) multidentata sp. nov., and D. (N.) setilobatoides sp. nov. Dolichipeza (N.) incisuralis Alexander, 1940 is redescribed and illustrated based on additional morphological characters. The female internal reproductive systems of D. (N.) incisuraloides sp. nov. and D. (N.) multidentata sp. nov. are documented. A key is provided to separate all known species of Nesopeza from China.

In order to explore the relationship between soil organic carbon(SOC) content and the four variables(including altitude, slope, bulk density and pH value), the distribution characteristics of SOC content along the altitudinal gradient ranging from 295 to 2 130 m in Wuyi Mountain Nature Reserve were analyzed and the regression model of SOC based on the main control factors was constructed. The results showed that, in the same altitude, the SOC content generally decreased with the increase of soil depth and its decreasing amplitude was also decreased. The SOC content ranging from 6.12 to 120.41 g?kg-1showed obvious surface assembly in the soil profile. The SOC content at the same soil depth generally increased with the increasing altitude, but its growth rate decreased accordingly. The SOC content was highly significantly positively correlated with altitude (P<0.01) and was negatively correlated with bulk density (P<0.01). There was significantly negative correlation (P<0.05) between SOC content and pH value only in the layer at the depth of 30-40 cm. The multiple linear regression model had higher goodness of fit than simple linear regression model for predicting SOC content. The combination of different factors can explain most of the variation of SOC in different soil layers with the explanation between 74.1% and 89.1%.

在福建武夷山黄岗山东南坡海拔1000m,以200m为一间隔设样,至山顶2140m外,共设置7个样地,调查样地面积28800m2,对调查数据进行归类整理,运用β多样性测度方法对其植物多样性进行分析.结果表明:武夷山黄岗山东南坡1000m至山顶2140m的海拔梯度上,乔木和灌木β多样性指数趋势逐渐降低,而草本β多样性指数则是呈U型趋势变化.二元属性测度方法能较好地揭示武夷山黄岗山β多样性指数变化,数量数据测度方法表现不明显.

Labile soil organic carbon (LOC) is an essential component in the global carbon (C) cycling due to its fast turnover and sensitivity to environmental changes. However, responses of the mineralization of LOC to current global warming are still not fully understood. In this study, we investigated LOC mineralization at 5, 15, 25 and 35 C incubation temperatures through laboratory incubation of soil samples and estimated the temperature sensitivity of LOC mineralization at various temperature ranges (i.e. 5-15, 15-25, and 25-35 degrees C) in an evergreen broad-leaf forest (EBF), a coniferous forest (CF), a sub-alpine dwarf forest (SDF), and an alpine meadow (AM) along an elevation gradient in the Wuyi Mountains in southeastern China. Our results showed that mineralization of LOC significantly increased along the elevation gradient and with increasing incubation temperatures. The interaction of elevation and incubation temperatures was additive on LOC mineralization. Moreover, the temperature sensitivity (Q(10)) of LOC mineralization significantly decreased with increasing incubation temperature ranges. However, elevation gradient had no statistically significant impact on Q(10) within each incubation temperature range. Our results suggest that soil organic C (SOC) at high elevations is more vulnerable to global warming. Moreover, consistent Q(10) of LOC mineralization along the elevation gradient indicates that locally, C quality maybe a minor factor in affecting LOC mineralization and it may be adequate to use a constant Q(10) value to represent the response of LOC mineralization to warming in regional climate-C cycling models.

We determined the water use efficiency and nitrogen and phosphorus concentrations of plants at different altitudes (600, 900, 1300, 1500, 1800, 2000, 2100 m) in Wuyi Mountains to understand the relationship of water use efficiency with foliar nutrients. The results showed that plant water use efficiency increased with altitude, and the leaf δ18O of tree showed no significant variance with altitude. On the whole, leaf nitrogen concentration showed no obvious trend, while leaf phosphorus concentration at high altitude was significantly higher than that at low altitude. No significant relationship between water use efficiency and foliar nitrogen concentration was found in this study, but water use efficiency had a positive correlation with foliar phosphorus concentration. In conclusion, the change of water use efficiency was mainly caused by the difference in photosynthetic rate. The effect of water status on plant water use efficiency was not significant. The variances of leaf phosphorus concentrations along the altitudinal gradient may affect photosynthetic rate and in turn the water use efficiency of plant in this area.

帽蕊草Mitrastemon yamamotoi Makino ,属名注解： mitra是指帽子或法冠,而stemon则是雄蕊的意思,结合起来即是“有帽状雄蕊的植物”,1年生、寄生小草本；茎单生,直立,肉质,有鳞片,鳞片交互对生,上部的最大；花两性,单生于茎顶,直立,近无柄,无苞片；花被辐射对称,合生；雄蕊合生成一帽状体,突出,初套着花柱和柱头,后脱落；花药合生成一阔带,孔裂,最初为一薄膜所包复,很快破裂,药隔扁圆锥状；子房上位,1室；胚珠多数,生于数个侧膜胎座上；花柱顶生,短、柱头厚；果为浆果状；种子多数。通常寄生在壳斗科中锥栗属Castanopsis,柯属Lithocarpus 和栎属Quercus的根上,蜂类或苍蝇因觅食接触花药与柱头帮助其授粉。种子传播方面,鸟类与蚂蚁可能扮演重要角色,种子也可能经由动物践踏或雨水冲刷而散布[1]。据记载,帽蕊草主要分布于中国的云南、广西、广东、福建和台湾,国外柬埔寨、日本和印度尼西亚也有分布。由于寄生植物较低的自然种群更新频率,加之人类活动的干扰,使得帽蕊草赖以生存的热带和亚热带阔叶林遭到不同程度的破坏。目前该类植物野外数量相当稀少,属于濒临灭绝的物种,以至于半个世纪以来中国未见相关的采集报道。

在武夷山国家级自然保护区30多年建设经验的基础上,提出一套科学有效的森林防火技术模式,同时也分析了当前保护区森林防火工作存在的困难和不足之处,据此提出今后保护区防火工作的重点以及改进建议.

武夷山保护区位于武夷山脉的最高地段,区内1500米以上高峰有112座.这里,濒临台湾海峡,能大量抬升、阻截北上的东南暖湿气流,又能有效阻挡、削弱南下的北方寒流,形成本地区温暖多雨、云雾缭绕的气候环境,是福建降水最丰富的地区.这里是福建母亲河闽江的重要源头和集水区,也是闽江水系与江西信江水系的分水岭,区有大小溪流150多条.然而由于20世纪50年代末至70年代的过度采伐,桐木等地的森林资源迅速枯竭,严重威胁到挂墩、大竹岚这两处世界闻名的生物模式标本产地的生存.

Despite the prevalence of disturbances in forests, the effects of disturbances on soil carbon processes are not fully understood. We examined the influences of a winter storm on soil respiration and labile soil organic carbon (SOC) of a Moso Bamboo (Phyllostachys heterocycle) plantation in the Wuyi Mountains in Southern China from May 2008 to May 2009. We sampled stands that were damaged at heavy, moderate, and light levels, which yielded aboveground biomass inputs to the soil at 22.12 ± 0.73 (mean ± 1 s.e.m.), 10.40 ± 1.09, and 5.95 ± 0.73 Mg per hectare, respectively. We found that soil respiration rate and annual cumulative CO2 emissions were significantly higher in heavily damaged sites than moderately and lightly damaged sites. Soil temperature was the most important environmental factor affecting soil respiration rate across all studied stands. However, soil respiration sensitivity to temperature (Q10) decreased in heavily damaged sites. Microbial biomass carbon and its proportion to total SOC increased with damage intensity. Soil respiration rate was positively correlated to microbial biomass carbon and soil moisture. Our results indicated that the increase of soil respiration following canopy disturbance from winter storm resulted from increased microbial biomass carbon, soil moisture, and temperature.

淡水生态系统水溶性有机碳(dissolved organic carbon,DOC)是全球碳循环的重要组成部分,也是淡水生态系统异养生物物质和能量来源,其对全球变化的响应很大程度上影响着全球碳汇的大小和淡水生态系统结构和功能.过去对陆地生态系统碳循环的研究较多,而有关淡水生态系统碳循环,特别是淡水生态系统DOC在全球碳循环中的作用及其对气候变化的响应研究相对缺乏.本文综述了近年全球变化对淡水生态系统DOC的影响,以及淡水生态系统DOC对全球变化的反馈.指出了全球变化各因子对淡水生态系统DOC的影响存在交互作用,各因子的影响程度也会随时间、空间而变化.淡水生态系统DOC对全球变的反馈程度也存在时空变异,但该方面的研究十分有限,反馈机制不十分清楚.基于目前研究,本文提出今后值得深入研究的三个方面,即:(1)扩展研究区域和范围,了解DOC在不同区域淡水生态系统中的动态变化特征;(2)加强全球变化对淡水生态系统DOC的组成和结构特征影响的研究;(3)深入研究淡水生态系统DOC对全球变化的反馈程度和机制.

This paper measured the activities of soil urease,sucrase,acid phosphatase,and catalase in four typical vegetation zones,i.e.,evergreen broadleaf forest(EBF) ,coniferous forest(CF) ,sub-alpine dwarf forest(SDF) ,and alpine meadow(AM) ,along an altitude gradient in the Natural Reserve of the Wuyi Mountains in Fujian Province of East China.In the four zones,there were no significant seasonal variations in the activities of test enzymes except acid phosphatase,whose activity was significantly higher in autumn than in any other seasons.The activities of test enzymes differed significantly with altitude,but less affected by the interaction of season and altitude.The enzyme activities showed an overall increasing trend with the altitude,being significantly higher in AM zone than in EBF and CF,and decreased with soil depth.The soil urease activity in the four zones was in the range of 1.28-3.87 mg·g-1·24 h-1,and in the order of AM>EBF>SDF>CF;soil sucrase activities was in the range of 36.18-244.08 mg·g-1·24 h-1,and in the order of AM>CF>EBF>SDF;acid phosphatase and catalase activities were in the ranges of 0.18-0.62 mg·g-1·2 h-1 and 1.78-1.98 ml·g-1·20 min-1,respectively,and in the order of AM>CF>SDF>EBF.The soil enzyme activities were significantly positively correlated with soil total organic carbon and total nitrogen,and had complicated correlations with soil temperature,moisture,and pH.

The 2008 snow storm in southern China was a huge natural disturbance to the forest ecosystem. We conducted an experiment in Phyllostachys heterocycla cv. pubescens forest in Wuyi Mountain to understand the influence of snow storm on major soil ecological factors and soil ecological processes. We divided the damage level of phyllostachys heterocycla cv. pubescens forest cause by the snow storm into three types i. e. heavy,middle and low level. The rate of damaged bamboo in heavy,middle and low level was 43. 7 % ,21. 8 % ,10. 3 % ,respectively. The aboveground biomass input to the ground caused by the snow storm was 2. 21,1. 04 and 0. 60 kg/m2,respectively. The canopy closure was significantly negatively correlated with soil moisture,soil respiration,soil temperature and soil microbial biomass carbon,respectively soil microbial biomass carbon,soil temperature and soil respiration were significantly correlated with the aboveground biomass loss. There were significant difference in soil respiration and microbial biomass carbon among different damage levels. The open of the canopy and the input of the litterfall and woody debris to the floor may lead to the changes of soil moisture,soil temperature,soil respiration,and soil microbial biomass carbon,and might alter the biological and ecological processes of phyllostachys heterocycla cv. pubescens forest.