热带气旋对海南岛臭氧污染的影响分析

基于2015～2020年西北太平洋生成的181个热带气旋资料,海南岛18个市县臭氧(O₃)小时浓度数据和气象观测资料,分析了热带气旋对海南岛O₃污染的影响.结果表明,近6年共有40个(22.1%)热带气旋的生命期间海南岛出现了O₃污染天气,热带气旋生成个数偏多的年份,O₃污染天数也偏多,其中2019年污染天数最多最严重,高污染(≥3个市县超标)天数高达39 d(54.9%).高污染(HP)类热带气旋有逐年增多趋势,趋势系数和气候倾向率分别为0.725(通过95%信度检验)和0.667个·a^-1.热带气旋强度与海南岛O₃最大8 h滑动浓度平均值(O₃-8h)成正相关关系,其中在台风(TY)等级,HP类热带气旋占所有样本数的比例高达35.4%.热带气旋路径聚类分析表明,南海生成影响型(A类)热带气旋生成个数最多,共有67个(37%),同时最容易造成海南岛出现大范围和高浓度的O₃污染,A类热带气旋中HP的个数和海南岛ρ...     

华东沿海热带气旋移动和降水特征研究

基于TRMM 3B42RT 3 h降水资料和欧洲中期天气预报中心（ECMWF）的500 hPa分析场资料,借助于GIS空间分析方法,对热带气旋降水大值区的分布落区与移动路径之间的空间关系进行了统计叠置,分析了2000～2009年共29个登陆华东沿海或进入华东近海海域的热带气旋的路径、强度、降水的空间分布以及500 hPa环流形势对其影响的规律。结果表明：不同500 hPa环流形势对登陆热带气旋的移动路径及降水的空间分布型态有规律可循,其中中高纬西风带环流形势（50°N以北）以及副高西脊点所处的位置在热带气旋路径和降水分布型的业务预报中起着重要的指示作用     

水肥管理对热带地区双季稻田CH4和N2O排放的影响

水稻土被广泛认为是甲烷（CH₄）和氧化亚氮（N₂O）主要排放源,深入研究不同水肥管理条件下热带地区双季稻田CH₄和N₂O的排放特征,对补充我国双季稻田温室气体排放研究的不足意义重大.本研究设置8个处理：常规灌溉-施磷钾肥（D-PK）、常规灌溉-施氮磷钾肥（D-NPK）、常规灌溉-施氮磷钾+有机肥（D-NPK+M）、常规灌溉-施有机肥（D-M）、长期淹水-施磷钾肥（F-PK）、长期淹水-施氮磷钾肥（F-NPK）、长期淹水-施氮磷钾+有机肥（F-NPK+M）和长期淹水-施有机肥（F-M）.采用密闭静态箱-气相色谱法测定双季稻田CH₄和N₂O排放量,测定水稻产量和估算全球增温潜势（GWP）及温室气体排放强度（GHGI）.结果表明：①早稻季和晚稻季CH₄累积排放量分别为10.3~78.9 kg·hm^-2和84.6~185.5 kg·hm^-2.与F-PK和F-NPK处理相比,早稻季F-NPK+M和F-M处理显著增加CH₄累积排放量.同一施肥条件下,长期淹水处理CH₄累积排放量高于常规灌溉处理.灌溉和施肥极显著影响早稻季CH₄累积排放量.②早稻季和晚稻季N₂O累积排放量分别为0.18~0.76 kg·hm^-2和0.15~0.58 kg·hm^-2.与F-PK处理相比,早稻季F-NPK处理N₂O累积排放量显著增加;与D-PK相比,D-NPK、D-NPK+M和D-M处理显著增加N₂O累积排放量.与F-PK相比,晚稻季长期淹水其它处理N₂O累积排放量显著增加;与D-PK处理相比,D-NPK和D-M处理N₂O累积排放量显著增加.施肥极显著影响早稻季N₂O排放;灌溉和施肥极显著影响晚稻季N₂O排放.③早稻和晚稻产量分别为7310.7~9402.4 kg·hm^-2和3902.8~7354.6 kg·hm^-2,且F-NPK和F-M处理下早稻产量显著高于F-PK和D-NPK、D-PK和D-NPK处理.与PK处理相比,同一灌溉条件下其余3种施肥处理均显著增加晚稻产量.早稻季GWP和GHGI分别为580.8~2818.5kg·hm^-2和0.08~0.30 kg·kg^-1.与F-PK处理相比,常规灌溉条件下早稻季各施肥处理间GWP无显著性差异;但长期淹水条件下F-NPK+M和F-M处理GWP均显著增加.早稻季F-NPK+M和F-M处理GHGI显著高于其它处理.晚稻季GWP和GHGI分别为3091.6~6334.2 kg·hm^-2和0.50~1.23 kg·kg^-1.灌溉显著影响早稻和晚稻季GWP和GHGI,施肥对晚稻季GWP和GHGI的影响不显著.④土壤NH₄⁺-N含量和5 cm土温均与CH₄排放呈极显著负相关,pH与CH₄排放呈极显著正相关,但与N₂O排放呈显著负相关.土壤NH₄⁺-N和NO₃^--N含量与N₂O排放呈极显著负相关.综合作物产量、GWP和GHGI考虑,D-NPK+M可推荐为当地最优的减排稳产的水肥管理模式.     

Human disturbance and shifts in vertebrate community composition in a biodiversity hotspot

Understanding how human modification of the landscape shapes vertebrate community composition is vital to understanding the current status and future trajectory of wildlife. Using a participatory approach, we deployed the largest camera-trap network in Mesoamerica to date to investigate how anthropogenic disturbance shapes the occupancy and co-occurrence of terrestrial vertebrate species in a tropical biodiversity hotspot: the Osa Peninsula, Costa Rica. We estimated species richness in different categories of land protection with rarefaction analysis and estimated the expected occupancy with a joint species distribution model that included covariates for anthropogenic disturbance, land protection, habitat quality, and habitat availability. Areas with the most stringent land-use protections (e.g., Corcovado National Park, 24 species [95% CI 23–25]) harbored significantly more species than unprotected areas (20 species [19.7–20.3]), mainly due to a reduced presence of large-bodied species of conservation concern in unprotected areas (e.g., jaguar Panthera onca and white-lipped peccary Tayassu pecari). Small-bodied generalist species, such as opossums (Didelphidae) and armadillos (Dasypus novemcinctus), in contrast, were more common at disturbed sites, resulting in a significant difference in vertebrate community composition between sites with low and high disturbance. Co-occurrence of species was also mainly associated with response to disturbance. Similar responses to disturbance create two groups of species, those whose site-level occupancy usually increased as anthropogenic disturbance increased and those whose estimated occupancy decreased. The absence of large-bodied species entails an important loss of ecological function in disturbed areas and can hinder forest development and maintenance. Efforts to protect and restore forested landscapes are likely having a positive effect on the abundance of some threatened species. These efforts, however, must be sustained and expanded to increase connectivity and ensure the long-term viability of the wildlife community.     

基于自然和模拟热带海洋大气环境中涂层性能变化的对比研究

目的 研究涂层在自然环境试验和实验室模拟环境试验下性能的变化情况，通过再现涂层在自然环境下的环境效应和损伤过程，进而验证该模拟热带海洋大气环境试验方法的合理性。方法 根据涂层在舰船、舰载机等装备上热带海洋大气实际服役环境的分析，通过对热带海洋大气环境温度、湿度、盐雾、太阳辐射环境因素的组合，综合设计模拟热带海洋大气环境试验方法的试验流程，开展3种涂层在海南万宁为期1 a和实验室总周期为7循环的对比试验。结果 3种涂层在自然环境试验和实验室模拟环境试验后，随着试验时间的延长，其性能变化趋势相似，失光率和色差增大，附着力明显降低，交流阻抗值减小。红外光谱分析显示，老化机理均未出现明显变化，以光泽和色差为基准的平均秩相关系数为0.87，为极强相关。结论 本模拟热带海洋大气环境试验方法设计合理，具有良好的模拟性。     

某产品大气腐蚀环境因素监测与环境数据应用模式研究

目的 对某产品服役环境中的主要腐蚀环境因素进行监测，并挖掘环境数据应用模式，为该产品服役环境的腐蚀条件分析提供数据支撑。方法 根据某产品寿命期环境剖面，对库房、舱室及户外环境中温度、相对湿度、盐雾等主要环境因素进行为期3 a的监测，并从多个方面探讨这3种环境因素的应用模式。结果 针对某产品开展了主要环境因素监测，得到了其在关键服役场所的腐蚀环境数据，监测数据成功应用于该型产品服役环境严酷度分析、实验室环境试验条件设计、维修保障措施拟定等方面。结论 开展某产品关键服役环境下的腐蚀环境因素监测，可支撑该型产品的“环境符合性评估”“大气腐蚀性严酷度评估”“环境控制要求制定”以及“环境试验方法研究”。得到的环境监测数据以及应用案例可供其他类似产品服役环境监测及数据应用提供参考。     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.