用遗传算法解算病态方程

对应用遗传算法解决病态方程问题进行了探讨。利用拟合法而不是通过法方程求解参数，从而避免了法方程系数求逆，使病态方程的解答有了较好的结果。通过模拟计算并和其他方法进行比较，证明该方法是可行的和有效的。     

Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

Soil respiration (SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO₂ emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests (Populus tomentosa (PT) and Robinia pseudoacacia (RP)), three artificial plantations (Armeniaca sibirica (AS), Punica granatum (PG) and Ziziphus jujuba (ZJ)) and one natural grassland (GR), to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct seasonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation (CV) of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen (STN), soil organic carbon (SOC), net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q₁₀ (temperature sensitivity of soil respiration) values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO₂ emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying CO₂ emissions via SR at regional scales.     

Characterizing landscape spatial heterogeneity in multisensor images with variogram models

Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l＇observation de la Terre （SPOT）, Ad- vanced Spacebome Thermal Emission and Reflection Radiometer （ASTER） and Landsat Thematic Mapper （TM） images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands.     

空地异常组合特征分析与找矿

根据航空物探资料及地面查证（包括地质观察、地面磁法、电法、化探等）资料,探讨了空地异常组合特征与铁及多金属矿产的关系。在综合分析的基础上,初步建立了利用空地异常组合特征寻找铁及多金属矿的分析方法,对于今后利用空地综合方法确定找矿目标具有一定的指导意义。     

从水体到沉积物:探寻有机质的沉积过程及其意义

自然界中有机质分布广泛、类型多样且性质各异,不论在水体还是在沉积物(岩)中都扮演着重要的角色。因此,探讨各类型有机质聚集和沉积过程的差异性,对深化认识有机质沉积特征和演化规律具有重要的意义。生物体在生长过程中产生了许多有机质,包括生物体自身、生物残体、动物排泄物以及生物分泌的有机分子等,各类型有机质的性质差异极大。由于研究方法的不同,可将海洋中有机质划分为颗粒有机质(particulate organic matter,POM)和溶解有机质(dissolved organic matter,DOM),而DOM又可划分为胶体有机质(colloidal organic matter,COM)和真溶解有机质;从聚合体形式上看,又有海雪和悬浮体等存在形式。进一步分析发现有机质的形态包括生物体、生物残体、排泄物和有机质聚合体等,并且各类型有机质与无机矿物以不同的形式共存。此外,DOM与POM间存在一定的转化关系。这些性质和特征架起了不同类型有机质间聚集和沉积的桥梁。在沉积物(岩)中通过粒度或密度分级分离及孢粉相分析,也发现不同类型的有机质,如生物体、生物残体和无定形等,它们常与特定的无机矿物共生,如无定形多富集在黏粒级颗粒中,而生物体和生物残体多富集在粗颗粒中。进一步溯源发现沉积物(岩)中的各类有机质与生物有机质或海洋中有机质的类型极具相似性,这些特征展现各类型有机质在沉积过程中的差异性。综合有机质的形态、性质以及与矿物共生关系,认为有机质可通过机械沉积、化学沉积和生物沉积等3种不同的方式沉积保存,其中机械沉积的有机质以惰性的生物残体为主,化学沉积的有机质以活性极强的无定形为主,生物沉积有机质以活性较强的微生物和粘附物为主。有机质沉积方式及有机质特征、矿物—有机质间关系和保存条件的差异,决定了有机质的演化命运的不同,进而对有机质生烃以及碳循环产生重要的影响,因而应引起人们的高度关注。     

数值试验中时间步长的选取

建立一个二维的海陆风静力模式来讨论时间步长的选取，发现定时间步长不宜取得太大或者太小，必须是某个适当的值。变时间步长的模拟效果要比定步长理想。时间步长越大，海风中心强度模拟值变小。     

中国马尾藻属的研究Ⅲ.丛伞托序族

对中国马尾藻属，真马尾藻亚属，滑托组，丛伞托序族的种类进行系统研究。此族种类的主要特征是生殖托光滑，聚伞状排列在小校上，生殖托柄状部位都有生殖窝。多孢马尾藻是该族的非常特殊种类，它的分校和小分枝上密生刺和羽状分裂的藻叶。文中还报道了一个新种一长干马尾藻。模式标本产自广东省徐闻，还见于海丰。至今为止，丛伞托序族在中国共有两种。     

静海地震台地磁短周期变化及其在地震短临预报中的应用

近年来的一些研究表明，由于地震前孕震区地下介质的电性结构的变化，将导致地磁短周期转换函数发生异常变化。通过对地震前后的地磁短周期转换函数的参数的计算、分析和研究，有可能提取出可靠的地震短临前兆异常（曾小苹等，１９９０）。为了进一步开展对该方法研究工作并使其在我区地震预测预报研究中得到应用，我们使用了静海台的地磁记录资料，分析计算了该台地磁短周期转换函数在地震前后的变化情况，确立了该方法应用天津地区地震预报的短临异常特征及指标，取得了较好的效果。     

三维地闪监测数据分析与校验

选取福建省2015年三维系统地闪资料,采用同期雷电定位系统(ADTD)资料对其时空分布特征进行分析,利用雷电流峰值记录仪数据对2套系统地闪探测效率和定位误差校验,同时结合IEEE工作组和电力行业推荐的概率公式对三维系统地闪雷电流分布特征进行分析。结果表明:(1)2套系统监测到全省地闪密度空间分布趋势比较一致,在三明西南部地区及福州西部零星地区,三维系统地闪密度更低。(2)2套系统地闪频次年变化和日变化均呈单峰变化特征,但年变化中的10—12月,以及日变化中的09:00—12:00,三维系统监测到地闪频次更少。(3)三维系统地闪回击探测效率为40%,平均定位误差为2.75km。(4)在0~50kA区间,相比于负极性地闪,三维系统正极性地闪雷电流幅值分布更加集中,在26~84kA区间三维地闪雷电流幅值相比于IEEE推荐值和规程推荐值偏大。     

Vegetation cover variation in the Qilian Mountains and its response to climate change in 2000–2011

An understanding 0f variati0ns in vegetati0n c0ver in resp0nse t0 climate change is critical f0r predicting and managing future terrestrial ec0system dynamics. Because scientists anticipate that m0untain ec0systems will be m0re sensitive t0 future climate change c0mpared t0 0thers, 0ur 0bjectives were t0 investigate the impacts 0f climate change 0n variati0n in vegetati0n c0ver in the Qilian M0untains （QLM）, China, between 2000 and 2011. T0 acc0mplish this, we used linear regressi0n techniques 0n 250-m MODIS N0rmalized Difference Vegetati0n Index （NDVI） datasets and mete0r0l0gical rec0rds t0 determine spati0temp0ral variability in vegetati0n c0ver and climatic fact0rs （i.e. temperature and precipitati0n）. Our results sh0wed that temperatures and precipitati0n have increased in this regi0n during 0ur study peri0d. In additi0n, we f0und that gr0wing seas0n mean NDVI was mainly distributed in the vertical z0ne fr0m 2,700 m t0 3,600 m in elevati0n. In the study regi0n, we 0bserved significant p0sitive and negative trends in vegetati0n c0ver in 26.71% and 2.27% 0f the vegetated areas. C0rrelati0n analyses indicated that rising precipitati0n fr0m May t0 August was resp0nsible f0r increased vegetati0n c0ver in areas with p0sitive trends in gr0wing seas0n mean NDVI. H0wever, there was n0 similar significant c0rrelati0n between gr0wing seas0n mean NDVI and precipitati0n in regi0ns where vegetati0n c0ver declined thr0ugh0ut 0ur study peri0d. Using spatial statistics, we f0und that veeetati0n c0ver freauentlvdeclined in areas within the 2,500-3,100 m vertical z0ne, where it has steep sl0pe, and is 0n the sunny side 0f m0untains. Here, the p0sitive influences 0f increasing precipitati0n c0uld n0t 0ffset the drier c0nditi0ns that 0ccurred thr0ugh warming trends. In c0ntrast, in higher elevati0n z0nes （3,900-4,500 m） 0n the shaded side 0f the m0untains, rising temperatures and increasing precipitati0n impr0ved c0nditi0ns f0r vegetati0n gr0wth. Increased precipitati0n als0 facilitated vegetati0n gr0wth in areas experiencing warming trends at l0wer elevati0ns （2,000-2,400 m） and 0n l0wer sl0pes where water was m0re easily c0nserved. We suggest that spatial differences in variati0n in vegetati0n as the result 0f climate change depend 0n l0cal m0isture and thermal c0nditi0ns, which are mainly c0ntr0lled by t0p0graphy （e.g. elevati0n, aspect, and sl0pe）, and 0ther fact0rs, such as l0cal hydr0l0gy.