状态空间模型在区域森林景观生态经济研究中的应用

通过对江苏省溧阳地区森林景观进行生态经济研究 ,获取区域森林景观的生态经济特征数据的基础上 ,结合森林动态数据 ,根据研究对象的系统机理建立状态空间模型。该模型可用于进行综合生态经济评价及其规划。文中应用状态空间模型进行区域森林景观生态经济功能的多目标规划.     

Year-round activity patterns in a hyperdiverse community of rainforest amphibians in Madagascar

Madagascar hosts a high diversity of amphibians estimated at over 500 species, nearly all of them endemic. Surprisingly few data are available on the activity cycles of this fauna, despite its importance for ecological, evolutionary and conservation research. Here we report the results of a year-round survey of amphibians along a transect bordering the Analamazaotra forest near Andasibe in central eastern Madagascar. During 120 transect walks evenly spaced through the year, a total of 2530 individuals of 40 species of anurans was observed. Abundance was higher during the warm/rainy season (December to April) and peaked in February. Of the five climatic predictors measured, only mean temperature and relative humidity showed high importance values, and multi-model averages indicate that these two variables have a strong effect on amphibian abundance along the transect. Species richness showed no evident peak during the study period and was best explained by a model including average temperature and rainfall. Canonical correspondence analysis indicates that Boophis sibilans, B. tephraeomystax, B. boehmei and Plethodontohyla notosticta were more frequently encountered along the transect on cold and humid days while Plethodontohyla mihanika, Gephyromantis boulengeri and Spinomantis aglavei were distinctly more abundant on cold and dry days, and Paradoxophyla palmata on warm and dry days. The results of our study flag a number of species as suitable candidates for future monitoring initiatives and suggest that a simple combination of visual and acoustic surveys can estimate amphibian activity with high sample sizes in Madagascar’s rainforests.     

Patterns of artificial avian nest predation by introduced rats in a fragmented laurel forest (Tenerife,Canary Islands)

The importance of introduced rats as damaging factors on island biotas is globally recognized. The predation of artificial avian nests by Ship rats (Rattus rattus) in fragmented laurel forests in Tenerife (Canary Islands) was explored. The influence of road edge, patch type, and position (ground versus tree) on nest survival in two forest remnants differing in conservation degree, were assessed using failure‐time analysis. Overall, nest predation was greater in the preserved than in the disturbed remnant. Nest predation also differed among and within patches, variation being greater within the disturbed remnant. The probability of nest failure was higher at the interior than along the road edge in both remnants, but the road edge effect on nest predation was more intense in the disturbed remnant. Predation pressure was higher in patches of mature, closed canopy or dense understorey with stump sprouting. Ground nests were predated at higher rates than tree nests at any location. These results contrast with other nest predation studies in fragmented landscapes where forest edges rather than the interior are more frequently used by predators. Predatory activity by rats seems negatively affected by forest disturbance and road edge effect. Overall, artificial nest predation patterns by rats confirm a potential predation risk for the avifauna of the Canarian laurel forest. This should be considered in implementing conservation management programmes.     

COD/N对亚硝酸盐型同步硝化反硝化脱氮的影响

采用序批式活性污泥法,对人工配制的城市污水,通过控制泥龄成功实现亚硝酸盐型同步硝化反硝化,并考察了不同COD/N对亚硝酸盐型同步硝化反硝化效果的影响.试验结果显示:适宜的泥龄下,在控制适宜的pH、DO及COD:N为6.5左右的条件下,COD、氨氮和总氮的去除率分别可达90%~95%、99%左右、90%以上.因此,适宜的泥龄时,控制反应器内适宜的COD/N,可以使亚硝酸盐型同步硝化反硝化取得很好的效果.     

数字签名保护的OSPF路由协议的安全性研究

OSPF路由协议是网络上应用最为广泛的链路状态协议之一,用于在网络上分发路由信息,但是这个担负着因特网上路由信息分发任务的重要协议在其制定之初并没有有效的安全手段.为此,IETF提出了数字签名保护的OSPF路由协议.阐述了数字签名保护的OSPF协议的设计思想和实现技术,构筑了带数字签名保护功能的路由器组成的实验网络,对路由协议的数字签名方案进行了仿真试验并得到了系统的数据,在此基础上分析了数字签名保护的OSPF协议的安全特性.     

宁夏彭阳县退耕还林还草研究

运用了生态学、经济学的办法,在彭阳县退耕还林还草的大前提下,对于彭阳县的各种状况进行了分析,探讨了以农林牧复合体系为指导的生了一条果园复合经营脱贫致富的新路子。态农业,并论证了其可行性,分析了三种模式综合所能带来的生态经济效益,开创     

浅论知识经济时代图书馆员的继续教育

论述了图书馆员继续教育的意义,分析了图书馆员继续教育的内容,并提出了图书馆员继续教育的若干措施和途径。     

基于MODIS数据的2001-2018年黑龙江省林火时空分布

[目的]黑龙江省是中国重要的林业省份之一,也是受林火危害最严重的地区之一.通过遥感数据获取森林火点信息,充分了解近年来黑龙江省林火发生的时空分布格局,探索林火发生规律.[方法]根据黑龙江省2001—2018年MODIS(分辨率成像光谱仪)遥感图像的MCD64A1火烧迹地产品数据集,提取林火火点信息,结合历史火灾记录资料...     

基于光学-ALS变量组合和非参数模型的天然次生林地上生物量估算

【目的】通过组合机载激光雷达(airborne laser scanning, ALS)数据和Sentinel-2A数据提取特征变量,探讨估算天然次生林地上生物量(aboveground biomass, AGB)最佳的变量组合方式和估算方法。【方法】以2015年ALS数据、2016年Sentinel-2A数据和黑龙江帽儿山林场森林资源连续清查固定样地数据为数据源,通过ALS数据提取高度特征变量(all the LiDAR variables, 记为A_L),Sentinel-2A数据提取若干植被指数变量(all the optical variables, 记为A_O),然后将光学-ALS结合变量(combined optical and LiDAR index, COLI,记为I_COL)结合成为新的变量 I_{\mathrm{CO}{\mathrm{L}}_1} 和 I_{\mathrm{CO}{\mathrm{L}}_2} ,以6组特征变量组合方式(A_O+A_L、 I_{\mathrm{CO}{\mathrm{L}}_1} 、 I_{\mathrm{CO}{\mathrm{L}}_2} 、 I_{\mathrm{CO}{\mathrm{L}}_1} +A_O+A_L、 I_{\mathrm{CO}{\mathrm{L}}_2} +A_O+A_L、 I_{\mathrm{CO}{\mathrm{L}}_1} + I_{\mathrm{CO}{\mathrm{L}}_2} +A_O+A_L)作为输入变量,分别使用多元线性逐步回归(stepwise multiple linear regression,SMLR)、K-最近邻法(K-nearest neighbor,K-NN)、支持向量回归(support vector regression,SVR)、随机森林(random forest, RF)和堆叠稀疏自编码器(stack sparse auto-encoder,SSAE)共5种方法构建了天然次生林AGB估算模型,探讨I_COLs变量以及不同模型对生物量估测精度的影响。【结果】结合变量I_COLs对于森林AGB的估算十分有效,加入I_COLs变量能够很大提高森林AGB模型的估算精度;与其他4种模型相比,无论使用哪些变量作为输入数据,SSAE模型的精度最高;当使用SSAE模型,以光学和ALS变量组合 ( I_{\mathrm{CO}{\mathrm{L}}_1} + I_{\mathrm{CO}{\mathrm{L}}_2} +A_O+A_L)作为输入特征变量时,模型的准确性最高:R²=0.83,均方根误差为11.06 t/hm²,相对均方根误差为8.23%。【结论】结合变量COLIs能够有效地提高天然次生林AGB的估算精度,而且深度学习模型(SSAE)在估算天然次生林AGB方面优于其他预测模型。总体而言,利用ALS和Sentinel-2A数据组合变量的SSAE模型可以较准确地估算森林AGB,为天然次生林地上生物量的估算和碳储量评估提供技术支持。     

基于ICESat-GLAS数据和模糊模式识别算法识别森林类型

【目的】利用冰、云和陆地高程卫星-地球科学激光测高系统(ICESat-GLAS)回波波形数据,通过模糊模式识别算法,提出波形特征参数组合,对森林类型进行识别研究,以期提高森林类型分类精度。【方法】利用不同森林类型冠层在GLAS回波波形上表现出的差异性,提取波形特征参数 R_{\mathrm{fi}{\mathrm{t}}_1} 、K₁'和 \overline{K_1} ;将本研究提取的波形特征参数与其他波形特征参数相结合,建立波形特征参数组合;对样本数据波形特征参数进行指标归一化和奇异点检测处理,剔除样本数据中的奇异点样本;结合模糊模式识别算法,计算不同森林类型分类精度。【结果】针叶林和阔叶林森林类型分类总精度为96.30%,其中,针叶林和阔叶林森林类型分类精度分别为92.86%和97.50%;针叶林、阔叶林和混交林森林类型分类总精度为84.51%,其中,针叶林、阔叶林和混交林森林类型分类精度分别为85.71%、97.50%和52.94%。【结论】模糊模式识别算法在森林类型分类方面具有一定优势,尤其在针叶林和阔叶林森林类型识别方面,识别精度较高。