“天舟一号”货运飞船在轨污染探测数据分析

目的分析"天舟一号"(TZ-1)货运飞船的空间污染探测器的在轨探测数据。方法 TZ-1货运飞船上的污染探测器采用石英晶体微量天平(QCM),利用污染物沉积在QCM探测器传感晶片表面引起的振荡频率变化情况来分析航天器在轨空间污染环境。根据其探测原理,通过分析下传的原始数据,得到航天器在轨的污染累积量结果。结果航天器在轨飞行过程中,污染累积已达到会导致污染敏感器件光学性能明显退化的程度,并且污染源温度是影响航天器污染累积量的一个重要因素,可以将其作为航天器在轨污染控制的重要措施。结论该研究结果可以为航天器污染设计、控制提供参考,为提高航天器可靠性设计提供数据支持。     

苯并(a)芘在黄河水体不同粒径颗粒物上的表面吸附和分配作用特征

模拟实验研究了苯并(a)芘在黄河水体不同粒径颗粒物上的吸附作用,重点探讨了颗粒物粒径对苯并(a)芘的表面吸附和分配作用的影响.结果表明:(1)苯并(a)芘在黄河水体颗粒物上的吸附符合表面吸附-分配作用复合模式(2)苯并(a)芘在粒径d≥0.025 mm颗粒物上的吸附以表面吸附为主,表面吸附对吸附的贡献在68.7%至82.4%之间;当苯并(a)芘液相平衡浓度为0～8.87μg·L-1时,其在粒径0 007 mm≤d＜0.025 mm颗粒物上的吸附以表吸附作用为主,当液相平衡浓度大于8.87μg·L-1时,吸附以分配作用为主;苯并(a)芘在粒径d＜0.007 mm颗粒物上的吸附以分配作用为主;(3)苯并(a)芘在不同粒径颗粒物上的表面吸附对总吸附的贡献大小顺序为:(d≥0.025 mm)＞(0.007 mm≤d＜0 025 mm)＞(d＜0.007 mm);(4)苯并(a)芘在不同粒径颗粒物中的分配系数与有机质含量呈线性相关,其标化分配系数Koc约为1.26×105L·kg-1.     

苏云金芽胞杆菌苏云金素缺失突变株的筛选及特性研究

利用高温和SDS对苏云金素高产菌株CT-43-1c进行了质粒消除,筛选得到一株不产苏云金素的无晶体突变株BMB0806;并通过SDS-PAGE、高效液相色谱(HPLC)和脉冲电泳(PFGE)分析了野生型菌株CT-43、出发菌株CT-43-1c和突变株BMB0806杀虫晶体蛋白的组成、苏云金素的产量和质粒图谱之间的差异.结果表明,突变株BMB0806与菌株CT-43和CT-43-1c相比,分别缺失了3个和2个大质粒,从而不再产生苏云金素和由cry1B基因编码的分子量为140×103的杀虫晶体蛋白.进一步分析三者质粒图谱后发现,突变株BMB0806中苏云金素的缺失和cry1B基因所在的大质粒A直接相关.图5参12     

多年连续种植转基因Bt汕优63稻田水体和土壤中Cry1Ab/c蛋白残留调查

以湖北武汉、随州、武穴和孝感以及山东德州5个多年转基因水稻种植区为试验地,在水稻生育期采集转cry1 Ab/c基因水稻Bt汕优63(Bt-SY63)和对照非转基因汕优63(SY63)稻田水体和土壤,使用酶联免疫吸附测定(ELISA)方法对稻田水体和土壤Cry1 Ab/c蛋白残留量进行动态监测.结果显示,与SY63稻田相比,连续种植2～4 a后,不同生育期Bt-SY63稻田水体Cry1Ab/c蛋白残留量大多与同一生育期SY63样品间差异未达显著水平(P＞0.05),最高残留量为0.373 ng· mL-1.与水体Cry1Ab/c蛋白残留情况相似,不同生育期Bt-SY63稻田土壤Cry 1Ab/c蛋白残留量大都低于试剂盒检测限(0.25 ng·g-1),仅随州苗期、德州拔节期和开花期样品有微量残留,鲜土残留量分别为0.261、0.540和0.361 ng·g-1,并分别与SY63样品间差异显著(P＜0.05).另外,多年连续种植Bt-SY63水稻后,2、3和4a种植年限的Bt-SY63稻田水体和土壤中Cry1Ab/c蛋白残留量之间大都没有显著差异(P＞0.05).认为连续种植2、3和4a的Bt-SY63水稻稻田水体和土壤仅存在微量Cry1Ab/c蛋白残留,不会造成Cry1Ab/c蛋白在稻田水体和土壤中的累积.     

苏云金芽孢杆菌新基因cry1Ab17的克隆和生物信息学

利用高效克隆PCR产物的专用载体pMD18T,直接从苏云金芽孢杆菌WB9的PCR产物中克隆了cry1Ab17新基因.测序结果表明,该基因(GenBank登录号为AY646166)由3471个碱基组成,其编码的蛋白质含有1156个氨基酸残基,其中亲水性氨基酸占30.8%,疏水性氨基酸占45.2%,酸性氨基酸占12.9%,碱性氨基酸占11.1%.氨基酸序列的同源性分析结果表明,Cry1Ab17蛋白与已报道的Cry1Ab蛋白同源性为95.4%～99.7%,该蛋白的4个氨基酸残基———Pro170、Gly449、Gly796和Gly863与其它已报道Cry1Ab蛋白相应位置的氨基酸残基均不同.在核苷酸序列和氨基酸序列多重比较的基础上,应用PAUP4.0构建了Cry1A蛋白家族的系统发育树.SignalP分析结果显示,Cry1Ab17蛋白中不含信号肽序列.此外,对Cry1Ab17蛋白的二级结构和3个结构域也进行了预测和分析.图4表2参15     

苯酚降解菌红球菌PNAN5菌株(Rhodococcus sp.strain PNAN5)的分离鉴定、降解特性及其开环双加氧酶性质研究

分离到一株能以苯酚、苯甲酸、对甲酚、萘为唯一碳源和能源生长、具有同时降解单环和双环芳烃能力的细菌菌株,经生理生化、16SrRNA基因序列分析等鉴定为红球菌PNAN5菌株(Rhodococcussp.strainPNAN5).在实验条件下和在温度为20～40℃、pH7 0～9 0范围内菌株PNAN5降解苯酚的效率保持在80%～100%之间,苯酚浓度在2～10mmol·L-1范围内变化对降解效率没有明显的影响.该菌株通过邻苯二酚1,2 双加氧酶催化的开环途径降解芳烃,不同于已知的浑浊红球菌(R.opacus)是通过邻苯二酚2,3 双加氧酶催化芳烃降解.以细胞裂解液测定该酶的酶促反应动力学常数Km值为35 94μmol·L-1,Vmax为0 84μmol·L-1·min-1·mg-1.     

Conservation implications of anthropogenic impacts on visual communication and camouflage

Anthropogenic environmental impacts can disrupt the sensory environment of animals and affect important processes from mate choice to predator avoidance. Currently, these effects are best understood for auditory and chemosensory modalities, and recent reviews highlight their importance for conservation. We examined how anthropogenic changes to the visual environment (ambient light, transmission, and backgrounds) affect visual communication and camouflage and considered the implications of these effects for conservation. Human changes to the visual environment can increase predation risk by affecting camouflage effectiveness, lead to maladaptive patterns of mate choice, and disrupt mutualistic interactions between pollinators and plants. Implications for conservation are particularly evident for disrupted camouflage due to its tight links with survival. The conservation importance of impaired visual communication is less documented. The effects of anthropogenic changes on visual communication and camouflage may be severe when they affect critical processes such as pollination or species recognition. However, when impaired mate choice does not lead to hybridization, the conservation consequences are less clear. We suggest that the demographic effects of human impacts on visual communication and camouflage will be particularly strong when human‐induced modifications to the visual environment are evolutionarily novel (i.e., very different from natural variation); affected species and populations have low levels of intraspecific (genotypic and phenotypic) variation and behavioral, sensory, or physiological plasticity; and the processes affected are directly related to survival (camouflage), species recognition, or number of offspring produced, rather than offspring quality or attractiveness. Our findings suggest that anthropogenic effects on the visual environment may be of similar importance relative to conservation as anthropogenic effects on other sensory modalities.     

Using environmental heterogeneity to plan for sea‐level rise

Environmental heterogeneity is increasingly being used to select conservation areas that will provide for future biodiversity under a variety of climate scenarios. This approach, termed conserving nature's stage (CNS), assumes environmental features respond to climate change more slowly than biological communities, but will CNS be effective if the stage were to change as rapidly as the climate? We tested the effectiveness of using CNS to select sites in salt marshes for conservation in coastal Georgia (U.S.A.), where environmental features will change rapidly as sea level rises. We calculated species diversity based on distributions of 7 bird species with a variety of niches in Georgia salt marshes. Environmental heterogeneity was assessed across six landscape gradients (e.g., elevation, salinity, and patch area). We used 2 approaches to select sites with high environmental heterogeneity: site complementarity (environmental diversity [ED]) and local environmental heterogeneity (environmental richness [ER]). Sites selected based on ER predicted present‐day species diversity better than randomly selected sites (up to an 8.1% improvement), were resilient to areal loss from SLR (1.0% average areal loss by 2050 compared with 0.9% loss of randomly selected sites), and provided habitat to a threatened species (0.63 average occupancy compared with 0.6 average occupancy of randomly selected sites). Sites selected based on ED predicted species diversity no better or worse than random and were not resilient to SLR (2.9% average areal loss by 2050). Despite the discrepancy between the 2 approaches, CNS is a viable strategy for conservation site selection in salt marshes because the ER approach was successful. It has potential for application in other coastal areas where SLR will affect environmental features, but its performance may depend on the magnitude of geological changes caused by SLR. Our results indicate that conservation planners that had heretofore excluded low‐lying coasts from CNS planning could include coastal ecosystems in regional conservation strategies.     

Effectiveness of conservation easements in agricultural regions

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity‐score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions.     

The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.