植物促生菌应用研究进展

植物促生菌即PGPB不仅在农业生产中促进植物生长以及防治植物病害,还逐渐应用于环境保护方面。文章从以下几方面就PGPB的研究进展进行了综述,包括PGPB在农业和环境中的应用、PGPB内生菌、生物防治型PGPB、PGPB的基因工程改良、PGPB剂型等。最后展望了该领域的研究方向。     

用SOS/umu试验评价降雨径流遗传毒性的变化

通过SOS/umu试验分析检测屋面和道路在2017年5、6月2场降雨过程中的遗传毒性变化。结果表明,从降雨初期到结束,在5月份屋面产生降雨径流2 h内和道路产生径流20 min内雨水样品的检测结果均呈阳性,诱导率IR均大于2,表现出DNA损伤效应;在6月份屋面产生降雨径流60 min内和道路产生径流10~60 min内雨水样品的结果均呈阳性,表现出遗传毒性。2场降雨中屋面和道路雨水样品的TEQ4-NQO均随降雨时间先增加后逐渐减小,5月份屋面雨水样品的毒性大于路面雨水样品的毒性,6月份则相反。遗传毒性分析降雨径流中污染物毒性的变化为雨水的安全利用提供理论基础。     

灾后应急资源配送的LRP模型与算法研究

针对灾后应急资源配送的优化问题,考虑配送中心定位和配送路径方案的相互影响,建立应急资源配送的“定位-路径安排问题”优化模型,给出应急配送中心定位和配送可靠路径的全局优化方案。根据该模型的特点,设计多吸引子的离散粒子群优化算法,并结合仿真与分析,验证模型和算法的有效性。模型与算法的研究,对于突发事件下不确定交通路网应急资源配送决策具有一定指导意义。     

基于B-P人工神经网络的环境测点的优选

为了对有多项污染物的环境测点进行优选,提出了单项污染物对环境作用的“相对贡献率"和多项污染物对环境综合作用的“作用和贡献率"的新概念及其计算公式。将B-P神经网络原理与逐步聚类分析思想相结合,用于环境测点聚类优选。该方法用于成都市12个环境测点的优选结果符合客观实际。此外,它还具有简便实用、客观性好的特点。      

Efficacy of Land-Cover Models in Predicting Isolation of Marbled Salamander Populations in a Fragmented Landscape

Abstract:  Amphibians worldwide are facing rapid declines due to habitat loss and fragmentation, disease, and other causes. Where habitat alteration is implicated, there is a need for spatially explicit conservation plans. Models built with geographic information systems (GIS) are frequently used to inform such planning. We explored the potential for using GIS models of functional landscape connectivity as a reliable proxy for genetically derived measures of population isolation. We used genetic assignment tests to characterize isolation of marbled salamander populations and evaluated whether the relative amount of modified habitat around breeding ponds was a reliable indicator of population isolation. Using a resampling analysis, we determined whether certain land-cover variables consistently described population isolation. We randomly drew half the data for model building and tested the performance of the best models on the other half 100 times. Deciduous forest was consistently associated with lower levels of population isolation, whereas salamander populations in regions of agriculture and anthropogenic development were more isolated. Models that included these variables and pond size explained 65–70% of variation in genetically inferred isolation across sites. The resampling analysis confirmed that these habitat variables were consistently good predictors of isolation. Used judiciously, simple GIS models with key land-cover variables can be used to estimate population isolation if field sampling and genetic analysis are not possible.     

Consideration of fuzziness: Is it necessary in modelling fish habitat preference of Japanese medaka (Oryzias latipes)?

The present study aims to clarify the necessity and effectiveness of considering fuzziness in modelling fish habitat preference, and the advantages which would be achieved by considering it. For this purpose, genetic algorithm (GA) optimized habitat preference models under three different levels of fuzzification were compared with regard to prediction ability of the habitat use of Japanese medaka (Oryzias latipes) dwelling in agricultural canals in Japan. Field surveys were conducted in agricultural canals in Japan to establish a relationship between fish habitat preference and physical environments of water depth, current velocity, lateral cover ratio and percent vegetation coverage. The habitat preference models employed for testing the fuzzy-based approach were category model, fuzzy habitat preference model, and fuzzy habitat preference model with fuzzy inputs. All the models were developed at 50 different initial conditions. The effectiveness of the fuzzification in fish habitat modelling was assessed by comparing mean square error and standard deviation of the models, and fluctuation in habitat preference curves evaluated by each model. As a result, the effect of fuzzification appeared as smoother curves and was found to reduce fluctuation in habitat preference curves in proportion to the level of fuzzification. The smooth curves would be appropriate for expressing uncertainty in habitat preference of the fish, by which fuzzy habitat preference model with fuzzy input achieve the best prediction ability among the models. In conclusion, the present study revealed that there are two advantages of fuzzification: reducing fluctuations in habitat preference evaluation and improving prediction ability of the model. Therefore, the consideration of fuzziness would be appropriate for representing fish habitat preference under natural conditions.     

Does interspecific competition influence relationships between heterozygosity and fitness-related behaviors in juvenile Atlantic salmon (<Emphasis Type="Italic">Salmo salar</Emphasis>)?

Very few studies have investigated the effect of genetic diversity on the behavioral and phenotypic traits linked to the competitive ability of individuals. In this study, we reared juvenile Atlantic salmon (Salmo salar) alone or with the competitive rainbow trout (Oncorhynchus mykiss) in order to: (1) to assess correlations between heterozygosity and traits related to individual competitive ability [i.e., heterozygosity–fitness correlations (HFCs)] in Atlantic salmon, and (2) to evaluate the effect of the competitive rainbow trout on any such HFCs. We also tested whether a few loci had a disproportionately large effect (i.e., the local effect hypothesis) or, on the contrary, if all loci contributed equally (i.e., the global effect hypothesis) in explaining the observed HFCs. We found significant HFCs for phenotypic traits related to the competitive ability of juvenile Atlantic salmon, i.e., the growth rate and the distance to the feeding source. Some HFCs were nonlinear, suggesting that individuals with intermediate levels of heterozygosity were favored. In addition, we found that the competition exerted by rainbow trout only weakly modified these HFCs as the relationships were highly consistent across treatments. We demonstrated that the local-effect hypothesis best explained both linear and nonlinear HFCs. Overall, our results illustrated the importance of genetic diversity in explaining the behavioral variability observed within populations. Moreover, we provide evidence that, even if a competitive species can have strong ecological effects, the relationships between genetic diversity and fitness-related traits in juvenile Atlantic salmon were not influenced by such effects.     

Dynamic reserve design with the union-find algorithm

When reserve networks are established over time, there is a risk that sites will be developed in areas planned for future reservation, reducing the effectiveness of reserves. We developed a dynamic reserve design model that maximizes the expected number of species conserved, taking account of the risk of future habitat loss and fragmentation. The model makes use of the union-find algorithm, which is an efficient method for maintaining a list of connected regions in a graph as nodes and edges are inserted. A simple extension of the algorithm allows us to efficiently determine, for each species, when a sequence of site selections results in a reserve in which the species can persist. The extension also allows us to determine when a sequence of deforestation events results in the species becoming non-viable. The dynamic reserve design model is much more effective than commonly used heuristics, particularly when multiple connected sites are required for species persistence. The model also is able to solve much larger problems with greater effectiveness than the only previous dynamic reserve design model that considered site connectivity relationships. The union-find algorithm has much scope for addressing ecological management problems in which dynamic connectivity needs to be considered.     

Phylogeography and Limited Genetic Connectivity in the Endangered Boring Giant Clam across the Coral Triangle

Abstract: The Coral Triangle is the global center of marine biodiversity; however, its coral reefs are critically threatened. Because of the bipartite life history of many marine species with sedentary adults and dispersive pelagic larvae, designing effective marine protected areas requires an understanding of patterns of larval dispersal and connectivity among geographically discrete populations. We used mtDNA sequence data to examine patterns of genetic connectivity in the boring giant clam (Tridacna crocea) in an effort to guide conservation efforts within the Coral Triangle. We collected an approximately 485 base pair fragment of mtDNA cytochrome c oxidase 1 (CO1) from 414 individuals at 26 sites across Indonesia. Genetic structure was strong between regions (φ_ST=0.549, p < 0.00001) with 3 strongly supported clades: one restricted to western Sumatra, another distributed across central Indonesia, and a third limited to eastern Indonesia and Papua. Even within the single largest clade, small but significant genetic structure was documented (φ_ST=0.069, p < 0.00001), which indicates limited gene flow within and among phylogeographic regions. Significant patterns of isolation by distance indicated an average dispersal distance of only 25–50 km, which is far below dispersal predictions of 406–708 km derived from estimates of passive dispersal over 10 days via surface currents. The strong regional genetic structure we found indicates potent limits to genetic and demographic connectivity for this species throughout the Coral Triangle and provides a regional context for conservation planning. The recovery of 3 distinct evolutionarily significant units within a well‐studied taxonomic group suggests that biodiversity in this region may be significantly underestimated and that Tridacna taxa may be more endangered than currently recognized.