Impact of wildflower strips on biological control of cabbage lepidopterans

In a 2-year experiment we investigated whether wildflower strips can be used to enhance the control of cabbage moth, Mamestra brassicae L., and cabbage white butterfly, Pieris rapae L. At two sites, including six organically cultivated fields, M. brassicae egg parasitism and predation rates were determined along with an assessment of larval parasitism rates in M. brassicae and P. rapae using a DNA-based approach. Within each field, plots with and without wildflower strips were sampled and a grid design of 3 m × 3 m was used to analyze the spatial pattern of parasitism. The provision of wildflower strips provided an idiosyncratic effect on the control of lepidopterans: parasitism rates in M. brassicae eggs and larvae were not affected, whereas parasitism rates of larval P. rapae were significantly enhanced by the wildflower strips at one of the two sites. Moreover, at one site predation rates on M. brassicae eggs were significantly enhanced in the wildflower strip plots. Geostatistical analysis showed no distinct spatial patterns in parasitism rates. These results demonstrate that the provision of wildflower strips does not necessarily enhance biological control of lepidopteran cabbage pests and suggest that site-specific environmental factors strongly affect the impact of wildflower strips.     

土壤中嗪草酮迁移和降解的研究

 通过两季马铃薯大田试验，研究了嗪草酮在灌溉沙壤土中的消失和移动情况。结果表明，表层土壤中，嗪草酮施用后最初7～15天内其含量急剧降低，此后随时间推移降低幅度平缓，1993年和1994年试验结束时的残留量分别为5.9μg/kg和2.3μg/kg。两年共采集的379个土样（分布在15～75cm各土层）中只有5个检测到有嗪草酮。1994年大田135cm土层处的水样中，嗪草酮的检测率高达66％，检测浓度范围为0.06～15.85μg/kg，平均浓度为1.94μg/kg。相比较，嗪草酮在大田试验中的消失速率远大于实验室控制条件下的降解速率。     

垃圾渗沥液中氨氮的电化学氧化

针对目前国内外垃圾渗沥液处理中存在的问题,采用电化学氧化与上流式厌氧污泥床（UASB）相结合,研究建立了对香港垃圾渗沥液的二步法处理工艺．本文着重探讨了电化学间接氧化去除渗沥液中氨氮的反应机制及主要影响因素,并通过实验找出了最佳的操作条件：入水初始 pH值为9.0;流速为0.01－0.10cm/s;CI加入量2000mg/L;电流密度 32.3mA/cm²．在此条件下,经过 6h电解后,UASB反应器出水中NH_－N和COD的去除率分别达到100％和87％．对该电化学氧化过程的运行成本进行了评估．     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.