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.     

Quantifying the effect of buffer zones,crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level

The development of genetically modified (GM) crops has led the European Union (EU) to put forward the concept of ‘coexistence’ to give farmers the freedom to plant both conventional and GM varieties. Should a premium for non-GM varieties emerge in the market, ‘contamination’ by GM pollen would generate a negative externality to conventional growers. It is therefore important to assess the effect of different ‘policy variables’ on the magnitude of the externality to identify suitable policies to manage coexistence. In this paper, taking GM herbicide tolerant oilseed rape as a model crop, we start from the model developed in Ceddia et al. [Ceddia, M.G., Bartlett, M., Perrings, C., 2007. Landscape gene flow, coexistence and threshold effect: the case of genetically modified herbicide tolerant oilseed rape (Brassica napus). Ecol. Modell. 205, pp. 169–180] use a Monte Carlo experiment to generate data and then estimate the effect of the number of GM and conventional fields, width of buffer areas and the degree of spatial aggregation (i.e. the ‘policy variables’) on the magnitude of the externality at the landscape level. To represent realistic conditions in agricultural production, we assume that detection of GM material in conventional produce might occur at the field level (no grain mixing occurs) or at the silos level (where grain mixing from different fields in the landscape occurs). In the former case, the magnitude of the externality will depend on the number of conventional fields with average transgenic presence above a certain threshold. In the latter case, the magnitude of the externality will depend on whether the average transgenic presence across all conventional fields exceeds the threshold. In order to quantify the effect of the relevant ‘policy variables’, we compute the marginal effects and the elasticities. Our results show that when relying on marginal effects to assess the impact of the different ‘policy variables’, spatial aggregation is far more important when transgenic material is detected at field level, corroborating previous research. However, when elasticity is used, the effectiveness of spatial aggregation in reducing the externality is almost identical whether detection occurs at field level or at silos level. Our results show also that the area planted with GM is the most important ‘policy variable’ in affecting the externality to conventional growers and that buffer areas on conventional fields are more effective than those on GM fields. The implications of the results for the coexistence policies in the EU are discussed.     

Yield response of potato to spatially patterned nitrogen application

Although crop response to nitrogen fertilization has long been studied, classical experimental designs have led to inadequate accounting of spatial variability in field properties and yield response. Analytical methods to explicitly account for spatial variability now exist but the complementary modification of experimental design is still developing. There is a need to combine these analytical methods with non-traditional experimental design. A 2-year study was implemented to assess the response of potato (Solanum tuberosum cv. Kennebec) yield to nitrogen fertilizer rate. We used a transect-type plot design where four nitrogen treatments (0, 56, 112, and 280 kg N ha^?1) were applied systematically in a continuous sinusoidal pattern along longitudinal transects. Measured field properties included topography, soil texture, pre-application soil nitrate levels, and plant available soil water content. A random field linear model was used to simultaneously account for treatment effects and soil properties. The results showed that treatment effects were significantly different from each other; however, if spatially correlated errors were accounted for, these differences were smaller and significance levels lower. Nitrogen response functions varied widely throughout the field. Of the covariates, only clay content proved important in explaining spatial differences in response to N. The sinusoidal response pattern of N was similar over the 2 years but the amplitudes varied due to differences in weather. Interactions between uncharacteristically high rainfall and a sandy field soil may have minimized discernable effects of the other covariates. The results demonstrated how the statistical analysis of potato response to a patterned application of nitrogen fertilizer can take advantage of spatial correlations to understand the response of potato to nitrogen application over larger areas.     

MAP沉淀法目标产物最优形成条件及分析方法

为了确定鸟粪石(MAP：MgNH₄PO₄·6H₂O)形成的最优条件,引入化学剖析法,利用酸溶液将鸟粪石沉淀法中所得沉淀物溶解后进行相应的元素分析;提出一种根据沉淀物中的NH⁺₄-N含量间接计算确定鸟粪石含量(即纯度)的分析方法.根据这种计算分析方法,分别得出了不同pH条件下以自来水(主要为地下水)和超纯水作为溶剂所合成的鸟粪石纯度,并对pH和Ca²⁺在鸟粪石形成过程中的影响进行了评估.结果表明,该计算分析方法能够有效实现对MAP沉淀法目标产物的定量分析,弥补了国内外目前普遍依靠XRD技术定性判断所得沉淀物中鸟粪石是否存在的缺陷.以超纯水作为溶剂时,使鸟粪石纯度>90%的最佳pH范围在7.5～9.0,而以自来水为溶剂时,获得相同鸟粪石纯度最佳pH范围则是7.0～7.5.实际污水中常常含有相当数量的Ca²⁺,实施碱性条件(pH>8.0)的MAP沉淀势必大幅降低鸟粪石的纯度.因此,对实际污水回收磷而言,MAP沉淀法的最优pH条件应控制在中性范围(<8.0)以内.     

Future risk of flooding: an analysis of changes in potential loss of life in South Holland (The Netherlands)

Potential loss of life is considered an important indicator of flood risk. We examine the future development of potential loss of life due to flooding for a major flood prone area in The Netherlands. The analysis is based on projections and spatial distribution of population under a high economic growth scenario and a loss of life model. Results show that the projected population growth in flood prone areas is higher than average in the Netherlands between 2000 and 2040. Due to this effect the potential number of fatalities is projected to increase by 68% on average for 10 different flood scenarios, not including impacts from climate change and sea level rise. Just sea level rise of 0.30 m leads to an average 20% increase in the number of fatalities. The combined impact of sea level rise and population growth leads to an estimated doubling in the potential number of fatalities. Taking into account increasing probability of flooding due to sea level rise and extreme river discharges, the expected number of fatalities could quadruple by 2040. The presented results give a conservative and upper bound estimate of the increase of the risk level when no preventive measures are undertaken. It is found that the consideration of the exact spatial distribution of population growth is essential for arriving at reliable estimates of future risk of flooding.     

Estimating carbon in savanna ecosystems: rational distribution of effort

Minimising the cost of repeatedly estimating C (C) stocks is crucial to the financial viability of projects that seek to sell C credits. Depending on the price of C, this may imply less or more sampling effort than would be applied for science objectives. In systems with heterogeneous C pools, such as savannas, this translates into a variable-effort sampling strategy that maximises the marginal additional C that can be claimed per incremental unit of effort expended. Analysis of a savanna in north-eastern South Africa indicates relatively modest returns per hectare due to the small C quantities and low sequestration rates. Under these conditions, areas in excess of 1,000 ha and infrequent sampling frequencies of 5–10 years are required to make such projects financially viable. For such projects the sample variance, number of samples, cost per sample and establishment costs have negligible impacts on financial viability. It was also found that the soil-C pool contributes up to three times the net returns of the aboveground C pool and provides a strong argument to monitor soil C for certification and market trading. The financial viability estimates, however, do not include the management or opportunity costs incurred in changing the land use. The economies of scale identified in this study combined with the massive area covered by savannas indicate that these additional costs can be covered. Further research is recommended to quantify these costs and interrogate the feasibility of large scale (in excess of 10,000 ha) C-sink projects in savanna systems.