Bias from farmer self-selection in genetically modified crop productivity estimates: Evidence from Indian data

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

Bryozoan populations reflect nutrient enrichment and productivity gradients in rivers

1. The hypothesis that nutrient enrichment will affect bryozoan abundance was tested using two complementary investigations; a field-based method determining bryozoan abundance in 20 rivers of different nutrient concentrations by deploying statoblast (dormant propagule) traps and an experimental laboratory microcosm study measuring bryozoan growth and mortality. These two methods confirmed independently that increased nutrient concentrations in water promote increases in the biomass of freshwater bryozoans. 2. Statoblasts of the genus Plumatella were recorded in all rivers, regardless of nutrient concentrations, demonstrating that freshwater bryozoans are widespread. Concentrations of Plumatella statoblasts were high in rivers with high nutrient concentrations relative to those with low to moderate nutrient concentrations. Regression analyses indicated that phosphorus concentrations, in particular, significantly influenced statoblast concentrations. 3. Concentrations of Lophopus crystallinus statoblasts were also higher in sites characterised by high nutrient concentrations. Logistic regression analysis revealed that the presence of L. crystallinus statoblasts was significantly associated with decreasing altitude and increasing phosphorus concentrations. This apparently rare species was found in nine rivers (out of 20), seven of which were new sites for L. crystallinus. 4. Growth rates of Fredericella sultana in laboratory microcosms increased with increasing nutrient concentration and high mortality rates were associated with low nutrient concentrations. 5. Our results indicate that bryozoans respond to increasing nutrient concentrations by increased growth, resulting in higher biomasses in enriched waters. We also found that an important component of bryozoan diets can derive from food items lacking chlorophyll a. Finally, bryozoans may be used as independent proxies for inferring trophic conditions, a feature that may be especially valuable in reconstructing historical environments by assessing the abundance of statoblasts in sediment cores.

Ambient solar wind's effect on ICME transit times

Most empirical and numerical models of Interplanetary Coronal Mass Ejection (ICME) propagation use the initial CME velocity as their primary, if not only, observational input. These models generally predict a wide spread of 1 AU transit times for ICMEs with the same initial velocity. We use a 3D coupled MHD model of the corona and heliosphere to determine the ambient solar wind's effect on the propagation of ICMEs from 30 solar radii to 1 AU. We quantitatively characterize this deceleration by the velocity of the upstream ambient solar wind. The effects of varying solar wind parameters on the ICME transit time are quantified and can explain the observed spread in transit times for ICMEs of the same initial velocity. We develop an adjustment formula that can be used in conjunction with other models to reduce the spread in predicted transit times of Earth-directed ICMEs.