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.

Nitrogen management is essential to prevent tropical oil palm plantations from causing ozone pollution

More than half the world's rainforest has been lost to agriculture since the Industrial Revolution. Among the most widespread tropical crops is oil palm (Elaeis guineensis): global production now exceeds 35 million tonnes per year. In Malaysia, for example, 13% of land area is now oil palm plantation, compared with 1% in 1974. There are enormous pressures to increase palm oil production for food, domestic products, and, especially, biofuels. Greater use of palm oil for biofuel production is predicated on the assumption that palm oil is an “environmentally friendly” fuel feedstock. Here we show, using measurements and models, that oil palm plantations in Malaysia directly emit more oxides of nitrogen and volatile organic compounds than rainforest. These compounds lead to the production of ground-level ozone (O3), an air pollutant that damages human health, plants, and materials, reduces crop productivity, and has effects on the Earth's climate. Our measurements show that, at present, O3 concentrations do not differ significantly over rainforest and adjacent oil palm plantation landscapes. However, our model calculations predict that if concentrations of oxides of nitrogen in Borneo are allowed to reach those currently seen over rural North America and Europe, ground-level O3 concentrations will reach 100 parts per billion (109) volume (ppbv) and exceed levels known to be harmful to human health. Our study provides an early warning of the urgent need to develop policies that manage nitrogen emissions if the detrimental effects of palm oil production on air quality and climate are to be avoided.

Measuring productivity growth when technological change is biased - a new index and an application to UK agriculture

Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TFP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953-2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector. (C) 2004 Elsevier B.V. All rights reserved.

The use of bootstrapped Malmquist indices to reassess productivity change findings: an application to a sample of Polish farms

This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

Toward a combined seasonal weather and crop productivity forecasting system: Determination of the working spatial scale

A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.

The maintenance requirement of domestic drakes

1. Mature domestic drakes of 7 genotypes, ranging in live weight from 1.1to 5.1 kg, were each given a daily allowance of feed just below the level of recorded ad libitum intake. 2. House temperature was maintained at 26 degrees C for 16 weeks and then at 10 degrees C for a further 8 weeks. 3. Under these conditions, live weight quickly adjusted to the level of feed supplied and then remained stable. 4. Regression of metabolisable energy intake on live weight (W) yielded estimates of maintenance requirement of 583 kJ/kg W-0.75 center dot d at 10 degrees C and 523 kJ/kg W-0.75 center dot d at 26 degrees C.

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.

Seeds of growth? Agricultural productivity and the transitional dynamics of the Ramsey model

A two-sector Ramsey-type model of growth is developed to investigate the relationship between agricultural productivity and economy-wide growth. The framework takes into account the peculiarities of agriculture both in production ( reliance on a fixed natural resource base) and in consumption (life-sustaining role and low income elasticity of food demand). The transitional dynamics of the model establish that when preferences respect Engel's law, the level and growth rate of agricultural productivity influence the speed of capital accumulation. A calibration exercise shows that a small difference in agricultural productivity has drastic implications for the rate and pattern of growth of the economy. Hence, low agricultural productivity can form a bottleneck limiting growth, because high food prices result in a low saving rate.

Productivity change in Polish agriculture: an illustration of a bootstrapping procedure applied to Malmquist indices

This article illustrates the usefulness of applying bootstrap procedures to total factor productivity Malmquist indices, derived with data envelopment analysis (DEA), for a sample of 250 Polish farms during 1996-2000. The confidence intervals constructed as in Simar and Wilson suggest that the common portrayal of productivity decline in Polish agriculture may be misleading. However, a cluster analysis based on bootstrap confidence intervals reveals that important policy conclusions can be drawn regarding productivity enhancement.

Changes in light intensity during the rearing period can influence egg production in domestic fowl

1. A total of 240 Shaver White and 240 ISA Brown pullets that had been reared in multi-bird cages on a 10-h photoperiod, and maintained at a light intensity of 3 or 25 lux, or changed from 3 to 25 lux or from 25 to 3 lux at 9 or 16 weeks of age, were moved into individual-bird cages at 20 weeks and transferred to 15-h photoperiods at 25 lux. 2. In both breeds, birds transferred from 3 to 25 lux at 16 or 20 weeks laid significantly more eggs than birds maintained on the brighter intensity from one day or increased to it at 9 weeks. 3. Mean egg weight, shell deformation, albumen height, feed intake and body weight gain in lay were not significantly affected by the light intensity treatments during the rearing period. There was, however, a small, but significant, negative correlation of egg numbers with mean egg weight, although this only partially explained the difference in egg numbers. The differences in egg production were unrelated to rate of sexual maturation.

Change in the effect of constant photoperiods on the rate of sexual maturation in modern genotypes of domestic pullet

1. Data for modern egg-type hybrids reared on constant daylengths show that, as expected, they mature more quickly than earlier genotypes. However, the constant photoperiod which gives earliest sexual maturity has not changed as a result of selection and is 10 h for both early and modern genotypes. 2. Further analysis showed that the rate of delay in sexual maturity for constant photoperiods above 10 h is similar for modern and for early hybrids ( +0.29 d for each incremental one hour of photoperiod), the response of modern hybrids below 10 h ( +4.22 d for each one-hour reduction in photoperiod) is more than double that of early hybrids ( +1.71 d/h).