Soil surface nitrogen losses from agriculture in India: A regional inventory within agroecological zones (2000–2001)

We present soil surface nitrogen (N) budgets for the agricultural sector of India, calculated as inputs minus outputs over 21 agroecological zones (AEZ), for 2000–2001. Nearly 35.4 Tg N was input from different sources, with output from harvested crops of about 21.2 Tg N. Soil surface N balance for agricultural lands showed a surplus of about 14.4 Tg. Livestock manure constituted 44% of total inputs, followed by 32.5% from inorganic fertilizer, 11.9% from atmospheric deposition and 11.6% from N fixation. Though the N balance was negative in some states, due to aggregation of states in agroecological regions, all regions showed surplus N loads, with a range of about 19–110 kg/ha. The lowest loads were found for AEZ 17 in the Eastern Himalaya, with 19 kg/ha surplus, and the highest surplus N load in AEZ 7 with 111 kg/ha in Deccan plateau and the Eastern Ghats. Temporal trends in fertilizer consumption from 1950–2000 for India suggested a massive increase of ～47-fold, whereas production of major crops, rice, wheat and maize, increased nearly ～4.0-, 10- and 6-fold, respectively. Fertilizer consumption patterns were highly concentrated in Tamilnadu (204.6 kg/ha), Haryana (132.0 kg/ha) and Punjab (148.6 kg/ha). The paper addresses the role of agricultural intensification and its implications for water quality in agroecological regions of India.     

Numerical analysis on the Brisbane River plume in Moreton Bay due to Queensland floods 2010–2011

During the Queensland floods in the summer of 2010–2011, a flood-driven Brisbane River plume extended into Moreton Bay, Queensland, Australia, and then seaward, travelling in a northward direction. It covered approximately 500 km $^{2}$ . This paper presents a three- dimensional hydrodynamic numerical model investigation into the behaviour of the Brisbane River plume. The model was verified by using satellite observations and field measurement data. The present study concludes that the high river discharge was the primary factor determining the plume size and its seaward extensions. A notable finding was that the plume was a bottom-trapped type rather than a buoyant type. Further, the southerly winds were found to have moderately confined the alongshore extension of the plume, and had caused the plume to mix thoroughly with the ocean water.     

How well do predators adjust to climate-mediated shifts in prey distribution? A study on Australian water pythons

Climate change can move the spatial location of resources critical for population viability, and a species' resilience to such changes will depend upon its ability to flexibly shift its activities away from no-longer-suitable sites to exploit new opportunities. Intuition suggests that vagile predators should be able to track spatial shifts in prey availability, but our data on water pythons (Liasisfuscus) in tropical Australia suggest a less encouraging scenario. These pythons undergo regular long-range (to >10 kmin) seasonal migrations to follow flooding-induced migrations by their prey (native dusky rats, Rattus colletti). However, when an extreme flooding event virtually eliminated rats for a three-year period, the local pythons did not disperse despite the presence of abundant rats only 8 km away; instead, many pythons starved to death. This inflexibility suggests that some vagile species that track seasonally migrating prey may do so by responding to habitat attributes that have consistently predicted prey availability over evolutionary time, rather than reacting to proximate cues that signal the presence of prey per se. A species' vulnerability to climate change will be increased by an inability to shift its activities away from historical sites toward newly favorable areas.     

A note on the thyroid function of the pregnant females in the USA: data from NHANES 1999–2002 and 2007–2012

Thyroid dysfunction during pregnancy has been shown to be associated with adverse pregnancy outcomes. Consequently, this study was undertaken to assess the thyroid health of the pregnant females in the United States. Publically available data from National Health and Nutrition Examination Survey for the cycles 1999–2002 and 2007–2012 were analyzed for this purpose. Over 22% (SE: 5.7%) of the pregnant females based on the unweighted data in their first trimester had higher than the recommended levels of thyroid-stimulating hormone (TSH) or 2.5 mIU/L. Free triiodothyronine (FT3) and free thyroxine (FT4) levels decreased over pregnancy trimesters. Based on unweighted data, about 6% (SE: 2.6%) pregnant females were positive for thyroglobulin antibodies and 34.9% (SE: 5.2%) pregnant females were positive for thyroid peroxidase antibodies. Over 55% (SE: 3.5%) pregnant females based on the unweighted data were iodine deficient. As many as 41% (SE: 3%) first trimester pregnant females having TSH > 2.5 mIU/L is of concern. Future research should concentrate on developing educational and other materials that can advise pregnant females during their prenatal care and other appointments about the adverse effects of high TSH levels and what they can do to keep their TSH levels within the recommended levels.     

A two-step local smoothing approach for exploring spatio-temporal patterns with application to the analysis of precipitation in the mainland of China during 1986–2005

There has been a growing interest on using local modelling techniques for the analysis of spatio-temporal data because of their powerfulness in extracting the underlying local patterns in the data. In this study, we propose a two-step local smoothing approach to explore spatial patterns and temporal trends of spatio-temporal data via combining the geographically weighted regression and the local polynomial smoothing procedure. The proposed method incorporates both spatial and temporal information into the calibration process and makes it easier to implement visualization of the results. A simulation experiment is conducted to assess the performance of the proposed method and the results show that the method works satisfactorily. A real-world spatio-temporal data set is analyzed to demonstrate the practical usefulness of the method.