Intensification of New Zealand beef farming systems

This study used whole-farm management, nutrient budgeting/greenhouse gas (GHG) emissions and feed formulation computer tools to determine the production, environmental and financial implications of intensifying the beef production of typical New Zealand (NZ) sheep and beef farming systems. Two methods of intensification, feeding maize silage (MS) or applying nitrogen (N) fertiliser, were implemented on two farm types differing in the proportions of cultivatable land to hill land (25% vs. 75% hill). In addition, the consequences of intensification by incorporating a beef feedlot (FL) into each of the farm types were also examined.Feeding MS or applying N fertiliser substantially increased the amount of beef produced per ha. Intensifying production was also associated with increased total N leaching and GHG emissions although there were differences between the methods of intensification. Feeding MS resulted in lower environmental impacts than applying N even after taking into account the land to grow the maize for silage. Based on 2007/08 prices, typical NZ sheep and beef farms were making a financial loss and neither method of intensification increased profitability with the exception of small annual applications of N, especially to the 75% hill farm. These small annual additions of N fertiliser (<50 kg N/ha/yr applied in autumn and late winter) resulted in only small increases in annual N leaching (from 11 to 14 kg N/ha) and GHG emissions (from 3280 to 4000 kg CO₂ equivalents/ha). Limited N applications were particularly beneficial to 75% hill farms because small increases in winter carrying capacity resulted in relatively large increases in the utilisation of pasture growth during spring and summer than the 25% hill farms. Intensification by incorporating a beef feedlot reduced environmental emissions per kg of beef produced but considerably decreased profitability due to higher capital, depreciation and labour costs. The lower land-use capability farm type (75% hill) was able to intensify beef production to a proportionally greater extent than the higher land-use capability farm (25% hill) because of greater potential to increase pasture utilisation associated with a lower initial farming intensity and inherent constraints in the pattern of pasture supply.     

Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data‐sparse situation

Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R²; 0.29–0.69) outperformed both PTF‐1 (R²; 0.11–0.18) and PTF‐2 (R²; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R²; 0.61–0.86) performed comparably as PTF‐1 (R²; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R²; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).     

A longitudinal study to identify constraints to dairy cattle health and production in rural smallholder communities in Northern Vietnam

The objective of the study was to investigate constraints to dairy cattle health and production in rural smallholder communities in northern Vietnam, one of the target areas of the Vietnam government's dairy development programme. A total of 99 dairy farms (11 per commune) were recruited from 9 of 32 communes in Ba Vi District, using random two-stage cluster sampling. After the initial questionnaire interviews were conducted, farms were visited at three monthly intervals over a period of 1 year. Information on several health and production parameters relating to the study cattle was collected. Using multiple indicator modelling, it was found that Fasciola infestation, farmers who had been involved in dairying for longer (not indicative of better management skills), larger herd size, and cattle being kept in a shed were linked to reduced reproductive performances.     

爬壁机器人翻越焊缝过程动力学建模研究

用于远洋渔船外板除锈的爬壁机器人在进行壁面作业时需要翻越焊缝,采用充气轮的爬壁机器人在翻越焊缝后会出现轮胎压缩量的减小,导致磁铁气隙增大、磁铁吸附力减小,从而削弱爬壁机器人的负载能力,降低了壁面行走可靠性,为此对爬壁机器人翻越焊缝的动力学过程进行研究。首先,将驱动轮轮胎简化为弹簧阻尼器,建立爬壁机器人翻越焊缝过程的动力学模型,并将驱动轮的翻越焊缝过程划分为不同的阶段;其次,利用数值方法求解该动力学模型,分析不同胎压下驱动轮翻越焊缝过程中爬壁机器人的运动状态;最后,进行了爬壁机器人翻越焊缝过程试验,结果表明,机器人翻越焊缝过程的试验结果与数值仿真结果基本一致,验证了本文所建动力学模型的正确性与合理性。     

Drivers for spatial modelling of a critically endangered seabird on a dynamic ocean area: Balearic shearwaters are non-vegetarian

1. Spatial modelling is an important research tool to improve our knowledge about the distribution of wildlife in the ocean. Using different modelling techniques (MaxEnt and a generalized linear mixed model), a predictive habitat suitability model was developed for one of the most threatened seabirds in the world: the Balearic shearwater, Puffinus mauretanicus.
2. Models were developed using a 10-year dataset from the Gulf of Cádiz (on the south-western Iberian Peninsula), a key foraging area for Balearic shearwaters during migration and the non-breeding season.
3. Predictive habitat maps strongly matched the observed distribution patterns, pointing to bathymetric features as the main modelling drivers. The species was concentrated on shallow areas (up to approximately 100 m in depth) of the continental shelf, very close to the mouth of the Guadalquivir River. In contrast with previous studies, Balearic shearwater distribution in the highly dynamic Gulf of Cádiz was not correlated with areas of high chlorophyll a concentration.
4. This lack of spatial correlation probably arises from the delay between the phytoplankton bloom and the response of the zooplankton and small fish that are preyed upon by Balearic shearwaters, which may result in important displacements of this trophic chain across the Gulf of Cádiz.
5. The analysis presented contributes to a better understanding of the spatial distribution and ecology of the critically endangered top predator in the Gulf of Cádiz and offers important information to improve management plans.

     

Current bycatch levels in Auckland Islands trawl fisheries unlikely to be driving New Zealand sea lion (Phocarctos hookeri)population decline

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Estimation of Runoff,Peak Discharge and Sediment Load at the Event Scale in a Medium‐Size Mediterranean Watershed Using the Annagnps Model

In this paper, the Annualized Agricultural Non‐Point Source (AnnAGNPS) model has been used to estimate runoff, peak discharge and sediment load at the event scale in a Mediterranean watershed. The study area is the Carapelle torrent, Southern Italy (area = 506 km²), where continuous rainfall, streamflow and sediment load data are available. Nineteen flood events have been registered in the period 2007–2009 and were used for the application of the model. The aim of the paper is to evaluate the predictive accuracy of the model at the event scale, in a medium‐size watershed, given the specific conditions of the semi‐arid environments. A sensitivity analysis has been carried out to assign the correct parameterization: the mean normalized output variation of the most meaningful input parameters pointed out the influence of the curve number on runoff, peak discharge and sediment load predictions (values greater than 1); the MN Manning's roughness coefficient and K, C and P factors of the universal soil loss equation showed a moderate influence on sediment load simulations (values between 0·5 and 1). The selection of the Soil Conservation Service synthetic storm types has been based on the observed storm events analysis to improve the peak discharge simulations. The model prediction has proved to be good for runoff (R² = 0·74, NSE = 0·75, W = 0·92) and peak discharge (R² = 0·85, NSE = 0·70, W = 0·94), and satisfactory for sediment yield (R² = 0·70, NSE = 0·63, W = 0·91). The relative error is lower for high events; this result is quite interesting in semi‐arid environments, where most of the annual sediment yield is concentrated in a few, severe events. Copyright © 2013 John Wiley & Sons, Ltd.     

Relationships between soil properties and the occurrence of the most agronomically important weed species in the field margins of eastern Arkansas – implications for weed management in field margins

The work presented in this study adds to previous research on the occurrence, distribution and growth habitat of common weeds along roadsides in the Mississippi River Delta region of eastern Arkansas, USA. It addresses the relationships between soil properties (i.e. defined as a group of individual soil characteristics or attributes such as P, K, Ca, Mn and other nutrients) and the most agronomically important weeds of which the occurrence at field margins accounted for ≥ 10% of the total sampling sites. These were three broad‐leaved weeds (Amaranthus palmeri, Ipomoea spp. and Sida spinosa) and four grass weeds (Echinochloa crus‐galli, Urochloa platyphylla, Sorghum halepense and Digitaria sanguinalis). Soil properties were used as explanatory variables for weed occurrence (presence–absence) using partition analysis; the occurrences of the weeds under examination were partitioned by the application of a decision‐tree method. The most important soil properties explaining the occurrence of these weeds in field margins were extractable soil nutrients, specifically sodium, boron and copper content, as well as soil physical attributes, in order of importance, bulk density, silt content, field moisture capacity, hydraulic conductivity, wilting point, available water and clay content. Soil chemical properties proved least reliable in explaining weed occurrence at roadside field margins. Knowledge of the relationships between soil properties and weed occurrence can add to our understanding of weed biology and hence enhance the efficiency of weed management strategies. For example, the occurrence of A. palmeri, in soils with high bulk density (>1.4 g cm^?3) and low organic matter content (<2.7%) and thus lower residual herbicide activity, will require integrated weed management of this species in field margins. This is of interest given the occurrence of herbicide resistance in roadside arable weeds, mainly A. palmeri, E. crus‐galli and S. halepense, in the Mississippi River Delta region of eastern Arkansas and other parts of the world.     

松口蘑的研究热点

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