Expanding Agri-Food Production and Employment in the Presence of Climate Policy Constraints: Quantifying the Trade-Off in Ireland

This chapter explores the trade-off between competing objectives of employment creation and climate policy commitments in Irish agriculture. A social accounting matrix (SAM) multiplier model is linked with a partial equilibrium agricultural sector model to simulate the impact of a number of GHG emission reduction scenarios, assuming these are achieved through a constraint on beef production. Limiting the size of the beef sector helps to reduce GHG emissions with a very limited impact on the value of agricultural income at the farm level. However, the SAM multiplier analysis shows that there would be significant employment losses in the wider economy. From a policy perspective, a pragmatic approach to GHG emissions reductions in the agriculture sector, which balances opportunities for economic growth in the sector with opportunities to reduce associated GHG emissions, may be required.

Sex differences in responsiveness to begging in a cooperative mammal

In species where young are provisioned by both parents, males commonly contribute less to parental care than females, and are less responsive to variation in begging rates. Similar differences in the care of young occur among adults in cooperative breeders, but fewer studies have investigated whether these are associated with differences in responsiveness. Here, we present results from a playback experiment investigating responsiveness to begging in the meerkat (Suricata suricatta), a cooperatively breeding mammal. Although increased begging rate raised the feeding rate of adults of both sexes, there was no consistent tendency for females to be more responsive than males. However, when we examined changes in the proportion of food items found that were fed to pups (generosity), we found that females were more responsive than males to increased begging rate. These results can be explained in terms of sex differences in dispersal: in meerkats, females are philopatric and receive considerable benefits from investing in young, both directly, by increasing group size, and indirectly, by recruiting helpers if they inherit the breeding position. In addition, they emphasize that generosity provides a more sensitive measure of responsiveness to begging than feeding rate, as it accounts for variation in foraging success. © 2008 The Royal Society.

On the Diversity-Multiplexing Tradefoff for Wireless Cooperative Multiple Access Systems

A spectrally efficient strategy is proposed for cooperative multiple access (CMA) channels in a centralized communication environment with $N$ users. By applying superposition coding, each user will transmit a mixture containing its own information as well as the other users', which means that each user shares parts of its power with the others. The use of superposition coding in cooperative networks was first proposed in , which will be generalized to a multiple-user scenario in this paper. Since the proposed CMA system can be seen as a precoded point-to-point multiple-antenna system, its performance can be best evaluated using the diversity-multiplexing tradeoff. By carefully categorizing the outage events, the diversity-multiplexing tradeoff can be obtained, which shows that the proposed cooperative strategy can achieve larger diversity/multiplexing gain than the compared transmission schemes at any diversity/multiplexing gain. Furthermore, it is demonstrated that the proposed strategy can achieve optimal tradeoff for multiplexing gains $0leq r leq 1$ whereas the compared cooperative scheme is only optimal for $0leq r leq ({1}/{N})$. As discussed in the paper, such superiority of the proposed CMA system is due to the fact that the relaying transmission does not consume extra channel use and, hence, the deteriorating effect of cooperative communication on the data rate is effectively limited.

Isotopic composition of tropospheric and soil N2O from successive depths of agricultural plots with contrasting crops and nitrogen amendments

Agricultural soils are the dominant contributor to increases in atmospheric nitrous oxide (N2O). Few studies have investigated the natural N and O isotopic composition of soil N2O. We collected soil gas samples using horizontal sampling tubes installed at successive depths under five contrasting agricultural crops (e.g., unamended alfalfa, fertilized cereal), and tropospheric air samples. Mean d 15N and d 18O values of soil N2O ranged from -28.0 to +8.9‰, and from +29.0 to +53.6‰. The mean d 15N and d 18O values of tropospheric N2O were +4.6 ± 0.7‰ and +48.3 ± 0.2‰, respectively. In general, d values were lowest at depth, they were negatively correlated to soil [N2O], and d 15N was positively correlated to d 18O for every treatment on all sampling dates. N2O from the different agricultural treatments had distinct d 15N and d 18O values that varied among sampling dates. Fertilized treatments had soil N2O with low d values, but the unamended alfalfa yielded N2O with the lowest d values. Diffusion was not the predominant process controlling N2O concentration profiles. Based on isotopic and concentration data, it appears that soil N2O was consumed, as it moved from deeper to shallower soil layers. To better assess the main process(es) controlling N2O within a soil profile, we propose a conceptual model that integrates data on net N2O production or consumption and isotopic data. The direct local impact of agricultural N2O on the isotopic composition of tropospheric N2O was recorded by a shift toward lower d values of locally measured tropospheric N2O on a day with very high soil N2O emissions.

Gene selection by cooperative competition clustering

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.