Chromolaena odorata (L.) King and Robinson (Asteraceae)

Chromolaena, or Siam weed, is a serious problem in several tropical and sub-tropical areas around the world. In our own region, it is a serious weed in New Guinea, East Timor and Indonesia and is also under an eradication regime in North Queensland. The chapter summarises current knowledge about the taxonomy, biology, distribution, ecology, impacts and control of the weed. Biological control has been a major multinational initiative against this weed in recent years and these efforts are described in some detail. Interestingly agents have not been universally effective because of weed biotype differences and climate. Considerable success has been achieved in New Guinea, principally with the tephritid fly Cecidocares connex and by the efforts of Michael Day, Rachel McFadyen and Graham Donnelly from Alan Fletcher Research Station.

An (O)over-tilde(mn) Gomory-Hu Tree Construction Algorithm for Unweighted Graphs

We present a fast algorithm for computing a Gomory-Hu tree or cut tree for an unweighted undirected graph G = (V, E). The expected running time of our algorithm is (O) over tilde (mc) where vertical bar E vertical bar = m and c is the maximum u-v edge connectivity, where u, v is an element of V. When the input graph is also simple (i.e., it has no parallel edges), then the u-v edge connectivity for each pair of vertices u and v is at most n - 1; so the expected run-ning time of our algorithm for simple unweighted graphs is (O) over tilde (mn). All the algorithms currently known for constructing a Gomory-Hu tree [8, 9] use n - 1 minimum s-t cut (i.e., max flow) subroutines. This in conjunction with the current fastest (O) over tilde (n(20/9)) max flow algorithm due to Karger and Levine[11] yields the current best running time of (O) over tilde (n(20/9)n) for Gomory-Hu tree construction on simple unweighted graphs with m edges and n vertices. Thus we present the first (O) over tilde (mn) algorithm for constructing a Gomory-Hu tree for simple unweighted graphs. We do not use a max flow subroutine here; we present an efficient tree packing algorithm for computing Steiner edge connectivity and use this algorithm as our main subroutine. The advantage in using a tree packing algorithm for constructing a Gomory-Hu tree is that the work done in computing a minimum Steiner cut for a Steiner set S subset of V can be reused for computing a minimum Steiner cut for certain Steiner sets S' subset of S.

New approach to improved detection and tracking performance in track-while-scan radars. Part 2: Detection, track nitiation and association

he paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan (TWS) radar. Part 1 presents a review of current status. In this part, Part 2, it is shown how the detection can be improved by utilising information from tracker. A new multitarget tracking algorithm, capable of tracking manoeuvring targets in clutter, is then presented. The algorithm is specifically tailored so that the solution to the combinatorial problem presented in a companion paper can be applied. The implementation aspects are discussed and a multiprocessor architecture identified to realise the full potential of the algorithm. Part 3 presents analytical derivations for quantitative assessment of the performance of the TWS radar system. It also shows how the performance can be optimised.

DNA bar-coding reveals source and patterns of Thaumastocoris peregrinus invasions in South Africa and South America.

Thaumastocoris peregrinus is a recently introduced invertebrate pest of non-native Eucalyptus plantations in the Southern Hemisphere. It was first reported from South Africa in 2003 and in Argentina in 2005. Since then, populations have grown explosively and it has attained an almost ubiquitous distribution over several regions in South Africa on 26 Eucalyptus species. Here we address three key questions regarding this invasion, namely whether only one species has been introduced, whether there were single or multiple introductions into South Africa and South America and what the source of the introduction might have been. To answer these questions, bar-coding using mitochondrial DNA (COI) sequence diversity was used to characterise the populations of this insect from Australia, Argentina, Brazil, South Africa and Uruguay. Analyses revealed three cryptic species in Australia, of which only T. peregrinus is represented in South Africa and South America. Thaumastocoris peregrinus populations contained eight haplotypes, with a pairwise nucleotide distance of 0.2-0.9% from seventeen locations in Australia. Three of these haplotypes are shared with populations in South America and South Africa, but the latter regions do not share haplotypes. These data, together with the current distribution of the haplotypes and the known direction of original spread in these regions, suggest that at least three distinct introductions of the insect occurred in South Africa and South America before 2005. The two most common haplotypes in Sydney, one of which was also found in Brisbane, are shared with the non-native regions. Sydney populations of T. peregrinus, which have regularly reached outbreak levels in recent years, might thus have served as source of these three distinct introductions into other regions of the Southern Hemisphere.

A genome-wide association study of tick burden and milk composition in cattle.

To study the genetic basis of tick burden and milk production and their interrelationship, we collected a sample of 1961 cattle with multiple tick counts from northern Australia of which 973 had dairy production data in the Australian Dairy Herd Information Service database. We calculated heritabilities, genetic and phenotypic correlations for these traits and showed a negative relationship between tick counts and milk and milk component yield. Tests of polymorphisms of four genes associated with milk yield, ABCG2, DGAT1, GHR and PRLR, showed no statistically significant effect on tick burden but highly significant associations to milk component yield in these data and we confirmed separate effects for GHR and PRLR on bovine chromosome 20. To begin to identify some of the molecular genetic bases for these traits, we genotyped a sample of 189 of these cattle for 7397 single nucleotide polymorphisms in a genome-wide association study. Although the allele effects for adjusted milk fat and protein yield were highly correlated (r = 0.66), the correlations of allele effects of these milk component yields and tick burden were small (|r| <= 0.10). These results agree in general with the phenotypic correlations between tick counts and milk component yield and suggest that selection on markers for tick burden or milk component yield may have no undesirable effect on the other trait.