Will biological control of Lantana camara ever succeed? Patterns, processes & prospects

Despite biocontrol research spanning over 100 years, the hybrid weed, commonly referred to as Lantana camara, is not under adequate control. Host specificity and varietal preference of released agents, climatic suitability of a region for released agents, number of agents introduced and range or area of infestation appear to play a role in limiting biocontrol success. At least one of 41 species of mainly leaf- or flower-feeding insects has been introduced, or spread, to 41 of the 70 countries or regions where lantana occurs. Over half (26) of these species have established, achieving varying levels of herbivory and presumably some degree of control. Accurate taxonomy of the plant and adaptation of potential agents to the host plant are some of the better predictors of at least establishment success. Retrospective analysis of the hosts of introduced biocontrol agents for L. camara show that a greater proportion of agents that were collected from L. camara or Lantana urticifolia established, than agents that were collected from other species of Lantana. Of the introduced agents that had established and were oligophagous, 18 out of 22 established. The proportion of species establishing, declined with the number of species introduced. However, there was no trend when oceanic islands were treated separately from mainland areas and the result is likely an artefact of how introductions have changed over time. A calculated index of the degree of herbivory due to agents known to have caused some damage per country, was not related to land area infested with lantana for mainlands nor for oceanic islands. However, the degree of herbivory is much higher on islands than mainlands. This difference between island and mainland situations may reflect population dynamics in patchy or metapopulation landscapes. Basic systematic studies of the host remain crucial to successful biocontrol, especially of hybrid weeds like L. camara. Potential biocontrol agents should be monophages collected from the most closely related species to the target weed or be phytophages that attack several species of lantana. Suitable agents should be released in the most ideal ecoclimatic area. Since collection of biocontrol agents has been limited to a fraction of the known number of phytophagous species available, biocontrol may be improved by targeting insects that feed on stems and roots, as well as the agents that feed on leaves and flowers.

The extent of population genetic subdivision differs among four co-distributed shark species in the Indo-Australian archipelago

Background: The territorial fishing zones of Australia and Indonesia are contiguous to the north of Australia in the Timor and Arafura Seas and in the Indian Ocean to the north of Christmas Island. The area surrounding the shared boundary consists of a variety of bio-diverse marine habitats including shallow continental shelf waters, oceanic trenches and numerous offshore islands. Both countries exploit a variety of fisheries species, including whaler (Carcharhinus spp.) and hammerhead sharks (Sphyrna spp.). Despite their differences in social and financial arrangements, the two countries are motivated to develop complementary co-management practices to achieve resource sustainability. An essential starting point is knowledge of the degree of population subdivision, and hence fisheries stock status, in exploited species. Results: Populations of four commercially harvested shark species (Carcharhinus obscurus, Carcharhinus sorrah, Prionace glauca, Sphyrna lewini) were sampled from northern Australia and central Indonesia. Neutral genetic markers (mitochondrial DNA control region sequence and allelic variation at co-dominant microsatellite loci) revealed genetic subdivision between Australian and Indonesian populations of C. sorrah. Further research is needed to address the possibility of genetic subdivision among C. obscurus populations. There was no evidence of genetic subdivision for P. glauca and S. lewini populations, but the sampling represented a relatively small part of their distributional range. For these species, more detailed analyses of population genetic structure is recommended in the future. Conclusion: Cooperative management between Australia and Indonesia is the best option at present for P. glauca and S. lewini, while C. sorrah and C. obscurus should be managed independently. On-going research on these and other exploited shark and ray species is strongly recommended. Biological and ecological similarity between species may not be a predictor of population genetic structure, so species-specific studies are recommended to provide new data to assist with sustainable fisheries management.

Characterization of north-eastern Australian environments using APSIM for increasing rainfed maize production

Recurring water stresses are a major risk factor for rainfed maize cropping across the highly diverse agro-ecological environments of Queensland (Qld) and northern New South Wales (NNSW). Enhanced understanding of such agro-ecological diversity is necessary to more consistently sample target production environments for testing and targeting release of improved germplasm, and to improve the efficiency of the maize pre-breeding and breeding programs of Qld and New South Wales. Here, we used the Agricultural Production Systems Simulator (APSIM) – a well validated maize crop model to characterize the key distinctive water stress patterns and risk to production across the main maize growing regions of Qld and NNSW located between 15.8° and 31.5°S, and 144.5° and 151.8°E. APSIM was configured to simulate daily water supply demand ratios (SDRs) around anthesis as an indicator of the degree of water stress, and the final grain yield. Simulations were performed using daily climatic records during the period between 1890 and 2010 for 32 sites-soils in the target production regions. The runs were made assuming adequate nitrogen supply for mid-season maize hybrid Pioneer 3153. Hierarchical complete linkage analyses of the simulated yield resulted in five major clusters showing distinct probability distribution of the expected yields and geographic patterns. The drought stress patterns and their frequencies using SDRs were quantified using multivariate statistical methods. The identified stress patterns included no stress, mid-season (flowering) stress, and three terminal stresses differing in terms of severity. The combined frequency of flowering and terminal stresses was highest (82.9%), mainly in sites-soils combinations in the west of Qld and NNSW. Yield variability across the different sites-soils was significantly related to the variability in frequencies of water stresses. Frequencies of water stresses within each yield cluster tended to be similar, but different across clusters. Sites-soils falling within each yield cluster therefore could be treated as distinct maize production environments for testing and targeting newly developed maize cultivars and hybrids for adaptation to water stress patterns most common to those environments.