Genetic population structure of red snappers (Lutjanus malabaricus Bloch & Schneider, 1801 and Lutjanus erythropterus Bloch, 1790) in central and eastern Indonesia and northern Australia

The genetic population structure of red snapper Lutjanus malabaricus and Lutjanus erythropterus in eastern Indonesia and northern Australia was investigated by allozyme electrophoresis and sequence variation in the control region of mtDNA. Samples were collected from eight sites in Indonesia and four sites in northern Australia for both species. A total of 13 allozyme loci were scored. More variable loci were observed in L. malabaricus than in L. erythropterus. Sequence variation in the control region (left domain) of the mitochondrial genome was assessed by RFLP and direct sequencing. MtDNA haplotype diversity was high (L. erythropterus, 0.95 and L. malabaricus, 0.97), as was intraspecific sequence divergence, (L. erythropterus, 0.0-12.5% and L. malabaricus, 0.0-9.5%). The pattern of mtDNA haplotype frequencies grouped both species into two broad fisheries stocks with a genetic boundary either between Kupang and Sape (L. malabaricus) or between Kupang and Australian Timor Sea (L. erythropertus). The allozyme analyses revealed similar boundaries for L. erythropterus. Seven allozymes stocks compared to two mtDNA stocks of L. malabaricus including Ambon, which was not sampled with mtDNA, however, were reported. Possible reasons for differences in discrimination between the methods include: i) increased power of multiple allozyme loci over the single mtDNA locus, ii) insufficient gene sampling in the mtDNA control region and iii) relative evolutionary dynamics of nuclear (allozyme loci) and mitochondrial DNA in these taxa. Allozyme and haplotype data did not distinguish separate stocks among the four Australian locations nor the central Indonesian (Bali and Sape locations) for both L. malabaricus and L. erythropterus.

APSIM – Evolution towards a new generation of agricultural systems simulation

Agricultural systems models worldwide are increasingly being used to explore options and solutions for the food security, climate change adaptation and mitigation and carbon trading problem domains. APSIM (Agricultural Production Systems sIMulator) is one such model that continues to be applied and adapted to this challenging research agenda. From its inception twenty years ago, APSIM has evolved into a framework containing many of the key models required to explore changes in agricultural landscapes with capability ranging from simulation of gene expression through to multi-field farms and beyond. Keating et al. (2003) described many of the fundamental attributes of APSIM in detail. Much has changed in the last decade, and the APSIM community has been exploring novel scientific domains and utilising software developments in social media, web and mobile applications to provide simulation tools adapted to new demands. This paper updates the earlier work by Keating et al. (2003) and chronicles the changing external challenges and opportunities being placed on APSIM during the last decade. It also explores and discusses how APSIM has been evolving to a “next generation” framework with improved features and capabilities that allow its use in many diverse topics.