Linking spatial stock dynamics and economics: Evaluation of indicators and fishery management for the travelling eastern king prawn (Melicertus plebejus)

Reduced economic circumstances have moved management goals towards higher profit, rather than maximum sustainable yields in several Australian fisheries. The eastern king prawn is one such fishery, for which we have developed new methodology for stock dynamics, calculation of model-based and data-based reference points and management strategy evaluation. The fishery is notable for the northward movement of prawns in eastern Australian waters, from the State jurisdiction of New South Wales to that of Queensland, as they grow to spawning size, so that vessels fishing in the northern deeper waters harvest more large prawns. Bio-economic fishing data were standardized for calibrating a length-structured spatial operating model. Model simulations identified that reduced boat numbers and fishing effort could improve profitability while retaining viable fishing in each jurisdiction. Simulations also identified catch-rate levels that were effective for monitoring in simple within-year effort-control rules. However, favourable performance of catch-rate indicators was achieved only when a meaningful upper limit was placed on total allowed fishing effort. The methods and findings will allow improved measures for monitoring fisheries and inform decision makers on the uncertainty and assumptions affecting economic indicators.

Genetic response to growth rate selection in pigs measured on two feeding levels

From the findings of McPhee et al. (1988), there is an expectation that selection in the growing pig for bodyweight gain measured on restricted feeding will result in favourable responses in the rate and efficiency of growth of lean pork on different levels of feeding. This paper examines this in two lines of Australian Large White pigs which have undergone 3 years of selection for high and for low growth rate over a 6-week period starting at 50 kg liveweight. Over this test period, pigs of both lines are all fed the same total amount of grower food, restricted to an estimated 80% of average ad libitum intake. 'Animal production for a consuming world': proceedings of 9th Congress of the AAAAP Societies and 23rd Biennial Conference of the ASAP and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, (DRF). Sydney, Australia.

Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: An integrated modelling approach in maize.

Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.

The genetic structure of Australasian green turtles (Chelonia mydas): Exploring the geographical scale of genetic exchange

Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.

No-tillage and nitrogen application affects the decomposition of 15N-labelled wheat straw and the levels of mineral nitrogen and organic carbon in a Vertisol

No-tillage (NT) practice, where straw is retained on the soil surface, is increasingly being used in cereal cropping systems in Australia and elsewhere. Compared to conventional tillage (CT), where straw is mixed with the ploughed soil, NT practice may reduce straw decomposition, increase nitrogen immobilisation and increase organic carbon in the soil. This study examined 15N-labelled wheat straw (stubble) decomposition in four treatments (NT v. CT, with N rates of 0 and 75 kg/ha.year) and assessed the tillage and fertiliser N effects on mineral N and organic C and N levels over a 10-year period in a field experiment. NT practice decreased the rate of straw decomposition while fertiliser N application increased it. However, there was no tillage practice x N interaction. The mean residence time of the straw N in soil was more than twice as long under the NT (1.2 years) as compared to the CT practice (0.5 years). In comparison, differences in mean residence time due to N fertiliser treatment were small. However, tillage had generally very little effect on either the amounts of mineral N at sowing or soil organic C (and N) over the study period. While application of N fertiliser increased mineral N, it had very little effect on organic C over a 10-year period. Relatively rapid decomposition of straw and short mean residence time of straw N in a Vertisol is likely to have very little long-term effect on N immobilisation and organic C level in an annual cereal cropping system in a subtropical, semiarid environment. Thus, changing the tillage practice from CT to NT may not necessitate additional N requirement unless use is made of additional stored water in the soil or mineral N loss due to increased leaching is compensated for in N supply to crops.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

Application of sorbers to mitigate greenhouse gas emissions from land-applied pig litter

Nitrous oxide is the foremost greenhouse gas (GHG)generated by land-applied manures and chemical fertilisers (Australian Government 2013). This research project was part of the National Agricultural Manure Management Program and investigated the potential for sorbers (i.e. specific naturally-occurring minerals) to decrease GHG emissions from spent piggery litter (as well as other manures)applied to soils. The sorbers investigated in this research were vermiculite and bentonite. Both are clays with high cation exchange capacities, of approximately 100–150 cmol/kg Faure 1998). The hypothesis tested in this study was that the sorbers bind ammonium in soil solution thereby suppressing ammonia (NH3)volatilisation and in doing so, slowing the kinetics of nitrate formation and associated nitrous oxide (N2O) emissions. A series of laboratory, glasshouse and field experiments were conducted to assess the sorbers’ effectiveness. The laboratory experiments comprised 64 vessels containing manure and sorber/manure ratios ranging from 1 : 10 to 1 : 1 incorporated into a sandy Sodosol via mixing. The glasshouse trial involved 240 pots comprising manure/sorber incubations placed 5 cm below the soil surface, two soil types (sandy Sodosol and Ferrosol) and two different nitrogen (N) application rates (50 kg N/ha and 150 kg N/ha) with a model plant (kikuyu grass). The field trial consisted of 96, 2 m · 2 m plots on a Ferrosol site with digit grass used as a model plant. Manure/ sorber mixtures were applied in trenches (5 cm below surface) to these plots at increasing sorber levels at anNloading rate of 200 kg/ha. Gas produced in all experiments was plumbed into a purpose-built automated gas analysis (N2O, NH3, CH4, CO2) system. In the laboratory experiments, the sorbers showed strong capacity to decreaseNH3 emissions (up to 80% decrease). Ammonia emissions were close to the detection limit in all treatments in the glasshouse and field trial. In all experiments, considerable N2O decreases (>40%) were achieved by the sorbers. As an example, mean N2O emission decreases from the field trial phase of the project are shown in Fig. 1a. The decrease inGHGemissions brought about by the clays did not negatively impact agronomic performance. Both vermiculite and bentonite resulted in a significant increase in dry matter yields in the field trial (Fig. 1b). Continuing work will optimise the sorber technology for improved environmental and agronomic performance across a range of soils (Vertosol, Dermosol in addition to Ferrosol and Sodosols) and environmental parameters (moisture, temperature, porosity, pH).