Fisheries Queensland Long Term Monitoring Program Underwater Visual Census of twenty-four reefs on the Great Barrier Reef between 1999 and 2004.

In 1999, the Department of Employment, Economic Development and Innovation (DEEDI), Fisheries Queensland undertook a new initiative to collect long term monitoring data of various important stocks including reef fish. This data and monitoring manual for the reef fish component of that program which was based on Underwater Visual Census methodology of 24 reefs on the Great Barrier Reef between 1999 and 2004. Data was collected using six 50m x 5m transects at 4 sites on 24 reefs. Benthic cover type was also recorded for 10m of each transect. The attached Access Database contains 5 tables being: SITE DETAILS TABLE Survey year Data entry complete REF survey site ID Site # (1-4) Location (reef name) Site Date (date surveyed) Observer 1 (3 initials to identify who estimated fish lengths and recorded benthic cover) TRANSECT DETAILS Survey ID Transect Number (1-6) Time (the transect was surveyed) Visibility (in metres) Minimum Depth surveyed (m) Maximum Depth surveyed (m) Percent of survey completed (%) Comments SUBSTRATE Survey ID Transect Number (1-6) then % cover of each of eth following categories of benthic cover types Dead Coral Live Coral Soft Coral Rubble Sand Sponge Algae Sea Grass Other COORDINATES (over survey sites) from -14 38.792 to -19 44.233 and from 145 21.507 to 149 55.515 SIGHTINGS ID Survey ID Transect Number (1-6) CAAB Code Scientific Name Reef Fish Length (estimated Fork Length of fish; -1 = unknown or not recorded) Outside Transect (if a fish was observed outside a transect -1 was recorded) Morph Code (F = footballer morph for Plectropomus laevis, S = Spawning colour morph displayed)

Sperm chromatin in beef bulls in tropical environments

Sperm chromatin status was assessed in 565 Zebu and Zebu crossbred beef bulls in extensive tropical environments using the sperm chromatin structure assay (SCSA). The SCSA involved exposure of sperm to acid hydrolysis for 0.5 or 5.0 minutes, followed by flow cytometry to ascertain relative amounts of double-stranded (normal) and single-stranded (denatured) DNA, which was used to generate a DNA fragmentation index (%DFI). With conventional SCSA (0.5-minute SCSA), 513 bulls (91%) had <15 %DFI, 24 bulls (4%) had 15 to 27 %DFI, and 28 bulls (5%) had >27 %DFI. In 5.0-minute SCSA, 432 bulls (76%) had <15 %DFI, 68 bulls (12%) had 15 to 27 %DFI and 65 bulls (12%) had >27 %DFI. For most bulls, the SCSA was repeatable on two to four occasions; however, because most bulls had <15 %DFI, repeatability of the SCSA will need to be determined in a larger number of bulls in the 15 to 27 %DFI and >27 %DFI categories. The %DFI was negatively correlated with several bull semen parameters and the strongest negative correlation was with normal sperm. There was a strong positive correlation between %DFI and sperm head abnormalities. Based on these findings, most Zebu beef bulls in extensive tropical environments had relatively stable sperm chromatin. Based on the apparent negative correlations with conventional semen parameters, we inferred that the SCSA measured a unique feature of sperm quality, which has also been suggested for other species. Further studies on the relationships between sperm chromatin stability and fertility are required in beef bulls before chromatin status can be used as an additional predictor of the siring capacity of individual bulls in extensive multiple-sire herds. (C) 2013 Elsevier Inc. All rights reserved.

Development and testing of allometric equations for estimating above-ground biomass of mixed-species environmental plantings

To quantify the impact that planting indigenous trees and shrubs in mixed communities (environmental plantings) have on net sequestration of carbon and other environmental or commercial benefits, precise and non-biased estimates of biomass are required. Because these plantings consist of several species, estimation of their biomass through allometric relationships is a challenging task. We explored methods to accurately estimate biomass through harvesting 3139 trees and shrubs from 22 plantings, and collating similar datasets from earlier studies, in non-arid (>300mm rainfallyear-1) regions of southern and eastern Australia. Site-and-species specific allometric equations were developed, as were three types of generalised, multi-site, allometric equations based on categories of species and growth-habits: (i) species-specific, (ii) genus and growth-habit, and (iii) universal growth-habit irrespective of genus. Biomass was measured at plot level at eight contrasting sites to test the accuracy of prediction of tonnes dry matter of above-ground biomass per hectare using different classes of allometric equations. A finer-scale analysis tested performance of these at an individual-tree level across a wider range of sites. Although the percentage error in prediction could be high at a given site (up to 45%), it was relatively low (<11%) when generalised allometry-predictions of biomass was used to make regional- or estate-level estimates across a range of sites. Precision, and thus accuracy, increased slightly with the level of specificity of allometry. Inclusion of site-specific factors in generic equations increased efficiency of prediction of above-ground biomass by as much as 8%. Site-and-species-specific equations are the most accurate for site-based predictions. Generic allometric equations developed here, particularly the generic species-specific equations, can be confidently applied to provide regional- or estate-level estimates of above-ground biomass and carbon. © 2013 Elsevier B.V.

Floristic composition and pasture condition of Aristida/Bothriochloa pastures in central Queensland. II. Soil and pasture condition interactions

Sustainable management of native pastures requires an understanding of what the bounds of pasture composition, cover and soil surface condition are for healthy pastoral landscapes to persist. A survey of 107 Aristida/Bothriochloa pasture sites in inland central Queensland was conducted. The sites were chosen for their current diversity of tree cover, apparent pasture condition and soil type to assist in setting more objective bounds on condition ‘states’ in such pastures. Assessors’ estimates of pasture condition were strongly correlated with herbage mass (r = 0.57) and projected ground cover (r = 0. 58), and moderately correlated with pasture crown cover (r = 0.35) and tree basal area (r = 0.32). Pasture condition was not correlated with pasture plant density or the frequency of simple guilds of pasture species. The soil type of Aristida/Bothriochloa pasture communities was generally hard-setting, low in cryptogam cover but moderately covered with litter and projected ground cover (30–50%). There was no correlation between projected ground cover of pasture and estimated ground-level cover of plant crowns. Tree basal area was correlated with broad categories of soil type, probably because greater tree clearing has occurred on the more fertile, heavy-textured clay soils. Of the main perennial grasses, some showed strong soil preferences, for example Tripogon loliiformis for hard-setting soils and Dichanthium sericeum for clays. Common species, such as Chrysopogon fallax and Heteropogon contortus, had no strong soil preference. Wiregrasses (Aristida spp.) tended to be uncommon at both ends of the estimated pasture condition scale whereas H. contortus was far more common in pastures in good condition. Sedges (Cyperaceae) were common on all soil types and for all pasture condition ratings. Plants identified as increaser species were Tragus australianus, daisies (Asteraceae) and potentially toxic herbaceous legumes such as Indigofera spp. and Crotalaria spp. Pasture condition could not be reliably predicted based on the abundance of a single species or taxon but there may be scope for using integrated data for four to five ecologically contrasting plants such as Themeda triandra with daisies, T. loliiformis and flannel weeds (Malvaceae).

A universal equation to predict methane production of forage-fed cattle in Australia

The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.