Evaluation of aerial photography for predicting trends in structural attributes of Australian woodland including comparison with ground-based monitoring data

The accurate assessment of trends in the woody structure of savannas has important implications for greenhouse accounting and land-use industries such as pastoralism. Two recent assessments of live woody biomass change from north-east Australian eucalypt woodland between the 1980s and 1990s present divergent results. The first estimate is derived from a network of permanent monitoring plots and the second from woody cover assessments from aerial photography. The differences between the studies are reviewed and include sample density, spatial scale and design. Further analyses targeting potential biases in the indirect aerial photography technique are conducted including a comparison of basal area estimates derived from 28 permanent monitoring sites with basal area estimates derived by the aerial photography technique. It is concluded that the effect of photo-scale; or the failure to include appropriate back-transformation of biomass estimates in the aerial photography study are not likely to have contributed significantly to the discrepancy. However, temporal changes in the structure of woodlands, for example, woodlands maturing from many smaller trees to fewer larger trees or seasonal changes, which affect the relationship between cover and basal area could impact on the detection of trends using the aerial photography technique. It is also possible that issues concerning photo-quality may bias assessments through time, and that the limited sample of the permanent monitoring network may inadequately represent change at regional scales

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

Application of phytotoxicity data to a new Australian soil quality guideline framework for biosolids

To protect terrestrial ecosystems and humans from contaminants many countries and jurisdictions have developed soil quality guidelines (SQGs). This study proposes a new framework to derive SQGs and guidelines for amended soils and uses a case study based on phytotoxicity data of copper (Cu) and zinc (Zn) from field studies to illustrate how the framework could be applied. The proposed framework uses normalisation relationships to account for the effects of soil properties on toxicity data followed by a species sensitivity distribution (SSD) method to calculate a soil added contaminant limit (soil ACL) for a standard soil. The normalisation equations are then used to calculate soil ACLs for other soils. A soil amendment availability factor (SAAF) is then calculated as the toxicity and bioavailability of pure contaminants and contaminants in amendments can be different. The SAAF is used to modify soil ACLs to ACLs for amended soils. The framework was then used to calculate soil ACLs for copper (Cu) and zinc (Zn). For soils with pH of 4-8 and OC content of 1-6%, the ACLs range from 8 mg/kg to 970 mg/kg added Cu. The SAAF for Cu was pH dependant and varied from 1.44 at pH 4 to 2.15 at pH 8. For soils with pH of 4-8 and OC content of 1-6%, the ACLs for amended soils range from 11 mg/kg to 2080 mg/kg added Cu. For soils with pH of 4-8 and a CEC from 5-60, the ACLs for Zn ranged from 21 to 1470 mg/kg added Zn. A SAAF of one was used for Zn as it concentrations in plant tissue and soil to water partitioning showed no difference between biosolids and soluble Zn salt treatments, indicating that Zn from biosolids and Zn salts are equally bioavailable to plants.

Australian Bat Lyssavirus

In Chapter 1, the literature relating to rabies virus and the rabies like lyssaviruses is reviewed. In Chapter 2, data are presented from 1170 diagnostic submissions for ABLV testing by fluorescent antibody test (Centocor FAT). All 27 non-bat submissions were ABLV-negative. Of 1143 bat accessions 74 (16%) were ABLV-positive, including 69 of 974 (7.1%) flying foxes (Pteropus spp.), 5 of 7 (71.4%) Saccolaimus flaviventris (Yellow-bellied sheathtail bats), none of 151 other microchiropteran bats, and none of 11 unidentified bats. Statistical analysis of data from 868 wild Black, Grey-headed, Little Red and Spectacled flying foxes (Pteropus alecto, P. poliocephalus, P. scapulatus, and P. conspicillatus) indicated that three factors; species, health status and age were associated with significant (p< 0.001) differences in the proportion of ABLV-positive bats. Other factors including sex, whether the bat bit a person or animal, region, year, and season submitted, were not associated with ABLV. Case data for 74 ABLV-positive bats, including the circumstances in which they were found and clinical signs, is presented. In Chapter 3, the aetiological diagnosis was investigated for 100 consecutive flying fox submissions with neurological signs. ABLV (32%), spinal and head injuries (29%), and neuro-angiostrongylosis (18%) accounted for most neurological syndromes in flying foxes. No evidence of lead poisoning was found in unwell (n=16) or healthy flying foxes (n=50). No diagnosis was reached for 16 cases, all of which were negative for ABLV by TaqMan PCR. The molecular diversity of ABLV was examined in Chapter 4 by sequencing 36 bases of the leader sequence, the entire N gene, and start of the P gene of 28 isolates from pteropid bats and 3 isolates from Yellow-bellied sheathtail (YBST) bats. Phylogenetic analysis indicated all ABLV isolates clustered together as a discrete group within the Lyssavirus genera closely related to rabies virus and European bat lyssavirus-2 isolates. The ABLV lineage consisted of two variants; one (ybst-ABLV) consisted of isolates only from YBST bats, the other (pteropid-ABLV) was common to Black, Grey-headed and Little Red flying foxes. No associations were found between the sequences and either the geographical location or year found, or individual flying fox species. In Chapter 5, 15 inocula prepared from the brains or salivary glands of naturally-infected bats were evaluated by intracerebral (IC) and footpad (FP) inoculation of Quackenbush mice in order to select and characterize a highly virulent inoculum for further use in bats (Inoculum 5). In Chapter 6, nine Grey-headed flying foxes were inoculated with 105.2 to 105.5 MICED50 of Inoculum 5 divided into four sites, left footpad, pectoral muscle, temporal muscle and muzzle. Another bat was inoculated with half this dose divided into the footpad and pectoral muscle only. Seven of 10 bats developed clinical disease of 1 to 4 days duration between PI-days 10 and 19 and were shown to be ABL-positive by FAT, HAM immunoperoxidase staining, virus isolation in mice, and TaqMan PCR. Five of the seven bats displayed overt aggression, one died during a seizure, and one showed intractable agitation, pacing, tremors, and ataxia. Viral antigen was demonstrated throughout the central and peripheral nervous systems and in the epithelial cells of the submandibular salivary glands (n=4). All affected bats had mild to moderate non-suppurative meningoencephalitis and severe ganglioneuritis. No ABLV was detected in three bats that remained well until the end of the experiment on day 82. One survivor developed a strong but transient antibody response. In Chapter 7, the relative virulence of inocula prepared from the brains and salivary glands of experimentally infected flying foxes was evaluated in mice by IC and FP inoculation and TaqMan assay. The effects in mice were correlated to the TaqMan CT value and indicated a crude association between virulence and CT value that has potential application in the selection of inocula. In Chapter 8, 36 Black and Grey-headed flying foxes were vaccinated with one (day 0) or two (+ day 28) doses of Nobivac rabies vaccine and co-vaccinated with keyhole limpet haemocyanin (KLH). All bats responded to the Nobivac vaccine with a rabies-RFFIT titer > 0.5 IU/mL that is nominally indicative of protective immunity. Plasma from bats with rabies titres >2 IU/mL had cross-neutralising ABLV titres >1:154. A specifically developed ELISA detected a strong but transient response to KLH.

Using catch rate data for simple cost-effective quota setting in the Australian spanner crab (Ranina ranina) fishery.

For many fisheries, there is a need to develop appropriate indicators, methodologies, and rules for sustainably harvesting marine resources. Complexities of scientific and financial factors often prevent addressing these, but new methodologies offer significant improvements on current and historical approaches. The Australian spanner crab fishery is used to demonstrate this. Between 1999 and 2006, an empirical management procedure using linear regression of fishery catch rates was used to set the annual total allowable catch (quota). A 6-year increasing trend in catch rates revealed shortcomings in the methodology, with a 68% increase in quota calculated for the 2007 fishing year. This large quota increase was prevented by management decision rules. A revised empirical management procedure was developed subsequently, and it achieved a better balance between responsiveness and stability. Simulations identified precautionary harvest and catch rate baselines to set quotas that ensured sustainable crab biomass and favourable performance for management and industry. The management procedure was simple to follow, cost-effective, robust to strong trends and changes in catch rates, and adaptable for use in many fisheries. Application of such “tried-and-tested” empirical systems will allow improved management of both data-limited and data-rich fisheries.

Fishing power and standardised catch rates: Implications of missing vessel-characteristic data from the Australian eastern king prawn fishery

Standardised time series of fishery catch rates require collations of fishing power data on vessel characteristics. Linear mixed models were used to quantify fishing power trends and study the effect of missing data encountered when relying on commercial logbooks. For this, Australian eastern king prawn (Melicertus plebejus) harvests were analysed with historical (from vessel surveys) and current (from commercial logbooks) vessel data. Between 1989 and 2010, fishing power increased up to 76%. To date, both forward-filling and, alternatively, omitting records with missing vessel information from commercial logbooks produce broadly similar fishing power increases and standardised catch rates, due to the strong influence of years with complete vessel data (16 out of 23 years of data). However, if gaps in vessel information had not originated randomly and skippers from the most efficient vessels were the most diligent at filling in logbooks, considerable errors would be introduced. Also, the buffering effect of complete years would be short lived as years with missing data accumulate. Given ongoing changes in fleet profile with high-catching vessels fishing proportionately more of the fleet’s effort, compliance with logbook completion, or alternatively ongoing vessel gear surveys, is required for generating accurate estimates of fishing power and standardised catch rates.