Laurie Laurenson

A comparison of trace element concentrations in cultured and wild carp (Cyprinus carpio) of Lake Kasumigaura, Japan

The concentrations of 13 elements were determined in the muscle, liver, intestine, kidney, and gonads of cultured and wild carp caught at two sites in Lake Kasumigaura, Japan, between September 1994 and September 1995. Despite having a reputation for being heavily polluted, the carp were not heavily burdened with metals. Our results suggest that despite their dietary differences, the wild and cultured fish were accumulating and distributing metals in the same manner and that aquaculture practices are not increasing metal concentrations in these fish. Metal concentrations were lowest in muscle, and did not exceed established quality standards for fish. The differences in metal concentrations between cultivated and wild carp are negligible and should pose no health problems for consumers of either type of fish.

Marine Benthic Habitat Mapping using Multibeam Data, GeoreferencedVideo and Image Classification Techniques in Victoria, Australia.

This paper contributes to a better understanding of geophysical characteristics and benthic communities in the Hopkins site in Victoria, Australia. An automated decision tree classification system was used to classify substrata and dominant biotic communities. Geophysical sampling and underwater video data collected in this study reveals a complex bathymetry and biological structure which complements the limited information of benthic marine ecosystems in coastal waters of Victoria. The technique of combining derivative products from backscatter and bathymetry datasets was found to improve separability for broad biota and substrate categories over the use of either of these datasets alone.

Dietary comparisons of six skate species (Rajidae) in south-eastern Australian waters

The diet of six skate species caught as bycatch in south-eastern Australian waters was examined over a 2-year period. The skates were segregated into two regions (continental shelf and continental slope) based on prey species and depth of capture. The shelf group consisted of four species, Dipturus sp. A, D. cerva, D. lemprieri and D. whitleyi, while the slope group comprised two species, Dipturus sp. B and D. gudgeri. The two groups varied in feeding strategies with the shelf species generally occupying a broader feeding niche and preying on a larger diversity of prey including a variety of crustaceans (brachyurans, anomurans, achelates, carideans and dendobranchiates), cephalopods, elasmobranchs and teleosts. Within the slope group, Dipturus sp. B and D. gudgeri were more specialised. Dipturus sp. B preyed primarily on anomurans (galatheids) and bachyurans (homolids), whereas D. gudgeri preyed primarily on teleosts. A size related change in diet was evident for all species with the exception of D. gudgeri in which all sizes preyed predominantly on teleosts. Smaller representatives of the four shelf species all preyed on numerous amounts of caridean shrimps, in particular Leptochela sydniensis. In contrast, the continental slope species, Dipturus sp. B consumed anomurans when small, shifting to brachyurans with increasing size. Of the six skate species examined in this study, three were secondary consumers (trophic level <3) and the remaining three tertiary consumers (trophic level >4). Although ANOSIM found significant differences in dietary composition between species within groups, there was some overlap in prey species amongst co-existing skates, which suggests that there is some degree of resource partitioning amongst them.

Integrating Multibeam Backscatter Angular Response, Mosaic and Bathymetry Data for Benthic Habitat Mapping

Multibeam echosounders (MBES) are increasingly becoming the tool of choice for marine habitat mapping applications. In turn, the rapid expansion of habitat mapping studies has resulted in a need for automated classification techniques to efficiently map benthic habitats, assess confidence in model outputs, and evaluate the importance of variables driving the patterns observed. The benthic habitat characterisation process often involves the analysis of MBES bathymetry, backscatter mosaic or angular response with observation data providing ground truth. However, studies that make use of the full range of MBES outputs within a single classification process are limited. We present an approach that integrates backscatter angular response with MBES bathymetry, backscatter mosaic and their derivatives in a classification process using a Random Forests (RF) machine-learning algorithm to predict the distribution of benthic biological habitats. This approach includes a method of deriving statistical features from backscatter angular response curves created from MBES data collated within homogeneous regions of a backscatter mosaic. Using the RF algorithm we assess the relative importance of each variable in order to optimise the classification process and simplify models applied. The results showed that the inclusion of the angular response features in the classification process improved the accuracy of the final habitat maps from 88.5% to 93.6%. The RF algorithm identified bathymetry and the angular response mean as the two most important predictors. However, the highest classification rates were only obtained after incorporating additional features derived from bathymetry and the backscatter mosaic. The angular response features were found to be more important to the classification process compared to the backscatter mosaic features. This analysis indicates that integrating angular response information with bathymetry and the backscatter mosaic, along with their derivatives, constitutes an important improvement for studying the distribution of benthic habitats, which is necessary for effective marine spatial planning and resource management.

Assessment of Spatiotemporal Varying Relationships Between Rainfall, Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R2 and lower corrected Akaike information criterion (AICC). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R2 and lower AICC. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.

Seasonal and diel comparisons of the diets of four dominant fish species within the main channel and flood-zone of a small intermittently open estuary in south-eastern Australia

The diets of four highly-abundant, dominant fish species within the Surrey River, a small intermittently open estuary in south-east Australia, were examined from specimens collected between July 2004 and June 2005. These four, similar-sized species (Atherinosoma microstoma, Galaxias maculatus, Philypnodon grandiceps and Pseudogobius olorum) have limited ability to spatially segregate along the length of the estuary owing to its small size relative to other estuarine habitats. All four species fed on a variety of prey items including crustaceans, insects and detritus. Despite this parity, the four species were demonstrated to occupy differing dietary niches that were concluded to be responsible for reducing interspecific feeding competition. Seasonal variations in the diets were observed for A. microstoma and Philypnodon grandiceps, with these species also exhibiting contrasting diel feeding behaviours. The closure of the estuary mouth led to the flooding of its margins, resulting in an increase in the size of the estuary and providing alternative food resources for the fish to exploit. It appears the inundation of the flood-zone facilitated further significant divergence in the diets of the fish and is likely to be of high ecological value to the estuary.

Using community-based monitoring with GIS to create habitat maps for a marine protected area in Australia

In recent years there has been an increase in community-based monitoring programmes developed and implemented worldwide. This paper describes how the data collected from such a programme could be integrated into a Geographic Information System (GIS) to create temperate subtidal marine habitat maps. A differential Global Positioning System was utilized to accurately record the location of the trained community-based SCUBA diver data. These georeferenced data sets were then used to classify benthic habitats using an aerial photograph and digitizing techniques. This study demonstrated that trained community-based volunteers can collect data that can be utilized within a GIS to create reliable and cost-effective maps of shallow temperate subtidal rocky reef systems.

Reproductive biology of the eastern shovelnose stingaree Trygonoptera imitata from south-eastern Australia

In applying a quantitative approach to the reproduction of Trygonoptera imitata, the present study contributes to understanding the wide diversity in the reproductive biology of the family Urolophidae and provides insights to help determine phylogenetic relationships. This localised species is taken as bycatch in several inshore fisheries and potentially impacted by a range of other anthropogenic pressures, including introduced species, particularly in shallow-water pupping areas. T. imitata can be characterised as a species of comparatively low matrotrophic histotrophy with an extended period of relatively large eggs in utero (5–8 months) followed by rapid growth of the embryos (4–6 months). The reproductive cycle is annual with parturition occurring during late-February–April, followed immediately by ovulation. Mean size-at-birth is ~225 mm total length and there is a ~1000% gain in mean wet mass from egg (15 g) to full-term embryo in utero (150 g), the lowest reported for any viviparous batoid. Litter size increases with maternal length, reaching a maximum of seven, and sex ratio of embryos is 1 : 1. Maximum length and estimates of the maturity–ogive parameters l50 and l95 are similar for females and males.

Biennial reproductive cycle in an extensive matrotrophic viviparous batoid: the sandyback stingaree Urolophus bucculentus from south-eastern Australia.

Urolophus bucculentus, the largest urolophid species found in southern Australia, exhibits a biennial reproductive cycle. Ovulation occurs during October to January followed by a 15-19 month period of gestation followed by parturition during April to May and a short rest period while the ovarian follicles continue to develop for subsequent ovulation. Male breeding condition peaks during April to June to coincide with the period of parturition. Urolophus bucculentus has the highest matrotrophic contribution reported for any urolophid species, with a mean wet mass gain from egg in utero (4 g) to full-term embryo in utero (250 g) of c. 6250% (maximum c. 7200%), and perhaps explains the biennial female reproductive cycle where 50% of females contribute to each years recruitment. Litter size (one to five) increases with total length (L(T) ). Females reach a longer maximum L(T) (L(Tmax) ) than do males (885 v. 660 mm). The L(T) at maturity for males and females at 50% mature (L(T50) ) is c. 414 mm (63% of L(Tmax) ) for males and c. 502 mm (57% of L(Tmax) ) for females, length at maternity indicates that recruitment production occurs later in life at c. 632 mm L(T) (71% of L(Tmax) ).

Quantification of Spatial and Thematic Uncertainty in the Application of Underwater Video for Benthic Habitat Mapping

This study presents an analysis of the application of underwater video data collected for training and validating benthic habitat distribution models. Specifically, we quantify the two major sources of error pertaining to collection of this type of reference data. A theoretical spatial error budget is developed for a positioning system used to co-register video frames to their corresponding locations at the seafloor. Second, we compare interpretation variability among trained operators assessing the same video frames between times over three hierarchical levels of a benthic classification scheme. Propagated error in the positioning system described was found to be highly correlated with depth of operation and varies from 1.5m near the surface to 5.7m in 100m of water. In order of decreasing classification hierarchy, mean overall observer agreement was found to be 98% (range 6%), 82% (range 12%) and 75% (range 17%) for the 2, 4, and 6 class levels of the scheme, respectively. Patterns in between-observer variation are related to the level of detail imposed by each hierarchical level of the classification scheme, the feature of interest, and to the amount of observer experience.