997 resultados para southern Moreton Bay
Resumo:
The eastern shovelnose ray, Aptychotrema rostrata (Rhinobatidae), is an endemic batoid common to the east coast of Australia. The reproductive cycle was studied in Moreton Bay, south-eastern Queensland, over a 14-month period. Aptychotrema rostrata is an aplacental yolksac viviparous species with an annual, seasonal reproductive cycle in Moreton Bay. Females mature at 54-66 cm total length, and males at 60-68 cm total length. Gravid females were observed during September-November and parturition occurred in November-December. Vitellogenesis does not proceed in parallel with gestation. Ovulation and copulation probably occur during July-September, resulting in a gestational period of 3-5 months. Uterine fecundity ranges from 4 to 18, with a significant positive relationship between uterine fecundity and maternal body length. In mature males, a peak in the proportion of mature spermatocysts in the testes was observed in July, whereas gonadosomatic index peaked in April.
Resumo:
Dugong abundances in Moreton Bay (south-east Queensland) were estimated during six bi- monthly aerial surveys throughout 1995. Sampling intensity ranged between 20 and 80% for different sampling zones within the Bay, with a mean intensity of 40.5%. Population estimates for dugongs were corrected for perception bias ( the proportion of animals visible in the transect that were missed by observers), and standardised for availability bias ( the proportion of animals that were invisible due to water turbidity) with survey and species-specific correction factors. Population estimates for dugongs in Moreton Bay ranged from 503 +/- 64 (s.e.) in July to 1019 +/- 166 in January. The highest uncorrected count was 857 dugongs in December. This is greater than previous population estimates, suggesting that either previous surveys have underestimated abundance and/or that this population may have increased through recruitment, immigration, or a combination of both. The high degree of variation in population estimates between surveys may be due to temporal differences in distribution and herding behaviour. In winter, dugongs were found in smaller herds and were dispersed over a wider area than in summer. The Eastern Banks region of the bay supported 80 - 98% of the dugong population at any one time. Within this region, there were several dugong 'hot spots' that were visited repeatedly by large herds. These 'hot spots' contained seagrass communities that were dominated by species that dugongs prefer to eat. The waters of Rous Channel, South Passage and nearby oceanic waters are also frequently inhabited by dugongs in the winter months. Dugongs in other parts of Moreton Bay were at much lower densities than on the Eastern Banks.
Resumo:
The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (~200 km**2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.
Resumo:
The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.