Natural and anthropogenic changes to mangrove distributions in the Pioneer River Estuary (QLD, Australia)

We analyzed a time series of aerial photographs and Landsat satellite imagery of the Pioneer River Estuary (near Mackay, Queensland, Australia) to document both natural and anthropogenic changes in the area of mangroves available to filter river runoff between 1948 and 2002. Over 54 years, there was a net loss of 137 ha (22%) of tidal mangroves during four successive periods that were characterized by different driving mechanisms: (1) little net change (1948– 1962); (2) net gain from rapid mangrove expansion (1962–1972); (3) net loss from clearing and tidal isolation (1972–1991); and (4) net loss from a severe species-specific dieback affecting over 50% of remaining mangrove cover (1991–2002). Manual digitization of aerial photographs was accurate for mapping changes in the boundaries of mangrove distributions, but this technique underestimated the total loss due to dieback. Regions of mangrove dieback were identified and mapped more accurately and efficiently after applying the Normalized Difference Vegetation Index (NDVI) to Landsat Thematic Mapper satellite imagery, and then monitoring changes to the index over time. These remote sensing techniques to map and monitor mangrove changes are important for identifying habitat degradation, both spatially and temporally, in order to prioritize restoration for management of estuarine and adjacent marine ecosystems

Classification and comparison of natural and altered flow regimes to support an Australian trial of the Ecological Limits of Hydrologic Alteration framework

The Ecological Limits of Hydrologic Alteration (ELOHA) is a new framework designed to develop environmental flow prescriptions for many streams and rivers in a user-defined geographic region or jurisdiction. This study presents hydrologic classifications and comparisons of natural and altered flows in southeast Queensland, Australia, to support the ecological steps of a field trial of the ELOHA framework. We extended existing protocols for flow classification by assessing the stability of flow classes. Model-based clustering distinguished six Reference classes (based on modelled pre-development flow data) and five Historic classes (based on stream gauge data). The principal flow regime change was loss of some of the original (natural) flow diversity accompanied by the emergence of a perennial flow class in the Historic classification composed mostly of gauges with flow regimes influenced by dams. However, similarities between Reference and Historic classifications indicate that hydrologic changes in southeast Queensland have not totally obscured Reference (pre-development) characteristics. Duration of low flow spells has undergone the greatest absolute change from Reference values.\ud \ud Dams had substantial but variable impacts on downstream flow regimes. Each dam created a unique downstream flow signature, indicating that environmental flow guidance for each regulated river must be tailored to the particulars of flow alterations, the associated ecological impacts and the desired future ecological state of the aquatic ecosystem. Other stressors were implicated in flow regime change, highlighting the need to consider the potential influence of factors other than prominent water infrastructure on flow regime alterations and associated ecological responses

Changes in forest area along stream networks in an agricultural catchment of the Great Barrier Reef Lagoon

Scenes from the series of multispectral sensors on the Landsat satellites were used to map recent changes (between 1972 and 2004) in forest cover within and adjacent to stream networks of an intensively farmed region of the southern Great Barrier Reef catchment (Australia). Unsupervised ISODATA classifications of Tasseled-Cap transformed data (at 57 m ground resolution) mapped forest and cleared areas within 150 m of Pisoneer catchment waterways with 72.2% overall accuracy (K = 0.469), when adjusted for the size of each class. Although the user's accuracy was higher for the forest class (82.1 ± 8.4% at α = 0.05), large errors of commission (34.2 ± 8.3%) substantially affected map accuracy for the cleared class. The main reasons for misclassification include: (1) failure to discriminate narrowly vegetated riparian strips; (2) misregistration of scenes; and (3) spectral similarity of ground cover. Error matrix probabilities were used to adjust the mapped area of classes, resulting in a decline of forest cover by 12.3% and increase of clearing by 18.5% (22.4 km change; 95% confidence interval: 14.3-29.6 km ) between 1972 and 2004. Despite the mapping errors, Landsat data were able to identify broad patterns of land cover change that were verified from aerial photography. Most of the forest losses occurred in open forest to woodland habitat dominated by Eucalyptus, Corymbia, and Lophostemon species, which were largely replaced by sugarcane cropping. Melaleuca communities were similarly affected, though they have a much smaller distribution in the catchment