Effects of high salinity from desalination brine on growth, photosynthesis, water relations and osmolyte concentrations of seagrass Posidonia australis

Highly saline brines from desalination plants expose seagrass communities to salt stress. We examined effects of raised salinity (46 and 54psu) compared with seawater controls (37psu) over 6weeks on the seagrass, Posidonia australis, growing in tanks with the aim of separating effects of salinity from other potentially deleterious components of brine and determining appropriate bioindicators. Plants survived exposures of 2-4weeks at 54psu, the maximum salinity of brine released from a nearby desalination plant. Salinity significantly reduced maximum quantum yield of PSII (chlorophyll a fluorescence emissions). Leaf water potential (Ψw) and osmotic potential (Ψπ) were more negative at increased salinity, while turgor pressure (Ψp) was unaffected. Leaf concentrations of K(+) and Ca(2+) decreased, whereas concentrations of sugars (mainly sucrose) and amino acids increased. We recommend leaf osmolarity, ion, sugar and amino acid concentrations as bioindicators for salinity effects, associated with brine released in desalination plant outfalls.

Corner inlet and Nooramunga habitat mapping project

Deakin University and the University of Tasmania were commissioned by Parks Victoria (PV) to create two updated habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. The team obtained a ground-truth data set using in situ video and still photographs. This dataset was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both ALOS (Advanced Land Observation Satellite) imagery atmospherically corrected by CSIRO and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, returning overall accuracies >73 % and kappa values > 0.62 for both study localities. Habitats predicted with highest accuracies included Zosteraceae in Nooramunga (91 %), reef in Corner Inlet (80 %), and bare sediment (no-visible macrobiota/no-visible seagrass classes; both > 76 %). The majority of classification errors were due to the misclassification of areas of sparse seagrass as bare sediment. For the Corner Inlet study locality the no-visible macrobiota (10,698 ha), Posidonia (4,608 ha) and Zosteraceae (4,229 ha) habitat classes covered the most area. In Nooramunga no-visible seagrass (5,538 ha), Zosteraceae (4,060 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

In addition to the commissioned work preliminary change detection analyses were undertaken as part of this project. These analyses indicated shifts in habitat extents in both study localities since the late 1990s/2000. In particular, a post-classification analysis highlighted that there were considerable increases in seagrass habitat (primarily Zosteraceae) throughout the littoral zones and river/creek mouths of both study localities. Further, the numerous channel systems remained stable and were free of seagrass at both times. A substantial net loss of Posidonia in the Corner Inlet locality is likely but requires further investigation due to potential misclassifications between habitats in both the 1998 map (Roob et al. 1998) and the current mapping. While the unsupervised Independent Components Analysis (ICA) change detection technique indicated some changes in habitat extent and distribution, considerable areas of habitat change observed in the post-classification approach are questionable, and may reflect misclassifications rather than real change. A particular example of this is an apparent large decrease in Zosteraceae and increase in Posidonia being related to the classification of Posidonia beds as Zosteraceae in the 1998 mapping. Despite this, we believe that changes indicated by both the ICA and post-classification approaches have a high likelihood of being ‘actual’ change. A pattern of gains and losses of Zosteraceae in the region north of Stockyard channel is an example of this. Further analyses and refinements of approaches in change detection analyses such as would improve confidence in the location and extent of habitat changes over this time period.

This work has been successful in providing new baseline maps using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Corner Inlet and Nooramunga Habitat Mapping Project – Part 2 : High resolution mapping and change detection analysis using 2011 Rapid Eye Satellite Image compared to 2009 ALOS Satellite Image

Building on a habitat mapping project completed in 2011, Deakin University was commissioned by Parks Victoria (PV) to apply the same methodology and ground-truth data to a second, more recent and higher resolution satellite image to create habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. A ground-truth data set using in situ video and still photographs was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both RapidEye satellite imagery (corrected for atmospheric and water column effects by CSIRO) and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, with error rates similar to or better than the earlier classification (>73 % and kappa values > 0.58 for both study localities). The RapidEye classification failed to accurately detect Pyura and reef habitat classes at the Corner Inlet locality, possibly due to differences in spectral frequencies. For comparison, these categories were combined into a ‘non-seagrass’ category, similar to the one used at the Nooramunga locality in the original classification. Habitats predicted with highest accuracies differed from the earlier classification and were Posidonia in Corner Inlet (89%), and bare sediment (no-visible seagrass class) in Nooramunga (90%). In the Corner Inlet locality reef and Pyura habitat categories were not distinguishable in the repeated classification and so were combined with bare sediments. The majority of remaining classification errors were due to the misclassification of Zosteraceae as bare sediment and vice versa. Dominant habitats were the same as those from the 2011 classification with some differences in extent. For the Corner Inlet study locality the no-visible seagrass category remained the most extensive (9059 ha), followed by Posidonia (5,513 ha) and Zosteraceae (5,504 ha). In Nooramunga no-visible seagrass (6,294 ha), Zosteraceae (3,122 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

Change detection analyses between the 2009 and 2011 imagery were undertaken as part of this project, following the analyses presented in Monk et al. (2011) and incorporating error estimates from both classifications. These analyses indicated some shifts in classification between Posidonia and Zosteraceae as well as a general reduction in the area of Zosteraceae. Issues with classification of mixed beds were apparent, particularly in the main Posidonia bed at Nooramunga where a mosaic of Zosteraceae and Posidonia was seen that was not evident in the ALOS classification. Results of a reanalysis of the 1998-2009 change detection illustrating effects of binning of mixed beds is also provided as an appendix.

This work has been successful in providing baseline maps at an improved level of detail using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Fine-scale patterns of genetic variation in a widespread clonal seagrass species

Seagrasses are ecosystem engineers that offer important habitat for a large number of species and provide a range of ecosystem services. Many seagrass ecosystems are dominated by a single species, with research showing that genotypic diversity at fine spatial scales plays an important role in maintaining a range of ecosystem functions. However, for most seagrass species, information on fine-scale patterns of genetic variation in natural populations is lacking. In this study, we use a hierarchical sampling design to determine the levels of genetic and genotypic diversity at different spatial scales (centimeters, meters, kilometers) in the Australian seagrass Zostera muelleri. Our analysis shows that at fine spatial scales (<1 m), levels of genotypic diversity are relatively low (R(Plots) = 0.37 ± 0.06 SE), although there is some intermingling of genotypes. At the site (10’s m) and meadow location (km) scale, we found higher levels of genotypic diversity (R(sites) = 0.79 ± 0.04 SE; R(Locations) = 0.78 ± 0.04 SE). We found some sharing of genotypes between sites within meadows, but no sharing of genotypes between meadow locations. We also detected a high level of genetic structuring between meadow locations (FST = 0.278). Taken together, our results indicate that both sexual and asexual reproductions are important in maintaining meadows of Z. muelleri. The dominant mechanism of asexual reproduction appears to occur via localized rhizome extension, although the sharing of a limited number of genotypes over the scale of 10’s of meters could also result from the localized dispersal and recruitment of fragments. The large number of unique genotypes at the meadow scale indicates that sexual reproduction is important in maintaining these populations, while the high level of genetic structuring suggests little gene flow and connectivity between our study sites. These results imply that recovery from disturbances will occur through both sexual and asexual regeneration, but the limited connectivity at the landscape scale implies that recovery at meadow-scale losses is likely to be limited.

Can mud (silt and clay) concentration be used to predict soil organic carbon content within seagrass ecosystems?

The emerging field of blue carbon science is seeking cost-effective ways to estimate the organic carbon content of soils that are bound by coastal vegetated ecosystems. Organic carbon (Corg) content in terrestrial soils and marine sediments has been correlated with mud content (i.e. silt and clay), however, empirical tests of this theory are lacking for coastal vegetated ecosystems. Here, we compiled data (n = 1345) on the relationship between Corg and mud (i.e. silt and clay, particle sizes <63 μm) contents in seagrass ecosystems (79 cores) and adjacent bare sediments (21 cores) to address whether mud can be used to predict soil Corg content. We also combined these data with the δ13C signatures of the soil Corg to understand the sources of Corg stores. The results showed that mud is positively correlated with soil Corg content only when the contribution of seagrass-derived Corg to the sedimentary Corg pool is relatively low, such as in small and fast growing meadows of the genera Zostera, Halodule and Halophila, and in bare sediments adjacent to seagrass ecosystems. In large and long-living seagrass meadows of the genera Posidonia and Amphibolis there was a lack of, or poor relationship between mud and soil Corg content, related to a higher contribution of seagrass-derived Corg to the sedimentary Corg pool in these meadows. The relative high soil Corg contents with relatively low mud contents (i.e. mud-Corg saturation) together with significant allochthonous inputs of terrestrial organic matter could overall disrupt the correlation expected between soil Corg and mud contents. This study shows that mud (i.e. silt and clay content) is not a universal proxy for blue carbon content in seagrass ecosystems, and therefore should not be applied generally across all seagrass habitats. Mud content can only be used as a proxy to estimate soil Corg content for scaling up purposes when opportunistic and/or low biomass seagrass species (i.e. Zostera, Halodule and Halophila) are present (explaining 34 to 91% of variability), and in bare sediments (explaining 78% of the variability).

Comparison of marine macrophytes for their contributions to blue carbon sequestration

Many marine ecosystems have the capacity for long-term storage of organic carbon (C) in what are termed "blue carbon" systems. While blue carbon systems (saltmarsh, mangrove, and seagrass) are efficient at long-term sequestration of organic carbon (C), much of their sequestered C may originate from other (allochthonous) habitats. Macroalgae, due to their high rates of production, fragmentation, and ability to be transported, would also appear to be able to make a significant contribution as C donors to blue C habitats. In order to assess the stability of macroalgal tissues and their likely contribution to long-term pools of C, we applied thermogravimetric analysis (TGA) to 14 taxa of marine macroalgae and coastal vascular plants. We assessed the structural complexity of multiple lineages of plant and tissue types with differing cell wall structures and found that decomposition dynamics varied significantly according to differences in cell wall structure and composition among taxonomic groups and tissue function (photosynthetic vs. attachment). Vascular plant tissues generally exhibited greater stability with a greater proportion of mass loss at temperatures > 300 degrees C (peak mass loss -320 degrees C) than macroalgae (peak mass loss between 175-300 degrees C), consistent with the lignocellulose matrix of vascular plants. Greater variation in thermogravimetric signatures within and among macroalgal taxa, relative to vascular plants, was also consistent with the diversity of cell wall structure and composition among groups. Significant degradation above 600 degrees C for some macroalgae, as well as some belowground seagrass tissues, is likely due to the presence of taxon-specific compounds. The results of this study highlight the importance of the lignocellulose matrix to the stability of vascular plant sources and the potentially significant role of refractory, taxon-specific compounds (carbonates, long-chain lipids, alginates, xylans, and sulfated polysaccharides) from macroalgae and seagrasses for their long-term sedimentary C storage. This study shows that marine macroalgae do contain refractory compounds and thus may be more valuable to long-term carbon sequestration than we previously have considered.

Linking nitrogen sources utilised by seagrass in a temperate marine embayment to patterns of seagrass change during drought

Reductions in the extent of seagrass Zostera nigricaulis coverage in Port Phillip Bay (PPB), Australia, between 2000 and 2011 coincided with a prolonged period of drought (1997 to 2009) characterized by decreases in freshwater and nutrient inputs. This led us to hypothesize that patterns of seagrass expansion and decline in PPB may be linked to nutrient availability. Seagrasses in PPB can make use of a range of different nitrogen (N) sources depending on their relative availability. Accordingly, there is a need to identify the origin of the N utilised by seagrasses in order to understand how changes in the availability of nutrients from various sources may influence seagrass growth. This study used stable isotope analysis to estimate the contribution of different sources of N to seagrass growth in different parts of PPB. Source modelling indicated that regional patterns of N source utilisation matched changes in seagrass extent from 2000 to 2011. Regions in which seagrass declined contained a similar array of sources, including significant contributions from the catchment area, whereas regions where seagrass areas remained unchanged were largely dependent on a single N source (either fixation/recycled or sewage-derived). We propose that reductions in N from the catchment during the drought may have contributed to the decline of seagrasses in regions where N from the catchment is an important source. This finding is likely to have implications for the growth, distribution and resilience of Z. nigricaulis seagrass in PPB as well as in other parts of its range in southern Australia.