Dynamic Habitat - CLLAMM technical briefing

HEADLINE TO BE PLACED IN THIS SPACE CLLAMMecology Dynamic Habitat Program Sunil Sharma, Simon Benger and Jason Tanner CLLAMMecology Research Cluster partners:

Dynamic Habitat Report Sections Sharma, S. K., Tanner, J.E. & S. Benger, 2009. Digital Elevation Model for the Coorong and surrounding areas. Sharma, S. K., Benger, S., Fernandez, M. & J.E. Tanner, 2009. Sediment mapping of the Coorong: implications for habitat distributions. Sharma, S. K., Benger, S. & J.E. Tanner, 2009. Habitat Mapping of the Coorong and Surrounds. Benger, S., Sharma, S.K., and J.E. Tanner, 2009. Mudflat geomorphology and availability at varying water levels in the Coorong. Sharma, S. K., Benger, S., Tanner, J.E. & I.T. Webster, 2009. Spatial Modelling of mudflat availability and fish habitat in the Coorong.

Bathymetry for the Murray Mouth and the South Lagoon -Needed to address data gaps -Allows for volumetric analyses of the lagoons -Not possible to survey completely -Modelled from Landsat and SPOT imagery

Bathymetry for the Murray Mouth and the South Lagoon 4.0 3.0 2.0 Depth in metres AHD 1.0 0.0 1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106 113 120 127 134 141 148 155 162 169 176 183 190 -1.0 -2.0 Measured depth Predicted depth -3.0 -4.0 Depth locations from Parnka Point to Salt Creek Modelling used Generalised Additive Model for predicting a response variable y at i location with predictive variables xij n yi = β 0 + ∑S i =1, j =1 j ( xij ) Depth = β0 + S1(x) + S2(y) S3(Ls1) + S4(Ls 2) + S5(Ls 3) + S6(Ls 4) + S7(Ls 5) + S8(Ls 6) + S9(Ls7) + S10(Sp1) + S11(Sp2) + S12(Sp3)

Sediment Modelling Response curves for predictor variables and mean grain size for the final 5 variable model for the North Lagoon. The solid line is the smooth function of the explanatory variable, while the dashed lines indicate the 95% confidence region. The rugplot indicates the values of the predictor variables for which observations were available. Generalized Additive Modelling (GAM) was used to assess the relationship between the sediment characteristics measured and a range of potential predictor variables g(SA)= β0 + s(Northing) + s(Easting) + s(Depth) + s(Slope) + s(Aspect) + s(distance to the east shore) + s(distance to (1) the west shore) + s(Nearest distance to shore) + s(distance from the Murray Mouth) + s(salinity)

Sediment Modelling

Quantifying Habitat Habitat in the Reference Sites was quantified using remote sensing, underwater videography, fieldwork, DEH mapping. A habitat classification scheme with 12 descriptors encompassing a range of geographical, physical, chemical and biological characteristics was developed Habitat Zone Habitat Type Habitat category Salinity Landform Vegetation Wetland system Cover Percent Water Regime Habitat Condition Wetland Type Habitat Area

Quantifying Habitat

Habitat Mapping

HEADLINE TO BE PLACEDhabitat for many species in the Coorong, in particular wader Mudflats form critical IN bird species. THIS SPACE Maximising the productivity of mudflats, through maintaining water levels and water quality is essential for ensuring the Ramsar status of the Coorong by providing coastal foraging habitat required by migratory birds. Healthy mudflats support large and diverse macroinvertebrate populations, are important as fish breeding areas and form substrate for submerged aquatic vegetation such as Ruppia species. Restoring the productivity of the Coorong mudflats is an important conservation goal for the region. CLLAMMecology Research Cluster partners: Mudflat Morphology

Mudflat Morphology

Mudflat Morphology Hypsometric Curves for each Reference Site Also characterised mudflat slope and area for a range of elevation classes

Mudflat Morphology Findings The characterisation of mudflat morphology allows for detailed estimates of mudflat habitat availability at different water levels. Study confirms the importance of the South Lagoon in terms of mudflat habitat, as it contains some 61% of available mudflat as measured in the reference sites. Mudflat areas at elevations between 0m and 0.5m AHD yield the greatest availability of habitat and suggest that manipulations of water level should be kept within this range. Most important elevation range is 0.2m to 0.4m AHD, as manipulations in this range accomplish wetting and drying of the maximum area of mudflat, most of which is found in the South Lagoon. Mudflats throughout the Coorong are generally likely to be geomorphically stable with mean mudflat slopes averaging 0.72%.

Linking to the Hydrodynamic Model of Webster (2007) Locations of water level and salinity data points generated through the hydrodynamic model. (Where GC = Goolwa Channel; MC = Mundoo Channel; EI = Ewe Island; BK = Barker Knoll; PP = Pelican Point; MP = Mark Point; LP = Long Point; NM = Noonameena; PA = Parnka Point; VY = Villa dei Yumpa; JP = Jack Point and SC = Salt Creek.

Linking the Hydrodynamic Model to Habitat The hydrodynamic model simulates water level and salinity for 117 years (the period between 1891 and 2008) in combination with an inflow model. For habitat modelling of the Coorong, we chose to predict habitat availability for the baseline scenario (Scenario A - the current state of agricultural development and current water management rules from CSIRO Sustainable Yields). Two ‘very wet’ and ‘very dry’ years in the past decades were selected for a comparison of habitat availability under these conditions. Under scenario A, we identified 1976 and 1993 as wet years; and 1988 and 2005 as dry years. The hydrodynamic model was run for these years and water level and salinity data were linked to the geographical coordinates of the respective points.

Barker Knoll 1988 1.2 1 Water level (AHDm) 0.8 0.6 0.4 0.2 0 -0.2 -0.4 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 January July Day of Month Noonameena 1988 1.4 1.2 Water level (AHDm) 1 0.8 0.6 0.4 0.2 0 -0.2 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 January July Day of Month

The Dynamic Habitat Model Part A Part B Part C Part D The fine resolution bathymetry (1 m2), water level data from the hydrodynamic model and a boundary layer covering up to the high water mark level were used to predict the spatial-temporal availability of mudflat habitats in the Coorong. The model is composed of six model parameters (blue ovals) and uses 12 processes (yellow rectangles) and generates 12 outputs (green ovals) including 9 intermediate and 3 final outputs: Exposed Area (WL to HW), Mudflat area (Eastern Shore), Mudflat area (Western Shore),

The Dynamic Habitat Model 3.50 Mudflat area (ha) 3.00 2.50 2.00 1.50 1.00 0.50 0.00 -0.30 -0.14 -0.07 0.00 0.09 0.18 0.20 0.26 0.31 0.34 0.56 0.72 0.87 1.17 Mean water level (mAHD) Eastern shore Western shore Channel Total Mudflat availability on the eastern shore, western shore, channel and the total areas at different water levels at Barker Knoll.

The Dynamic Habitat Model 8.00 0.9 0.8 Water Level (mAHD) Mudflat area (ha) 0.7 6.00 0.6 0.5 4.00 0.4 0.3 2.00 0.2 0.1 0.00 0 6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 Hours (22 Jan. 1976) Mudflat - Barker Knoll Mudflat - Noonameena Mudflat - Salt Creek Water Level - Barker Knoll Water Level - Noonameena Water Level - Salt Creek Mudflat availability and water levels between 6:00 - 20:00 at three reference sites on 22 Jan. 1976. The average water level on this day was the monthly maximum for January 1976.

Predicting fish habitat based on fish occurrence probability using logistic regression

Model coefficients and parameters for seven key species in the Coorong.

Habitat prediction for Smallmouth Hardyhead in July 1976, July 1988 and January 2005.

Habitat prediction for Yelloweye Mullet in July 1976, July 1988 and January 2005

The Dynamic Habitat Model: Conclusions Salinity range from 5 to 90 g/L along the Lagoon was best in terms of the suitability of entire Lagoon for the four key fish species as well as supporting other important biological communities including both macrophytes and infauna. Analysis of mudflat availability at different water levels suggests that average water level of 0.12m AHD gives the maximum average mudflat area. Outputs depict the mudflat areas up to 12 cm depth from the water level at 1 cm vertical resolution. Waterbirds are specific in their prey and are specialized in their use of mudflats under different water depths. Possible to model the relationship between different waterbirds and their requirements at particular depths. These spatial models can be a management tool allowing quantification of habitats for key species for specified flow scenarios and can inform decisions on the amount and frequency of barrage outflows once the Lower Lakes are recharged and excess water is available for the Coorong.

Dynamic Habitat - CLLAMM technical briefing

by University of Adelaide on Jul 20, 2009

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