of flooding for habitats (lakes, swamps) used by waterbird communities but these events are highly variable. The Lake Eyre Basin is widely regarded as one of the few desert river systems in the world without significant development () and as a result its ecosystems should be in good condition. Governments have implemented a Lake Eyre Basin Rivers Assessment (LEBRA) to assess the condition of the freshwater ecosystems of the Lake Eyre Basin. In this rivers assessment, all freshwater ecosystems dependent on surface water flows are considered. Unfortunately relatively few long-term biological data exist for such an assessment, particularly over a large part of the basin. This contrasts rainfall and flow data but even these are not so well represented (see Kennard et al. ()). One of the few long-term relevant data sets is the aerial survey of waterbirds in eastern Australia which extends across about half of the Lake Eyre Basin, surveying about 10% of this area ((, ); Fig. 1). This project used data collected from the aerial waterbird survey of eastern Australia over a long period (1983-2011,(, )), during which waterbird species and their total abundance were surveyed each year (Fig. 1). These waterbird data represent one of the longest data sets available for assessing the health of the rivers of the Lake Eyre Basin, contributing to the Lake Eyre Basin Rivers Assessment. The project focused on assessment at different spatial scales: the Basin (area where data exist) and individual wetlands. Further, the waterbird community were examined at the entire community level, abundance and species richness, functional groups (e.g. piscivores) and individual species. Analyses of functional groups provided understanding of potential changes in relation to other biota (e.g. fish and piscivores). We also modelled changes in waterbird communities in relation to time, river flows, rainfall, wetland area and the SOI index. Objectives There were five original objectives (see below) but scale of analyses was not separated out in these objectives making it difficult to clearly differentiate and so we have further disaggregated these scales so that they refer specifically to particular analyses done and the structure of this report (see below). Original objectives
Table 12. Ranking of models that performed best (within 2 AICs of best fit) in terms of explaining waterbird abundance across Lake Dunn, 1983-2012, in relation to each of the explanatory variables tested (see Table 1b for acronyms). Models were ranked from the best performing (highest AIC) to worst performing from 2048 candidate models. Model# Intercept Local Rain Lag1_Rain LEB_WTA Rain Lag1_Local Rain Lag1_Lake.Dunn.WTA Lag1_LEB_WTA Lake.Dunn.WTA Local.Flow SOI df logLik AICc delta weight 129 2.43 + 3.93 -19.81 49.03 0.00 0.34 130 2.43 + + 5.69 -17.28 49.23 0.20 0.31 161 2.41 + + 4.93 -18.91 50.24 1.21 0.19 193 2.41 + + 4.93 -19.10 50.61 1.58 0.16
Figure 74. Relative importance of the explanatory variables, calculated as a sum of the AIC weights over all of the models (see Table 1b for acronyms). Lake Yamma Yamma This large freshwater lake depends on Cooper Creek for its flows. Despite its size it did not have particularly high numbers of waterbirds, although species richness was reasonably high (Fig. 72). There was no evidence for any significant trends in abundance or species richness (Table 34). Figure 75. Abundance and species richness of waterbirds surveyed on Lake Yamma Yamma, during annual surveys of the Lake Eyre Basin, 1983-2012. The duck functional group was the most abundant, followed by the piscivores and herbivores (Table 34, Fig. 73). There was no evidence for any trends in abundances of functional groups (Table 34). Figure 76. Abundances of functional groups (du-ducks, he-herbivores, la-large waders, sh-shorebirds; see Appendix 1) on Lake Yamma Yamma, 1983-2012. There were only two years when breeding was recorded (Fig. 74). Figure 77. Breeding abundance (nests and broods) and richness of breeding species surveyed during annual surveys of Lake Yamma Yamma, 1983-2012. Grey teal, Pacific black duck and pink-eared duck were the dominant species (Fig. 75). Figure 78. Relative composition of waterbird species in Lake Yamma Yamma, showing the 12 most common species (total abundances) estimated during annual surveys of the Lake Eyre Basin, 1983-2012.
Modelling waterbird abundance We found the most contributing predictor variables from 2048 possible models were local wetland area and current and lagged LEB total wetlands area (Fig. 77). The highest ranking model (AICc score) included local wetland area and current and lagged LEB total wetlands area (Table 35 and 36). The model (Eq. 11) was highly significant (t=15.99, p<0.001), explaining 96.1% of the variance of the intercept (adjusted R2 = 0.95). L_Lake.Yamma.Yamma ~ LEB_WTA + Lag1_LEB_WTA+ Lake.Yamma.Yamma.WTA (Eq. 11) Table 35. Performance and coefficients of best model used to predict waterbird abundance, across the surveyed area of the Lake Yamma Yamma. Variable Estimate Std.Error t/F valuea Pr(>|t|) Intercept 1.05654 0.06608 15.99 9.65e-14 LEB_WTA 3.991 0.0329 Lag1_LEB_WTA 4.116 0.0303 Lake.Yamma.Yamma.WTA 200.358 <2e-16 at value estimated for intercept and F value for other variables