Fig. 2: Quantifying how river flows influence fishery catches.
From: Integrated assessment of river development on downstream marine fisheries and ecosystems
a,b, Observed variability (black points) in the total annual commercial catch (t) of common banana prawns, barramundi and mud crabs from each of five catchment systems in the GoC; blue lines show the best model fits achievable when estimating catches based on fishing effort but ignoring river flows, compared with the improved ability of the model to fit the observed catches (red lines) (a) when linking end-of-system flow variability to the system dynamics, using weekly or monthly flow inputs with an example plot showing interannual variability in flows (b). The Mornington region was assumed influenced by the adjacent Flinders River flows. c, For prawns, the model also estimates the importance of different rivers influencing recruitment (to the fishery) per model region based on flow anomalies contributed by the different river systems. The model estimates relative contributions that are bounded between 0 and 1 (that is, results suggest no effect of a river on that region’s prawn recruitment, or varying influences; values shown are model version 5 estimates; see Supplementary Table 8 for associated standard deviations). Hence, for example, model results suggest that the Norman River is the dominant driver of prawns caught directly offshore of the Norman River model region, with some contribution from the Flinders River. The Norman River is also estimated to be an important driver of prawn catches in the neighbouring Gilbert River model region. By contrast, prawn catches in the Mitchell and Flinders model regions are predicted to be driven on average by a combination of flow anomalies across all four river systems (see Supplementary Table 8 for details of model fits). Credit: species icons, PhyloPic.
