Fish modelling

How do flows and climate affect growth dynamics of Murray–Darling Basin fishes?

Individual growth rate of fish has a strong influence on critical population processes including survival. However, our understanding of how managed and natural flows affect growth of the Basin’s fishes is rudimentary.

By using fish otoliths (ear bones) collected as a part of the Commonwealth Long Term Intervention Monitoring (LTIM) program, this research proposes to back-calculate the growth rates of individual fish from three native fish species - Murray cod, Bony herring and Golden perch - at sites across the Basin, and to then model those growth rates to determine the effects of flow and temperature on growth histories.


Due to their socio-economic importance, fish are recognised as a critical indicator of flow outcomes under the Basin Plan (Basin Plan 2012). A key objective within the Basin-Wide Watering Strategy is to manage flows to improve survival rates of fishes with medium to long life-spans (MDBA 2014).

If we wish to see increases in fish population size, then meeting this objective is critical. From a scientific perspective, however, direct estimation of flow-survival relationships is a great challenge, and takes several years of quality data to establish (Walters 1997). The impact of flows on fish survival in the Basin is being studied directly as part of the Commonwealth’s Long Term Intervention Monitoring (LTIM) program. To complement the Long Term Intervention Monitoring directly, long-term analyses of flow-survival relationships at the Basin-scale, there is a need for further short-term studies that take novel approaches to the problem; studies that improve our predictive understanding of how flows affect proxies of survival, and hence our ability to report on flow outcomes at the temporal scale of 1–5 years.

Individual growth rate has a strong influence on critical population processes (Sauer and Slade 1987), including survival (Jensen and Johnsen 1999). However, our understanding of how managed and natural flows affect growth of the Basin’s fishes is rudimentary (Tonkin et al. 2011). e propose to use fish otoliths (ear bones) collected as part of Long Term Intervention Monitoring (LTIM) to determine the effects of flows and temperature on growth histories of Murray cod (Maccullochella peelii peelii Mitchell), Bony herring (Nematalosa erebi Günther) and Golden perch (Macquaria ambigua ambigua Richardson) at six sites throughout the Basin (Gwydir, Lachlan, Murrumbidgee, Edward-Wakool, Goulburn and lower Murray Rivers).

The approach we plan on taking has been used to study impacts of environmental change on population performance in various contexts (Morrongiello and Thresher 2015; Morrongiello et al. 2012; Morrongiello et al. 2014; Neuheimer et al. 2011), but has not been used to understand the impacts of environmental flows at any temporal scale. It follows that in addition to generating highly desirable outcomes to water managers (see Management outcomes), we are also breaking new ground from a scientific point of view.


The objectives of this research theme are to:

  1. For Murray cod, Golden perch and Bony herring, use otoliths obtained as part of Long Term Intervention Monitoring (LTIM) to back-calculate time series of the growth rates of individuals, and model those growth rates as a function of flows and temperature throughout fishes’ lives.
  2. Parameterise a model that facilitates forecasting of how flows and temperature affect growth of these species throughout the Basin.
  3. Integrate growth models developed in Objectives 1 and 2 within a structured population model that enables us to forecast how a changing climate interacts with flows to affect the dynamics of fish populations within the Basin.

Management implications

Improved capacity to evaluate outcomes from managed flows

The work proposed here will yield inferences that enable us to report against key Basin Plan objectives. Further, a key challenge facing the Commonwealth Environmental Water Office (CEWO) is reporting on fish response to managed flows (a) within monitored selected areas of the Basin, and (b) outside monitored areas of the Basin. This study will help Commonwealth Environmental Water Office (CEWO) with both of these reporting objectives. First, we are using otoliths collected from Commonwealth Environmental Water Office's (CEWO) key monitoring areas throughout the Basin, which means we can back-calculate the growth of fishes that have been exposed to Commonwealth environmental water in recent years, and we will also have good hydrology data from those areas; data where the managed and background components of the hydrograph have been separated. Second, we will be estimating the parameters of models that can then be used for inferring the likely range of managed flow impacts on fish growth in unmonitored areas, where good hydrology data exist, using ‘predictive inference’.

Increases effectiveness of flow delivery

The models generated will facilitate decision making within and across years, specifically with respect to how hydrograph features (e.g. timing, magnitude etc.) affect growth. The spatial scale of the analysis (whole-of-Basin) greatly broadens the generality of any inferences we make, hence its utility within the Basin.

Improved capacity to anticipate emerging risks

As the Basin-Wide Watering Strategy evolves, we must improve our capacity to predict how changing climate will interact with flows to affect Basin Plan objectives (MDBA 2014). This study specifically aims to improve our understanding of climate-flow interactions and generates models that enable us to forecast and, hence anticipate emerging threats to fish growth.

MMCP Fact Sheet 4 Fish Growth Dynamics [PDF 1.0MB]


Jensen AJ, Johnsen BO (1999). The functional relationship between peak spring floods and survival and growth of juvenile Atlantic Salmon (Salmo salar) and Brown Trout (Salmo trutta). Functional Ecology 13: 778-785.

Morrongiello JR, Thresher RE (2015). A statistical framework to explore ontogenetic growth variation among individuals and populations: a marine fish example. Ecological Monographs 85: 93-115.

Morrongiello JR, Thresher RE, Smith DC (2012). Aquatic biochronologies and climate change. Nature Climate Change 2: 849-857.

Morrongiello JR, Walsh CT, Gray CA, Stocks JR, Crook DA (2014). Environmental change drives long-term recruitment and growth variation in an estuarine fish. Global Change Biology 20: 1844-1860.

Neuheimer AB, Thresher RE, Lyle JM, Semmens JM (2011). Tolerance limit for fish growth exceeded by warming waters. Nature Climate Change 1: 110-113.

Sauer JR, Slade NA (1987). Size-based demography of vertebrates. Annual Review Ecology and Systematics 18: 71-90.

Tonkin ZD, King AJ, Robertson AI, Ramsey DSL (2011). Early fish growth varies in response to components of the flow regime in a temperate floodplain river. Freshwater Biology 56: 1769-1782.

Walters C (1997). Challenges in adaptive management of riparian and coastal ecosystems. Ecology and Society 1: 1-19.