More models

Species specific water requirements

Flow assessment

Generalised and process models

Low flow spawning fish

About low flow spawning fish

The low flow spawning model was created to quantify changes in suitable spawning conditions for fish species of Queensland freshwater streams that require stable low flow conditions for successful recruitment.

Water requirements

This model has been designed for serial spawning fish species, i.e. that different females within a local population can lay eggs at different times to each other and the maximum number of spawning events is one per day per female. Results are therefore calculated as a moving window of overlapping recruitment opportunities.

Model purpose

The purpose of the model is to assess the long term population viability of fish that are dependent on stable low flow conditions for successful spawning.

Development context

This model has been developed using quantitative life-history information from the literature and expert opinion (see Cockayne et al 2010).

Spatial application

This model may be applied to series spawning fish that depend on suitable temperature and stable flow conditions to spawn.

Model description

Ecohydrological rules

Stable low-flows are required for successful recruitment. Suitable water temperature required for successful spawning as well as egg and larvae development. Stable water levels are also required for successful egg and larval development and survival.

A recruitment opportunity for a species is assumed to have occurred when suitable water temperature and water level stability have occurred for the duration of egg and larval development. The parameters are:

  • water temperature > a threshold value (or it is within a defined spawning season) and
  • water level remains stable, e.g. ±5cm of starting level for the duration of egg development, and
  • water level changes gradually, e.g. < 5cm per day for the duration of larval development.

Assessment methods

This model produces binary daily results (daily spawning success). These results are then aggregated to a yearly result, and then further to a temporal result based on the defined assessment parameters.

The temporal results are then analysed across locations to report an overall landscape risk by considering the simultaneous occurrence of failures across the system.

Inputs

Data
  • Daily depth data – required
  • Daily flow data – optional
  • Daily temperature data – optional (if not loaded the seasonal start and end is used for every year)
Parameter Sections
  • Lowflow – define the lowflow requirement. Either a set threshold or the median flow across the time series.
  • Breeding Season – define the breeding season, which lowflow much occur in. Either a set season between dates, or based on temperature if the 7 day moving average of temperature exceeds a set threshold.
  • Life Stages Criteria (Egg) – define egg success, given breeding success. A total max change in depth, across a set number of days.
  • Life Stages Criteria (Larvae) – optionally define larvae success, given egg success. If considered, a max daily change in depth, across a set number of days following egg criteria success.

Outputs

  • Daily time series of recruitment success, including intermediate results such as if the day is in breeding season, if the flow threshold is not exceeded, if there is suitable time to complete the event (enough days to check egg and larvae criteria), the egg criteria success and finally the larvae criteria success.
  • Yearly time series of assessment results
  • Temporal time series of assessment results
  • Spatial time series of assessment results

User interface

Underlying code

This plugin is written in Python and its underlying code is publicly available from the Eco Risk Projector computation repository.

References

Cockayne B, McGregor G, Marshall J, Lobegeiger J, and Menke N 2010, ‘Fitzroy Water Resource Plan review technical report 3: ecological risk assessment’, Department of Environment and Resource Management, Queensland Government, Brisbane.