Advertisement

Environmental Management

, Volume 61, Issue 3, pp 398–407 | Cite as

Make the Most of the Data You’ve Got: Bayesian Models and a Surrogate Species Approach to Assessing Benefits of Upstream Migration Flows for the Endangered Australian Grayling

  • J. Angus Webb
  • Wayne M. Koster
  • Ivor G. Stuart
  • Paul Reich
  • Michael J. Stewardson
Article

Abstract

Environmental water managers must make best use of allocations, and adaptive management is one means of improving effectiveness of environmental water delivery. Adaptive management relies on generation of new knowledge from monitoring and evaluation, but it is often difficult to make clear inferences from available monitoring data. Alternative approaches to assessment of flow benefits may offer an improved pathway to adaptive management. We developed Bayesian statistical models to inform adaptive management of the threatened Australian grayling (Prototroctes maraena) in the coastal Thomson River, South-East Victoria Australia. The models assessed the importance of flows in spring and early summer (migration flows) for upstream dispersal and colonization of juveniles of this diadromous species. However, Australian grayling young-of-year were recorded in low numbers, and models provided no indication of the benefit of migration flows. To overcome this limitation, we applied the same models to young-of-year of a surrogate species (tupong—Pseudaphritis urvilli)—a more common diadromous species expected to respond to flow similarly to Australian grayling—and found strong positive responses to migration flows. Our results suggest two complementary approaches to supporting adaptive management of Australian grayling. First, refine monitoring approaches to allow direct measurement of effects of migration flows, a process currently under way. Second, while waiting for improved data, further investigate the use of tupong as a surrogate species. More generally, alternative approaches to assessment can improve knowledge to inform adaptive management, and this can occur while monitoring is being revised to directly target environmental responses of interest.

Keywords

Adaptive management Environmental flows Australian grayling Bayesian Surrogate species Cross-taxon response-indicator species 

Notes

Acknowledgements

This work was funded through DELWP Research Contract, “VEFMAP Stage V: Further analysis of VEFMAP data”. We thank Fiona Spruzen, Paulo Lay, and the project Technical Reference Group for their guidance. We also acknowledge the long-term data collection efforts of the staff from the Arthur Rylah Institute and other providers, as well as the management of VEFMAP by the West Gippsland Catchment Management Authority.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. Backhouse G, O’Connor J, Jackson J (2008) National recovery plan for the Australian grayling Prototroctes maraena. Department of Sustainability and Environment, MelbourneGoogle Scholar
  2. Berra TM, Cadwallader PL (1983) Age and growth of Australian grayling, Prototroctes maraena Gunther (Salmoniformes: Prototroctidae), in the Tambo River, Victoria. Mar Freshw Res 34:451–460. doi: 10.1071/MF9830451 CrossRefGoogle Scholar
  3. Brown VA, Harris JA, Russell YR (2010) Tackling wicked problems through the transdisciplinary imagination. CSIRO Publishing, MelbourneGoogle Scholar
  4. Cadwallader PL, Backhouse GN (1983) Guide to the freshwater fish of Victoria. Victorian Government Printing Office, MelbourneGoogle Scholar
  5. Caro T (2010) Conservation by proxy. Island Press, Washington DCGoogle Scholar
  6. Chee Y, Webb A, Stewardson M, Cottingham P (2009) Victorian Environmental Flows Monitoring and Assessment Program: monitoring and assessing environmental flow releases in the Thompson River. eWater Cooperative Research Centre, MelbourneGoogle Scholar
  7. Clark JS (2005) Why environmental scientists are becoming Bayesians. Ecol Lett 8:2–14CrossRefGoogle Scholar
  8. Crook DA et al. (2010) Catadromous migrations by female tupong (Pseudaphritis urvillii) in coastal streams in Victoria, Australia. Mar Freshw Res 61:474–483CrossRefGoogle Scholar
  9. Crook DA, Macdonald JI, O’Connor JP, Barry B (2006) Use of otolith chemistry to examine patterns of diadromy in the threatened Australian grayling Prototroctes maraena. J Fish Biol 69:1330–1344CrossRefGoogle Scholar
  10. DEPI (2013) FLOWS—a method for determining environmental water requirements in Victoria: Edition 2. Department of Environment and Primary Industries, MelbourneGoogle Scholar
  11. Dudgeon D et al. (2006) Freshwater biodiversity: importance, threats, status and conservation challenges. Biol Rev 81:163–182CrossRefGoogle Scholar
  12. EarthTech (2003) Thomson River environmental flow requirements & options to manage flow stress. Earth Tech Engineering Pty Ltd, MelbourneGoogle Scholar
  13. Favreau JM, Drew CA, Hess GR, Rubino MJ, Koch FH, Eschelbach KA (2006) Recommendations for assessing the effectiveness of surrogate species approaches. Biodivers Conserv 15:3949–3969CrossRefGoogle Scholar
  14. Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models: analytical methods for social research. Cambridge University Press, Cambridge, NYGoogle Scholar
  15. Gippel CJ, Stewardson MJ (1995) Development of an environmental flow management strategy for the Thomson River, Victoria, Australia. Regul Rivers Res Manage 10:121–135CrossRefGoogle Scholar
  16. Gwinn DC, Beesley LS, Close P, Gawne B, Davies PM (2016) Imperfect detection and the determination of environmental flows for fish: challenges, implications and solutions. Freshw Biol 61:172–180CrossRefGoogle Scholar
  17. Hart BT (2015a) The Austalian Murray-Darling Basin Plan: challenges in its implementation (part 1). Int J Water Resour Dev 32:819–834. doi: 10.1080/07900627.2015.1083847 CrossRefGoogle Scholar
  18. Hart BT (2015b) The Austalian Murray-Darling Basin Plan: challenges in its implementation (part 1). Int J Water Resour Dev 32:835–852. doi: 10.1080/07900627.2015.1084494 CrossRefGoogle Scholar
  19. Hortle ME (1978) The ecology of the sandy, Pseudaphritis urvillii, in south-east Tasmania. BSc (Hons) Thesis. The University of Tasmania, Hobart, AustraliaGoogle Scholar
  20. Jager HI, Rose KA (2003) Designing optimal flow patterns for fall Chinook salmon in a Central Valley, California, River. N Am J Fish Manage 23:1–21CrossRefGoogle Scholar
  21. Knight AT, Cowling RM, Rouget M, Balmford A, Lombard AT, Campbell BM (2008) Knowing but not doing: selecting priority conservation areas and the research-implementation gap. Conserv Biol 22:610–617. doi: 10.1111/j.1523-1739.2008.00914.x CrossRefGoogle Scholar
  22. Koster WM, Amtstaetter F, Dawson DR, Reich P, Morrongiello JR (2016) Provision of environmental flows promotes spawning of a nationally threatened diadromous fish. Mar Freshw Res. doi: 10.1071/MF15398
  23. Koster WM, Dawson DR, Crook DA (2013) Downstream spawning migration by the amphidromous Australian grayling (Prototroctes maraena) in a coastal river in south-eastern Australia. Mar Freshw Res 64:31–41. doi: 10.1071/Mf12196 CrossRefGoogle Scholar
  24. Lindenmayer DB, Likens GE (2011) Direct measurement versus surrogate indicator species for evaluating environmental change and biodiversity loss. Ecosystems 14:47–59CrossRefGoogle Scholar
  25. Lunn D, Spiegelhalter D, Thomas A, Best N (2009) The BUGS project: evolution, critique and future directions (with discussion). Stat Med 28:3049–3082CrossRefGoogle Scholar
  26. Marohasy J (2003) Myth and the Murray: measuring the real state of the river environment. IPA Backgrounder 15(5): 1–28, http://ipa.org.au/library/IPABackgrounder15-5.pdf
  27. Murphy DD, Weiland PS, Cummins KW (2011) Critical assessment of the use of surrogate species in conservation planning in the Sacramento-San Joaquin Delta, California (U.S.A.). Conserv Biol 25:873–878CrossRefGoogle Scholar
  28. O’Connor JP, Mahoney JC (2004) Observations of ovarian involution in the Australian grayling (Prototroctes maraena). Ecol Freshw Fish 13:70–73CrossRefGoogle Scholar
  29. Papps D (2016) Adaptive management of commonwealth environmental water in the Murray-Darling Basin. Paper presented at the ABARES Outlook, CanberraGoogle Scholar
  30. Le Quesne T, Kendy E, Weston D (2010) The implementation challenge: taking stock of government policies to protect and restore environmental flows. The Nature Conservancy & WWF, Surrey, UK.Google Scholar
  31. SKM (2007) Environmental flows monitoring for the Goulburn and broken rivers: monitoring design report. Sinclair Knight Merz, MelbourneGoogle Scholar
  32. Walters CJ (2007) Is adaptive management helping to solve fisheries problems? Ambio 36:304–307CrossRefGoogle Scholar
  33. Webb JA, Arthington AH, Olden JD (2017a) Models of ecological responses to flow regime change to inform environmental flow assessments. In: Horne AC, Webb JA, Stewardson MJ, Richter BD, Acreman M (eds) Water for the environment: from policy and science to implementation and management. Elsevier, Cambridge, MA, pp 293–323Google Scholar
  34. Webb JA, de Little SC, Miller KA, Stewardson MJ, Rutherfurd ID, Sharpe AK, Poff NL (2015) A general approach to predicting ecological responses to environmental flows: making best use of the literature, expert knowledge, and monitoring data. River Res Appl 31:505–514. doi: 10.1002/rra.2832 CrossRefGoogle Scholar
  35. Webb JA, Miller KA, de Little SC, Stewardson MJ (2014) Overcoming the challenges of monitoring and evaluating environmental flows through science-management partnerships. Int J River Basin Manage 12:111–121. doi: 10.1080/15715124.2014.901332 CrossRefGoogle Scholar
  36. Webb JA, Stewardson MJ, Chee YE, Schreiber ESG, Sharpe AK, Jensz MC (2010a) Negotiating the turbulent boundary: the challenges of building a science-management collaboration for landscape-scale monitoring of environmental flows. Mar Freshw Res 61:798–807CrossRefGoogle Scholar
  37. Webb JA, Stewardson MJ, Koster WM (2010b) Detecting ecological responses to flow variation using Bayesian hierarchical models. Freshw Biol 55:108–126. doi: 10.1111/j.1365-2427.2009.02205.x CrossRefGoogle Scholar
  38. Webb JA, Watts RJ, Allan C, Warner AT (2017b) Principles for monitoring, evaluation and adaptive management of environmental flows. In: Horne AC, Webb JA, Stewardson MJ, Richter BD, Acreman M (eds) Water for the environment: from policy and science to implementation and management. Elsevier, Cambridge, MA, pp 607–631Google Scholar
  39. Wiens JA, Hayward GD, Holthausen RS, Wisdom MJ (2008) Using surrogate species and groups for conservation planning and management. BioScience 58:241–252CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Infrastructure EngineeringThe University of MelbourneParkvilleAustralia
  2. 2.Arthur Rylah Institute for Environmental Research, Department of Environment, Land, Water and PlanningHeidelbergAustralia

Personalised recommendations