Summer reading

PlanningLast week I was fortunate to attend a workshop in Queensland with colleagues from CSIRO and UQ, hosted by Iadine Chadès. It was a small and focused group skewed heavily towards the most quantitative environmental management research. Together we reviewed and classified adaptive management optimisation algorithms, from the foundational fisheries work of Carl J. Walters et al. in the 1970s and 80s, through the waterfowl hunting papers of the 1990s and 2000s to the recent contributions of our own research labs and the advances made in computer science that could determine our future directions.

Literature tableIt was a luxury to spend three straight days poring over the literature (not to mention the 5pm head-clearing beach visits). Most of us had several “Aha!” moments as we took the time to really interrogate the models and philosophies in articles we might have already read and cited several times before. Though they were severely restricted in computational capacity, early adaptive management researchers had some incredibly valuable insights into the nature and value of experimental management strategies; insights that we’ve sometimes forgotten or overlooked in subsequent work.

I’d encourage other researchers (and especially students!) to dig deep into the literature of your field – you’re bound to find some gems, and may save yourself from rehashing a problem already solved.

Adaptive management hall of fame:

Walters C.J. (1975) Optimal harvest strategies for salmon in relation to environmental variability and uncertain production parameters. Journal of the Fisheries Research Board of Canada 21: 1777-1784.

Walters C.J. & Hilborn R. (1978) Ecological optimization and adaptive management. Annual Review of Ecology and Systematics 9: 157-188.

Smith A.D.M & Walters C.J. (1981) Adaptive management of stock-recruitment systems. Canadian Journal of Fisheries and Aquatic Sciences 38: 690-703.

Nichols J.D., Johnson F.A. & Williams B.K. (1995) Managing North American waterfowl in the face of uncertainty. Annual Review of Ecology and Systematics 26: 177-199.

Johnson F.A., Moore C.T., Kendall W.L., Dubovsy, J.A., Caithamer D.F., Kelley, J.R. & Williams B.K. (1997) Uncertainty and the management of mallard harvests. The Journal of Wildlife Management 61: 202-216.

Parma A.M. & the NCEAS Working Group on Population Management. (1998) What can adaptive management do for our fish, forests, food, and biodiversity? Integrative Biology 1: 16-26.

Johnson F.A., Kendall W.L. & Dubovsky J.A. (2002) Conditions and limitations on learning in the adaptive management of mallard harvests. Wildlife Society Bulletin 30:176-185.

Runge M.C., Converse S.J. & Lyons J.E. (2011). Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program. Biological Conservation 144: 1214-1223.

Shameless nepotism:

McCarthy M.A. & Possingham H.P. (2007) Active adaptive management for conservation. Conservation Biology 21: 956-963.

Hauser C.E. & Possingham H.P. (2008) Experimental or precautionary? Adaptive management over a range of time horizons. Journal of Applied Ecology 45: 72-81.

Moore A.L., Hauser C.E. & McCarthy M.A. (2008) How we value the future affects our desire to learn. Ecological Applications 18: 1061-1069.

Rout T.M., Hauser C.E. & Possingham H.P. (2009) Optimal adaptive management for the translocation of a threatened species. Ecological Applications 19: 515-526.

McDonald-Madden E., Probert W.J.M., Hauser C.E., Runge M.C., Possingham H.P., Jones M.E., Moore, J.L., Rout T.M., Vesk P.A. & Wintle B.A. (2010) Active adaptive conservation of threatened species in the face of uncertainty. Ecological Applications 20(5): 1476-1489.

Moore A.L. & McCarthy M.A. (2010) On valuing information in adaptive-management models. Conservation Biology 24: 984-993.

Probert W.J.M., Hauser C.E., McDonald-Madden E., Runge M.C., Baxter P.W.J. & Possingham H.P. (2011) Managing and learning with multiple models: objectives and optimization algorithms. Biological Conservation 144: 1237-1245.

Recommended Reading | December 2013

Rather than drawing on their impressively rich data-set to empirically test questions about how brain connectivity characteristics relate to behaviour, the authors instead offer untested stereotype-based speculation.

– another well-timed neurosexism smackdown from Cordelia Fine.

Urban ecology point transects.

Peter Higgs wouldn’t be productive enough for today’s academic environment.

More on how publication incentives are interfering with quality science.

John Morgan observes the Victorian alps, then and now.

LOL, their theses.

Nature‘s top 10 people who mattered in 2013.

Some of the best online science writing of 2013.