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In New Zealand, five of the six endemic bird species that breed primarily in South Island braided river beds are classed as threatened. A major cause of decline for these species is predation by introduced mammals, and predator-trapping programs are undertaken in the braided rivers of the Mackenzie Basin to protect them. Trapping programs carried out between September 1997 and April 2001 provided the opportunity to investigate predator diet from the gut contents of 375 cats (Felis catus), 371 ferrets (Mustela furo) and 86 stoats (Mustela erminea). As a percentage frequency of occurrence of the main prey items, cat diet consisted of lagomorphs (present in 70% of guts), birds (in 47%), lizards (30%) and invertebrates (36%). Ferret diet consisted of lagomorphs (69%) and birds (28%). Stoat diet consisted of lagomorphs (50%), birds (51%), lizards (21%) and invertebrates (23%). The frequency of occurrence of birds in all three predators was higher in the spring/summer of 1997 – immediately after rabbit haemorrhagic disease (RHD) was introduced – than in any other previous diet study on these braided rivers. This suggests that RHD did lead to increased predation pressure on birds, at least in the short term.

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Decision theory provides an organised approach to decision making in natural resource conservation. The theory requires clearly stated objectives, decision alternatives and decision-outcome utilities, and thus allows for the separation of values (conservation and other societal objectives) from beliefs. Models express belief in the likely response of the system to conservation actions, and can range from simple, graphical representations to complex computer models. Models can be used to make predictions about likely decision-outcomes, and hence guide decision making. Decision making must account for uncertainty, which can be reduced but never eliminated. Uncertainty can be described via probabilities, which in turn can be used to compute the expected value of alternative decisions, averaging over all relevant sources of uncertainty. Reduction of uncertainty, where possible, improves decision making. Adaptive management involves the reduction of uncertainty via prediction under two or more alternative, structural models, comparison of model predictions to monitoring, and feedback via Bayes' Theorem into revising model weights, which in turn influences decision making. As part of a 3-day workshop on structured decision making (SDM) and adaptive resource management (ARM), we constructed a prototypical decision model for the recovery for Hector's dolphin (Cephalorynchus hectori), an endangered dolphin endemic to New Zealand coastal waters. Our model captures several steps in the process of building an SDM/ARM framework, and should be useful for managers wishing to apply these principles to dolphin conservation or other resources problems.

1. Applied ecologists are often interested in understanding the effects of management on ecological systems. If management (treatment) is applied nonrandomly, as in observational studies, then analysis must account for the potential confounding caused by variables that could have influenced both treatment assignment and the outcome of interest. Methods that do not adjust for all confounding variables can only estimate associations between treatment and outcome, not treatment effects.2. Data collected in observational studies are usually analysed with linear or generalized linear models, which can estimate treatment effects by adjusting for confounding variables. However, if there is little overlap in the distributions of confounding variables among the treatment groups then conventional regression extrapolates to areas of the covariate space where at least one of the treatment groups was unlikely to be observed.3. An alternative procedure for assessing treatment effects is to use the propensity score, which is the probability of treatment assignment given potential confounding variables. The propensity score can be used to reduce systematic differences in confounding variables among the treatment groups, ensuring that data more closely resemble that expected under a randomized experiment. The propensity score also identifies situations where treatment inferences must rely on strong assumptions. 4. We used Monte Carlo simulation to examine the properties of commonly used propensity score methods for estimating treatment effects in the presence of nonrandom allocation of treatments. We then illustrated their application in a case study estimating the effects of invasive herbivore management on tree condition. 5.Our results indicate that propensity score methods can be robust to model misspecification, allowing the estimation of average causal effects and resulting in more reliable inferences. We discuss key considerations for using propensity score methods for analysing ecological data. K E Y W O R D SANCOVA, average treatment effect, average treatment effect on the treated, brushtail possum, counterfactual, inverse probability of treatment weighting, matching, observational study | 321Methods in Ecology and Evoluঞon RAMSEY Et Al.