Fig 1.
The total benefit of implementing conservation management is the sum of averted losses and additional gains above the current value.
The top solid line represents trends in conservation value with offset and the lower solid line represents the trends under the counterfactual. While our elicitations focused on estimating management gain, where possible we also estimated averted loss and total benefit. Adapted from Maron et al. [7].
Table 1.
Individual vegetation condition attributes that formed the basis for the structured elicitation.
Table 2.
The three Western Slope Grassy Woodland (WSGW) scenarios for which future values of 13 vegetation attributes were elicited (also see S3 File).
Fig 2.
Boxplots of expert estimates of vegetation condition (A, E), management gain (B, F), averted loss (C, G) and total benefit (D, H). A through D are the five common vegetation patches provided to all 29 experts. Each patch in E through H was assessed by 4–6 experts. In all graphs the sites are ranked according to panel E, i.e. by their median current expert vegetation condition score. Averted loss and total benefit are based on estimates from 16 experts.
Fig 3.
Boxplots of averted loss, management gain and total benefit after 20 years for individual vegetation attributes within a Western Slopes Grassy Woodland with moderate starting values.
For each attribute, data are derived by pooling 2100 random draws from the future and reference probability distributions of 25 experts. Total benefit is the sum of averted loss and management gain. Averted loss is estimated as the difference between the counterfactual and the initial attribute condition and therefore takes a positive value when the attribute is expected to decline relative to the reference under a business as usual scenario. Ltrees = Large Trees.
Fig 4.
Individual expert average estimates of averted loss and management gain for each of 11 vegetation attributes, with relationships indicated by simple linear fits.
Each point represents the mean opinion of an individual expert, derived from their elicited probability distributions. Estimates in the top left quadrant of each panel indicate an optimistic opinion about future trends under both BAU and an offset (i.e. low AL, high MG). Estimates in the bottom right quadrat indicate those where experts were pessimistic about future trends, regardless of management scenario (i.e. high AL, low MG). Those in the top right were pessimistic about trends under BAU but optimistic about trends with an offset (i.e. high AL, high MG).
Fig 5.
Median expert predictions of management gain and current condition for each of 11 vegetation attributes in poor-, moderate- and good-quality WSGW.
Management gains are changes in the individual attributes, relative to a reference value, predicted to occur as a result of 20 years of offset management. Points are medians and lines are upper and lower quartiles derived from 2100 randomisations across 25 expert probability distributions. The broad qualitative site quality is supported by numeric estimates of aggregate vegetation condition, out of 100, derived from expert BRT models (condition score in legend in brackets).