Effective management of global biodiversity requires careful planning based on an understanding of distribution, abundance and variety (Parkes, Newell & Cheal 2003). Vegetation communities are often used as a surrogate for biodiversity; however, assessing vegetation communities at a landscape-scale can be a daunting task. Advances in satellite imagery and aerial photography have enabled substantial progress to be made in determining the spatial distribution of vegetation (Cherrill et al. 1995), yet the successful management of remnant vegetation also depends on understanding its attributes, which typically requires on-ground assessments (Landres, Morgan & Swanson 1999). Land management agencies have recognized the importance of understanding vegetation condition and have different definitions of condition for different purposes (Keith & Gorrod 2006). We define vegetation condition, for biodiversity conservation, as the extent to which the attributes of the vegetation differ from the average condition of mature and long-undisturbed examples of the same community (Parkes et al. 2003).
To use vegetation condition as a surrogate for biodiversity, the parameters measured include habitat features for many species of fauna (e.g. presence of tree hollows) and common indicators of habitat degradation (e.g. invasive species abundance; Keith & Gorrod 2006). Vegetation condition assessments can then be used to: (i) measure success (Keddy & Drummond 1996), (ii) establish offsets for biodiversity lost through development actions (ten Kate, Bishop & Bayon 2004), (iii) determine appropriate financial incentives for biodiversity conservation on private land (Oliver et al. 2005; USDA 2003), (iv) inform strategic management planning (NSW DEC 2005) and (v) report biodiversity conservation progress (CBD 2004). While a useful planning tool for biodiversity conservation, the costs of vegetation condition assessment methods can be prohibitively high; hence, there is an ongoing need for accurate and cost-effective on-ground vegetation condition assessments (Jensen et al. 2000; Beck & Gessler 2008).
There is an inherent relationship between the resolution of vegetation condition data and the cost of assessment techniques (Cohen et al. 2005). Many assessment methods have been developed globally (e.g. Dahms & Geils 1997; Gibbons et al. 2005; NCC 1990; Parkes et al. 2003), and generally adopt one of two approaches: systematic or visual assessments. Systematic assessments estimate condition by measuring attributes of the vegetation, then combining these into an index of condition (e.g. Rooney & Rogers 2002; Hargiss et al. 2008) often based on comparisons with a benchmark (e.g. Parkes et al. 2003; Gibbons et al. 2005). These assessments tend to provide more repeatable, higher-resolution estimates of condition but can be resource-intensive (Helm & Mead 2004). For landscape-scale condition assessments, purely visual assessment methods, using unstructured estimates of condition made in a largely intuitive manner (University of Ballarat 2001; Hockings et al. 2009), offer a lower cost alternative. Visual assessments can be made during visits to reserves made in the course of regular management activities and be applied over larger areas, but generally provide lower-resolution estimates of condition. However, the subjective nature of these judgements can generate criticism about their reliability (Burgman 2001). Where resources are limited, a compromise must be reached between the cost and resolution of estimates that still achieves the objectives of the assessment (Archaux, Berges & Chevalier 2007). We must therefore understand the degree to which different condition assessment methods can meet these different objectives to select the most appropriate technique.
Although higher-resolution estimates are often perceived as preferable to lower-resolution estimates, there have been few real tests of their ability to reflect the ‘true’ condition of vegetation, and repeatability may be an issue for both methods (see Gorrod & Keith 2009). Given that the appropriate compromise between the resolution and cost of condition estimates depends on the purpose of the assessment, we do not discuss the relative accuracy of systematic and visual methods in this study, but instead consider whether they can achieve the five main purposes of condition assessments.
To determine which assessment methods are most appropriate for the different purposes of condition assessments we use an assessment technique applied in protected areas in Australia as a case study. Both systematic and visual assessment methods were employed for the same quadrats, thus excluding spatial and temporal variations between the assessment types and allowing the relationship between the approaches to be examined. We use these data to investigate: (i) the degree to which visual judgements of condition reflect measured assessments; (ii) which elements of condition, if any, observers respond to when making visual assessments; and (iii) the implications for using the two assessment methods for different purposes of condition assessments.