Conservation, restoration and management goals often aim for benchmarks and reference states that are perceived through a historical, near-natural or relatively undisturbed conceptual lens. Due to rapid transformation of the biosphere, we argue that historical reference frames are effectively unmeasurable and unknowable. There is also growing evidence that for some ecosystems, regaining these references states is often unachievable.
To address this problem, we must reframe the conceptual underpinnings of these historical reference states, to an alternate framework that is more appropriate for the conservation, restoration and management of biodiversity in contemporary landscapes. Furthermore, we must identify appropriate and defensible means of operationalizing contemporary benchmarks and the reference states they describe.
Here, we demonstrate the potential to use vegetation plot data to describe the empirical benchmarks for ‘best-on-offer’ reference state for vegetation within contemporary landscapes in New South Wales (approximately 800 000 km2 or 308 000 mi2), Australia.
Results/Conclusions
We assembled the compositional and structural attributes for six growth form groups (trees, shrubs, grasses, forbs, ferns and others) from over 37000 vegetation plots, surveyed between 1984 and 2015. We modelled ‘best-on-offer’ as the 75th percentiles of the data distribution for each compositional and structural attribute to quantitatively define the contemporary empirical benchmarks. Our models accounted for differences in bioregion, vegetation type, climate, season and the total rainfall for the prior 12 months.
Through the use of archived vegetation plot data, we have delivered an operational approach to defining empirical contemporary benchmarks and have generated 9152 empirical benchmarks for 656 bioregional vegetation types to support management and restoration of ecosystems.
This approach overcomes the intractable shortfalls of using historical reference states. Empirical contemporary benchmarks provide a framework for informing evidence-based decisions and are necessary for effective conservation, restoration and management within our current and future human-dominated landscapes.