The value proposition for systematic long-term vegetation studies

Abstract

Long-term vegetation observations are rare but essential for the effective management of our natural assets. Studies of 3-4 years allow us to discern short-term variability, but long-term trends are only detectable over multiple decades. Through a meta-analysis of several medium to long-term studies in Australia—Kidman Springs, 30 and 50 years; Koonamore, 90+ years; the Brigalow Catchment study, 60 years; the Wambiana grazing trial, 26 years; several Australian Wildlife Conservancy sites across northern Australia, 19+ years; and one site in the USA, Jornada, 105 years—we discuss their benefits, the challenges, the management of the resulting data and information, and their future. We will argue that such sites are vital for the determination of the effects of perturbations caused by fire, thinning, grazing, water diversion, soil erosion, pollution, pathogens, weeds, insect pests and feral animals. They provide points of validation for a variety of types of models, help us better understand the systems involved, and inform management. Quite often these benefits are unpredictable and depend on multi-disciplinary synthesis. The interpretation of the data from such sites can be enhanced by integration with longer term remote sensed data. Ongoing measurement, management and custodianship is, however, often fraught. Measurements that were designed, for example, in 1920, are not always seen as relevant today, a disincentive for participating researchers. Support from the institutions managing the sites has proved variable. Sites can be attractive for a sponsoring body for their sheer age, but usually there is little understanding of the discipline involved, or what is required for their continuation. The expectation for data and information from such sites has changed profoundly with time. Repositories and observatories like the Environmental Data Initiative in the USA and TERN in Australia provide data from several long-term sites. We can expect changes and expectations to evolve into the future.