Interacting effects of vegetation, soils and management on the sensitivity of Australian savanna rangelands to climate change

Abstract

There is an increasing need to understand what makes vegetation at some locations more sensitive to climate change than others. For savanna rangelands, this requires building knowledge of how forage production in different land types will respond to climate change, and identifying how location-specific land type characteristics, climate and land management control the magnitude and direction of its responses to change. Here, a simulation analysis is used to explore how forage production in 14 land types of the north-eastern Australian rangelands responds to three climate change scenarios of +3°C, +17% rainfall; +2°C, −7% rainfall; and +3°C, −46% rainfall. Our results demonstrate that the controls on forage production responses are complex, with functional characteristics of land types interacting to determine the magnitude and direction of change. Forage production may increase by up to 60% or decrease by up to 90% in response to the extreme scenarios of change. The magnitude of these responses is dependent on whether forage production is water or nitrogen (N) limited, and how climate changes influence these limiting conditions. Forage production responds most to changes in temperature and moisture availability in land types that are water-limited, and shows the least amount of change when growth is restricted by N availability. The fertilisation effects of doubled atmospheric CO 2 were found to offset declines in forage production under 2°C warming and a 7% reduction in rainfall. However, rising tree densities and declining land condition are shown to reduce potential opportunities from increases in forage production and raise the sensitivity of pastures to climate-induced water stress. Knowledge of these interactions can be applied in engaging with stakeholders to identify adaptation options.

Grazing impacts on the susceptibility of rangelands to wind erosion: The effects of stocking rate, stocking strategy and land condition

“…The approach also provides a basis for a better understanding of future changes in landscape erodibility in response to the interacting effects of climate variability, climate change and grazing land management. Webb et al (2012) simulated forage production under various climate change scenarios for several land types in Queensland including the four in this study. They show that under hotter (+3°C) and wetter (+17% mean annual rainfall) climate, forage production could increase up to 60%, which should reduce the sensitivity of landscape to wind erosion and reduce accelerated wind erosion rates across if current grazing practices are maintained.…”

“…They show that under hotter (+3°C) and wetter (+17% mean annual rainfall) climate, forage production could increase up to 60%, which should reduce the sensitivity of landscape to wind erosion and reduce accelerated wind erosion rates across if current grazing practices are maintained. Under a warmer (+2°C) and drier (À7% mean annual rainfall) climate or a hotter (+3°C) and drier (À46% mean annual rainfall) climate, Webb et al (2012) reported potential decreases in forage production as large as 90%. Combined with expected reductions in soil moisture under this scenario, we might expect land erodibility to increase across the study area.…”

“…The model parameterisations sought to represent the effects of landforms, pasture species and soil attributes (texture, fertility and drainage) on the soil water balance and pasture biomass dynamics that influence land erodibility in each land type. The parameterisations follow those of Day et al (1997) and Webb et al (2012). Appendix A summarises the key functional parameters that define the productivity of each land type.…”

“…GRASP was parameterised to represent each of the study land types in four conditions: excellent, good, fair, and poor (following Webb et al, 2012). The land conditions were described in terms of a decline of perennial grasses and a reduction of plant density through the grass basal area.…”

“…AUSLEM draws input data from a spatially distributed pasture production model (AussieGRASS). The one-dimensional version of this model, the grass and livestock production model GRASP, can be applied to assess pasture degradation risk in response to climate variability and change (Day et al, 1997;Ash et al, 2000;McKeon et al, 2000McKeon et al, , 2004Howden et al, 1999;Webb et al, 2012). We use GRASP here to provide a scenario-based analysis of the effects grazing management practices on landscape elements that control wind erosion across a range of land types.…”