Topography may mitigate drought effects on vegetation along a hillslope gradient through redistribution of soil moisture. We examined the interaction of topography, climate, soil moisture, and transpiration in a low-elevation, mixed-hardwood forest in the southern Appalachian Mountains.The effects of meteorological variation (wet and dry years) and topographic position (upslope and cove) were tested on daily soil moisture amplitude and recession and plot and species-specific transpiration. Trees in the cove plot were 17% taller and had 45% greater sapwood area than those in the upslope plot. Lower rates of soil moisture recession following rainfall events were observed at the cove plot compared to the upper plot. Greater daily soil moisture amplitude and plot transpiration, even in dry years, suggest that lower slope positions may have been buffered against moderate drought. We also observed similar transpiration in Quercus spp., Carya spp., and Liriodendron tulipifera in the cove plot between dry and wet years. Plot transpiration was reduced by 51% in the dry year in the upslope plot only, and transpiration by individual species in the plot reflected this pattern, suggesting water stress in dry years may be exacerbated by topography. With drought predicted to increase for these systems, the different drought responses of species, in addition to topographic effects, may lead to complex shifts in species composition.

[1] Long lead rainfall forecasts are highly valuable for planning and management of water resources and agriculture. In this study, we establish multiple statistical calibration and bridging models that use general circulation model (GCM) outputs as predictors to produce monthly rainfall forecasts for Australia with lead times up to 8 months. The statistical calibration models make use of raw forecasts of rainfall from a coupled GCM, and the statistical bridging models make use of sea surface temperature (SST) forecasts of the GCM. The forecasts from the multiple models are merged through Bayesian model averaging to take advantage of the strengths of individual models. The skill of monthly rainfall forecasts is generally low. Compared to forecasting seasonal rainfall totals, it is more challenging to forecast monthly rainfall. However, there are regions and months for which forecasts are skillful. In particular, there are months of the year for which forecasts can be skillfully made at long lead times. This is most evident for the period of November and December. Using GCM forecasts of SST through bridging clearly improves monthly rainfall forecasts. For lead time 0, the improvement is particularly evident for February to March, July and October to December. For longer lead times, the benefit of bridging is more apparent. As lead time increases, bridging is able to maintain forecast skill much better than when only calibration is applied.

No abstract

Forest species composition may change following a disturbance. This change can affect long term water yield from forested catchments when the replaced and replacement species have different evapotranspiration rates. Following strip-thinning experiments that removed 50% of the overstorey basal area in several Eucalyptus regnans water supply catchments in south eastern Australia, Acacia spp. (Acacia dealbata and Acacia melanoxylon) became the dominant overstorey species in most of the cut strips. More recently, low regeneration of E. regnans following wildfires in 2009 may result in mixed Acacia and E. regnans stands in some catchments. We compared transpiration of E. regnans and Acacia stands in the uncut and cut strips of a catchment that was stripthinned in early 1980s (Crotty Creek). We also compared transpiration and throughfall in a mixed E. regnans-A. dealbata regrowth stand 20 years after clear-fell logging (Road 8). Sap flow was measured for 13 and 6 months at Crotty Creek and Road 8, respectively. In both studies, mean daily sap flow density of Acacia spp. was lower than of E. regnans. Estimated Leaf Area Index of E. regnans stands was slightly greater than that of Acacia spp. Stomatal conductance (g c ), estimated by inverting the Penman-Monteith equation, differed between the species suggesting species-level physiological differences with Acacia being more sensitive to vapour pressure deficit than E. regnans. Throughfall measurements at Road 8 indicated interception was slightly higher in A. dealbata but only enough to offset about 13% of the difference in transpiration. Replacement of E. regnans by Acacia dominated stands may, therefore, decrease catchment evapotranspiration and increase streamflow.