Forest reorganisation effects on fuel moisture content can exceed changes due to climate warming in wet temperate forests.

The distributions of vegetation and fire activity are changing rapidly in response to climate warming. In many regions, climate effects on dead fuel moisture content (FMC) are expected to increase future wildfire activity. However, forest FMC is largely driven by microclimate conditions, which are moderated from open weather by vegetation canopies. As shifts in vegetation increase under climate warming, the extent to which future fire activity will be driven by climate directly or associated vegetation shifts remains unresolved. Here, we present a study aimed at quantifying the relative magnitudes of (i) direct climate warming, and (ii) vegetation change, on FMC. Field sites to evaluate these effects were established in a natural laboratory of altered forest states to mature wet temperate forest in south-eastern Australia. FMC was estimated using a process-based model and 48 years of reconstructed climate data. Canopy effects on microclimate were captured by transferring inputs from climate to microclimate using models parameterised with field observations. To evaluate the relative magnitude of climate and vegetation effects, we calculated the maximum difference in mean annual FMC across annual climate replicates and compared this to FMC differences across reorganising forest sites. Our results show vegetation effects on FMC can exceed those related to expected climate change. Changes to forest structure and composition increased (+15.7%) and decreased (-12.3%) mean annual FMC, with a larger negative effect when forest cover was completely removed (-18.5%). In contrast, the largest climate effect on FMC was -6.6% across 48-years of data. Our study demonstrates that the magnitude of vegetation effects on FMC can exceed expected climate change effects. Models of future fire activity that do not account for changing vegetation effects on microclimate are omitting a key biophysical control on FMC and therefore may not be accurately predicting future fire activity.

Long-term hydrological response emerges from forest self-thinning behaviour and tree sapwood allometry.

Fires in forested catchments are of great concern to catchment managers due to their potential effect on water yield. Among other factors such as meteorological conditions and topography, dominant vegetation and its regeneration traits can play a key role in controlling the variability in the type and recovery-time of the hydrological response between forested catchments after stand-replacing fires. In temperate South-Eastern Australia, a long-term reduction in streamflow from catchments dominated by regenerating tall-wet Eucalyptus obligate seeder forests was observed, which has substantial implications for Melbourne's water supply. While the unusual hydrological response has been attributed to the higher water-use of the regrowth forests, the dominant underlying mechanism has not yet been identified. Here we show analytically and with a closed-form solution that this streamflow pattern can emerge from forest dynamics, namely the combination of growth and tree mortality as constrained by the self-thinning line (STL) and sapwood allometry of the dominant overstory tree species under non-limiting rainfall regimes. A sensitivity analysis shows that observed variations in the relative streamflow anomaly trend can be explained by parameters controlling: (i) the shape of the STL; (ii) regeneration success; (iii) radial tree growth rate; and (iv) fire severity. We conclude that the observed variation in long-term post-disturbance streamflow behaviour might have resulted from different trajectories of forest dynamics and suggest that to minimize uncertainty in future water-balance predictions, eco-hydrological models for even aged forests include a mechanistic representation of stand demography processes that are constrained by forest inventory data.

2019-2020 Bushfire impacts on sediment and contaminant transport following rainfall in the Upper Murray River catchment.

During the 2019-2020 Australian bushfire season, large expanses (~47%) of agricultural and forested land in the Upper Murray River catchment of southeastern (SE) Australia were burned. Storm activity and rainfall following the fires increased sediment loads in rivers, resulting in localized fish kills and widespread water-quality deterioration. We collected water samples from the headwaters of the Murray River for sediment and contaminant analysis and assessed changes in water quality using long-term monitoring data. A robust runoff routing model was used to estimate the effect of fire on sediment loads in the Murray River. Peak turbidity in the Murray River reached values of up to 4200 nephelometric turbidity units (NTU), shown as pitch-black water coming down the river. The increase in suspended solids was accompanied by elevated nutrient concentrations during post-bushfire runoff events. The model simulations demonstrated that the sediment load could be five times greater in the first year after a bushfire than in the prefire condition. It was estimated that Lake Hume, a large reservoir downstream from fire-affected areas, would receive a maximum of 600 000 metric tonnes of sediment per month in the period immediately following the bushfire, depending on rainfall. Total zinc, arsenic, chromium, nickel, copper, and lead concentrations were above the 99% toxicant default guideline values (DGVs) for freshwater ecosystems. It is also likely that increased nutrient loads in Lake Hume will have ongoing implications for algal dynamics, in both the lake and the Murray River downstream. Information from this study provides a valuable basis for future research to support bushfire-related policy developments in fire-prone catchments and the mitigation of postfire water quality and aquatic ecosystem impacts. Integr Environ Assess Manag 2021;17:1203-1214. © 2021 Commonwealth of Australia. Integrated Environmental Assessment and Management © 2021 Society of Environmental Toxicology & Chemistry (SETAC).

Spatio-temporal transpiration patterns reflect vegetation structure in complex upland terrain.

Topography exerts control on eco-hydrologic processes via alteration of energy inputs due to slope angle and orientation. Further, water availability varies with drainage position in response to topographic water redistribution and the catena effect on soil depth and thus soil water storage capacity. Our understanding of the spatio-temporal dynamics and drivers of transpiration patterns in complex terrain is still limited by lacking knowledge of how systematic interactions of energy and moisture patterns shape ecosystem state and water fluxes and adaptation of the vegetation to these patterns. To untangle the effects of slope orientation and hillslope position on forest structure and transpiration patterns, we measured forest structure, sap flux, soil moisture, throughfall and incoming shortwave radiation along two downslope transects in a forested head water catchment in south-east Australia. Our plot locations controlled for three systematically varying drainage position levels (topographic wetness index: 5.0, 6.5 and 8.0) and two levels of energy input (aridity index: 1.2 and 1.8). Vegetation patterns were generally stronger related to drainage position than slope orientation, whereas sap velocity variations were less pronounced. However, in combination with stand sapwood area, consistent spatio-temporal transpiration patterns emerged in relation to landscape position, where slope orientation was the primary and drainage position the secondary controlling factor. On short temporal scales, radiation and vapor pressure deficit were most important in regulating transpiration rates, whereas soil water limitation only occurred on shallow soils during summer. The importance of stand structural parameters increased on longer time scales, indicating optimization of vegetation in response to the long-term hydro-climatic conditions at a given landscape position. Thus, vegetation patterns can be conceptualized as a 'time-integrated' predictor variable that captures large fractions of other factors contributing to transpiration patterns.