Scaling of fast-start performance and its thermal dependence in mummichog Fundulus heteroclitus.

Fast-start predator-escape performance and its sensitivity to temperature (24, 30, and 36°C) were evaluated in mummichog Fundulus heteroclitus across a range of body sizes spanning YOY to adult (35-68 mm standard length). Mummichogs exhibit isometry of body dimensions and areas of the dorsal and anal fins but negative allometry of the caudal fin area. These scaling relationships are consistent with observed decreases in fast-start angular velocities with increasing body size. Linear velocity, on the contrary, does not vary with size, and both large and small mummichogs are capable of traversing similar distances in a given amount of time. In addition, temperature influences fast-start performance in similar ways over the size range, though the magnitude of the effect varies with size for some performance measures. In general, fast-start performance increases with test temperature, but mummichogs acclimated to warmer temperatures exhibit lower performance at each test temperature. Altogether, our results suggest that mummichogs across the adult size range may suffer decreases in their predator-escape performance as increasing sea temperatures combine with short-term temperature fluctuations in the estuaries these fish occupy.

Fast-start escape performance across temperature and salinity gradients in mummichog Fundulus heteroclitus.

Fast-start predator-escape performance of mummichogs Fundulus heteroclitus was tested across field-informed variation in temperature (24, 30 and 36°C) and salinity (2, 12 and 32 ppt). Performance was similar across temperatures and salinities when fish were allowed to acclimate to these conditions. However, when mummichogs experienced acute temperature changes, performance exhibited thermal dependence in two contrasting ways. Fast-start turning rates and linear speeds varied directly with the temperature at which the manoeuvre was executed, but these aspects of performance varied inversely with acclimation temperature, with cool-acclimated fish exhibiting faster starts across test temperatures. Temperature effects were consistent across salinities. These results suggest that while mummichogs increase performance with acute temperature increases, long-term rises in sea temperature may cause these fish to become more susceptible to predation during abrupt cooling events, such as when storm events flood shallow water estuaries with cool rainwater.

Models of reforestation productivity and carbon sequestration for land use and climate change adaptation planning in South Australia.

Environmental management and regional land use planning has become more complex in recent years as growing world population, climate change, carbon markets and government policies for sustainability have emerged. Reforestation and agroforestry options for environmental benefits, carbon sequestration, economic development and biodiversity conservation are now important considerations of land use planners. New information has been collected and regionally-calibrated models have been developed to facilitate better regional land use planning decisions and counter the limitations of currently available models of reforestation productivity and carbon sequestration. Surveys of above-ground biomass of 264 reforestation sites (132 woodlots, 132 environmental plantings) within the agricultural regions of South Australia were conducted, and combined with spatial information on climate and soils, to develop new spatial and temporal models of plant density and above-ground biomass productivity from reforestation. The models can be used to estimate productivity and total carbon sequestration (i.e. above-ground + below-ground biomass) under a continuous range of planting designs (e.g. variable proportions of trees and shrubs or plant densities), timeframes and future climate scenarios. Representative spatial models (1 ha resolution) for 3 reforestation designs (i.e. woodlots, typical environmental planting, biodiverse environmental plantings) × 3 timeframes (i.e. 25, 45, 65 years) × 4 possible climates (i.e. no change, mild, moderate, severe warming and drying) were generated (i.e. 36 scenarios) for use within land use planning tools.

Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures).