School of Agriculture, Food and Ecosystem Sciences - Research Publications
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ItemTrading Water for Carbon: Maintaining Photosynthesis at the Cost of Increased Water Loss During High Temperatures in a Temperate Forest(American Geophysical Union, 2020-01-01)Carbon and water fluxes are often assumed to be coupled as a result of stomatal regulation during dry conditions. However, recent observations evidenced increased transpiration rates during isolated heatwaves across a range of eucalypt species under experimental and natural conditions, with inconsistent effects on photosynthesis (ranging from increases to stark declines). To improve the empirical basis for understanding carbon and water fluxes in forests under hotter and drier climates, we measured the water use of dominant trees and ecosystem‐scale carbon and water exchange in a temperate eucalypt forest over three summer seasons. The forest maintained photosynthesis within 16% of baseline rates during hot and dry conditions, despite ~70% reductions in canopy conductance during a 5‐day heatwave. While carbon and water fluxes both decreased by 16% on exceptionally dry days, gross primary productivity only decreased by 5% during the hottest days and increased by 2% during the heatwave. However, evapotranspiration increased by 43% (hottest days) and 74% (heatwave), leading to ~40% variation in traditional water use efficiency (water use efficiency = gross primary productivity/evapotranspiration) across conditions and approximately two‐fold differences between traditional and underlying or intrinsic water use efficiency on the same days. Furthermore, the forest became a net source of carbon following a 137% increase in ecosystem respiration during the heatwave, highlighting that the potential for temperate eucalypt forests to act as net carbon sinks under hotter and drier climates will depend not only on the responses of photosynthesis to higher temperatures and changes in water availability, but also on the concomitant responses of ecosystem respiration.
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ItemReliability and limitations of a novel terrestrial laser scanner for daily monitoring of forest canopy dynamics(ELSEVIER SCIENCE INC, 2015-09-01)Leaf area index (LAI) or plant area index (PAI) are commonly used to represent canopy structure and dynamics, but daily estimation of these variables using traditional ground-based methods is impractical and prone to multiple errors during data acquisition and processing. Existing terrestrial laser scanners can provide accurate representation of forest canopy structure, but the sensors are expensive, data processing is complex, and measurements are typically confined to a single event, which severely limits their utility in the interpretation of canopy trends indicated by remotely sensed data. We tested a novel, low-cost terrestrial laser scanner for its capacity to provide reliable and successive assessments of canopy PAI in an evergreen eucalypt forest. Daily scans comprised of 920 range measurements were made by three scanners at one forest site over a two-year period, providing mostly consecutive estimates of PAI, and of vertical structure profiles (as Plant Area Volume Density, PAVD). Data filtering, involving objective statistical methods to identify outliers, indicated that scan quality was adversely affected by moist weather and moderate wind speeds (>4ms−1), suggesting limited utility in some forest environments. Data cleaning (associated with sensor malfunctions) plus filtering removed 32 to 49% of scans, leaving on average 57% of data over the two-year period. Nonetheless, we found strong agreement between lidar-derived PAI estimates, and those from monthly hemispherical images (±0.1 PAI); with both methods indicating mostly stable PAI over multiple seasons. The PAVD profiles from the laser scanner indicated that leaf flush in the upper canopy concomitantly balanced leaf loss from the middle canopy in summer, which was consistent with measured summer peaks in litter fall. This clearly illustrated the advantages of three-dimensional lidar data over traditional two-dimensional PAI estimates in monitoring tree phenology, and in interpreting changes in canopy reflectance as detected by air- and space-borne remotely sensed data.