Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy-scale photosynthesis.

The proliferation of digital cameras co-located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra-annual and interannual variability in canopy photosynthesis. We used 59 site-years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needleleaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.

Measuring Rapid A-Ci Curves in Boreal Conifers: Black Spruce and Balsam Fir.

Climate change is steering tree breeding programs towards the development of families and genotypes that will be adapted and more resilient to changing environments. Making genotype-phenotype-environment connections is central to these predictions and it requires the evaluation of functional traits such as photosynthetic rates that can be linked to environmental variables. However, the ability to rapidly measure photosynthetic parameters has always been limiting. The estimation of V c,max and J max using CO2 response curves has traditionally been time consuming, taking anywhere from 30 min to more than an hour, thereby drastically limiting the number of trees that can be assessed per day. Technological advancements have led to the development of a new generation of portable photosynthesis measurement systems offering greater chamber environmental control and automated sampling and, as a result, the proposal of a new, faster, method (RACiR) for measuring V c,max and J max . This method was developed using poplar trees and involves measuring photosynthetic responses to CO2 over a range of CO2 concentrations changing at a constant rate. The goal of the present study was to adapt the RACiR method for use on conifers whose measurement usually requires much larger leaf chambers. We demonstrate that the RACiR method can be used to estimate V c,max and J max in conifers and provide recommendations to enhance the method. The use our method in conifers will substantially reduce measurement time, thus greatly improving genotype evaluation and selection capabilities based on photosynthetic traits. This study led to the developpement of an R package (RapidACi, https://github.com/ManuelLamothe/RapidACi) that facilitates the correction of multiple RACiR files and the post-measurement correction of leaf areas.

Decreasing photosynthesis at different spatial scales during the late growing season on a boreal cutover.

The relationship between photosynthesis and accumulated cold degree days (CDD) over the late growing season was examined at the shoot, ecosystem and landscape scales in a boreal cutover in eastern Canada predominated by black spruce (Picea mariana Mill. BSP), lowbush blueberry (Vaccinium angustifolium Ait.) and sheep laurel (Kalmia angustifolia L.). We calculated CDD as the sum of minimum daily temperatures below a 5 degrees C threshold. Light-saturated photosynthesis at the shoot level (A(max)) of black spruce and V. angustifolium decreased steadily with increasing CDD once temperatures below the CDD threshold value became frequent in mid-September, whereas K. angustifolia showed a more irregular pattern. Tissue acclimation played an important role in the decrease in A(max) as the season progressed, but only V. angustifolium showed decreasing foliar nitrogen concentrations. Based on eddy covariance flux tower data, maximum daily gross primary productivity (GPP(max)-tower) at the ecosystem level was more strongly related to CDD (r(2) = 0.59) than was maximum daily net ecosystem exchange (r(2) = 0.32). The GPP(max) was likely influenced by both tissue acclimation and the direct effects of changing temperatures and irradiances on physiological rates. Mean daily GPP, calculated for consecutive 8-day periods for a 25 km(2) area around the tower by the MODIS MOD17A2 Collection 4 satellite algorithm (GPP- MODIS), decreased more rapidly with increasing CDD than did GPP(max)-tower. Although GPP-MODIS was closely correlated with mean daily GPP from the tower (GPP(daily)-tower, r(2) = 0.95) over the late growing season, the former was about twice as high. Although MODIS estimates of air temperature closely tracked the ground data, the maximum light-use efficiency parameter used by the MODIS algorithm was much higher than that indicated by the tower measurements. There was a 3% decline in GPP(max)-tower with an increase of 10 CDD, corresponding to the percent decline in branch-level A(max) of black spruce and V. angustifolium.