Is a short, sharp shock equivalent to long-term punishment? Contrasting the spatial pattern of acute and chronic ozone damage to soybean leaves via chlorophyll fluorescence imaging.

Experimental investigations of ozone (O(3)) effects on plants have commonly used short, acute [O(3)] exposure (>100 ppb, on the order of hours), while in field crops damage is more likely caused by chronic exposure (<100 ppb, on the order of weeks). How different are the O(3) effects induced by these two fumigation regimes? The leaf-level photosynthetic response of soybean to acute [O(3)] (400 ppb, 6 h) and chronic [O(3)] (90 ppb, 8 h d(-1), 28 d) was contrasted via simultaneous in vivo measurements of chlorophyll a fluorescence imaging (CFI) and gas exchange. Both exposure regimes lowered leaf photosynthetic CO(2) uptake about 40% and photosystem II (PSII) efficiency (F(q)'/F(m)') by 20% compared with controls, but this decrease was far more spatially heterogeneous in the acute treatment. Decline in F(q)'/F(m)' in the acute treatment resulted equally from decreases in the maximum efficiency of PSII (F(v)'/F(m)') and the proportion of open PSII centres (F(q)'/F(v)'), but in the chronic treatment decline in F(q)'/F(m)' resulted only from decrease in F(q)'/F(v)'. Findings suggest that acute and chronic [O(3)] exposures do not induce identical mechanisms of O(3) damage within the leaf, and using one fumigation method alone is not sufficient for understanding the full range of mechanisms of O(3) damage to photosynthetic production in the field.

Comparison of photosynthetic damage from arthropod herbivory and pathogen infection in understory hardwood saplings.

Arthropods and pathogens damage leaves in natural ecosystems and may reduce photosynthesis at some distance away from directly injured tissue. We quantified the indirect effects of naturally occurring biotic damage on leaf-level photosystem II operating efficiency (Phi(PSII)) of 11 understory hardwood tree species using chlorophyll fluorescence and thermal imaging. Maps of fluorescence parameters and leaf temperature were stacked for each leaf and analyzed using a multivariate method adapted from the field of quantitative remote sensing. Two tree species, Quercus velutina and Cercis canadensis, grew in plots exposed to ambient and elevated atmospheric CO(2) and were infected with Phyllosticta fungus, providing a limited opportunity to examine the potential interaction of this element of global change and biotic damage on photosynthesis. Areas surrounding damage had depressed Phi(PSII )and increased down-regulation of PSII, and there was no evidence of compensation in the remaining tissue. The depression of Phi(PSII) caused by fungal infections and galls extended >2.5 times further from the visible damage and was approximately 40% more depressed than chewing damage. Areas of depressed Phi(PSII) around fungal infections on oaks growing in elevated CO(2) were more than 5 times larger than those grown in ambient conditions, suggesting that this element of global change may influence the indirect effects of biotic damage on photosynthesis. For a single Q. velutina sapling, the area of reduced Phi(PSII) was equal to the total area directly damaged by insects and fungi. Thus, estimates based only on the direct effect of biotic agents may greatly underestimate their actual impact on photosynthesis.

A method for quantitative analysis of spatially variable physiological processes across leaf surfaces.

Many physiological processes are spatially variable across leaf surfaces. While maps of photosynthesis, stomatal conductance, gene expression, water transport, and the production of reactive oxygen species (ROS) for individual leaves are readily obtained, analytical methods for quantifying spatial heterogeneity and combining information gathered from the same leaf but with different instruments are not widely used. We present a novel application of tools from the field of geographical imaging to the multivariate analysis of physiological images. Procedures for registration and resampling, cluster analysis, and classification provide a general framework for the analysis of spatially resolved physiological data. Two experiments were conducted to illustrate the utility of this approach. Quantitative analysis of images of chlorophyll fluorescence and the production of ROS following simultaneous exposure of soybean leaves to atmospheric O3 and soybean mosaic virus revealed that areas of the leaf where the operating quantum efficiency of PSII was depressed also experienced an accumulation of ROS. This correlation suggests a causal relationship between oxidative stress and inhibition of photosynthesis. Overlaying maps of leaf surface temperature and chlorophyll fluorescence following a photoinhibition treatment indicated that areas with low operating quantum efficiency of PSII also experienced reduced stomatal conductance (high temperature). While each of these experiments explored the covariance of two processes by overlaying independent images gathered with different instruments, the same procedures can be used to analyze the covariance of information from multiple images. The application of tools from geographic image analysis to physiological processes occurring over small spatial scales will help reveal the mechanisms generating spatial variation across leaves.