C. van der Tol

Optimum vegetation characteristics, assimilation, and transpiration during a dry season: 2. Model evaluation

Received 8 June 2007; revised 3 December 2007; accepted 12 December 2007; published 21 March 2008. [1] In a companion paper, a conceptual model was presented to predict two important vegetation parameters from climatic constraints in water limited conditions, notably photosynthetic capacity and internal carbon dioxide concentration. In this study, the model is evaluated using data of four experimental forest plots in sub-Mediterranean Slovenia which were selected for their topography induced differences in climate and contrasting vegetation characteristics. Data were collected during a regular (2004) and an exceptionally dry year (2003). Measurements showed that photosynthetic capacity decreases with vapor pressure deficit, and internal carbon dioxide concentration correlates positively with available water. Variations in soil water storage at the start of the dry season and vapor pressure deficit during the dry season are responsible for a large part of these differences. Winter precipitation has a large effect on the shape of the seasonal course of transpiration during the following season. The model explained observed differences among sites and years in photosynthetic capacity and the seasonal cycle of transpiration. Although the magnitude of calculated optimum internal carbon dioxide concentrations agreed with observations, the model could not explain observed differences in internal carbon dioxide concentration or the correlation between internal carbon dioxide concentration and water availability. The optimality hypothesis, despite its limitations, can be used to predict the seasonal cycle of transpiration.

Contact and directional radiative temperature measurements of sunlit and shaded land surface components during the SEN2FLEX 2005 campaign

Evapotranspiration models require thermodynamic temperatures as a state variable characterizing the surface energy balance. The thermodynamic temperature is calculated using the brightness temperature and the emissivity because no effective method exists to measure thermodynamic temperatures in space and time. A method was therefore developed to measure thermodynamic temperatures in time using contact probes and spatial variations of the thermodynamic temperature using a thermal camera. Using an extraction scheme, the brightness temperatures of canopy and soil were extracted from the thermal images and compared with the contact temperatures. The contact temperatures had similar amplitudes and time‐variability as the brightness temperatures for both components. The slope and offset parameters of a scatter plot were calculated. The slope of the scatter plot was lower than unity for canopy, and higher than unity for soil. Because of the spread in the scatter plot, the emissivities of the components could not be calculated. We conclude that kinematic temperature measurements by contact probes can be a valuable extension to current techniques for measuring continuous component temperatures. The extraction scheme could be a useful tool for extracting the component brightness temperatures for low‐resolution imagery.

Remote sensing of plant-water relations: An overview and future perspectives

Vegetation is a highly dynamic component of the Earth surface and substantially alters the water cycle. Particularly the process of oxygenic plant photosynthesis determines vegetation connecting the water and carbon cycle and causing various interactions and feedbacks across Earth spheres. While vegetation impacts the water cycle, it reacts to changing water availability via functional, biochemical and structural responses. Unravelling the resulting complex feedbacks and interactions between the plant-water system and environmental change is essential for any modelling approaches and predictions, but still insufficiently understood due to currently missing observations. We hypothesize that an appropriate cross-scale monitoring of plant-water relations can be achieved by combined observational and modelling approaches. This paper reviews suitable remote sensing approaches to assess plant-water relations ranging from pure observational to combined observational-modelling approaches. We use a combined energy balance and radiative transfer model to assess the explanatory power of pure observational approaches focussing on plant parameters to estimate plant-water relations, followed by an outline for a more effective use of remote sensing by their integration into soil-plant-atmosphere continuum (SPAC) models. We apply a mechanistic model simulating water movement in the SPAC to reveal insight into the complexity of relations between soil, plant and atmospheric parameters, and thus plant-water relations. We conclude that future research should focus on strategies combining observations and mechanistic modelling to advance our knowledge on the interplay between the plant-water system and environmental change, e.g. through plant transpiration.