Drought-induced decline in Mediterranean truffle harvest

gridded maps of biomass to be produced over time6. Radar backscatter is sensitive to vegetation fresh biomass7. At long wavelengths (0.7 m or longer), radar penetrates deep into the canopy and the backscatter energy depends on a combination of variables including the size, number density, and the water content and wood specific gravity of branches and stems. However, radar backscatter suffers from gradual loss of sensitivity as biomass increases. The phenomenon referred to as ‘saturation’ occurs often in radar backscatter at shorter wavelengths, but is not unique to radar and forests, and can occur in all types of remote-sensing measurements, even for non-woody vegetation. However, at longer wavelengths (>0.7 m), radar backscatter remains sensitive to a wide range of AGB. Variation in tree density may impact radar backscatter, but does not cause loss of sensitivity. In spatially heterogeneous forests, the largest source of error in deriving the relationship between radar backscatter and biomass is from the geometry of measurement and the difference between the biomass sensed by radar and that sampled on the ground. The ground data are too often based on small inventory plots, leading to large errors that are often ignored. By increasing the plot size used for remote-sensing calibration, the relationship improves significantly5. Woodhouse et al.1 criticize the use of regression models that convert the backscatter into AGB, which are derived using collections of sites spanning a range of forest types. Mixing data across forest types to sample a wider range of AGB is a common statistical approach used not only in most remote-sensing studies but also repeatedly in field estimation, where inventory data from a limited number of trees is used to predict AGB values over the full range of trees from different regions. Regardless of the type of models used, prediction never implies accuracy. A systematic radar observation at long wavelengths from space, as recommended by European Space Agency’s BIOMASS mission, accompanied by remote-sensingspecific field inventory data provides the only way to circumvent the limitations of field inventory-only biomass monitoring at the global scale. Extending current studies beyond the landscape scale is a priority if radar remote sensing is to fulfil its potential in the context of the Reducing Emissions from Deforestation and Forest Degradation programme (www.un-redd.org). ❐