Natalia Forest 2.mov

Plant species aboveground allometry can be viewed as a functional trait that reflects the evolutionary trade-off between above- and belowground resources. In forest trees, allometry is related to productivity and resilience in different environments, and it is tightly connected with a compromise between efficiency-safety and competitive ability. A better understanding on how this trait varies within and across species is critical to determine the potential of a species/population to perform along environmental gradients. We followed a hierarchical framework to assess tree height-diameter allometry variation within and across four common European Pinus species. Tree height-diameter allometry variation was a function of solely genetic components -approximated by either population effects or clinal geographic responses of the population's site of origin- and differential genetic plastic responses -approximated by the interaction between populations and two climatic variables of the growing sites (temperature and precipitation)-. Our results suggest that, at the species level, climate of the growing sites set the tree height-diameter allometry of xeric and mesic species (Pinus halepensis, P. pinaster and P. nigra) apart from the boreal species (P. sylvestris), suggesting a weak signal of their phylogenies in the tree height-diameter allometry variation. Moreover, accounting for interpopulation variability within species for the four pine species aided to: (1) detect genetic differences among populations in allometry variation, which in P. nigra and P. pinaster were linked to gene pools -genetic diversity measurements-; (2) reveal the presence of differential genetic variation in plastic responses along two climatic gradients in tree allometry variation. In P. sylvestris and P. nigra, genetic variation was the result of adaptive patterns to climate, while in P. pinaster and P. halepensis, this signal was either weaker or absent, respectively; and (3) detect local adaptation in the exponent of the tree height-diameter allometry relationship in two of the four species (P. sylvestris and P. nigra), as it was a function of populations' latitude and altitude variables. Our findings suggest that the four species have been subjected to different historical and climatic constraints that might have driven their aboveground allometry and promoted different life strategies.

natalia forest 2.mov

ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.

N2 - ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression.

AB - ESA Forest Carbon Monitoring project (FCM) is developing Earth Observation based, user-centric approaches for forest carbon monitoring. Forest carbon accounting based on forest inventory requires precise and timely estimation of forest variables at various spatial levels accompanied by verifiable uncertainty information. In this paper, we present the algorithm trade-off and selection approach and preliminary results of the algorithm intercomparison exercise in the FCM project. The studies were performed over 7 European test sites located in Finland, Ireland, Romania, Spain and Switzerland, and one tropical forest site in Peru. EO datasets were represented by Sentinel-1, Sentinel-2, TanDEM-X and ALOS-2 PALSAR-2 imagery. Examined approaches include popular parametric and SAR/InSAR scattering physics based approaches, and nonparametric and machine learning approaches such as k-NN, random forests, support vector regression. 041b061a72