Leaf chlorophyll is central to the exchange of carbon, water and energy between the biosphere and the atmosphere, and to the functioning of terrestrial ecosystems. This paper presents the first spatially continuous view of terrestrial leaf chlorophyll content (ChlLeaf) across a global scale. Weekly maps of ChlLeaf were produced from ENIVSAT MERIS full resolution (300 m) satellite data with a two-stage physically-based radiative transfer modelling approach. Firstly, leaf-level reflectance was derived from top-of-canopy satellite reflectance observations using 4-Scale and SAIL canopy radiative transfer models 3 for woody and non-woody vegetation, respectively. Secondly, the modelled leaf-level reflectance was used in the PROSPECT leaf-level radiative transfer model to derive ChlLeaf. The ChlLeaf retrieval algorithm was validated with measured ChlLeaf data from sample measurements at field locations, and covering six plant functional types (PFTs). Modelled results show strong relationships with field measurements, particularly for deciduous broadleaf forests (R 2 = 0.67; RMSE = 9.25 µg cm -2 ; p<0.001), croplands (R 2 = 0.41; RMSE = 13.18 µg cm -2 ; p<0.001) and evergreen needleleaf forests (R 2 = 0.47; RMSE = 10.63 µg cm -2 ; p<0.001). When the modelled results from all PFTs were considered together, the overall relationship with measured ChlLeaf remained good (R 2 = 0.47, RMSE = 10.79 µg cm -2 ; p<0.001).This result was an improvement on the relationship between measured ChlLeaf and a commonly used chlorophyll-sensitive spectral vegetation index; the MERIS Terrestrial Chlorophyll Index (MTCI; R 2 = 0.27, p<0.001). The global maps show large temporal and spatial variability in ChlLeaf, with evergreen broadleaf forests presenting the highest leaf chlorophyll values with global annual median of 54.4 µg cm -2 . Distinct seasonal ChlLeaf phenologies are also visible, particularly in deciduous plant forms, associated with budburst and crop growth, and leaf senescence. It is anticipated that this global ChlLeaf product will make an important step towards the explicit consideration of leaf-level biochemistry in terrestrial water, energy and carbon cycle modelling.
Correlation and causal relationships among 21 horticultural traits were determined using 71 walnut genotypes selected from seven valleys in Kerman Province, Iran. Pearson's correlation coefficient was calculated. Kernel percentage and blight susceptibility were used as dependent variables in a stepwise regression model to determine predictor variables. Direct and indirect effects of each independent variable were calculated using path analysis. A highly significant correlation was observed between lateral bearing habit and yield. Lateral-bearing trees were also more susceptible to blight and winter cold than terminal bearers. Kernel and nut weights, shell thickness, and difficulty of extracting kernel halves were the most important traits accounting for kernel variation. Kernel weight and difficulty extracting kernel halves had the strongest positive direct effects and nut weight the most negative. Flowering habit, nut shape, and leafing date had positive direct effects on blight susceptibility, but the large residual effects suggest there are other important determinant traits for blight susceptibility, which were not considered in this study.
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