Timing leaf senescence

Subtitle:a generalized additive models for location, scale and shape approach

Accurate estimations of phenophases in deciduous trees are important to understand forest ecosystems and their feedback on the climate. In particular, the timing of leaf senescence is of fundamental importance to trees’ nutrient stoichiometry and drought tolerance and therefore to trees’ vigor and fecundity. Nevertheless, there is no integrated view on the significance, and direction, of seasonal trends in leaf senescence, especially for years characterized by extreme weather events. Difficulties in the acquisition and analyses of hierarchical data can account for this. We collected four years of chlorophyll content index (CCI) measurements in thirty-eight individuals of four deciduous tree species (Betula pendula, Fagus sylvatica, Populus tremula and Quercus robur) in Belgium, Norway and Spain, and analyzed these data using generalized additive models for location, scale and shape (GAMLSS). As a result, (I) the phenological strategy and seasonal trend of leaf senescence in these tree species could be clarified for exceptionally dry and warm years, and (II) the daily average (air) temperature, global radiation, and vapor pressure deficit could be established as main drivers behind the variation in the timing of the senescence transition date. Our results show that the onset of the re-organization phase in the leaf senescence, which we approximated and defined as local minima in the second derivative of a CCI graph, was in all species mainly negatively affected by the average temperature, global radiation and vapor pressure deficit. All together the variables explained 89 to 98% of the variability in the leaf senescence timing. An additional finding is that the generalized beta type 2 and generalized gamma distributions are well suited to model the chlorophyll content index, while the senescence transition date can be modeled using the normal-exponential-student-t, generalized gamma and zero-inflated Box-Cox Cole and Green distributions for beech, oak and birch, and poplar, respectively.

Publication year:2022

Keywords:A1 Journal article

Accessibility:Open