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The current study tested the assumption that floristic and functional diversity patterns are negatively related to soil nitrogen content. We analyzed 20 plots with soil N-contents ranging from 0.63% to 1.06% in a deciduous forest near Munich (Germany). To describe species adaptation strategies to different nitrogen availabilities, we used a plant functional type (PFT) approach. Each identified PFT represents one realized adaptation strategy to the current environment. These were correlated, next to plant species richness and evenness, to soil nitrogen contents. We found that N-efficient species were typical for low soil nitrogen contents, while N-requiring species occur at high N-contents. In contrast to our initial hypotheses, floristic and functional diversity measures (number of PFTs) were positively related to nitrogen content in the soil. Every functional group has its own adaptation to the prevailing environmental conditions; in consequence, these functional groups can co-exist but do not out-compete one another. The increased number of functional groups at high N-contents leads to increased species richness. Hence, for explaining diversity patterns we need to consider species groups representing different adaptations to the current environmental conditions. Such co-existing ecological strategies may even overcome the importance of competition in their effect on biodiversity.
The estimation model PhytoCalc allows a non-destructive quantification of dry weight and nutrient pools of understorey plants in forests by using the relationship between species biomass, cover and mean shoot length. The model has been validated with independent samples in several German forest types and can be a useful tool in forest monitoring. However, in open areas within forests (e.g. clearcuts), the current model version underestimates biomass and produces unreliable nutrient pool estimations. Thus, tissue density, as approximated by leaf dry matter content (LDMC), is systematically higher under high light compared to low light conditions. We demonstrate that the ratio of LDMC under clearcut conditions to LDMC under forest conditions can be used to adjust the PhytoCalc model to clearcut conditions. We investigated the LDMC ratio of five exemplary species commonly occurring on clearcuts. Integrating the square of the ratio as a correction factor improved estimates of biomass to more than 70% fit between observations and predictions. Results also suggest this ratio can be used to correct nutrient concentrations modelled in PhytoCalc, which tend to be overestimated in clearcuts. As morphological groups of plant species exhibit significantly different ratios, we advise using group-specific correction factors for clearcut adjustments in the future.