Reflexionen eines Zoologen zum „Tollwut”-Problem

Ohne ZusammenfassungHerrn Professor Dr. Max Wolff (Naumburg/Saale), emeritierten Ordinarius für Forstzoologie und Forstparasitologie der damaligen Forsthochschule Eberswalde, in Verehrung nachträglich zum 80. Geburtstag (6. IX. 1959) gewidmet.     

Does canopy mean nitrogen concentration explain variation in canopy light use efficiency across 14 contrasting forest sites?

The maximum light use efficiency (LUE?=?gross primary production (GPP)/absorbed photosynthetic photon flux density (aPPFD)) of plant canopies has been reported to vary spatially and some of this variation has previously been attributed to plant species differences. The canopy nitrogen concentration [N] can potentially explain some of this spatial variation. However, the current paradigm of the N-effect on photosynthesis is largely based on the relationship between photosynthetic capacity (A(max)) and [N], i.e., the effects of [N] on photosynthesis rates appear under high PPFD. A maximum LUE-[N] relationship, if it existed, would influence photosynthesis in the whole range of PPFD. We estimated maximum LUE for 14 eddy-covariance forest sites, examined its [N] dependency and investigated how the [N]-maximum LUE dependency could be incorporated into a GPP model. In the model, maximum LUE corresponds to LUE under optimal environmental conditions before light saturation takes place (the slope of GPP vs. PPFD under low PPFD). Maximum LUE was higher in deciduous/mixed than in coniferous sites, and correlated significantly with canopy mean [N]. Correlations between maximum LUE and canopy [N] existed regardless of daily PPFD, although we expected the correlation to disappear under low PPFD when LUE was also highest. Despite these correlations, including [N] in the model of GPP only marginally decreased the root mean squared error. Our results suggest that maximum LUE correlates linearly with canopy [N], but that a larger body of data is required before we can include this relationship into a GPP model. Gross primary production will therefore positively correlate with [N] already at low PPFD, and not only at high PPFD as is suggested by the prevailing paradigm of leaf-level A(max)-[N] relationships. This finding has consequences for modelling GPP driven by temporal changes or spatial variation in canopy [N].     

Concept and feasibility study for the integrated evaluation of environmental monitoring data in forests

In the 1970s unexpected forest damages, called “new type of forest damage” or “forest decline”, were observed in Germany and other European countries. The Federal Republic of Germany and the German Federal States implemented a forest monitoring system in the early 1980s, in order to monitor and assess the forest condition. Due to the growing public awareness of possible adverse effects of air pollution on forests, in 1985 the ICP Forests was launched under the convention on long-range transboundary air pollution (CLRTAP) of the United Nations Economic Commission for Europe (UN-ECE). The German experience in forest monitoring was a base for the implementation of the European monitoring system. In 2001 the interdisciplinary case study “concept and feasibility study for the integrated evaluation of environmental monitoring data in forests”, funded by the German Federal Ministry of Education and Research, concentrated on in-depths evaluations of the German data of forest monitoring. The objectives of the study were: (a) a reliable assessment of the vitality and functioning of forest ecosystems, (b) the identification and quantification of factors influencing forest vitality, and (c) the clarification of cause-effect-relationships leading to leaf/needle loss. For these purposes additional data from external sources were acquired: climate and deposition, for selected level I plots tree growth data, as well as data on groundwater quality. The results show that in particular time series analysis (crown condition, tree growth, and tree ring analysis), in combination with climate and deposition are valuable and informative, as well as integrated evaluation of soil, tree nutrition and crown condition data. Methods to combine information from the extensive and the intensive monitoring, and to transfer process information to the large scale should be elaborated in future.

Species proportions by area in mixtures of Scots pine (<Emphasis Type="Italic">Pinus sylvestris</Emphasis> L.) and European beech (<Emphasis Type="Italic">Fagus sylvatica</Emphasis> L.)

Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) dominate many of the European forest stands. Also, mixtures of European beech and Scots pine more or less occur over all European countries, but have been scarcely investigated. The area occupied by each species is of high relevance, especially for growth evaluation and comparison of different species in mixed and monospecific stands. Thus, we studied different methods to describe species proportions and their definition as proportion by area. 25 triplets consisting of mixed and monospecific stands were established across Europe ranging from Lithuania to Spain in northern to southern direction and from Bulgaria to Belgium in eastern to western direction. On stand level, the conclusive method for estimating the species proportion as a fraction of the stand area relates the observed density (tree number or basal area) to its potential. This stand-level estimation makes use of the potential from comparable neighboring monospecific stands or from maximum density lines derived from other data, e.g. forest inventories or permanent observations plots. At tree level, the fraction of the stand area occupied by a species can be derived from the proportions of their crown projection area or of their leaf area. The estimates of the potentials obtained from neighboring monospecific stands, especially in older stands, were poorer than those from the maximum density line depending on the Martonne aridity index. Therefore, the stand-level method in combination with the Martonne aridity index for potential densities can be highly recommended. The species’ proportions estimated with this method are best approximated by the proportions of the species’ leaf areas. In forest practice, the most commonly applied method is an ocular estimation of the proportions by crown projection area. Even though the proportions of pine were calculated here by measuring crown projection areas in the field, we found this method to underestimate the proportion by 25% compared to the stand-level approach.     

Static site indices from different national forest inventories: harmonization and prediction from site conditions

Key message

Static site indices determined from stands’ top height are derived from different forest inventory sources with height and age information and thus enable comparisons and modeling of a species’ productivity encompassing large environmental gradients.

Context

Estimating forest site productivity under changing climate requires models that cover a wide range of site conditions. To exploit different inventory sources, we need harmonized measures and procedures for the productive potential. Static site indices (SI) appear to be a good choice.

Aims

We propose a method to derive static site indices for different inventory designs and apply it to six tree species of the German and French National Forest Inventory (NFI). For Norway spruce and European beech, the climate dependency of SI is modeled in order to estimate trends in productivity due to climate change.

Methods

Height and age measures are determined from the top diameters of a species at a given site. The SI is determined for a reference age of 100 years.

Results

The top height proves as a stable height measure that can be derived harmoniously from German and French NFI. The boundaries of the age-height frame are well described by the Chapman-Richards function. For spruce and beech, generalized additive models of the SI against simple climate variables lead to stable and plausible model behavior.

Conclusion

The introduced methodology permits a harmonized quantification of forest site productivity by static site indices. Predicting productivity in dependence on climate illustrates the benefits of combined datasets.