Structural diversity promotes productivity of mixed, uneven-aged forests in southwestern Germany.

Forest diversity-productivity relationships have been intensively investigated in recent decades. However, few studies have considered the interplay between species and structural diversity in driving productivity. We analyzed these factors using data from 52 permanent plots in southwestern Germany with more than 53,000 repeated tree measurements. We used basal area increment as a proxy for productivity and hypothesized that: (1) structural diversity would increase tree and stand productivity, (2) diversity-productivity relationships would be weaker for species diversity than for structural diversity, and (3) species diversity would also indirectly impact stand productivity via changes in size structure. We measured diversity using distance-independent indices. We fitted separate linear mixed-effects models for fir, spruce and beech at the tree level, whereas at the stand level we pooled all available data. We tested our third hypothesis using structural equation modeling. Structural and species diversity acted as direct and independent drivers of stand productivity, with structural diversity being a slightly better predictor. Structural diversity, but not species diversity, had a significant, albeit asymmetric, effect on tree productivity. The functioning of structurally diverse, mixed forests is influenced by both structural and species diversity. These sources of trait diversity contribute to increased vertical stratification and crown plasticity, which in turn diminish competitive interferences and lead to more densely packed canopies per unit area. Our research highlights the positive effects of species diversity and structural diversity on forest productivity and ecosystem dynamics.

Survival of Norway spruce remains higher in mixed stands under a dryer and warmer climate.

Shifts in tree species distributions caused by climatic change are expected to cause severe losses in the economic value of European forestland. However, this projection disregards potential adaptation options such as tree species conversion, shorter production periods, or establishment of mixed species forests. The effect of tree species mixture has, as yet, not been quantitatively investigated for its potential to mitigate future increases in production risks. For the first time, we use survival time analysis to assess the effects of climate, species mixture and soil condition on survival probabilities for Norway spruce and European beech. Accelerated Failure Time (AFT) models based on an extensive dataset of almost 65,000 trees from the European Forest Damage Survey (FDS)--part of the European-wide Level I monitoring network--predicted a 24% decrease in survival probability for Norway spruce in pure stands at age 120 when unfavorable changes in climate conditions were assumed. Increasing species admixture greatly reduced the negative effects of unfavorable climate conditions, resulting in a decline in survival probabilities of only 7%. We conclude that future studies of forest management under climate change as well as forest policy measures need to take this, as yet unconsidered, strongly advantageous effect of tree species mixture into account.

GIS-based estimation of the winter storm damage probability in forests: a case study from Baden-Wuerttemberg (Southwest Germany).

Data on storm damage attributed to the two high-impact winter storms 'Wiebke' (28 February 1990) and 'Lothar' (26 December 1999) were used for GIS-based estimation and mapping (in a 50 × 50 m resolution grid) of the winter storm damage probability (P(DAM)) for the forests of the German federal state of Baden-Wuerttemberg (Southwest Germany). The P(DAM)-calculation was based on weights of evidence (WofE) methodology. A combination of information on forest type, geology, soil type, soil moisture regime, and topographic exposure, as well as maximum gust wind speed field was used to compute P(DAM) across the entire study area. Given the condition that maximum gust wind speed during the two storm events exceeded 35 m s(-1), the highest P(DAM) values computed were primarily where coniferous forest grows in severely exposed areas on temporarily moist soils on bunter sandstone formations. Such areas are found mainly in the mountainous ranges of the northern Black Forest, the eastern Forest of Odes, in the Virngrund area, and in the southwestern Alpine Foothills.

Modelling the wind damage probability in forests in Southwestern Germany for the 1999 winter storm 'Lothar'.

The wind damage probability (P (DAM)) in the forests in the federal state of Baden-Wuerttemberg (Southwestern Germany) was calculated using weights of evidence (WofE) methodology and a logistic regression model (LRM) after the winter storm 'Lothar' in December 1999. A geographic information system (GIS) was used for the area-wide spatial prediction and mapping of P (DAM). The combination of the six evidential themes forest type, soil type, geology, soil moisture, soil acidification, and the 'Lothar' maximum gust field predicted wind damage best and was used to map P (DAM) in a 50 x 50 m resolution grid. GIS software was utilised to produce probability maps, which allowed the identification of areas of low, moderate, and high P (DAM) across the study area. The highest P (DAM) values were calculated for coniferous forest growing on acidic, fresh to moist soils on bunter sandstone formations-provided that 'Lothar' maximum gust speed exceeded 35 m s(-1) in the areas in question. One of the most significant benefits associated with the results of this study is that, for the first time, there is a GIS-based area-wide quantification of P (DAM) in the forests in Southwestern Germany. In combination with the experience and expert knowledge of local foresters, the probability maps produced can be used as an important tool for decision support with respect to future silvicultural activities aimed at reducing wind damage. One limitation of the P (DAM)-predictions is that they are based on only one major storm event. At the moment it is not possible to relate storm event intensity to the amount of wind damage in forests due to the lack of comprehensive long-term tree and stand damage data across the study area.

Comment on "Critical wind speed at which trees break".

Virot et al. [E. Virot et al., Phys. Rev. E 93, 023001 (2016)10.1103/PhysRevE.93.023001] assert that the critical wind speed at which ⩾50% of all trees in a population break is ≈42 m/s, regardless of tree characteristics. We show that empirical data do not support this assertion, and that the assumptions underlying the theory used by Virot et al. are inconsistent with the biomechanics of trees.