Benefits of hierarchical predictions for digital soil mapping—An approach to map bimodal soil pH

Maps of soil pH are an important tool for making decisions in sustainable forest management. Accurate pH mapping, therefore, is crucial to support decisions by authorities or forest companies. Soil pH values typically exhibit a distinct distribution characterized by two frequently encountered pH ranges, wherein aluminium oxides (Al2O3) and carbonates (CaCO3) act as the primary buffer agents. Soil samples with moderately acid pH values (pH CaCl2 of 4.5-6) are less commonly observed due to their weaker buffering capacity. The different strength of buffer agents results in a distinct bimodal distribution of soil pH values with peaks at pH of around 4 and 7.5. Commonly used approaches for spatial mapping neglect this often observed characteristic of soil pH and predict unimodal distributions with too many moderately acid pH values. For ecological map applications this might result in misleading interpretations. This article presents a novel approach to produce pH maps that are able to reproduce pedogenic processes. The procedure is suitable for bimodal responses where the response distribution is naturally inherent and needs to be reproduced for the predictions. It is model-agnostic, namely independent from the used statistical prediction method. Calibration data is optimally split into two parts corresponding each to a data culmination, i.e. for soil pH values belonging to the ranges of the two principal buffer agents (Al2O3 and CaCO3). For each subset a separate model is then built. In addition, a binary model is fitted to assign every new prediction location a probability to belong either to Al2O3 or CaCO3 buffer range. Predictions are combined by weighted mean. Weights are derived from probabilities predicted by the binary model. Degree of smoothness is chosen by sigmoid transform which allows for optimal continuous transition of the pH values between Al2O3 and CaCO3 buffer ranges. For each location uncertainty distributions may be combined by using the same weights. We illustrated application of the new approach to a medium and strong bimodal distributed response (1) pH in 0–5 cm and (2) pH in 60–100 cm of forest soils in Switzerland (2 530 calibration sites). While model performance measured at 354 validation sites slightly dropped compared to a common modelling approach (drop of R2 of 0.02–0.03) distributional properties of the predictions are much more meaningful from a pedogenic point of view. We were able to demonstrate the benefits of considering specific distributional properties of responses within the prediction process and expanded model assessment by comparing observed and predicted distributions

Slower growth prior to the 2018 drought and a high growth sensitivity to previous year summer conditions predisposed European beech to crown dieback.

The record-breaking drought in 2018 caused premature leaf discoloration and shedding (early browning) in many beech (Fagus sylvatica L.) dominated forests in Central Europe. However, a high degree of variability in drought response among individual beech trees was observed. While some trees were severely impacted by the prolonged water deficits and high temperatures, others remained vital with no or only minor signs of crown vitality loss. Why some beech trees were more susceptible to drought-induced crown damage than others and whether growth recovery is possible are poorly understood. Here, we aimed to identify growth characteristics associated with the variability in drought response between individual beech trees based on a sample of 470 trees in northern Switzerland. By combining tree growth measurements and crown condition assessments, we also investigated the possible link between crown dieback and growth recovery after drought. Beech trees with early browning exhibited an overall lower growth vigor before the 2018 drought than co-occurring vital beech trees. This lower vigor is mainly indicated by lower overall growth rates, stronger growth declines in the past decades, and higher growth-climate sensitivity. Particularly, warm previous year summer conditions negatively affected current growth of the early-browning trees. These findings suggest that the affected trees had less access to critical resources and were physiologically limited in their growth predisposing them to early browning. Following the 2018 drought, observed growth recovery potential corresponded to the amount of crown dieback and the local climatic water balance. Overall, our findings emphasize that beech-dominated forests in Central Europe are under increasing pressure from severe droughts, ultimately reducing the competitive ability of this species, especially on lowland sites with shallow soils and low water holding capacity

Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960-2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 +/- 0.006 Mg C ha(-1) year(-1) km(-1) for P. abies and 0.93 +/- 0.010 Mg C ha(-1) year(-1) km(-1) for F. sylvatica). During warm-dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm-dry extremes. Importantly, cold-dry extremes had negative impacts on regional forest NPP comparable to warm-dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.Peer reviewe

Climate Change Impairs Nitrogen Cycling in European Beech Forests

European beech forests growing on marginal calcareous soils have been proposed to be vulnerable to decreased soil water availability. This could result in a large-scale loss of ecological services and economical value in a changing climate. In order to evaluate the potential consequences of this drought-sensitivity, we investigated potential species range shifts for European beech forests on calcareous soil in the 21st century by statistical species range distribution modelling for present day and projected future climate conditions. We found a dramatic decline by 78% until 2080. Still the physiological or biogeochemical mechanisms underlying the drought sensitivity of European beech are largely unknown. Drought sensitivity of beech is commonly attributed to plant physiological constraints. Furthermore, it has also been proposed that reduced soil water availability could promote nitrogen (N) limitation of European beech due to impaired microbial N cycling in soil, but this hypothesis has not yet been tested. Hence we investigated the influence of simulated climate change (increased temperatures, reduced soil water availability) on soil gross microbial N turnover and plant N uptake in the beech-soil interface of a typical mountainous beech forest stocking on calcareous soil in SW Germany. For this purpose, triple 15N isotope labelling of intact beech seedling-soil-microbe systems was combined with a space-for-time climate change experiment. We found that nitrate was the dominant N source for beech natural regeneration. Reduced soil water content caused a persistent decline of ammonia oxidizing bacteria and therefore, a massive attenuation of gross nitrification rates and nitrate availability in the soil. Consequently, nitrate and total N uptake of beech seedlings were strongly reduced so that impaired growth of beech seedlings was observed already after one year of exposure to simulated climatic change. We conclude that the N cycle in this ecosystem and here specifically nitrification is vulnerable to reduced water availability, which can directly lead to nutritional limitations of beech seedlings. This tight link between reduced water availability, drought stress for nitrifiers, decreased gross nitrification rates and nitrate availability and finally nitrate uptake by beech seedlings could represent the Achilles’ heel for beech under climate change stresses

Hochauflösende Bodenkarten für den ­Schweizer Wald

Bei der Beurteilung von Standortsbedingungen im Schweizer Wald spielt der Boden neben Klima und Relief eine entscheidende Rolle. Flächige Bodeninformationen für den Schweizer Wald sind jedoch nur in grober Form verfügbar. Basierend auf rund 2000 Waldbodenprofilen haben wir mittels maschinellen Lernens verschiedene Bodeneigenschaften (z.B. pH- und Sandgehalt) von sechs Bodentiefen für die gesamte Waldfläche der Schweiz mit einer Auflösung von 25 m × 25 m vorausgesagt. Während die Güte der Modellierung für die Bodendichte zufriedenstellend war, waren der Gehalt an organischem Kohlenstoff und die Bodengründigkeit schwieriger vorauszusagen. Zu jeder Bodenkarte berechneten wir zudem eine Unsicherheitskarte, sodass die Qualität der Bodenkarten auch räumlich beurteilt werden kann

Microtopography shapes soil pH in flysch regions across Switzerland

As topography is a key factor controlling soil genesis and strongly influences physical and chemical soil properties, terrain attributes are routinely used in digital soil mapping to spatially predict soil properties. Forests on flysch sediments along the northern slopes of the Swiss Alps often have a strong microrelief. The dominant soil types are Gleysols in depressions and Cambisols on ridges, with large pH variation within short distances. Based on the theory of soil development we expected that soil-forming processes driven by micro-scale topographic variation shape similar micro-scale spatial patterns of soil properties at different sites within the flysch region. Therefore, the main objective of the study was to investigate model extrapolation within flysch regions, which has turned out to be difficult on many other geological substrates. At three sites, each of about 2 ha, we first built three local models to examine whether a relationship between microtopography and topsoil pH could be inferred from high-resolution terrain attributes and pH measurements. Using data from all three sites we then calibrated a joint model and examined model extrapolation by calibrating models with data from two sites and predicting pH at the third. All models were based on multiple linear regressions that used 0.5 m resolution terrain attributes derived by a multiscale approach as explanatory variables. The cross-validated R2 for the local pH models varied between 0.56 and 0.77, and the corresponding RMSE between 0.57 and 0.64 pH units. The R2 and RMSE for the joint model were 0.60 and 0.76, respectively. The results of the local models suggest that microtopography is a dominant soil-forming factor on flysch sediments that triggers soil genesis on a spatial scale from submetre to metres. Although the extrapolated models showed a reduced prediction ability with R2 values of 0.25, 0.46 and 0.53, the selected terrain attributes were relatively similar among the models, which may indicate the common driving processes. The results for the joint model suggest that using high-resolution terrain attributes yields a fairly accurate spatial prediction of the highly variable topsoil pH in forests on flysch sediments across Switzerland.</p