The cumulative impacts of droughts and N deposition on Norway spruce (Picea abies) in Switzerland based on 37 years of forest monitoring.

Norway spruce is one of the most important tree species in Central Europe, however, it is facing major problems with recent droughts. In this study we present 37 years (1985-2022) of long-term forest observation data on 82 different forest sites across Switzerland including 134'348 tree observations. The sites consists of managed spruce or mixed forest stands with beech (Fagus sylvatica) and comprise large gradients in altitude (290-1870 m), precipitation (570-2448 mm a-1), temperature (3.6-10.9 °C) or total nitrogen deposition (8.5-81.2 kg N ha-1 a-1). Long-term tree mortality has increased more than fivefold due to the multiple drought years 2019, 2020 and 2022, which is more than double the increase following the 2003 drought. We used a Bayesian multilevel model including three years of lagged drought indicator to predict spruce mortality. Besides stand age, the most important factors were drought and N deposition. Especially under drought conditions spruce mortality was increased on sites with high N deposition. Moreover, N deposition increased the imbalance of foliar phosphorus concentrations, with negative impacts on tree mortality. Mortality was increased by a factor of 1.8 in spruce compared to mixed beech and spruce stands. Stands with high mortality rates showed previously an increased proportion of trees with damaged crowns, especially after the droughts of 2003 and 2018. Taken together, we found evidences of an increase in spruce mortality droughts amplified under high N depositions. The perennial drought of 2018-2020 resulted in a cumulative spruce mortality of 12.1 % (564 dead trees in 82 sites) in only three years. With a Bayesian change-point regression framework we estimated a critical empirical load for nitrogen of 10.9 ± 4.2 kg N ha-1 a-1, which is in line with current thresholds, above which future plantings of spruce in Switzerland may not be a sustainable option due to the observed interaction between drought and nitrogen deposition.

Hierarchical change-point regression models including random effects to estimate empirical critical loads for nitrogen using Bayesian Regression Models (brms) and JAGS.

The concept of critical loads is used in the framework of the Convention on Long-range Transboundary Air Pollution (UNECE) to define thresholds below which no damaging effects on habitats occur based on the latest scientific knowledge. Change-point regression models applied in a Bayesian framework are useful statistical tools to estimate critical empirical loads. While hierarchical study designs are common in ecological research, previous methods to estimate critical loads using change-point regression did not allow to analyse data collected under such a design. This method update provides an implementation of hierarchical data structure by including random effects such as study sites or as in this example tree species within the Bayesian approach of change-point regression models using two different approaches. The example data set is an European wide gradient study of the impact of climate change and air pollution on forest tree health assessed by foliar nutrient status of nitrogen (N) to phosphorus (P) from 10 different conifer tree species originated from 88 forest sites and 9 countries covering 22 years (1995-2017). Both modelling approaches using JAGS and Bayesian Regression Models using 'Stan' (brms) resulted in reasonable and similar estimations of the critical empirical load for nitrogen (CLempN) for temperate forests. These methodological examples of using different approaches of Bayesian change-point regression models dealing with random effects could prove useful to infer CLempN for other ecosystems and long-term data sets.•Hierarchical change-point regression models are suitable for estimating critical empirical loads.•The Bayesian framework of these models provides the inclusion of the current critical load and various confounding or modifying variables.•Here we present two ways of implementing hierarchical data sets in Bayesian change-point regression models using JAGS and brms.

Corrigendum to "Modification of the RUSLE slope length and steepness factor (LS-factor) based on rainfall experiments at steep alpine grasslands" [MethodsX 6 (2019), 219-229].

[This corrects the article DOI: 10.1016/j.mex.2019.01.004.].

Soil solution in Swiss forest stands: A 20 year's time series.

Soil solution chemistry is influenced by atmospheric deposition of air pollutants, exchange processes with the soil matrix and soil-rhizosphere-plant interactions. In this study we present the results of the long-term Intercantonal Forest Observation Program in Switzerland with soil solution measurements since 1998 on a current total of 47 plots. The forest sites comprise two major forest types of Switzerland including a wide range of ecological gradients such as different nitrogen (N) deposition and soil conditions. The long-term data set of 20 years of soil solution measurements revealed an ongoing, but site-specific soil acidification. In strongly acidified soils (soil pH below 4.2), acidification indicators changed only slowly over the measured period, possibly due to high buffering capacity of the aluminum buffer (pH 4.2-3.8). In contrast, in less acidified sites we observed an increasing acidification rate over time, reflected, for example, by the continuous decrease in the ratio of base cations to aluminum (BC/Al ratio). Nowadays, the main driver of soil acidification is the high rate of N deposition, causing cation losses and hampering sustainable nutrient balances for tree nutrition. Mean nitrate leaching rates for the years 2005-2017 were 9.4 kg N ha-1 yr-1, ranging from 0.04 to 53 kg N ha-1 yr-1. Three plots with high N input had a remarkable low nitrate leaching. Both N deposition and nitrate leaching have decreased since 2000. However, the latter trend may be partly explained due to increased drought in recent years. Nonetheless, those high N depositions are still affecting the majority of the forest sites. Taken together, this study gives evidence of anthropogenic soil acidification in Swiss forest stands. The underlying long-term measurements of soil solution provides important information on nutrient leaching losses and the impact climate change effects such as droughts. Furthermore, this study improves the understanding of forest management and tree mortality regarding varying nitrate leaching rates.

Direct and indirect effects of urban gardening on aboveground and belowground diversity influencing soil multifunctionality.

Urban gardens are popular green spaces that have the potential to provide essential ecosystem services, support human well-being, and at the same time foster biodiversity in cities. We investigated the impact of gardening activities on five soil functions and the relationship between plant (600 spp.) and soil fauna (earthworms: 18 spp., springtails: 39 spp.) in 85 urban gardens (170 sites) across the city of Zurich (Switzerland). Our results suggest that high plant diversity in gardens had a positive effect on soil fauna and soil multifunctionality, and that garden management intensity decreased plant diversity. Indices of biological activity in soil, such as organic and microbial carbon and bacterial abundance, showed a direct positive effect on soil multifunctionality. Soil moisture and disturbance, driven by watering and tilling, were the driving forces structuring plant and soil fauna communities. Plant indicator values proved useful to assess soil fauna community structure, even in anthropogenic plant assemblages. We conclude that to enhance soil functions, gardeners should increase plant diversity, and lower management intensity. Soil protective management practices, such as applying compost, mulch or avoiding soil tilling, should be included in urban green space planning to improve urban biodiversity and nature's contribution to people.

Modification of the RUSLE slope length and steepness factor (LS-factor) based on rainfall experiments at steep alpine grasslands.

The slope length and slope steepness factor (LS-factor) is one of five factors of the Universal Soil Loss Equation (USLE) and its revised version (RUSLE) describing the influence of topography on soil erosion risk. The LS-factor was originally developed for slopes less than 50% inclination and has not been tested for steeper slopes. To overcome this limitation, we adapted both factors slope length L and slope steepness S for conditions experimentally observed at Swiss alpine grasslands. For the new L-factor (Lalpine), a maximal flow path threshold, corresponding to 100 m, was implemented to take into account short runoff flow paths and rapid infiltration that has been observed in our experiments. For the S-factor, a fitted quadratic polynomial function (Salpine) has been established, compiling the most extensive empirical studies. As a model evaluation, uncertainty intervals are presented for this modified S-factor. We observed that uncertainty increases with slope gradient. In summary, the proposed modification of the LS-factor to alpine environments enables an improved prediction of soil erosion risk including steep slopes. •Empirical experiments (rainfall simulation, sediment measurements) were conducted on Swiss alpine grasslands to assess the maximal flow length and slope steepness factor (S-factor).•Flow accumulation is limited to a maximal flow threshold (100 m) at which overland runoff is realistic in alpine grassland.•Slope steepness factor is modified by a fitted S-factor equation from existing empirical S-factor functions.

Litter decomposition driven by soil fauna, plant diversity and soil management in urban gardens.

In the face of growing urban densification, green spaces in cities, such as gardens, are increasingly important for biodiversity and ecosystem services. However, the influences of urban green space management on biodiversity and ecosystem functioning (BEF) relationships is poorly understood. We investigated the relationship between soil fauna and litter decomposition in 170 urban garden sites along a gradient of urbanisation intensity in the city of Zurich, CH. We used litter bags of 1 and 4 mm mesh size to evaluate the contribution of soil meso- and macrofauna on litter decomposition. By using multilevel structural equation models (SEM), we investigated direct and indirect environmental effects and management practices on litter decomposition and litter residue quality. We evaluated the role of taxonomic, functional and phylogenetic diversity of soil fauna species on litter decomposition, based on a sample of 120 species (81,007 individuals; 39 collembola, 18 earthworm, 16 isopod, 47 gastropod species). We found highest litter decomposition rates using 4 mm mesh size litter bags, highlighting the importance of soil macrofauna. Urban warming, a proxy for urbanisation intensity, covaried positively, whereas soil disturbances, such as intensive soil and crop management, were negatively correlated with decomposition rates. Interestingly, soil fauna species richness decreased, with the exception of gastropods, and soil fauna abundance increased with urban warming. Our data also show that plant species richness positively affected litter decomposition by increasing soil fauna species richness and microbial activity. A multivariate analysis of organic compounds in litter residues confirmed the importance of soil fauna species richness and garden management on litter decomposition processes. Overall, we showed, that also in intensively managed urban green spaces, such as gardens, biodiversity of plants and soil fauna drives key ecosystem processes. Urban planning strategies that integrate soil protecting management practices may help to maintain important ecosystem services in this heavily used urban environment.