Swiss Federal Institute for Forest, Snow and Landscape Research

About: Swiss Federal Institute for Forest, Snow and Landscape Research is a facility organization based out in Birmensdorf, Switzerland. It is known for research contribution in the topics: Climate change & Soil water. The organization has 1256 authors who have published 3222 publications receiving 161639 citations. The organization is also known as: WSL.

Distribution of Zn in functionally different leaf epidermal cells of the hyperaccumulator Thlaspi caerulescens

Abstract: The aim of this study was to show the potential of Thlaspi caerulescens in the cleaning-up of a moderately Zn -contaminated soil and to elucidate tolerance mechanisms at the cellular and subcellular level for the detoxification of the accumulated metal within the leaf. Measured Zn concentrations in shoots were high and reached a maximum value of 83 mmol kg -1 dry mass, whereas total concentrations of Zn in the roots were lower (up to 13 mmol kg -1 ). In order to visualize and quantify Zn at the subcellular level in roots and leaves, ultrathin cryosections were analysed using energy-dispersive X-ray micro-analysis. Elemental maps of ultrathin cryosections showed that T. caerulescens mainly accumulated Zn in the vacuoles of epidermal leaf cells and Zn was almost absent from the vacuoles of the cells from the stomatal complex, thereby protecting the guard and subsidiary cells from high Zn concentrations. Observed patterns of Zn distribution between the functionally different epidermal cells were the same in both the upper and lower epidermis, and were independent of the total Zn content of the plant. Zinc stored in vacuoles was evenly distributed and no Zn-containing crystals or deposits were observed. From the elemental maps there was no indication that P, S or Cl was associated with the high Zn concentrations in the vacuoles. In addition, Zn also accumulated in high concentrations in both the cell walls of epidermal cells and in the mesophyll cells, indicating that apoplastic compartmentation is another important mechanism involved in zinc tolerance in the leaves of T. caerulescens.

Sinks for nitrogen inputs in terrestrial ecosystems: a meta‐analysis of 15N tracer field studies

Abstract: Effects of anthropogenic nitrogen (N) deposition and the ability of terrestrial ecosystems to store carbon (C) depend in part on the amount of N retained in the system and its partitioning among plant and soil pools. We conducted a meta-analysis of studies at 48 sites across four continents that used enriched 15N isotope tracers in order to synthesize information about total ecosystem N retention (i.e., total ecosystem 15N recovery in plant and soil pools) across natural systems and N partitioning among ecosystem pools. The greatest recoveries of ecosystem 15N tracer occurred in shrublands (mean, 89.5%) and wetlands (84.8%) followed by forests (74.9%) and grasslands (51.8%). In the short term (< 1 week after 15N tracer application), total ecosystem 15N recovery was negatively correlated with fine-root and soil 15N natural abundance, and organic soil C and N concentration but was positively correlated with mean annual temperature and mineral soil C:N. In the longer term (3-18 months after 15N tracer application), total ecosystem 15N retention was negatively correlated with foliar natural-abundance 15N but was positively correlated with mineral soil C and N concentration and C:N, showing that plant and soil natural-abundance 15N and soil C:N are good indicators of total ecosystem N retention. Foliar N concentration was not significantly related to ecosystem 15N tracer recovery, suggesting that plant N status is not a good predictor of total ecosystem N retention. Because the largest ecosystem sinks for 15N tracer were below ground in forests, shrublands, and grasslands, we conclude that growth enhancement and potential for increased C storage in aboveground biomass from atmospheric N deposition is likely to be modest in these ecosystems. Total ecosystem 15N recovery decreased with N fertilization, with an apparent threshold fertilization rate of 46 kg N x ha(-1) x yr(-1) above which most ecosystems showed net losses of applied 15N tracer in response to N fertilizer addition.

Model averaging in ecology: a review of Bayesian, information-theoretic, and tactical approaches for predictive inference

Abstract: In ecology, the true causal structure for a given problem is often not known, and several plausible models and thus model predictions exist. It has been claimed that using weighted averages of these models can reduce prediction error, as well as better reflect model selection uncertainty. These claims, however, are often demonstrated by isolated examples. Analysts must better understand under which conditions model averaging can improve predictions and their uncertainty estimates. Moreover, a large range of different model averaging methods exists, raising the question of how they differ in their behaviour and performance. Here, we review the mathematical foundations of model averaging along with the diversity of approaches available. We explain that the error in model‐averaged predictions depends on each model's predictive bias and variance, as well as the covariance in predictions between models, and uncertainty about model weights. We show that model averaging is particularly useful if the predictive error of contributing model predictions is dominated by variance, and if the covariance between models is low. For noisy data, which predominate in ecology, these conditions will often be met. Many different methods to derive averaging weights exist, from Bayesian over information‐theoretical to cross‐validation optimized and resampling approaches. A general recommendation is difficult, because the performance of methods is often context dependent. Importantly, estimating weights creates some additional uncertainty. As a result, estimated model weights may not always outperform arbitrary fixed weights, such as equal weights for all models. When averaging a set of models with many inadequate models, however, estimating model weights will typically be superior to equal weights. We also investigate the quality of the confidence intervals calculated for model‐averaged predictions, showing that they differ greatly in behaviour and seldom manage to achieve nominal coverage. Our overall recommendations stress the importance of non‐parametric methods such as cross‐validation for a reliable uncertainty quantification of model‐averaged predictions.

Biotic homogenization can decrease landscape-scale forest multifunctionality

Abstract: Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality.