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When regulators are faced with practical challenges, policy instrument choice theories can help them find the best solution. However, not all such theories are equally helpful. This paper aims to offer regulators a better alternative to the current policy instrument choice theories. We will specifically address the shortcomings of "smart regulation theory" and present an alternative that keeps the best of that theory while remediating its weak points. Some authors (Bocher and Toller 2003; Baldwin and Black 2008) say that smart regulation theory does not address institutional issues, compliance type-specific response, performance-sensitivity and adaptability of regulatory regime. We have resolved these problems by merging the smart regulation theory with the policy arrangement approach and the policy learning concept. We call the resulting approach "regulatory arrangement approach" (RAA). The central idea of the RAA is to constrain the almost infinite "smart" regulatory options by: the national policy style; adverse effects of policy arrangements of adjoining policies; the structure of the policy arrangement of the investigated policy and competence dependencies of other institutions. The reduction can be so drastic that the potential governance capacity falls below the smart regulation threshold. In other words, no smart regulatory arrangement can be developed in that institutional context unless policy learning occurs. In addition, a "smart" regulatory arrangement is no guarantee that the policy will succeed. For this reason, the performance of the regulatory arrangement is measured and evaluated. Performance below a certain threshold indicates that the regulatory arrangement needs to be adapted, which then results in policy learning. We illustrate the usefulness of this new approach with a secondary analysis of the Flemish sustainable forest management policy. Adapted from the source document.

[Background]: In contrast with the negligible contribution of the forest understorey to the total aboveground phytobiomass of a forest, its share in annual litter production and nutrient cycling may be more important. Whether and how this functional role of the understorey differs across forest types and depends upon overstorey characteristics remains to be investigated. ; [Methods]: We sampled 209 plots of the FunDivEUROPE Exploratory Platform, a network of study plots covering local gradients of tree diversity spread over six contrasting forest types in Europe. To estimate the relative contribution of the understorey to carbon and nutrient cycling, we sampled non-lignified aboveground understorey biomass and overstorey leaf litterfall in all plots. Understorey samples were analysed for C, N and P concentrations, overstorey leaf litterfall for C and N concentrations. We additionally quantified a set of overstorey attributes, including species richness, proportion of evergreen species, light availability (representing crown density) and litter quality, and investigated whether they drive the understorey's contribution to carbon and nutrient cycling. [Results and conclusions]: Overstorey litter production and nutrient stocks in litterfall clearly exceeded the contribution of the understorey for all forest types, and the share of the understorey was higher in forests at the extremes of the climatic gradient. In most of the investigated forest types, it was mainly light availability that determined the contribution of the understorey to yearly carbon and nutrient cycling. Overstorey species richness did not affect the contribution of the understorey to carbon and nutrient cycling in any of the investigated forest types. ; [Results and conclusions]: Overstorey litter production and nutrient stocks in litterfall clearly exceeded the contribution of the understorey for all forest types, and the share of the understorey was higher in forests at the extremes of the climatic gradient. In most of the investigated forest types, it was mainly light availability that determined the contribution of the understorey to yearly carbon and nutrient cycling. Overstorey species richness did not affect the contribution of the understorey to carbon and nutrient cycling in any of the investigated forest types. ; This study was performed within the framework of the FunDivEUROPE project and has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement n° 265171. Dries Landuyt was supported by a postdoctoral fellowship of the Research Foundation-Flanders (FWO). Kris Verheyen was supported by the ERC Consolidator Grant 614839 that is linked with the project PASTFORWARD.

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. ; We thank the Hainich National Park administration as well as Felix Berthold and Carsten Beinhoff for support of this study and Gerald Kaendler and the Johann Heinrich von Thünen-Institut for providing access to the German National Forest Inventory data. The research leading to these results received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under Grant Agreement 265171. ; This is the final version of the article. It first appeared from the National Academy of Sciences via https://doi.org//10.1073/pnas.1517903113