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Due to climate change, the frequency and intensity of droughts are expected to increase. To improve resilience to droughts, proactive drought management is essential. Economic assessments are typically included to decide on the drought risk-reducing investments to make. The choice of both methods and scope of economic assessments influences the outcome, and thus the investment choice. This paper aims to identify how comprehensively economic assessments are applied in practice. Through a systematic literature review, 14 actual economic assessments are identified and their methods are evaluated based on seven criteria for economic assessments as derived from the United Nations Framework Convention on Climate Change (UNFCCC). The results show that in practice, economic assessments rarely address all criteria. Applying a limited number of criteria reduces the scope and narrows the approach, possibly leading to the underestimation of drought risk reduction approaches' related benefits. Applying the seven criteria in practice will improve the results of economic assessments of drought risk reduction measures, allowing for optimal investment selection. Based on the different criteria, a Framework for Economic Assessments of Drought Risk-Reducing Applications (FEADRRA) is proposed. Applying the criteria of the framework can support decision-makers in drought risk management and in carrying out the most fitting drought interventions.

Moisture availability is a strong determinant of decomposition rates in forests worldwide. Climate models suggest that many terrestrial ecosystems are at risk from future droughts, suggesting moisture limiting conditions will develop across a range of forests worldwide. The impacts of increasing drought conditions on forest carbon (C) fluxes due to shifts in organic matter decay rates may be poorly characterised due to limited experimental research. To appraise this question, we conducted a meta-analysis of forest drought experiment studies worldwide, examining spatial limits, knowledge gaps and potential biases. To identify limits to experimental knowledge, we projected the global distribution of forest drought experiments against spatially modelled estimates of (i) future precipitation change, (ii) ecosystem total above-ground C and (iii) soil C storage. Our assessment, involving 115 individual experimental study locations, found a mismatch between the distribution of forest drought experiments and regions with higher levels of future drought risk and C storage, such as Central America, Amazonia, the Atlantic Forest of Brazil, equatorial Africa and Indonesia. Decomposition rate responses in litter and soil were also relatively under-studied, with only 30 experiments specifically examining the potential experimental impacts of drought on C fluxes from soil or litter. We propose new approaches for engaging experimentally with forest drought research, utilising standardised protocols to appraise the impacts of drought on the C cycle, while targeting the most vulnerable and relevant forests.

The nature of linkages between soil C and N cycling is important in the context of terrestrial ecosystem responses to global environmental change. Extracellular enzymes produced by soil microorganisms drive organic matter decomposition, and are considered sensitive indicators of soil responses to environmental variation. We investigated the response of eight hydrolytic soil enzymes (four peptidases and four glycosidases) to experimental warming in a long-term climate manipulation experiment in a sub-arctic peat bog, to determine to what extent the response of these two functional groups are similar. We found no significant effect of experimental spring and summer warming and/or winter snow addition on either the potential activity or the temperature sensitivity (of V

The adverse effects of soil acidification are extensive and may result in hampered ecosystem functioning. Admixture of tree species with nutrient rich litter has been proposed to restore acidified forest soils and improve forest vitality, productivity and resilience. However, it is common belief that litter effects are insufficiently functional for restoration of poorly buffered sandy soils. Therefore we examined the effect of leaf litter on the forest floor, soil chemistry and soil biota in temperate forest stands along a range of sandy soil types in Belgium, the Netherlands and Germany. Specifically, we address: i) Which tree litter properties contribute most to the mitigation of soil acidification effects and ii) Do rich litter species have the potential to improve the belowground nutrient status of poorly buffered, sandy soils? Our analysis using structural equation modelling shows that litter base cation concentration is the decisive trait for the dominating soil buffering mechanism in forests that are heavily influenced by atmospheric nitrogen (N) deposition. This is in contrast with studies in which leaf litter quality is summarized by C/N ratio. We suggest that the concept of rich litter is context dependent and should consider Liebig's law of the most limiting: if N is not limiting in the ecosystem, litter C/N becomes of low importance, while base cations (calcium, magnesium, potassium) become determining. We further find that on poorly buffered soils, tree species with rich litter induce fast nutrient cycling, sustain higher earthworm biomass and keep topsoil base saturation above a threshold of 30%. Hence, rich litter can trigger a regime shift to the exchange buffer domain in sandy soils. This highlights that admixing tree species with litter rich in base cations is a promising measure to remediate soil properties on acidified sandy soils that receive, or have received, high inputs of N via deposition.

AbstractSpecies distributions are conventionally modelled using coarse‐grained macroclimate data measured in open areas, potentially leading to biased predictions since most terrestrial species reside in the shade of trees. For forest plant species across Europe, we compared conventional macroclimate‐based species distribution models (SDMs) with models corrected for forest microclimate buffering. We show that microclimate‐based SDMs at high spatial resolution outperformed models using macroclimate and microclimate data at coarser resolution. Additionally, macroclimate‐based models introduced a systematic bias in modelled species response curves, which could result in erroneous range shift predictions. Critically important for conservation science, these models were unable to identify warm and cold refugia at the range edges of species distributions. Our study emphasizes the crucial role of microclimate data when SDMs are used to gain insights into biodiversity conservation in the face of climate change, particularly given the growing policy and management focus on the conservation of refugia worldwide.