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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.

AbstractAlthough our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.

This study assesses the socio-economic impacts in terms of value added, imports and employment of sugarcane-derived bioethanol production in Northeast (NE) Brazil. An extended inter-regional Input–Output (IO) model has been developed and is used to analyse three scenarios, all projected for 2020: a business-as-usual scenario (BaU) which projects current practices, and two scenarios that consider more efficient agricultural practices and processing efficiency (scenario A) and in addition an expansion of the sector into new areas (scenario B). By 2020 in all scenarios, value added and imports increase compared to the current situation. The value added by the sugarcane–ethanol sector in the NE region is 2.8 billion US$ in the BaU scenario, almost 4 billion US$ in scenario A, and 9.4 billion US$ in scenario B. The imports in the region will grow with 4% (BaU scenario), 38% (scenario A) and 262% (scenario B). This study shows that the large reduction of employment (114,000 jobs) due to the replacement of manual harvesting by mechanical harvesting can be offset by additional production and indirect effects. The total employment in the region by 2020 grows with 10% in scenario A (around 12,500 jobs) and 126% in scenario B (around 160,000 jobs). The indirect effects of sugarcane production in the NE are large in the rest of Brazil due to the import of inputs from these regions. The use of an extended inter-regional IO model can quantify direct and indirect socio-economic effects at regional level and can provide insight in the linkages between regions. The application of the model to NE Brazil has demonstrated significant positive socio-economic impacts that can be achieved when developing and expanding the sugarcane–ethanol sector in the region under the conditions studied here, not only for the NE region itself but also for the economy of the rest of Brazil.

Climate change will bring warmer and wetter conditions and more frequent extreme events in the Nemoral climate zone. These changes are expected to affect maize growth and yields. In this study, we applied the AgroC model to assess climate change impact on changes in growing environmental conditions, growing season length, yield and potential yield losses due to multiple abiotic stresses. The model was calibrated and validated using data from dedicated field experiments conducted in Lithuania during four meteorologically contrasting years (2015, 2016, 2017 and 2019). We simulated the climate impacts on rainfed maize for long-term future climate conditions from 2020 to 2100 under the RCP2.6 (low), RCP4.5 (medium) and RCP8.5 (high) emission scenarios. As a result, we found that air temperature, sum of growing degree days and amount of precipitation during the growing season of maize will increase, especially under medium and higher emission scenarios (RCP4.5 and RCP8.5), with significantly positive effect on yields. The simulation results showed that average maize grain yield will increase under RCP2.6 by 69 kg ha-1 per decade, under RCP4.5 by 197 kg ha-1 per decade and under RCP8.5 by 304 kg ha-1 per decade. The future potential maize yield reveals a progressive increase with a surplus of +10.2% under RCP4.5 and +14.4% under RCP8.5, while under RCP2.6 the increase of potential yield during the same period will be statistically not significant. The yield gap under RCP2.6 and RCP4.5 will fluctuate within a rather narrow range and under RCP8.5, it will decrease.

Miscanthus (ANDERSSON) is considered a promising perennial industrial crop for providing biomass in a growing bioeconomy. One approach to increasing the biodiversity-enhancing ecosystem services of Miscanthus is the co-cultivation of flower-rich native wild plant species (WPS), for example, the perennial WPS common tansy (Tanacetum vulgare L.) and mugwort (Artemisia vulgaris L.), as well as the biennial WPS wild teasel (Dipsacus fullonum L.) and yellow melilot (Melilotus officinalis L.). This study tested whether these selected WPS would be as suitable for combustion as Miscanthus, in this case the sterile hybrid Miscanthus x giganteus Greef et Deuter, allowing for a mixing of the biomasses. By doing so, no additional value chain (e.g. biogas production) would be necessary to economically exploit the diversification of the agricultural system for bioenergy production. Feedstock samples of Miscanthus and the four above-mentioned WPS from a field trial in southwest Germany were used to investigate the combustion characteristics as well as the higher heating value (HHV). It was found that all WPS exhibited better combustion properties than Miscanthus with respect to ash melting behavior at similar HHVs of 16.3–17.5 MJ kg−1. From an admixture of >30% WPS to the Miscanthus biomass, a significant increase in the ash melting temperature by 20% from 1000 to 1200 °C was shown. Thus, the mixture of WPS and Miscanthus could potentially improve the combustion quality, leading to reduced costs in the incineration plant operation process. However, the reduced costs of incineration should be greater than the loss in productivity due to the lower biomass yields from the WPS. This is highly dependent on the particular site conditions and the establishment success of the WPS and needs to be investigated in long-term studies.

While clonal integration can improve the performance of rhizomatous plants, it remains unclear whether their clonal integration strategy changes under contrasting clipping and saline-alkali homogeneous and heterogeneous environments. Leymus chinensis is a clonal grass native to the Songnen grassland where heavy grazing and patchy saline-alkali stress are serious environmental and ecological problems. We hypothesized that L. chinensis overcomes these stresses through clonal integration, in particular the transfer of nitrogen and carbohydrates.A pot experiment was carried out with 15N isotope soil labeling method to study clonal integration strategy in the connected mother and daughter ramets of L. chinensis. The connected ramet pairs were grown in homogeneous (both connected ramets were treated) and heterogeneous (only daughter ramets were treated) environments with four treatments: control, clipping (60% aboveground biomass removal), saline-alkali (3.45 g of NaCl, NaHCO3, and Na2CO3 per pot), and clipping × saline-alkali.A significant amount (22.5%) of 15N was transferred from mother to daughter ramets under non-stressed conditions. When homogeneously stressing both mother and daughter ramets, N transfer was significantly reduced to 8.5--14.6%, independent of the nature of the stress. When only daughters were stressed (heterogeneous stress), saline-alkali stress led to a division of labor where daughters had enhanced photosynthesis, and mother ramets had increased 15N uptake and growth. Clipping only daughters reduced biomass and 15N uptake of both daughter and mother ramets.Our results demonstrated that clonal integration also occurs in homogeneous favorable environments but is reduced under homogeneous stress. In heterogeneous environments, clonal integration is used to translocate resource after clipping and a division of labor is established to overcome saline-alkali stress. Clonal integration continued even when daughters were severely stressed by the combined treatments. Our findings suggest that these mechanisms are key to the success of L. chinensis in the Songnen grassland.

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