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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.

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.

Exotic annual grasses invasion across northern Great Basin rangelands has promoted a grass-fire cycle that threatens the sagebrush (Artemisia spp.) steppe ecosystem. In this sense, high accumulation rates and persistence of litter from annual species largely increase the amount and continuity of fine fuels. Here, we highlight the potential use and transferability of remote sensing-derived products to estimate litter biomass on sagebrush rangelands in southeastern Oregon, and link fire regime attributes (fire-free period) with litter biomass spatial patterns at the landscape scale. Every June, from 2018 to 2021, we measured litter biomass in 24 field plots (60 m × 60 m). Two remote sensing-derived datasets were used to predict litter biomass measured in the field plots. The first dataset used was the 30-m annual net primary production (NPP) product partitioned into plant functional traits (annual grass, perennial grass, shrub, and tree) from the Rangeland Analysis Platform (RAP). The second dataset included topographic variables (heat load index -HLI- and site exposure index -SEI-) computed from the USGS 30-m National Elevation Dataset. Through a frequentist model averaging approach (FMA), we determined that the NPP of annual and perennial grasses, as well as HLI and SEI, were important predictors of field-measured litter biomass in 2018, with the model featuring a high overall fit (R2 = 0.61). Model transferability based on extrapolating the FMA predictive relationships from 2018 to the following years provided similar overall fits (R2 ≈ 0.5). The fire-free period had a significant effect on the litter biomass accumulation on rangelands within the study site, with greater litter biomass in areas where the fire-free period was <10 years. Our findings suggest that the proposed remote sensing-derived products could be a key instrument to equip rangeland managers with additional information towards fuel management, fire management, and restoration efforts.

This study focuses on the economic feasibility for large-scale biomass production from soybeans or switchgrass from a region in Argentina. This is determined, firstly, by estimating whether the potential supply of biomass, when food and feed demand are met, is sufficient under different scenarios to 2030. On a national level, switchgrass has a biomass potential of 99 × 106 (1.9 EJ) to 243 × 106 tdm (4.5 EJ)/year depending on the scenario. Soybean (crude vegetable oil content) production for bioenergy has a potential of 7.1 × 106 (0.25 EJ) to 13.8 × 106 tdm (0.5 EJ)/year depending on the scenario. The most suitable region (La Pampa province) to cultivate energy crop production is selected based on a defined set of criteria (available land for biomass production, available potential for both crops, proximity of logistics and limited risk of land use competition). The available potential for bioenergy in La Pampa ranges from 1.2 × 105 to 1.8 × 105 tdm/year for soybean production (based on vegetable oil content) and from 6.3 × 106 to 18.2 × 106 tdm/year for switchgrass production, depending on the scenario. Bioenergy chains for large-scale biomass production for export or for local use are further defined to analyse the economic performance. In this study, switchgrass is converted to pellets for power generation in the Netherlands or for local heating in Argentina. Soybeans are used for biodiesel production for export or for local use. Switchgrass cultivation costs range from 33–91 US$/tdm (1€ = 1.47 US$ based on 19 February 2008). Pellet production costs are 58–143 US$/tdm for local use and 150–296 US$/tdm until delivery at the harbour of Rotterdam. Total conversion costs for electricity in the Netherlands from switchgrass pellets range from 0.06–0.08 US$/kWh. Heating costs in Argentina from switchgrass pellets range from 0.02–0.04 US$/kWh. Soybean cultivation costs range from 182–501 US$/tdm depending on the scenario. Biodiesel production costs are 0.3–1.2 US$/l for local use and 0.5–1.7 US$/l after export to the Netherlands. Key parameters for the economic performance of the bioenergy chains in La Pampa province are transport costs, cultivation costs, pre-processing and conversion costs and costs for fossil fuels and agricultural commodities.

AbstractMountain treelines are thought to be sensitive to climate change. However, how climate impacts mountain treelines is not yet fully understood as treelines may also be affected by other human activities. Here, we focus on “closed‐loop” mountain treelines (CLMT) that completely encircle a mountain and are less likely to have been influenced by human land‐use change. We detect a total length of ~916,425 km of CLMT across 243 mountain ranges globally and reveal a bimodal latitudinal distribution of treeline elevations with higher treeline elevations occurring at greater distances from the coast. Spatially, we find that temperature is the main climatic driver of treeline elevation in boreal and tropical regions, whereas precipitation drives CLMT position in temperate zones. Temporally, we show that 70% of CLMT have moved upward, with a mean shift rate of 1.2 m/year over the first decade of the 21st century. CLMT are shifting fastest in the tropics (mean of 3.1 m/year), but with greater variability. Our work provides a new mountain treeline database that isolates climate impacts from other anthropogenic pressures, and has important implications for biodiversity, natural resources, and ecosystem adaptation in a changing climate.

Worldwide, marginalized and low-income communities will disproportionately suffer climate change impacts while also retaining the least political power to mitigate their consequences. To adapt to environmental shocks, communities must balance intensifying natural resource consumption with the need to ensure the sustainability of ecosystem provisioning services. Thus, scientists have long been providing policy recommendations that seek to balance humanitarian needs with the best outcomes for the conservation of ecosystems and wildlife. However, many conservation and development practitioners from biological backgrounds receive minimal training in either social research methods or participatory project design. Without a clear understanding of the sociocultural factors shaping decision-making, their initiatives may fail to meet their goals, even when communities support proposed initiatives. This paper explores the underlying assumptions of a community's agency, or its ability to develop and enact preferred resilience-enhancing adaptations. We present a context-adaptable toolkit to assess community agency, identify barriers to adaptation, and survey perceptions of behaviour change around natural resource conservation and alternative food acquisition strategies. This tool draws on public health and ecology methods to facilitate conversations between community members, practitioners and scientists. We then provide insights from the toolkit's collaborative development and pilot testing with Vezo fishing communities in southwestern Madagascar.This article is part of the theme issue ‘Climate change adaptation needs a science of culture’.