Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change depend on the magnitude of climate forcing, interactions with other anthropogenic and natural changes, and the characteristics of the ecosystem itself. Therefore, the magnitude and manner in which freshwater ecosystems respond to climate change is difficult to predict . We present a conceptual model to elucidate how freshwater ecosystems are altered by climate change. We identify eleven indicators that describe the response of freshwater ecosystems to climate change, discuss their potential value and limitations, and describe supporting measurements. Indicators are organized in three inter-related categories: hydrologic, water quality, and ecosystem structure and function. The indicators are supported by data sets with a wide range of temporal and spatial coverage, and they inform important scientific and management needs. Together, these indicators improve the understanding and management of the effects of climate change on freshwater ecosystems.

Climate change and indebtedness have been repeatedly highlighted as major causes of distress for rural households in India. However, despite the close connection between climate conditions and rural livelihoods, there has been little attempt to systematically examine the association between the two. To address this gap, we combine national-level longitudinal data from IHDS, MERRA-2, and the Indian Ministry of Agriculture to study the impact of climate anomalies on household indebtedness across rural India. Using a longitudinal approach that accounts for potential confounders at household, village, and district levels, we find pervasive effects of season-specific, five-year climate anomalies on multiple dimensions of household debt, particularly in arid and semi-arid areas. Most notably, temperature anomalies in the winter cropping season in arid and semi-arid areas are associated with increasing household indebtedness. We further find that climate change interacts with existing socioeconomic differences-caste and landholding in particular-to deepen both the size and the depth of indebtedness for rural households.

The global food system, and animal agriculture in particular, is a major and growing contributor to climate change, land system change, biodiversity loss, water consumption and contamination, and environmental pollution. The copious production and consumption of animal products are also contributing to increasingly negative public health outcomes, particularly in wealthy and rapidly industrializing countries, and result in the slaughter of trillions of animals each year. These impacts are motivating calls for reduced reliance on animal-based products and increased use of replacement plant-based products. However, our understanding of how the production and consumption of animal products, as well as plant-based alternatives, interact with important dimensions of human and environment systems is incomplete across space and time. This inhibits comprehensively envisioning global and regional food system transitions and planning to manage the costs and synergies thereof. We therefore propose a cross-disciplinary research agenda on future target-based scenarios for food system transformation that has at its core three main activities: (1) data collection and analysis at the intersection of animal agriculture, the environment, and societal well-being, (2) the construction of target-based scenarios for animal products informed by these new data and empirical understandings, and (3) the evaluation of impacts, unintended consequences, co-benefits, and trade-offs of these target-based scenarios to help inform decision-making.

Public and scientific consensus about climate change do not align. Problematically, higher scientific knowledge has been associated with lower acceptance of climate information among those with more conservative socio-political ideologies. Positive attitudes towards science can attenuate this effect. We investigated the association between (ESI) and decision-making with scientific evidence about climate policies. Participants rated support for 16 climate policies accompanied by weaker or stronger evidence. In study 1 ( = 503), higher ESI was associated with greater discernment between strongly and weakly evidenced climate policies, irrespective of worldview. In studies 2 ( = 402) and 3 ( = 600), an ESI intervention improved discrimination, and, in study 3, increased ESI specifically for hierarchical/individualistic participants. Unlike ESI, the link between scientific knowledge and evaluation of evidence was influenced by worldview. Increasing ESI might improve the evaluation of scientific evidence and increase public support for evidence-based climate policies.

In recent years, countries like France, UK, Germany, and Denmark have all carried out climate citizens' assemblies where a group of representatively selected citizens come together to discuss issues around climate politics and provide policy recommendations to decision-makers. The hope is that these deliberative-democratic innovations can circumvent the flaws of representational politics and help break the existing gridlock around climate politics. In this article, relying on the case of the Danish climate citizens' assembly that began its work in 2020, we argue that to truly realize the democratic potentials of climate citizens' assemblies, there is a need to think about how citizens' assemblies might come to multiply and proliferate in political spaces away from, or at least in addition to, those in and around the state, so they can become local drivers of democratic action and community empowerment. The argument is not that citizens' assemblies should give up on affecting the state and parliamentary politics altogether, but that we must be careful not to put too much faith in state institutions, and also look for spaces outside the state where the conditions for transformative change and democratic capacity-building currently appear more fecund. Drawing together these arguments, we offer what we call a more radical vision of the democratic potentials of climate citizens' assemblies, and provide some guidelines for what that would look like in practice.

Responding to climate change requires that people engage in different forms of climate citizenship. These span from individual consumption choices, to taking part in forms of collective action to steer the behaviour of governments and in the private sector. Here we analyse data from the Net Zero Diaries project to explore how attitudes to different forms of climate citizenship develop as people become more aware about the scale of societal change required to reach net zero carbon emissions by 2050. The Net Zero Diaries project was a deliberative mini-public, composed of 41 citizens broadly representative of the UK adult population, which convened over five months between 2021 and 2022 to debate the UK policies for reaching net zero emissions by 2050. We show that people identify government as the prime actor needed to drive the transition, but doubt that they will act due to a range of constraints vis-à-vis the public and private sector. This tension provides a novel explanation for why some people prioritise forms of individual and consumption focused climate citizenship, whilst also doubting the efficacy of such actions. We conclude by suggesting that efforts to drive more engaged forms of climate citizenship need to attend to underlying feelings about state efficacy, rather than focus on just how the issue of climate change is framed.

National Climate Change Risk Assessments (CCRAs) have a key role in informing priorities for adaptation policy but face significant challenges due to multiple facets of risk and adaptation. Issues are especially pronounced for meeting goals of environmental sustainability due to the complex dynamics of socio-ecological systems. In practice, a CCRA can therefore differ from its original conceptual blueprint. These challenges are explored from a knowledge systems perspective, focusing on the role of stakeholders/policymakers, risk descriptors, methods, evidence sources, and scientists. A UK case study evaluates recent developments (CCRA3) including identification of policy urgency through adaptation shortfalls and its application to the natural environment. Important science-policy issues are also highlighted regarding inclusion of opportunities, systemic risks, residual risks, and risk tolerance. A general conclusion is that CCRAs inevitably leave open questions which lead back to their evolving role in the science-policy interface. A knowledge systems perspective identifies CCRAs as open, adaptive, reflexive processes that help redefine interpretations of risk and adaptation, rather than just providing a specific policy-relevant product. This perspective identifies scope for progressive refinement of CCRAs to enhance collective science-policy adaptive capacity whilst also engaging wider society. For environmental sustainability, this open process can be used to iteratively redefine robust future pathways and system reference conditions that also better reflect evolving societal perceptions and tolerance on sustainability risk in the face of climate change.

Water regulation has contributed to the decline in Pacific salmon in British Columbia (Canada) despite attempts to manage reservoir operations to achieve operational requirements while meeting environmental needs to limit fish thermal stress. The ability of reservoir managers to meet these trade-offs in a changing climate is unknown. Here, we examine the reliability and vulnerability of the Nechako Reservoir to meet hydropower production commitments and fisheries needs under two projected Shared Socioeconomic Pathway scenarios (SSP2-4.5 and SSP5-8.5). While our findings are specific to the operation of the Nechako Reservoir, the issues that emerge are likely common to many reservoirs in areas where reservoir inflow regimes are currently snow-storage dominated. We found that projected changes in the timing of water availability have little to no influence on hydropower generation commitments. However, larger water releases will be required to avoid compromising reservoir safety, possibly endangering downstream fish habitat through scouring. Furthermore, the temperature of water released from the reservoir is projected to more frequently exceed a level, 20°C, that is detrimental to migrating sockeye salmon. Water released is subject to further warming as it travels towards the lower reaches of the Nechako River used by migrating salmon. Hence, there is a need to adapt reservoir operations to ensure reservoir safety and mitigate adverse effects on salmon habitat.

Effective climate change adaptation requires a thorough understanding of whether and how affected populations perceive climatic and environmental changes. Existing research has been inconclusive regarding the consistency of these perceptions compared to objective meteorological indicators. Moreover, no systematic comparison has been done for the perception of discrete environmental events such as floods or erosion. This study relies on novel panel survey data of approximately 1700 households residing along the Jamuna River in Bangladesh as well as on unique individual-level, satellite-based erosion data. It compares respondents' perceptions of environmental events, namely riverbank erosion, and three climate change indicators, specifically long-term temperature change and changes in precipitation during wet and dry seasons, to objective measurements using satellite imagery and climatic time-series data (CRU TS). I find that long-term temperature change is perceived more accurately than long-term changes in precipitation. Given that educational attainment and climate change literacy among the study population are low, this indicates that global temperature increases are felt even by remote populations who have never heard the term climate change. Erosion is strongly overestimated, especially by those respondents who had been personally affected by it. Since human behavior is guided by perceptions rather than objective data, this has important policy implications, underlining the importance of considering people's perceptions if the goal is to assist them in adapting to environmental changes.

Climate models predict meteorological variables for outdoor spaces. Nevertheless, most people work indoors and are affected by heat indoors. We present an approach to transfer climate projections from outdoors to climate projections of indoor air temperature () and thermal comfort based on a combination of indoor sensors, artificial neural networks (ANNs), and 22 regional climate projections. Human thermal comfort and measured by indoor sensors at 90 different workplaces in the Upper Rhine Valley were used as training data for ANN models predicting indoor conditions as a function of outdoor weather. Workplace-specific climate projections were modeled for the time period 2070-2099 and compared to the historical period 1970-1999 using the same ANNs, but ERA5-Land reanalysis data as input. It is shown that heat stress indoors will increase in intensity, frequency, and duration at almost all investigated workplaces. The rate of increase depends on building and room properties, the workplace purpose, and the representative concentration pathway (RCP2.6, RCP4.5, or RCP8.5). The projected increase of the mean air temperature in the summer (JJA) outdoors, by + 1.6 to + 5.1 K for the different RCPs, is higher than the increase in at all 90 workplaces, which experience on average an increase of + 0.8 to + 2.5 K. The overall frequency of heat stress is higher at most workplaces than outdoors for the historical and the future period. The projected hours of indoor heat stress will increase on average by + 379 h, + 654 h, and + 1209 h under RCP2.6, RCP4.5, and RCP8.5, respectively.

Today, a major challenge for climate science is to overcome what is called the "usability gap" between the projections derived fromclimate models and the needs of the end-users. Regional Climate Models (RCMs) are expected to provide usable information concerning a variety of impacts and for a wide range of end-users. It is often assumed that the development of more accurate, more complex RCMs with higher spatial resolution should bring process understanding and better local projections, thus overcoming the usability gap. In this paper, I rather assume that the credibility of climate information should be pursued together with two other criteria of usability, which are salience and legitimacy. Based on the Swiss climate change scenarios, I study the attempts at meeting the needs of end-users and outline the trade-off modellers and users have to face with respect to the cascade of uncertainty. A conclusion of this paper is that the trade-off between salience and credibility sets the conditions under which RCMs can be deemed adequate for the purposes of addressing the needs of end-users and gearing the communication of the projections toward direct use and action.

The usability gaps between climate information producers and users have always been an issue in climate services. This study aims to tackle the gap for rice farmers in Bangladesh by exploring the potential value of tailored agronomic monsoon onset definitions. Summer rice is primarily cultivated under rainfed conditions, and farmers rely largely on monsoon rainfall and its onset for crop establishment. However, farmers' perception of the arrival of sufficient rains does not necessarily coincide with meteorological definitions of monsoon onset. Therefore, localized agronomic definitions of monsoon onset need to be developed and evaluated to advance in the targeted actionable climate forecast. We analyzed historical daily rainfall from four locations across a north-south gradient in Bangladesh and defined dynamic definitions of monsoon onset based on a set of local parameters. The agronomic onset definition was evaluated in terms of attainable yields simulated by a rice simulation model compared to results obtained using conventional meteorological onset parameters defined by the amount of rainfall received and static onset dates. Our results show that average simulated yields increase up to 7 - 9% and probabilities of getting lower yields are reduced when the year-to-year varying dynamic onset is used over the two drier locations under fully rainfed conditions. It is mainly due to earlier transplanting dates, avoiding the impact of drought experienced with early monsoon demise. However, no yield increases are observed over the two wetter locations. This study shows the potential benefits of generating "localized and translated" climate predictions.

This paper analyzes the effectiveness of agriculture-led versus non-agriculture-led development strategies under climate-induced economic uncertainty. Utilizing Malawi as a case study, we introduce the application of Stochastic Dominance (SD) analysis, a tool from decision analysis theory, and compare the two strategies in the context of weather/climate-associated economic uncertainty. Our findings suggest that an agriculture-led development strategy consistently surpasses its non-agriculture-led antagonist in poverty and undernourishment outcomes across almost all possible weather/climate scenarios. This underscores that, despite increasing exposure of the entire economy to weather/climate uncertainty, agriculture-led development remains the optimal strategy for Malawi to reduce poverty and undernourishment. The study also endorses the broader use of SD analysis in policy planning studies, promoting its potential to integrate risk and uncertainty into policymaking.

As Arctic sea ice continues to retreat, the seasonally navigable Arctic expected by mid-century or earlier is likely to facilitate the growth of polar maritime and coastal development. Here, we systematically explore the potentials for opening of trans-Arctic sea routes across a range of emissions futures and multi-model ensembles on daily timescales. We find a new Transpolar Sea Route in the western Arctic for open water vessels starting in 2045 in addition to the central Arctic corridor over the North Pole, with its frequency comparable to the latter during the 2070s under the worst-case scenario. The emergence of this new western route could be decisive for operational and strategic outcomes. Specifically, the route redistributes transits away from the Russian-administered Northern Sea Route, lowering the navigational and financial risks and the regulatory friction. Navigational risks arise from narrow straits that are often icy choke points. Financial risks arise from the substantial interannual sea ice variability and associated uncertainty. Regulatory friction arises from Russian requirements imposed under the Polar Code and Article 234 of the UN Convention on the Law of the Sea. These imposts are significantly reduced with shipping route regimes that enable open water transits wholly outside Russian territorial waters, and these regimes are revealed most accurately using daily ice information. The near-term navigability transition period (2025-2045) may offer an opportunity for maritime policy evaluation, revision, and action. Our user-inspired evaluation contributes towards achieving operational, economic and geopolitical objectives and serves the goal of planning a resilient, sustainable, and adaptive Arctic future.

Landslides are an important natural hazard in mountainous regions. Given the triggering and preconditioning by meteorological conditions, it is known that landslide risk may change in a warming climate, but whether climate change has already affected individual landslide events is still an open question, partly owing to landslide data limitations and methodological challenges in climate impact attribution. Here, we demonstrate the substantial influence of anthropogenic climate change on a severe event in the southeastern Alpine forelands with some estimated 952 individual landslides in June 2009. Our study is based on conditional event attribution complemented by an assessment of changes in atmospheric circulation. Using this approach, we simulate the meteorological event under observed and a range of counterfactual conditions of no climate change and explicitly predict the landslide occurrence probability for these conditions. We find that up to 10%, i.e., 95 landslides, can be attributed to climate change.

The geographic distribution of natural ecosystems is affected by both climate and cropland. Discussions of future land use/land cover usually focus on how cropland expands and displaces natural vegetation especially as climate change impacts become stronger. Less commonly considered is the direct influence of climate change on natural ecosystems simultaneously with cropland incursion. We combine a natural vegetation model responsive to climate with a cropland allocation algorithm to assess the relative importance of climate change compared to cropland incursion. Globally, the model indicates that climate change drives larger gains and losses than cropland incursion. For example, in the Amazonian rainforests, more than one sixth of the forest area could be lost due to climate change with cropland playing virtually no role. Our findings suggest that policies to protect specific ecosystems may be undercut by climate change and that localized analyses that fully account for the impacts of a changing climate on natural vegetation and agriculture are necessary to formulate policies that preserve natural ecosystems over the long term.

Moving beyond technocratic approaches to climate action, climate justice articulates a paradigm shift in how organizations think about their response to the climate crisis. This paper makes a conceptual contribution by exploring the potential of this paradigm shift in higher education. Through a commitment to advancing transformative climate justice, colleges and universities around the world could realign and redefine their priorities in teaching, research, and community engagement to shape a more just, stable, and healthy future. As inequitable climate vulnerabilities increase, higher education has multiple emerging opportunities to resist, reverse, and repair climate injustices and related socioeconomic and health disparities. Rather than continuing to perpetuate the concentration of wealth and power by promoting climate isolationism's narrow focus on technological innovation and by prioritizing the financial success of alumni and the institution, colleges and universities have an opportunity to leverage their unique role as powerful anchor institutions to demonstrate climate justice innovations and catalyze social change toward a more equitable, renewable-based future. This paper explores how higher education can advance societal transformation toward climate justice, by teaching climate engagement, supporting impactful justice-centered research, embracing non-extractive hiring and purchasing practices, and integrating community-engaged climate justice innovations across campus operations. Two climate justice frameworks, Green New Deal-type policies and energy democracy, provide structure for reviewing a breadth of proposed transformational climate justice initiatives in higher education.

Parameterization and parameter tuning are central aspects of climate modeling, and there is widespread consensus that these procedures involve certain subjective elements. Even if the use of these subjective elements is not necessarily epistemically problematic, there is an intuitive appeal for replacing them with more objective (automated) methods, such as machine learning. Relying on several case studies, we argue that, while machine learning techniques may help to improve climate model parameterization in several ways, they still require expert judgment that involves subjective elements not so different from the ones arising in standard parameterization and tuning. The use of machine learning in parameterizations is an art as well as a science and requires careful supervision.

We investigate whether communication strategies that portray climate change as a nonlinear phenomenon provoke increases in laypeople's climate change risk perceptions. In a high-powered, preregistered online experiment, participants were exposed to linear or nonlinear predictions of future temperature increases that would be expected if global greenhouse gas emissions were not reduced. We hypothesized that the type of climate change portrayal would impact perceptions of qualitative risk characteristics (catastrophic potential, controllability of consequences) which would, in turn, affect laypeople's holistic risk perceptions. The results of the study indicate that the type of climate change portrayal did not affect perceptions of risk or other social-cognitive variables such as efficacy beliefs. While participants who were exposed to a nonlinear portrayal of climate change perceived abrupt changes in the climate system as more likely, they did not perceive the consequences of climate change as less controllable or more catastrophic. Notably, however, participants who had been exposed to a linear or nonlinear portrayal of climate change were willing to donate more money to environmental organizations than participants who had not been presented with a climate-related message. Limitations of the present study and directions for future research are discussed.

We summarise the contributions to the Topical Collection on quality of climate information for adaptation decision support. Based on these contributions, we draw some further lessons for the development of high-quality climate information and services, bridging between a "credibility-first" paradigm (exemplified by top-down information provision from systematic downscaling or impact projections) and a "salience-first" paradigm (exemplified by user-led tailored information products or storylines) by looking to identify their respective strengths and use cases. We emphasise that a more nuanced collective understanding of the dimensions of information quality in climate information and services would be beneficial to users and providers and ultimately support more confident and effective climate adaptation decisions and policy-making.