There is an urgent need for climate change–informed decision-making and adaptation actions for cultural heritage. Challenges arise in incorporating and balancing multiple considerations, including robust understandings of climate change vulnerability, the objectives of current management paradigms, the need for meaningful engagement, the risk of maladaptation, and constrained resources to implement. We offer a conceptual framework and guide to integrate climate science and cultural heritage management to produce a range of adaptation actions for cultural heritage, categorized as Acclimate, Dislocate, Abandon, Protect, and Tell the Story (ADAPT) approaches. The ADAPT framework is intended to aid archaeologists and other cultural heritage managers in developing and evaluating possible adaptation actions that directly respond to findings from climate change vulnerability assessments, critically integrating management postures and constraints, and coproducing climate change adaptations with Indigenous rightsholders and community stakeholders.

The Arbaeen ceremony is the largest annual mass gathering in the world, attracting millions of Muslim pilgrims each year. However, the event takes place during the summer in Iraq, coinciding with extreme heat and dust storms. Climate change hazards, such as heat waves and dust storms, can have destructive effects on human health, leading to increased mortality and the spread of various diseases. This manuscript recommends measures to stakeholders in emergency or public health management to develop a preventive plan for the Arbaeen ceremony. These measures include improving planning and risk assessment, enhancing capacities, reducing vulnerabilities, increasing knowledge and awareness among pilgrims, developing communication and support systems, ensuring compliance with safety protocols, and regularly assessing evacuation routes. Implementing these measures will contribute to ensuring the safety and well-being of participants during the Arbaeen ceremony in the years ahead.

We review shoreline monitoring methodologies used by members of the South Carolina Department of Natural Resources (SCDNR) Archaeology, Geology, and Wildlife Biology teams from February 2021 to December 2022 on Pockoy Island in Charleston County, South Carolina, USA. Our project objectives were to better understand the driving forces behind the landward movement of the shoreline (transgression), to apply new understanding to the rate of shoreline erosion of the island that directly impacts the Pockoy Island Shell Ring Complex (38CH2533), and to establish best practice for future community science monitoring efforts. Each member of our team used a different shoreline monitoring methodology (a nested methodology approach). Multiple unoccupied aerial vehicle (UAV)-derived orthoimagery datasets, on-the-ground transect measurements, and Arrow Gold real-time kinematic (RTK) unit measurements have been collected monthly following significant storms or king (perigean) tide events. Moving forward, the erosion transect approach tested within this project will serve as the foundation for community science monitoring at heritage at-risk sites in South Carolina. In this article, we introduce initial efforts in establishing a community science monitoring program in South Carolina that will influence future research, land management, and policy, and we propose how our research might be adapted for other sites at risk.

Ixodes ricinus, commonly known as the castor bean tick and sheep tick, is a significant vector of various diseases, such as tick-borne encephalitis and Lyme borreliosis. Owing to climate change, the distribution and activity of I. ricinus are expected to increase, leading to an increase in the number of diseases transmitted by this species. Most distribution models and ecological niche models utilize macroclimate datasets such as WorldClim or CHELSA to map the distribution of disease-transmitting ticks. However, microclimatic factors are crucial for the activity and survival of small arthropods. In this study, an ecological niche modelling approach was used to assess the climatic suitability of I. ricinus using both microclimatic and macroclimatic parameters. A Mixed model was built by combining parameters from the Soiltemp (microclimate) and Wordclim (macroclimate) databases, whereas a Macroclimate model was built with the CHELSA dataset. Additionally, future suitabilities were projected via the macroclimate model under the SSP3-7.0 and SSP5-8.5 scenarios. Macroclimate and Mixed models showed similar distributions, confirming the current distribution of I. ricinus. The most important climatic factors were seasonality, annual temperature range, humidity and precipitation. Future projections suggest significant expansion in northern and eastern Europe, with notable declines in southern Europe.

Michelia lacei W.W. Smith, a magnolia species categorized as Endangered on the IUCN Red List, is subject to severe disturbance. We carried out field surveys and a review of literature records to present a detailed description of the current status of M. lacei. We then predicted the potential distribution of M. lacei under different climatic scenarios based on 60 occurrence records (53 recorded during our field surveys and 7 earlier records) and 19 bioclimatic variables from the WorldClim database. We selected 18 locations and four bioclimatic variables for model training. Temperature seasonality and annual temperature range were the most influential variables for predicting the potential distribution of the species. We used MaxEnt to model distribution under current climate conditions and four Shared Socioeconomic Pathway scenarios in four future time periods to determine the effects of future climate change on the habitat suitable for the species. We predict areas of moderately and highly suitable habitat will gradually decrease over time. We recommend increased in situ and ex situ conservation efforts to mitigate this habitat decline and protect populations of M. lacei.

Atmospheric chemical reactions play an important role in air quality and climate change. While the structure and dynamics of individual chemical reactions are fairly well understood, the emergent properties of the entire atmospheric chemical system, which can involve many different species that participate in many different reactions, are not well described. In this work, we leverage graph-theoretic techniques to characterize patterns of interaction (“motifs”) in three different representations of gas-phase atmospheric chemistry, termed “chemical mechanisms.” These widely used mechanisms, the master chemical mechanism, the GEOS-Chem mechanism, and the Super-Fast mechanism, vary dramatically in scale and application, but they all generally aim to simulate the abundance and variability of chemical species in the atmosphere. This motif analysis quantifies the fundamental patterns of interaction within the mechanisms, which are directly related to their construction. For example, the gas-phase chemistry in the very small Super-Fast mechanism is entirely composed of bimolecular reactions, and its motif distribution matches that of an individual bimolecular reaction well. The larger and more complex mechanisms show emergent motif distributions that differ strongly from any specific reaction type, consistent with their complexity. The proposed motif analysis demonstrates that while these mechanisms all have a similar design goal, their higher-order structure of interactions differs strongly and thus provides a novel set of tools for exploring differences across chemical mechanisms.