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Research on issues such as adapting to rapid environmental change should include indigenous and local people in developing more robust and inclusive diagnoses and responses. Various studies indicate that such projects may face challenges. Researchers touch on these in papers where they reflect on their own work, but to a lesser extent in their empirical papers. Based on interviews with, and articles by, a varied sample of 15 researchers who work with local or indigenous peoples around the globe, I identified the challenges they face and how they deal with them. Thematic analysis of interview transcripts revealed eight themes: (1) external pressure, (2) engaging local people, (3) relevance of projects, (4) prior negative experiences, (5) cultural, historical, and geographical differences, (6) language challenges, (7) payment for participation, and (8) diverging epistemic cultures. Respondents' statements in all themes contain reflections displaying care, consideration, or responsibility for the projects and the local people they involve. This links the challenges with everyday ethics. Analysis of scientific papers written by the respondents showed that they hardly write about the challenges they face, whereby neither local participants nor other readers of these texts are actively informed by and engaged in critical-reflective discussions about the challenges arising during the research and the strategies used to deal with them. The research community has a responsibility to remedy this shortcoming: in their papers, authors should discuss the main challenges faced and develop, describe, and promulgate strategies for dealing with them. [ABSTRACT FROM AUTHOR]

The functioning of Mediterranean coastal waters is deeply affected not only by global environmental changes (e.g., global warming, climate change) but also by improvements in sewage treatment as required by the European Water Framework Directive. These changes affect nutrient concentrations and cycling, and primary production. The present paper presents the time series analysis (2005–2020) of stable isotope ratios (hereafter δ13C and δ15N), elemental (C and N), and biochemical compositions (proteins, lipids, carbohydrates) within the 300–500 µm zooplankton size fraction from bimonthly monitoring samples (0–55 m) collected in the Bay of Marseille (NW-Mediterranean Sea). The zooplankton seasonality was mostly related with the dynamic of proxies of phytoplankton biomass and nutrients in the system. In spring, protein content and energy increased and δ15N of zooplankton decreased; in late spring, lipid and carbohydrate content peaked; and in late summer, δ13C increased. At the interannual scale, major changes in the zooplankton biochemical and isotopic composition have occurred since 2009. Lipid content decreased while protein and stable isotope ratios increased. These shifts were concomitant with changes in the nutrient concentrations, nutrient stoichiometry, and particulate organic matter concentrations. The changes in biochemical composition led to an increase of energy content from 2011, but the total quantity of energy available to higher trophic positions remained stable because of a reduction in biomass. The variations of the zooplankton stable isotopes and biochemical compositions can be indicative of changes in individual biochemistry (energy allocation) and/or in the zooplankton community (changes in relative abundance of lipid-rich vs protein-rich species). [ABSTRACT FROM AUTHOR]

The spatiotemporal distribution of industrial heat sources (IHS) is an important indicator for assessing levels of energy consumption and air pollution. Continuous, comprehensive, dynamic monitoring and publicly available datasets of global IHS (GIHS) are lacking and urgently needed. In this study, we built the first long-term (2012–2021) GIHS dataset based on the density-based spatiotemporal clustering method using multi-sources remote sensing data. A total of 25,544 IHS objects with 19 characteristics are identified and validated individually using high-resolution remote sensing images and point of interest (POI) data. The results show that the user's accuracy of the GIHS dataset ranges from 90.95% to 93.46%, surpassing other global IHS products in terms of accuracy, omission rates, and granularity. This long-term GIHS dataset serves as a valuable resource for understanding global environmental changes and making informed policy decisions. Its availability contributes to filling the gap in GIHS data and enhances our knowledge of global-scale industrial heat sources. [ABSTRACT FROM AUTHOR]