The dynamics of phosphorus (P) in the environment is important for regulating nutrient cycles in natural and managed ecosystems and an integral part in assessing biological resilience against environmental change. Organic P (P_o) compounds play key roles in biological and ecosystems function in the terrestrial environment being critical to cell function, growth and reproduction.

Purpose: Accurately assessing soil organic carbon (SOC) content is vital for ecosystem services management and addressing global climate challenges. This study undertakes a comprehensive bibliometric analysis of global estimates for SOC using remote sensing (RS) and machine learning (ML) techniques. It showcases the historical growth and thematic evolution in SOC research, aiming to amplify the understanding of SOC estimation themes and provide scientific support for climate change adaptation and mitigation. Materials and Methods: Employing extensive literature database analysis, bibliometric network analysis, and clustering techniques, the study reviews 1,761 articles on SOC estimation using RS technologies and 490 articles on SOC employing both RS and ML technologies. Results and Discussion: The results indicate that satellite-based RS, particularly the Landsat series, is predominant for estimation of SOC and other associated studies, with North America, China, and Europe leading in evaluations with Africa is having low evaluations adopting RS technology. Trends in the research demonstrate an evolution from basic mapping to advanced topics such as carbon (C) sequestration, complex modeling, and big data utilization. Thematic clusters from co-occurrence analysis suggest the interplay between technology development, environmental surveys, soil properties, and climate dynamics. Conclusion: The study highlights the synergy between RS and ML, with advanced ML techniques proving to be critical for accurate SOC estimation. These findings are crucial for comprehensive ecosystem SOC estimation, informed environmental management and strategic decision-making.

The exchange rate of inorganic phosphorus (P) between the soil solution and solid phase, also known as soil solution P turnover, is essential for describing the kinetics of bioavailable P. While soil solution P turnover (K_m) can be determined by tracing radioisotopes in a soil–solution system, few studies have done so. We believe that this is due to a lack of understanding on how to derive K_m from isotopic exchange kinetic (IEK) experiments, a common form of radioisotope dilution study. Here, we provide a derivation of calculating K_m using parameters obtained from IEK experiments. We then calculated K_m for 217 soils from published IEK experiments in terrestrial ecosystems, and also that of 18 long-term P fertilizer field experiments. Analysis of the global compilation data set revealed a negative relationship between concentrations of soil solution P and K_m. Furthermore, K_m buffered isotopically exchangeable P in soils with low concentrations of soil solution P. This finding was supported by an analysis of long-term P fertilizer field experiments, which revealed a negative relationship between K_m and phosphate-buffering capacity. Our study highlights the importance of calculating K_m for understanding the kinetics of P between the soil solid and solution phases where it is bioavailable. We argue that our derivation can also be used to calculate soil solution turnover of other environmentally relevant and strongly sorbing elements that can be traced with radioisotopes, such as zinc, cadmium, nickel, arsenic, and uranium.