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Abstract Global climate during the Holocene was relatively stable compared to the late Pleistocene. However, evidence from lacustrine records in South America suggests that tropical latitudes experienced significant water balance variability during the Holocene, rather than quiescence. For example, a tight coupling between insolation and carbonate δ¹⁸O records from central Andean lakes (e.g., Lakes Junín, Pumacocha) suggest water balance is tied directly to South American summer monsoon (SASM) strength. However, lake carbonate δ¹⁸O records also incorporate information about temperature and evaporation. To overcome this ambiguity, clumped and triple oxygen isotope records can provide independent constraints on temperature and evaporation. Here, we use clumped and triple oxygen isotopes to develop Holocene temperature and evaporation records from three central Andean lakes, Lakes Junín, Pumacocha, and Mehcocha, to build a more complete picture of regional water balance (P–E). We find that Holocene water temperatures at all three lakes were stable and slightly warmer than during the latest Pleistocene. These results are consistent with global data assimilations and records from the foothills and Amazon basin. In contrast, evaporation was highly variable and tracks SASM intensity. The hydrologic response of each lake to SASM depends greatly on the physical characteristics of the lake basin, but they all record peak evaporation in the early to mid‐Holocene (11,700 to 4,200 years BP) when regional insolation was relatively low and the SASM was weak. These results corroborate other central Andean records and suggest synchronous, widespread water stress tracks insolation‐paced variability in SASM strength. 

Abstract Background The use of systems science methodologies to understand complex environmental and human health relationships is increasing. Requirements for advanced datasets, models, and expertise limit current application of these approaches by many environmental and public health practitioners. Methods A conceptual system-of-systems model was applied for children in North Carolina counties that includes example indicators of children’s physical environment (home age, Brownfield sites, Superfund sites), social environment (caregiver’s income, education, insurance), and health (low birthweight, asthma, blood lead levels). The web-based Toxicological Prioritization Index (ToxPi) tool was used to normalize the data, rank the resulting vulnerability index, and visualize impacts from each indicator in a county. Hierarchical clustering was used to sort the 100 North Carolina counties into groups based on similar ToxPi model results. The ToxPi charts for each county were also superimposed over a map of percentage county population under age 5 to visualize spatial distribution of vulnerability clusters across the state. Results Data driven clustering for this systems model suggests 5 groups of counties. One group includes 6 counties with the highest vulnerability scores showing strong influences from all three categories of indicators (social environment, physical environment, and health). A second group contains 15 counties with high vulnerability scores driven by strong influences from home age in the physical environment and poverty in the social environment. A third group is driven by data on Superfund sites in the physical environment. Conclusions This analysis demonstrated how systems science principles can be used to synthesize holistic insights for decision making using publicly available data and computational tools, focusing on a children’s environmental health example. Where more traditional reductionist approaches can elucidate individual relationships between environmental variables and health, the study of collective, system-wide interactions can enable insights into the factors that contribute to regional vulnerabilities and interventions that better address complex real-world conditions.