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Abstract Cooling energy demand is sensitive to urban form and socioeconomic characteristics of cities. Climate change will impact how these characteristics influence cooling demand. We use random forest machine learning methods to analyze the sensitivity of cooling demand in Chicago, IL, to weather, vegetation, building type, socioeconomic, and control variables by dividing census tracts of the city into four groups: below-Q1 income–hot days; above-Q1 income–hot days; below-Q1 income–regular days; and above-Q1 income–regular days. Below-Q1 census tracts experienced an increase in cooling demand on hot days while above-Q1 census tracts did not see an increase in demand. Weather (i.e. heat index and wind speed) and control variables (i.e. month of year, holidays and weekends) unsurprisingly had the most influence on cooling demand. Among the variables of interest, vegetation was associated with reduced cooling demand for below-Q1 income on hot days and increased cooling demand for below-Q1 income on regular days. In above-Q1 income census tracts building type was the most closely associated non-weather or control variable with cooling demand. The sensitivity of cooling demand for below-Q1 income census tracts to vegetation on hot days suggests vegetation could become more important for keeping cities cool for low-income populations as global temperatures increase. This result further highlights the importance of considering environmental justice in urban design. 

Society is confronted by interconnected threats to ecological sustainability. Among these is the devastation of forests by destructive non-native pathogens and insects introduced through global trade, leading to the loss of critical ecosystem services and a global forest health crisis. We argue that the forest health crisis is a public-good social dilemma and propose a response framework that incorporates principles of collective action. This framework enables scientists to better engage policymakers and empowers the public to advocate for proactive biosecurity and forest health management. Collective action in forest health features broadly inclusive stakeholder engagement to build trust and set goals; accountability for destructive pest introductions; pooled support for weakest-link partners; and inclusion of intrinsic and nonmarket values of forest ecosystems in risk assessment. We provide short-term and longer-term measures that incorporate the above principles to shift the societal and ecological forest health paradigm to a more resilient state. Expected final online publication date for the Annual Review of Phytopathology, Volume 61 is September 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

Thin-film lithium-niobate-on-insulator (LNOI) has emerged as a superior integrated-photonics platform for linear, nonlinear, and electro-optics. Here we combine quasi-phase-matching, dispersion engineering, and tight mode confinement to realize nonlinear parametric processes with both high efficiency and wide wavelength tunability. On a millimeter-long, Z-cut LNOI waveguide, we demonstrate efficient ( $1900\pm <\#comment/>500\mathrm{\%<\#comment/>}{\mathrm{W}}^{-<\#comment/>1}{\mathrm{c}\mathrm{m}}^{-<\#comment/>2}$) and highly tunable ( $-<\#comment/>1.71\mathrm{n}\mathrm{m}/\mathrm{K}$) second-harmonic generation from 1530 to 1583 nm by type-0 quasi-phase-matching. Our technique is applicable to optical harmonic generation, quantum light sources, frequency conversion, and many other photonic information processes across visible to mid-IR spectral bands.