Landscapes influence precipitation via the water vapor and energy fluxes they generate. Biologically active landscapes also generate aerosols containing microorganisms, some being capable of catalyzing ice formation and crystal growth in clouds at temperatures near 0 °C. The resulting precipitation is beneficial for the growth of plants and microorganisms. Mounting evidence from observations and numerical simulations support the plausibility of a bioprecipitation feedback cycle involving vegetated landscapes and the microorganisms they host. Furthermore, the evolutionary history of ice nucleation‐active bacteria such as Pseudomonas syringae supports that they have been part of this process on geological time scales since the emergence of land plants. Elucidation of bioprecipitation feedbacks involving landscapes and their microflora could contribute to appraising the impact that modified landscapes have on regional weather and biodiversity, and to avoiding inadvertent, negative consequences of landscape management.

The temperature sensitivity of soil organic carbon decomposition is critical for predicting future climate change because soils store 2-3 times the amount of atmospheric carbon. Of particular controversy is the question, whether temperature sensitivity differs between young or labile and old or more stable carbon pools. Ambiguities in experimental methodology have so far limited corroboration of any particular hypothesis. Here, we show in a clear-cut approach that differences in temperature sensitivity between young and old carbon are negligible. Using the change in stable isotope composition in transitional systems from C3 to C4 vegetation, we were able to directly distinguish the temperature sensitivity of carbon differing several decades in age. This method had several advantages over previously followed approaches. It allowed to identify release of much older carbon, avoided un-natural conditions of long-term incubations and did not require arguable curve-fitting. Our results demonstrate that feedbacks of the carbon cycle on climate change are driven equally by young and old soil organic carbon.

For decades, drop-freezing instruments have contributed to a better understanding of biological ice nucleation and its likely implications for cloud and precipitation development. Yet, current instruments have limitations. Drops analysed on a cold stage are subject to evaporation and potential contamination. The use of closed tubes provides a partial solution to these problems, but freezing events are still difficult to be clearly detected. Here, we present a new apparatus where freezing in closed tubes is detected automatically by a change in light transmission upon ice development, caused by the formation of air bubbles and crystal facets that scatter light. Risks of contamination and introduction of biases linked to detecting the freezing temperature of a sample are then minimized. To illustrate the performance of the new apparatus we show initial results of two assays with snow samples. In one, we repeatedly analysed the sample (208 tubes) over the course of a month with storage at +4 °C, during which evidence for biological ice nucleation activity emerged through an increase in the number of ice nucleators active around −4 °C. In the second assay, we indicate the possibility of increasingly isolating a single ice nucleator from a precipitation sample, potentially determining the nature of a particle responsible for a nucleation activity measured directly in the sample. These two seminal approaches highlight the relevance of this handy apparatus for providing new points of view in biological ice nucleation research.