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Title: Plant traits alone are poor predictors of ecosystem properties and long-term ecosystem functioning
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  1. Open-source projects do not exist in a vacuum. They benefit from reusing other projects and themselves are being reused by others, creating complex networks of interdependencies, i.e., software ecosystems. Therefore, the sustainability of projects comprising ecosystems may no longer by determined solely by factors internal to the project, but rather by the ecosystem context as well. In this paper we report on a mixed-methods study of ecosystem-level factors affecting the sustainability of open-source Python projects. Quantitatively, using historical data from 46,547 projects in the PyPI ecosystem, we modeled the chances of project development entering a period of dormancy (limited activity) as a function of the projects' position in their dependency networks, organizational support, and other factors. Qualitatively, we triangulated the revealed effects and further expanded on our models through interviews with project maintainers. Results show that the number of project ties and the relative position in the dependency network have significant impact on sustained project activity, with nuanced effects early in a project's life cycle and later on.
  2. Understanding the processes that influence and control carbon cycling in Arctic tundra ecosystems is essential for making accurate predictions about what role these ecosystems will play in potential future climate change scenarios. Particularly, air–surface fluxes of methane and carbon dioxide are of interest as recent observations suggest that the vast stores of soil carbon found in the Arctic tundra are becoming more available to release to the atmosphere in the form of these greenhouse gases. Further, harsh wintertime conditions and complex logistics have limited the number of year-round and cold season studies and hence too our understanding of carbon cycle processes during these periods. We present here a two-year micrometeorological data set of methane and carbon dioxide fluxes that provides near-continuous data throughout the active summer and cold winter seasons. Net emission of methane and carbon dioxide in one of the study years totalled 3.7 and 89 g C m−2 a−1 respectively, with cold season methane emission representing 54% of the annual total. In the other year, net emission totals of methane and carbon dioxide were 4.9 and 485 g C m−2 a−1 respectively, with cold season methane emission here representing 82% of the annual total – a larger proportionmore »than has been previously reported in the Arctic tundra. Regression tree analysis suggests that, due to relatively warmer air temperatures and deeper snow depths, deeper soil horizons – where most microbial methanogenic activity takes place – remained warm enough to maintain efficient methane production whilst surface soil temperatures were simultaneously cold enough to limit microbial methanotrophic activity. These results provide valuable insight into how a changing Arctic climate may impact methane emission, and highlight a need to focus on soil temperatures throughout the entire active soil profile, rather than rely on air temperature as a proxy for modelling temperature–methane flux dynamics.« less