paper_2022.bib

@article{Pallandt_BG_2022,
  author = {Pallandt, M. M. T. A. and Kumar, J. and Mauritz, M. and Schuur, E. A. G. and Virkkala, A.-M. and Celis, G. and Hoffman, F. M. and G\"ockede, M.},
  title = {Representativeness assessment of the pan-Arctic eddy covariance site
network and optimized future enhancements},
  journal = {Biogeosciences},
  volume = {19},
  year = {2022},
  number = {3},
  pages = {559--583},
  url = {https://bg.copernicus.org/articles/19/559/2022/},
  doi = {10.5194/bg-19-559-2022},
  note = {\url{https://doi.org/10.5194/bg-19-559-2022}}
}
@article{Simmonds_DSJ_2022,
  author = {Simmonds, MB and Riley, WJ and Agarwal, DA and Chen, X and Cholia, S and Crystal-Ornelas, R and Coon, ET and Dwivedi, D and Hendrix, VC and Huang, M and Jan, A and Kakalia, Z and Kumar, J and Koven, CD and Li, L and Melara, M and Ramakrishnan, L and Ricciuto, DM and Walker, AP and Zhi, W and Zhu, Q and Varadharajan, C.},
  title = {{{Guidelines For Publicly Archiving Terrestrial Model
Data to Enhance Usability, Intercomparison, and Synthesis}}},
  journal = {Data Science Journal},
  pages = {1--18},
  year = {2022},
  doi = {https://doi.org/10.5334/dsj-2022-003},
  volume = {In press},
  note = {\url{https://doi.org/10.5334/dsj-2022-003}}
}
@article{Novick_GCB_2022,
  author = {Novick, Kimberly A and Metzger, Stefan and Anderegg, William R.L. and Barnes, Mallory and Cala, Daniela S. and Guan, Kaiyu and Hemes, Kyle S. and Hollinger, David Y and Kumar, Jitendra and Litvak, Marcy and Lombardozzi, Danica and Normile, Caroline P. and Oikawa, Patty and Runkle, Benjamin R.K. and Torn, Margaret and Wiesner, Susanne},
  title = {Informing Nature-based Climate Solutions for the U.S. with the best-available science},
  journal = {Global Change Biology},
  volume = {n/a},
  number = {n/a},
  pages = {},
  keywords = {climate adaptation, climate mitigation, ecosystem carbon cycling, Natural climate solutions, net-zero},
  doi = {https://doi.org/10.1111/gcb.16156},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.16156},
  eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.16156},
  abstract = {Abstract Nature-based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem-scale carbon fluxes, e.g., by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state-of-the-art remote sensing products and land-surface models are not yet being widely used to inform NbCS policy making or implementation. As a result, there is a critical mismatch between the point- and tree- scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policy making. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. We outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem-scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre-existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach.}
}