Article activity feed

  1. eLife

    Author Response

    Reviewer #1 (Public Review):

    Wang et al. adapt a new statistical framework on a multi-site multi-year database to investigate the effects of environmental variables on the temporal stability of plant communities and biomass productivity in Chinese grassland. The authors show with several lines of evidence that 1. the temporal stability of the region is due to spatial asynchrony of community dynamics, 2. this stability relies on dominant species, but less so on other community metrics, and 3. reductions, but also increasing variability in water availability reduces the stability of the system, with rather important future consequences to humans living in the region.

    A significant strength of the ms lies in solid statistics. Wang et al. apply to a real dataset a new framework (and two pathways, i.e., community-level vs. population-level metrics) with formulas the authors develop (in special for dominant species). Additionally, they provide a summary/test of the effect of environmental variables in shaping regional stability with SEM analyses. This new framework may be one that the larger ecological and ecosystem academic communities, interested in temporal changes of ecological processes across large spatial scales, are looking for.

    Thank you for your positive assessment of our study. We have tried to incorporate all your suggestions in the revised manuscript.

    Reviewer #2 (Public Review):

    The authors analyse an impressive dataset of field data collected across Inner Mongolian Grasslands to test theory concerning the mechanisms promoting temporal stability of plant biomass.

    Overall, the analyses seem solid, and the paper is based on strong theory, but the overall message is diluted by a large number of different analyses, making the analysis, results, and interpretation confusing in several places.

    The unfocused nature of the analysis and presentation of the results makes it difficult to evaluate whether the authors achieve their aims, and whether their results support the conclusions. My general impression is that they do, but the number of different analyses, supplementary results, etc., really complicates the narrative and interpretation.

    The paper is an interesting test of theory, and a practical test of the theory outlined in a previous paper (Wang et al.) could be a real asset to anyone aiming to explore the mechanisms promoting temporal stability across scales. The dataset too is a large and potentially useful one.

    That said, without a clearer narrative and streamlined set of analyses, it is difficult to interpret the potential impact of this work - which is a shame, because clearly the work put in was considerable. By focusing on only a few key analyses and results, interpretability and potential impact could be much improved.

    Thank you very much for your constructive suggestions. We have revised the paper throughout to increase the focus and readability. To help readers to easily understand stability theory and analysis as used in this study, we added Box 1 which combines the theoretical framework with hypotheses, especially about proposed effects of species diversity on stability, and provides a glossary of terms. In addition, we summarize our approach at the end of the Introduction section and in the Results section first present the analysis using all species and then the analysis using only dominant species. Furthermore, to focus on our main findings, we removed detailed analyses (but deliver them as summary files together with dataset and R script to a third-party data deposition). Finally, we added calculations of CV and synchrony across spatial scales to the Methods section.

  2. eLife

    Evaluation Summary:

    Wang et al. adapt a new statistical framework for a multi-site multi-year data set to investigate the effects of environmental variables on the temporal stability of plant communities and biomass productivity in Chinese grassland communities. This new framework may well turn out to be one that the larger ecological and ecosystem academic communities, interested in temporal changes of ecological processes across large spatial scales, have been looking for.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    Wang et al. adapt a new statistical framework on a multi-site multi-year database to investigate the effects of environmental variables on the temporal stability of plant communities and biomass productivity in Chinese grassland. The authors show with several lines of evidence that 1. the temporal stability of the region is due to spatial asynchrony of community dynamics, 2. this stability relies on dominant species, but less so on other community metrics, and 3. reductions, but also increasing variability in water availability reduces the stability of the system, with rather important future consequences to humans living in the region.

    A significant strength of the ms lies in solid statistics. Wang et al. apply to a real dataset a new framework (and two pathways, i.e., community-level vs. population-level metrics) with formulas the authors develop (in special for dominant species). Additionally, they provide a summary/test of the effect of environmental variables in shaping regional stability with SEM analyses. This new framework may be one that the larger ecological and ecosystem academic communities, interested in temporal changes of ecological processes across large spatial scales, are looking for.

  4. eLife

    Reviewer #2 (Public Review):

    The authors analyse an impressive dataset of field data collected across Inner Mongolian Grasslands to test theory concerning the mechanisms promoting temporal stability of plant biomass.

    Overall, the analyses seem solid, and the paper is based on strong theory, but the overall message is diluted by a large number of different analyses, making the analysis, results, and interpretation confusing in several places.

    The unfocused nature of the analysis and presentation of the results makes it difficult to evaluate whether the authors achieve their aims, and whether their results support the conclusions. My general impression is that they do, but the number of different analyses, supplementary results, etc., really complicates the narrative and interpretation.

    The paper is an interesting test of theory, and a practical test of the theory outlined in a previous paper (Wang et al.) could be a real asset to anyone aiming to explore the mechanisms promoting temporal stability across scales. The dataset too is a large and potentially useful one.

    That said, without a clearer narrative and streamlined set of analyses, it is difficult to interpret the potential impact of this work - which is a shame, because clearly the work put in was considerable. By focusing on only a few key analyses and results, interpretability and potential impact could be much improved.

  5. Version 1 published on bioRxiv