the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Local environmental context drives heterogeneity of early succession dynamics in alpine glacier forefields
Bradley Z. Carlson
Anaïs Zimmer
Sophie Vallée
Antoine Rabatel
Edoardo Cremonese
Gianluca Filippa
Cédric Dentant
Christophe Randin
Andrea Mainetti
Erwan Roussel
Simon Gascoin
Dov Corenblit
Philippe Choler
Abstract. Glacier forefields have long provided ecologists with a model to study patterns of plant succession following glacier retreat. While plant survey-based approaches applied along chronosequences provide invaluable information on plant communities, the “space-for-time” approach assumes environmental uniformity and equal ecological potential across sites and does not account for spatial variability in initial site conditions. Remote sensing provides a promising avenue for assessing plant colonisation dynamics using a so-called “real-time” approach. Here, we combined 36 years of Landsat imagery with extensive field sampling along chronosequences of deglaciation for eight glacier forefields in the south-western European Alps to investigate the heterogeneity of early plant succession dynamics. Based on the two complementary and independent approaches, we found strong variability in the time lag between deglaciation and colonisation by plants and in subsequent growth rates, and in the composition of early plant succession. All three parameters were highly dependent on the local environmental context, i.e., local vegetation surrounding the forefields and energy availability linked to temperature and snowmelt gradients. Potential geomorphological disturbance did not emerge as a strong predictor of succession parameters, perhaps due to insufficient spatial resolution of predictor variables. Notably, elapsed time since deglaciation showed no consistent relationship to plant assemblages, i.e., we did not identify a consistent order of successional species across forefields as a function of time. Overall, both approaches converged towards the conclusion that early plant succession is not stochastic as previous authors have suggested but rather deterministic. We discuss the importance of scale in deciphering the unique complexity of plant succession in glacier forefields and provide recommendations for improving botanical field surveys and using Landsat time series in glacier forefields systems. Our work demonstrates complementarity between remote sensing and field-based approaches for both understanding and predicting future patterns of plant succession in glacier forefields.
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Arthur Bayle et al.
Status: final response (author comments only)
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RC1: 'Comment on egusphere-2022-1164', Thomas Wagner, 29 Nov 2022
GENERAL COMMENT
The well written manuscript provides valuable insights in the vegetation succession of glacier forefields. While the remote sensing part and the respective analysis is appropriate and the methods and encountered problems are comprehensively described, I have a number of critical comments regarding the evaluation and assessment of the vegetation.
SPECIFIC COMMENTS
- Succession dynamics in glacier forefields
In the discussion, the authors state that their results confirm that the time lag between deglaciation and plant establishment is dependent on the vegetation in the vicinity. However, I think that falls somewhat short, as the establishment of vegetation is generally also influenced by topographic factors and modulated by avalanches and debris flow etc. Larger and more frequent debris flows will clearly reduce (or reverse) recruitment even under equal seed pressure. Further higher elevations are not only accompanied with a less dense vegetation but also with generally lower establishment rates (due to climatic conditions). Although this does hardly weaken the results, this should be included into the discussion.
In this context, it would be also interesting to see the overall turnover of pixels from vegetation to unvegetated for each glacier (in addition to % vegetated, Fig. 5). This could give an idea of the debris flows and habitat loss typical for each glacier.
- Plant assemblages and succession dynamics
This is the part I do have some problems with. The authors use about 15 plots per time period of deglaciation. Due to the different shape of the respective zones, for some of their sites the plots are far from each other while for other sites the plots lie quite close to each other. Hence spatial autocorrelation is likely, which should be considered when applying test.
Another problem is the small plot size. 2x2m plots may be sufficient for lichens, but for higher vegetation they may be too small. Many rare species will be overlooked as they will only be detected using larger plots. Further, a minimum distance between plots may be associated with spatial autocorrelation, particularly when we assume, that colonization is dependent on the seed pressure of the surrounding vegetation.
Further, for example, while one Pinus mugo in a small plot might contribute considerable to the vegetation cover a small Saxifraga might be neglected. Hence correlating vegetation cover derived from remote sensing with a pixel representing ~30x30m and the vegetation survey on a 2x2m plot might be difficult.
For their NMDS the authors use all the plots of a site together, regardless of the period of deglaciation they represent. Hence, different successional stages are combined into one community. Inferences about different succession is consequently not possible, particularly if succession occurs at different rates for the individual glaciers.
I would expect a separate consideration here or, if this is not possible only the communities after a certain time.
Further, instead of a simple envfit, I would prefer to see a Mantel test for the respective environmental variables. Here the authors could also account for the spatial autocorrelation of the plots by simply including the plot coordinates (in UTM, meter) into the distance matrix.
The results of the NMDS in terms of community composition (vegetation associated with the respective glacier forefield) should be discussed briefly.
- Methods general
For future research that does not rely on historic data, the use of UAV data should be discussed, as they provide high resolution just-in-time data (e.g. Woellner & Wagner, Healy & Kahn ...)
Woellner, R., & Wagner, T. C. (2019). Saving species, time and money: Application of unmanned aerial vehicles (UAVs) for monitoring of an endangered alpine river specialist in a small nature reserve. Biological conservation, 233, 162-175.
Healy, S. M., & Khan, A. L. (2022). Mapping Glacier Ablation With a UAV in the North Cascades: A Structure-from-Motion Approach. Frontiers in Remote Sensing, 57.
TECHNICAL COMMENTS
L114: heterogeneity in what context? please elaborate
L145: please also provide the resolution of these data
L253 and thereafter: Instead of "local vegetation" I would prefer the term "vegetation cover in the vicinity", to make clear that you do not look at the vegetation composition (which I expected, when I read the term first).
L292: Excluding species with less than 5 occurrences might be a problem, as this will exclude plots in early successional stages.
L297: Please provide number of Iterations and dimensions for NMDS
L299: see specific comments: better use Mantel tests instead of vector fitting
L350: Please consider, that trees and shrubs have a generally higher seed rain and higher dispersal distances!
L379: I suppose this should be Fig. 3
L342ff: Please provide a table with all vegetation data (supplementary material). This is necessary to see the vegetation cover in context of the respective community.
L363: I would chose another term instead of heterogeneity here, as for me, heterogeneity suggests that the species composition differs
Caption Fig. 1: Please include to what chronosequence the colored lines relate to; I presume red is 0 Years, Blue 10 years ...
L376ff: Describing the succession should include naming the relevant species and how community composition changes over time
Citation: https://doi.org/10.5194/egusphere-2022-1164-RC1 - AC2: 'Reply on RC1', Arthur Bayle, 23 Mar 2023
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CC1: 'Comment on egusphere-2022-1164', Danilo Godone, 21 Feb 2023
Dear authors,
concerning the investigation of deglaciation and primary succession drivers, I suggest, if I may, checking the work by Garbarino et al. (2010) entitled "Patterns of larch establishment following deglaciation of Ventina glacier, central Italian Alps", published in Forest Ecology and Management. The paper focuses only on larch ecesis in deglaciated areas, in the forefield of Ventina glacier (Val Malenco, central Italian Alps), uses aerial photograms interpretation and tries to summarize several influencing factors of the phenomenon and can be considered, to a certain extent, a precursor of your research which copes with the issue in a broader context.
Thanks for your kind attention.
Citation: https://doi.org/10.5194/egusphere-2022-1164-CC1 -
AC1: 'Reply on CC1', Arthur Bayle, 04 Mar 2023
Dear Dr. Godone,
Thank you for your interest in our research and for sharing your paper with us. I have read it with great interest and found it to be quite compelling. I regret that I did not come across it during my own research, as it appears to be highly relevant to our work. We have since incorporated it into our discussion.
Thank you once again for bringing this to my attention.
Best regards.
Citation: https://doi.org/10.5194/egusphere-2022-1164-AC1
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AC1: 'Reply on CC1', Arthur Bayle, 04 Mar 2023
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RC2: 'Comment on egusphere-2022-1164', Jana Eichel, 02 Mar 2023
The authors present an impressive and novel study quantifying the role of environmental heterogeneity on vegetation succession in glacier forelands. The study very nicely combines classical field with novel remote sensing approaches, making it possible to compare vegetation succession across eight glacier forelands in the Alps. From the technical side, the authors dealt in my opinion very well with many difficulties arising in the study’s context, such as assigning a continuous deglaciation age, problems with Landsat data quality etc. The manuscript is very well written and was a pleasure to read.
I only have a few general comments and some specific comments (see below):
When comparing your real-time remote sensing approach with a chronosequence approach, your time scale is limited to <40 years by the availability of Landsat data. So maybe the time since deglaciation becomes more meaningful on longer timescales (centuries) than you investigated and the chronosequence approach, despite all its large limitations, is still needed to investigate the complete vegetation succession since the end of the Little Ice Age. This needs to be mentioned and discussed.
In addition, I see the use of snow free-growing degree days somewhat critical, as you could only determine them for one season (2019). Over a period of nearly 40 years in a changing climate, I would expect that snow cover and growing degree days changed over and between the years, which would have affected vegetation succession. Thus, the reliability of this key indicator needs to be discussed. Looking at your NMDS and pairwise correlation results, it appears that SF-GDD is closely related to elevation anyway, so elevation of the glacier forelands might be a similarly important and more reliable factor for vegetation succession onset and dynamics.
Specific comments:
l. 57: Space-for-time approaches: This method does not necessarily rely on the position of plant surveys to estimate time since deglaciation, but can also be done using known terrain ages from glacier stages maps, dating etc. (cf. Matthews, 1992, "The ecology of recently deglaciated terrain"). Please revise.
l. 213: “Thus, we applied the same method as in Bayle et al. (2022)”. Please add details which method exactly and for which purpose.
l. 222: Add “The” before “complete workflow”
l. 237: add “-“ after intra
l. 315 ff: If I understand your interpretation of Figure 4 correctly, you are looking at when the mean NDVImax per terrain age class crosses the NDVI threshold? Because the error bars seem to imply that some pixels already crossed that threshold earlier than stated here in the text? If this is the case, please clarify in the text that you are talking about mean NDVImax.
l. 336 “Floristic plots are representative of glacier forefields vegetation dynamics“. Wouldn’t it be the other way around that your Landsat detection matches what is happening at the ground in the plots?
l. 395: “dynamic” in which sense? Vegetation colonization? Please specify.
l. 451: “periglacial”
l. 460: “that” instead of “the”
l. 470: I would not term natural disturbances such as geomorphic processes in glacier forelands “erratic”. They do follow a certain pattern in time during paraglacial adjustment (e.g. Ballantyne et al., 2002; Eichel et al. 2018) and geomorphic processes can have a certain magnitude-frequency distribution. So those geomorphic disturbances are not erratic but can follow certain patterns.
Figure 3: Which data is exactly shown ? Changes of all pixels in one glacier foreland? Changes of one pixel at the site of the coordinates given? Please provide more information in the figure caption.
Fig. 10: Missing reference to Fig. 10 in results section.
Table 1: Coarse debris is given as an indicator for instability – is this correct or would it more be an indicator for stability?
Terminology: different terms are used to refer to the interactions between ecologic and geomorphic processes, e.g. bio-geomorphic and eco-geomorphological. I would suggest you choose one term to use throughout the manuscript, most commonly used is in my opinion biogeomorphic (ecogeomorphology was first defined for fluvial systems).
Citation: https://doi.org/10.5194/egusphere-2022-1164-RC2 - AC3: 'Reply on RC2', Arthur Bayle, 23 Mar 2023
Arthur Bayle et al.
Arthur Bayle et al.
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