the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Oct 2025
Norway spruce shows stronger growth sensitivity and weaker intrinsic water-use efficiency response than Scots pine under increasing water limitation in southern Finland
Abstract. Boreal forests, essential for carbon sequestration and multiple ecosystem services, face increasing pressure from climate-induced water stress. This study investigates how increasing water limitation affects growth and intrinsic water-use efficiency (iWUE) in Scots pine (Pinus sylvestris L) and Norway spruce (Picea abies (L.) Karst) in southern Finland. We combined site-level tree-ring data on basal area increment (BAI) and carbon isotope discrimination (Δ13C) from three sites per species, representing contrasting soil moisture conditions (dry versus wet), with regional growth indices from the Finnish National Forest Inventory (NFI) spanning 1990–2022. Our results show that forests in southern Finland have become increasingly water-limited over the past decade. Site-level and NFI based growth decline post-2015 is pronounced in Norway spruce, indicating strong sensitivity to water limitation, while Scots pine exhibits only marginal reductions beginning around 2010. Δ13C analyses indicate increased stomatal regulation in Scots pine and, to a lesser extent, in Norway spruce after 2015, consistent with intensifying water limitations. iWUE derived from tree ring Δ13C increased more steeply Scots pine than in Norway spruce, suggesting weaker physiological adjustment in spruce to rising atmospheric moisture demand. Interannual variability in both growth and iWUE for both species was strongly correlated with the standardized precipitation-evapotranspiration index (SPEI) and vapor-pressure-deficit (VPD). Linear mixed-effects models confirm that Norway spruce growth sensitivity to VPD and SPEI intensified after 2015, whereas Scots pine showed consistent Δ13C responses and relatively buffered growth. These findings highlight the growing vulnerability of boreal conifers, particularly Norway spruce, to intensifying water stress. Sensitivity varied by soil type: Scots pine was more responsive on organic soils, while Norway spruce was more vulnerable on mineral soils. Species- and site-specific differences in water-use strategies underscore the importance of adaptive forest management, including species choice, site matching, and silvicultural planning, to support forest resilience and productivity under warmer, drier climate.
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- RC1: 'Comment on egusphere-2025-4994', Andreas Lundgren, 30 Oct 2025
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RC2: 'Comment on egusphere-2025-4994', Anonymous Referee #2, 19 Jan 2026
I thank the authors for their thoughtfully written paper and for EGU's BG journal and community for the opportunity to review this manuscript. This manuscript investigates long-term growth and eco-physiological responses of Norway spruce and Scots pine in southern Finland, using Growth Indices (GI) alongside basal area increment (BAI), intrinsic water-use efficiency (iWUE), and carbon isotope discrimination (d13C) using Finnish NFI as well as independent observational data. The authors aim to identify temporal trends in growth and to attribute species-specific differences in these trajectories to underlying physiological responses to increasing water limitation. The study addresses an important question in forest ecology and climate change, and the integration of NFI growth metrics with independent field observations and isotopic indicators is a clear strength. This study is well suited for the journal and will be of particular interest to the readership of EGU Biogeosciences. However, several aspects of the statistical treatment and interpretation (particularly related to uncertainty, sampling imbalance, and effect-size interpretation) require clarification or revision before the conclusions can be considered robust.
Specific Comments
Figure 1: This is an effective figure that clearly illustrates the increasing vulnerability of the study region to climate change. I have one stylistic suggestion: for panels in which the color scale includes zero (Fig. 1B, 1E), a diverging color scheme may be more appropriate. In the current perceptually uniform, non-diverging scheme, values near zero are difficult to distinguish from potentially meaningful positive or negative deviations.Equation 1: In the text (e.g., line 206), Equation 1 is referenced as the calculation for VPD, but the equation itself is labeled as VPsat, which is a distinct quantity. This discrepancy should be clarified here and in line 206.
Lines 153–170: Figure 2 shows a substantial decline in the number of sampled trees after approximately 2005. This section of the Methods (“Finnish NFI data”) should acknowledge and explain this pattern. Additional context on the history and design of this dataset may be warranted, particularly given the apparent temporal and spatial unevenness in sampling effort (see comments below). Further comments later in the methods should explain how this is addressed to prevent statistical artifacts.
Line 173: These sites are described as “experimental,” but the study is observational and does not involve experimental manipulation. I suggest rephrasing this terminology accordingly.
Line 320: Were predictors mean-centered only (y−$\bar{y}$), or standardized using z-scores (y−$\bar{y}$)/sd(y)? It would be nice to be extremely clear here since this is a decision that meaningfully impact the interpretation of results presented later.
Lines 335–345: Figure 2 indicates a marked decline in the number of sampled trees after approximately 2005, as well as a strong imbalance in sampling effort between soil types (with roughly five times more trees sampled on mineral soils than on organic soils). However, the plots in Figure 2 (and the analyses in Section 3.1 that rely on them) appear to ignore this fact, or otherwise be based on simple annual mean estimates of GI.
This raises statistical concerns. NFI data are inherently samples from a population, and the authors here treat annual estimates as unbiased and known values. Collapsing the data to annual means implicitly treats these values as known without error, thereby ignoring uncertainty arising from finite and declining sample sizes. This issue becomes increasingly severe in later years (e.g., post-2010), when sample sizes are smallest and sampling bias is most likely. Consequently, inter-annual variability and heterogeneous uncertainty among sites are likely underestimated, and differences between soil types may be overstated.
Moreover, ad perhaps most importantly, because these periods of reduced and imbalanced sampling coincide with the most recent portion of the time series (i.e. the part of the time series were change point detection algorithms suggested a break point), they may exert disproportionate leverage on trend estimation and change-point detection, potentially leading to spurious or overconfident inferences. Under these conditions, the change-point analyses and associated p-values are difficult to interpret as valid. Explicitly accounting for sampling uncertainty—e.g., through hierarchical modeling or another form of uncertainty propagation—would substantially strengthen the robustness of the results.
At a minimum, the authors should provide uncertainty estimates around these trends, visualize this uncertainty in the time-series plots, and propagate uncertainty from the fitted models into the subsequent change-point analyses rather than relying solely on point estimates.
Lines 413–422 and Figure 6: The Results section would benefit from a clearer discussion of the biological relevance of the estimated effect sizes. For example, given the fitted models, what does a one-"unit change" (as written in Figure 6) in VPD or SPEI correspond to in terms of changes in BAI or d13C, and are these effects large, moderate, or negligible from a biological perspective?
Lines 465–470: Given the concerns about potential statistical artifacts in Figure 2 (see above), together with the relatively modest and somewhat opaque regression results in Figures 5 and 6, the evidence presented here that Norway spruce has been more strongly impacted by rising VPD appears limited. While the alignment with independent plot-level data and previous studies (e.g., Lagergren and Lindroth, 2002; Lévesque et al., 2013) is noted, this section as currently written provides only weak additional support beyond existing literature.
Additionally, this section appears to rely heavily on statistical significance, with relatively little discussion of the biological significance of the estimated effects (see also my previous comment). With p-values and $R^2$ values reported but limited interpretation of effect magnitudes, it is difficult for the reader to assess whether statistically significant results correspond to biologically meaningful changes.
Suggestions for spelling and grammar
Note: I've removed comments here that were already pointed out by another referee.Line 320
"Climate predictors and years were **centered** before"Citation: https://doi.org/10.5194/egusphere-2025-4994-RC2
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I thoroughly enjoyed reading the manuscript and thank the authors for this contribution. Please see the attached PDF for comments, questions for the authors, and suggestions for improvements.