Ecological Response of Forest Vegetation Communities to Snow Damage: A Meta-Analysis

Abstract

Damage caused by snowfall can result in broken crowns and trunks and even lead to the uprooting of forest trees. Damage or death of forest trees creates forest gaps and alters overall forest demographics, but predicting the exact nature and influence of this damage remains challenging. In general, the effects of various biotic and abiotic factors on snow damage remain understudied. To address this gap in knowledge, we conducted a meta-analysis of existing literature, ultimately screening 38 manuscripts that describe 142 plant species. Our findings indicate that snow damage significantly reduced annual litterfall, Leaf Area Index, canopy density, abundance, and area at breast height when considering plant communities. However, snow damage also tended to significantly increase Shannon’s Diversity Index, Simpson’s Diversity Index, Pielou’s Evenness Index, and diameter at breast height. In addition, at the population level, snow damage was found to significantly reduce density, abundance, and annual litterfall while significantly increasing diameter at breast height. Further, the response of different forest vegetation community characteristics to snow damage is significantly influenced by factors such as forest type, elevation, slope, and aspect.

1. Introduction

Disturbances affect the structure and ecological processes of an ecosystem, altering the availability of resources over time or across space [1]. Disturbances can generally be categorized as either natural or anthropogenic in origin. Natural disturbances include events such as wind, fire, hail, drought, snow, earthquakes, landslides, or the introduction of new pests or diseases. Anthropogenic disturbances encompass activities like deforestation, logging, conservation, grazing, mining, tourism, and industrial pollution [2,3,4,5]. Disturbances are key factors influencing community structure and dynamics, playing an important role in species coexistence and biodiversity maintenance [6]. The type and intensity of disturbances impact communities and biodiversity in different ways, further affecting ecosystem stability and functioning [7,8,9,10]. Large-scale natural disturbances, such as snowstorms, fires, and hurricanes, can cause extensive direct damage to the canopy and branches of forest trees, affecting the community structure and ecological processes. For example, disturbances can create or extend forest gaps, thereby altering the availability of understory light resources, which, in turn, affects plant regeneration [11,12]. In addition, disturbances can affect individual trees, leading to the formation of patches of varying sizes and altering the structure of the original pattern, which subsequently influences competition between tree species and the environmental conditions in which they grow.

The intermediate disturbance hypothesis (IDH) suggests a pattern of biodiversity-disturbance relationships that form a single-peaked curve, where localized species diversity and likelihood of species survival are highest under intermediate intensities of disturbance or in the middle stages of recovery during post-disturbance community recovery. This hypothesis has now been widely confirmed in numerous cases [13,14,15,16]. However, a large number of studies have also refuted the existence of a significant relationship between disturbance and diversity, supporting that disturbance does not maintain species diversity [17,18,19]. In the context of rising global temperatures and an increase in the frequency of extreme weather events, most available research focuses on frequent disturbances. However, there is a notable lack of research examining how extreme disturbances, such as snow damage, affect the mechanisms of biodiversity maintenance in forests.

Disturbance has a clear impact on the distribution and dynamics of vegetation populations in forests [20,21,22,23]. A considerable body of research highlights the importance of forest gaps in maintaining biodiversity. These forest gaps provide the conditions that allow shade-intolerant, colonizing species to thrive, while species with insufficient adaptive capacities may experience a reduction in their distribution area. As a consequence, the continued presence of patchily distributed forest gaps leads to corresponding changes in the reproduction patterns of species with varying levels of adaptation, thereby influencing the spatial demography of forest populations. Another way in which disturbance can influence forest demography is by changing the resources provided by trees, particularly through changes in the rhythm and composition of litterfall. For example, Laigle et al. (2021) investigated the direct and indirect effects of anthropogenic disturbances on polytrophic soil communities in boreal forests, demonstrating that disturbances have an effect on leaf litter decomposition [24]. Similarly, Morffi-Mestre et al. (2020) assessed the litter production in semi-deciduous dry forests at different successional stages in Yucatan, Mexico, at different time scales over a five-year period [25]. They concluded that litter production may increase in response to climatic changes such as decreasing precipitation, increasing temperatures, and more frequent hurricanes. In another study, Cheng et al. (2020) investigated the effects of typhoon disturbance on the litterfall in coniferous and broadleaf forests in central Taiwan, finding that typhoon disturbance on litterfall in coniferous and broadleaf forests in central Taiwan, finding that typhoons produced more litterfall in coniferous forests compared to broadleaf forest [26]. As the frequency and intensity of extreme weather events continue to rise due to global warming, studying the effects of disturbances on forest vegetation communities becomes increasingly important.

Snow damage is a common manifestation of disturbances during extreme cold temperatures, which refers to the physical damage sustained by trees and forests during or after a heavy snowfall [27]. When the snow accumulation on the canopy exceeds the tree’s capacity to bear the load, specific parts of the tree may fail, resulting in the breaking of branches and the canopy, and in severe cases the bending or breaking of stems, and in some cases the uprooting or death of the tree altogether [28,29,30,31].

The impact of snow damage on forest species diversity has been debated, with some studies suggesting it remains stable, while others indicate that diversity is dramatically influenced [32,33,34]. This suggests that different forest types have different levels of resistance and resilience to snow disturbances, enabling them to maintain ecosystem diversity after varying degrees of natural disturbances [35,36]. Further, we are increasingly aware that the influence of snow damage may vary among species and between individuals of variable radial scales and heights, which potentially leads to directional changes in community composition [32]. For example, it is well known that different tree species have different sensitivities to snow damage. Generally, trees with a larger diameter at breast height (DBH) and a higher height tend to be more resistant to snow damage. Since dominant species are an important part of the forest community, accounting for the majority of the number of individuals and playing a crucial role in forest structure and function, some studies have shown that the response of these species to extreme climatic events can provide valuable insights into how forest ecosystems as a whole respond to such disturbances [37].

In general, differences in the response of different species to snow may result in the replacement of more susceptible species with those that are relatively less susceptible, leading to overall community change as forest demography adapts to the stress of snow damage [38]. Cold temperatures or freezing can also cause significant seedling mortality, with variable recovery based on habitat and topographic factors. Additionally, the creation of forest gaps due to snow damage can also have a significant impact on the growth and placement of new seedlings [39,40,41]. Deadwood caused by snow damage can also contribute to natural regeneration in a number of ways. On the one hand, some studies have shown that seedlings germinating in deadwood grow better than those germinating directly on the ground, and on the other hand, deadwood can regulate temperature, moisture, and nutrients to create a microtopographic environment favorable to natural regeneration [42,43,44]. As stated, litter production is influenced by snow damage, and litter is an important characterization of nutrient cycling in forest ecosystems. It has been established that litter production tends to be lower in years with significant snow disturbance compared to normal years, although some studies have shown that snow damage leads to increased litter production by damaging the canopy and branches [45,46].

The different contexts of independent studies on how snow damage affects forest vegetation communities may lead to findings that are influenced by different confounding factors. It remains unclear whether different explanatory variables lead to different changes in forest vegetation communities. Therefore, we conducted a meta-analysis to reveal the integrated response of forest vegetation communities of different forest types to snow damage. In this study, we quantified the effects of snow damage on forest vegetation community characteristics at both the community and population levels, encompassing a total of 1111 cases from 38 studies. In this meta-analysis, we sought to analyze the role of different explanatory variables (forest type, snowfall duration, elevation, mean annual temperature, and mean annual precipitation) in moderating the disturbance effects of snow damage. This study intends to answer the following questions: (1) Does snow damage significantly affect different ecological indicators of forest vegetation at the community and population levels? (2) Can the intermediate disturbance hypothesis be validated in the effects of snow damage on forest plant community diversity, i.e., that forest plants have the highest diversity under moderately intense snow damage disturbances and in the intermediate stages of forest recovery after snow damage? (3) Are the effects of snow damage on forest vegetation constrained by other factors?

2. Materials and Methods

2.1. Data Collection

We conducted our search for experimental data on the effects of snow damage on forest vegetation communities by carefully reviewing and screening ‘gray’ literature (journals and dissertations) published between 2000 and 2024. In order to improve the completeness and scientific validity of the literature used in the meta-analysis and to meet the reproducibility standards, we strictly followed the PRISMA 2020 process for the screening of papers [47] (Figure S1). The databases we used include the China National Knowledge Infrastructure (CNKI), Web of Science, Scopus, and Google Scholar. We used two sets of keyword combinations: (1) (Snow-Disaster OR Snow-Damage OR Snow-hazard OR Snow-Calamity OR Ice-and-Snow-Disaster OR Ice-and-Snow-Calamity OR ice-damage OR ice-disaster OR ice-hazard OR Blizzard-Disaster OR Freezing-disaster) AND (Tree-species OR Shrub OR Herbaceous OR Tree-cover OR Deciduous-forest OR Taiga OR Coniferous-forest OR Mixed-forest OR Broadleaf-forest); (2) (“Snow Disaster” OR “Snow Damage” OR “Snow hazard” OR “Snow Calamity” OR “Ice and Snow Disaster” OR “Ice and Snow Calamity” OR “ice damage” OR “ice disaster” OR “ice hazard” OR “Blizzard Disaster” OR “Freezing disaster”) AND “Forest” AND (“Litter” OR “Leaf litter” OR “Forest litter” OR “Plant detritus” OR “Organic litter”). Based on the above keyword combinations, we searched several databases (CNKI, Web of Science, Scopus, and Google Scholar) and exported all relevant information into a single document. Initially, we identified 2876 sources, and after removing duplicates, we were left with 2405 sources. In the next step, we filtered this body of literature by excluding studies that did not meet our criteria. (1) the study had to be carried out in forest ecosystems, not in other types (grasslands, wetlands, urban, etc.); (2) the study had to analyze the impacts of the snow damage on the vegetation at the community and population levels; (3) post-disaster surveys and damage assessments were not included; (4) literature in languages other than Chinese and English was excluded. Following a preliminary review of the abstracts, we identified 178 relevant papers. A further detailed review of the full texts allowed us to narrow down the literature pool based on the following criteria: (1) The studies had to be field experiments, including both observational experiments in which natural snow damage occurred and experiments simulating snow damage; (2) the studies had to include both experimental and control groups, either as before and after controls in the same vegetation community or as comparisons between snow-disturbed and undisturbed areas (both areas have to be in the same forest to ensure similar environmental conditions); (3) the study must measure at least one of the key variables in the community and population of vegetations (Figure S2); (4) it must be possible to extract the sample size from the literature as well as the mean values of the indicators described in (3). In addition, we increased our literature search to include studies focusing on particular forest covers disturbed by snowstorms, even if they lacked pre-snowstorm data as a control. In such cases, we supplemented the control group by using long-term stationary forest monitoring sample plots studied in these literatures. We collected the relevant literature on these plots before the snowstorm from the database mentioned earlier, ensuring that the research contents and requirements matched those studied in the literature of the experimental group. In the end, a total of 38 sources of information on snow-damaged disturbances to forest vegetation were eligible for inclusion in the meta-analysis, including 423 community-level cases and 688 population-level cases from 75 study sites, mainly in eastern North America, Europe, and southern China (Figure 1).

2.2. Data Extraction

To estimate average sample size, we extracted the number of sample plots from both experimental and control groups across 38 papers. Subsequently, we estimated mean values for specific population or community metrics reported in these manuscripts. If the data was given in tables or text, we copied it directly. For data displayed in charts, we extracted it using a tool called Web Plot Digitizer (https://apps.automeris.io/wpd/ accessed on 1 December 2023) [48]. Different studies presented different response variables. For our meta-analysis, we included a response variable only if we determined it appeared in at least two or more studies. Additionally, we further identified and extracted a number of other descriptive variables that we assumed might influence the impact of snow damage. For example, the type of forest was determined by reviewing the description of the study area in the literature. We categorized the different cases of forests into different types according to four different criteria: origin, stand, life form, and physiognomy (Table S1). The geographic location (longitude and latitude) of each case was also extracted from the study area in the literature. If this information was not unavailable, we obtained it from Google Maps (https://www.google.com/maps/ accessed on 1 December 2023). Similarly, the elevation, slope, and aspect of each site were either extracted directly from the literature or derived using the DEM dataset GMTED2010 (https://www.usgs.gov/coastal-changes-and-impacts/gmted2010 accessed on 1 December 2023) and processed with ArcMap10.2 [49,50]. For the purpose of this analysis, we classified the slopes of the study sites in all cases into shady and sunny slopes (Table S2). According to the China Meteorological Administration (CMA), we use the snowfall converted to precipitation over a specified time period as the basis for classifying the intensity of snow damage. We test the intermediate disturbance hypothesis by analyzing the pattern of biodiversity under different intensities of snow disturbance. Precipitation during snow events at each study site was extracted from the CHIRPS precipitation dataset (https://www.chc.ucsb.edu/data/chirps accessed on 1 December 2023) using ArcMap 10.2 based on latitude and longitude [51]. In addition, we supplemented precipitation data at high latitudes using the TerraClimate precipitation dataset (https://www.climatologylab.org/terraclimate.html accessed on 1 December 2023) [52]. We have developed a reasonable precipitation rating scale, divided into three levels, to quantify the intensity of snow damage (Table S3). Each species described in the case was standardized based on the plantlist program package using R 4.3.2 software, and the corresponding family and genus were extracted. e (In addition, the following data were collected from the literature for meta-analysis: (1) authors’ information; (2) year of publication; (3) title of the literature; (4) type of literature and source of publication; (5) name of the study area; (6) sample information; (7) the time of snow damage and the time of activities in the experimental and control groups were used to characterize the duration of recovery and to quantify the duration of recovery by dividing the number of years of recovery into different classes (Table S4); and (8) type of experiment, whether it is a control of the same vegetation community before and after snow damage or control between a snow-disturbed community and a non-snow-disturbed community. I would consider a table including this information).

2.3. Data Analysis

We estimated the effect value of a parameter using a response ratio (RR). The effect value can reflect the degree of difference between the snow-disturbed and non-snow-disturbed groups, pointing out the degree of impact of snow damage on forest vegetation communities [53]. Here, we used RR to assess the effects of snow disturbance on forest vegetation communities. The result is then back-transformed into percent change to represent the relative difference between snow-disturbed and snow-undisturbed communities:

$$y=\left(RR-1\right)\times 100\%=\left({\displaystyle \frac{Y_e}{Y_c}}-1\right)\times 100\%$$

(1)

where Y_e and Y_c are the mean values of ecological indicators for snow-disturbed and non-snow-disturbed communities, respectively. If there is no overlap between the 95% confidence intervals of the effect values in different cases, they are considered significantly different. If the effect value is greater than 0, it indicates that the snow damage disturbance has a positive effect on the forest vegetation community; if it is less than 0, it indicates a negative effect; and if it is equal to 0, it has no significant effect. If the 95% confidence interval of the effect value does not intersect with 0, it indicates a significant effect [54,55].

Calculation of within-case variance: $v$. Within-case variance, denoted as $v$, reflects the level of variation in the degree of impact of the snow damage on the vegetation community, i.e., a smaller variance indicates greater precision in the results obtained for that case [56]. Here we use $v$ to assess the precision of different cases of snow-damaged disturbed vegetation communities:

$$v={\displaystyle \frac{N_e{N}_c}{N_e+N_c}}$$

(2)

where N_e represents the sample size of snow-disturbed communities, and N_c represents the sample size of communities without snow-disturbed communities [57,58].

Calculation of the cumulative effect value: the cumulative effect value, denoted as $\overline{y}$, can indicate the overall outcome cases overall, i.e., whether a snowstorm had an effect on a forest vegetation community. The calculation of cumulative effect values depends on the choice of model. In this study, we chose a random-effects model rather than a fixed-effects model because ecological studies often exhibit real variation in effects between studies, in addition to random sampling variation [59]. We used the Restricted-Maximum-Likelihood Method (REML) to calculate the variance ${\tau }^2$ between cases [60]. Because of the variation that exists between cases, the total variation for a single case is equal to the within-case plus the between-case variance, with the latter being the same for all cases. After determining the model, we used the following method to calculate the total variance $v^{\ast }$ and weights $\omega$ for individual cases and the cumulative effect value $\overline{y}$ for all cases overall:

$$v^{\ast }=v+{\tau }^2$$

(3)

$$w={\displaystyle \frac{1}{v^{\ast }}}={\displaystyle \frac{1}{v^{\ast }+{\tau }^2}}$$

(4)

$$\overline{y}={\displaystyle \frac{{\sum }_{i=1}^k{w}_i{y}_i}{{\sum }_{i=1}^k{w}_i}}$$

(5)

$$SE=\sqrt{{\displaystyle \frac{1}{{\sum }_{i=1}^k{w}_i}}}$$

(6)

where $i$ represents the case $i$, $k$ represents the total number of cases, ${\omega }_i$ represents the weight of the case $i$, and $y_i$ represents the effect value of the case $i$. The 95% confidence interval of the cumulative effect value indicates that the ecological response of forest vegetation communities to snow damage is significant (if the p-value is less than 0.05).

Calculation of heterogeneity between cases caused by a factor:$Q_m$. To determine which factors contributed to the differences in effect values between cases, we assessed the heterogeneity of effect values based on the overall heterogeneity of cases, $Q_t$. We then determined whether $Q_t$ obeyed a chi-square distribution and whether it is necessary to introduce explanatory variables. If the conditions are met, we decompose $Q_t$ and choose a mixed-effects model to determine the degree of influence of the explanatory variables on the effect values through the heterogeneity caused by the explanatory variables [61]. It is worth mentioning that in this step, we tested the moderate disturbance hypothesis by analyzing biodiversity patterns of different groups. The specific formulas are as follows:

$$Q_t={\sum }_{i=1}^k{w}_i{\left(y_i-\overline{y}\right)}^2={\sum }_{i=1}^k{w}_i{\left(y_i\right)}^2-{\displaystyle \frac{{\left({\sum }_{i=1}^k{w}_i{y}_i\right)}^2}{{\sum }_{i=1}^k{w}_i}}$$

(7)

$$Q_t=Q_m+Q_e$$

(8)

$$Q_m={\sum }_{j=1}^p{w}_j{\left(\overline{Y_j}-\overline{Y}\right)}^2$$

(9)

$$\overline{Y_j}={\displaystyle \frac{{\sum }_{i=1}^k{w}_{ji}{y}_{ji}}{{\sum }_{i=1}^k{w}_{ji}}}$$

(10)

$$w_j={\sum }_{i=1}^k{w}_{ji}^{\ast }$$

(11)

$$w_{ji}^{\ast }={\displaystyle \frac{1}{v_{ji}+{\tau }^2}}$$

(12)

The larger the $Q_t$ value, the higher the heterogeneity. An explanatory variable needs to be introduced when the p-value is less than 0.05. $Q_m$ represents the heterogeneity caused by a known variable, $Q_e$ represents residual heterogeneity caused by an unexplained unknown variable, $p$ represents the number of groups of the known variable, and $j$ represents the group $j$. The larger the $Q_m$ value, the greater the influence of the known variable on the effect value. $\overline{Y_j}$ and $w_j$ represent the cumulative effect value and weight of the explanatory variable for group $j$, respectively.

Due to the non-independence between species on the phylogenetic tree, it is important to incorporate a variance-covariance structure based on phylogenetic relationships, in addition to weighting effect sizes by the inverse of the total variance of the cases. At the population level, we conducted phylogenetic mixed-effects meta-analyses by combining the response variable with interactions between snowfall duration and other explanatory variables. We constructed phylogenetic trees in R 4.3.2 software using the V. PhyloMaker2 program package, using the mega-tree GBOTB.extended.TPL.tre as phylogenetic support [62] (Figure 2).

Finally, we use funnel plots and Egger‘s regression test for model diagnostics [63]. A more symmetrical funnel shape indicates lower bias and a more reliable conclusion. Egger’s regression tests this symmetry; if the result of the test is greater than 0.05, it further proves the reliability of the conclusion.

3. Results

3.1. Overall Effect of Snow Damage on Forest Vegetation Communities

At the community level, snow damage has the greatest attenuation effect on diameter at breast height, while forest communities with snow disturbances had significantly lower annual litterfall, Leaf Area Index (LAI), canopy density and abundance than the control treatment (Figure 3a). Furthermore, the disturbance effect of snow damage has a significant enhancement effect on Shannon’s Diversity Index, Simpson’s Diversity Index, Pielou’s Evenness Index, and diameter at breast height compared to the vegetation communities that were not disturbed by snow damage (Figure 3a). However, there was no significant change in species richness and Margalef Index, meaning that these two indicators did not respond significantly to snow damage (Figure 3a).

At the population level, snow damage has a significant attenuation effect on the density, abundance, and annual litterfall of trees, while it has a significant enhancement effect on diameter at breast height (Figure 3b). Importance value, basal area, and seedling abundance were not affected by snow damage disturbance (Figure 3b).

3.2. Influence of Snow Intensity and Duration of Post-Disaster Recovery on the Disturbing Effects of Snow Damage

Differences in the disturbance effect of snow damage on forest plant community diversity indices can be observed across the intensity of snow damage and post-disaster recovery time gradients. The distribution of biodiversity indicators for different snow intensity classes showed that the highest biodiversity of forest plant communities was found under moderate snow intensity disturbance, with growth rates of 17.17% and 6.78% for Shannon Index and Simpson Index, respectively (Figure 4a,b). The same phenomenon was observed in the distribution of biodiversity indexes at different levels of recovery time, and the growth rates of these indexes were 10.42%, 15.28%, and 14.77%, respectively (Figure 4c,d,e).

At the community level, the disturbing effects of snow damage on Leaf Area Index, canopy density, and abundance are significantly and positively correlated with the intensity of snow damage (Figure 5a–c). In contrast, the disturbance effect at diameter at breast height in forest vegetation communities shows a significant negative correlation with the intensity of snow damage (Figure 5d). Simultaneously, the number of years of post-disaster recovery is significantly and positively correlated with the disturbance effects of snow damage on canopy density and area at breast height, while it is significantly and negatively correlated with annual litterfall abundance (Figure 6a–d).

At the population level, the disturbance effects of snow damage on diameter at breast height and density of forest-dominant species are significantly negatively correlated with the intensity of snow damage (Figure 5e,f). In addition, the number of years of post-disaster recovery is significantly positively correlated with the effect of snow on the diameter at breast height of forest dominant species and significantly negatively correlated with their density and abundance (Figure 6e–g).

3.3. Influence of Forest Type on the Disturbing Effects of Snow Damage

The disturbance effect of snow damage on forest vegetation community characteristics varies with forest type. At the community level, Shannon’s Diversity Index, canopy density, area at breast height, and Pielou’s Evenness Index have significant heterogeneity due to forest origin. Especially, for Shannon’s Diversity Index, the positive effect is 97.68% for plantations (Figure 7a). For canopy density, the negative effect is −6.66% for natural forests, and −22.05% for plantations (Figure 7b). In terms of area at breast height, the negative effect is −19.38% for natural forests and −61.14% for plantations (Figure 7c). In terms of Pielou’s Evenness Index, the positive effect is 4.36% for natural forests and 35.73% for plantations (Figure 7d). In addition, there is significant heterogeneity between annual litterfall and diameter at breast height in forests of different stands. In terms of annual litterfall, the negative effect is −13.47% for pure forests and −65.20% for mixed forests (Figure 8a). For diameter at breast height, the effect is −7.53% for pure forests and forests, while it is −1.64% for mixed forests (Figure 8b). At the same time, the abundance of different forest vegetation communities was significantly heterogeneous depending on the forest life forms. The significant negative effect of snow damage on abundance was −14.86% in evergreen forests and −87.04% in mixed forests (Figure 9). Finally, annual litterfall, Shannon’s Diversity Index, Pielou’s Evenness Index, and diameter at breast height are significantly heterogeneous across forests with different physiognomies. In terms of annual litterfall, the negative effect is −12.06% for coniferous forests, −17.24% for broad-leaved forests, and −76.85% for conifer-broadleaf mixed forests (Figure 10a). In terms of Shannon’s Diversity Index, the positive effect is 97.68% for coniferous forests, 4.46% for broad-leaved forests, and 3.70% for conifer-broadleaf mixed forests (Figure 10b). In terms of Pielou’s Evenness Index, the positive effect is 35.73% for coniferous forests, 4.61% for broad-leaved forests, and 3.33% for conifer-broadleaf mixed forests (Figure 10c). In terms of diameter at breast height, the positive effect is 8.43% for coniferous forests, 7.31% for broad-leaved forests, and −1.64% for conifer-broadleaf mixed forests (Figure 10d).

At the population level, the abundance of dominant species varies considerably depending on the forest life form. The negative effect is −8.21% for evergreen forests, while the negative effect for mixed forests reaches −80.57% (Figure 9b). In addition, the density of dominant species varies significantly depending on the forest physiognomy. The negative effect is −38.24% for broad-leaved forests, whereas the positive effect for conifer-broadleaf mixed forests reaches 4.83% (Figure 10e).

3.4. Influence of Terrain Factors on the Disturbing Effects of Snow Damage

At the community level, elevation is significantly and negatively correlated with the disturbance effect of snow damage on the forest vegetation community leaf area index, canopy density, abundance, and Pielou’s Evenness Index (Figure 11). In addition, slope is significantly and positively correlated with the effect of snow damage on canopy density and area at breast height, while it is significantly and negatively correlated with the effect of snow damage on forest vegetation communities Shannon’s Diversity Index, Pielou’s Evenness Index, and diameter at breast height (Figure 12). Finally, annual litterfall, Shannon’s Diversity Index, and diameter at breast height have significant heterogeneity due to slope aspect (Figure 13). In terms of annual litterfall, the negative effect is −7.74% for sunny slopes, while it reaches −26.02% on shady slopes. In terms of Shannon’s Diversity Index, the positive effect is 2.71% for sunny slopes, compared to 21.70% on shady slopes. In terms of diameter at breast height, the positive effect is 8.10% for sunny slopes and 3.91% on shady slopes. In addition, at the population level, slope was significantly and positively correlated with the disturbance effect of snow damage on the diameter at breast height of forest vegetation populations.

4. Discussion

4.1. Overall Effects of Snow Damage

In this study, the general response of forest vegetation community characteristics to snow damage is revealed by a meta-analysis of 423 cases at the community level and 688 cases at the population level.

At the community level, the extended period of snow disturbances, significant decreases in the annual litterfall, Leaf Area Index, canopy density, area at breast height (ABH), as well as abundance of forest plant communities occur. Previous studies have shown that snow damage directly damages the canopy and even individual trees, so significant reductions in the indicators associated with it can occur [45,64,65]. Our study shows that after the snow damage, the Species Diversity Index, the Species Evenness Index, and the Pielous Evenness Index of forest plant communities underwent a significant increase, while the Species Richness Index and the Margalef’s Index did not change significantly. During snow disturbances, heavy snow covers the crowns and branches of trees, causing varying degrees of damage and resulting in abnormal litterfall. This damage creates or enlarges gaps in the forest, altering its structure [66,67,68,69,70,71]. Specifically, within the forest gaps, increased light exposure changes temperature and humidity conditions due to direct sunlight reaching the forest ground [72,73,74]. Additionally, the absence of canopy cover allows precipitation to reach the ground directly, increasing soil moisture [75]. In addition, fallen trees and broken branches alter the microtopography within the forest gaps, and these materials are converted into nutrients by microorganisms and decomposers [76,77,78]. As a result, there are significant differences in the community habitat before and after the snow damage. Previous studies have shown that changes in habitat lead to significant changes in the biodiversity of the plant community [79,80]. At the same time, previous studies have shown that patchy habitats typically have higher biodiversity than those in continuous habitats, with forest gaps and patches playing a crucial role in this dynamic [81,82]. In addition, previous studies on the response of forest plant community species richness to snow damage were inconsistent with our findings for two possible reasons: First, we speculate that snow damage may cause mortality of certain species due to physical damage and low temperatures, as well as subsequent disturbance by pests and diseases. Secondly, snow damage can create gaps that favor light-loving pioneer species, altering their relative abundance compared to naïve plant species. A significant increase in the level of diameter at breast height of forest vegetation communities occurred after snow damage. This is consistent with previous findings that trees with smaller DBH may be more severely affected [29,30,37,83,84,85].

At the population level, significant reductions in annual litterfall, density, and abundance occur in populations of each species as a result of snow damage. Although the specific effects of snow damage on different species in our dataset are inconsistent, the overall results are also generally consistent with previous studies [86]. As at the community level, snow damage significantly increased diameter at breast height (DBH) at the population level. Within the same species, individuals with a small diameter at breast height (DBH) are more prone to heavier damage, such as collapse and root and stem overthrow, as they are less able to withstand snow pressure, thus increasing the DBH of the entire population. There was no significant effect at the level of snow damage on the mean basal area of the forest population. We hypothesize that trees with larger basal areas are more susceptible to severe damage from snow, such as tip breaks, branch breaks, and compression bends, though the basal portions are less affected. This is consistent with previous studies that the damage to the base, such as collapse and uprooting, is less common compared to other types of mechanical damage [30,79]. The exclusion of species different in our study results in no significant changes in the importance values of individual species populations. Specifically, community species composition is influenced by external disturbance and the duration of the study period [87]. Consistent with previous findings, the dominant species often manage to self-renew and maintain stability over time, resulting in no significant change in their importance values [88,89]. In addition, as we analyzed at the previous community level, the growth and development of certain species while creating favorable conditions for others, For example, snow damage may kill or damage dominant canopy species, while suppressed trees and seeds in the seed bank may thrive and replenish the tree layer after the snow disturbance [90,91]. At the same time, the resistance of species to snow damage is often related to their own physiological characteristics [67,92]. At the population level, our study showed no significant change in seedling abundance in individual plant populations. Previous studies have shown that prior to the snow event, the species composition of seedlings in the native population in the forest was dominated by shade-tolerant species, while the snow event creates forest gaps in the forest that result in a large invasion of alien light-loving pioneer species [93,94]. In addition, seedlings are also damaged by broken branches and fallen trees due to low temperatures and snow damage, and the change in light conditions is detrimental to the growth of shade-tolerant species.

We found large heterogeneity in area at breast height and Margalef Index at the community level, as well as in basal area and seed abundance at the population level. Our analysis indicates that the large heterogeneity in basal area at the population level is primarily due to the inclusion of studies covering extensive time periods. In these studies, forests have undergone a large degree of regeneration and development after the snow damage, complicating the clear assessment of snow damage impacts. The source of heterogeneity observed in other indicators is likely attributable to variations in environmental conditions across different forest locations and differences in species composition. These factors may contribute to the variability in the responses of forest vegetation metrics to snow disturbances.

4.2. Impact of Snow Intensity and Duration of Post-Disaster Recovery on Snow Damage Effects

Our results suggest that the enhancement effects on all diversity indices were higher at moderate snow damage disturbance intensities and in the middle of post-disaster recovery compared to other periods. According to the intermediate disturbance hypothesis, forest plant communities exhibit the highest number of species coexisting and biodiversity in two scenarios: in both scenarios, i.e., they have the highest biodiversity [95,96,97]. The first scenario is a moderate disturbance, and the second scenario is the middle stage of recovery in the process of recovery of the community after the disturbance. When snow disturbance intensity is too low, a few competitive species may dominate the community, leading to reduced biodiversity; conversely, if the intensity of snow disturbance is too high, only those species with fast growth rates and exceptionally strong encroachment abilities will survive [97,98]. In addition, species diversity tends to be highest during the mid-successional stage following the onset of snow disturbances, with late successional species eventually replacing early successional ones, thereby decreasing the overall diversity of the community [99]. However, due to the limitations of the study itself, disturbances that are moderate for a given forest community may not have been included in the study.

As the intensity of snow damage increases, it also damages trees with larger diameter at breast height (DBH), so that the increasing effect of snow damage on DBH tends to decrease as the intensity of snow damage increases, both at the community level and at the population level. At the same time, as the intensity of snow damage increases, the structure of the stand is more severely damaged, allowing a greater reduction in stand density to occur. Our results show that a longer recovery period results in a reduced attenuation effect on canopy density and area at breast height (ABH) at the community level, while the larger the enhancement effect of diameter at breast height (DBH) at the population level. Previous findings have shown that forest ecosystems, being self-regulating, gradually recover over time as the post-disaster recovery progresses [100,101,102]. In addition, our study also observed that at the community level, the attenuation effects on Leaf Area Index and canopy density are smaller with increased snow damage intensity, while at the population level, the attenuation effects on density are larger with longer post-disaster recovery periods. This phenomenon may be attributed to variations in forest types and species compositions, which exhibit different resistance and response to disturbances, as well as different abilities to recover and self-regulation capabilities [103,104,105]. In addition, the attenuating effects of snow damage on abundance all increased significantly with the number of years of post-disaster recovery. We believe that the reasons for this phenomenon are, on the one hand, due to the fact that forest restoration enhances abundance to different degrees in different landscapes, and, on the other hand, it may be that other subsequent impacts indirectly caused by snow damage, such as pests and diseases, are not effectively managed [106,107]. It has been shown that the abundance of plants in forest gaps is significantly higher than in non-forest gaps [108,109]. As the intensity of snow damage increases, the structure of the forest is more severely damaged, resulting in the formation of more forest gaps of varying sizes. Although snow damage in general leads to the death of most individuals and thus reduces overall abundance, more gaps in the forest can help to recruit more alien species after snow damage occurs, thus mitigating the attenuation effect to a certain extent [110]. In addition to snow intensity, the presence of other influences on the response of forest plant communities to snow disturbances interferes with the study of disturbance intensity alone. At the same time, the annual litterfall with the year of post-disaster recovery variables also shows a trend completely opposite to the theory. In addition to the above reasons, some studies have shown that the amount of forest litterfall is also influenced by climatic zonation and forest type [111,112,113,114].

4.3. Effects of Snow Damage Among Different Forest Types

At the community level, ecological indicators of different types of forests have different responses to snow damage. As we described in the overall impact of snow damage section, snow damage tends to have a greater enhancement effect on the Diversity Index in plantation forests than in natural forests and a more pronounced attenuation effect on the area at breast height (ABH) and the canopy density. In terms of forest origin, plantation forests, characterized by a single dominant species and a single vertical structure, are therefore less resistant to mechanical stress [115], compared to natural forests, which have more complex structure with multiple layers, including a tree layer, tree sublayer, and shrub layer. These layers offer synergistic protective effects and can effectively disperse and alleviate the pressure stress of snow accumulation in the canopy (Cai et al., 2008; Li et al., 2005) [86,116]. Our study showed that snow damage had little effect on diameter at breast height (DBH) in the mixed forests compared to pure forests, where it had a significant enhancement effect on DBH. This discrepancy may be due to smaller-diameter trees in pure forests being more affected by the broken branches from taller trees. Previous studies have shown that mixed forests possess complex age structures, high biodiversity, and stability, which confer resilience against snow damage [116,117,118]. Surprisingly, snow damage seems to have a greater attenuation effect on annual litterfall in mixed forests compared to pure forests, indicating other factors besides snow damage may influence litterfall. In terms of forest life forms, some studies have shown that deciduous species are less affected by snow damage than evergreen species because they drop their leaves in winter, reducing snow accumulating on their branches [70,104,119]. However, regional variations and additional factors can affect how different life forms respond to snow-damaged disturbances [31,105]. Our findings show that the attenuation effect of snow damage on abundance is smaller in evergreen forests than in mixed evergreen-deciduous forests. By analyzing the information related to different forest life types, we found that the sample size for mixed evergreen-deciduous forests is relatively small compared to that for evergreen forests. This suggests that the mechanism of the influence of forest life forms on snow damage requires further investigation, especially considering other topographic factors. For example, the evergreen forests, which are located at higher elevations, may have been acclimatized to the low temperatures and snowfall, while mixed evergreen-deciduous forests may experience a greater intensity of snow damage [118,120]. In terms of forest physiognomy, conifers are more frost-resistant than broadleaf trees in the face of extreme cold weather [121]. Conifers typically have shorter, softer branches and much smaller leaves than broadleaf species, resulting in less snow accumulation and a lower likelihood of snow sticking to their crowns and branches [122]. On the other hand, broadleaf tree crowns are more expansive and evenly distributed, which increases the area of snowfall accumulation [123,124]. In summary, the attenuation effect of snow damage on annual litterfall tends to be smaller in coniferous forests than in broadleaf forests. However, some studies have also pointed out that conifers are actually more sensitive to snow damage than broadleaf trees, which aligns with our results that snow damage has a greater enhancement effect on diversity and diameter at breast height (DBH) in conifers than in broadleaf forests [86,125].

At the population level, we found that the ecological response of forests to snow damage was related only to forest life form and physiognomy. On the one hand, as we described in the community section, the attenuation effect of snow damage on stand abundance was lower in evergreen than in mixed evergreen-deciduous forests. Additionally, in broadleaf forests, snow damage greatly reduces the density of dominant populations, as broadleaf trees tend to accumulate more snow. This effect is less pronounced in mixed coniferous and broadleaf forests, where conifers’ structural characteristics mitigate the impact of snow accumulation.

4.4. Impact of Topographic Factors on Snow Damage Effects

In our study, we found that as the slope increases, the enhancement effect of snow damage on Diversity Index shifts to an attenuation effect. This aligns with the intermediate disturbance hypothesis, suggesting that snow damage to forests reaches a threshold beyond which it becomes detrimental. At the same time, the enhancing effect of snow damage on diameter at breast height (DBH) of forest vegetation communities decreases with increasing slope. This is consistent with the findings of many previous studies. Firstly, because of the phototropic nature of trees, as the slope increases, the asymmetry in canopy growth increases, leading to an uneven distribution of snow on the canopy [125,126,127]. Secondly, trees on steep slopes have shallow root systems, making them less resistant to disturbance [105]. Finally, trees on steep slopes are more likely to topple and fall when damaged, potentially causing damage to neighboring trees [104]. However, from the results of the study, the attenuation effect of snow damage on the canopy density and area at breast height (ABH) of the forest community decreased with increasing slope, and its enhancement effect on the diameter at breast height (DBH) of the dominant forest species group increases with slope. This could be due to the gentle range of slopes included in our cases or suggest that the disturbance effect of snow damage on forests is not strictly related to slope.

Our study suggests that at the community level, snow damage has a greater attenuation effect on the annual litterfall of forests on shady slopes than on sunny slopes. Slope aspect is an important topographic factor influencing the effects of snow damage on forest disturbance. Previous studies have shown that on shady slopes, which receive less sunlight, temperatures tend to be cooler, and snow accumulation lasts longer [128,129]. In addition, it has also been shown that humidity is higher on shady slopes during snowfall, leading to increased snow and ice accumulation at the top of the canopy [130,131,132]. In summary, forests on shady slopes experience more severe snow damage compared to those on sunny slopes, a finding consistent with our study. Our study also shows that snow damage significantly increases Shannon’s Diversity Index on shady slopes, while it has no significant effect on forest communities on sunny slopes. This is due to the fact that patch habitats resulting from snow damage clearly promote the invasion and growth of other species [133]. Additionally, the enhancement effect of snow damage on diameter at breast height (DBH) is smaller on shady slopes compared to sunny slopes. Previous studies have shown that sunny slopes support better forest growth with greater density due to more favorable light conditions [134]. The greater the stand density, the greater the proportion of snow damage in the stand [135]. Overall, the slope aspect has some influence on the effect of snow damage on forest disturbance, though further analysis is needed to fully understand the specifics.

The disturbing effects of snow damage on forests are related to elevation. As elevation increases, temperatures decrease, leading to greater snow accumulation on the canopy and longer duration of snow cover [31,125,136]. Our findings align with this, showing that the attenuation effects of snow damage on the Leaf Area Index, canopy density, and abundance of forest communities increase with elevation. At the same time, the enhancement effect of snow damage on the Pielou’s Diversity Index shifts an attenuation effect with elevation rises.

5. Conclusions

Globally, this meta-analysis demonstrates that snow damage has different effects on different ecological indicators of forests at both community and population levels in distinct ways. Our results suggest that the effects of snow damage on forest vegetation communities are influenced by a variety of factors and may vary widely. These key factors include snow damage intensity, post-disaster recovery time, forest type, elevation, slope, and aspect. Specifically, snow damage intensity has a significant attenuation effect on dominant forest species, while its influence varies over time, exhibiting both enhancement and attenuation effects with post-disaster recovery time at the community and population levels. The study also tests the intermediate disturbance hypothesis, aligning with its predictions. Overall, the disturbance effects of snow damage were greater in plantations compared to natural forests and are greater in mixed evergreen deciduous forests than in evergreen forests. However, the disturbance effects of snow damage on forests of different stands and physiognomies still require further discussion. In addition, while the relationship between snow damage and elevation is significant, the connections with slope and aspect remain unclear. In conclusion, our study provides a foundational understanding of how forests respond to snow disturbance and post-disaster recovery over time. However, further research is necessary to fully grasp the long-term effects of snow on various ecological indicators of forest vegetation communities and how these impacts shape the structure and the function of forest ecosystems in the long run. In addition, when snowfall causes damage to forest trees, it is often accompanied by the action of other processes, such as wind damage, frost damage, and consequent insect damage that act together on trees over a longer time scale, and it is of great interest to further explore the processes and mechanisms underlying these disturbances.