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Plant–rodent interactions after a heavy snowfall decrease plant regeneration and soil carbon emission in an old-growth forest

Plant–rodent interactions after a heavy snowfall decrease plant regeneration and soil carbon... Background: Climate extremes are likely to become more common in the future and are expected to change ecosystem processes and functions. As important consumers of seeds in forests, rodents are likely to affect forest regeneration following an extreme weather event. In April 2015, we began a field experiment after an extreme snowfall event in January 2015 in a primary forest that was > 300 years old. The heavy snow broke many tree limbs, which presumably reduced the numbers of seeds produced. Two treatments (rodent exclusion and rodent access) were established in the forest, in which rodent exclusion were achieved by placing stainlessness nets around the plot borders. Plant abundance, plant species richness, soil properties, soil microbial community composition, basal and substrate-induced respiration were determined in December 2017. Results: Plant abundance and species richness significantly increased, but soil microbial biomass decreased with rodent exclusion. Urease activity and soil basal respiration also significantly decreased with rodent exclusion. Most other soil properties, however, were unaffected by rodent exclusion. The relative effects of multiple predictors of basal respiration were mainly explained by the composition of the soil microbial community. Conclusions: After a heavy snowfall in an old-growth forest, exclusion of rodents increased plant regeneration and reduced microbial biomass and soil basal respiration. The main factor associated with the reduction in soil basal respiration was the change in the composition of the soil microbial community. These findings suggest that after a heavy snowfall, rodents may interfere with forest regeneration by directly reducing plant diversity and abundance but may enhance carbon retention by indirectly altering the soil microbial community. Keywords: Climate extreme, PLFAs, Soil respiration, Forest ecosystem, Enzyme activity − 1 Introduction Pg∙year , with the largest uncertainties in tropical for- Forests cover about 4 billion ha worldwide and provide ests (Pan et al. 2011). Because primary forests account important ecosystem goods and functions (Fei et al. for more than one-third of the total forest area on the 2018; Jactel et al. 2018; Keenan et al. 2015). In particular, planet and because tropical/subtropical forests represent the net global forest carbon sink was estimated to be 1.1 nearly half of the primary forest area (Luyssaert et al. 2008; Morales-Hidalgo et al. 2015), understanding the carbon dynamics in tropical/subtropical primary forests * Correspondence: yangblue@ahu.edu.cn; jianping.wu@ynu.edu.cn 4 is important. Climate extremes (such as droughts, heat- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China waves, and rainstorms) are expected to become more Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary common in the future (Kayler et al. 2015; Reyer et al. Ecology, Yunnan University, Kunming 650500, China 2015). Although the high productivity and biodiversity Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Zhou et al. Forest Ecosystems (2021) 8:30 Page 2 of 10 of primary forests may help mitigate climate change and relationships among predators, plants, and soil functions climate extremes (Stephenson et al. 2014; Zhou et al. (Mundim and Bruna 2016; Sitters and Venterink 2015). 2006), our understanding of the responses of above- and Mammalian herbivores can affect soil nutrient cycling belowground properties to climate extremes remains by grazing on aboveground plant tissues in grassland limited in primary forest ecosystems. ecosystems (Bardgett and Wardle 2003). How climate Among the climate extremes, extreme snowfall events change-driven alterations in the relationships between are likely to have substantial effects on forest ecosystems plants and herbivores/“seed predators”, i.e., animals that (Ashley et al. 2020; Zhao et al. 2016). Previous relevant consume seeds, can affect soil carbon and nutrients in studies mainly focused on boreal and temperate forests forest ecosystems is still unclear. In primary forests, re- because such forests frequently experience heavy snow generation and recruitment of plants were strongly regu- loads in the winter (Ashley et al. 2020; Venalainen et al. lated by the activities of scatter-hoarding rodents, who 2020). Heavy snowfall, for example, frequently causes can damage seedlings and can eat, remove, and cache substantial damage (including the breaking of stems and plant seeds (Boone and Mortelliti 2019; Cao et al. 2016; uprooting of trees) in Finnish forests (Lehtonen et al. Wang et al. 2013a, b). When snow storms decreased − 2 2016). In boreal forests, a snowfall mass of 20–40 kg∙m seed production, seed predators may alter its feeding is sufficient to break the stems of Scots pine and Norway preference and thereby substantially influence seed dis- spruce (Peltola et al. 1997). Forest canopies composed of persal (Zhou et al. 2013). The changes in the interac- mixed tree species are apparently more vulnerable to tions between seeds and seed predators induced by snow damage than forest canopies composed of one tree climate extremes may also affect soil microbial commu- species (Diaz-Yanez et al. 2017). In addition, the snow- nities and soil carbon emission in primary forest ecosys- pack in winter can also change soil carbon emission by tems (Mundim and Bruna 2016). If these interactions affecting soil temperature and moisture (Contosta et al. increase soil carbon emissions, they could result in a 2016). Consistent with the latter result, a meta-analysis positive feedback loop between soil carbon emissions revealed that an increase in snowpack depth can increase and climate change. soil respiration and microbial biomass by increasing soil In the present study, we conducted a field experiment temperature and water content (Li et al. 2016). with two treatments in April 2015 after an extreme For subtropical forest ecosystems, snowstorms are rare snowfall event in January 2015. The extreme snowfall but can occur given climate change (Zhao et al. 2016; event was the largest record during past 40 years, which Zhou et al. 2013). An anomalous extreme snow storm in covered half-meter on the floor (Song et al. 2017b). The 2008 caused a substantial disturbance to subtropical for- experimental site was a primary subtropical evergreen est ecosystems (Zhou et al. 2013). After another snow broadleaved forest that was > 300 years old (Tan et al. storm in a subtropical forest, researchers found that tree 2011). The treatments (± rodent exclusion) were applied mortality exceeded seed recruitment and that evergreen to the replicated plots. As described in a conceptual dia- broad-leaved species were more susceptible than decidu- gram (Fig. 1), we hypothesized that exclusion of rodents ous broad-leaved species (Ge et al. 2015). In addition, would increase plant abundance and plant species rich- snow storms can enhance canopy gaps that facilitate ness, which would increase carbon input into the soil in light penetration to the forest floor and thereby increase the form of litter and rhizodeposition; the increased car- germination and invasion by non-native herbaceous spe- bon input would increase soil carbon content but would cies (Song et al. 2017b). By increasing the sizes of can- also increase soil microbial activity and biomass, which opy gaps in another subtropical forest, snow storms also would increase soil carbon emissions. decreased soil organic carbon and nutrient contents (Xu et al. 2016). Using an eddy covariance technique, re- Materials and methods searchers recently found that, although a snow storm Study site strongly decreased the carbon sink in a primary subtrop- The experiment was conducted at the Ailaoshan Na- ical forest (Song et al. 2017a), the net carbon uptake was tional Nature Reserve (101°01′E, 24°32′N, 2450 m a.s.l.), quickly restored in the following year, suggesting that Yunnan Province, Southwestern China. The area has a forest ecosystems are highly resilient in their responses typical subtropical monsoon climate, with a mean an- to extreme weather events (Reyer et al. 2015; Song et al. nual precipitation of 1840 mm and a mean annual 2017a). These previous studies have demonstrated that temperature of 11.3 °C. The forest has a loamy alfisol. As extreme weather events can greatly affect above- and be- noted earlier, the evergreen broadleaved forest in this lowground organisms and processes (Bardgett and study was > 300 year old and occupied a protected area Caruso 2020; Bardgett and van der Putten 2014). Under- of 5110 ha. The average tree height was 20 m, and the standing those factors may increase our understanding average tree density was 2728 per ha. The mean soil or- − 1 of above- and belowground food webs, including the ganic carbon content was 116 g∙kg ; the mean soil total Zhou et al. Forest Ecosystems (2021) 8:30 Page 3 of 10 Fig. 1 A conceptual diagram showing how exclusion of rodents could decrease soil carbon emissions in a sub-tropical forest. We hypothesized that more seeds in soil would remain and geminate in plots without than with rodents because rodents consume seeds. The colored circles along the top sides of the upper rectangles represent the plant species whose seeds would survive predation by rodents. As a consequence of rodent exclusion, more seeds of more species would germinate following an extreme weather event (a heavy snowfall), resulting in sustained inputs of carbon to the soil via litter and rhizodeposition and the maintenance of soil carbon pools (bottom left rectangle). If rodents are not excluded, fewer seeds of fewer species would germinate following a heavy snowfall, resulting in a decrease of carbon inputs into soil and a decrease of soil carbon pools (bottom right rectangle) − 1 nitrogen content was 7 g∙kg ; and the mean soil pH plots were surrounded with a stainless steel mesh that was 4.2. The dominant tree species included Castanopsis was 1.3 m in height above ground and that extended 10 rufescens, Castanopsis wattii, Hartia sinensis, Lithocar- cm into the soil. The 1-cm openings in the mesh were pus chintungensis, Lithocarpus hancei, Lithocarpus xylo- sufficient to exclude rodents but presumably had min- carpus,and Vaccinium ducluoxii (Song et al. 2017a; Tan imal effects on light, air, and moisture penetration. Ro- et al. 2011). The dominant rodent species included Apo- dent “access” plots were not surrounded with stainless demus draco, Apodemus latronum, and Niviventer ful- steel mesh and were adjacent to rodent exclusion plots. vescens. An anomalous extreme snowfall event occurred Each pair of plots (± mesh, i.e., ± rodent exclusion) rep- in January 2015; it resulted in a snow depth on the forest resented one replicate. The two plots in a replicate were floor of 50 cm. It also caused substantial damage to tree less than 1 m apart, and replicate pairs were separated limbs and branches, and a substantial increase in the by ≥10 m and were randomly arranged under the forest openness of the canopy (Song et al. 2017b). canopy as shown in Supplementary Material Figure S1. Plant properties, soil properties, and microbial proper- Experimental design ties were assessed in December 2017. For plant proper- We began the experiment in April 2015 at which time ties, we determined the species of all woody plants taller the primary forest had experienced 3 months with a sub- than 5 cm within a 1 m × 1 m subplot in each plot; the stantial snowpack following the heavy snow in January. data were used to determine plant richness and plant We randomly selected 24 pairs of plots (a total of 48 abundance in plots with and without rodent exclusion. plots) from established 194 pairs of circular field plots, In addition, three soil cores (3-cm diameter) were col- each measuring 1.3 m in diameter. Rodent exclusion lected at depths of 0–10 cm; the cores were collected Zhou et al. Forest Ecosystems (2021) 8:30 Page 4 of 10 from the center of each plot to account for any hetero- Statistical analyses geneity resulting from position. Plant litter was removed T-test was used to determine the effect of rodent exclu- from the soil surface before the cores were taken. The sion on plant properties, soil properties, soil enzymes, three cores were combined to form one composite soil and soil microbial community with stats package in R. sample per plot. Fresh soils were passed through a 2- The normality and heterogeneity were tested before T- mm sieve, and remaining roots and stones were removed test. Data was made a Log-transformation when data did by hand. Soil samples were divided in half; one half was not fit the standard. Multiple regression models were used for determination of soil physico-chemical charac- used to determine the total effects of plants (species teristics, and the other half was used for phospholipid richness and abundance), soil enzyme activity (urease, fatty acid (PLFA) analysis. sucrose, and cellulase), soil properties (soil organic car- − + For physico-chemical analyses, soil samples were air dried, bon, soil total nitrogen, NO -N, NH -N, pH, soil water 3 4 ground, and passed through a 0.25-cm sieve. Soil water con- content, and dissolved organic carbon) and soil microor- tent was measured by comparing weights before and after ganisms (community, soil bacterial, and soil fungal oven-drying at 105 °C for 24 h. Soil pH was determined using PLFAs) on the variance in basal respiration. We first de- a 1:2.5 ratio of soil mass to deionized water volume. Soil or- leted the collinear variables and subsequently con- ganic carbon and dissolved organic carbon (after extraction structed a full model based on the standard with ΔAIC − 1 with 0.5 mol∙L K SO ) were measured with an elemental < 2 with MuMIn and performance packages in R. The 2 4 analyzer (vario TOC, Elementar Analysensysteme GmbH, parameter coefficients were used to calculate the relative Langenselbold, Germany). Total soil nitrogen was measured effect of each predictor on basal respiration. All statis- after micro-Kjeldahl digestion (CleverChem380, DeChem- tical analyses were performed with R version 3.3.2 (R Tech. GmbH, Hamburg, Germany). Soil nitrate and ammo- Core Team 2016). nium concentrations were determined with a chemical analyzer (CleverChem380, DeChem-Tech. GmbH, Ham- Results − 1 burg, Germany) after digestion in 1 mol∙L KCl. The activ- Responses of plants and soil properties to rodent ities of cellulase, sucrose, and urease were measured using a exclusion modified fluorescent-linked substrate microplate protocol Plant abundance (T = 2.72, P = 0.01, Fig. 2a) and plant with the situ soil pH conditions and the laboratory species richness (T = 2.47, P = 0.02, Fig. 2b) were signifi- temperature (Liu 1996). cantly greater with rodent exclusion than without rodent Soil microbial communities as indicated by PLFAs exclusion. Abundance increased by 59%, and richness in- were examined as described by (Frostegård and Bååth creased by 31% when rodents were excluded. 1996). Different PLFAs were used to represent different Soil organic carbon content and most soil properties groups of soil microorganisms. Bacterial PLFAs were were not significantly affected by rodent exclusion represented by i15:0, a15:0, 15:0, i16:0, 16:1ω9, i17:0, (Table 1). Rodent exclusion, however, significantly de- a17:0, 17:1ω8, 17:0, cy17:0, 18:1ω7, and cy19:0; fungal creased urease activity (Table 1). Bacterial PLFAs (T = PLFAs were represented by the PLFAs 18:1ω9, 18:2ω6, 4.07, P = 0.001, Fig. 3a), fungal PLFAs (T =3.17, P =0.006, and 18:3ω6 (Frostegård et al. 2011; Frostegård and Bååth Fig. 3b), and total PLFAs (T =3.95, P = 0.001, Fig. 3d) were 1996). The ratio of fungal PLFAs to bacterial PLFAs (F: significantly lower in the rodent exclusion plots than in B) was used to estimate the microbial community com- the plots without exclusion. Relative to the non-exclusion position in soil (Bardgett et al. 1996). All of the PLFAs plots, rodent exclusion reduced numbers of bacterial, fun- were indicated by MIDI peak identification software gal, and total PLFAs by 19%, 21%, and 17%, respectively. (MIDI, Inc., Newark, DE, USA). In contrast, the ratio of fungi to bacteria (T =2.83, P = Soil basal respiration and substrate-induced respiration 0.01, Fig. 3c) was significantly higher with than without were measured with a microcosm experiment modified from rodent exclusion. Wardle and Zackrisson (2005). In brief, a 5-g (dry weight) subsample of fresh soil from each of 12 randomly selected Responses of soil basal respiration to rodent exclusion plots with and without rodent exclusion was placed in a 228- Basal respiration (T = 4.87, P = 0.005, Fig. 4a) was signifi- mL glass bottle, and the soil moisture was adjusted to 100% cantly lower (by 15%) with than without rodent exclu- of water holding capacity to eliminate water limitation. For sion. Substrate-induced respiration (T = 0.34, P = 0.75, each treatment (± rodent exclusion), 6 bottles were amended Fig. 4b) was not significantly affected by rodent exclu- with 5 mg of glucose and 6 bottles were not amended with sion. The ratio of basal respiration to substrate-induced glucose. The bottles were sealed and incubated at room tem- respiration was significantly lower with than without ro- perate (25 °C). After 0 and 2 h of incubation, headspace CO dent exclusion (T = 3.21, P = 0.02, Fig. 4c). concentration was measured with a gas chromatograph (GC- A multiple regression model indicated that most of 2014, Shimadzu, Japan). the variance in basal respiration was explained by soil Zhou et al. Forest Ecosystems (2021) 8:30 Page 5 of 10 Fig. 2 Plant abundance (a) and plant species richness (b) per plot with and without rodent exclusion. Values are means ± SE, n =24 properties and soil microbial properties and especially by Bruna 2016) and increase the percentage of seeds con- the microbial community composition (ratio of fungi to sumed by predators (Zhou et al. 2013). Consistent with bacteria) (Fig. 5). The total effects of plant properties our hypothesis, plant abundance and species richness and soil enzymes on basal respiration were marginal. were significantly enhanced by rodent exclusion. Based on the increase in plant regeneration, we expected that Discussion exclusion would increase carbon input into the soil and Rodents strongly affect plant regeneration and commu- increase soil organic carbon content given the tight link- nity composition in forest ecosystems by their scatter- ages between above- and belowground systems (Bardgett hoarding of seeds and by changing plant–plant interac- and Wardle 2003; Wardle and Zackrisson 2005). How- tions (Kang et al. 2020; Yang et al. 2020). In the current ever, soil organic carbon content was not significantly study, we examined the indirect effects of rodents on increased by rodent exclusion (Table 1). The failure of carbon emission from soil after a heavy snowfall. Heavy rodent exclusion to increase soil organic carbon content snowfalls can reduce seed production by breaking might be explained by the high levels carbon in the soil branches and limbs. Consequently, plant–predator (seed of our study site. Also, our study covered only 3 years; consumer) interactions would be altered (Mundim and perhaps a longer study would have revealed a positive Zhou et al. Forest Ecosystems (2021) 8:30 Page 6 of 10 Table 1 Soil properties and enzyme activities in plots without and with rodent exclusion. Values are means ± SE, n = 24. Means in a row are not significantly different except for urease activity (P < 0.05) Variable Without rodent exclusion With rodent exclusion Soil organic carbon (SOC, %) 15.02 ± 0.59 15.37 ± 0.66 Total nitrogen (TN, %) 1.10 ± 0.04 1.13 ± 0.04 SOC: TN 13.73 ± 0.21 13.57 ± 0.25 Soil water content (%) 50.59 ± 0.66 50.64 ± 0.71 pH 4.45 ± 0.12 4.68 ± 0.13 − 1 Dissolved organic carbon (mg∙kg ) 178.98 ± 10.83 167.68 ± 12.39 + − 1 NH -N (mg∙kg ) 2.01 ± 0.15 1.70 ± 0.15 − − 1 NO -N (mg∙kg ) 7.72 ± 1.00 6.42 ± 0.77 − 1 − 1 Cellulase activity (μg∙g ∙h ) 10.44 ± 0.77 9.68 ± 0.95 − 1 − 1 Sucrase activity (μg∙g ∙h ) 111.37 ± 5.87 113.91 ± 6.65 − 1 − 1 Urease activity (mg∙g ∙d ) 5.96 ± 028a 5.07 ± 0.33b Fig. 3 Bacterial PLFAs (a), fungal PLFAs (b), fungal:bacterial PLFAs (c), and total PLFAs (d) with and without rodent exclusion. Values are means ± SE, n =22 or 24 Zhou et al. Forest Ecosystems (2021) 8:30 Page 7 of 10 Fig. 4 Basal respiration (a), substrate-induced respiration (b), and their ratios (c) with and without rodent exclusion. Values are mean ± SE, n =6 Zhou et al. Forest Ecosystems (2021) 8:30 Page 8 of 10 Fig. 5 Relative contribution of factors to basal respiration by using multiple regression model. The factors were divided into four groups of predictors (plant properties, soil enzymes, soil properties, and soil microbial properties). The relative contribution of four groups were calculated as the sum of the standardized regression coefficients for each group. The averaged parameter estimates of multiple predictors were obtained from standardized coefficients. Components of the four groups of predictors are indicated by colored symbols on the right side of the figure; the lines through the symbols indicate the range of the effects. SWC = soil water content. DOC = dissolved organic carbon content effect of rodent exclusion on soil organic carbon con- community. Positive relationships between soil basal res- tent. Since evergreen broad-leaved forest are susceptible piration and microbial biomass carbon were also re- to extreme snow in the subtropical regions (Ge et al. ported in other ecosystems (Lange et al. 2015; Wardle 2015). and Zackrisson 2005). Although rodent exclusion re- We found that rodent exclusion significantly decreased duced soil basal respiration, it did not significantly affect soil microbial biomass, which was inconsistent with our substrate-induced respiration, perhaps because of the hypothesis and also with previous findings that increases high background level of carbon in the soil. A decrease in plant diversity increased soil microbial biomass (Jing in soil basal respiration has the potential to increase soil et al. 2015; Lange et al. 2015). The significant difference carbon sequestration over the long term. Another ex- in soil microbial biomass and community composition periment at the same study site also found that net eco- between plots with and without rodent exclusion has at system CO exchange and ecosystem respiration were least two possible explanations. First, increases in plant strongly decreased by heavy snow in 2015 but then abundance and species richness in rodent exclusion sharply increased in 2016 (Song et al. 2017a), which sup- plots may have increased plant uptake of nutrients and ported our results. thereby increased the competition for nutrients experi- Based on our camera trap surveys (unpublished data), enced by soil microorganisms (Ullah et al. 2019;Wu some other mammals have been occasionally detected et al. 2011). Second, plant seeds of canopy trees usually (e.g., muntjacs and boars) although small rodents are the contain tannin, no matter the seed size is large or small dominant floor animals in our study forest. Nevertheless, (Wang et al. 2013; Yang et al. 2020), which may have our enclosure treatment excluded all kinds of floor ani- suppressed soil microbial activity to a greater degree in mals, and there faeces may potentially affect the soil plots with than without rodent exclusion. properties. Furthermore, the enclosure may have little Consistent with the decline in soil microbial biomass, effects on light penetration, air flow, temperature, and soil basal respiration was significantly lower with than moisture, because of the relatively large openings in the without rodent exclusion. According to multiple regres- mesh. Scatter-hoarding rodents play an important role sion analysis, the major factor affecting soil basal respir- on seedling regeneration in our study forest via seed pre- ation was the composition of the soil microbial dation and seed dispersal (Lang and Wang 2016). As we Zhou et al. Forest Ecosystems (2021) 8:30 Page 9 of 10 suggested earlier in the Discussion that heavy snowfall is Declarations likely to increase the percentage of seeds consumed by Ethics approval and consent to participate rodents, such that the effects of rodents on plant regen- Not applicable. eration would differ depending on whether or not exclu- Consent for publication sion occurred after a heavy snowfall. In addition, the Not applicable. dominant herbivores in our study forest were insects (unpublished data of herbivory survey), so the effect of Competing interests rodents on seedling damage can be ignored. Therefore, The authors declare no competing interests. the effects of enclosure on seedling regeneration may Author details mainly depend on seed predation and dispersal by Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary rodents. Ecology, Yunnan University, Kunming 650500, China. Key Laboratory of Soil Ecology and Health in Universities of Yunnan Province, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China. Conclusions Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla 666303, China. School of Resources and Environmental Engineering, This study presented plant-rodent interactions after heavy Anhui University, Hefei 230601, China. snowfall in an old growth forest. We compared plots with and without rodent exclusion following a heavy snowfall Received: 10 January 2021 Accepted: 27 April 2021 in an old forest. There were three main ecological outputs. First, rodent exclusion enhanced plant regeneration (as in- References dicated by increased plant species richness and abun- Ashley WS, Haberlie AM, Gensini VA (2020) Reduced frequency and size of late- dance). Second, soil basal respiration was strongly twenty-first-century snowstorms over North America. Nat Clim Chang 10(6): 539–544. https://doi.org/10.1038/s41558-020-0774-4 decreased by rodent exclusion, which indicates that Bardgett RD, Caruso T (2020) Soil microbial community responses to climate plant–rodent interactions indirectly affect soil carbon dy- extremes: resistance, resilience and transitions to alternative states. Philos Trans namics. Third, the main factor associated with the de- R Soc B-Biol Sci 375(1794):20190112. https://doi.org/10.1098/rstb.2019.0112 Bardgett RD, Hobbs PJ, Frostegård Å (1996) Changes in soil fungal:bacterial crease in soil basal respiration and therefore with the biomass ratios following reductions in the intensity of management of an potential for increased soil carbon sequestration in upland grassland. Biol Fertil Soils 22(3):261–264. https://doi.org/10.1007/ rodent-exclusion plots was the composition of the soil mi- BF00382522 Bardgett RD, van der Putten WH (2014) Belowground biodiversity and ecosystem crobial community, which in turn was regulated by plants. functioning. Nature 515(7528):505–511. https://doi.org/10.1038/nature13855 The above conclusions and implications produced by this Bardgett RD, Wardle DA (2003) Herbivore-mediated linkages between study can be important for sustainable forest management aboveground and belowground communities. Ecology 84(9):2258–2268. https://doi.org/10.1890/02-0274 in face of extreme snow storm in future. Boone SR, Mortelliti A (2019) Small mammal tree seed selection in mixed forests of the eastern United States. Forest Ecol Manage 449:117487. https://doi. org/10.1016/j.foreco.2019.117487 Supplementary Information Cao L, Wang Z, Yan C, Chen J, Guo C, Zhang Z (2016) Differential foraging preferences on The online version contains supplementary material available at https://doi. seed size by rodents result in higher dispersal success of medium-sized seeds. org/10.1186/s40663-021-00310-2. Ecology 97(11):3070–3078. https://doi.org/10.1002/ecy.1555 Contosta AR, Burakowski EA, Varner RK, Frey SD (2016) Winter soil respiration in a Additional file 1: Figure S1. Field experimental plots setting after humid temperate forest: the roles of moisture, temperature, and snowpack. J extreme snow event in 2015. The up one means the conceptual figure of Geophys Res-Biogeosci 121(12):3072–3088. https://doi.org/10.1002/201 experiment design, the below ones show the mesh on the field plot. 6JG003450 Core Team R (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Acknowledgments Diaz-Yanez O, Mola-Yudego B, Ramon Gonzalez-Olabarria J, Pukkala T (2017) How We thank Zhiyun Lu and Hangdong Wen from the Ailaoshan Station for does forest composition and structure affect the stability against wind and Subtropical Forest Ecosystem Studies for their field assistance. We also thank snow? Forest Ecol Manage 401:215–222. https://doi.org/10.1016/j.foreco.2017. three anonymous reviewers for their insightful comments. 06.054 Fei SL, Jo I, Guo QF, Wardle DA, Fang JY, Chen AP, Oswalt CM, Brockerhoff EG Authors’ contributions (2018) Impacts of climate on the biodiversity-productivity relationship in BW and JW acquired the funding and designed the experiment. QZ, JW, SX, natural forests. Nat Commun 9(1):5436. https://doi.org/10.1038/s41467-018- ZC, BW, and DL collected and analyzed the data. The authors jointly 07880-w contributed to the writing of the manuscript and approved the final Frostegård Å, Bååth E (1996) The use of phospholipid fatty acid analysis to manuscript. estimate bacterial and fungal biomass in soil. Biol Fertil Soils 22(1-2):59–65. https://doi.org/10.1007/BF00384433 Funding Frostegård Å, Tunlid A, Bååth E (2011) Use and misuse of PLFA measurements in This research was funded by National Natural Science Foundation of China soils. Soil Biol Biochem 43(8):1621–1625. https://doi.org/10.1016/j.soilbio.201 (Nos. 31971497, 31971444), by Yunnan Key Laboratory of Plant Reproductive 0.11.021 Adaptation and Evolutionary Ecology and Yunnan University (No. Ge J, Xiong G, Wang Z, Zhang M, Zhao C, Shen G, Xu W, Xie Z (2015) Altered C176210103). dynamics of broad-leaved tree species in a Chinese subtropical montane mixed forest: the role of an anomalous extreme 2008 ice storm episode. Ecol Availability of data and materials Evol 5(7):1484–1493. https://doi.org/10.1002/ece3.1433 The datasets used and/or analyzed during the current study are available Jactel H, Gritti ES, Drossler L, Forrester DI, Mason WL, Morin X, Pretzsch H, from the corresponding author on reasonable request. Castagneyrol B (2018) Positive biodiversity-productivity relationships in Zhou et al. Forest Ecosystems (2021) 8:30 Page 10 of 10 forests: climate matters. Biol Lett 14(4):20170747. https://doi.org/10.1098/ Stephenson NL, Das AJ, Condit R, Russo SE, Baker PJ, Beckman NG, Coomes DA, rsbl.2017.0747 Lines ER, Morris WK, Rüger N, Álvarez E, Blundo C, Bunyavejchewin S, Jing X, Sanders NJ, Shi Y, Chu H, Classen AT, Zhao K (2015) The links between Chuyong G, Davies SJ, Duque Á, Ewango CN, Flores O, Franklin JF, Grau HR, ecosystem multifunctionality and above- and belowground biodiversity are Hao Z, Harmon ME, Hubbell SP, Kenfack D, Lin Y, Makana JR, Malizia A, mediated by climate. Nat Commun 6(1):8159. https://doi.org/10.1038/ Malizia LR, Pabst RJ, Pongpattananurak N, Su SH, Sun IF, Tan S, Thomas D, ncomms9159 van Mantgem PJ, Wang X, Wiser SK, Zavala MA (2014) Rate of tree carbon accumulation increases continuously with tree size. Nature 507(7490):90–93. Kang H, Chang M, Liu S, Chao Z, Zhang X, Wang D (2020) Rodent-mediated https://doi.org/10.1038/nature12914 plant community competition: what happens to the seeds after entering the Tan ZH, Zhang YP, Schaefer D, Yu GR, Liang N, Song QH (2011) An old-growth adjacent stands? Forest Ecosyst 7(1):56. https://doi.org/10.1186/s40663-020- subtropical Asian evergreen forest as a large carbon sink. Atmos Environ 00270-z 45(8):1548–1554. https://doi.org/10.1016/j.atmosenv.2010.12.041 Kayler ZE, De Boeck HJ, Fatichi S, Gruenzweig JM, Merbold L, Beier C, McDowell Ullah S, Muhammad B, Amin R, Haider AH (2019) Sensitivity of Arbuscular N, Dukes JS (2015) Experiments to confront the environmental extremes of mycorrhizal fungi in old-growth forest: direct effect on growth and soil climate change. Front Ecol Environ 13(4):219–225. https://doi.org/10.1890/14 carbon storage. Appl Ecol Environ Res J 17:13749–13758 Venalainen A, Lehtonen I, Laapas M, Ruosteenoja K, Tikkanen OP, Viiri H, Ikonen Keenan RJ, Reams GA, Achard F, de Freitas JV, Grainger A, Lindquist E (2015) VP, Peltola H (2020) Climate change induces multiple risks to boreal forests Dynamics of global forest area: results from the FAO global forest resources and forestry in Finland: a literature review. Glob Chang Biol 26(8):4178–4196. assessment 2015. For Ecol Manag 352:9–20. https://doi.org/10.1016/j.foreco.2 https://doi.org/10.1111/gcb.15183 015.06.014 Wang B, Philips JS, Tomlinson KW (2013) Tradeoff between physical and chemical Lang ZW, Wang B (2016) The effect of seed size on seed fate in a subtropical defense in plant seeds is mediated by seed mass. Oikos 127:440–447 forest, southwest of China. iForest-Biogeosci For 9:652–657 Wang B, Philips JS, Tomlinson KW (2013a) Tradeoff between physical and chemical Lange M, Eisenhauer N, Sierra CA, Bessler H, Engels C, Griffiths RI, Mellado- defense in plant seeds is mediated by seed mass. Oikos 127:440–447 Vazquez PG, Malik AA, Roy J, Scheu S, Steinbeiss S, Thomson BC, Trumbore Wang B, Ye CX, Cannon CH, Chen J (2013b) Dissecting the decision making SE, Gleixner G (2015) Plant diversity increases soil microbial activity and soil process of scatter-hoarding rodents. Oikos 122(7):1027–1034. https://doi. carbon storage. Nat Commun 6(1):6707. https://doi.org/10.1038/ncomms7707 org/10.1111/j.1600-0706.2012.20823.x Lehtonen I, Kamarainen M, Gregow H, Venalainen A, Peltola H (2016) Heavy Wardle DA, Zackrisson O (2005) Effects of species and functional group loss on snow loads in Finnish forests respond regionally asymmetrically to projected island ecosystem properties. Nature 435(7043):806–810. https://doi.org/10.103 climate change. Nat Hazards Earth Syst Sci 16(10):2259–2271. https://doi. 8/nature03611 org/10.5194/nhess-16-2259-2016 Wu J, Liu Z, Chen D, Huang G, Zhou L, Fu S (2011) Understory plants can make Li W, Wu J, Bai E, Jin C, Wang A, Yuan F, Guan D (2016) Response of terrestrial substantial contributions to soil respiration: evidence from two subtropical carbon dynamics to snow cover change: a meta-analysis of experimental plantations. Soil Biol Biochem 43(11):2355–2357. https://doi.org/10.1016/j. manipulation (II). Soil Biol Biochem 103:388–393. https://doi.org/10.1016/j. soilbio.2011.07.011 soilbio.2016.09.017 Xu J, Xue L, Su Z (2016) Impacts of forest gaps on soil properties after a severe Liu G (1996) Soil physical and chemical analysis and description of soil profiles. ice storm in a Cunninghamia lanceolata stand. Pedosphere 26(3):408–416. China Standard Press, Beijing (in Chinese) https://doi.org/10.1016/S1002-0160(15)60053-4 Luyssaert S, Schulze ED, Börner A, Knohl A, Hessenmöller D, Law BE, Ciais P, Yang X, Yan C, Gu H, Zhang Z (2020) Interspecific synchrony of seed rain shapes Grace J (2008) Old-growth forests as global carbon sinks. Nature 455(7210): rodent-mediated indirect seed–seed interactions of sympatric tree species in 213–215. https://doi.org/10.1038/nature07276 a subtropical forest. Ecol Lett 23(1):45–54. https://doi.org/10.1111/ele.13405 Morales-Hidalgo D, Oswalt SN, Somanathan E (2015) Status and trends in global Zhao CY, Fang YH, Luo Y, Wang J (2016) Interdecadal component variation primary forest, protected areas, and areas designated for conservation of characteristics in heavy winter snow intensity in north-eastern China and its biodiversity from the global forest resources assessment 2015. Forest Ecol response to sea surface temperatures. Atmos Res 180:165–177. https://doi. Manage 352:68–77. https://doi.org/10.1016/j.foreco.2015.06.011 org/10.1016/j.atmosres.2016.05.016 Mundim FM, Bruna EM (2016) Is there a temperate bias in our understanding of Zhou G, Liu S, Li Z, Zhang D, Tang X, Zhou C, Yan J, Mo J (2006) Old-growth how climate change will alter plant-herbivore interactions? A meta-analysis forests can accumulate carbon in soils. Science 314(5804):1417. https://doi. of experimental studies. Am Nat 188(S1):S74–S89. https://doi.org/10.1086/ org/10.1126/science.1130168 Zhou Y, Newman C, Chen J, Xie Z, Macdonald DW (2013) Anomalous, extreme Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA, Phillips OL, weather disrupts obligate seed dispersal mutualism: snow in a subtropical Shvidenko A, Lewis SL, Canadell JG, Ciais P, Jackson RB, Pacala SW, McGuire forest ecosystem. Glob Chang Biol 19(9):2867–2877. https://doi.org/10.1111/ AD, Piao S, Rautiainen A, Sitch S, Hayes D (2011) A large and persistent gcb.12245 carbon sink in the world’s forests. Science 333(6045):988–993. https://doi. org/10.1126/science.1201609 Peltola H, Nykanen ML, Kellomaki S (1997) Model computations on the critical combination of snow loading and windspeed for snow damage of scots pine, Norway spruce and birch sp. at stand edge. Forest Ecol Manage 95(3): 229–241. https://doi.org/10.1016/S0378-1127(97)00037-6 Reyer CPO, Brouwers N, Rammig A, Brook BW, Epila J, Grant RF, Holmgren M, Langerwisch F, Leuzinger S, Lucht W, Medlyn B, Pfeifer M, Steinkamp J, Vanderwel MC, Verbeeck H, Villela DM (2015) Forest resilience and tipping points at different spatio-temporal scales: approaches and challenges. J Ecol 103(1):5–15. https://doi.org/10.1111/1365-2745.12337 Sitters J, Venterink HO (2015) The need for a novel integrative theory on feedbacks between herbivores, plants and soil nutrient cycling. Plant Soil 396(1-2):421–426. https://doi.org/10.1007/s11104-015-2679-y Song QH, Fei XH, Zhang YP, Sha LQ, Wu CS, Lu ZY, Luo K, Zhou WJ, Liu YT, Gao JB (2017a) Snow damage strongly reduces the strength of the carbon sink in a primary subtropical evergreen broadleaved forest. Environ Res Lett 12: Song X, Hogan JA, Brown C, Cao M, Yang J (2017b) Snow damage to the canopy facilitates alien weed invasion in a subtropical montane primary forest in southwestern China. Forest Ecol Manage 391:275–281. https://doi.org/10.101 6/j.foreco.2017.02.031 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Forest Ecosystems" Springer Journals

Plant–rodent interactions after a heavy snowfall decrease plant regeneration and soil carbon emission in an old-growth forest

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10.1186/s40663-021-00310-2
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Abstract

Background: Climate extremes are likely to become more common in the future and are expected to change ecosystem processes and functions. As important consumers of seeds in forests, rodents are likely to affect forest regeneration following an extreme weather event. In April 2015, we began a field experiment after an extreme snowfall event in January 2015 in a primary forest that was > 300 years old. The heavy snow broke many tree limbs, which presumably reduced the numbers of seeds produced. Two treatments (rodent exclusion and rodent access) were established in the forest, in which rodent exclusion were achieved by placing stainlessness nets around the plot borders. Plant abundance, plant species richness, soil properties, soil microbial community composition, basal and substrate-induced respiration were determined in December 2017. Results: Plant abundance and species richness significantly increased, but soil microbial biomass decreased with rodent exclusion. Urease activity and soil basal respiration also significantly decreased with rodent exclusion. Most other soil properties, however, were unaffected by rodent exclusion. The relative effects of multiple predictors of basal respiration were mainly explained by the composition of the soil microbial community. Conclusions: After a heavy snowfall in an old-growth forest, exclusion of rodents increased plant regeneration and reduced microbial biomass and soil basal respiration. The main factor associated with the reduction in soil basal respiration was the change in the composition of the soil microbial community. These findings suggest that after a heavy snowfall, rodents may interfere with forest regeneration by directly reducing plant diversity and abundance but may enhance carbon retention by indirectly altering the soil microbial community. Keywords: Climate extreme, PLFAs, Soil respiration, Forest ecosystem, Enzyme activity − 1 Introduction Pg∙year , with the largest uncertainties in tropical for- Forests cover about 4 billion ha worldwide and provide ests (Pan et al. 2011). Because primary forests account important ecosystem goods and functions (Fei et al. for more than one-third of the total forest area on the 2018; Jactel et al. 2018; Keenan et al. 2015). In particular, planet and because tropical/subtropical forests represent the net global forest carbon sink was estimated to be 1.1 nearly half of the primary forest area (Luyssaert et al. 2008; Morales-Hidalgo et al. 2015), understanding the carbon dynamics in tropical/subtropical primary forests * Correspondence: yangblue@ahu.edu.cn; jianping.wu@ynu.edu.cn 4 is important. Climate extremes (such as droughts, heat- School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China waves, and rainstorms) are expected to become more Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary common in the future (Kayler et al. 2015; Reyer et al. Ecology, Yunnan University, Kunming 650500, China 2015). Although the high productivity and biodiversity Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Zhou et al. Forest Ecosystems (2021) 8:30 Page 2 of 10 of primary forests may help mitigate climate change and relationships among predators, plants, and soil functions climate extremes (Stephenson et al. 2014; Zhou et al. (Mundim and Bruna 2016; Sitters and Venterink 2015). 2006), our understanding of the responses of above- and Mammalian herbivores can affect soil nutrient cycling belowground properties to climate extremes remains by grazing on aboveground plant tissues in grassland limited in primary forest ecosystems. ecosystems (Bardgett and Wardle 2003). How climate Among the climate extremes, extreme snowfall events change-driven alterations in the relationships between are likely to have substantial effects on forest ecosystems plants and herbivores/“seed predators”, i.e., animals that (Ashley et al. 2020; Zhao et al. 2016). Previous relevant consume seeds, can affect soil carbon and nutrients in studies mainly focused on boreal and temperate forests forest ecosystems is still unclear. In primary forests, re- because such forests frequently experience heavy snow generation and recruitment of plants were strongly regu- loads in the winter (Ashley et al. 2020; Venalainen et al. lated by the activities of scatter-hoarding rodents, who 2020). Heavy snowfall, for example, frequently causes can damage seedlings and can eat, remove, and cache substantial damage (including the breaking of stems and plant seeds (Boone and Mortelliti 2019; Cao et al. 2016; uprooting of trees) in Finnish forests (Lehtonen et al. Wang et al. 2013a, b). When snow storms decreased − 2 2016). In boreal forests, a snowfall mass of 20–40 kg∙m seed production, seed predators may alter its feeding is sufficient to break the stems of Scots pine and Norway preference and thereby substantially influence seed dis- spruce (Peltola et al. 1997). Forest canopies composed of persal (Zhou et al. 2013). The changes in the interac- mixed tree species are apparently more vulnerable to tions between seeds and seed predators induced by snow damage than forest canopies composed of one tree climate extremes may also affect soil microbial commu- species (Diaz-Yanez et al. 2017). In addition, the snow- nities and soil carbon emission in primary forest ecosys- pack in winter can also change soil carbon emission by tems (Mundim and Bruna 2016). If these interactions affecting soil temperature and moisture (Contosta et al. increase soil carbon emissions, they could result in a 2016). Consistent with the latter result, a meta-analysis positive feedback loop between soil carbon emissions revealed that an increase in snowpack depth can increase and climate change. soil respiration and microbial biomass by increasing soil In the present study, we conducted a field experiment temperature and water content (Li et al. 2016). with two treatments in April 2015 after an extreme For subtropical forest ecosystems, snowstorms are rare snowfall event in January 2015. The extreme snowfall but can occur given climate change (Zhao et al. 2016; event was the largest record during past 40 years, which Zhou et al. 2013). An anomalous extreme snow storm in covered half-meter on the floor (Song et al. 2017b). The 2008 caused a substantial disturbance to subtropical for- experimental site was a primary subtropical evergreen est ecosystems (Zhou et al. 2013). After another snow broadleaved forest that was > 300 years old (Tan et al. storm in a subtropical forest, researchers found that tree 2011). The treatments (± rodent exclusion) were applied mortality exceeded seed recruitment and that evergreen to the replicated plots. As described in a conceptual dia- broad-leaved species were more susceptible than decidu- gram (Fig. 1), we hypothesized that exclusion of rodents ous broad-leaved species (Ge et al. 2015). In addition, would increase plant abundance and plant species rich- snow storms can enhance canopy gaps that facilitate ness, which would increase carbon input into the soil in light penetration to the forest floor and thereby increase the form of litter and rhizodeposition; the increased car- germination and invasion by non-native herbaceous spe- bon input would increase soil carbon content but would cies (Song et al. 2017b). By increasing the sizes of can- also increase soil microbial activity and biomass, which opy gaps in another subtropical forest, snow storms also would increase soil carbon emissions. decreased soil organic carbon and nutrient contents (Xu et al. 2016). Using an eddy covariance technique, re- Materials and methods searchers recently found that, although a snow storm Study site strongly decreased the carbon sink in a primary subtrop- The experiment was conducted at the Ailaoshan Na- ical forest (Song et al. 2017a), the net carbon uptake was tional Nature Reserve (101°01′E, 24°32′N, 2450 m a.s.l.), quickly restored in the following year, suggesting that Yunnan Province, Southwestern China. The area has a forest ecosystems are highly resilient in their responses typical subtropical monsoon climate, with a mean an- to extreme weather events (Reyer et al. 2015; Song et al. nual precipitation of 1840 mm and a mean annual 2017a). These previous studies have demonstrated that temperature of 11.3 °C. The forest has a loamy alfisol. As extreme weather events can greatly affect above- and be- noted earlier, the evergreen broadleaved forest in this lowground organisms and processes (Bardgett and study was > 300 year old and occupied a protected area Caruso 2020; Bardgett and van der Putten 2014). Under- of 5110 ha. The average tree height was 20 m, and the standing those factors may increase our understanding average tree density was 2728 per ha. The mean soil or- − 1 of above- and belowground food webs, including the ganic carbon content was 116 g∙kg ; the mean soil total Zhou et al. Forest Ecosystems (2021) 8:30 Page 3 of 10 Fig. 1 A conceptual diagram showing how exclusion of rodents could decrease soil carbon emissions in a sub-tropical forest. We hypothesized that more seeds in soil would remain and geminate in plots without than with rodents because rodents consume seeds. The colored circles along the top sides of the upper rectangles represent the plant species whose seeds would survive predation by rodents. As a consequence of rodent exclusion, more seeds of more species would germinate following an extreme weather event (a heavy snowfall), resulting in sustained inputs of carbon to the soil via litter and rhizodeposition and the maintenance of soil carbon pools (bottom left rectangle). If rodents are not excluded, fewer seeds of fewer species would germinate following a heavy snowfall, resulting in a decrease of carbon inputs into soil and a decrease of soil carbon pools (bottom right rectangle) − 1 nitrogen content was 7 g∙kg ; and the mean soil pH plots were surrounded with a stainless steel mesh that was 4.2. The dominant tree species included Castanopsis was 1.3 m in height above ground and that extended 10 rufescens, Castanopsis wattii, Hartia sinensis, Lithocar- cm into the soil. The 1-cm openings in the mesh were pus chintungensis, Lithocarpus hancei, Lithocarpus xylo- sufficient to exclude rodents but presumably had min- carpus,and Vaccinium ducluoxii (Song et al. 2017a; Tan imal effects on light, air, and moisture penetration. Ro- et al. 2011). The dominant rodent species included Apo- dent “access” plots were not surrounded with stainless demus draco, Apodemus latronum, and Niviventer ful- steel mesh and were adjacent to rodent exclusion plots. vescens. An anomalous extreme snowfall event occurred Each pair of plots (± mesh, i.e., ± rodent exclusion) rep- in January 2015; it resulted in a snow depth on the forest resented one replicate. The two plots in a replicate were floor of 50 cm. It also caused substantial damage to tree less than 1 m apart, and replicate pairs were separated limbs and branches, and a substantial increase in the by ≥10 m and were randomly arranged under the forest openness of the canopy (Song et al. 2017b). canopy as shown in Supplementary Material Figure S1. Plant properties, soil properties, and microbial proper- Experimental design ties were assessed in December 2017. For plant proper- We began the experiment in April 2015 at which time ties, we determined the species of all woody plants taller the primary forest had experienced 3 months with a sub- than 5 cm within a 1 m × 1 m subplot in each plot; the stantial snowpack following the heavy snow in January. data were used to determine plant richness and plant We randomly selected 24 pairs of plots (a total of 48 abundance in plots with and without rodent exclusion. plots) from established 194 pairs of circular field plots, In addition, three soil cores (3-cm diameter) were col- each measuring 1.3 m in diameter. Rodent exclusion lected at depths of 0–10 cm; the cores were collected Zhou et al. Forest Ecosystems (2021) 8:30 Page 4 of 10 from the center of each plot to account for any hetero- Statistical analyses geneity resulting from position. Plant litter was removed T-test was used to determine the effect of rodent exclu- from the soil surface before the cores were taken. The sion on plant properties, soil properties, soil enzymes, three cores were combined to form one composite soil and soil microbial community with stats package in R. sample per plot. Fresh soils were passed through a 2- The normality and heterogeneity were tested before T- mm sieve, and remaining roots and stones were removed test. Data was made a Log-transformation when data did by hand. Soil samples were divided in half; one half was not fit the standard. Multiple regression models were used for determination of soil physico-chemical charac- used to determine the total effects of plants (species teristics, and the other half was used for phospholipid richness and abundance), soil enzyme activity (urease, fatty acid (PLFA) analysis. sucrose, and cellulase), soil properties (soil organic car- − + For physico-chemical analyses, soil samples were air dried, bon, soil total nitrogen, NO -N, NH -N, pH, soil water 3 4 ground, and passed through a 0.25-cm sieve. Soil water con- content, and dissolved organic carbon) and soil microor- tent was measured by comparing weights before and after ganisms (community, soil bacterial, and soil fungal oven-drying at 105 °C for 24 h. Soil pH was determined using PLFAs) on the variance in basal respiration. We first de- a 1:2.5 ratio of soil mass to deionized water volume. Soil or- leted the collinear variables and subsequently con- ganic carbon and dissolved organic carbon (after extraction structed a full model based on the standard with ΔAIC − 1 with 0.5 mol∙L K SO ) were measured with an elemental < 2 with MuMIn and performance packages in R. The 2 4 analyzer (vario TOC, Elementar Analysensysteme GmbH, parameter coefficients were used to calculate the relative Langenselbold, Germany). Total soil nitrogen was measured effect of each predictor on basal respiration. All statis- after micro-Kjeldahl digestion (CleverChem380, DeChem- tical analyses were performed with R version 3.3.2 (R Tech. GmbH, Hamburg, Germany). Soil nitrate and ammo- Core Team 2016). nium concentrations were determined with a chemical analyzer (CleverChem380, DeChem-Tech. GmbH, Ham- Results − 1 burg, Germany) after digestion in 1 mol∙L KCl. The activ- Responses of plants and soil properties to rodent ities of cellulase, sucrose, and urease were measured using a exclusion modified fluorescent-linked substrate microplate protocol Plant abundance (T = 2.72, P = 0.01, Fig. 2a) and plant with the situ soil pH conditions and the laboratory species richness (T = 2.47, P = 0.02, Fig. 2b) were signifi- temperature (Liu 1996). cantly greater with rodent exclusion than without rodent Soil microbial communities as indicated by PLFAs exclusion. Abundance increased by 59%, and richness in- were examined as described by (Frostegård and Bååth creased by 31% when rodents were excluded. 1996). Different PLFAs were used to represent different Soil organic carbon content and most soil properties groups of soil microorganisms. Bacterial PLFAs were were not significantly affected by rodent exclusion represented by i15:0, a15:0, 15:0, i16:0, 16:1ω9, i17:0, (Table 1). Rodent exclusion, however, significantly de- a17:0, 17:1ω8, 17:0, cy17:0, 18:1ω7, and cy19:0; fungal creased urease activity (Table 1). Bacterial PLFAs (T = PLFAs were represented by the PLFAs 18:1ω9, 18:2ω6, 4.07, P = 0.001, Fig. 3a), fungal PLFAs (T =3.17, P =0.006, and 18:3ω6 (Frostegård et al. 2011; Frostegård and Bååth Fig. 3b), and total PLFAs (T =3.95, P = 0.001, Fig. 3d) were 1996). The ratio of fungal PLFAs to bacterial PLFAs (F: significantly lower in the rodent exclusion plots than in B) was used to estimate the microbial community com- the plots without exclusion. Relative to the non-exclusion position in soil (Bardgett et al. 1996). All of the PLFAs plots, rodent exclusion reduced numbers of bacterial, fun- were indicated by MIDI peak identification software gal, and total PLFAs by 19%, 21%, and 17%, respectively. (MIDI, Inc., Newark, DE, USA). In contrast, the ratio of fungi to bacteria (T =2.83, P = Soil basal respiration and substrate-induced respiration 0.01, Fig. 3c) was significantly higher with than without were measured with a microcosm experiment modified from rodent exclusion. Wardle and Zackrisson (2005). In brief, a 5-g (dry weight) subsample of fresh soil from each of 12 randomly selected Responses of soil basal respiration to rodent exclusion plots with and without rodent exclusion was placed in a 228- Basal respiration (T = 4.87, P = 0.005, Fig. 4a) was signifi- mL glass bottle, and the soil moisture was adjusted to 100% cantly lower (by 15%) with than without rodent exclu- of water holding capacity to eliminate water limitation. For sion. Substrate-induced respiration (T = 0.34, P = 0.75, each treatment (± rodent exclusion), 6 bottles were amended Fig. 4b) was not significantly affected by rodent exclu- with 5 mg of glucose and 6 bottles were not amended with sion. The ratio of basal respiration to substrate-induced glucose. The bottles were sealed and incubated at room tem- respiration was significantly lower with than without ro- perate (25 °C). After 0 and 2 h of incubation, headspace CO dent exclusion (T = 3.21, P = 0.02, Fig. 4c). concentration was measured with a gas chromatograph (GC- A multiple regression model indicated that most of 2014, Shimadzu, Japan). the variance in basal respiration was explained by soil Zhou et al. Forest Ecosystems (2021) 8:30 Page 5 of 10 Fig. 2 Plant abundance (a) and plant species richness (b) per plot with and without rodent exclusion. Values are means ± SE, n =24 properties and soil microbial properties and especially by Bruna 2016) and increase the percentage of seeds con- the microbial community composition (ratio of fungi to sumed by predators (Zhou et al. 2013). Consistent with bacteria) (Fig. 5). The total effects of plant properties our hypothesis, plant abundance and species richness and soil enzymes on basal respiration were marginal. were significantly enhanced by rodent exclusion. Based on the increase in plant regeneration, we expected that Discussion exclusion would increase carbon input into the soil and Rodents strongly affect plant regeneration and commu- increase soil organic carbon content given the tight link- nity composition in forest ecosystems by their scatter- ages between above- and belowground systems (Bardgett hoarding of seeds and by changing plant–plant interac- and Wardle 2003; Wardle and Zackrisson 2005). How- tions (Kang et al. 2020; Yang et al. 2020). In the current ever, soil organic carbon content was not significantly study, we examined the indirect effects of rodents on increased by rodent exclusion (Table 1). The failure of carbon emission from soil after a heavy snowfall. Heavy rodent exclusion to increase soil organic carbon content snowfalls can reduce seed production by breaking might be explained by the high levels carbon in the soil branches and limbs. Consequently, plant–predator (seed of our study site. Also, our study covered only 3 years; consumer) interactions would be altered (Mundim and perhaps a longer study would have revealed a positive Zhou et al. Forest Ecosystems (2021) 8:30 Page 6 of 10 Table 1 Soil properties and enzyme activities in plots without and with rodent exclusion. Values are means ± SE, n = 24. Means in a row are not significantly different except for urease activity (P < 0.05) Variable Without rodent exclusion With rodent exclusion Soil organic carbon (SOC, %) 15.02 ± 0.59 15.37 ± 0.66 Total nitrogen (TN, %) 1.10 ± 0.04 1.13 ± 0.04 SOC: TN 13.73 ± 0.21 13.57 ± 0.25 Soil water content (%) 50.59 ± 0.66 50.64 ± 0.71 pH 4.45 ± 0.12 4.68 ± 0.13 − 1 Dissolved organic carbon (mg∙kg ) 178.98 ± 10.83 167.68 ± 12.39 + − 1 NH -N (mg∙kg ) 2.01 ± 0.15 1.70 ± 0.15 − − 1 NO -N (mg∙kg ) 7.72 ± 1.00 6.42 ± 0.77 − 1 − 1 Cellulase activity (μg∙g ∙h ) 10.44 ± 0.77 9.68 ± 0.95 − 1 − 1 Sucrase activity (μg∙g ∙h ) 111.37 ± 5.87 113.91 ± 6.65 − 1 − 1 Urease activity (mg∙g ∙d ) 5.96 ± 028a 5.07 ± 0.33b Fig. 3 Bacterial PLFAs (a), fungal PLFAs (b), fungal:bacterial PLFAs (c), and total PLFAs (d) with and without rodent exclusion. Values are means ± SE, n =22 or 24 Zhou et al. Forest Ecosystems (2021) 8:30 Page 7 of 10 Fig. 4 Basal respiration (a), substrate-induced respiration (b), and their ratios (c) with and without rodent exclusion. Values are mean ± SE, n =6 Zhou et al. Forest Ecosystems (2021) 8:30 Page 8 of 10 Fig. 5 Relative contribution of factors to basal respiration by using multiple regression model. The factors were divided into four groups of predictors (plant properties, soil enzymes, soil properties, and soil microbial properties). The relative contribution of four groups were calculated as the sum of the standardized regression coefficients for each group. The averaged parameter estimates of multiple predictors were obtained from standardized coefficients. Components of the four groups of predictors are indicated by colored symbols on the right side of the figure; the lines through the symbols indicate the range of the effects. SWC = soil water content. DOC = dissolved organic carbon content effect of rodent exclusion on soil organic carbon con- community. Positive relationships between soil basal res- tent. Since evergreen broad-leaved forest are susceptible piration and microbial biomass carbon were also re- to extreme snow in the subtropical regions (Ge et al. ported in other ecosystems (Lange et al. 2015; Wardle 2015). and Zackrisson 2005). Although rodent exclusion re- We found that rodent exclusion significantly decreased duced soil basal respiration, it did not significantly affect soil microbial biomass, which was inconsistent with our substrate-induced respiration, perhaps because of the hypothesis and also with previous findings that increases high background level of carbon in the soil. A decrease in plant diversity increased soil microbial biomass (Jing in soil basal respiration has the potential to increase soil et al. 2015; Lange et al. 2015). The significant difference carbon sequestration over the long term. Another ex- in soil microbial biomass and community composition periment at the same study site also found that net eco- between plots with and without rodent exclusion has at system CO exchange and ecosystem respiration were least two possible explanations. First, increases in plant strongly decreased by heavy snow in 2015 but then abundance and species richness in rodent exclusion sharply increased in 2016 (Song et al. 2017a), which sup- plots may have increased plant uptake of nutrients and ported our results. thereby increased the competition for nutrients experi- Based on our camera trap surveys (unpublished data), enced by soil microorganisms (Ullah et al. 2019;Wu some other mammals have been occasionally detected et al. 2011). Second, plant seeds of canopy trees usually (e.g., muntjacs and boars) although small rodents are the contain tannin, no matter the seed size is large or small dominant floor animals in our study forest. Nevertheless, (Wang et al. 2013; Yang et al. 2020), which may have our enclosure treatment excluded all kinds of floor ani- suppressed soil microbial activity to a greater degree in mals, and there faeces may potentially affect the soil plots with than without rodent exclusion. properties. Furthermore, the enclosure may have little Consistent with the decline in soil microbial biomass, effects on light penetration, air flow, temperature, and soil basal respiration was significantly lower with than moisture, because of the relatively large openings in the without rodent exclusion. According to multiple regres- mesh. Scatter-hoarding rodents play an important role sion analysis, the major factor affecting soil basal respir- on seedling regeneration in our study forest via seed pre- ation was the composition of the soil microbial dation and seed dispersal (Lang and Wang 2016). As we Zhou et al. Forest Ecosystems (2021) 8:30 Page 9 of 10 suggested earlier in the Discussion that heavy snowfall is Declarations likely to increase the percentage of seeds consumed by Ethics approval and consent to participate rodents, such that the effects of rodents on plant regen- Not applicable. eration would differ depending on whether or not exclu- Consent for publication sion occurred after a heavy snowfall. In addition, the Not applicable. dominant herbivores in our study forest were insects (unpublished data of herbivory survey), so the effect of Competing interests rodents on seedling damage can be ignored. Therefore, The authors declare no competing interests. the effects of enclosure on seedling regeneration may Author details mainly depend on seed predation and dispersal by Yunnan Key Laboratory of Plant Reproductive Adaptation and Evolutionary rodents. Ecology, Yunnan University, Kunming 650500, China. Key Laboratory of Soil Ecology and Health in Universities of Yunnan Province, School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China. Conclusions Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla 666303, China. School of Resources and Environmental Engineering, This study presented plant-rodent interactions after heavy Anhui University, Hefei 230601, China. snowfall in an old growth forest. We compared plots with and without rodent exclusion following a heavy snowfall Received: 10 January 2021 Accepted: 27 April 2021 in an old forest. There were three main ecological outputs. First, rodent exclusion enhanced plant regeneration (as in- References dicated by increased plant species richness and abun- Ashley WS, Haberlie AM, Gensini VA (2020) Reduced frequency and size of late- dance). Second, soil basal respiration was strongly twenty-first-century snowstorms over North America. Nat Clim Chang 10(6): 539–544. https://doi.org/10.1038/s41558-020-0774-4 decreased by rodent exclusion, which indicates that Bardgett RD, Caruso T (2020) Soil microbial community responses to climate plant–rodent interactions indirectly affect soil carbon dy- extremes: resistance, resilience and transitions to alternative states. Philos Trans namics. Third, the main factor associated with the de- R Soc B-Biol Sci 375(1794):20190112. https://doi.org/10.1098/rstb.2019.0112 Bardgett RD, Hobbs PJ, Frostegård Å (1996) Changes in soil fungal:bacterial crease in soil basal respiration and therefore with the biomass ratios following reductions in the intensity of management of an potential for increased soil carbon sequestration in upland grassland. Biol Fertil Soils 22(3):261–264. https://doi.org/10.1007/ rodent-exclusion plots was the composition of the soil mi- BF00382522 Bardgett RD, van der Putten WH (2014) Belowground biodiversity and ecosystem crobial community, which in turn was regulated by plants. functioning. Nature 515(7528):505–511. https://doi.org/10.1038/nature13855 The above conclusions and implications produced by this Bardgett RD, Wardle DA (2003) Herbivore-mediated linkages between study can be important for sustainable forest management aboveground and belowground communities. Ecology 84(9):2258–2268. https://doi.org/10.1890/02-0274 in face of extreme snow storm in future. Boone SR, Mortelliti A (2019) Small mammal tree seed selection in mixed forests of the eastern United States. Forest Ecol Manage 449:117487. https://doi. org/10.1016/j.foreco.2019.117487 Supplementary Information Cao L, Wang Z, Yan C, Chen J, Guo C, Zhang Z (2016) Differential foraging preferences on The online version contains supplementary material available at https://doi. seed size by rodents result in higher dispersal success of medium-sized seeds. org/10.1186/s40663-021-00310-2. Ecology 97(11):3070–3078. https://doi.org/10.1002/ecy.1555 Contosta AR, Burakowski EA, Varner RK, Frey SD (2016) Winter soil respiration in a Additional file 1: Figure S1. Field experimental plots setting after humid temperate forest: the roles of moisture, temperature, and snowpack. J extreme snow event in 2015. The up one means the conceptual figure of Geophys Res-Biogeosci 121(12):3072–3088. https://doi.org/10.1002/201 experiment design, the below ones show the mesh on the field plot. 6JG003450 Core Team R (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Acknowledgments Diaz-Yanez O, Mola-Yudego B, Ramon Gonzalez-Olabarria J, Pukkala T (2017) How We thank Zhiyun Lu and Hangdong Wen from the Ailaoshan Station for does forest composition and structure affect the stability against wind and Subtropical Forest Ecosystem Studies for their field assistance. We also thank snow? Forest Ecol Manage 401:215–222. https://doi.org/10.1016/j.foreco.2017. three anonymous reviewers for their insightful comments. 06.054 Fei SL, Jo I, Guo QF, Wardle DA, Fang JY, Chen AP, Oswalt CM, Brockerhoff EG Authors’ contributions (2018) Impacts of climate on the biodiversity-productivity relationship in BW and JW acquired the funding and designed the experiment. QZ, JW, SX, natural forests. Nat Commun 9(1):5436. https://doi.org/10.1038/s41467-018- ZC, BW, and DL collected and analyzed the data. The authors jointly 07880-w contributed to the writing of the manuscript and approved the final Frostegård Å, Bååth E (1996) The use of phospholipid fatty acid analysis to manuscript. estimate bacterial and fungal biomass in soil. Biol Fertil Soils 22(1-2):59–65. https://doi.org/10.1007/BF00384433 Funding Frostegård Å, Tunlid A, Bååth E (2011) Use and misuse of PLFA measurements in This research was funded by National Natural Science Foundation of China soils. Soil Biol Biochem 43(8):1621–1625. https://doi.org/10.1016/j.soilbio.201 (Nos. 31971497, 31971444), by Yunnan Key Laboratory of Plant Reproductive 0.11.021 Adaptation and Evolutionary Ecology and Yunnan University (No. Ge J, Xiong G, Wang Z, Zhang M, Zhao C, Shen G, Xu W, Xie Z (2015) Altered C176210103). dynamics of broad-leaved tree species in a Chinese subtropical montane mixed forest: the role of an anomalous extreme 2008 ice storm episode. Ecol Availability of data and materials Evol 5(7):1484–1493. https://doi.org/10.1002/ece3.1433 The datasets used and/or analyzed during the current study are available Jactel H, Gritti ES, Drossler L, Forrester DI, Mason WL, Morin X, Pretzsch H, from the corresponding author on reasonable request. Castagneyrol B (2018) Positive biodiversity-productivity relationships in Zhou et al. Forest Ecosystems (2021) 8:30 Page 10 of 10 forests: climate matters. Biol Lett 14(4):20170747. https://doi.org/10.1098/ Stephenson NL, Das AJ, Condit R, Russo SE, Baker PJ, Beckman NG, Coomes DA, rsbl.2017.0747 Lines ER, Morris WK, Rüger N, Álvarez E, Blundo C, Bunyavejchewin S, Jing X, Sanders NJ, Shi Y, Chu H, Classen AT, Zhao K (2015) The links between Chuyong G, Davies SJ, Duque Á, Ewango CN, Flores O, Franklin JF, Grau HR, ecosystem multifunctionality and above- and belowground biodiversity are Hao Z, Harmon ME, Hubbell SP, Kenfack D, Lin Y, Makana JR, Malizia A, mediated by climate. Nat Commun 6(1):8159. https://doi.org/10.1038/ Malizia LR, Pabst RJ, Pongpattananurak N, Su SH, Sun IF, Tan S, Thomas D, ncomms9159 van Mantgem PJ, Wang X, Wiser SK, Zavala MA (2014) Rate of tree carbon accumulation increases continuously with tree size. Nature 507(7490):90–93. Kang H, Chang M, Liu S, Chao Z, Zhang X, Wang D (2020) Rodent-mediated https://doi.org/10.1038/nature12914 plant community competition: what happens to the seeds after entering the Tan ZH, Zhang YP, Schaefer D, Yu GR, Liang N, Song QH (2011) An old-growth adjacent stands? Forest Ecosyst 7(1):56. https://doi.org/10.1186/s40663-020- subtropical Asian evergreen forest as a large carbon sink. Atmos Environ 00270-z 45(8):1548–1554. https://doi.org/10.1016/j.atmosenv.2010.12.041 Kayler ZE, De Boeck HJ, Fatichi S, Gruenzweig JM, Merbold L, Beier C, McDowell Ullah S, Muhammad B, Amin R, Haider AH (2019) Sensitivity of Arbuscular N, Dukes JS (2015) Experiments to confront the environmental extremes of mycorrhizal fungi in old-growth forest: direct effect on growth and soil climate change. Front Ecol Environ 13(4):219–225. https://doi.org/10.1890/14 carbon storage. Appl Ecol Environ Res J 17:13749–13758 Venalainen A, Lehtonen I, Laapas M, Ruosteenoja K, Tikkanen OP, Viiri H, Ikonen Keenan RJ, Reams GA, Achard F, de Freitas JV, Grainger A, Lindquist E (2015) VP, Peltola H (2020) Climate change induces multiple risks to boreal forests Dynamics of global forest area: results from the FAO global forest resources and forestry in Finland: a literature review. Glob Chang Biol 26(8):4178–4196. assessment 2015. For Ecol Manag 352:9–20. https://doi.org/10.1016/j.foreco.2 https://doi.org/10.1111/gcb.15183 015.06.014 Wang B, Philips JS, Tomlinson KW (2013) Tradeoff between physical and chemical Lang ZW, Wang B (2016) The effect of seed size on seed fate in a subtropical defense in plant seeds is mediated by seed mass. Oikos 127:440–447 forest, southwest of China. iForest-Biogeosci For 9:652–657 Wang B, Philips JS, Tomlinson KW (2013a) Tradeoff between physical and chemical Lange M, Eisenhauer N, Sierra CA, Bessler H, Engels C, Griffiths RI, Mellado- defense in plant seeds is mediated by seed mass. Oikos 127:440–447 Vazquez PG, Malik AA, Roy J, Scheu S, Steinbeiss S, Thomson BC, Trumbore Wang B, Ye CX, Cannon CH, Chen J (2013b) Dissecting the decision making SE, Gleixner G (2015) Plant diversity increases soil microbial activity and soil process of scatter-hoarding rodents. Oikos 122(7):1027–1034. https://doi. carbon storage. Nat Commun 6(1):6707. https://doi.org/10.1038/ncomms7707 org/10.1111/j.1600-0706.2012.20823.x Lehtonen I, Kamarainen M, Gregow H, Venalainen A, Peltola H (2016) Heavy Wardle DA, Zackrisson O (2005) Effects of species and functional group loss on snow loads in Finnish forests respond regionally asymmetrically to projected island ecosystem properties. Nature 435(7043):806–810. https://doi.org/10.103 climate change. Nat Hazards Earth Syst Sci 16(10):2259–2271. https://doi. 8/nature03611 org/10.5194/nhess-16-2259-2016 Wu J, Liu Z, Chen D, Huang G, Zhou L, Fu S (2011) Understory plants can make Li W, Wu J, Bai E, Jin C, Wang A, Yuan F, Guan D (2016) Response of terrestrial substantial contributions to soil respiration: evidence from two subtropical carbon dynamics to snow cover change: a meta-analysis of experimental plantations. Soil Biol Biochem 43(11):2355–2357. https://doi.org/10.1016/j. manipulation (II). Soil Biol Biochem 103:388–393. https://doi.org/10.1016/j. soilbio.2011.07.011 soilbio.2016.09.017 Xu J, Xue L, Su Z (2016) Impacts of forest gaps on soil properties after a severe Liu G (1996) Soil physical and chemical analysis and description of soil profiles. ice storm in a Cunninghamia lanceolata stand. Pedosphere 26(3):408–416. China Standard Press, Beijing (in Chinese) https://doi.org/10.1016/S1002-0160(15)60053-4 Luyssaert S, Schulze ED, Börner A, Knohl A, Hessenmöller D, Law BE, Ciais P, Yang X, Yan C, Gu H, Zhang Z (2020) Interspecific synchrony of seed rain shapes Grace J (2008) Old-growth forests as global carbon sinks. Nature 455(7210): rodent-mediated indirect seed–seed interactions of sympatric tree species in 213–215. https://doi.org/10.1038/nature07276 a subtropical forest. Ecol Lett 23(1):45–54. https://doi.org/10.1111/ele.13405 Morales-Hidalgo D, Oswalt SN, Somanathan E (2015) Status and trends in global Zhao CY, Fang YH, Luo Y, Wang J (2016) Interdecadal component variation primary forest, protected areas, and areas designated for conservation of characteristics in heavy winter snow intensity in north-eastern China and its biodiversity from the global forest resources assessment 2015. Forest Ecol response to sea surface temperatures. Atmos Res 180:165–177. https://doi. Manage 352:68–77. https://doi.org/10.1016/j.foreco.2015.06.011 org/10.1016/j.atmosres.2016.05.016 Mundim FM, Bruna EM (2016) Is there a temperate bias in our understanding of Zhou G, Liu S, Li Z, Zhang D, Tang X, Zhou C, Yan J, Mo J (2006) Old-growth how climate change will alter plant-herbivore interactions? A meta-analysis forests can accumulate carbon in soils. Science 314(5804):1417. https://doi. of experimental studies. Am Nat 188(S1):S74–S89. https://doi.org/10.1086/ org/10.1126/science.1130168 Zhou Y, Newman C, Chen J, Xie Z, Macdonald DW (2013) Anomalous, extreme Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA, Phillips OL, weather disrupts obligate seed dispersal mutualism: snow in a subtropical Shvidenko A, Lewis SL, Canadell JG, Ciais P, Jackson RB, Pacala SW, McGuire forest ecosystem. Glob Chang Biol 19(9):2867–2877. https://doi.org/10.1111/ AD, Piao S, Rautiainen A, Sitch S, Hayes D (2011) A large and persistent gcb.12245 carbon sink in the world’s forests. Science 333(6045):988–993. https://doi. org/10.1126/science.1201609 Peltola H, Nykanen ML, Kellomaki S (1997) Model computations on the critical combination of snow loading and windspeed for snow damage of scots pine, Norway spruce and birch sp. at stand edge. Forest Ecol Manage 95(3): 229–241. https://doi.org/10.1016/S0378-1127(97)00037-6 Reyer CPO, Brouwers N, Rammig A, Brook BW, Epila J, Grant RF, Holmgren M, Langerwisch F, Leuzinger S, Lucht W, Medlyn B, Pfeifer M, Steinkamp J, Vanderwel MC, Verbeeck H, Villela DM (2015) Forest resilience and tipping points at different spatio-temporal scales: approaches and challenges. J Ecol 103(1):5–15. https://doi.org/10.1111/1365-2745.12337 Sitters J, Venterink HO (2015) The need for a novel integrative theory on feedbacks between herbivores, plants and soil nutrient cycling. Plant Soil 396(1-2):421–426. https://doi.org/10.1007/s11104-015-2679-y Song QH, Fei XH, Zhang YP, Sha LQ, Wu CS, Lu ZY, Luo K, Zhou WJ, Liu YT, Gao JB (2017a) Snow damage strongly reduces the strength of the carbon sink in a primary subtropical evergreen broadleaved forest. Environ Res Lett 12: Song X, Hogan JA, Brown C, Cao M, Yang J (2017b) Snow damage to the canopy facilitates alien weed invasion in a subtropical montane primary forest in southwestern China. Forest Ecol Manage 391:275–281. https://doi.org/10.101 6/j.foreco.2017.02.031

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Published: May 17, 2021

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