Effects of grazing on plant diversity and productivity in a subtropical forest

doi:10.21203/rs.3.rs-1747154/v1

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Effects of grazing on plant diversity and productivity in a subtropical forest

https://doi.org/10.21203/rs.3.rs-1747154/v1

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Background

Controversies exist in the relationship between plant diversity and productivity. One contributing factor to the controversies is that plant productivity is determined by different sets of factors at different scales. On a regional scale, climate, topography, soil and temperature play a major role in productivity. On a local scale, human interference, natural interference or the mechanism of plant regeneration ability after disturbance are the main factors affecting plant productivity.

Methods

To determine the effect of grazing intensity on the relationship between plant diversity and productivity, and comprehensively analyze the impact of livestock grazing on its species composition, ecosystem productivity and soil nutrient cycling. We conducted a livestock grazing category experiment based on the dry weight of livestock manure collected in a subtropical forest in Hubei Province, China.

Results

The results showed that grazing significantly reduced stand density, above-ground biomass (AGB), soil total phosphorus (STP), soil total nitrogen (STN), Shannon-Wiener index and plant productivity, but increased Berger–Parker index. Moreover, grazing altered the relationship between plant diversity index, soil nutrients and plant productivity. In light grazing areas, the general linear model showed that soil organic carbon (SOC), STP, STN and stand density were positively correlated with the Shannon-Wiener index and plant productivity. SOC, STP, STN and stand density were negatively correlated with Berger–Parker index. The Shannon–Wiener index was positively correlated with plant productivity. The Berger–Parker index was negatively correlated with plant productivity. In heavy grazing areas, however, the relationship between SOC, STP, STN, stand density and Shannon–Wiener index and plant productivity was reversed, and the correlation between SOC, STP, STN, stand density and Berger-Parker index also changed from negative to positive.

Conclusions

Our study suggested that heavy grazing altered the relationship between plant diversity and productivity. Therefore, appropriate grazing management could lead to a better understanding of the relationship between subtropical plant diversity and productivity.

Forest

Grazing

Plant productivity

Subtropical

Grazing is an important factor affecting plant composition and structure. Moreover, grazing changes the status of plant resources and the competitive relationship between plant species (Boughton et al. 2016). Specifically, the feeding intensity of grazing on plants can change the competitiveness of plants to resources in the community. Plants can change their composition and spatial structure in order to resist livestock feeding. To a certain extent, appropriate grazing is conducive to the improvement of vegetation structure and the proportion of dominant species and has a positive impact on species richness and diversity (Fagundez 2016). According to the moderate disturbance hypothesis (Connell 1978), there is a unimodal relationship between grazing intensity and plant diversity, that is, moderate disturbance levels can maintain higher diversity (Roxburgh et al. 2004). However, heavy grazing also usually increases plant diversity on humid grassland, and grazing on low productivity grassland usually reduces plant diversity (Bakker et al. 2006). Under the condition of light grazing, the level of plant diversity in North American grassland is relatively high (Collins 1987). High grazing intensity significantly reduces plant α and β diversity indices (tree and shrub layers) in Northeast Brazil, and South America (Schulz et al. 2019). Grazing on plants β diversity index has a positive impact, increasing species heterogeneity and making species highly replaced (Oldén and Halme 2016). The species diversity of Tibetan temperate grassland is high under no grazing conditions but is significantly reduced under moderate and heavy grazing conditions (Xiang et al. 2019).

The effects of grazing on plant productivity are not consistent at different scales. Grazing has a neutral or reduced effect on plant productivity (Yan and Haiping 2010), and a few studies show that grazing could increase plant productivity (Dong et al. 2004). Grazing can effectively change the regeneration ability of the plant. The effect of grazing on the above-ground biomass of plants is to reduce the leaf area index of plants by eating the leaves and twigs of plants, and then interfere with the synthesis and supply of carbohydrates and the accumulation of storable nutrients, thus affecting the normal growth of plants. Livestock grazing may stimulate plant growth, leading to higher biomass production (Ellison 1960). Due to the differences in the production and accumulation capacity of plant photosynthates, as well as the differences in feeding mode and feeding preference of livestock, the above-ground biomass of the community varies greatly under different grazing intensities (Del Pozo et al. 2006), and the regeneration capacity of plants under grazing disturbance depended on the trade-off between promoting and inhibiting growth mechanisms. According to the grazing optimization hypothesis (McNaughton 1979), moderate grazing can stimulate the growth of forage and increase the fitness of plants (Dyer 1975). Compared with no grazing, the primary productivity of plants increases in low grazing decreases in high grazing and reaches the maximum in medium grazing. Moderate grazing is conducive to the increase of species, thus increasing the level of plant diversity (Huston and systematics 1985). Other studies have found that the productivity of plants decreases with the increase in grazing intensity (Yan and Haiping 2010). The plant leaves eaten by livestock reduce the leaf area and photosynthesis, which seriously affects the growth of plants (Danell and Bergstrm 2002). Livestock feeding and trampling affect the productivity and ecological function of plants, plant mortality, the spatial structure of plants, the species composition of aboveground vegetation and the direction of community succession (Li et al. 2009).

Grazing is one of the main factors that interfere with the change of soil properties in a forest ecosystem. In the soil-plant-livestock system, grazing affects the soil's physical and chemical properties. Heavy grazing reduces the concentration of soil C and K, the ratio of C/N and C/ P (Mipam et al. 2021), and has a significant negative impact on soil organic matter, total nitrogen, available nitrogen, total phosphorus and available phosphorus (Wu et al. 2009). Overgrazing leads to the fragmentation of plant residues, the reduction of litter, the reduction of coverage, the serious degradation of grassland, the reduction of soil water infiltration, and the serious soil erosion (Fox 2001; Yates et al. 2000). Soil nutrients are directly and indirectly affected by livestock dung and urine and grazing-induced variations in soil heat-water conditions (Wang et al. 2016). Continued livestock grazing causes soil compaction under vegetation (Piñeiro et al. 2010), destroys surface vegetation, increases soil erosion severity (Pfister et al. 1986), and causes changes in species composition. Grazing can enhance root exudates and microbial activity and increase nutrient availability to plants, thereby altering plant nutrient stoichiometry (Frank 2008). However, as the grazing intensity increases, the frequent trampling of livestock reduces the vegetation cover and litter, soil organic matter, soil organic carbon and total nitrogen (Dong et al. 2012).

The subtropical forest of China has a warm and humid climate, abundant precipitation, many forest resources and high vegetation coverage. Therefore, the forest area is strongly affected by human disturbance (grazing and logging). The increase of external interference frequency can reduce the plant productivity of temperate forests with a long recovery time (Silva Pedro et al. 2016). Human interference can reduce the plant diversity and heterogeneity of the Pearl River Source Nature Reserve and delay the process of vegetation restoration and succession (Wen 2002). In eastern China, soil nutrients have an important direct impact on plant diameter at breast height, and species diversity has a direct positive impact on above-ground biomass (Ali et al. 2017). In the forest ecosystem in Southwest China, road interference has the greatest impact on plant diversity. The left waste leads to the serious destruction of plant vegetative propagules. Plant seed germination is inhabited due to a lack of water and soil, resulting in reduced species richness and diversity (Zhou and Long 2011). Canopy gap disturbance in subtropical regions reduces competition and repulsion among plants, enhances stand structure diversity, provides a better growth environment for suppressed vegetation under forests, and enhances plant productivity (Ren et al. 2021). Previous studies have investigated the effects of age, abundance and stand density on forest plant productivity in subtropical regions (Ouyang et al. 2019), effects of biodiversity and functional properties on plant biomass and productivity during forest restoration (Miao et al. 2021) and effects of biodiversity on tree growth during forest plant succession in a subtropical zone (Barrufol et al. 2013). However, it is rarely reported that the effects of grazing on forest plant diversity and CWP in subtropical regions. Here, we studied the effects of grazing by goats in a subtropical forest in Hubei Province. We sampled the grazing areas of farmers and divided the sample plots into three categories: light grazing, moderate grazing and heavy grazing. We aimed to (1) test whether there is a linear relationship between plant diversity and productivity under three grazing levels (2)study the relationship between grazing and soil nutrients and (3) explore the relationship between grazing and plant diversity and productivity.

Study Area and Experimental Design

This study was conducted in a forest farm located in a subtropical forest of Nanzhang county, Xiangyang region, Northwest Hubei Province, China (Fig. 1). The area has a subtropical monsoon climate with four distinct seasons, moderate rainfall, sufficient sunlight and a long frost-free period. The average annual precipitation is 800-1200mm, 68% of which is in the April to September period (Table.1). The average annual relative humidity is 76.3%. The area is a part of the Jingshan Mountain Range with low mountains and hills. Elevation of the area varies from 300 to 800 m and is high in the west and low in the east. The main soil is yellow-brown soil and fluvo-aquic soil. The texture is mainly sandy soil, light soil, medium soil and heavy soil. The soil thickness is generally 10-15cm. Livestock mainly feeds tree species on Lindera glauca, Quercus acutissima, Cyclobalanopsis gracilis, Robinia pseudoacacia, Lithocarpus glaber, Cyclobalanopsis glauca. shrub species on Rosa multiflora, Rhododendron simsii, Forsythia suspensa, Liquidambar formosana. herb species on Erigeron annuusetc, Viola philippica, Imperata cylindrica, Rubus lambertianus, Pennisetum alopecuroides.

In the study area, livestock roamed freely in the unfenced forest areas.The movement of livestock is uncontrolled. Hence. it is not possible to estimate the grazing intensity based on the stocking rate. We used the weight of animal manure per m² as the indicator of livestock loads and grazing intensity (Schulz et al. 2016). Apart from direct grazing, farmers harvested large quantities of young leaves and shoots of the tree species as fodder during the dry season. This practice may also lead to changes in plant productivity and community species composition. Therefore, a restricted random method was used to cover the grazing intensity. Goat grazing was visually assessed in August 2015, 12 plots (20×20 m) were selected for study and divided into three grazing categories based on the signs of goat activities. Grazing category: heavy grazing, more than 50% of the plants showed signs of grazing and goat trampling; moderate grazing, 10–50% of the vegetation showed signs of grazing and goat trampling; and light grazing, < 10% of the vegetation showed signs of grazing and goat trampling. We then established 4 plots (4×4 m) in each of the grazing categories. The final grazing intensity of each plot was determined based on the dry weight of livestock manure collected. Grazing intensity was divided into: (a) light grazing (goat manure < 2 g/m², LG); (b) moderate grazing (goat manure = 2 ~ 20 g/m², MG); (c) heavy grazing (goat manure > 20 g/m², HG). In order to reflect the grazing system, we collected all the dung of livestock on the plot (20 m × 20 m) and recorded the number of woody plants with obvious signs of grazing in each plot. We found that these two variables were positively correlated, thus validating the method of quantifying grazing intensity by manure weight (Schulz et al. 2019). In May 2016, we established a total of 89 plots (30 LG, 28 MG and 31 HG). All individual trees (diameter at breast height ≥ 1 cm) within the plot. Within each plot, we marked 5 quadrats of 4m × 4m (Fig. 1 showing the layout of the quadrats), shrubs and herbs within the plot were marked, mapped, measured, and species identified, we collected soil variables (depth and nutrient content). These quadrats were surveyed again in May 2018 and May 2020.

Table 1 The monthly average temperature and precipitation for the study period and the long term average of the study site. Data are from the China Meteorological Data Network (http://data.cma.cn)

Data Collection and Calculation

In the plot survey, we recorded the following data for tree species, diameter at breast height, species, tree height, crown width, relative density, canopy cover and frequency. For herb and grass species, we measured species, height, canopy cover and frequency. Stand density represents the strength of plant-plant interactions (Forrester and Bauhus 2016), summarizing the number of individual trees in a quadratic. The number of species within each quadrat and plot was used as the plant species richness (N) at the plot and plot level, respectively. The quadrants near each fixed quadrat were used to assess AGB, all plants in each quadrat were collected, kept in specimen holders, and performed in the laboratory, roots were rinsed with water, and then mixed with other live plant material at 65℃ after drying in an oven for 48 hours, the samples were weighed (Wu et al. 2009). Each sample was air-dried and stored at room temperature until the soil's physical and chemical properties could be determined. For soil sampling, in the quadrats soil samples were taken at three points the other two corners and the center, along that diagonal on which root samples had not been collected. Soil samples from a depth of 15 cm per quadrat were measured using a soil bulk sampler with a 5 cm diameter and a 5 cm high stainless steel cutting ring at points adjacent to where soil samples had been collected for chemical analysis. In each of the UG, LG and MG plots, five replicated soil samples were collected and were passed through a 2 mm screen to remove roots and other debris (Bueno et al. 2013). Soil organic carbon and total nitrogen were determined by Walkley Black method (Nelson and Sommers 1996) and Kjeldahl acid digestion method (Foss Kjeltec 8400, Foss, DK), respectively. Total phosphorus was determined by Mo-Sb colorimetric method (UV-2102C, UNICO, Shanghai, China). We used the number of plant families, genera and species from the field inventories as a measurement of plant diversity, we calculated the Shannon–Wiener diversity index (Eq. 1), which is calculated from relative species dominance (Pi), where Pi is the relative importance of species i. The Berger-Parker index (Eq. 2), which is the ratio of the maximum number of dominant species (N_max) to the number of all species (N), was also calculated.

β diversity refers to the difference in species composition in different communities or the species replacement rate along the environmental gradient (Baselga and biogeography 2010). We calculated β diversity index across treatments at the 240-plot level. Species turnover was expressed as Simpson dissimilarity (Eq. 3). Species nestedness was expressed as a nestedness-resultant fraction of Sørensen dissimilarity (Eq. 4). Species overall β diversity was expressed as Sørensen dissimilarity (Eq. 5), where r is the number of species shared in the two plots, s is the number of species that appeared only on the species-poorest plots, and t is the number of species that appeared only on the species-richest plots.

We used all individuals with DBH ≥ 5 cm for analysis to calculate the above-ground biomass of each tree, and we calculated the AGB using the species-specific equation (Appendix). The initial above-ground biomass is used to evaluate the impact of the number of vegetation on productivity (Lohbeck et al. 2015; Yuan et al. 2019), where the sum of the biomass of all trees in each quadrat is expressed, and the plant productivity of each plot is determined as the biomass increment from t1 to t2 (Eq. 6). We calculated the crude wood productivity, and then add the production values of all trees in the quadrat (Eq. 7), and scaled up to Mg ha^− 1 year^− 1 (Yuan et al. 2018). CWP_i is the coarse wood productivity of the ith single tree in the jth quadrat, AGB_t1 and AGB_t2 are the AGB of the ith single tree in the jth quadrat measured in t1 and t2 respectively, where k represents LG, MG or HG.

(1)

B = N_max/N (2)

βsim=\(\frac{\text{s}}{\text{r}+\text{s}}\) (3)

βsne=(\(\frac{\text{t}-\text{s}}{2\text{r}+\text{s}+\text{t}}\))(\(\frac{\text{s}}{\text{r}+\text{s}}\)) (4)

βsor = βsim + βsne (5)

CWP_i=\(\frac{\text{A}\text{G}\text{B}\text{t}2-\text{A}\text{G}\text{B}\text{t}1}{\text{t}2-\text{t}1}\) (6)

(7)

Statistical analyses

To determine the effects of grazing intensity on vegetation and soil nutrients, we used one-way ANOVA to compare differences in species diversity, stand density, soil nutrient content, initial above-ground biomass and plant productivity (CWP) between plots of different grazing intensities. We used the general linear model (GLM) to analyze the relationship between soil nutrients, stand density, plant diversity index and plant productivity under different grazing intensities. All data analyses were performed using R statistical software version 4.0.3 for Windows (Team 2013).

Comparisons of Soil nutrients, AGB, Stand density and CWP

As grazing intensity increased, STN and STP decreased significantly, SOC, AGB, stand density and CWP increased first and then decreased (Fig. 2). STN and STP were significantly lower under MG conditions than under LG. In contrast, SOC, AGB, stand density and CWP were significantly higher under MG conditions than under LG. STN, STP, AGB, stand density and CWP under HG conditions were significantly lower than under LG and MG, but SOC was significantly higher than that of LG (Fig. 2c, p < 0.001). Soil STN under HG was lower than that under LG and MG, but showed no significant difference between HG and MG (Fig. 2a, p > 0.05). The AGB under MG was higher than that under LG and HG, but showed no significant difference in AGB between HG and MG (Fig. 2d, p > 0.05). The stand density under MG was higher than that under LG and HG, but showed no significant difference between LG and MG (Fig. 2e, p > 0.05). The CWP under HG was lower than that under LG and MG, but showed no significant difference between HG and MG (Fig. 2f, p > 0.05)

Comparisons of Community Assembly

Community dissimilarities were dominated by species turnover, the dissimilarity value of species turnover between LG and HG was 0.167 in 2016, which was lower than that between LG and MG (0.206) and MG and HG (0.195). In 2018, the dissimilarity value of species turnover reached the lowest, 0.145 (for between MG and HG), 0.153 (for between LG and MG), and 0.147 (for between MG and HG). The dissimilarity values of species turnover increased from 2018 to 2020 (Fig. 3a). The contribution of nestedness components in this study was relatively small(Fig. 3b). The nestedness dissimilarity between LG and HG, LG and MG, and MG and HG were similar from 2016 to 2020, showing a trend of first increasing and then decreasing. In 2018, the nestedness dissimilarity value between LG and MG reached a maximum value of 0.164, which was higher than that between LG and HG (0.139) and between MG and HG (0.112). For the total dissimilarity, the changes between LG and HG, LG and MG and MG and HG were similar, showing a gradual upward trend from 2016 to 2020. Additionally, the total dissimilarity value between LG and MG was higher than that between LG and HG, MG and HG, the total dissimilarity value between LG and MG reached the maximum of 0.329 in 2020 ( Fig. 3c). There were significant differences in Shannon–Wiener index between grazing treatments between LG and MG from 2016 to 2020, and between MG and HG in 2016, 2018 and 2020 (Fig. 4a 4b 4c, p < 0.01). The Shannon–Wiener index under LG showed an upward trend from 2016 to 2018, while the Shannon–Wiener index under MG and HG showed a downward trend. There was no significant difference in Berger–Parker index between LG and MG treatments in 2018 (Fig. 4e, p > 0. 05). In 2020, there was no significant difference in Berger–Parker index between MG and HG (Fig. 4f, p > 0.05). However, in 2016, there were significant differences in Berger–Parker indices between all treatments (Fig. 4d, p < 0.01). There was a significant difference in Berger–Parker index between MG and HG treatments in 2018 (Fig. 4e, p < 0.05), and a significant difference in Berger–Parker index between LG and MG in 2020 (Fig. 4f, p < 0.01).

The Relationship between Plant diversity, Stand density, Soil nutrients and CWP

There was a significant negative correlation between soil nutrients SOC, STN, STP and Berger–Parker indices under LG conditions, but under MG and HG conditions, grazing changed the linear relationship between SOC (Fig. 5a), STN (Fig. 5b), STP (Fig. 5c) and Berger–Parker indices from a negative correlation to a positive correlation, and the slopes of SOC, STN, STP and Berger–Parker indices became smaller as grazing intensity increased. Under LG conditions, the Shannon-Wiener index increased with increasing SOC, STN and STP, but under MG and HG conditions, grazing changed the linear relationship between SOC (Fig. 5d), STN (Fig. 5e), STP (Fig. 5f) and Shannon-Wiener indices, showing a negative correlation, and the slopes of SOC, STN, STP and Shannon-Wiener indices became smaller as grazing intensity increased. Under LG conditions, there was a significant positive correlation between SOC, STN, STP and CWP, but under MG and HG conditions, grazing changed the pattern of SOC (Fig. 5g), STN (Fig. 5h), STP (Fig. 5i) and CWP from a negative correlation to a positive correlation. As grazing intensity increased, the slope of CWP became steeper with the change of SOC, STN and STP. Under LG and MG conditions, the slope of Berger–Parker index changed more slowly with stand density as grazing intensity increased, and there was a significant negative correlation between stand density and Berger–Parker index, and under HG conditions, heavy grazing changed the pattern between stand density and Berger–Parker index from a negative correlation to a positive correlation (Fig. 5j). Under LG conditions, there was a significant positive correlation between stand density and Shannon–Wiener index, but grazing changed the linear relationship between stand density and Shannon–Wiener index, showing a negative correlation (Fig. 5k). Under LG conditions, there was a significant positive correlation between stand density and CWP, but under MG and HG conditions, grazing changed the linear relationship between stand density and CWP from a positive correlation to a significant negative correlation (Fig. 5l). As the grazing intensity increased, the slope of CWP became steeper. In contrast, the slope of CWP was reduced as stand density changed. Under LG and MG conditions, the slope of Berger–Parker index changed more slowly with CWP as grazing intensity increased, there was a significant negative correlation between Berger–Parker index and CWP, but under HG conditions, heavy grazing changed the linear relationship between Berger–Parker index and CWP from a negative correlation to a positive correlation (Fig. 5m). There was a significant negative correlation between Berger–Parker and Shannon–Wiener indices in all treatments, and the slope of Berger–Parker index changed more slowly with Shannon–Wiener index as grazing intensity increased, and the slope became steeper (Fig. 5n). The slope of Shannon-Wiener index showed a graduate change as grazing intensity increased, there was a significant positive correlation between Shannon–Wiener index and CWP under LG and MG conditions, and heavy grazing changed the linear relationship between Shannon–Wiener index and CWP from a positive correlation to a negative correlation under HG conditions (Fig. 5o).

In the present study, we demonstrated that grazing changed the relationship between stand density and CWP in subtropical forest areas (Fig. 5l). As grazing intensity increased, stand density and AGB decreased, and plant α and β diversity also changed. There was a positive linear relationship between soil nutrients and plant CWP, but heavy grazing decreased the SOC (Fig. 5g), STN (Fig. 5h) and STP (Fig. 5i) contents of soil nutrients, and changed the linear relationship between SOC, STN, STP and CWP from a positive correlation to a negative correlation. In general, the GLM showed that heavy grazing altered the diversity and productivity of forest plants in subtropical regions. All potential mechanisms and causes are discussed below.

Effects of Grazing Intensity on AGB, Stand density, Soil nutrients and CWP

Grazing in subtropical areas reduced the productivity of forest plants. Our results showed that the plant AGB decreased significantly with the increase in grazing intensity (Fig. 2d), which in turn reduced plant productivity (Fig. 2f). Our results also confirmed other studies that moderate grazing made dwarf shrubs basically disappear and reduced their primary productivity (Olofsson et al. 2001). Sheep grazing disturbance had a great impact on the above-ground biomass of plants in the desert grassland in northern China. The increase in grazing intensity led to the continuous decline of plant community productivity (Zhang et al. 2018). Therefore, in our study, the response of plant AGB and productivity to grazing disturbance was obvious. This was because livestock directly reduced AGB by eating a large number of herbaceous plants (such as Gramineae, oxalicaceae, etc. ) and leaves and branches of shrub plants (Rosaceae, Euphorbiaceae, etc. ), resulting in fragmentation and miniaturization of population plants. The reduction of plant biomass affected the photosynthesis and transpiration of plants, thus hindering the growth and reproduction of plants, and finally leading to the direct decline of plant CWP. Plants under heavy grazing disturbance reduced stand density in this study (Fig. 2e), Other studies had also confirmed that more elk herds reduced the density of vegetation, and species richness and changed the speed of vegetation succession (Randall et al. 2011). Heavy grazing caused stand density to decline because strong predation pressure from livestock limited plant nutrient replenishment and growth, resulting in severe plant population reductions. However, under the condition of moderate grazing, the stand density of a few plots increased. On the one hand, we believe that the long precipitation time in the study area resulted in the livestock being fed by farmers in the livestock pens and could not be eaten in the wild. Furthermore, the precipitation increased the wet weight of the soil and enabled the plants to continue to grow again. On the other hand, moderate grazing could benefit root distribution and germination capacity adaptation syndrome (Milchunas and Lauenroth 1993), increase vegetation light availability, and enhance plant photosynthesis effect, stimulate plant growth, and promote the increase of plant density based on the interaction between grazing and vegetation growth. Soil properties are important factors affecting plant biomass, species richness and species composition. Grazing intensity is an important factor affecting the change of soil properties of the ecosystem, soil nutrients (SOC, STN, STP) are affected in grazing areas (Dingaan et al. 2016). In our study, Grazing had significant adverse effects on soil physicochemical properties in a subtropical forest. STN (Fig. 2a) and STP (Fig. 2b) showed a downward trend with the increase in grazing intensity. Under the condition of heavy grazing, the contents of soil STN and STP were less than light grazing. Our results were consistent with other researchers. The effect of grazing on soil STN and STP was obvious, and the content of STN and STP gradually decreased with the increase in grazing intensity (Dong et al. 2012; Zhang et al. 2018). In addition, the feeding, trampling and arching of animals in the coastal area reduced the vegetation coverage, severely disturbed areas even became bare land, and soil nutrients were significantly reduced (An et al. 2020). The result of this study was the increase in livestock excreta and livestock activities under the condition of heavy grazing pressure. In the meantime, the trampling caused the hardiness of soil, decreasing soil porosity, water content, the coverage of surface plants. It accelerated soil-surface evaporation and soil erosion by wind, and the loss of soil STN and STP (Buxton et al. 1996; Wu et al. 2010). Continuous grazing led to the reduction of vegetation cover and litter accumulation, the exposure and coarseness of soil, the low concentration of STN and STP and the reduction of soil biological characteristics (Su et al. 2005). Strangely, in individual plots, we found that soil STN and STP increased, we thought that the feed for livestock contained more salt. After digestion and absorption, part of the salt was excreted as feces and urine, resulting in the increase of salt content in the soil and further increasing the content of nitrogen and phosphorus in the soil. This was the result of the joint action of the reduction of plant absorption and the increase of soil salt. Compared with light grazing, moderate grazing significantly increased the content of SOC (Fig. 2c). This result is consistent with the findings of other studies. The content of soil SOC under moderate grazing was significantly higher than that under heavy grazing in the semi-arid grasslands of South Africa (Dingaan et al. 2016). When under moderate grazing, the trampling by livestock helped the integration of organic matter with the soil, coupled with direct N and P input through feces and urine. As a result, plant growth increased. Under heavy grazing conditions, soil SOC decreased significantly. On the one hand, Heavy trampling may have exposed soil surface and decreased soil microbial activity, which hinders the decomposition of plant residues and slows down the release of nutrients from the litter. On the other hand, soil organic carbon in forest is derived mainly from the decomposition of plant litter (Liu et al. 2017). Due to the destruction of vegetation and feeding by grazing under heavy grazing conditions, the litter was decreased, thus reducing the carbon input in the soil (Peng et al. 2018). The soil is one of the important sources for plants to obtain nutrition and plays an important role in the process of plant growth. Soil and plants interacted and developed in coordination (Li et al. 2014). Soil, vegetation and livestock are important components of the forest ecosystem. Soil is an important substrate for biomass production, a repository for soil nutrients, a place for animal and plant decomposition and circulation, and a carrier for plant and livestock. The two influenced and restricted each other. Therefore, we need to find out the impact of grazing on soil physical and chemical properties, understand the process and mechanism of soil degradation caused by unreasonable grazing, and then take reasonable grazing management measures, which is of great significance to soil and water conservation under the sustainable development of forest ecosystem.

Effects of Grazing Intensity on Plant Community Assembly

Plant turnover is a common phenomenon of plant coexistence in plant community species (Bar-Massada and Hadar 2017; Chesson and Systematics 2000), and grazing is an important factor affecting species importance values and a direct driving force for species turnover. Under long-term free grazing conditions, the composition of vegetation, biodiversity, and replacement of invasive species have changed (Sour et al. 2013), grazing can contribute to better management with the appropriate condition of pasture carrying capacity and grazing rate, making plant turnover more stable (Sanaei et al. 2018). In our study, community dissimilarities are closely related to species composition and turnover (Fig. 3a), which strongly correlated with precipitation under LG. Herb communities exhibited high rates of temporal species turnover, which can be explained by the modern co-existence theory, species turnover may be correlated with the different land management. livestock foraged grasses or shrubs such as Gramineae, Rosaceae, Euphorbiaceae, Cyperaceae, Oxalaceae, Moraceae, Fagaceae, Jugaceae, etc. With the increase in grazing intensity, the total dissimilarity of plants showed a rising trend from 2016 to 2020 (Fig. 3c ). This was the process of livestock feeding in the forest, which caused the habitat to be severely damaged, grazing behavior could limit the growth of dominant species, thereby increasing the heterogeneity of the habitat. Due to the trampling and eating of grazing, the normal growth of plants was limited, and even some plants could not survive (Su et al. 2005). In grazing areas, the trampling of numerous livestock and the deposition of feces and urine led to niche differentiation among species with different strategies, which could enhance environmental heterogeneity (Fischer et al. 2019). In this study, grazing significantly affected the diversity index of subtropical forest plants. With increasing grazing intensity, the plant Shannon-Wiener index decreased significantly and the Berger-Parker index increased significantly from 2016 to 2020 (Fig. 4). This might be due to the preference and trampling of plants by livestock, resulting in the reduction of plant biomass, which seriously inhibited the compensatory growth of plants, lessened the regeneration success rate of some species and reduced the species diversity of plant communities (Wei et al. 2008), Furthermore, heavy grazing caused significant changes in dominant species, and the plant species became single, thus changing the stability of plant communities. Similar results were found in other researchers. Grazing significantly decreased vegetation biomass and vegetation coverage, and had a serious impact on the stability of grassland ecosystems in alpine grasslands (Lu et al. 2017). The Shannon-Wiener index of plants under moderate grazing conditions changed little compared with that under light grazing in 2016 (Fig. 4a), we thought that due to the difference in the selective feeding and intensity of livestock, and the functional groups were complementary to each other. Other studies found that grazing prohibition was an effective way to restore the plant diversity of alpine meadows. Grazing prohibition improved significantly the vegetation coverage and species richness in the Qinghai Tibet Plateau (Liu et al. 2020). In other words, the plant coverage diversity of low grazing intensity was higher than that of heavy grazing intensity. This was because the weakening of grazing intensity reduced the number of livestock, indirectly decreased the water evaporation of soil, and then increased the soil humidity, which made it possible to restore vegetation and reduced plant dissimilarity (Deng et al. 2017; Wu et al. 2014). Therefore, it just verified our view that the plant diversity under LG was significantly higher than that under HG, the plant dissimilarity under LG was lower than that under HG.

Effects of Grazing Intensity on the Biodiversity-Productivity Relationship

In our study, SOC (Fig. 5a), STN (Fig. 5b) and STP (Fig. 5c) were negatively correlated with the Berger-Parker index under light grazing and moderate grazing conditions, but the Berger-Parker index increased with the raise of SOC STN and STP under heavy grazing conditions. One possible reason was the significant decline in the coverage and height of various groups due to heavy grazing and trampling of livestock under heavy grazing conditions. Under light grazing conditions, the Shannon-Wiener index increased with the increase of SOC (Fig. 5d),STN (Fig. 5e) and STP (Fig. 5f), but under the condition of grazing, the Shannon-Wiener index decreased with the increase of SOC, STN and STP. These results are similar to those of other researchers (Prober et al. 2012). Grazing intensities had differential effects on soil nutrients, challenging past positive correlations between plant diversity and soil nutrients under variable grazing intensities (Mipam et al. 2021). The possible reason was that due to the destruction of livestock trampling, the relatively large excretion of feces and urine, the increase of cations content in the soil, the reduction of vegetation, the exposure of the surface, the increase of surface water evaporation, and the accumulation of soluble salts dissolved in groundwater on the soil surface with the rise and migration of root capillary. Therefore, the process made the soil alkaline, resulting in the decline of plant biomass, and then affecting the Shannon-Wiener index. Soil SOC (Fig. 5g), STN (Fig. 5h), and STP (Fig. 5i) were significantly positively correlated with plant CWP under light grazing conditions, and a close relationship between soil properties and plant productivity was demonstrated in other studies (Bai et al. 2000; Xu et al. 2019), but under grazing condition, grazing changed this linear relationship into a negative correlation. Especially, under heavy grazing conditions, grazing extremely changed the slope of the linear regression equation of SOC, STN and STP. The reason was that grazing caused the plants to be sparse, and even part of the surface was exposed, reducing the interception effect of surface dwarf plants on precipitation. With the increase of grazing intensity, grazing made the soil compact, the soil porosity became smaller, the soil water content gradually decreased, the soil moisture evaporation increased, and soil erosion became severe, affecting the soil nutrient composition strongly, which led to the decline of SOC, STN and STP, and ultimately limited plant productivity (Peng et al. 2018). Under the condition of light grazing, stand density was significantly negatively correlated with the Berger-Parker index (Fig. 5j), and stand density was positively correlated with the Shannon-Wiener index (Fig. 5k) and CWP (Fig. 5l), but under heavy grazing conditions, grazing changed these linear relationships. On the one hand, these changes were due to temperature, precipitation and soil nutrient limitations at different spatial scales in the study site. On the other hand, the reason was that the long-term grazing made the above-ground parts of plants ingested, small shrubs and trees were seriously trampled and died, the plant cover and the stand density were reduced, the stand density was decreased, the photosynthesis of the destroyed plants was affected, which hindered the growth, development and reproduction of plants, decreased the Shannon-Wiener index of the plants, and increased the Berger-Parker index. Simultaneously, intensive grazing affected and changed stand density, further triggering changes in plant diversity and reducing plant productivity. Plant diversity is a major factor affecting plant community productivity (Bai et al. 2007), and overgrazing altered the relationship between species diversity and productivity. Under light grazing and moderate conditions, the Berger-Parker index was negatively correlated with plant CWP (Fig. 5m), the Shannon-Wiener index and the Berger-Parker index showed a very significant negative correlation (Fig. 5n), the Shannon-Wiener index and plant CWP were positively correlated (Fig. 5o). Probably, because species with different rooting distributions in a plant community could promote coexistence among species and utilize soil resources more fully and harmoniously, where each species could make full use of natural resources (such as light, available water and soil nutrients) to grow normally (Zuo et al. 2012). In addition, when the number of individuals of each species in the plant community was relatively small, the number of species was large simultaneously, the plant diversity will be larger and the difference will be reduced. Therefore, the species Shannon-Wiener index and plant productivity showed a positive linear pattern. The species Berger-Parker index and plant productivity showed a negative linear pattern. However, heavy grazing conditions significantly altered the relationship between species diversity and productivity. This was similar to other researchers (Guo and Berry 1998), in the long history of grazing, plant diversity and productivity decreased linearly with the raise of grazing intensity, affecting plant community patterns and thus ecosystem resilience (Milchunas et al. 1988). In our study, the difference between the positive correlation between light grazing and the negative correlation between heavy grazing was related to grazing intensity. Heavy grazing transformed the stability of the plant community and the competitiveness between plant species, resulting in a change in plant species niche, thus the linear relationship was significantly altered (Pavlu et al. 2021; Rillig et al. 2019). In the meantime, heavy grazing damaged the forest vegetation seriously and changed the diversity of plants, and then altered the competition and exclusion between plants and the synchronization of species in the community, which reduced the competition between species and increased the remaining niche breadth of other species. Thus, heavy grazing affected the relationship between forest plant diversity and productivity in a subtropical forest.

Our study showed that under light grazing conditions, the Shannon-Wiener index was positively correlated with CWP and the Berger-Parker index was negatively correlated with plant CWP, Heavy grazing reduced stand density, soil SOC, STP, SOC and plant diversity, led to high plant species turnover, decreased the productivity of forest plants, and altered the characteristics of the plant community, soil nutrients, stand density and the linear relationship between plant diversity and productivity. Therefore, according to the carrying capacity of subtropical forests, reasonable grazing is of great significance to forest ecological protection.

Credit author statement

WPJ: Conceptualization, Data curation, Methodology, Formalanalysis, Visualization, Writing-original draft. XYW: Resources, Funding acquisition, Conceptualization. LWX: Data curation. Z S: Software. NLK: Resources, Methodology.

Acknowledgement

This study was financially supported by the National Natural Science Foundation of China (31270740); Hubei Province Technical Innovation Special Major Project(2019ABA113)

Declaration of Competing Interest

In submitting the manuscript, we would like to make the following statements: (1) No conflict of interest exists in the submission of this manuscript; (2) The manuscript is approved by all authors; (3) The work described was original that has not been published previously, and is not under consideration for publication elsewhere, in whole or in part; (4) All the authors listed have made substantial contributions to research design, or the acquisition, analysis or interpretation of data, or drafting the paper or revising it critically; and (5) Nobody who qualifies for authorship has been excluded.

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Table 2 Allometric equations for the calculation of above-ground biomass for each tree species.

Species	Allometric equation	R²
Lithocarpus glaber	AGB = 0.104823D^2.5522	0.97
Liquidambar formosana	AGB = 0.1599D^2.3512	0.97
Loropetalum chinense	AGB = 0.1599D^2.3512	0.97
Cinnamomum camphora	AGB = 0.31599 D^2.04	0.91
Choerospondias axillaris	AGB = 0.25069D^2.23	0.91
Ilex chinensis	AGB = 0.3165D^2.15	0.97
Cyclobalanopsis glauca	AGB = 0.201035 D^2.34	0.97
Ilex hylonoma	AGB = 0.3165D^2.15	0.97
Pinus massoniana	AGB = 0.0459(D²H)^0.8867+0.0127(D²H)^0.7886+0.0283(D²H)^0.6012	0.93
Cunninghamia lanceolata	AGB = 0.00849(D²H)1.10729+ 0.00175(D²H)^1.091916+0.00071D^3.88664	0.93
Larix gmelinii	AGB = 0.099496(D²H)^0.78653+0.09862(D²H)^0.598367+0.294136(D²H)^0.357506	0.93
Metasequoia glyptostroboides	AGB = 0.08004(D²H)^0.8026	0.93
Liriodendron chinense	AGB = 0.02426(D²H)^0.9423+0.000349(D²H)^1.268+0.000419(D²H)^1.0487+0.004283(D²H)^0.86245	0.96
Populus simonii	AGB = 0.03(D²H)^0.5734+0.0174(D²H)^0.5574+0.4562(D²H)^0.3193	0.99
Robinia pseudoacacia	AGB = 0.714 + 0.029(D²H)	0.93
Sassafras tzumu	AGB = 0.31599D^2.04	0.91
Toxicodendron sylvestre	AGB = 0.25069D^2.23	0.91
Symplocos sumuntia	AGB = 0.211D^2.25852	0.93
Ilex buergeri	AGB = 0.3165D^2.15	0.97
Cyclobalanopsis gracilis	AGB = 0.201035D^2.34	0.97
Castanopsis sclerophylla	AGB = 0.1475D^2.33	0.99
Quercus variabilis	AGB = 0.201035D^2.34	0.97
Quercus acutissima	AGB = 0.201035D^2.34	0.97
Cyclobalanopsis stewardiana	AGB = 0.201035D^2.34	0.97
Cyclobalanopsis sessilifolia	AGB = 0.201035D^2.34	0.97
Cupressus funebris	AGB = 0.127(D²H)^0.6912	0.94
Populus lasiocarpa	AGB = 0.03(D²H)^0.5734+0.0174(D²H)^0.5574+0.4562(D²H)^0.3193	0.99
Paulownia fortunei	AGB = 0.01693(D²H)^0.9234+0.00247(D²H)^1.0977+0.145(D²H)^0.7156	0.95
Platycladus orientalis	AGB = 0.127(D²H)^0.6912	0.94
Juniperus formosana	AGB = 0.127(D²H)^0.6912	0.94
Juniperus chinensis	AGB = 0.127(D²H)^0.6912	0.94
Other species	AGB = 0.226D^2.23	0.91
Note: D is DBH and H is tree height.

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Effects of grazing on plant diversity and productivity in a subtropical forest

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