The Stable Carbon Isotope Composition of Pinus yunnanensis Pollen and Leaf in Northwestern Yunnan, China

Abstract

The basis for the δ¹³C values of plant tissues used to infer past ecological environments is their relationships with modern ecological conditions. A total of 71 pairs of pollen and leaf samples were collected from Pinus yunnanensis, an endemic species of the Yunnan plateau, in northwestern Yunnan, China. Their carbon isotopic composition was examined to investigate the two tissues’ difference of stable carbon isotopes, possible factors affecting their δ¹³C values, and their distinctiveness within Pinus and Pinaceae. Our study showed that pollen δ¹³C values range from −32.92 to −26.34‰ with an average of −30.88‰, whereas leaf δ¹³C values vary between −33.79 and −28.96‰ with an average value of −31.2‰, suggesting an isotope fractionation between the two tissues. A statistically significant negative correlation between the pollen δ¹³C values and altitudes of the sampling sites as well as no significant correlation between the leaf δ¹³C values and altitudes suggested that pollen may be more sensitive to some climatic parameters than leaf. A comparison of the pollen and leaf δ¹³C values from Pinus yunnanensis with the available data from other Pinus species and other genus species of Pinaceae indicated that the pollen and leaf δ¹³C values of Pinus yunnanensis are the lowest, partially due to the effects of water availability.

1. Introduction

Analysis of the carbon stable isotope composition of plant tissues and plant compounds has been widely used in biological, ecological, geological, and environmental studies [1,2,3,4,5]. It has been used not only to elucidate the photosynthetic pathway and different forms of resource stress, such as low soil water or nitrogen availability, low light, or salinity stress in modern plant ecosystems [1,6,7], but also to reconstruct past climatic and ecological changes [8,9,10,11]. Understanding the modern processes driven by biotic and abiotic controls on carbon stable isotopes is the basis for the paleoclimatic and paleoecological interpretation of fossil carbon stable isotopes from plant tissues and plant compounds, which requires a grasp of not only some fundamental principles of carbon isotope behavior but also the underlying basis of observed variation in the carbon isotope composition of diverse materials at different temporal and spatial scales based on a well-developed sampling network [3,7]. Such networks for carbon stable isotopes of some plant tissues and plant compounds have been well developed, such as tree-ring [12,13,14], leaf [4,15,16,17], n-alkanes [18,19], peat cellulose [20,21], and charcoal [22]. They also have shown their potential in the paleoclimatic and paleoecological interpretation of fossil carbon stable isotopes. Among plant tissues and plant compounds, pollen is an ideal material for environmental and climate reconstructions as it is composed primarily of a highly resistant biopolymer sporopollenin, and conventional pollen analysis provides a large-scale history of vegetation dynamics over long geological times. However, a sampling network of pollen carbon stable isotope composition has not been built, although few studies showed its feasibility and potential in the paleoclimatic and paleoecological interpretation of fossil pollen carbon stable isotopes [23,24,25]. Therefore, more sampling sites and more sampling species are needed to develop a detailed picture of different pollen carbon isotope composition at different temporal and spatial scales so that we may understand the fundamental principles of pollen carbon isotope behavior and the underlying basis of observed variation.

Pinus yunnanensis (Yunnan pine) is an endemic tree species of Southwest China. Its modern distribution region (23°–30° N and 96°–108° E) involves Yunnan, southwest Sichuan, southeast Tibet, as well as west Guizhou and Guangxi, and its distribution center is the Yunnan plateau. Geomorphologically, it generally grows in highland mountains and high-middle mountain valleys in an altitude range from 250 to 3500 m, concentrating on an altitude of 1600–2900 m [26]. It is a highly adaptable species in the modern environment, and it also occurred in the ancient environment of the Yunnan plateau during the geological times. Pinus yunnanensis not only has high ecological, economic, and social benefits, but it also plays an important role in water, soil, and water conservation in the plateau area [27]. For example, it is not only the pioneer species of barren mountain afforestation, but also the preferred tree species of shelterbelt in mountainous farmland. In this study, leaf and pollen samples were collected from the south bank of Lugu Lake in northwestern Yunnan (southern Hengduan mountains), China. Their carbon isotopic compositions were measured to study the relationships between the pollen and leaf stable isotope values of Pinus yunnanensis, as well as the relationships between their stable isotope values and environmental factors. Finally, a comparison of the pollen and leaf δ¹³C values from Pinus yunnanensis with those from other Pinus species and other genus species of Pinaceae was made to reveal the distinctiveness of Pinus yunnanensis.

2. Materials and Methods

2.1. Regional Setting

The study area is located on the south bank of Lugu Lake in northwestern Yunnan (27°65′~27°71′ N, 100°74′~100°8′ E), China (Figure 1). The altitudes of the sampling sites range from 2731 to 3085 m, with a relative elevation difference of 354 m. The climate in the study area is controlled by the South Asian monsoon in summer and westerlies in winter, with distinct rainy and dry seasons [28]. The observational data of 1961–2010 at the Ninglang meteorological station near Lugu Lake shows a mean annual precipitation of 931 mm, 88% of which is concentrated in the rainy season from May to October. The mean annual temperature is 12.6 °C, with the warmest temperature of 19.2 °C in July and the coldest temperature of 4.1 °C in January (Figure 2). In the mountains near the Lugu Lake occurs a marked gradient of the climatic parameters. As the altitude increases, the temperature declines, precipitation increases, and humidity rises [29].

The Lugu Lake watershed is occupied by a Pinus yunnanensis forest and a sclerophyllous evergreen oak forest. The Pinus yunnanensis forest is the largest extant vegetation type. It generally grows below the altitude of 3000 m and reaches occasionally an altitude as high as 3200 m [30]. The topography of the study area is complex, the habitat niche varies greatly, and thus the mosaic distribution of the vertical vegetation belts is prominent [31]. From 3200 to 3600 m, the sclerophyllous evergreen oak forest, Tsuga dumosa forest, Picea likiangensis forest, and Abies forrestii forest exist in mosaic. Mountains above 3600 m are occupied by the Larix potaninii var. macrocarpa forest and subalpine shrub meadow [32]. As one of the least anthropologically disturbed regions in China, the vegetation on the surrounding mountains has experienced little anthropogenic impact.

2.2. Sampling, Stable Isotope Analysis, and Data Processing

Pollen and leaf samples were collected from the mature specimens of Pinus yunnanensis along an altitude gradient range of 2731–3085 m on the south bank of Lugu Lake in the northwestern Yunnan Province (Figure 1) in 2018. The pollen and leaf collection was performed during late May because Pinus yunnanensis in the study area generally produces pollen during this time. The sampling sites were located using GPS, which are away from roads and human activities. One pair of pollen and leaf samples were taken from the same Pinus yunnanensis individual, and a total of 71 pairs were collected from different sampling sites. One leaf sample was a mixture of mature leaves from different directions growing normally in the same year. One pollen sample was taken from yellow Pinus yunnanensis pollen sacs. Pollen and leaf samples were packed in envelope bags and brought back to the laboratory for analysis within 4 days. The pollen samples were dried and then stored after a 0.2 mm aperture (60 mesh) sieve. The leaf samples were washed and dried, and then they were placed in a 60 °C constant temperature box for continuous drying for 48 h to eliminate the potential impact of air humidity. The samples were then ground to a fine uniform powder and passed a 60 mesh sieve treatment in preparation for stable isotope analysis.

The pollen and leaf samples were analyzed for the δ¹³C value using Thermo Scientific’s MAT253 gas stable isotope mass spectrometer combined with a Flash EA element analyzer at the Yunnan Key Laboratory of Plateau Geographical Processes and Environmental Changes in Yunnan Normal University. Two mg subsamples were introduced to the combustion system in pure tin capsules. The stable isotope values are reported in the standard δ-notation: δ¹³C = (R_sample/R_standard − 1) × 1000 (‰). The reporting standard is the Pee Dee Formation Belemnite (PDB) [33]. The analytical uncertainty associated with each measurement was less than 0.1‰ [34].

The experimental data were analyzed using Excel and SPSS26.0. The data were also grouped and averaged at a 10 m interval at an altitude to eliminate the sampling noises induced by the tree-age, intra-site variability, and micro-climate [35]. Both the original and grouped data were processed using the same methods. The figures were plotted using Grapher12 and ArcGIS10.5.

3. Results

The carbon stable isotope analysis of 71 pairs of Pinus yunnanensis pollen and leaf samples (

Table 1. Results of stable carbon isotope analysis on pollen and leaf samples (n = 71).

Sample	Latitude	Longitude	Altitude (m)	Pollen δ13C (‰)	Leaf δ13C (‰)
LHL-01	27.7079	100.7477	2793.8	−26.34	−28.96
LHL-02	27.6790	100.7653	2731.0	−31.21	−31.23
LHL-03	27.6811	100.7626	2801.0	−29.62	−32.92
LHL-04	27.6810	100.7624	2800.3	−30.38	−30.49
LHL-05	27.6811	100.7623	2806.1	−30.66	−30.76
LHL-06	27.6811	100.7622	2803.9	−31.47	−29.79
LHL-07	27.6811	100.7622	2803.0	−31.01	−30.08
LHL-08	27.6811	100.7622	2811.3	−30.30	−31.99
LHL-09	27.6811	100.7621	2810.9	−31.52	−30.72
LHL-10	27.6811	100.7621	2815.1	−31.62	−30.25
LHL-11	27.6810	100.7621	2816.2	−31.46	−30.99
LHL-12	27.6810	100.7620	2818.8	−30.35	−32.60
LHL-13	27.6810	100.7619	2820.1	−31.16	−32.40
LHL-14	27.6809	100.7615	2834.7	−31.40	−30.02
LHL-15	27.6808	100.7614	2837.9	−31.43	−30.48
LHL-16	27.6808	100.7614	2837.9	−30.67	−31.94
LHL-17	27.6808	100.7613	2842.6	−29.92	−31.96
LHL-18	27.6808	100.7612	2854.7	−28.80	−30.10
LHL-19	27.6805	100.7612	2866.1	−30.75	−30.85
LHL-20	27.6813	100.7628	2794.0	−29.51	−32.82
LHL-21	27.6775	100.7627	2838.1	−30.56	−30.56
LHL-22	27.6777	100.7625	2853.2	−29.43	−29.75
LHL-23	27.6778	100.7625	2857.9	−31.39	−32.68
LHL-24	27.6780	100.7622	2863.4	−29.76	−32.25
LHL-25	27.6781	100.7621	2872.4	−29.28	−30.45
LHL-26	27.6780	100.7620	2874.0	−28.82	−31.80
LHL-27	27.6781	100.7618	2879.5	−27.50	−30.39
LHL-28	27.6781	100.7617	2886.9	−30.33	−30.32
LHL-29	27.6780	100.7616	2889.8	−30.50	−31.65
LHL-30	27.6779	100.7614	2890.9	−32.85	−31.03
LHL-31	27.6780	100.7613	2895.0	−30.05	−30.87
LHL-32	27.6781	100.7609	2896.4	−30.87	−29.72
LHL-33	27.6781	100.7606	2895.1	−31.92	−30.67
LHL-34	27.6780	100.7600	2896.8	−31.08	−33.18
LHL-35	27.6781	100.7593	2901.3	−31.93	−32.30
LHL-36	27.6782	100.7587	2913.3	−31.62	−30.54
LHL-37	27.6783	100.7581	2914.0	−30.90	−31.79
LHL-38	27.6785	100.7566	2929.4	−30.17	−31.57
LHL-39	27.6785	100.7562	2939.2	−31.64	−31.06
LHL-40	27.6788	100.7553	2950.0	−32.47	−32.23
LHL-41	27.6787	100.7552	2964.6	−30.47	−29.70
LHL-42	27.6787	100.7549	2966.7	−30.51	−31.11
LHL-43	27.6784	100.7544	2985.4	−31.09	−31.65
LHL-44	27.6785	100.7538	2997.0	−31.81	−32.21
LHL-45	27.6581	100.8066	3046.4	−32.92	−30.94
LHL-46	27.6578	100.8064	3052.9	−32.20	−31.35
LHL-47	27.6578	100.8062	3056.5	−31.40	−33.79
LHL-48	27.6576	100.8059	3062.5	−30.90	−30.33
LHL-49	27.6574	100.8058	3067.8	−31.19	−31.39
LHL-50	27.6572	100.8057	3072.5	−31.75	−32.43
LHL-51	27.6571	100.8055	3075.9	−30.35	−29.98
LHL-52	27.6567	100.8053	3083.2	−30.86	−30.11
LHL-53	27.6564	100.8052	3080.9	−30.37	−32.26
LHL-54	27.6563	100.8052	3077.2	−32.24	−31.45
LHL-55	27.6564	100.8050	3076.6	−31.49	−30.69
LHL-56	27.6559	100.8052	3078.5	−31.11	−30.52
LHL-57	27.6557	100.8053	3079.2	−30.98	−30.63
LHL-58	27.6555	100.8052	3085.0	−31.87	−32.34
LHL-59	27.6554	100.8053	3076.1	−31.05	−30.39
LHL-60	27.6582	100.8060	3051.7	−29.67	−32.24
LHL-61	27.6582	100.8054	3042.5	−31.33	−30.53
LHL-62	27.6582	100.8051	3038.1	−30.95	−32.06
LHL-63	27.6583	100.8051	3036.4	−31.97	−30.56
LHL-64	27.6583	100.8049	3034.2	−31.97	−32.23
LHL-65	27.6582	100.8042	3028.1	−32.39	−31.14
LHL-66	27.6583	100.8039	3018.8	−31.06	−32.18
LHL-67	27.6583	100.8039	3015.0	−31.85	−30.38
LHL-68	27.6583	100.8037	3011.2	−32.32	−30.81
LHL-69	27.6584	100.8036	3008.9	−30.84	−32.03
LHL-70	27.6584	100.8036	3004.6	−31.68	−31.35
LHL-71	27.6584	100.8036	2998.4	−29.03	−30.44
			Mean	−30.88	−31.20
			Minimum	−26.34	−28.96
			Maximum	−32.92	−33.79
			Range	−6.58	−4.83
			1σ	1.14	0.99

) showed their variations of δ¹³C values. The pollen δ¹³C values varied between −32.92 and −26.34‰, and they were mainly distributed in the range of −32 to −30‰, with an average value of −30.876 ± 1.143‰; the leaf δ¹³C values varied between −33.79 and −28.96‰, and they were mainly distributed in the range of −33.5 to −30‰, with an average value of −31.203 ± 0.989‰. Overall, these δ¹³C values formed a cluster very close to the 1:1 line for the relationship between pollen and leaf (Figure 3a). The carbon isotope difference between the pollen and leaf values in the same tree at the same sampling sites (Δ_{pollen–leaf}) varied between −1.98‰ and +3.31‰, with >80% of data pairs within Δσ_{pollen–leaf} = ±2.00‰. However, it is evident that the leaf δ¹³C values were more negative than the pollen δ¹³C values. No significant relationship was found between the pollen and leaf δ¹³C values. The grouped data were also used to analyze their relationship. However, the result was the same as the original data, as showed by Figure 3b.

Along an elevation gradient from ca. 2700 to 3100 m, a distinct difference occurred between the pollen and leaf δ¹³C values of Pinus yunnanensis (Figure 4a,b). A negative correlation between the pollen δ¹³C values and altitude, which is statistically significant at the 0.05 confidence level (r² = 0.13, p < 0.05), indicated that the pollen δ¹³C values of Pinus yunnanensis decreased linearly with the increase in the altitude. However, no significant relationship between the leaf δ¹³C values of Pinus yunnanensis and the altitude was found. The pollen and leaf δ¹³C values were also grouped at 10 m in an altitude with the mean δ¹³C for each interval to eliminate the sampling noises. A linear regression analysis of the grouped data (Figure 4c,d) also showed a statistically significant relationship between the pollen δ¹³C and altitude (r² = 0.21, p < 0.05), but not any significant relationship between the leaf δ¹³C and the attitude (Figure 4c,d).

4. Discussion

4.1. Isotopic Differences between Pollen and Leaf δ¹³C of Pinus yunnanensis

Our study revealed a general trend that the Pinus yunnanensis leaf δ¹³C values were more negative than the pollen δ¹³C values. A comparison of the pollen and leaf δ¹³C values from Pinus yunnanensis with the available data from the Pinaceae species [35,36] indicated that this general trend also occurred in the pollen and leaf δ¹³C values from Pinaceae species (Figure 5). Among 25 Pinaceae species, 18 species showed the same trend as Pinus yunnanensis. This general trend can be partially explained by the composition difference of pollen and leaf, since the major components of the plant tissues have different carbon isotope signatures. Pollen grains are composed primarily of sporopollenin, callus, active protein, cellulose, and pectin, while the leaves mainly consist of polysaccharides (65%–90% by mass), lignin (9%–30% by mass), lipids (1%–5% by mass), and various secondary compounds such as secondary metabolites and amino acids [36].

This general trend can be also partially explained by environmental changes in pollen and leaf formation and growth, since these factors affect photosynthetic processes and thus δ¹³C composition. In the study area, little difference occurs in the sunshine duration from January to May, but the temperature rises rapidly to more than 10 °C in May, so it can be inferred that Yunnan pine does not rely on a specific amount of sunshine for seasonal growth but a certain temperature for the pollination [37]. Meanwhile, the leaves of the Yunnan pine grow long before May and show a high photosynthetic rate [38]. The carbon content in plant pollen almost remains unchanged during the flowering stage. Pollen primordia had formed in the previous year, and then the pollen continued to mature after dormancy in winter [39]. Carolina et al. [40] showed no significant change in the δ¹³C values (−25.6‰ and −25.7‰, respectively) of the two pollen samples from Pinus sylvestris var. mongolica taken 11 weeks apart. However, the δ¹³C values in the plant leaves are highly influenced by the weather [41] and thought to be a sensitive marker of physiological changes, especially the cold wind and temperature inversion in spring [42]. Therefore, a difference in the pollen and leaf δ¹³C of Pinus yunnanensis was not unexpected. As suggested by Bell et al. [35], such a difference may also result from the post-photosynthetic fractionation effects. However, our study did not show a significant relationship between the Pinus yunnanensis pollen and leaf δ¹³C values, limiting the further discussion on this issue.

4.2. Factors Affecting Pinus yunnanensis Pollen and Leaf δ¹³C Values

Figure 5 also showed that Pinus yunnanensis pollen and leaf have the lowest δ¹³C values among Pinaceae species. Among 11 Pinus species, the maximum difference in the pollen and leaf δ¹³C values occurred between P. yunnanensis and P. canariensis, whereas the minimum difference occurred between P. yunnanensis and P. echinate. P. canariensis is a native species in the Canary Islands with the Mediterranean climate, which occupies fairly extensive forest areas above an altitude of 1200 m to ca. 2200 m a.s.l. [43]. P. echinata is a native species in the southeastern United States with a subtropical humid climate, which mostly grows from ca. 150 m up to the foothills of the Appalachian Mountains at ca. 600 m a.s.l. [44]. This comparison implied that the Pinus yunnanensis pollen and leaf δ¹³C values are affected by different natural factors from habitats of other Pinaceae species, especially P. canariensis. As an endemic tree species of Southwest China, the flowing period of Pinus yunnanensis is generally from March to April, but its flowing period in the study area postpones as late as May due to the effect of environmental factors such as temperature and precipitation. In the study area, the month of May, at the point of late spring and early summer, is the transition between the dry and rainy seasons, when the moist airmass driven by the South Asian monsoon from the Bay of Bengal brings about more and more rainfall, reaching as high as 110.2 mm. On the other hand, both the precipitation and humidity increase as the altitude increases in the study area [29]. Furthermore, the study area is located on the south bank of Lugu Lake; the influence of the lake microclimate thus keeps the study area humid. Three factors make a no water deficit in plants. When precipitation and transpiration are in equilibrium, stomatal conductance becomes larger and thus the δ¹³C value in plants becomes lower, as suggested by Bell et al. [25,35]. The stomata of plants were completely open, and ¹²CO₂ and ¹³CO₂ moved freely between the atmosphere and cells under humid conditions. The larger the stomatal conductance was, the lower the δ¹³C values of plant pollen and leaf were [45].

Our study seems to support that water availability or humidity is a major control on the pollen δ¹³C values [25,35]. Our study showed a statistically significant decrease trend in the pollen δ¹³C values of Pinus yunnanensis with the increase in altitude, but there was no significant relationship between the leaf δ¹³C values and altitude. Altitude is an important environmental factor for plant growth. It often causes the redistribution of heat and water, making the plant growth environment more complicated due to the complex mountainous climate [29]. Work to date on the relationship between the δ¹³C values of plant tissues and altitude has not gotten a consistent conclusion [46,47,48,49,50,51,52]. Earlier studies showed that C3 plant δ¹³C is positively correlated with the altitude on a global scale, but a negative correlation or an unobvious change trend occurs in local areas because the δ¹³C value of plants is also affected by the local micro-habitats [46]. In recent decades, Čada et al. [50] found that the δ¹³C of Norwegian spruce exhibited a less negative trend with an increasing altitude, whereas Van de Water et al. [48] and Wang et al. [49] obtained an opposite pattern, that the δ¹³C values of plants gradually became more negative with an increasing altitude. Meanwhile, Chen et al. [52] did not find an altitudinal trend in plant δ¹³C over an arid region. Due to the limited spatial scale of our study area, it is difficult to get a solid conclusion that the pollen δ¹³C values of Pinus yunnanensis become more negative with the increase in the altitude due to the increase in precipitation and humidity. A large spatial scale study covering the distribution region of Pinus yunnanensis is thus needed for revealing the relationships of the pollen δ¹³C values of Pinus yunnanensis with the temperature and precipitation. However, it seems reasonable that the pollen δ¹³C of Pinus yunnanensis may be more sensitive to some climatic and environmental parameters than leaf δ¹³C.

Pinus yunnanensis is an absolute dominant species in Southwest China. Its fossil pollen was widely found in the fossil pollen records from lakes in this region such as Lugu Lake [53], Dianchi Lake [54], Fuxian Lake [55], and Yangzonghai Lake [56]. Pollen is an ideal material for past environmental and climate reconstruction because it is mainly composed of highly resistant sporopollenin and has absolute advantages compared to other plant organs [57]. As the technical development of stable carbon isotope analysis [58], the study of Pinus yunnanensis pollen δ¹³C will assuredly contribute to Quaternary paleoclimatic and paleoecological studies in Southwest China. It is evident that the relationship between modern pollen δ¹³C and the environment at a well-developed sampling network with high spatial and temporal scales is essential for future study.

5. Conclusions

A stable carbon isotope analysis of 71 pairs of pollen and leaf samples from Pinus yunnanensis was conducted to study the difference in stable carbon isotopes between the two tissues, the possible factors influencing their δ¹³C values, and their distinctiveness within Pinus and Pinaceae. Our study showed that:

(1)

A marked difference occurs between the pollen and leaf δ¹³C values, indicating an isotope fractionation between the two tissues.

(2)

A statistically significant negative correlation between the pollen δ¹³C values and the altitudes of the sampling sites, and no significant correlation between the leaf δ¹³C values and altitudes, suggesting that pollen may be more sensitive to some climatic parameters than leaf.

(3)

The pollen and leaf δ¹³C values of Pinus yunnanensis have the lowest values among the Pinus species and the other genus species of Pinaceae with the available δ¹³C values of the two tissues, implying the effects of the water availability on the pollen and leaf δ¹³C values, especially pollen.