Effect of Long-term Experimental Warming on the Nutritional Quality of Alpine Meadows in the Northern Tibet

Wei SUN; Shaowei LI; Yangjian ZHANG; Gang FU

doi:10.5814/j.issn.1674-764x.2020.05.009

Journal of Resources and Ecology, Volume. 11, Issue 5, 516(2020)

Effect of Long-term Experimental Warming on the Nutritional Quality of Alpine Meadows in the Northern Tibet

Wei SUN, Shaowei LI, Yangjian ZHANG, and Gang FU^*

Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

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Figures & Tables(9)

Fig. 1. Fig. 1

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Fig. 3. Fig. 3

Fig. 4. Fig. 4

Fig. 5. Fig. 5

Table 1.
Annual mean temperature (AT) and precipitation (AP), and growing season (June-September) temperature (GST) and precipitation (GSP) in 1963-2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China
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Table 1.
Annual mean temperature (AT) and precipitation (AP), and growing season (June-September) temperature (GST) and precipitation (GSP) in 1963-2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China
Year AT (℃) AP (mm) GST (℃) GSP (mm)
1963-2019 1.96±0.80 476.36±96.69 10.02±0.62 400.45±86.83
2018 2.67 667.00 10.82 589.10
2019 3.08 426.20 11.14 372.40

Table 2.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (T_s), soil moisture (SM), air temperature (T_a) and vapor pressure deficit (VPD)

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Table 2.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (T_s), soil moisture (SM), air temperature (T_a) and vapor pressure deficit (VPD)

Site Model		T_s		SM		T_a		VPD
Site Model		F	P	F	P	F	P	F	P
A	W	25.01	0.007	1.22	0.331	0.95	0.385	0.14	0.731
	Y	12.11	0.025	1.60	0.275	0.09	0.774	5.29	0.083
	W×Y	0.02	0.891	0.11	0.753	0.02	0.897	0.79	0.425
B	W	215.52	<0.001	3.41	0.139	4.33	0.106	17.07	0.014
	Y	5.00	0.089	6.62	0.062	0.42	0.554	81.01	0.001
	W×Y	1.93	0.237	0.00	0.952	0.02	0.883	2.90	0.164
C	W	43.26	0.003	1.78	0.253	10.09	0.034	149.08	<0.001
	Y	0.19	0.683	14.93	0.018	0.15	0.718	379.35	<0.001
	W×Y	5.49	0.079	1.21	0.334	1.10	0.355	25.49	0.007

Table 3.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

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Table 3.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

Site Model		CP		ADF		NDF		Ash		EE		WSC
Site Model		F	P	F	P	F	P	F	P	F	P	F	P
A	W	2.40	0.197	6.71	0.061	0.15	0.716	0.25	0.645	0.01	0.919	0.11	0.761
	Y	32.37	0.005	5.86	0.073	8.59	0.043	3.86	0.121	2.75	0.172	1.36	0.308
	W×Y	0.85	0.410	2.29	0.205	0.05	0.841	0.03	0.870	2.12	0.220	0.21	0.670
B	W	79.22	0.001	4.99	0.089	23.00	0.009	24.52	0.008	5.73	0.075	0.85	0.409
	Y	24.56	0.008	1.61	0.273	15.18	0.018	0.65	0.467	0.44	0.545	10.49	0.032
	W×Y	0.00	0.975	0.08	0.793	2.38	0.198	2.78	0.171	1.07	0.360	9.33	0.038
C	W	0.21	0.668	3.98	0.117	0.77	0.429	1.14	0.346	0.06	0.813	0.79	0.423
	Y	77.38	0.001	17.92	0.013	41.27	0.003	1.00	0.373	0.53	0.506	1.38	0.306
	W×Y	4.21	0.109	0.01	0.926	1.33	0.313	2.96	0.161	0.64	0.470	0.18	0.690

Table 4.
The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality
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Table 4.
The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality
Model F P
W 4.59 0.028
Y 21.71 0.001
S 1.52 0.231
W×Y 1.75 0.173
W×S 0.76 0.542
Y×S 1.51 0.214
W×Y×S 1.29 0.287

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Wei SUN, Shaowei LI, Yangjian ZHANG, Gang FU. Effect of Long-term Experimental Warming on the Nutritional Quality of Alpine Meadows in the Northern Tibet[J]. Journal of Resources and Ecology, 2020, 11(5): 516

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Paper Information

Received: Mar. 27, 2020

Accepted: Jun. 2, 2020

Published Online: Oct. 17, 2020

The Author Email: FU Gang (fugang@igsnrr.ac.cn)

DOI:10.5814/j.issn.1674-764x.2020.05.009

Topics

Resource Economy

Research Articles

Table 1. Annual mean temperature (AT) and precipitation (AP), and growing season (June-September) temperature (GST) and precipitation (GSP) in 1963-2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China

Table 1. Annual mean temperature (AT) and precipitation (AP), and growing season (June-September) temperature (GST) and precipitation (GSP) in 1963-2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China

Table 2. Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (Ts), soil moisture (SM), air temperature (Ta) and vapor pressure deficit (VPD)

Table 2. Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (Ts), soil moisture (SM), air temperature (Ta) and vapor pressure deficit (VPD)

Table 3. Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

Table 3. Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

Table 4. The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality

Table 4. The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality

Table 1.
Annual mean temperature (AT) and precipitation (AP), and growing season (June-September) temperature (GST) and precipitation (GSP) in 1963-2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China

Table 1.
Annual mean temperature (AT) and precipitation (AP), and growing season (June-September) temperature (GST) and precipitation (GSP) in 1963-2019, 2018 and 2019 in the Damxung County, Lhasa City, Tibet, China

Table 2.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (T_s), soil moisture (SM), air temperature (T_a) and vapor pressure deficit (VPD)

Table 2.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on soil temperature (T_s), soil moisture (SM), air temperature (T_a) and vapor pressure deficit (VPD)

Table 3.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

Table 3.
Repeated analysis of variance for the main and interactive effects of experimental warming (W) and measurement year on the content of crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), ether extract (EE) and water-soluble carbohydrate (WSC)

Table 4.
The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality

Table 4.
The permutational multivariate analysis of variance of experimental warming (W), measurement year (Y) and measurement site (S) on nutritional quality