Variation of functional traits of alternative distribution of Caragana species along environmental gradients in Nei Mongol, China

doi:10.17521/cjpe.2021.0491

Abstract

Abstract:

Aims Trait-trait relationships and trait-environment relationships are critical for understanding species distribution, community assembly and plant strategy to environmental change. Caragana species distribute widely in arid Mongolia Plateau, and shape the alternative distribution along the environmental gradients. To understand the plant strategies to climate and soil, the trait-trait relationships and trait-environmental relationships were documented for Caragana species in Nei Mongol region.
Methods We measured eight morphological and chemical traits from nine Caragana species distributed across 41 sites in Nei Mongol, including plant height (h), leaf dry matter content (LDMC), specific leaf area (SLA), stem tissue density (STD), leaf area (LA), leaf nitrogen content (LNC), leaf phosphorus content (LPC), and leaf nitrogen to phosphorus ratio (N:P). We tested the trait-trait relationships between species and within species, and explored their relationships with aridity, soil nitrogen content and pH at the genus levels.
Important findings We found that the aridity index explained more than 29% of the variation in most functional traits (except N:P), with h, SLA, LA, LNC, and LPC decreased, while LDMC and STD increased with increasing drought. h, SLA, LDMC, STD and LNC were also affected by soil total nitrogen content. However, soil pH explained less for Caragana traits. The synchronous correlations or trade-offs among different functional traits were stronger at the genus level, while the trait-trait relationships within species were weak. There was a consistent increase in h, SLA, LA, LNC and LPC, but a decrease in LDMC and STD to declined aridity. We only observed significant correlations at the within-species level for C. korshinskii and C. microphylla, which were the most widely distributed. Plants with smaller distribution range have weak intraspecific covariation relationships among functional traits, which indicated that the plant economic spectrum theory is not necessarily suitable to explain the utilization of resources and the adaptation strategies of plants to environmental changes at the local scale at the individual level.

Key words: plant functional trait, trait covariation relationship, aridity index, soil nitrogen content, Caragana species

LUO Yuan-Lin, MA Wen-Hong, ZHANG Xin-Yu, SU Chuang, SHI Ya-Bo, ZHAO Li-Qing. Variation of functional traits of alternative distribution of Caragana species along environmental gradients in Nei Mongol, China[J]. Chin J Plant Ecol, 2022, 46(11): 1364-1375.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2021.0491

https://www.plant-ecology.com/EN/Y2022/V46/I11/1364

Figures/Tables 8

References 48

[1]	Albert CH, Thuiller W, Yoccoz NG, Douzet R, Aubert S, Lavorel S (2010). A multi-trait approach reveals the structure and the relative importance of intra- vs. interspecific variability in plant traits. Functional Ecology, 24, 1192-1201. DOI URL
[2]	Anderegg LDL, Berner LT, Badgley G, Sethi ML, Law BE, HilleRisLambers J (2018). Within-species patterns challenge our understanding of the leaf economics spectrum. Ecology Letters, 21, 734-744. DOI PMID
[3]	Blumenthal DM, Mueller KE, Kray JA, Ocheltree TW, Augustine DJ, Wilcox KR (2020). Traits link drought resistance with herbivore defence and plant economics in semi-arid grasslands: the central roles of phenology and leaf dry matter content. Journal of Ecology, 108, 2336-2351. DOI URL
[4]	Bowsher AW, Mason CM, Goolsby EW, Donovan LA (2016). Fine root tradeoffs between nitrogen concentration and xylem vessel traits preclude unified whole-plant resource strategies in Helianthus. Ecology and Evolution, 6, 1016-1031. DOI PMID
[5]	Bruelheide H, Dengler J, Purschke O, Lenoir J, Jiménez-Alfaro B, Hennekens SM, Botta-Dukát Z, Chytrý M, Field R, Jansen F, Kattge J, Pillar VD, Schrodt F, Mahecha MD, Peet RK, et al. (2018). Global trait-environment relationships of plant communities. Nature Ecology & Evolution, 2, 1906-1917.
[6]	Chave J, Coomes D, Jansen S, Lewis SL, Swenson NG, Zanne AE (2009). Towards a worldwide wood economics spectrum. Ecology Letters, 12, 351-366. DOI PMID
[7]	de la Riva EG, Tosto A, Pérez-Ramos IM, Navarro-Fernández CM, Olmo M, Anten NPR, Maranon T, Villar R (2016). A plant economics spectrum in Mediterranean forests along environmental gradients: Is there coordination among leaf, stem and root traits? Journal of Vegetation Science, 271, 87-199.
[8]	Di Biase L, Fattorini S, Cutini M, Bricca A (2021). The role of inter-and intraspecific variations in grassland plant functional traits along an elevational gradient in a Mediterranean Mountain area. Plants, 10, 359. DOI: 10.3390/plants10020359. DOI
[9]	England JR, Attiwill PM (2006). Changes in leaf morphology and anatomy with tree age and height in the broadleaved evergreen species, Eucalyptus regnans F. Trees, 20, 79-90. DOI URL
[10]	Fick SE, Hijmans RJ (2017). WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37, 4302-4315. DOI URL
[11]	Freschet GT, Cornelissen JHC, Aerts R (2010). Evidence of the ‘plant economics spectrum’ in a subarctic flora. Journal of Ecology, 98, 362-373. DOI URL
[12]	Fyllas NM, Michelaki C, Galanidis A, Evangelou E, Zaragoza- Castells J, Dimitrakopoulos PG, Tsadilas C, Arianoutsou M, Lloyd J (2020). Functional trait variation among and within species and plant functional types in mountainous Mediterranean forests. Frontiers in Plant Science, 11, 212. DOI: 10.3389/fpls.2020.00212. DOI
[13]	Garnier E, Shipley B, Roumet C, Laurent G (2001). A standar- dized protocol for the determination of specific leaf area and leaf dry matter content. Functional Ecology, 15, 688-695. DOI URL
[14]	Grime JP (1977). Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. The American Naturalist, 111, 1169-1194. DOI URL
[15]	He NP, Li Y, Liu CC, Xu L, Li MX, Zhang JH, He JS, Tang ZY, Han XG, Ye Q, Xiao CW, Yu Q, Liu SR, Sun W, Niu SL, et al. (2020). Plant trait networks: improved resolution of the dimensionality of adaptation. Trends in Ecology & Evolution, 35, 908-918. DOI URL
[16]	Hinsinger P (2001). Bioavailability of soil inorganic P in the rhizosphere as affected by root-induced chemical changes: a review. Plant and Soil, 237, 173-195. DOI URL
[17]	Jardine EC, Thomas GH, Forrestel EJ, Lehmann CER, Osborne CP (2020). The global distribution of grass functional traits within grassy biomes. Journal of Biogeography, 47, 553-565. DOI URL
[18]	Jin DM, Cao XC, Ma KP (2014). Leaf functional traits vary with the adult height of plant species in forest communities. Journal of Plant Ecology, 7, 68-76. DOI URL
[19]	Kemppinen J, Niittynen P le Roux PC, Momberg M, Happonen K, Aalto J, Rautakoski H, Enquist BJ, Vandvik V, Halbritter AH, Maitner B, Luoto M (2021). Consistent trait-environment relationships within and across tundra plant communities. Nature Ecology & Evolution, 5, 458-467.
[20]	Korall P, Pryer KM (2014). Global biogeography of scaly tree ferns (Cyatheaceae): evidence for Gondwanan vicariance and limited transoceanic dispersal. Journal of Biogeography, 41, 402-413. PMID
[21]	Lambers H, Chapin III FS, Pons TL (1998). Plant Physiological Ecology. Spinger-Verlag, New York.
[22]	Laughlin DC, Lusk CH, Bellingham PJ, Burslem DFRP, Simpson AH, Kramer-Walter KR (2017). Intraspecific trait variation can weaken interspecific trait correlations when assessing the whole-plant economic spectrum. Ecology and Evolution, 7, 8936-8949. DOI PMID
[23]	Liao JX, Chen J, Jiang MX, Huang HD (2012). Leaf traits and persistence of relict and endangered tree species in a rare plant community. Functional Plant Biology, 39, 512-518. DOI PMID
[24]	Liu MZ, Wang ZW,Li SS Lü X, Wang XB, Han XG (2017). Changes in specific leaf area of dominant plants in temperate grasslands along a 2500-km transect in Northern China. Scientific Reports, 7, 10780. DOI: 10.1038/s41598- 017-11133-z. DOI
[25]	Liu XJ, Ma KP (2015). Plant functional traits—Concepts, applications and future directions. Scientia Sinica (Vitae), 45, 325-339.
	[ 刘晓娟, 马克平 (2015). 植物功能性状研究进展. 中国科学: 生命科学, 45, 325-339.]
[26]	Lusk CH, Reich PB, Montgomery RA, Ackerly DD, Cavender-Bares J (2008). Why are evergreen leaves so contrary about shade? Trends in Ecology & Evolution, 23, 299-303. DOI URL
[27]	Meng H, Wei X, Franklin SB, Wu H, Jiang M (2017). Geographical variation and the role of climate in leaf traits of a relict tree species across its distribution in China. Plant Biology, 19, 552-561. DOI PMID
[28]	Messier J, McGill BJ, Enquist BJ, Lechowicz MJ (2017). Trait variation and integration across scales: Is the leaf economic spectrum present at local scales? Ecography, 40, 685-697. DOI URL
[29]	Niinemets Ü (2015). Is there a species spectrum within the world-wide leaf economics spectrum? Major variations in leaf functional traits in the Mediterranean sclerophyll Quercus ilex. New Phytologist, 205, 79-96. PMID
[30]	Ordoñez JC, van Bodegom PM, Witte JPM, Wright IJ, Reich PB, Aerts R (2009). A global study of relationships between leaf traits, climate and soil measures of nutrient fertility. Global Ecology and Biogeography, 18, 137-149. DOI URL
[31]	Pérez-Harguindeguy N, Díaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P, Bret-Harte MS, Cornwell WK, Craine JM, Gurvich DE, Urcelay C, Veneklaas EJ, Reich PB, Poorter L, Wright IJ, et al. (2013). New handbook for standardised measurement of plant functional traits worldwide. Australian Journal of Botany, 61, 167-234. DOI URL
[32]	Pietsch KA, Ogle K, Cornelissen JHC, Cornwell WK, Bönisch G, Craine JM, Jackson BG, Kattge J, Peltzer DA, Penuelas J, Reich PB, Wardle DA, Weedon JT, Wright IJ, Zanne AE, Wirth C (2014). Global relationship of wood and leaf litter decomposability: the role of functional traits within and across plant organs. Global Ecology and Biogeography, 23, 1046-1057. DOI URL
[33]	Preston KA, Cornwell WK, DeNoyer JL (2006). Wood density and vessel traits as distinct correlates of ecological strategy in 51 California coast range angiosperms. New Phytologist, 170, 807-818. PMID
[34]	Reich PB, Ellsworth DS, Walters MB, Vose JM, Gresham C, Volin JC, Bowman WD (1999). Generality of leaf trait relationships: a test across six biomes. Ecology, 80, 1955-1969. DOI URL
[35]	Reich PB, Wright IJ, Lusk CH (2007). Predicting leaf physiology from simple plant and climate attributes: a global GLOPNET analysis. Ecological Applications, 17, 1982-1988. DOI URL
[36]	Sack L, Cowan PD, Jaikumar N, Holbrook NM (2003). The “hydrology” of leaves: co-ordination of structure and function in temperate woody species. Plant, Cell & Environment, 26, 1343-1356.
[37]	Stearns SC (1989). Trade-offs in life-history evolution. Functional Ecology, 3, 259-268. DOI URL
[38]	Sultan SE (2000). Phenotypic plasticity for plant development, function and life history. Trends in Plant Science, 5, 537-542. DOI PMID
[39]	Turtureanu PD, Barros C, Bec S, Hurdu BI, Saillard A, Šibík J, Balázs ZR, Novikov A, Renaud J, Podar D, Thuiller W, Pușcaș MH, Choler P (2020). Biogeography of intraspecific trait variability in matgrass (Nardus stricta): high phenotypic variation at the local scale exceeds large scale variability patterns. Perspectives in Plant Ecology, Evolution and Systematics, 46, 125555. DOI: 10.1016/j.ppees. 2020.125555 DOI
[40]	Violle C, Navas ML, Vile D, Kazakou E, Fortunel C, Hummel I, Garnier E (2007). Let the concept of trait be functional! Oikos, 116, 882-892. DOI URL
[41]	Wei H, Wu B, Yang W, Luo T (2011). Low rainfall-induced shift in leaf trait relationship within species along a semi-arid sandy land transect in northern China. Plant Biology, 13, 85-92. DOI PMID
[42]	Westoby M (1998). A leaf-height-seed (LHS) plant ecology strategy scheme. Plant and Soil, 199, 213-227. DOI URL
[43]	Wilson PJ, Thompson K, Hodgson JG (1999). Specific leaf area and leaf dry matter content as alternative predictors of plant strategies. New Phytologist, 143, 155-162. DOI URL
[44]	Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, et al. (2004). The worldwide leaf economics spectrum. Nature, 428, 821-827. DOI URL
[45]	Xie LN, Ma CC, Guo HY, Li QF, Gao YB (2014). Distribution pattern of Caragana species under the influence of climate gradient in the Inner Mongolia region, China. Journal of Arid Land, 6, 311-323. DOI URL
[46]	Yang SS, Wen ZM, Miao LP, Qi DH, Hua DW (2014). Responses of plant functional traits to micro-topographical changes in hilly and gully region of the Loess Plateau, China. Chinese Journal of Applied Ecology, 25, 3413-3419.
	[ 杨士梭, 温仲明, 苗连朋, 戚德辉, 花东文 (2014). 黄土丘陵区植物功能性状对微地形变化的响应. 应用生态学报, 25, 3413-3419.]
[47]	Yang YZ, Wang H, Harrison SP, Prentice IC, Wright IJ, Peng CH, Lin GH (2019). Quantifying leaf-trait covariation and its controls across climates and biomes. New Phytologist, 221, 155-168. DOI PMID
[48]	Zhou DW (1996). Study on distribution of the genus Caragana Fabr. Bulletin of Botanical Research, 16, 428-435.

物种 Species	干燥度指数范围 Aridity index range	土壤氮含量范围 Soil nitrogen content range (mg·g^-1)	土壤pH范围 Soil pH range	样点数 Sample number
矮脚锦鸡儿 C. brachypoda	0.17-0.33	0.2-0.5	8.49-8.90	5
毛刺锦鸡儿 C. tibetica	0.25-0.43	0.3-3.2	8.55-8.86	4
荒漠锦鸡儿 C. roborovskyi	0.31-0.45	0.7-3.7	8.07-8.78	2
矮锦鸡儿 C. pygmaea	0.30-0.49	0.3-0.3	8.69-8.87	3
柠条锦鸡儿 C. korshinskii	0.15-0.75	0.2-1.3	8.01-9.12	12
狭叶锦鸡儿 C. stenophylla	0.22-0.69	0.5-1.2	8.54-8.57	4
中间锦鸡儿 C. intermedia	0.30-0.59	0.3-3.0	8.62-8.87	5
小叶锦鸡儿 C. microphylla	0.52-0.75	0.3-4.4	6.39-8.57	10
鬼箭锦鸡儿 C. jubata	0.88	6.3	7.17	1

物种 Species	干燥度指数范围 Aridity index range	土壤氮含量范围 Soil nitrogen content range (mg·g^-1)	土壤pH范围 Soil pH range	样点数 Sample number
矮脚锦鸡儿 C. brachypoda	0.17-0.33	0.2-0.5	8.49-8.90	5
毛刺锦鸡儿 C. tibetica	0.25-0.43	0.3-3.2	8.55-8.86	4
荒漠锦鸡儿 C. roborovskyi	0.31-0.45	0.7-3.7	8.07-8.78	2
矮锦鸡儿 C. pygmaea	0.30-0.49	0.3-0.3	8.69-8.87	3
柠条锦鸡儿 C. korshinskii	0.15-0.75	0.2-1.3	8.01-9.12	12
狭叶锦鸡儿 C. stenophylla	0.22-0.69	0.5-1.2	8.54-8.57	4
中间锦鸡儿 C. intermedia	0.30-0.59	0.3-3.0	8.62-8.87	5
小叶锦鸡儿 C. microphylla	0.52-0.75	0.3-4.4	6.39-8.57	10
鬼箭锦鸡儿 C. jubata	0.88	6.3	7.17	1

变异来源 Source of variation	h		LDMC		SLA		STD		LA		LNC		LPC		N:P
变异来源 Source of variation	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%
AI	24.70	31.06^***	32.72	40.80^***	21.57	33.68^***	16.61	29.76^***	87.13	67.39^***	20.45	31.80^***	16.69	34.89^***	2.77	8.42
SN	15.70	19.74^***	6.99	8.71^*	5.61	8.76^*	8.41	15.07^**	0.26	0.20	14.93	23.21^***	0.82	1.72	1.17	3.54
SpH	0.00	0.00	2.26	2.81	0.26	0.40	0.87	1.56	0.20	0.15	0.32	0.50	0.24	0.51	0.00	0.00
AI × SN	1.10	1.38	2.21	2.76	0.38	0.60	0.32	0.57	7.74	5.99^**	2.49	3.87	0.63	1.32	0.03	0.08
AI × SpH	1.17	1.47	1.38	1.72	2.52	3.94	0.04	0.07	0.79	0.61	0.07	0.11	1.18	2.48	3.25	9.85
SN × SpH	0.28	0.35	0.01	0.02	0.18	0.28	0.39	0.70	0.60	0.46	0.25	0.39	0.17	0.35	0.01	0.03
AI × SN × SpH	4.59	5.77^*	2.62	3.27	1.54	2.40	0.18	0.32	0.58	0.45	0.81	1.25	0.09	0.20	0.73	2.20

变异来源 Source of variation	h		LDMC		SLA		STD		LA		LNC		LPC		N:P
变异来源 Source of variation	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%	F	SS%
AI	24.70	31.06^***	32.72	40.80^***	21.57	33.68^***	16.61	29.76^***	87.13	67.39^***	20.45	31.80^***	16.69	34.89^***	2.77	8.42
SN	15.70	19.74^***	6.99	8.71^*	5.61	8.76^*	8.41	15.07^**	0.26	0.20	14.93	23.21^***	0.82	1.72	1.17	3.54
SpH	0.00	0.00	2.26	2.81	0.26	0.40	0.87	1.56	0.20	0.15	0.32	0.50	0.24	0.51	0.00	0.00
AI × SN	1.10	1.38	2.21	2.76	0.38	0.60	0.32	0.57	7.74	5.99^**	2.49	3.87	0.63	1.32	0.03	0.08
AI × SpH	1.17	1.47	1.38	1.72	2.52	3.94	0.04	0.07	0.79	0.61	0.07	0.11	1.18	2.48	3.25	9.85
SN × SpH	0.28	0.35	0.01	0.02	0.18	0.28	0.39	0.70	0.60	0.46	0.25	0.39	0.17	0.35	0.01	0.03
AI × SN × SpH	4.59	5.77^*	2.62	3.27	1.54	2.40	0.18	0.32	0.58	0.45	0.81	1.25	0.09	0.20	0.73	2.20

x	y	锦鸡儿属 C. species		矮锦鸡儿 C. pygmaea		矮脚锦鸡儿 C. brachypoda		鬼箭锦鸡儿 C. jubata		荒漠锦鸡儿 C. roborovskyi		毛刺锦鸡儿 C. tibetica		柠条锦鸡儿 C. korshinskii		狭叶锦鸡儿 C. stenophylla		小叶锦鸡儿 C. microphylla		中间锦鸡儿 C. intermedia
x	y	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept	斜率 Slope	截距 Intercept
h	LDMC	-0.31^***	0.21	0.61	-1.40	0.50^*	-1.03	-0.39	0.29	-0.15^**	-0.04	-0.39	0.16	-0.56^***	0.80	0.86	-1.66	-0.45^***	0.52	-0.26	0.19
	SLA	0.33^***	1.45	0.75	0.70	-0.47	2.69	0.70	0.81	-0.18^*	2.27	-0.51	2.43	0.69^***	0.62	-0.79	3.24	0.54^***	1.00	0.23^**	1.56
	STD	-0.43^***	0.52	-1.40	2.33	0.43	-0.76	-0.49	0.69	0.21	-0.55	-0.23	-0.02	-0.75^**	1.29	0.95	-1.74	-0.65^***	0.97	-0.83	1.16
	LA	0.64^***	-1.83	1.02	-2.71	0.51	-1.75	-0.89	1.60	0.24^*	-1.10	0.64^*	-1.53	0.98^***	-2.64	0.42	-1.66	0.38^**	-1.21	0.47	-1.36
	LNC	0.25^***	1.06	0.68	0.37	0.19	1.15	0.38	0.77	-0.10^**	1.49	0.17	1.16	0.42^*	0.65	-0.54	2.41	0.26^***	1.04	0.20	1.12
	LPC	0.37^***	-0.55	1.14	-1.76	-0.46	0.72	0.79	-1.27	0.51	-0.65	0.41^**	-0.44	0.88^***	-1.74	-0.80	1.45	0.36^***	-0.55	0.44	-0.71
	N:P	-0.26	1.82	-0.75	2.65	0.45	0.72	-0.60	2.44	-0.55	2.06	-0.33^**	1.69	-0.58^***	2.64	0.31	0.87	-0.23	1.84	0.38	0.74
LDMC	SLA	-1.07^***	1.67	-1.24	1.58	-0.95^***	1.71	-1.79	1.33	1.21	2.32	-1.28	1.67	-1.23^***	1.60	-0.92	1.71	-1.20^***	1.62	-0.87	1.72
	STD	1.32^***	0.20	2.23	0.64	-0.85	-0.41	-1.26	-0.90	-0.75	-0.41	-0.49	-0.31	1.33^***	0.22	1.11	0.11	1.35^***	0.20	3.19	0.55
	LA	-2.07^***	-1.39	1.69	-0.34	-1.03	-1.32	-2.27	-1.26	-1.61^*	-1.16	-1.51	-1.24	-1.74^***	-1.26	0.49	-0.85	-0.83^*	-0.78	1.79	-0.06
	LNC	-0.86^***	1.21	-1.13	1.18	-0.37	1.31	-0.98	1.05	0.66^**	1.51	-0.43	1.24	-0.74^***	1.23	-0.64^***	1.35	-0.75^***	1.27	-0.77	1.27
	LPC	-1.32^***	-0.33	-1.88^**	-0.43	-0.91^*	-0.22	-2.01	-0.69	-3.36	-0.78	-1.04	-0.27	-1.69^***	-0.55	-0.94^***	-0.11	-1.06^**	-0.22	1.69	0.52
	N:P	0.88^***	1.67	1.23^**	1.77	0.90	1.64	1.54	2.00	3.66	2.21	0.83	1.56	1.04^***	1.83	0.37^***	1.48	0.68	1.63	-1.46	1.02
SLA	STD	-1.21^***	2.22	-1.84	3.57	0.90	-1.94	-0.70	1.26	-0.28	0.36	0.34	-0.89	-1.08^***	1.96	1.21	-2.57	-1.13^**	2.03	-3.66	6.85
	LNC	0.82^***	-0.18	0.91	-0.26	0.39	0.64	0.55	0.33	0.55	0.24	-0.34	1.99	0.59^***	0.30	-0.70	2.91	0.69^*	0.11	0.89^*	-0.26
	LPC	1.25^***	-2.42	1.51	-2.81	0.96	-1.87	1.12	-2.18	2.79	-5.58	-0.81	1.53	1.31^***	-2.62	-1.03	2.19	0.99^*	-1.87	1.95^*	-3.74
	N:P	-0.85^***	3.09	-1.00	3.34	-0.94	3.25	0.86	-0.64	-3.04	7.44	0.64	0.13	-0.83^***	3.14	-0.40	2.16	-0.63	2.68	-1.67	4.68
STD	LA	-1.62^***	-1.11	0.75	-0.84	1.20	-0.83	1.80	0.36	2.33	-0.25	-1.46	-1.32	-1.31^**	-0.96	0.44	-0.90	-0.63	-0.67	0.56	-0.37
	LNC	-0.57^**	1.35	0.49	1.62	-0.44	1.36	-0.78	1.31	-0.58	1.21	0.64	1.46	-0.54^*	1.36	-0.57	1.42	-0.37	1.43	0.24	1.55
	LPC	-0.92^*	-0.12	0.85	0.33	1.07	0.22	-1.60	-0.17	-12.72	-2.28	1.85	0.31	-1.16^**	-0.25	-0.85	0	-0.56	-0.01	0.53	0.23
	N:P	0.62	1.54	0.55	1.41	-1.05	1.21	1.23	1.60	12.63	3.58	-1.54	1.08	0.75^*	1.65	-0.33	1.31	0.36	1.50	-0.46	1.27
LA	LNC	0.38^***	1.76	0.67	2.19	0.36	1.78	0.43	1.60	-0.41^*	1.03	0.27	1.58	0.44^***	1.78	1.29	2.81	0.74^*	1.88	0.43	1.71
	LPC	0.57^***	0.51	1.11	1.26	0.89	0.96	-0.89	0.14	2.09	1.65	0.65^*	0.55	0.87^***	0.59	1.91	2.04	1.05	0.65	0.94^*	0.57
	N:P	-0.39^*	1.10	0.73	2.02	0.87	2.24	0.68	1.36	-2.28	-0.44	-0.51	0.91	-0.61^***	1.06	-0.74	0.64	-0.67	1.08	-0.81^*	0.97
LNC	LPC	1.56^***	-2.21	1.66^**	-2.38	2.46	-3.44	2.05	-2.86	-5.05	6.87	2.40^**	-3.24	2.24^***	-3.31	1.48^***	-2.11	1.42^***	-2.03	2.19^*	-3.17