EVALUATING THE COMPETITIVE ENVIRONMENT FOR WILD PISTACHIO (<i>Pistacia atlantica Desf</i>.) SEEDLINGS IN THE CENTRAL FORESTS OF IRAN

Kiani, Bahman; Amiri, Asma

doi:10.1590/1806-90882018000600007

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Articles • Rev. Árvore 42 (6) • 2018 • https://doi.org/10.1590/1806-90882018000600007 copy

EVALUATING THE COMPETITIVE ENVIRONMENT FOR WILD PISTACHIO (Pistacia atlantica Desf.) SEEDLINGS IN THE CENTRAL FORESTS OF IRAN

AVALIAÇÃO DO AMBIENTE COMPETITIVO DE MUDAS DE PISTACHE SELVAGEM (Pistacia atlantica Desf.) EM FLORESTAS CENTRAIS DO IRÃ

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Wild pistachio (Pistacia atlantica Desf.) is an important tree species from dry forests of Eurasia. Seedlings must usually compete with other tree and shrub species in the dry harsh environment of mountain forests. In this study, we identified the main competitor species and evaluated some widely used competition indices, including distance-dependent and distance-independent ones, to quantify the relationship between the reference seedlings and their neighbors. The results indicated that the main competitors are mountain almond (Amygdalus scoparia Spach.), thorny almond (Amygdalus lycioides Spach.), montpellier maple (Acer monspessulanum subsp. cinerascens Boiss.) and other wild pistachio seedlings. We found that competition increases the height growth but reduces the diameter, basal area growth and crown development of wild pistachio seedlings. Some competition indices had a noticeable correlation with seedling growth, indicating that competition does exist. A combination of log-transformed indices could explain 85% of the diameter growth variations, 46% of height growth, 76% of basal area growth and 72% of crown area development with a good precision.

Keywords:
Competition; Growth; Modeling

Table 1 Competition indices evaluated in this study (DI: distance-independent; DD: distance dependent).

Index	Source	Equation
C₁	Reineke (1933)Reineke LH. Perfecting a stand density index for even-aged forest. Journal of Agricultural Researches. 1933;46(7):627-38. DI	$10^{(\log N + 1.605 \times \log dg - 1.605)}$
C₂	Rivas et al., (2005)Rivas JJC, Gonzalez JG, Aguirre O, Hernandez FG. The effect of competition of individual tree basal area growth in mature stands of Pinus cooperi Blanco in Durango (Mexico). European Journal of Forest Research. 2005;124:133-42. DI	$(\sum_{i = 1}^{n} (π \times {cw}_{i}^{2}) / 4) / s$
C₃	Wykoff et al., (1982)Wykoff WR, Crookston NL, Stage AR. User's guide to the stand prognosis model. Washington: USDA Forest Service; 1982. 119p. (General Technical Report, INT-133) DI	$(\sum_{i = 1}^{n} (π \times d^{2}_{\max j}) / 4)$
C₄	Contreras et al., (2011)Contreras MA, Affleck D, Chung W. Evaluating tree competition indices as predictors of basal area increment in western Montana forests. Forest Ecology and Management. 2011;262:1939-49. DD	$n (number of neighbors)$
C₅	Hegyi (1974)Hegyi F. A simulation model for managing jack pine stands. In: Fries J, editor. Proceedings of IUFRO meeting S4.01.04 on Growth models for tree and stand simulation. Stockolm: Royal College of Forestry; 1974. p.74-90. DD	$\sum_{i = 1}^{n} d_{i} / (d \times {dist}_{i})$
C₆	Rouvinen and Kuuluwainen (1997)Rouvinen S, Kuuluvainen T. Structure and asymmetry of tree crowns in relation to local competition in a natural mature Scot pine forest. Canadian Journal Forest Research. 1997;27:890-902. DD	$\sum_{i = 1}^{n} \arctan (d_{i} / {dist}_{i})$
C₇	Stadt et al., (2007)Stadt KJ, Huston C, Coated KD, Feng Z, Dale MRT, Lieffers VJ. Evaluation of competition and light estimation indices for predicting diameter growth in mature boreal mixed forests. Annals of Forest Science. 2007;64(5):477-90. DI	$(1 / S) (π / 4) \sum_{i = 1}^{n} d_{i}^{2}$
C₈	Stadt et al., (2007)Stadt KJ, Huston C, Coated KD, Feng Z, Dale MRT, Lieffers VJ. Evaluation of competition and light estimation indices for predicting diameter growth in mature boreal mixed forests. Annals of Forest Science. 2007;64(5):477-90. DI	$(1 / S) (1 / d) \sum_{i = 1}^{n} d_{i}$
C₉	Stadt et al., (2007)Stadt KJ, Huston C, Coated KD, Feng Z, Dale MRT, Lieffers VJ. Evaluation of competition and light estimation indices for predicting diameter growth in mature boreal mixed forests. Annals of Forest Science. 2007;64(5):477-90. DI	$(1 / S) (1 / d^{2}) \sum_{i = 1}^{n} d_{i}^{2}$
C₁₀	Stadt et al., (2007)Stadt KJ, Huston C, Coated KD, Feng Z, Dale MRT, Lieffers VJ. Evaluation of competition and light estimation indices for predicting diameter growth in mature boreal mixed forests. Annals of Forest Science. 2007;64(5):477-90. DI	${(-)}_{S}^{π} \sum_{i = 1}^{n} {cw}_{i}^{2}$
C₁₁	Burkhar and Tome (2012)Burkhart HE, Tome M. Modeling forest trees and stands. Dordrecht: Springer; 2012. DI	$(10000 / n) \times (g_{i} / \bar{g})$

Table 2 Bivariate correlation between Pistacia atlantica seedling growth and competition indices in mountain forests, Iran.

		C₁	C₂	C₃	C₄	C₅	C₆	C₇	C₈	C₉	C₁₀	C₁₁
Height	r	-0.03	-0.12	-0.41	0.37	0.03	0.25	-0.04	-0.19	-0.19	-0.12	0.38
Increment	P-	0.847	0.404	0.003	0.009	0.851	0.075	0.771	0.181	0.185	0.404	0.006
(cm.year^-1)	value
DRC	r	-0.06	-0.24	-0.25	0.17	-0.31	0.10	-0.07	-0.45	-0.35	-0.24	0.27
Increment	P-	0.663	0.109	0.097	0.260	0.035	0.516	0.624	0.002	0.016	0.109	0.070
(cm.year^-1)	value
Crown	r	-0.19	-0.34	-0.22	0.42	-0.05	0.35	-0.17	-0.42	-0.25	-0.34	0.23
Area	P-	0.189	0.016	0.134	0.003	0.736	0.012	0.232	0.003	0.081	0.016	0.103
Growth	value
(m².year^-1)

Table 3 Model coefficients and fit statistics for log-linear models.

Dependent	Predictor	Parameter estimate	t	p-value	R²	R²_adj	RMSE	NRMSE %
DRC growth	Constant	0.105	14.1	0.000
(cm.year^-1)	logC₇	0.178	14.98	0.000
	logC₅	-0.195	-16.92	0.000	0.86	0.85	0.029	8.5
	logC₄	-0.53	-4.51	0.000
Height growth	(Constant)	6.22	15.56	.000
(cm.year^-1)	logC₅	-4.97	-6.47	.000	0.48	0.46	0.97	7.9
	logC₇	4.1	5.53	.000
Basal area	(Constant)	0.08	1.69	0.097
growth (cm².year^-1)	logC₇	0.86	11.45	.000	0.77	0.76	0.19	10.2
	logC₅	-0.9	-12.33	.000
	logC₄	-0.26	-3.55	.001
	(Constant)	0.33	5.26	.000
Crown area	logC₈	-0.076	-6.94	.000
growth	logC₄	0.17	7.06	.000
(m².year^-1)	logC₁₁	-0.044	-7.8	.000	0.75	0.72	0.018	8.1
	logC₁	-0.087	-4.5	.000
	logC₇	0.058	4.22	.000
	logC₆	-0.021	-2.12	.040

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