Optimizing continuous cover management of boreal forest when timber prices and tree growth are stochastic

Forest Ecosystems

Table 2 Results calculated from 1000 stochastic simulations with the optimal values of decision variables for a risk neutral decision maker in different problem formulations when tree growth, ingrowth and timber price are stochastic (Det = deterministic optimization, Anti = stochastic anticipatory optimization, Ada = stochastic adaptive optimization)

Number of the cutting	Young spruce			Mature spruce			Young pine			Mature pine
Number of the cutting	Det	Anti	Ada	Det	Anti	Ada	Det	Anti	Ada	Det	Anti	Ada
	Cutting year
1^st	20	20	21.9	0	0	4.6	20	20	25.3	0	0	5.6
2^nd	35	35	42.1	20	15	19.6	35	35	47.4	15	15	21.2
3^rd	55	50	62.9	55	45	30.8	55	50	70.3	45	25	39.2
	Diameter before cutting (cm)
1^st	19.1	19.1	19.6	23.0	23.0	24.4	17.5	17.6	18.6	21.0	21.0	22.2
2^nd	19.9	19.7	21.9	28.3	26.6	27.7	17.8	18.9	20.0	23.5	23.5	23.8
3^rd	23.3	22.3	25.3	31.5	30.5	29.9	19.9	19.1	21.6	24.8	24.3	23.7
	Basal area before cutting (m² · ha⁻¹)
1^st	35.7	35.7	37.1	28.1	28.1	31.3	32.1	32.2	35.8	25.1	25.1	28.1
2^nd	29.5	27.1	33.6	21.6	19.8	19.7	26.7	26.6	33.2	16.4	19.4	19.5
3^rd	27.6	25.7	29.0	26.7	21.6	14.9	27.6	26.0	32.0	23.9	14.1	19.6
	Basal area after cutting (m² · ha⁻¹)
1^st	14.6	12.4	14.5	9.8	10.8	11.1	13.5	13.4	14.4	9.3	11.8	11.5
2^nd	10.6	12.7	12.5	6.4	5.5	9.2	10.5	12.8	12.5	7.1	9.4	8.7
3^rd	10.5	12.6	10.1	11.6	7.2	5.1	11.3	12.1	11.2	9.2	6.2	9.3
	Removed volume (m³ · ha⁻¹)
1^st	176	192	192	197	187	219	140	141	167	150	126	162
2^nd	163	126	190	164	153	113	129	111	175	93	99	109
3^rd	160	122	182	167	157	109	141	118	181	153	78	93
Total	499	440	564	528	497	441	410	370	523	396	303	364
	Average roadside saw log price obtained (€ · m⁻³)
1^st	56.8	55.8	64.6	56.1	56.3	61.9	56.7	56.4	66.8	55.7	56.3	62.9
2^nd	56.2	56.5	65.0	56.5	56.4	66.2	56.1	55.8	67.0	56.2	56.5	67.5
3^rd	56.5	55.6	65.1	54.5	55.1	67.4	55.6	55.8	65.2	54.5	55.7	68.1