Evaluating Strategies for the Management of Douglas-Fir in Central Europe
Abstract
:1. Introduction
- (i)
- The calibration of Douglas-fir for the growth simulator (MOSES) as a diagnostic tool for silvicultural scenario analysis.
- (ii)
- The analysis of the long-term impact of different Douglas-fir management variants by running scenarios with the growth simulator, MOSES.
2. Materials and Methods
2.1. Identification of the Principal Douglas-Fir Management Issues, Based on a Survey
2.1.1. Planting Options Considering in the Modeling
2.1.2. Survival of Natural Regeneration
2.1.3. Tending/Thinning Strategies Considering in the Modeling
2.2. The Tree Growth Model MOSES
3. Results
3.1. Calibration of the Tree Growth Model
3.2. Management Scenarios
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variety/Provenance | The principal variety was coastal Douglas-fir (Pseudotsuga menziesii var. viridis), origins are Ashford Elbe, Darrington, Snoqualmie River, Trout Lake (USA), Centre Creek, Heffley Lake (Canada) [25]. |
Site and stand characteristics | Summer warm and dry climate in the Eastern part of Austria, oceanic climate in the Alpine foreland of Austria, and low mountain range in Germany, astonished climate at the northern edge of the Alps; the majority of stands at altitudes 650 m to 850 m, on silicate bedrock with soil depth 30 cm to 120 cm, 14% on limestone with soil depth <15 cm to 30 cm; water balance on silicate sites was moderately fresh to fresh, on limestone moderately dry; 76% of stands are aged <20 years. |
Species mixture | The principal associated species were Norway spruce, common beech, silver fir, larch, Scots pine, sessile oak, maple; with stem number of Douglas-fir smaller 0.3 (44%); greater 0.3 and smaller 0.5 (21%); greater 0.5 (14%). |
Planting | Use of bare-rooted plants was most common (73%); planting operations performed by concave spade and whole driller (77%), or by planting ditches (18%); spacing from 1.5 × 2.5 m to 5 × 5 m, most common being 1.8 × 2 m; most common initial stem number 2700/ha; portion of Douglas-fir on average was 30%; mixture form principally was tree by tree with Douglas-fir every 5 to 10 m, planting Douglas-fir in rows or groups was rare; planting largely occurs in spring; frequently reported problem was a fail of Douglas-fir due to insufficient initial stem number. |
Natural regeneration | Establishment of Douglas-fir under the shelter of mature trees by opening up or group removal; insufficient opening up causes inadequate rooting and poor crown development; threats come from competitive vegetation, especially native tree species, and game damages. |
Tending | Most commonly at top height 2 to 6 m (74%), stem number reduction by 30%; sudden drop-down of young Douglas-fir after release, as result of poorly developed roots and crowns (6%); problem was the spread of blackberry (Rubus fruticosus) after release. |
Thinning | First thinning at top height 8 to 10m (83%), with removed volume 30–50 m3/ha; subsequent interventions at intervals 5 to 10 years, with removed volume 50–120 m3/ha; thinning method was future crop tree selection (68%); mentioned problem was a degradation of the crown after thinning due to insufficient thinning and too late thinning (16%). |
Debranching | Debranching at top height 8 to 10 m (37%), at 12 to 15 m (44%); debranched section of tree was between 5 and 10 m (77%); reported problem was the big workload. |
Stand | Age | N/ha | DH (m) | Dq (cm) | V/ha (m3) | Elev (m) | Annual Temp. (°C) | Annual Precip. (mm) | Geology |
---|---|---|---|---|---|---|---|---|---|
1 | 90 | 136 | 35 | 52 | 324 | 290 | 9.9 | 600 | Loess |
2 | 84 | 164 | 43 | 62 | 720 | 460 | 9.6 | 720 | Boulders in a sand-loam matrix |
3 | 82 | 211 | 43 | 57 | 721 | 560 | 9.1 | 790 | Mica schist, quartz phyllonite |
4 | 40 | 399 | 23 | 32 | 278 | 520 | 9.3 | 770 | Muscovite gneiss |
5 | 38 | 558 | 24 | 32 | 371 | 360 | 9.5 | 650 | Sand and argillaceous marl |
6 | 52 | 188 | 27 | 39 | 223 | 370 | 9.1 | 570 | Granulite |
7 | 108 | 61 | 32 | 62 | 219 | 400 | 9.0 | 580 | Granulite |
8 | 58 | 748 | 33 | 39 | 822 | 430 | 9.1 | 640 | Granulite |
9 | 43 | 306 | 31 | 39 | 474 | 440 | 8.9 | 620 | Magmatized granite-gneiss |
10 | 42 | 285 | 29 | 39 | 386 | 410 | 9.0 | 610 | Paragneis |
11 | 70 | 165 | 39 | 64 | 595 | 330 | 9.4 | 960 | Rubble |
12 | 121 | 247 | 39 | 59 | 863 | 530 | 7.9 | 710 | Granite |
13 | 110 | 160 | 53 | 81 | 1317 | 820 | 7.1 | 2100 | Carbonate-free, fine sandstone |
14 | 109 | 76 | 50 | 82 | 740 | 640 | 8.0 | 900 | Granite |
15 | 105 | 108 | 53 | 77 | 829 | 660 | 7.9 | 910 | Granite |
16 | 104 | 207 | 50 | 73 | 821 | 590 | 8.3 | 890 | Granite |
17 | 54 | 324 | 33 | 50 | 650 | 660 | 8.1 | 1110 | Gravel in sand matrix, fluvial |
18 | 95 | 221 | 43 | 67 | 821 | 810 | 7.7 | 1450 | Sandstone calcareous marl |
19 | 100 | 226 | 48 | 67 | 1199 | 480 | 8.8 | 960 | Silt, clayey-sandy, often gravelly |
20 | 72 | 360 | 37 | 53 | 695 | 680 | 7.3 | 900 | Biotite-granite |
21 | 58 | 221 | 39 | 52 | 627 | 480 | 8.6 | 780 | Impact breccia |
22 | 62 | 350 | 39 | 49 | 749 | 670 | 8.2 | 1120 | Glacial till, silt, sand, gravel |
23 | 109 | 146 | 50 | 78 | 1158 | 660 | 7.9 | 870 | Gravel, silt, clay, often stones |
24 | 40 | 544 | 22 | 32 | 245 | 700 | 7.7 | 900 | Limestone, dolomite |
25 | 41 | 612 | 23 | 32 | 391 | 700 | 7.8 | 890 | Corallian limestone |
26 | 60 | 298 | 37 | 51 | 673 | 890 | 7.0 | 1050 | Limestone, dolomite |
27 | 51 | 366 | 34 | 41 | 453 | 450 | 9.1 | 970 | Limestone, dolomite |
28 | 50 | 279 | 32 | 48 | 579 | 520 | 8.8 | 1010 | Dolomite |
29 | 53 | 594 | 32 | 30 | 465 | 290 | 9.9 | 600 | Variegated sandstone |
30 | 37 | 910 | 28 | 31 | 873 | 460 | 9.6 | 720 | Variegated sandstone |
Age Class | Trees | Characteristics of the Trees (Mean, Min, Max) | |||||
---|---|---|---|---|---|---|---|
h (m) | ih (m) | dbh (cm) | id (cm) | hlc (m) | ∆hlc (m) | ||
Calibration Data | |||||||
<30 | 22 | 17.7 | 1.52 | 15.1 | 1.61 | 8.02 | 3.14 |
(10.8–21.1) | (0.101–2.81) | (7.12–25.4) | (0.110–4.32) | (3.11–10.5) | (0.122–6.23) | ||
31–50 | 24 | 18.23 | 1.10 | 15.7 | 1.31 | 8.62 | 2.93 |
(11.1–21.6) | (0.120–2.83) | (7.91–26.4) | (0.141–4.22) | (3.13–11.6) | (0.101–7.23) | ||
>50 | 58 | 24.0 | 1.4 | 25.3 | 1.73 | 14.9 | 1.74 |
(12.4–47.0) | (0.143–2.92) | (9.01–56.5) | (0.132–3.93) | (5.54–26.1) | (0.143–4.92) | ||
Validation Data | |||||||
<30 | 106 | 22.1 | 1.55 | 22.4 | 1.38 | 14.1 | 1.10 |
(11.6–29.9) | (0.102–2.63) | (8.32–49.5) | (0.132–5.40) | (6.62–25.4) | (0.122–3.81) | ||
31–50 | 103 | 22.2 | 1.80 | 25.2 | 1.70 | 11.4 | 1.70 |
(12.3–33.7) | (0.112–3.62) | (7.71–46.2) | (0.104–4.62) | (5.73–20.0) | (0.143–4.11) | ||
>50 | 124 | 27.4 | 1.70 | 33.5 | 1.70 | 16.3 | 1.75 |
(11.5–51.0) | (0.140–3.52) | (9.12–97.1) | (0.144–5.02) | (5.50–28.1) | (0.133–4.15) |
Trees | xobs (Min, Max) | sD | CI | PI | TI | |||
---|---|---|---|---|---|---|---|---|
Eckmüllner | ||||||||
ih (m) | 333 | 1.68 | (0.102–3.62) | 0.032 | 0.87 | −0.063 to 0.13 | −1.69 to 1.75 | −2.38 to 2.44 |
id (cm) | 333 | 1.6 | (0.104–5.40) | 0.031 | 1.11 | −0.089 to 0.15 | −2.15 to 2.21 | −3.02 to 3.08 |
Δhlc (m) | 333 | 1.53 | (0.122–4.15) | −0.034 | 1.31 | −0.21 to 0.13 | −2.62 to 2.55 | −5.32 to 5.26 |
Bergel | ||||||||
ih (m) | 333 | 1.68 | (0.102–3.62) | 0.029 | 0.9 | −0.062 to 0.12 | −1.74 to 1.79 | −2.43 to 2.49 |
id (cm) | 333 | 1.6 | (0.104–5.40) | −0.245 | 1.13 | −0.36 to −0.13 | −2.47 to 1.98 | −3.34 to 2.73 |
Δhlc (m) | 333 | 1.53 | (0.122–4.15) | 0.133 | 1.29 | −0.02 to 0.286 | −2.41 to 2.68 | −3.45 to 3.71 |
Random | Square | Strip | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
N/ha | V/ha (m3) | hL (m) | Dq (cm) | N/ha | V/ha (m3) | hL (m) | Dq (cm) | N/ha | V/ha (m3) | hL (m) | Dq (cm) | |
Spruce | 155 | 5 | 11 | 8 | 411 | 140 | 19 | 22 | 422 | 150 | 19 | 22 |
Dou f | 244 | 72 | 17 | 20 | 255 | 258 | 23 | 33 | 355 | 483 | 25 | 38 |
Beech | 455 | 747 | 25 | 44 | 488 | 487 | 24 | 34 | 444 | 330 | 23 | 30 |
∑ | 854 | 824 | 1154 | 885 | 1222 | 964 |
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Eberhard, B.R.; Eckhart, T.; Hasenauer, H. Evaluating Strategies for the Management of Douglas-Fir in Central Europe. Forests 2021, 12, 1040. https://doi.org/10.3390/f12081040
Eberhard BR, Eckhart T, Hasenauer H. Evaluating Strategies for the Management of Douglas-Fir in Central Europe. Forests. 2021; 12(8):1040. https://doi.org/10.3390/f12081040
Chicago/Turabian StyleEberhard, Benno Richard, Tamara Eckhart, and Hubert Hasenauer. 2021. "Evaluating Strategies for the Management of Douglas-Fir in Central Europe" Forests 12, no. 8: 1040. https://doi.org/10.3390/f12081040
APA StyleEberhard, B. R., Eckhart, T., & Hasenauer, H. (2021). Evaluating Strategies for the Management of Douglas-Fir in Central Europe. Forests, 12(8), 1040. https://doi.org/10.3390/f12081040