Landowner Acceptability of Silvicultural Treatments to Restore an Open Forest Landscape
Abstract
:1. Introduction
- What silvicultural treatments are seen as acceptable and unacceptable in a restoration context?
- To what extent does the acceptability of treatments that are verbally described match the acceptability of those that are visually depicted?
- Does the provision of information about the purpose and goals of restoration influence the acceptability of treatments?
- Are respondents heterogeneous in their acceptability of treatments?
1.1. Acceptability of Forest Restoration Treatments
1.2. Verbal Description vs. Visual Depiction of Restoration Treatments
1.3. Preference, Acceptability, and the Effects of Information
1.4. Heterogeneity of Acceptability Judgments
2. Materials and Methods
2.1. Study Area and Project Description
2.2. Research Design
2.3. Selection and Specification of Restoration Treatments
2.3.1. Verbal Descriptions and Acceptability Rating Scales
2.3.2. Visual Scenarios and Acceptability Choice Experiment
2.4. Informational Intervention and Other Questionnaire Items
2.5. Data Collection
2.6. Data Analysis
2.6.1. Analysis of Verbal Acceptability Ratings
2.6.2. Analysis of Visual Scenarios and Comparison with Verbal Ratings
3. Results
3.1. Profile of Respondents
3.2. Verbal Acceptability Ratings
Landowner Heterogeneity
3.3. Visual Acceptability Scenarios
3.3.1. Overall Logit Model
3.3.2. Logit Model Segmentation by Landowner Clusters
4. Discussion
4.1. Acceptability of Treatments and Comparison of Judgment Approaches
4.2. Information Effects and Heterogeneity of Acceptability Judgments
4.3. Management Implications
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Hypotheses | Analyses | |
---|---|---|
H1 | Acceptability of restoration treatments: Less intensive treatments such as selective thinning, small openings, and low frequency burning would be more acceptable than highly intensive treatments such as large openings and frequent burning. | Compare mean scores (verbal scales); compare weights of individual attribute levels (DCE) |
H2 | Verbal versus visual acceptability judgments: Treatments such as large openings and frequent burning that are both described verbally and depicted visually would be judged similarly. | Comparison of findings between verbal and visual approaches; comparison of attribute level DCE model estimates for cluster-defined segments |
H3 | Effects of information: Landowners who received an informational statement about the characteristics and goals of pine barrens restoration would rate the acceptability of treatments higher than those not receiving the statement. | Yes/no segmentation of respondents and comparison of acceptability judgments for verbal and visual approaches |
H4 | Heterogeneity of acceptability judgments: Landowners who had greater familiarity and experience with forestry issues and pine barrens management would rate the acceptability of treatments higher than those with lesser familiarity and experience. | Cluster analysis of verbal acceptability factor ratings and exploratory covariate analysis; cluster segmentation of DCE logit estimates |
Attributes | Attribute Levels | Description |
---|---|---|
Spatial configuration |
| The spatial configuration attribute simulated increasing openness by showing trees concentrated in the foreground (Level 1), midground (Level 3), or background (Level 4). Level 2 distributed evenly trees across the landscape. Levels 5 and 6 explored specific treatment designs by placing 1% of all trees close to the observer viewpoint in the foreground and the rest of the trees distributed in the mid- or background. |
Tree density |
| Tree cover ranged between 5%–35%, reflecting the range characterized by forest experts. In cases of high tree density, a small view corridor was always present in the image, allowing a view to the background landscape. |
Tree distribution |
| This attribute showed different design options by trees either scattered in the landscape (Level 1), grouped as clumps (Level 2), or appearing as a 1:1 mix of both tree distributions (Level 3). |
Fire interval |
| Each interval simulated conditions just before the next fire. Level 1 showed lower understory vegetation, greater thermal pruning of trees and more dark open patches of ground, and a darker bark of trees to simulate fire charring compared to the other levels. |
Shrub density |
| Shrub density ranged from 0%–60% of land cover. The height of shrubs, not their amount, depended on the fire interval. Frequent fire intervals reduced the height of shrubs. |
Standing dead trees & blueberries |
| The number of standing dead trees ranged from 0–8 and were shown in the foreground. Flowering blueberry bushes were shown in the immediate foreground (Level 3). |
How Acceptable to You Is the Use of Each of These Approaches to Restore a Pine Barrens? | Factors | |||
---|---|---|---|---|
Mean | Large Openings (1) | Selective Openings (2) | Fire (3) | |
Large areas where most of the trees are cut, 40 acres (16 ha) | 2.58 | 0.928 | ||
Very large areas where most of the trees are cut, 100+ acres (40 ha) | 2.17 | 0.893 | ||
Medium areas where most of the trees are cut, 20 acres (8 ha) | 2.94 | 0.797 | (−0.411) | |
Selective logging to thin trees | 4.05 | 0.760 | ||
Small areas where most of the trees are cut, less than 10 acres (4 ha) | 3.44 | (−0.489) | 0.680 | |
Mowing or mechanical means to maintain open understory conditions | 3.55 | 0.678 | ||
Planned and controlled, low-intensity fire every 10 years | 3.50 | 0.876 | ||
Planned, low-intensity fire every 3 years | 3.02 | 0.843 | ||
Reintroduction of endangered plant species | 3.87 | |||
Leaving dead trees standing in the landscape | 3.05 | |||
Use of herbicides to remove invasive woody species | 2.81 | |||
Variance explained (total 75.1%) | 32.60% | 21.70% | 20.80% | |
Cronbach’s Alpha | 0.894 | 0.614 | 0.746 |
Means | All | Cluster 1 (19.5%) “All Are Acceptable” | Cluster 2 (41.0%) “No Clearcut” | Cluster 3 (24.9%) “In Between” | Cluster 4 (14.6%) “Nothing Is Acceptable” | |
---|---|---|---|---|---|---|
Factors | ANOVA (Welch) | |||||
Larger Openings (1) | 2.56 | 3.85 a | 1.97 b | 3.26 c | 1.33 d | F = 517.8, p < 0.0001 |
Selective Openings (2) | 3.68 | 4.34 a | 3.86 b | 3.49 c | 2.58 d | F = 178.7, p < 0.0001 |
Fire (3) | 3.26 | 4.26 a | 3.27 b | 2.89 c | 2.53 d | F = 121.7, p < 0.0001 |
Single items | Kruskal-Wallis-Test | |||||
Large areas where most of the trees are cut, 40 acres (16 ha) | 2.58 | 4.00 a | 1.88 b | 3.37 c | 1.26 d | p < 0.0001 |
Very large areas where most of the trees are cut, 100+ acres (40 ha) | 2.17 | 3.36 a | 1.45 b | 2.97 ac | 1.21 bd | p < 0.0001 |
Medium areas where most of the trees are cut, 20 acres (8 ha) | 2.94 | 4.19 a | 2.57 b | 3.42 c | 1.50 d | p < 0.0001 |
Selective logging to thin trees | 4.05 | 4.57 a | 4.19 b | 3.88 c | 3.22 d | p < 0.0001 |
Small areas where most of the trees are cut, less than 10 acres (4 ha) | 3.44 | 4.25 a | 3.55 b | 3.48 b | 1.97 c | p < 0.0001 |
Mowing or mechanical means to maintain open understory conditions | 3.55 | 4.21 a | 3.84 b | 3.12 c | 2.54 c | p < 0.0001 |
Planned and controlled, low-intensity fire every 10 years | 3.50 | 4.33 a | 3.59 b | 3.08 c | 2.85 c | p < 0.0001 |
Planned, low-intensity fire every 3 years | 3.02 | 4.2 a | 2.93 b | 2.71 b | 2.22 c | p < 0.0001 |
Reintroduction of endangered plant species † | 3.87 | 4.21 a | 3.88 b | 3.65 c | 3.75 abc | p < 0.0001 |
Leaving dead trees standing in the landscape † | 3.05 | 3.37 a | 2.97 b | 3.04 b | 2.87 b | p < 0.05 |
Use of herbicides to remove invasive woody species † | 2.81 | 3.44 a | 2.73 b | 2.86 b | 2.10 c | p < 0.0001 |
Items | All | Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | Kruskal-Wallis-Test |
---|---|---|---|---|---|---|
Manage timber for logging | 3.85 | 4.10 a | 3.83 ab | 3.90 ab | 3.47 b | p < 0.05 |
Increase species diversity | 3.99 | 4.24 a | 3.96 b | 3.97 b | 3.81 b | p < 0.001 |
Reintroduce rare habitats | 3.79 | 4.07 a | 3.86 ab | 3.61 cd | 3.54 bd | p < 0.0001 |
Manage wildlife habitat | 4.45 | 4.69 a | 4.47 ab | 4.41 bc | 4.15 bc | p < 0.0001 |
Manage fisheries | 4.37 | 4.68 a | 4.34 b | 4.30 b | 4.15 b | p < 0.0001 |
Prevent wildfire | 4.46 | 4.49 | 4.52 | 4.52 | 4.18 | n.s |
Manage roads in the forest | 3.98 | 4.23 a | 3.92 b | 3.97 b | 3.87 ab | p < 0.001 |
Provide recreation opportunities | 4.06 | 4.26 a | 4.08 ab | 4.10 ab | 3.68 b | p < 0.05 |
Provide beautiful landscapes | 4.11 | 4.11 | 4.22 | 4.01 | 3.94 | n.s. |
Maintain water quality | 4.74 | 4.79 | 4.81 | 4.64 | 4.65 | n.s |
Reduce greenhouse gas emissions | 4.10 | 3.92 | 4.21 | 4.05 | 4.06 | n.s. |
Activities | All | Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | 𝝌2 |
---|---|---|---|---|---|---|
Viewing scenery | 86.7 | 93.4 a | 88.0 ab | 77.6 bc | 89.7 abc | p < 0.01 |
Relaxing | 86.1 | 91.2 a | 89.0 a | 79.3 a | 82.4 a | p < 0.05 |
Hiking/walking | 83.5 | 86.8 abc | 86.4 b | 73.3 c | 88.2 abc | p < 0.01 |
Fishing | 77.3 | 86.8 | 73.8 | 77.6 | 73.5 | n.s. |
Wildlife/bird Watching | 60.7 | 57.1 | 60.7 | 63.8 | 60.3 | n.s. |
Berry picking | 57.9 | 69.2 a | 60.2 bc | 51.7 bc | 47.1 c | p < 0.05 |
Hunting | 57.1 | 71.4 a | 52.4 bc | 63.8 ab | 39.7 c | p < 0.001 |
Motor boating | 53.2 | 51.6 | 52.9 | 52.6 | 57.4 | n.s. |
ATV/UTV riding | 51.5 | 57.1 | 47.1 | 56.0 | 48.5 | n.s. |
Non-motorized boating | 45.1 | 51.6 | 45.5 | 36.2 | 50.0 | n.s. |
Camping | 32.8 | 36.3 | 30.9 | 28.4 | 41.2 | n.s. |
Picnicking | 25.8 | 27.5 | 26.2 | 19.8 | 32.4 | n.s. |
Cross-country skiing/snowshoeing | 24.5 | 34.1 ab | 25.1 bc | 12.1 c | 30.9 ab | p < 0.001 |
Snowmobiling | 21.7 | 24.2 | 20.4 | 20.7 | 23.5 | n.s. |
Road biking | 17.2 | 13.2 | 18.3 | 15.5 | 22.1 | n.s. |
Mountain biking | 9.4 | 12.1 | 10.5 | 6.0 | 8.8 | n.s. |
Running | 9.4 | 13.2 | 7.9 | 6.9 | 13.2 | n.s. |
Off-road/dirt biking | 6.2 | 7.7 | 6.3 | 5.2 | 5.9 | n.s. |
Trapping | 4.3 | 12.1 a | 3.7 b | 1.7 b | 0.0 b | p < 0.001 |
Attributes and Attribute Levels | Parameter Estimates | S.E. | Z-Value | Wald Statistic |
---|---|---|---|---|
Spatial configuration | *** 1075.1 | |||
| *** 1.135 | 0.074 | 15.419 | |
| *** 1.055 | 0.072 | 14.690 | |
| *** −1.206 | 0.062 | −19.417 | |
| *** −1.366 | 0.063 | −21.731 | |
| *** 0.206 | 0.058 | 3.533 | |
| ** 0.175 | 0.058 | 3.017 | |
Tree density | * 10.0 | |||
| * −0.123 | 0.048 | −2.553 | |
| * 0.115 | 0.050 | 2.303 | |
| −0.039 | 0.049 | −0.797 | |
| 0.047 | 0.049 | 0.949 | |
Tree distribution | * 10.9 | |||
| * −0.124 | 0.050 | −2.470 | |
| ** 0.140 | 0.048 | 2.885 | |
| −0.016 | 0.049 | −0.317 | |
Fire interval | *** 65.8 | |||
| *** −0.334 | 0.048 | −7.023 | |
| 0.022 | 0.049 | 0.443 | |
| *** 0.312 | 0.051 | 6.121 | |
Shrub density | * 8.5 | |||
| ** −0.123 | 0.048 | −2.553 | |
| * 0.098 | 0.050 | 1.985 | |
| −0.019 | 0.049 | −0.383 | |
| 0.044 | 0.049 | 0.895 | |
Standing dead trees | (*) 7.0 | |||
| (*) 0.098 | 0.050 | 1.938 | |
| −0.084 | 0.049 | −1.728 | |
| 0.048 | 0.049 | 0.972 | |
| −0.062 | 0.049 | −1.273 | |
Constant | *** 0.885 | 0.029 | 30.400 | *** 924.1 |
Pseudo-R2(0)/R2: 0.32/0.18 |
Attributes | All | Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 |
---|---|---|---|---|---|
Spatial configuration | 50.7 | 41.5 | 53.5 | 43.4 | 52.5 |
Tree density | 4.8 | 2.5 | 5.3 | 9.8 | 5.2 |
Fire interval | 13.1 | 10.9 | 13.3 | 11.5 | 16.7 |
Tree distribution | 5.3 | 2.0 | 7.0 | 3.6 | 5.2 |
Shrub density | 4.5 | 5.4 | 2.5 | 8.5 | 9.5 |
Standing dead trees | 3.7 | 5.4 | 2.5 | 6.6 | 7.8 |
Constant | 17.9 | 32.3 | 16.0 | 16.5 | 3.1 |
Attributes and Attribute Levels | Parameter Estimates | Differences Wald Statistic | |||
---|---|---|---|---|---|
Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | ||
Spatial configuration | *** 33.7 | ||||
| *** 0.772 | *** 1.367 | *** 1.073 | *** 1.263 | |
| *** 0.764 | *** 1.236 | *** 0.865 | *** 1.409 | |
| *** −0.945 | *** −1.425 | *** −1.162 | *** −1.322 | |
| *** −1.141 | *** −1.596 | *** −1.302 | *** −1.534 | |
| 0.250 | ** 0.269 | 0.136 | 0.229 | |
| (*) 0.299 | 0.149 | ** 0.391 | −0.045 | |
Tree density | 10.1 | ||||
| −0.069 | −0.056 | * −0.239 | −0.179 | |
| 0.030 | 0.066 | ** 0.299 | 0.054 | |
| −0.009 | (*) −0.151 | 0.003 | 0.113 | |
| 0.048 | (*) 0.141 | −0.063 | 0.013 | |
Tree distribution | 4.4 | ||||
| −0.001 | * 0.164 | 0.080 | 0.151 | |
| −0.039 | ** −0.221 | −0.119 | −0.138 | |
| 0.040 | 0.057 | 0.038 | −0.013 | |
Fire interval | 4.1 | ||||
| * −0.266 | *** −0.404 | ** −0.283 | *** −0.462 | |
| 0.030 | 0.073 | −0.066 | −0.011 | |
| (*) 0.235 | *** 0.331 | *** 0.348 | *** 0.473 | |
Shrub density | 12.1 | ||||
| −0.000 | −0.030 | ** −0.254 | * −0.312 | |
| 0.151 | 0.060 | 0.084 | 0.144 | |
| −0.098 | 0.048 | −0.041 | −0.054 | |
| −0.054 | −0.078 | * 0.211 | (*) 0.222 | |
Standing dead trees | 7.8 | ||||
| 0.176 | −0.014 | * 0.229 | 0.051 | |
| −0.031 | −0.055 | −0.087 | −0.173 | |
| −0.075 | 0.084 | −0.008 | * 0.264 | |
| −0.070 | −0.015 | −0.134 | −0.142 | |
Constant | *** −1.490 | *** −0.888 | *** −0.900 | * −0.174 | *** 160.6 |
Pseudo-R2(0)/R2: 0.32/0.18 | 0.45/0.10 | 0.36/0.23 | 0.32/0.17 | 0.26/0.24 |
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Arnberger, A.; Gobster, P.H.; Schneider, I.E.; Floress, K.M.; Haines, A.L.; Eder, R. Landowner Acceptability of Silvicultural Treatments to Restore an Open Forest Landscape. Forests 2022, 13, 770. https://doi.org/10.3390/f13050770
Arnberger A, Gobster PH, Schneider IE, Floress KM, Haines AL, Eder R. Landowner Acceptability of Silvicultural Treatments to Restore an Open Forest Landscape. Forests. 2022; 13(5):770. https://doi.org/10.3390/f13050770
Chicago/Turabian StyleArnberger, Arne, Paul H. Gobster, Ingrid E. Schneider, Kristin M. Floress, Anna L. Haines, and Renate Eder. 2022. "Landowner Acceptability of Silvicultural Treatments to Restore an Open Forest Landscape" Forests 13, no. 5: 770. https://doi.org/10.3390/f13050770
APA StyleArnberger, A., Gobster, P. H., Schneider, I. E., Floress, K. M., Haines, A. L., & Eder, R. (2022). Landowner Acceptability of Silvicultural Treatments to Restore an Open Forest Landscape. Forests, 13(5), 770. https://doi.org/10.3390/f13050770