The influence of wildfire risk reduction programs and practices on recreation visitation
Eric M. White A * , Samantha G. Winder B and Spencer A. Wood BA
B
Abstract
The increasing extent and severity of uncharacteristic wildfire has prompted numerous policies and programs promoting landscape-scale fuels reduction.
We used novel data sources to measure how recreation was influenced by fuels reduction efforts under the US Forest Service Collaborative Forest Landscape Restoration (CFLR) Program.
We used posts to four social media platforms to estimate the number of social media user-days within CFLR landscapes and asked: (1) did visitation within CFLR Program landscapes between 2012 and 2020 change in a manner consistent with the pattern on nearby lands, and (2) was there a relationship between the magnitudes of specific fuel treatment activities within CFLR landscapes and visitation to that landscape?
In aggregate, visitation to the CFLR landscapes changed at a rate mirroring the trend observed elsewhere. Within CFLR landscapes, pre-commercial thinning and pruning had slight positive influences on visitation whereas prescribed burning and managed wildfire had slight negative influences.
Fuel treatments can have a modest influence on visitation, but we didnot find any wholesale changes in visitation within CFLR landscapes.
Social media and other novel data sources offer an opportunity to fill in gaps in empirical data on recreation to better understand social-ecological system linkages.
Keywords: Collaborative Forest Landscape Restoration Program, digital mobility data, ecosystem services, fuels reduction, recreation user-days, recreation visitation, risk reduction program, social media data, volunteered geographic information.
References
Borrie WT, McCool SF, Whitmore JG (2006) Wildland fire effects on visits and visitors to the Bob Marshall Wilderness Complex. International Journal of Wilderness 12(1), 32-38.
| Google Scholar |
Brown RNK, Rosenberger RS, Kline JD, Hall TE, Neeham MD (2008) Visitor preferences for managing wilderness recreation after wildfire. Journal of Forestry 106(1), 9-16.
| Crossref | Google Scholar |
Chen W, Flatnes JE, Miteva DA, Klaiber HA (2022) The impact of deforestation on nature-based recreation: evidence from citizen science data in Mexico. Land Economics 98(1), 22-40.
| Crossref | Google Scholar |
Ciesielski M, Stereńczak K (2021) Using Flickr data and selected environmental characteristics to analyze the temporal and spatial distribution of activities in forest areas. Forest Policy and Economics 129, 102509.
| Crossref | Google Scholar |
Di Minin E, Tenkanen H, Toivonen T (2015) Prospects and challenges for social media data in conservation science. Frontiers in Environmental Science 3, 63.
| Crossref | Google Scholar |
Echeverri A, Smith JR, MacArthur-Waltz D, Lauck KS, Anderson CB, Monge Vargas R, Alvarado Quesada I, Wood SA, Chaplin-Kramer R, Daily G (2022) Biodiversity and infrastructure interact to drive tourism to and within Costa Rica. Proceedings of the National Academy of Sciences 119(11), e2107662119.
| Crossref | Google Scholar |
English DBK, White EM, Zarnoch SJ, Bowker JM, Winter SM (2020) A review of the Forest Service’s National Visitor Use Monitoring Program. Agricultural and Resource Economics Review 49(1), 64-90.
| Google Scholar |
Evans SG, Holland TG, Long JW, Maxwell C, Scheller RM, Patrick E, Potts MD (2022) Modeling the risk reduction benefit of forest management using a case study in the Lake Tahoe Basin. Ecology and Society 27(2), 18.
| Crossref | Google Scholar |
Fisher DM, Wood SA, White EM, Blahna DJ, Lange S, Weinberg A, Tomco M, Lia E (2018) Recreational use in dispersed public lands measured using social media data and onsite counts. Journal of Environmental Management 222, 465-474.
| Crossref | Google Scholar | PubMed |
Gunderson VS, Frivold LH (2008) Public preferences for forest structures: a review of quantitative surveys from Finland, Norway and Sweden. Urban Forestry & Urban Greening 7, 241-258.
| Crossref | Google Scholar |
Hausmann A, Toivonen T, Slotow R, Tenkanen H, Moilanen A, Heikinheimo V, Minin E (2018) Social media data can be used to understand tourists’ preferences for nature-based experiences in protected areas. Conservation Letters 11(1), e12343.
| Crossref | Google Scholar |
Hessburg PF, Prichard SJ, Hagmann RK, Povak NA, Lake FK (2021) Wildfire and climate change adaptation of western North American forests: a case for intentional management. Ecological Applications 31(8), 54-71.
| Crossref | Google Scholar |
Hesseln H, Loomis JB, González-Cabán A, Alexander S (2003) Wildfire effects on hiking and biking demand in New Mexico: a travel cost study. Journal of Environmental Management 69, 359-368.
| Crossref | Google Scholar | PubMed |
Hunter ME, Iniguez JM, Lentile LB (2011) Short- and long-term effects on fuel, forest structure, and wildfire potential from prescribed fire and resource benefit fire in southwestern forests, USA. Fire Ecology 7(3), 108-121.
| Crossref | Google Scholar |
Johnston J, Olszewski JH, Miller BA, Schmidt MR, Vernon MJ, Ellsworth LM (2021) Mechanical thinning without prescribed fire moderates wildfire behavior in eastern Oregon, USA, ponderosa pine forests. Forest Ecology and Management 501, 119674.
| Crossref | Google Scholar |
Kearney AR, Bradley GA (2011) The effect of viewer attributes and preference for forest scenes: contributions of attitude, knowledge, demographic factors, and stakeholder group membership. Environment and Behavior 43(2), 147-181.
| Crossref | Google Scholar |
Keeler BL, Wood SA, Polasky S, Kling C, Filstrup CT, Downing JA (2015) Recreational demand for clean water: evidence from geotagged photographs by visitors to lakes. Frontiers in Ecology and the Environment 13(2), 76-81.
| Crossref | Google Scholar |
Kooistra C, Sinkular E, Schultz C (2022) Characterizing the context and demand for the US Forest Service’s Collaborative Forest Landscape Restoration Program in 2020. Journal of Forestry 120, 64-85.
| Crossref | Google Scholar |
Leggett CG (2017) Sampling strategies for on-site recreation counts. Journal of Survey Statistics and Methodology 5(3), 326-349.
| Crossref | Google Scholar |
Levin N, Lechner AM, Brown G (2017) An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. Applied Geography 79, 115-126.
| Crossref | Google Scholar |
Loomis J, Gonzalaez-Caban A, Englin J (2001) Testing for differential effects of forest fires on hiking and mountain biking demand and benefits. Journal of Agricultural and Resource Economics 26(2), 508-522.
| Google Scholar |
Lorber C, Dittrich R, Jones S, Junge A (2021) Is hiking worth it? A contingent valuation case study of Multnomah Falls, Oregon. Forest Policy and Economics 128, 102471.
| Crossref | Google Scholar |
R Core Team (2023) ‘R: A language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna, Austria) Available at https://www.R-project.org/ [verified 17 February 2024]
Ribe RG (2006) Perceptions of forestry alternatives in the US Pacific Northwest: information effects and acceptability distribution analysis. Journal of Environmental Psychology 26, 100-115.
| Crossref | Google Scholar |
Ribe RG (2009) In-stand scenic beauty of variable retention harvests and mature forests in the U.S. Pacific Northwest: the effects of basal area, density, retention pattern and down wood. Journal of Environmental Management 91, 245-260.
| Crossref | Google Scholar | PubMed |
Ryan RL, Haman E (2009) Wildland–urban interface communities’ response to post-fire salvage logging. Western Journal of Applied Forestry 24(1), 36-41.
| Crossref | Google Scholar |
Schultz CA, Jedd T, Beam RD (2012) The Collaborative Forest Landscape Restoration Program: a history and overview of the first projects. Journal of Forestry 110(7), 381-391.
| Crossref | Google Scholar |
Sessions C, Wood SA, Rabotyagov S, Fisher DM (2016) Measuring recreational visitation at U.S. National Parks with crowd-sourced photographs. Journal of Environmental Management 183(3)), 703-711.
| Crossref | Google Scholar | PubMed |
Silvennoinen H, Pukkala T, Tahvanainen L (2002) Effect of cutting on the scenic beauty of a tree stand. Scandinavian Journal of Forest Research 17(3), 263-273.
| Crossref | Google Scholar |
Sinclair M, Mayer M, Woltering M, Ghermandi A (2020) Using social media to estimate visitor provenance and patterns of recreation in Germany’s national parks. Journal of Environmental Management 263, 110418.
| Crossref | Google Scholar | PubMed |
Starbuck CM, Berrens RP, McKee M (2006) Simulating changes in forest recreation demand and associated economic impacts due to fire and fuels management activities. Forest Policy and Economics 8, 52-66.
| Crossref | Google Scholar |
Sullivan BL, Wood CL, Iliff MJ, Bonney RE, Fink D, Kelling S (2009) eBird: a citizen-based bird observation network in the biological sciences. Biological Conservation 142(10), 2282-2292.
| Crossref | Google Scholar |
Tanner S, Lupi F, Garnache C (2022) Estimating visitor preferences for recreation sites in wildfire prone areas. International Journal of Wildland Fire 31(9), 871-885.
| Crossref | Google Scholar |
Tenkanen H, Di Minin E, Heikinheimo V, Hausmann A, Herbst M, Kajala L, Toivonen T (2017) Instagram, Flickr, or Twitter: assessing the usability of social media data for visitor monitoring in protected areas. Scientific Reports 7(1), 17615.
| Crossref | Google Scholar | PubMed |
Tyrväinen L, Silvennoinen H, Hallikainen V (2017) Effect of the season and forest management on the visual quality of the nature-based tourism environment: a case from Finnish Lapland. Scandinavian Journal of Forest Research 32(4), 349-359.
| Crossref | Google Scholar |
USDA Forest Service (2022) Wildfire crisis strategy. Available at https://www.fs.usda.gov/sites/default/files/Confronting-Wildfire-Crisis.pdf [verified 17 February 2024]
USDA Forest Service (2023) US Forest Service National Visitor Use Monitoring survey results, National Summary Report. Data collected FY 2018 through FY 2022. Available at https://www.fs.usda.gov/sites/default/files/2022-National-Visitor-Use-Monitoring-Summary-Report.pdf [verified 17 February 2024]
USDA Forest Service (n.d.) Collaborative Forest Landscape Restoration Program 10-year report to Congress. Available at https://www.fs.usda.gov/restoration/documents/cflrp/REF_Report-CollaborativeForestLandscapeRestoration-508.pdf [verified 17 February 2024]
Warziniack T, Thompson M (2012) Wildfire risk and optimal investments in watershed protection. Western Economics Forum 12(2), 19-28.
| Crossref | Google Scholar |
Watson AE, Cole DN, Turner DL, Reynolds PS (2000) ‘Wilderness recreation use estimation: a handbook of methods and systems.’ General Technical Report RMRS-56. 198 p. (USDA Forest Service, Rocky Mountain Research Station: Ft. Collins, CO) 10.2737/RMRS-GTR-56
White EM, Bergerson TR, Hinman ET (2020) Research note: quick assessment of recreation use and experience in the immediate aftermath of wildfire in a desert river canyon. Journal of Outdoor Recreation and Tourism 29, 100251.
| Crossref | Google Scholar |
White EM, Winder SG, Wood SA (2022) Applying novel visitation models using diverse social media to understand recreation change after wildfire and site closure. Society & Natural Resources 36(1), 58-75.
| Crossref | Google Scholar |
Wilkins EJ, Howe PD, Smith JW (2021) Social media reveal ecoregional variation in how weather influences visitor behavior in U.S. National Park Service units. Scientific Reports 11(1),.
| Crossref | Google Scholar |
Wood SA, Guerry AD, Silver JM, Lacayo M (2013) Using social media to quantify nature-based tourism and recreation. Scientific Reports 3, 2976.
| Crossref | Google Scholar | PubMed |
Wood SA, Winder SG, Lia EH, White EM, Crowley CSL, Milnor AA (2020) Next-generation visitation models using social media to estimate recreation on public lands. Scientific Reports 10(1), 15419.
| Crossref | Google Scholar | PubMed |