Decision analysis rooted in Indigenous and Western scientific knowledge identifies cost-effective strategies for managing hyperabundant deer to restore keystone places
Data files
Nov 19, 2025 version files 190.34 KB
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Consequences.csv
18.62 KB
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Costing.xlsx
47.26 KB
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DeerPopulationModel.xlsx
27.12 KB
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ExpertElicitation_BenefitsFeasibilities.xlsx
62.70 KB
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README.md
15.66 KB
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Tradeoffs.csv
18.98 KB
Abstract
The hyperabundance of herbivores—a result of altered human relationality with the land and the extirpation of predators—is leading to large-scale degradation of keystone ecosystems across the globe. Designing and implementing socially acceptable and cost-effective strategies that meaningfully reduce herbivore populations while allowing for the recovery of ecological function and cultural relationality is an inherently complex issue. As a result, decision paralysis is common, leading to delayed or avoided action and continued ecosystem loss and degradation. Using a structured decision-making process that incorporated expert elicitation, population modeling, and cost-effectiveness analyses while honoring multiple knowledge systems, we identified five discrete and four portfolio strategies for managing hyperabundant black-tailed deer (Odocoileus hemionus columbianus) in the Southern Gulf Islands of British Columbia, Canada, with consideration to benefit, feasibility, and cost objectives. Hunting led by local Indigenous Nations was ranked the most cost-effective strategy when benefits were considered in terms of the well-being of peoples and place holistically, and accounted for both Indigenous and Western science worldviews. When only Western perspectives were included, increased licensed hunting by local communities and hiring professional deer reduction specialists were ranked the most cost-effective. However, while increased licensed hunting had a >50% likelihood of project uptake and success (i.e., feasibility), the strategy had <50% likelihood of achieving any benefit objective. In comparison, Indigenous-led hunting, professional deer reduction specialists, and all portfolio strategies had >50% likelihood of meeting at least one benefit objective, although only Indigenous-led hunting also had >50% likelihood of achieving feasibility objectives. We provide a roadmap for decision-makers across the globe to robustly and transparently assess the problem of herbivore hyperabundance and inform solutions within their context. Within the Salish Sea, our work highlights the need to support hunting, and in particular, Indigenous-led hunting, as cost-effective strategies to promote revitalization of wellbeing of peoples and place.
Dataset DOI: 10.5061/dryad.b8gtht7rc
Description of the data and file structure
Our methodology combined structured decision-making, expert elicitation, population modeling, and cost-effectiveness approaches to identify effective herbivore management strategies that are rooted in place-based context and that honor multiple knowledge systems. Data was derived from a combination of expert elicited and modeled values for the benefits, feasibilities, and costs of strategies. Files are available for developed data on consequence and tradeoff values, as well as the benefit, feasibility, and cost data underlying consequences. Supplementary materials are also available describing the values, justification, and sources behind the deer population model and the strategy costing variables.
File: ExpertElicitation_BenefitsFeasibilities.xlsx
Description: Data from structured expert elicitation of benefits and feasibilities, as part of the Consequences section of structured decision making. The two sheets provide the elicitation values from Indigenous and Western experts respectively, as each group of experts had tailored elicitation approaches. All units of elicited estimates are 0 to 100% likelihood of the strategy meeting the objective for the island scope.
Indigenous Experts
- Expert: anonymous expert name
- Objective: objective being elicited
- Strategy: strategy being elicited
- Scope: large- or small-island scope
- bestguess: best-guess average elicited estimate
- upper_stand80: upper confidence intervals from the group’s standard error, standardized to 80% confidence interval
- lower_stand80: lower confidence intervals from the group’s standard error, standardized to 80% confidence interval
Western Experts
- Expert: anonymous expert name
- Objective: objective being elicited
- Strategy: strategy being elicited
- Scope: large- or small-island scope
- bestguess: best-guess average elicited estimate
- confidence: expert confidence in their lower and upper estimates
- lower: lower elicited estimate
- upper: upper elicited estimate
- lower_stand80: lower elicited estimate standardized to 80% confidence interval
- upper_stand80: upper elicited estimate standardized to 80% confidence interval
File: DeerPopulationModel.xlsx
Description: Spreadsheet detailing the variables and justifications underlying the deer population model. First sheet is a README that outlines the purpose of each subsequent sheet. The second sheet—'Deer Density’—outlines the deer density assumptions by island and across island scopes. The following sheets outline the variables for plants, competition, deer, cougars, or humans. Citations supporting values listed in ‘Sources’ columns, with references at the end of this document (p. comm. P. Arcese & T. Martin) (Arcese et al., 2014; Beckwith, 2004; Endara and Coley, 2011; Gillingham, 2008; Gillingham et al., 1997; Gladders, 2003; Gonzales, 2008; Hahn, 2001; Hanley and McKendrick, 1985; Hatter, 1988; Hatter and Janz, 1994; KNOPFF et al., 2010; McNay and Voller, 1995; Ministry of Environment, 1996; Mowat, 2023; Murphy, 1998; Parker et al., 1999; Ruth and Murphy, 2009; Shackelford et al., 2019; Sharpe, 1999; Waller, 2008; Wielgus et al., 2013).
Deer Density
By Island:
- Island: island name(s)
- Scope: large- or small-island scope
- Area_km2: area of island (kilometers squared)
- Deerkm2_Estimate: best-guess average number of deer per kilometer squared for each island
- Deerkm2_Low: lower-guess average number of deer per kilometer squared for each island
- Deerkm2_High: upper-guess average number of deer per kilometer squared for each island
Summarized Large & Small Islands:
- Scope: large- or small-island scope
- Islands: number of islands in scope group
- Area: total area per scope group (kilometers squared)
- Deer_BestEstimate: total best-guess estimate of number of deer per scope
- Deer_LowerEstimate: lower estimate of number of deer per scope
- Deer_UpperEstimate: upper estimate of number of deer per scope
Plants
- Scope: large- or small-island scope
- Palatability Class: deer palatability class groups
- Variable: model variable
- Estimate: best-guess estimate of model variable
- Low: lower estimate of model variable
- High: upper estimate of model variable
- Source: references behind values
- Justification: evidence and arguments behind values
Competition
- Competition Species: palatability class of first species
- Competition Effect: palatability class of second species
- Estimate: impact of first species on second species, best-guess estimate
- Low: impact of first species on second species, lower estimate
- High: impact of first species on second species, upper estimate
- Source: references behind values
- Justification: evidence and arguments behind values
Deer
- Deer Variables: abbreviated name of model variable
- Full name: full name of model variable
- Estimate: best-guess estimate of model variable
- Low: lower estimate of model variable
- High: upper estimate of model variable
- Source: references behind values
- Justification: evidence and arguments behind values
Cougars
- Cougar Variables: abbreviated name of model variable
- Estimate: best-guess estimate of model variable
- Low: lower estimate of model variable
- High: upper estimate of model variable
- Source: references behind values
- Justification: evidence and arguments behind values
Humans
- Human Variables: abbreviated name of model variable
- Estimate: best-guess estimate of model variable
- Low: lower estimate of model variable
- High: upper estimate of model variable
- Source: references behind values
- Justification: evidence and arguments behind values
File: Costing.xlsx
Description: Spreadsheet detailing the items underlying each of the strategies. First sheet is a README that outlines the purpose of each subsequent sheet. Following sheets outline the overarching actions of each strategy ('Strategies'), the annual costs per item of each discrete strategy computed by the deer population model, the action items of each of the discrete strategies ('Strategy "X"'), the portfolio combinations of discrete strategies ('Portfolio'), and the list of enabling actions behind each strategy ('Enabling Actions'). Costs per unit are not shared as they were determined from confidential interviews with managers and experts, whom are recognized in the manuscript and supplementary materials.
Strategies
- Strategies: numbered strategy name
- Name: textual strategy name
- Goal: the goal of each discrete strategy
- List of Actions: the list of action components behind each discrete strategy
- Description: general description of each strategy action item
- Abbreviation: abbreviated form of each action item, used as action abbreviation in subsequent sheets
Costing
- Strategy: strategy number
- Item: abbreviated name of the budget item
- Units: metric unit of the budget item
- Budget: whether item part of the reduced cost analysis (yes or no)
- Year 1 to Year 10: columns provide the total cost ($CAD) per year per item of each strategy
Strategy 1-5/Enabling Actions
- Action Abbreviation: strategy action type per item
- Item Abbreviation: item name (abbreviated form)
- Item Description: description of item
- Units: metric unit of item
- Notes: additional details behind the item
- Budget: whether item is included in reduced budget version (yes or no), with those marked as “no” highlighted in pink to visualize items removed from strategy under the budgeted version
Portfolio
- Strategy: numbered name of portfolio strategy
- Name: long-form name of portfolio strategy including discrete strategy composition
- Description: discrete strategies composing portfolio strategy
- Percent Strategy "X" Budget: the proportion of the discrete strategy costs used for costing the portfolio strategy
- Rationale Strategy "X": the justification behind the proportion of each strategy used
File: Consequences.csv
Description: Data from the Consequences section of structured decision making, providing benefit, feasibility, and cost values developed from previous steps in the analysis.
Consequences
- Strategy: strategy number
- Scope: large-or small-island scope
- Estimate: bestguess, lower, or upper sensitivity values
- Maximize wellbeing: 0-100% likelihood of strategy meeting objective
- Maximize ecosystem function: 0-100% likelihood of strategy meeting objective
- Maximize project success:0-100% likelihood of strategy meeting objective
- Maximize project uptake:0-100% likelihood of strategy meeting objective
- Minimize deer density:0-100% likelihood of strategy meeting objective
- InterestRate: various discount rates (0, 0.04, 0.07)
- BudgetCosts: net present value ($CAD) for reduced budget costs
- TotalCosts: net present value ($CAD) for total costs
File: Tradeoffs.csv
Description: Data from the cost-effectiveness (CE) analysis of the Trade-offs section of structured decision making, developed from previous steps in the analysis.
Tradeoffs
- strategy: strategy number per alternative
- scope: large- or small-island scope
- estimate: best guess, upper, or lower estimate value
- interest_rate: various discount rates (0, 0.04, 0.07)
- MaxEcoFunction_TotalCost: CE value for the maximize ecosystem function objective using total costs
- MinDeerDensity_TotalCost: CE value for the reduce deer density objective using total costs
- MaxWellbeingBenefit_TotalCost: CE value for the maximize wellbeing objective using total costs
- MaxWellbeingBenefit_TotalCost_NoFeas: CE value for the maximize wellbeing objective using total costs and no feasibility values
- MaxEcoFunction_ReducedCost: CE value for the maximize ecosystem function objective using reduced costs
- MinDeerDensity_ReducedCost: CE value for the reduce deer density objective using reduced costs
- MaxWellbeingBenefit_ReducedCost: CE value for the maximize wellbeing objective using reduced costs
- MaxWellbeingBenefit_ReducedCost_NoFeas: CE value for the maximize wellbeing objective using reduced costs and no feasibility values
References
Arcese, P., Schuster, R., Campbell, L., Barber, A., Martin, T.G., 2014. Deer density and plant palatability predict shrub cover, richness, diversity and aboriginal food value in a North American archipelago. Divers. Distrib. 20, 1368–1378. https://doi.org/10.1111/ddi.12241
Beckwith, B.R., 2004. The queen root of this clime: ethnoecological investigations of blue camas (Camassia leichtlinii (Baker) Wats., C. quamash (Pursh) Greene; Liliaceae) and its landscapes on southern Vancouver Island, British Columbia.
Endara, M., Coley, P.D., 2011. The resource availability hypothesis revisited: a meta‐analysis. Funct. Ecol. 25, 389–398. https://doi.org/10.1111/j.1365-2435.2010.01803.x
Gillingham, M.P., 2008. Ecology of black-tailed deer in north coastal environments. Presented at the Lessons from the Islands: Proceedings from the Research Group on Introduced Species 2002 Conference, Queen Charlotte City, British Columbia. Canadian Wildlife Service, Environment Canada, Ottawa, Canada, pp. 39–47.
Gillingham, M.P., Parker, K.L., Hanley, T.A., 1997. Forage intake by black-tailed deer in a natural environment: bout dynamics. Can. J. Zool. 75, 1118–1128.
Gladders, A.D., 2003. Predation behaviour of Vancouver Island cougar (Puma concolor vancouverensis) and its relation to micro-and macroscale habitat.
Gonzales, E.K., 2008. The effects of herbivory, competition, and disturbance on island meadows (PhD Thesis). University of British Columbia.
Hahn, A.M., 2001. Social and spatial organization of Vancouver Island cougar (Puma concolor vancouverensis, Nelson and Goldman, 1943). University of British Columbia. https://doi.org/10.14288/1.0090208
Hanley, T.A., McKendrick, J.D., 1985. Potential nutritional limitations for black-tailed deer in a spruce-hemlock forest, southeastern Alaska. J. Wildl. Manag. 103–114.
Hatter, I., 1988. Effects of wolf predation on recruitment of black-tailed deer on northeastern Vancouver Island. Wildlife Branch, Ministry of Environment.
Hatter, I.W., Janz, D.W., 1994. Apparent demographic changes in black-tailed deer associated with wolf control on northern Vancouver Island. Can. J. Zool. 72, 878–884. https://doi.org/10.1139/z94-119
KNOPFF, K.H., KNOPFF, A.A., KORTELLO, A., BOYCE, M.S., 2010. Cougar Kill Rate and Prey Composition in a Multiprey System. J. Wildl. Manag. 74, 1435–1447.
McNay, R.S., Voller, J.M., 1995. Mortality causes and survival estimates for adult female Columbian black-tailed deer. J. Wildl. Manag. 138–146.
Ministry of Environment, 1996. Safety Guide to Cougars [WWW Document]. URL http://wwwt.env.gov.bc.ca/wld/documents/cougsf.htm (accessed 1.29.24).
Mowat, G., 2023. A review of cougar biology and management in British Columbia, Technical report. Province of British Columbia, Victoria, BC.
Murphy, K.M., 1998. The ecology of the cougar (Puma concolor) in the northern Yellowstone ecosystem: interactions with prey, bears, and humans. University of Idaho.
Parker, K.L., Gillingham, M.P., Hanley, T.A., Robbins, C.T., 1999. Energy and protein balance of free-ranging black-tailed deer in a natural forest environment. Wildl. Monogr. 3–48.
Ruth, T.K., Murphy, K., 2009. Cougar-prey relationships. Cougar Ecol. Conserv. Univ Chic. Press Chic. 138–155.
Shackelford, N., Murray, S., Bennett, J., Lilley, P., Starzomski, B., Standish, R., 2019. Ten years of pulling: Ecosystem recovery after long-term weed management in Garry oak savanna. Conserv. Sci. Pract. 1. https://doi.org/10.1111/csp2.92
Sharpe, S., 1999. Management of deer on the Queen Charlotte Islands: biology of the species. Presented at the Proceedings of the Cedar Symposium: Growing Western Redcedar and Yellow-Cypress on the Queen Charlotte Islands/Haida Gwaii. Edited by GG Wiggins. BC Ministry of Forests/Canada–British Columbia South Moresby Forest Replacement Account, Victoria, BC, Citeseer, pp. 118–124.
Waller, D.M., 2008. White-tailed deer impacts in North America and the challenge of managing a hyperabundant herbivore. Presented at the Proceedings from the research Group on Introduced Species 2002 Symposium, Queen Charlotte City, Queen Charlotte Islands, British Columbia, Canada. Canadian Wildlife Service, Environment Canada, Ottawa, Ontario, Canada, pp. 135–147.
Wielgus, R.B., Morrison, D.E., Cooley, H.S., Maletzke, B., 2013. Effects of male trophy hunting on female carnivore population growth and persistence. Biol. Conserv. 167, 69–75. https://doi.org/10.1016/j.biocon.2013.07.008
Code & Software
All data files can be viewed in microsoft excel spreadsheets, or any application able to view .xlsx or .csv files.
Access Information
Other publicly accessible locations of the data:
- No other publicly accessible locations
Data was derived from the following sources:
- Expert elicitation
- Regional deer population modeling literature
- Regional costing literature and interviews
