Conservation prioritization can resolve the flagship species conundrum

The paper addresses whether requiring the presence of a flagship species in place-based conservation prioritization impedes the ability to meet biodiversity objectives at a global scale. Traditional flagship campaigns focus on a few charismatic species to raise funds, but critics argue this can misallocate resources and poorly represent broader biodiversity. Prior studies evaluating flagships as surrogates suggested that selecting places solely by charismatic species presence inadequately represents biodiversity. The authors reframe the problem: can we systematically prioritize places important for biodiversity while ensuring each selected place contains at least one flagship, thereby aligning fundraising potential with conservation outcomes? They motivate the need for clearly defined, quantifiable objectives in conservation planning to transparently evaluate trade-offs when adding constraints like flagships and place attributes (ecoregional uniqueness, protection status, human impact).

The study situates itself within multiple strands of literature: (1) flagship species in conservation marketing, including expansions beyond purely charismatic megafauna to species chosen for a wider range of appeal attributes; (2) critiques of single-species surrogacy (flagship/umbrella/keystone) and evidence that charismatic species presence does not reliably capture broader biodiversity; (3) global place-based prioritization frameworks, including centers of endemism, biodiversity hotspots, Global 200 ecoregions, ecosystem services, and wilderness; (4) decision-theoretic guidance emphasizing objective-driven planning, representation, and complementarity. The authors build on these by integrating fundraising potential (via presence of candidate flagships) into a formal prioritization that maximizes representation of non-flagship “background” species, thus addressing surrogacy concerns while leveraging marketing advantages of flagships.

Study design: The terrestrial realm was divided into a global equal-area grid of 100 km × 100 km planning units (places), initially within WWF Global 200 terrestrial and freshwater ecoregions. Each place was assigned to the dominant ecoregion present. Additional attributes were attached per place: proportion covered by IUCN Protected Areas (WDPA; excluding Proposed, including Not Reported) and mean Human Footprint Index.

Candidate flagship species: The team compiled 534 plausibly charismatic species across mammals, birds, and reptiles. Mammals included existing conservation flagships (N=80) and “Cinderella” species (N=183) with flagship-like traits (large size, forward-facing eyes) from Smith et al. Reptiles and birds were selected using online popularity (Wikipedia page views), taking the top 100 reptiles (from Roll et al.) and top 500 birds (Mittermeier et al., unpublished; IOC World Bird List v7.1 mapping). Species were retained only if distribution maps were available from IUCN (mammals, reptiles) and BirdLife/Handbook of the Birds of the World (birds). All candidates were then classified by IUCN Red List status; a threatened subset (Near Threatened or higher) comprised 338 species.

Background species: Background biodiversity to be represented included 19,616 species across freshwater crustaceans, carnivorous insects, and amphibians (plus non-flagship mammals, birds, reptiles where applicable as stated), with distributions from IUCN. For all taxa, range polygons marked as native or reintroduced, and presence as extant, possibly extant, or possibly extinct, were used. Presence–absence matrices for candidates and background species were constructed by intersecting species ranges with planning units. No minimum area threshold within a cell was imposed due to coarse resolution.

Place-based constraints and thresholds:

• Ecoregional uniqueness: planning units restricted to Global 200 ecoregions and assigned uniquely.
• Protected Areas (PAs): cells retained if PA coverage between ≥10% and ≤90%, reflecting feasibility (scenario variants also assessed without this criterion).
• Human Footprint: cells retained if mean Human Footprint <4, representing landscapes not human-dominated.

Scenarios: Eight integrated global planning scenarios combined species- and place-based constraints:

• a) G200 ecoregions; all candidate flagships (534); 10,200 places.
• b) G200; threatened flagships (IUCN NT+; 338); 10,200 places.
• c) G200 + PAs; all flagships (494); 3,097 places.
• d) G200 + PAs; threatened flagships (295); 3,097 places.
• e) G200 + Human Footprint; all flagships (447); 3,961 places.
• f) G200 + Human Footprint; threatened flagships (247); 3,961 places.
• g) G200 + PAs + Human Footprint; all flagships (402); 1,068 places.
• h) G200 + PAs + Human Footprint; threatened flagships (207); 1,068 places.

Prioritization approaches:

• Integrated approach (primary): Select places to maximize representation (number) of background species subject to the constraint that every selected place contains at least one candidate flagship species. The approach respects representation and complementarity principles.
• Place-only approach (benchmark): Select places to maximize background species representation without any flagship constraints.
• Random (null) approach: Randomly select the same number of places as in the integrated solution (100 iterations per scenario) without ecoregional representation constraints, to estimate baseline performance.

Evaluation metrics: For each scenario, the number of background species captured by the integrated solution was compared to that of the place-only solution for the same number of places, reporting efficiency retained (%). Additional evaluation considered realized efficiency for the top ten places (those contributing most to the objective). Random approach performance was summarized as mean efficiency retained relative to the place-only solution.

Implementation: Spatial processing used PostGIS 2.3 and ArcGIS v10.3. Prioritization and analyses were implemented in R (R Core Team), with customized source code (authors A. L. M. Chauvenet and J. McGowan). Randomizations were repeated 100 times per scenario. Data sources: IUCN Red List species ranges; BirdLife/HBW for birds; WDPA for protected areas; Global 200 ecoregions (Data Basin); Human Footprint (NASA SEDAC).

• Across all eight scenarios, the integrated flagship-constrained prioritization retained 79–89% of the background species that the unconstrained place-only approach could represent, for the same number of places.
• Considering only the ten most beneficial places per scenario, realized efficiencies improved to 87–97% of the place-only benchmark.
• Random (null) selections retained on average 39–55% of background species relative to place-only, and were consistently outperformed by the integrated approach.
• In the most efficient scenario (h: G200 + PAs + Human Footprint; threatened flagships), the integrated solution selected 47 places and captured 6,849 background species versus 7,702 in the place-only solution (efficiency retained 89%). The place-only solution, unconstrained by flagships, identified 287 places in total for full coverage.
• Scenario h’s 47 places collectively contained 176 candidate flagship species (111 mammals, 53 birds, 12 reptiles). Individual places contained between 1 and 20 flagships; the Naga-Manupuri-Chin hills moist forests (India, Bangladesh, Myanmar) had the most (20).
• Example: The Hengduan Shan Conifer Forests place (China) includes iconic flagships such as Giant Panda (Ailuropoda melanoleuca), Takin (Budorcas taxicolor), Golden snub-nosed monkey (Rhinopithecus roxellana), Snow Leopard (Panthera uncia), and Chinese softshell turtle (Pelodiscus sinensis), illustrating multiple viable flagship options in a single high-priority place.
• Summary of Table 1 efficiencies: a) 82% (top-10: 87%); b) 79% (90%); c) 84% (92%); d) 82% (92%); e) 85% (89%); f) 89% (96%); g) 87% (93%); h) 89% (97%).

Requiring each prioritized place to include at least one flagship species does not substantially compromise the ability to meet a biodiversity representation objective. By integrating flagships into an objective-driven prioritization, organizations can leverage the fundraising and outreach benefits of flagships while efficiently targeting places that conserve a large number of non-flagship (background) species. This approach differs from evaluating flagships as biodiversity surrogates; rather than assuming co-occurrence of other taxa with a given flagship, it uses flagships as marketing anchors while optimizing place selection for biodiversity outcomes. Consequently, funds raised using flagship-focused campaigns can transparently support broader conservation needs within priority places, including taxa and habitats (e.g., freshwater systems) not represented by the flagship itself. The framework is flexible and can be adapted to alternative objectives (e.g., minimizing extinction risk, maximizing ecosystem services) and additional spatial constraints (e.g., wilderness, climate refugia, KBAs/AZEs). Multiple flagships per place provide options to align with donor preferences, local contexts, and feasible actions. The results underscore the importance of clear objectives and structured trade-off assessment in reconciling fundraising strategies with conservation efficiency at global scales.

The study demonstrates that integrating fundraising considerations via flagship species into systematic, objective-based conservation prioritization can retain 79–89% (up to 97% for top places) of biodiversity representation compared to approaches that ignore fundraising potential. Hence, carefully selected flagships need not conflict with cost-effective, place-based conservation and can help direct resources to high-impact locations. The proposed framework offers a transparent, adaptable mechanism for NGOs and private ventures to align marketing, donor engagement, and conservation outcomes. Future work should: (i) incorporate alternative objectives (e.g., extinction risk reduction, ecosystem services), costs, and feasibility to refine priorities; (ii) integrate additional spatial datasets (e.g., KBAs, AZEs, climate refugia, wilderness); (iii) downscale to finer resolutions with local species and threat data; and (iv) evaluate temporal dynamics (changing human footprint, protection trajectories) to inform timing and sequencing of actions.

• Spatial resolution: Species ranges and planning units (100 km × 100 km) are coarse, leading to potential errors of omission/commission. The authors note range maps are suitable for global prioritization but should be supplemented with local data for finer-scale decisions.
• Threshold choices: PA coverage bounds (≥10% and ≤90%) and Human Footprint threshold (<4) were chosen for perceived feasibility and landscape condition; these are somewhat arbitrary and may influence which places qualify in scenarios.
• Assumed flagship equivalence: All candidate flagships were assumed to have equal capacity to function as marketing flagships given sufficient effort, which may not hold universally across audiences and contexts.
• Not prescriptive: The study does not advocate specific species or places for action; results demonstrate a method rather than a finalized global priority set.
• Null model simplification: Random selections did not include ecoregional representation constraints, serving as a coarse baseline rather than a sophisticated alternative prioritization.
• Data availability and taxonomic scope: Background species sets were limited to taxa with available global range maps (e.g., freshwater crustaceans, carnivorous insects, amphibians), potentially omitting poorly mapped groups.