Hauling field gear up Gothic Mountain…
Bridges movement ecology, disease epidemiology, and land-use planning by treating the working landscape as the substrate on which prion transmission actually unfolds.
Chronic wasting disease is a fatal prion disease of deer and elk that spreads through both direct animal contact and environmental contamination, with prevalence climbing across much of the Mountain West. In western Colorado, cervid herds move seasonally across a patchwork of public and private lands organized administratively into Game Management Units, but the animals themselves do not respect those lines. Whether disease surveillance and harvest-based management can keep pace with transmission depends on understanding how the real movement network of deer and elk maps onto, or cuts across, the administrative geometry used to manage them.
AI-generated synthesis. An AI-synthesized knowledge-frontier description that clusters gap statements from research neighborhoods and articulates them as a single named frontier — with key questions, concrete actions, and data gaps.
Read it as a synthesized articulation of where the literature points toward a knowledge boundary, not as an authoritative research agenda. The neighborhoods clustered to form it are listed; the synthesis is the model's reading of their gap statements.
The unresolved questions sit at the intersection of movement ecology, disease epidemiology, and land-use planning. Prevalence data are typically aggregated at the management-unit scale, while transmission actually plays out at the scale of individual contacts, shared winter ranges, and corridors that traverse multiple jurisdictions and ownerships. The gap is partly resolution — prevalence and movement are rarely characterized at compatible spatial and temporal grains — and partly integration: linking GPS-derived contact networks to prion exposure risk, and linking both to the parcel-level land-use decisions (subdivision approvals, fencing, conservation easements, trail siting) that reshape connectivity. Advancing the boundary requires moving from unit-level prevalence summaries toward spatially explicit transmission models that treat the landscape as a permeability surface, identify high-risk corridors and bottlenecks, and predict how alternative harvest or habitat interventions would shift trajectories. Whether administrative units are even the right epidemiological denominators is itself an open question.
Key blockers are scale mismatch (prevalence reported by unit, transmission occurring at finer grain), data gaps (sparse GPS coverage relative to herd size, uneven harvest sampling, limited longitudinal prevalence series), jurisdictional fragmentation (state wildlife agencies, BLM, USFS, county planning, and private landowners each control different pieces of the system), and method gaps in coupling movement networks with prion exposure dynamics. Translation gaps also persist between movement-ecology research outputs and the parcel-scale decisions made by county planners and land managers.
A coordinated movement-and-prevalence dataset spanning multiple Game Management Units in the Gunnison Basin and Arkansas Valley would be foundational: paired GPS telemetry on mule deer and elk, harvest-location records with age and sex, and georeferenced prion testing at finer-than-unit resolution. On top of this, a spatially explicit transmission modeling platform could integrate contact-network structure, environmental prion persistence, and landscape permeability derived from land-cover and ownership layers, enabling scenario testing of targeted harvest, fencing, and corridor protection. A framework redefining epidemiological units from movement data — rather than inheriting administrative ones — would let surveillance design follow biology. Complementary efforts could include experimental evaluation of targeted-removal effectiveness at suspected transmission bottlenecks, integration with county-level land-use scenarios to anticipate how subdivision and trail networks alter risk, and a synthesis pulling together prevalence, movement, and harvest data across Colorado's western slope herds into a shared analytical backbone.
Concrete, fundable actions categorized by kind of work and effort tier (near-term = single lab; ambitious = focused multi-year program; major = multi-institutional; consortium = agency-program scale).
Descriptions of needed data (not existing datasets), drawn directly from the atomic statements feeding this frontier.
Colorado Parks and Wildlife sets harvest quotas, surveillance intensity, and targeted-removal policy at the Game Management Unit level; a movement-informed redefinition of epidemiological units would directly inform those decisions. BLM Resource Management Plan revisions and travel-management decisions in the Gunnison Resource Area depend on credible corridor maps that also carry disease-risk implications. County and municipal planners in the Arkansas Valley — including Salida and Poncha Springs — make subdivision and trail-siting choices that alter cervid connectivity, and risk-mapped guidance would let those decisions account for downstream disease consequences. Hunters, outfitters, and landowners benefit from more spatially precise surveillance and clearer expectations about long-term herd trajectories.
Every claim in the synthesis above derives from the source atomic statements below, grouped by their research neighborhood of origin. Click a neighborhood to follow its primer and full citation chain.
Framing notes: Two source statements converge tightly on the same gap, so the frontier is framed narrowly around CWD-connectivity integration rather than broader cervid ecology.