Wildlife crossings are often discussed after a collision, a field observation, or a proposed construction project. North Idaho Wildlife Bottlenecks asks whether public data can be combined earlier to identify places that deserve closer ecological and transportation attention.
A Python and GIS workflow that combines public geography, transportation, habitat, and incident evidence to rank candidate wildlife bottlenecks in North Idaho.
The aim. Help focus local research and mitigation attention without presenting modeled candidates as proven ecological corridors.
01The problem behind the project
Wildlife crossings compete for attention and funding. A transparent screening layer can show where better field data or mitigation analysis may be worth the effort.
The analysis avoids treating one score as a discovered truth. Mortality evidence, road safety, economic cost, landscape connectivity, and source quality describe different questions; preserving those dimensions makes it easier to see why a location appears important and what evidence is still missing.
Transportation planners, conservation groups, researchers, residents, and wildlife may benefit. Landowners and agencies are affected when locations are characterized, so claims require careful sourcing.
02How it took shape
Reproducible Python ingestion and geospatial analysis separate mortality, safety, economic, connectivity, and evidence dimensions rather than collapsing them into an opaque score.
A reproducible Python and geospatial pipeline collects public layers, transforms them into comparable spatial evidence, and produces ranked candidate areas with source history. The output is a research screen that can guide field work, not a substitute for animal-movement data or agency review.
Josiah framed the local problem, evidence categories, interpretive limits, and publication boundary while directing agent-assisted research and implementation.
The working analysis produces source-linked candidate locations and preserves the inputs and reasoning used to rank them.
03What the project means now
The project demonstrates a useful role for transparent modeling in local conservation: narrowing an enormous landscape into a defensible set of next questions. Its honesty depends on calling those locations candidates until independent ecological evidence confirms more.
The outputs are screening hypotheses, not proof of animal movement or project feasibility. Field validation, current agency data, and ecological review remain necessary.
A useful map can narrow the next question without pretending the map itself has answered it.
Publish the public-data methodology and candidate atlas with clear uncertainty labels, then seek domain review.