Updated July 2026:
This is the main website for the Conifer Pyrometrics modelling system (CP, also called Canadian Conifer Pyrometrics or ConPyro). ConPyro is an empirically-based fire behaviour prediction system based on Canadian experimental fire and wildfire data. At present, ConPyro predicts wildfire equilibrium rate of spread (ROS) and type of fire with respect to crowning tendency: surface, passive crown fire, or active crown fire) for variable fuel structure conifer forests. The model can be accessed via a newly released R package or using the FuelDash calculator and dashboard. At present, model outputs represent a one-dimensional, stand-level framework that applies to headfire spread on flat ground, but this is likely to change soon (by end of 2026). Related methods from the Canadian Fire Behavior Prediction (FBP) System can also be used to predict fuel consumption and fire intensity. ROS outputs are in m/min, while surface fuel consumption (SFC, an input for ConPyro that can be estimated) is in kg/m2, as per FBP System convention.
While methods for incorporating variable slope and fire acceleration have been developed, they have not been published yet. Novel methods for estimating ladder fuel influence to crown fire initiation have also been developed and are available in draft form. There are exciting developments in progress to incorporate ConPyro into a full-fledged fire growth model, (spoiler alert: PyroCell), along with ensemble modelling linkages for a wide variety of simulations.
Until a more comprehensive guide becomes available, this page houses the latest official ‘production’ software and reference documents for users.
The ConPyro R Package has been developed by Nicholas Hebda and I, and is an easy way to access CP for analysts and modellers. It is not yet up on CRAN, but installation and usage instructions can be found on Nick’s ConPyro GitHub page. To install, you will need the ‘remotes’ package, and can install via
remotes::install_github(“nhebda/conpyro”) from the R terminal. See the GitHub page for more detailed instructions and function examples.
FuelDash (online or Desktop) is a dashboard and calculator that has a been an important ConPyro conceptual tool from day one (see Perrakis et al. 2020, linked below) and is also a great introduction and training tool for ConPyro . It was developed based on FuelGraph, a similar tool for the FBP System.
On its own, FuelDash is a graphing tool that shows fire type and equilibrium ROS and allows for a quick visual representation of what happens to fire behaviour when fuel structure or weather inputs (raw weather or indices) change. This makes it idea for developing hazard reduction fuel treatments, as the different inputs can be adjusted manually to show immediately how ROS and fire type change. It also contains some related calculators, which produce quantitative outputs that can be easier to report than the graph results. As this is a rich field for new research findings and developments, there remains much room for progress, but I’m proud of how easily and readily FuelDash shows some of the nuances of fuel treatment design.
FuelDash – online: Shiny app
FuelDash – desktop: Excel
There’s also an Excel-based tool for calculating the stand-adjusted litter moisture content (Wotton and Beverly 2007), one of the important ConPyro intermediate outputs.
(Note – these are the ConPyro applications, not to be confused with the FBP-based FuelGraph app.)
If you haven’t looked at FuelDash (formerly FuelGraph-CP) in a couple of years, you will note a much cleaner user interface than in older versions, as well as some additional tools and capabilities. Newish additions include a precise probability of CFI calculator, stand-adjusted mc estimator, and options for using Cruz and Alexander’s ‘10% rule’ (actually 8.4% for conifer forests) when active crown fire is predicted. The surface fire models also have a few new choices. Finally, the ‘smooth CFI’ option presents a smooth ROS transition between surface fire and crown fire, based on the probability of crowning function (calculated based on the equations from the 2023 paper).
ConPyro Reference Papers and Documents The papers describing the ConPyro sub-models have gradually been getting published, though this is still a work in progress.
Current reference documents are as follows.
1. Conference paper describing the overall CP scheme:
2. Updated empirical crown fire model paper, published in IJWF, with extensive appendices and online supplemental material:
See also the Supplemental Material.
3. Ladder fuel theory conference paper. This short paper (extended abstract) was presented at the April, 2024 Fire Behaviour and Fuels conference in Boise, ID, USA, and has been published in the Proceedings document.
4. Surface fire modelling paper (new!). Recently published in Fire, this paper describes a number of operational surface ROS models that can be used when crown fire is not predicted.
Perrakis, D.D.B., Hebda, N.J.R., and Taylor, S.W. 2026. Simple spread models for understory surface fires. Fire 9(302): 1–29. MPDI. doi:https://doi.org/10.3390/fire9070302.
5. Working paper (2022) describing the crown fire reanalysis and linkages with other associated models. This document is largely obsolete following the publication of the 2023 crown fire occurrence and 2026 surface fire papers (above), but could be useful for seeing some earlier versions of the surface and crown fire models that were delivered in workshops in 2020-2024.
In addition to these tools and documents, there are several other papers currently in the works using these models in field and case study applications that should help with real world credibility. Together with collaborators from Monash University, Australia, some related machine learning models were also developed from the surface and crown fire data; we may try to incorporate these methods into future versions if possible. There is also a GIS tool and spatial fire growth model in the works, both exciting developments led by some collaborators that provide workable solutions to some persistent questions and gaps. So stay tuned!
As described elsewhere on this blog, this all started as a quest to develop a simple FuelGraph-like tool for the CFIS system. Once a need for data reanalysis became apparent, it became a bona fide research project and system in its own right. The conference paper, working paper, updated crown fire model, and ladder fuel and surface fire models followed. At present, it represents a vision for a mostly-empirically based conifer fire behaviour prediction system that uses continuous forest structure variables and avoids the need for subjective fuel type decisions. It may be overshadowed within a few years by the ‘Next Generation’ FBP System (see the NG-CFFDRS vision document), but will likely be supported as a legitimate system in its own right for many years to come.
At this time, I suspect that the largest potential source of error (and uncertainty) in ConPyro occurs when trying to use the system for non-boreal conifer stands. For instance, anecdotal evidence suggests that ConPyro may overpredict crown fire occurrence in Douglas-fir – Ponderosa pine stands in southern BC. This is an important potential use case, as these fire-dependent ecosystems are generally excellent candidates for hazard reduction fuel treatments and ecosystem restoration via prescribed fire. So resolving this is a priority, but will likely involve some more research. There is always more to know and do.
For those interested in the code, I am gradually getting everything on GitHub, as noted here, but it’s all still a bit messy.
Finally, it has been a slow process to get the ‘final’ models published, even while most of the vision has been in place for more than 5 years at this point. I appreciate everyone’s patience. Clearly, it is a bit risky to propose and teach methods that have not yet been sanctioned by the research community via peer-review. And yet as the models get published, the original vision has been justified. I don’t believe that any big errors have emerged in the past 5 years regarding these models, but we’re always looking for opportunities for improvement. Please contact me if you have suggestions, find bugs or have other comments.
-DP
FireResearch.ca 