More Forest Thinning Science

1. You need Water for Ecohydrology

I previously wrote about the effects of thinning Southwestern ponderosa pine forests on forest hydrology.  AE Brown et al (Journal of Hydrology, 2005) summarized the last 50 years of hydrology research around the world on exactly this question.  Their conclusion was that yes, thinning increases water availability by decreasing evapotranspiration (ET).  However, at drier sites there is less of a difference.

In the figure above, the difference between the grass and forest curves represents the change in mean annual water yield for 100% conversion of one vegetation type to the other.  Partial conversion (i.e. thinning) was shown to have a proportional partial response.  The lack of difference between grass and forest in drier climates (below 500mm or 20 inches precipitation/year) indicates that most ET is actually just evaporation in these areas.  Therefore, because transpiration does not play a large role, reducing transpiration via thinning would not be expected to generate a large increase in water availability.

2. Don't Miss the Forest for the Trees

This classic forestry study found that thinning ponderosa forests increased growth of the remaining trees, but decreased total wood production.  In other words, the increase in vigor didn't compensate for the decrease in trees.  This even includes the decrease in disease (bark beetles) in thinned forests. So the question becomes, do you want a healthier forest or more wood?  

Data is from the The Level-of-Growing-Stock (LOGS) study on thinning ponderosa pine forests in the US West: A long-term collaborative experiment in density management.  A 2020 follow up provides a summary review of this study that started in 1962.  The The AZ portion of the study was conducted at Fort Valley experimental Forest just north of Flagstaff.   PDF with much more info is available from https://www.fs.usda.gov/rm/pubs/rmrs_p055.pdf.

Fire Frequency in Arizona Ecosystems

 

Introduction

How likely a given area is to encounter wildfire is important for planning and wildfire mitigation. Historic or expected fire return statistics are often cited for ecosystems in Arizona, but I was curious how often wildfire actually burns across different Arizona ecosystems.

Figure 1 Example wildfire polygons around Clints Well, AZ showing overlapping fires from newer (blue, labelled), to older (shades of brown, unlabelled).  Data sources include WFIGS and GeoMAC.

Wildfire Data

I used the WFIGS Interagency Fire Perimeter GIS data, which has good data on wildfires from 2000-2023.  I limited this analysis to USFS land in Arizona.

Out of a total of 11.168 million acres of USFS land in AZ, wildfire has burned 4.8 million cumulative acres in the last 24 years.  This counts areas that burned more than once as additional acres.  It includes natural and human-ignitions, as well as wildfire managed for resource benefit.  

Figure 2 Example WFIGS Interagency Fire Perimeters in AZ

Figure 3 Wildfire acreage over time in AZ.  2011 was the Wallow fire.

Vegetation Types

To evaluate wildfire probabilities in Arizona ecosystems, I looked at the 15 most common ecosystem types, as defined by the USFS Ecosystem Response Unit (ERU) vegetation type GIS layer.  Together, these 15 ecosystems account for 9.1 million out of the 11.1 million acres of USFS land in Arizona.

Figure 6 Example ERU polygons showing aspen (pink) and mixed conifer around the San Franscisco Peaks, AZ.

To calculate the percent of each ERU burned per year, I divided total acres burned by total acres of ERU and divided that by 24 years.   Spruce-Fire forest and Mixed Conifer is most likely to burn, whereas Mixed Conifer with Aspen is least likely.  Ponderosa pine ecosystems rank in the middle, at around 3% chance. 

This analysis counts acres more than once if they burned more than once in the 24 year time period.  For example, Spruce Fir Forest ERU has more acres of wildfire than there are total acres of ERU.  This does not mean that every acre burned, but some acres burned more than once.   

ERU	ERU Acres	Wildfire Acres	% burned in 24 years	% burned per year
Ponderosa Pine Forest	1,966,603	1,431,424	72.79%	3.03%
PJ Woodland	1,175,545	208,685	17.75%	0.74%
PJ Evergreen Shrub	1,136,221	311,254	27.39%	1.14%
Mojave-Sonoran Desert Scrub	779,939	386,363	49.54%	2.06%
Semi-Desert Grassland	730,015	300,189	41.12%	1.71%
Interior Chaparral	713,754	533,678	74.77%	3.12%
Juniper Grass	539,830	299,074	55.40%	2.31%
Colorado Plateau / Great Basin Grassland	367,114	41,812	11.39%	0.47%
Ponderosa Pine – Evergreen Oak	362,838	238,365	65.69%	2.74%
Madrean Pinyon-Oak Woodland	354,836	92,160	25.97%	1.08%
Mixed Conifer - Frequent Fire	349,006	304,104	87.13%	3.63%
Mixed Conifer w/ Aspen	242,169	9,782	4.04%	0.17%
Montane / Subalpine Grassland	157,163	92,461	58.83%	2.45%
Spruce-Fir Forest	112,827	124,593	110.43%	4.60%
PJ Grass	96,016	8,995	9.37%	0.39%
Madrean Encinal Woodland	93,939	23,092	24.58%	1.02%

Figure 7 ERU acres, wildfire acres, percent burned in 24 years, and percent burned per year.  Table ranked from most to least common ERU.

Wildfire Return Interval

Fire return interval is the average length of time until fire returns at a given point in the landscape.  The chance that any given acre burns depends on a large number of complex factors, including when it last burned, the topography, fuel reduction treatments, proximity to WUI and/or human use.  Still, percent burned per year in the table above (Wildfire/Year, W) can be used to calculate expected return intervals of fire, all else being equal.

Calculations – Fire per Year

To calculate expected return intervals, first calculate the probability (P) that fire will not occur in a given span of time (X).

P = (1-W)^X

For example, for Ponderosa Pine Forest over 10 years:

P = (1-0.0303)^10

P = (0.9697)^10

P = 73.5% chance that fire will not occur, or 26.5% chance that fire will occur in 10 years.

20 years:

(0.9697)^20=54% chance that fire will not occur, or 46% chance that fire will occur.

 

Figure 8 Cumulative probability of wildfire in AZ Ponderosa Pine ERU

Calculations – Fire Return Interval

If we determine a Probability, but need to know the span of time until fire occurs, we can solve for X:

P = (1-W)^X

P = log x / log (1-W)

For example, if we determine "expected return interval" to be the length of time necessary for 50% chance of fire:

 0.5  = (0.9697)^X

X = log (0.5) / log (0.9697)

X = 22 years until there is a 50% chance of fire in Ponderosa Pine Forest.

However, if we interpret "expected return interval" to be the length of time necessary for 90% chance of fire:

0.1  = (0.9697)^x

X = log (0.1) / log (0.9697)

X = 75 years until there is a 90% chance of fire in Ponderosa Pine Forest.

Over time, the probability approaches, but never actually reaches, 100% that a wildfire will occur:

Figure 9 Cumulative Probability of Fire in Ponderosa Pine ERU

Conclusion

The length of time until fire returns at a given point in the landscape depends on how certain we want to be of the chance of fire.  If we want to be very certain (90% probability), then we would expect to wait 75 years on average.  If we are OK taking the flip of a coin (50% probability), than we would expect fire to return at any given point in 22 years.  If we are risk adverse, and can only tolerate a 10% chance of fire visiting our chosen point, we should expect fire every 3.5 years, on average.

Cutting Trees for Water: Are Thinned Forests Wetter or Drier?

Forest thinning can be controversial.  Concerned citizens want to know when logging counts as restoration;  can thinning a forest have beneficial ecological effects beyond reducing the risk of stand-replacing wildfires?  Will cutting trees increase soil moisture because there are less "straws sucking up water", or does it decrease soil moisture due to increased windspeed and more sunlight drying out the forest understory?

April 2017 - views of Rogers Lake, AZ overlooking untreated (left) and treated (right) areas.  Photos by Conor Flynn.  Click this link to play with the slider.  

Whether thinned forests are drier or wetter is complicated.  The excellent paper "Adapting western North American forests to climate change and wildfires: 10 common questions" by Prichard et al provides a good introduction to this question:

"Decreasing canopy bulk density can change site climatic conditions (Agee and Skinner 2005). Wildfire ignition potential is largely driven by fuel moisture, which can decrease on drier sites when canopy bulk density is reduced through commercial thinning (e.g., Reinhardt et al. 2006). Reduced canopy bulk density can lead to increased surface wind speed and fuel heating, which allows for increased rates of fire spread in thinned forests (Pimont et al. 2009, Parsons et al. 2018). Other studies show no effect of thinning on surface fuel moisture (Bigelow and North 2012, Estes et al. 2012), suggesting that thinning effects on surface winds and fuel moisture are complex, site specific, and likely vary across ecoregions and seasons."

Anecdotally, some people have noticed springs beginning to flow again after thinning and prescribed fire in AZ.  My research in NM pinyon noted increased soil moisture at thinned sites (unpublished data), however this could be due to the specifics of how thinning was accomplished at those sites.  Thinned slash was chipped and the chips were left on-site without follow-up prescribed fire.

In addition to water quantity, water quality should also be considered.  Prichard et al point out that "Treatments in watersheds that are distant from the WUI and protect municipal and agricultural water supplies are critical to minimizing high-severity fire impacts that can jeopardize clean water delivery (Bladon 2018, Hallema et al. 2018). For example, post-fire erosion and debris flows may cause more detrimental and longer-term impacts to watersheds than the wildfires themselves (Jones et al. 2018, Kolden and Henson 2019)."  However, even carefully managed thinning and prescribed fire can generate excess erosion from new roads, decreased large woody debris, and increased mobility of light charred wood.  Charcoal washing into local lakes can cause fish kills, even when not generated by catastrophic wildfire.  Creating erosion-control structures as part of forest thinning work could help to mitigate these risks.  

Further research is needed to ensure that large thinning projects adequately account for water cycle restoration in addition to natural stand density and fire interval restoration.  

"Improper" Tree Hazard Assessments?

The Summer 2020 issue of FSEEE Forest News argues that the Forest Service improperly uses tree hazard assessments to justify closing public lands.

Based on the article, it appears that FS spokespeople have not always done a good job communicating the reason for post-fire closure areas.  There are many reasons to close areas post-fire, but tree risk assessments by themselves would probably not justify backcountry trail closures. 

The FS Field Guide for Hazard Tree Identification and Mitigation cited in the article applies a numerical probability assessment to hazards by scoring Failure Indicators and adding these with Damage Potential to obtain a numerical Hazard Rating.   This methodology would be familiar to any arborist and follows standard arboriculture practices.  If there are dead or damaged trees around developed FS facilities or campgrounds than clearly there would be a high Hazard Rating and it would make sense to close those areas until the hazard can be mitigated.  But applying this same methodology to backcountry trails would result in scores that are relatively low because of the sparse or nonexistent targets for the hazard trees. So on this point the Forest News article is correct: hazard trees alone do not justify backcountry forest closures.

However, there are other hazards in recently burned areas besides dead trees, including active restoration/revegetation projects, burned-out root systems, unstable soils, potential debris flows, and obscured or impassable trails.  It may make sense to close these areas to the public until trails can be repaired or ongoing restoration work is completed.  

Habitat in the Endangered Species Act

Response to Jake Li's response to FWS revised definition of "habitat".

A couple of points about critical habitat.  First, it is often not stated by those who understand the ESA, and often misunderstood by those who do not, that critical habitat designations only have regulatory force on federal lands or for projects that involve a federal nexus (such that a federal agency would consult with FWS). While this may seem like nitpicking, it is crucial to understand the regulatory impact of the change in definition, as many federal agencies do not rely exclusively on critical habitat designations but instead consult with FWS based on the SME of their biologists whenever a project may impact a listed species.  

For private land, where many people are most worried about critical habitat, any changes in the areas designated would have little to no impact due to the fact that critical habitat has little to no impact on private land.

Second, it is interesting to consider how this change in the definition of habitat would affect monarchs. I think it would not affect monarch habitat due to the inclusion of "ephemeral and seasonal habitat" in the definition.  Even if monarchs only inhabit an area for a few months of the year, that area could still be designated critical habitat. 

You write that the 7a habitat protection is redundant if an area is occupied (and therefore protected by the jeopardy prohibition).  But monarchs (and many other species) only seasonally occupy parts of their critical habitat, so the 7a protection will continue to be relevant in those cases. 

---

Thoughts about possible monarch listing:

Planting milkweed habitat

Some people are afraid of creating milkweed habitat because apparently they think they would never be able to destroy or modify this habitat.  I find this unlikely.  More likely is that they would be restricted from destroying or modifying the habitat while monarch caterpillars are present.  During winter months, they could destroy this habitat without adversely affecting individual monarchs.  Habitat protection in the ESA is often misunderstood on this point.

CCAA

I assume that monarchs will be listed.  Even so, there are many reasons for not joining CCAA, but I will focus on reasons that FWS enforcement will not be detrimental to business operations at companies with well-developed IVM programs.

A mature IVM program already has the goal to move away from mowing/mastication toward spot treatment of incompatibles with herbicide.  Although there will need to be mowing in some areas, the reason for mowing is that the areas are overgrown with woody vegetation. Therefore these areas would not support monarch milkweed habitat.

There may be incidental work in monarch milkweed habitat, but most of this work would not impact monarch breeding. For example tree cutting. I consider it unlikely the FWS would broadly restrict all activities in monarch milkweed habitats, due to the vast and unenforceable impact this would have on ordinary activities across the country.

I believe FWS will restrict some activities that would impact monarch milkweed habitat, during the monarch breeding season, especially ground-disturbing activities.  Biological opinions for species impacted by ground disturbing work implement mitigation measures that include timing restrictions and crew trainings.  FWS has provided incidental take statements based on these mitigation measures and reporting requirements.  I expect a similar scenario when monarch are listed. 

Ponderosa Mortality After Fire

The best data comes from Hull Sieg, Carolyn, et al. "Best predictors for postfire mortality of ponderosa pine trees in the Intermountain West." Forest Science 52.6 (2006): 718-728.

This graph shows probability of death based on both “crown consumption” (actual burning of the crown) and “crown scorch” (browning of needles due to heat injury). It shows that probability of tree death increases above 50% when Crown Scorch increases past 75%, whereas tree death is above 50% when crown consumption is only 25%. A combination of the two is determined to be the best predictor of tree mortality.

Here are some diagrams of crown scorch and crown consumption. In general, if there are brown needles on the tree that is scorch, if they are black or missing it is consumption.



(from Tree and forest restoration following wildfire by Peter Kolb)

Rosemont mine delayed by 1872 Mining Law

Quotes from Arizona Daily Star:

In his 37-page decision, Soto hammered almost exclusively at the Forest Service’s approval of Hudbay’s plan to dump mine waste rock and tailings from its 955-acre pit onto 2,447 acres of nearby public land on the Santa Ritas’ eastern slopes.

Opponents’ lawsuits argued that only public lands directly above valuable mineral deposits are covered by the federal 1872 mining law’s definition of mining rights.

Soto wrote in his decision that for Hudbay to gain access to valuable copper, molybdenum and silver from the pit, the company would need to extract about 1.2 billion tons of economically worthless waste rock and about 700 million tons of mine tailings.

The Forest Service's primary error in this case was to accept, without question, that Hudbay's unpatented mining claims on those 2,447 acres were valid, thereby allowing them to be used for placement of the waste rock and tailings, he wrote.

Source.

Forest Service Completes WRAP Watershed Condition Map