Effects of restoration treatments on ponderosa pine ecosystems,

Front Range, Colorado2011-2013

Monitoring update, LR team meetingJanuary 23, 2013

Jenny Briggs, USGSPaula Fornwalt, RMRSJonas Feinstein, NRCS

Our objectives• Expand the scope of the planned CFLR monitoring to include:

• Additional sites beyond NF lands• Control (untreated) as well as treated sites• Variables mentioned in CFLR objectives but not funded by

planned CSE monitoring

• “Test” monitoring methods under discussion by LR team

• Utilize complementary funding awarded by the Southern Rockies Landscape Conservation Collaborative (SRLCC) and Boulder County Parks and Open Space (BCPOS)

Reminder! Front Range CFLRP objectives

1. Complex mosaic of tree density, age, size (at stand scale)

2. More characteristic fire regime3. More favorable distribution of tree

species4. Diverse native plant communities5. Improved habitat for expected wildlife

species6. Complex mosaic of forest density, age,

size (at landscape scale)

View from Heil Valley Ranch, Boulder County

Study sites – 2011-13Fort Collins

Estes Park

Boulder

Denver

Woodland Park

Colorado Springs

Pike San Isabel NF (PSI NF) – 2 units

Boulder County Parks & Open Space (BCPOS) – 4 units

Arapaho-Roosevelt NF (AR NF) – 3 units

Study design and treatment typesSite 

Unit T or C Pre trt data?

Post trt data? 

Trt type

PSINF Phantom1 T 2011 2012 Mech. Thin  C 2011 2012   Phantom2 T 2011 2012 Mech. Thin  C 2011 2012  BCPOS Hall2 T - 2012 Hand Thin + pile burn  C - 2012   Heil5 T 2011 2013 Mech. thin  C 2011 2013   Heil7 T 2011 2013 Mech. thin  C 2011 2013   Heil3 T - 2012 Mech. Thin  C - 2012 ARNF Estes5-34 T 2011 2012 Hand Thin  C 2011 2012   Estes5- 28 T 2011 2012 Hand Thin  C 2011 2012   Estes5- 13 T 2011 2013 Hand Thin + mastication

  C 2011 2013

• Plot selection: random + targeted approach

• Used subset of CSE plots on subset of CFLR units

• Plot density: 1 per 10 ac - 1 per 50 ac

• Sample sizes: 3-10 plots per “unit”; 10 units

• Total = 52 treatment plots, 47 controls

Sampling design

• Overstory trees

• Surface fuels

• Stand structure transects

• Understory plants

• Wildlife use

• Tree regeneration

Field measurements

Variable-radius plot – Basal Area Factor (BAF) 10

Field measurements – overstory

-To quantify within-stand heterogeneity

- Ran 100-m transects N from plot centers

Field methods – stand structure transects

Single Story

Multi Story

Openings

Stand Structure “Clumpiness” Transect

100 meter transect, measuring number and distance of openings vs. “clumps” (single story/multistory canopy cover)

a. Percent cover of species and forest floor elements*• 4 point-intercept transects per 0.1

acre plot• 100 observations per transect

*Data on litter, soil, fine fuels, and coarse fuels included today

Field methods - understory

b. Complete species inventory• All additional species

were recorded for the 0.1 ac plot

• Recorded wildlife use (recent vs. older sign) on:

- All in-plot trees, snags, stumps- Forest floor in 0.1 ac plot

• ID-ed in field and/or photos later checked by specialist(s)

• Distinguished fresh sign pre-treatment (since snowmelt in season pre-trt), older pre-trt sign, & fresh post-trt sign

• Not included in analyses: - Older sign pre-trt (may compare w. older sign @ 5 yrs post-trt)- Visual and acoustic observations of animals in plots- Pitfall trap data for ground insects – not included today

Field methods – wildlife use

Statistical analyses• Mixed-model approach in SAS:

– How was each metric affected by treatment? • Treated vs. untreated areas• 2011 (pre) vs. 2012/2013 (1 yr post treatment)

– Plot data were coded by unit (area) within site (= random effects); site was not a main effect in models

– We present means (+/- standard errors; SEs) for each metric across sites, for treated vs. untreated areas, pre vs. post treatment

• Statistically significant differences between means ( alpha level p <0.05)

Results: How were overstory conditions

impacted by treatments?

Decreased Basal Area & TPAns; similar % ponderosa

Untreated TreatedTotal basal area (BA; ft2/ac) Pre-treatment 109.4(7.2)a 110.9 (7.5)a

1 yr post-treatment . 69.4 (6.8)b

Ponderosa trees per acre (TPA) Pre-treatment 318.8 (71.1)a 222.7 (33.3)a

1 yr post-treatment . 119.1(21.0)a

Percent BA ponderosa pine Pre-treatment 77.5 (4.8)a 74.4 (5.3)a

1 yr post-treatment . 80.2 (4.5)a

How was stand structure impacted?

Increased % open; same # openings but larger

Untreated TreatedPercent open (per 100m) Pre-treatment 41.7 (2.7)a 36.3 (3.2)a

1 yr post-treatment . 65.7 (3.0)b

Number of openings (per 100m) Pre-treatment 6.4 (0.3)a 6.7 (0.4)a

1 yr post-treatment . 5.9 (0.3)a

Average opening size (m) Pre-treatment 6.5 (0.4)a 5.6 (0.5)a

1 yr post-treatment . 13.2 (1.5)b

Same # clumps but smaller; Less multi-story

Untreated TreatedAverage # clumps (closed sections) Pre-treatment 6.7(0.3)a 7.0(0.5)a

1 yr post-treatment . 5.7(0.3)a

Average size of clump (m) Pre-treatment 9.4(0.8)a 11.1(1.2)a

1 yr post-treatment . 6.0 (0.5)b

% clumps with single: multi story Pre-treatment 49.1 (17.2)a 43.5 (20.1)a

1 yr post-treatment . 83.4 (14.7) b

How were understory plants impacted by treatments?

Forest floor elements were (somewhat) influenced by treatments

– Litter cover:  Decreased– Soil cover:  Increased (kind of)

Untreated TreatedLitter cover (%)       Pre-treatment 85.3 (1.5) a 85.0 (1.5) a   1 yr post-treatment 82.5 (1.5) a 75.3 (1.7) b     Soil cover (%)       Pre-treatment 3.0 (0.9) a  3.0 (0.7) ab

   1 yr post-treatment   3.0 (0.9) ab 4.9 (0.8) b

Treatments increased cover of fine fuels; coarse woody debris change not represented w/ this method

Untreated TreatedFine fuels cover (%) Pre-treatment 11.9 (2.0) a 10.4 (1.0) a

1 yr post-treatment 7.2 (1.0) b 18.3 (2.0) c

Coarse woody debris cover (%) Pre-treatment ~low ~ low 1 yr post-treatment ~low often high!

- Fine fuels includes chips from mastication where present- Coarse fuels includes slash logs/piles where present

Examples of slash treatment

Total understory cover and richness were not influenced by treatments…

– Cover: Averaged 11.5% across all treatments, years– Richness: Averaged 30.8 species/plot

Untreated TreatedTotal plant cover (%) Pre-treatment 13.3 (1.8) a 11.1 (1.3) a

1 yr post-treatment 13.0 (1.7) a 8.7 (1.2) a

Total plant richness (species/plot) Pre-treatment 32.4 (1.3) a 29.3 (1.1) a

1 yr post-treatment 31.4 (1.5) a 30.3 (1.5) a

… and remained uninfluenced no matter how data were sliced and diced

Sliced by life form…

• Graminoid/forb/shrub cover– Gram cover: 3.6%– Forb cover: 1.8%– Shrub cover: 6.0%

• Graminoid/forb/shrub richness– Gram richness: 6.1 species/plot– Forb richness: 19.3– Shrub richness: 4.6

Sliced by life span…

• Short-lived/long-lived plant cover– Short-lived cover: 0.4%– Long-lived cover: 11.0%

• Short-lived/long-lived plant richness– Short-lived richness: 2.9 species/plot– Long-lived richness: 27.1

Sliced by nativity…

• Native/exotic cover– Native cover: 10.9%– Exotic cover: 0.5%

• Native/exotic richness– Native richness: 29.1 species/plot– Exotic richness: 1.5

How was wildlife use impacted by treatments?

Wildlife use sign

GUILD EXAMPLES  OF SIGN  RECORDED

Tree squirrels Abert’ssquirrel cone cobs

Pine squirrelcone cobs

Needleclippings

Middens Nests

Birds Nests Cavities Bole foraging

Owl pellets, turkey poop

(Feathers)

Ungulates Deer/elk pellets

Game trails Resting beds

Aspen browse marks

Grazed saplings

Large mammals Scat-bear, coyote

Scat- lion, fox, bobcat

Foragedlogs

Predated carcasses

Small mammals Scat- rodent/rabbit/hare

Burrows Feeding sign

Invertebrates Ant hills Ground-dwellinginsects in pitfall traps

Some short-term response to treatmentsUntreated Treated

Guilds represented per plot (0-6) Pre-treatment 1.9 (0.4) a 2.2 (0.2) a

1 yr post-treatment 2.1 (0.7) a 1.2 (0.2) b

Plots with presence of recent sign from any guild (%) Pre-treatment 100 (0) a 97.1 (2.9) a

1 yr post-treatment 87.5 (5.9) a 73.5 (7.7) a

Plots w presence of recent sign tree squirrels (%) Pre-treatment 87.5 (5.9) a 64.7 (8.3) a

1 yr post-treatment 68.8 (8.3) a 29.4 (7.9) b

No detectable change in presence of recent sign of other “guilds”

Average % plots with recent sign across all treatments/years:

– Ungulates: 31.7% – Birds: 49.2%– Small mammals: 12.2%– Large mammals: 2.9%

Trends (non significant) for lower use of treated sites, and/or annual variation

Exploring preliminary relationships (regressions) among variables

Summary of treatment effects: forest floor

• Small decrease in litter cover, small increase in soil cover

• Moderate increases in woody debris

Progress toward desired conditions? Yes for litter and soil – small changes in desired direction

No or ? for woody debris – depending on wildlife vs. fuels perspective

Summary of treatment effects: understory plants

• No change in understory plant cover or richness – understories were resilient to treatment disturbance

– Consistent with the literature for first year response

– Increases in cover/richness following treatments can take several years

– Understories may not respond at all if canopy not opened up enough and if forest floor not exposed

• Very low proportion of exotics

Progress toward desired conditions? Did not move AWAY from desired conditions, but did not move toward them either (at least not yet)

Summary of treatment effects: overstory

• 30% decrease in overstory BA• 50% decrease in total TPA• ~5% increase in percent ponderosa pine

• Progress toward desired conditions? - Yes in terms of direction- ? In terms of amount of change

Summary of treatment effects: stand structure

• 2-fold increase in amount of open-ness in stands• Increased size of openings but low variation in size• Same number of openings• Same number and smaller size of “clumps”• ~ 2-fold increase in single- vs. multi-story canopy structure

Progress toward desired conditions?- Yes on direction of most changes – increasing mosaic- ? on amount of change & variability of changes within/among stands

Consider retaining larger clumps, multi-story components, and increasing range of sizes of clumps & interspaces

Summary of treatment effects:wildlife use

• Few detectable changes in use by most groups

• Small decrease in use of treated sites by tree squirrels

• Too short-term to tell if these changes will persist• Not enough detailed data to tell if these changes reflect important

population- or community-level trends

• Progress toward desired conditions?– Uncertain based on these data

Arewe treating 

the rightareas?

Aretreatments contributing 

to DCs?

Define Restoration Actions/TreatmentsDefined by Front Range Roundtable; agreed by Agencies

Define Desired Conditions (DCs) for Ecological Restoration and identify uncertaintiesDefined by Front Range Roundtable* and Agencies

Define Restoration AreasProposed by Agencies; agreed by Front Range Roundtable (pre-NEPA)

Project Planning,NEPA

Project Implementation and Implementation  

monitoring**

Goal: To Sustain Front Range Montane Ecosystems

No

No

Yes

Yes

Pre-Treatment MonitoringHave

we defined appropriate

DCs?

Didwe definethe goal(s) correctly?

No

No

Post-TreatmentMonitoring

Yes

Develop/Modify Monitoring Plan

Analysis/EvaluationBy Agencies and Front Range Roundtable* Currently delegated to the Landscape Restoration Team

** See explanation in accompanying text

Are wemonitoring theright things? Is 

monitoringeffective?

Yes

Effectiveness monitoring: long-term, landscape-scale

External/InternalResearch

Adaptive monitoring: Continual and long term

No

How effective were our methods?• Overstory – CSE methods effective for plot-based overstory statistics

– Consider modifying scale and intensity of effort in future yrs– Improve methods for capturing fuels and regeneration data

• Stand Transects – surprising amount of info beyond plot level for small time/cost! (10-30 min/transect)– add perpendicular measures of clump width?– Correlate with imagery analysis

• Understory -- transects may not capture % cover for as many species as ideal, but was effective approach combined w/ 100% search of plot– New team will evaluate possible modifications

• Wildlife use -- achieved goal of getting “pilot” data on presence/absence of guilds’ use of the actual trees & plots in forest inventory

- but sign counting methods were very general, not targeted to best spatial scale for key species/guilds of interest

- prone to observer variation/errors in ID of freshness as well as species

Wildlife monitoring effort should be significantly expanded based on team’s input, to get more detailed info on population status and trends of the most ecologically informative species’ response to treatment over time!

How effective were our methods?

Possible next steps/future directions

• Within LR team/Roundtable setting – Continue larger “data evaluation” process with CFRI team– Recommendations for A.M. for CFLR, 2014 & beyond– Contribute to national indicator assessment– Prepare manuscript for journal submission

• Beyond – Build connections with other CFLRs? – Extend timeline to learn more abt Tier 2 variables? – Funding?

Many thanksSRLCC proposal partners & LR team players• Craig Hansen, USFWS; Casey Cooley, CPW• Sara Mayben, Jeff Underhill, Janelle Valladares, PSINF• Paige Lewis and Mike Babler, TNC• Jessica Clement and Peter Brown, CFRI• Greg Aplet, The Wilderness Society• Mike Battaglia, RMRS• Claudia Regan, R2• Hal Gibbs, ARNF; • Scott Woods, CSFS

PSINF, ARNF, BCPOS staff• Felix Quesada, Janelle Valladares, Ed Biery, Chris Oliver, PSINF• Dave Hattis, Adam Messing, Kevin Zimlinghaus, ARNF• Chad Julian, Susan Spaulding, Nick Stremel, & volunteers - BCPOS

Field crews• Stephanie Asherin, Abby Smith, Peter Pavlowich, Danny Volz, Rebecca

Harris, Matt Thomas, Kristen Doyle, Akasha Faist, Colton Heeney