Effects of restoration treatments on ponderosa pine ecosystems, Front Range, Colorado 2011-2013 Monitoring update, LR team meeting January 23, 2013 Jenny.

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Presentation transcript:

Effects of restoration treatments on ponderosa pine ecosystems, Front Range, Colorado Monitoring update, LR team meeting January 23, 2013 Jenny Briggs, USGS Paula Fornwalt, RMRS Jonas 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 regime 3. More favorable distribution of tree species 4. Diverse native plant communities 5. Improved habitat for expected wildlife species 6. Complex mosaic of forest density, age, size (at landscape scale) View from Heil Valley Ranch, Boulder County

Study sites – Fort 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 types Site UnitT or C Pre trt data? Post trt data? Trt type PSINFPhantom1T Mech. Thin C Phantom2T Mech. Thin C BCPOSHall2T -2012Hand Thin + pile burn C Heil5T Mech. thin C Heil7T Mech. thin C Heil3T -2012Mech. Thin C ARNFEstes5-34T Hand Thin C Estes5- 28T Hand Thin C Estes5- 13T Hand Thin + mastication C

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 StoryMulti 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 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 & TPA ns ; similar % ponderosa UntreatedTreated Total basal area (BA; ft 2 /ac) Pre-treatment 109.4(7.2) a (7.5) a 1 yr post-treatment (6.8) b Ponderosa trees per acre (TPA) Pre-treatment (71.1) a (33.3) a 1 yr post-treatment (21.0) a Percent BA ponderosa pine Pre-treatment 77.5 (4.8) a 74.4 (5.3) a 1 yr post-treatment (4.5) a

How was stand structure impacted?

Increased % open; same # openings but larger UntreatedTreated Percent 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 (1.5) b

Same # clumps but smaller; Less multi-story UntreatedTreated Average # 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 (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) UntreatedTreated Litter cover (%) Pre-treatment Pre-treatment 85.3 (1.5) a 85.0 (1.5) a 1 yr post-treatment 1 yr post-treatment 82.5 (1.5) a 75.3 (1.7) b Soil cover (%) Pre-treatment Pre-treatment 3.0 (0.9) a 3.0 (0.7) ab 3.0 (0.7) ab 1 yr post-treatment 1 yr post-treatment 3.0 (0.9) ab 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 UntreatedTreated Fine 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 1 yr post-treatment ~lowoften 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 UntreatedTreated Total 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 GUILDEXAMPLES OF SIGN RECORDED Tree squirrelsAbert’s squirrel cone cobs Pine squirrel cone cobs Needle clippings MiddensNests BirdsNestsCavitiesBole foraging Owl pellets, turkey poop (Feathers) UngulatesDeer/elk pellets Game trailsResting beds Aspen browse marks Grazed saplings Large mammalsScat-bear, coyote Scat- lion, fox, bobcat Foraged logs Predated carcasses Small mammalsScat- rodent/ rabbit/hare BurrowsFeeding sign InvertebratesAnt hillsGround-dwelling insects in pitfall traps

Some short-term response to treatments UntreatedTreated 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

Are we treating the right areas? Are treatments contributing to DCs? Define Restoration Actions/Treatments Defined by Front Range Roundtable; agreed by Agencies Define Desired Conditions (DCs) for Ecological Restoration and identify uncertainties Defined by Front Range Roundtable* and Agencies Define Restoration Areas Proposed 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 Yes Pre-Treatment Monitoring Have we defined appropriate DCs? Did we define the goal(s) correctly? No Post-Treatment Monitoring Yes Develop/Modify Monitoring Plan Analysis/Evaluation By Agencies and Front Range Roundtable Analysis/Evaluation By Agencies and Front Range Roundtable * Currently delegated to the Landscape Restoration Team ** See explanation in accompanying text Are we monitoring the right things? Is monitoring effective? Yes Effectiveness monitoring: long- term, landscape-scale External/ Internal Research External/ Internal Research 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 thanks SRLCC 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