snampannualmeeting2013 afternoon compress...

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snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project

Working Lunch 12:30-‐1:15


Today’s Agenda 10-‐10:15am Welcome and overview – John Ba�les

10:15-‐10:35am Implementa�on & American Fire update – USFS District Rangers 10:35-‐11:30pm UC Science Team Integra�on Plan – Peter Hopkinson & Susie Kocher 11:30-‐12:30pm UC Science Team updates

Spa�al Team – Maggi Kelly Fire and Forest Ecosystem Health – Danny Fry Water Team – Roger Bales and Martha Conklin

12:30-‐1:15pm Working Lunch (provided) 1:15-‐1:45pm Dialogue Groups Part 1

Fire and Forest Ecosystem Health Team Water Team

1:45-‐2:45pm UC Science Team updates, con�nued Public Par�cipa�on Team – Lynn Huntsinger, Susie Kocher, Maggi Kelly Wildlife (Owl and Fisher Teams) – Zach Peery and Craig Thompson

2:45-‐3:15pm Dialogue Groups Part 2 Wildlife (Owl and Fisher Teams)

3:15-‐3:30pm Next steps/Evalua�on – John Ba�les, Kim Rodrigues

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Dialogue Groups Part 1 -‐ 1:15 – 1:45

-‐Fire and Forest Ecosystem Health Team

-‐Water Team


SNAMP Science Team Updates

Part 2: A�ernoon Session 1:45 – 2:45  Public Par�cipa�on Team – Lynn Huntsinger, Susie Kocher, Maggi Kelly  Wildlife (Owl and Fisher Teams) – Rocky Gu�érrez and Craig Thompson

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UC Science Team Updates

Public Par�cipa�on Team


SNAMP PPT: UPDATE 2013

1.  Introduc�on: Lynn

2.  SNAMP PPT Database

3.  Key outreach highlights: Susie

4.  Web update and transi�on: Maggi

5.  Research highlight: Shufei’s network analysis

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Analyzing SNAMP PPT Database: Interviews, surveys, mee�ng metrics from the beginning to the end

  1. Divergence or convergence of people’s interests and ideas about forest health, SPLATs, fire, Adap�ve management, UC role.   2. Percep�ons of impacts of SPLATs, fire, on studied resources, connec�on to people’s views of forests/forest health.   3. Frequency of topics over �me in mee�ng notes, comments. Web hits, a�endance, and networking by topic.


Metrics for Assessment of Collabora�ve Adap�ve Management Model

  4. Type, persistence, and diversity of engagement: web, mee�ngs, integra�on team, field trips, workshops.   5. Change in comprehension/mutual learning.   6. Impact of third party par�cipa�on: more confidence in the process?   7. Change in ideas about adap�ve management.   8. Final Data Collec�on: Interviews, Email survey.

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Key outreach highlights: Susie

On-‐going outreach ac�vi�es   Facilitation: Annual and MOUP

meetings   Presentations: 12 to 210 people   Exhibit: SNAMP exhibit at UC

Merced, July – Sept 2013   Field trips: Sugar Pine 9-19-12,

Last Chance 10-16-12   UCANR Green Blogs: 4 on

rodenticide, road kill, fire ecology and public participation

  News/Newsletter: 7 on rodenticide, logging, snow sensors, roadkill, and public involvement

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New this year

  Integra�on Team mee�ngs: none

  Collabora�ve Adap�ve Management Workshops:

  Developed training modules to facilitate community CAM efforts in the future

  Held workshops for managers and stakeholders   Auburn (1/31, 2/28, 3/28 & 8/1/13 – 40 a�ended),   Oakhurst (2/14, 3/14, 4/18, & 10/14/13 – 40)   Jackson (8/8 & 9/10/2013 – 10 a�ended)

  Developed on-‐line collabora�ve tools site with curriculum and discussion for mutual support


Collabora�ve Adap�ve Management workshops

Desired Outcomes:   To improve

communication and facilitation skills between natural resource managers and stakeholders

  To learn effective CAM and mutual learning techniques

  To increase the effectiveness and efficiency of the collaboration process

Train the trainer style curriculum

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Collabora�ve Adap�ve Management topics

  Defini�on & Purpose of Collabora�ve Adap�ve Management   Facilita�on objec�ves: building agreements/measuring success   Understanding constraints -‐ environmental, economic, staffing,   Dis�nguishing content versus process Issues   Listening as an ally   Understanding the stages of discussion   The decision making process   Logis�cs of a successful mee�ng   Learning styles and group dynamics   Crucial conversa�ons and understanding inference   Dealing with difficult behaviors & reducing conflict   Integra�on and capacity transfer of CAM   Pu�ng facilita�on tools into prac�ce

About 12 hours of instruction


Who is a�ending? Federal agencies US Forest Service Tahoe, Eldorado, & Sierra NF, & PSW Research, USGS, NRCS State agencies CalFire, Cal Department of Fish & Wildlife, Sierra Nevada Conservancy University UC Berkeley, UC Merced, UC Office of the President Local government/Districts Nevada & Placer County Resource Conserva�on Dist, Plumas Corpora�on, Central Sierra Watershed Commi�ee, Yosemite Sequoia RC&D, Placer County, Calaveras Irriga�on District Local organiza�ons/Non-‐profits Oakhurst Chamber of Commerce, Foothill Conservancy, Stewardship Council Other Consultant, Farmer, Calvin Crest Outdoor Ed. School

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5-‐ strongly agree, 4-‐agree, 3-‐neutral, 2-‐disagree, 1-‐strongly disagree I learned ac�ve listening techniques and how to use them 4.7 I learned ways to organize an effec�ve mee�ng 4.3

I learned the importance of a stakeholder analysis 4.4 I learned to iden�fy and capture desired outcomes 4.5

I learned tools to deal with difficult behaviors in par�cipants 4.5

I learned ways to reduce conflict within groups 4.7

The guest speaker was informa�ve about collabora�on 5.0

The facilita�on prac�ce with 'real world' scenarios was helpful 4.9

This workshop was �mely and relevant-‐it dealt with issues with which I am currently dealing.

4.9

This workshop provided prac�cal and useful knowledge and skills that are applicable to my job.

4.6

This workshop provided new informa�on, ideas, methods and techniques. 4.6

The way that this workshop was delivered was effec�ve for me to learn 4.7

I had enough �me to understand, learn, and integrate the workshop materials. 3.9

The instructor generated ac�ve discussion and involvement by par�cipants 5.0

Overall, I was sa�sfied with the instructor 5.0

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Outreach Priori�es for Coming Year

  On-‐going ac�vi�es: presenta�ons, blogs, newsle�ers, Facilita�on support for MOUP and public mee�ngs

  Integra�on Team mee�ngs with all teams using post treatment data – cri�cal feedback before final report

  2nd Water IT   Fisher outreach as possible (web updates, IT mee�ngs, field trips, scien�st presenta�ons)

  Working with agencies who may want to offer manager feedback on report format

  Field trips – Last Chance post American fire, others   Messaging on changes in SNAMP – fisher team and American fire

  Addi�onal CAM workshops if feasible


Web and Informa�on Tracking update and transi�on

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New SNAMP Paper: Public Par�cipa�on and the Web Case Study: how has the website helped to facilitate

par�cipa�on in SNAMP? Ø  communica�on – consulta�on – par�cipa�on

“Because management projects in conten�ous natural resource

contexts o�en involve finding reasonable compromise or shared understandings between par�cipants, the success (or failure) of such management is partly about informa�on: control of informa�on, differen�al access to informa�on, and transparency of informa�on flow”


Research Priori�es for Coming Year -‐ Web

  Disserta�on by Shufei Lei: Networks of Informa�on, People, and Space in Adap�ve Management: the Sierra Nevada Adap�ve Management Project –  Informa�on tracking and adap�ve management: the produc�on, use, and impact of mutual learning

–  Social networks of people and places: structural par�cipa�on through events   Can SNA provide insights into adap�ve co-‐management in SNAMP in terms of geography, social cohesion, and resilience.

–  Self-‐Organizing Maps to analyze mee�ng notes

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Social Network Analysis: a more quan�ta�ve and formal model for the adap�ve cycle in the resilience framework

Can SNA provide insights into adaptive co-management in SNAMP? In terms of geography, social cohesion, and resilience.


1. SNAMP par�cipant geography Posi�on: We have a clear North/South split, and core and peripheral par�cipants.

SNAMP PublicMOUPUCST

Meetings in the SouthMeetings in the North

SNAMP PeopleSNAMP Meetings

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2. Social Cohesion The centraliza�on (%) of the network and average a�endance increased from 2005-‐2010, but fell a�er that.

This suggests that overall the project has been successful in building up the network un�l 2010 (funding issues?).

0

10

20

30

40

50

60

70

80

90

2007 2008 2009 2010 2011 2012

Avg a�endance Centraliza�on (%)


Resilience at the actor level: Core par�cipants from both the MOUP and the Public group stayed on despite the fluctua�on of the cohesiveness at the network level.

3. Social Resilience

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SNAMP Website

  Up and running, but will need to be moved into archive mode probably spring 2015.

  We’ll do a retrospec�ve of what worked what didn’t as part of the final report.


UC Science Team Updates

Owl Team

Zach Peery

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Tes�ng Predicted Short vs Long-‐term Risk of SPLATS in Two Stages

No SPLATS

Time

SPLATS

SPLAT

n

High risk due to loss of forest structure

Low risk due to reduc�on in high-‐severity fires

Increased risk because

of more high-‐severity

fires

Risk to

Owls

Baseline

Stage 2 (Indirect, long-‐term)

Stage 1 (Direct, short-‐term)

Year 30 Year 0

Stage 1 (Modified) Study Design

 Insufficient treatment territories in Last Chance → Expansion to Eldorado Study Area

 Delay in treatments/low power → Retrospec�ve analysis (1993-‐2012); n = 74 territories

 “Quasi-‐experimental” evalua�on of SPLATs → Correla�ve assessment of many treatments types

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1993 2009

Stage 1: Effect of Habitat and Habitat Change on Owl Demography

400 ha analysis circle


Veg class 4Veg class 3

Veg class 2

Veg class 1Hardwood Clearcut/Brush/Sapling

Pole-‐sized forest

Vegeta�on Classes

12-‐24” dbh 30-‐70% CC

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Veg class 7 Veg class 9

Veg class 5

Veg class 6

12-‐24” dbh ≥ 70% CC

< 30% CC >24” dbh ≥ 70% CC

>24” dbh 30-‐70% CC


Timber Harvest Categories   Heavy

–  Clear cut, overstory removal, seed tree removal, seed tree cut, shelterwood removal/commercial thin, shelterwood seed step

  Medium (with and without understory removal) –  commercial thin, selec�on, single-‐tree selec�on, group

selec�on, thinning for hazardous fuels removal, fuel break, SPLATS

  Light –  Pre-‐commercial thin, sanita�on salvage

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Analy�cal Approach   Dependent variables: Reproduc�ve Output, Survival, and Occupancy (ex�nc�on and coloniza�on)

  Development of a priori models –  Stage 1: owl habitat variables –  Stage 2: secondary habitat variables –  Stage 3: �mber harvest, fire

  3-‐, 6-‐, and 9-‐year “moving windows” for stage 3 variables


Status of Stage 1   All habitat mapping and treatment delinea�on has been completed   Stage 1 habitat-‐demography and sensi�vity analyses have been completed   Methods, results, and conclusions have been “wri�en up” in manuscript form   We will submit the manuscript containing all results to Ecological Applica�ons by November 1.   Results will be shared with partners and stakeholders if/when the paper is in press.

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Stage 1 Challenges   Characterizing the effect of habitat change and treatments on CSO demography is challenged by: –  Correla�ve rather than experimental nature of study –  Broad range of treatments and disturbances –  Resolu�on of habitat map

  Coarse and subjec�ve binning of habitat classes   Large and residual trees not mapped   Understory characteris�cs not mapped

–  Timing of treatments –  Lag effects of treatments on owl demography –  Variability in “quality” among individual owls


Stage 2: Fire-‐Owl Habitat/Demography Modeling

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Owl Habitat Metrics   Fireshed Scale

– Area of suitable owl nes�ng habitat with threshold levels of “large” trees and “high” canopy cover (Habitat)

  PAC Scale – “Fireshed scale” metrics limited to areas within PACS (Habitat)

– Number of PACs and total area within PACs affected by any fire and by fire (Fire Risk)

  Analysis Circle Scale (400 ha) – Area of CWHR vegeta�on classes (Demography)

  Demographic Metrics – Reproduc�ve, Survival, Ex�nc�on, and Coloniza�on Rates

–  Integrated Metrics   Popula�on growth rate (λ) from matrix model parameterized with survival and reproduc�ve rates.   Equilibrium occupancy

  Scale of Demographic Metrics – Mean of all Analysis Circles (400 ha) in Last Chance (n = 4 to 6)

Owl Demographic Metrics

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Status of Stage 2   Integra�ng closely with FFEH

– Fire and Forest model outputs = Owl inputs – Have established preliminary work flow – Have agreed on team responsibili�es

  Conduc�ng “dry run” of fire-‐owl modeling – Using outputs from Collins et al. (Forest Science, 57: 77-‐88)

– Use dry run to refine conceptual model and work flow as needed

  Use final conceptual model as founda�on for Fisher integra�on


 1. Habitat Mapping-‐ García-‐Feced, C., D. Tempel, and M. Kelly 2011. LiDAR as a tool to characterize wildlife habitat: California spo�ed owl nes�ng habitat as an example. Journal of Forestry 108: 436-‐443.  2. Sampling Design – Popescu, V. D., P. de Valpine, D. J. Tempel, and M. Z. Peery. 2012. Es�ma�ng popula�on impacts via dynamic occupancy analysis of Before–A�er Control–Impact studies. Ecological Applica�ons. Ecological Applica�ons 22: 1389-‐1404.  3. Climate Change -‐ Peery, M. Z., R. J. Gu�érrez, R. Kirby, O. E. LeDee, and W. S. LaHaye. 2012. Climate change and spo�ed owls: poten�ally contras�ng responses in the southwestern United States. Global Change Biology 18:865-‐880.  4.Habitat Management -‐ Berigan, W. J., R. J. Gu�érrez, and D. J. Tempel. 2012. Evalua�ng the efficacy of protected habitat areas for the California Spo�ed Owl using long-‐term monitoring data. Journal of Forestry 110:299-‐305.  5. Popula�on Trend -‐Tempel, D. J. and R. J Gu�érrez. 2013. The rela�onship between occupancy and abundance for a territorial species, the California Spo�ed Owl. Conserva�on Biology.  6. Gene�cs -‐ Barrowclough et al. 2011. Owl subspecies boundaries between Northern and California spo�ed owls in the Cascade-‐northern Sierra Nevada. Condor 113:581-‐589.  7. Conflict Resolu�on -‐ Redpath et al. In Press. Understanding and Managing Conserva�on Conflicts. Trends in Ecology and Evolu�on (online early: h�p://www.cell.com/trends/ecology-‐evolu�on/newar�cles)  8. Assessing Territory Quality -‐ Peery, M. Z. and R. J. Gu�érrez. 2013. Life-‐history trade-‐offs in California spo�ed owls: Implica�ons for assessments of territory quality. The Auk.  9. Popula�on Dynamics -‐ Stoel�ng, R*., R. J. Gu�érrez, W. L. Kendall, and M. Z. Peery. In Review. Cost of reproduc�on and popula�on dynamics: Do life history trade-‐offs drive reproduc�ve cycles in spo�ed owls (Strix occidentalis)? Evolu�onary Ecology.  10. Habitat-‐demography -‐ D. Tempel, R. J. Gu�errez, S. Whitmore, M. Reetz, W. Berigan, R. Stoel�ng, M. E. Seamans, and M. Z. Peery. In Prep. Effect of forest management and vegeta�on change on the demography of Spo�ed Owls in the Sierra Nevada. Ecological Applica�ons.  11. Doug Tempel’s PhD Thesis!!!

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Ongoing SNAMP-‐related Projects Individual vs Territory Quality

? ?

Jorgan Frank Mike Cong

Mike Cong

 What is the rela�ve importance of individual versus territory quality in driving spa�al varia�on in spo�ed owl demographic rates?


 How will expected changes in climate influence territory occupancy of spo�ed owls?

G

Ongoing SNAMP-‐related Projects Climate Change

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UC Science Team Updates: Fisher Team

Dr. Craig Thompson USDA Forest Service

Pacific Southwest Research Station

Dr. John Battles – UC

Berkeley Gary Roller – UC Berkeley Dr. Rick Sweitzer – Great

Basin Institute


Major Fisher Research Objectives: Ø  Assess responses of fishers to fuel treatments

Develop biologically-appropriate integration metrics

Ø  Estimate population parameters, identify limiting factors

Ø  Describe habitat use, occupancy, and population viability

Primary Methods: Ø  Capture & radio telemetry

Ø  Monitoring survival and reproduction

Ø  Remote camera surveys

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2013 SNAMP Fisher Update:

Ø  Year 6 camera surveys completed: 31 Aug 2013

Ø  Reproduction: 27 new dens trees identified (26% reuse)

Ø  Survival: 61 mortalities recovered to date

Ø  Dispersal records: Male >37 km, female 22.3 km Survey year

Grids surveyed

Grids with detec�ons

Percent ac�ve

2007-‐’08 117 70 60%

2008-‐’09 127 72 57%

2009-‐’10 125 74 59%

2010-‐’11 125 83 66%

2011-‐’12 128 97 76%

2012-‐’13 130 69 53%


Year % females reproduc�ve

# kits / female

Spring ’08 0.89 1.50 Spring ’09 0.76 1.36 Spring ’10 0.81 1.73 Spring ’11 0.85 1.80 Spring ’12 0.82 1.45 Spring ‘13 0.80 1.25





Ø  Dispersal records: Male >37 km, female 22.3 km

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SNAMP annual fisher survival

Year Male Female

2008-‐’09 0.83 0.80

2009-‐’10 0.71 0.86

2010-‐’11 0.76 0.57

2011-‐’12 0.42 0.91

2012-‐’13 0.72 0.81












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2014 Priorities 1. Completion of SNAMP report / habitat models

2. Transition into USFS / PSW Sugar Pine project

3. Expand research into rodenticide / pesticide impacts

4. Expand research into carnivore community response to fuel treatments


Proposed SNAMP Integration metrics:

1. Occupancy   Based on annual camera surveys   Core watershed area only   SNAMP data only

2. Intensity of use   Based on telemetry locations (aerial

and ground)   Combined SNAMP & Kings River data

3. Reproductive habitat quality   Based on a variety of datasets   Combined SNAMP & Kings River data

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Integra�on metric #1. Camera-‐based occupancy (SNAMP core watershed data only)

As of 1 January 2013:  948,412 images archived

 98,160 fisher images Survey year 6 completed

as of 31 August 2013


Grid Yr1 Yr2 Yr3 Yr4 Yr5

267-‐4148 0.33 0.28 0.29 0.31 0.22

268-‐4147 0.10 0.33 0.50 0.05 0.49

272-‐4148 0.00 0.00 0.03 0.13 0.11

272-‐4147 0.26 0.21 0.21 0.16 0.22

Key Watershed – pretreatment veg structure

Integra�on metric #1. Camera-‐based occupancy (SNAMP core watershed data only)

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Integra�on metric #2. Intensity of use (SNAMP and KRFP data combined)

SNAMP 109 animals >24,000 telemetry locations

KRFP 105 animals ~5,000 telemetry locations

0 - 10.27

10.27000001 - 20.54

20.54000001 - 30.81

30.81000001 - 41.08

41.08000001 - 51.35

51.35000001 - 61.62

61.62000001 - 71.89

71.89000001 - 82.16

82.16000001 - 92.43

92.43000001 - 102.7

102.7000001 - 112.97

112.9700001 - 123.24

123.2400001 - 133.51

133.5100001 - 143.78

143.7800001 - 154.05

154.0500001 - 164.32

164.3200001 - 174.59

174.5900001 - 184.86

184.8600001 - 195.13

195.1300001 - 205.4


Integra�on metric #3. Reproduc�ve habitat quality (SNAMP and KRFP data combined)

Conservation Biology Institute CBI Denning habitat model

2 vegetation variables

Structure2 (big, dense trees) 90% predictive power

Proportion hardwood 10% predictive power

98% dens in CWHR density class D (> 60% canopy cover)

98% dens in CWHR size class 4 & 5

(>11” DBH)

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Integra�on metric #3. Reproduc�ve habitat quality (SNAMP and KRFP data combined)

In collabora�on with Conserva�on Biology Ins�tute


20162013 20152014

Monitoring 2007 2008 2009 2010 2011 2012 Jan Feb

Mar Apr

May Jun Jul Aug

Sept

Oct Nov Dec

Jan Feb

Mar Apr

May Jun Jul Aug

Sept

Oct Nov Dec

extensive trapping treatment area treatment area trappingLivetrapping

Camera Surveys

Aerial Telemetry

Reprod. monitoring den cameras

Treatments

Cedar Valley pre-‐treat post-‐treatment monitroing

Sonny N & S post-‐treatment monitoring

Sugar Pine

Fish Camp

Grey's Mtn pre-‐treatment monitoring

key watershed occupancy surveys

ongoing

pre-‐treatmen

pre-‐treatment monitoring

extensive trapping

den cameras

ongoing

key watershed occupancy surveys

den cameras & climbs

post-‐treatment monitoring

post-‐treatment monitoring

pre-‐treatment monitoring

key watershed s

treatment area treatment area trapping

key watershed occupancy

SNAMP Sugar Pine

Integration metric models completed – April 2014

SNAMP / Sugar Pine fisher project workplan:

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2013 Research Publications:

Thompson, C., R. Sweitzer, M. Gabriel, K. Purcell, R. Barrett, and R. Poppenga. 2013. Impacts of rodenticide and insecticide toxicants from marijuana cultivation sites of fisher survival rates in the Sierra National Forest, California. Conservation Letters. doi: 10.1111/conl.12038 Matthews, S., J.M. Higley, J.T. Finn, K.M. Rennie, C.M. Thompson, K.L. Purcell, R.A. Sweitzer, S.L. Haire, P.R. Sievert, and T.K. Fuller. 2013. An evaluation of a weaning index for wild fishers (Martes pennanti) in California. Journal of Mammalogy doi: http://dx.doi.org/10.1644/12-MAMM-A-249.1 Popescu, V.D., P. de Valpine, and R.A. Sweitzer. Reconciling different types of animal space use data: camera traps and telemetry for Fishers in the Sierra Nevada (Pekania pennanti). Submitted to Journal of Animal Ecology. Wengert, G., M. Gabriel, S. Matthews, M. Higley, R. Sweitzer, C. Thompson, K. Purcell, R. Barrett, L. Woods, R. Green, S. Keller, P. Gaffney, M. Jones, and B. Sacks. Intraguild predation on fishers in California: patterns of predation by three larger carnivores. Submitted to Journal of Wildlife Management and Wildlife Monographs.


Dialogue Groups Part 2 -‐ 2:45 – 3:15

-‐Wildlife (Owl and Fisher Teams)

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2013 SNAMP PUBLIC MEETING

Next Steps and Evalua�on – John Ba�les and Kim Rodrigues

snampannualmeeting2013 afternoon compress...

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