to burn or not to burn: using population models to address the management challenges of ceanothus...

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To Burn Or Not To Burn: Using Population

Models to Address the Management

Challenges of Ceanothus verrucosus

California Native Plant Society Conference

1/13/12

Kevin Cummins, UCSD

Dawn Lawson, US Navy

Keith Lombardo, NPS

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Objectives

• Describe a developing case-study of

using modeling to inform the resource

management process

• Provide some insight on when and how

modeling can be useful to managers

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Outline

• Overview of models in ecology

• Ceanothus verrucosus (CEVE)

• CEVE modeling

• Utilization of CEVE models

Models CEVE Results Utilization

All Managers Use Models

Types of models:

Verbal

Graphical

Mathematical

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Use of Models by Managers


Example Model:

CEVE populations recruit

after fires and eventually

die out without fire

5Models CEVE Results Utilization

From Chitty 1996

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Mathematical Models

• Quantitative formalizations of verbal models

Provides quantification of outcomes

• Verbal models address qualitative features

They can miss complex dynamics.


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Types of Mathematical Models

• Deterministic

Analytical solutions

Poor forecasting

• Spatial

Different dynamics

• Stochastic

Embraces random variation


What Has Changed for Managers?

• Relevant Models: First generation of

managers with spatial-stochastic models

• Accessible Models: The species experts

can develop their own models

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Dangerous?


Case Study: Ceanothus verrucosus

Long-lived

Obligate post-fire seeder

Short dispersal distances


Limited Distribution

C. verrucosus

Cabrillo National Monument


Demography of Long-lived

Plants

• Understanding of plant

population dynamics

developed with studies of

short-lived species

• Effects of management

options difficult to assess

within a single career

Image of 90yr CMN stand here instead

90 Year Old Stand

of CEVE

Management Concerns

• Habitat loss

• Altered fire regimes

• Interval

• Intensity

• Habitat fragmentation

• Size


Example Management

Question

What are the consequences of adopting

various fire policies at CNM on the

maintenance of CEVE populations?

When do they need to start burning?

What fire regime should be targeted?


Structure of CEVE Models

• Stochastic

• Spatial

• Age based

RAMAS GIS (Applied Biomathematics)


CEVE Modeling Results

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Average Fire Return Interval (years)

How often should CEVE stands burn?


Population Trajectories

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Time (years)

GFDL

PCM

Present Climate

Habitat Loss

Increase

Decrease

Which anthropogenic changes are the

greatest threat to CEVE?


Sensitivity Analysis

A model parameter is sensitive if the model output is

varies by a relatively large amount compared to the

initial perturbation of the parameter.

What features of the CEVE models are

sensitive to estimation error?


More Sensitive Less Sensitive

Seedbank Longevity Later stage survival

Juvenile Survival Fecundity

Germination Rate Carrying capacity

Plant Longevity

Sensitivity Exemplars

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Baseline Model

Baseline Model

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Baseline Model

ExtendedLifespan

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Baseline Model

ExtendedSeedbank

ExtendedLifespan


Conclusions from the Modeling

• Climate change poses greatest risk of population decline

– however depending on the extent of development, habitat loss may

be a greater threat than either climate change or increased fire

• More frequent fires are bigger risk than less frequent fires

• Development reduces abundance but population trajectory stable


CNM Management Take

• Improve estimate of upper tail of CEVE survival

curves and seedbank attrition

• Specify CNM fire return history specific models to

guide risk assessment

• Run small experimental burns (assess and refine

model parameter estimates)

• Continue model assessment & refinement


Continuous Model-Data-

Management Integration

• Conclusions are no better than

the model

• Constant evaluation/updating to

ensure structure is good

• Monitoring to ensure parameter

estimates adequate

• Customize to target

particular questions

• Remember that a model is not

the real system


Acknowledgements

• DoD SERDP

• Dr. Helen Regan

• Dr. Janet Franklin

• Dr. Paul Zedler

• San Diego 2050

Project

• Resit Akçakaya

• Kim O’Connor

• Andrea Compton

• Stephen Phillips

• Jerre Stallcup

• Marti Whitter

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A model is an attempted simplification of reality

“Make everything as simple as

possible, but not simpler”

Albert Einstein

“All models are wrong, some models are useful.”

George Box

Select a model that provides a useful description or is good predictor

Good data needed

end

Models CEVE Models Utilization 25

Present Climate GFDL Prediction

2100

Suitable HabitatNot Suitable Habitat

PCM Prediction

2100

(151 populations) (85 populations) (29 populations)

Habitat Suitability Submodel

Considerations

• Difficult to quantify causal mechanisms.

• Species may not be at equilibrium with their environment.

• Limiting factors may change under different climate.

• Competitive interactions may change under different climate.

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