Conservation biology in practice: lessons from a...

1

Outline• Implementing single-population PVAs• Landscape models of habitat,

population structure, and persistence• Putting the pieces together for

management on the ground

Conservation biology in practice: lessons from a threatened fish

Cutthroat trout distribution-

Eight major subspeciesIn North America

*All listed under ESAor of “special concern”

Cutthroat trout distribution-

Eight major subspeciesIn North America

*All listed under ESAor of “special concern”

Lahontan cutthroat trout

Eastern Lahontan basin

Status

•Federally listed threatened species (1973)

•<15% of historical habitat occupied

•>20 populations gone since listing

Threats

•Habitat loss and fragmentation

•Nonnative trout

2

Goldfield Nevada, ca. 1900 Rawhide Nevada, 1908

Cattle drive Elko Co. 1940 Cattle grazing, Washoe Co. 1940

Habitat loss: “legacy” effects of past land uses Continuing land uses that affect habitat

Roads andculverts

Livestock grazing(Elko BLM photos)Altered fire regimes

Mining Agricultural and municipal water use

Nonnative trout

Photo credit: USFS

Photo credit: USFS

Photo credit: R.M. McDowallPhoto credit: Pam Fuller

Brook trout Rainbow trout

Brown trout Cutthroat trout

Management issues

•How do we identify populations at risk?

•Single-population PVAs•Landscape models of persistence•Developing a conservation assessment

Population viability analysis

A comprehensive analysis of the many environmental and demographic factors affecting the survival of a population, usually applied to small populations at risk of extinction.

Population viability analysis

A comprehensive analysis of the many environmental and demographic factors affecting the survival of a population, usually applied to small populations at risk of extinction.

What are the four main factorsthat cause extinctions in small populations?

3

PVA Model

GeneticsDemography

EnvironmentCatastrophe

PVA Model

GeneticsDemography


What data do we need for a PVA???

PVA Model

GeneticsDemography


A short list of possible things to know•Demography (age, stage, size…)

•Birth, death, maturity, fecundity, survival, etc.

•Relationships between demography and key drivers

•Intrinsic – density dependence, genetic factors•Extrinsic – environmental drivers, catastrophes

•Information on environmental variability•Models to relate the above and project dynamics

PVA Model

GeneticsDemography


What outputs do we want from a PVA?

PVA Model

GeneticsDemography


•What is the probability of persistence?•What is the minimum viable population size?•What factors are most important – model sensitivity?•What are the biggest sources of uncertainty?

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

1978

1979

1980

1981

1982

1983

1984

1985

1993

1994

1995

1996

1997

1998

1999

2000

Po

p S

ize

(Ag

es 1

+)

Developing a model for LCT(Chris Ray and Mary Peacock)

Total population trends in Gance Creek

4

0

50

100

150

200

250

300

350

1978 1979 1980 1981 1982 1983 1984 1985 1993 1994 1995 1996 1997 1998 1999 2000

1+ 2+ 3+ 4+ 5+ 6+

reduced (but sufficient) sampling effort

Dynamics among age classes A very simple population growth model(simple is better)

What factors drive recruitment and survival???

N1 N2 N3 N4

Recruitment

Survival

Potential recruitment models

fall t

winter t-1

fall t-1

summer t-1

spring t-1

summer t

spring t

(-) (+)

Which model is most

consistent with the data?

Predicting recruitment

R 2 = 0.64

P = 0.02

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 500 1000 1500 2000 2500 3000 3500 4000

combined flow* predictorRt ~ flowt-1 – flowt

(*flow = March-June average daily CFS)

recr

uit

s th

is y

ear

(Rt)

flow last year

recr

uit

s th

is y

ear

flow this year

recr

uit

s th

is y

ear

Potential recruitment models

fall t

winter t-1

fall t-1

summer t-1

spring t-1

summer t

spring t

(-) (+)

Best recruitment model

fall t

spring t-1

spring t

(-) (+)

Survival is density-dependent

R 2 = 0.48**

R 2 = 0.48**

R 2 = 0.50**

-4

-3

-2

-1

0

1

2

0 1000 2000 3000 4000 5000

number in age class

survivalln(n t+1 /n t+.01)

age 1-2 yrs

age 2-3 yrs

age 3-4 yrs

5

Spring Flowaverage daily CFSMarch 1 - June 30

Marys River

0

100

200

300

400

500

600

1940 1950 1960 1970 1980 1990 2000

N0

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0 500 1000 1500 2000 2500 3000 3500 4000

combined flow predictor

R0

N1

R2 = 0.48**

R2 = 0.48**

R2 = 0.50**-4

-3

-2

-1

0

1

2

0 1000 2000 3000 4000 5000number in class

S0

Projecting population dynamics

N1 N2 N3 N4

Survival = f (within-class density dependence)

# Age 1+ = f (stream discharge)

“Flow – density” model

Sensitivity AnalysisVariation in streamflows

basemodel

Foreman

Frazer

Gance

lowercapacity

lowerflows

higherflows

highervariancepop

> 5%

< 5%

< 1%

“risk”

Genetic bottlenecks and isolation(Helen Neville 2003)O R E G O NO R E G O N

II DD AA HH OOII DD AA HH OO

0 50 100 150 200 km0 50 100 150 200 km

NN EEVV AA DD AANN EEVV AA DD AA

ReeseReeseRiverRiver

CoyoteLake BasinCoyoteLake Basin

Walker LakeWalker LakeWalker RiverWalker River

Carson RiverCarson River

Lake TahoeLake Tahoe

HumboldtHumboldtRiverRiver

NNN

CALIFORNIACALIFORNIA

Truckee RiverTruckee River

Pyramid LakePyramid LakePyramid Lake

QuinnRiverQuinnQuinnRiverRiver

Summit LakeSummit Lake

Review• Factors affecting populations

– Small is not beautiful (but simple is)!• PVA simulations indicate loss of habitat is the largest

demographic risk• PVA inferences supported by evidence for genetic

bottlenecks or founder events in smaller isolated populations

• None of these places (so far) has nonnative trout…• And, none has been applied to more than a handful

of populations…

Zooming out to look at many populations – “landscape” models

• How to describe a “landscape” for trout?• How does landscape structure relate to

persistence?

6

Defining the fish-scape• Fish populations are not uniformly distributed

across the landscape

Defining the fish-scape• Fish populations are not uniformly distributed

across the landscape• Fish distributions usually tied to specific habitat

features – both are patchy – both can be mapped

A thermal bull trout - scape

Spawningand rearing(suitable year-round)

Migratory(seasonal use)

Unsuitable

Refugium

“Latitude” (UTM north X 10“Latitude” (UTM north X 1066))4.34.3 4.44.4 4.54.5 4.64.6 4.74.7

14001400

16001600

18001800

20002000

22002200

24002400

26002600

28002800

Ele

vati

on

(m

) o

f E

leva

tio

n (

m)

of

do

wn

stre

am

do

wn

stre

am

dis

trib

uti

on

lim

its

dis

trib

uti

on

lim

its

R2 = 0.67-0.71P < 0.001

Streams with Lahontancutthroat trout onlyn = 19 from UNR surveys

n = 11 from agency surveys

Fish distributions among streams on a regional scale

4.3 4.4 4.5 4.6 4.7

1400

1600

1800

2000

2200

2400

2600

2800

“Latitude” (UTM north X 106)

Ele

vati

on

(m

) o

f d

ow

nst

ream

d

istr

ibu

tio

n li

mit

s

Effects of nonnative trout

Baseline predictionfrom “allopatric” model

GIS“PATCH”

DELINEATION

= “Pour”point

7

Patch structure: Eastern Lahontan basin

Reese River sub-basin Patch networksand isolated patches

Patcheswithin networks

50 km

Defining Habitat Fragmentation

Patches = populations?

Within-patch

genetic structuring

(Neville 2003)

Patch area (ha)

103 104 105

0.00

0.25

0.50

0.75

1.00 Probability of occurrence

Habitat fragmentation and persistence of local populations

Few large, many very small

Patch area (ha)0 20000 40000 60000

0

20

40

60

80

100Percentage of patches

Var

ian

ce in

p

atch

qu

ality

Dispersal distanceInterpatch distance

Metapopulation dynamics – Key Factors

1) PATCH QUALITY (E.G. SIZE, PRODUCTIVITY)

2) PATCH ISOLATION

3) SPECIES’ DISPERSAL ABILITY

ISLAND-MAINLANDISLAND-MAINLAND

PATCHYPATCHYLEVINSLEVINSNON-EQUILIBRIUMNON-EQUILIBRIUM

8

Landscape-metapopulation perspectives

• Emerging work shows key linkages• Least understood scale in management

Fausch et al. (2002)“Riverscapes”

Number and condition of DPSsRegion

Number and condition of recovery units in a DPS

Subbasin

Number of patches, overall pattern of connectivity, distribution of conditions among patches

Patch network

Size, connectivity, distribution of conditions within patches

Patch

Temperature, channel features, etc.

SitePotential indicatorsScale

Patches = “intermediate” scale?

(Dunham et al. 2002)

Review• Habitat loss and fragmentation is a major

threat• Nonnative trout also appear to be important,

but influences are highly variable• Effects of habitat fragmentation are

predictable• Effects of nonnative trout less predictable

Research on the Ground!

• Nice pubs aren’t enough

• Scientists need to be directly involved

“Judging by one criterion, it is Extinct!”

“Judging by one criterion, it is Extinct!”

“But judging by another, it is alive and healthy in places!”

Management questions – space, time, location•Where are the biggest risks?•What are the threats?•What do we do about them?•Where and when to do it?•How do we use the best available science?

Lahontan cutthroat trout

Problem:

Many local populations and habitats, limited resources

Management alternatives:

Opportunistic approach:

Driven by available $$, stakeholder support

Strategic approach:

Driven by a conservation assessment toprioritize efforts

9

Conservation Assessments – Integratedanalysis of conservation units

AKA – putting the pieces together

The pieces:

1. Units – Conservation units can be delineatedusing genetic, demographic or ecologicalinformation.

2. Risks – The risk of extinction in a unit must be assessed (e.g., as indicated by probability of occurrence, PVA, etc.).

3. Threats – What specific factors contribute most to risks within each unit?

The pieces:

1. Units – Defined by landscape models: Patches

2. Risks – Defined by model of occurrence, with corroboration from local PVA and genetic analyses

3. Threats – Defined by studies of LCT distributions and influences of nonnatives

Conservation Assessment

Is the habitat isolated?

Are nonnatives sympatric?

Is the fish distribution limited

by habitat?

Is the habitat large?

Is the distribution limited by

nonnatives?


Are nonnatives present?

Are nonnatives hybridizing?


ReintroductionsNonnativesHabitat loss

Unoccupied Unoccupied patchespatches

Patches occupied by Patches occupied by cutthroat troutcutthroat trout


Are nonnatives sympatric?

Is the fish distribution limited

by habitat?


Is the distribution limited by

nonnatives?


Are nonnatives present?

Are nonnatives hybridizing?


ReintroductionsNonnativesHabitat loss

Unoccupied Unoccupied patchespatches

Patches occupied by Patches occupied by cutthroat troutcutthroat trout

Assessing management actions relative to potential threats Threat Classification: Example

Occupied patches Unoccupied

Reintroductionpotential

NonnativesHabitat

Classification/ranking of threats

- ID general management options, recovery activities

-Spatially explicit classification of recovery activities

-Importance of location

Why do we need a spatially explicit classification of recovery activities?

…Because – Improvements in recovery activities may not come from changing what we are doing, but where we are doing it.

10

Prioritization: Importance of space

Biological perspective

LocalLocal

Subwatershed

Local-stream

Subbasin

Lahontan basin

Po

pu

lati

on

Rec

ove

ry u

nit

ES

U -

DP

S

Sp

ecie

s

Management perspective Strategic management:

Perspectives from a conservation assessment -

How do priorities compare to existing efforts?

Are we addressing the right threats in the right places?

Are we saving individuals or populations but losing the species?

Is management being driven by opportunities, priorities, or both?

Getting closer to the ground:Addressing threats within patches

Habitat loss

SourcesLivestock grazing

RoadsAgriculture

MiningEtc.

ResponsesTemperature

SedimentRiparianChannel

Etc.

What to manage? What to manage? What to measure? What to measure?

What is theproblem? What is theproblem?

Implementation

Assessment

?

Lessons Learned• Good conservation science:

– Identifies appropriate scales for applications– Addresses what we can do something about– Follows the KISS principle without sacrificing

rigor or reality– Produces operational results

• Reprints alone ? conservation biology– People on the ground need your expertise!

Where do barriers pose the biggest threats?

Effects of small dams on persistence of white-spotted charr(Morita and Yamamoto 2002)

Salvelinus leucomaenis

1.0

0.75

0.50

0.25

00.1 1.0 10.0

3 years

10

20

4050

30

1.0

0.75

0.50

0.25

00.1 1.0 10.0

3 years

10

20

4050

30

Prob

abili

ty o

f oc

curr

ence

Basin area (km2)

Persistence: a matter of space and time

11

Will connectivity restoration allow nonnative invasions?

Conservation biology in practice: lessons from a...

Documents

Transcript of Conservation biology in practice: lessons from a...