EI Monitoring – Science Challenges

EI Monitoring – Science Challenges

Condition MonitoringMonitoring conducted over the whole park in the

long term to detect major trends in park EI - “What is the state of park EI?”

Monitoring conducted over small areas to assess the effectiveness of specific park management actions –

“What are we doing to improve park EI?”

Management Effectiveness Monitoring

Common Issues/Common Solutions

Generally the same elements are missing in almost all park monitoring programs

Permanent, long term monitoring of ecosystem process

measures at local and landscape scales

conceptual ecosystem models linking EI components

(biodiversity, processes, stressors) for major park

ecosystems to EI Measures and Indicators

‘final suite’ of EI measures

management targets and thresholds for EI Measures

assessment methodologies for EI Indicators

Given the same missing program elements we can work together to develop

common solutions to park EI monitoring and reporting

issues

Science Challenges

1. How do we ‘capture EI’?

2. What do we measure?

3. What do our measurements mean?

4. Communicate!!!

‘Capturing EI’

• EI monitoring framework

• major park ecosystems as EI indicators

• core conceptual ecosystem models

• local and landscape scales of measurement

Ecosystem Realms and Major Park Ecosystems

UPLANDS

FRESHWATERMARINE

COASTAL

WETLANDS

inter-tidalsub-tidalnear-shore pelagic

forests/woodlandsarctic/alpine tundragrasslandsother non-forested

rivers/streamslakes/ponds

beachesdunescliffs

lagoons

riparian,wetlands

estuaries

*MPEs for Great Lakes Bioregion

Science environment

Public environment

feedback biodiversity/processes

human dimension

stressors

EI Indicator

measures/data

statistics

models

EI Impaired High EI

Concerned

major park ecosystems

The North Pacific Coastal

Interior Plains

Great Lakes

Quebec Atlantic

Montane Cordillera

n

Forest Forests and

woodlands

Forest Forest Forest Terrestrial

Ecosystems

Tundra Non-forest Grasslands Non-forest ‘Barrens’

Wetlands Lakes and

wetlands

Wetlands Wetlands Wetlands Aquatic

Ecosystems

Freshwater Streams and

rivers

Lakes Lakes Freshwater

(Lakes)

Native

Biodiversity

Glaciers Islets/

shorelines

Streams Streams Freshwater

(Streams)

Geology and

landscapes

Coastal Inter-tidal Great Lakes

Shore

Coast Climate and

atmosphere

Marine Sub-tidal Marine support for EI

EI INDICATORS by BIOREGION

Species richness- change in species richness*- numbers and extent of exotics*

Population Dynamics- mortality/natility rates of indicator species*- immigration/emigration of indicator species*- population viability of indicator species*

Trophic structure- size class distribution of all taxa-predation levels

Succession/retrogression- disturbance frequencies and size (fire. insects, flooding)*- vegetation age class distributions*

Productivity- landscape or by site

Decomposition-by site

Nutrient retention-Ca, N by site

Human land-use patterns- land use maps, roads densities, population densities.*

Habitat fragmentation- patch size, inter-patch distance, forest interior*

Pollutants*- sewage, petrochemicals etc.- long-range transport of toxics

Climate*- weather data- frequency of extreme events

Other*-park specific issues

Biodiversity Process and Function Stressors

Ecological Integrity Monitoring Framework

Ecologically Comprehensive

Forests

Wetlands

Lakes

Streams

‘Barrens’

Coastal

Marine

EI INDICATOR* Biodiversity

Processes Stressors

EI FRAMEWORK

√

√

√

√

√ √

√

√

√√

√

√

√

√

√

√

√

√

√ √ √

* EI indicators for Atlantic-Quebec Bioregion

Data

Stand Level Forest EI

Landscape Level Forest EI

tree productivity, songbird index, salamander populations change, foliar nutrient index, decomposition efficiency

dbh, canopy condition, species composition, chopstick dry weight loss, songbird/salamander density, relative soil arthropod abundance, foliar nutrient concentrations

FF BioD Index (SAR, top predators, ungulates), CFBioD Index (ecosystem representation), connectivity, productivity

Forest EI Indicator

SAR and other species population assessments, relative ecosystem abundance, Fragstats, AVHRR

Models

Measures

Critical

Concerned

Healthy

trampling/disturbance

vegetationvegetation

mineral soilmineral soil

soil humussoil humus

herbivoresherbivores

carnivorescarnivores

predationpredation

nutrient/moisturenutrient/moistureuptakeuptake

decompositiondecomposition

herbivoryherbivory

Core Bioregional Forest Stand Model

climateclimatechangechange

acid deposition

hyper-abundant ungulates

climatechange

Core Bioregional Forest Landscape Model

acid deposition

huntingtrapping

spatial character, compositionspatial character, composition and productivity of and productivity of forest communitiesforest communities

distribution and character of distribution and character of park park landformslandforms (floodplains, (floodplains,

moraines, karst, organics, avalanchemoraines, karst, organics, avalanchetracks, glaciers, glacial outwash) tracks, glaciers, glacial outwash)

size, vigour and genetic diversitysize, vigour and genetic diversity of of focal herbivorefocal herbivore populations populations

size, vigour and genetic diversitysize, vigour and genetic diversity of of focal carnivorefocal carnivore populations populations

predation

landformprocesses

herbivoryhabitat effects

disturbanc

e

Roles of Ecosystem Conceptual Models

• reduce ecosystem complexity: essential components of biodiversity, processes and stressors (EI) to prioritize monitoring measures; organize protocols and measures

• COMMUNICATE approach and results:

science peers inside and outside parks

park managers, interpreters etc

all Canadians

• improve EI assessments: conceptually related and co-located measures (long term plot data) provides internal logic

• incorporate other park management activities: ecological frame for including restoration, infrastructure changes, visitor changes, operational changes, etc

Data






Forest EI Indicator


Models

Measures

Critical

Concerned

Healthy

Conceptual Model – Streams

benthic macroinvertebratesriparian vegetation

periphyton

fishamphibians

flows/temperature/water chemistry/

nutrients

macrophytes

CWD,habitat structure/

channel stability

predationfiltering

light/heat

allochthonous inputs

herbivory

climate change

riparian disturbance

human effects (fishing, invasive aliens, pollution)

riparian condition

benthic invertebrate

index

water flows,water quality

water temperature

fish diversity index

periphytonindex

Reporting Park EI

Forests Wetlands Lakes Streams Marine

SOP synopsis (indicators)

science foundation (measurements and models)

6-8 EI Indicators

Coastal

• given the vast number of things we could measure, what do we measure?

• PSOCLCIEIMs – the Holy Grail

• measuring the park – study designs

What to Measure and How to Measure it?

The Holy Grail

To find a parsimonious suite of co-located, ecologically inter-

related EI measures that provide a comprehensive summary of

park forest EI at an acceptable financial and human resources

cost

Data






Forest EI Indicator


Models

Measures

Critical

Concerned

Healthy

Selecting Measures

• cost-effective, information-rich, low signal to noise

• credible – supported by science community/research

• feasible to measure (technical field staff); ‘same day suites’

• comes with a ‘story’, e.g., soil arthropods?

• works well as part of a ecologically-integrated suite that covers conceptual model components

• shared by monitoring partners (provinces/territories, communities, model forests, industry)

Ecosystem Componen

tEcosystem

Process

Ecosystem Stressor Proposed

Measures

soil humus

mineral soil

vegetation

herbivores

carnivores

soil mineral

weathering

humus decomposition

nutrient uptake

plant productivity

plant recruitment

plant mortality

herbivory

predation

acid deposition

climate change

air pollution

trampling

harvesting

invasive aliens

1. soil

decomposition

index

2. foliar nutrient

concentrations

3. vegetation plot

data

4. forest songbirds

5. forest

salamanders

6. soil arthropods

7. arboreal lichens

FOREST STANDS

trampling/disturbance






predationpredation



herbivoryherbivory

Core Bioregional Forest Stand Model


acid deposition

hyper-abundant ungulatesForest vegetation plot: DBH/height

increment of stand dominants; native/alien species diversity, tree canopy condition; tree recruitment and mortality, browse, arboreal lichens,

epidemic insect outbreaks

(epidemics/5years)

foliar nutrient concentrations (N, P, K, Ca, Mg)

forest songbird guild densitiesforest salamander densities

% dry weight loss of soil

decomposition standard

relative abundance of indicator soil arthropods

Ecosystem Component

Ecosystem Process/Functio

n

Ecosystem Stressor

Proposed

Measures

• landforms/soils

• forest

communities

• large

herbivores

• large

carnivores

• landscape connectivity

• interior forest function

• landscape level

productivity

• coarse filter

biodiversity

• fine filter biodiversity

• stand-replacing

disturbance

• landform processes

(flooding and

sedimentation, coastal

erosion, permafrost

depth)

• climate change

• acid deposition

• other pollutants

• park

infrastructure

• visitor effects

• harvesting

• invasive aliens

• GPE effects

fragmentation

metrics

• ecosystem

productivity

• habitat suitability

and population

viabilities of

managed species

• ecosystem

representation

• phenological

observations

• invasive alien index

• landform changes

FOREST LANDSCAPES

climatechange

Core Bioregional Forest Landscape Model

acid deposition

human effects

spatial character, compositionspatial character, composition and productivity of forest communitiesand productivity of forest communities

distribution and character of distribution and character of park landforms (floodplains,park landforms (floodplains,

moraines, karst, organics, avalanchemoraines, karst, organics, avalanchetracks, glaciers, glacial outwash) tracks, glaciers, glacial outwash)

size, vigour and genetic diversitysize, vigour and genetic diversity of focal herbivore populationsof focal herbivore populations

size, vigour and genetic diversitysize, vigour and genetic diversity of focal carnivore populationsof focal carnivore populations

predation

landformprocesses

herbivoryhabitat effects

disturbanc

e

change analysis (fragmentation, focal species habitat suitability, ecosystem representation), productivity, phenology, alien species

focal ungulate populations (moose, deer. caribou, hare)

focal predator populations (bear, wolf, coyote, fox)

glacier changes, flooding regimes,ice processes, avalanche rates

Establishing Long Term Monitoring

General Rules1. For all EI indicators data on biodiversity, processes

and stressors should be collected at 2 scales – local and landscape

Representative local ecosystems of the major park

ecosystem (forest stands, eelgrass beds, stream

reaches, kelp beds, wetland types) need to be

selected for measurement based on available

resources, park management priorities and

bioregional approaches

Whole park and greater park measures and assessments of

indicators based on EO/RS – GIS data

Changes in Forest Site - Spatial Variability

Changes in Forest Structure – Temporal Variability

Forest Site

SMR/SNR

Shru

b

Herb

Young

Forest

Mature

Forest Old Forest

dry outcrops;

coarse soils

dry/poor 0 0 5 0

coarse-

textured tills,

mors

mesic/poor 1 5 0 5

medium-

textured tills,

mors

mesic/

medium

5 5 25 5

medium-

textured tills

with seepage,

moders

moist/rich 1 1 15 2

Bogs wet/poor 0 0 5 15Swamps wet/rich 0 0 0 5

FOREST ECOSYSTEM REPRESENTATION

Selecting ‘Representative Ecosystems’

• average (mesic) ecosystems• most abundant ecosystems• ecosystems with high conservation importance • ecosystems most sensitive to known stressors

base poor ecosystems susceptible to acid rain

droughty ecosystems where prolonged summer drought is forecast

N

EW

S

50m

= Bird sample point

= Salamander board

= Vegetation plot

= Potential vegetation plot

Legend

5m

Arthropod traps

veg plot

decay sticks

salamanders

soil insects

foliar nutrientsdefoliators

songbirds

A CO-LOCATED, ECOLOGICALLY INTER-RELATED SUITE OF LOCAL FOREST EI

MEASURES

Data






Forest EI Indicator


Models

Measures

Critical

Concerned

Healthy

• What’s the question?

• What’s the answer?

• Developing targets and thresholds.

Targets and Thresholds

“What is the state of park EI?”

The question is………….

aciddeposition

climatechange

Humus Decomposition Sub-model

soil biota interactio

ns and processes

Dry Weight Loss of Wood Decomposition Standard

rate of humus decomposition(percent dry weight loss)

heat/moisture vertebrate predators

condition of litter inputs

nutrient availability/uptakefoliar nutrient contentplant productivityplant vigourpests and pathogensherbivore/predator effects

Ecological Effects

Targets, Baselines and Thresholds

42

Dry Weight Loss of Wood Decomposition Standard

(percent dry weight loss)

High EI concerned EI Impaired

target

confidence interval

62

30 20

thresholds

baseline (mean)

82

‘precautionary principle’

Mean percent weight loss of tongue depressors(in ground) within varying sites.

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

0 1 2 3 4 5 6

site no.

mea

n %

wei

ght l

oss

(+/-

80%

C.I.

)

Site 1Landform: beach sandsSoil: O.DYB moderately coarse, rapidly drainedVeg Comm: Red Oak / Trembling AspenStand Origin: fire

Site 5Landform: glacio-marineSoil – O.GL; very fine, poorly drainedVeg Comm: White Cedar / Balsam FirStand Origin: natural

Establishing Targets and ThresholdsSoil Decomposition

Clear Monitoring QuestionsH01: local scale (stand level) forest ecological integrity

has not changed significantly over the last 5 years in mature eastern hemlock ecosystems in Kejimkujik NPH01.1: soil humus decomposition has not changed more

than 35%

H01.2: forest salamander population densities have not

decreased more than 12%

H01.3: foliar N concentrations have not decreased more

than 0.5% foliar dry weight

etc

Bacteria and fungi in the soil humus decompose the tree

litter, making nutrients available for plant growth

Tree needles,

leaves, and branches fall to the

forest floor

Trees take up nutrients from the

soil enhancing growth and

delivering nutrients back to the ecosystem

Communicating EI Monitoring

To monitor changes in nutrient cycling, we

monitor soil decomposition using

buried tongue depressors and measuring weight loss of the wood as an

index of soil decomposition function

Nutrient Cycling

• most parks are not ‘natural’ and have had historical impacts that require management/restoration

• active landscape management is required to meet park conservation needs – prescribed burning, ecosystem restoration, species re-introductions, alien invasives

• management activities require performance reporting targets to assess progress towards desired goals; landscape targets will be set against patterns of natural successions and disturbance

• ‘Desired condition’ targets for terrestrial landscapes need to be based on ‘desired conservation services’ the landscape can realistically provide

‘Desired Condition’ forForest Landscapes: Rationale

‘Desired Condition’ forForest Landscapes: Conservation

Services • Habitat suitability: for focal species, e.g., charismatic, major park

ungulates and carnivores, indicators, keystones, species at risk

• Ecosystem representation: rare ecosystems, old forests, structural stage targets

• Landscape productivity: within historical range of productivity as measured by NDVI or NPP

• Landscape pattern: desired states for connectivity/fragmentation

• Landscape processes: ice features (permafrost, thermokarst, solifluction etc), flooding regimes, mass wasting rates,

• Operational and safety needs: fire/fuel management, RoWs, roads and visitor access/use, harvesting

0

5

10

15

% Park Forest Area

Ecosite

Regen

Pole

Young

Mature

OldTime 1

0

5

10

15

% Park Forest Area

Ecosite

Regen

Pole

Young

Mature

Old

Desired Landscape Condition

02468

1012

% Park Forest Area

Ecosite

Regen

Pole

Young

Mature

OldTime 2

EI Assessment of EI Assessment of Change Analysis Change Analysis

DataData

Hypothesis Testing/Monitoring Questions

H01: landscape scale forest ecological integrity has not changed significantly over the last 5 years in Kejimkujik NPH01.1: fragstat index target

H01.2: forest ecosystem representation target

H01.3: white tailed deer density is between 0.25 and 0.75

animals/ha

H01.4: cow:calf ratio in white tailed deer is greater than 1.2

H01.5: NPP of forest landscapes is between ? and ?

etc

EI Assessments

• What is the state of park EI?

• How to defensibly Integrate and assess monitoring results to report the state of the park?

• IBI approaches – stress gradients

• ‘Internal logic’ / rule systems based on conceptual ecosystem models

Bruce Peninsula National Park

Stress Gradients

Bruce Peninsula National Park

1 3 5salamanderabundance

forest birdrichness

effectivepatch size

decomposition

regeneration(height class)

productivity(NDVI)

lichendiversity

crownvigor

fragmentation(ENN)

BIODIVERSITY

PROCESSES

STRESSORS

0 45

0 22

0.2 78.4

11% 89%

0 13

0.1 0.9

14 35

0%20%

50250

15 30

7.3 14.6

26.3 52.6

37% 63%

10% 5%

3 6

0.4 0.7

21 28

117184

- Rocky Bay = 39- Pendall Point = 25

Measures to Indicators Simple Roll Up

Measures to Indicators Simple Roll Up

42 - Shouldice Lake

25 - Pendall Point

27 - Fathom Five Landbase

34 - Cameron Lake Dunes

30 - Horse Lake Trail

22 - South Cameron Lake

39 - Rocky Bay

29 - Emmett Lake

Site Comparison

9 4521 33

bootstrapped percentiles from across monitoring stations

Forest Indicator = 31 (±2.4)

graphical & numericalrepresentation

but close to






predationpredation



herbivoryherbivory


humanhuman effectseffects

LTEMPs

humus decompositionsoil arthropods

foliar nutrients

growth/health of stand dominants

species diversity/dominance/abundance

ingress/mortality

EMAN

plot data

epidemic insect outbreaks

forest salamandersforest songbirds

What an excellent

monitoring measure – a top predator and one of a conceptually inter-related

suite of measures to assess aquatic ecosystem EI

That man is so cool –

he’s monitoring

EI

The Day Monitoring Became Cool

Documents

EI Monitoring – Science Challenges