Download - 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
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* 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
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
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
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
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
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 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
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
• 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
vegetationvegetation
mineral soilmineral soil
soil humussoil humus
herbivoresherbivores
carnivorescarnivores
predationpredation
nutrient/moisturenutrient/moistureuptakeuptake
decompositiondecomposition
herbivoryherbivory
climateclimatechangechange
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