The Multiple Species Inventory and Monitoring
Protocol
A Monitoring Solution for National Forest System
lands and the Nation Patricia N. Manley, Ph.D and Bea Van Horne,
Ph.D.USDA Forest Service
Research and Development
International Monitoring Science and Technology Symposium
September 2004
Growing Need for Biodiversity
Conservation and MonitoringJohannesburg Earth Summit (2002) highlighted
increasing sustainability challenges driven by population growth
Recent ecoregional assessments in the US document a large proportion of all vertebrate species are of concern and interest• Columbia River Basin – 37% • Sierra Nevada – 46% • Southern California – 38% • Southern Appalachian Mtns – 29%
Monitoring ShortfallsGAO (1997) reports that monitoring has historically
been given low priority by the US Forest Service - not unlike many public land management agencies
Primary reasons for inadequate monitoring traced to the lack of….•clear objectives•specified sampling design•standardized monitoring protocols•commitment to funding
MSIM Objectives
Nationally consistent protocol to provide spatially and temporally coincident data on an extensive array of vertebrate and plant species and their habitats across a broad scale in time and space
Data to be used to meet monitoring obligations and information needs to support Land Management Planning, regional assessments, and national assessments (e.g., RPA)
National FrameworkCo-located with US Forest Inventory and
Analysis grid – exists on all land ownerships
National FrameworkCo-located with US Forest Inventory and
Analysis grid – exists on all land ownerships Set of primary survey methods are specified
that are standardized, commonly employed methods selected to detect a broad spectrum of plant and animal species
National FrameworkCo-located with US Forest Inventory and
Analysis grid – exists on all land ownerships Set of primary survey methods are specified
that are standardized, commonly employed methods selected to detect a broad spectrum of plant and animal species
Presence data are the target for population monitoring, but many methods yield more information (abundance, population structure)
National FrameworkCo-located with US Forest Inventory and
Analysis grid – exists on all land ownerships Set of primary survey methods are specified
that are standardized, commonly employed methods selected to detect a broad spectrum of plant and animal species
Presence data are the target for population monitoring, but many methods yield more information (abundance, population structure)
Regional scale design and implementation (survey methods, sample size, grid density, resample frequency)
FIA Grid Hexagonal grid across entire country 2400 ha cell size – one monitoring
point/cell
Primary Survey Methods:
Birds
Method Target taxa CorePoint counts Song birds,
woodpeckersX
Nocturnal broadcast surveys
Nocturnal birds
Primary Survey Methods:Mammals
Method Target taxa CoreSherman live trapping
Small-bodied mammals
X
Track stations with cameras
Medium to large omnivores-carnivores
Bat mistnetting Bats
Primary Survey Methods:
Amphibians and Reptiles
Method Target taxa CoreVisual searches Amphibians and
reptiles (and other vertebrates)
X
Aquatic surveys Amphibians and reptiles (and other vertebrates)
Primary Survey Methods:
Vascular Plants
Method Target taxa CoreQuadrats
(as per FIA)
Herbaceous plants (sp, cover)
X
Subplots
(as per FIA)
Woody plants (sp, cover, density)
X
Transects All plants (sp, freq, vertical structure)
X
N
Meadow
Lake
Riparian
Conifer forest
Small pondTrack stations Monitoring point
Bat mist nets
Live trappingBird point counts
Pitfalls
Plant surveys
Aq. vert. surveys
Note: not to scale.
Habitat measures
Augmented Serially Alternating Panel (ASAP) Design
* =50 PSUs .= 0 PSUs x=50 PSUs 250 independent PSUs
Year 1 2 3 4 5 6 7 8 9 10 Panel 1 X . . . X . . .
X . 2 . X . . . X . . . X 3 . . X . . . X . . . 4 . . . X . . . X . . 5 X X X X X X X X X X
100 100 100 100 100 100 100 100 100 100
Effort: 100 PSUs visited per year
We asked the question…If we implemented 10 primary
survey methodsAt each FIA grid point on federal lands
in the Sierra Nevada, andBased on estimates of the number of points in
each species range and their probability of detection with the 10 protocols, then
Which species would we expect to observe at enough points to detect > 20% relative change between two time periods with 80% confidence and power?
MSIM Simulated Implementation
Over 70% of all vertebrate species were predicted to be observed frequently enough to detect a 20% change
Species represented a balance of life history characteristics, habitat associations, and species of concern and interest
MSIM Predicted Effectiveness
Manley et al. 2004Ecological Applications
California
FIA hexagon clusters
Lake Tahoe
Sierra Nevada Pilot Study
California
Sierra Nevada
FIA hexagon clusters
Lake Tahoe
Evaluate effectiveness of survey methods• Species expected present vs. detected• Detection probabilities
Evaluate sampling efficiency per point• Number of sites• Number of visits per site
Evaluate trend detection capabilityCost, feasibility, sampling options
Pilot Test Objectives
Preliminary Pilot Results
Species DetectionsGroup All
speciesFocal MIS SOC
Birds 48% 58% 50% 40%
Mammals 64% 56% 50% 63%
Amphibians 75% 80% - -
Reptiles 67% 67% - -
Overall 52%151 of 290
58%74 of 127
50%4 of 8
46%
11 of 24
Survey Effort Evaluation
0
1
2
3
4
5
6
0 1 2 3 4
Number of Visits
Sp
ecie
s A
ccu
mu
late
d
1 Site
2 Sites
3 Sites
Power AnalysisP1=.5, n=328, m=263, S 1=2, S2=2,
0.0 0.1 0.2 0.3 0.4 0.5
Change from P11
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Sim
ula
ted
Po
wer
0.50.30.2
Detection probability
Baldwin and King in prep
Potential Yields from MSIM
MonitoringAt the scale of most national forests For other land allocations of interest, such as
wilderness For hundreds of species of plants and animals
• Proportion of points occupied• Spatial distribution and site occupancy • Estimates of abundance for land birds, small
mammals, and plants• Measures of population structure (age ratio, sex
ratio, reproduction)
Potential Yields from MSIM
Scientific Discovery Environmental thresholds for populations Community structure and dynamics under
a wide variety of environmental conditions Models of suitable habitat at site and
landscape scales for many species Indicators and direct measures of
sustainability derived from empirical data
