great plains landscape conservation cooperative monitoring grid

Conserving Birds & Their Habitats

Great Plains Landscape Conservation Cooperative Monitoring Grid

Rob Sparks and David Hanni

Conserving birds and their habitats.

Presentation Outline

• Current RMBO monitoring programs

• GPLCC standardized grid

• GPLCC landbird monitoring strata

• Conservation products


Guidelines for Avian Monitoring

Goal 1: Integrate monitoring into bird management and conservation practices.

Goal 2: Coordinate monitoring programs among organizations and integrate them across spatial scales.

Goal 3: Increase the value of monitoring information by improving statistical design.

Goal 4: Maintain bird population monitoring data in modern data management systems.

http://www.nabci-us.org/aboutnabci/monitoringreportfinal0307.pdf


Our Objectives

1) Provide a design framework to integrate bird monitoring efforts

2) Precisely estimate distribution, density, site occupancy, population trends and species richness

3) Provide habitat association data relevant to landscape changes

4) Maintain a high-quality database, accessible online

5) Create decision support tools to help guide conservation efforts


Bird Conservation Regions


Current Monitoring Programs

All lands in BCR 17

All lands in CO, WY and MT

Portions of 9 additional states

All BLM lands in: CO, WY, MT, ND, SD

All USFS lands in Regions 1 & 2 (CO, WY, NE, KS, SD, ND, ID, MT)

3 National Forests in Region 3(Kaibab, Coconino, Prescott)


2010 Landbird Monitoring


Colorado Division of WildlifeWyoming Game and Fish DepartmentMontana Fish, Wildlife and ParksSouth Dakota Game, Fish and ParksUSFS: 27 National Forests, 9 National

Grasslands, 4 regions, 12 statesBLM in 5 statesNational Park Service…(continued)

Current Partnerships


Northern Great Plains Joint VentureAudubon WyomingWyoming Natural Diversity DatabaseMontana Natural Heritage ProgramIdaho Bird ObservatoryAvian Science CenterGreat Plains Landscape Conservation

Cooperative

Current Partnerships (cont.)


Sampling Design and Methods

• Sampling Frame• Sampling Units• Sample Selection• Sample Allocation (effort)• Sampling Methods


Sampling Frame: BCRs


Sampling Units

1 km2 cell

Step 1: Overlay grid on sampling frame

Step 2: Attribute each cell with pertinent data (unique ID, spatial location, land ownership, elevation, soil type, …)


Sample Selection

Spatially Balanced: Generalized Random Tessellation Stratification (GRTS)

Ensures a spatially balanced distribution of samples within each stratum

~ Random

Analyses can incorporate spatial information in estimation of sampling variance


• Minimum of 2 samples required/stratum Recommend 10

• Determined by funding partners• May vary annually

Sample Allocation


Example: Base Sample in BCR 18


Additional Samples in Colorado


Additional Samples - Comanche NG


Sampling methods

• 16 points per cell 250 m spacing 125 m from edge

• 6 minute point count 1 minute intervals

• Record distance to each bird seen or heard

• Record species and sex for each observation


Questions?

Jeff Jones


GPLCC Monitoring Grid Objectives

• Create a standardized monitoring grid• USNG or MGRS

• Develop long term bird monitoring strata for GPLCC• Grid attributes

• Select samples• Spatially balanced sampling

– GRTS function in R


Great Plains LCC

Landscape Conservation Cooperatives (LCCs)

• Science-based Partnerships

• Help guide and coordinate conservation efforts at regional levels

• Great Plains LCC consists of BCRs 18 & 19


GPLCC Monitoring Grid

• The need for a monitoring framework at the regional level• Spatial context for statistical inferences and

predictions

• USNG Monitoring Grid• Biologists can use grid to monitor a variety of taxa at

multiple scales• Key grid elements: spatial extent, datum/projection,

scalability, standards


US National Grid (USNG)

• USNG identified as a potential standard for monitoring populations at regional levels

• Developed by FGDC for emergency response coordination

• 1-km square grid cells

• Contains key elements for a proper monitoring grid (national coverage, commonly used datum/projection, scalable)


USNG (cont.)

• Based on the NAD 83 geographic coordinate system• Universal Transverse Mercator (UTM)

projection• Similar to the Military Grid Reference

System (MGRS)• MGRS uses WGS 84 datum

• Covers the entire United States• MGRS worldwide coverage


USNG Scalability• The unique addressing system for the USNG allows

scalability from 100,000-km square to 1-m square. • Labeling system

– UTM Zone Designation. – 100,000-meter square designation– USNG: unique grid coordinates for a 1-km square

• Eastings/Northings

• Each 1-kilometer square grid cell has a spatial address (e.g. 13TGF3437)– Grid zone designator (13T)– 100,000-meter square identification (GF)– Unique grid coordinates (3437)/Eastings (34), Northings (37)


USNG Issues

• Zipper effect: Cells along UTM zone junctions are smaller than 1-km square. • Only affects 0.33% of grid cells in GPLCC• Causes sampling problems; may bias estimates• Many possible solutions

– Remove zipper cells– Merge zipper cells to adjacent cells– Overlap zone junction cells


Zipper Effect


Zipper Effect Solution: Merge Cells

• Merged cells smaller than 0.95-km square into their adjacent cells• Equal probability of being

selected• No gaps or overlap• If selected for sampling, a 1-

km square will be randomly placed inside cell


Grid Attribution

• We used GIS to attribute GPLCC grid• NRCS Soils

• NRCS Major Land Resource Areas (ecoregions)

• Federally owned or managed lands

• National Hydrography Dataset (NHD) Strahler order

• USFS proclaimed boundaries

• Nebraska: Biologically Unique Landscapes

• Priority Conservation Areas


Final Product

• ArcGIS geodatabase• Grid datasets established by UTM zone, State,

and BCR–Location of cell centroid

• Naming convention:“STATE_USNG_UTMxx_BCRxx”

Example: CO_USNG_UTM13_BCR18


Benefits of a standardized grid

• Same starting point• Spatial continuity across different projects

• Decrease project costs, necessary labor, and duplicate sampling efforts• No need to create multiple grids for multiple

projects


Benefits (Cont.)

• Should improve partnership coordination at the landscape and local level to accomplish shared conservation goals (ABC and NBII)

• Can also be used for other monitoring programs• FLAM surveys across western US• Bat surveys USFS• Grouse Surveys CDOW


Stratification Development

Stratification should be defined by areas to which we want to make inferences

Strata are based on fixed attributes • Federal/state land ownership• Elevation, latitude, soil type, ecoregion

All vegetation types available for sampling

Flexible: Each state within the BCR and each BCR within a state can be stratified differently (depending on local needs)


GPLCC Stratification

Strata based on GIS layers:• NRCS Ecoregions • Soils• Federal Land Ownership• Rivers (Strahler order)• Biologically Unique

Landscapes (NE)• Priority Conservation Areas


NE BCR 18 Strata

• Pine Ridge BUL• Wildcat Hills BUL• Niobrara River• Oglala N.G• Agate Fossil Beds

N.M


NE BCR 19 Strata

• Rainwater Basin• Loess Uplands

Ecoregion• Niobrara River• Nebraska Sand

Hills Ecoregion• Rolling Plains and

Breaks Ecoregion• Crescent Lake,

Valentine NWR


WY BCR 18 Strata

• BLM lands• DOD lands• All other lands


NM BCR 18 Strata

• Soils• Alfisols• Aridosols• Entisols• Inceptisols• Mollisols• Vertisols• Rock Outcrop

• Rivers


KS BCR 18 Strata


• Central High Tableland Ecoregion

• Cimarron N.G• Rivers


KS BCR 19 Strata


• Rivers• All Other


CO BCR 18 Strata

• Pawnee N.G• Comanche N.G• DOD lands• North of Platte R. • Platte River• Platte R. to I-70• I-70 to Arkansas R. • Arkansas River• South of Arkansas

River


OK BCR 18 Strata

• Southern High Plains Northern Part Ecoregion (Private lands)

• Rita Blanca N.G.• Rivers


OK BCR 19 Strata• Black Kettle N.G.• Ecoregions:

North Cross Timbers

Central Rolling Red Plains

Southern High Plains & Breaks

Central Rolling Red Prairies

Wichita Mtns• Rivers• USFWS


TX BCR 18 Strata

• Rita Blanca N.G.• Ecoregions:

Southern High Plains N. Part

Southern High Plains S. Part

Edwards PlateauSouthern Desertic

Basins• Rivers• USFWS


Integrating USNG Grids

• USFWS lands• Muleshoe National Wildlife Refuge

– 250 meter USNG grids nesting in the 1km grids– Repeat visits– Same methods


Muleshoe National Wildlife Refuge


TX BCR 19 Strata

• Ecoregions:

Southern High Plains Breaks

Central Rolling Plains Red Prairies

Central Rolling Plains W. Part

Edwards Plateau• Rivers


• Collaboration• Shared costs among partners• Handles fluctuating funding• Ability to compare bird trend to habitat trend• Ability to compare local to regional results• Flexibility in stratification• All vegetation types available for sampling• Can be (is) used for other taxa

Benefits of Integrated Monitoring


Questions?

Bill Schmoker


Conservation products

• Density/Occupancy estimates• BCR/State level• Stratum level

• Habitat occupancies at multiple scales• Brewer’s Sparrow

• Maxent modeling• Grasshopper Sparrow• Chestnut-collared Longspur


Analytical methods

Estimate detection probability and density• Distance sampling (Buckland et al. 2001)

• Removal sampling (Farnsworth et al. 2002)

Estimate detection probability and occupancy rate

• Combined Removal and Occupancy modeling (Pavlacky et al. in press)

Habitat modeling


Results: Density and Abundance

Example: Brewer’s Sparrow

D N %CV n

Pawnee N.G 12.22 213,801 31 84

Comanche N.G 6.78 32,811 71 8

Colorado BCR 18 4.92 558,368 33 55


Results: Site Occupancy

Example: Brewer’s Sparrow

Psi %CV n Tran

Pawnee N.G 0.222 63 2

Comanche N.G 0.293 61 2

Colorado BCR 18 0.253 28 15


Habitat occupancy at multiple scales

• Can large-scale monitoring inform habitat management local scales?

• Local scale• Territory occupancy

• Habitat condition

• Habitat degradation

• Large scale• Regional occupancy

• Landscape context

• Habitat loss and fragmentation


Brewer’s Sparrow (Spizella breweri)

• Southern Rockies / Colorado Plateau Bird Conservation Region (BCR 16)

• Sagebrush obligate

• Species of conservation concern

• BBS: 50% decline in 25 years


Predicted distribution: BCR 16

Wyoming

ColoradoProbability of occupancy0.30 - 0.390.40 - 0.490.50 - 0.590.60 - 0.690.70 - 0.790.80 - 0.890.90 - 1.00


Large-scale regional occupancy

Sagebrush area (%)

0 20 40 60 80 100

Pro

babi

lity

of la

rge-

scal

e oc

cup

ancy

(P

si)

0.0

0.2

0.4

0.6

0.8

1.0

Mean patch size of sagebrush (ha)

0 20 40 60 80 100P

roba

bilit

y of

larg

e-sc

ale

occu

panc

y (P

si)

0.0

0.2

0.4

0.6

0.8

1.0


Small-scale territory occupancy

Sagebrush cover (%)

0 10 20 30 40 50

Pro

babi

lity

of s

ma

ll-sc

ale

occu

panc

y (T

heta

)

0.0

0.2

0.4

0.6

0.8

Tree canopy cover (%)

0 20 40 60 80P

roba

bilit

y of

sm

all-

scal

e oc

cupa

ncy

(The

ta)

0.0

0.2

0.4

0.6

0.8


Small-scale territory occupancy

Grass height (cm)

0 10 20 30 40 50 60P

roba

bilit

y of

sm

all-

scal

e oc

cupa

ncy

(The

ta)

0.0

0.2

0.4

0.6

0.8

Shrub height of all species (m)

0 1 2 3 4

Pro

babi

lity

of s

ma

ll-sc

ale

occu

panc

y (T

heta

)

0.0

0.2

0.4

0.6

0.8


South Dakota

Maximum Entropy Models


Questions?

Jim Watson

great plains landscape conservation cooperative monitoring grid

Documents

habitatsconserving birds

bcrsconserving birds

prescott conserving

bird monitoring efforts

david hanniconserving

current monitoring programs

avian monitoring goal

coordinate monitoring