DOI: 10.1007/s002670010049
JACK F. CULLY, JR .*
STEPHEN L. WINTER
U.S. Geological Survey, Biological Resources Division
Kansas Cooperative Fish and Wildlife Research Unit
Division of Biology
204 Leasure Hall
Kansas State University
Manhattan, Kansas 66506, USA
ABSTRACT / Land condition trend analysis (LCTA) is a longterm monitoring program used on military training lands to identify ecological changes that result from training and management activities. We initiated LCTA at the Kansas
Army National Guard Training Facility (KANGTF) in Saline
County, Kansas, in March 1998. This paper evaluates the
LCTA methodology for birds by comparing LCTA results with a modified methodology designed to place sampling transects in field-identified rather than satellite-identified landcover types. In the satellite-identified land-cover types developed at the site, grassland habitats included a large component of woody vegetation, which resulted in poor resolution of bird assemblages associated with the different land-cover types. Using these cover classes, mixed grass prairie included five grass/forb (g/f) and 10 woody-dependent species; old-field included four g/f and four woody-dependent species; and riparian included one g/f and six woody-dependent species. LCTA sampling was too limited in the ecologically important riparian woodland habitat with the result that bird species were not adequately sampled there. In the alternate sampling strategy, we identified three land-cover classes (grassland, hedgerow, and riparian woodland) by field reconnaissance and increased sampling in the riparian woodland. Grassland included six g/f and three woody-dependent species; hedgerow included six g/f and 20 woody-dependent species, and riparian included two g/f and 19 woody-dependent species. The modifications greatly improved the resolution of bird assemblages associated with land-cover classes at the KANGTF. Use of the alternative sampling method should improve the ability to detect long-term trends in the bird communities.
The U.S. Army manages 12.4 million acres of land on
186 installations worldwide (Tazik and others 1992) making it an important steward of wildlife and other natural resources. Natural vegetation provides an important environmental component for the training mission, and the army developed a program, land condition trend analysis (LCTA), to monitor the impacts of training and management activity on the flora and fauna of its major training installations. The primary goal of LCTA is to use long-term monitoring to detect biotic changes that result from too intensive use of military training land (Tazik and others 1992).
The army is also subject to regulations stemming from the Endangered Species Act of 1973 (as amended), formalized in Army Regulation AR 200-3 (1995). Army lands contain 57 federal endangered species and 43 threatened species as well as numerous sensitive species
(Rubenson and others 1992). LCTA also serves to monitor the presence of listed and candidate species and therefore constitutes an important aspect of natural resources management on these lands.
KEY WORDS: Birds, Kansas, LCTA, Military, Monitoring, Sampling
*Author to whom all correspondence should be addressed.
Environmental Management Vol. 25, No. 6, pp. 625–633
We began an LCTA program at the Kansas Army
National Guard Training Facility (KANGTF) in March
1998. Standardized methodology is used for all LCTA programs on U.S. Army installations (Tazik and others
1992). Standard LCTA methodology was used to remotely identify three land cover classes: grassland, old-field, and riparian (see Methods). Prior to beginning the bird data collection portion of the LCTA program, we identified five concerns about the strict application of the standardized LCTA methodology at
KANGTF (Table 1).
Our objective was to compare an alternative sampling plan to the LCTA methodology to determine if standard LCTA methodology could be improved for birds. We believed the alternative sampling plan would identify habitat types with distinct and unique bird communities, and that the type of bird community present at each habitat type would in large part be a function of the amount and type of woody vegetation present at each habitat type. The alternative sampling plan also sampled extensive areas of each habitat type, and samples at each habitat type were replicated. The modifications improved the resolution of bird communities in different habitats and should improve the ability to detect changes in community structure by use of long term monitoring.
r 2000 Springer-Verlag New York Inc.

626 J. F. Cully, Jr. and S. L. Winter
Table 1.
Perceived problems with LCTA methods and suggested solutions
Problem Solution
1. Two land-cover classes, old-field and mixed grass prairie, did not appear to differ in a way that is relevant to bird communities. Because both herbaceous landcover classes appeared to be essentially identical herbaceous communities we expected the bird communities to be essentially identical as well.
2. The remote identification of land-cover classes did not distinguish between herbaceous communities with differing amounts of woody vegetation, with the result that both classes have similar foliage height diversity.
3. Variation in vegetation structural diversity will limit the ability of monitoring to detect long-term changes in bird community structure.
4. The strict application of standard LCTA methodology may result in an undersampling uncommon land-cover types at KANGTF.
5. LCTA plots may not be large enough to sample adequate numbers of species or individuals.
Establish study plots in distinctive habitat types, grassland, hedgerow, and riparian.
Establish study plots that differ in plant community structure.
Establish study plots that differ in plant community structure.
Establish replicate sites in all sampled cover types.
Establish larger study plots to determine minimum area necessary to adequately sample birds.
Study Site
We were asked to develop an LCTA monitoring program on the KANGTF in Saline County, Kansas. The
KANGTF is a 1417-ha site in mixed-grassland prairie and former farmed land in the Smoky Hills located at
38°40
8 lat., 97°45
8 long. Land use along the eastern portion of the reservation is primarily row-crop agriculture. On the west the reservation abuts the Smoky Hills
Air National Guard Bombing Range. Vegetation on the bombing range is native prairie, and there is a cattle grazing program. The KANGTF is used primarily for small arms training on several small firing ranges along the east side of the reservation. The grasslands experience hay harvest and some burning under a prescribed fire program. With the exception of the shooting ranges, the reservation receives very light human use.
LCTA Sampling Methodology
Standard LCTA methodology (Warren and others
1990, Tazik and others 1992) specifies using an unsupervised classification of three bands of SPOT satellite digital data (green, red, and near infrared) to develop an initial identification of cover types. We used thematic mapper data from two Landsat scenes (Path 28, Row 33) from 30 July and 15 August 1993 to remotely identify three classes identified as riparian woodland, grassland, and mowed developed areas (shooting ranges). The mowed areas were small, and because they were developed as shooting ranges access was unreliable. This cover type was not included in the LCTA project. The satellite classification was then joined with a soil cover classification (USDA, NRCS 1996) in a geographic information system (GIS), which resulted in further dividing the grassland cover class into two: identified as native mixed-grass prairie (MGP) and old-field. The old-field class was believed to be dominated by cool season grasses, primarily smooth brome (Bromus inermis
Leyss. subsp. inermis); however, subsequent fieldwork indicated that the class is broadly overlapping in plant species composition with MGP. MGP was dominated by little bluestem (Schizachyrium scoparium (Michx.) Nash-
Gould), big bluestem (Andropogon gerrardii Vitman), and side-oats grama (Bouteloua curtipendula Michx.) with a variety of forb species. Areas classified as riparian land cover were narrow belts of woody vegetation growing in association with intermittent streams. Overstory species of woody vegetation in riparian areas included green ash (Fraxinus pennsylvanica Marsh.), American elm (Ul-
mus americana L.), hackberry (Celtis occidentalis L.), cottonwood (Populus deltoides Marsh. subsp. monolifera
(Ait.) Eckenw.), osage-orange (Maclura pomifera (RAF.)
Schneid.), and honeylocust (Gleditsia triacanthos L.).
LCTA sample plots were randomly located on the land-cover map generated by the GIS and subsequently located on the ground with the aid of a global positioning system unit. LCTA guidelines call for no more than one LCTA plot for 200 ha of habitat. The number of plots in each cover class is proportional to the total area of the cover class. Because of the small area of the
KANGTF (1417 ha) we increased the density to approximately one plot/100 ha. We established 15 LCTA core plots; 9 were in MGP, 5 were in old-field, and 1 was in riparian woodland. Mixed grass prairie and old-field land covers had varying amounts of woody vegetation, primarily osage-orange, present within or adjacent to

Avian Land Condition Trend Analysis 627 them as scattered invading individuals or as linear hedgerows.
Avian data collection occurred between 27 May and
10 June 1998 on days when the wind speed was less than
25 km per hr and it was not raining. Data were collected according to LCTA guidelines between sunrise and 4 hr after sunrise and again during the 4 hr preceding sunset. Data were collected following LCTA guidelines by walking the length of a 100 m transect in 6 min (line out), pausing at the end of the transect for 8 min (end point), and returning to the start of the transect in 6 min (line in). All birds detected on vegetation, the ground, or flushing within 100 m of any point on the transect were recorded. Species identity and mated status were recorded where possible for each individual bird, and effort was made to not record individual birds more than once. We also recorded the segment (line out, end point, or line in) being sampled when each individual bird was detected.
Alternative Sampling Methodology
Visual observations of the study site were used to identify what we believed were the three primary habitats at KANGTF: grassland habitats, grasslands with woody vegetation, and riparian habitats. Grassland habitats were large areas of herbaceous vegetation, dominated by warm-season perennial grasses, with a minimal amount of woody vegetation. Grasslands with woody vegetation were characterized by hedgerows. Hedgerow habitats consisted of linear strips of trees, primarily osage-orange, which were located in grassland habitats with varying densities of woody vegetation. Hedgerow habitats often paralleled gravel roads and were sometimes intersected by riparian habitats. The description of riparian land cover provided in the LCTA methodology above applies to the riparian habitats used in the alternative sampling plan.
Transects were established at three replicates of each habitat type. Grassland habitats had three or four transects at each replicate and each transect was between 400 and 600 m long. A total of 5600 m of transect were sampled in grassland habitats. Hedgerow habitats had one transect at each replicate, and each transect was between 800 and 2400 m long. A total of 4600 m of transect were sampled in hedgerow habitats. Riparian habitats had one transect at each replicate, and each transect was 400 m long. A total of 1200 m of transect were sampled in riparian habitats. Grassland and hedgerow transects were straight lines marked with flags every 100 m. Riparian transects were not straight lines but were instead bent periodically to remain within the narrow, winding belt of woody vegetation. Riparian transects were marked every 25 m with flagging.
Data collection occurred between 9 June and 12
June 1998. Data were collected between sunrise and 4 hr after sunrise, when wind speeds were less than 25 km/hr and it was not raining. Grassland and hedgerow transects were walked at a slow steady pace. Riparian transects were walked slowly with a 2-min pause every 25 m. All birds detected within 100 m of a transect were recorded, and the 100-m segment (grassland and hedgerow) or 25-m segment (riparian) each bird was closest to was recorded. The perpendicular distance to the transect was estimated for each bird detected.
For data collected using both methodologies we followed Zimmerman (1997) and Johnsgard (1979) to categorize each species into one of the following groups:
1.
grass/forb-dependent species that require grasses or forbs for nesting and/or foraging.
2.
woody-dependent species that require woody vegetation for nesting and/or foraging.
3.
species without a habitat classification that are nesting/foraging habitat–independent or that commonly nest and/or forage in both types of vegetation.
Summary statistics were calculated for the following variables using the data collected with the LCTA methodology: individuals of all species combined per plot, individuals of each species per plot, species richness per plot, species richness of grass/forb dependent species per plot, and species richness of woody dependent species per plot. Summary statistics were calculated for the following variables using the data collected with the alternative sampling methodology: individuals of all species combined per 200-m segment of transect, individuals of each species per 200-m segment of transect, species richness per 200-m segment of transect, species richness of grass/forb dependent species per 200-m segment of transect, and species richness of woody dependent species per 200-m segment of transect.
Differences in grassland bird species richness and woodydependent bird species richness of 200-m transect segments among habitat types at the alternative sampling sites and within the LCTA plots were compared for differences using analysis of variance (SAS Version
6.12, Proc GLM; SAS 1996). Significance was assumed when probability ⬍ 0.05.
Sampling of the LCTA plots in the morning resulted in the detection of 17 species (5 grass/forb-dependent,
10 woody-dependent, 2 without a classification) on the
MGP plots, 10 species (4 grass/forb-dependent, 4 woodydependent, 2 without classification) on the old-field

628 J. F. Cully, Jr. and S. L. Winter
Table 2.
Total abundance, number of birds per plot, and species richness of birds recorded on LCTA plots in the morning at the KANGTF, Saline County, Kansas, USA
N
Old-field
(N
⫽
5)
Mean
⫾
SE N
MGP
(N
⫽
9)
Mean
⫾
SE
Riparian
(N
⫽
1)
N
Grass/forb-dependent species
Eastern meadowlark (Sturnella magna)
Red-winged blackbird (Agelaius phoeniceus)
Dickcissel (Spiza americana)
Grasshopper sparrow (Ammodramus savannarum)
Henslow’s sparrow (Ammodramus henslowii)
Woody-dependent species
Eastern kingbird (Tyrannus tyrannus)
Scissor-tailed hycatcher (Muscivora forficata)
Great-crested flycatcher (Myiarchus crinitus)
Blue jay (Cyanocitta cristata)
Black-capped chickadee (Parus atricapillus)
House wren (Troglodytes aedon)
Northern mockingbird (Mimus polyglottos)
Brown thrasher (Toxostoma rufum)
Eastern bluebird (Sialis sialia)
Orchard oriole (Icterus spurius)
Baltimore oriole (Icterus galbula)
Common crackle (Quiscalus quiscula)
Northern cardinal (Cardinalis cardinalis)
American goldfinch (Carduelis tristis)
Field sparrow (Spizella pusilla)
Species without a habitat classification
Mourning dove (Zenaida macroura)
Brown-headed cowbird (Molothrus ater)
Unknown sparrow*
Unknown species*
Total all species
Total species richness
Species richness/plot
*Not included in species richness calculations.
0
0
0
0
1
0
1
0
1
0
0
0
0
5
0
5
11
2
4
67
10
16
13
6
0
2
1.20
⫾
0.73
0
3.20
⫾
0.73
2.60
⫾
0.87
0.40
⫾
0.24
1.00
⫾
0.32
0
0
0
0
0.20
⫾
0.20
0
0.20
⫾
0.20
0
0
0
0
0
0.20
⫾
0.20
0
1.00
⫾
0.55
2.20
⫾
1.02
0.40
⫾
0.40
0.80
⫾
0.49
13.40
⫾
2.60
5.40
⫾
1.50
2
0
2
2
0
1
3
4
0
1
0
5
0
6
2
3
13
0
10
113
17
10
16
12
18
3
1.11
⫾
0.35
1.78
⫾
1.05
1.33
⫾
0.73
2.00
⫾
0.37
0.33
⫾
0.24
0.67
⫾
0.33
0.22
⫾
0.22
0
0.56
⫾
0.29
0
0
0.11
⫾
0.11
0.33
⫾
0.24
0.44
⫾
0.34
0.22
⫾
0.22
0.22
⫾
0.22
0.22
⫾
0.22
0
0
0.11
⫾
0.11
0.33
⫾
0.24
1.44
⫾
0.47
0
1.11
⫾
0.45
12.56
⫾
1.12
5.33
⫾
0.37
1
1
0
0
0
0
0
0
1
0
1
1
3
0
0
11
7
7
0
2
0
0
0
0
0
1
0 plots, and 7 species (1 grass/forb-dependent, 6 woodydependent) on the riparian plot. Mean richness was
5.33 species/plot on MGP plots and 5.40 species/plot on old-field plots (Table 2). Mean richness of grass/forbdependent species was 2.80 species/plot on old-field plots, 3.40 species/plot on MGP plots, and 1.00 species/ plot on the riparian plot. Mean richness of woodydependent species was 1.40 species/plot on the oldfield plots, 1.20 species/plot on the MGP plots, and 7 species/plot on the riparian plot. Old-field plots had two species unique to that land cover, MGP plots had seven, and the riparian plot had three. Nine species were recorded on MGP plots that were not recorded on old-field plots, all but one of them being woodydependent species.
Sampling of the LCTA plots in the evening resulted in the detection of 15 species (5 grass/forb-dependent,
8 woody-dependent, 2 without a classification) on the
MGP plots, 9 species (5 grass/forb-dependent, 3 woodydependent, 1 without a classification) on the old-field plots, and 5 species (1 grass/forb-dependent, 4 woodydependent) on the riparian plot (Table 3). Mean richness was 3.56 species/plot on MGP plots and 4.60
species/plot on old-field plots. Mean richness of grass/ forb-dependent species was 2.11 species/plot on MGP plots, 2.67 species/plot on old-field plots, and 0 species/ plot on the riparian plot. Mean richness of woodydependent species was 1.11 species/plot on the MGP plots, 1.78 species/plot on the old-field plots, and 10 species/plot on the riparian plot.
Sampling of the grassland, hedgerow and riparian habitats using the alternative sampling methodology resulted in the detection of 11 species (6 grass/forbdependent, 3 woody-dependent, 2 without a classification) in the grassland habitats, 26 species (6 grass/forbdependent, 15 woody-dependent, 2 without a classification) in the hedgerow plots, and 22 species (2 grass/forb-dependent, 19 woody-dependent, 1 without

Avian Land Condition Trend Analysis 629
Table 3.
Total abundance, number of birds per plot, and species richness of birds recorded on LCTA plots in the evening at KANGTF, Saline County, Kansas, USA
N
Old-field
(N
⫽
5)
Mean
⫾
SE N
MGP
(N
⫽
9)
Mean
⫾
SE
Riparian
(N
⫽
1)
N
Grass/forb-dependent species
Common yellowthroat (Geothlypis trichas)
Eastern meadowlark
Western meadowlark (Sturnella neglecta)
Red-winged blackbird
Dickcissel
Grasshopper sparrow
Henslow’s sparrow
Woody-dependent species
Wild turkey (Meleagris gallopavo)
Yellow-billed cuckoo (Coccyzus americanus)
Eastern kingbird
Great-crested flycatcher
Blue jay
House wren
Northern mockingbird
Brown thrasher
Loggerhead shrike (Lanius ludovicianus)
Baltimore oriole
Northern cardinal
Field sparrow
Species without habitat classification
Killdeer (Charadrius vociferus)
Mourning dove
Unknown sparrow*
Unknown species*
Total all species
Total species richness
Species richness/plot
*Not included in species richness calculations.
1
0
0
0
0
0
5
0
0
1
0
0
53
9
1
1
0
1
18
16
2
1
0
0
6
0
1.20
⫾
0.37
0.20
⫾
0.20
0
3.60
⫾
0.66
3.20
⫾
0.66
0.40
⫾
0.24
0
0
1.00
⫾
0.32
0
0
0.20
⫾
0.20
0
0.20
⫾
0.20
0
0
0
0
0
0.20
⫾
0.20
0.20
⫾
0.20
0.20
⫾
0.20
10.60
⫾
1.21
4.6
⫾
0.40
0
1
1
1
1
0
4
2
0
0
1
1
70
15
1
2
1
5
0
11
0
8
18
9
3
0
1.22
⫾
0.46
0
0.89
⫾
0.65
2.00
⫾
1.21
1.00
⫾
0.37
0.33
⫾
0.24
0.11
⫾
0.11
0
0.44
⫾
0.24
0.11
⫾
0.11
0.11
⫾
0.11
0
0.11
⫾
0.11
0
0.11
⫾
0.11
0.22
⫾
0.22
0
0.11
⫾
0.11
0.11
⫾
0.11
0.56
⫾
0.44
0.11
⫾
0.11
0.22
⫾
0.22
7.78
⫾
1.88
3.56
⫾
0.63
6
5
10
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
1
0
1
1
0
0
0 a classification) in the riparian habitats (Table 4). Mean richness was 3.46 species/200-m segment in the grassland habitats, 4.80 species/200-m segment in the hedgerow habitats, and 8.33 species/200-m segment in the riparian habitats. Mean richness of grass/forb-dependent species was 2.94 species/200-m segment in the grassland habitats, 1.62 species/200-m segment in the hedgerow habitats, and 0.33 species/200-m segment in the riparian habitats. Mean richness of woody vegetation dependent species was 0.21 species/200-m segment in the grassland habitats, 2.47 species/200-m segment in the hedgerow habitats, and 6.50 species/200-m segment in the riparian habitats. Grassland habitats had two species unique to that habitat, hedgerow habitats had seven, and riparian habitats had nine.
Richness of grassland species was not different between the MGP and old-field habitat types (F
⫽
0.05; d.f. 1, 12; P ⫽ 0.83), nor was there any difference among woody-dependent species (F
⫽
0.18; d.f. 1, 12;
P
⫽
0.68). Because there was only one riparian plot at the LCTA series, that habitat was not included in the analysis. All three habitats at the alternative sites differed significantly in grassland dependent species richness (grassland
⫽
2.9, hedgerow
⫽
1.6, and riparian
⫽
0.3; F
⫽
24.38; d.f. 2, 53; P
⬍
0.0001), and woodydependent bird species (grassland
⫽
0.29, hedgerow
⫽
2.2, and riparian
⫽
6.5 species per 200-m transect segment; F
⫽
74.70; d.f. 2, 53, P
⬍
0.0001).
Attribution of land-cover types to digital data classes is always subjective. In addition, if few classes are defined, each is likely to have considerable variation in plant species composition and other attributes. Although the LCTA land cover classification makes a good first attempt at identifying unique cover classes, we were concerned that the apparent similarity of the two

630 J. F. Cully, Jr. and S. L. Winter
Table 4.
Total abundance, number of birds per 200-m transect length, and species richness of birds recorded on the alternative sampling plan transects at KANGTF, Saline County, Kansas, USA
N
Grassland
(N
⫽
3)
Mean
⫾
SE N
Hedgerow
(N
⫽
3)
Mean
⫾
SE N
Riparian
(N
⫽
3)
Mean
⫾
SE
Grass/forb-dependent species
Common yellowthroat
Eastern meadowlark
Red-winged blackbird
Dickcissel
Grasshopper sparrow
Henslow’s sparrow
Lark sparrow (Chondestes grammacus)
Woody-dependent species
Coopers hawk (Accipiter cooperii)
Red-tailed hawk (Buteo jamaicensis)
Common bobwhite (Colinus virginianus)
Yellow-billed cuckoo
Northern flicker (Colaptes auratus)
Red-bellied woodpecker (Melanerpes carolinus)
Red-headed woodpecker (Melanerpes erythrocenphalus)
Hairy woodpecker (Picoides villosus)
Downy woodpecker (Picoides pubescens)
Eastern kingbird
Scissor-tailed flycatcher
Great-crested flycatcher
Blue jay
American crow (Corvus brachyrhynchos)
Black-capped chickadee
House wren
Bewicks wren (Thyromanes bewickii)
Northern mockingbird
Gray catbird (Dumetella carolinensis)
Brown thrasher
European starling (Sturnus vulgaris)
Baltimore oriole
Northern cardinal
Indigo bunting (Passerina cyanea)
American goldfinch
Field sparrow
Species without habitat classification
Mourning dove
Brown-headed cowbird
Unknown sparrow*
Unknown species*
Total all species
Total species richness
Species richness/plot
0
0
0
0
0
0
0
0
0
4
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
2
1
39
24
89
23
11
0
1
31
23
11
5
1
0.03
⫾
0.03
1.48
⫾
0.51
0.78
⫾
0.24
3.15
⫾
0.28
0.87
⫾
0.26
0.41
⫾
0.09
0
3
3
9
0
16
1
1
0
2
1
3
0
0
1
7
9
2
0
1
0
0
3
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0.06
⫾
0.06
0
0
0
0
0
0
0.21
⫾
0.10
0
0
0
0
0
0
0.11
⫾
0.11
0
0.03
⫾
0.03
0.99
⫾
0.50
0.20
⫾
0.06
0.04
⫾
0.04
8.35
⫾
0.46
3.46
⫾
0.23
2
33
1
3
20
0
1
16
25
1
12
179
24
0.03
⫾
0.03
0.12
⫾
0.09
0.06
⫾
0.06
1.37
⫾
0.11
0.86
⫾
0.07
0
0.03
⫾
0.03
0
0.08
⫾
0.08
0
0.10
⫾
0.05
0
0
0
0
0.03
⫾
0.03
0.48
⫾
0.22
0.06
⫾
0.06
0.08
⫾
0.08
0.31
⫾
0.15
0
0
0.84
⫾
0.33
0.05
⫾
0.05
0.05
⫾
0.05
0
0.34
⫾
0.08
0
0.14
⫾
0.14
0.16
⫾
0.05
0.06
⫾
0.06
0.05
⫾
0.05
0.14
⫾
0.07
0.54
⫾
0.28
0.93
⫾
0.27
0.08
⫾
0.08
0.49
⫾
0.13
7.56
⫾
0.41
4.80
⫾
0.19
78
22
0
0
7
0
2
0
0
0
0
1
2
0
0.33
⫾
0.33
0
0
0.17
⫾
0.17
0
0
0
0.17
⫾
0.17
0
0
0.17
⫾
0.17
0.17
⫾
0.17
0.33
⫾
0.17
0.67
⫾
0.17
0.33
⫾
0.33
0
0.50
⫾
0.50
0
0.33
⫾
0.17
1.00
⫾
0.29
0.33
⫾
0.33
1.00
⫾
0.50
2.83
⫾
1.09
0
0
0.33
⫾
0.33
0.17
⫾
0.17
0.67
⫾
0.67
0.50
⫾
0.29
0.17
⫾
0.17
1.17
⫾
0.73
0.17
⫾
0.17
0
0
0.33
⫾
0.33
0
1.17
⫾
0.17
13.0
⫾
2.78
7.00
⫾
1.16
3
1
1
4
17
0
0
2
7
1
0
2
6
2
6
3
0
2
0
2
4
1
1
1
0
0
*Not included in species richness calculations.
nonforest classes, MGP and old-field, and the inclusion of woody species in both classes would degrade the ability of long-term monitoring to detect changes in bird communities caused by future management or training. Because both classes are similar and include the full range of nonforest vegetation, any changes that occurred would be masked by the presence of woody dependent species and grass/forb-dependent species being equally abundant on both cover types. We believed a monitoring plan that could differentiate between these groups would be far more likely to detect long-term changes in bird communities.
The MGP and old-field plots from the LCTA sampling were both identified a priori as grass/forb dominated plant communities. When bird species were compared between the two cover types, the grass/forb dependent composition was similar (Figure 1a). Redwinged blackbirds were detected in relatively high

Avian Land Condition Trend Analysis 631
Figure 1.
The numbers of grass/forb-dependent and woodydependent bird species at the Kansas Army National Guard
Training Facility, Saline County, Kansas, are broadly overlapping on the three cover classes in the LCTA plots (a). On the
LCTA plots, woodland species are dominant in the mixed grass prairie (MGP) sites, which are described as grassland habitat. In fact, more woodland species are present there than on the riparian site, at least in part because there was only one
LCTA plot allocated to the riparian habitat. The distribution of grassland and woodland birds on the alternative sites (b) reflect real habitat differences with numerous grass/forb species at the grassland and hedgerow sites and few at the riparian site, with the opposite pattern among woodydependent bird species.
numbers only on the MGP plots, but this is because of the presence of ponds and their associated vegetation within the sampled area at some of the MGP plots.
Woody-dependent species richness and total species richness was higher on the MGP plots than on old-field plots or the riparian plot. The higher number of woody-dependent species recorded in MGP plots (nine plots) relative to old-field plots (five plots) may be a function of the greater area of MGP plots that were sampled. It is also possible that MGP plots had a larger component of woody vegetation than the old-field plots; woody vegetation outside of the riparian areas was not identified in the land-cover classification. However, based on the similarity of the grass/forb-dependent bird species for these two herbaceous land-cover types, the distinction between MGP and old-field land-cover types at KANGTF do not appear to be relevant to monitoring of bird populations.
Previous research has found a positive relationship between habitat structural diversity and bird community species richness (MacArthur and MacArthur 1961,
MacArthur 1965). Grasslands, a structurally simple habitat, have been characterized by a suite of unique grassland bird species (Herkert 1994, Knopf 1996) and relatively low bird species richness in Kansas (Zimmerman 1997) and in numerous other locations in the western hemisphere (Cody 1968, Wiens 1989). The random locations of the LCTA plots within areas that had been remotely classified as MGP or old-field in many instances resulted in the presence of woody vegetation having a substantial influence on the composition of the bird community recorded at those sites.
Plots were sometimes located in places that were infested with small to medium-sized trees, in places where the sampling area overlapped adjacent hedgerows or riparian habitats and in places where the plot was essentially a small herbaceous opening surrounded on all sides by woody vegetation.
As a result of the presence of woody vegetation within or adjacent to old-field and MGP plots, woodydependent species substantially influenced the composition of the bird communities detected on the old-field and MGP plots sampled with the LCTA methodology.
The result may be an inflated estimate of the bird species richness of the grassland habitats at KANGTF.
Woody-dependent bird species represented the majority of the species detected on the grassland plots.
Considering the bird species composition of some of the areas classified as grassland land-cover, the appropriateness of the title ‘‘grassland’’ seems questionable.
Even considering the disparity in the total area sampled of MGP/old-field habitats and the riparian habitat, it seems counterintuitive for the LCTA methodology to result in twice as many species being detected in MGP and old-field, land covers that are supposedly structurally simple, than in a structurally diverse riparian habitat. The suitability of a strict application of the
LCTA methodology seems especially questionable for birds considering the fact that the sampling effort in the

632 J. F. Cully, Jr. and S. L. Winter grassland land cover gave a better representation of the woody-dependent species present at KANGTF than the sampling effort in the riparian land cover.
The alternative sampling methodology resulted in woody vegetation having a minimal influence on the types of species detected in the grassland habitats
(Figure 1b). The bird species composition of the grassland habitats sampled with the alternative plan is composed almost entirely of grass/forb-dependent species. The hedgerow habitats sampled with the alternative sampling plan are characterized by a mixture of grass/forb-dependent species and woody-dependent species, similar to the composition of species found on the old-field and grassland plots sampled with the LCTA methodology.
The increased sampling effort in riparian habitats resulted in 22 species being detected, as opposed to the
10 species detected on the LCTA riparian plot in the morning and evening. Thirteen of the species detected in the riparian habitats with the alternative sampling plan had not been detected on the LCTA riparian plot.
The problem of inadequate sampling we encountered at KANGTF is partly a result of the small area of the installation. Even at larger sites, however, the stratified random sampling design employed by LCTA will not provide adequate samples for uncommon cover types.
The area sampled on individual LCTA plots appears to be sufficient to detect numerous individuals and numerous species at each plot, but neither the LCTA methodology nor the alternative sampling methodology was suitable for monitoring uncommon species, such as upland sandpipers (Bartramia longicauda), blackbilled magpies (Pica pica), and red-tailed hawks (Buteo
jamaicensis), all of which have been observed breeding at KANGTF (R. Charlton, personal communication).
The comparison of the LCTA methodology with the alternative sampling methodology indicates that the primary deficiencies of a strict application of the LCTA sampling methodology are:
1.
The location of putative MGP and old-field LCTA plots in areas where woody vegetation substantially influences the composition of the bird community may result in muddled information about the bird communities at KANGTF. Areas classified as MGP or old-field may have bird communities composed primarily of woody-dependent species.
2.
The strict application of the LCTA sampling methodology results in riparian areas being greatly undersampled.
3.
Some uncommon species that are known breeders at KANGTF are not being encountered on the current plots.
The following recommendations are made to address the deficiencies of the LCTA sampling methodology. Use the LCTA methodology to locate preliminary plot locations as in the guidelines, however, during the first year, refine the GIS-based map to better reflect true land-cover classes and relocate LCTA plots to adequately sample field validated cover classes. Use a semirandom process to locate new LCTA plots to ensure placement in defined cover types to reduce the problem of confounding of grassland and woodland bird faunas.
For example, locate grassland plots in grassland habitat that contains a minimum amount of woody vegetation within or adjacent to them and locate additional LCTA plots in hedgerow areas. This will facilitate monitoring a bird community occurring in herbaceous landscapes that contain substantial amounts of woody vegetation in a grassland matrix. Ensure that all surveyed habitats have a large enough number of plots to provide a representative sample of birds from their respective habitats. The LCTA plot size appears sufficient for the detection of numerous individuals at each plot and a sufficient number of plots should sample habitats adequately. Retention of the LCTA plot design for the additional sampling will allow a direct comparison with the results obtained from the original LCTA plots and will also allow comparisons of the results with the data from other military installations.
The goal of LCTA is to be able to detect long-term changes in the flora and fauna that result from management and training activities. This is done so that remedial actions can be taken to reverse undesirable trends or to maintain desirable ones. Current LCTA methodology has a number of positive attributes. LCTA requires defining land-cover classes and then monitoring several taxonomic groups that may be sensitive to different types of human impacts in each cover class. We enthusiastically endorse those efforts. We believe that a shortcoming of LCTA is that land-cover classes are determined by remote sensing, and the methods do not call for accuracy assessment to ensure that study plots are located at appropriate sites. A result is that the sampling plan so produced fails to take advantage of refinements that will result from the initial field work.
We have shown how refining the land-cover map and the LCTA plot locations can improve the quality of the monitoring data for one group of organisms, birds.
We are grateful to Ralph Charlton, Matt Whiles, and
Brent Brock for their helpful comments on the paper.
Scott Wilson and Ray Hinchman provided insightful

Avian Land Condition Trend Analysis 633 reviews. We thank The Kansas Army National Guard for funding this study.
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