RESEARCH ARTICLE

Markov models of land cover dynamics in a southern GreatPlains grassland region

Bryan R. Coppedge Æ David M. Engle ÆSamuel D. Fuhlendorf

Received: 2 June 2006 / Accepted: 27 May 2007 / Published online: 14 July 2007

� Springer Science+Business Media B.V. 2007

Abstract Grassland regions of the southern Great

Plains are fragmented by agricultural activity and

many habitat remnants have experienced encroach-

ment by juniper (Juniperus virginiana L.). Recently,

many cropland areas have been converted to mono-

culture grassland (pastures) and enrolled into the

Conservation Reserve Program (CRP). Our objectives

were to develop spatial and temporal Markov models

to characterize land cover dynamics relative to juniper

expansion and CRP using aerial photography from

1965, 1981, and 1995. We used landscapes surround-

ing three Breeding Bird Survey routes with varying

levels of juniper encroachment in Oklahoma as study

areas. As expected, land cover changes from 1965 to

1995 included increases in juniper woodland, mixed

juniper-deciduous woodland, and pastures from CRP

activity. Markov models revealed that juniper had a

low likelihood of self-replacement in early stages of

encroachment. In all areas, relatively little native

grassland was lost to juniper encroachment, but other

native habitat types such as deciduous woodland were

heavily impacted. Transition probabilities for land

cover dynamics varied significantly both spatially and

temporally. Projections of these raw transition matri-

ces produced widely varying models of future land

cover conditions. By modifying the matrices to

account for recent and potential socio-political and

ecological changes occurring in this region, a number

of more plausible land cover scenarios were produced

than those resulting from simple projections of raw

transition matrices.

Keywords Conservation Reserve Program �Grassland � Fragmentation � Juniper � Landscape �Oklahoma � Transition matrix

Introduction

Landscape change is rarely a random process. Land

use history and previous cover types, social and

political changes, and ecological processes all affect

land cover dynamics, often interactively (Antrop

1998). Human-induced landscape change can also

precipitate ecological processes that result in further

landscape change. Grassland ecosystems, for exam-

ple, occupy 40% of the global terrestrial landscape

and form the basis of many important agronomic and

ecological processes (Chapin et al. 2001). Grasslands

are a key component of the global carbon cycle and

sequester large amounts of soil C (Schimel et al.

1994). Historically, vast amounts of global grasslands

were lost to large-scale conversion to cropland

B. R. Coppedge � D. M. Engle � S. D. Fuhlendorf

Department of Natural Resource Ecology and

Management, Oklahoma State University, 008C Ag Hall,

Stillwater, OK 74078, USA

B. R. Coppedge (&)

Science and Math Division, TCC-West, 7505 W. 41st

Street, Tulsa, OK 74107, USA

e-mail: bcoppedg@tulsacc.edu

123

Landscape Ecol (2007) 22:1383–1393

DOI 10.1007/s10980-007-9116-4

agriculture. Although agricultural conversion contin-

ues, most current losses are due to changes in land

management and ecological processes whose mech-

anisms were triggered in part by human activities

(Mitchell 2000).

A key ecological process threatening remnant

grasslands (i.e., those not converted to cropland) is

woody plant and shrub encroachment, a worldwide

phenomenon with examples from North and South

America (Dussart et al. 1998; Van Auken 2000),

Africa (Moleele and Perkins 1998), and Australia

(Brown and Carter 1998). In grasslands of the Great

Plains of North America, encroachment is thought to

be the result of several interacting processes, includ-

ing landscape fragmentation, fire suppression, over-

grazing, and global climate change (Archer 1994;

Briggs et al. 2005). Fire suppression is especially

important in the spread of a particular group of

encroaching species, fire-intolerant junipers (Junipe-

rus spp.). Native species normally restricted to sites

protected from fire, junipers have spread extensively

into grasslands and other habitats of the Great Plains

(Briggs et al. 2002). In Oklahoma, the primary

encroaching species is eastern redcedar (J. virgini-

ana), which is spreading due in part to fire suppres-

sion associated with exurban development and

landscape fragmentation occurring across the state

(Coppedge et al. 2001a).

During the westward expansion of the United

States, Great Plains grasslands were found to harbor

rich soils that were favorable to both grain and forage

production. As a result, grasslands were widely

converted and now both cropland agriculture and

livestock production are nearly synonymous with the

Great Plains in American culture. However, the

region experiences variable climatic conditions

resulting in highly variable crop and forage produc-

tivity (Riddel and Skold 1997). Furthermore, soil

erosion is a constant concern, including wind erosion

during recurring droughts. During the late 1970s,

high prices for grain exports led to intensification in

grain crop production in the Great Plains, especially

wheat (Triticum aestivum) cultivation (Laycock

1988). Over eight million hectare of new cropland

were added in the United States between the early

1970s and early 1980s, which included the plowing

of previously undisturbed grasslands. This is turn lead

to growing concerns over soil conservation given the

cyclical nature of precipitation and the history of

drought and erosion (Worster 1979; Glantz 1994;

Laycock 1988). The Conservation Reserve Program

(CRP) was enacted in 1985 (Dunn et al. 1993) with

the goals of curtailing overproduction and removing

marginally productive and potentially erosive crop-

land from cultivation and placing these areas under

perennial vegetative cover. Over half of the national

CRP cropland enrollments are located in the Great

Plains (Laycock 1991).

The purpose of this study was to characterize land

cover dynamics in this grassland-agricultural region.

We previously reported on land cover type and

landscape pattern change in the region and how those

changes affected the avian community (Coppedge

et al. 2001b). However, studies of land cover dynam-

ics, especially in landscapes dominated by agriculture,

often report only absolute area changes over discrete

timeframes, which may not fully elucidate the driving

forces behind the change (Burgi et al. 2004). Land

cover change for any particular location may not be

random but dependent on previous or current land

uses. Thus, cover type changes are often modeled with

Markov processes (Usher 1992), which are stochastic

models in which the transitions among land cover

types occur with a probability that depends only on the

current state of the system (Baker 1989; Boerner et al.

1996). Markov models have been widely used to

characterize and predict patterns of landscape change

(Lippe et al. 1985; Turner 1987; Muller and Middle-

ton 1994). Herein we report on the development and

testing of spatial and temporal Markov models for a

grassland region of the southern Great Plains subject

to changing agricultural conditions and woody (juni-

per) encroachment levels.

Methods

Study area description

The study region was located in northwestern Okla-

homa, an area with a continental climate, mean

annual temperature of 168C and mean annual

precipitation of 65 cm (Tyrl et al. 2002). As part of

a larger study of long-term landscape and avian

community dynamics (Coppedge et al. 2001b), we

used landscapes surrounding three Breeding Bird

Survey routes for study because of the availability of

long-term bird census data. Although located in the

1384 Landscape Ecol (2007) 22:1383–1393

123

same region, each specific area naturally varied

slightly in initial cover type composition. Most

importantly, each area differed in the amount and

severity of juniper encroachment occurring within

native habitat remnants. The Eagle City route was the

most severely affected by encroaching juniper,

followed by the Tegarden route. The Lookout route

had minimal juniper encroachment and served as a

baseline for assessing juniper-related effects (Copp-

edge et al. 2001c). Land cover in the study region is

primarily native perennial grassland, interspersed

with cropland, pasture, and small scattered areas of

deciduous woodland. The regional grassland type is

‘mixed-grass prairie’ (Tyrl et al. 2002) and is

dominated by mixtures of perennial grasses such as

little bluestem (Schizachyrium scoparium), switch-

grass (Panicum virgatum), buffalograss (Buchloe

dactyloides), and grama species (Bouteloua spp.).

Landscape data

Land cover type dynamics were assessed from 1:7,920

scale black-and-white aerial photography. Winter

(November–March) photography from 1965, 1981,

and 1995 was used specifically to document land

cover type changes and distinguish encroaching

evergreen juniper from other woody vegetation,

especially where juniper occurred as an understory

component in deciduous woodland (Coppedge et al.

2001c). Initial work involved delineating homogenous

landscape patches onto acetate overlays to create

vector coverages that were subsequently digitized into

a GIS. Polygons with a minimum size of ca. 0.05 ha

resulting from the ca. 16 km2 orthorectified photomo-

saics were then classified into one of eight land cover

types (Table 1). Polygon classification followed

training in which cover types in the field were

compared to the 1995 photography signatures. Similar

cover types were distinguished based on color,

uniformity, density, and heterogeneity. Cultivation

characteristics and linear features associated with

mechanical soil manipulation such as plow furrows

and terracing were also important in delineating

retired or abandoned cropland with vegetative cover.

Analysis

The nine vector images (three areas with three

dates each) were subsequently rasterized with a

standard cell size of 25 m · 25 m. Dated images

for each respective area were overlayed, and

temporal land cover data from 450 randomly

selected cells from each area were collected for

analysis for a total of 2,700 observed cell transi-

tions. We first calculated cover type compositional

dynamics for each area for each time period. We

then examined the magnitude of land cover

dynamics within the given time periods of photog-

raphy by calculating rates of change for each area

by time period (Antrop 1998). Nearest neighbor

probabilities (fi,j) for the various land cover types

were derived following the methods of Turner

(1988) using the formula

fi; j ¼ni; j

Nið1Þ

where fi,j = nearest neighbor probability of cells of

cover type i next to j; ni,j = number of cells of

cover type i adjacent to type j; and Ni = number of

cells of type i. A Rooks move sampling pattern (4-

neighbor) was used to determine nearest neighbor

frequencies and also to check for spatial influence

of juniper. We examined the neighbors of cells

converted to either juniper or mixed woodland in

any time period to determine if the proximity to

juniper was a factor in a cell transitioning to either

of these cover types.

An overall (pooled across areas and dates) tally

matrix (N) of cell cover type dynamics was then used

to derive a transition probability matrix (P) following

the methodology of Usher (1992). To ascertain the

nature of land cover transitions in the region, we

tested for statistical independence of the probability

matrix P (indicating random cover type changes)

using the test statistic

�2ðln kÞ ¼ 2+m

ij nij lnpij

pj

� �ð2Þ

where ‘ln’ is the natural logarithm, m is the number of

land cover types, nij is the element in the ith row and

jth column of N, pij is the corresponding element in P,

and pj is the marginal probability of the jth column of

N, given by

pj ¼+m

i¼1nij

+m

i¼1+m

j¼1nij

ð3Þ

Landscape Ecol (2007) 22:1383–1393 1385

123

where -2(ln k) is distributed asymptotically as v2 with

(m-1)2 degrees of freedom.

Spatio-temporal stationarity of transition probabil-

ities was also examined by subdividing the matrix N

into Nt tally matrices, where t = either the number of

spatial areas studied (n = 3), time periods studied

(n = 2), or the interaction of these factors (n = 6). The

test of significance is based on the null hypothesis

that the series of accompanying P(t), t = 1, 2,...T,

transition probability matrices are equal. The test

statistic

�2ðln kÞ ¼ 2+m

ij +T

t¼1nijðtÞ ln

pijðtÞpij

� �ð4Þ

is a derivation of Eq. 2 wherein the symbols are as

previously described, except that pij is the element in

the ith row and jth column of P as in Eq. 2.0. Again, -

2(ln k) is distributed asymptotically as v2 with m(m-

1)(T-1) degrees of freedom (Usher 1992).

Markov modeling

To determine how observed land cover dynamics

could affect the study areas on a long-term basis, we

generated a set of land cover type predictions for the

year 2045 using stochastic Markov chain models

(Baker 1989). Rather than use matrices from indi-

vidual study sites, we pooled data from the three

study areas to produce regional means. This regional

cover type composition data for 1995 was used to

initialize each model and for comparison to predicted

land cover composition. After converting the final

matrices to annual timesteps, 50 iterations of the

transition probability matrices resulting from our

spatial and temporal stationarity tests were used to

produce predictions (Urban and Wallin 2002). In our

modeling exercises discussed in detail below, we

follow the terminology of Boerner et al. (1996), who

modeled temporal changes under dynamic rules

governing transitions as ‘Old rules’ and ‘New rules’.

Based on our previous work (Coppedge et al. 2001c),

we also intentionally altered certain matrix compo-

nents for this modeling effort. For example, the long-

term future of the CRP is unknown, as funding is

controlled at the federal level by the United States

Congress and thus subject to a dynamic political

environment. Thus, this program faces an uncertain

future varying from partial or complete elimination to

continuation through renewed enrollments (Harris

1991). It is even plausible (although unlikely) that the

program could receive increased funding and oppor-

tunity for limited expansion. Similar outcomes for

juniper encroachment also exist. Although the com-

plete elimination of woody encroachment is probably

not economically or ecologically realistic, future

funding for control programs is possible given the

attention focused on the issue, the scope of the

problem (Van Auken 2000; Briggs et al. 2005), and

the increasing economic impact encroachment con-

trol can have locally (Engle et al. 1996). Thus, we

specifically altered matrix rules governing juniper

woodland and pasture transitions to build predictive

models of land cover composition resulting from

potential socioeconomic and ecological changes in

the study area.

Table 1 Descriptions of land cover types used to classify habitats in landscapes of northwestern Oklahoma, 1965–1995

Land cover type Description

Juniper woodland Wooded areas with cover of Juniperus spp. >60%

Mixed woodland Wooded areas with approximately equal cover of Juniperus and deciduous spp. and total woody cover >60%

Deciduous

woodland

Wooded areas with >60% cover of deciduous trees such as Quercus, Populus, and Celtis spp.

Shrubland Areas with >50% cover of short-statured woody perennials

Native grassland Areas dominated by native herbaceous perennial vegetation

Pasture Land used for grazing or hay production; dominated by perennial forage grasses, such as Cynodon, Eragrostis, or

Bothriochloa spp.

Cropland Annually cultivated agricultural areas

Developed Includes residential areas, petroleum production sites, ponds, and roads

1386 Landscape Ecol (2007) 22:1383–1393

123

Results

Land cover dynamics

Land cover change between 1965 and 1981 included

an 8% increase in cropland cover in the Eagle City

area, with decreases in deciduous woodland and

shrubland, and slight increases in juniper and mixed

woodlands. An 8% decrease in native grassland cover

occurred during this same period in the Tegarden

area, along with small increases in cropland, pasture,

deciduous and mixed woodland. Other than minor

increases in cropland, deciduous woodland, and

shrubland, land cover type changes from 1965 to

1981 were relatively small in the Lookout area

(Fig. 1).

Land cover type dynamics were more pronounced

in the region during the 1981–1995 period. Both the

Eagle City and Tegarden areas saw increases in

juniper woodland of 4–5% total composition and

decreases in deciduous woodland. Cover of mixed

woodland more than doubled in the Eagle City area,

while native grassland cover declined by 4%. In

contrast, native grassland cover increased slightly in

both the Tegarden and Lookout areas. All areas saw

increases in pasture (6–8% of cover type composi-

tion) with similar decreases in cropland cover

(Fig. 1). The relative rate of cover type change was

much higher from 1981 to 1995 than in the earlier

period of 1965–1981. Overall, cell transition occurred

at a relative higher frequency in the Eagle City area,

wherein 30 and 37% of the cells changed cover type

during each respective time period. Less than 25% of

the cells changed in the Teagarden area, and less than

20% changed during any time period in the Lookout

area. Thus, based on our sampling, land cover type

transitions occurred at about twice the rate in the

Eagle City area as in the Lookout area (Fig. 2).

Land cover change and differences among areas is

also evident in nearest neighbor probabilities. In the

Eagle City area, juniper woodland was first observed

in 1981, and was most often bordered by cells of the

same cover type in 1981 (92% juniper–juniper

adjacency). Between 1981 and 1995, the spread of

juniper across the Eagle City area resulted in juniper

having more neighbors of differing cover types.

Juniper woodland-native grassland adjacency dou-

bled from 1981 to 1995 from 8 to 15%, while

juniper–juniper adjacency declined during this period

%0

%02

%04

%06

%08

%001

5991 1891 5691

Cov

er ty

pe c

ompo

sitio

n

5991 1891 5691

repinuJdnaldoow

dexiMdnaldoow

suoudiceDdnaldoow

dnalburhS

evitaNdnalssarg

erutsaP

dnalporC

depoleveD

5991 1891 5691

ytiC elgaE nedrageT tuokooLFig. 1 Land cover type

dynamics for three areas of

northwestern Oklahoma,

1965–1995

0

5

01

51

02

52

03

53

0418-5691

59-1891

Rat

e of

cov

er t

ype

chan

ge (

%)

Eagle City Tegarden Lookout

Fig. 2 Rates of land cover type changes for three areas of

northwestern Oklahoma for two time periods, 1965–1981 and

1981–1995

Landscape Ecol (2007) 22:1383–1393 1387

123

from 92 to 80%. Nearest neighbor adjacency was

relatively more dynamic in the Tegarden area.

Juniper–juniper adjacency declined by half from

1965 (50%) to 1981 (25%), then more than doubled

from 1981 (25%) to 1995 (63%). Juniper woodland in

1965 had a 30% probability of being adjacent to a

developed cell. By 1981, that probability had fallen to

0%, suggesting that juniper control efforts were

conducted in areas nearest human developments. In

the Lookout area, shrubland adjacency varied widely,

showing steadily increasing proximity to deciduous

woodland from 1965 (0%) to 1981 (10%) to 1995

(41%). Shrubland self-adjacency declined during this

same period from 88 to 80 to 38%. Pasture-native

grassland probability also increased in this area from

1981 (10%) to 1995 (67%), whereas developed area

self-proximity declined drastically from 1981 (50%)

to 1995 (20%).

A total of 94 cells transitioned to juniper or mixed

woodland in the three areas from 1965 to 1995. Of

these 94 cells, only three had juniper in a neighboring

cell prior to their transition. This results in an

inconsequential 3.2% likelihood of a cell being

converted to or affected by juniper if it is present in

an adjacent cell.

Stationarity tests

The test for statistical independence of the transition

matrix P produced a v2 statistic of 3,844, far

exceeding the critical value of 68 at p = 0.05

(df = 49). Thus, land cover type transitions in the

region are not random. The null hypothesis of equal

transition matrices among the three study areas (i.e.,

spatial stationarity) was rejected (v2 = 223; df = 112;

p < 0.05), indicating that transition matrices were

significantly different among the study sites. Simi-

larly, the null hypothesis of equal matrices between

time periods (i.e., temporal stationarity) was also

rejected (v2 = 263; df = 56; p < 0.05), indicating that

P(t) transition matrices also differed between time

periods. A third stationarity test was conducted to

examine the potential interaction of these factors

(space and time) on cell transitions. After partitioning

the main effects from the test statistic, the remaining

value (v2 = 86; df = 112) did not exceed the critical

value (p > 0.05), indicating that transition matrices

did not differ among areas over time periods.

Spatial and temporal differences in transition

matrices can be summarized by examining the self-

replacement probabilities of each land cover type

(Table 2). In all areas and time periods, native

grassland, cropland, and developed cover types

exhibited the most stability and highest probability

of self-replacement. In contrast, shrubland and pas-

ture exhibited the lowest self-replacement rates in

general, but especially so during from 1965 to 1981.

Consistent with known processes affecting this

region, some cover types had highly variable rates

of self-replacement. Pasture increased dramatically

from 1981 to 1995, consistent with the CRP imple-

mentation timeframe. But in the Eagle City area,

which contained the highest relative amount of

cropland (Fig. 1), pasture self-replacement was

particularly low. Juniper woodland was essentially

non-existent in this region in 1965, and what little

occurred in that time period (1965–1981) apparently

did not persist. But by 1995, when juniper had

Table 2 Self-replacement probabilities for land cover types by area and time period as identified by tests of transition matrix

stationarity from 1965 to 1995 in the northwestern Oklahoma region

Land cover type Areas (1965–1995) Time periods

Eagle City Tegarden Lookout 1965–1981 1981–1995

Juniper woodland 0.33 0.17 – 0.00 0.50

Mixed woodland 0.53 0.08 – 0.25 0.35

Deciduous woodland 0.38 0.39 0.71 0.53 0.31

Shrubland 0.05 0.13 0.57 0.11 0.19

Native grassland 0.71 0.84 0.88 0.80 0.85

Pasture 0.08 0.50 0.44 0.00 0.53

Cropland 0.79 0.84 0.78 0.91 0.71

Developed 0.94 0.81 0.85 0.85 0.88

1388 Landscape Ecol (2007) 22:1383–1393

123

become solidly established in both the Eagle City and

Tegarden areas (Fig. 1), juniper woodland self-

replacement increased to 50%. Interestingly, both

deciduous woodland and shrubland persistence was

lowest in both areas where juniper encroachment

occurred.

Scenarios of change in land cover

Although spatial transition matrices were found to

be significantly different from one another, in

preliminary modeling, differences between the land

cover changes each predicted was small and so

similar to each other as to preclude their usefulness

for further modeling. Following Boerner et al.

(1996), the temporal transition matrix resulting from

the 1965–1981 time period was termed the ‘Old

rules’, whereas the temporal model produced from

the latter 1981–1995 time period was termed the

‘New rules’. After modeling each of these matrices

separately, we focused modeling exercises on mod-

ified versions of the ‘New rules’ matrix as it best

accounted for recent changes driving land cover and

landscape pattern dynamics in the region. When

considering only transition probabilities >0.1 and

spatial positioning in a box-and-arrow schematic,

‘New rules’ cover type dynamics were clearly

partitioned into two groups relative to the native

grassland matrix and whether transitions from native

grassland were to either semi-natural and natural or

intensively-managed land cover types (Fig. 3). This

made the basic model and modifications thereof

ideal for predicting future scenarios under variable

land management alternatives.

To simulate potential change in land management

regimes, we modified values in columns or rows of

the ‘New rules’ matrix for juniper woodland and

pasture cover types to create a number of cover type

transition scenarios for modeling. For example,

conversion rates of other cover types to both juniper

and pasture (columns of matrix P) were doubled to

simulate a possible increase in juniper encroachment

and CRP. Conversely, conversion rates to juniper and

pasture were halved to simulate decreased juniper

encroachment or increasing juniper control efforts,

whereas halving the rate of pasture conversion could

indicate CRP reduction or elimination. Similarly, we

doubled and halved conversion rates of juniper and

pasture to other cover types (rows of matrix P) to

simulate similar changes in land management. For

example, increased conversion of juniper woodland

to other cover types could be indicative of juniper

control efforts, whereby increased conversion of

pasture to other cover types could also be an

indication of CRP reduction or elimination.

The ten non-stationary Markov models (Baker

1989) produced for use in modeling future land cover

possibilities predicted different and varied land cover

scenarios for the region in the year 2045. The ‘Old

rules’ pre-dated both CRP implementation and juni-

per encroachment. However, this was a period of

some agricultural intensification (see Sect. ’Introduc-

tion’). Aptly, this model predicted a 50% increase in

regional cropland cover from 1995 levels; a decline

in native grassland, shrubland, and pasture cover

types; and declines in juniper and mixed woodland.

The ‘New rules’ model predicted substantial differ-

ences in land cover, including nearly 50% reduction

suoudiceDdnaldoow

13.0

repinuJdnaldoow

05.0

dexiMdnaldoow

53.0

depoleveD88.0

erutsaP35.0

dnalporC17.0

dnalburhS91.0

62.0

22.0

52.081.0

31.0

33.0

31.051.091.0

91.0

91.0

03.052.0

52.022.0

sepyt revoc dnal larutan-imes dna larutaN sepyt revoc dnal deganam-ylevisnetnI

evitaNdnalssarg

58.0

seitilibaborp noitisnarT91.0 - 1.0 92.0 - 2.0

≥ 3.0

Fig. 3 Box and arrow diagram illustrating land cover

transition rules for the northwestern Oklahoma region, 1981–

1995. For clarity, only transition probabilities >0.1 were

included. Values within boxes are self-replacement probabil-

ities, whereas values positioned on arrows are transition

probabilities

Landscape Ecol (2007) 22:1383–1393 1389

123

in cropland cover in the year 2045 and an increase in

all three woodland types, native grassland and pasture

(Table 3).

By doubling the rate of observed conversion to

juniper woodland, predicted composition of juniper

woodland would actually triple from observed 1995

levels by the year 2045 (Model A, Table 3). In

contrast, either halving the conversion rate to juniper

(Model B) or doubling the conversion rate of juniper

(Model C) would not only result in juniper woodland

composition remaining near observed 1995 levels, it

would also result in a modest increase in native

grassland and pasture. Halving the conversion rate of

juniper resulted in land cover predictions that were

similar to the original ‘New rules’ model (Model D,

Table 3).

Doubling the conversion rate of cover types to

pasture (Model W) and halving the conversion rates

of pasture to other cover types (Model Z) produced

similar results, essentially doubling the amount of

pasture cover by 2045. As with the ‘New rules’

model, all four scenarios wherein pasture transition

rates were modified predicted decreases in cropland

cover from 1995 levels regardless of the type or

direction of change in transition rules (Table 3).

Discussion

We found site-specific rates of land cover change

ranging from 15% in 16 years in the Lookout area to

over 35% in 14 years in the Eagle City area (Fig. 2).

This equates to 2.5% of the landscape cover changing

annually in the Eagle City area. Unfortunately,

neither land cover change rates nor numbers of

transitions for specific cells, patches or points useful

for deriving such rates are common in the literature,

making land cover change rates comparisons difficult

(Burgi et al. 2004). However, we were able to

calculate such rates from data reported by Muller and

Middleton (1994), who found that urbanization of

agricultural land was the biggest land use change in

the Niagara region of southern Canada. In their study,

rates ranged from 7% in a 16-year period to 12% in

13 years. Thus, our observed rates are relatively high

for a depopulating, rural agricultural region (Roberts

1987) not undergoing urbanization.

Studies in forested systems have shown that

landscape structure is a key determinant in both the

extent and type of cover types change (Iverson 1988;

Pan et al. 1999). Furthermore, landscape attributes

may influence the rate and probability of change

Table 3 Results of Markov model projections of transition matrices to predict land cover type composition after a 50-year period.

Projections began with observed 1995 cover type data which are included for reference

Composition Land cover type %

Model Year Juniper

woodland

Mixed

woodland

Deciduous

woodland

Shrubland Native

grassland

Pasture Cropland Developed

Observed 1995 4.1 2.5 3.9 1.3 46.1 8.0 28.2 5.5

‘Old rules’ 2045 0.3 1.9 5.1 0.8 42.9 1.3 42.4 4.9

‘New rules’ 2045 7.0 4.1 4.5 1.3 50.6 10.1 17.0 4.9

Conversion rates to juniper

(A) Doubled 2045 12.6 4.0 4.5 1.0 46.0 9.8 16.7 4.9

(B) Halved 2045 4.0 4.2 4.4 1.5 53.2 10.2 17.1 5.0

Conversion rates of juniper

(C) Doubled 2045 4.3 5.0 5.2 1.3 51.6 10.1 17.1 5.0

(D) Halved 2045 9.8 3.2 3.7 1.3 49.8 10.0 17.0 4.9

Conversion rates to pasture

(W) Doubled 045 6.9 4.1 4.3 1.3 49.3 16.5 12.6 4.7

(X) Halved 2045 7.1 4.2 4.6 1.3 51.2 6.1 20.1 5.1

Conversion rates of pasture

(Y) Doubled 2045 7.2 4.2 4.6 1.4 53.7 5.5 18.0 5.0

(Z) Halved 2045 6.9 4.1 4.4 1.2 47.2 15.2 15.8 4.9

1390 Landscape Ecol (2007) 22:1383–1393

123

relative to woody plant encroachment as well (Brown

and Carter 1998). Our previous work also showed

that grassland structure was a key determinate of

juniper encroachment extent and severity (Coppedge

et al. 2001c). Thus, grassland landscapes containing

large numbers of smaller, intermingled patch types

(i.e., high landscape heterogeneity and diversity)

appear to provide an environment conducive to rapid

woody encroachment by providing isolated patches

juxtaposed with pockets of seed sources. The frag-

mented nature of these landscapes and direct human

intervention prevents the spread of fire, as does

grazing which reduces fuel loads necessary for fire

spread (Archer 1994). Thus, once a few seed-

producing woody plants are locally established and

fire is suppressed, a feedback cycle quickly begins

with seed vectors that eventually results in dense

well-established stands of woody vegetation. This

pattern appears consistent in both invasive non-native

plants such as Acacia nilotica in Australia with cattle

as seed vectors (Brown and Carter 1998), and with

Juniperus species and their avian seed dispersers in

North America (Holthuijzen and Sharik 1985).

Given the relatively rapid encroachment observed

in the region (Fig. 2) and the patterns of establish-

ment seen in other unburned southern plains grass-

lands (Briggs et al. 2002), the low self-replacement

rates for juniper woodland we observed were unex-

pected. However, in our study period of 30 years,

only the latter 14-year period had any noticeable

juniper expansion. This is much less than the 40-year

timeframe in which broad areas of closed-canopy

juniper woodland can become established in more

mesic tallgrass prairie sites (Briggs et al. 2002), or the

75 years in which Ashe juniper (J. ashei) can

establish close canopy woodlands in a semi-arid area

in Texas (Fuhlendorf et al. 1996). Furthermore,

juniper growth rates are known to decline from east

to west across Oklahoma following the declining

precipitation gradient (Engle and Kulbeth 1992). This

suggests that juniper in the study area probably did

not grow quite as rapidly as those farther east in

tallgrass prairie areas, putting the likely timeframe for

closed-canopy woodland development in mixed-grass

prairie habitats somewhere between 40 and 75 years.

Despite the low rate of persistence for individual

cells of juniper woodland, overall composition of

juniper and mixed woodland did increase in the

region. Our models showed that doubling the rate of

cover type conversion to juniper woodland was

predicted to triple juniper woodland cover by 2045,

but Engle et al. (1995) estimated that juniper

encroachment was actually proceeding at an expo-

nential rate in Oklahoma. If their rate of expansion

holds true, our models may have underestimated

future levels of juniper encroachment in northwestern

Oklahoma. Given this threat, the conservation out-

look for native grassland remnants and associated

biodiversity in southern plains grassland remains

uncertain despite the high self-replacement probabil-

ities we observed for native grassland. For example,

unless comprehensive changes are made to reduce the

spread of juniper, a number of grassland obligate and

facultative birds are predicted to continue to decline

in the southern plains (Coppedge et al. 2004). By

reducing grazing and allowing herbaceous litter

buildup, small junipers can be eradicated with

prescribed burning (Engle et al. 1996). But it will

take a cultural movement to change established

management practices with nearly 95% of the Great

Plains being privately owned. The most difficult tasks

are to not only convince landowners to apply fire as a

management tool in a society with a contentious view

of burning and a propensity for litigation (Yoder et al.

2003), but also effectively applying fire in a land-

scape being continuously fragmented by exurban and

urban sprawl such as that occurring in many areas of

Oklahoma (Coppedge et al. 2001a). Interestingly, our

models predicted that halving cover type conversion

rates to juniper, as would occur in a preventative

mode of management, resulted in a slightly more

desirable land cover scenario (less juniper and total

woodland cover types, more native grassland) than

the model wherein conversion rates of juniper to

other cover types were doubled (Model B vs. C,

Table 3). This scenario coincides well with studies in

other grassland ecosystems, and we reiterate their

general conclusions suggesting that prevention and

containment of woody plant encroachment and

invasion is ecologically and economically more

feasible than efforts to eradicate well-established

areas of woody vegetation (Brown and Carter 1998;

Van Auken 2000).

An interesting phenomenon known as ‘slippage’

often accompanies agricultural land set-aside pro-

grams. Slippage is when the amount of land enrolled

in set-aside programs does not result in an equivalent

reduction in land cultivated for crop production

Landscape Ecol (2007) 22:1383–1393 1391

123

(Leathers and Harrington 2000). Slippage occurs

because producers compensate for land taken out of

production in set-aside programs by putting new

areas into production. This often results in more land

being put into crop production than before the set-

aside program began. Also, many newly cultivated

areas are often highly erosive, wetlands, or areas

never before plowed or used for cropping. Studies of

slippage rates relative to CRP implementation have

reported widely varying results. Skold (1989) re-

ported a 1% rate of slippage for wheat cultivation

between 1956 and 1985. In contrast, Joyce and Skold

(1988) reported a 55% slippage rate for the southern

plains region, which was comprised of only Okla-

homa and Texas. In southwestern Kansas, Leathers

and Harrington (2000) reported highly variable

slippage rates temporally and spatially between

1988 and 1994, averaging 53%. We noted a

substantial drop in cropland cover from 1981 to

1995, with equivalent increases in pasture during the

same period. This corresponds with known dates of

CRP implementation. However, comparing the long-

term trends, only the Eagle City area ended the study

in 1995 with an equivalent area of cropland as when

the study began in 1965. Thus, slippage may have

occurred in Eagle City but not in the other areas

studied. We speculate that slippage may be related to

the severity of juniper encroachment in this particular

area. Land owners who invested in juniper control

may have sought a venue for recovering these

expenditures, and did so through increased crop

production. Although our study produced no direct

evidence of this trend, the potential relationship

between increasing levels of woody plant encroach-

ment and agricultural intensification would make an

interesting area for future research.

Acknowledgments This work was supported by the USDA

NRI Competitive Grants Program (grant no. 9600853) and the

Warth Distinguished Professorship at Oklahoma State

University. We thank J. Swicegood and B. Blankenship for

assistance with data entry and analysis. This article is published

with the approval of the director, Oklahoma Agricultural

Experiment Station.

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