factors affecting corn bunting miliaria calandra abundance in a

7/30/2019 Factors Affecting Corn Bunting Miliaria Calandra Abundance in A

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Agriculture, Ecosystems and Environment 77 (2000) 219226

Factors affecting corn bunting Miliaria calandra abundance in a

Portuguese agricultural landscape

C. Stoate a,, R. Borralho b, M. Arajob,1a The Game Conservancy Trust, Fordingbridge, Hampshire SP6 1EF, UK

b ERENA, Av. Visconde Valmor 11-3, 1000 Lisbon, Portugal

Received 14 December 1998; received in revised form 18 June 1999; accepted 1 July 1999

Abstract

Breeding and winteringabundance of cornbuntingsin an agricultural landscape of Alentejo (southernPortugal)was assessed

in relation to agricultural intensification and other environmental variables during 19941997, using distance sampling and

multivariate regression. Bird abundancewas lowest in intensively managed farmlandin both seasons, and was related positively

to fallow area in winter and to the presence of game management and oats in spring. Fallows and oats were associated

with extensively managed farmland, but the implementation of a managed hunting regime was unrelated to agricultural

intensification. The importance of extensive arable systems to corn bunting conservation is discussed. 2000 Elsevier Science

B.V. All rights reserved.

Keywords: Agricultural intensification; Breeding abundance; Fallow; Montado; Winter abundance; Portugal

1. Introduction

Corn buntings Miliaria calandra are associated,throughout their distribution range, with arable land-

scapes. Their numbers have declined in northern

Europe since the 1960s as a result of agricultural in-

tensification (Tucker and Heath, 1994). This decline

is attributed to increased winter mortality, caused

by reduced abundance of winter food (Donald and

Evans, 1994), and to poor breeding performance

caused by increased use of agro-chemicals (Aebischer

and Ward, 1997; Brickle and Harper, in press). In-

Corresponding author.

E-mail address: [email protected] (C. Stoate).1 Present address: Biogeography and Conservation Laboratory,

The Natural History Museum, Cromwell Road SW7 5BD London,

UK. Tel.: +44-1425-652381; fax: +44-1425-651026.

creased use of herbicides throughout northern Europe

has resulted in the loss of many arable weeds, and

hence of phytophagous invertebrates, which providedan essential source of food for many farmland birds,

as Potts (1986) demonstrated convincingly for grey

partridge Perdix perdix.

Corn bunting breeding densities are currently

highest in Turkey, Spain and Portugal (Diaz and

Telleria, 1997), where their numbers appear to be

stable. Although cereal production has intensified

in parts of these countries, there still are large ar-

eas of extensively managed farmland (Bignal and

McCracken, 1996). In Portugal, Alentejo is the

main cereal growing region, and extensive systems

are still widely adopted there. Corn bunting has a

widespread distribution in this region, and is de-scribed as abundant (Rufino, 1989; Elias et al.,

1999).

0167-8809/00/$ see front matter 2000 Elsevier Science B.V. All rights reserved.

PII: S 0 1 6 7 - 8 8 0 9 ( 9 9 ) 0 0 1 0 1 - 2


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220 C. Stoate et al. / Agriculture, Ecosystems and Environment 77 (2000) 219226

In these extensive arable systems, grazed fallow pro-

vides a source of food in the form of seeds in winter

and invertebrates in summer. Cereal crops also sup-

port an invertebrate community with relatively large

insects, such as caterpillars (Lepidoptera larvae) and

grasshoppers (Orthoptera), taken by corn buntings dur-

ing the breeding season in the north of their range

(Brickle and Harper, in press). This study assesses the

abundance of corn buntings in December and April

in relation to three arable systems and other environ-

mental variables in an agricultural landscape of Baixo

Alentejo, southern Portugal, considering, in particu-

lar, various levels of agricultural intensification, and

the potential effects of fallow area and private game

interests.

2. Methods

2.1. Study area

The study area included parts or all of five ad-

ministrative regions in Baixo Alentejo (Ferreira

do Alentejo, Aljustrel, Castro Verde, Ourique and

Almodvar), with a total area of 155,000 ha. Within

this region, three land-use systems were recog-

nised: intensive agriculture, extensive agriculture and

montado (Table 1).

The intensive agriculture category is characterised

by a greater frequency (>55%) of heavy soils, much

of the area being irrigated. Wheat Triticum aestivum

and barley Hordeum distichum are the main cerealcrops, and silage grass Lolium sp., sunflower He-

lianthus annuus, sugar beet Beta vulgaris and oilseed

rape Brassica napus are also grown. Wheat yields

are 2.53.5 tonnesha1 without irrigation, but can

be almost doubled with full irrigation (P. Eden, pers.

comm., 1998). There are short rotations with little or

no fallow (e.g., sunflower-1st cereal-2nd cereal). This

system requires frequent use of fertiliser (130 units of

N2 per hectare (P. Eden, pers. comm., 1998)) and her-

bicides relative to the other land-use categories. With

the exception of some olive Olea europea groves,

there is little tree cover.

The extensive agriculture category is characterisedby thin soils and the largest average farm size of

the three categories (Table 1). There is no irriga-

Table 1

Agricultural statistics for the three land-use categories considered

in Alentejo, Portugal (source: Cordovil, 1993).

Intensive Extensive Montado

Mean farm size (ha) (all farms) 48 161 66

Small farms 10 24 17

Medium farms 69 151 154

Large farms 310 519 438

Crop area (%)

Total annual crops 81 42 28

Winter cereals 45 40 21

Sunflower 20 0.3 0

Forage crops 6 2 7

Fallow 15 52 66

Perennial crops 11 0.8 2

Olive 10 0.8 2

Vines 1 0 0

Land area per tractor (ha) 58 125 194

Livestock (%)

Sheep 68 78 83

Cattle 8 11 7Pigs 22 8 5

Goats 2 3 5

tion, and fallow area is relatively high. A typical

rotation takes the form: plough fallow-1st cereal-2nd

cereal-fallow-fallow, with fallow periods often last-

ing five years or more (Rio Carvalho et al., 1995).

Wheat yields are 1.52.5 tonnes ha1, with yields at

the lower end of this range being more common (P.

Eden, pers. comm., 1998). Triticale Triticum aestivum

Secale cereale and oats Avena sativa are frequently

grown in the extensive category, and grazed or cutfor silage. The incorporation of a fallow period into

the rotation, and the relatively low potential yields

are associated with considerably lower annual inputs

than in the intensive category.

Montado (equivalent to the Spanish dehesa) is

characterised by thin soils and tree cover, dominated

by holm oak Quercus rotundifolia and cork oak Q.

suber. Like the extensive category, there is no irriga-

tion and the fallow area is high. A typical rotation is

similar to that of the extensive category, although the

fallow stage is often longer and forage lupins Lupinus

luteus may be included.

Sheep Ovis aries, cattle Bos taurus and pigs Susscrofa are kept in all three land-use categories. Zero

grazing is adopted on some farms in the intensive cat-


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C. Stoate et al. / Agriculture, Ecosystems and Environment 77 (2000) 219226 221

egory, but livestock normally graze fallows. Table 1

lists the proportion of crops and livestock in each cat-

egory. Public hunting of wild game is open to all li-

censed hunters over much of the area, with no control

on the game bags taken and without any management.

However, some areas are managed as private or asso-

ciative game estates, implying a control on game bags

and some management measures.

2.2. Field methods

A total of 115250 m transects, starting in 1 km

grid intersections and stratified by land-use categories,

were walked along a random bearing. Transects were

walked in the first three hours after dawn, or in the two

hours before dusk, in December and April, from De-

cember 1994 to April 1997. Perpendicular distances

from the transect line to each detected bird were es-

timated visually to the nearest 10 m. The number of

birds seen together at an observation was recorded.Tree density estimates were based on counts within

a belt 25 m each side of the transect line. After each

spring count, the crop type and vegetation structure

was sampled over the first 50 m of each transect, by

plotting vegetation height on millimetric paper, and

proportional cover was determined for each of seven

height classes (Table 2). A Shannon diversity index of

these cover classes was computed for each transect.

Table 2 gives sources of other environmental variables.

In April 1997, broad-leaved weed cover within cereal

crops in extensive and intensive categories was esti-

mated within a 4 m2 quadrat at 50 m intervals along

each transect. Lepidoptera larvae and Orthoptera were

sampled using one sample of ten sweeps (of approxi-

mately 3 m amplitude) along the start of each transect,

using a 50 cm diameter net.

2.3. Analytical methods

2.3.1. Density estimates

Density estimates were calculated for each land-use

category using line transect sampling and the com-

puter program DISTANCE (Buckland et al., 1993;

Laake et al., 1993). For the data gathered in Decem-

ber, when birds were in flocks, flock size (mean 4.2,range 140) was accommodated within the analysis,

and a hazard rate model with cosine adjustments was

selected by the program. In April, flocks were not

present and individuals or pairs seen together were

recorded as single units. A half-normal model with

cosine adjustments was selected by the program and

applied to the April data. Analyses used (i) clusters

(1 individual) as analytical units, (ii) ungrouped

data, and (iii) untruncated perpendicular distance

data. A variety of recommended robust estimators im-

plemented by DISTANCE was used, the final model

selected in each case being the one with the lowest

Akaikes Information Criterion value (Buckland et

al., 1993). Differences in log-transformed density

estimates (weighed by 1/variance) between years

and land-use categories were tested using one-way

ANOVA.

2.3.2. Environmental models

In order to evaluate the main environmental factors

affecting corn bunting abundance in the study area,

two models (winter and spring) of corn bunting rela-tive abundance were computed using multivariate re-

gression and the number of buntings detected in each

transect as the dependent variable. As this could have

been affected by differential habitat visibility between

land-use categories, it was checked before analysis

whether there was a significant correlation between

the visibility-corrected line transect density estimates

and the mean number of buntings detected in each

survey/farming system, using: (i) all cases (n= 18),

and (ii) only significantly different line transect es-

timates (n= 6). These correlations were highly sig-

nificant (rs = 0.92, p< 0.001, in the first case; rs = 1,

p= 0, in the second), indicating that the number ofbuntings detected per transect and the line transect es-

timates had similar value as indices of relative abun-

dance. Before analysis, the dependent variable was

logarithmically transformed [A= log(x+ 1)] to nor-

malise the distribution of residuals and equalise the

variances (Zar, 1984). Tables 24 list the independent

variables considered and the sources of data. The data

were incorporated and manipulated in a vector-based

Geographic Information System (GIS-ArcCAD).

A two-stage analysis was followed to generate the

models, with a stepwise procedure in each stage. At

the first stage, independent variables constant in each

transect between years (see Table 2) and the logarith-mically transformed between-year averages (A) of the

number of corn buntings detected per transect were


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Table 2

Independent variables considered in the environmental models of corn bunting relative abundance

Variables Sources of data

Game management: managed or unmanaged sitea Field work

Percentage of vegetation cover on the first 50 m of

each transect, for the following height classes: 020cm,

2040 cm, 4060 cm, 6080 cm, 80100 cm, 100400cm,

400800cm

Field work

Structural diversity of vegetation cover: Shannon diversity index of above Field work

Proportion of each land-use class along the transects;

the land uses considered were plough, fallow, wheat, oats,

rye, lupin, sunflower, and olive groves

Field work

Tree density (trees/ha)a Field work

Farming system: montado, extensive agriculture, and intensive agriculturea Field work, ERENA (1994)

Distance to the nearest water line (m)a 1 : 25,000 topographic maps, GIS

Distance to the nearest dirt track (m)a 1 : 25,000 topographic maps, GIS

Distance to the nearest road (m)a 1 : 25,000 topographic maps, GIS

Average annual air humidity at 9 T.M.G. (%)a Servio Meteorologico Nacional (1975a)

Average annual rainfall (mm)a Servio Meteorologico Nacional (1975b)

Average annual temperature (C)a Servio Meteorologico Nacional (1975c)

Total length of field edges within a 500 m buffer around

the starting point of the transect (m)a1 : 30,000 aerial photographs of 1993, GIS

Diversity of land uses (Shannon index) within a 500mbuffer around the starting point of the transecta

1 : 30,000 aerial photographs of 1993, GIS

a Variables with constant values within sites between years.

Table 3

Means standard errors of the independent variables constant in each 250 m transect between years

Variables Montado Extensive agriculture Intensive agriculture

(n=42) (n=42) (n=31)

Game managed sites (%) 33.3 29.3 34.5

Tree density (trees/ha) 10.540.70 0.360.32 0.390.15

Distance to water line (m) 88.4810.27 81.639.80 102.2116.12

Distance to dirt track (m) 144.3417.19 161.5020.42 133.6222.24

Distance to road (m) 701.6288.98 870.0290.37 612.6786.38

Average air humidity (%) 76.790.37 75.900.31 79.120.26

Average rainfall (mm) 60.950.46 59.740.26 63.550.87Average temperature (C) 16.140.08 16.670.15 16.040.05

Length of field edges within a 500 m buffer (m) 3455.74136.54 1344.61155.48 1303.70185.70

Diversity of land uses within a 500 m buffer (Shannon index) 0.390.02 0.200.02 0.180.03

Table 4

Means standard errors of the independent variables not constant in each 250 m transect between years

Variables Montado Extensive agriculture Intensive agriculture

Winter Spring Winter Spring Winter Spring

Cover diversity (Shannon index) 0.670.04 0.40 0.04 0.33 0.05

Proportion plough 0.04 0.02 0.030.02 0.040.02 0.03 0.01 0.49 0.05 0.25 0.05

Proportion fallow 0.76 0.04 0.800.03 0.700.04 0.71 0.04 0.05 0.02 0.06 0.02

Proportion cereal 0.22 0.04 0.190.03 0.270.04 0.28 0.04 0.39 0.04 0.68 0.05

Proportion lupin 0.010.01 Proportion sunflower 0.04 0.02

Proportion olive groves 0.04 0.02 0.04 0.02


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considered exclusively. Variables entering the mod-

els (winter and spring) were selected through forward

stepwise selection. In the second stage, 114 transects

and two-year dummy variables were considered to

account for between-site and between-year variation,

and the remaining independent variables that changed

between years within each transect. The dummy vari-

ables were entered at step 0, and the stepwise selection

proceeded from there. Once the final models of this

stage were determined, the dummy variables were re-

placed by the variables selected in stage 1, and nested

models with all the non-dummy variables selected in

the two stages were fitted. Finally, it was checked

whether the nested models successfully explained the

between-transect and between-year variation by com-

paring the models with the dummy variables (model

1) with the nested models (model 2), using an F test,

calculated as: (model 1 sum of squaresmodel 2 sum

of squares)/(model 1 df model 2 df)/(model 1 resid-

ual sum of squares)/(model 1 residual df), the degreesof freedom being equal to (model 1 df model 2 df),

(model 1 residual df).

A correlation matrix of the selected variables was

generated for the final winter and spring models.

Additionally, significant differences between land-use

categories for the variables selected were determined

using one-way ANOVAs for the independent contin-

uous variables and chi-square tests for the categorical

ones.

3. Results

3.1. Density estimates

In winter, corn bunting density was lowest in inten-

sive, and highest in extensive categories in all three

years (Table 5), but the differences were not signif-

icant among land-use categories (F2,6 = 2.89, ns), or

among years (F2,6 = 1.83, ns).

In the breeding season, lowest densities occurred

again in intensively managed farmland. Montado

supported higher breeding densities than extensive

farmland in two years. Differences among land-use

categories were significant (F2,6 = 11.89, p< 0.01),whereas those among years were not (F2,6 =

0.16, ns).

3.2. Environmental models

Table 6 presents the environmental models.

Both nested models successfully explained the

between-transect and between-year variation in

corn bunting abundance, the comparisons with the

two-stage models being non-significant (F104,165

=

1.33, p > 0.05 for the winter models; F114,203 = 1.10,

p > 0.05 for the spring ones).

Of the variables selected by the models, fal-

low area was significantly smaller in the inten-

sive land-use category than in the others ANOVA

(F2,270 = 98.71, p< 0.001), and temperature was

higher in the extensive land-use category than the

others (F2,109 = 10.76, p


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Table 5

Relative density of corn buntings in three Alentejo farming systems in winter and spring (n= number of 250m transects), 95% confidence

limits (c.l.), total numbers of birds and the numbers of bird groups in winter (clusters)

Montado Extensive Intensive

n Density birds 95% c.l. Birds/ n Density birds 95% c.l. Birds/ n Density birds 95% c.l. Birds/

per km2 clusters per km2 clusters per km2 clusters

Winter

1994 38 33.7 19.358.9 72/27 32 170.8 73.7395.9 210/23 27 4.1 0.438.7 5/4

1995 26 35.9 17.673.4 74/19 35 48.9 17.5136.5 81/15 31 2.8 1.17.2 4/4

1996 42 37.0 22.460.7 86/34 42 104.6 61.6177.7 166/38 31 17.6 6.746.2 16/7

Spring

1995 42 55.9 46.167.8 125 42 30.0 23.039.1 60 31 29.1 21.439.7 43

1996 41 42.0 33.652.6 88 34 49.9 41.360.2 133 26 12.0 8.018.0 24

1997 42 54.5 44.466.9 109 36 35.4 27.146.2 59 28 16.9 11.425.2 25

Europe (Donald and Evans, 1994), and with the find-

ings of Diaz and Telleria (1997) in Spain. The associ-

ation with fallow also explains the low winter density

in intensively managed farmland. The relatively low

winter densities associated with montado are also con-sistent with the findings of Diaz and Telleria (1997),

who suggested that low densities in relatively enclosed

habitats, such as montado and shrubland, might be the

result of a greater risk of predation in these habitats.

Whereas Diaz and Telleria (1997) report wider

habitat use in winter than in the breeding season, the

present data suggest the reverse. In Spain, highest

breeding densities (120 birds per km2) were found in

treeless cereal cropland and grassland was preferred

over cereals, whereas in this study, montado supports

breeding densities at least as high as those of exten-

sively managed open farmland. Tree density in Alen-

tejo (10.54 trees/ha se= 0.70, range 2.4018.40)could be lower now than in the past (Natividade,

1950; Palma et al., 1985), and than that in Spain,

Table 6

Environmental models, TRANSECT and YEAR being dummy variables in the second-stage models

Winter Spring

First stage model (variables with constant

values)

A=4.640.78 Intensive 0.23 Temperature

(r=0.43, F2,95 = 10.61, p < 0.001)

A=1.100.53 Intensive+ 0.18 Game Man-

agement (r= 0.55, F2,95 =20.90 p< 0.001)

Second stage model (variables with

non-constant values)

A= 0.41+TRANSECT+YEAR+ 0.70 Fal-

low (r=0 70 F107,165 = 1.50, p < 0.01)

A= 0.25+TRANSECT+YEAR+ 0.22 Oats

(r=0.69, F117,203 =1.65, p< 0.001)

Nested model A= 3.21+ 0.09 Fallow 0.44 Intensive0.16 Temperature (r= 0.28, F3,261 = 7.33

p < 0001)

A= 0.41+ 0.25 Oats 0.21 Inten-sive+0.09 Game Management (r=0.42,

F3,300 =21.80, p< 0.001

because of government incentives to clear land for

wheat growing in the first half of the century and later

disease amongst oak trees (Vieira and Eden, 1995).

The influence of private and associative game in-

terests on breeding corn bunting abundance can beattributed to the maintenance of nesting and foraging

habitats for the red-legged partridge Alectoris rufa,

a species with similar habitat requirements to corn

bunting. Game management is already suspected to

contribute to the conservation of other non-game

species, such as bustards Otis tarda and Tetrax tetrax,

in Alentejo (Rio Carvalho et al., 1995).

Aebischer and Ward (1997) found that British corn

bunting breeding densities were positively correlated

with caterpillar abundance in cereals. In Alentejo, in-

tensive farmland receives lower fertiliser and pesti-

cide inputs than do cereal crops in northern Europe

(Eurostat, 1997, 1998), and this may account for thefact that there was no difference in the abundance of

caterpillars between intensive and extensive farm-


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land. In the current study, corn buntings were observed

carrying grasshoppers in the early morning (when they

are probably easier to catch). Although abundance of

Lepidoptera larvae appeared to be related to that of

arable weeds, higher abundance of Orthoptera in ex-

tensively managed cereals could be the result of incor-

poration of fallows into the extensive system, which

provide stable conditions over winter.

As extensively managed farmland appears to offer

suitable foraging habitats in both winter and spring,

productivity and winter survival may be highest un-

der this form of management. Although present in in-

tensively managed areas in the breeding season, corn

buntings in this habitat might represent sink popula-

tions (Pulliam, 1988), whose existence is dependent on

extensive cereal management elsewhere in the region.

In terms of corn bunting conservation, continuation of

extensive management of open cereal cropland should

be a priority. This habitat supports more bird species

of current conservation concern than any other (Tuckerand Heath, 1994; Santos, 1996; Arajo et al., 1996).

Some of these species (e.g., lesser kestrel Falco nau-

manni, great bustard O. tarda, little bustard T. tetrax

and roller Coracias garrulus) share the corn buntings

requirement for relatively large invertebrates, such as

Orthoptera.

Extensive cereal production is increasingly difficult

to justify in economic terms, and areas that are un-

suitable for intensification are experiencing a longer

fallow stage or complete abandonment, followed by

scrub encroachment or afforestation (Baldock, 1991;

Bignal and McCracken, 1996).

Adoption of appropriately designed agri-environ-mental measures provides one opportunity for the

conservation of corn buntings and other steppe species

(Potts, 1997). In part of Alentejo, a zonal plan under

EU regulation 2078/92 provides for economic mea-

sures to maintain arable management on environmen-

tal and social grounds, but implementation of such

measures has been limited by a lack of state funding,

and by poor ecological and economic understand-

ing on the part of farmers. Encouragement of game

management for private or associative hunting could

provide one means of maintaining more ecologically

beneficial practices. These issues should be addressed

if the core of Europes corn bunting population andmany of the continents most threatened birds are to

be maintained.

Acknowledgements

This study was part of a wider project on biodiver-

sity of European farming systems and was funded by

ERENA and the European Commission Environment

Programme (PL93-2239). Additional funding was pro-

vided by the Portuguese Institute for Agrarian Re-

search (INIA) through the project PAMAF-8151. Peter

Eden provided agricultural information. Nicholas Ae-

bischer advised on statistical analysis. He, Francisco

Moreira and an anonymous referee helped to improve

the manuscript.

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