Buntings (Emberizidae) as indicators of HNV of farmlands: a case of study in Central Italy

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Buntings (Emberizidae) as indicatorsof HNV of farmlands: a case of study inCentral ItalyF. Morellia & M. Girardellob

a University of Urbino, DiSTeVA, Campus Scientifico Enrico Mattei,61029 Urbino, Italyb Centre d’Etudes Biologiques de Chizé, CNRS UPR, 79360 Villiers-en-Bois, FrancePublished online: 05 Nov 2013.

To cite this article: F. Morelli & M. Girardello , Ethology Ecology & Evolution (2013): Buntings(Emberizidae) as indicators of HNV of farmlands: a case of study in Central Italy, Ethology Ecology &Evolution, DOI: 10.1080/03949370.2013.852140

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Buntings (Emberizidae) as indicators of HNVof farmlands:a case of study in Central Italy

F. MORELLI1,3 and M. GIRARDELLO

2

1 University of Urbino, DiSTeVA, Campus Scientifico Enrico Mattei, 61029 Urbino, Italy2 Centre d’Etudes Biologiques de Chizé, CNRS UPR, 79360 Villiers-en-Bois, France

Received 19 December 2012, accepted 26 September 2013

Farmlands represent one of the most important habitats for several bird spe-cies in Europe, but during the last few decades, agricultural landscapes have beensubject to a rapid and large-scale change, caused by the intensification and mechan-ization of agricultural activities, that is one of the main drivers of worldwide biodi-versity decline. The high nature value farmlands (HNV) are characterized throughthree criteria: low-intensity farming, presence of residual semi-natural vegetation(hedgerows, uncultivated, shrubs, scattered trees, marginal uncultivated) and diver-sity of land cover mosaic; values that are often correlated with highest farmland birddiversity. In this work, we used Generalized Linear Models to evaluate the presence ofdifferent bunting species, typical of farmlands in Central Italy, as potential indicatorsof HNV of farmland and surrogates of landscape heterogeneity. Our results showedhow the presence of bunting species is associated with markedly different environ-mental parameters. A species which could potentially be more useful for identifyingHNV farmlands (more heterogeneous landscape, supporting also greater bird speciesrichness) is the Cirl Bunting. The Corn Bunting and Ortolan Bunting were lesspredictive as indicators of farmland heterogeneity. Ortolan Bunting was unrelatedto the complexity of farmlands and bird richness. This information is important forthe planning of large-scale conservation policies and to increase our understanding offarmland bird indicators.

KEY WORDS: farmland birds, agroecosystem, landscape heterogeneity, HNVindicators.

INTRODUCTION

Farmlands represent one of the most important habitats for birds in Europe.However, during the last few decades, agricultural landscapes have been subject torapid modifications, due to large-scale changes of the land-use mosaic, caused by theintensification and mechanization of agricultural activities (CHAMBERLAIN et al. 2000;DONALD et al. 2001; FOX 2004). Recent studies have highlighted the importance of

3 Corresponding author: Federico Morelli, Università di Urbino, DiSTeVA, Campus ScientificoEnrico Mattei, 61029 Urbino, Italy. Tel. +390722304251 (E-mail: [email protected]).

Ethology Ecology & Evolution, 2013http://dx.doi.org/10.1080/03949370.2013.852140

© 2013 Dipartimento di Biologia, Università di Firenze, Italia

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landscape features for conserving habitat quality. In particular, several studies haveshown that organic systems can enhance bird diversity over non-organic counterparts,as a result of increased complexity of landscape features and also due to a lower use ofagrochemicals (BEECHER et al. 2002; BENTON et al. 2002; NORTON et al. 2009). Mainlyfor this reason, farmers are increasingly being encouraged to conserve biodiversitythrough the maintenance or preservation of semi-natural landscape features (KLEIJN

et al. 2009). Several studies have also attempted to evaluate agricultural landscapes inEurope, by identifying high nature value farmlands (HNV) (e.g. ANDERSEN et al. 2003;BARTEL 2009). HNV farmlands are characterized by three features: (1) low-intensityfarming, (2) presence of semi-natural vegetation (hedgerows, uncultivated, shrubs,scattered trees, etc.), and (3) diversity in terms of land-cover mosaic. It has beenshown how HNV are correlated with higher spatial heterogeneity of farmland andwith highest bird diversity values, too (BATÁRY et al. 2011; WUCZYŃSKI et al. 2011).

Local studies are important and needed to understand farmland systems as awhole. Although analyses developed over large geographical areas have a high gen-eralizing power, they have found limited applicability to local contexts (TRYJANOWSKI

et al. 2011) as they do not take into account regional differences in agriculturallandscapes. The identification of species more sensitive to changes in farmland fea-tures appears to be of primary importance, as they can be used as bioindicators(BURGER 2006). Among vertebrates, birds have been often used as bioindicators formany reasons, including the fact that the relationships between bird communities andvegetation or territory characteristics have been well studied (PADOA-SCHIOPPA et al.2006).

Bunting species (Emberizidae) are a relatively widespread group of farmlandbirds in Central Italy and one of the most representative of farmland landscape. Manyspecies have been listed as species of conservation concern (BIRDLIFE INTERNATIONAL

2004) but, despite their large distributional ranges, they have been rarely used asbioindicators (TRYJANOWSKI 1997). The present study aims to explore relationshipsbetween the presence of three bunting species and landscape heterogeneity surrogatesand overall bird species richness, in order to evaluate their respective importance aspossible indicators of HNV of farmlands in Central Italy.

METHODS

Eighty sampling sites were selected randomly on the agricultural landscape of the Marcheregion, Central Italy, separated from each other by at least 500 m, from the coast to 800 m abovesea level (study area centroid: 43°45'47.30“N; 12°45'5.20”E). The study area covers the maintypologies of agroecosystems present here (from extensive to intensive farmlands). The total sur-face of the study area was ca 1800 ha. Each sampled site was monitored by means of a point-count,that records all birds seen or heard within a fixed 100-m radius over a 10-min period. The fieldwork was carried out during the breeding period of 2010, from 15 May to 15 July. All bird countswere carried out in the morning within the 5 hr following sunrise, with sunny weather conditions.The sampled sites were visited at least 2 times during the breeding season. For each sampled site,species richness was calculated as the sum of all recorded bird species. The three buntings selectedfor our analyses were: Corn Bunting Milaria calandra, Cirl Bunting Emberiza cirlus and OrtolanBunting Emberiza hortulana.

The environmental variables used in this study were derived from two different sources:

(1) fine-scale variables recorded by direct observation of the habitat attributes in the field.These included terrain slope, road type and the number of electric wires, if present. Slope

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was categorized as: null slope (less than 3°), low slope (between 3 and 8°), mean slope(greater than 8°). The road type was classified as: unpaved, paved or mixed; and

(2) geographic information system (GIS)-analysis derived variables, from a regional LandCover Map (C.T.R. 1:10.000 2008). These included the area of each land use categorybased on a series of landscape metrics, calculated using land cover data extracted from afixed radius of 100 m around the sampled point. The land cover variables included wereall the categories of land use present in the regional Land Cover Map (C.T.R. 1:10.0002008).

The landscape metrics included a measure of edge density, calculated as the sum ofthe perimeters of all polygons contained in the buffer zone per number of land-usetypologies (HARGIS et al. 1998), patch richness, calculated as number of different landuse categories contained within the 100-m buffer zone, a measure of land-cover diversity,calculated using the Shannon’s diversity index: H’ = − Σpi × log pi, where pi is the relativeproportion of land-use and a shape index, calculated using a measure of perimeter-to-arearatio with the V-LATE extension for ArcGIS. Intercorrelation among environmental vari-ables was explored using a correlation matrix. The only two variables that displayed a highdegree of correlation were edge density and patch richness (rho = 0.69). All the othervariables displayed a low degree of correlation (rho < 0.30). We decided, however, to retainthese two variables, as we deemed them as equally important in determining speciesdistribution and richness patterns in farmland birds. In order to explore whether buntingspecies were related to HNV of farmlands we conducted a three-step analysis whereby we:(i) quantified the relationships between bunting occurrence and overall species richness,(ii) quantified the relationship between bunting presence and the abovementioned envir-onmental predictors and (iii) quantified the relationship between total bird species rich-ness and the same environmental variables used in Step ii.

All analyses were carried out using a Generalized Linear Modelling (GLM) approach. The errorstructure associatedwith the distributional models (Step 2) was assumed to be binomial with logit linkfunction. The error structure for the models relating bunting presence with species richness, andspecies richness with environmental predictors, was assumed to be poisson with a log link function.The models were ranked using the Akaike information criterion (AIC) and the Akaike weight for eachmodel was estimated (ωi) following BURNHAM & ANDERSON (2002). We constructed a 95% confidenceset of models by starting with the highest Akaike weight and adding to the model the next highestweight until the cumulative sum of weights exceeded 0.95. As no single model was clearly superior tothe others in the set, we used a multi-model inference approach based on model averaging. Thecoefficients were calculated as the average of all the regression coefficients within the confidence set,weighted by their Akaike weights.

All the analyses were carried out within the R programming environment (R DevelopmentCore Team 2011).

RESULTS AND DISCUSSION

Of the 80 sampled sites in the farmlands, 78.8% were occupied by at least one ofthe bunting species. The most widespread species was the Cirl Bunting, present in66.2% of our study sites, whereas the Corn Bunting and Ortolan Buntings were presentin 42.5 and 35.7% of the sites, respectively.

Our analyses showed that there was a modest correlation between the presence oftwo bunting species and overall bird species richness. The Cirl Bunting was the speciesthat showed the strongest correlation with total bird richness in farmlands (D2 = 0.31,χ2 = 26.907, P < 0.001), followed by the Corn Bunting (D2 = 0.15, χ2 = 13.2, P < 0.001).On the other hand, the presence of Ortolan Bunting was unrelated to bird richness(D2 = 0.01, χ2 = 1.44, NS).

Bunting species and HNV farmlands 3

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The bunting species showed a markedly different associations with environmentalparameters. The farmlands where Cirl Bunting was recorded were mainly characterizedby medium terrain slope, relatively high values of edge density and land cover diversity(some characteristics that can be considered as surrogate of HNV farmlands). The CornBunting was recorded mainly in relatively homogeneous farmlands (unrelated to edgedensity values or land cover diversity, and slightly negatively correlated with patchrichness). Furthermore, the species was negatively related to the amount of arableland with trees and both paved and mixed roads (Tables 1 and 2).

The Ortolan Bunting was found in all types of farmlands, independently from anyheterogeneity gradient (Table 1 and 2). The environmental variables did not seem tohave a strong effect on the occurrence of this species, shown by the results of modelaveraging (Table 1). This result is concordant with a recent study carried out in thesame area, which showed that the presence of Ortolan Bunting in Central Italy seemsless related to landscape heterogeneity than it is in northern Europe (MORELLI 2012).

Mean species richness was 15.3 ± 3.9 (max: 25, min: 5, n: 80). The highest numberof bird species was recorded on a very heterogeneous farmland. According to FULLER

et al. (1997), habitat structure and spatial heterogeneity in farmlands are stronglyrelated to bird richness and abundance, because of an increase in environmental niches(KISEL et al. 2011). Landscape structure can affect biodiversity in two ways: throughthe diversity of bio-physical conditions and through patterns of land use (WALZ &SYRBE 2013). In the specific case of farmland bird richness, the presence of residualunproductive habitat and marginal vegetation could have a key role (CERESA et al.2012; MORELLI et al. 2012; MORELLI 2013).

Our results, however, do not show a strong concordance in the responses ofspecies richness and bunting occurrence to landscape composition and heterogeneity.One possible explanation is that species richness does not strongly correlate with the

Table 1.

Ranking of the importance of the explanatory variables included in the final models. Variable impor-tance is represented by the sum of the Akaike weights across the 95% confidence set.

Variable name

Variable importance

Milariacalandra

Emberizacirlus

Emberizahortulana

Speciesrichness

Slope 0.25 0.96 0.39 0.75

Road type 1.00 0.49 0.13 0.96

Woodland 0.26 0.27 0.28 0.27

Edge density 0.33 0.73 0.30 0.43

Number of electric wires 0.40 0.34 0.25 0.34

Non-arable land (with bushes) 0.37 0.27 0.36 0.41

Patch richness 0.56 0.40 0.41 0.31

Arable land (with trees) 0.65 0.30 0.27 0.28

Land cover diversity 0.36 0.57 0.31 0.38

Mean shape index 0.45 0.85 0.53 0.32

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Tab

le2.

Mod

el-average

dpa

rameter

estimates

and95

%co

nfide

nce

limitsfortheeffectsof

theen

vironmen

talva

riab

leon

theoc

curren

ceof

thethreebu

ntingsp

ecies

andtotalbird

speciesrich

ness.

Variablenam

eAverage

deffect

Mila

riaca

landra

Emberiza

cirlus

Emberiza

hortulana

Spe

cies

rich

ness

Intercep

t2.27

(−0.39

,4.92

)−2.08

(−4.92

,0.76

)−0.82

(−3.08

,1.44

)2.59

(2.26,

2.92

)

Slope

Low

1.4(−

1.28

,4.07

)Low

0.82

(−1.19

,2.83

)Low

1.52

(−0.75

,3.79

)Low

0.25

(0.02,

0.48

)

Med

ium

0.63

(−2.12

,3.39

)Med

ium

2.74

(0.5,4.98

)Med

ium

0.83

(−1.56

,3.21

)Med

ium

0.29

(0.04,

0.54

)

Roa

dtype

Pav

ed−2.69

(−4.21

,−1.17

)Pav

ed−1.34

(−2.9,

0.21

)Pav

ed−0.15

(−1.4,

1.1)

Pav

ed−0.23

(−0.38

,−0.08

)

Mixed

−1.68

(−3.55

,0.18

)Mixed

−0.36

(−2.49

,1.77

)Mixed

−0.69

(−2.45

,1.07

)Mixed

−0.13

(−0.32

,0.06

)

Woo

dlan

d0(−

0.86

,0.86

)0.09

(−0.57

,0.76

)−0.13

(−0.72

,0.46

)0.01

(−0.06

,0.08

)

Edg

eDen

sity

0.18

(−10

.12,

10.48)

8.54

(−1.38

,18

.47)

1.17

(−6.63

,8.96

)0.38

(−0.29

,1.04

)

Numbe

rof

electric

wires

−0.15

(−0.44

,0.13

)−0.12

(−0.4,

0.17

)−0.01

(−0.23

,0.22

)0.01

(−0.02

,0.04

)

Non

-arableland(w

ithbu

shes)

1.41

(−1.71

,4.53

)0.34

(−1.73

,2.42

)0.97

(−1.34

,3.27

)−0.11

(−0.31

,0.08

)

Patch

rich

ness

−0.1(−

0.27

,0.06

)−0.04

(−0.24

,0.16

)−0.06

(−0.19

,0.07

)0(−

0.01

,0.01

)

ArableLan

d(w

ithtrees)

−0.43

(−0.92

,0.07

)−0.15

(−0.66

,0.37

)−0.07

(−0.49

,0.36

)−0.01

(−0.06

,0.05

)

Lan

dco

verdiversity

−0.9(−

3,1.19

)1.82

(−0.53

,4.16

)−0.53

(−2.21

,1.15

)0.1(−

0.11

,0.31

)

Mea

nShap

eInde

x0.19

(−0.13

,0.5)

−0.42

(−1.05

,0.21

)0.16

(−0.09

,0.4)

−0.01

(−0.03

,0.01

)

Bunting species and HNV farmlands 5

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habitat features typical of HNV farmland, as pointed out by DOXA et al. (2010). It ispossible that other components of species diversity (e.g. functional diversity) couldshow a better concordance. This, however, remains to be tested.

Buntings were used in this study because their populations have undergone asteep decline in Europe during the last decades (PONZ et al. 1996; GOŁAWSKI &DOMBROWSKI 2002; MENZ et al. 2009; MENZ & ARTLETTAZ 2011), but are widespreadspecies, typical of farmlands in Central Italy, with a high contactability rate (singingoften on exposed posts) (KOSIŃSKI & TRYJANOWSKI 2000). Furthermore, some ofthese bunting species were already proposed as indicators for agro-ecosystems(TRYJANOWSKI 1997). Our results, however, suggest that two species considered heredo not seem to be particularly good indicators of HNV farmlands. The species whichcould potentially be more useful for identifying HNV farmlands (recognized as themore heterogeneous agricultural landscape supporting often also a greater bird diver-sity) is the Cirl Bunting. The Corn and Ortolan Buntings were even less related tofarmland heterogeneity and total bird species richness. The results of this work high-lighted also how the Ortolan Bunting wasn’t a suitable species for assessment of HNVfarmlands. Contrary to the results obtained by BERG (2008) in Central Sweden, whereheterogeneity in habitat features increased the occurrence of Ortolan Bunting, inCentral Italy the species presence seems not to be linked to landscape heterogeneitymeasurements. However, the small scale and sample size prevent us from concludingthat these species are not good indicators of HNV farmlands, as shown in other studies.Most importantly, our results can help us to understand the spatial features that havegreater effect on the distribution of these farmland bird species in Central Italy. This isan important goal, considering that most of our knowledge of farmland bird ecologyconcerns only a few countries. A quick literature survey showed that 76% of studiescome from the UK, France, Netherlands, Spain, Germany and Sweden, and less than10% from Central and Eastern European countries (BÁLDI & BATÁRY 2011). So, fillingthis gap with studies carried out in Southern Europe could be very important for thedevelopment of large-scale conservation policies and increasing our understanding offarmland bird indicators (GREGORY et al. 2005; TRYJANOWSKI et al. 2011).

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