Habitat quality and connectivity in agricultural landscapes:

The role of land use systems at various scales in time

Francoise Burel a,*, Jacques Baudry b

a UMR Ecobio CNRS – Universite de Rennes 1, Campus de Beaulieu, 35042 Rennes Cedex, Franceb INRA SAD Armorique, 65 rue de Saint Brieuc, 35042 Rennes Cedex, France

Accepted 1 April 2005

Abstract

Connectivity is a key concept of landscape ecology as it relates to flows and movements of organisms as driven by landscape

structure. More and more aspects of landscape heterogeneity are considered in measuring connectivity, as the diversity of crops

in agricultural landscapes. In this paper, we explored the value of considering changes and cumulated effects of connectivity over

time. As an example, we analysed connectivity among patches influenced by maize over 7 years in an agricultural landscape in

Brittany, France.

Clear temporal patterns appeared: maize is concentrated in certain parts of the landscape, but over the period the whole area,

70% of the landscape, used for maize was connected. Instead of discrete patches, maize may produce large clusters allowing

movement from patch to patch from year to year. This reinforces the importance of understanding land use allocation rules

within farms and landscapes to evaluate the ecological effects of agriculture.

# 2005 Elsevier Ltd. All rights reserved.

Keywords: Connectivity; Agriculture; Landscape; Dynamics

This article is also available online at:www.elsevier.com/locate/ecolind

Ecological Indicators 5 (2005) 305–313

1. Introduction

In fragmented and heterogeneous agricultural

landscapes, movement is a key process for survival

of plants and animals (Wiens et al., 1993). For

mobile species, daily movements are for food search

and for predator avoidance. For all species,

individuals or propagules disperse among local

* Corresponding author. Tel.: +33 223236145;

fax: +33 223235026.

E-mail address: francoise.burel@univ-rennes1.fr (F. Burel).

1470-160X/$ – see front matter # 2005 Elsevier Ltd. All rights reserved

doi:10.1016/j.ecolind.2005.04.002

populations or colonize new habitats, at time scale of

a year or more. Before the period of land use

intensification from the 1950s onward, patches and

linear elements of semi-natural habitats facilitated

the movements of several species. Since then, these

habitats have decreased dramatically in intensively

farmed regions (Leonard and Cobham, 1977; Meeus,

1990).

Nevertheless, numerous forest species continue to

thrive in these environments (Burel, 1996). Survival of

these population is due to continuing landscape

connectivity that, in this paper, is defined as ‘‘the

.

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313306

degree to which the landscape facilitates or impedes

movement among resource patches’’ (Taylor et al.,

1993) is one of the main controls for populations of

these species (Bennett, 1999).

A direct measure of landscape connectivity, there-

fore, must incorporate a measure of some aspect of

organism movement through the landscape. Several

authors have developed the idea that ‘‘connectivity’’

of a landscape depends not only on the distance

between habitat patches, but also on the presence of

corridors and stepping stones and on the resistance of

the surrounding matrix (Fahrig and Merriam, 1994;

Moilanen and Hanski, 1998; Pain et al., 2000;

Ricketts, 2001). In agricultural landscapes, the mosaic

of crops and uncultivated patches, woodlots, heath

land, wetlands and hedgerows, influences individual

movements for carabid beetles (Martin et al., 2001),

butterflies (Ricketts, 2001), badgers (Schippers et al.,

1996) and damselflies (Pither and Taylor, 1998).

Interactions among individual movements of a species

and a given land use depend on its phenological state

(Ouin et al., 2000), available resources and/or refuge

effect (Henein et al., 1998). Millan-Pena et al. (2003)

find in Brittany, France, that in landscapes showing

similar organization of woodlands and hedgerows,

communities of carabids differ according to farming

systems. In landscapes with few woods remaining,

carabid communities in dairy farms, with a high

proportion of maize, differ markedly from the ones in

landscapes, where pig production, characterized by a

high proportion of cereals, are dominant. The first

ones have communities’ characteristic of still dense

hedgerow network landscapes. A crop such as maize

may in some instance be a substitute for woodland.

Nevertheless, measures of connectivity must

involve spatial heterogeneity of the land as well as

individual species area requirement and dispersal

distance (Vos et al., 2001) and may act as a refuge for

wildlife (Bro et al., 2004).

Agricultural landscapes are dynamic at several

temporal levels. On long-temporal scales, changes in

farming systems induce durable changes that affect the

size and the shape of cropping areas and of natural or

extensively farmed areas (Baudry et al., 2000; Le

Coeur et al., 2002). Within year growth and harvest of

crops change the mosaic of resources, among years

crop succession in a given farming system changes the

spatial arrangement of the mosaic, with no or few

effects on the shape and size of the fields (Baudry and

Papy, 2001).

Farming systems generate specific landscape

patterns for several reasons. Good agronomic prac-

tices imply that in a given landscape different annual

crops are implemented from year to year to save

nutrients and prevent diseases (Colbach et al., 1997).

Hence, as different farming systems differ by the type

of crops, the different crops of a system form a specific

pattern. Field size, topography and soil diversity also

participate to the production of landscape patterns

(Deffontaines et al., 1995).

Due to the growing interest in sustaining biodi-

versity in agricultural areas and for conservation of

integrated pest management (Altieri, 1980), it is now

important to do more than consider habitats in a binary

world that reduces a landscape to two basic categories,

suitable habitats and uninhabitable matrix (Levins,

1970; Gilpin and Hanski, 1991; Hanski, 1997). Rather

the heterogeneity of the whole matrix and its

variability through time must be included (Baudry

et al., 2003).

Therefore, measures of connectivity integrate more

and more land use heterogeneity, but usually consider

only one state of the landscape that can be past (Petit

and Burel, 1998) or most of the time current

(Tischendorf and Fahrig, 2000). We hypothesize that

organization of the shifting crop mosaic through time

may influence connectivity over years, from mechan-

isms of a step by step movement through the

landscapes using suitable habitats, which contiguity

or adjacency varies according to the farmer’s rules

from year to year. A crop mosaic is typically a shifting

mosaic from year to year. The pattern a given year may

permit the displacement of individuals of a species on

part of the landscape, the movement continues the year

after as new opportunities to move across the

landscape as a new crop pattern appears. It may then

be that after a few years the species has the opportunity

to spread out over all the landscape or only on part of

it.

In this paper, we considered the effects of a few

years’ crop successions on the measure of connectiv-

ity. The analysis is done on a set of data from a long-

term ecological research site, where land use maps are

available since 1996. The aim is to explore the

relevance of considering crop succession data at

different time steps to measure connectivity in

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313 307

agricultural landscapes. The question is the incorpora-

tion of time in ecological indicators. How different is

an indicator of connectivity measured over a single

year or over several years?

Previous simulations (Baudry et al., 2003) show

that over a single year connectivity as related to

cropping patterns is similar in random patterns and

patterns produced by using land allocation rules. Only

when cumulated over several years do the two patterns

differ.

2. Study sites

The research was carried out in a hedgerow

network landscape 60 km north of Rennes, Brittany,

France. This is a typical ‘‘bocage’’ landscape used for

milk production. Meadows (grazed or mowed), maize

for silage, forage and a few cereals make up 90% of

the land cover, with the remainder being hedges, field

margins and road verges, see a detailed description in

Baudry et al. (2000). Even where the land cover was

meadow, farming techniques and social factors have

led to differences in land use and land management.

The analysis of land use in our study area shows a

significant relationship between landscape patterns

and types of farming systems (Thenail, 2002). Within

farms, a general pattern of land use allocation to fields

is found (Thenail and Baudry, 2004), but the authors

also find deviation according to landscape structure.

The general pattern is that pastures for dairy cows are

close to farmstead, fodder for winter (maize) further

and even further cereals. Crop succession leads to a

mixture of crops; the general pattern only indicates

dominance of crops. Field size and soil hydromorphy

also influence land use (Thenail and Baudry, 2004).

Deviations in different landscapes are due to

difference in field patterns, in landscapes with a

dense network of hedgerows, fields are more scattered

and distance to farms is only relative, the mixture of

fields from different farms further blurs patterns.

3. Methods

We used the land cover maps of a 630 ha area from

1996 to 2002 to measure connectivity induced by

maize and it’s cumulating over years.

3.1. Land cover mapping

Land cover maps were digitized using both the 1/

25,000 map of the Institut National Geographique as a

background to provide the placement of roads, etc. and

air photos at the 1/10,000 scale to draw field limits.

Those air photos also provided the information of the

crops present in the different fields. The photos were

taken each year (1996–2002) in June to have a

maximum of contrast between crops, especially as

maize fields are almost bare ground.

3.2. Measures of connectivity

In this paper, we considered a habitat-specific

forest species, which moves between suitable forest

patches either for supplementation or complementation

(Dunning et al., 1992). Individuals move from patch to

patch in continuously varying elements, within spatially

explicit landscapes. Data from the literature and

previous research on our study sites underlined the role

ofmaizeasasurrogatefor forestconditionswhengrown.

So, we concentrated here our assessment of landscape

connectivity on the part due to maize fields over years

within the five surveyed years.

We looked at the spatial distribution of habitat

patches at the landscape level. Hence, the measure of

connectivity is the total size of habitat patches. To create

the patches, we used the notion of a critical distance

representing an organism ability to move between

resource patches. We considered 100 m � 100 m

windows, the average maize field size and centred on

each pixel of the map. A pixel is considered as a suitable

habitat if an individual of the target species can

move everywhere within the surrounding window.

Contiguous ‘‘habitat pixels’’ form a habitat patch.

We took the example of forest small mammals,

using methods and data provided by Sutherland et al.

(2000). The median and probable dispersal between

suitable patches is approximately 60 m; these small

mammals may use pixels as habitat, with at least 50%

of maize in the surrounding 100 m � 100 m window.

By overlaying patches of suitable habitats of the

different years, we obtain clusters representing the

frequency of connection for the different areas in the

landscape. From these maps, we extracted the area of

the different clusters formed by connected woods and

hedgerows and connected pieces of farmland.

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313308

4. Results

4.1. Dynamics of land cover and dynamics of

connectivity

Fig. 1 gives the area of maize per year, the total area

decreased of more than 10% over the period.

Fig. 2 displays examples of maps of maize

patches as defined above. Each year presents

continuous patches, but variable from one year to

the next. The total area of those patches, which is the

maize connectivity, fluctuated independently of the

area (Fig. 3). This indicates that the spatial

distribution of maize varied. A lesser area of maize

Fig. 1. Year to year are

Fig. 2. Habitat patches i

evenly spread over the landscape may lead to a

connectivity equal too the one resulting from a larger

area.

Over the period, the area at least once in a habitat

patch increased up to 70% of the whole area, levelling

off. In the meantime, the largest cumulated cluster of

maize windows (i.e. the cluster resulting from the

overlay of maize windows over time) tended to be the

only cluster. Its size increased by steps (Fig. 4), but

after 7 years, it is the area once covered by maize

windows (Fig. 4). This indicated, in this landscape,

there is an area for growing maize that is continuous

and segregated from a ‘‘non-maize’’ area. We

examined this hypothesis later.

a of maize fields.

n 1997 and 2002.

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313 309

Fig. 3. Connectivity of habitat patches.

In this area for maize, it returned with a high

frequency (up to every year) in some clusters, while it

was present only once in other area (Fig. 5). An

analysis of the map Fig. 5 showed that crowns of

decreasing frequency of maize surround clusters of

frequent maize. Patches were maize, present seven

times are mostly interconnected, and then connected

to patches of frequency 6, the same for patches of

frequencies 6 and 5 (Fig. 6). Others are not

represented. Therefore, parts of the landscape are

strongly connected for maize from year to year, parts

were never connected and other parts were links

Fig. 4. Percent of the area within a habitat patch at least once (% total) a

cluster).

between patches of strong connections from time to

time. It appeared that connectivity varied over time; it

is a time-dependent variable.

Fig. 7 displays the percent cover of the different

frequency patches or clusters. As time goes, high

frequencies increased, ‘‘frequency 1’’ decreased, but

persisted as new fields are used for maize.

Parts of the landscape with no maize were close to

streams, where woods and villages were present. Over 5

years, most woodland remained unconnected to maize

(Fig. 8), this curve of ‘‘no connection’’ levelled off

rapidly. Always the samewoods are connected to maize.

nd size of the cumulated largest cluster of habitat patches (% large

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313310

Fig. 5. Clusters cumulated habitat patches, the darker the cluster,

the more frequent the presence of a habitat patch.

5. Discussion

Variability of connectivity has been until now

restricted to aquatic systems, where ecological

connectivity depends on hydrological regime and

several studies have shown the importance of flow

regulation on aquatic macro invertebrates biodiversity

(Sheldon et al., 2002; Ward and Stanford, 1995).

Dynamics of agricultural landscapes at several

Fig. 6. Connections between clusters of different maize frequency. For the

pixels of that frequency and pixels of all frequencies (x-axis).

temporal scales is largely described, but has never

been related to the temporal variability of connectiv-

ity, except in some conceptual approach (Geertsema

et al., 2002) with no relation with actual agricultural

systems and crop rotations. Our results based on long-

term precise data on land use showed high variability

of connectivity from year to year in a given landscape,

due to the variation in area of the crops, but also on

their spatial organization.

In many studies, farming parts of landscapes are

considered as undifferentiated, it is the ‘‘matrix’’;

hence, their behavior is not taken into account. In the

landscape we studied, there are only slight differences

from year to year, but strong differences between the

different parts of the landscape when the recurrence of

patterns being looked at.

We gained insights on both aspects of the ecology

of landscapes: the first aspect is connectivity, a driver

of ecological processes; the second is the making of

landscape patterns by human activities.

Connectivity appeared to be related to time, for this

annual crop, maize, some parts of the landscape are

frequently connected, others seldom and for almost a

third of the landscape ‘‘never’’. The expected

consequences are two folds: (1) time lags effects

when studying the relationships between species

distribution and landscape structure and (2) the

constinus disconnections between certain landscape

elements. Future biodiversity sampling should take

this cumulated effect into account. It already appears

different frequencies, the graph displays the % connections between

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313 311

Fig. 7. Percent cover of the area with a habitat patch one, two, . . ., seven times.

Fig. 8. Connections between habitat patches and woods: from never (0) to six times (6). Seven times does not exist.

that crop succession is a major factor to explain field

margin floristic composition (Le Coeur et al., 2002).

Maize as a crop has specific characteristics that change

landscape: bare soil in spring, shade in summer, more

use of herbicide on the margins (Baudry and Jouin,

2003). So, frequent maize probably produce specific

landscape conditions.

One consequence is that connectivity measures

must consider ‘‘ephemeral stages’’ in landscapes.

‘‘Ephemeral’’ is the time grain over which individuals

or populations of a species can survive without being

connected to a new suitable patch. This can be less

than a year.

This pattern resulted from the land use allocation

rules that Thenail and Baudry (2004) deciphered for

this area. Not all fields with a soil suitable to grow

maize were used for that purpose, because of other

factors such as field size or distance from the farm.

Thenail and Baudry also take time into account as

they analyze the spatial distribution of crop

successions. They have found that, in this area,

the succession with most maize is present in large

fields mostly 1 km away from farmsteads. This is

consistent with our landscape analysis showing

frequent maize on specific places. The use of

frequencies instead of crop successions permitted

F. Burel, J. Baudry / Ecological Indicators 5 (2005) 305–313312

us to capture infrequent events that may be

ecologically important.

We see that there may be different standpoints

when analyzing a landscape phenomenon. From a

farming systems point of view, the question is ‘‘What

are the general rules for land use allocation?’’ and

from an ecological standpoint, the question is ‘‘How

often parts of landscape under the influence of maize

are connected?’’ The two approaches are needed to

understand landscape processes. Models of agricul-

tural landscapes must incorporate land use allocation

mechanisms to simulate landscapes considering the

heterogeneity due to cropping systems and to measure

the dynamic patterns of connectivity.

Acknowledgments

We thank the ministry in charge of the environment

(DIVA programme) and the CNRS (Zone Atelier

project) for their financial support. We are grateful to

Nicolas Schermann for preparing the original land use

maps.

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