Landscape structure and bird species richness: implications for conservation in rural areas between natural parks

Landscape and Urban Planning 49 (2000) 35±48

Landscape structure and bird species richness: implications for conservation in rural areas between natural parks Joan Pinoa,*, Ferran RodaÁa, Josep Ribasb, Xavier Ponsa,c a

Center for Ecological Research and Forestry Applications (CREAF), Universitat AutoÁnoma de Barcelona, 08193 Bellaterra, Spain b Entenc,a 6, 08100 Mollet del ValleÁs, Spain c Departament de Geogra®a, Universitat AutoÁnoma de Barcelona, 08193 Bellaterra, Spain Received 23 March 1999; received in revised form 30 November 1999; accepted 21 January 2000

Abstract Regional planning is bound to play an increasing role in nature conservation policies because much biodiversity is located outside natural parks and other protected areas. Differences in landscape structure between natural parks and surrounding areas may affect their respective species richness and may provide seasonal habitats that enhance total biodiversity. To test these ideas, we analyzed patterns of bird species richness, and its associated conservation value in a largely forested rural area that lies between the natural parks of Sant Llorenc, del Munt and Montseny (Catalonia, NE Spain). Relationships of species richness with spatial gradients (X and Y Universal Transversal of Mercator (UTM) coordinates) and with altitude and landscape variables were tested by stepwise multiple regression analysis. Regressions were performed separately for both breeding and wintering species, and considering both all species and only several dominant ecological groups (forest, forestcropland and cropland species). Bird species richness and its associated conservation value were higher in the study area than in the surrounding borders of natural parks. Cropland and forest-cropland species concentrated outside the natural parks, whereas forest species were uniformly distributed. Total bird species richness was mainly related to landscape diversity and to abundance of open habitats like croplands and shrublands. Cropland species were the most dependent on the abundance of crops and on landscape diversity, whereas forest and forest-cropland species exhibited weak correlations with landscape variables. Most forest species were year-round residents, whereas forest-cropland and cropland species exhibited seasonal shifts in the number of species, mainly because of interchanges with other areas. Results indicate that rural areas play a role complementary to the surrounding natural protected areas in the conservation of bird species richness at different scales. Implications for the design and optimization of ecological networks in the perimetropolitan area of Barcelona are discussed. # 2000 Elsevier Science B.V. All rights reserved. Keywords: Landscape structure; Bird species richness; Rural planning; Conservation biology

1. Introduction *

Corresponding author. Tel.: ‡34-93-5812915; fax: ‡34-93-5811312. E-mail address: [email protected] (J. Pino) 0169-2046/00/$20.00 # 2000 Elsevier Science B.V. All rights reserved. PII: S 0 1 6 9 - 2 0 4 6 ( 0 0 ) 0 0 0 5 3 - 0

Land-use changes are a major cause in the decline of biodiversity in recent decades (SouleÂ, 1991; White et al., 1997). Traditional conservation efforts have

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focused on maintaining charismatic (rare, vulnerable, endangered) species primarily by minimizing exposure to human activities through establishment of protected areas, but without taking a regional, more holistic view (Farina, 1998). However, since ecological systems are ®rst and foremost networks of interacting populations, the close relationship between the conservation of the ecological functionality of natural areas and the preservation of biodiversity is becoming evident (Solbrig, 1991; Barbault, 1995). Consequently, traditional conservation thinking has evolved to a new one that shifts emphasis from species to ecosystems and even landscapes or regions (Barbault, 1995; Machado, 1996; Miller et al., 1997; White et al., 1997). As a result of this trend, the ecological value of areas placed outside protected sites is increasingly recognized. Indeed, these areas act not only as linkages between natural areas, but they also take part in many landscape ecological processes (Felton, 1996). Conservation policies usually tend to enhance restoration of natural forest and shrubland communities by promoting land reclamation in these areas, in order to improve their corridor functions in future ecological networks (Nowicki, 1996). These policies are related to current thinking in conservation biology, which identi®es fragmentation of natural habitats as one of the major threats for the conservation of ecosystem functionality worldwide (Hobbs, 1994; Meffe and Carroll, 1994). However, the design of ecological networks rarely takes into consideration areas with abundant seminatural habitats such as crops and pastures, although these habitats play an important role in the conservation of ecological processes and endangered species (Barbault, 1995; Farina, 1995; Paoletti, 1995). Landscape ecology provides a suitable conceptual framework for the development of ecological networks because it focuses attention on spatial and temporal dynamics and promotes larger-scale view than traditional site-based conservation (Forman and Godron, 1986; Forman, 1995; Rookwood, 1995; Fry, 1996; White et al., 1997). Landscape structure usually determines and is in turn determined by many, if not most, ecological processes (Forman and Godron, 1986; Forman, 1995), meaning that spatial analysis of a landscape might be a sound way to understand the underlying ecological relationships (Turner and Gardner, 1993; Miller et al., 1997; Farina, 1998). This analysis has often been performed by not only study-

ing the relative abundance of the different landscape units but also by de®ning landscape indices that try to describe landscape structural and functional properties (Forman and Godron, 1986; Turner, 1989; Colville, 1995; Aronson and Le Floc'h, 1996; Miller et al., 1997; Farina, 1998). The aim of this paper is to highlight the role of rural areas placed outside natural parks in the conservation of biodiversity and ecosystem processes using simple landscape analysis. The study analyzed the spatial and temporal pattern of bird species richness, a major component of species biodiversity in the Mediterranean region, and its relationship with several relief and landscape attributes in a largely-forested rural area sited between natural parks in the perimetropolitan area of Barcelona. We ®nally discuss the implications for landscape planning in these areas and also for optimizing the design of an ecological network in the perimetropolitan area of Barcelona, where local and regional administrations are increasingly interested in developing strategies to enhance biodiversity and landscape conservation at a regional level. 2. Material and methods 2.1. The study area The study was carried out in the perimetropolitan area of Barcelona (Catalonia, NE of Spain), an area with several mountain ranges dominated by Mediterranean forests and shrublands and ¯oodplains occupied by crops and urban areas (Fig. 1). Conservation efforts during the last two decades have led to the establishment of natural parks in the main ranges, where intense afforestation has been enhanced by land abandonment and also by conservation policies subsequent to delimitation of protected areas. A rural area of 480 km2 between Sant Llorenc, del Munt and Montseny natural parks (Figs. 1 and 2) was selected for the study. This is a transition area from the inland plateaus of the Iberian Peninsula to coastal ranges, with a NW±SE gradient from a continental to a maritime climate, and also from submediterranean to Mediterranean conditions. Land cover of the area is dominated by forests (Table 1), with a gradient from deciduous oak (Quercus humilis) and Scots pine (Pinus sylvestris) forests in the NW to holm oak

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Fig. 1. Geographic location of the study area, between the natural parks of Sant Llorenc, del Munt and Montseny in the central coastal area of Catalonia (NE Spain). The main natural areas and cities of the perimetropolitan area of Barcelona are represented in grey and black areas, respectively. Small border corresponds to the study area.

(Quercus ilex) and Aleppo pine (Pinus halepensis) forests in the SE. Non-irrigated herbaceous crops are abundant in the ¯at areas. Human settlements are mainly concentrated in the SE area, which is included into the dispersed urban system around Barcelona. 2.2. Bird species richness Bird species distribution was studied from 1992 to 1998 by ®eld sampling by one of us (JR). The study

area was divided following the Universal Transversal of Mercator (UTM) 1 km1 km squares. Each of these UTM squares were sampled once or twice a year for both breeding and wintering species. Samplings were conducted from March to July to record breeding species (i.e. those species that displayed reproductive activity in their reproductive habitat and during their reproductive period), and from November to February to record wintering species. In each sampling, a transect of about 1±1.5 h of

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J. Pino et al. / Landscape and Urban Planning 49 (2000) 35±48

Fig. 2. Land-use map of the study area in 1987 based on a reclassi®cation of Landsat categories. Minimal and maximal UTM-31N coordinates (in m) are shown. The study area is that included within the small border. Black convolute lines correspond to the limits of Sant Llorenc, del Munt (left) and Montseny (right) natural parks.

duration was made each year by walking within each UTM square. Along these transects, bird species were recorded by both visual and hearing contacts, and Table 1 Landsat landscape units in the study area (1987) Landsat landscape unitsa

Relative ground cover

Coniferous (pine) forests Shrublands Herbaceous non-irrigated crops Sclerophyllous oak forests Urban dispersed areas Deciduous oak forests Herbaceous irrigated crops Denuded areas Towns and villages Non-irrigated orchards Industrial areas Irrigated orchards Vineyards

0.445 0.214 0.162 0.071 0.023 0.022 0.021 0.016 0.014 0.011 0.018 0.001 0.001

a

VinÄas and Baulies (1995).

main habitat preferences were assigned to each of them. Species were assigned to one of these habitat categories according to their predominant ecology: aquatic habitats, crops, forests, shrublands, rocks and cliffs, urban habitats, and several combinations of them (forests±crops, rocks±crops, urban±crops). This assignment was performed basically from ®eld data, and also from bibliographic sources (Baucells et al., 1999). Data concerning species as a whole and for each habitat category were summarized in the number of both breeding and wintering species per UTM square, and converted to raster format using MiraMon, an in-house developed geographic information system (GIS) (Marcer and Pons, 1998). 2.3. Conservation value Species were also classi®ed according to their conservation status using two indices derived from

J. Pino et al. / Landscape and Urban Planning 49 (2000) 35±48

the EU Birds Directive (70/409/CEE) and the IUCN criteria for Spanish vertebrates (Blanco and Gonzalez, 1992). The Directive-based index was computed by assigning a value of 1 to the species included in the Birds Directive, and 0 to the remaining species. For the IUCN-based index, species were scored as 0 (not threatened), 1 (insuf®cient data), 2 (non-determined), 3 (rare), 4 (vulnerable), and 5 (threatened). For each index, and separately for nesting and wintering species, the conservation values of all species present within each UTM 1 km1 km square were summed and rasterized, yielding maps of the distribution of the conservation importance for the bird fauna in the study area. 2.4. Landscape information The landscape structure of the study area was analyzed from a land-use raster generated by the Cartographic Institute of Catalonia (ICC) using multispectral TM images obtained by the satellite Landsat 5 during 1987 (VinÄas and Baulies, 1995). After successive processes of simpli®cation and classi®cation, the de®nitive raster had a spatial resolution of 30 m30 m, and included the thematic categories or landscape units shown in Table 1. This land use raster was used to calculate several landscape indices for each 1 km1 km UTM square: P 1. Habitat diversity Hˆÿ pi log…pi †, corresponding to Shannon and Weaver's diversity index calculated for each UTM square, where pi corresponds to the proportion of the area covered by each landscape category, and log is the logarithm to base 2. P 2. Habitat dominance Dˆ‰Hmax ‡ pi log…pi †Š= Hmax , which measures the value of dominance of one landscape category over the others. Hmax corresponds to the maximum Shannon diversity index, calculated as the log of the number of landscape categories. 3. Landscape microscale heterogeneity, measured by means of two patchiness indices: the number of different landscape categories (NDC) and the number of landscape categories different from that of the central cell (CVN). Both indices were calculated in a grid of 33 cells around each cell in the land use raster, and subsequently their mean

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value for each UTM 1 km1 km was obtained. The GIS Idrisi was used for this purpose. 2.5. Altitude data Data on the relief of the study area were obtained from a Digital Elevation Model (DEM) generated by the ICC from topographic 1:50,000 maps. The DEM has a spatial resolution of 45 m and it was used to calculate the minimal, mean and maximal altitudes within each UTM 1 km1 km square. 2.6. Spatial variability of bird species richness and relationship with relief and landscape variables Factors affecting the spatial distribution of bird species richness were analyzed considering different variability sources: (1) a set of physical and landscape parameters, (2) regional gradients, and (3) the remaining autocorrelation at a more local level. Stepwise multiple regression analysis was used to assess the signi®cance of landscape and relief variables and that of spatial gradients in explaining the spatial pattern of both breeding and wintering bird species richness. Stepwise multiple regression, already used in similar studies (Rafe et al., 1985), adds independent variables accounting for their contribution to total variance, thus giving an ordination of relative importance (from more to less) of these variables in the regression. Altitude data, landscape indices, and the cover proportion of the different landscape units were considered as physical and landscape variables. Landscape units were grouped into basic categories (forests, shrublands, crops, urban areas and other) to reduce the number of independent variables and thus increase the robustness of the analysis. A third-order polynomial constructed with X and Y UTM coordinates was added to the model to account for the spatial variability due to regional and local gradients, thus performing a trend surface analysis in the regression model (Burrough and McDonell, 1998). X and Y coordinates were previously rescaled by subtraction of their means in order to avoid collinearity problems derived from the inclusion of the different th-power terms of the polynomial (Rawlings et al., 1998). The inclusion of surface analysis in the regression model permitted the reduction of autocorrelation to acceptable levels. Indeed, maximum Moran coef®cients

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(Cliff and Ord, 1981) calculated for each regression model ranged from 0.15 to 0.28. Stepwise regression analyses were performed separately for nesting and wintering species, ®rst pooling together all habitats, and thereafter for species grouped into forest, cropland and forest-cropland categories, which were the predominant species groups in the study area. Correlation analyses between all landscape, altitude and position variables were previously performed in order to select the de®nitive independent variables. As a result, landscape dominance and heterogeneity indices, and maximal and minimal altitudes were rejected because they were highly correlated (r2>0.8) with landscape diversity and mean altitude, respectively. Forest cover was also discarded because of its high negative correlation with cropland and shrubland cover (multiple r2ˆ0.98). Final variables considered in the analyses are summarized in Table 2. 3. Results 3.1. Distribution and components of birds species richness A total of 114 nesting and 108 wintering bird species were recorded in the study area. Spatial richness of both breeding and wintering bird species was not uniformly distributed across the study area (Fig. 3), but concentrated mainly in the SE and in the N. These areas correspond respectively to the ValleÁs and the MoianeÁs plains, with an heterogeneous landscape made up by a matrix of non-irrigated herbaceous crops and abundant forest and human settlement patches. The rest of the study area, with a more homogeneous landscape broadly dominated by forests and shrublands, exhibited much lower values of bird species richness. The conservation value of bird fauna exhibited a similar pattern (Fig. 4). Indeed, high values of both UE Birds Directive and IUCN indices associated with either nesting or wintering species concentrated outside the natural parks. Correlation between both indices was moderate (r2ˆ0.39) for nesting species and high (r2ˆ0.80) for wintering species. The majority of bird species were classi®ed into three ecological groups: forest species (24% of all nesting species and 20% of wintering species), crop-

Table 2 Variables used in the different stepwise multiple regression analysesa Variables Dependent variables Nesting species Total number of species Number of forest species Number of cropland species Number of forest-cropland species Wintering species Total number of species Number of forest species Number of cropland species Number of forest-cropland species Independent variables Landscape Diversity index Relative shrubland cover Relative cropland cover Relative cover of urban areas Relief Mean altitude Position UTM X coordinate UTM Y coordinate X2 coordinate Y2 coordinate XY coordinate X3 coordinate Y3 coordinate XY2 coordinate X2Y coordinate a

Regression analyses were performed using all the independent variables for each dependent variable.

land species (16% of nesting and 28% of wintering species) and forest-cropland species (25% of nesting and 14% of wintering species). The spatial distribution of species richness for these main groups was rather different (Fig. 5). In a manner similar to total species richness, cropland species concentrated outside the natural parks, and mainly to the N and the SE of the study area where open habitats (mainly dry-land herbaceous crops and fallows) are dominant. Forestcropland species were also more concentrated in agricultural areas, mainly in the N where the landscape is made up by a crop±forest mosaic. In contrast, forest species richness exhibited a more uniform

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Fig. 3. Spatial pattern of breeding and wintering bird species richness in the study area. Legend gives the number of bird species for each UTM 1 km1 km square. White lines correspond to the limits of Sant Llorenc, del Munt (left) and Montseny (right) natural parks. Plotted area coincides with the small border of Fig. 2.

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Fig. 4. Spatial pattern of the conservation importance of both nesting and wintering bird species richness, according to EU Birds Directive and IUCN criteria. Legend gives for each UTM 1 km1 km square the number of bird species included in the EU Directive and the mean conservation value according to IUCN criteria (0: not threatened, 1: insuf®cient data, 2: non-determined, 3: rare, 4: vulnerable, and 5: threatened). Black lines correspond to the limits of Sant Llorenc, del Munt (left) and Montseny (right) natural parks. Plotted area coincides with the small border of Fig. 2.

distribution, with only lower values in the rural areas of the SE corner where forests are residual. For each group, the distribution pattern of bird species richness was similar between seasons, although changes in the number of species were observed.

3.2. Spatial variability of bird species richness and relationships with landscape and relief Stepwise multiple regression analyses for nesting species are summarized in Table 3. There were 10

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Fig. 5. Spatial pattern of breeding and wintering bird species richness for the main ecological groups of birds in the study area. Legend gives the number of bird species for each UTM 1 km1 km square. Black lines correspond to the limits of Sant Llorenc, del Munt (left) and Montseny (right) natural parks. Plotted area coincides with the small border of Fig. 2.

variables signi®cantly correlated with the spatial variations of total nesting species richness (accumulated r2ˆ0.389, F10,448ˆ28.493, p<0.0001). Cropland cover was the most signi®cant variable (multiple r2 changeˆ0.144), displaying a positive correlation, and was followed by shrubland cover (0.098), the X coordinate (0.039), and landscape diversity (0.044). Cropland species exhibited a closer relationship with the independent variables (r2ˆ0.712,

F9447ˆ122.88, p<0.0001). The most signi®cant variable was cropland cover (multiple r2 changeˆ 0.625) which exhibited a positive relationship with cropland nesting species richness and represented 88% of the total correlation. Forest and forestcropland species showed weaker relationships with the selected variables than cropland species (r2ˆ0.462, F12,444ˆ31.800, p<0.0001 for forest species and r2ˆ0.394, F13,443ˆ22.184, p<0.0001 for

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Table 3 Stepwise multiple regression analyses for nesting bird species richnessa Variables

Regression coefficient (standard error)

Accumulated multiple r2

Significance (p)

1. Total nesting species Relative cropland cover Relative shrubland cover X coordinate (km) Landscape diversity

11.781.46 6.911.62 ÿ0.2870.055 4.110.86

0.144 0.243 0.281 0.325

<0.0001 <0.0001 <0.0001 <0.0001

2. Cropland species Relative cropland cover Landscape diversity X3 coordinate (km3) XY coordinate (km2)

10.930.45 1.570.35 ÿ0.00010.0003 ÿ0.0130.003

0.624 0.664 0.675 0.688

<0.0001 <0.0001 <0.0001 0.0047

ÿ6.440.68 ÿ10.391.60 0.0020.001 ÿ0.0120.003

0.297 0.384 0.414 0.428

<0.0001 <0.0001 <0.0001 0.0010

5.120.87 5.580.74 ÿ0.2610.057 1.940.49

0.194 0.234 0.323 0.351

<0.0001 <0.0001 <0.0001 <0.0001

3. Forest species Relative cropland cover Relative cover of urban areas Mean altitude (m) X2 coordinate (km2) 4. Forest-cropland species Relative shrubland cover Relative cropland cover X coordinate (km) Landscape diversity a

Only the four most correlated variables are shown for each regression.

forest-cropland species). Forest species were mainly correlated with the cover of croplands (r2 changeˆ0.297) and urban areas (0.087), both with negative correlations. Forest-cropland species were positively correlated with shrubland cover (r2 changeˆ0.194) and also with the X coordinate (0.140). Stepwise multiple regression analyses performed for wintering species are summarized in Table 4. Total wintering species richness was more closely correlated with the selected variables than nesting species richness (accumulated r2ˆ0.488, F10,448ˆ42.633, p<0.0001). Cropland cover was the most correlated variable (r2 changeˆ0.367), followed by landscape diversity (0.044). In a manner similar to cropland nesting species, cropland wintering species richness exhibited a close relationship with the independent variables (r2ˆ0.646, F12,444ˆ67.396, p<0.0001). The most correlated variable was cropland cover (multiple r2 changeˆ0.563) followed by landscape diversity (0.041), both with positive correlations. In contrast, forest and forest-cropland species showed weak cor-

relations with landscape and relief variables (r2ˆ0.225, F9447ˆ14.399, p<0.0001 for forest species, and r2ˆ0.293, F10,446ˆ18.479, p<0.0001 for forest-cropland species). Forest species richness was mainly and negatively correlated with cropland cover (r2 change ˆ0.131). In contrast, forest-cropland species richness was positively correlated with the cropland (r2 changeˆ0.130) and shrubland (0.108) cover. Species richness of the different groups exhibited signi®cant and negative correlations with single, quadratic and cubic terms of UTM X, Y coordinates, indicating a non-negligible effect of spatial gradients. However, since position variables usually occupy the third or fourth position in the stepwise regression analyses and multiple correlations between the third-order XY polynomial and the dependent variables represented about a half of total correlation (ranging from 0.14 for forest-cropland nesting species to 0.33 for cropland nesting species), it can be considered that the effect of position variables was less important than that of landscape variables in explaining the variability of bird species richness.

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Table 4 Stepwise multiple regression analyses for wintering bird species richnessa Variables

Regression coefficient (standard error)

Accumulated multiple r2

Significance (p)

1. Total wintering species Relative cropland cover Landscape diversity XY2 coordinate (km3) X2 coordinate (km2)

16.641.41 2.690.80 ÿ0.0050.001 ÿ0.0210.006

0.367 0.411 0.446 0.454

<0.0001 <0.0001 <0.0001 0.0078

2. Cropland species Relative cropland cover Landscape diversity X3 coordinate (km3) Relative cover of urban areas

14.290.84 1.500.56 ÿ0.00050.0003 5.261.89

0.563 0.603 0.614 0.620

<0.0001 <0.0001 0.0003 0.0065

3. Forest species Relative cropland cover X2 coordinate (km2) XY coordinate (km2) Relative cover of urban areas

ÿ3.570.61 ÿ0.0070.003 ÿ0.0120.003 ÿ2.291.23

0.131 0.157 0.179 0.189

<0.0001 0.0002 0.0005 0.0230

4. Forest-cropland species Relative cropland cover Relative shrubland cover XY2 coordinate (km3) Y coordinate (km)

3.570.45 2.870.58 ÿ0.0120.0004 0.0620.023

0.130 0.238 0.267 0.275

<0.0001 <0.0001 0.0002 0.0284

a

Only the four most correlated variables are shown for each regression.

3.3. Ecological groups and their seasonal shifts The main ecological groups considered in the study (forest, cropland, and forest-cropland species) exhibited contrasting species shifts from nesting to wintering seasons (Fig. 6). Forest species richness remained relatively constant over the year, with 29 nesting species and 24 wintering species. The majority of species (21) remained for the winter, and the small shifts primarily took place between habitats within the study area. Cropland species exhibited a clear increase in species number (from 19 nesting to 33 wintering) mainly due to arrivals from outside the study area (14 species), and also from other habitats within the study area (eight species). In contrast, the number of forest-cropland species decreased from 30 nesting to 16 wintering, mainly due to species migrating outside the study area (17 species). 4. Discussion Fig. 6. Seasonal bird species shifts in the main ecological groups considered. Figures are number of bird species. Arrows indicate changes from nesting to wintering seasons.

In our study area, whose landscape is mostly dominated by forests, nesting and wintering species rich-

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ness are signi®cantly related to landscape diversity and landscape attributes that affect diversity, like the abundance of several open habitats such as croplands and shrublands within the forest matrix. These results agree with other previous works that demonstrate the important role of landscape structure and diversity in determining the number of available habitats which, in turn, in¯uences the number of species (Pearson, 1993; Farina, 1995; Miller et al., 1997). Indeed, landscape heterogeneity helps to increase the predictive power of species±area models for bird species (Rafe et al., 1985; Boecklen, 1986). In our case, relationships between landscape and species richness are signi®cant and relatively close even though they can be affected by the low spatial resolution used in the study (1 km1 km), and methodological artifacts related to the fact that landscapes are usually measured from a human perspective rather than from a wildlife perspective (Fry, 1996). Since total bird species richness summarizes a composite response of the habitat needs of individual species (Mùller, 1987; Hansen and Urban, 1992), the performance of separate regression analysis for the main ecological groups of birds allows to increase the predictive power of the model. Regression analyses performed for the main ecological groups of birds (forest, cropland and forest-cropland species) showed contrasting responses to landscape patterns. Cropland species were highly dependent on the abundance of crops (mainly herbaceous non-irrigated crops) and on landscape diversity, as can be expected in a landscape with a matrix made up by forests and shrublands. In contrast, forest species, which exploit the forest matrix and thus exhibit a relatively uniform distribution, showed only a weak relationship with landscape variables, especially during the wintering period. Our study highlights the importance of the rural area placed between Sant Llorenc, del Munt and Montseny natural parks for bird preservation in the perimetropolitan area of Barcelona. The conservation value of this area is not related only to the absolute number of species but also to their conservation status and their inclusion in the list of species that need special conservation measures. Indeed, several threatened birds of prey such as Bubo bubo (Eagle-Owl), Hieraetus fasciatus (Bonelli's Eagle), Falco peregrinus (Peregrine Falcon), Circaetus gallicus (Short-toed

Eagle) and Circus cyaneus (Northern Harrier), and a number of species living in open habitats are found in these rural areas but are rare or even absent in the adjacent protected areas. In addition, because of the combination of natural, seminatural, and urban habitats, rural areas are becoming hot spots of landscape diversity that allow a high concentration of species with contrasting habitat needs. This is particularly valuable in perimetropolitan environments where, in a manner similar to other areas of the Mediterranean region (Farina, 1991; Naveh, 1993; Makhzoumi, 1996), intense processes of land abandonment and afforestation affecting the traditional landscape are causing a gradual decrease in landscape diversity and complexity. These processes of land use change have been particularly intense in mountain areas, which often enjoy protected status. As a result, these areas have undergone a progressive enrichment in forest species and also a decrease in total species richness due to the gradual disappearance of species living in open areas. Therefore, rural areas adjacent to mountains are becoming more and more important for the conservation of cropland and forestcropland birds, as indicated by the grouped distribution of these species in the study area (Fig. 6). Seasonal species shifts also have implications for bird conservation at a regional scale (Farina, 1995). While the assemblage of forest bird species is the most stable over the year, cropland and forest-cropland species groups are more dynamic and undergo noticeable species shifts from nesting to wintering seasons. These shifts are determined by not only habitat changes within the same area but also by interchanges with other adjacent or separate regions. Indeed, species such as Serinus serinus and Emberiza cirlus seasonally migrate at a regional scale from forests in adjacent mountain areas in summer to open habitats in ¯at areas in winter. Similarly, many migrating birds such as C. cyaneus use croplands as wintering areas or as stepping stones in their long way northwards or southwards, thus indicating that agricultural landscapes also play an important ecological role at broader spatial scales. Several implications of these results might be considered for the design, management and conservation of bird species richness in the perimetropolitan area of Barcelona. Traditional planning, management and conservation strategies that have promoted land aban-

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donment and afforestation in protected areas should be complemented by others that consider the role of semi-natural and agricultural landscapes in providing for landscape, ecological and species biodiversity and for conserving natural resources (Yokohari et al., 1994; Makhzoumi, 1996). This might allow to preserve the existing landscape diversity, thus helping to maintain bird species richness at the landscape scale. On the other hand, ¯at agricultural areas and the adjacent natural parks play complementary roles in maintaining biodiversity components at a regional scale. While rural areas are occupied by open-habitat species and are also used by a heterogeneous pool of species as wintering areas, natural protected areas house many endangered species and, also, large populations of forest bird species that increase the colonization probability of small and isolated woodlots in the adjacent ¯at areas. A sound planning strategy would be the design of ecological networks that would include natural protected areas as core areas and rural adjacent areas as buffers, corridors or nature development areas (Nowicki, 1996). To achieve this, and since natural protected areas are often designed and managed so that a maximum number of habitats or charismatic species are represented (Pickett and Thompson, 1978; Boecklen, 1986), it is important to develop regional policies that evaluate rural landscapes for their ecological services as well as for their economic value (Naveh and Leiberman, 1990). Acknowledgements This study has been funded by the Servei d'Accio Territorial of the Diputacio de Barcelona. The authors also wish to thank J. Retana and R. Salvador for their advice in performing statistical analyses. References Aronson, J., Le Floc'h, E., 1996. Vital landscape attributes: missing tools for restoration ecology. Restor. Ecol. 4, 377±387. Barbault, R., 1995. Biodiversity dynamics: from population and community ecology approaches to a landscape ecology point of view. Landscape and Urban Planning 31, 89±98. Baucells, J., Camprodon, J., Ordeix, M., 1999. La fauna vertebrada d'Osona. Lynx, Barcelona. Blanco, J.C., Gonzalez, J.L., 1992. Libro Rojo de los Vertebrados de EspanÄa. ICONA, Madrid.

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Boecklen, W.J., 1986. Effects of habitat heterogeneity on the species±area relationships of forest birds. J. Biogeogr. 13, 59±68. Burrough, P.A., McDonell, R.A., 1998. Principles of Geographical Information Systems. Oxford University Press, New York. Cliff, A.D., Ord, J.K., 1981. Spatial processes. Models and applications. Pion, Norwich. Colville, D., 1995. Ecological landscape analysis using GIS. In: Domon, G., Falardeau, J. (Eds.), Landscape Ecology in Land Use Planning. Methods and Practice. Canadian Society for Landscape Ecology and Management, Polyscience Publications, Morin Heights, Canada, pp. 143±148. Farina, A., 1991. Recent changes of the mosaic pattern in a montane landscape (North Italy) and consequences on vertebrate fauna. Options MeÂditerraneÂenes 15, 121±134. Farina, A., 1995. Distribution and dynamics of birds in a rural subMediterranean landscape. Landscape and Urban planning 31, 269±280. Farina, A., 1998. Principles and Methods in Landscape Ecology. Chapman & Hall, London. Felton, M., 1996. Natura 2000, the ecological network of the European Union: using buffer areas and corridors to reinforce areas designated by member states. In: Nowicki, P., Bennett, G., Middleton, D. (Eds.), Perspectives in Ecological Networks. ECNC, Arnhem, The Netherlands, pp. 133±141. Forman, R.T.T., 1995. Some general principles of landscape and regional ecology. Landscape Ecol. 10, 133±142. Forman, R.T.T., Godron, M., 1986. Landscape Ecology. Wiley, New York. Fry, G.L.A., 1996. A landscape perspective of biodiversity indices, models and planning. In: Simpson, I.A., Dennis, P. (Eds.), The Spatial Dynamics of Biodiversity, Proceedings of the 5th IALE (UK) Conference, Striling, pp. 3±13. Hansen, A.J., Urban, D.L., 1992. Avian response to landscape pattern: the role of species' life histories. Landscape Ecol. 7, 163±180. Hobbs, R.J., 1994. Fragmentation in the wheatbelt of Western Australia: landscape scale problems and solutions. In: Dover, J.W. (Ed.), Fragmentation in Agricultural Landscapes. Proceedings of the 3rd annual IALE (UK) Conference, Preston, pp. 3± 20. Machado, A., 1996. Preface. In: Nowicki, P., Bennett, G., Middleton, D. (Eds.), Perspectives in Ecological Networks. ECNC, Arnhem, The Netherlands, pp. 4±5. Makhzoumi, J.M., 1996. The spatial and ecological diversity of rural landscapes as a foundation for regional planning. In: Simpson, I.A., Dennis, P. (Eds.), The Spatial Dynamics of Biodiversity. Proceedings of the 5th IALE (UK) Conference, Striling, pp. 131±138. Marcer, A., Pons, X., 1998. Park GIS implementation. In: CDROM Proceedings of the International Conference and Exhibition on Geographical Information Systems, GIS PlaNET'98, p. 68. MeffeÂ, G.K., Carroll, C.R., 1994. Principles of Conservation Biology. Sinauer Associated Inc., Sunderland, MA. Miller, J.N., Brooks, R.P., Croonquist, M.J., 1997. Effects of landscape patterns on biotic communities. Landscape Ecol. 12, 137±153.

48

J. Pino et al. / Landscape and Urban Planning 49 (2000) 35±48

Mùller, A.P., 1987. Breeding birds in habitat patches: random distribution of species and individuals? J. Biogeogr. 14, 225±236. Naveh, Z., 1993. Red Books for threatened Mediterranean landscapes as an innovative tool for holistic landscape conservation. Introduction to Western Crete Reed Book case study. Landscape and Urban Planning 24, 241±247. Naveh, Z., Leiberman, A., 1990. Landscape Ecology. Springer, New York. Nowicki, P., 1996. European ecological networks: perspectives in policy, planning and law. In: Nowicki, P., Bennett, G., Middleton, D. (Eds.), Perspectives in Ecological Networks. ECNC, Arnhem, The Netherlands, pp. 161±169. Paoletti, M.G., 1995. Biodiversity, traditional landscapes and agroecosystem management. Landscape and Urban Planning 31, 117±128. Pearson, S.M., 1993. The spatial extent and relative in¯uence of landscape-level factors on wintering bird populations. Landscape Ecol. 8, 3±18. Pickett, S.T.A., Thompson, J.N., 1978. Patch dynamics and the design of nature reserves. Biol. Conserv. 13, 27±37. Rafe, R.W., Usher, M.B., Jefferson, R.G., 1985. Birds on reserves: the in¯uence of area and habitat on species richness. J. Appl. Ecol. 22, 327±335. Rawlings, J.O., Pantula, S.G., Dickey, D.A., 1998. Applied Regression Analysis. A Research Tool. Springer, New York. Rookwood, P., 1995. Landscape planning for biodiversity. Landscape and Urban Planning 31, 379±385. Solbrig, O.T., 1991. From Genes to Ecosystems: a Research Agenda for Biodiversity. IUBS, Paris. SouleÂ, M.E., 1991. Conservation: tactics for a constant crisis. Science 253, 744±750. Turner, M.G., 1989. Landscape ecology: the effect of pattern on process. Ann. Rev. Ecol. Syst. 20, 171±197. Turner, M.G., Gardner, R.H., 1993. Quantitative methods in landscape ecology: an introduction. In: Turner, M.G., Gardner, R.H. (Eds.), Quantitative Methods in Landscape Ecology. Springer, New York, pp. 3±14. VinÄas, O., Baulies, X., 1995. 1:250 000 Land-use map of Catalonia (32 000 km2) using multitemporal Landsat-TM data. Int. J. Remote Sens. 16, 129±146. White, D., Minotti, P.G., Barczak, M.J., Sifneos, J.C., Freemark, K.E., Santelmann, M.V., Steinitz, C.F., Ross Kiester, A., Preston, E.M., 1997. Assessing risk to biodiversity from future landscape change. Conserv. Biol. 11, 349±360.

Yokohari, M., Brown, R.D., Takeuchi, K., 1994. A framework for the conservation of rural ecological landscapes in the urban fringe area in Japan. Landscape and Urban Planning 29, 103± 116. Joan Pino has a Ph.D. in biology (1995) from the University of Barcelona (Spain) and an M.S. degree in geographic information technology (1998) from the Autonomous University of Barcelona. He is also lecturer of botany and plant ecology at the University of Barcelona and a researcher at the Center for Ecological Research and Forestry Applications (CREAF). His major research topics are dynamics and management of plant populations, and the application of landscape ecology to nature conservation in perimetropolitan areas. Ferran RodaÁ has a Ph.D. in biology (1983) from the Autonomous University of Barcelona and is Full Professor of ecology at the same University. He has been the director of CREAF since 1998. His main fields of research interest are the functional ecology of terrestrial ecosystems (namely the hydrology, biogeochemistry, primary production and fire ecology of Mediterranean forests and shrublands), and the applications of landscape ecology to nature conservation. Josep Ribas has a biology degree from the Autonomous University of Barcelona and he is doing his Ph.D. at the University of Barcelona. His major research topic is the study of the bird fauna in rural areas around Barcelona. He has been monitoring bird populations of these areas for more than 6 years and he has contributed with these data to the Bird Atlas of Catalonia (NE of Spain). Xavier Pons has a Ph.D. in remote sensing and GIS (1992) and an M.S. degree in geography (1995) from the Autonomous University of Barcelona. He is Associate Professor at the Department of Geography of the Autonomous University of Barcelona and a coordinator of research activities in GIS and remote sensing at CREAF. His main work is on radiometric and geometric corrections of satellite imagery, cartography of ecological parameters from airborne sensors, spectral responses of Mediterranean vegetation, and GIS development. He has recently worked on descriptive climatology models, on modelling forest fire hazards and on the analysis of landscape changes from a long series of satellite images.