Determinants of bird species richness: role of climate and vegetation structure at a regional scale

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1 Journal of Biogeography, 26, Determinants of bird species richness: role of climate and vegetation structure at a regional scale Victor R. Cueto 1 and Javier Lopez de Casenave 2 1 División Ornitología, Museo Argentino de Ciencias Naturales Bernardino Rivadavia, Av. Angel Gallardo 470, 1405 Buenos Aires, Argentina and 2 Departamento de Biología, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Piso 4, Pabellón 2, Ciudad Universitaria, 1428 Buenos Aires, Argentina Abstract We examined the respective roles of climate and vegetation structure on geographical variation in bird species richness. The Province of Buenos Aires (central-eastern Argentina) was divided into 146 squares of 50 km on a side. For each square we evaluated the number of bird species, the value of thirteen climatic variables, and the value of a vegetation strata index. The climatic matrix was analyzed by Principal Component Analysis (PCA), and the first factors resulting from PCA were considered as multifactorial climatic gradients. Simple and Partial Correlation Analysis among bird species richness, vegetation strata, and the first two factors derived from PCA (65% of total variation) indicated that bird richness distribution was determined by the availability of vegetation strata, associated with different vegetation types that, at the same time, were influenced by the climatic conditions summarized in the first climatic factor (a gradient of precipitation, relative humidity, annual termical amplitude, and frost occurrence). This relationships reflect the complexity of factors that can act directly as well as indirectly on the geographical patterns in species richness. Also, we evaluated the importance of study scale comparing our results with previous studies at macrogeographic and local scales, found out that the vegetation structure was the principal determinant of bird species richness at this three geographical scales. Keywords Bird species richness, climatic gradients, vegetation structure, spatial scale, Buenos Aires Province, Argentina. INTRODUCTION The geographical distribution of species is a result of the action of both historical and ecological factors in time and space (Vuilleumier & Simberloff, 1980). The number of species present at a given locality can be viewed as a variable that responds to the influence of several (local) ecological factors, while (largely temporal) historical factors are responsible for the biogeographic species pool from which the local community is derived (Ricklefs, 1987; Wiens, 1991). Among the numerous ecological factors that determine the spatial variation of bird species richness, climate seems to be important at the macrogeographic scale (Tramer, 1974; MacArthur, 1975; Herrera, 1978; Rotenberry, 1978; Schall & Pianka, 1978; Short, 1979; Heggberget, 1987; Virkkala, 1987; Root, 1988; Tellería & Santos, 1993, 1994). In addition, habitat structure (usually measured through estimates of vegetation structure) is also related to variations in bird species richness (Pitelka, 1941; Recher, 1969; Rotenberry & Wiens, 1980; Crowe & Crowe, 1982; Emlen et al., 1986; Gentilli, 1992; Tellería et al., 1992). However, few studies have assessed the respective roles of climate and vegetation structure (but see Rotenberry & Wiens, 1980; Tellería et al., 1992). Myers & Giller (1988) point out that, at a macrogeographic scale, the effect of habitat structure could be negligible and the role of climate be more important, whereas the inverse situation could occur at a local scale. However, such situations are the extreme points in a gradient of geographical scale. One needs to explore the relationship between ecological patterns and study scale in intermediate situations (Böhning-Gaese, 1997). Rabinovich & Rapoport (1975) in an analysis of geographical variation in species richness of passerine birds in Argentina, found that it does not only depends on temperature, rainfall and topography, but also on vegetation structure. The comparison of their macrogeographic results with an analysis 1999 Blackwell Science Ltd

2 488 Victor R. Cueto and Javier Lopez de Casenave Figure 1 Phytogeographic map of Buenos Aires Province, Argentina, from Cabrera (1968) as modified by Narosky & Di Giacomo (1993); and the index of availability of vegetation strata. at a regional scale, could help to understand whether the factors that act upon species diversity patterns depend on scale. We studied the geographical variation of bird species richness at a regional scale in the Province of Buenos Aires, centraleastern Argentina, in order to evaluate the role of both climate and vegetation structure as determinants of spatial pattern of bird species richness. METHODS Table 1 Climatic variables and their factor loadings for the firsts principal components derived from Principal Component Analysis accomplished on climatic matrix data of Buenos Aires Province, Argentina. Climatic variables Factor 1 Factor 2 January average temperature July average temperature January maximum temperature July minimum temperature Annual termical amplitude Number of days with spring frost Number of days without frost Number of days with snow cover Total annual precipitation January precipitation July precipitation January relative humidity July relative humidity Percentage of variance account Giacomo (1993). For each species these authors provide a map in which the sites where it has been recorded are indicated. Species with doubtful presence in the Province (following the classification in Narosky & Di Giacomo, 1993) were not considered here. This includes those which currently do not inhabit in the Province, or which were misidentified, or those which are accidental. Also, records prior to 1938 were not considered, since could not have value at present (see Narosky & Di Giacomo, 1993). For this reason, we considered that our bird species richness data for grassland vegetation type (see below and Fig. 1) reflect the composite effects of natural grasslands and agriculture lands. On the distribution map of each species we overlaid an acetate sheet of the Province of Buenos Aires, divided into 146 squares km. This procedure enabled us to establish a reference system on which the presence or absence of each species can be recorded and, consequently, to assess the bird species richness in each square. The size of the square was determined by a strictly geographical criterion (sensu Birks, 1987), that took into account the degree of detail and the form in which the geographical species distributions in Narosky & Di Giacomo (1993) were expressed. Climatic characteristics of the Province were analyzed through 13 variables (see Table 1). These were selected in function of the potential effects they could have on birds (Rotenberry, 1978). We overlaid the grid of 146 squares on climatic maps (Burgos, 1968; Chioza & Figueira, 1981; Defina, 1992), obtaining the values of the thirteen variables in each The Province of Buenos Aires (about 307,570 km 2 ), located in central-eastern Argentina (Fig. 1), includes the most important agricultural zones of the country. For that reason, both the climatological record and the floristic inventory of this Province are available. Grasslands and, at present, the agroecosystems, constitute the dominant plant communities (Fig. 1). In the northeast of the Province there is a zone occupied by riparian forests (Selva Paranaense, Cabrera, 1976), along the coasts of the Paraná, Uruguay, and de la Plata rivers. A coastal strip in the northeastern and eastern parts is occupied by xerophilous woodlands ( talares ) of Tala (Celtis tala) and Coronillo (Scutia buxifolia), which grow on the banks of the Paraná and de la Plata rivers, and along the Atlantic coast (Parodi, 1940). In the southwest, there are scattered remnants of xerophilous woodlands ( caldenales ) of Calden (Prosopis caldenia) (Parodi, 1940). Finally, the southern portion of the Province is occupied square. The resulting data matrix (146 squares 13 variables) by a shrub-steppe of Jarilla (Larrea divaricata) that forms the was submitted to a Principal Component Analysis (PCA), after southeastern border of the Monte Phytogeographic Province previous standardization of the variables. First components (Morello, 1958). resulting from the PCA synthesize the greater part of the climatic Bird species distribution in the Province of Buenos Aires is variation. The spatial expression of each PCA component was well known (see Narosky & Di Giacomo, 1993; references considered a multifactorial climatic gradient that can be related therein). The information on geographical distribution of to both bird and vegetation distribution. passerines in Buenos Aires was taken from Narosky & Di Information about the natural vegetation of the Province of

3 Determinants of bird species richness 489 Buenos Aires was obtained from Cabrera (1968), and also from more recent descriptions in Narosky & Di Giacomo (1993). For each vegetation type corresponding to Phytogeographic Provinces or Districts in Buenos Aires Province, we established the following number of vegetation strata: Riparian Forest= 4; Talar woodland=3; Caldenal woodland=3; Shrub-steppe= 2; Grassland=1. Superposing the grid of 146 squares on the vegetation map (Fig. 1), we determined the availability of vegetation strata in this form: for each square we established the number of vegetation strata corresponding to vegetation type that covers more than 50% of the square. Statistical relationships among variables representing climate, vegetation structure and bird species richness were analysed through Simple Correlation Analysis and Partial Correlation Analysis. The last was used to solve the problem of the interactions among variables (Zar, 1996). The first climatic factor derived from the PCA was transformed with a squared function to comply with the requirement of lineality between variables (Zar, 1996). RESULTS We evaluated the geographical distribution of 197 passerine bird species in Buenos Aires Province. Species richness was greater in the northeastern part of the Province, where it surpassed 100 species/square. The smaller values were found in the centre of the Province, while the richness was intermediate in the southwest (Fig. 2). We used the first two factors derived from the PCA performed on climatic data, because only these two factors Figure 2 Geographic variation of bird species richness in Buenos had eigenvalues greater than 1. These two factors explained Aires Province, Argentina. 65% of the variation among squares for the considered variables (Table 1). The first factor was associated with a southwest northeast gradient (Fig. 3) generated by an increase in suggesting (although it did not prove it), that the independent precipitation and relative humidity and a decrease in annual variable that remained constant (i.e., vegetation strata) was termical amplitude and spring frosts towards the northeast the cause of the association detected in the Simple Correlation (Table 1). The second factor was related to a Analysis between the bird species richness and the first climatic southeast northwest gradient (Fig. 4) determined by an increase factor. The second climatic factor had neither a relationship in January average temperature and annual termical amplitude with bird species richness nor with vegetation strata (Tables 3 towards the northwest (Table 1). and 4). The availability of vegetation strata was greater in the northeast of the Province, where riparian forests and talares woodlands are found. In the southwest, the values were DISCUSSION intermediate due to the presence of the caldenales woodlands The distribution of animal diversity has been often explained and the shrub-steppe, and in the centre it was minimum, in terms of simple environmental factors. Temperature coinciding with the grasslands (see Fig. 1). (MacArthur, 1975; Heggberget, 1987; Root, 1988), energy Simple Correlation Analyses indicate that bird species supply (Wright, 1983; Turner et al., 1987, 1988; Currie & Fritz, richness was related mainly to the availability of vegetation 1993; Wright et al., 1993), and productivity (Abramsky & strata, secondarily to the first climatic factor, and that it Rosenzweig, 1984; Owen, 1988; Rosenzweig & Abramsky, was unrelated with the second climatic factor (Table 2). The 1993) has been alternatively considered as key factors in the relationship between bird species richness and availability of determinantion of geographical variations of diversity. In vegetation strata was maintained when the effects of the climate contrast, Abramsky (1988) observed that productivity as well were controlled (Partial Correlation Analysis, Table 3); but the as habitat structure are important in the determination of the association between bird species richness and the first climatic diversity of desert rodents in Israel, and Tellería & Santos factor was lost when the effect of vegetation strata was (1994) pointed out that habitat structure as well as climate controlled (Table 3). This pattern arises from the association affect the distribution of individual bird species in Iberian between the availability of vegetation strata and the first temperate forests. The results of this study support, in principle, climatic factor (Partial Correlation Analysis, Table 4), the hypothesis that simple factors are important in generating

4 490 Victor R. Cueto and Javier Lopez de Casenave Figure 3 Geographic variation of the first climate factor derived from Principal Component Analysis performed on climatic data of Buenos Aires Province, Argentina. Figure 4 Geographic variation of the second climate factor derived from Principal Component Analysis performed on climatic data of Buenos Aires Province, Argentina. geographical patterns of species richness, since bird species our study at a regional scale. Thus, the vegetation structure richness in Buenos Aires was correlated with the availability was a principal determinant upon the spatial pattern of bird of vegetation strata. However, it was evaluated through the species richness at the two scales, whereas the climate was different vegetation types present in the Province, that are in a secondary (or indirect) factor on that pattern. Indeed, a turn influenced by climatic conditions summarized in the first simplification of the vegetation structure within the talares climatic factor (i.e., a gradient of precipitation, relative woodlands appears to decrease bird species richness (Cueto, humidity, annual termical amplitude and spring frosts 1996). So, we could infer that vegetation structure is the occurrence). In conclusion, bird species richness distribution in principal determinant of bird species richness at three spatial Buenos Aires Province is influenced by a simple factor, but also scales: macrogeographic, regional, and local. However, our there are factors that acts indirectly in the determination of analysis is based on remarkable differences in terms of bird distribution. This result reinforces the idea that the study vegetation structure (grasslands, shrub-steppe, woodlands, of animal distribution patterns in large areas must be carried riparian forest). It would be interesting to study if the out through integrative approaches (Tellería & Santos, 1994; relationships among climate, vegetation and bird species Brown, 1995). richness at different scales are supported when look at an area The perception of the relative importance of habitat structure where differences in climate generate differences in vegetation and/or climatic factors on species distributions could depend composition rather than in vegetation structure (e.g. different on the scale of analysis (Wiens, 1989). In Argentina, types of forests). macrogeographic variation of bird species richness appears to Böhning-Gaese (1997) demonstrated for landscape scale the be mainly related to the availability of vegetation strata (Simple importance of variables related to spatial heterogeneity over Correlation Analysis, r=0.912) and secondarily to mean annual those related to available energy. We obtained for regional temperature (r=0.752), altitude (r=0.392), and precipitation scale a similar result. Furthermore, when we explored the (r=0.289) (Rabinovich & Rapoport, 1975). Though these importance of different scales on bird species richness authors did not analyze the interaction among variables, their distribution, we also detected the same patterns at results at a macrogeographical scale were similar to those of macrogeographical and regional scales. These results did not

5 Determinants of bird species richness 491 Table 2 Simple Correlation Analyses (d.f.= 144) among bird species richness, vegetation structure (evaluated with an index of availability of vegetation strata, see methods) and the two first factors derived from Principal Component Analysis performed on climatic data. Vegetation structure First climatic factor Second climatic factor Bird species richness NS Vegetation structure NS First climatic factor 0.01 NS P< ; NS not significant. Table 3 Partial Correlation Analysis (d.f.= 144) among bird species richness, vegetation structure and the two first factors derived from Principal Component Analysis performed on climatic data. Vegetation structure First climatic factor Second climatic factor Bird species richness 0.54 t= t=0.74 NS 0.06 t=0.69 NS P< ; NS not significant. Table 4 Partial Correlation Analysis (d.f.=144) among vegetation Chioza, E. & Figueira, R. 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