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Keywords:

  • afforestation programmes;
  • area effects;
  • bird communities;
  • habitat structure;
  • management;
  • nested subsets;
  • pine plantations

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix
  • 1
    Afforestation of the Northern Negev, Israel, from 1956 resulted in patches of primarily coniferous trees that fragmented large scrubland areas. This alteration in landscape pattern was followed by immigration of mediterranean bird species to the Negev.
  • 2
    We counted breeding birds, and measured various environmental variables in scrubland and planted forest patches, to test whether bird assemblages were random subsets of the regional species pool, and whether area or habitat structure was the major correlate with species abundance and distribution.
  • 3
    Of 22 bird species recorded, only three appeared in both scrub and forest, showing that these two habitats were occupied by different species assemblages. In both habitats, species richness increased with area at a rate greater than that expected by random sampling. In the scrub this increase was related to area per se, while in the forest it was related to habitat diversity in terms of stand age and tree type.
  • 4
    The density of forest species was unaffected by area, but specialist scrubland species declined as area decreased. We suggest that edge effects might reduce species abundance in small scrubland patches.
  • 5
    Nested subset analysis indicated that, at the community level, species composition was not random. However, at the species level, the distribution of three forest-dwelling species appeared as random, as it was associated with habitat rather than with patch size.
  • 6
    Our results indicate that increased diversity of breeding birds in the Northern Negev will require scrub patches larger than 50 ha among the increasingly forested landscape. In contrast, increasing forest area would hardly increase species diversity in the whole landscape. Future forest management regimes should also aim to increase habitat diversity by adding foliage layers, especially in the understorey. Exotic coniferous forests support fewer species than deciduous forests in mediterranean zones around the world. The suggested management regime may improve such forests as habitat for species-rich bird communities.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix

Habitat fragmentation due to the conversion of natural habitats into agricultural, industrial or urbanized land has received much attention from conservation biologists (Saunders, Hobbs & Margules 1991; Haila, Saunders & Hobbs 1993; Fahrig & Merriam 1994; Murcia 1995; White et al. 1997). These studies have extended the view of habitat area loss per se to postulate that two more components might be important: (i) reductions in average habitat patch size and (ii) the increase in patch isolation, which turns habitat patches into islands (Andren 1994). Studies of habitat fragmentation generally emphasize the response of biological populations to changes in patch size, shape or configuration at various scales (Picket & Cadenasso 1995; Wiens 1995). In fragmented landscapes, reduction in patch size and increasing isolation enhance the negative effect of the reduction in total habitat area on population size (Andren 1994). Habitat fragmentation often reduces connectivity, which breaks continuous populations into metapopulations (Hanski & Gilpin 1991) or source–sink populations (Pulliam 1988). It may also increase negative edge effects from stochastic processes (reviewed by Simberloff 1994) or from predators or parasites that enter small patches from the core environment (Ambuel & Temple 1983; Wilcove 1985; Blake & Karr 1987; Robinson et al. 1995). The extirpation of a particular species from isolated fragments may be followed by recolonization by individuals of the same or different species according to the concept of dynamic equilibrium (MacArthur & Wilson 1967). Whether a species is re-established and remains in sink populations (Pulliam 1988), or fails to recolonize a patch, may, in turn, influence species diversity.

Prior to the development of landscape ecology, species abundance, distribution and diversity were generally related to habitat structure (MacArthur & MacArthur 1961; Pianka 1967; Cody 1975). Following the theory of island biogeography (MacArthur & Wilson 1967), ecologists have tried to separate the effects of area and habitat structure by various experimental and statistical methods (Schoener & Schoener 1981; Tonn & Magnuson 1982; Haila 1983; Haila, Jarvinen & Kuusela 1983; Kohn & Walsh 1994).

A major process that both alters and fragments natural habitats is the creation of pine plantations. Exotic pine forests have become increasingly popular in afforestation programmes in mediterranean zones world-wide (Gordo & Gil 1990; Cal 1994; Barbero 1995). For example, pines have been planted in Spain in large areas where oak woodlands were initially cleared to create arable land (Gordo & Gil 1990; Diaz et al. 1998). Studies on bird communities suggested that the reforestation of these former arable lands with pines might not increase forest bird species diversity because suitable microhabitats for specialists are absent, especially in the understorey (Lopez & Moro 1997; Diaz et al. 1998).

In the Northern Negev, Israel, thousands of hectares of scrubland have been afforested with exotic conifers (mostly Pinus halepensis Mill, Pinus pinea L., Pinus canariensis Smith and Cupressus sempervirens L.) since 1956. The mediterranean and semi-arid scrubs of Israel are characterized by low and thick perennials that are unique habitat for specialists such as the long-billed pipit Anthus similis (Shirihai 1995). While many studies on birds in fragmented habitats have involved natural forests fragmented by commercial clear-cutting (Ambuel & Temple 1983; Blake & Karr 1987; Moller 1987; Lynch & Saunders 1991; Robinson et al. 1995; Telleria & Santos 1997), the Negev provides an opportunity to assess effects where forest is the new habitat fragmenting open habitats. Over the past four decades, these forest islands have grown both in size and age, while the once continuous scrub area has become a patchy habitat. These changes in landscape structure have been followed by dramatic changes in the local bird community composition. One conspicuous phenomenon was the immigration of several mediterranean bird species from northern and central Israel to the Negev and their establishment in the plantations (Shirihai 1996).

We investigated whether bird abundance and distribution correlated with area or habitat structure in planted forest and scrubland patches in the Northern Negev. We assumed that two different processes shape bird assemblages in each habitat. In the fragmented scrub we assumed that the reduction in patch size leads to extinction of specialist species, whereas in the planted forests the observed bird assemblage would be the product of colonization. Because the spatial scale in our study was relatively small, we did not consider distance from source populations as an important factor affecting forest bird species diversity. Five of the species studied were long-distance migrants, and the spatial scale of our study is negligible compared with the distance to their wintering grounds. Rather, we assumed that bird species colonize forest patches according to the presence of their preferred habitat subtypes (in terms of tree types or age). We hypothesized that assemblages in both habitats are non-random sets of a regional species pool, and are not the result of an increase in species richness due to increasing area and sample size (Connor & McCoy 1979; Haila 1983) but rather are affected by habitat structure or edge effects (hereafter biological effects). We predicted that (i) in each habitat there will be an increase in both species richness and species diversity with an increase in patch size; (ii) in the fragmented scrub, where specialist species exist, area will be a major correlate with species diversity and population density; and (iii) in the forest, habitat structure will be the primary correlate with species diversity and population density, whereas area would be of minor importance.

Study area and methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix

Study area

Within an area of 1000 km2 north of Beer-Sheva, Israel (Fig. 1), we sampled all habitat patches (scrub or forest) larger than 50 ha. Patches smaller than 50 ha were selected according to their resolution level. That is, we selected patches with well-defined borders from the rest of the environment, so that patch size and habitat characteristics could be defined. Altogether we sampled 14 scrub patches that ranged from 2·5 to 2000 ha, and 10 forest patches between 4 and 3000 ha. The study area was located between the mediterranean zone in the north and the desert zone in the south. Average annual precipitation decreases from 350 mm in the north to 250 mm in the south. Settled and agricultural habitats exist, but semi-desert scrub and planted forests cover about 80% of the total area.

image

Figure 1. A map of the studied forest and scrub patches north of Beer-Sheva, Israel. Scrub patches larger than 50 ha are shown. For more information see text.

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Bird and habitat sampling

To sample bird densities we used line transects (Bibby & Burgess 1992) of 250 m that were surveyed for 15 min each. Generally, all 250 m fell within the plot. In four cases, however, the transect crossed plots of different habitat subtypes (e.g. young – old coniferous; pine – broadleaf plots) because plantations were too small. We counted pairs, singing males and active nests within 50 m to each side of the line. All bird counts were done by three observers throughout three consecutive breeding seasons, 1996–98. Birds flying overhead were not counted. As patch area increased, the number of transects increased from 1 to 10 (log number of transects = 0·35 log area – 0·55). This protocol allowed us to cover most of the habitat subtypes in the forest (e.g. different stand age, broadleaf and coniferous plots) because the number of habitat subtypes was not linearly correlated with area. Censuses lasted for 4 h from first light. Because summer birds arrive in late spring and breed later than resident birds, we repeated each transect three times during each breeding season (late March–mid-June). For the same reason, for each species we used the highest number observed per transect (see the Appendix for common and scientific names).

We sampled habitat characteristics by measuring several variables in each line transect plot (250 × 100 m). In forest transects we randomly chose 20 trees and measured their height, diameter at base (basal area; BA), diameter at breast height (d.b.h.) and distance to the nearest neighbouring tree. Height of tall trees was recorded by measuring the length of a tree shadow standardized against the shadow length of a 1-m pole.

Within each line transect plot we measured natural vegetation cover along two 50-m transects (vegetation transect). Along each vegetation transect, we measured the total proportion of area covered by low perennial plants (mainly Sarcopoterium spinosum, Euphorbia hierosolymitana, Ballota undulata and Phlomis brachyodon; nomenclature after Danin 1970). The density of large bushes (above 1 m, mainly Thymelaea hirsuta, Rhamnus palaestinus and Ephedra campylopoda) was measured by counting all bushes in a line transect plot. We then randomly selected half of the bushes and measured maximum width and height to the nearest 10 cm.

Because our study area was located on the border between two biogeographical zones (mediterranean and desert), we included altitude, longitude and latitude of each transect in our analysis. Some mediterranean species (e.g. Sardinian warbler, Eurasian jay, long-billed pipit and rock sparrow) were found only in the northern part of the study area; desert species were found only in the south (desert finch and desert lark: border with the Negev Desert) or east (desert lark and scrub warbler: border with the Judean Desert).

To assess how environmental factors might affect the distribution of individual bird species, we performed detrended canonical correspondence analysis (DCCA) using canoco (ter Braak 1986, 1992). Densities of each species on a transect were first averaged over the three breeding seasons, 1996–98. Environmental data used in the analysis included both geographical and vegetation variables measured during spring 1997 (Table 1).

Table 1.  Results of PCA showing the first three axes (PC1, PC2 and PC3) of habitat structure and environmental variables at our Northern Negev research site (see text for details). The numbers represent correlation of each variable with each axis. Only significant loadings (P < 0·05) are shown
VariablePC1PC2PC3
  1. d.b.h., diameter at breast height.

Area −0·523−0·554
Altitude −0·600−0·752
Longitude −0·625−0·663
Latitude−0·301  
Tree height  0·942  
Tree density  0·880  
Basal area  0·961  
d.b.h.  0·942  
Perennial cover−0·875  
Total tree species  0·856  
Bush density −0·530  0·562
Bush height −0·722  0·531
Bush width −0·743  0·542
% variance 40·519·117·9
Total percentage 40·559·677·5

Gradients in biogeography and vegetation structure among plots were described using principal component analysis (PCA; Morrison 1967) based on 13 environmental variables. We calculated component scores for each plot from the first three principal components (PC) extracted during the analysis.

To assess how bird species respond to environmental variables, we used stepwise multiple regression (holding P to enter = 0·05 and P to remove = 0·1) in which bird densities were the dependent variable. We first regressed the abundance of each species against each environmental variable separately, starting with PC 1, 2 and 3 (following Blake & Karr 1987). When bird densities were significantly correlated with one or more of these components, we did not use individual environmental variables to explain bird abundance, but noted which environmental variable gave the best fit. When species densities were not correlated with any PC variable, we correlated densities against each true environmental variable. Only in cases where functions appeared non-linear, and where non-linear transformations yielded a better fit, did we apply these transformations to the model. We did either second-degree polynomial or exponential transformations and always selected the variable with the best fit (i.e. the one with the highest r2).

Species richness and diversity

We plotted species–area curves for scrub and forest patches on a log–log scale (Arrhenius 1921) for all passerine species. To test whether the increase in species richness with area was due to random sampling or biological factors, we calculated Fisher's alpha diversity index (Fisher, Corbet & Williams 1943) using the total number of individuals and species extracted from all three breeding seasons. The random sample hypothesis (Connor & McCoy 1979) stated that larger patches sample more individuals of a regional species pool, and therefore more species. The observed species–area relationship is therefore expected by chance. However, an increase in Fisher's alpha with sample size indicates that species richness increases due to biological factors, such as habitat structure, edge effects or isolation (Rosenzweig 1995). We chose this index because other indices, such as rarefaction (Sanders 1968) or Simpson's index (Simpson 1949), may, by themselves, be sensitive to sample size (Rosenzweig 1995). To test whether changes in species diversity are scale-dependent, we applied linear and higher-order polynomial regression analysis to the observed species diversity patterns (i.e. the change in Fisher's alpha as patch size increases). Additional variables were included in the species diversity equations only if significant.

Species composition

In each habitat (scrub or forest), we tested whether the bird community had a nested subset pattern by using the randomization program random1 (Patterson & Atmar 1986). We found this program to be more conservative than the more modern program nested (Atmar & Patterson 1993). random1 compares species distribution patterns on habitat islands (presence/absence scores) of 1000 random assemblages to the observed community using the equivalent of the Student's t-test. For this analysis we used all species that breed regularly in the forest patches, based on a long-term survey (Shirihai 1996).

To test which species diverge from nestedness we developed a simple algorithm to calculate how many displacements-of-presence scores are needed to bring each species to perfect nestedness (Simberloff & Levin 1985). For this procedure, the null hypothesis (H0) was that species occurrences on the different patches were random. To test H0, the program randomized species presence scores within each species column to create a random species distribution, and compared the number of displacements required to achieve complete nestedness between the observed community and the random pattern. This process was repeated 10 000 times. We accepted H0 in cases where the number of transformations in the randomized patterns was equal to or smaller than that of the observed pattern in more than 500 iterations (i.e. P < 0·05).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix

Habitat structure

Three PCs accounted for 76% of the variation in habitat structure (Table 1). The first component separated plots on the basis of vegetation structure, being positively correlated with tree density, tree maturity (e.g. tree height, BA and d.b.h.) and the number of tree species, but negatively correlated with perennial cover. The second axis contrasted plots according to patch size, altitude, longitude and bush structure (i.e. density, height and width of bushes). The third component was similar to the second factor, but separated bush density, height and width (Table 1).

Bird community composition

Altogether, 36 common birds (25 passerines and 11 non-passerines) breed in the scrubland and forest in the Northern Negev (see the Appendix). Ten species breed only in scrub, 17 only in forest and nine in both habitats. We applied statistical analysis to 20 species of passerines we detected in our line transects, omitting all non-passerine species and five passerines with < 5% of the total records. Of the 20 passerines, 15 were resident or nomadic within the study area, while five were long-distance migrants (see the Appendix). Eighteen of these species were found in all 3 years and two (scrub warbler and rock sparrow) in 1 year.

In DCCA (Table 2), the first ordination axis consisted of vegetation structure and separated species according to the vegetation with which they were associated (tree age and perennial cover). The second axis consisted of geographical or physical variables such as area (patch size), latitude, longitude and altitude, and further separated each bird assemblage (Fig. 2). Among scrub-dwelling species, three species that occasionally also bred in the forest (crested lark, graceful prinia and woodchat shrike) were grouped together. Among the forest-dwelling species, the five new immigrant species (great tit, spotted flycatcher, blackbird, jay and Sardinian warbler) that were associated with large and old forests were also grouped, whereas desert finch was separated (Fig. 2).

Table 2.  Results of DCCA of 20 bird species in 67 plots in the Northern Negev. The total unconstrained eigenvalue was 2·64. Species ordination diagram is shown in Fig. 2
 Axis 1Axis 2
Canonical eigenvalues      0·87           0·16
Species variance accounted by axes (%)      33           6
Species variance accounted by arrows (%)     63·9     55·2
Species–environment correlations      0·984      0·790
Monte Carlo simulation, P-values< 0·01< 0·01
image

Figure 2. Ordination diagram of the first two axes of detrended canonical correspondence analysis for bird species and environmental variables in forest and scrub in the Northern Negev, Israel. Axis 1 and axis 2 accounted for 33% and 6% of the variance in the species data. Arrows represent directions of greatest change of environmental variables. The location of a species’ score relative to the arrows indicates the environmental preferences of that species. Open squares, species breeding in both scrub and forest; filled squares, local woodland dwelling species; open circles, new immigrant forest species; filled circles, scrubland species. The locations of two widespread woodland generalist non-passerine species (collared dove and turtle dove) are also shown (triangles).

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Area and habitat relationships

We first tested area effects on species richness and diversity. In the forest, a multiple regression model yielded a significant third-order polynomial regression for the species diversity pattern (Fig. 3a). The decrease in Fisher's alpha between the two smaller patches and the decrease among the three to four largest forest patches were both significant, indicating that at these spatial scales species richness increased due to a random sample (Fig. 3a). In contrast, Fisher's alpha increased significantly within the four to five mid-sized patches, indicating that, at this scale, species richness increased as a result of a biological effect (Fig. 3a). Scrubland species richness increased linearly with area (Fig. 3b). suggesting that species accumulation was due to biological factors over the whole range of scrub patch sizes.

image

Figure 3. Passerine species–area relationships and Fisher's alpha index for species diversity in forest and scrub patches in the Northern Negev study area. (a) In forest patches all three parameters of the Fisher's alpha curve (i.e. area, area2 and area3) were significant. (b) In scrub patches high second- and third-order polynomial regressions did not yield significant curves.

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To test whether habitat structure may be the factor affecting the species diversity, we evaluated habitat diversity for forest and scrubland patches by calculating a coefficient of variance (CV) of vegetation structure corrected for sample size (Sokal & Rohlf 1981). In the forest we calculated CV for BA, whereas in the scrub CV was calculated for perennial cover density. We then plotted Fisher's alpha against CV for each habitat and calculated the Spearman correlation. In the forest, bird species diversity increased significantly with habitat diversity as BA (Fig. 4a), with one outlier patch (Fig. 3a; Dixon's test P < 0·05; Sokal & Rohlf 1981). This 150-ha patch comprised coniferous subunits only, planted mostly during the 1960s with 16 ha of conifers planted in 1988. Thus, while this patch was less diverse in tree structure than other large patches, its unique pattern gave a CV of BA that was much higher. In the scrub, perennial cover CV and Fisher's alpha were not correlated (Fig. 4b), suggesting that habitat diversity is not the factor that affects species diversity.

image

Figure 4. The relationship between habitat diversity and bird species diversity. (a) In forest bird species, diversity increases according to patch habitat diversity (as measured by coefficient of variance of tree basal area). The correlation was calculated after omitting one outlier (square) from the analysis (for all the data r2 = 0·648, P = 0·005). (b) In the scrub, no correlation was found between bird species diversity and habitat diversity (as measured by coefficient of variance of perennial cover).

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We further examined area vs. habitat structure effects by testing their influence on bird densities using manova. Area may affect population density due to the extinction of habitat-specialist species from small patches. For this analysis we used stand age in the forest and perennial cover in the scrub as the habitat structure variables.

We first tested whether there were differences in bird densities between years, and found that densities were significantly different in the forest (Wilk's λ, F34,176 = 1·721, P = 0·013) but not in the scrub (Wilk's λ, F14,142 = 0·801, P = 0·667). Therefore we analysed the effect of area and habitat structure on forest species abundance using the data set for each year separately.

In the forest there was a significant correlation between total bird density and patch area in 1996, but not in 1997 or in 1998 (Table 3). However, of all forest species found in 1996, only one (great tit) had lower density in small patches than in large ones, while 11 other species showed no differences in densities. In contrast, bird density was related to stand age in all 3 years of study (Table 3). Three species increased in density in old-growth plots (blackbird, great tit and spotted flycatcher), while two (rufous bush-robin and the graceful prinia) were significantly more abundant in young stands. There was no significant interaction between the effect of area and habitat structure on forest bird densities (Table 3). In the scrub, species density was lower in small patches due to the low density of three scrub specialists in small patches: desert lark, long-billed pipit and spectacled warbler. Habitat structure did not have a significant effect on total bird density (Table 3).

Table 3. manova of habitat structure and area effects on total bird densities. Forest bird densities varied significantly between years, and therefore are shown for each year separately. Habitat structure significantly affected bird densities in forest but not in scrub. In contrast, area affected bird densities in scrub, whereas in forest it had a significant effect on bird densities only in 1996. Interactions between habitat structure and area were not significant in both scrub and forest, and are not shown. Num, numerator; Den, denominator; d.f., degrees of freedom
 Wilk's λF-value(Num)d.f.(Den)d.f.P-value
 19960·3372·78912170·026
 19970·2122·73315110·049
 19980·2442·65614120·049
 19960·3133·10912170·016
 19970·2592·09915110·110
 19980·2822·17714120·092
 Factor     
 Log area0·5269·131 7710·0001
 % Perennial0·8661·576 7710·157

Bird status and habitat

In multiple regression, density of permanent resident forest species (see the Appendix) increased along the first PC, associated with old-growth plots, and declined with altitude (Table 4). Densities of five new immigrants from the mediterranean zone also increased along PC1 and with area (Table 4). The total density of five species of long-distance migrants that bred in the forest (see the Appendix) was correlated only with altitude, longitude and latitude (Table 4). These equations emphasize the relative importance of PC1, which is a measure of vegetation, for forest species. In contrast, the densities of three scrub specialists (see the Appendix) correlated only with scrub patch area (Table 4).

Table 4.  Stepwise multiple regression equations (multivariate habitat models) relating bird species densities in different groups to (log) environmental factors. Variables in each equation are listed from most to least important. PC1 (a measure of vegetation structure) is a primary factor in the forest. Area is the only factor that enters the equation of scrub specialist density
GroupEquationR2P <
Permanent residentsY = 3·70 + 0·018 (PC1) − 1·159 Log (Altitude)0·3250·001
Long-distance migrantsY = 5·30 − 2·24 Log (Altitude) + 0·65 Log (Longitude) + 0·57 Log (Latitude)0·4770·001
New immigrantsY = −0·683 + 0·01 (PC1) + 0·101 Log (Area)0·4860·001
Scrub specialistsY = −0·150 + 0·255 Log (Area)0·7640·001

At the species level, five of 15 forest dwellers were correlated with PC1 (four positively and one negatively) but none with PC2 or PC3 (Table 5). Area had significant effect on five species, but only one was positive (Table 5). Of the five new immigrant species, only the Eurasian jay increased weakly with area. In contrast, the abundances of three out of four scrub-dwelling species increased with area (Table 5). Except for one case (spectacled warbler, a scrub specialist), one environmental variable was sufficient to explain the abundances of all scrub species (Table 5).

Table 5.  Multivariate habitat models for species densities vs. (log) environmental variables. Variables in each equation are listed from most to least important. In cases where PC1 entered equations, the variable that gave the best fit with bird density, of all variables correlated with PC1, is given. Bush, bush density; ht, height
SpeciesEquationR2P
  • *

    New immigrants.

  • Scrub specialists.

Crested lark0·216 − 0·195 Log (Latitude)0·266      0·001
Graceful prinia0·132 − 0·003 (PC1:Basal) + 0·056 Log (Bush)20·389< 0·001
Olivaceous warbler0·830 − 0·333 Log (Altitude) + 0·172 Log (Latitude)0·235      0·007
Sardinian warbler*−0·04 + 0·085 Log (Bush)0·218      0·002
Spotted flycatcher*−0·096 + 0·003 (PC1:Basal)0·225      0·002
Rufous bush-robin0·345 − 0·005 (PC1:Basal) − 0·016 Log (Area)2 + 0·142 Log (Bush)0·456< 0·001
Blackbird*−0·227 + 0·005 (PC1:d.b.h.) + 0·127 Log (Latitude)0·359< 0·001
Great tit*0·332 + 0·001 Log (tree ht)2 − 0·21 Log (Bush ht)0·326      0·023
Goldfinch0·065 + 0·01 Log (d.b.h.)0·094      0·050
Greenfinch1·240 − 0·392 Log (Altitude)0·156      0·012
Desert finch0·422 − 0·372 Log (Latitude) − 0·006 Log (Area)20·653< 0·001
House sparrow0·285 − 0·113 Log (Latitude) − 0·041 Log (Area)0·462< 0·001
Eurasian jay*0·019 + 0·037 Log (Area)0·105      0·041
Desert lark0·580 − 0·507 Log (Latitude)0·441< 0·001
Long-billed pipit−0·048 + 0·066 Log (Area)0·439< 0·001
Woodchat shrike0·046 + 0·135 Log (Bush)20·540< 0·001
Graceful prinia0·243 − 0·053 Log (Area)0·189      0·023
Scrub warbler−0·243 + 0·202 Log (Longitude)0·585< 0·001
Spectacled warbler−0·303 + 0·031 Log (Area)2 + 0·230 Log (Perennial)0·698< 0·001
Black-eared wheatear−0·011 − 0·043 (PC3)0·169      0·033

Species composition

Species composition in both forest and scrub patches had a nested subset pattern (random1, P < 0·001), with species from small patches being sets of those in larger patches (Patterson & Atmar 1986). A species-level analysis revealed that in the scrub all eight passerine species included in the analysis contributed to the nested pattern. In the forest, three out of 15 species had a distribution that was not significantly different from random. These species were yellow-vented bulbul (randomization, P = 0·06), woodchat shrike (P = 0·06) and desert finch (P = 0·72).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix

The theory of island biogeography (MacArthur & Wilson 1967) initially favoured area over habitat diversity as the primary factor affecting species diversity. Subsequently, however, the relative importance of these two factors has been extensively debated, but their resolution is difficult because the two are often highly correlated (Rosenzweig 1995). Other problems in macroecological studies emerge from dealing with uncontrolled variables that hardly provide evidence for processes or mechanisms involved (Manel, Buckton & Ormerod 2000). To overcome these problems we (i) used multivariate statistical techniques that control for autocorrelations; and (ii) determined whether several complementary hypotheses concurred with one another.

We found that bird distribution in the Northern Negev is not random: ordination analysis separated the whole-landscape bird community into two assemblages representing scrubland and forest (Fig. 2). Area was a good estimator of species richness in both habitats (Figs 2b, 3a), and species diversity increased with area, indicating that species accumulation was faster than expected from random sampling (Fisher, Corbet & Williams 1943; Connor & McCoy 1979; Rosenzweig 1995). In other words, species in both habitats appear to respond to biological factors. The question is whether these factors are associated with area (e.g. edge effects) or with habitat structure (e.g. vegetation profile).

The third-order polynomial pattern of forest species diversity vs. area (Fig. 3a) concurs with forest habitat structure, where patches can be classified into three spatial scale classes. The first class includes small homogeneous patches (5–10 ha). Here, patches consisted of one coniferous plot, planted during one year. These patches are occupied by habitat generalist species only (species that breed in various habitats throughout the Northern Negev), such as olivaceous warbler, greenfinch, goldfinch and other, non-passerine, species (collared dove and turtle dove). At this scale Fisher's alpha decreases, indicating a random sampling. At the second class, 15–1500 ha, patches become heterogeneous. Patches larger than 15 ha include several plantations of either different aged conifers or mixed coniferous and deciduous trees. The addition of new habitat subtypes was succeeded by a substantial increase in species diversity. This increase continued as long as more habitat subtypes were added. The third class included patches larger than 1500 ha. Here, no new habitat subtypes were included, and the few new species were added, again, due to a random sampling process. The idea that habitat diversity is the main factor influencing forest bird species diversity is strongly supported by the direct correlation between these two variables. When Fisher's alpha is plotted vs. BA (Fig. 4a), a linear correlation is sufficient to explain species diversity. This suggests that forest patches in the Negev ‘sample’ bird species according to their habitat composition, as described for true archipelagos in a much larger scale (Haila, Jarvinen & Kuusela 1983).

Other results indicated that habitat structure is the main determinant of forest bird species abundance and distribution. First, area per se did not affect forest species densities (Table 3). In contrast, forest stand age, an estimator of habitat diversity, had a significant effect on overall bird densities in all 3 years (Table 3). Secondly, multivariate habitat models further supported the idea of the importance of forest habitat structure upon area. Area was significantly and positively correlated with the overall population densities of new immigrants (Table 4), but only after accounting for habitat structure. This result tentatively suggests that, as in other case studies (reviewed by Rosenzweig 1995), forest bird diversity in the Negev is influenced by habitat diversity that, in turn, increases with area (BA CV was positively correlated with patch size, Spearman correlation coefficient = 0·78, P = 0·001). We believe that the presence of a suitable habitat subtype per se determines whether breeding birds become established in the planted forests. New immigrants (e.g. Eurasian jay, great tit, spotted flycatcher and blackbird) were more abundant in larger patches, simply because old stands are more common in these patches. We found no indication that this was due to negative edge effects. While different geographical or habitat structure variables frequently entered multivariate habitat models, area was included in relatively few cases (Table 5). In bird populations a decrease in density as patch size decreases may indicate edge effects. However, in our study such a positive correlation between patch size and density exists for Eurasian jay only.

A species-level nested-subset analysis suggested that three forest-dwelling species diverged from nestedness because they were associated with a unique habitat subtype rather than with patch size. Yellow-vented bulbuls breed only in broadleaf trees, and woodchat shrikes rarely breed in pines. These two species were found in small patches with broadleaf groves, but not in larger ones that consisted of mainly coniferous forest. Desert finch distribution had, as far as we can tell, a nested pattern. Yet even here the distribution was probably not random, but a result of habitat preference. Desert finches breed almost exclusively in young pines in small patches. Moreover, as the only forest species that is not originally a mediterranean species (Shirihai 1996), it was restricted to the southern part of the study area (as indicated by its multivariate habitat model; Table 5).

In contrast to the forest species, the abundance and distribution of scrubland birds appeared to be affected by area. This result agrees with findings from other studies where habitat patchiness was the result of fragmentation (Ambuel & Temple 1983; Blake & Karr 1987). The increase of diversity with scrubland area (Fig. 3b) suggests that biological factors are responsible for the observed species–area relationship. The effect of area on the density of scrub specialists (Table 3) suggests that disturbances reduce population density in small scrub patches. Furthermore, area was the only variable that entered the multivariate habitat model of scrub specialist species (Table 4), indicating that it is the most important factor affecting their abundance.

Implications for conservation and management

Habitat fragmentation is generally viewed as a unidirectional process that breaks continuous natural habitat into small and isolated patches (Ambuel & Temple 1983; Wilcove 1985; Blake & Karr 1987; Robinson et al. 1995). However, habitat fragmentation also involves a reverse process in which islands of the new habitat grow to form a continuous habitat. In cases where the new habitat is not completely hostile to the focal organisms, the landscape can be viewed as an undivided mosaic (sensuAddicott et al. 1994) where fitness differs in different patch types but is always greater than zero.

Studies using the mosaic approach (Enoksson, Angelstam & Larsson 1995; McGarigal & McComb 1995; Estades & Temple 1999) suggest that the effect of landscape on bird abundance is species specific. Enoksson, Angelstam & Larsson (1995) in Sweden, and Estades & Temple (1999) in Chile, studied bird communities in landscapes where natural forests have been fragmented by exotic pine plantations. Their results suggest that such landscapes are settled by several bird species as undivided landscapes. The mosaic approach may seem highly relevant to the Negev afforestation programme. On one hand, pines were planted within a scrubland habitat, creating a divided landscape for most scrubland species. Ecologically, this process is similar to forest fragmentation by farmlands. On the other hand, the new human-made habitat in the Negev is relatively diverse in vegetation structure, and is inhabited by more bird species than the scrub it is replacing.

Altogether, afforestation in the Negev increased bird species diversity in the whole landscape. However, the new immigrant mediterranean species are originally habitat generalists that appear to have become habitat specialists in the Negev. These species extended their distribution at the expense of scrub specialists. Thus, conservation efforts should be aimed at scrub species, not at the forest species. Any further decrease in scrub area will reduce scrub species densities, such as long-billed pipit and spectacled warbler, as shown in Tables 2, 3 and 4. These species are sensitive not only to habitat loss, but to any subtle change in their habitat structure where scrublands are prepared for planting. To conserve populations of these threatened species, further scrub fragmentation must be minimized.

In order to increase species diversity in the Northern Negev, the best approach is not to increase forest area, because there was only a slight increase in species richness between 200-ha and 3000-ha forests, but to increase forest habitat diversity. This can be done at two different levels: the habitat subtype level (forest subunit composition) and the microhabitat level (foliage layers).

At the habitat subtype level species diversity may be increased by increasing the proportion of broadleaf trees. Studies in Wales (Bibby, Phillips & Seddon 1985; Bibby, Aston & Bellamy 1989) and Arizona (Rosenstock 1998) showed that mixed oak–conifer stands support higher bird species diversity than exclusive conifer plantations. Easton & Martin (1998) showed that the reduction in deciduous vegetation due to herbicide treatment in managed conifer forests in British Columbia reduced bird species richness and abundance. In the Negev, deciduous forest species attempt to breed in broadleaf plantations, but the total area and average size of broadleaf stands are too small (Shochat 1999). Increasing broadleaf plantation area may increase the abundance of scarce or sporadic breeding species in the forest. Another important habitat variable was coniferous stand age; forest species composition changes as pine trees mature. Continuous replacement of old-growth plantations with young ones would help to maintain a large variety of subunits of different ages with their unique foliage structure.

At the microhabitat level, foliage profile enrichment is required. The forest bird community in pine plantations in the Negev is much poorer than the mediterranean broadleaf woodland bird community in central and northern Israel. The reason may be that the structure of the plantations is comparatively simple and lacks one essential vegetation layer for forest specialists: the understorey. Bibby, Aston & Bellamy (1989) demonstrated how the presence of understorey in old-growth spruce plantations in Wales increased species richness. Because understorey is almost absent in the Negev, it is hard to evaluate its importance to bush-nesting species. Yet, the low density of several understorey-breeding species, and the absence of others, suggests that future management strategy should involve the creation of understorey as the most important step. This may increase densities of Sardinian warbler and rufous bush-robin. It may also facilitate the establishment of species that have started to spread southwards in Israel in recent years (Shochat 1999).

A global perspective

Exotic conifers are now central in afforestation programmes across countries with mediterranean climates, such as Spain, Italy, Australia, South Africa and Chile (reviewed by Izhaki 1999). Cody (1975) showed how planted pine forests in Chile are as rich in bird species as native pine forests in California, whereas similar forests in South Africa are ornithological deserts. He gave two explanations for these findings. First, African bird species are mostly specialists, whereas in Chile there are many more generalists. Secondly, natural bushes and shrubs in Chile, unlike in South Africa, invade pine plantations and form an understorey level. Disney & Stokes (1976) showed that both bird species diversity and density were higher in sclerophyl forests (especially wet ones) than in planted pine forests in Australia. In Spain, Lopez & Moro (1997) showed the importance of the understorey in Aleppo pine forests in south-eastern Spain for several bird species. Diaz et al. (1998) claimed that artificial pine forests, planted on former arable lands in Spain, were too small, and that increasing forest area would not increase species richness of the forest bird community because these forests do not provide high quality habitats. They drew conclusions similar to ours, even though their study was done on a much larger spatial scale, in a more productive area, with a richer and more complex bird community. Our results therefore support the idea that pine forests in mediterranean zones are generally too simplistic in structure to maintain rich bird communities. Because mediterranean bird species co-evolved with low and thick vegetation, managed pine forests appear to be a challenge for new colonizers from native woodlands. Therefore, the management strategies we suggest may be useful across a much larger spatial scale then the Negev, and may serve as the future challenge in modern afforestation programmes.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix

Financial support for this research was provided by the Jewish National Fund. We thank Ido Tsurim, Nir Sapir and Arnon Tsairi for their assistance in the field work, and Ofer Ovadia for his help in developing a computer programs and statistical analysis. Burt Kotler and Mary Whitehouse constructively criticized the manuscript. This is paper number 328 of the Mitrani Department for Desert Ecology.

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  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix
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Appendix

  1. Top of page
  2. Summary
  3. Introduction
  4. Study area and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix
Table 6. Appendix. Breeding birds recorded in scrubland and forest in the Northern Negev during 1996–98. Species included in our analysis are in bold. NI, new immigrants. Status: R, resident; (N), nomadic; S, summer breeder (long distance migrants). Habitat: S, scrubland; F, forest (in cases where birds occupy both habitats, major habitat is mentioned first)
SpeciesNIStatusHabitat
Chukar (Alectoris chukar) RSF
Stone curlew (Burhinus oedicnemus) RFS
Rock pigeon (Columba livia) RSF
Collared dove (Streptopelia decaocto) RF
Turtle dove (Streptopelia turtur) SF
Great spotted cuckoo (Clamator glandarius) SF
Little owl (Athene noctua) RSF
Hoopoe (Upupa epops) RFS
Bee-eater (Merops apiaster) SS
Roller (Coracias garrulus) SS
Syrian woodpecker (Dendrocopus syriacus) RF
Crested lark (Galerida cristata) RSF
Desert lark (Ammomanes deserti) RS
Red-rumped swallow (Hirundo daurica) SS
Long-billed pipit (Anthus similis) RS
Yellow-vented bulbul (Pycnonotus xanthopygos) RF
Rufous bush-robin (Cercotrichas galactotes) SF
Black-eared wheatear (Oenanthe hispanica) SS
Blackbird (Turdus merula)+RF
Graceful prinia (Prinia gracilis) RSF
Scrub warbler (Scotocerca inquieta) RS
Olivaceous warbler (Hippolais pallida) SF
Sardinian warbler (Sylvia melanocephala)+R(N)F
Spectacled warbler (Sylvia conspicilata) RS
Spotted flycatcher (Muscicapa striata)+SF
Great tit (Parus major)+RF
Woodchat shrike (Lanius senator) SSF
Jay (Garrulus glandarius)+RF
Hooded crow (Corvus corone cornix)+RF
Rock sparrow (Petronia petronia) RS
House sparrow (Passer domesticus) R(N)FS
Spanish sparrow (Passer hispaniolensis) R(N)F
Goldfinch (Carduelis carduelis) RF
Greenfinch (Carduelis chloris) RF
Desert finch (Rhodopechys obsoleta) R(N)F
Corn bunting (Miliaria calandra) R(N)S