Habitat Matrix Effects on Pond Occupancy in Newts - ESA Journals

Habitat Matrix Effects on Pond Occupancy in Newts PIERRE JOLY,*‡ CLAUDE MIAUD,*§ ANTHONY LEHMANN,† AND ODILE GROLET* *UMR CNRS 5023 Ecologie des Eaux Douces et des Grands Fleuves, Université Claude Bernard Lyon 1, 69622 Villeurbanne Cedex, France †Laboratoire d’Ecologie et de Biologie Aquatique, Université de Genève, 18 chemin des Clochettes, 1206 Geneva, Switzerland

Abstract: In farmlands, the population viability of many amphibians is suspected to depend on the resistance the matrix of crop fields presents to movements between ponds and terrestrial sites and movements among ponds. Over recent decades the increase in cereal growing at the expense of cattle breeding has caused a drastic change in habitat matrix in many European regions. We investigated the effect of such change on populations of three newt species ( Triturus helveticus, T. alpestris, and T. cristatus) by comparing their abundances in sites that varied in amount of cultivated ground. A multivariate regression analysis of the relationship of newt abundance to both pond and landscape variables demonstrated the negative influence of cultivated ground on abundance. The width of the uncultivated sector linking the pond to the forest was a good predictor of abundance after the influences of both pond area and fish presence were removed. Moreover, newt presence was positively related to the number of ponds within that 50-ha surrounding area, highlighting the role of metapopulation functioning in newt occupancy of ponds. The relationship between newt abundance and width of uncultivated sectors agrees with present knowledge of the orientation mechanisms that underlie migration movements in urodeles. Such a relationship between connectedness and sector width shows that narrow, linear corridors such as hedgerows may not be useful in newt conservation. Our study also highlights the need to incorporate a behavioral component of habitat use into models of connectivity in conservation biology. Efecto de la Matriz del Hábitat en la Ocupación de Estanques por Tritones Resumen: Se considera que en tierras de cultivo la disponibilidad poblacional de muchos anfibios depende de la resistencia que la matriz de las tierras de cultivo presentan a los movimientos entre estanques y los sitios terrestres, y entre estanques. Durante las décadas recientes el incremento en la producción de cereal a cambio de la cría de ganado ha ocasionado un cambio drástico en la matriz del hábitat en muchas regiones de Europa. Investigamos los efectos de estos cambios en las poblaciones de tres especies de tritones ( Triturus helveticus, T. alpestris y T. cristatus) comparando sus abundancias en sitios que variaron en la cantidad de tierra cultivada. Un análisis de regresión multivariado de las relaciones entre la abundancia de tritones y las variables de los estanques y del paisaje demostró las influencias negativas de las tierras de cultivo sobre la abundancia. La amplitud de sectores sin cultivar que conectó a los estanques con el bosque fue un buen pronosticador de la abundancia después de remover las influencias del área del estanque y la presencia de peces. Más aún, la presencia de tritones estuvo positivamente relacionada con el número de estanques dentro de un área adyacente de 50 ha, resaltando el papel del funcionamiento de la metapoblación en la ocupación de estanques. La relación entre la abundancia de tritones y la amplitud de sectores sin cultivar concuerda con el conocimiento actual sobre los mecanismos de orientación que delimitan los movimientos de migración en urodelos. Esta relación entre la conectividad y la amplitud del sector muestra que los corredores estrechos y lineales como lo son los cercos podrían no ser útiles para la conservación de tritones. Nuestro estudio también resalta la necesidad de incorporar un componente conductual del uso del hábitat cuando se modela la conectividad en estudios de conservación biológica.

‡ email [email protected] § Current address: Université de Savoie, F-73370 Le Bourget du Lac, France Paper submitted April 19, 1999; revised manuscript accepted May 3, 2000.

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Introduction At a local scale, the metapopulation concept supposes that species occurrence depends on population dynamics at local and regional scales and on movements among populations (Levins 1970; Hanski & Simberloff 1997). Within a metapopulation, movements of individuals are expected to be related primarily to distance between suitable habitat patches (Marsh et al. 1999). These movements can also be influenced by the physical quality of the matrix to be crossed, particularly in animals that move on the ground (Wiens 1997; Moilanen & Hanski 1998). In this respect, a goal of conservation biology is to relate local dynamics to landscape features, including the permeability of matrix habitats to dispersion. Directly ascribing a permeability coefficient to each habitat type is not an easy task (Pither & Taylor 1998), but the influence of the matrix structure can be indirectly estimated by comparing the abundance of individuals in habitat patches differing in composition and the configuration of the matrix surrounding them. For ground-dispersing animals that have to cross open fields to reach a target habitat fragment, the extension of cultivated grounds at the expense of grasslands creates new ecological conditions that can drastically influence the movements and survival of many species (Macdonald & Smith 1990). Because of their ground-dwelling habits, amphibians are suitable candidates for an analysis of the influence of matrix quality on species occurrence and abundance (Hecnar & M’Closkey 1996; Semlitsch & Bodie 1998). Besides metapopulation functioning, the complex amphibian life cycle implies regular migrations between terrestrial and aquatic habitats, either by breeding adults or by postmetamorphic juveniles. Dispersal through the matrix can have energy costs and increased mortality risks because much of the matrix may be regarded as unsuitable habitat (Ims & Yoccoz 1997) or habitat outside the species niche (Holt 1996). The permeability these areas offers to migrating amphibians constitutes a major influence on population viability and falls within the connectivity concept (Merriam 1984; Baudry & Merriam 1988). When both low local abundance and high dispersion prevail throughout the matrix, reproductive populations experience high sensitivity to both demographic and environmental stochasticity (Shaffer 1981, 1987; Foley 1992). In such small populations, immigration is expected to play a key role in compensating for extinction risks at the local scale. If immigration is favored by the shortness of the distances that separate suitable habitat patches, the connectedness of the matrix habitat also influences its success. Many amphibian species are in this situation, and they have proved suitable for empirical studies (Gill 1978a, 1978b; Sinsch 1992; Sinsch & Seidel 1995; Halley et al. 1996; Semlitsch 1998).

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In temperate regions of Europe, newts (genus Triturus) occur on land used for cattle breeding as long as farm ponds (natural or artificial ponds used as water sources for domestic cattle) provide suitable conditions for their reproduction. In such agricultural ecosystems, forests are usually used by the newts as aestivation and hibernation habitats (Miaud 1990; Joly & Miaud 1993). Spatial separation of woods and ponds implies that open fields have to be crossed by newts. In the past few centuries, these open fields were largely pastures. During the last few decades, however, the area devoted to grain crops has increased at the expense of pastures. Where such a change in land use has occurred, some cattle ponds have been destroyed and others have become more or less surrounded by cultivated grounds. Our goal was to evaluate the influence of such a matrix modification on the population viability of newts. We compared the abundance of three newt species in habitat sites differing in degree of enclosure by cultivated grounds. We focused particularly on the matrix environments separating each studied pond from forested grounds.

Methods Study Area and Ecological Variables In the lowlands of Bresse and Dombes (northeast of Lyon, southeastern France), agriculture results in a complex landscape matrix of pastures, cultivated grounds, forests, and fish ponds (large ponds for fish breeding). In these regions, we selected 79 farm ponds from pasture areas to provide a sample of ponds that varied in degree of enclosure by cultivated land. To focus on the problem of the replacement of pastures by cultivated fields, this selection excluded all sites where connectedness was altered by causes other than cultivation, such as major roads or urbanized areas. For each pond we collected information on intrinsic variables thought capable of influencing newt presence: depth, area, percentage of gently sloping bank (slope of ⬍20%), proportion of area occupied by floating vegetation, and fish presence. Fish present in the farm ponds were predominantly pumpkinseed (Lepomis gibbosus), black bullhead (Ictalurus melas), roach (Rutilus rutilus), and tench (Tinca tinca). We studied the influence of landscape structure within circular, 50-ha areas, with a 400-m radius centered on each pond; 400 m corresponds to the average migration distance of newts (Dolmen 1980; Griffiths 1984; Cooke 1986; R. Jehle, unpublished results). Within each 50-ha area, we measured the following variables: proportion of matrix occupied by forest (main terrestrial habitat of the newts), proportion of matrix occupied by cultivated fields, length of hedgerow (possible substitutive terres-

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tablished in the field by plotting of land use on enlarged maps from the French National Geographic Institute. We estimated areas by counting pixels. Estimation of Newt Species Richness and Abundance In the studied region, three newt species coexist as a size-structured guild. From the smallest to the largest species, this guild is composed of Triturus helveticus (palmate newt), T. alpestris (Alpine newt), and T. cristatus (crested newt). The latter is considered a threatened species and is registered in Appendix II of the Bern Convention. Sampling took place in 1991–1993 from 15 April to 15 May. This period corresponds to the peak of breeding in the Bresse-Dombes region (Miaud 1990). Because dip-netting efficiency in cattleponds is relatively high during this period, with a capture probability between 0.4 and 0.8 (unpublished results), sampling was performed only once. We caught newts with a 5-mm mesh hand-net. Sampling duration varied from 30 to 60 minutes, depending on pond area (even when no newts were found). The variable used in the analysis was a standardized estimation of abundance, namely the mean number of newts caught during a 15-minute sampling bout. Data Analyses

Figure 1. The (a) measurement of the width of uncultivated sectors (in degrees) in the study area. This variable is calculated as the sum of all the azimuths in which a straight line between the pond and a forest patch did not cross a cultivated field. Sector width is a ⫹ b ⫹ c. Pond enclosure by cultivated fields is d ⫹ e. The (b) distribution of uncultivated sectors among the sampled sites.

trial habitat), number of ponds (suspected to influence metapopulation dynamics), and angle of the uncultivated sector. This last variable was estimated as the angular sum of all the directions from which a straight line between the pond and a forest did not cross cultivated field (Fig. 1a). Although such a sector proved nonexistent in 25 ponds, the other sites constituted a balanced sample of all degrees of sector width (Fig. 1b). All these variables were estimated from maps of the stations es-

The relationships between environmental characteristics and newt abundance were assumed to result from causative processes. In this context, many authors have taken advantage of generalized linear models (GLM: McCullagh & Nelder 1989; Guisan et al. 1998) and generalized additive models (GAM: Yee & Mitchell 1991; Leathwick 1995; Lehmann 1998). We used a GAM in our study to relate occurrence and abundance in each newt species to the environmental characteristics of the ponds and the surrounding landscape. We preferred Poisson models to binomial models (presence-absence to take into account the additional information supported by abundance on the health of local populations [Winston & Angermeier 1995]). We used S-PLUS software (Mathsoft Inc., Seattle), which specifies a Poisson family with a log function as link. Significant explanatory variables were selected for each species based on a stepwise procedure (Hastie & Tibshirani 1990; Chambers & Hastie 1993). Uncultivated sectors (ncs) that were highly correlated (r ⫽ 0.79) to the percentage of wood (woa) were preselected to account for the importance of forest habitat. The recent progress in computer technologies enables easy fitting of such models (Hastie & Tibshirani 1990; Chambers & Hastie 1993). The GLM and GAM present several advantages over classical multiple regression approaches in that they integrate data from different statistical distributions with the appropriate modeling of sta-


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tistical error (e.g., normal as in multiple regression, binomial for presence-absence data, ordinal for classes of abundance, Poisson or negative binomial for species or individual counts). These more general formulations of regression models allow continuous variables (e.g., depth) and/or categorical variables (e.g., presence of fish) to be combined. As a nonparametric extension of GLM, GAM builds a model directly on a smoothed function from the explanatory variables instead of pre-establishing a parametric model. This allows one to test whether a response curve is bell-shaped or not and directly estimates the additive effect of each explanatory variable from its response curves in the prediction.

Results There were no newts in 21.5% of the study sites. Occurrence of each species was negatively related to mean body size, with T. helveticus occurring in 72.2% of the ponds, T. alpestris in 63.3%, and T. cristatus in 41.7%. The three species coexisted in 36.7% of the sampled sites. In 24.1% of the sites, the assemblage was composed only of T. alpestris and T. helveticus. Some sites were occupied by only a single species (16.5%), with T. helveticus alone more frequently than any other species alone (Fig. 2a). In the same way, abundance was also negatively related to species body size, with T. helveticus reaching the highest densities and T. cristatus the lowest (Fig. 2b). Abundance did not vary significantly between T. helveticus and T. alpestris, and only T. cristatus abundance proved significantly lower than those of the other species ( p ⬍ 0.005 in each comparison; KolmogorovSmirnov test; Siegel & Castellan 1988). The overall predictive power of the proposed models (GAM) was assessed by plotting the fitted against the observed abundances (Fig. 3). For each species, the number of included variables depended on the goodness-offit of the model. The best models fitted the data with r2 values of 0.80 for T. helveticus, 0.82 for T. alpestris, and 0.88 for T. cristatus: Triturus helveticus, s(poa) ⫹ s(dep) ⫹ s(fvg) ⫹ s(hed) ⫹ s(npo) ⫹ s(aga) ⫹ s(ucs) ⫹ fish; Triturus alpestris, s(poa) ⫹ s(dep) ⫹ s(gsb) ⫹ s(fvg) ⫹ s(hed) ⫹ s(npo) ⫹ s(aga) ⫹ s(ucs) ⫹ fish; and Triturus cristatus, s(poa) ⫹ dep ⫹ s(gsb) ⫹ s(fvg) ⫹ hed ⫹ s(aga) ⫹ ucs ⫹ fish; where s(x) is smoothed variable, poa is pond area, dep is depth, gsb is gently sloping bank, fvg is floating vegetation, woa is wood area, hed is hedgerow length, npo is number of ponds, aga is arable grounds area, and ucs is uncultivated sectors. Response curves for the three species in relation to the environment variables varied from one species to another and were not always linear (Fig. 4). Relative sensitivity of abundance to each habitat variable was estimated by deviance increase when the variable was


Figure 2. Pond occupancy by newts: (a) number of sites according to newt assemblages (Ta, Triturus alpestris; Tc, T. cristatus; and Th, T. helveticus) and (b) number of sites according to newt abundance.

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Figure 3. Results of the generalized additive models analysis, expressed as the relationship between fitted and observed abundance of each newt species. Abundance is n individuals per 15-minute sampling effort. dropped from the model (Table 1). Overall, the abundances of the three species were negatively related to pond area, fish presence, and hedgerow length. We predicted that abundance would be positively associated with floating vegetation and uncultivated sectors. Proportion of cultivated area was related to the abundance of the three species following a bell curve: abundance increased with cultivated area until a threshold, above which it drastically declined. This relationship appeared more drastic in T. cristatus than in the other species. Relative sensitivity of abundance to each variable varied among species (Table 1). No major variable strongly affected the abundances of the three species. Four variables were shown to heavily influence the abundances of two species: floating vegetation for T. helveticus and T. cristatus, hedgerow length for T. helveticus and T. alpestris, arable-grounds area for T. helveticus and T. cristatus, and uncultivated sector for T. helveticus and T. alpestris. Other variables appeared less influential. To distinguish the influences of uncultivated sectors from that of forested areas (these two variables were positively correlated), we investigated the relationship between newt abundance and uncultivated sectors in a subsample of 20 sites where forested area varied within the limited range from 25% to 40% (the uncultivated sector varied from 0 to 360⬚). Within this selection of sites, high abundances were observed only when the width of the uncultivated sector exceeded 180⬚ for T. helveticus and T. alpestris and 140⬚ for T. cristatus (Fig. 5), suggesting a threshold effect. Considering only newt occurrence (and not abundance as in GAM analysis), a relationship was detected with number of ponds within the 50 ha (Fig. 6a). Whereas the probability of occupancy by a population of each newt species was high when the number of ponds exceeded 5/per 50 ha, it decreased as the ponds became more rare. The shape of such a relationship differed among species. Whereas neither linear regression

nor threshold were perceptible in T. helveticus (r 2 ⫽ 0.29), the occurrence of T. alpestris drastically increased when pond density increased from 2 to 3/per 50 ha (nonlinear regression; r2 ⫽ 0.43). In contrast, a linear regression model fitted the relationship between T. cristatus occurrence and pond density ( p ⫽ 0.04; r2 ⫽ 0.59) Moreover, the relationship between pond number and newt abundance also differed among species. In the smaller species, T. helveticus and T. alpestris, observed abundance was not high in situations where the number of ponds was the highest, but rather in those with 2 or 3 ponds/per 50 ha (Fig. 6b). There was only one pond frequency (5/per 50 ha) at which T. cristatus abundance was occasionally greater.

Discussion The distributions of the three newt species conform globally with the abundance-occupancy theory, with the commonest species also being locally the most abundant (Hanski 1982; Brown 1984; Gaston 1996). Despite low local abundances, T. cristatus was present in one-third of the sites. The relative rarity of this large species is probably related to the relative smallness of the studied ponds that prevent populations from reaching high numbers. Consequently, T. cristatus is probably the species most sensitive to habitat fragmentation (highest local extinction risk) (Shaffer 1987). Generalized additive models made it possible to jointly analyze influences of both aquatic and terrestrial components of the landscape environments. Variables describing the physico-chemical quality of water were not included in this analysis because of the usual low relevance of these variables compared to more macroscopic ecological ones in explaining newt distribution (Cooke & Frazer 1976; Beebee 1985; Giacoma 1988; Pavignano et


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al. 1990; Ildos & Ancona 1994). The four pond variables contributed significantly to the regressive model of each species, although their respective contributions varied. Pond area, extent of floating vegetation, and fish presence were the most influential variables in the models. Whereas most landscape variables (except forest area) influenced the abundances of the three species, number of ponds did not influence those of T. cristatus abundance. Pond area, hedgerow length, high proportion of land occupied by cultivated fields, and fish presence were negatively related to the abundance of each species. The negative relationship between abundance and pond area may result from a habitat-island effect (MacArthur & Wilson 1967), the highest abundances being predicted in the smallest patches (50–80 m2 ), which is consistent with the data we collected. But site area may also have lead to biased sampling efficiency, and the possibility of hand-netting yielding false absence or low abundance was probably higher in the largest habitat patches

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(ponds). Nevertheless, the variability of this relationship between area and abundance increased with increasing area, suggesting a higher sensitivity of abundance to factors other than area in the largest sites. More intriguing was the negative relationship between newt abundance and hedgerow length, suggesting that hedgerows do not constitute substitutive terrestrial habitats for the species of interest or that their effects on population dynamics were masked by other population processes. As expected, newt abundance was negatively related to the proportion of land occupied by cultivated fields. In two species (T. helveticus and T. cristatus), this relationship was bell-shaped, suggesting that newt abundance within a pond is enhanced in landscapes where the proportion of area in cultivation remains moderate. Such an enhancement of abundance probably results from a crowding effect. The negative influence of fish presence suggested by the GAMs confirms findings from previous studies (Aronsson & Stenson 1995). T. cristatus may have a greater vulnerability to fish presence than T.

Figure 4. Response curves of the abundances of Triturus helveticus, T. alpestris, and T. cristatus to the environmental characteristics (pond and surrounding area) kept in the generalized additive models analysis (center lines). The y-axes are log-scale (link function), are based on partial residuals, and indicate the relative influence of each explanatory variable on the prediction. Distance between the upper and lower curves indicates two times the pointwise standard errors for each curve or factor level. N.S., not significant and for fish variable; 0, absent; 1, present.


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Table 1. Null deviance, residual deviance, degree of freedom, and residual df of each model of three newt species after the stepwise selection of explanatory variables. Parameter* Null deviance Residual deviance Degrees of freedom Residual df DI: pond area DI: depth DI: gently sloping banks DI: floating vegetation DI: hedgerow length DI: number of ponds DI: arable-grounds area DI: non-cultivated sector DI: fish

Triturus helveticus

Triturus alpestris

Triturus cristatus

1220 331 78 49.4 41 (4.6) 41 (4.6) ns 81 (9.1) 72 (8.1) 22 (2.5) 83 (9.3) 73 (8.2) 28 (3.1)

1054 261 78 45.6 40 (5) 17 (2.1) 25 (3.1) 10 (1.3) 65 (8.2) 25 (3.1) 14 (1.8) 66 (8.3) 10 (1.3)

230 40 78 58 12 (6.3) 3 (1.6) 25 (13.2) 44 (23.1) 11 (5.8) ns 37 (19.5) 4 (2.1) 16 (8.4)

*Residual deviance, deviance not supported by the selected variables. Difference between degrees of freedom and residual df is due to smoothing functions. Deviance increase (DI), marginal increases in deviance associated with dropping each selected variable from the species models, expressed by percentage in parentheses (deviance increase/[null deviance ⫺ residual deviance] ⫻ 100) (ns, nonsignificant influence).

helveticus and T. alpestris because of the nectonic behavior of its larvae. Of the environmental variables considered, only floating vegetation and uncultivated sectors were positively associated with newt abundance. Floating vegetation is used by the newts for egg laying, particularly in T. helveticus and T. cristatus (Miaud 1995). The positive relationship between the width of the uncultivated sector and newt abundances validates the hypothesis that this sector is the main component of connectivity between terrestrial and aquatic habitats in newts. Because the relationship between forest area and the abundances of both T. alpestris and T. cristatus was not significant, connectedness was the main landscape determinant of the abundances of these two species. The relationship between the width of the uncultivated sector and newt abundance suggests that the broader the sector the more individuals use it. This is in accordance with our knowledge of the orientation mechanisms that underlie urodele migrations. When migrating between their terrestrial and aquatic sites, these animals take a straight path (Shoop 1968; Madison & Shoop 1970; Shoop & Doty 1972; Douglas & Monroe 1981; Kleeberger & Werner 1982, 1983; Madison 1997). Most newt individuals are faithful to a given aquatic site ( Joly & Miaud 1989) and probably also to a terrestrial site (R. Jehle, unpublished results). At present, pilotage toward chemical cues emanating from the target site and magnetic compass are the only two orientation mechanisms that have been demonstrated experimentally (Hershey & Forester 1980; Phillips 1986a, 1986b, 1987; McGregor & Teska 1989; Phillips & Borland 1992; Joly & Miaud 1993). Both mecha-

Figure 5. Relationship between newt abundance and the width of the uncultivated sector (in degrees) in sites where woods covered from 25% to 40% of the 50-ha area surrounding the pond (Fig.1).

nisms determine straight trajectories. From one year to the next, most individuals follow the same path (P.J. & C.M., unpublished data). No evidence of the use of a cognitive map, which would allow animals to skirt a cultivated field, is presently available. Consequently, there is no evidence that linear corridors such as hedgerows or ditches can be used by newts as corridors allowing an efficient substitutive solution to reduction of the extent of fields permeable to their movements. Favorable migration habitat between terrestrial and aquatic sites has to be as broad as possible. In this context, newts differ from small rodents, for which linear corridors such as fencerows can ensure a valuable level of connectivity (Fahrig & Merriam 1985; Bennett 1990; Merriam & Lanoue 1990; La Polla & Barrett 1993).


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Figure 6. Relationship (a) between newt occurrence and number of ponds (n) within the 50-ha area surrounding the pond (1, n ⫽ 13; 2, n ⫽ 25; 3, n ⫽ 16; 4, n ⫽ 8; 5, n ⫽ 11; ⬎6, n ⫽ 6; hel, T. helveticus; alp, T. alpestris; cri, T. cristatus) and (b) for each species, between newt abundance and number of ponds in the surrounding area. Size of circles is positively related to numbers of sites. Conservation Biology Volume 15, No. 1, February 2001

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The width of the uncultivated sector probably modulates the number of newts able to complete their life cycles, whereas pond frequency in the immediate landscape probably influences metapopulation dynamics. Dispersal and migration, favored by a low interpond distance, are expected to ensure the continued presence of newts at a site, irrespective of their local reproductive success (Levins 1970; Gill 1978b; Hanski 1991). Our results (Fig. 6) confirm this hypothesis by establishing a positive relationship between newt occurrence in a pond and the number of ponds in close vicinity, despite variation in other environmental factors. The modality of the dependence of newt occurrence on pond frequency varied among species. Although no clear model was established for T. helveticus, a threshold effect was detected in T. alpestris and a linear relationship in T. cristatus. At least for these two species, abundance reached its highest levels in landscape configurations with intermediate pond frequency, suggesting that crowding occurs in configurations where spread to other ponds is restricted by isolation. Such pond frequencies also correspond to a habitat availability below which the species locally disappears (Wiens 1997). Other mechanisms can also be assumed to explain high abundances, such as high local connectivity, conspecific attraction, or other factors limiting population increase despite pond availability. In species with complex life cycles, processes operating in both aquatic and terrestrial phases are expected to contribute to the regulation of population numbers. The contribution of each phase may be expected to depend on the spatial configuration of these aquatic and terrestrial habitat types (Semlitsch 1998). Aquatic habitats are expected to influence population dynamics more prominently when they are scantily distributed, and the influence of terrestrial habitats is expected to predominate in configurations where ponds are plentiful. High newt abundances in situations of intermediate pond frequency support this hypothesis. But the ponds we sampled were selected to avoid the influence of ecological succession on abundance (newly created ponds or ponds filled with alluvium, which can be another important determinant of population dynamics) (Skelly & Meir 1997). Our study confirms the wide applicability of the connectivity concept to conservation biology (Hess 1996; Drechsler & Wissel 1998). It also demonstrates that the use of such a concept cannot be restricted to corridor design because the efficiency of corridors depends on the relationship between space-use behavior and landscape configuration for particular taxa. The integration of such behavioral contingencies in conservation biology represents a challenge for the coming years (Lima & Zollner 1996; Tischendorf et al. 1998). On the other hand, in analyzing only two levels of habitat determinants—local patch and close landscape—our study does

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not account for habitat influence at a broader scale. Further investigations should incorporate such an influence by using geographic information systems and landscape analysis in a metapopulation dynamics approach (Moilanen & Hanski 1998).

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