Biological Conservation 122 (2005) 151–158 www.elsevier.com/locate/biocon
Phyllostomid bat diversity in a variegated coﬀee landscape Catherine Numa
, Jose´ R. Verdu´
, Pedro Sa´nchez-Palomino
Instituto de Investigacio´n de Recursos Biolo´gicos Alexander von Humboldt, Carrera 7 #35-20, Bogota´, DC, Colombia Centro Iberoamericano de la Biodiversidad (CIBIO), Universidad de Alicante, Ctra. San Vicente del Raspeig s/n, E-03080 Alicante, Spain c Estacio´n de Biologı´a Tropical ‘‘Roberto Franco’’. Cr 33 No. 33-76 Barrio Porvenir, Villavicencio, Meta, Colombia Received 8 March 2004; received in revised form 7 July 2004; accepted 7 July 2004
Abstract We examined bat diversity at two diﬀerent spatial scales: habitat and matrix, in the Quindı´o coﬀee region in Colombia. Habitats were: forest, shaded coﬀee and associated coﬀee; and matrices were: associated coﬀee (M1) and shaded coﬀee (M2). Three sampling sites from each type of habitat were located at each matrix. The forest areas of the Quindı´o region are severely fragmented and less structurally complex than coﬀee patches. The shaded coﬀee habitat had patches that were larger and more complex. In spite of limited patch size and lower complexity, the forest remnants were those with greatest species richness and demonstrated clear similarities even between the two matrices. This was not observed in coﬀee plantations, neither in associated coﬀee nor shaded coﬀee. On the landscape scale, M2 showed lower b diversity and greater edge density (ED) than M1. This fact explains that greater connectivity between diﬀerent habitats exists in M2 than in M1. Our results suggest that production and conservation are compatible, as maintenance of forest remnants in a mosaic structure by landowners of the vegetation is suﬃcient to conserve phyllostomid bats at landscape level. 2004 Elsevier Ltd. All rights reserved. Keywords: Coﬀee agroecosystem; a Diversity; b Diversity; Forest fragmentation; Landscape matrices; Northern Andes
1. Introduction Studies on biodiversity of fragmented landscapes in Neotropics have generally focused on natural vegetation itself and overlooked the fact that traditional human activities through the ages have increased landscape heterogeneity, and therefore its biodiversity. Recently, studies have become increasingly aware that the landscape matrix within which forest fragments or remnants exist may be as important for biodiversity as the forest fragments themselves (Laurance, 1991; Wiens, 1995; Vandermeer and Perfecto, 1997; Renjifo, 2001; Perfecto and Vandermeer, 2002).
Corresponding author. Tel.: 34 965903400. E-mail addresses: [email protected]
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0006-3207/$ - see front matter 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2004.07.013
The inﬂuence of agricultural systems on biodiversity has traditionally been studied from a native forest perspective (Estrada et al., 1993; Estrada and CoatesEstrada, 2002) and a coﬀee shaded management perspective (Greenberg et al., 1997; Perfecto et al., 1996) in relatively well-conserved landscapes. That is, the original forest and forest remnants are a representative habitat in the territory (mainly a natural reserve), which have an important inﬂuence on agricultural habitats diversity depending on the distance between the main forest fragments and the agricultural patches (Ricketts et al., 2001). However, high production coﬀee regions in Colombia provide another scenario showing a good example of the degradation of coﬀee agroecosystems. As part of a strategy to increase production, the industry advocated the techniﬁcation of coﬀee, whereby shade trees are removed and the use of chemical fertilizers is common
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(Rice and Ward, 1997). In this sense, whereas twentyﬁve years ago, the majority of coﬀee production was associated with traditional practices (shaded coﬀee), in the 1990s 68% of coﬀee surface area was techniﬁed and 400,000 ton of chemical fertilizers were used (Rice and Ward, 1997). Coﬀee has been cultivated since the second half of the 19th century (Renjifo, 1999) in the Quindı´o department, and growers use both sun and shaded techniﬁed systems. In this area a few organic coffee farms have emerged lately but there are no rustic or traditional systems (similar to those described by Moguel and Toledo, 1999), and some patches of forest remain in areas that are diﬃcult to cultivate, or in order to preserve water supplies. Thus, we could consider this landscape as an extreme scenario of coﬀee landscape. To analyse biodiversity in these habitats, we have used bats, a group proposed as promising indicators for analysing biodiversity and habitat disruption due to their high ecological, trophic and species diversity and their easy sampling methods (Fenton et al., 1992; Wilson et al., 1996; Medellin et al., 2000; Moreno and Halﬀter, 2000). We focused on bats to answer several questions: (1) What inﬂuence does relative habitat surface, complexity (measured as a fractal dimension) and connectivity (measured as edge dimension) have on bat diversity distribution? (2) How does bat diversity diﬀer among forest, shaded coﬀee and associated coﬀee habitats?, and (3) What inﬂuence does matrix type have on bat diversity distribution at landscape scale?
2. Methods 2.1. Study area The study was carried out between October 1999 and February 2000 coinciding with the rainy season and the ﬂowering and fruiting of coﬀee plantations in the Quindı´o department on the western slope of the Central Andes in Colombia (410 0 N:7535 0 W to 440 0 N:7550 0 W), at elevations ranging from 1100 to 1850 m. The mean annual temperature in this region is 20.5 C. Total precipitation between February 1999 and February 2000 was 2850 mm, exceeding the mean annual rainfall of 2262 mm (Federacio´n Nacional de Cafeteros de Colombia, 2000). The Quindı´o coﬀee region includes approximately 76,422 ha. The landscape is an agricultural mosaic dominated by coﬀee plantations (65.5%) interspersed with some patches of other crops and land use such as banana plantations (Musa paradisiaca L., and M. sapientum L.) and pastures for livestock (24.5%). Natural habitat remains in lower montane forest patches (3.35%) and bamboo (Guadua angustifolia Kunth) patches (1.14%).
We focused our study on the three main habitat types: (1) associated coﬀee, a sun growing method including coﬀee (Coﬀea arabica L.) in monoculture or mixed with banana, with no tree species or isolated trees, if present; (2) shaded coﬀee, comprising coﬀee plantations with shadow tree species such as Inga codonantha (Pittier); I. edulis (Mart); I. densiﬂora (Benth) and associated eventually with banana; and (3) forest, present as small fragments in the coﬀee region. The principal families of these fragments include Moraceae (Brosimum, Ficus, Sorocea), Lauraceae (Ocotea, Nectandra), Melastomataceae (Miconia) and Rubiaceae (Psychotria, Palicourea). At the landscape scale, two diﬀerent matrix landscapes can be observed in the Quindı´o coﬀee region: M1 where associated coﬀee is the predominant habitat and M2, with shaded coﬀee as the main habitat. 2.2. Landscape analysis The Quindı´o coﬀee region map (Fig. 1) was analysed by GIS Unity of IavH (Villarreal, 2000) from a classiﬁcation of CRQ (1997) based on a 1996 Landsat TM satellite imagery with a 23 m resolution (each pixel was 23 m by 23 m). In this map, 21,100 ha (100.03 SD 1.70 ha) spatial windows were selected at random for calculation of diﬀerent spatial metrics with FRAGSTATS (McGarigal and Marks, 1995). We selected mean patch size (MPS) and mean patch fractal dimension (MPFD) to evaluate the spatial structure and complexity of diﬀerent habitats studied. We examined fractal dimension using a perimeter–area method, because this is a good spatial metric to determine the fragmentation level resulting from anthropogenic activities (Krummel et al., 1987). This fact was evaluated using a simple linear regression model. The Durbin–Watson test for ﬁrst order autocorrelation in regression residuals was used to examine independence of variables (Sokal and Rohlf, 1995). At landscape level, the type of matrix could determine the connectivity level between diﬀerent habitats. The existence of two diﬀerent coﬀee systems, one without shade trees and another structurally more similar to the forest, suggests the use of edge metrics to determine this eﬀect. As an edge refers to the border between two diﬀerent habitats, we calculated edge density (ED) as an estimator of connectivity between diﬀerent patch types. ED (in m/ha) takes the shape and complexity of patches into account, being a measurement of the spatial heterogeneity of a landscape mosaic. We used a non-parametric Kruskal–Wallis ANOVA on ranks to evaluate diﬀerences in MPS of patches among habitat types and mean ranks to make pair-wise multiple comparisons using post hoc DunnÕs test. To examine diﬀerences in MPFD of patches between habitat types, one-way ANOVA analysis with FisherÕs PLSD test for pair-wise comparisons was used. For compara-
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Table 1 Sampling eﬀort for bat surveys in the 18 localities of the Quindı´o coﬀee region Habitat type
Number of sampling sites
Total number of survey nights
Total sampling eﬀort a
Forest Associated coﬀee Shaded coﬀee Total
6 6 6 18
18 18 18 54
5587.8 5897.5 6133.5 17,618.8
a Total net meters multiplied by the total hours that the nets were open each night for a given site (Moreno and Halﬀter, 2001).
2.3. Sampling design and bat sampling We selected 18 sampling sites distributed throughout the three vegetation types in the Quindı´o coﬀee region: six forest fragments, six associated coﬀee and six shaded coﬀee plantations. Three sampling sites of each habitat were located at each matrix (M1 and M2). Bats were sampled with 50–80 m of mist nets (6–12 m long · 3 m high). Nets were exposed at dusk for 5–8 h and monitored every 45 min for three consecutive nights with no full moon at each location (Table 1). Each bat captured was identiﬁed to species level, sexed, measured (forearm length), marked and released. Each bat was temporarily marked with nail varnish to identify recaptures at each sample site. This study was restricted to species belonging to the Phyllostomidae family in order to avoid biases in the estimation due to species detectability, because mist nets tend to underestimate the presence of other bat families foraging at higher altitudes (Kalko et al., 1996). 2.4. Diversity analysis
Fig. 1. The study site in the coﬀee region of Quindı´o: (a) location of the windows (white squares) for spatial landscape analysis and coﬀee growing types (see the existence of two matrices); (b). location of sampling sites and distribution of forest remnants (black patches). Abbreviations: F, forest; Ca, associated coﬀee; and Cs, shaded coﬀee.
tive purposes of ED means between matrices, the Wilcoxon signed-ranks test was used (Sokal and Rohlf, 1995; Gardiner, 1997).
Species richness (S) was evaluated at two scales: at the habitat scale, comparing the three habitats localized in the coﬀee region; and at the landscape scale, comparing the same habitat when located in the two diﬀerent landscape matrices. To compare species richness among habitat types, we calculated a species accumulation curve using rarefaction methods for each habitat type. The rarefaction algorithm generates expected species richness based on a speciﬁed number of individuals randomly drawn from a community sample. We calculated the expected species richness E(Sn) and generated a mean and variance of species richness for each abundance by 1000 randomly iterations with EcoSim 7.0 (Gotelli and Entsminger, 2003). For spatial b diversity measures, we used a complementarity index calculated as deﬁned by Colwell and Coddington (1994) using EstimateS software (Colwell, 1997) based on bats assemblages along the spatial gradient. Pair-wise comparisons were made of the three habitats in each matrix type, resulting in a triangular matrix
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with 15 data points. After analysis, we carried out a cluster analysis by WardÕs method for linkage (StatSoft, 1997). At landscape scale, we used the WhittakerÕs diversity index (Whittaker, 1972) and a new index based on biotic distinctness among a gradient of habitats and suggested as an overall measure of the level of continuity in species composition within a system of n habitat (‘‘sensu lato turnover’’ attributable to spatial heterogeneity). This formula was inspired by RapoportÕs Index of cosmopolitism (C) (Rapoport, 1982) and the related endemicity index (EN) (Verdu´ and Galante, 2002). Thus, from presence–absence matrices, we proposed the following formula: N P nS n =S 1 bN ¼ 1 n¼1 ; N 1 where n is the number of habitats occupied by each species, Sn is the number of species which occur in nth habitat, S is the total number of species and N is the total number of habitats considered. Thus, the dimensionless b diversity measured by this formula varies from 0, when all species are present in all habitats (uniformity of spatial gradient), to 1, when all species occur in only one habitat (ÔuniqueÕ). Using this formula, we can compare the b diversity among diﬀerent landscape units (especially in landscapes with distinct grades of human modiﬁcation) showing the same habitat classiﬁcation. In this study, habitat was deﬁned as a discrete variable, but in practice it can also be quantiﬁed as a continuous variable using ranks or levels (e.g., temperature ranks, elevation, deforestation level, vegetation cover, etc.). Spatial c diversity was calculated in each matrix to compare the percentage explained by a and b diversity components. In this case, we used the formula proposed by Schluter and Ricklefs (1993), c diversity being the result of multiplying the average a diversity in the N habitats of the region, b diversity as the inverse of average number of habitats occupied by a species, and N as the total number of habitats considered.
with forest and associated coﬀee patches (Kruskal–Wallis H = 23.04, df = 2, p = 0.0001; DunnÕs test, Wij = 9.83, diﬀerences in average ranks, shaded/associated coffee = 12.99, p < 0.05; shaded coﬀee/forest = 16.82, p < 0.05), whereas forest and associated coﬀee patches did not diﬀer signiﬁcantly (diﬀerence in average ranks = 3.91, p > 0.05) (Fig. 2). Based on spatial structure, forest remnants showed the smaller fractal dimension on average (1.064, SD 0.016) and therefore were the less complex of the studied habitats (ANOVA F = 3.13, df = 2, p = 0.05) (Fig. 2). Only forest and shaded coﬀee patches diﬀered signiﬁcantly in their fractal dimension (Fisher PLSD = 0.029, p < 0.05). Thus, native forest is notably reduced to very small patches (average area 6.24 SD 3.04 ha), these being signiﬁcantly smaller and simpler in the landscape studied. A positive and signiﬁcant relation was observed between mean patch size and fractal dimension of forest patches (r2 = 0.73, Z = 2.51, p < 0.05) (Fig. 3). At landscape scale, M2 had greater ED (90.09 SD 22.69) than M1
Fig. 2. Spatial characterization of three habitat studied using mean patch size (in gray) and mean fractal dimension (in white). In all cases n = 11 and mean values were bracketed by their SD .
3. Results 3.1. Landscape analysis The coﬀee landscape of Quindı´o is severely fragmented, forming a mosaic structure dominated by coﬀee plantations. The vegetation map (Fig. 1(a)) corroborated the existence of two landscape matrices characterized by both associated (M1) and shaded (M2) coﬀee. In the Quindı´o, the lower montane forest was represented by small patches distributed along the river basins and included coﬀee matrices as small islets (Fig. 1(b)). The shaded coﬀee patches diﬀered signiﬁcantly in their areas
Fig. 3. Relation between mean patch size and mean patch fractal dimension of forest (r2 = 0.73, Z = 2.51, p = 0.022).
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Table 2 Phyllostomid bat species captured in diﬀerent habitat types at Quindı´o coﬀee region Species
Total coﬀee region
Glossophaga soricina (Pallas) Artibeus jamaicensis (Leach) Artibeus lituratus (Olfers) Carollia perspicillata (L.) Sturnira lilium (E. Geoﬀroy) Carollia brevicauda (Schinz) Platyrrhinus vittatus (Peters) Sturnira ludovici (Anthony) Chiroderma salvini Dobson Anoura geoﬀroyi (Gray) Artibeus phaeotis (Miller) Phyllostomus discolor (Wagner) Desmodus rotundus (Geoﬀroy) Platyrrhinus helleri (Peters) Carollia castanea (H. Allen) Choeroniscus godmani (Thomas) Phyllostomus hastatus (Pallas) Vampyressa pusilla (Wagner) Platyrrhinus dorsalis (Thomas) Uroderma bilobatum Peters Mimon crenulatum (E´. Geoﬀroy Saint-Hilaire) Total individuals Total species
30 45 22 28 17 15 14 10 7 2 12 0 6 2 4 4 0 0 1 1 1 221 18
192 72 50 55 9 14 5 0 3 1 2 2 0 2 0 0 2 2 0 1 0 412 15
122 109 74 39 23 17 5 1 11 11 4 5 0 2 1 0 1 0 2 1 0 428 17
344 226 146 122 49 46 24 11 21 14 18 7 6 6 5 4 3 2 3 3 1 1061 21
(59.27 SD 38.19) (Wilcoxon signed-ranks, Z = 2.49, p < 0.05). 3.2. Bat diversity With an eﬀort of 17,618.8 m/h at the 18 sampling sites in the Quindı´o coﬀee region, we recorded 1061 bats belonging to 21 species (Table 2). Rarefaction analysis showed that at n = 200 individuals, the forest was signiﬁcantly the richest habitat in expected species (E(Sn) = 16.80, SD 0.41). The same analysis showed that the species richness between coﬀee growing types was similar to the sample for associated coﬀee (E(Sn) = 11.97, SD 1.13), which fell within 95% conﬁdence interval of the rarefaction curve for shaded coﬀee (E(Sn) = 13.67, SD 1.14) (Fig. 4(c)). At landscape scale, the three habitats studied diﬀer in accumulated species richness between landscape matrices. At M1, species richness showed a similar pattern with the habitat scale analysis. Rarefaction analysis showed that at n = 150, forest at M1 was the richer habitat (E(Sn) = 14.61, SD 0.56), with species richness being similar between the two types of coﬀee plantations, since shaded coﬀee richness (E(Sn) = 9.36, SD 0.69) fell within the 95% conﬁdence interval of the associated coﬀee sample (E(Sn) = 7.86 SD 0.83) (Fig. 4(a)). These patterns are diﬀerent at shaded coﬀee matrix (M2). At n = 34, species richness in all habitats were similar since forest (E(Sn) = 9.85, SD 0.36) and associated coﬀee (E(Sn) = 9.80, SD 1.18) fell in the 95% conﬁdence interval of the shaded coﬀee sample (E(Sn) = 9.43, SD 1.26) (Fig. 4(b)).
In the dissimilarity cluster (Fig. 5) based on complementarity index, both matrices form distinct groups from the coﬀee habitat viewpoint. However, both forests were more similar to the shaded coﬀee matrix than associated coﬀee matrix. Associated coﬀee matrix (M1) showed greater b diversity (bW = 0.58; bN = 0.55) than shaded coﬀee matrix (M2) (bW = 0.32; bN = 0.36).c diversity in the shaded coﬀee matrix was higher (19.08 species) than that observed in associated coﬀee matrix (18.04 species). c diversity in the overall landscape was 21.53 species.
4. Discussion Coﬀee landscape in Quindı´o could be considered as a man-made landscape where agricultural patches dominate the territory and forest patches appear highly fragmented, less complex and immersed in the coﬀee matrices. From a spatial point of view, progressive fragmentation of the forest involves a reduction of the area of patches, and a progressive loss of structural complexity (Fig. 2). Fractal dimension has been suggested as a promising comparative measure of complexity and human disturbance in landscapes (Krummel et al., 1987; OÕNeill et al., 1988; Mladenoﬀ et al., 1993). The lower values of MPFD and the positive and signiﬁcant relation between MPS and MPFD found in forest patches of the Quindı´o landscape conﬁrm a strong degradation process of forest, being reduced to small and disperse circular patches (Fig. 1(b)).
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Fig. 4. Rarefaction curves for the three habitat and two landscape matrix studied. Comparisons were made at: (a) n = 150 at associated coﬀee matrix; (b) n = 34 for shaded coﬀee matrix; (c) n = 200 for the whole Quindı´o coﬀee region.
Fig. 5. Cluster analysis dendrogram (from complementarity matrix) showing diﬀerences in bat assemblage structure for the three habitat types at two landscape matrices. M1, Associated coﬀee matrix; M2, Shaded coﬀee matrix; F, forest; C, associated coﬀee; S, shaded coﬀee.
The structural diﬀerences between coﬀee system patches determined the complexity of the landscape matrices. In this sense, the landscape analysis showed the existence of two delimited aﬄuent areas with partic-
ular characteristics. The shaded coﬀee matrix (M2) formed by larger shaded coﬀee patches was more complex in structure of edges between habitats (ED) than associated coﬀee matrix (M1), where associated coﬀee patches had more simple forms and less area. The fact that shaded coﬀee shows a structure of intermediate cover between the forest and associated coﬀee allows us to conﬁrm that in M2 the connectivity between patches is greater. This fact was corroborated by the existence of a greater edge density (ED) between patches in M2, being an estimation of greater connectivity between habitats. In spite of spatial characteristics, forest patches at the coﬀee region of Quindı´o play an important role in biodiversity conservation. We found the highest species richness and some ‘‘unique’’ species in this habitat. Due to their spatial characteristics it is unlikely that forest fragments themselves may be suitable for sustenance and persistence of bat populations. Earlier studies of countryside landscapes have also found high diversity in relatively well-conserved forest fragments (Estrada et al., 1993; Estrada and Coates-Estrada, 2002; Daily et al., 2001). The bat species living in the Quindı´o coﬀee zone could be considered as an agricultural assemblage that can survive and breed in this landscape. The four most abundant species present in all habitats studied have been reported occurring in several habitats including agricultural, semi-urban and urban environments (Bredt and Uieda, 1996; Zorte´a and Chiarello, 1994; Estrada et al., 1993). Only three ÔuniqueÕ species, Desmodus rotundus, Choeroniscus godmani and Mimon crenulatum, seem to be highly dependent on the forest. The presence of refuges in the forest could be one of the factors that explain this behaviour because these species have been reported as using hollow trees, fallen logs and caves as refuges (Handley, 1976), which are not as readily available in coﬀee plantations. The occurrence of the hematophagous D. rotundus in the forest surrounded predominately by coﬀee also indicates the progressive process of the change from coﬀee to cattle (Sadeghian et al., 1998), especially in lower coﬀee zones (1000– 1200 m). This countryside bat assemblage had a low response in species richness to structural diﬀerences of coﬀee system management. As bat species can be segregated or beneﬁted by the roost site selection (Kunz, 1982; Fenton, 1997), we suggest that in this case banana, the main species cultivated with coﬀee in associated coﬀee systems could provide temporal refuge and food resources for bats (Roubik, 1995; Fleming, 1986), allowing a similar co-occurrence as in the shaded coﬀee. This factor could explain the higher abundance of the nectarivore Glossophaga soricina at the coﬀee plantations. Diet and roost habits of this habitat generalist include pollen and nectar of Inga and Musa (Fleming, 1986) and a high variety
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of roost sites, including man-made structures (C. N., pers. obs.). Landscape context plays a determining role for bat diversity distribution in this coﬀee region since the same habitats immersed in matrices with diﬀerent structural complexity were diﬀerent. While forest fragments at M1 were the richer habitat, at M2 this habitat was similar to both coﬀee systems, seeming to lose importance for concentrating bat species. This was conﬁrmed by the lower b diversity values at M2 in relation to M1. The M2 area showed more complexity in patch forms but was more homogeneous in habitat structure landscape than M1, which had lower patch complexity and more heterogeneity of habitat structure. Moreover, the spatial distribution of bat species was more homogeneous in M2 than in M1. In this sense b diversity at the Quindı´o coﬀee region was more important to determine c diversity than in other agricultural regions with similar c diversity (Moreno and Halﬀter, 2001). In spite of high vagility and a high number of generalist species, the distribution of bat assemblages responded to the habitat type (Table 2). The importance of forests was conﬁrmed when complementarity was examined: the forests at both M1 and M2 conserved their ‘‘species identity’’ in relation to the other habitat whereas coﬀee plantations were more inﬂuenced by matrix type than by the coﬀee growing system. The two coﬀee systems at M2 were more similar to each other than the same habitat at M1. This was also observed at the two coﬀee systems at M1, with the species composition of coﬀee habitat being more similar to the forest in M2 than in M1. Diﬀerences in species distribution of bat ‘‘agricultural’’ assemblage between matrix type and habitat type show the need to establish diﬀerent strategies for biodiversity conservation of this agricultural region. The bat assemblage could survive in a landscape with very reduced fragments of forest that serve as refuge and provide food for many species, some unique to this habitat. This fact explains that in some groups, species richness does not diﬀer signiﬁcantly between very small forest fragments and larger areas (Sekercioglu et al., 2002). Our results suggest that the maintenance of the connectivity between the diﬀerent patches from the mosaic is necessary to maintain intrinsic forest diversity. In this sense, although forest ÔuniquesÕ species should be considered for the conservation of forest diversity, the best determinant of the impact of disturbance and fragmentation could be bat species common to both forest and shaded coﬀee (see Table 2). At landscape scale, the maintenance of landscape structure in a variegated form is necessary for biodiversity conservation. The landscape dominated by coﬀee plantations is clearly suitable for the studied bat assemblage. We argue that production and conservation are not incompatible in this case. In order to conserve higher diversity in landscapes of this kind, high priority must be given to maintenance and protection of the forest
remnants that were preserved traditionally by land owners. We suggest that the key is to maintain spatial heterogeneity where the natural habitat and the countryside are alternated on diﬀerent scales. Acknowledgements We thank the GIS unit of Alexander von Humboldt Institute for their support in providing maps and FRAGSTATS data. We are grateful to E. Galante, G. Halﬀter, C. Moreno and J.M. Lobo for their comments and suggestions of this manuscript. We are indebted to Yenyfer Mona´ and Pablo Zanabria for their assistance in ﬁeld work. We thank Yaneth Mun˜oz-Saba for ﬁnal determination of the bat reference collection and Kate Burke for checking the English manuscript. This work was funded by COLCIENCIAS through ÔBiodiversity and agricultural systems at coﬀee zone (Quindı´o) projectÕ from the Instituto de Investigacio´n Alexander von Humboldt. We thank the Corporacio´n Auto´noma Regional del Quindı´o (CRQ), UMATAS, Cenicafe´, landowners and farm administrators for research permission and collaboration. This paper is dedicated to D. Rodrı´guez (in memoriam). References Bredt, A., Uieda, W., 1996. Bats from urban and rural environments of the Distrito Federal, mid-western Brazil. Chiroptera Neotropical 2, 54–57. Colwell, R.K., 1997. EstimateS: Statistical Estimation of Species Richness and Shared Species from Samples. Version 6.0b. Available from Accessed on 6/6/03. Colwell, R.K., Coddington, J.A., 1994. Estimating terrestrial biodiversity through extrapolation. Philosophical Transactions of the Royal Society (Series B) 345, 101–108. CRQ., 1997. Mapa de coberturas vegetales y ocupacio´n del espacio en el departamento del Quindı´o (1:25000 scale). Corporacio´n Auto´noma Regional del Quindı´o. Armenia, Colombia. Daily, G.C., Ehrlich, P.R., Sa´nchez-Azofeifa, G.A., 2001. Countryside biogeography: utilization of human-dominated habitats by the avifauna of southern Costa Rica. Ecological Applications 11, 1–13. Estrada, A., Coates-Estrada, R., Merrit, D., 1993. Bat species richness and abundance in tropical rain forest fragments and in agricultural habitats at Los Tuxtlas, Mexico. Ecography 16, 309–318. Estrada, A., Coates-Estrada, R., 2002. Bats in continuous forest, forest fragments and in an agricultural mosaic habitat-island at Los Tuxtlas, Mexico. Biological Conservation 103, 237–245. Federacio´n Nacional de Cafeteros de Colombia, 2000. Centro de Investigaciones de Cafe´ ‘‘CENICAFE’’, Disciplina de agroclimatologı´a, archivos clima´ticos, Chinchina´, Caldas, Colombia. Fenton, M.B., 1997. Science and the conservation of bats. Journal of Mammalogy 78, 1–14. Fenton, M.B., Acharya, L., Audet, D., Hickey, M.B.C., Merriman, C., Obrist, M.K., Syme, D.M., Adkins, B., 1992. Phyllostomid bats (Chiroptera: Phyllostomidae) as indicators of habitat disruption in the neotropics. Biotropica 24, 440–446. Fleming, T.H., 1986. The structure of neotropical bat communities: a preliminary analysis. Revista Chilena de Historia Natural 59, 135– 150.
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