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One of the most crucial concerns of tropical ecologists is to assess the impact of habitat loss and fragmentation on species diversity, as well as the underlying ecological processes leading to local species extinctions (Stouffer & Bierregaard 1995a,b; Laurance & Bierregaard 1997; Gascon et al. 1999; Laurance et al. 2002; Ewers & Didham 2006). Habitat fragmentation may affect animal species’ densities through a variety of direct and indirect mechanisms, such as pure habitat loss, increasing edge effect and associated microclimatic changes on small fragments, isolation of habitat fragments, or greater extinction risks of small populations (Saunders, Hobbs & Margules 1991; Andrén 1994). To satisfy the needs of both theoretical and applied conservation biology, various hypotheses have been proposed to explain the density and distribution of animal species within fragmented landscapes. Early hypotheses were based on the equilibrium theory of island biogeography (MacArthur & Wilson 1967), stating that as in true islands, the occurrence of species in habitat fragments is a function of fragment area and isolation distance from the mainland (Simberloff 1988).
However, the theory of island biogeography has its own limits, and the ‘island metaphor’, consisting in treating habitat fragments as islands embedded in an inhospitable matrix, gives imperfect insights about the distribution of organisms in fragmented areas. Border shape of both fragments and mainland may also greatly influence colonization and dispersal rates, independently from fragment size or isolation distance (Taylor 1987a,b). Moreover, the occurrence of some species in fragments may depend more on dispersal movements from other fragments rather than from the mainland (Fahrig & Merriam 1994), making the notion of isolation distance difficult to apply. Conversely, some mainland areas bordering the inhospitable matrix are likely to undergo noticeable faunal changes as well, due to habitat disruptions, edge effect, or invading species. Thus, whenever possible, it is important to consider ecological processes along a continuous gradient of landscape disturbance rather than in a patch-based approach. Finally, the assumption that the matrix surrounding fragments is inhospitable regarding the focal species is often violated (Norton, Hannon & Schmiegelow 2000; Ricketts 2001; Brotons, Mönkkönen & Martin 2003; Kupfer, Malanson & Franklin 2006). For instance, forest birds may find valuable food resources in pastures or logged areas surrounding their natural habitat, leading to greater population densities than expected in fragmented areas (Brotons, Herrando & Martin 2004; Brotons et al. 2005). Therefore, it is of special interest to control for possible mitigating effects related to matrix quality.
The recent discipline of landscape ecology, using GIS-based analyses of landscape structure, offers solutions to side-step these limitations. Landscape analyses can provide integrative measurements of spatial heterogeneity, combining many environmental variables and their spatial interactions. Among the descriptors of landscape structure, landscape connectivity may provide valuable insights for understanding ecological processes related to habitat fragmentation. Landscape connectivity describes the degree to which the landscape facilitates or impedes movements of animals among resource patches (Taylor et al. 1993) and may be used to predict the distribution of their movements and activity in fragmented areas. Landscape connectivity has been successfully linked to ecological processes in an increasing number of studies (With, Gardner & Turner 1997), including analyses of dispersal distances and genetic relatedness among animal individuals or populations (Manel et al. 2003; Coulon et al. 2004).
More recently, Bélisle (2005) reviewed the notions of structural and functional connectivity. On one hand, landscape parameters that measure ‘the degree to which some landscape elements of interest are contiguous or physically linked to one another’ refer to structural connectivity (With et al. 1997; Tischendorf & Fahrig 2000). On the other hand, landscape parameters that take into account dispersal or movement abilities of the studied organisms – i.e. that measure landscape connectivity with respect to how organisms may perceive landscape – refer to functional connectivity. Species-specific studies would gain in efficiency and applicability if behaviour-based functional connectivity was favoured. Without any tight link to behaviour, it is necessary to consider in connectivity analyses several to many landscape descriptors, as well as their respective interactions. Furthermore, several trials may be necessary to determine which spatial scale is the most relevant for the target species. Overall, batteries of nonindependent analyses repeated at different spatial scales may be required. This increases risks of misinterpretations due to type I statistical errors (null hypothesis rejected while it is true), or even to type II errors (null hypothesis accepted while it is false) if probability values are corrected for too many tests.
The objectives of this study were: (1) to develop an index of functional landscape connectivity for a Neotropical understorey frugivorous bat Rhinophylla pumilio Peters (Phyllostomidae), whose foraging pattern has been well described (Henry & Kalko 2007); (2) to test whether functional connectivity, jointly with resource availability, may contribute to explain the distribution and sustainability of these bats within a fragmented rainforest; and (3) to assess whether the functional connectivity index may be also applied to the other species of the guild of understorey frugivorous bats, including the genera Carollia and Sturnira (Phyllostomidae). These understorey frugivorous bats act as important seed dispersers in tropical forests (Henry & Jouard 2007) and are sensitive to modifications of landscape structure (Estrada, Coates-Estrada & Merrit 1993; Brosset et al. 1996; Kalko 1998; Schulze, Seavy & Whitacre 2000; Estrada & Coates-Estrada 2001, 2002; Faria 2006). Previous studies (Gorresen & Willig 2004) succeeded to link the abundance of frugivorous bats to various indicators of structural landscape connectivity (e.g. forest cover, densities of fragments). In this study, we further introduce keystone behavioural components to develop an indicator of functional landscape connectivity.
Understorey frugivorous bats feed on well-scattered food items, mainly small fruits produced in small amounts and for extended periods of time (‘steady-state’ fruit crops; Kalko 1998; Thies & Kalko 2004) by understorey plants. This forces bats to be constantly engaged in flights devoted to food search, and to rarely commute over long distances (Fleming, Heithaus & Sawyer 1977; Heithaus & Fleming 1978; Thies, Kalko & Schnitzler 2006; Henry & Kalko 2007). This foraging behaviour appears incompatible with the patchy distribution of resources in fragmented forests. Thus, we hypothesized that the distribution of understorey fruit bats was more dependent on the degree of landscape connectivity (ensuring spatial continuity of resource distribution) than on local conditions of resource availability.
For that purpose, we pursued a long-term bat survey, coupled with local estimates of resource availability, that was initiated 10 years ago in Saint-Eugène, French Guiana (Granjon et al. 1996; Cosson, Pons & Masson 1999a; Cosson et al. 1999b; Pons & Cosson 2002). In this study area, forest fragments are land bridge islands recently isolated from the continuous forest by a reservoir lake. Therefore, one can consider that the landscape is composed of two elements only – the mature forest and an aquatic matrix devoid of fruit resources that could modify the local conditions of resource availability and spatial continuity (Leigh et al. 2002). After validating a connectivity modelling in this simplified system, one may transpose it into more complex landscape mosaics with matrix habitats of various quality.
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Our results have shown that we can rely on radio-tracking data to develop an index of functional landscape connectivity that may help in explaining the distribution of bats in heterogeneous landscapes or may predict their future variations in changing landscapes. Using landscape descriptors based on the foraging pattern of R. pumilio, we have shown that this species is sensitive to the loss of landscape connectivity per se, unrelated to food resource availability. The equations of regression lines in Fig. 5 may be used to predict the abundance of R. pumilio in landscapes with similar habitats and matrix. Furthermore, the same connectivity index contributed to explain variation in the abundance of other understorey frugivorous bat species, suggesting that one may use well-documented species as study models to make crude predictions about the distribution of other species of the same guild.
Figure 5. Effect of landscape connectivity on abundance index 2 of understorey fruit bats during the recent and older fragmentation periods. All periods combined, equations of linear regressions are [y = 0·0039x – 0·4623] and [y = 0·0034x – 0·4046] for R. pumilio and shrub-frugivorous bats, respectively.
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A functional connectivity index measures the degree of landscape connectivity with respect to how organisms may perceive the landscape structure (Bélisle 2005). In the present study, we expected the continuity of forest habitat to be an important feature for R. pumilio given its diet and foraging behaviour. Roost availability was not regarded herein as an essential feature as the roosting behaviour of R. pumilio appears flexible. Individuals roost in small groups under large leaves of fairly common epiphyte or palm tree species, located within or close to their foraging area. They can change roost every few days (Charles-Dominique 1993; Zortéa 1995; Simmons & Voss 1998; Henry & Kalko 2007). In other case studies, like cave-dwelling bats displaying high roost fidelity, roost availability may appear as the proximal factor influencing individuals’ distribution in landscapes. Thus, a functional connectivity index should have a special link with roosting behaviour, taking into account roost locations or densities and/or distances between roosts and foraging habitats.
r. pumilio, a case study
In the simplified system of Saint-Eugène composed of a forested habitat and an aquatic matrix, we found that the distribution of R. pumilio individuals was strongly influenced by our proximal index of forest connectivity based on foraging behaviour. Results support the prediction that local abundance of R. pumilio is more dependent on habitat fragmentation per se, i.e. the loss of landscape connectivity, than on resource availability. Landscape connectivity was the main determinant of its abundance, while food resource availability did not explain a significant portion of the variation in its abundance. The abundance of R. pumilio decreased along a decreasing gradient of landscape connectivity, whereas estimates of food availability remained stable (epiphytes) or even increased (Piper) along the same gradient. It is possible that changes in light and microclimate factors after the creation of the fragments locally increased the density of light-demanding pioneer Piper. Newly created edges are characterized by greater light penetration due to increased tree mortality and foliage drop induced by the physiological stress of moisture and temperature changes (Lovejoy et al. 1986; Kapos 1989; Malcolm 1994; Ferreira & Laurance 1997; Laurance et al. 1998, 2002) and it appears that Piper flourishes under these conditions.
The sensitivity of R. pumilio to the loss of landscape connectivity, despite the maintenance of food resource availability, could stem from the incompatibility of their foraging strategy with the obligation to cross expanses of matrix devoid of food sources. The foraging strategy, i.e. the manner in which bats move across landscapes to search for and exploit food resources, can be roughly decomposed into two components: search flights and commuting flights (Fleming et al. 1977; Heithaus & Fleming 1978; Henry 2005; Thies et al. 2006). While search flights are devoted to finding food items within foraging areas, commuting flights refer to longer straightforward flights conducted by bats among several foraging areas. To find their widely scattered food items, understorey fruit bats mostly rely on search flights and less frequently on longer commuting flights (Fleming et al. 1977; Heithaus & Fleming 1978; Bonaccorso & Gush 1987; Henry 2005; Thies et al. 2006). As a consequence, they might be reluctant to, or fail to, efficiently exploit patchily distributed food resources that impose frequent commuting flights over an unexploited matrix.
The foraging strategy of R. pumilio could even be considered as an extreme search strategy because these bats use almost exclusively search flights and therefore exploit a single small foraging area (Henry & Kalko 2007). Most of the surveyed fragments (0·8–7·5 ha) are smaller in size than their foraging area (3·5–14·1 ha; Henry & Kalko 2007). This might force individuals to split their foraging area into smaller ones distributed over two or several contiguous fragments, resulting in regular disruptions of search flights and thus lower their foraging efficiency.
Nevertheless, our data suggest that although R. pumilio was strongly affected by the loss of landscape connectivity, it could subsist at low densities in poorly connected habitats away from the mainland and could be a resident in the fragmented area. As a pre-requisite, we got direct evidence from telemetry that individuals can cross narrow habitat disruptions between fragments when these fragments are smaller in size than their home range. Most importantly, habitat remoteness, which was directly calculated from the proximal connectivity index, did not influence the abundance of R. pumilio. This indicates that the presence of R. pumilio in rather remote sites does not depend on the proximity of mainland, and suggests that local reproductive recruitment may occur in fragmented areas. Accordingly, on many occasions we found juveniles and reproductive (gestating or lactating) females in small fragments. Reproductive activity does not seem precluded by the loss of landscape connectivity for R. pumilio.
r. pumilio as a model species
R. pumilio was a successful model to build a connectivity index applicable to other species of the same guild, namely Carollia and Sturnira species, for which search flights are also thought to be an important component of foraging behaviour. However, the equation linking connectivity index to abundance (Fig. 5) should be regarded as a very rough predictor because it is based on scarce capture data combining several species. More capture data would be welcomed to refine the model, but this seems hardly feasible in this context where shrub-frugivorous bats have apparently deserted fragments during the transition from recent to older fragmentation periods. This general decline in abundance, also depicted by GLM analyses (Table 2) may be related to the pervasive decrease of Piper as a food resource over the study area (Fig. 4). A progressive closure of canopy foliage within edges could have resulted in the disappearance of many light-demanding Piper plants during the 5 years separating the two plant surveys. Many stems of dead young Piper were found in the later period.
We suggest that enlarging the spatial scale of the study would provide better insights about the relation between landscape connectivity and the abundance of Carollia and Sturnira species. At least, Carollia perspicillata exploits larger home ranges than R. pumilio and may regularly perform longer commuting flights among several (two to three) foraging areas located 500–1500 m apart (Heithaus & Fleming 1978). Thus, C. perspicillata is likely to perceive landscape connectivity in a different way, or at a different spatial scale. Accordingly, Gorresen & Willig (2004) found significant effects of landscape structure on the abundance of C. perspicillata within focus windows of 1–5 km radii, which is 2·5–12 times the spatial scale used for R. pumilio. We can imagine that our study transposed to C. perspicillata would yield a much extended curve of flight frequency distribution (Fig. 3) with high weighting coefficients attributed to landscape units situated within a much larger radius. This would produce connectivity values much smaller than for R. pumilio in the fragmented area, and also with much less intersite variability. In other words, C. perspiscillata is likely to perceive and respond to fragmentation at an earlier degree of structural connectivity loss compared with R. pumilio. This could also explain why Carollia species eventually disappeared from fragments at Saint-Eugène while R. pumilio did not.
difficulties and alternatives
Collecting data on the foraging pattern of bats poses a technical challenge due to their high mobility. Detailed data on flight distance collected herein could even be seen as an exception within bat studies, given the unusually short displacements displayed by R. pumilio (mostly < 200 m at a time) compared with other well-studied species. Available tracking data commonly state home ranges encompassing several tens to several hundreds of hectares in a few days, making flight distances difficult to monitor. Nevertheless, an increasing number of well-documented studies with standardized tracking protocols are now available, concerning either shrub-frugivorous bats (Thies et al. 2006) or insectivorous bats (Weinbeer & Kalko 2004; Meyer, Weinbeer & Kalko 2005). Although these studies may not document flight distance between successive hanging locations with as much accuracy as in the small home-ranged R. pumilio, they can at least document flight distance observed at fixed time intervals (e.g. every 3 min, or every 10 min).
In studies where the positioning of bats is irregular in time, we propose to rely on density kernels generated by analyses of home range or foraging area (e.g. Weinbeer & Kalko 2004; Henry & Kalko 2007). Methods of probabilistic kernels produce concentric density contours delineating areas of a given probability of presence. By plotting the inverse probability of presence (1 – P) on the vertical axis, against the radius of the corresponding area on the horizontal axis, one may obtain curves similar in shape to the frequency distribution of maximal flight distance (Fig. 3).
Finally, other methods than telemetry could provide data on flight distance frequency distribution, but these could only be operational at greatest temporal and spatial scales. Capture–recapture data, when summed over many individuals in a well-sampled study area, could be treated as flight distances. Genetic analyses performed on pollen or seeds collected on captured individuals can give data on the location of visited plants, providing plants are already indexed in the vicinity. Finally, homing experiments measuring the time it takes individuals to return to their roost as a function of translocation distance, have been used in various taxa as a means to assess landscape connectivity (see the review by Bélisle 2005, p. 1993). Homing experiments could be conducted on cave-dwelling bats.
implications and future directions
Our study contrasts with the other bat surveys conducted in forest fragments surrounded by abundant second-growth vegetation characterized by very high densities of the bat plants Piper, Solanum or Vismia (Estrada et al. 1993; Brosset et al. 1996; Kalko 1998; Schulze et al. 2000; Estrada & Coates-Estrada 2001, 2002; Gorresen & Willig 2004). In these studies, Carollia and Sturnira species remained abundant in forest fragments, second growth and pastures where they are effective seed dispersers (Galindo-González, Guevara & Sosa 2000). Therefore, bat surveys in Saint-Eugène indirectly underline the important role of second growth vegetation in shaping fruit bat communities in fragmented forests. A matrix colonized by second growth vegetation may provide bats with compensatory food supplies that favour the spatial continuity of resource distribution (matrix compensation and supplementation hypotheses; Dunning, Danielson & Pulliam 1992; Norton et al. 2000). In further studies, indicators of landscape connectivity should be adapted to more complex environments including various habitat types. In the modelling calculation, the different habitat types should be assigned to different suitability values ranging between 0 and 200, depending for instance on their relative contribution to the diet of bats. Such modelling connectivity in more realistic landscape mosaics is urgently needed. Among others, it would help understanding how bat diversity patterns may be influenced by the spatial configuration of the various neighbouring habitat types, and how communities are likely to be modified in changing landscapes.
Indicators of landscape connectivity may also contribute to an understanding of ecological processes at different levels of analysis. One may, for instance, expect intraspecific variation in the perception of landscape connectivity. Breeding females have to face critical energetic, temporal and behavioural constraints, and are usually forced to reduce the spatial extent of their foraging movements (e.g. Racey & Swift 1985; Kurta et al. 1989; Charles-Dominique 1991; Henry et al. 2002). In particular, lactating R. pumilio reduce their foraging area and flight distances by 42% and 25%, respectively (Henry & Kalko 2007), and are then likely to perceive landscape connectivity in a different way. This raises questions about spatial variation of population dynamics in fragmented areas. At the interspecific level, landscape connectivity may help investigate or predict possible effects of competition relaxation in areas where perceived landscape connectivity varies greatly among competitors. Conversely, studies of the mutualistic interactions between plants and seed-dispersing bats could benefit from a better knowledge of what landscape connectivity means from dispersers’ eyes.
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We are grateful to G. Dubost and C. Erard who initiated this project. We thank R. Barbault, P. Charles-Dominique, T.H. Fleming, P.M. Forget, E.K.V. Kalko, L. Granjon, J.L. Martin, N.G. Yoccoz and H.J. Young for providing valuable criticism and suggestions. Many thanks also go to all the people who participated or helped in any aspect of the fieldwork, especially P. Cerdan (Laboratoire Hydreco, barrage de Petit-Saut), S. Poirot, A.S. Hennion, A. Lyet, R. Kirsch and D. Pons. The fieldwork was supported by the ‘Electricité de France’ (Convention Muséum/EDF CQZH 1294) and the Laboratoire d’Ecologie Générale de Brunoy (MNHN-CNRS, UMR 5176, France). M.H. received a Ph.D. grant from La Fondation des Treilles.