To quantify the hindrance to dispersal caused by habitat fragmentation, landscape ecologists use the notion of landscape connectivity (Merriam 1984, Schippers et al. 1996, Schumacher 1996; With et al. 1997). Landscape connectivity refers to the degree to which the landscape facilitates or impedes movement among patches (Hansson 1991). In metapopulations (and metacommunities), connectivity is not only a property of the landscape but also an attribute of each patch, indicating how accessible the patch is for individuals from other patches. The connectivity of a patch increases with decreasing distances, and increasing sizes of other existing populations, given a species-specific migration rate. The distance may be the Euclidean distance or a more complex measure taking into account the influence of landscape structure on dispersal (Hanski 1998).
In zooplankton, resting stages are considered to be major dispersing agents. They are passively transported by wind, water, or organisms that can migrate actively to other habitats (Proctor 1964, Proctor and Malone 1965). In systems with interconnected water bodies, however, dispersal may also be mediated by water currents carrying along the active population component (Sandlund 1982, Akopian et al. 1999, Michels et al. 2001). Although resting stages are no doubt important for long-range dispersal in zooplankton, dispersal of the active population component is likely to be quantitatively much more important for neighboring ponds that are physically connected by rivulets and overflows than dispersal of resting stages (Jenkins and Underwood 1998, Brendonck and Riddoch 1999, Michels et al. 2001). In such systems, the Euclidean distance may not be the appropriate measure for inter-patch connectivity. The connectivity among zooplankton populations, i.e., the probability of successful dispersal of zooplankton organisms among populations, will be determined by the presence of a functional connection, the length of the dispersal pathway between source and target population (Schippers et al. 1996), the physical properties of the connecting elements (Michels et al. 2001), the habitat preferences, and the behavioral characteristics of the dispersing organisms (Jann and Bürgi 1988, Michels et al. 2001).
In an effort to quantify the effective geographic distance, the connectivity among zooplankton populations in a set of interconnected ponds located in the nature reserve “De Maten” was modelled. We define the effective geographic distance as the effective distance a dispersing zooplankton organism has to travel from the “source” pond to the “target” pond via the pathway of connecting elements (e.g., rivulets or overflows) between them. In a heterogeneous landscape, the effective geographic distance is a function of the travelling distance and the permeability of the interjacent landscape elements a dispersing organism encounters on its route. The effective geographic distance was modelled in a GIS (Geographic Information System) environment using the IDRISI software package (Version 2.0; Eastman 1997). DISPERSE is a function that models phenomena that have no motive force behind it. Rather, it is subject to anisotropic forces that cause it to move (Eastman 1997). For each connecting element, the direction of the force was defined according to its water flow orientation, since the passive dispersal of zooplankton with the water flow is an anisotrope process. Flow rates (mL/s) were estimated based on field data of water velocitiy and measurements of the cross section of the overflows. Water velocity (m/s) in all connecting elements was measured by timing the interval between adding NaCl and the passage of conductivity peak 10 m downstream, averaged over four measurements. The cross-section of each element was measured at 2-m intervals along the connecting element.
Figure 1A visualizes the effective geographic distance among ponds in “De Maten”. Three different clusters in the effective geographic distance matrix (obtained using Nonmetric Multidimensional Scaling, see Michels et al. 2001) correspond with three distinct branches of the pond complex “De Maten”: the upstream ponds (Ponds 32–22), the downstream ponds (17–2), and the ponds located northwest of the remainder of the complex (Ponds 18–21). Starting at the most upstream pond (Pond 32), the Stiemerbeek provides the water supply to the rest of the complex. There is no direct connection between the different clusters of ponds; only an indirect one, via the rivulet. As a result, the ponds belonging to different clusters are relatively isolated from another. Within each of the branches, however, overflows between ponds provide direct ways for zooplankton dispersal from pond to pond. Ponds 1 and 34 lack any physical connection to other ponds and could therefore not be included in the effective geographic distance matrices.
Fig. 1A: Geographic position of the study site, the nature reserve “De Maten” (50° 57´ N, 5° 27´ E; Genk, Province of Limburg, Belgium). Map of the pond complex showing pond numbers. Inflow at I1 , I2 (Pond 32) and I3 (Pond 18). Outflow at O1 (Pond 23) and O2 (Pond 7). The overall direction of water flow is from Pond 32 to Ponds 3 and 5. The total altitudinal difference between the most up- and downstream pond is 15 m. The different groups indicate the different clusters that are identified by the NMDS of the effective geographic distance matrix (see Fig. 1).
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