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From Metapopulations to Metacommunities: Linking Theory with Empirical Observations of the Spatial Population Dynamics of Stream Fishes Jeffrey A

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From Metapopulations to Metacommunities: Linking Theory with Empirical Observations of the Spatial Population Dynamics of Stream Fishes Jeffrey A American Fisheries Society Symposium 73:207–233, 2010 © 2010 by the American Fisheries Society From Metapopulations to Metacommunities: Linking Theory with Empirical Observations of the Spatial Population Dynamics of Stream Fishes Jeffrey A. Falke* and Kurt D. Fausch Department of Fish, Wildlife and Conservation Biology, Colorado State University Fort Collins, Colorado 80523, USA Abstract.—Stream fishes carry out their life histories across broad spatial and temporal scales, leading to spatially structured populations. Therefore, incorporat- ing metapopulation dynamics into models of stream fish populations may improve our ability to understand mechanisms regulating them. First, we reviewed empiri- cal research on metapopulation dynamics in the stream fish ecology literature and found 31 papers that used the metapopulation framework. The majority of papers applied no specific metapopulation model, or included space only implicitly. Al- though parameterization of spatially realistic models is challenging, we suggest that stream fish ecologists should incorporate space into models and recognize that metapopulation types may change across scales. Second, we considered metacom- munity theory, which addresses how trade-offs among dispersal, environmental heterogeneity, and biotic interactions structure communities across spatial scales. There are no explicit tests of metacommunity theory using stream fishes to date, so we used data from our research in a Great Plains stream to test the utility of these paradigms. We found that this plains fish metacommunity was structured mainly by spatial factors related to dispersal opportunity and, to a lesser extent, by environ- mental heterogeneity. Currently, metacommunity models are more heuristic than predictive. Therefore, we propose that future stream fish metacommunity research should focus on developing testable hypotheses that incorporate stream fish life history attributes, and seasonal environmental variability, across spatial scales. This emerging body of research is likely to be valuable not only for basic stream fish eco- logical research, but also multispecies conservation and management. Introduction their life history (Schlosser 1991; Fausch et al. 2002). Additionally, streams are linear habi- Stream fishes require multiple habitat types tats, arranged in hierarchical dendritic patterns (e.g., spawning, rearing, and refuge) to com- (Fagan 2002; Campbell Grant et al. 2007). As plete their life cycles (Schlosser and Anger- a result, natural and anthropogenic barriers meier 1995). These habitats are often dispersed can easily block movements among habitats in in space, throughout the riverscape, so that fish such branching networks (Ward 1983; Win- must move among habitat patches to carry out ston et al. 1991; Morita and Yamamoto 2002). * Corresponding author: [email protected] Therefore, the spatial arrangement of habitats 207 208 falke and fausch and the ability to move among them are critical and dispersal both vary in strength in differ- for stream fish persistence and recolonization ent communities and that trade-offs between dynamics. Moreover, incorporating spatial in- these two forces can help explain fundamental formation into models of stream fish popula- differences in community structure and the tions should improve our understanding of the processes that shape it. One tenet of the meta- mechanisms that control their dynamics. community approach is that local commu- The metapopulation concept has been used nities often do not have discrete boundaries by stream fish ecologists to help explain variabil- (Holyoak et al. 2005). In fact, patches within ity in local-scale population dynamics (Rieman which local communities reside are often tem- and McIntyre 1995; Schlosser and Angermeier porary and vary in position over time. Habitat 1995). Metapopulations are defined as groups patches in stream ecosystems may fit this mod- of habitat patches that support local popula- el well, due to variation in their persistence and tions, within a matrix that is not suitable habitat. location seasonally owing to fluctuations in Metapopulation theory states that all local pop- stream flow, and over longer time scales owing ulations eventually go extinct, but that dispersal to succession after disturbance. However, the among them has a quantitative influence on relative importance of spatial versus temporal population dynamics, including rescuing them habitat heterogeneity remains to be addressed from extinction or allowing for recolonization for stream fish assemblages in the context of after extinction (Hanski and Simberloff 1997). metacommunity theory. Therefore, a metapopulation approach may be Our objectives in this chapter are to review well suited for the study of fish population dy- and synthesize what is known about stream fish namics across the spatially dispersed, heteroge- metapopulations and metacommunities and to neous habitats common to streams (Schlosser provide a simple test of metacommunity mod- and Angermeier 1995). This approach has most els using empirical data for Great Plains stream commonly been used in the conservation and fishes in the western United States. Specifically, management of salmonids (Rieman and Dun- we first conducted a literature review of stream ham 2000). However, empirical support for fish metapopulation research to evaluate (1) metapopulation dynamics in most stream fish what empirical evidence exists for stream fish populations remains to be quantified, especially metapopulation dynamics, (2) what types of for nonsalmonid species. models have been used to test for metapopula- Because there are strong effects of spatial tion dynamics in stream fishes and the extent scale, habitat heterogeneity, and dispersal on to which these models incorporate space, stream fish populations, it stands to reason that and (3) what metapopulation type (Harrison stream fish communities also may be spatially 1991; Schlosser and Angermeier 1995) best structured. Recent work has built upon three fits stream fish metapopulations based on a decades of metapopulation theory to bridge consensus among empirical studies. Second, the gap between spatial population structure we reviewed stream fish and metacommunity and spatial community dynamics (Leibold et literature to evaluate (1) what empirical evi- al. 2004). Metacommunity models attempt dence exists for stream fish metacommunity to “scale up” the concepts set forth by meta- dynamics, and (2) whether four metacommu- population models to the community level. nity paradigms might apply to stream fish com- Metacommunity theory holds that biotic in- munities. Finally, we used data from our own teractions (e.g., competition and predation) research to evaluate how dispersal opportunity stream fish metapopulations and metacommunities 209 and habitat heterogeneity affect community ing patches (e.g., patch size, patch quality). structure across scales in a Great Plains stream The most well known is the incidence func- fish metacommunity. We also evaluated what tion model (Hanksi 1994). metacommunity model best fits these data. In addition to the type of metapopula- tion model used in each study, we classified Metapopulation Dynamics in whether or not the authors observed or mea- Stream Fish Populations sured metapopulation dynamics in the popu- lation and what metapopulation structure was Methods found. Metapopulation structure was catego- We reviewed the literature on stream fish ecol- rized among five types defined by Harrison ogy to evaluate empirical evidence for metapo- (1991), as modified by Schlosser and Anger- pulation dynamics. We included only primary meier (1995; Figure 1). research papers that dealt with lotic fishes Classic metapopulation.—The concept of a and included the term “metapopulation” or population of populations linked by dispersal “source-sink” in the title, abstract, or keywords. (i.e., metapopulation) was first proposed by We used the Web of Science © database as the Richard Levins (1969, 1970). Levins showed primary method of identifying these papers. that a metapopulation could be maintained Our review covers articles published from by dispersal among several subpopulations 1900 to 2008 from all journals included in the in discrete habitat patches. He assumed that Web of Science. all patches were of equal size, patches were Once located, papers were categorized by the same distance from one another, rates of the degree to which space was incorporated, colonization and extinction were equal, and based on model types identified in Hanksi subpopulations had independent dynamics and Simberloff (1997). Spatially implicit (Hanski and Simberloff 1997; Gotelli 2001). models are the simplest type of metapopu- Some patches can remain vacant at equilibri- lation model and assume all subpopulations um in this model type. Although this “classic” are identical and equally connected. No habi- metapopulation structure is unrealistic and tat heterogeneity is included in these models, probably rare, it serves as a null model and a and spatial locations of patches are not incor- basis on which to build more spatially realis- porated. An example is Levins’ metapopula- tic models of metapopulations. tion model (Levins 1969, 1970). In contrast, Source-sink metapopulation.—Several mod- spatially explicit models incorporate space els based on empirical evidence of metapo- or habitat heterogeneity into the model but pulation dynamics were proposed by Harrison not necessarily both. Examples are cellular (1991) and
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