Spatial synchrony occurs when properties measured in populations (e.g., species abundance), communities (species richness) or ecosystems (e.g., primary productivity) vary synchronously. Several studies have demonstrated synchrony of temporal dynamics in local population densities (Knops and Koenig 1998; Shanker and Sukumar 1999; Cattadori et al 1999; Liebhold et al 2004a). Other studies also revealed synchrony as an ubiquitous pattern, occurring in different regions (temperate and tropical), ecosystem types (e.g., aquatic and terrestrial) and on different groups of organisms (Moran 1953a, b; Ranta et al 1995, 2008; Bj??rnstad et al 1999; Ims and Andreassen 2000; Koenig 2001; Tedesco et al 2004; Lansac-T??ha et al 2008; Stange et al 2011).
Thus, spatial synchrony has important implications for population persistence. Empirical and theoretical studies indicate that synchrony enhance is associated with the increasing of regional extinction probability (Paradis et al. 1999). The more synchronous a metapopulation is, the lower is the expectation of the persistence time (Liebhold et al. 2004a). In this context, a process that causes extinction of a local population would lead all populations that fluctuate synchronously to the same risk of extinction. Besides, some level of synchronization can also allow local populations to function as source and restore extinct populations (Matter and Roland 2010).
Asynchronous population dynamics require a greater number of monitoring locations (Burrows et al. 2002). In this context, another important implication for spatial synchronization studies is the possibility to reduce the effort of sampling, since synchronous dynamic populations can be monitored in few environments (Stoddard et al. 1998; Anneville et al. 2004; Rhodes and Jonz??n 2011). Assuming regionalized or synchronous dynamic, the data from local “sentinels” can then be extrapolated to the whole area of interest (Anneville et al. 2004).
In general, the ubiquity of synchronous patterns has motivated ecologists in the search of underlying mechanisms. For example, geographical distance between local populations are generally negatively correlated with spatial synchrony, in other words, synchrony values decrease with increasing distances between pairs of local populations (Ranta et al. 1999; Koenig 2002). This synchrony decline can be explained in both terms of lower dispersal rates between environments separated by greater distances (Ranta et al. 1995; Lande et al. 1999; Paradis et al. 1999), as well as the decrease of environmental similarity versus distance (Ranta et al. 1999; Koenig 2002).
Trophic interactions between species can also synchronize local population dynamics (Buonaccorsi et al. 2001; Liebhold et al. 2004a). For example, on Lake Inari islands (Finland), mustelids predation was the primary cause of synchronous dynamics of small rodents populations (Heikkila et al. 2012). A study involving rodent populations Ondatra zibethicus L. and the predator Neovison vison Schreber in Canada also obtained similar results (Estay et al. 2011). However, those studies emphasized that different processes (dispersal, predation and fluctuations in precipitation) can explain the patterns of synchrony.
Environmental factors also exhibit a synchronizing effect on local populations dynamics (Liebhold et al. 2004b). In many regions, spatially disjunct populations may exhibit synchronic fluctuations determined by environmental variations (Hudson and Cattadori 1999; Koenig 1999, 2002). …
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