2020
DOI: 10.1111/1365-2745.13503
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Micro‐scale geography of synchrony in a serpentine plant community

Abstract: Fluctuations in population abundances are often correlated through time across multiple locations, a phenomenon known as spatial synchrony. Spatial synchrony can exhibit complex spatial structures, termed ‘geographies of synchrony’, that can reveal mechanisms underlying population fluctuations. However, most studies have focused on spatial extents of 10s to 100s of kilometres, making it unclear how synchrony concepts and approaches should apply to dynamics at finer spatial scales. We used network analyses, mul… Show more

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Cited by 19 publications
(33 citation statements)
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“…We estimated modularity for species‐specific networks and for the mean synchrony and mean anti‐synchrony networks. We determined the membership of each node using an extension of the method proposed by Newman (2006), which can be used when the network has some negative weights (Gómez et al., 2009; Walter et al., 2020). For this purpose, we used the functions cluseigen and modularity from the wsyn package (Reuman et al., 2019).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We estimated modularity for species‐specific networks and for the mean synchrony and mean anti‐synchrony networks. We determined the membership of each node using an extension of the method proposed by Newman (2006), which can be used when the network has some negative weights (Gómez et al., 2009; Walter et al., 2020). For this purpose, we used the functions cluseigen and modularity from the wsyn package (Reuman et al., 2019).…”
Section: Methodsmentioning
confidence: 99%
“…The relative influence of different mechanisms on spatial synchrony can be potentially investigated using matrix regression models (e.g., Anderson, Walter, et al., 2018; Haynes et al., 2013; Walter et al., 2017). Complementarily, the use of network‐based methods is a promising approach to detail the geography of synchrony (Dallas et al., 2020; Walter et al., 2017, 2020). In a network graph, nodes represent the local populations and edges represent the strength of pairwise synchrony (Walter et al., 2017).…”
Section: Introductionmentioning
confidence: 99%
“…Nevertheless, heterogeneity in factors such as soil conditions and habitat structure within sites has the potential to affect community stability directly, as well as indirectly through effects on biomass production, species richness, and species composition (Wilcox et al, 2017). Yet, the question whether small‐scale spatial heterogeneity of conditions affects temporal biomass stability and species synchrony in the local plant community has been less studied (McGranahan et al, 2016; Walter et al, 2020). Furthermore, stabilizing mechanisms have been mostly examined in grasslands with high dominance of perennial species (Hallet et al, 2014; Xu et al, 2015; Lepš et al, 2018), but seldom studied in annual plant communities in resource‐limited systems (Valone & Barber, 2008; Grman et al, 2010).…”
Section: Introductionmentioning
confidence: 99%
“…Spatial structure in abundance (i.e., detectable repeating patterns) across different scales was examined using a wavelet analysis (Fortin and Dale, 2005 ; Ma et al, 2021 ). Wavelet analyses have typically been used to detect patterns in time‐series datasets (e.g., Walter et al., 2020 ), but were applied here to a spatial signal, that is, patterns in sea urchin abundance along their linear range in South Africa. For each species, the wavelet power spectrum was generated with the Morlet wavelet (100 simulations).…”
Section: Methodsmentioning
confidence: 99%