The geography of spatial synchrony

Walter, Jonathan A.; Sheppard, Lawrence W.; Anderson, Thomas L.; Kastens, Jude H.; Bjørnstad, Ottar N.; Liebhold, Andrew M.; Reuman, Daniel C.

doi:10.1111/ele.12782

Cited by 128 publications

(226 citation statements)

References 96 publications

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“…, Walter et al. ). The NMD model predicts that any two populations of species between quadrats would present some degree of distributional correlation, which is a function of both the shape parameter k and the quadrat characteristics (e.g., area size, neighbor distance, environmental heterogeneity, and so forth).…”

Section: Discussionmentioning

confidence: 99%

Community‐level species’ correlated distribution can be scale‐independent and related to the evenness of abundance

Chen

Shen

Condit

et al. 2018

Ecology

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The spatial distribution of species is not random; instead, individuals tend to gather, resulting in a non‐random pattern. Previous studies used the independent negative binomial distribution (NBD) to model the distributional aggregation of a single species, in which the independence of the distribution of individuals of a species in different quadrats had been assumed. This way of analyzing aggregation will result in the scale‐dependent estimation of the aggregation or shape parameter. However, because non‐random (and therefore non‐independent) distribution of individuals of a species in a finite area can be caused by either correlated or clumped distribution of individuals of a species between neighboring sites, an alternative model would assume that the distribution of individuals of a species over different sampling areas is multinomial. Here, we showed that, by assuming that regional species abundance followed a NBD while using a multinomial distribution to assign individuals of species in different non‐overlapped sampling quadrats that are from a partition of the entire region (quantifying positive correlation or synchrony), the estimation of the shape parameter in this probabilistic model, which is the negative multinomial distribution (NMD), was scale‐invariant (i.e., the estimated shape parameter is identical across different partitions of the study region). Accordingly, the estimation of the shape parameter was related to regional species distribution alone. This implied that, the shape parameter at the community level, using the NMD model, reflected the evenness of interspecific abundance. As a comparison, if the distribution of individuals of a single species followed independent NBDs as studied previously, the shape parameter would measure the evenness of intraspecific abundance (quantifying single‐species’ distributional aggregation). Moreover, our study highlighted the necessity for adjusting the model for the effects of unsampled species when studying community‐level distributional patterns. Collectively, as long as a target area is partitioned into non‐overlapping quadrats (no matter how their sizes vary), the proposed NMD model in this study, along with the independent NBDs model, can be jointly formulated as a framework to reconcile the scale‐dependent debate on the shape parameter, unifying the relationship between inter‐ or intraspecific abundance and distributional patterns.

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Section: Discussionmentioning

confidence: 99%

Community‐level species’ correlated distribution can be scale‐independent and related to the evenness of abundance

Chen

Shen

Condit

et al. 2018

Ecology

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“…, Walter et al. , Thorson et al. ), and species insurance can further stabilize metacommunity biomass if the metapopulation dynamics of the constituent species vary asynchronously in time (Wang et al.…”

Section: Introductionmentioning

confidence: 99%

Species insurance trumps spatial insurance in stabilizing biomass of a marine macroalgal metacommunity

Lamy

Wang

Renard

et al. 2019

Ecology

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Because natural ecosystems are complex, it is difficult to predict how their variability scales across space and levels of organization. The species‐insurance hypothesis predicts that asynchronous dynamics among species should reduce variability when biomass is aggregated either from local species populations to local multispecies communities, or from metapopulations to metacommunities. Similarly, the spatial‐insurance hypothesis predicts that asynchronous spatial dynamics among either local populations or local communities should stabilize metapopulation biomass and metacommunity biomass, respectively. In combination, both species and spatial insurance reduce variation in metacommunity biomass over time, yet these insurances are rarely considered together in natural systems. We partitioned the extent that species insurance and spatial insurance reduced the annual variation in macroalgal biomass in a southern California kelp forest. We quantified variability and synchrony at two levels of organization (population and community) and two spatial scales (local plots and region) and quantified the strength of species and spatial insurance by comparing observed variability and synchrony in aggregate biomass to null models of independent species or spatial dynamics based on cyclic‐shift permutation. Spatial insurance was weak, presumably because large‐scale oceanographic processes in the study region led to high spatial synchrony at both population‐ and community‐level biomass. Species insurance was stronger due to asynchronous dynamics among the metapopulations of a few common species. In particular, a regional decline in the dominant understory kelp species Pterygophora californica was compensated for by the rise of three subdominant species. These compensatory dynamics were associated with positive values of the Pacific Decadal Oscillation, indicating that differential species tolerances to warmer temperature and nutrient‐poor conditions may underlie species insurance in this system. Our results illustrate how species insurance can stabilize aggregate community properties in natural ecosystems where environmental conditions vary over broad spatial scales.

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“…Additionally, according to a recent study by Walter et al. (), MRM is a powerful, albeit underexploited, tool to infer the mechanisms behind synchrony. MRM models were carried out using the MRM function of the ecodist package (Goslee & Urban, ).…”

Section: Methodsmentioning

confidence: 99%

“…In general, the conditions most favourable to biological production are predicted to occur in this region (Kimmel, Lind, & Paulson, ). Because geographic patterns in synchronising environmental variables may account for spatial variation in population synchrony (Walter et al., ), one can expect that reservoir zonation would be an important factor to desynchronising plankton populations in reservoirs. Thus, (c) we assessed the relative roles of geographic and environmental distances in influencing the levels of spatial synchrony.…”

Section: Introductionmentioning

confidence: 99%

Environmental distances are more important than geographic distances when predicting spatial synchrony of zooplankton populations in a tropical reservoir

et al. 2018

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Several studies have shown that spatial synchrony, which is defined as the strength of the correlation between time series, is a common pattern that occurs in different regions, types of ecosystems and groups of organisms. In addition to applied research (optimisation of monitoring networks and population persistence), spatial synchrony has important implications for unravelling the processes underlying environmental and biological dynamics. We quantified the levels of synchrony among six sites in a tropical reservoir (Lajes Reservoir, Rio de Janeiro, Brazil) over 85 months (from August 2001 to December 2009) for twelve environmental variables, four broad zooplankton groups (testate amoebae, rotifers, cladocerans and copepods) and 23 abundant taxa. We hypothesised that (a) environmental synchrony would be higher than biological synchrony; (b) high synchrony would be found; and (c) biological synchrony matrices would be positively correlated with environmental synchrony and negatively correlated with both environmental and geographic distances. A strong relationship between biological synchrony and environmental matrices, when compared to geographic distance, would be consistent with the hypothesis that similar environmental variability synchronises the dynamics of local populations (Moran effect). In comparison to previous studies, we found high levels of synchrony. Environmental synchrony was often higher than biological synchrony, which was in line with our expectation and previous findings. The high levels of synchrony found in this study suggest that reservoir zonation was not enough to desynchronise the dynamics at the sites for both environmental and biological variables. Spatial synchrony in zooplankton populations declined more consistently with environmental distance than with geographic distance. Additionally, environmental distances were unrelated to geographic distances. Taken together, these results indicate a preponderant role of the Moran effect. Thus, as synchrony increases extinction rates, we speculate that novel ecosystems may be highly susceptible to regional‐wide changes in environmental factors.

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The geography of spatial synchrony

Cited by 128 publications

References 96 publications

Community‐level species’ correlated distribution can be scale‐independent and related to the evenness of abundance

Community‐level species’ correlated distribution can be scale‐independent and related to the evenness of abundance

Species insurance trumps spatial insurance in stabilizing biomass of a marine macroalgal metacommunity

Environmental distances are more important than geographic distances when predicting spatial synchrony of zooplankton populations in a tropical reservoir

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