2022
DOI: 10.1101/2022.02.10.480007
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Spatial patterns from a dispersal limitation perspective: revealing biotic interactions

Abstract: Local spatial distributions of populations are often studied in comparison to Complete Spatial Randomness (CSR) and are found to be ubiquitously aggregated, likely due to dispersal limitation. Here we theoretically examine the advantages of comparing observed distributions to simulated populations subject only to drift and Dispersal Limitation (DL). Compared to this DL null, local competition produces overdispersion out to surprisingly large scales, much larger than the scale of competitive interactions. Furth… Show more

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Cited by 1 publication
(5 citation statements)
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“…While we expect overdispersion to occur primarily at the short distances at which CNDD operates 3,5,8 , species are typically overdispersed at distances up to ~100 meters, having ~ 45% fewer neighbors 75 – 125 meters away from a typical tree (under the Standard null, but this is not the case under all null variants, Figure 2, Extended Data Table 1). Our recent simulation study shows that such long-distance overdispersion can be observed in a model with short-distance CNDD 42 . Intuitively, while each tree “repels” only its neighbors, they in turn repel their neighbors and so forth, creating large-scale patterns from short-distance interactions 43 .…”
Section: Resultsmentioning
confidence: 87%
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“…While we expect overdispersion to occur primarily at the short distances at which CNDD operates 3,5,8 , species are typically overdispersed at distances up to ~100 meters, having ~ 45% fewer neighbors 75 – 125 meters away from a typical tree (under the Standard null, but this is not the case under all null variants, Figure 2, Extended Data Table 1). Our recent simulation study shows that such long-distance overdispersion can be observed in a model with short-distance CNDD 42 . Intuitively, while each tree “repels” only its neighbors, they in turn repel their neighbors and so forth, creating large-scale patterns from short-distance interactions 43 .…”
Section: Resultsmentioning
confidence: 87%
“…Intuitively, when HNDD = CNDD the competitive effect of neighbors is equal for all neighbors regardless of their species, and so competition cannot generate a strong repulsion from conspecifics. Moreover, in a theoretical study of simulations across a wide range of parameter space of the strengths of CNDD and HNDD 42 , we found that large values of HNDD "erode" the species-specific overdispersion created by CNDD even when CNDD > HNDD. Hence, only the scenario CNDD >> HNDD is compatible with patterns of overdispersion observed here.…”
Section: Resultsmentioning
confidence: 88%
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