2022
DOI: 10.1016/j.ecoinf.2022.101894
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Comparing distance-decay parameters: A novel test under pairwise dependence

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Cited by 4 publications
(4 citation statements)
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References 79 publications
(36 reference statements)
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“…Each standardized distance value ( d s ) was computed as d s = ( d i ‐min( d ))/(max( d )‐min( d )) where d i is the original spatial or climatic distance value, and d is the vector of all original spatial or climatic distances. Standardized spatial and climatic distance‐decay models were built fitting power‐law, negative exponential and Gompertz functions (Martín‐Devasa et al., 2022a) to the relationship between similarity and standardized spatial/climatic distances with the decay.model function of the R package betapart . The negative exponential model was selected for subsequent analyses as it showed the lowest AIC values in most cases (Tables S1 and S2 in Supplementary Material).…”
Section: Methodsmentioning
confidence: 99%
“…Each standardized distance value ( d s ) was computed as d s = ( d i ‐min( d ))/(max( d )‐min( d )) where d i is the original spatial or climatic distance value, and d is the vector of all original spatial or climatic distances. Standardized spatial and climatic distance‐decay models were built fitting power‐law, negative exponential and Gompertz functions (Martín‐Devasa et al., 2022a) to the relationship between similarity and standardized spatial/climatic distances with the decay.model function of the R package betapart . The negative exponential model was selected for subsequent analyses as it showed the lowest AIC values in most cases (Tables S1 and S2 in Supplementary Material).…”
Section: Methodsmentioning
confidence: 99%
“…We then fit two models of distance decay for the pairs of plots belonging to the same ecoregion and for those belonging to different ecoregions. We quantified the strength of the ecoregion effect by comparing the intercepts of the curves of distance decays (calculated for the whole community) for pairs of plots within and between ecoregions, which is a way of measuring the difference in community similarity at a null geographical distance, using the Zdep statistic (Martín-Devasa et al, 2022). This method is analogous to a t -test on model parameters, based on a site-block permutation test of the observations (nperm = 1,000).…”
Section: Methodsmentioning
confidence: 99%
“…We then fit two models of distance decay for the pairs of plots belonging to the same ecoregion and for those belonging to different ecoregions. We quantified the strength of the ecoregion effect by comparing the intercepts of the curves of distance decays (calculated for the whole community) for pairs of plots within and between ecoregions, which is a way of measuring the difference in community similarity at a null geographical distance, using the Zdep statistic (Martín‐Devasa et al., 2022). This method is analogous to a t ‐test on model parameters, based on a site‐block permutation test of the observations (nperm = 1000).…”
Section: Methodsmentioning
confidence: 99%