André Menegotto, Derek P. Tittensor, Robert K. Colwell, Thiago F. Rangel
{"title":"Sampling Simulation in a Virtual Ocean Reveals Strong Sampling Effect in Marine Diversity Patterns","authors":"André Menegotto, Derek P. Tittensor, Robert K. Colwell, Thiago F. Rangel","doi":"10.1111/geb.13952","DOIUrl":null,"url":null,"abstract":"AimUndersampling and other sources of sampling bias pose significant issues in marine macroecology, particularly when shaping conservation and management decisions. Yet, determining the extent to which such biases impact our understanding of marine diversity remains elusive. Here, utilising empirical data on sampling efforts, we sampled from virtually established species distributions to evaluate how deep is the influence of sampling bias on estimations of the latitudinal gradient in marine diversity.LocationAtlantic Ocean.Time PeriodPresent.Taxa StudiedOphiuroidea.MethodsWe developed a computer simulation that implements two null models of species distribution (the geometric constraints and the area model) in a two‐dimensional domain, replicates the latitudinal distribution of historical sampling efforts and then quantifies diversity metrics (observed and estimated species richness) and sample completeness for each grid cell and latitudinal band.ResultsWe found consistent patterns of observed species richness across models, noting peaks at midlatitudes regardless of whether the true richness was unimodal or flat. Dips in equatorial diversity persisted even after using different methods of species richness estimation. Additional simulations showed that estimators' accuracy improved with increased sampling efforts, but only when samples were randomly distributed. Spatially aggregated samples inflate completeness without necessarily enhancing estimators' accuracy.Main ConclusionsThis finding emphasises the imperative of bolstering sampling efforts at tropical latitudes and deploying robust statistical techniques to mitigate undersampling effects. Meanwhile, we suggest considering sampling bias as an alternative null hypothesis for recorded marine diversity patterns.","PeriodicalId":176,"journal":{"name":"Global Ecology and Biogeography","volume":"11 1","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Ecology and Biogeography","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1111/geb.13952","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
AimUndersampling and other sources of sampling bias pose significant issues in marine macroecology, particularly when shaping conservation and management decisions. Yet, determining the extent to which such biases impact our understanding of marine diversity remains elusive. Here, utilising empirical data on sampling efforts, we sampled from virtually established species distributions to evaluate how deep is the influence of sampling bias on estimations of the latitudinal gradient in marine diversity.LocationAtlantic Ocean.Time PeriodPresent.Taxa StudiedOphiuroidea.MethodsWe developed a computer simulation that implements two null models of species distribution (the geometric constraints and the area model) in a two‐dimensional domain, replicates the latitudinal distribution of historical sampling efforts and then quantifies diversity metrics (observed and estimated species richness) and sample completeness for each grid cell and latitudinal band.ResultsWe found consistent patterns of observed species richness across models, noting peaks at midlatitudes regardless of whether the true richness was unimodal or flat. Dips in equatorial diversity persisted even after using different methods of species richness estimation. Additional simulations showed that estimators' accuracy improved with increased sampling efforts, but only when samples were randomly distributed. Spatially aggregated samples inflate completeness without necessarily enhancing estimators' accuracy.Main ConclusionsThis finding emphasises the imperative of bolstering sampling efforts at tropical latitudes and deploying robust statistical techniques to mitigate undersampling effects. Meanwhile, we suggest considering sampling bias as an alternative null hypothesis for recorded marine diversity patterns.
期刊介绍:
Global Ecology and Biogeography (GEB) welcomes papers that investigate broad-scale (in space, time and/or taxonomy), general patterns in the organization of ecological systems and assemblages, and the processes that underlie them. In particular, GEB welcomes studies that use macroecological methods, comparative analyses, meta-analyses, reviews, spatial analyses and modelling to arrive at general, conceptual conclusions. Studies in GEB need not be global in spatial extent, but the conclusions and implications of the study must be relevant to ecologists and biogeographers globally, rather than being limited to local areas, or specific taxa. Similarly, GEB is not limited to spatial studies; we are equally interested in the general patterns of nature through time, among taxa (e.g., body sizes, dispersal abilities), through the course of evolution, etc. Further, GEB welcomes papers that investigate general impacts of human activities on ecological systems in accordance with the above criteria.