Sampling simulation in a virtual ocean reveals strong sampling effect in marine diversity patterns
Aim Undersampling 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 empiric...
| Authors: | , , , |
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| Format: | article |
| Publication Date: | 2024 |
| Country: | España |
| Institution: | Universidad Autónoma de Madrid |
| Repository: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Language: | English |
| OAI Identifier: | oai:repositorio.uam.es:10486/741120 |
| Online Access: | https://hdl.handle.net/10486/741120 https://dx.doi.org/10.1111/geb.13952 |
| Access Level: | Open access |
| Keyword: | Biodiversity gradient computer simulation knowledge gaps macroecology marine biodiversity richness estimate sampling bias species distribution Wallacean shortfall Biología y Biomedicina / Biología |
| Summary: | Aim Undersampling 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. Location Atlantic Ocean. Time Period Present. Taxa Studied Ophiuroidea. Methods We 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. Results We 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 Conclusions This 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 |
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