Tovo, A, Formentin, M, Suweis, S et al. (3 more authors) (2019) Inferring macro-ecological patterns from local presence/absence data. Oikos, 128 (11). pp. 1525-1677. ISSN 0030-1299
Abstract
Biodiversity provides support for life, vital provisions, regulating services and has positive cultural impacts. It is therefore important to have accurate methods to measure biodiversity, in order to safeguard it when we discover it to be threatened. For practical reasons, biodiversity is usually measured at fine scales whereas diversity issues (e.g. conservation) interest regional or global scales. Moreover, biodiversity may change across spatial scales. It is therefore a key challenge to be able to translate local information on biodiversity into global patterns.
Many databases give no information about the abundances of a species within an area, but only its occurrence in each of the surveyed plots. In this paper, we introduce an analytical framework (implemented in a ready‐to‐use R code) to infer species richness and abundances at large spatial scales in biodiversity‐rich ecosystems when species presence/absence information is available on various scattered samples (i.e. upscaling).
This framework is based on the scale‐invariance property of the negative binomial. Our approach allows to infer and link within a unique framework important and well‐known biodiversity patterns of ecological theory, such as the species accumulation curve (SAC) and the relative species abundance (RSA) as well as a new emergent pattern, which is the relative species occupancy (RSO).
Our estimates are robust and accurate, as confirmed by tests performed on both in silico‐generated and real forests. We demonstrate the accuracy of our predictions using data from two well‐studied forest stands. Moreover, we compared our results with other popular methods proposed in the literature to infer species richness from presence to absence data and we showed that our framework gives better estimates. It has thus important applications to biodiversity research and conservation practice.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Authors. Oikos © 2019 Nordic Society Oikos. This is the peer reviewed version of the following article: Tovo, A. , Formentin, M. , Suweis, S. , Stivanello, S. , Azaele, S. and Maritan, A. (2019), Inferring macro‐ecological patterns from local presence/absence data. Oikos, 128: 1641-1652, which has been published in final form at https://doi.org/10.1111/oik.06754. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
Keywords: | biodiversity patterns; spatial ecology; species–abundance distribution; species–accumulation curve; upscaling biodiversity patterns |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Jul 2019 09:26 |
Last Modified: | 06 Jul 2020 00:40 |
Status: | Published |
Publisher: | Nordic Ecological Society |
Identification Number: | 10.1111/oik.06754 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148409 |