Quantifying Biodiversity: Methods and Applications
Deadline for manuscript submissions: 20 May 2024 | Viewed by 10335
Biodiversity is a comprehensive concept of large amounts of ecological or biological information. In addition, the term biodiversity can be closely related to ecological conservation, monitoring, and management. As such, under different contexts of sampling schemes or model assumptions, a lot of biodiversity indices have been developed for simply and objectively measuring the concept quantitatively. However, it is not easy to directly assess biodiversity using observations or survey data in field work. Instead, in order to accurately and reliably quantify and infer assemblage biodiversity, proposing well-developed statistical toolkits is always welcome and essential in practical applications and monitoring ecosystems.
Diversity welcomes submissions of reviews as well as practical, modeling or observational studies to this Special Issue on topics including but not limited to: formulating new biodiversity indices, proposing novel statistical methods of well-known typical indices, creating novel sampling methods, and exploring new findings in biodiversity assessment and comparison.
Dr. Tsung-Jen Shen
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diversity is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- biodiversity index
- statistical model
- biodiversity sampling
- biodiversity assessment
- biodiversity conservation
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Applicability of common algorithms in species-area relationship model fitting
Abstract: The species-area relationship (SAR) describes a law of species richness changes as the sampling area varies, which is of great significance in the fields of biogeography, population ecology and conservation biology, and has been studied for more than 100 years. Accordingly, there are many algorithms available for fitting the SARs, but their applicability is not numerically evaluated yet. Here, we choose three typical and widely used algorithms, and discuss their applicability from three aspects: the number of iterations, the time consumption, and the sensitivity to the initial-parameter setting. Our results showed that, the Gauss-Newton method and the Levenberg-Marquardt method require relatively few iteration steps but consume more time, the Nelder-Mead method requires relatively more iteration steps but consumes the least time. Regarding the sensitivity of the algorithm to the initial parameters, the Gauss-Newton method and the Nelder-Mead method are more sensitive to the choice of initial parameters, while Levenberg-Marquardt method is relatively insensitive to the choice of initial parameters. Considering that the Gauss-Newton method and the Levenberg-Marquardt method can only fit the smooth SAR models, we argued conclusively that the Levenberg-Marquardt is the best choice to fit the smooth SARs, while the Nelder-Mead method is the best choice to fit the non-smooth SARs.