Methods in Ecology and Evolution

Top Research Topics at Methods in Ecology and Evolution?

The journal investigates areas of study like Statistics, Ecology, Econometrics, Data mining and Artificial intelligence. The Statistics study featured in the journal draws connections with the study of Abundance (ecology). It aims to address concerns in Ecology, specifically in the areas of Habitat, Ecology (disciplines), Biodiversity, Species richness and Ecosystem.

It connects the study in Biodiversity with the closely related area of Environmental resource management. Econometrics research is the primary subject tackled in the journal with a focus on Covariate. While the journal focused on Artificial intelligence, it was also able to explore topics like Machine learning, Computer vision and Pattern recognition.

• Statistics (23.47%)
• Ecology (21.87%)
• Econometrics (12.35%)

What are the most cited papers published in the journal?

• A general and simple method for obtaining R2 from generalized linear mixed-effects models (5633 citations)
• phytools: an R package for phylogenetic comparative biology (and other things) (4571 citations)
• A protocol for data exploration to avoid common statistical problems (4139 citations)

Research areas of the most cited articles at Methods in Ecology and Evolution:

The most cited papers are mainly concerned with subjects like Statistics, Ecology, Econometrics, Data mining and Phylogenetic tree. The most cited papers investigate Statistics research which frequently intersects with Abundance (ecology). The Data mining studies discussed in the most cited publications incorporate research from disciplines like

• Software and related Artificial intelligence,
• Inference which intersects with area such as Machine learning..

What topics the last edition of the journal is best known for?

• Ecology
• Statistics
• Artificial intelligence

The previous edition focused in particular on these issues:

Methods in Ecology and Evolution aims to foster the development of research in Artificial intelligence, Remote sensing, Statistics, Data mining and Ecology. Topics in Artificial intelligence were tackled in line with various other fields like Machine learning, Movement (music), Computer vision and Pattern recognition. Remote sensing (archaeology) is a major topic of Remote sensing research presented in it.

Statistics, which encompasses Range (statistics) and Sampling (statistics), is the main subject of Methods in Ecology and Evolution.

The most cited articles from the last journal are:

• raxmlGUI 2.0: A graphical interface and toolkit for phylogenetic analyses using RAxML (39 citations)
• Network measures in animal social network analysis: Their strengths, limits, interpretations and uses (27 citations)
• A deep active learning system for species identification and counting in camera trap images (20 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Methods in Ecology and Evolution (based on the number of publications) are:

• David I. Warton (16 papers) absent at the last edition,
• Olivier Gimenez (15 papers) absent at the last edition,
• Shinichi Nakagawa (13 papers) published 3 papers at the last edition, 2 more than at the previous edition,
• Gurutzeta Guillera-Arroita (13 papers) published 2 papers at the last edition,
• J. Andrew Royle (13 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Methods in Ecology and Evolution (based on the number of publications) are:

• Centre national de la recherche scientifique (70 papers) published 8 papers at the last edition, 5 more than at the previous edition,
• University of Oxford (59 papers) published 7 papers at the last edition, 2 more than at the previous edition,
• University of St Andrews (53 papers) published 8 papers at the last edition, 4 more than at the previous edition,
• University of New South Wales (50 papers) published 5 papers at the last edition the same number as at the previous edition,
• University of Melbourne (50 papers) published 9 papers at the last edition, 4 more than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 1.67% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 24.58% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.32% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.49% of all publications and 46.61% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.