Ten simple rules to bridge ecology and palaeoecology by publishing outside palaeoecological journals.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2024-10-15 DOI:10.1371/journal.pcbi.1012487
Nick Schafstall, Xavier Benito, Sandra O Brugger, Althea L Davies, Erle Ellis, Sergi Pla-Rabes, Alicja Bonk, M Jane Bunting, Frank M Chambers, Suzette G A Flantua, Tamara L Fletcher, Caroline Greiser, Armand Hernández, Benjamin Gwinneth, Gerbrand Koren, Katarzyna Marcisz, Encarni Montoya, Adolfo Quesada-Román, Amila S Ratnayake, Pierre Sabatier, John P Smol, Nancy Y Suárez-Mozo
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Abstract

Owing to its specialised methodology, palaeoecology is often regarded as a separate field from ecology, even though it is essential for understanding long-term ecological processes that have shaped the ecosystems that ecologists study and manage. Despite advances in ecological modelling, sample dating, and proxy-based reconstructions facilitating direct comparison of palaeoecological data with neo-ecological data, most of the scientific knowledge derived from palaeoecological studies remains siloed. We surveyed a group of palaeo-researchers with experience in crossing the divide between palaeoecology and neo-ecology, to develop Ten Simple Rules for publishing your palaeoecological research in non-palaeo journals. Our 10 rules are divided into the preparation phase, writing phase, and finalising phase when the article is submitted to the target journal. These rules provide a suite of strategies, including improved networking early in the process, building effective collaborations, transmitting results more efficiently and cross-disciplinary, and integrating concepts and methodologies that appeal to ecologists and a wider readership. Adhering to these Ten Simple Rules can ensure palaeoecologists' findings are more accessible and impactful among ecologists and the wider scientific community. Although this article primarily shows examples of how palaeoecological studies were published in journals for a broader audience, the rules apply to anyone who aims to publish outside specialised journals.

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在古生态学期刊之外发表文章,架起生态学与古生态学桥梁的十条简单规则。
尽管古生态学对于了解生态学家所研究和管理的生态系统的长期生态过程至关重要,但由于其方法的专业性,古生态学往往被视为与生态学相分离的领域。尽管在生态建模、样本年代测定和基于代用物的重建方面取得了进展,有助于将古生态学数据与新生态学数据进行直接比较,但从古生态学研究中获得的大部分科学知识仍然是孤立的。我们调查了一批具有跨越古生态学与新生态学鸿沟经验的古生态学研究人员,制定了在非古生态学期刊上发表古生态学研究论文的十条简单规则。我们的十条规则分为准备阶段、写作阶段和向目标期刊投稿时的定稿阶段。这些规则提供了一整套策略,包括在整个过程的早期改善网络、建立有效的合作关系、更高效地跨学科传递成果,以及整合吸引生态学家和更多读者的概念和方法。遵守这 "十条简单规则 "可确保古生态学家的研究成果更容易被生态学家和更广泛的科学界所接受并产生更大的影响。虽然本文主要展示了古生态学研究如何在面向更广泛读者的期刊上发表的例子,但这些规则适用于任何希望在专业期刊之外发表论文的人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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