Improving peer review capacity and integrity in forestry journals

The peer review process in forestry journals has remained largely unchanged despite significant shifts in the academic publishing landscape over the past decade. Using data from 156 forestry journals and detailed metrics from 10 selected journals, we examine trends in peer-review capacity, associate editor roles, and publishing volume from 2000 through 2024. Over this period, the number of forestry articles published annually has increased more than fourfold, while the pool of available reviewers has contracted, creating unsustainable pressure on the review system. Open-access publishing now accounts for 45% of forestry articles, up from 20% in 2000, with implications for review timelines and quality assurance. We evaluate the potential of artificial intelligence tools to assist with peer review, while acknowledging associated risks to scientific integrity. Drawing on a comparison of reviews from human experts and large language models, we propose recommendations for experimenting with alternative review models, implementing version control, and integrating artificial intelligence (AI) responsibly into the peer review process.