The final, formatted version of the article will be published soon.
PERSPECTIVE article
Front. Ecol. Evol.
Sec. Biogeography and Macroecology
Volume 12 - 2024 |
doi: 10.3389/fevo.2024.1112712
This article is part of the Research Topic Insights in Biogeography and Macroecology: 2022 View all 6 articles
A perspective on the need for integrated frameworks linking species distribution and dynamic forest landscape models across spatial scales
Provisionally accepted- 1 Wageningen University and Research, Wageningen, Netherlands
- 2 Institute for Alpine Environment, Eurac Research, Bozen/Bolzano, Italy, Bozen, Italy
- 3 Department of Soil Sciences, Plants and Food, University of Bari Aldo Moro, via G. Amendola 165/A, 70126, Bari, Italy
- 4 Department of Forestry and Wildlife Management, Faculty of Applied Ecology, Agricultural Sciences and Biotechnology, Inland Norway University of Applied Sciences, Evenstad, Norway
- 5 Institute of Ecology, Faculty of Biology, University of Innsbruck, Innsbruck, Austria
- 6 Institute of Botany of the Czech Academy of Sciences, Průhonice, Czechia
- 7 Natural Resources Institute Finland (Luke), Helsinki, Uusimaa, Finland
- 8 Department of Forestry and Renewable Forest Resources, Faculty of Biotechnical, University of Ljubljana, Ljubljana, Slovenia
- 9 Department of Wildlife, Fish and Environment, Faculty of Forest Sciences, Swedish University of Agricultural Sciences, Umeå, Västerbotten, Sweden
- 10 DEPT. AGRICULTURAL AND ENVIRONMENTAL SCIENCES, University of Milan, Milan, Italy
Climate change significantly alters species distributions. Numerous studies project the future distribution of species using Species Distribution models (SDMs), most often using coarse resolutions. Working at coarse resolutions in forest ecosystems fails to capture landscape-level dynamics, spatially explicit processes, and temporally defined events that act at finer resolutions and that can disproportionately affect future outcomes. Dynamic Forest Landscape Models (FLMs) can simulate the survival, growth, and mortality of (stands of) trees over long time periods at small resolutions. However, as they are able to simulate at fine resolutions, study landscapes remain relatively small due to computational constraints. The large amount of feedbacks between biodiversity, forest, and ecosystem, processes cannot completely be captured by FLMs or SDMs alone. Integrating SDMs with FLMs enables a more detailed understanding of the impact of perturbations on forest landscapes and their biodiversity. Several studies have taken this approach at landscape scales, using fine resolutions. Yet, many scientific questions in the fields of biogeography, macroecology, conservation management, among others, require a focus on both large scales and fine resolutions. Here, drawn from literature and experience, we provide our perspective on the most important challenges that need to be overcome to use integrated frameworks at spatial scales larger than the landscape and at fine resolutions. Future research should prioritize these challenges to better understand drivers of species distributions in forest ecosystems and effectively design conservation strategies under the influence of changing climates on spatially and temporally explicit processes. We further discuss possibilities to address these challenges.
Keywords: Climate Change, dynamic landscape modelling, forests, species distribution modelling, species conservation climate change, species conservation
Received: 30 Nov 2022; Accepted: 28 Aug 2024.
Copyright: © 2024 Hof, Mina, Mairota, Aguilar, Leitinger, Brůna, Koivula, Klopčič, Sjögren and Vacchiano. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Anouschka R. Hof, Wageningen University and Research, Wageningen, Netherlands
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.