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Managing for the unexpected: building resilient forest landscapes to cope with global change: Supporting data

Authors: Mina, Marco;

Managing for the unexpected: building resilient forest landscapes to cope with global change: Supporting data

Abstract

Input files and installers of the versions of LANDIS-II, PnET-Succession and other extensions used in the associated paper. They can be used to to reproduce results of the study. The model documentation is freely available at https://www.landis-ii.org/ The LANDIS-II code is distributed under an open source license at https://github.com/LANDIS-II-Foundation. ------------------------------------------------------------------------------------------------------------------------------------------------------------ If interested in using this dataset for a research study or project, please contact Marco Mina ------------------------------------------------------------------------------------------------------------------------------------------------------------ ABSTRACT. Natural disturbances exacerbated by novel climate regimes are increasing worldwide, threatening the ability of forest ecosystems to mitigate global warming through carbon sequestration and to provide other key ecosystem services. One way to cope with unknown disturbance events is to promote the ecological resilience of the forest by increasing both functional trait and structural diversity and by fostering functional connectivity of the landscape to ensure a rapid and efficient self-reorganization of the system. We investigated how expected and unexpected variations in climate and biotic disturbances affect ecological resilience and carbon storage in a forested region in southeastern Canada. Using a process-based forest landscape model (LANDIS-II), we simulated ecosystem responses to climate change and insect outbreaks under different forest policy scenarios – including a novel approach based on functional diversification and network analysis – and tested how the potentially most damaging insect pests interact with changes in forest composition and structure due to changing climate and management. We found that climate warming, lengthening the vegetation season, will increase forest productivity and carbon storage, but unexpected impacts of drought and insect outbreaks will drastically reduce such variables. Generalist, non-native insects feeding on hardwood are the most damaging biotic agents for our region, and their monitoring and early detection should be a priority for forest authorities. Higher forest diversity driven by climate-smart management and fostered by climate change that promotes warm-adapted species, might increase disturbance severity. However, alternative forest policy scenarios led to a higher functional and structural diversity as well as functional connectivity – and thus to higher ecological resilience – than conventional management. Our results demonstrate that adopting a landscape-scale perspective by planning interventions strategically in space and adopting a functional trait approach to diversify forests is promising for enhancing ecological resilience under unexpected global change stressors.

Marco Mina´s additional funding: Swiss National Science Foundation (Grant n.175101, Early Postdoc.Mobility ) Resilience-based forest management: Coupling spatially explicit tree-community and landscape models with functional diversity science using network theory

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Keywords

insect outbreaks, LANDIS-II, ecological resilience, carbon stock, forest ecosystem management, forest landscape modelling, drought, functional diversity, network analysis

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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