GreenPole is an interdisciplinary research project, committed to decision support for a sustainable use of Nordic forests. We assess trade-offs and synergies between climate, biodiversity and human well-being in policy-making. Our approach is based on a socio-ecological systems understanding and scientific integrity.
As depicted above, we think of forest governance as a socio-ecological system in which policy interventions affect how people interact with the ecosystem. Here, we consider the outcomes of human land use decisions in terms of extracted timber, carbon storage and habitat quality. Furthermore, we consider the trade-flows of wood-products to compute a more comprehensive carbon balance. Thereby, we aim to assess trade-offs between climate, biodiversity, and human-well being. To do so we make use of different models and epistemic approaches:
Qualitative systems thinking
In order to conduct a comprehensive policy evaluation, GreenPole project will co-develop a broad socio-ecological system understanding together with expert-based from the field.
–> visualization of causation in socio-ecological systems
Crafty is an agent-based model (ABM) that captures human interaction among themselves and with the natural ecosystem to capture resource extraction and other management decisions.
–> model github
LPJGuess is a dynamic ecosystem model of plant functional type competition and soil processes to capture responses to natural disturbances and forest management practices.
–> model website
Environmentally extended multi-regional input-output (EE-MRIO) models capture resource flow that are traded between different parts of the world and will be used to trace carbon embedded in trade.
–> exiobase showcase
Joint species distribution models (JSDM) predict the reponse of species to landscape features and habitat quality which we will use to assess model bird species distribution in response to forest management.
–> hierarchical modelling of species approach
Structural equation models (SEM) are a way to translate theoretical assumptions about causal processes into a formal ontological system model that can then be assessed quantitatively.
–> system archetypes