Stochastic, Empirically Informed Model of Landscape Dynamics and Its Application to Deforestation Scenarios

Land change including deforestation undermines the sustainability of the environment. Using data on 1992–2015 pattern change in over 1.7 million mesoscale landscapes worldwide we developed a stochastic model of long‐term landscape dynamics. The model suggests that observed heterogeneous landscapes a...

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Bibliographic Details
Published in:Geophysical research letters 2019-12, Vol.46 (23), p.13845-13852
Main Authors: Nowosad, J., Stepinski, T. F.
Format: Article
Language:English
Subjects:
Agriculture
Case studies
Computer simulation
Conservation
Deforestation
Dynamics
Environmental policy
Evolution
Forest conservation
Forests
Land cover
Land use
Landscape
Mesoscale phenomena
Mosaics
Probability distribution
Probability theory
Sequencing
Statistical methods
Stochastic models
Stochasticity
Sustainability
Sustainable development
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Summary:Land change including deforestation undermines the sustainability of the environment. Using data on 1992–2015 pattern change in over 1.7 million mesoscale landscapes worldwide we developed a stochastic model of long‐term landscape dynamics. The model suggests that observed heterogeneous landscapes are short‐lived stages in a transition between quasi‐stable homogeneous landscapes of different themes. As a case study we used Monte Carlo simulations based on our model to derive a probability distribution for evolutionary scenarios of landscapes that undergo a forest‐to‐agriculture transit, a prevalent element of deforestation. Results of simulations show that most likely and the fastest deforestation scenario is through the sequence of highly aggregated forest/agriculture mosaics with a decreasing share of the forest. Simulations also show that once forest share drops below 50% the remainder of the transit is rapid. This suggests that possible conservation policy is to protect mesoscale tracts of land before the forest share drops below 50%. Plain Language Summary Land change across the world undermines the sustainability of the environment. Understanding the dynamics of landscape change would help to find trade‐offs between the development and sustainability of the environment. We developed a data‐driven model capable of providing plausible scenarios of long‐term evolution of landscapes. Using this model, we proposed a general principle of landscape evolution: heterogeneous landscapes are short‐lived stages in transit between two homogeneous landscapes of different land cover. As a case study we applied our model to identify the most likely scenarios of the forest‐to‐agriculture transit, a dominant source of deforestation. The model suggests that scenarios of the forest‐to‐agriculture transits that proceed through a sequence of aggregated mosaics are more frequent and more damaging to an environment than transits proceeding through a sequence of disaggregated mosaics. It also suggests that preserving mesoscale (∼100 km2) tracts of land before they lose 50% of forest share may be a good conservation strategy. Key Points Long‐term evolution of an individual landscape is stochastically modeled using a worldwide data set of short‐term landscape changes Model suggests that heterogeneous landscapes are transitional stages between homogeneous landscapes of different themes In a transit from forested to agricultural landscapes, losing the first 50% of the forest is
ISSN:0094-8276
1944-8007
DOI:10.1029/2019GL085952