bioRxivEcologyPreprint
A predictive model of fractional land use
Abstract
O_LILand use change leads to shifts in species ranges and declines in biodiversity across the world. By mapping likely future land use under projections of socio-economic change, these ecological changes can be predicted to inform conservation decision-making. C_LIO_LIWe present a land use modelling approach that enables ecologists to map changes in land use under various socio-economic scenarios at fine spatial resolutions. Its predictions can be used as a direct input to virtually all existing spatially-explicit ecological models. C_LIO_LIThe most commonly used land use modelling approaches provide binary predictions of land use. However, continuous representations of land use have been shown to improve ecological models. Our approach maps the fractional cover of land use within each grid cell, providing higher information content than discrete classes at the same spatial resolution. C_LIO_LIWhen parametrized using data from 1990, the method accurately reproduced land use patterns observed in the Amazon from 1990 until 2018. Predictions were accurate in terms of the fractional amounts allocated across the landscape and the correct identification of areas with declines and increases in different land uses. A small case study showcases the successful application of our model to reproduce patterns of agricultural expansion and habitat decline. C_LIO_LIThe model source code is provided as an open-source R package, making this new, open method available to ecologists to bridge the gap between socio-economic, land use and biodiversity modelling. C_LI
- research focus: ecology & biodiversity
- research focus: benchmarking
- research focus: software / tool
- approach: deep learning
- approach: statistical model
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Worldwide impacts of past and projected future land-use change on local species richness and the Biodiversity Intactness Index
Samantha L.L. Hill, Ricardo Gonzalez, … Andy Purvis·bioRxiv·May 1, 2018
- Predicting future patterns of land cover from climate projections using machine learning
T. F. Stepinski·bioRxiv·Jul 14, 2024
- Supporting global biodiversity assessment through high-resolution macroecological modelling: Methodological underpinnings of the BILBI framework
A. J. Hoskins, T. D. Harwood, … S. Ferrier·bioRxiv·Jun 4, 2019
- Biodiversity loss under future global socio-economic and climate scenarios
Abhishek Chaudhary, Arne O. Mooers·bioRxiv·Dec 18, 2017
- Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty
B. W. Allred, B. T. Bestelmeyer, … D. R. Uden·bioRxiv·Jun 10, 2020
- Assessing the effects of agricultural intensification on natural habitats and biodiversity in Southern Amazonia
J. Göpel, J. Schüngel, … N. Löbelt·bioRxiv·Nov 18, 2019