Using a hybrid demand-allocation algorithm to enable distributional analysis of land use change patterns

Abstract

Future land use projections are needed to inform long-term planning and policy. However, most projections require downscaling into spatially explicit projection rasters for ecosystem service analyses. Empirical demand-allocation algorithms input coarse-level transition quotas and convert cells across the raster, based on a modeled probability surface. Such algorithms typically employ contagious and/or random allocation approaches. We present a hybrid seeding approach designed to generate a stochastic collection of spatial realizations for distributional analysis, by 1) randomly selecting a seed cell from a sample of n cells, then 2) converting patches of neighboring cells based on transition probability and distance to the seed. We generated a collection of realizations from 2001-2011 for the conterminous USA at 90m resolution based on varying the value of n, then computed forest area by fragmentation class and compared the results with observed 2011 forest area by fragmentation class. We found that realizations based on values of n � 256 generally covered observed forest fragmentation at regional scales, for approximately 70% of assessed cases. We also demonstrate the potential of the seeding algorithm for distributional analysis by generating 20 trajectories of realizations from 2020-2070 from a single example scenario. Generating a library of such trajectories from across multiple scenarios will enable analysis of projected patterns and downstream ecosystem services, as well as their variation.

The United States’ Implementation of the Montréal Process Indicator of Forest Fragmentation

“…Despite the progress made, the United States' Montréal Process reporting still contains significant gaps, most notably the lack of full geographic coverage of Alaska, Hawaii, and US territories. Looking ahead, the method is equally applicable to other input data and the remarkable improvements in mapping historical forest land use and cover [52,53] as well as potential future forests [54] will undoubtedly improve the scope and utility of forest fragmentation reporting in the United States.…”

Forest-Associated Fishes of the Conterminous United States

“…gov/GIS/huc.html, accessed on 3 September 2020. Please see [38,39] for the forest land use data sets used in this study. The baseline forest raster-and watershed-level maps are available upon request.…”

“…The area of each HUC8 categorized with forested land was calculated from a baseline forest raster for the conterminous U.S. This raster was generated by harmonizing a map of the land base [33] with land use maps from the National Land Cover Dataset series [34][35][36][37] according to the methods of Brooks et al [38]. We constrained statewide forest areas to match tabulated 2016-2017 statewide total forest areas (Figure 3) as defined by the Resource Planning Act [39].…”