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Table 2 Driving forces and possible effects

From: The spatiotemporal changes of marshland and the driving forces in the Sanjiang Plain, Northeast China from 1980 to 2016

Driving forces

Possible effects

Sources and types

Biophysical factors

 Distance to river (m)

Marshland near river exhibited fewer loss

River was from land use map in 2016 and then GIS analysis: Vector data

 Elevation (m)

Marshland in lower areas more prone to loss

GIS analysis of data from RESDC: Raster, 30 m

 Slope (°)

Marshland loss is more likely to occur in flat areas

GIS analysis based on the elevation: Raster

 Average annual precipitation (mm)

The marshland loss rate increase with decrease precipitation

GIS analysis of data from RESDC: Raster

 Average annual temperature (°C)

Marshland are more likely to be converted at warmer temperatures

GIS analysis of data from RESDC: Raster

 Potential crop yield (kg/km2)

Marshland are more likely to be converted when potential crop yields are high

GIS analysis of data from RESDC: Raster

Socio-economic factors

 Distance to settlement (m)

Marshland tend to be vulnerable to losses when adjacent to residents

Settlements was from land use map in 2016: Vector data

 Distance to road (m)

Marshland near roads tend to be prone to loss

GIS analysis of data from RESDC: Vector data

 Gross domestic product (yuan/km2)

Marshland distributed in the poor areas are more likely to be lost

GIS analysis of data from RESDC: Raster

 Population density (persons/km2)

Marshland loss is more likely to occur in high-density population areas

GIS analysis of data from RESDC: Raster

Land management factors

 Ditch density (length/km2)

Marshland in the region with high ditch density are more likely to be prone to loss

Ditch regime was digitized from the Atlas of Water Conservancy Projects Present Situations in Heilongjiang Reclamation Area 2010: Vector data