Predicting anthropogenic soils across the Amazonia

Hidden under the forest canopy in lowland Amazonia are nutrient-enriched soils, called terra pretas (or Amazonian black earths), which were formed by prehistoric indigenous populations. These anthrosols are in stark contrast to typical nutrient-poor Amazonian soils, and have retained increased nutrient levels for hundreds of years. Because of their long-term nutrient retaining ability, terra pretas may be crucial for developing sustainable agricultural practices in Amazonia, especially given the deforestation necessary for traditional slash-and-burn systems. However, the frequency and distribution of terra preta soils across the landscape remains debatable, and archaeologists have estimated that terra pretas cover anywhere from 0.1% to 10% of the lowland Amazonian forests. The highest concentration of terra preta soils has been found along the central and eastern portions of the Amazon River and its major tributaries, but whether this is a true pattern or simply reflects sampling bias remains unknown. A possible explanation is that specific environmental or biotic conditions were preferred for human settlement and terra preta formation. Here, we use environmental parameters to predict the probabilities of terra preta soils across lowland Amazonian forests. We compiled a database of 2708 sites across Amazonia, including locations that contain terra pretas (n = 917), and those that are known to be terra preta-free (n = 1791). More than 20 environmental variables, including precipitation, elevation, slope, soil fertility, and distance to river were converted into 90-m resolution raster images across Amazonia and used to model the probability of terra preta occurrence. The relationship between the predictor variables and the occurrence of terra preta was examined using three modeling techniques: logistic regression, auto-logistic regression, and maximum entropy estimations. All three techniques provided similar predictions for terra preta distributions and the amount of area covered by terra preta. Distance to river, locations of bluffs, elevation, and soil fertility were important factors in determining distributions of terra preta, while other environmental variables had less effect. Terra pretas were most likely to be found in central and eastern Amazonia near the confluences of the Amazon River and its major tributaries. Within this general area of higher probability, terra pretas are most likely found atop the bluffs overlooking the rivers as opposed to lying on the floodplain. Interestingly, terra pretas are more probable in areas with less-fertile and more highly weathered soils. Although all three modeling techniques provided similar predictions of terra preta across Amazonia, we suggest that maximum entropy modeling is the best technique to predict anthropogenic soils across the vast Amazonian landscape. The auto-logistic regression corrects for spatial autocorrelation inherent to archaeological surveys, but still requires absence data, which was collected at different times and on different spatial scales than the presence data. The maximum entropy model requires presence only data, accounts for spatial autocorrelation, and is not affected by the differential soil sampling techniques.