Land Use Change and Policy in Iowa’s Loess Hills

Abstract

<p class="sar-body"><span lang="EN-US">Land use changes have important implications on ecosystems and society. Detailed identification of the nature of land use changes in any local region is critical for policy design. In this paper, we quantify land use change in Iowa’s Loess Hills ecoregion, which contains much of the state’s remaining prairie grasslands. We employ two distinct panel datasets, the National Resource Inventory data and multi-year Cropland Data Layers, that allow us to characterize spatially-explicit land use change in the region over the period 1982-2010. We analyze land use trends, land use transitions and crop rotations within the ecoregion, and contrast these with county and state-level changes. To better comprehend the underlying land use changes, we evaluate our land use characterizing metrics conditional on soil quality variables such as slope and erodibility. We also consider the role of contemporary agricultural policy and commodity markets to seek explanations for land use changes during the period of our study. Although crop production has expanded on the Loess Hills landform since 2005, much of the expansion in corn acres has been from reduced soybean acreage. We find that out of the total 258 km<sup>2</sup> increase in corn acreage during 2005-’10, about 100 km<sup>2</sup> transitioned from soybeans. Data also indicate intensifying monoculture with higher percentage of corn plantings for two to four consecutive years during 2000-’10. In addition, crop production is found to have moved away from more heavily sloped land. Cropping does not appear to have increased on lands with higher crop productivity.</span></p>

Land-Use, Crop Choice, and Proximity to Ethanol Plants

“…Of course, the results using instrumental variables are preferred. Due to high transportation costs, the locations of ethanol refineries are likely to be close to farmlands where corn is grown, which can cause an endogenous correlation between the distance variable and the error term in the model [19,20,37]. To address the endogeneity of locations of ethanol refineries, we calculated the distance between individual parcels and the nearest train station to utilize proximity to the nearest train station as an instrument variable (IV) [38].…”

Studies on factors affecting the evolution of agroecosystems in the Dakotas

“…Exceptions in spatial resolution (56m) occurred for a period between 2006 and 2009 when AWiFS sensor data were the primary source of inputs for the program.. It should be noted that extraction and analysis of these CDL data across this time span has been known to confound or complicate quantification of precise land use transitions in some studies (Arora et al 2016a).…”

“…Second, land use type classification errors among the different years of CDL in the archive are considerable (Arora et al 2016a). The CDL program provides state-specific accuracy levels for individual land cover types, which reveals regional discrepancy in the performance of their underlying land cover identification algorithm.…”

“…Cropland and grassland accuracy levels were high in crop-dominant and grassdominant areas, respectively. Arora et al (2016a) identified numerous areas of illogical, multi-…”

“…If care is taken in the data preprocessing phase of CDL time series analyses to screen out such errors, then great potential exists to accurately illuminate multiple driving forces behind observed trends in land use land cover change, especially in agricultural regions (Arora et al 2016a). For example, analyzed grass to corn/soy and corn/soy to grass transitions in the Dakotas between 2006 -the first year of CDL for SD-and 2011 following and concurrent with a period of sharp commodity price increases , USDA 2017.…”