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1.
Conserv Biol ; 25(2): 276-84, 2011 Apr.
Article in English | MEDLINE | ID: mdl-21166716

ABSTRACT

Much of the remaining grassland, particularly in North America, is privately owned, and its conversion to cultivated cropland is largely driven by economics. An understanding of why landowners convert grassland to cropland could facilitate more effective design of grassland-conservation programs. We built an empirical model of land-use change in the Prairie Pothole Region (north-central United States) to estimate the probability of grassland conversion to alternative agricultural land uses, including cultivated crops. Conversion was largely driven by landscape characteristics and the economic returns of alternative uses. Our estimate of the probability of grassland conversion to cultivated crops (1.33% on average from 1979 to 1997) was higher than past estimates (0.4%). Our model also predicted that grassland-conversion probabilities will increase if agricultural commodity prices continue to follow the trends observed from 2001 to 2006 (0.93% probability of grassland conversion to cultivated crops in 2006 to 1.5% in 2011). Thus, nearly 121,000 ha (300,000 acres) of grassland could be converted to cropland annually from 2006 to [corrected] 2011. Conversion probabilities, however, are spatially heterogeneous (range 0.2% to 3%), depending on characteristics of a parcel (e.g., soil quality and economic returns). Grassland parcels with relatively high-quality land for agricultural production are more likely to be converted to cultivated crops than lower-quality parcels and are more responsive to changes in the economic returns on alternative agricultural land uses (i.e., conversion probability increases by a larger magnitude for high-quality parcels when economics returns to alternative uses increase). Our results suggest that grassland conservation programs could be proactively targeted toward high-risk parcels by anticipating changes in economic returns, such as could occur if a new biofuel processing plant were to be built in an area.


Subject(s)
Ecosystem , Environment , Agriculture/economics , Agriculture/trends , Conservation of Natural Resources , Likelihood Functions , Midwestern United States , Models, Theoretical , Montana , Probability , Soil , Triticum/economics , Zea mays/economics
2.
Conserv Biol ; 22(5): 1320-30, 2008 Oct.
Article in English | MEDLINE | ID: mdl-18717691

ABSTRACT

Native grasslands that support diverse populations of birds are being converted to cropland at an increasing rate in the Prairie Pothole Region of North America. Although limited funding is currently available to mitigate losses, accurate predictions of probability of conversion would increase the efficiency of conservation measures. We studied conversion of native grassland to cropland in the Missouri Coteau region of North and South Dakota (U.S.A.) during 1989-2003. We estimated the probability of conversion of native grassland to cropland with satellite imagery and logistic regression models that predicted risk of conversion and by comparing the overlap between areas of high biological value and areas most vulnerable to conversion. Annualized probability of conversion was 0.004, and 36,540 ha of native grassland were converted to cropland during the period of our study. Our predictive models fit the data and correctly predicted 70% of observed conversions of grassland. Probability of conversion varied spatially and was correlated with landscape features like amount of surrounding grassland, slope, and soil productivity. Tracts of high biological value were not always at high risk of conversion. We concluded the most biologically valuable areas that are most vulnerable to conversion should be prioritized for conservation. This approach can be applied broadly to other systems and offers great utility for implementing conservation in areas with spatially variable biological value and probability of conversion.


Subject(s)
Agriculture , Conservation of Natural Resources/methods , Ecosystem , Poaceae , Algorithms , Logistic Models , North Dakota , Probability , South Dakota
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