Climate and Land-Use Change Effects on Soil Carbon Stocks over 150 Years in Wisconsin, USA

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 12; p. 1504
• Main Authors: Huang, Jingyi, Hartemink, Alfred E., Zhang, Yakun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.06.2019
• Subjects: 4 per 1000; Agricultural practices; Agriculture; Algorithms; Annual precipitation; best management practice; Carbon; carbon pool; Carbon sequestration; carbon sink; carbon sinks; climate; Climate change; Cover crops; Crop rotation; Dairy farms; data collection; Datasets; Digital Elevation Models; Digital mapping; Environmental factors; forests; Global warming; industrial revolution; Land cover; Land use; land use change; Landsat; Landsat satellites; Learning algorithms; Legumes; Machine learning; model validation; Organic carbon; Organic soils; Precipitation; reduced tillage; Remote sensing; Respiration; Soil erosion; Soil improvement; Soil management; soil organic carbon; Soil profiles; Soil properties; Soil sciences; Soil temperature; Soil types; Soils; Spodosols; Studies; temperature; temporal variation; Temporal variations; Tillage; wetlands; Wheat; Wisconsin; United States > US; Wisconsin
• DOI: 10.3390/rs11121504
• ISSN: 2072-4292

Soil organic carbon is a sink for mitigating increased atmospheric carbon. The international initiative “4 per 1000” aims at implementing practical actions on increasing soil carbon storage in soils under agriculture. This requires a fundamental understanding of the soil carbon changes across the globe. Several studies have suggested that the global soil organic carbon stocks (SOCS) have decreased due to global warming and land cover change, while others reported SOCS may increase under climate change and improved soil management. To better understand how a changing climate, land cover, and agricultural activities influence SOCS across large extents and long periods, the spatial and temporal variations of SOCS were estimated using a modified space-for-time substitution method over a 150-year period in the state of Wisconsin, USA. We used legacy soil datasets and environmental factors collected and estimated at different times across the state (169,639 km2) coupled with a machine-learning algorithm. The legacy soil datasets were collected from 1980 to 2002 from 550 soil profiles and harmonized to 0.30 m depth. The environmental factors consisted of 100-m soil property maps, 1-km annual temperature and precipitation maps, 250-m remote-sensing (i.e., Landsat)-derived yearly land cover maps and a 30-m digital elevation model. The model performance was moderate but can provide insights on understanding the impacts of different factors on SOCS changes across a large spatial and temporal extent. SOCS at the 0–0.30 m decreased at a rate of 0.1 ton ha−1 year−1 between 1850 and 1938 and increased at 0.2 ton ha−1 year−1 between 1980 and 2002. The spatial variation in SOCS at 0–0.30 m was mainly affected by land cover and soil types with the largest SOCS found in forest and wetland and Spodosols. The loss between 1850 and 1980 was most likely due to land cover change while the increase between 1980 and 2002 was due to best soil management practices (e.g., decreased erosion, reduced tillage, crop rotation and use of legume and cover crops).