Funes I., Savé R., Rovira P., Molowny-Horas R., Alcañiz J.M., Ascaso E., Herms I., Herrero C., Boixadera J., Vayreda J. (2019) Agricultural soil organic carbon stocks in the north-eastern Iberian Peninsula: Drivers and spatial variability. Science of the Total Environment. 668: 283-294.EnllaçDoi: 10.1016/j.scitotenv.2019.02.317
Estimating soil organic carbon (SOC) stocks under agriculture, assessing the importance of their drivers and understanding the spatial distribution of SOC stocks are crucial to predicting possible future SOC stocks scenarios under climate change conditions and to designing appropriate mitigation and adaptation strategies. This study characterized and modelled SOC stocks at two soil depth intervals, topsoil (0–30 cm) and subsoil (30–100 cm), based on both legacy and recent data from 7245 agricultural soil profiles and using environmental drivers (climate, agricultural practices and soil properties) for agricultural soils in Catalonia (NE Spain). Generalized Least Square (GLS) and Geographical Weighted Regression (GWR) were used as modelling approaches to: (i) assess the main SOC stock drivers and their effects on SOC stocks; (ii) analyse spatial variability of SOC stocks and their relationships with the main drivers; and (iii) predict and map SOC stocks at the regional scale. While topsoil variation of SOC stocks depended mainly on climate, soil texture and agricultural variables, subsoil SOC stocks changes depended mainly on soil attributes such us soil texture, clay content, soil type or depth to bedrock. The GWR model revealed that the relationship between SOC stocks and drivers varied spatially. Finally, the study was only able to predict and map topsoil SOC stocks at the regional scale, because controlling factors of SOC stocks at the subsoil level were largely unavailable for digital mapping. According to the resulting map, the mean SOC stock value for Catalan agriculture at the topsoil level was 4.88 ± 0.89 kg/m 2 and the total magnitude of the carbon pool in agricultural soils of Catalonia up to 30 cm reached 47.9 Tg. The present study findings are useful for defining carbon sequestration strategies at the regional scale related with agricultural land use changes and agricultural management practices in a context of climate change. © 2019 Elsevier B.V.
Tiné M., Perez L., Molowny-Horas R. (2019) Hybrid spatiotemporal simulation of future changes in open wetlands: A study of the Abitibi-Témiscamingue region, Québec, Canada. International Journal of Applied Earth Observation and Geoinformation. 74: 302-313.EnllaçDoi: 10.1016/j.jag.2018.10.001
Among the most productive ecosystems around the world, wetlands support a wide range of biodiversity such as waterfowl, fish, amphibians, plants and many other species. They also provide ecosystem services that play important roles in relation to nutrient cycling, climate mitigation and adaptation, as well as food security. In this research, we examined and projected the spatiotemporal trends of change in open wetlands by coupling logistic regression, Markov chain methods and a multi-objective land allocation model into a hybrid geosimulation model. To study the changes in open wetlands we used multi-temporal land cover information interpreted from LANDSAT images (1985, 1995, and 2005). We predicted future spatial distributions of open wetlands in the administrative region of Abitibi-Témiscamingue, Quebec, Canada for 2015, 2025, 2035, 2045 and 2055. A comparison and assessment of the model's outcomes were performed using map-comparison techniques as well as landscape metrics. Change analysis between 1985 and 2005 showed an increase of about 63% in open wetlands, while simulation results indicated that this tendency would persist into 2055 with a continuous augmentation of open wetlands in the region. The spatial distribution of predicted trends in open wetlands could provide support to local biodiversity assessments, management and conservation planning of the open wetlands in Quebec, Canada. © 2018 Elsevier B.V.
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