Forest dynamics in Mississippi, USA: a hybrid statistical and geospatial analysis |
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Authors: | In-Young Yeo Chengquan Huang |
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Institution: | 1. University of Maryland, College Park, MD, USA
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Abstract: | Understanding forest changes and its trajectory is important to develop policy options and future scenarios for climate analysis. This research is conducted to gain insights on secondary forests change using Mississippi, USA, as a case study. We investigate the spatial patterns and temporal dynamics of secondary forests at high resolution and examine the forces driving their changes. An extensive literature review is conducted to refine the conceptual framework of forest changes and identify the underlying key factors. Forest changes are quantified at high spatial (30-m) and temporal (biennial) resolutions, using time series remotely sensed data between 1984 and 2007. A number of geospatial and socioeconomic data were compiled to analyze the spatial variations of forest disturbances and their linkages to various socioeconomic, political, and biogeophysical factors. The results show that the secondary forests are highly dynamic and variable. Disturbances and regeneration occur continuously everywhere in a systematic and coordinated fashion. This pattern prevents an extensive disturbance and increases total forest cover. Market conditions (i.e., timber price) are the key predictor of the level and overall trend of forest disturbances. However, spatial patterns of forest dynamics cannot be explained by location-specific biophysical, socioeconomic, and policy factors identified in the literature. They can best be described by the ecological characteristics of the forests (i.e., the forest type and age distribution), which have a clear economic linkage. The research shows that regenerated forests frequently experience loss and gain of their extent, and their ecological characteristics change drastically on a short-term basis. These results point out challenges and opportunities in forest management and policy with regard to reforestation. |
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