Over the last millennium peatlands have accumulated significant carbon stores. Drainage for agricultural use has been widespread and has altered the functioning of these mires: shifting them towards carbon release. Recently, in recognition of the range of ecosystem services derived from these landscapes peatland restoration projects have been initiated. Carbon storage is often cited amongst the aims of these projects, especially since the inclusion of rewetting wetlands in the Kyoto Protocol. However, little is known about the effects of ditch blocking on CO2 fluxes, particularly in Molinia caerulea dominated peatlands, a species common on degraded peatlands which tolerates a range of water table depths. This thesis aims firstly to quantify CO2 fluxes from a drained Molinia caerulea dominated blanket bog and to improve understanding of the temporal and spatial controls on these fluxes and secondly, to quantify the immediate effects of ditch blocking. Closed chamber measurements of net ecosystem exchange and partitioned below-ground respiration from control-restored paired sites were collected over the growing seasons immediately pre- (2012) and post-restoration (2013/2014). These flux data were coupled with remotely sensed data quantifying vegetation phenology and structure with a fine resolution (daily/cm) over large extents (annual/catchment). Although temporal variation in water table depth was not related to CO2 fluxes, the seasonal average related to vegetation composition suggesting raising water tables may promote a change in vegetation composition within these species-poor ecosystems. The distribution of water table depths, vegetation composition and CO2 fluxes did not vary with proximity to drainage ditches despite their prominence. An empirical model suggests in a drained state these peatlands are CO2 sources, indicating carbon previously accumulated is gradually being lost. Data suggest restoration does not always significantly affect water tables and consequently CO2 fluxes in the short-term. Where shallower water tables were maintained during dry conditions photosynthesis decreased and heterotrophic respiration increased: enhancing carbon release. Research undertaken during atypical weather has been unable to determine if restoration will be able to raise water tables sufficiently to protect the existing peat store and promote the vegetation change required to reinstate CO2 sequestration in the longer-term.

Vegetation phenology controls seasonal variation in ecosystem processes and exerts important controls on land-atmosphere exchanges of carbon, water, and energy. However, the ecological processes and interactions between climate and vegetation that control phenology and associated feedbacks to the atmosphere are not fully understood. In this dissertation, I use remote sensing in combination with climate and ecological data to improve understanding of biophysical controls and feedbacks between vegetation phenology and the atmosphere in temperate forest ecosystems of North America. In the first part of this dissertation, I evaluate the agreement and characterize the similarities and differences between land surface phenology products from two remote sensing instruments (MODIS and VIIRS) that are designed to provide long-term continuity of land surface phenology measurements at global scale. Results from this analysis indicate that the VIIRS land surface phenology product provides excellent continuity with the MODIS record despite subtle differences between each instrument and the algorithms used to generate each product. In the second part of this dissertation, a state-space Bayesian modeling framework is applied to seventeen years of MODIS and daily weather data to improve understanding of what controls the timing of springtime phenology in deciduous forests of temperate and boreal North America. Results show that photoperiod is more important in warmer regions than in colder regions, which contradicts a widely held hypothesis that photoperiod provides a key safety mechanism preventing early leaf-out during springtime. In the final part of this dissertation, I use a physically-based attribution method to quantify the relative importance of covarying surface biophysical and atmospheric variables in modifying the surface energy balance during springtime. Results show that the widely observed decrease in the Bowen ratio that occurs with leaf emergence is not solely attributable to changes in surface resistance caused by increasing leaf area during spring. Rather, observed changes in the Bowen ratio reflect the combined effects of changes in surface properties and atmospheric conditions. The results from this dissertation provide an improved foundation for long-term studies focused on observing and modeling springtime vegetation phenology and associated feedbacks to the atmosphere in deciduous forest ecosystems at local-to-continental scales.

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.