Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP)

Predicting Fire Season Severity in South America Using Sea Surface Temperature Anomalies

Fires in South America cause forest degradation and contribute to carbon emissions associated with land use change. Here we investigated the relationship between year-to-year changes in satellite-derived estimates of fire activity in South America and sea surface temperature (SST) anomalies. We found that the Oceanic Ni o Index (ONI) was correlated with interannual fire activity in the eastern Amazon whereas the Atlantic Multidecadal Oscillation (AMO) index was more closely linked with fires in the southern and southwestern Amazon. Combining these two climate indices, we developed an empirical model that predicted regional annual fire season severity (FSS) with 3-5 month lead times. Our approach provides the foundation for an early warning system for forecasting the vulnerability of Amazon forests to fires, thus enabling more effective management with benefits for mitigation of greenhouse gas and air pollutant emissions

Climate-driven shifts in continental net primary production implicated as a driver of a recent abrupt increase in the land carbon sink

The world's ocean and land ecosystems act as sinks for anthropogenic CO2, and over the last half century their combined sink strength grew steadily with increasing CO2 emissions. Recent analyses of the global carbon budget, however, have uncovered an abrupt, substantial (????1?PgC?yr?1) and sustained increase in the land sink in the late 1980s whose origin remains unclear. In the absence of this prominent shift in the land sink, increases in atmospheric CO2 concentrations since the late 1980s would have been ????30?% larger than observed (or ????12?ppm above current levels). Global data analyses are limited in regards to attributing causes to changes in the land sink because different regions are likely responding to different drivers. Here, we address this challenge by using terrestrial biosphere models constrained by observations to determine if there is independent evidence for the abrupt strengthening of the land sink. We find that net primary production significantly increased in the late 1980s (more so than heterotrophic respiration), consistent with the inferred increase in the global land sink, and that large-scale climate anomalies are responsible for this shift. We identify two key regions in which climatic constraints on plant growth have eased: northern Eurasia experienced warming, and northern Africa received increased precipitation. Whether these changes in continental climates are connected is uncertain, but North Atlantic climate variability is important. Our findings suggest that improved understanding of climate variability in the North Atlantic may be essential for more credible projections of the land sink under climate change

Modeling the impacts of major forest disturbances on the Earth\u27s coupled carbon-climate system, and the capacity of forests to meet future demands for wood, fuel, and fiber

The carbon balance of forested ecosystems are fundamentally linked to cycles of disturbance and recovery. Two of the most extreme natural disturbances are tropical cyclones and Amazon forest fires. While an average of more than 80 tropical storms and hurricanes occur per year, the number, severity, and impacts of these storms varies through time and may be increasing, while the committed carbon emissions from a single large storm such as Katrina can be as large as the net annual carbon sequestration of U.S. forest trees. Forest fires are a growing concern too, particularly in the sensitive Amazon region where they potentially compound the risk of forest die-back from climate change. The overall science goal of this project is to understand how altered natural disturbance rates could affect the carbon balance of terrestrial ecosystems, and as a consequence, the development strategies designed to mitigate against future climate change. In particular, we address two major science questions: 1) How could potentially altered disturbance rates from tropical cyclones and Amazonian fires affect vegetation, carbon stocks and fluxes, and the development of climate change mitigation strategies? 2) How does remote sensing data quantity and quality constrain model projections of the effects of altered disturbance rates on vegetation, carbon stocks and fluxes, and the development of climate change mitigation strategies? These science questions are addressed through four linked objectives: 1) remote sensing and modeling forest disturbances (tropical cyclones and Amazonian fires); 2) assess the consequences of forest disturbances in integrated assessments; 3) link ecological and socio-economic models addressing forest disturbance; and 4) quantify the implications of forest disturbances for future satellite missions and Earth System models