Graduate researcher, Pietro Sciusco, is a Ph.D. candidate in the Landscape Ecology and Ecosystem Science-LEES Lab at Michigan State University. His research interest is to estimate ecological processes and their contribution to climate change in highly managed agricultural landscapes in southwestern Michigan. This is primarily through satellite data (i.e., multi-source imaging, optical and radar) and ground measurements.
There is strong scientific evidence that human activities, such as burning fossil fuels and industrial processes, are the major driver of climate change since the pre-industrial era. In fact, the released of carbon dioxide (CO2) in the atmosphere due to such anthropogenic activities represents the highest contribution to the total greenhouse gas emission during the last decades (1970-2010). In turn, current and future changes in climate, such as warming and rising sea levels, have shown to have negative impacts on all kind of coupled natural-human systems worldwide. Ultimately current and future climate changes represent a real problem to the sustainable development of our current natural-human systems. Therefore, assessing the exposure and vulnerability of our system has become a fundamental goal in climate change research.
The Intergovernmental Panel on Climate Change (IPCC) has introduced two metrics to help comparisons across different adaptation and mitigation strategies: the radiative forcing (W m-2) and the global warming impact (CO2-equivalent; CO2eq). This means that any mitigation strategy can be put onto the same scale (i.e., cooling or warming effects expressed in W m-2 and CO2-equivalent mitigation), facilitating comparisons across techniques. Specifically, the global warming impact or GWI (aka global warming potential), has become the default emission-based metric among a range of international cooperation parties, such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol.
Geoengineering options represent a set of methods and tools that have the goal of deliberately altering the climate system of the Earth in order to reduce climate change impacts. For example, by removing greenhouse gasses from the atmosphere, or by reducing the amount of absorbed solar energy that reaches the Earth, we can help reverse the effects of climate change. The second option refers to the climate benefits due to albedo — the amount of solar radiation reflected by a surface relative to the total incident on it.
Although geoengineering is currently considered an option in climate intervention proposals, there are still many uncertainties and research gaps. The main research focus has been on understanding carbon sequestration across fragmented landscapes, meaning little effort has been made to understand changes in albedo-induced global warming impact in the context of landscape mosaic at broader temporal scales and for multiple anthropogenic land uses. This brings the forcing effects of albedo due to land-use land cover change (LULCC) to be ranked as medium-low relative to the rich scientific evidence of the forcing effects due to anthropogenic greenhouse gasses.
The main focus of my research is the climate regulations induced by biogeophysical and biogeochemical mechanisms in the context of global warming impact. The questions that I want to answer fall within three areas: (i) What are the contributions of cropland-forest landscapes, climate, and seasonality to the overall variation in albedo and how do they affect the GWI across five contrasting ecoregions of equal area for three different years? (Sciusco et al. 2020) (ii) What are the contributions of land mosaic (i.e., major cover types) to seasonal and monthly albedo-induced GWIs at landscape level and for 19-year study period across five contrasting ecoregions in the Kalamazoo River Watershed? (iii) What are the main physical and biophysical drivers to the net ecosystem exchange (NEE) of major cover types and how do the climate regulation due to NEE compare (i.e., trade-offs) to that due to albedo at landscape scale?
I will take a multi-scale (i.e., spatial and temporal) approach to achieve my study objectives based on ground measurements and remote sensing images at multiple spatial and temporal resolutions. The conceptual framework in Figure 1 synthesizes the two mechanisms involved in the trade-off analysis of GWI proposed.
The overarching goal of the research work is to first investigate both biogeochemical and biogeophysical mechanisms separately in the context of GWI, and then to delineate their climate regulation off-sets. To achieve this goal, I select the Kalamazoo River Watershed as study area for my investigations (Figure 2).
As LTER fellow, I had the opportunity to complete my four years of summer fieldwork at some of the long term ecological research (LTER) sites located at Kellogg Biological Station (KSB). In fact, part of my research outlined above will consider two groups of pre-existing LTER sites at KBS: the scale-up sites (for a total of seven sites; Figure 2b), and the main cropping system experiment (MCSE) sites (for a total of 9 sites; Figure 2c). The scale-up sites fall within two groups of sites: Lux Arbor (corn, prairie, and switchgrass) and Marshall (reference, corn, prairie, and switchgrass); among the MCSE sites, I selected nine plots that have been maintained as corn-soybeans-wheat rotations, prairie, and switchgrass (each one replicated three times) for more than 30 years. Regarding the data, each of the seven scale-up sites is equipped with an eddy covariance (EC) flux tower, which takes continuous instantaneous measurements of NEE fluxes and other ancillary measurements. In addition to that, other ground measurements will be employed as result of four years (2018-2021) of summer fieldworks conducted during the months of June, July, and August (Figure 3). In particular, the measurements collected during the fieldwork campaigns include: leaf area index, SPAD index (i.e., leaf chlorophyll content), soil water content, and vegetation height (Htveg). Such additional measurements have been collected at subplot level (five subplots at each scale-up site and 3 subplots at each MCSE site; Figure2 b-c) every ~14 days for the three months June, July, and August. Regarding the remote sensing (RS) data, the multi sensor approach at multiple scales (i.e., spatial and temporal) will be based on the use of optical satellite products collected for the entire study period (2018-2021) from the Sentinel-2 Multi-Spectral Instrument (MSI) aboard the European Sentinel-2A and -2B satellites and from the Vegetation and Environmental New Micro Spacecraft (VenµS) satellite.