Grasslands cover about one-half of Earth’s surface, fix 30-35% of terrestrial carbon, sustain 30% of the world’s human population, and support most global livestock production. Grassland ecosystems are under increasing pressure of global change drivers particularly climate change, land use change and invasive species. These drivers interact at different spatial and temporal scales to determine grassland health and the consequent provisioning of ecosystem services.
My research aims to contribute to the understanding of grasslands functioning that will in turn inform decision makers and land managers helping them to achieve a sustainable future for these valuable ecosystems. In order to achieve this goal, I combine complementary approaches from manipulative experiments to synthesis of long-term data and simulation modeling.
This experiment was the central part of my dissertation work. It explores the effect of interannual precipitation variability on grassland primary production and biodiversity. During my postdoc, I continued this experiment and it has been running for 10 years showing very interesting composition changes that reversed the initial productivity decline.
Another experiment, part of the NIFA-USDA grant funding my postdoc, aims to understand the interactive effects of grazing, seed predation and precipitation on the establishment of two key invasive species, Honey mesquite and Lehmann lovegrass. The experiment consists of 30 plots encompassing thee levels of precipitation where we simulate grazing in a split plot design. Within these plots, we nested seed predation and seedling herbivory treatments. As part of this effort, we are designing a smartphone app that will help rangeland managers to make decisions on when and where control the spread of invasions.
This experiment was the main field component of the NSF grant that funded my postdoc. The objective of this experiment was to explore regional and temporal effect of precipitation regimes on the partitioning of primary productivity between above and belowground components. The experiment consisted on 40 plots per site running from the Jornada Basin LTER in New Mexico, to the Semiarid Grassland Research Center in Colorado to the Konza Prairie LTER in Kansas.
Global Synthesis and Modeling
In order to expand the spatial extent of my research, I carried out a data-synthesis effort where I tested hypotheses that emerged from field experiments at the global scale. Using data from grasslands around the world, I tested the effect of precipitation variability on primary production and found that arid and mesic grasslands showed opposite responses. Arid grasslands responded positively while mesic grasslands responded negatively to enhanced interannual precipitation variability. Non-linear productivity responses provided a mechanism to explain these global patterns of grassland responses.
Following the same rationale, I am working now on another synthesis effort looking at global patters of grassland productivity partitioning between above and belowground components. In this case, I expanded the scope from only grasslands to all biomes. Using a combination of field and satellite-derived data, I estimated belowground productivity and the above-belowground productivity ratio for 103 sites worldwide.